\r\n\tThis book will describe the self-assembly of materials and supramolecular chemistry design principles for a broad spectrum of materials, including bio-inspired amphiphiles, metal oxides, metal nanoparticles, and organic-inorganic hybrid materials. It will provide fundamental concepts of self-assembly design approaches and supramolecular chemistry principles for research ideas in nanotechnology applications. The book will focus on three main themes, which include: the self-assembly and supramolecular chemistry of amphiplies by coordination programming, the supramolecular structures and devices of inorganic materials, and the assembly-disassembly of organic-inorganic hybrid materials. The contributing chapters will be written by leading scientists in their field, with the hope that this book will provide a foundation on supramolecular chemistry principles to students and active researchers who are interested in nanoscience and nanoengineering fields.
",isbn:"978-1-83969-702-9",printIsbn:"978-1-83969-701-2",pdfIsbn:"978-1-83969-703-6",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,isSalesforceBook:!1,isNomenclature:!1,hash:"e9cc643ae0a219e91e445a1e61b33a22",bookSignature:"Prof. Hemali Rathnayake and Dr. Gayani Pathiraja",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11908.jpg",keywords:"Amphiphiles, Artificial Siderophores, Coordination Chemistry, Self-Assembly Design, Supramolecular Structures, Metal Oxides, Metal Particles, 2D Inorganic Materials, Supramolecular Devices, Stimuli-Responsive Materials, Assembly-Disassembly Design, Superstructures",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"April 27th 2022",dateEndSecondStepPublish:"July 1st 2022",dateEndThirdStepPublish:"August 30th 2022",dateEndFourthStepPublish:"November 18th 2022",dateEndFifthStepPublish:"January 17th 2023",dateConfirmationOfParticipation:null,remainingDaysToSecondStep:"a month",secondStepPassed:!0,areRegistrationsClosed:!1,currentStepOfPublishingProcess:3,editedByType:null,kuFlag:!1,biosketch:"Dr. Rathnayake is a pioneering researcher in self-assembly and supramolecular chemistry, with a Ph.D. from the University of Massachusetts Amherst, US. She is an inventor of three innovative technologies, including the Bioinspried Sub-7 nm self-assembled structures for patterning, and holder of multiple registered patents.",coeditorOneBiosketch:"Dr. Gayani Pathiraja is a Postdoctoral Research Scholar at the Joint School of Nanoscience and Nanoengineering (JSNN). She received her Ph.D. in Nanoscience from the University of North Carolina at Greensboro in 2021. Her research interests focus on the crystal growth mechanism and kinetics of metal oxide nanostructure formation via self-assembly.",coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"323782",title:"Prof.",name:"Hemali",middleName:null,surname:"Rathnayake",slug:"hemali-rathnayake",fullName:"Hemali Rathnayake",profilePictureURL:"https://mts.intechopen.com/storage/users/323782/images/system/323782.jpg",biography:"Dr. Hemali Rathnayake, Associate Professor in the Department of Nanoscience at the Joint School of Nanoscience and Nanoengineering, the University of North Carolina at Greensboro, USA, obtained her B.S. in Chemistry from the University of Peradeniya in Sri Lanka. She obtained her Ph.D. from the University of Massachusetts Amherst (UMass), Department of Chemistry in 2007. She was a Postdoctoral research fellow at Polymer Science & Engineering, UMass Amherst. \r\nDr. Rathnayake is a pioneer scientist and a chemist in the field of Nanomaterials Chemistry, with a focus on the interfacial interaction of nanomaterials, molecules, macromolecules, and polymers in homogeneous and heterogeneous media. Her research on the design, synthesis, self-assembly, and application of well-defined superstructures in nanoelectronics, environmental remediation, and sustainable energy has impacted the scientific community with highly rated peer-reviewed journals publications, and more than 80 invited talks to scientific and non-scientific communities including colleges and high schools.",institutionString:"University of North Carolina at Greensboro",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"2",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"University of North Carolina at Greensboro",institutionURL:null,country:{name:"United States of America"}}}],coeditorOne:{id:"427650",title:"Dr.",name:"Gayani",middleName:null,surname:"Pathiraja",slug:"gayani-pathiraja",fullName:"Gayani Pathiraja",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003CCSN2QAP/Profile_Picture_1644217020559",biography:"Dr. Gayani Pathiraja is a Postdoctoral Research Scholar at the Joint School of Nanoscience and Nanoengineering (JSNN). She received her Ph.D. in Nanoscience from the University of North Carolina at Greensboro (UNCG) in 2021. Her expertise area of focus is investigating the crystal growth mechanism and kinetics of metal oxide nanostructure formation via in-situ self-assembly design principles. \r\nDr. Pathiraja earned her master’s degree in electrochemistry/Environmental Engineering from the University of Peradeniya, Sri Lanka, and her Bachelor’s degree in Materials Science and Technology from Uva Wellassa University, Sri Lanka. Dr. Pathiraja started her academic career as a lecturer at the Department of Engineering Technology, University of Ruhuna, Sri Lanka in 2016. She is a co-author of several peer-reviewed journal publications and a book chapter, and she has presented her work at several regional, international, and national conferences.",institutionString:"University of North Carolina at Greensboro",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"University of North Carolina at Greensboro",institutionURL:null,country:{name:"United States of America"}}},coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"8",title:"Chemistry",slug:"chemistry"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"466998",firstName:"Dragan",lastName:"Miljak",middleName:"Anton",title:"Mr.",imageUrl:"https://mts.intechopen.com/storage/users/466998/images/21564_n.jpg",email:"dragan@intechopen.com",biography:"As an Author Service Manager my responsibilities include monitoring and facilitating all publishing activities for authors and editors. 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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"}},{type:"book",id:"3092",title:"Anopheles mosquitoes",subtitle:"New insights into malaria vectors",isOpenForSubmission:!1,hash:"c9e622485316d5e296288bf24d2b0d64",slug:"anopheles-mosquitoes-new-insights-into-malaria-vectors",bookSignature:"Sylvie Manguin",coverURL:"https://cdn.intechopen.com/books/images_new/3092.jpg",editedByType:"Edited by",editors:[{id:"50017",title:"Prof.",name:"Sylvie",surname:"Manguin",slug:"sylvie-manguin",fullName:"Sylvie Manguin"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"72",title:"Ionic Liquids",subtitle:"Theory, Properties, New Approaches",isOpenForSubmission:!1,hash:"d94ffa3cfa10505e3b1d676d46fcd3f5",slug:"ionic-liquids-theory-properties-new-approaches",bookSignature:"Alexander Kokorin",coverURL:"https://cdn.intechopen.com/books/images_new/72.jpg",editedByType:"Edited by",editors:[{id:"19816",title:"Prof.",name:"Alexander",surname:"Kokorin",slug:"alexander-kokorin",fullName:"Alexander Kokorin"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"2270",title:"Fourier Transform",subtitle:"Materials Analysis",isOpenForSubmission:!1,hash:"5e094b066da527193e878e160b4772af",slug:"fourier-transform-materials-analysis",bookSignature:"Salih Mohammed Salih",coverURL:"https://cdn.intechopen.com/books/images_new/2270.jpg",editedByType:"Edited by",editors:[{id:"111691",title:"Dr.Ing.",name:"Salih",surname:"Salih",slug:"salih-salih",fullName:"Salih Salih"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"117",title:"Artificial Neural Networks",subtitle:"Methodological Advances and Biomedical Applications",isOpenForSubmission:!1,hash:null,slug:"artificial-neural-networks-methodological-advances-and-biomedical-applications",bookSignature:"Kenji Suzuki",coverURL:"https://cdn.intechopen.com/books/images_new/117.jpg",editedByType:"Edited by",editors:[{id:"3095",title:"Prof.",name:"Kenji",surname:"Suzuki",slug:"kenji-suzuki",fullName:"Kenji Suzuki"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3828",title:"Application of Nanotechnology in Drug Delivery",subtitle:null,isOpenForSubmission:!1,hash:"51a27e7adbfafcfedb6e9683f209cba4",slug:"application-of-nanotechnology-in-drug-delivery",bookSignature:"Ali Demir Sezer",coverURL:"https://cdn.intechopen.com/books/images_new/3828.jpg",editedByType:"Edited by",editors:[{id:"62389",title:"PhD.",name:"Ali Demir",surname:"Sezer",slug:"ali-demir-sezer",fullName:"Ali Demir Sezer"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"872",title:"Organic Pollutants Ten Years After the Stockholm Convention",subtitle:"Environmental and Analytical Update",isOpenForSubmission:!1,hash:"f01dc7077e1d23f3d8f5454985cafa0a",slug:"organic-pollutants-ten-years-after-the-stockholm-convention-environmental-and-analytical-update",bookSignature:"Tomasz Puzyn and Aleksandra Mostrag-Szlichtyng",coverURL:"https://cdn.intechopen.com/books/images_new/872.jpg",editedByType:"Edited by",editors:[{id:"84887",title:"Dr.",name:"Tomasz",surname:"Puzyn",slug:"tomasz-puzyn",fullName:"Tomasz Puzyn"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3569",title:"Biodegradation",subtitle:"Life of Science",isOpenForSubmission:!1,hash:"bb737eb528a53e5106c7e218d5f12ec6",slug:"biodegradation-life-of-science",bookSignature:"Rolando Chamy and Francisca Rosenkranz",coverURL:"https://cdn.intechopen.com/books/images_new/3569.jpg",editedByType:"Edited by",editors:[{id:"165784",title:"Dr.",name:"Rolando",surname:"Chamy",slug:"rolando-chamy",fullName:"Rolando Chamy"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"50117",title:"Software for Reliability Analysis",doi:"10.5772/62367",slug:"software-for-reliability-analysis",body:'This short overview gives only some of the commercial programs for reliability assessment. They range from simple ones at moderate prices and suitable for a limited range of problems to program systems for the analysis of complex problems. For getting practice and for the solution of simple problems, the reader can create own programs based on universal software such as Excel, although their possibilities are limited.
A simple Monte Carlo simulation program VaP enables the probabilistic analysis of a user-defined function
Anthill is a computer program for the calculation of reliability and other statistical analyses based on the Monte Carlo method. The user-defined model for analysis can use various mathematical and logical functions and predefined histograms. After the trials with random values of input quantities have been performed, a statistical analysis of sampled values is performed, and the results are displayed. The resulting histograms and statistical parameters can be saved for further postprocessing. Favorable price-performance ratio.
FReET is a multipurpose probabilistic software for statistical, sensitivity, and reliability analysis of engineering problems, developed at the Brno University of Technology, Institute of Structural Mechanics. It allows the simulation of random uncertainties in various problems, especially in civil and mechanical engineering (material properties, loading and geometrical imperfections). It uses the following probabilistic techniques: crude Monte Carlo simulation, Latin hypercube sampling, simulated annealing, first-order reliability method (FORM), and others. Favorable price-performance ratio.
Strurel is a set of programs for the reliability analysis of constructions (especially in civil engineering). It consists of three programs: Statrel (reliability-oriented statistical analysis), Comrel (time-invariant and time-variant analysis), and Sysrel (a program for system reliability analysis). It can work with analytical functions and performs reliability analysis using various methods, such as Monte Carlo or FORM and SORM (first-order or second-order reliability methods), used for the solution of the problems of load-resistance type.
In addition to the above software, oriented mostly on the determination of failure probability of one component or construction, also software systems exist, which use various tools and enable comprehensive reliability analysis of very complex objects, such as aircrafts or weapon systems. Here, four brands will be mentioned.
This software firm (USA) offers various products, such as ITEM ToolKit. This is a suite of several analytical and reliability prediction modules in one integrated environment, such as
MIL-HDBK-217 module. A reliability prediction program based on the internationally recognized method of calculating electronic equipment reliability defined in military handbook MIL-HDBK-217 (published by the U.S. Department of Defense).
IEC 62380 Electronic Reliability Prediction module. It supports reliability prediction methods based on the latest European reliability prediction standard IEC.
NSWC Mechanical Reliability Prediction module. It uses a series of models for various types of mechanical devices including actuators, springs, bearings, seals, electric motors, pumps, compressors, brakes, and clutches to predict failure rates based on temperature, stresses, flow rates, and various other parameters. The module is based on the Naval Surface Warfare Center Handbook of Reliability Prediction Procedures for Mechanical Equipment.
China 299B Electronic Reliability Prediction module: A reliability prediction program based on the internationally recognized method of calculating electronic equipment reliability provided in the Chinese Military/Commercial Standard GJB/z 299B.
Telcordia Electronic Reliability Prediction module: Based on the Telcordia (Bellcore) TR-332 and SR-332 standards, calculates the reliability (steady-state failure rate) for various categories of electronic, electrical, and electromechanical components for various quality levels, environmental conditions, electrical stress conditions, and other parameters.
In addition to these modules, the ITEM ToolKit contains several other modules, for example for failure modes, effects, and criticality analysis (FMECA); for fault tree analysis (FTA); for construction of reliability block diagrams (RBD); for Markov analysis; and for maintenance and others.
This U.S. software firm offers a group of programs in one integrated environment, such as Weibull±±® for reliability analysis; ALTA® for Accelerated Life Testing Data Analysis; DOE±±® for design of experiments; BlockSim® for the creation of reliability block diagrams based on fault tree analysis; RENO® simulation software for risk and decision analysis; Xfmea® – software for facilitating data management and reporting for all types of FMEA and FMECA; RCM±±® – software for the support of reliability-centered maintenance; Lambda Predict® – for reliability assessment based on standards; RBI® – risk-based inspection analysis for oil, gas, chemical, and power plants in adherence to the guidelines presented in the American Petroleum Institute’s publications API RP 580 and RP 581, as well as the American Society of Mechanical Engineers ASME; XFRACAS® – software system for web-based incident/failure/data reporting, analysis, and corrective action; and RGA® – software for the analysis and support of reliability growth.
Isograph offers various software for reliability analysis, such as:
Availability Workbench: A system for availability simulation and reliability-centered maintenance RCM. It is used to optimize maintenance and spare parts, predict system availability and throughput, and estimate life-cycle costs. It includes Weibull analysis and life cycle costing modules as well as modeling methods such as FMECA, reliability block diagram analysis, and fault tree analysis.
Reliability Workbench: An integrated visual environment in which failure rate and maintainability prediction, FMECA, reliability allocation, reliability block diagram, fault tree, event tree, and Markov analysis are combined. Failure rate predictions are calculated from the Telcordia, MIL-HDBK-217, 217 Plus, and IEC TR 62380 standards for electronic equipment and the NSWC-98/LE1 Handbook for mechanical parts. FMECA, reliability block diagram, and fault tree analysis are performed to well-known standards such as MIL-STD 1629 and IEC 61508.
Hazop±: software for hazard and operability studies, with visual environment using the forms for entering Hazop information. Extensive reporting facilities are available.
More information, including other products, is available at the web site.
PTC Windchill Quality Solutions combines quality, reliability, and risk management into an integrated toolset with the following products:
PTC Windchill CAPA: corrects and prevents actions and demonstrates compliance.
PTC Windchill Nonconformance: manages, corrects, and tracks internal quality issues.
PTC Windchill FRACAS: identifies and prioritizes failure-related trends.
PTC Windchill FMEA: identifies and mitigates potential failures.
PTC Windchill MSG-3: manages aircraft reliability according to industry standards.
PTC Windchill FTA: utilizes fault tree analysis to investigate safety and reliability issues.
PTC Windchill Prediction: predicts failure rate of components and system reliability.
PTC Windchill RBD: Reliability Block Diagrams manage quality in complex systems.
PTC Windchill Maintainability: predicts maintenance and repairs.
PTC Windchill LCC: Life Cycle Cost software analyzes the lifetime cost of a product.
PTC Windchill Weibull: Life data analysis or Weibull estimates on the life data of a product.
PTC Windchill ALT : Accelerated Life Testing software predicts product reliability.
PTC Windchill Markov: Visual analysis software that models complex systems.
PTC Windchill Customer Experience Management: reports and manages quality-related field issues.
Almost half of the world populations rely on biomass fuels (BMF) for cooking, heating and lightning purpose. Household air pollution (HAP) from incomplete combustion of BMF is now understood to be a major risk factor for adverse health outcomes [1]. According to the 2016 Global Burden of Disease Study (GBD), HAP is ranked as the single most significant environmental health risk factor globally. It accounted for 2.6 million deaths and 77.2 million disability-adjusted life years (DALYs) in year 2016 [2], with greater than 99% of death occurring in low and middle income countries [3]. The health effect ranges from cardiovascular, respiratory, neurocognitive and reproductive health effect. The most important one is cardiovascular and respiratory health effect [4, 5, 6].
\nThe association between high levels of air pollutants and adverse health outcomes has been known since the seventeenth century [7]. In the 17th century, Queen Elizabeth I forbid the burning of coal near the palace at Westminster due to the unpleasant nature of smoke, by 1661 in London, John Evelyn suggested that factories should be located far from residential area [7]. In the 19th century, clinicians started linking lung diseases to air pollution in England [8]. Also, smog incidents in Meuse Valley, Belgium in 1930, Donora, Pennsylvania in 1948, and London, UK in 1952 acutely affected the elderly and those with existing cardiac and respiratory diseases and it caused increased hospitalizations and deaths. As a result of the London smog, an estimated 4000 people died and over 100,000 people suffered adverse health effects [9, 10]. Earlier this year, millions of Australians have been reported to be affected by air pollution, especially in the southwestern part of Australia where fire killed about 20 people including 3 volunteered fire fighters from the country wildfire [11].
\nBiomass fuel (BMF) is any living or recently living plant or animal-based material that is burned by humans as fuels, for example wood, dried animal dung, charcoal, grass and agricultural residue such as straw and sticks, dried leaves, twigs and wild grass [12, 13]. Although biomass fuel is primarily used by women in developing countries for domestic cooking and it is also used in developed countries primarily for the purpose of heating at homes, for example, 5% of household surveyed in Australia used woodstoves for indoor heating. BMF may also be chosen for cooking in developing countries because of the flavor they impact during cooking processes e.g. barbecues, smoked meat and wood-fired pizza [14]. There is also occupational exposure to BMF in developing countries, such occur as fire fighters [15]. In addition, air pollution from BMF also result from planned forest fires for agricultural practices during autumn and spring, and bushfires from countries with substantial parks and bush lands such as Canada and the USA during summer [14].
\nAlthough, incomplete combustion of BMF from cooking and heating result mainly in household air pollution (HAP), it is also an important contributor to ambient (outdoor) air pollution (AAP), accounting for an estimated 10–30% of ambient fine particulate matter (PM) [16], this is particularly so in developing countries. However, exposure to biomass PM is increasing in developed countries mainly from domestic heating purposes, increasing wild fires, and which can substantially contribute to ambient PM concentrations, particularly in winter months [13, 14, 15, 16].
\nThe air pollutants from burning of BMF is numerous and has been shown to consist of 200 different compounds. Some of the pollutants are PM, carbon monoxide, sulphur and nitrogen oxides; organic compound like formaldehyde, acrolein, etc. [17, 18, 19]. The exact chemical composition of biomass smoke is dependent upon the fuel type, the temperature of burning, whether an open fire or free radicals incinerator is used, and local conditions (e.g., wind speed, humidity, indoor or outdoor fires) [14].
\nAlthough there are many pollutants, it is PM that have received most of the attention in scientific literature, on the basis of robust epidemiological, clinical and toxicological association between PM, and respiratory and cardiovascular diseases [19, 20].
\nPM components of air pollution are mixtures of solid, liquid and mixed phased particles suspended in air. It consists of carbonaceous particles with associated adsorbed organic chemicals and reactive metals. Common components of PM include nitrates, sulfates, PAH, endotoxin, and metals such as iron, copper, nickel, zinc, and vanadium [17]. PM is heterogeneous and variations in the characteristics of particles (e.g. particle size, surface area, and composition) (e.g. PAH, metal, and endotoxin content) released from different emission sources can influence the biological response [21]. The composition of PM to air pollution is highly dependent on season, density of sources and the specific technologies employed as well as meteorology and topography. In middle and low income countries, homes using BMF with poor designs that do not have flues or hood to take smoke out of the living area are often affected by the adverse health effects of HAP due to lack of ventilations [12].
\nPM can be classified based on aerodynamic diameter; this determine the site of deposition [22, 23, 24]. PM with a diameter of 0.1 μm or less are termed ultrafine PM and are deposited in the alveoli. While diameter of 2.5 μm or less are termed fine PM.
\nPM which are light and can remain suspended in air for longer periods and they are deposited throughout the respiratory tract, particularly in small airways and alveoli [24, 25]. These particles can be inhaled deep into the lungs, and have been linked to oxidative stress and inflammation induced damage of the respiratory system [26]. Coarse PM has an aerodynamic diameter of 2.5–10 μm and are deposited in large airways [27, 28]. The concentration of PM can be as high as 100 times the recommended 24 hour concentration by the U.S. Environmental Protection Agency and the WHO [29]. Although much of the research has been on PM, other components of BMF contribute significantly to the damaging effect of the respiratory system [30].
\nSeveral studies have reported association of PM with different respiratory diseases, cardiovascular diseases, cancers, reproductive, neurocognitive and metabolic diseases [18, 25, 31, 32]. In a meta-analysis by Atkinson and colleagues, every 10 μg/cm3 increase in PM2.5 concentration was associated with a 1.04% (95% CI 0.52%–1.56%) increase in all-cause mortality [33]. Using 85 studies from 12 low- and middle-income countries in a meta-analysis study, Newell et al. reported that a 0.47% (95% CI 0.34–0.61) increase for cardiovascular mortality and 0.57% (95% CI 0.28–0.86) increase for respiratory mortality for every 10 μg/cm3 increase in PM2.5 concentration [34].
\nOne of the commonly cited mechanism for the relationship between air pollutants is oxidative stress. Both particulate and gaseous pollutants can produce oxidative stress and can act independently or synergistically together [26]. However, most of the research on mechanism has focused on PM, as discussed earlier. Also, while the toxicological and health effects of air pollutants from BMF and other sources may be informative, people are exposed to a toxic mixture of all the components and maybe challenging to extrapolate individual effect to the compound exposure of air pollutants.
\nOxidative stress refers to the imbalance between the productions of reactive oxygen species (ROS) and the cells ability to detoxify reactive intermediates or to repair cellular damage caused by ROS, examples of ROS are hydroxyl radicals and superoxide. When air pollution occurs, there is a dramatic increase in ROS level, resulting in significant damage to cellular components, including proteins, lipids, and DNA [35]. ROS can be derived from components of BMF smoke as well as the inflammatory cells recruited to the lungs [14]. Inflammatory response is produced through upregulation of pro-inflammatory cytokines such as tumour necrosis factor alpha, interleukin 6, and granulocyte colony stimulatory factor. Also, the immune cells are also recruited as well as upregulation of matrix metalloproteinases 2 and 9 and epithelial-mesenchymal transition [36]. In the airway and alveoli, this oxidative stress leads to alveolar macrophages activation and injury in the epithelial lining which in turn attracts inflammatory cells from the circulation [37]. In addition, PM in alveoli macrophages has been shown to modulate innate immune system and increased susceptibility to infection [38].
\nLung inflammatory reaction can spill over into the systemic circulation and contribute to adverse effect in other organs [32]. PM exposure has been associated with systemic markers of oxidative stress which includes atherogenic precursors such as oxidized lipids, makers of hypercoagulability and thrombosis such as Von Willebrand factor and soluble CD 40 ligand, endothelial dysfunction, increased blood pressure and cardiac arrhythmias [31]. The systemic circulation could also be responsible for reproductive and intrauterine health effect [32].
\nGeneration of ROS can also initiate free radical chain reactions which ultimately reach the nucleus and damage DNA leading to lung cancer and other cancers such as head and neck cancer. Additionally, gaseous pollutant present in air pollution such as nitrogen dioxide and volatile compound such as benzene can also lead to oxidative DNA damage. PAHs present in PM also form DNA adducts that has been implicated in carcinogenesis [39, 40].
\nThere are compiling evidences associating exposure to solid fuel combustion products with respiratory diseases. Acute lower respiratory infection in children (ALRIs), chronic obstructive pulmonary disease (COPD) in women and lung cancer in women exposed to coal smoke are the three types of lung disease found to have strong evidence of association with exposure to solid fuel smoke: [12, 25].
\nThe first report of indoor cooking smoke associated with childhood pneumonia and bronchiolitis was reported by Sofoluwe in Nigeria [41]. Acute lower respiratory tract infection (ALRI) is a leading contributor to the global burden of disease, it is also the commonest causes of morbidity and mortality particularly in children younger than five years. Almost all of this burden occurs in developing country where BMF is the primary source of household energy [12]. The relative risk for ALRIs for children exposed to BMF which include coal has been quantified in a number of studies [12]. In general, there is 2 to 3 times greater risk of developing ALRI in young children living in households exposed to solid fuel as compared to those not exposed [42].
\nThe most recent meta-analysis by Smith and colleagues in 2014, using 23 observational studies and 1 randomized control trial, documented the pooled odds ratio of 1.78 (95% CI: 1.45–2.18) [18]. Although most of these studies are observational studies especially case control, and they used poor quality exposure measurement.
\nA recent study in Ethiopia, Adane and other investigators, recruited 5830 children less than 4 years old, and found that ALRI was linked with cow dung fuel use [AOR = 1.54 (95% CI: 1.02–2.330)], presence of extra indoors burning events [AOR =2.19 (95% CI: 1.41–3.40)], child spending time near stove during cooking [AOR =1.41 (95% CI: 1.06–1.88)] and frequent cooking of meals [AOR =1.55 (95% CI: 1.13–2.13)] [43].
\nAlthough, there are many observational epidemiologic data that support an association between early childhood exposure to HAP and ALRI. Randomized control trials of interventions of improved cook stoves to reduce exposure to BMF smoke in order to prevent childhood ALRIs are emerging. A recent meta-analysis, of the six studies reporting child pneumonia outcomes, demonstrated no significant benefit in intention-to-treat analysis [44].
\nTuberculosis is one of the leading causes of morbidity and mortality in the world, with a rate of 140 (95% CI: 915–1150) per 100,000 people. Exposure to HAP could impair the function of pulmonary alveolar macrophages and render the lungs prone to infections including tuberculosis [45]. There are conflicting results on the risk of tuberculosis and exposure to BMF. A meta-analysis by Lin et al. in 2014 reported that there were no association between BMF exposure and tuberculosis. With pooled odd ratio of 1.17 (95% CI: 0.83–1.65) for case–control study and 1.62 (95%CI 0.89–2.93) for cross sectional study [46]. Although, in Congo, Katoto reported that household air pollution is associated with chronic cough after completion of pulmonary tuberculosis treatment in adults [47].
\nThe COVID-19 pandemic is still ongoing, there have been report of association of COVID-19 with AAP. Although, there are no available data specifically for HAP. Yao investigated the associations between PM concentrations and the case fatality rate of COVID-19 in 49 China cities, he found positive associations between PM pollution and COVID-19 in the 49 cities. Every increase in PM2.5 and PM10 concentrations by 10 μg/m3, raised the COVID-19 case fatality rate by 0.24% (0.01–0.48) and 0.26% (0.00–0.51) respectively [48]. Also, in Italy, Zoran and colleagues found positive correlations between confirmed COVID-19 daily new cases in Milan and air pollution with PM as follows, namely: with daily maxima PM10 (R2 = 0.51), daily average surface air PM2.5 (R2 = 0.25), daily air quality index (R2 = 4.35) [49]. In a USA study, after adjusting for factors such as population, weather, socioeconomic and behavioral variables, Wu and colleagues reported that increase of only 1 μg/m3 in PM2.5 is associated with an 8% increase in the COVID-19 death rate (95% CI: 2%, 15%) [50]. However, air pollution has been documented to reduce during the lockdown period in different countries [51, 52], more epidemiological and experimental research are needed to estimate the impact of PM2.5 on the incidence, severity and mortality of COVID-19.
\nCOPD is the fourth leading cause of mortality globally, causing more than 3 million death annually and over 80% of these deaths occur in low- and middle-income countries. It is also a substantial cause of economic and social burden [2]. It is characterised by persistent airflow limitation, associated with chronic inflammation of the airways and lungs in response to exposure to noxious particles and gases [53]. Previous systematic review has documented consistent association of biomass fuel with COPD. Kurmi et al. demonstrated that people exposed to BMF are at an increased risk of COPD compared to those that are not exposed [54]. Similarly, Hu et al. showed that people exposed to BMF smoke had increased odds ratio (OR) of 2.44 (95% CI, 1.9–3.33) for developing COPD, as compared to those that are not exposed, exposure to BMF was associated for developing COPD in Asian population, non-Asian population, in men and women [55].
\nIn a recent meta-analysis by Sana et al., using 5 case–control studies and 19 cross sectional studies, they reported that biomass-exposed women were 1.38 times more likely to be diagnosed with COPD than non-exposed (OR 1.38, 95%Cl 1.28 to 1.57). The evidence is more for cross sectional studies than for case control studies but consistent in both rural and urban area [56]. HAP has been associated with increased risk of COPD exacerbation [57]. Effect of forest fire on emergency visit for COPD has been explored. Johnston et al. documented the odd ratio for COPD as 1.12 (95% CI: 1.02, 1.24) [58].
\nIntervention studies to prevent COPD from HAP is sparse, a prospective Chinese study show that substituting solid fuel with biogas for cooking and improving cooking ventilation were associated with a reduced decrease in FEV1 and risk of COPD [59]. In a recent meta-analysis by Thakur et al., they documented that improved cook stoves were associated with a significant reduction in COPD among women: RR = 0.74 (95% CI 0.61 to 0.90). They also reported that ICS resulted in reductions in cough RR = 0.72 (95% CI 0.60 to 0.87), phlegm RR = 0.65 (95% CI 0.52 to 0.80), wheezing/breathing difficulty RR = 0.41 (95% CI 0.29 to 0.59) [60].
\nAsthma is a non-communicable respiratory disease that is cause by chronic inflammation of the airways and results in wheezing, chest tightness, and cough. In 2015, approximately 400,000 people died of asthma worldwide [61]. In contrast to multiple studies on the risk of BMF smoke exposure and COPD, data are sparse on the risk of BMF and asthma. Although, there have been conflicting association or relationship between biomass exposure and asthma; evidences are emerging that biomass exposure may be linked with asthma risk, prevalence or incidence.
\nBarry et al. accessed 508 respondents and showed that individuals using wood or coal for cooking had increased odd of 2.3 (95% CI: 1.1–5.0) for reporting current asthma symptom [62]. Oluwole et al. also reported increased odds of asthma symptom in children who lived in household that used biomass had an adjusted OR of 1.33 (95% CI 1.05–1.6) for any of the asthma symptoms [63]. They further observed that biomass fuel use was associated with increased odds of severe symptoms of OR 2.39 (95% CI 1.16–4.84) [64]. Ayuk in their retrospective analysis of ISAAC phase III study found that open fire cooking was among the factors associated with asthma 1.28 (95% 1.06–1.51) [65].
\nHowever there are other studies that did not find an association between BMF and Asthma [66, 67]. Noonan et al. conducted a randomized control trial of air-filter intervention in asthmatic children exposed to BMF smoke, the intervention did not improve asthma quality of life. Although, there was an improvement in secondary measure of diurnal peak flow variability [68].
\nBMF exposure is also associated with interstitial lung disease referred to as ‘hut lung’ [12]. Hut lung disease is characterized by carbon disposition, dust macules, and mixed dust fibrosis, and it has been reported in cases primarily of women with chronic high-level exposure to indoor biomass smoke in developing countries [27]. In addition, bronchial anthracofibrosis has also been reported in elderly women who have worked long hours in poorly ventilated kitchen full of smoke due to incomplete combustion of BMF [69].
\nLung cancer causes more death globally than any other cancer and it is the seventh leading cause of death globally [70], the International Agency for Research on Cancer concluded emissions from household coal combustion are a Group 1 carcinogen, while those from biomass were categorised as 2A due to epidemiologic limitations Although, smoking is the major risk factor for lung cancer worldwide, about 1.5% of lung cancer death are attributed to exposure to carcinogens from biomass fuel smoke annually [71].
\nIn a meta-analysis to estimate the risk of lung cancer with the risk of BMF for cooking and heating, using 14 studies that were all case control, they found out that the risk of lung cancer with biomass for cooking and/or heating was OR 1.17 (95% CI 1.01 to 1.37). Although, more than 50% of the study did not report a clean reference category. When analyses restricted to studies with clean reference category, the evidence still remain the same for men and women [72]. A study published by Raspanti and colleagues, after the meta-analysis also reported OR: 1.77, (95% CI: 1.00–3.14), with the estimate more robust for non-smokers (Ptrend = 0.01). Their study was a case control study of 606 lung cancer cases and 606 healthy controls matched on age (±5 years), gender, and geographical residence and adjusting for potential confounders such as tobacco use, tuberculosis status, Social economic status, age, gender, ethnicity, and exposure to second hand smoke. Conclusively, there was an increased risk of lung cancer among those who were exposed to HAPs [73].
\nGlobally, gastric cancer is the fifth most common cancer and it is third among the causes of cancer mortality [74]. In a recent research carried out in Zambia, Kayamba et al. reported that there was an association between gastric cancer and reliance on BMF (OR, 3.5; 95% CI, 1.9 to 6.2; P < 0001) [40]. Okello and colleagues in a systematic review and meta-analysis using 16 case control studies, reported that the use of BMF was associated with increased risk of esophageal squamous cell carcinoma OR 3.02(95% CI 2.22, 4.11). Analysis by continent showed that Africa and Asia had the highest odds of esophageal squamous cell carcinoma [75].
\nJosyula and colleagues evaluated the relationship between HAP and other cancers apart from lung cancer in a meta-analysis, they found out that HAP was associated with cervical cancer neoplasia (OR = 6.46; 95% CI = 3.12–13.36); nasopharyngeal (OR = 1.80; 95% CI = 1.42–2.29); oral (OR = 2.44; 95% CI =1.87–3.19); laryngeal (OR = 2.35; 95% CI = 1.72–3.51) cancers and pharyngeal (OR = 3.56; 95% CI = 2.22–5.70). The association between HAP and upper aero-digestive cancers remained significant even when the analysis was restrained to only studies that controlled for smoking [76].
\nCataract is the clouding of the eye lens by preventing the passage of light and it is highly prevalent in developing countries. It is a leading cause of blindness globally [77]. Several studies have shown an association between cataract and BMF. GBD Risk factors collaboration in 2015 reported that cataract is a global leading cause of blindness and it account for approximately 0.12% of all DALYS [77]. Smith et al. using seven studies from India and Nepal provided estimates for association between HAP and cataract, they reported a pooled OR of 2.64 (1.74, 3.50); the evidence for men was inconclusive. However, the estimate for women was OR 2.47 (1.61, 3.73) was deemed reliable [14].
\nA meta-analysis also reported in 2014, despite study heterogeneity, BMF use was associated with an increased risk of cataract with summary effect size of 2.12; 95% CI 1.61–2.80 [78]. Thakur et al. in a meta-analysis of 3 studies documented that improved cook stoves among women significantly reduce the presence of ocular symptoms RR =0.58, (95% CI 0.43–0.78) [60].
\nCardiovascular disease is a leading cause of mortality worldwide and this is rapidly increasing in developing countries [31]. Although, there is a growing body of research linking HAP with sub-clinical indicators of cardiovascular disease risk including blood pressure, carotid atherosclerotic plaque, and arterial stiffness, epidemiological evidence linking BMF smoke and cardiovascular disease is limited [32]. According to a recent publication, it was reported that in middle- and low-income countries, household air pollution, along with other factors had stronger effects on cardiovascular disease or mortality compared to high income countries [79]. According to WHO, 12% of all death due to stroke can be attributable to the daily exposure to household air pollution arising from cooking with solid fuels and kerosene [80].
\nFatmi and Coggon conducted a meta-analysis of 26 studies, 10 in south Asia, 4 in China, 2 in Turkey, 1 in Iran and 8 in Central and south American reported that the current balance of epidemiological evidence points to an increased risk of cardiovascular disease from HAP as a consequences of using solid and especially BMF for cooking and heating. Relative risks from long term exposure could be 2- to 4- fold [81]. In accordance with this study, using nationally representative and internationally comparable data, Arku et al. examined the association between solid fuel use and BP in 77,605 largely premenopausal women (aged 15–49) from ten resource-poor countries. They found that primary use of solid fuel was associated with 0.58 mmHg higher systolic BP (95% CI: 0.23, 0.93) as compared to primary use of clean fuel [82]. Ofoli et al. reported that use of BMF was associated with higher systolic blood pressure, more carotid intima media thickness (CIMT) and increased odds of pre-hypertension (OR: 1.67, 95% CI: 1.57–4.99, P = 0.035) [83].
\nIn a cross sectional Chinese study involving more than 14,000 men and women aged 18 years or older showed that BMF and coal was associated with self-report of physician diagnosed ischemic heart disease with an adjusted OR 2.6 for ever versus never of solid fuel and significant trend across duration of use for stroke, hypertension and diabetes [32].
\nIn addition, Right heart failure and pulmonary arterial hypertension were associated with HAP. Interestingly, women were almost two times more likely to present with pulmonary arterial hypertension (OR 1.72, 95% CI 1.17–2.55; p = 0.006), suggesting gender- related risk factors that may include HAP and HAP was also identified as a risk factor in women with isolated right heart failure in Kenya [84].
\nMost of the studies on metabolic diseases arose from ambient air studies [31, 32]. For example, a large study conducted in the United States reported that diabetes prevalence increases by 1% with each 10 μg/m3 PM2.5 [85]. Since HAP has been understudied with respect to cardiovascular disease most of our pathogenic hypothesis and more specific research is needed.
\nThere is limited but accruing evidence linking HAP exposure from solid fuel combustion with adverse maternal and perinatal outcomes. Also, epidemiologic evidence connecting AAP exposure with adverse pregnancy outcomes has been accumulating worldwide over the last two decades with several studies also attempting to summarize the available evidence [86].
\nIn a meta-analysis by Amegah et al. including 19 studies, BMF use resulted in reduced birth weight, [86.4 g (95% CI: 55.5, 117.4)]. There was also an increased risk of low birth weight and stillbirth in those exposed to BMF, [OR (1.35, 95% CI: 1.23, 1.48)] and [OR (29, 95% CI: 1.18, 1.41)] respectively [86]. Interventional studies assessing HAP and low-birth weight are limited. However, Thompson et al. found an increase of 89 g in the birth weight of children of mothers using the intervention stoves (vs. open fires) (95% CI −27, 204), and reduced odds of a low birth weight child (OR 0.74, 95% CI 0.33–1.66) [87].
\nIn a cross-sectional comparative study, Murkerjee and colleagues reported that there was positive association between BMF smoke exposure and menstrual irregularities such as irregular cycle (OR = 1.8, 95% CI 1.33–2.34), shortened menstrual cycle (OR = 5.1, 95% CI 3.62–9.21), spontaneous abortions (OR = 1.7, 95% CI 1.10–4.10), after controlling the potential confounders [88].
\nAgarwal and Yamamoto, using data from India’s third National Family Health Survey (NFHS-3, 2005–2006) of 39,657 women aged 15–49 years who had a live birth in the previous 5 years, reported that women residing in houses using BMF had higher odd of reporting preeclampsia/eclampsia symptoms compared to those who reside in houses using cleaner fuels (OR = 2.21; 95%: 1.26–3.87;
A recently published data from Ghana showed that using BMF was associated with adverse Apgar score at 5 min (aOR: 3.83, 95%CI: 1.44–10.11) and perinatal mortality (aOR: 7.6, 95%CI: 1.67–36.0) [91]. In sum, there are increasing evidences that BMF use are associated with menstrual irregularities, adverse pregnancy outcomes and perinatal morbidity and mortality.
\nThere is a convergence of human, animal, and in vitro studies on the effects of air pollution on the brain, although most study has been associated with ambient PM [92]. Several neurological diseases have linked with exposure to air pollution ranging from neuro degenerative disease, to psychiatric disease, to neurodevelopmental and behavioural disorders in children.
\nDementia denote memory loss and other cognitive abilities severe enough to interfere with daily life. Worse performance in tests evaluating episodic memory especially cognitive function tests had been associated with PM2.5 [93]. Other study has found associations between long-term exposure to PM2.5 among adults (>65 years) and neurodegenerative diseases such as Alzheimer’s, and Parkinson’s diseases [94].
\nPre-natal maternal or child exposure to air pollutants during pregnancy, infancy or childhood (when the brain neocortex develops rapidly) has been related to delays in cognitive development in children [95, 96]. A metanalysis by Lam et al., involving 17 case–control, 4 ecological, 2 cohort studies, they documented that PM was associated with autism; summary odds ratios (ORs) of 1.07 (95% CI: 1.06, 1.08) per 10-μg/m3 increase in PM10 exposure and 2.32 (95% CI: 2.15, 2.51) per 10-μg/m3 increase in PM2.5 exposure [97]. It has been postulated that air pollution induced oxidative stress can be related to dopaminergic neurotoxicity, and can cause depression and other neuropsychiatry disorder such as anxiety [93].
\nExposure to air pollutants is one of the most important avoidable risks to health globally [98]. Air pollution has been termed the “silent killer” by the World Health Organization because its effects often go unnoticed or are not easily measured. Although the pulmonary and cardiac diseases have been the most studied adverse health, there are emerging evidence that air pollutants can damage any organ of the body and cause more ill-health. Chronic liver diseases [99], skin diseases [100], bone diseases [101] and autoimmune diseases [102] are increasingly been associated with air pollution. As data continues to increase on health effect of both HAP and AAP which are overlapping and contribute to each other, it is pertinent that all stakeholders; individuals, families, health care professionals, policy makers, governmental and non-governmental institutions work together to minimise the adverse health effects of the world’s biggest environmental risk factor.
\nWe appreciate Almighty God for granting the strength and wisdom to write the manuscript and we are also grateful to Miss Nene Raphael for typesetting this article.
\nAAP | Ambient air pollution |
ALRI | Acute lower respiratory tract infection |
AOR | Adjusted odd ratio |
BMF | Biomass fuel smoke |
HAP | Household air pollution |
CI | Confidence interval |
COPD | Chronic obstructive pulmonary disease |
COVID-19 | Corona virus disease 2019 |
DALYs | Disability-adjusted life years |
DNA | Deoxyribonucleic acid |
FEV1 | Forced expiratory volume in 1 second |
GBD | Global Burden of Disease Study |
OR | Odd ratio |
P | Significance value |
PAHs | Polycyclic aromatic hydrocarbons |
PM2.5\n | Particulate matter with aerodynamic diameter 2.5 μm or less |
PM10\n | Particulate matter with aerodynamic diameter 2.5–10 μm |
PM | Particulate matter |
R2\n | Coefficient of determination |
ROS | Reactive oxygen species |
WHO | World health organisation |
CD | Cluster of differentiation |
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His studies in robotics lead him not only to a PhD degree but also inspired him to co-found and build the International Journal of Advanced Robotic Systems - world's first Open Access journal in the field of robotics.",institutionString:null,institution:{name:"TU Wien",country:{name:"Austria"}}},{id:"441",title:"Ph.D.",name:"Jaekyu",middleName:null,surname:"Park",slug:"jaekyu-park",fullName:"Jaekyu Park",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/441/images/1881_n.jpg",biography:null,institutionString:null,institution:{name:"LG Corporation (South Korea)",country:{name:"Korea, South"}}},{id:"465",title:"Dr.",name:"Christian",middleName:null,surname:"Martens",slug:"christian-martens",fullName:"Christian Martens",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Rheinmetall (Germany)",country:{name:"Germany"}}},{id:"479",title:"Dr.",name:"Valentina",middleName:null,surname:"Colla",slug:"valentina-colla",fullName:"Valentina Colla",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/479/images/358_n.jpg",biography:null,institutionString:null,institution:{name:"Sant'Anna School of Advanced Studies",country:{name:"Italy"}}},{id:"494",title:"PhD",name:"Loris",middleName:null,surname:"Nanni",slug:"loris-nanni",fullName:"Loris Nanni",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/494/images/system/494.jpg",biography:"Loris Nanni received his Master Degree cum laude on June-2002 from the University of Bologna, and the April 26th 2006 he received his Ph.D. in Computer Engineering at DEIS, University of Bologna. On September, 29th 2006 he has won a post PhD fellowship from the university of Bologna (from October 2006 to October 2008), at the competitive examination he was ranked first in the industrial engineering area. He extensively served as referee for several international journals. He is author/coauthor of more than 100 research papers. He has been involved in some projects supported by MURST and European Community. His research interests include pattern recognition, bioinformatics, and biometric systems (fingerprint classification and recognition, signature verification, face recognition).",institutionString:null,institution:null},{id:"496",title:"Dr.",name:"Carlos",middleName:null,surname:"Leon",slug:"carlos-leon",fullName:"Carlos Leon",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Seville",country:{name:"Spain"}}},{id:"512",title:"Dr.",name:"Dayang",middleName:null,surname:"Jawawi",slug:"dayang-jawawi",fullName:"Dayang Jawawi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Technology Malaysia",country:{name:"Malaysia"}}},{id:"528",title:"Dr.",name:"Kresimir",middleName:null,surname:"Delac",slug:"kresimir-delac",fullName:"Kresimir Delac",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/528/images/system/528.jpg",biography:"K. Delac received his B.Sc.E.E. degree in 2003 and is currentlypursuing a Ph.D. degree at the University of Zagreb, Faculty of Electrical Engineering andComputing. His current research interests are digital image analysis, pattern recognition andbiometrics.",institutionString:null,institution:{name:"University of Zagreb",country:{name:"Croatia"}}},{id:"557",title:"Dr.",name:"Andon",middleName:"Venelinov",surname:"Topalov",slug:"andon-topalov",fullName:"Andon Topalov",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/557/images/1927_n.jpg",biography:"Dr. Andon V. Topalov received the MSc degree in Control Engineering from the Faculty of Information Systems, Technologies, and Automation at Moscow State University of Civil Engineering (MGGU) in 1979. He then received his PhD degree in Control Engineering from the Department of Automation and Remote Control at Moscow State Mining University (MGSU), Moscow, in 1984. From 1985 to 1986, he was a Research Fellow in the Research Institute for Electronic Equipment, ZZU AD, Plovdiv, Bulgaria. In 1986, he joined the Department of Control Systems, Technical University of Sofia at the Plovdiv campus, where he is presently a Full Professor. He has held long-term visiting Professor/Scholar positions at various institutions in South Korea, Turkey, Mexico, Greece, Belgium, UK, and Germany. And he has coauthored one book and authored or coauthored more than 80 research papers in conference proceedings and journals. His current research interests are in the fields of intelligent control and robotics.",institutionString:null,institution:{name:"Technical University of Sofia",country:{name:"Bulgaria"}}},{id:"585",title:"Prof.",name:"Munir",middleName:null,surname:"Merdan",slug:"munir-merdan",fullName:"Munir Merdan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/585/images/system/585.jpg",biography:"Munir Merdan received the M.Sc. degree in mechanical engineering from the Technical University of Sarajevo, Bosnia and Herzegovina, in 2001, and the Ph.D. degree in electrical engineering from the Vienna University of Technology, Vienna, Austria, in 2009.Since 2005, he has been at the Automation and Control Institute, Vienna University of Technology, where he is currently a Senior Researcher. His research interests include the application of agent technology for achieving agile control in the manufacturing environment.",institutionString:null,institution:null},{id:"605",title:"Prof",name:"Dil",middleName:null,surname:"Hussain",slug:"dil-hussain",fullName:"Dil Hussain",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/605/images/system/605.jpg",biography:"Dr. Dil Muhammad Akbar Hussain is a professor of Electronics Engineering & Computer Science at the Department of Energy Technology, Aalborg University Denmark. Professor Akbar has a Master degree in Digital Electronics from Govt. College University, Lahore Pakistan and a P-hD degree in Control Engineering from the School of Engineering and Applied Sciences, University of Sussex United Kingdom. Aalborg University has Two Satellite Campuses, one in Copenhagen (Aalborg University Copenhagen) and the other in Esbjerg (Aalborg University Esbjerg).\n· He is a member of prestigious IEEE (Institute of Electrical and Electronics Engineers), and IAENG (International Association of Engineers) organizations. \n· He is the chief Editor of the Journal of Software Engineering.\n· He is the member of the Editorial Board of International Journal of Computer Science and Software Technology (IJCSST) and International Journal of Computer Engineering and Information Technology. \n· He is also the Editor of Communication in Computer and Information Science CCIS-20 by Springer.\n· Reviewer For Many Conferences\nHe is the lead person in making collaboration agreements between Aalborg University and many universities of Pakistan, for which the MOU’s (Memorandum of Understanding) have been signed.\nProfessor Akbar is working in Academia since 1990, he started his career as a Lab demonstrator/TA at the University of Sussex. After finishing his P. hD degree in 1992, he served in the Industry as a Scientific Officer and continued his academic career as a visiting scholar for a number of educational institutions. In 1996 he joined National University of Science & Technology Pakistan (NUST) as an Associate Professor; NUST is one of the top few universities in Pakistan. In 1999 he joined an International Company Lineo Inc, Canada as Manager Compiler Group, where he headed the group for developing Compiler Tool Chain and Porting of Operating Systems for the BLACKfin processor. The processor development was a joint venture by Intel and Analog Devices. In 2002 Lineo Inc., was taken over by another company, so he joined Aalborg University Denmark as an Assistant Professor.\nProfessor Akbar has truly a multi-disciplined career and he continued his legacy and making progress in many areas of his interests both in teaching and research. He has contributed in stochastic estimation of control area especially, in the Multiple Target Tracking and Interactive Multiple Model (IMM) research, Ball & Beam Control Problem, Robotics, Levitation Control. He has contributed in developing Algorithms for Fingerprint Matching, Computer Vision and Face Recognition. He has been supervising Pattern Recognition, Formal Languages and Distributed Processing projects for several years. He has reviewed many books on Management, Computer Science. Currently, he is an active and permanent reviewer for many international conferences and symposia and the program committee member for many international conferences.\nIn teaching he has taught the core computer science subjects like, Digital Design, Real Time Embedded System Programming, Operating Systems, Software Engineering, Data Structures, Databases, Compiler Construction. 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