Learn about the effect of deforestation and then reforestation on river channel morphology.\n Understand the composite mathematical modelling for continuous simulations of hydro-geomorphological processes.\n Know about the process-response models for estimation of cliff erosion and its quantitative predictions.\n Grow your knowledge about various geomorphometric tools that are available in freely available GIS software.",isbn:"978-953-51-3574-6",printIsbn:"978-953-51-3573-9",pdfIsbn:"978-953-51-4625-4",doi:"10.5772/65532",price:119,priceEur:129,priceUsd:155,slug:"hydro-geomorphology-models-and-trends",numberOfPages:122,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"865bfca98cafeeb9fdcf21c9453845f6",bookSignature:"Dericks P. Shukla",publishedDate:"October 18th 2017",coverURL:"https://cdn.intechopen.com/books/images_new/5805.jpg",numberOfDownloads:10138,numberOfWosCitations:12,numberOfCrossrefCitations:13,numberOfCrossrefCitationsByBook:2,numberOfDimensionsCitations:20,numberOfDimensionsCitationsByBook:3,hasAltmetrics:1,numberOfTotalCitations:45,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"September 28th 2016",dateEndSecondStepPublish:"October 19th 2016",dateEndThirdStepPublish:"January 15th 2017",dateEndFourthStepPublish:"April 15th 2017",dateEndFifthStepPublish:"June 14th 2017",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6,7",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"176921",title:"Dr.",name:"Dericks",middleName:null,surname:"Shukla",slug:"dericks-shukla",fullName:"Dericks Shukla",profilePictureURL:"https://mts.intechopen.com/storage/users/176921/images/6252_n.jpg",biography:"Dr. Dericks P. Shukla, assistant professor in the School of Engineering, Indian Institute of Technology Mandi (IIT Mandi), has more than 7 years of experience in the areas of remote sensing and GIS, natural hazard assessment and mapping, climatic-tectono-geomorphology and hydro-geochemistry. He has published more than 17 research papers in peer-reviewed journals and various conference papers. He has been working in the field of landslide susceptibility/hazard zonation and prediction, groundwater pollution mainly arsenic contamination and fluvial and glacial geomorphologic studies using remote sensing and GIS techniques. He has five ongoing projects as principal investigator funded by DLR (German Aerospace Agency); Space Application Centre, Indian Space Research Organization (SAC-ISRO); and Department of Science and Technology (DST).",institutionString:null,position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"2",totalChapterViews:"0",totalEditedBooks:"1",institution:{name:"Indian Institute of Technology Mandi",institutionURL:null,country:{name:"India"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"648",title:"Geomorphometry",slug:"geomorphometry"}],chapters:[{id:"57063",title:"Introductory Chapter: Geomorphology",doi:"10.5772/intechopen.70823",slug:"introductory-chapter-geomorphology",totalDownloads:2703,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:1,abstract:null,signatures:"Dericks Praise Shukla",downloadPdfUrl:"/chapter/pdf-download/57063",previewPdfUrl:"/chapter/pdf-preview/57063",authors:[{id:"176921",title:"Dr.",name:"Dericks",surname:"Shukla",slug:"dericks-shukla",fullName:"Dericks Shukla"}],corrections:null},{id:"55152",title:"Computation of Hydro-geomorphologic Changes in Two Basins of Northeastern Greece",doi:"10.5772/intechopen.68655",slug:"computation-of-hydro-geomorphologic-changes-in-two-basins-of-northeastern-greece",totalDownloads:1598,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"This chapter presents a composite mathematical model aiming at continuous simulations of hydro-geomorphological processes at the basin scale. Continuous hydrologic simulations, as well as continuous simulations of soil and streambed erosion processes, are performed in two neighbouring basins in northeastern Greece: Kosynthos river basin (district of Xanthi, Thrace, northeastern Greece) and Nestos river basin (Macedonia-Thrace border, northeastern Greece). Both basins are mountainous and covered by forested and bushy areas in their greatest part. Kosynthos river basin extends to an area of 237 km2, whilst Nestos river basin is quite bigger, covering an area of approximately 840 km2. The characteristic of Nestos river basin is the presence of a dam at its northwestern boundary, which largely affects the discharge, as well as the sediment transport in Nestos River. The application of the model results in continuous hydrographs and sediment graphs at the outlets of the two basins. Fine temporal scales are used, providing this way a continuous assessment of water and sediment discharge. The statistic efficiency criteria utilized for the comparison between computed and measured values of water and sediment discharge at the basin outlet provide satisfactory results. Therefore, it is concluded that the continuous hydro-geomorphologic modelling can be successfully applied to Kosynthos and Nestos river basins.",signatures:"Konstantinos Kaffas and Vlassios Hrissanthou",downloadPdfUrl:"/chapter/pdf-download/55152",previewPdfUrl:"/chapter/pdf-preview/55152",authors:[{id:"37707",title:"Prof.",name:"Vlassios",surname:"Hrissanthou",slug:"vlassios-hrissanthou",fullName:"Vlassios Hrissanthou"},{id:"200942",title:"Dr.",name:"Konstantinos",surname:"Kaffas",slug:"konstantinos-kaffas",fullName:"Konstantinos Kaffas"}],corrections:null},{id:"54918",title:"Analysis of the Impacts of Changes in Streamflow and of Restoration on the Morphological Evolution of the Matambin River Channel in the St. Lawrence Lowlands (Quebec, Canada)",doi:"10.5772/intechopen.68444",slug:"analysis-of-the-impacts-of-changes-in-streamflow-and-of-restoration-on-the-morphological-evolution-o",totalDownloads:1431,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:0,abstract:"Although many plots of land that were once farmed have been reforested in the St Lawrence Lowlands of Quebec since the 1950s, no study has yet looked at the morphological impacts of this land‐use change. To address this, we analyzed the evolution of the Matambin River (99 km2) channel width and sinuosity using diachronic analysis of air photographs taken between 1935 and 2008. Results of this analysis show a roughly 21% decrease in mean channel bankfull width from 1935 to 1964. This time interval was characterized by a low frequency of strong flood flows in the region and a roughly 32% increase in the forested land area, the reforestation having started in the 1950s. After 1964, a trend of increasing mean channel bankfull width is observed. This increase is associated with the increase in frequency of strong flood flows in the region and a decrease in the amount of suspended sediments produced by soil erosion following the increase in forest cover in the watershed. In contrast, channel sinuosity did not change much over the period from 1935 to 2008.",signatures:"Ali Assani, Lisanne Chauvette and Stéphane Campeau",downloadPdfUrl:"/chapter/pdf-download/54918",previewPdfUrl:"/chapter/pdf-preview/54918",authors:[{id:"50312",title:"Prof.",name:"Ali",surname:"Assani",slug:"ali-assani",fullName:"Ali Assani"}],corrections:null},{id:"54919",title:"The Modelling of Coastal Cliffs and Future Trends",doi:"10.5772/intechopen.68445",slug:"the-modelling-of-coastal-cliffs-and-future-trends",totalDownloads:1675,totalCrossrefCites:3,totalDimensionsCites:5,hasAltmetrics:0,abstract:"About 80% of the world’s oceanic shorelines include diverse types of cliffed and rocky coasts: plunging cliffs, bluffs backing beaches and rocky shore platforms. In combination, approximately 60% of the world’s population lives within 60 km of the coast. Rapidly retreating soft cliffs may be found worldwide and are particularly vulnerable to changes in the forcing factors. The study and analysis of the rate of change in shoreline position through time is important or even imperative for coastal management. The development of cliff erosion predictive models is mainly limited to geomorphological data because of the complex interactions between physical‐chemical processes acting simultaneously in time and space that result in large scale variations. Current historical extrapolation models use historical recession data, but different environments with the same historical values can produce identical annual retreat characteristics despite the potential responses to a changing environment being unequal. For that reason, process‐response models (PRMs) are necessary to provide quantitative predictions of the effects of natural and human‐induced changes that cannot be predicted using other models. Several models are explained and discussed, including a process‐response model, based on real data at Holderness Coast (UK).",signatures:"Ricardo Castedo, Carlos Paredes, Rogelio de la Vega‐Panizo and\nAnastasio P. Santos",downloadPdfUrl:"/chapter/pdf-download/54919",previewPdfUrl:"/chapter/pdf-preview/54919",authors:[{id:"196739",title:"Dr.",name:"Ricardo",surname:"Castedo",slug:"ricardo-castedo",fullName:"Ricardo Castedo"},{id:"204921",title:"Dr.",name:"Carlos",surname:"Paredes",slug:"carlos-paredes",fullName:"Carlos Paredes"},{id:"204922",title:"Dr.",name:"Rogelio",surname:"De La Vega-Panizo",slug:"rogelio-de-la-vega-panizo",fullName:"Rogelio De La Vega-Panizo"},{id:"204923",title:"Dr.",name:"Anastasio P.",surname:"Santos",slug:"anastasio-p.-santos",fullName:"Anastasio P. Santos"}],corrections:null},{id:"55617",title:"Digital Elevation Models in Geomorphology",doi:"10.5772/intechopen.68447",slug:"digital-elevation-models-in-geomorphology",totalDownloads:2731,totalCrossrefCites:8,totalDimensionsCites:13,hasAltmetrics:1,abstract:"This chapter presents place of geomorphometry in contemporary geomorphology. The focus is on discussing digital elevation models (DEMs) that are the primary data source for the analysis. One has described the genesis and definition, main types, data sources and available free global DEMs. Then we focus on landform parameters, starting with primary morphometric parameters, then morphometric indices and at last examples of morphometric tools available in geographic information system (GIS) packages. The last section briefly discusses the landform classification systems which have arisen in recent years.",signatures:"Bartłomiej Szypuła",downloadPdfUrl:"/chapter/pdf-download/55617",previewPdfUrl:"/chapter/pdf-preview/55617",authors:[{id:"196721",title:"Ph.D.",name:"Bartłomiej",surname:"Szypuła",slug:"bartlomiej-szypula",fullName:"Bartłomiej Szypuła"}],corrections:null}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},subseries:null,tags:null},relatedBooks:[{type:"book",id:"1591",title:"Infrared Spectroscopy",subtitle:"Materials Science, Engineering and Technology",isOpenForSubmission:!1,hash:"99b4b7b71a8caeb693ed762b40b017f4",slug:"infrared-spectroscopy-materials-science-engineering-and-technology",bookSignature:"Theophile Theophanides",coverURL:"https://cdn.intechopen.com/books/images_new/1591.jpg",editedByType:"Edited by",editors:[{id:"37194",title:"Dr.",name:"Theophile",surname:"Theophanides",slug:"theophile-theophanides",fullName:"Theophile Theophanides"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3161",title:"Frontiers in Guided Wave Optics and Optoelectronics",subtitle:null,isOpenForSubmission:!1,hash:"deb44e9c99f82bbce1083abea743146c",slug:"frontiers-in-guided-wave-optics-and-optoelectronics",bookSignature:"Bishnu Pal",coverURL:"https://cdn.intechopen.com/books/images_new/3161.jpg",editedByType:"Edited by",editors:[{id:"4782",title:"Prof.",name:"Bishnu",surname:"Pal",slug:"bishnu-pal",fullName:"Bishnu Pal"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"371",title:"Abiotic Stress in Plants",subtitle:"Mechanisms and Adaptations",isOpenForSubmission:!1,hash:"588466f487e307619849d72389178a74",slug:"abiotic-stress-in-plants-mechanisms-and-adaptations",bookSignature:"Arun Shanker and B. 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\r\n\tThis book will aim to be a self-contained collection of scholarly papers targeting an audience of practicing researchers, academics, psychologists, social workers, mentors, motivational speakers, life coaches, students, and other scientists. The contents of the book are intended to be written by multiple authors and experts from different related fields of psychology, philosophy, education, public health, human resource, and other human social sciences.
\r\n
\r\n\tCombining Motivation and Success as a book title demonstrates that these are complementary goods. When two goods are complements, they experience join demand. Meaning that the demand for one good is linked to the demand for another good. Indeed, our esteemed authors will aim to put together their scholarly work to showcase the importance of motivation leading to success and vice versa. Defined as a drive or a need, motivation is a driving force inside an individual to pursue a designated goal. While success is a state of meeting a targeted goal. This simply implies that motivated individuals are most successful and this is the core theme of the book.
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From chapter submission and review, to approval and revision, copy-editing and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. 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Venkateswarlu",coverURL:"https://cdn.intechopen.com/books/images_new/371.jpg",editedByType:"Edited by",editors:[{id:"58592",title:"Dr.",name:"Arun",surname:"Shanker",slug:"arun-shanker",fullName:"Arun Shanker"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"44437",title:"Combustion and Exhaust Emission Characteristics of Diesel Micro-Pilot Ignited Dual-Fuel Engine",doi:"10.5772/54613",slug:"combustion-and-exhaust-emission-characteristics-of-diesel-micro-pilot-ignited-dual-fuel-engine",body:'
1. Introduction
To satisfy increasingly strict emissions regulations, engines with alternative gaseous fuels are now widely used. Natural gas and synthesis gas appear to be greener alternatives for internal combustion engines [1-3]. In many situations where the price of petroleum fuels is high or where supplies are unreliable, the syngas, for example, can provide an economically viable solution. Syngas is produced by gasifying a solid fuel feedstock such as coal or biomass. The biomass gasification means incomplete combustion of biomass resulting in production of combustible gases. Syngas consists of about 40% combustible gases, mainly carbon monoxide (CO), hydrogen (H2) and methane (CH4). The rest are non-combustible gases and consists mainly of nitrogen (N2) and carbon dioxide (CO2). Varying proportions of CO2, H2O, N2, and CH4 may be present [4].
H2 as a main component of a syngas has very clean burning characteristics, a high flame propagation speed and wide flammability limits. H2 has a laminar combustion speed about eight times greater than that of natural gas, providing a reduction of combustion duration and as a result, an increase in the efficiency of internal combustion (IC) engines, if the H2 content in the gaseous fuel increases. Main point of interest in increasing H2 content in the gaseous fuel is that with the addition of H2, the lean limit of the gas operation can be extended, without going into the lean misfire region. Lean mixture combustion has a great potential to achieve higher thermal efficiency and lower emissions [5]. In particular, the lean mixture combustion will result in low and even extremely low NOx levels with only a slight increase in hydrocarbons [6, 7].
Some gas engines fueled with syngas have been developed recently [8-10]. Most of them have a spark-ignition (SI) combustion system. An SI engine is not suitable for this kind of fuel under high load conditions because of the difficulty in achieving stable combustion due to the fluctuation of the syngas components. In addition, the syngas is a low energy density fuel and the extent of power degrading is large when compared with high-energy density fuels like gasoline and natural gas. Natural gas and syngas have high auto-ignition temperature and hence cannot be used in CI engines without a means of initiating combustion, as the temperature attained at the end of the compression stroke is too low for the mixture to be auto-ignited. Therefore, dual-fuel-mode engine operation is required, in which gaseous fuel is ignited by pilot diesel fuel. Dual fueling can serve as a way of allowing the current fleet of CI engines to reduce their dependence on conventional diesel fuel while minimizing harmful emissions.
A number of researchers have performed experiments with natural gas and syngas to determine engine performance and exhaust emissions in dual-fuel engines. Their results indicate that lower NOx and smoke can be achieved in dual-fuel engines compared with conventional diesel engines, while maintaining the same thermal efficiency as a diesel engine. McTaggart-Cowan et al. [11] investigated the effect of high-pressure injection on a pilot-ignited, directly injected natural gas engine. They found that at high loads, higher injection pressures substantially reduce PM emissions. At low loads, the amount of PM emissions are independent of the injection pressure. Without EGR, NOx emissions are slightly increased at higher injection pressures due to the faster and more intense combustion caused by improved mixing of air and fuel and increased in-cylinder temperature. Su and Lin [12] studied the amount of pilot injection and the rich and lean boundaries of natural gas dual-fuel engines. They found that there is a critical amount of pilot diesel fuel for each load and speed. Tomita et al. [13] investigated the combustion characteristics and performance of the supercharged syngas with micro-pilot (injected fuel - 2 mg/cycle) ignition in a dual-fuel engine. They found that premixed flame of syngas-air mixture develops from multiple flame kernels produced by the ignition of diesel fuel. It was found that with the certain increase of hydrogen content in syngas the engine could operate even at equivalence ratio of 0.45 with stable combustion and high efficiency, because the increased hydrogen content enhanced the lean limit of the mixture. Liu and Karim [14] concluded that the observed values of the ignition delay in dual-fuel operation are strongly dependent on the type of gaseous fuels used and their concentrations in the cylinder charge. They showed that changes in the charge temperature during compression, preignition energy release, external heat transfer to the surroundings, and the contribution of residual gases appear to be the main factors responsible for controlling the length of the ignition delay of the engine.
The autoignition of the premixed mixture in the end-gas region is affected by the composition of syngas, in particular, by the amount of H2, CO, CO2 and CH4 in the gas. H2 has low ignition energy, and therefore, is easier to ignite, that results in a stronger tendency to autoignition and knock. H2 has a flame speed much greater than that of hydrocarbon fuels. Also, it has a lean limit of ϕlim=0.1, much lower than the theoretical limit of methane (ϕlim=0.5) [15]. Carbon dioxide, on the other hand, can weaken the reactivity of the in-cylinder mixture by diluting it, which results in a longer ignition delay time and slower heat release rate. Methane has excellent anti-knock properties, but suffers from low flame propagation rates and high auto-ignition temperature. Carbon monoxide can also affect the reactivity of the mixture. In fact, the oxidation of CO in the presence of H2 is important question concerning the syngas oxidation mechanism. It is well known that the overall reactivity is greatly accelerated if trace amounts of H2 and moisture are present. The oxidation route between CO and OH is the dominant pathway, and it accounts for a significant portion of the heat release [16].
The aforementioned results suggest that if certain operating conditions are maintained, including the control of pilot fuel injection quantity, pressure and timing, gaseous fuel equivalence ratio, and EGR rate, a compromise between increased efficiency and low exhaust emissions can be achieved. In this chapter, we document the range of operating conditions under which the new higher-efficiency PREMIER (PREmixed Mixture Ignition in the End-gas Region) combustion mode was experimentally tested. The objective of this work was in brief to discuss conventional micro-pilot injected dual-fuel combustion and in detail to explain about PREMIER combustion and emission characteristics in a pilot ignited supercharged dual-fuel engine fueled with natural gas and syngas, and to study the effect of H2 and CO2 content in syngas on the combustion and emission formation over the broad range of equivalence ratios under lean conditions.
This study used water-cooled four-stroke single-cylinder engine, with two intake and two exhaust valves, shown in Figure 1 (A). In this engine, the autoignition of a small quantity of diesel pilot fuel (2 mg/cycle), injected into the combustion chamber before top dead center, initiates the combustion. The burning diesel fuel then ignites the gaseous fuel. The pilot fuel was ultra low-sulfur (<10ppm) diesel. A commercial solenoid-type injector that is typically used for diesel-only operations was modified. A nozzle of the commercial injector with seven holes was replaced by the one with four holes of 0.1 mm in diameter to ensure a small quantity of injected fuel.
Diesel fuel injection timing and injection duration were controlled through the signals transferred to the injector from the injector driver. A common rail injection system (ECD U2-P, Denso Co.) was employed to supply the constant injection pressure to the injector. The common rail pressure was set and controlled via computer. The fuel injection pressure varied from 40 MPa to 150 MPa, and the injected pilot diesel fuel quantity was 2 mg/cycle and 3 mg/cycle. The experimental conditions and different types of primary gaseous fuel compositions used in this study are given in Table 1 and Table 2, respectively.
The in-cylinder pressure history of combustion cycles was measured with KISTLER-6052C pressure transducer in conjunction with a 0.5º crank-angle encoder to identify the piston location. The rate of heat release (ROHR) was calculated using this equation [17]:
dQdθ=γγ−1pdVdθ+1γ−1VdpdθE1
where θ is the crank angle (CA), p is the in-cylinder pressure at a given crank angle, V is the cylinder volume at that point and γ is the specific heat ratio. The ROHR represents the rate of energy release from the combustion process. The combustion transition from the first stage (slow flame propagation) to the second stage (end-gas autoignition) is identified from the ROHR. CO and NOx emissions were measured with a four-component analyzer Horiba PG-240, smoke was measured with a smoke meter Horiba MEXA-600s and HC emissions were measured with Horiba MEXA-1170HFID.
An elongated cylinder liner and elongated piston were installed on the engine, Figure 1 (B), to visualize dual-fuel combustion events and to capture images of combustion in an optical engine. The engine mentioned above in Figure 1 (A) was modified to allow facilitating the visualization experiments.
Table 1.
Experimental conditions
Table 2.
Gas composition
A sapphire window was installed on the top of the elongated piston. Temporal and spatial evolutions of visible flames were investigated by acquiring several images per cycle with MEMRECAM fx-K5, a high speed digital camera with the frame rate of 8000 fps in combination with a 45º mirror located inside the elongated piston. An engine shaft encoder and delay generator were used to implement camera-engine synchronization. The engine was first operated with motoring, then it was fired on only one cycle during which combustion images were captured.
Figure 2.
Dual fuel combustion of syngas with different amounts of injected diesel fuel (A) 10 mg and (B) 2 mg
Figure 2 shows the effect of pilot diesel fuel amount on combustion of syngas as a primary fuel. A distinct separation of diesel diffusion flame and syngas premixed flame is seen when larger amount of diesel fuel, 10 mg, is injected. The mixture burns only when the required oxygen is present. As a result, the flame speed is limited by the rate of diffusion. For syngas well-premixed mixture, the flame is not limited by the rate of diffusion and the mixture burning rate is much faster than that of diesel-air mixture. When only 2 mg of diesel fuel is injected the fuel evaporates and mixes with the oxidizer much faster providing distributed ignition centers in the cylinder for syngas-air mixture which is burnt as a premixed flame propagating towards the cylinder wall.
Figure 3 shows the dual-fuel combustion with natural gas (A) and syngas (B) as a primary fuel. The flame area growth for syngas is slower due to the presence of CO2 and CO. Although syngas contains H2, the effect of H2 on flame propagation is not clearly seen due to simultaneous oxidation of H2 and CO and the effect of CO2 diluting the air-fuel mixture. The effect of CO oxidation in the presence of H2 on flame propagation is a quite complex topic and is outside the scope of this chapter.
3. PREMIER micro-pilot ignited dual-fuel combustion
3.1. Concept of PREMIER combustion
Before giving a description to PREMIER (PREmixed Mixture Ignition in the End-gas Region) combustion, it is necessary to explain the differences of phenomenological outline between conventional combustion and knocking combustion in the dual-fuel engine. Conventional combustion is a combustion process which is initiated by a timed pilot ignited fuel and in which the multiple flame fronts caused by multiple ignition centers of pilot fuel, moves completely across the combustion chamber in a uniform manner at a normal velocity. Knocking combustion is a combustion process in which some part or all of the charge may be consumed (autoignited) in the end-gas region at extremely high rates. Much evidence of end-gas mixture auto-ignition followed by knocking combustion can be obtained from high-speed laser shadowgraphs [18], high-speed Schlieren photography [19], chemiluminescent emission [20], and laser-induced fluorescence [21]. In addition, Stiebels et al. [22] and Pan and Sheppard [23] showed that multiple autoignition sites occur during knocking combustion. The combustion mode we have monitored we believe differs from knocking combustion in terms of the size, gradients, and spatial distribution of the exothermic centers in the end-gas. This combustion concept was given a name PREMIER combustion.
A conceptual outline of PREMIER combustion is presented in Figure 4. In the first stage of this combustion mode, the pilot diesel fuel is injected, evaporated, and auto-ignited prior to top dead center (TDC). The energy released by the diesel fuel auto-ignition initiates the gaseous flame development and outward propagation from the ignition centers toward the cylinder wall. Once the end-gas region is sufficiently heated and the temperature of the fuel mixture has reached the auto-ignition temperature of the gaseous fuel/air mixture after TDC, the second-stage combustion begins and is completed as the gas expands and cools, producing work. The second-stage heat release occurs over a chemical reaction timescale and is faster than heat release by turbulent flame propagation. Thus, the combustion transition from the first stage to the second stage takes place when the overall heat release rate changes from the slower first-stage flame rate to the faster second-stage rate, and that transition is here measured as the point where the second derivative of the heat release rate is maximized, as shown in Figure 4.
Figure 4.
PREMIER combustion concept
PREMIER combustion in a dual-fuel engine is comparable to combining SI and CI combustion, which is being investigated by several researchers [24-26]. One disadvantage of these combustion strategies is that they are difficult to control under lean mixture conditions. The spark discharge is very short, and under light load and lean mixture conditions, the flame is too weak to propagate strongly and may be extinguished. Therefore, the combustion chamber must be specially designed to facilitate a stratified mixture charge around the spark plug electrodes. In a dual-fuel engine, on the other hand, combustion of the injected diesel fuel proceeds concurrently with that of the gaseous fuel mixture. This slow combustion of the diesel fuel helps to maintain the natural gas flame propagation and prevents the misfires that may occur under lean mixture conditions. The lean limit for the gaseous fuel/air mixture is of practical importance, as lean operation can result in both higher efficiency and reduced emissions. The major benefit of lean operation is the accompanying reduction in combustion temperature, which leads directly to a significant reduction in NOx emissions. The lean limit is the point where misfire becomes noticeable, and it is usually described in terms of the limiting equivalence ratio ϕlim that supports complete combustion of the mixture. For example, with the natural gas, if we operate slightly above the limiting equivalence ratio (for methane, ϕlim ≈ 0.5 [27]), the mixture reactivity becomes very sensitive to even very small variations in the air–fuel ratio. This high sensitivity is due to the presence of n-butane in the natural gas. It is known that small changes in the volume fraction of n-butane strongly affect the ignition properties of natural gas [28-31]. During hydrocarbon fuel oxidation, an H-atom is more easily abstracted from an n-butane molecule (with two secondary carbon atoms) than from other hydrocarbons such as methane, ethane, or propane [32]. As the equivalence ratio increases, the n-butane mass fraction in the natural gas/air mixture increases proportionally. During a fuel oxidation reaction, the in-cylinder gas temperature rises, and more of the radicals that initiate methane oxidation are created by increasing the ratio of n-butane. Similar results were documented by other researchers who investigated the auto-ignition and combustion of the natural gas in an HCCI engine [33]. They found that very small increases in the equivalence ratio of the methane/n-butane/air mixture produced significant changes in the profiles of the in-cylinder pressure traces.
If not extinguished during the early combustion stage, the pilot diesel flame may continue to a later stage, and pilot flame energy contributes to the stability of the combustion process [34]. The remaining unburned in-cylinder mixture from the first stage, located beyond the boundary of the flame front, is then subjected to a combination of heat and pressure for certain duration. As the flame front propagates away from the primary ignition points, end-gas compression raises the end-gas temperature and pressure. When the mixture is preheated throughout the combustion chamber volume and the end-gas mixture reaches the auto-ignition point, simultaneous auto-ignition occurs in several limited locations (known as exothermic centers), with a sharp increase in heat release. This part of the combustion appears as a rapid energy release in the second stage of the heat release curve shown in Figure 4.
A prime requirement for maintaining PREMIER combustion mode in a dual-fuel engine is that the mixture must not auto-ignite spontaneously during or following the rapid release of pilot energy. Failure to meet this requirement can lead to the onset of knock, which manifests itself in excessively sharp pressure increases and overheating of the walls, resulting in significant loss of efficiency with increased cyclic variations. When much smaller pilots are used, the energy release during the initial stages of ignition and the resulting turbulent flame propagation can (under certain conditions) lead to auto-ignition of the charge well away from the initial ignition centers, in the end-gas regions ahead of the propagating flames. This can occur in a manner that resembles the occurrence of knock in spark-ignition engines, but with controlled heat release. For the sake of convenience, the total energy release rate during PREMIER combustion can be divided into three sequential components. The first of these is due to the ignition of the pilot fuel. The second is due to the combustion of the gaseous fuel in the immediate vicinity of the ignition centers of the pilot, with consequent flame propagation. The third is due to auto-ignition in the end-gas region.
4. PREMIER combustion detection (Natural gas)
4.1. Cyclic variations and FFT of in-cylinder pressure
Cycle-to-cycle variations of the in-cylinder pressure during conventional, PREMIER, and knocking combustion with natural gas are identified by over-plotting 80 cycles of a measured pressure trace. From Figure 5, we observe that cycle-to-cycle pressure variations were present in all cases considered, and they varied according to the injection timing θinj. It should be noted that under normal combustion conditions, the magnitude of the peak pressure (which is directly related to the power output) depends on θinj, and Pmax is higher for advanced θinj. Unfortunately, the advantage of this peak pressure increase is offset by the disadvantages of increased fluctuation and the occurrence of knock.
Figure 5.
Cyclic maximum pressure versus its angle (Pmax, θPmax) for different injection timings. Pinj=80 MPa, Pin=200 kPa, Dhole= 0.1 mm, Nhole=3, mdf=2 mg/cycle, ϕt=0.6
Thus, when slow combustion dominates, the Pmax fluctuations are small, whereas during fast combustion, the Pmax fluctuations are larger. With advanced fuel injection timing, the combustion was too fast, and the mixture auto-ignited spontaneously during or following the rapid pilot energy release. This led to the onset of knock. However, with a slight retardation of the injection timing, the energy release during the initial stages of ignition and the resulting turbulent flame propagation may induce auto-ignition of the charge in the end-gas regions ahead of the propagating flame, followed by PREMIER combustion. The stability of PREMIER combustion was confirmed by running an engine mentioned in Figure 1 (A) continuously for 30 minutes. As the engine operation reached a steady condition, Pmax stabilized within a definite range between conventional and knocking combustion modes. It should be noticed that the present achieved stability of PREMIER combustion allows using this mode in stationary engines, such as engines used for power generation. In order to utilize PREMIER combustion in vehicles, further research is required to find optimum ways to precisely control the conditions inside the cylinder at various loads.
The transition from PREMIER combustion to knocking combustion was evaluated by fast Fourier transform (FFT) analysis of the in-cylinder pressure and the knock-sensor signal. The details of FFT analysis are given in [35]. Unlike during knocking in traditional spark-ignition engines, high frequency oscillations of in-cylinder pressure and knock-sensor signals were not observed during the PREMIER combustion mode.
The in-cylinder pressure and knock-sensor signals were filtered using an FFT band-pass filter with 4-20 kHz cutoff frequencies. The filtered pressure data was used to define the knock intensity. Figure 6 shows that during PREMIER combustion mode, the measured cylinder pressure curve was smooth, and the maximum rate of pressure rise (which was only 0.36 MPa/CA deg.) occurred at 17º ATDC under the conditions Pint=200 kPa, mdf=2 mg/cycle, Pinj=80 MPa and θinj=4.5º BTDC. Pressure oscillations did not occur, and the pressure sensor was unable to detect a sawtooth pattern on the measured pressure trace. For the same conditions mentioned above, but at θinj=5º BTDC, the transition from PREMIER to knocking combustion occurred at the maximum rate of pressure increase (dP/dθ=0.55 MPa/CA deg.), with a knock intensity of KINT=0.3 MPa. At θinj=5.5º BTDC, strong knocking combustion was detected with dP/dθ=1.87 MPa/CA deg. and KINT=1.45 MPa. As the figure indicates, oscillations of the in-cylinder pressure and the knock sensor signal were not detected during PREMIER combustion mode. Weak oscillations were detected during the transition from PREMIER to knocking combustion, and stronger oscillations were detected at 6.52 kHz and 10.1 kHz during knocking combustion. The peak at the transition to knocking combustion was correspondingly lower than the peak that occurred during heavy knocking combustion.
Figure 6.
FFT analysis of in-cylinder pressure. Pinj=80 MPa, Pin=200 kPa, Dhole= 0.1 mm, Nhole=3, mdf=2 mg/cycle, ϕt=0.6
4.2. Spectroscopy analysis
The configuration of our optical engine made it difficult to directly visualize auto-ignition in the end-gas region with an optical engine setup shown in Figure 1 (B). Since auto-ignition in the end-gas region usually occurs closer to the cylinder wall, the auto-ignition region was hidden from the camera view by the top of the elongated piston, where a sapphire window was installed. Thus, an optical sensor was inserted in the region based on the most probable occurrence of auto-ignition in the end-gas region, as shown in Figure 7. The small effect of measurement location on autoignition and flame development was confirmed based on several preliminary experiments. Besides, this measurement location was selected to keep the sensor away from the highly luminescent soot radiation. If the sensor is placed too close to the luminous emissions from diesel combustion, these emissions can supersede the OH* radical emissions, which are expected to occur during PREMIER combustion. Chemical luminescence emissions from the propagating flame and end-gas region auto-ignition were measured using a spectrometer equipped with intensified charge-coupled device (ICCD). The regions of spectroscopy measurements for conventional, PREMIER and knocking combustion, along the crank angle degrees, are shown in Figure 8. In-cylinder pressure and the rate of pressure rise change as injection timing is advanced for conventional, θinj=4º BTDC, PREMIER, θinj=8º BTDC and knocking, θinj=13º BTDC, combustion. Exposure time of the spectrometer for all three combustion regimes was set to 3º CA. The highlighted region on each graph shows the interval within which the measurements were taken.
Figure 9 shows the background light-subtracted ensemble-averaged spectra obtained between 200 and 800 nm as the propagating flame arrived in the vicinity of the optical sensor and auto-ignition occurred in the end-gas region. The background light was subtracted by the signal processing using a percentile filter. The waveforms of the emission spectroscopy were obtained for knocking cycles in the range of 0º-3º, 3º-6º, and 6º-9º ATDC, for PREMIER cycles in the range of 6º-9º, 9º-12º, and 12º-15º ATDC, and for conventional cycles in the range of 12º-15º, 15º-18º, and 18º-21º ATDC.
Figure 7.
Optical sensor location and design
High OH* radical emission intensities were evident at wavelength 310 nm and very weak intensities at wavelength 286 nm when the flame front reached the optical sensor location region. OH* radical emission intensities at this wavelengths were stronger for knocking combustion cycles than for PREMIER combustion cycles, and for conventional combustion cycles these emission intensities were not seen. A similar trend was observed by Itoh et al. [36] and Hashimoto et al. [37]. These authors reported that under non-knocking operation, OH* radicals exhibit comparatively weak emission intensities. However, the OH* radical emission intensity gradually increased for autoignition and knocking cycles in comparison with a conventional cycle.
Figure 8.
In-cylinder pressure and the rate of pressure rise. Pinj=40 MPa, Pin=200 kPa, Dhole=0.1mm, Nhole=3, mdf=2 mg/cycle, ϕt=0.6
Figure 9 shows that for the knocking cycle, the OH* peak at 310 nm increased sharply at 6º ATDC and then decreased at 9º ATDC. 6º ATDC corresponds to the timing of the maximum rate of pressure rise, and 9º ATDC corresponds to the timing when the rate of pressure rise is gradually decreased. Before natural gas propagating flame (1st stage combustion) is stabilized, the rapid autoignition occurs in multiple spots. The end-gas autoignition kernel growth rate is much faster than that of flame propagation.
The drastic increase in OH* emissions is related to the sharp pressure and temperature increases in the end-gas region. It has been reported that the concentration of OH* radicals shows a strong temperature dependence in the thermal ignition region [38]. The thermal ignition is the hydrogen-oxygen system reactions, and the CO conversion into CO2 with the assistance of OH* takes place simultaneously with the hydrogen-oxygen system reactions. It has been observed that the OH* emission intensity at auto-ignition shows the same tendency as the correlation between the occurrence of auto-ignition and the knocking intensity [39]. On the other hand, the OH* peaks of PREMIER combustion at 12º and 15º ATDC have the same magnitude. 12º ATDC corresponds to the timing of the maximum rate of pressure rise, and 15º ATDC corresponds to the timing after the peak of the rate of pressure rise. The reason for the same magnitude in OH* is that the maximum rate of pressure rise is slower than that of during knocking case. The end-gas autoignition kernel growth rate is comparable with that of flame propagation. The mixture in the end-gas region reacts steadily with the steady OH*emission.
Figure 9.
Detailed spectra in the end-gas region. Pinj=40 MPa, Pin=200 kPa, Dhole=0.1 mm, Nhole=3, mdf=2 mg/cycle, ϕt=0.6
The emissions at the wavelengths above 700 nm are due to diesel luminous flame. The previous shock tube measurements showed that continuum emission at wavelengths above 650 nm was due to either young soot particles or large hydrocarbon molecules [40]. Zhao and Ladommatos [41] showed that the maximum emissive power of soot particles, estimated as a blackbody, occurs in the range of about 680–1100 nm. Vattulainen et al. [42] confirmed that the light emitted by a diesel flame is dominated by soot incandescence, and the emission range was determined to be about 650–800 nm. The emissions at the wavelengths above 700 nm shown in Figure 9 correspond to 1-5% of the total wavelength emission band from a blackbody at the estimated average peak burned-gas temperature of 2310 K under knocking conditions, which correspond to 1.823×105-4.935×105 W/m2 μm of spectral emissive power, with the maximum spectral emissive power at that temperature that equals to 8.459×105 W/m2 μm [43].
5. PREMIER combustion characteristics
5.1. Natural gas combustion characteristics
To maintain PREMIER combustion in a dual-fuel natural gas engine, the effects of several operating parameters must be identified. Our experimental results show that the major parameters that may significantly influence the energy release pattern during dual-fuel PREMIER combustion are pilot diesel fuel injection timing and the EGR rate, which can affect the total equivalence ratio based on oxygen content. Other parameters such as pilot fuel injection pressure, injected pilot fuel amount, nozzle hole diameter, and hole number have minor effects on PREMIER combustion.
5.1.1. Effect of injection timing
As shown in Figure 10, PREMIER combustion can be maintained within a wide range of pilot fuel injection pressures. However, it can be maintained within only a very narrow range of fuel injection timings. At a fixed total equivalence ratio, advancing the injection timing resulted in the earlier occurrence of combustion during the cycle, increasing the peak cylinder pressure during first-stage combustion. With the burned gas of first-stage combustion, the in-cylinder pressure and temperature continued to rise after TDC, as shown in Figure 10. Although the piston began to move downward after TDC, and the volume thus expanded, the heat release from first-stage combustion induced local temperature and pressure increases during second-stage combustion. Higher peak cylinder pressures resulted in higher peak charge temperatures. Retarding the injection timing decreased the peak cylinder pressure during first-stage combustion, as more of the fuel burned after TDC.
Advancing the injection timing resulted in better diesel fuel evaporation and mixing with the in-cylinder gas. Therefore, diesel fuel auto-ignition occurred more quickly and with more complete diesel fuel combustion and natural gas flame propagation during the first stage, resulting in rapid combustion and high heat release rate during the second stage due to the rapid heating of the end-gas region mixture.
Figure 10.
Effect of pilot fuel injection timing on cylinder pressure and the rate of heat release. Experimental conditions are given in Table 3.
5.1.2. Mass fraction burned in the second stage of ROHR
Figure 11 shows a relation between the rate of maximum pressure rise and the second stage autoignition delay. The second stage autoignition delay time was estimated as a time between two peaks of the second derivative of the ROHR, as shown in Figure 4. Figure 11 also shows that for the range of experimental conditions the mass fraction burned during the second stage of the ROHR is remained nearly the same, although IMEP increases. This increase in IMEP is due to faster and more intense combustion with the shorter duration in both first and second stage of the ROHR. Reduced heat loss during shorter combustion duration ensures higher in-cylinder pressure and temperature, and therefore, higher IMEP. This trend suggests that the second stage combustion is influenced by the first stage. Although the mass fraction burned in the second stage is the same, the combination of several operational parameters such as pilot fuel injection pressure, injection timing, the amount of injected pilot fuel, gaseous fuel equivalence ratio and nozzle characteristics may affect, to a certain degree, the progress of PREMIER combustion.
Figure 11.
Second stage autoignition delay and mass fraction burned during the second stage of combustion of natural gas
5.1.3. Effect of EGR
PREMIER combustion becomes clearly recognizable if the EGR rate remains below a certain level. When the EGR rate surpasses this level, the unburned mixture temperature decreases, retarding the combustion of the natural gas and affecting the reactivity of the mixture to auto-ignite in the end-gas region. As Figure 12 shows, at 200 kPa of intake pressure and moderate EGR rates, the first-stage combustion rate increased, and second-stage heat release was able to occur. A similar trend was also observed at 101 kPa of intake pressure, although not shown here. These results suggest that the use of EGR may not be advantageous for achieving PREMIER combustion. However, it should be noted that for engine operation close to the knock-limit conditions, the high combustion rate of natural gas may be markedly decreased by using a certain limited EGR rate, and maintaining PREMIER combustion mode as the knocking effect is suppressed.
Figure 12.
Effect of EGR on cylinder pressure and the rate of heat release. Pinj=40 MPa, Pin=200 kPa, Dhole=0.1 mm, Nhole=3, mdf=2 mg/cycle
5.2. Natural gas exhaust emission characteristics
Figure 13 shows the engine performance characteristics and exhaust gas emissions. The encircled data on (A) and (B) of the figure correspond to PREMIER combustion. During PREMIER combustion, a considerable increase in the indicated mean effective pressure and thermal efficiency was observed. This was due to the sharp increase of the second heat-release peak within a shorter crank-angle time, as seen in Figures 10 and 12. Moreover, this implies that the total combustion time for PREMIER combustion mode was shorter than the total time required for conventional combustion. Although HC and CO emissions were greatly decreased, NOx emissions increased considerably compared with conventional combustion. This increase in NOx emissions is expected, as in-cylinder temperature increase hastens the oxidation reactions of in-cylinder nitrogen and oxygen.
Figure 13.
Effect of pilot fuel injection timing and EGR on engine performance and emissions. (A) conditions correspond to those of Figure 10, (B) conditions correspond to those of Figure 12.
5.3. Syngas combustion characteristics
Figure 14 indicates the relationship between the rate of maximum pressure rise and the second stage autoignition delay. The second stage autoignition delay time was estimated as time between two peaks of the second derivative of the ROHR as shown in Figure 4. It was found that for all types of gases investigated in this chapter the autoignition delay of the second stage decreases with the increase of the rate of maximum pressure rise.
Figure 15 shows the in-cylinder pressure and ROHR for Type 1 (A) and Type 2 (B) of syngas at different equivalence ratios and various injection timings. The results show that the maximum pressure and heat release rate reached higher values for the gas with higher H2 content. As the injection timing was gradually advanced, PREMIER combustion with second-stage heat release occurred. PREMIER combustion was observed at various equivalence ratios for certain injection timings. For instance, for Type 1 gas, two-stage heat release appeared at ϕ = 0.4 starting from 23º BTDC, at ϕ = 0.52 from 15º BTDC, at ϕ = 0.68 from 9º BTDC, and at ϕ = 0.85 from 7º BTDC. The same trend was observed for Type 2 gas, but the maximum heat release rate was higher than that of Type 1, due to the higher H2 content. The maximum cylinder pressure for Type 2 decreased at an equivalence ratio of 0.83, since the injection timing in that case needed to be retarded to around TDC (and even to the expansion stroke) to avoid knock. At the same time, for Type 1 gas at an equivalence ratio of 0.85 and injection timings before TDC, PREMIER combustion was clearly observed without any knock. These results seem to suggest that the increased H2 content of Type 2 gas affected the ignitability and corresponding progress of combustion that leads to engine knock.
Figure 14.
Second stage autoignition delay. Pinj=80 MPa, Pin=200 kPa, mdf=3 mg/cycle
Figure 15.
Comparison of in-cylinder pressure and ROHR. Syngas, (A) Type 1, (B) Type 2
5.3.1. Effect of H2 content on PREMIER combustion
An increase in hydrogen content of syngas results in an increase of ignitability and a corresponding reduction in ignition delay of the first stage. To investigate the effect of mass fraction burned in the second stage and the effect of hydrogen content on the rate of maximum pressure rise, the ratio MFB2stHR/MFBtotal was evaluated. MFB2stHR is the integral of the mass fraction burned during the second stage, computed from the transition point where the peak of d2(ROHR)/dθ2 is maximized to the 80% MFB. MFBtotal is the integral of the total mass fraction burned, computed from the first peak of d2(ROHR)/dθ2 to the 80% MFB. Figure 16 shows that as the mass fraction burned increases the rate of maximum pressure rise also increases. The same trend was monitored at various equivalence ratios.
Figure 17 shows the effect of H2 content on the mean combustion temperature, IMEP, indicated thermal efficiency and NOx for conventional and PREMIER combustion at the same input energy Qin=2300 J/cycle and injection timing at the minimum advance for the best torque (MBT). As this figure shows, the increase in H2 amount affects the engine combustion characteristics. For PREMIER combustion, the mean combustion temperature and consequently the NOx significantly increase when compared with those of conventional combustion. IMEP and indicated thermal efficiency increase about 10%. Therefore, in dual-fuel combustion of low-energy density syngas, PREMIER combustion is an important combustion mode that tends to increase the engine efficiency.
Figure 16.
Fuel mass fraction burned with the change of H2 content
5.3.2. Effect of CO2 content on PREMIER combustion
An increase in CO2 content in syngas results in a dilution of the mixture with the corresponding reduction in the rate of fuel oxidation reactions and consequent combustion. To investigate the effect of mass fraction burned in the second stage and the effect of CO2 content on the rate of maximum pressure rise, the same procedure was applied as explained in the previous section.
Figure 17.
Effect of H2 content on engine performance characteristics at θinj=MBT
Figure 18 shows that for Type 1 and Type 4 as the mass fraction burned during the second stage increases the rate of maximum pressure rise also increases. However, for Type 5 with 34% of CO2 content in syngas, the rate of maximum pressure rise decreases with the increase of the mass of fuel burned in the second stage. This can be explained by the fact that although the total mass of syngas burned during the second stage increases, the CO2 fraction in the gas also proportionally increases. Eventually, the certain threshold can be reached when the effect of CO2 mass fraction in the gas on combustion overweighs the effect of H2.
Figure 18.
Fuel mass fraction burned with the change of CO2 content
Figure 19 shows the effect of CO2 content on the mean combustion temperature, IMEP, indicated thermal efficiency and NOx for conventional and PREMIER combustion at the same input energy Qin=2300 J/cycle and injection timing at MBT. In this figure the trend mentioned earlier in Figure 18 is clearly observed.
The mean combustion temperature, IMEP, the indicated thermal efficiency and the NOx shows the increase when CO2 content in the gas increases from 16.8% to 23%. However, as CO2 concentration reaches 34%, above mentioned combustion characteristics decrease. This trend was observed for both conventional and PREMIER combustion. Therefore, in order to achieve high combustion efficiencies in dual-fuel engines fuelled with low-energy density syngas, CO2 fraction in syngas needs to be controlled.
Figure 19.
Effect of CO2 content on engine performance characteristics at θinj=MBT
5.4. Syngas exhaust emission characteristics
Increasing hydrogen content in syngas has a substantial impact on engine performance and pollutants formation. Engine performance characteristics and concentrations of pollutants CO, HC and NOx are shown in Figures 20 and 21. It should be noticed that the smoke level was negligibly low. Figure 3 (B) shows highly luminous diesel fuel droplets burn exposed to the high temperature syngas flame. This concurrent micro-pilot diesel fuel and syngas combustion contributes to the faster oxidation and burn out of soot by the end of the combustion process.
Figures 20 and 21 show the experimental operation region for IMEP, CO, HC and NOx. The comparison is given for H2 effect between Type 1 and Type 2, for CO2 effect between Type 1 and Type 5, and for gas - type effect between Type 6 (Coke-oven gas) and Type 8 (Pure hydrogen). The dash-dotted line is the boundary separated the conventional combustion from the PREMIER combustion at corresponding equivalence ratios and injection timings.
Figure 20.
Experimental mapping of IMEP and CO distribution
Figure 20 shows that higher IMEP levels appear at higher equivalence ratios and advanced injection timings. PREMIER combustion mode may pass through different IMEP levels, depending on the equivalence ratio and injection timing. As H2 fraction increases in the syngas (from Type 1 to Type 2), PREMIER combustion region expands at lower equivalence ratios and shrinks at higher equivalence ratios. On the contrary, as CO2 fraction increases in the syngas, from Type 1 (16.8% CO2) to Type 5 (34% CO2), the same maximum level of IMEP, as for Type 1 and 2, can be achieved with only higher equivalence ratios. Type 1 and Type 5 show that as CO2 content increases IMEP slightly decreases. With the increase of CO2 fraction in the syngas the PREMIER combustion region threshold is shifted towards the boundary of operation domain. This implies that the operational region of PREMIER combustion mode is reduced.
Figure 20 (Type 1 and Type 2) and Figure 21 (Type 1 and Type 2) show that with the increase of H2 concentration in the gas content, CO and HC emissions are reduced. The cause of these reductions is most likely the enhanced oxidation occurring because of improved combustion and higher concentrations of reactive radicals since the carbon content in the gas is the same for both types of fuel. The NOx emissions, as in Figure 21, are higher for Type 2 than those for Type 1 due to higher H2 content. This is in part a direct result of hydrogen’s higher flame temperature effect on NO formation chemistry. NOx emissions are consistently reduced by lowering equivalence ratio for both types. For Type 5, as CO2 content in the gas increases to 34%, the NOx reduction trend is obvious.
Figure 21.
Experimental mapping of HC and NOx distribution
The opposite trend is observed for Type 6, as shown in Figure 20. This type of gas has very high content of H2-56.8%, and very low content of CO2-2.2%. For the limited range of equivalence ratios and injection timings, the PREMIER combustion region is very narrow, and at even higher equivalence ratios, the stable combustion will easily turn to knocking. These results show that in order to achieve PREMIER combustion with the best case scenario in terms of efficiency and emissions the equivalence ratio and injection timing should be maintained within certain range, depending on H2 and CO2 fractions in syngas. Figure 21 shows that for Type 6 the NOx emissions can be compared with those of Type 2. Even with the retarding of the injection timing closer to TDC, NOx emissions level is still comparably high. On the other hand, CO emissions are significantly reduced.
In addition, the performance and emissions of pilot-ignited dual-fuel engine operated on 100% H2 as a primary fuel was investigated, shown as Type 8. The data at equivalence ratios of 0.2, 0.25 and 0.3 are related to the engine operation without dilution. Further increase in equivalence ratio above 0.3 caused knocking combustion. To further increase the energy supply from hydrogen the equivalence ratio of 0.35 was used with the 40%, 50% and 60% of N2 dilution. Previous research suggests that NOx emissions in hydrogen-fueled engines can be reduced by using EGR or using the nitrogen dilution [44, 45]. These studies reported that NOx emissions were reduced by the reduction in peak combustion temperature due to the presence of diluent gas. Mathur et al. [45] showed that with larger concentrations of nitrogen as diluent, a greater amount of combustion heat can be absorbed, which results in reducing peak flame temperature and NOx. IMEP increases with the equivalence ratio. For the equivalence ratios of 0.2 and 0.25, the minimum advanced injection timing for the maximum IMEP was obtained at 17º BTDC and 12º BTDC, respectively. At these injection timings PREMIER combustion occurs. For the case with N2 dilution, injection timing has greater effect on IMEP than the dilution rate. IMEP gradually increased as the injection timing was advanced along with the increased amount of diluent from 40% to 60%. Due to low equivalence ratios, very low level of NOx was detected without N2 dilution. At the conditions with N2 dilution the NOx showed further decrease. For the conditions without dilution, CO and HC emissions were significantly reduced to the level of about 6 ppm and 20 ppm, respectively. However, for the conditions with N2 dilution CO varied from min.-15 ppm to max.-891 ppm and HC varied from min.-20 ppm to max.-125 ppm.
6. Conclusion
The new PREMIER combustion mode in a dual-fuel engine fuelled with natural gas, syngas and hydrogen was investigated via engine experiments. The following conclusions can be drawn from this research:
PREMIER combustion combines two main stages of heat release, the first is gaseous fuel flame propagation and the second is end-gas mixture auto-ignition. The second stage can be mainly controlled by the pilot fuel injection timing, gaseous fuel equivalence ratio, and EGR rate. The delay time for mixture autoignition in the end-gas region is defined as the time from early kernel development to the transition point where slower combustion rate (flame propagation) is changed to faster combustion rate (autoignition). It was found that the rate of maximum pressure rise increases as the second stage ignition delay decreases. PREMIER combustion was observed for natural gas and all syngas types investigated in this paper. This type of combustion can enhance the engine performance and increase the efficiency.
In both PREMIER and knocking combustion with natural gas, moderate and high intensities of OH* radicals were detected, respectively, at wavelengths of 286 and 310 nm when the flame front reached the optical sensor location region. In knocking combustion, the OH* radical emission intensities were stronger than those in PREMIER combustion, and in conventional combustion, these emission intensities could barely be detected. PREMIER combustion differs from knocking combustion in terms of size, gradients, and spatial distribution of exothermic centers in the end-gas region. High-frequency oscillation of the in-cylinder pressure did not occur during the PREMIER combustion mode with natural gas.
An increase in the fuel mass fraction burned in the second stage of heat release affects the rate of maximum pressure rise. When hydrogen content in syngas is increased the same rate of maximum pressure rise can be achieved with lower amount of fuel mass fraction burned during the second stage, meaning that the increased amount of hydrogen in syngas induces an increase in the mean combustion temperature, IMEP and efficiency, but also a significant increase in NOx emissions. The results also show that when CO2 content in the gas reaches 34%, the rate of maximum pressure rise, as well as, the mean combustion temperature, IMEP, thermal efficiency and NOx decrease despite the increase in fuel mass fraction burned during the second stage of heat release rate.
For pure hydrogen at equivalence ratios of 0.2, 0.25 and 0.3 without dilution, very low CO and HC emissions were detected. The further increase in equivalence ratio above 0.3 led to knocking combustion. At the equivalence ratio of 0.35 with N2 dilution, NOx level significantly decreased but CO level increased.
\n',keywords:null,chapterPDFUrl:"https://cdn.intechopen.com/pdfs/44437.pdf",chapterXML:"https://mts.intechopen.com/source/xml/44437.xml",downloadPdfUrl:"/chapter/pdf-download/44437",previewPdfUrl:"/chapter/pdf-preview/44437",totalDownloads:10834,totalViews:728,totalCrossrefCites:9,totalDimensionsCites:14,totalAltmetricsMentions:14,introChapter:null,impactScore:5,impactScorePercentile:93,impactScoreQuartile:4,hasAltmetrics:1,dateSubmitted:"November 22nd 2011",dateReviewed:"October 24th 2012",datePrePublished:null,datePublished:"April 30th 2013",dateFinished:"April 29th 2013",readingETA:"0",abstract:null,reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/44437",risUrl:"/chapter/ris/44437",book:{id:"2432",slug:"diesel-engine-combustion-emissions-and-condition-monitoring"},signatures:"Ulugbek Azimov, Eiji Tomita and Nobuyuki Kawahara",authors:[{id:"142408",title:"Dr.",name:"Ulugbek",middleName:null,surname:"Azimov",fullName:"Ulugbek Azimov",slug:"ulugbek-azimov",email:"ulugbek.azimov@northumbria.ac.uk",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/142408/images/3892_n.jpg",institution:{name:"Northumbria University",institutionURL:null,country:{name:"United Kingdom"}}},{id:"142429",title:"Prof.",name:"Eiji",middleName:null,surname:"Tomita",fullName:"Eiji Tomita",slug:"eiji-tomita",email:"tomita@mech.okayama-u.ac.jp",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"Okayama University",institutionURL:null,country:{name:"Japan"}}},{id:"142431",title:"Prof.",name:"Nobuyuki",middleName:null,surname:"Kawahara",fullName:"Nobuyuki Kawahara",slug:"nobuyuki-kawahara",email:"kawahara@mech.okayama-u.ac.jp",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"Okayama University",institutionURL:null,country:{name:"Japan"}}}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Conventional micro-pilot injected dual-fuel combustion",level:"1"},{id:"sec_2_2",title:"2.1. Experimental procedure and conditions",level:"2"},{id:"sec_4",title:"3. PREMIER micro-pilot ignited dual-fuel combustion",level:"1"},{id:"sec_4_2",title:"3.1. Concept of PREMIER combustion",level:"2"},{id:"sec_6",title:"4. PREMIER combustion detection (Natural gas) ",level:"1"},{id:"sec_6_2",title:"4.1. Cyclic variations and FFT of in-cylinder pressure",level:"2"},{id:"sec_7_2",title:"4.2. Spectroscopy analysis",level:"2"},{id:"sec_9",title:"5. PREMIER combustion characteristics",level:"1"},{id:"sec_9_2",title:"5.1. Natural gas combustion characteristics ",level:"2"},{id:"sec_9_3",title:"Table 3.",level:"3"},{id:"sec_10_3",title:"5.1.2. Mass fraction burned in the second stage of ROHR",level:"3"},{id:"sec_11_3",title:"5.1.3. Effect of EGR",level:"3"},{id:"sec_13_2",title:"5.2. Natural gas exhaust emission characteristics",level:"2"},{id:"sec_14_2",title:"5.3. Syngas combustion characteristics",level:"2"},{id:"sec_14_3",title:"5.3.1. Effect of H2 content on PREMIER combustion ",level:"3"},{id:"sec_15_3",title:"5.3.2. Effect of CO2 content on PREMIER combustion",level:"3"},{id:"sec_17_2",title:"5.4. Syngas exhaust emission characteristics",level:"2"},{id:"sec_19",title:"6. Conclusion",level:"1"}],chapterReferences:[{id:"B1",body:'WeaverC. SNatural gas vehicles- a review of the state of the art, SAE Paper, 892133.'},{id:"B2",body:'NicholsR. JThe challenges of change in the auto industry: Why alternative fuels? J Eng Gas Turb Power 199411672732'},{id:"B3",body:'LieuwenTYangVYetterRSynthesis gas combustion: Fundamentals and applications. Taylor & Francis Group 2010'},{id:"B4",body:'ShillingN. ZLeeD. TIGCC-Clean power generation alternative for solid fuels: GE Power Systems. PowerGenAsia 2003'},{id:"B5",body:'Bade Shrestha SOKarim GA. 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Trans. Japan Soc. Mech. Eng. 1985'},{id:"B40",body:'CoatsC. Mand WilliamsAInvestigation of the ignition and combustion of n-Heptane-oxygen mixtures. Proc. Combust. Institute 197917611621\n\t\t\t'},{id:"B41",body:'ZhaoHand LadommatosNOptical diagnostics for soot and temperature measurement in diesel engines. Prog. Energy Combust. Sci. 199824221255'},{id:"B42",body:'VattulainenJExperimental determination of spontaneous diesel flame emission spectra in a large diesel engine operated with different diesel fuel qualities. SAE Paper, 981380.\n\t\t\t'},{id:"B43",body:'IncroperaF. Pand DewittD. PFundamentals of heat and mass transfer, 4th edition, 1996John Wiley & Sons).\n\t\t\t'},{id:"B44",body:'BoseP. KMajiDAn experimental investigation on engine performance and emissions of a single cylinder diesel engine using hydrogen as induced fuel and diesel as injected fuel with exhaust gas recirculation. Int J Hydrogen Energy 200934484754'},{id:"B45",body:'MathurH. BDasL. MPatroT. NHydrogen-fuelled diesel engine: Performance improvement through charge dilution techniques. Int J Hydrogen Energy 19931842131'}],footnotes:[],contributors:[{corresp:null,contributorFullName:"Ulugbek Azimov",address:null,affiliation:'
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1. Introduction
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The main function of a spermatozoon is to convey the male genome remotely to the female one, which occurs in case of fish by swimming in the external milieu, marine or freshwater. Spermatozoa must access, bind, and penetrate an egg, for successful fertilization. Therefore, most of the physiological activity of fish spermatozoa is motility oriented. These processes include as a prerequisite the activation of spermatozoon motility. In case of fish species, spermatozoa stored in the seminal plasma are immotile during transit through the genital tract of most externally fertilizing teleost and chondrostean. Motility is induced immediately following the release of spermatozoa from the male genital tract into the aqueous environment. External trigger agents for the initiation of motility depend on the species’ reproductive behavior that is mostly controlled by the aquatic environment (fresh or salt water). Triggering signals include osmotic pressure, ionic and gaseous components of the external media, and, in some cases, egg-derived substances used for sperm guidance. Environmental factors influencing fish spermatozoon motility have received a large attention: these extensive studies led to several mechanisms of activation for freshwater and marine fish spermatozoa. However, after reception of the signal, a transduction pathway initiated by these mechanisms must lead the information to the flagellar motility apparatus (axoneme). This review presents the current knowledge with respect to (1) membrane reception of the activation signal and its transduction through the spermatozoon plasma membrane via the external membrane components such as ion channels or aquaporins; (2) cytoplasmic trafficking of the activation signal; (3) final steps of the signaling, including signal transduction to the axonemal machinery, and activation of axonemal dynein motors and regulation of their activity; (4) signaling involved in guidance processes that control the sperm/egg approach and meeting; and (5) pathways supplying energy for the short flagellar motility period of fish spermatozoa. For each step in this signaling process, quantitative methods were developed to evaluate the quality of the sperm samples that are used for aquaculture propagation of many fish species. These methods as well as examples of their usefulness for application to fish artificial reproduction are presented in the last part of this chapter.
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2. Fish sperm structure and spermatogenesis
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The main traits of the flagellar mechanics of spermatozoa and the main factors that regulate their motility have been described in details in a recent review chapter by Cosson et al. [1].
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2.1. Structure of fish spermatozoa: a brief presentation
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Compared to mammalian spermatozoa, the structure of a fish spermatozoon is qualified as “simple sperm”, mostly because the flagellum structure does not include additional columns flanking the motor part (axoneme) that are present in mammal sperm. In teleost fish, spermatozoa generally have no acrosome (in contrast to chondrostean such as sturgeon), and the impenetrable chorion presents a micropyle that gives access to the membrane of the oocyte. Spermatozoa often show a spherical nucleus with homogenous, highly condensed chromatin, a nuclear fossa, a midpiece of variable size with or without a cytoplasmic channel, and one or two long flagella [2]. Moreover, fish spermatozoa can be classified into two forms, aqua sperm and intro-sperm, according the external or internal mode of fertilization, respectively [2].
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The main components present in a fish spermatozoon [3, 4] are: the head is occupied mostly by the nucleus with paternal DNA material. In most fish species, the head has an almost spherical shape (diameter of 2–4 μm). In some case such as sturgeon, paddlefish, and eel spermatozoa, the shape of head is elongated (up to 9 μm long and 2 μm wide) [5, 6, 7], the midpiece is mostly composed of the centrioles, and the mitochondria (usually from 2 to 9 per each spermatozoon) is generating energy (ATP) for motility [8]. In a mature spermatozoon, because the protein synthesis machinery is absent, no gene expression occurs. The centriolar complex of midpiece consists of the proximal and the distal centrioles, which forms the basal body of the flagellum, used for anchoring the flagellum to the head of the sperm cell.
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The flagellum is a highly conserved organelle during evolution, and there are very few differences between molecular composition of sperm flagella relatively to that in protists [1, 10]. Fish sperm flagellar length varies from 20 to 100 μm, depending on species. Flagellar bending is generated by a highly organized cylindrical system of microtubules, called the axoneme, emanating from the basal body [11]. In turn, the canonical “9 + 2” axoneme consists of nine pairs of peripheral microtubular doublets and one central pair of singlet microtubules. This structural arrangement [12] is illustrated in Figure 1. Such axonemal pattern is highly conserved and almost identical among eukaryotic cilia and flagella from protozoans to human. Nevertheless, in Anguilliformes and Elopiformes sperm flagella present a “9 + 0” pattern lacking central microtubules [6, 7, 13].
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Figure 1.
Schematic structure of the head-tail junction of a model spermatozoon: the artistic view applies to a teleost such as trout [9] as an example of sperm cell. m, membrane surrounding both the head (top) and the tail; a, axoneme, the mechanical part actuating the flagellum (bottom); t, microtubule doublets, the major scaffold of the 9 + 2 axoneme; c, centriolar complex, at the basal part of the axoneme, made of microtubule triplets. In many fish species, the mitochondria (not shown for simplification) are localized in this head-tail junction zone, and two centrioles are orthogonally assembled to form the centriolar complex.
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The structural connections between the nine peripheral outer doublets and the sheath surrounding the central pair occur through the radial spokes. The central pair of singlets is enclosed in this sheath of proteins forming a series of projections that are well positioned to interact with each of the spoke heads and regulate the wave propagation [14]. Each of the outer doublets is connected to adjacent pairs of doublets by nexin links, presenting elastic properties allowing to resist the free sliding of the microtubules; nexin is a dynein regulatory protein [15]. The peripheral doublets are strung with two rows of dynein arms along the entire length of microtubules. These dynein arms consist of macromolecular ATPase complex [16, 17] and represent the basic motor actuating the whole axoneme; they extend from an outer doublet toward an adjacent doublet [18]. Both the spokes and the dynein complex contain different calcium-binding proteins so as for flagella to be able to respond to regulation by free calcium concentration through altering their beating pattern [19, 20]. As briefly described above, axonemes are complex structures composed of at least 500 different protein components [21].
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The bending process in an axoneme is caused by sliding between two adjacent doublets of outer microtubules that slide relatively to each other due to the motive force, generated by molecular dynein motor activity [16]. Due to enzymatic hydrolysis of ATP by the latter, which induces force generation of the power stroke of individual dynein molecules, the dynein arms interact with tubulin of the B tubule from the adjacent doublet, causing a process of active sliding in a cooperative way [22]. Several local bending processes occur because this sliding activity is present in only some segments of the axoneme at a given time, while other segments remain inactive [4]. Wave propagation from head to tip provokes the translation of the whole spermatozoon in the opposite (forward) direction.
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2.2. Spermatogenesis in fish
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For obtainment of full efficiency of motility, all the elements of the flagellum must have been, during spermatogenesis, correctly assembled mostly as an elongated structure called axoneme playing the role of propelling engine, surrounded by the plasma membrane, and this device must be provided in energy in terms of ATP [8], the fuel common to many cell types that is mostly generated by mitochondrial respiration in case of fish sperm as detailed in paragraph 4.
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Spermatogenesis is an important phase in case of fish spermatozoa because it is the ATP store that constitutes the main source of energy that will sustain the short but highly energy-demanding motility period [8].
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A detailed description of fish spermatogenesis is well documented in many species. Briefly, spermatogenesis is a developmental process during which a small number of diploid stem cells (spermatogonia) produce a large number of highly differentiated spermatozoa carrying a haploid, recombined genome, and a structurally complete flagellum. Survival and development of those germ cells depend on their close contact with specific cells called Sertoli cells. Apart from their phagocytic role, the Sertoli cells change the growth factor expression, and subsequently, modulate germ cell proliferation/differentiation via complex mechanisms involving, in fish, both pituitary gonadotropins LH and FSH that stimulate gonadal sex steroid hormone production directly by the activation of another cell type called Leydig cells.
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Fishes represent the largest and most diverse group of vertebrates. However, our knowledge on spermatogenesis in this group is limited to a few species used in basic research and/or in aquaculture biotechnologies such as guppy, catfish, cod, eel, medaka, salmon, tilapia, trout, and zebrafish. In an amniote vertebrates (fishes and amphibians), one observes a cystic type of spermatogenesis, which presents two main differences compared to higher vertebrates [23]. First, within the spermatogenic tubules, cytoplasmic extensions of Sertoli cells form cysts that envelope a single, clonally and hence synchronously developing group of germ cells deriving from a single spermatogonium. Second, the cyst-forming Sertoli cells retain their capacity to proliferate also in the adult fish. Sertoli cells are surrounding and nursing one synchronously developing germ cell clone. Different clones being in different stages of development generate a tubular compartment containing differently sized groups of germ cells in different stages of spermatogenesis.
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So as for the distribution of spermatogonia in the germinal compartment, one can observe either a first type of restricted spermatogonial distribution, which is found in the higher teleost groups, such as in the order Atheriniformes, Cyprinodontiformes, and Beloniformes, where the distal regions of the germinal compartment are occupied by Sertoli cells surrounding early, undifferentiated spermatogonia. While the cells divide and enter in meiosis and the cysts migrate toward the region of the spermatic ducts located centrally in the testis, this is where spermiation occurs, i.e. the cysts open to release spermatozoa.
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In a second type, where an unrestricted spermatogonial distribution that is considered a more primitive pattern found in less evolved taxonomic groups, such as in the order Cypriniformes, Characiformes, and Salmoniformes, occurs, spermatogonia are spread along the germinal compartment throughout the testis. The cysts do not migrate during their development. In addition, intermediate forms also exist between restricted and unrestricted spermatogonial distribution, such as in Perciformes, tilapia, Pleuronectiformes, or Gadiformes.
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Therefore, the development of spermatogenic cells strictly depends on their interaction with the somatic elements of the testis, among which Sertoli cells play a crucial role. During fish spermatogenesis, Sertoli cells are formed by mitosis just in time and in exactly the number required. This tailored Sertoli cell proliferation was first described in the guppy [24]. So far, we observe that spermatogenesis is a highly organized and coordinated process, in which diploid spermatogonia proliferate and differentiate to form spermatozoa in their final morphology. The duration of this process is usually shorter in fish than in mammals. In principle, this process can be divided, from a morpho-functional point of view, in three different phases: (i) the mitotic or spermatogonial phase with the different generations of spermatogonia, (ii) the meiotic phase with the primary and secondary spermatocytes, and (iii) the spermiogenic phase with the haploid spermatids emerging from meiosis and differentiating, without further proliferation, into flagellated spermatozoa.
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Analysis of the role of hormones reveals a complex process. Three steps at which reproductive hormones play a critical regulatory role are (i) the balance between self-renewal and differentiation of spermatogonial stem cells, (ii) the transition from type A spermatogonia to rapidly proliferating type B spermatogonia, and (iii) the entry into meiosis. During later developmental stages, on the other hand, the endocrine system seems to ensure a permissive rather than stimulatory role, enabling Sertoli cells and possibly other somatic cells to generate a microenvironment that germ cells require to proceed through meiosis and spermiogenesis [25]. In case of fish, three types of spermiogenesis have been described, based on the orientation of the flagellum relatively to the nucleus and on whether or not a nuclear rotation occurs.
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2.3. Flagellum genesis
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The main organelle in the flagellum, the axoneme, is resulting from the progressive assembly of groups of elements synthesized in the cell body and then transported to the flagellar compartment and delivered to the flagellar tip to elongate it thanks to the motility of specific transporters called intra-flagellar transport (IFT) along the internal side of the flagellar membrane [21]. The trafficking is ensured by two important molecular motors, belonging to the dynein group (retrograde, meaning from tip to base of the flagellum) and to the kinesin group (anterograde, meaning from the cell body to the flagellum tip) [26].
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3. Successive steps leading to fish sperm motility
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3.1. The maturation step
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Maturation is the step following the end of spermatogenesis and that provides to the spermatozoon its ability to respond to motility-activating factors [27]. Signals for maturation are quite various among fish species. Sperm maturation is also regulated by the endocrine system.
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Examples of sperm maturation have been studied in details in different fish species: salmonids, cyprinids, and sturgeons. In salmonids, the group of Morisawa, in Japan, demonstrated, in particular in case of salmon, that maturation is mainly under control of cAMP and pH of the water where fish are transiting during migration [28]. In carp, results from Redondo et al. [29] indicate that an ionic equilibration across the sperm membrane is the main factor responsible for maturation. In case of sturgeon species, it was shown that spermatozoa are not able to become activated at simple contact with external water [30]; sperm cells need a transient contact with urine, the latter getting mixed with milt prior to ejaculation [31] which is enough to render spermatozoa fully motile.
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3.2. The activation step per se
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This is a very brief event lasting a fraction of a second [32, 33]. Among several kinds of activating signals, one can mention (1) osmolarity, the most common, (2) specific ions such as K+ in a few species (salmonids and sturgeons as examples), and (3) other signaling molecules such as CO2 in few cases [34]. The osmolarity signal depends on the external medium where fish delivers its sperm: marine fish spermatozoa activate when coming in contact with sea water, a salty solution of high osmolarity, while freshwater fish species shed their sperm in a very low-osmolarity medium. In both cases, the spermatozoa sustain a large stress that consists in a jump from seminal fluid ranging an osmolarity 300 mOsmol/kg to either sea water (around 1100 mOsmol/kg) or freshwater (maximum 50 mOsmol/kg).The environmental osmotic pressure appears consistently to be the main factor involved in fish motility activation among species [35, 36]. In a few fish species, osmolarity is acting in synergy with another factor such as specific ions [35]. In some marine species such as herring, activation of spermatozoa requires egg-derived substances. Two types of sperm-activating factors have been identified in Pacific herring, Clupea pallasii, eggs: a water-soluble protein released into the surrounding water [37] and a water-insoluble sperm motility-initiating factor localized in the vicinity of the micropylar opening of eggs [38].
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3.3. The perception of the signal by the sperm membrane
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Freshwater fish sperm cells when released into the surrounding water can increase their cytoplasmic volume in response to osmotic stress. In case of carp spermatozoa, the cell volume increases several times as a result of the influx of water [39]. Results of Cabrita et al. [40] show that small change of cell volume occurs in response to hypo-osmotic shock. The comparative study of Bondarenko et al. [41] puts forward a large species specificity regarding the osmotic reaction (swelling) among freshwater species and demonstrates that there is no change of trout sperm volume measured during the motility period. Altogether, the volume change, if any, represents a long-term osmotic reaction rather than the immediate signal for motility activation given its time delay (several tens of seconds) relative to the briefness of motility appearance (less than a second according to Prokopchuk et al. [33].
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A series of experiments by Takei et al. [42] aims to better explore the respective roles of K+ ions and osmolarity; this paper proposes a mechanism involving aquaporins and volume changes as a response to osmolarity stress. However, the volume changes measured by the authors are of low amplitude: the engendered volume difference is so low that it cannot be responsible of a physiological role in motility control. Furthermore, the time scale and the volume change measurements obtained at 5 min after motility activation correspond to time scales that are not fit with the previously published results of Prokopchuk et al. [33] showing that the motility response occurs about 100 ms after reception of the activation signal of fish spermatozoa. In addition, previous results by Bondarenko et al. [41] demonstrate that no significant volume change follows the motility activation of trout spermatozoa, a situation that contrasts with that of carp.
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In many marine teleost species, hypertonicity induces the motility of spermatozoa. Nevertheless, an increase in external osmolality is sometimes not the only condition for motility activation of marine fish spermatozoa: in case of herring, this activation also needs the contact of sperm with egg-derived substances, facilitating fertilization [37, 38, 43, 44]. Sperm-activating factors are two types of in the Pacific herring, Clupea pallasii: a water-soluble herring egg protein [37, 43, 44] and water-insoluble initiating factor, from the vicinity of the micropylar opening of the egg [38]. In another group of marine fish species collectively named flatfishes, the main signal perceived by the sperm membrane is the CO2 concentration [34] that is high in the genital tract but very low in sea water. The intracellular equilibrium between CO2 and bicarbonate constitutes the second step in the control of intracellular ionic concentration that leads to regulation of flagellar motility [33].
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3.4. The transduction of the signal across the membrane and the cytoplasm
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In fish spermatozoa, external signals triggering sperm motility activation are acting at the level of spermatozoon plasma membrane, hyperpolarization/depolarization of membrane, and ion channels or aquaporins activity, but this topic is still challenging because of the scarcity of experimental results in this area. As mentioned above, it is clear that water transport itself is not a main process involved in fish sperm motility activation. Nevertheless, in the presence of aquaporins in the head and flagella plasma membrane of the seawater fish, gilthead sea bream (Sparus aurata) spermatozoa and their involvement in cAMP-mediated phosphorylation of axonemal proteins were established [45, 46]. In this species, the water efflux via aquaporins would determine a reduction in the cell volume, which would raise the intracellular concentration of ions. This would lead to the activation of adenylyl cyclase and motility initiation by cyclic AMP-dependent protein phosphorylation and dephosphorylation [46]. Such cascade of events remains hypothetical because of the timing of such process compared to the extreme briefness (less than 0.1 s) of the reaction of the axoneme activation [33].
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The presence of different ion channels was described in sperm plasma membrane [34]. Cytosolic pH could be considered as another participant of signaling pathways, as it is known to be one of the parameters influencing sperm motility [47, 48]. Environmental conditions that inhibit spermatozoa motility can decrease the intracellular pH, resulting in a more acidic cytoplasm in nonmotile spermatozoa than in motile spermatozoa [49]. The decrease of internal pH in sperm would directly affect flagellar movement through inhibition of dynein activity. The involvement of the Na+/H+ exchangers in sperm motility activation process was reported for Cyprinus carpio [50] and was proposed for Brycon henni [51]. The former authors suggest that the regulation of the exchangers depends on osmolality conditions [52]. According to Krasznai et al. [53], an opening and closing of K+ channels in the plasma membrane of the spermatozoon under hypo-osmosis-induced initiation of sperm motility is resulting in a remarkable local hyperpolarization or depolarization of the spermatozoon plasma membrane. Such transient depolarization may open Ca2+ channels, resulting in an influx of Ca2+ and activation of the flagellar motility of carp sperm.
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The involvement of K+ and Ca2+ transport through ion channels at the plasma membrane of spermatozoa in the triggering of the motility initiation has also been shown for rainbow trout (Salmo gairdneri) spermatozoa [54]. As for Na+ channels, Tanimoto and Morisawa [54] supposed that Na+ channels do not play an important role in sperm motility in rainbow trout, although they did not exclude its possible involvement in sperm motility control, for example, through Na+-H+ exchange.
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Altogether, the precise mechanisms of regulation of ion channel activity and their participation in the hyperpolarization of the spermatozoon membrane, which is associated with the activation of sperm motility [35, 53], remain poorly understood. What are the next-step processes occurring at the level of membrane leading the subsequent activation of the axoneme?
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3.5. Transduction and reception of the signal at the axoneme level
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Among other processes, an increase of intracellular concentration of ions could lead to the activation of adenylyl cyclase, which in turn would determine the motility initiation by a cAMP-dependent protein phosphorylation and dephosphorylation mechanism [46]. It is known that, in mammals, protein tyrosine phosphorylation of several proteins is upregulated by reactive oxygen species (ROS). ROS (especially H2O2) may enhance tyrosine phosphorylation through the selective suppression of tyrosine phosphatase activity [55] or activation of adenylyl cyclase, thus producing a higher cAMP level and leading to the subsequent activation of the serine/threonine kinase A [56].
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Cyclic AMP is an important factor in the activation process of fish spermatozoa. The link between cAMP concentration increase and motility initiation at the axoneme level was mainly investigated in Salmonidae. It involves a complex series of phosphorylation and dephosphorylation events. This includes the cAMP-dependent phosphorylation of the 15 kDa movement-initiating phosphoprotein [57, 58] of a PKA [59] and of the 22 kDa dynein light chain [60]. Protein phosphorylation is also regulated by proteasomes [60, 61]. The precise dependence between protein phosphorylation and microtubule sliding and movement initiation is still under investigation. A Ca2+-mediated and/or cAMP-dependent phosphorylation signaling mechanism through the radial spoke/central pair system of the axoneme has been proposed [62, 63].
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The potential role of reactive oxygen species (ROS) generated at the contact of sperm with aerobic condition such as the external medium at ejaculation and the molecular mechanisms by which these reactive metabolites exert their biological activity has been put forward by Baker and Aitken [64]. A gas, NO, was also observed to enhance motility of fathead minnow spermatozoa [65]. Nevertheless, the mechanism by which NO affects sperm motility is probably unrelated to osmolality, because of its very low active concentration range.
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3.6. The motility period
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During the period after spermatozoa comes in contact with an activating medium, the ion concentrations inside the sperm cell are rebalanced, and osmotic pressure affecting the sperm membrane becomes harmful for sperm integrity, limiting the period of motility to a short interval [32]. These phenomena are much faster and more obvious in freshwater species, in which sperm motility usually does not last for more than 0.5–2 min [32].
Brook trout (Salvelinus fontinalis) spermatozoa recorded while swimming in a swimming medium composed of low osmolarity (10 mM Tris at pH 8.0 + 10 mM CaCl2). Remark the briefness of motility (around 30 s duration at 10°C) (courtesy of Dr. Galina Prokopchuk).
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In case of sperm collection for artificial reproduction or in vitro studies, particular care should be taken to avoid precocious activation of motility: one should avoid any contact of sperm cells with external water [66] or urine during stripping [67, 68]. Any assessment of motility parameters should be started as soon as possible after sperm activation, bearing in mind that the earliest period of motility (the most efficient one) should be characterized. Fish spermatozoa are usually characterized by a very high initial velocity (up to 200 μm s−1) due to the high flagellar beat frequency (up to 100 Hz; [32]); this “most active” period lasts only a few seconds immediately after contact with the activating medium.
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Values of all motility parameters decrease rapidly immediately after initiation of fish sperm flagella movement [36, 69], which is why any motility parameter must refer to a precise time point after activation for intra- or interspecies comparisons [36, 69, 70]. Generally, the duration of motility is a trade-off between the level of energy stocks possessed by a cell and the process of osmotic damage experienced by this cell. The latter is more critical in freshwater fish species, and the former is important for marine fish [36]. At a precise time point, most spermatozoa have very similar characteristics [69, 70].
Carp (Cyprinus carpio) spermatozoa recorded while swimming in two different media successively; the first part of the record shows the carp sperm population activated in a swimming solution composed of 45 mM NaCl +5 mM KCl + Tris at pH 8.0, while the second part shows spermatozoon activation in a low-osmolarity medium (distilled water + Tris at pH 8.0). Remark the curling of the flagellar tip which limits the duration of motility at low osmolarity (courtesy of Dr. Volodymyr Bondarenko).
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4. Energetic of sperm motility
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Storage of energy mostly results from mitochondrial respiration that generates ATP. Energy metabolism also involves other compounds such as creatine phosphate that contributes to the maintenance of the intracellular energy level in connection with ATP.
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4.1. Mitochondrial respiration
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In many fish species, measurement of respiratory activity presents difficulties because of the low oxygen consumption of spermatozoa, in contrast to model species such as sea urchin [71]; in addition, the low respiratory activity remains almost unchanged when fish spermatozoa are transferred into motility-activating solutions [72], while it is about 50-fold increased when sea urchin sperm is transferred into sea water [71]. Efficient respiration needs to be coupled in mitochondria to ATP production via the ATP synthase [73]. For estimation of the full respiratory capacity of mitochondria, it is useful to apply diffusible “uncouplers” such as CCCP or FCCP (carbonylcyanide-4-trifluromethoxy-phenylhydrazone): these compounds are diffusible through the membranes and allow full rate of electron transfer in the electron chain of mitochondria without restriction due to its control by ATP synthase. The effects of respiratory inhibitors such as oligomycin [73] or KCN and their relationship with ATP stores of fish sperm were studied in details by Dreanno et al. [74]. Mitochondrial inhibitors have little effect in case of trout [75, 76, 77, 78] or turbot [79] spermatozoa. Respiration rate in quiescent fish spermatozoa (before motility activation) needs to be only minimal but enough to maintain this ATP level prior to ejaculation. Such low but substantial respiration is enough for basal metabolism to maintain ionic exchanges and balances across the plasma membrane [8, 76, 79].
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4.2. Generation and storage of ATP
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Generation of ATP by mitochondria occurs by electron transfer along the mitochondrial respiratory chain that generates a proton gradient across the inner mitochondrial membrane. Dissipation of the proton gradient occurs by passage of H+ through a specific ATP synthase localized at the inner part of the mitochondrial membrane [8, 73]. ATP thus accumulated is transported out of the mitochondrion by a translocase (ATP-ADP exchanger) toward the flagellar compartment; then, ATP molecules diffuse along the axoneme possibly assisted by a carrier device called energy shuttle as explained in Section 4.4.
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The energy stored in fish sperm prior to and used during the motility period was evaluated in several fish species [80, 81, 82]. This was described in turbot, for example [79, 83, 84], sea bass [85] perch [86], bluegill [87, 88], trout [71, 89, 90], carp [39, 91], sturgeon [92, 93], and catfish [94]. Values for spermatozoa of other fish species can also be found in Cosson [8, 32, 95], Dzyuba et al. [30], and Ingermann [96].
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4.3. Consumption of ATP during the motility period
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ATP is the only high-energy compound that is hydrolyzed by the motor protein of the axoneme called dynein ATPase [16, 17, 97]. Dyneins are macromolecular assemblies of more than 1 MDa molecular weight linearly bound to each microtubule doublet of the axoneme and which function is mechanochemical. Its role it to collect the chemical energy generated by hydrolysis of an ATP molecule so as to induce a trans-conformation that constitutes the elementary step of movement generation. Rows of dyneins positioned along each microtubule amplify in a cooperative way this elementary movement so as to provoke the sliding between adjacent microtubules of the axoneme. Differential sliding generates bending, and the bending waves that propagate along the flagellum (usually from the head to the tip of the axoneme) result in a translational movement of the whole sperm cell [21].
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In case of fish spermatozoa, dynein molecules have an intense activity: this fast activity results in a beat frequency (up to 80–100 Hz) much higher than in species other than fish. As a result, ATP is hydrolyzed at high speed, and the ATP store is rapidly decreasing, becoming partly exhausted at the end of the motility period [32].
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4.4. Other energetic molecules assisting ATP maintenance
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Following its synthesis by mitochondria, ATP should be transported and distributed all along the flagellum so as to supply chemical energy to sustain the mechanical energy generated by the dynein motors that are distributed all around the flagellar axoneme. Theoretical considerations lead to postulate the presence of a distribution system that ensures a constant ATP concentration at any point along the axoneme [98, 99]. Such shuttle system involves an additional high-energy compound and assistance of enzymatic system that was shown to be present in fish sperm cells [90] and is detailed below.
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Even though the ATP molecule is the most common high-energy compound used as a fuel for many cell functions, including motility [8], several other high-energy molecules are present in living cells such as creatine phosphate or arginine phosphate. In fish, creatine phosphate (CrP) is the main high-energy compound that was characterized in spermatozoa of several fish species as a complement of ATP [74, 79, 85]. In the last decades, many studies have demonstrated the decrease of the ATP concentration inside the fish sperm cells during the motility period [39, 67, 74, 76, 79, 85, 90, 91, 93, 100]. A more restricted number of studies have investigated the concentration of ATP related compound such as ADP, AMP, CrP, and others [74, 79, 85, 100]. All these compounds are part of an intracellular network under control of different enzymes that are able to transfer high-energy phosphate bonds from one to another (see Figure XX in Chapter 1 of Cosson [21]), for example, the equilibrium ATP< = >ADP + Pi is catalyzed by enzymes called ATPases. In another example, ADP + CrP < = >ATP + Cr is controlled by enzymes called creatine kinases. One creatine kinase is mitochondrial, while a second one is in the flagellum and distributed all along the axoneme (Figure 1). The mitochondrial creatine kinase delivers CrP that diffuses along the flagellum, both creatine kinases being present in trout sperm cells. The rate of diffusion of CrP molecules is higher than that of ATP [99]. Such an arrangement of catalytic activities and substrates constitutes an intracellular network ensuring the correct production and distribution of energy in fish sperm cells (Figure 1) and is called the “ATP shuttle” [99].
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A local axonemal paralysis appears in sperm flagella of many species during the motility period: this is an indication that the renewal of ATP is not fully efficient, and the production of ATP from CrP in this distal portion of the flagellum is too slow, while the proximal portion, that is close to the mitochondrion, can use directly the ATP still produced by the latter. Stiffening of the distal flagellar tip was observed in vivo (but not in reactivated sperm) in two sea urchin species [101] but also in trout sperm (Cosson, unpublished) after application of thiourea, an inhibitor of respiratory phosphorylation (Figure 2).
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Figure 2.
Evolution of the flagellar shape of fish spermatozoa during the motility period. From left to right, successive positions of a turbot (Scophthalmus maximus) spermatozoon video recorded at different time points post-activation: (a) right after transfer in sea water, (b) 2 min later, (c) more than 3 min later, (d) after full stop. Dark field microscopy with stroboscopic illumination (150 Hz); 100× objective lens [32].
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5. Control of fish sperm physiology by other factors
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Changes in the environment of fish spermatozoa impose other chemicals as well as physical constrains: temperature is controlling sperm physiology at many levels such as membrane permeation, enzymatic activities, or energetic metabolism [102]. Fish species are exposed to a large variety of temperature conditions, especially during their reproduction period; thus, an optimal choice of temperature is a key parameter for controlling the best conditions for best adapted sperm physiology.
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Viscosity of the swimming medium is also an important factor influencing the physiology of fish spermatozoa. According to physical laws, especially microfluidics, progression of the sperm cell occurs because of the friction of the flagellum against the external milieu, water being a quite viscous fluid. Higher viscosity is encountered by fish spermatozoa when getting close to the fluids surrounding the egg, which modifies and thus controls the swimming physiology of the sperm cells [21, 103] including female cryptic choice of sperm cells by the egg [104].
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Among other factors that play a signaling role for fish physiology are some molecules that control the sperm/egg interplay at fertilization; these molecules are commonly called chemoattractants and are able to finely tune the motility function of fish spermatozoa so as to optimally guide sperm cells to egg which ultimately results in an increase of fertility success [21]. In case of fish, the spermatozoon must localize the entrance point at the surface of the egg so as to penetrate and deliver the male genome [105]. Ultimately, the male genome will combine with that of the female so as to constitute the zygote.
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6. An update of modern technologies allowing fish sperm quality assessment
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6.1. CASA systems
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Evaluation of fish sperm swimming performances needs at first good quality video records so as to measure the distance covered by each sperm head for a time period corresponding, for example, to the time separating two successive video frames, such as 20 ms for the European video standard (Figure 3).
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Figure 3.
Video image of swimming sturgeon spermatozoa. Dark-field video microscopy with stroboscopic illumination. Flashes are every 10 ms. At bottom right is the indication from the stop-watch giving the time (in milliseconds) spent since motility activation.
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Several works in the last decade have reported the use of CASA systems to assess sperm motility in fish [106]. Based on the integration by the computer of successive positions of the moving head of spermatozoa in consecutive frames of video records to calculate the trajectories and their characteristics, CASA describes different parameters of sperm swimming linked to velocity, for example, VCL or instant speed (frame to frame displacement) along the real track, VAP or velocity along a smoothed track, VSL or progressive velocity following the straight line from the origin to the end of the track during the corresponding period of time and other parameters linked to the wobble of sperm head such as Mean angular displacement (MAD), amplitude of lateral head displacement (ALH) and beat cross frequency (BCF) and linearity. Lastly, the ratio between average path and straight-line path is used to describe the straightness of the trajectories (reviewed in Rurangwa et al. [107]).
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The CASA system recently developed by Wilson-Leedy and Ingermann [108] as a plug-in to image J software freely available from NIH site (http://rsb.info.nih.gov/ij/plugins/casa.html) has been tested in different species including zebrafish [109]. More recently, it was improved and adapted to trout sperm motility by Purchase and Earle [110].
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One important aspect for motility estimation of sperm quality by CASA is that the practical conditions employed to perform such tests are in several respects not reflecting the natural situation. Many broadcast spawners like salmon or trout reproduce in highly turbulent water, which certainly influences the sperm/egg meeting chances and thus the fertilization success. Effect of such turbulent water shear at some optimal values was studied using biophysical methods by Crimaldi and Browning [111], and it was shown experimentally to increase the proportion of fertilized eggs in sea urchin [112].
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Also, for practical reasons, CASA records are obtained in conditions where spermatozoa swim in the vicinity of glass surfaces: such situation was shown in literature to affect motility parameters [113, 114]. An important consequence of this is that the motility parameters mostly refer to a situation where sperm cells swim in a planar manner; it is well known since early studies [115] that when spermatozoa swim freely far from any surface, they adopt a helical trajectory. The latter was shown to decrease up to 10-fold the efficient gross velocity but surprisingly to increase around 6-fold the fertilization kinetics [116]. All these findings emphasize several limits of the application of these CASA systems when used to predict quality of sperm regarding the fertilization rate.
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The comparative values of sperm velocity among fish species, including salmonid, can be found in Cosson [32] with respect to motility duration and ATP stores prior to activation.
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6.2. Evaluation of flagella performances
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Behavior of the flagellum determines the motility guideline of the spermatozoon, so the description of intrinsic flagellar wave properties is considered as one of the most informative methods for assessing and controlling sperm motility. In order to observe the detailed pattern of live flagella or of their major components, it was proposed to use phase contrast or dark field optical microscopy with high magnification (40×−100×) objective lenses, which, if applied with oil immersion, result in a bright image of the very small diameter object that constitutes a flagellum. To achieve complementary assessment, additional methods, such as stroboscopic illumination or high-speed video techniques, allow to record sperm during its motion and specially to obtain flagellar images of high quality and resolution. Multiflash stroboscopic illumination thus allows visualization on each frame of well-defined successive positions of a same moving spermatozoon at time intervals ranging in milliseconds. Alternatively, high-speed video recording provides higher spatial and temporal resolutions (up to several 1000 images/s). Serial frames individually selected from such video records allow to follow successive positions (every millisecond or less) of flagellum waves covering one or several full beat cycles [32].
Legend of the video: a sturgeon spermatozoon was recorded by phase-contrast video microscopy according to conditions similar to those described in Figure 4 (courtesy of Dr. Bondarenko Volodymyr). Spermatozoa of Siberian sturgeon (Acipenser baerii) were activated by dilution in pond water and recorded 10 s after activation. The length of flagella is about 50 μm long. Image rate is 100-fold slower than real. Remark that some spermatozoa show abnormal shape.
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Figure 4.
Successive positions of a sturgeon sperm flagellum recorded by high-speed video microscopy. Initial record was at 5000 images/s with a 100× phase-contrast lens and an Olympus high-speed video camera. In this panel from left to right, successive images collected every millisecond are presented so as to show the wave propagation of three successive waves and the minor progression of the head tip (white straight lines) during this short time period.
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Evaluation of sperm flagellum performances on a large variety of fish species leads to a series of predictions briefly summarized below (see Figure 5):
The swimming velocity is linearly proportional to the flagellar beat frequency.
The smaller the flagellum length, the lower the swimming velocity.
The number of waves along the flagellum varies linearly with the flagellum length.
The power output of the flagellum varies in proportion with the flagellar beat frequency.
The flagellar length has no significant influence on the swimming velocity.
The swimming efficiency increases in proportion with the swimming speed.
The wave amplitude and the swimming velocity are linearly related.
The swimming velocity is lowly dependent of the medium viscosity, but the latter greatly affects the wave shape.
Waves of helical shape generate rotation of the sperm cell at a frequency that is in proportion with the flagellar beat frequency but less efficient than planar waves.
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Figure 5.
Flagellar parameters of a swimming fish spermatozoon. The sperm cell, such as that recorded according to Figure 3, is represented in two successive positions (1–2) separated by a short time period (0.5 ms, for example).
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While the whole cell is moving from left to right, the flagellum wave progresses from right to left. The wavelength is defined as the distance “L” between two inflection points. The half wave amplitude is represented as “A” and the bend angle of each wave as “a”. The number of waves generated every second is called the beat frequency. Such parameters are quantified and used to characterize fish sperm cells exposed to various swimming situations affecting their physiology.
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Two other examples of high-speed video records of fish spermatozoa are presented below.
Pangasius (Pangasianodon hypophthalmus) spermatozoa recorded by high-speed video combined with dark-field microscopy and was visualized 10-fold slower than normal. Sperm movement was recorded at 13 s post-activation in a 10% sea water solution. Length of flagellum is about 50 μm (courtesy of Dr. Galina Prokopchuk).
Tilapia (Sarotherodon melanotheron heudelotii) spermatozoon recorded by high-speed video microscopy and visualized 20-fold slower. Sperm movement was recorded at 18 s post-activation in 50% sea water containing bovine serum albumin (BSA at 0.5%) to prevent sticking to the glass slide. Notice the short sperm flagellum in this species and the swollen midpiece, mostly composed of mitochondria (courtesy of Dr. Galina Prokopchuk).
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6.3. Biochemical methods
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6.3.1. Respiration, oxidative stress, free radicals, and DNA damage
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Fish spermatozoa present a low respiratory rate that makes this evaluation quite delicate because of the sensibility of detection methods. Respiratory activity commonly uses oxygen electrodes that measure the oxygen concentration of a small volume of sperm suspension. These media are either preventing or activating motility and can be complemented by different effectors (substrates, uncouplers, or inhibitors) of respiration. In general, mitochondrial inhibitors have little effect on the motility of fish spermatozoa. Sperm oxygen consumption rate published in literature was presented in a comparative way for about 10 different fish species by Ingermann [96] and shows that values present a large variability from 1.4 to 70 nmoles O2/min/109 spermatozoa depending on species.
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The contact of fish sperm with the external milieu occurring at ejaculation leads to exposure of sperm cells to high concentration of oxygen, provoking different kinds of stress [117]. Among other chemicals responsible of stress, reactive oxygen species are highly aggressive [118, 119]. The oxidative stress can be evaluated by several methods. Results of these studies show that several protections against the oxidative stress are present in fish sperm cells and in the seminal fluid [31, 120].
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Also, the presence of free radicals leads to DNA damage during stressing situations such as those due to application of cryo-techniques that influence the quality of the progeny [121]. Recent studies on genes and protein expression of fish sperm cells show that both are controlled by various factors of the external milieu such as salinity or timing during the reproductive season [122, 123]. Among other factors, the level of phosphorylation of specific proteins constitutes important signaling factors controlling function efficiency of fish spermatozoa [124, 125]. Proteomics represent a promising approach to study specific physiological situations encountered by fish spermatozoa [126].
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6.3.2. Evaluation of energetic compounds concentration
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ATP content of sperm cells can be evaluated by several methods, including measurement in a single spermatozoon cell as recently shown by Chen et al. [127]. The most popular method for evaluation of the ATP content classically uses a coupling with the light-emitting system composed of luciferin and luciferase. A full evaluation of the storage of energy in fish sperm cells needs the determination not only of the internal content of ATP but also that of other energetic compounds that are able to exchange high-energy phosphate bonds able to be transferred to ADP and allow to reconstitute the intracellular ATP store. Such evaluation was established in case of sturgeon sperm [100, 128] by the use of liquid chromatography combined to HPRS or in case of turbot or sea bass sperm where the adenine nucleotides’ energetic balance was determined by H+-NMR and 31P-NMR analysis, [74, 79] as well as in trout by 31P-NMR [89, 90]. All these results clearly point out to the fact that ATP level can be rescued by the CrP generated by the mitochondrial metabolism. This means that other phosphagen compounds are as important as ATP in the energy balance of fish sperm cells [129].
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7. Conclusion
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Fish sperm physiology is under control of various parameters of the external milieu: the latter is subjected to changes due to the different environmental conditions that sperm cells have to deal with such as (1) the ionic concentration of internal as well as external fluids, (2) the pH, (3) the osmolarity, (4) the temperature, and (5) specific molecules acting as signals such as chemoattractants that control the sperm-egg interaction at fertilization [21]. In fish spermatozoa, the interplay between the different actors results in a complex signaling network that exquisitely optimizes the various functions of fish spermatozoa, especially that of motility, in a large variety of situations. A better understanding of this complex network is important so as to decrease the effects of possible damage (osmotic, oxidative, etc.) when fish sperm cells are exposed to drastic conditions such as those imposed during application of cryopreservation methods.
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Acknowledgments
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The author is thankful to the Faculty of Fisheries and Protection of Waters, Univ. of South Bohemia in Ceske Budejovice, Czech Republic, especially to Dr. Galina Prokopchuck and Dr. Volodymyr Bondarenko for their high-speed video records of fish spermatozoa. The study was financially supported by the Ministry of Education, Youth and Sports of the Czech Republic projects CENAKVA (LM2018099), by project Biodiversity (CZ.02.1.01./0.0/0.0/16_025/0007370 Reproductive and genetic procedures for preserving fish biodiversity and aquaculture), and by the Grant Agency of the University of South Bohemia in Ceske Budejovice (125/2016/Z).
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\n',keywords:"flagellum, sperm energetics, sperm signaling, sperm motility, osmolarity",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/66461.pdf",chapterXML:"https://mts.intechopen.com/source/xml/66461.xml",downloadPdfUrl:"/chapter/pdf-download/66461",previewPdfUrl:"/chapter/pdf-preview/66461",totalDownloads:1904,totalViews:266,totalCrossrefCites:11,dateSubmitted:"October 19th 2018",dateReviewed:"February 12th 2019",datePrePublished:"March 29th 2019",datePublished:"July 10th 2019",dateFinished:"March 29th 2019",readingETA:"0",abstract:"For reproduction, most fish species adopt external fertilization: their spermatozoa are delivered in the external milieu (marine- or freshwater) that represents both a drastic environment and a source of signals that control the motility function. This chapter is an updated overview of the signaling pathways going from external signals such as osmolarity and ionic concentration and their membrane reception to their transduction through the membrane and their final reception at the flagellar axoneme level. Additional factors such as energy management will be addressed as they constitute a limiting factor of the motility period of fish spermatozoa. Modern technologies used nowadays for quantitative description of fish sperm flagella in movement will be briefly described as they are more and more needed for prediction of the quality of sperm used for artificial propagation of many fish species used in aquaculture. The chapter will present some applications of these technologies and the information to which they allow access in some aquaculture species.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/66461",risUrl:"/chapter/ris/66461",signatures:"Jacky Cosson",book:{id:"7912",type:"book",title:"Biological Research in Aquatic Science",subtitle:null,fullTitle:"Biological Research in Aquatic Science",slug:"biological-research-in-aquatic-science",publishedDate:"July 10th 2019",bookSignature:"Yusuf Bozkurt",coverURL:"https://cdn.intechopen.com/books/images_new/7912.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",isbn:"978-1-78923-814-3",printIsbn:"978-1-78923-813-6",pdfIsbn:"978-1-78923-959-1",isAvailableForWebshopOrdering:!0,editors:[{id:"90846",title:"Prof.",name:"Yusuf",middleName:null,surname:"Bozkurt",slug:"yusuf-bozkurt",fullName:"Yusuf Bozkurt"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"188281",title:"Dr.",name:"Jacky",middleName:null,surname:"Cosson",fullName:"Jacky Cosson",slug:"jacky-cosson",email:"jacosson@gmail.com",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRIQXQA4/Profile_Picture_1612961771333",institution:{name:"University of South Bohemia in České Budějovice",institutionURL:null,country:{name:"Czech Republic"}}}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Fish sperm structure and spermatogenesis",level:"1"},{id:"sec_2_2",title:"2.1. Structure of fish spermatozoa: a brief presentation",level:"2"},{id:"sec_3_2",title:"2.2. Spermatogenesis in fish",level:"2"},{id:"sec_4_2",title:"2.3. Flagellum genesis",level:"2"},{id:"sec_6",title:"3. Successive steps leading to fish sperm motility",level:"1"},{id:"sec_6_2",title:"3.1. The maturation step",level:"2"},{id:"sec_7_2",title:"3.2. The activation step per se",level:"2"},{id:"sec_8_2",title:"3.3. The perception of the signal by the sperm membrane",level:"2"},{id:"sec_9_2",title:"3.4. The transduction of the signal across the membrane and the cytoplasm",level:"2"},{id:"sec_10_2",title:"3.5. Transduction and reception of the signal at the axoneme level",level:"2"},{id:"sec_11_2",title:"3.6. The motility period",level:"2"},{id:"sec_13",title:"4. Energetic of sperm motility",level:"1"},{id:"sec_13_2",title:"4.1. Mitochondrial respiration",level:"2"},{id:"sec_14_2",title:"4.2. Generation and storage of ATP",level:"2"},{id:"sec_15_2",title:"4.3. Consumption of ATP during the motility period",level:"2"},{id:"sec_16_2",title:"4.4. Other energetic molecules assisting ATP maintenance",level:"2"},{id:"sec_18",title:"5. Control of fish sperm physiology by other factors",level:"1"},{id:"sec_19",title:"6. An update of modern technologies allowing fish sperm quality assessment",level:"1"},{id:"sec_19_2",title:"6.1. CASA systems",level:"2"},{id:"sec_20_2",title:"6.2. Evaluation of flagella performances",level:"2"},{id:"sec_21_2",title:"6.3. Biochemical methods",level:"2"},{id:"sec_21_3",title:"6.3.1. Respiration, oxidative stress, free radicals, and DNA damage",level:"3"},{id:"sec_22_3",title:"6.3.2. Evaluation of energetic compounds concentration",level:"3"},{id:"sec_25",title:"7. 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Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:{name:"Association for Computing Machinery",country:{name:"United States of America"}}},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. 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He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",slug:"yalcin-isler",fullName:"Yalcin Isler",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",biography:"Yalcin Isler (1971 - Burdur / Turkey) received the B.Sc. degree in the Department of Electrical and Electronics Engineering from Anadolu University, Eskisehir, Turkey, in 1993, the M.Sc. degree from the Department of Electronics and Communication Engineering, Suleyman Demirel University, Isparta, Turkey, in 1996, the Ph.D. degree from the Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey, in 2009, and the Competence of Associate Professorship from the Turkish Interuniversity Council in 2019.\n\nHe was Lecturer at Burdur Vocational School in Suleyman Demirel University (1993-2000, Burdur / Turkey), Software Engineer (2000-2002, Izmir / Turkey), Research Assistant in Bulent Ecevit University (2002-2003, Zonguldak / Turkey), Research Assistant in Dokuz Eylul University (2003-2010, Izmir / Turkey), Assistant Professor at the Department of Electrical and Electronics Engineering in Bulent Ecevit University (2010-2012, Zonguldak / Turkey), Assistant Professor at the Department of Biomedical Engineering in Izmir Katip Celebi University (2012-2019, Izmir / Turkey). He is an Associate Professor at the Department of Biomedical Engineering at Izmir Katip Celebi University, Izmir / Turkey, since 2019. In addition to academics, he has also founded Islerya Medical and Information Technologies Company, Izmir / Turkey, since 2017.\n\nHis main research interests cover biomedical signal processing, pattern recognition, medical device design, programming, and embedded systems. He has many scientific papers and participated in several projects in these study fields. He was an IEEE Student Member (2009-2011) and IEEE Member (2011-2014) and has been IEEE Senior Member since 2014.",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"310576",title:"Prof.",name:"Erick Giovani",middleName:null,surname:"Sperandio Nascimento",slug:"erick-giovani-sperandio-nascimento",fullName:"Erick Giovani Sperandio Nascimento",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0033Y00002pDKxDQAW/ProfilePicture%202022-06-20%2019%3A57%3A24.788",biography:"Prof. Erick Sperandio is the Lead Researcher and professor of Artificial Intelligence (AI) at SENAI CIMATEC, Bahia, Brazil, also working with Computational Modeling (CM) and HPC. He holds a PhD in Environmental Engineering in the area of Atmospheric Computational Modeling, a Master in Informatics in the field of Computational Intelligence and Graduated in Computer Science from UFES. He currently coordinates, leads and participates in R&D projects in the areas of AI, computational modeling and supercomputing applied to different areas such as Oil and Gas, Health, Advanced Manufacturing, Renewable Energies and Atmospheric Sciences, advising undergraduate, master's and doctoral students. He is the Lead Researcher at SENAI CIMATEC's Reference Center on Artificial Intelligence. In addition, he is a Certified Instructor and University Ambassador of the NVIDIA Deep Learning Institute (DLI) in the areas of Deep Learning, Computer Vision, Natural Language Processing and Recommender Systems, and Principal Investigator of the NVIDIA/CIMATEC AI Joint Lab, the first in Latin America within the NVIDIA AI Technology Center (NVAITC) worldwide program. He also works as a researcher at the Supercomputing Center for Industrial Innovation (CS2i) and at the SENAI Institute of Innovation for Automation (ISI Automação), both from SENAI CIMATEC. He is a member and vice-coordinator of the Basic Board of Scientific-Technological Advice and Evaluation, in the area of Innovation, of the Foundation for Research Support of the State of Bahia (FAPESB). He serves as Technology Transfer Coordinator and one of the Principal Investigators at the National Applied Research Center in Artificial Intelligence (CPA-IA) of SENAI CIMATEC, focusing on Industry, being one of the six CPA-IA in Brazil approved by MCTI / FAPESP / CGI.br. He also participates as one of the representatives of Brazil in the BRICS Innovation Collaboration Working Group on HPC, ICT and AI. He is the coordinator of the Work Group of the Axis 5 - Workforce and Training - of the Brazilian Strategy for Artificial Intelligence (EBIA), and member of the MCTI/EMBRAPII AI Innovation Network Training Committee. He is the coordinator, by SENAI CIMATEC, of the Artificial Intelligence Reference Network of the State of Bahia (REDE BAH.IA). He leads the working group of experts representing Brazil in the Global Partnership on Artificial Intelligence (GPAI), on the theme \"AI and the Pandemic Response\".",institutionString:"Manufacturing and Technology Integrated Campus – SENAI CIMATEC",institution:null},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:'"Politechnica" University Timişoara',institution:null},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. Science CV available at: https://www.cienciavitae.pt//pt/8E1C-A8B3-78C5 and ORCID: https://orcid.org/0000-0002-0298-3974',institutionString:"University of Lisbon",institution:{name:"Universidade Lusófona",country:{name:"Portugal"}}},{id:"241400",title:"Prof.",name:"Mohammed",middleName:null,surname:"Bsiss",slug:"mohammed-bsiss",fullName:"Mohammed Bsiss",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241400/images/8062_n.jpg",biography:null,institutionString:null,institution:null},{id:"276128",title:"Dr.",name:"Hira",middleName:null,surname:"Fatima",slug:"hira-fatima",fullName:"Hira Fatima",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/276128/images/14420_n.jpg",biography:"Dr. Hira Fatima\nAssistant Professor\nDepartment of Mathematics\nInstitute of Applied Science\nMangalayatan University, Aligarh\nMobile: no : 8532041179\nhirafatima2014@gmal.com\n\nDr. Hira Fatima has received his Ph.D. degree in pure Mathematics from Aligarh Muslim University, Aligarh India. Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. She is a member of Indian Mathematical Society.",institutionString:null,institution:null},{id:"414880",title:"Dr.",name:"Maryam",middleName:null,surname:"Vatankhah",slug:"maryam-vatankhah",fullName:"Maryam Vatankhah",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Borough of Manhattan Community College",country:{name:"United States of America"}}},{id:"414879",title:"Prof.",name:"Mohammad-Reza",middleName:null,surname:"Akbarzadeh-Totonchi",slug:"mohammad-reza-akbarzadeh-totonchi",fullName:"Mohammad-Reza Akbarzadeh-Totonchi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Ferdowsi University of Mashhad",country:{name:"Iran"}}},{id:"414878",title:"Prof.",name:"Reza",middleName:null,surname:"Fazel-Rezai",slug:"reza-fazel-rezai",fullName:"Reza Fazel-Rezai",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"American Public University System",country:{name:"United States of America"}}},{id:"426586",title:"Dr.",name:"Oladunni A.",middleName:null,surname:"Daramola",slug:"oladunni-a.-daramola",fullName:"Oladunni A. Daramola",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Federal University of Technology",country:{name:"Nigeria"}}},{id:"357014",title:"Prof.",name:"Leon",middleName:null,surname:"Bobrowski",slug:"leon-bobrowski",fullName:"Leon Bobrowski",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Bialystok University of Technology",country:{name:"Poland"}}},{id:"302698",title:"Dr.",name:"Yao",middleName:null,surname:"Shan",slug:"yao-shan",fullName:"Yao Shan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Dalian University of Technology",country:{name:"China"}}},{id:"354126",title:"Dr.",name:"Setiawan",middleName:null,surname:"Hadi",slug:"setiawan-hadi",fullName:"Setiawan Hadi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Padjadjaran University",country:{name:"Indonesia"}}},{id:"125911",title:"Prof.",name:"Jia-Ching",middleName:null,surname:"Wang",slug:"jia-ching-wang",fullName:"Jia-Ching Wang",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"National Central University",country:{name:"Taiwan"}}},{id:"332603",title:"Prof.",name:"Kumar S.",middleName:null,surname:"Ray",slug:"kumar-s.-ray",fullName:"Kumar S. Ray",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Statistical Institute",country:{name:"India"}}},{id:"415409",title:"Prof.",name:"Maghsoud",middleName:null,surname:"Amiri",slug:"maghsoud-amiri",fullName:"Maghsoud Amiri",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Allameh Tabataba'i University",country:{name:"Iran"}}},{id:"357085",title:"Mr.",name:"P. Mohan",middleName:null,surname:"Anand",slug:"p.-mohan-anand",fullName:"P. Mohan Anand",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"356696",title:"Ph.D. Student",name:"P.V.",middleName:null,surname:"Sai Charan",slug:"p.v.-sai-charan",fullName:"P.V. Sai Charan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"357086",title:"Prof.",name:"Sandeep K.",middleName:null,surname:"Shukla",slug:"sandeep-k.-shukla",fullName:"Sandeep K. Shukla",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}}]}},subseries:{item:{id:"27",type:"subseries",title:"Multi-Agent Systems",keywords:"Collaborative Intelligence, Learning, Distributed Control System, Swarm Robotics, Decision Science, Software Engineering",scope:"Multi-agent systems are recognised as a state of the art field in Artificial Intelligence studies, which is popular due to the usefulness in facilitation capabilities to handle real-world problem-solving in a distributed fashion. The area covers many techniques that offer solutions to emerging problems in robotics and enterprise-level software systems. Collaborative intelligence is highly and effectively achieved with multi-agent systems. Areas of application include swarms of robots, flocks of UAVs, collaborative software management. Given the level of technological enhancements, the popularity of machine learning in use has opened a new chapter in multi-agent studies alongside the practical challenges and long-lasting collaboration issues in the field. It has increased the urgency and the need for further studies in this field. We welcome chapters presenting research on the many applications of multi-agent studies including, but not limited to, the following key areas: machine learning for multi-agent systems; modeling swarms robots and flocks of UAVs with multi-agent systems; decision science and multi-agent systems; software engineering for and with multi-agent systems; tools and technologies of multi-agent systems.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/27.jpg",hasOnlineFirst:!0,hasPublishedBooks:!1,annualVolume:11423,editor:{id:"148497",title:"Dr.",name:"Mehmet",middleName:"Emin",surname:"Aydin",slug:"mehmet-aydin",fullName:"Mehmet Aydin",profilePictureURL:"https://mts.intechopen.com/storage/users/148497/images/system/148497.jpg",biography:"Dr. Mehmet Emin Aydin is a Senior Lecturer with the Department of Computer Science and Creative Technology, the University of the West of England, Bristol, UK. His research interests include swarm intelligence, parallel and distributed metaheuristics, machine learning, intelligent agents and multi-agent systems, resource planning, scheduling and optimization, combinatorial optimization. Dr. Aydin is currently a Fellow of Higher Education Academy, UK, a member of EPSRC College, a senior member of IEEE and a senior member of ACM. In addition to being a member of advisory committees of many international conferences, he is an Editorial Board Member of various peer-reviewed international journals. He has served as guest editor for a number of special issues of peer-reviewed international journals.",institutionString:null,institution:{name:"University of the West of England",institutionURL:null,country:{name:"United Kingdom"}}},editorTwo:null,editorThree:null,series:{id:"14",title:"Artificial Intelligence",doi:"10.5772/intechopen.79920",issn:"2633-1403"},editorialBoard:[{id:"275140",title:"Dr.",name:"Dinh Hoa",middleName:null,surname:"Nguyen",slug:"dinh-hoa-nguyen",fullName:"Dinh Hoa Nguyen",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRbnKQAS/Profile_Picture_1622204093453",institutionString:null,institution:{name:"Kyushu University",institutionURL:null,country:{name:"Japan"}}},{id:"20259",title:"Dr.",name:"Hongbin",middleName:null,surname:"Ma",slug:"hongbin-ma",fullName:"Hongbin Ma",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRhDJQA0/Profile_Picture_2022-05-02T08:25:21.jpg",institutionString:null,institution:{name:"Beijing Institute of Technology",institutionURL:null,country:{name:"China"}}},{id:"28640",title:"Prof.",name:"Yasushi",middleName:null,surname:"Kambayashi",slug:"yasushi-kambayashi",fullName:"Yasushi Kambayashi",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYOQxQAO/Profile_Picture_1625660525470",institutionString:null,institution:{name:"Nippon Institute of Technology",institutionURL:null,country:{name:"Japan"}}}]},onlineFirstChapters:{paginationCount:2,paginationItems:[{id:"82936",title:"Soil Degradation Processes Linked to Long-Term Forest-Type Damage",doi:"10.5772/intechopen.106390",signatures:"Pavel Samec, Aleš Kučera and Gabriela Tomášová",slug:"soil-degradation-processes-linked-to-long-term-forest-type-damage",totalDownloads:3,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Forest Degradation Under Global Change",coverURL:"https://cdn.intechopen.com/books/images_new/11457.jpg",subseries:{id:"94",title:"Climate Change and Environmental Sustainability"}}},{id:"82124",title:"Assessment of Diversity, Growth Characteristics and Aboveground Biomass of Tree Species in Selected Urban Green Areas of Osogbo, Osun State",doi:"10.5772/intechopen.104982",signatures:"Omolara Aremu, Olusola O. 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\r\n\tThe era of antibiotics led us to the illusion that the problem of bacterial infection is over. However, bacterial flexibility and adaptation mechanisms allow them to survive and grow in extreme conditions. The best example is the formation of a sophisticated society of bacteria defined as a biofilm. Understanding the mechanism of bacterial biofilm formation has changed our perception of the development of bacterial infection but successfully eradicating biofilm remains a challenge. Considering the above, it is not surprising that bacteria remain a major public health threat despite the development of many groups of antibiotics. Additionally, increasing prevalence of acquired antibiotic resistance forces us to realize that we are far from controlling the development of bacterial infections. On the other hand, many infections are endogenous and result from an unbalanced relationship between the host and the microorganism. The increasing use of immunosuppressants, such as chemotherapy or organ transplantation, increases the incidence of patients highly susceptible to bacterial infections in the population.
\r\n
\r\n\tThis topic will focus on the current challenges and advantages in the diagnosis and treatment of bacterial infections. We will discuss the host-microbiota relationship, the treatment of chronic infections due to biofilm formation, and the development of new diagnostic tools to rapidly distinguish between colonization and probable infection.
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The most common fungal infection pathways are human to human (anthropophilic), animal to human (zoophilic), and environment to human (soilophile). Diseases are common as a result of widespread exposure to pathogenic fungus dispersed into the environment. \r\nFungi that are both common and emerging are intertwined. In Southeast Asia, for example, Talaromyces marneffei is an important pathogenic thermally dimorphic fungus that causes systemic mycosis. Widespread fungal infections with complicated and variable clinical manifestations, such as Candida auris infection resistant to several antifungal medicines, Covid-19 associated with Trichoderma, and terbinafine resistant dermatophytosis in India, are among the most serious disorders. \r\nInappropriate local or systemic use of glucocorticoids, as well as their immunosuppressive effects, may lead to changes in fungal infection spectrum and clinical characteristics. Hematogenous candidiasis is a worrisome issue that affects people all over the world, particularly ICU patients. CARD9 deficiency and fungal infection have been major issues in recent years. Invasive aspergillosis is associated with a significant death rate. Special attention should be given to endemic fungal infections, identification of important clinical fungal infections advanced in yeasts, filamentous fungal infections, skin mycobiome and fungal genomes, and immunity to fungal infections.\r\nIn addition, endemic fungal diseases or uncommon fungal infections caused by Mucor irregularis, dermatophytosis, Malassezia, cryptococcosis, chromoblastomycosis, coccidiosis, blastomycosis, histoplasmosis, sporotrichosis, and other fungi, should be monitored. \r\nThis topic includes the research progress on the etiology and pathogenesis of fungal infections, new methods of isolation and identification, rapid detection, drug sensitivity testing, new antifungal drugs, schemes and case series reports. It will provide significant opportunities and support for scientists, clinical doctors, mycologists, antifungal drug researchers, public health practitioners, and epidemiologists from all over the world to share new research, ideas and solutions to promote the development and progress of medical mycology.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/4.jpg",keywords:"Emerging Fungal Pathogens, Invasive Infections, Epidemiology, Cell Membrane, Fungal Virulence, Diagnosis, Treatment"},{id:"5",title:"Parasitic Infectious Diseases",scope:"Parasitic diseases have evolved alongside their human hosts. In many cases, these diseases have adapted so well that they have developed efficient resilience methods in the human host and can live in the host for years. Others, particularly some blood parasites, can cause very acute diseases and are responsible for millions of deaths yearly. Many parasitic diseases are classified as neglected tropical diseases because they have received minimal funding over recent years and, in many cases, are under-reported despite the critical role they play in morbidity and mortality among human and animal hosts. The current topic, Parasitic Infectious Diseases, in the Infectious Diseases Series aims to publish studies on the systematics, epidemiology, molecular biology, genomics, pathogenesis, genetics, and clinical significance of parasitic diseases from blood borne to intestinal parasites as well as zoonotic parasites. We hope to cover all aspects of parasitic diseases to provide current and relevant research data on these very important diseases. In the current atmosphere of the Coronavirus pandemic, communities around the world, particularly those in different underdeveloped areas, are faced with the growing challenges of the high burden of parasitic diseases. At the same time, they are faced with the Covid-19 pandemic leading to what some authors have called potential syndemics that might worsen the outcome of such infections. Therefore, it is important to conduct studies that examine parasitic infections in the context of the coronavirus pandemic for the benefit of all communities to help foster more informed decisions for the betterment of human and animal health.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/5.jpg",keywords:"Blood Borne Parasites, Intestinal Parasites, Protozoa, Helminths, Arthropods, Water Born Parasites, Epidemiology, Molecular Biology, Systematics, Genomics, Proteomics, Ecology"},{id:"6",title:"Viral Infectious Diseases",scope:"The Viral Infectious Diseases Book Series aims to provide a comprehensive overview of recent research trends and discoveries in various viral infectious diseases emerging around the globe. The emergence of any viral disease is hard to anticipate, which often contributes to death. A viral disease can be defined as an infectious disease that has recently appeared within a population or exists in nature with the rapid expansion of incident or geographic range. This series will focus on various crucial factors related to emerging viral infectious diseases, including epidemiology, pathogenesis, host immune response, clinical manifestations, diagnosis, treatment, and clinical recommendations for managing viral infectious diseases, highlighting the recent issues with future directions for effective therapeutic strategies.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/6.jpg",keywords:"Novel Viruses, Virus Transmission, Virus Evolution, Molecular Virology, Control and Prevention, Virus-host Interaction"}],annualVolumeBook:{},thematicCollection:[],selectedSeries:{title:"Infectious Diseases",id:"6"},selectedSubseries:null},seriesLanding:{item:null},libraryRecommendation:{success:null,errors:{},institutions:[]},route:{name:"profile.detail",path:"/profiles/62664",hash:"",query:{},params:{id:"62664"},fullPath:"/profiles/62664",meta:{},from:{name:null,path:"/",hash:"",query:{},params:{},fullPath:"/",meta:{}}}},function(){var e;(e=document.currentScript||document.scripts[document.scripts.length-1]).parentNode.removeChild(e)}()