\r\n\tThe present book intends to provide to the reader a comprehensive overview of the state of art in empathy studies, embracing the different theoretical points of view and illustrating the advanced research such as the application of new technologies to promote perspective-taking. The critical aspects and the future directions of the study on empathy will also be presented.
",isbn:"978-1-80356-612-2",printIsbn:"978-1-80356-611-5",pdfIsbn:"978-1-80356-613-9",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,isSalesforceBook:!1,isNomenclature:!1,hash:"4c1042dfe15aa9cea6019524c4cbff38",bookSignature:"Ph.D. Sara Ventura",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11443.jpg",keywords:"Theoretical Model, Skill, Perspective Taking, Training Programs, Practical Implications, Advanced Research, Future Directions, Virtual Reality, Augmented Reality, New Trends, Assistive Technology",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"April 1st 2022",dateEndSecondStepPublish:"June 8th 2022",dateEndThirdStepPublish:"August 7th 2022",dateEndFourthStepPublish:"October 26th 2022",dateEndFifthStepPublish:"December 25th 2022",dateConfirmationOfParticipation:null,remainingDaysToSecondStep:"a month",secondStepPassed:!0,areRegistrationsClosed:!1,currentStepOfPublishingProcess:3,editedByType:null,kuFlag:!1,biosketch:"Passionate researcher in the application of new technologies to psychological treatments, neuro-rehabilitation, human behavior, and the evolution of the human-computer interaction. In 2017 Dr. Ventura won a competitive grant (Santiago Grisolia) at the University of Valencia at LABPSITEC group, where she was awarded her Ph.D. degree, supervised by Prof. Rosa Baños at the University of Valencia, and co-directed by Prof. Giuseppe Riva of the Catholic University of Milan.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"227763",title:"Ph.D.",name:"Sara",middleName:null,surname:"Ventura",slug:"sara-ventura",fullName:"Sara Ventura",profilePictureURL:"https://mts.intechopen.com/storage/users/227763/images/system/227763.jpg",biography:"Sara Ventura gained a B.Sc in Psychology at the University of Padua (Italy) in 2013 and an M.Sc. in Ergonomic Psychology at the Catholic University of Milan (Italy) in 2015. In 2016, she carried out a postgraduate training at Universidad Nacional Autónoma de Mexico (Mexico) at the Ciberpsychology lab, working on a rehabilitation protocol for people with acquired brain injury through Virtual Reality. In 2020, Sara gained the Ph.D. in Clinical Psychology at University of Valencia (Spain) working with the LabPsitec group and focusing her research on the study of embodiment and empathy with the support of Virtual Reality. Actually, she is working both with Alma Mater Studiorum – University of Bologna (Italy), and the University of Valencia (Spain) on the fields of embodiment, stroke rehabilitation, empathy and patient care. Her research interests mainly focus on the adoption of new technologies, particularly Virtual/Augmented Reality and Artificial Intelligence for the psycho-social wellbeing with clinical and non-clinical populations, the study of human-computer interaction, and the user experience. 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From chapter submission and review, to approval and revision, copyediting and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. I maintain constant and effective communication with authors, editors and reviewers, which allows for a level of personal support that enables contributors to fully commit and concentrate on the chapters they are writing, editing, or reviewing. I assist authors in the preparation of their full chapter submissions and track important deadlines and ensure they are met. I help to coordinate internal processes such as linguistic review, and monitor the technical aspects of the process. As an ASM I am also involved in the acquisition of editors. Whether that be identifying an exceptional author and proposing an editorship collaboration, or contacting researchers who would like the opportunity to work with IntechOpen, I establish and help manage author and editor acquisition and contact."}},relatedBooks:[{type:"book",id:"6494",title:"Behavior Analysis",subtitle:null,isOpenForSubmission:!1,hash:"72a81a7163705b2765f9eb0b21dec70e",slug:"behavior-analysis",bookSignature:"Huei-Tse Hou and Carolyn S. 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1. Introduction
\n
Bioluminescence is rare, but widespread. This seemingly contradictory statement refers to the fact that there is almost no animal phylum that does not have at least a few bioluminescent species, even if the vast majority are non-luminescent. Freshwater contains the smallest number of bioluminescent species; terrestrial environments possess a slightly greater number, but the oceans are inhabited by a wide variety of bioluminescent creatures and the vertebrate class of Pisces represents one of the best examples of this [1]. When one thinks of the evolutionary plasticity of fishes and the fact that most of the ocean is dark, it is not surprising that these animals show a high degree of remarkable luminous features. In fact, fishes present the most diverse and complex examples of bioluminescent adaptations in the world [2].
\n
In an environment where organic light is used for different biological purposes [1, 3], light perception may be a determinant factor for the survival and success of the species involved [4]. The eyes of all animals on the planet are adapted to the light regimes of the habitat they are meant to function in [5] and bioluminescent fishes are no exception. The visual capacities of oceanic fishes are adapted not only to the spectral properties and intensity of downwelling sunlight at depths the fish inhabit, but also to the bioluminescence in their environment [6]. Vision and bioluminescence (at least in fishes) are likely to share a common evolutionary history, which is reflected in the bioluminescent fishes’ ontogeny, behaviour and ecology.
\n
\n
2. Taxonomy of luminous fishes
\n
While preparing this chapter, the authors found records of bioluminescence for around 1500 species of fish, but most likely this number is too low as some records of luminescent species may still be missing. The tally of luminescent fishes represents about 8% of the approximately 20,000 known species [7]. At least 43 families of 11 orders of bony fishes and 3 families of 1 order of sharks are luminous (Table 1). There are families with no luminescent representatives and there are families in which the luminescent species are more abundant than in some other families, which is often a reflection of the habitat that these species inhabit (see next section of this chapter).
R [2], M [46], L [4], S [46], CI [2], I [48], A [46], Sa, Br [4]
\n
\n\n
Table 1.
Bioluminescent families and genera of fishes and respective suggested ecological functions.
aR—recognition; M—mate; L—lure; S—school; CI—counterillumination; I—illumination; A—aposematism; Br—blink and run; Sa—startle predators; Ss—smokescreen; ?—unreported functions in the references.
bRatio, the number of the genera containing luminous species/the total number of the genera in the family; All, all the species are luminous.
cEtmopterids also seem to use its photophore patterns to coordinate hunting in schools [8].
dBioluminescence in Haplomacrurus is only stated by Herring [23] and no other references found to contradict or agree with this information. The taxonomy used in this table is in accordance with the WoRMS Editorial Board, 2016 [7]. The taxonomic data used in this table are included and available online in the website of the Living Light List Project (http://www3.chubu.ac.jp/faculty/oba_yuichi/Living%20Light%20List/).
\n
In cartilaginous fishes, bioluminescence is not as common as in bony fishes. Only three families of luminous sharks are known, Dalatiidae, Etmopteridae and Somniosidae [8, 9]. Luminescence in rays and skates as well as in Holocephali seems non-existent or has not been confirmed. In the luminescent sharks, numerous small light organs are predominantly present in the ventral region of the body, but lower densities can even reach the dorsal areas in dalatiid species [10]. Luminous sharks, like the majority of fish species, possess external light organs with intrinsic light production, which are denominated as photophores [8, 11].
\n
In bony fishes, bioluminescence reaches its zenith in terms of complexity and diversity of light organs and their corresponding biological and ecological functions. It is common to find whole families of bioluminescent species, such as the Myctophidae [11], Leiognathidae, Anomalopidae [12], Platytroctidae [13] and several families of anglerfishes [14]. In such cases, the patterns or shapes of the light organs are generally species-specific and can even be used for taxonomic purposes. Nevertheless, the most common scenario is that only some genera of fishes are bioluminescent as, for example, in families of the order Perciformes with very few luminescent species or in Macrouridae with considerably more luminescent species [2]. An uncommon scenario is when there is only a single luminous species known in an entire order as is the case with Coilia dussumieri in the Clupeiformes [15] and Lumiconger arafura in the order Anguilliformes [16, 17]. Equally uncommon is it to find only one luminescent species within a family as for the merluciid Steindachneria argentea [2] and the ogcocephalid Dibranchus atlanticus [17]. On the other hand, we have the order Stomiiformes, in which all of its species produce their own light [1].
\n
Generally speaking, the origin of the light emissions do not vary much within families, being either bacterial or intrinsic. Exceptions exist in the Apogonidae where only Siphamia species are known to have bacterial symbionts whereas the remainder of the luminescent species employ intrinsic bioluminescence with Cypridina luciferin [18]. A rare case is observed in anglerfishes of the families Lynophrinidae and Centrophrynidae which have an intrinsic bioluminescent barbel in addition to the symbiotic luminous lure of the first ray of the dorsal fin that projects from the dorsum of the anglerfishes and is known as the esca [14]. The location of the light organs is also generally similar within a family, but exceptions exist, namely in families where all the species are luminous. In Myctophidae, for example, only members of the genus Diaphus have head photophores and unlike fishes of some other genera do not possess caudal glands. Another example is that of luminous barbels, present in some species of Stomiidae [15]. Indirect bioluminescence is produced by internal luminous organs that depend on transparent tissues underneath to emit diffuse light from the ventral part of the body. Although this method is more common in the shallow-water species like those of the families Leiognathidae and Apogonidae [19], it can also be found in some fishes of greater depths as from the families of Opisthoproctidae [12] and Evermannellidae [2].
\n
2.1. Dubious species
\n
Misidentifications, confusion of non-luminous tissues and luminous bacteria on damaged specimens [20] are common sources of errors that led to reports of the luminous species, which do not exist or are not luminescent at all. Furthermore, unusual phylogenetic and habitat placements in records for certain species claimed to be luminous, apparently backed up with dubious references, are suspicious vis-à-vis the phylogeny and habitat preferences of the accepted luminous species and therefore cast doubt on the validity of some records. Another problematic issue are contradictory statements, when some authors report a species to be luminescent and others contradict such statements. As the authors of this chapter did not have the chance to observe and confirm the status of luminosity of all the species mentioned, they decided to be neutral and include in the chapter cases that could be dubious.
\n
The batoid Benthobatis moresbyi [20] is one of the most doubtful cases of bioluminescence reported in fishes. Sharks of the genus Somniosus were erroneously categorized as bioluminescent [2]. The megamouth shark possesses reflective tissue along its upper jaw, which can be used to attract its prey through reflecting the bioluminescence of other animals [1].
\n
In bony fishes, reports of luminescent members of opisthoproctids, Dolichopteryx, Bathylychnops and Bathylagus have been shown to be erroneous [2]. Some trachichthyid genera like Hoplostethus [21] and Sorosichthys [22] may have luminous members, but there is no convincing proof of their bioluminescence. In macrourids, the genera Coryphaenoides, Mesobius, Pseudocetonurus, Macrourus and Idiolophorhynchus andriashevi are stated as luminous by some, but not all investigators [21, 23, 24]. Antimora is another uncertain case among otherwise luminescent morids [2, 23].
\n
Apart from the well-known anglerfishes, two unrelated species of shallower water lophiiformes, Antennarius hispidus and Chaunax [20, 25] are described as luminous based on a single reference. There are also some species of ogcocephalids, which have dubiously been reported as luminous [21, 23]. Bioluminescence in cetomimids has been stated by reference [21], but other authors disagree [26]. Reference [21] consider luminescence in the species of the families Halosauridae and Brotulidae and the gempylidae genus Ruvettus as dubious. The uncertainty of bioluminescence in Kasidoron and Bathylagus has been discussed [2] and possible luminescence in Derichthys serpentines has been muted [27] but definitive proof is lacking. The silaginid Sillago bassensis was found with bioluminescent bacteria [28] probably attached to its skin; this might also have been the explanation for the dorsal luminescence of a flying fish reported in Japan [29].
\n
\n
\n
3. Habitat dispersal of luminous fishes
\n
Light penetrates the sea and is then subjected to scattering by air bubbles and water molecules [3], phytoplankton and zooplankton as well as suspended particles [30]. This essentially imposes limits on the use of vision in the aquatic environment [31]. Major light attenuation occurs in the epipelagic zone where the planktonic biomass, dissolved nutrients and floating debris ‘filter’ most of the light, reducing its intensity and altering its spectral composition. However, the angle of this light is almost completely vertical apart from very near the surface [32]. Not many bioluminescent fishes inhabit the epipelagic zone (Figure 1) and in those that are present, photoreceptive structures and visually induced behaviours seem less complex than that encountered in species inhabiting deeper habitats [33]. This seems likely to be related to two main factors. Primarily, at these shallow depths light intensities, especially during the day, are too high for luminescence [4, 31] to be useful for ecological purposes without investing a considerable energy [32]. Secondly, if a very strong light were to be produced, it would readily be spotted by keen eyes of the abundant photopic predators around [32, 33]. The bioluminescent epipelagic species are mainly active at night [34] and use internal counterillumination to deter and avoid dusk-active piscivorous predators [19, 33]. Some exceptions are the headlights of anomalopid and monocentrid species [12, 35] and fishes with photophores, like the batrachoidid Porichthys.
Figure 1.
Schematic representation of the spatial distribution of bioluminescent fish families and some ecological details.a Lophiiformes families other than Thaumatichthyidae, Linophrynidae, Caulophrynidae and Ogcocephalidae. The data presented only refer to species that are known as bioluminescent. The order of disposition within the coastal, coastal-oceanic and oceanic categories is ecological and not spatial. References used for spatial distribution and diel vertical migrations [10, 13, 15, 26, 40, 65, 79, 95–99] and for bioluminescence [2, 9, 16, 21, 24, 47, 48, 50, 58, 60, 67, 100].
\n
Only dim light from the short wavelength spectra of the blue–green component of sunlight (but no moonlight) reaches the mesopelagic zone [30]. In contrast to the epipelagic zone, the mesopelagic zone is characterized by a uniformity of light in all lateral directions and the highest intensity from above [4, 30]. This is the oceanic ‘bioluminescent hotspot’ where more than 80% of the species present are bioluminescent [32, 36] and biological light reaches its greatest splendour in diversity and complexity of structures and purposes [37]. In terms of fish biomass, it is the mesopelagic zone that stands out [38]. Myctophids are one of the families of teleosts with a very high number of species, representing the second most abundant taxon of mesopelagic fishes. In terms of sheer numbers, the gonostomatid genera Vinciguerria and Cyclothone represent the most abundant fauna on the planet [11]. The mesopelagic zone is also the transference zone from an extended origin of light to a point source. The downwelling sunlight is the primary source of light in the upper mesopelagic zone (200–610 m depth) while bioluminescence takes over as the main source of light in the lower mesopelagic zone (610–1000 m depth). Under the essentially monochromatic scotopic light, the use of bioluminescence is far more advantageous for camouflage and vision, be it in the case of predators or prey, than at depths more brightly illuminated by a fuller spectrum of light. In the depths where silhouette distinction is of visual importance and it comes as no surprise that most of the bioluminescent fish species inhabit this realm. The colorations of the fish at greater depths are a reflection of the different light environment. In the upper mesopelagic silver bodies acting as mirrors and assisting in camouflaging are common [30]. The animals inhabiting the lower mesopelagic and bathypelagic tend to have darker bodies, preventing reflections of bioluminescence in these deeper realms [4, 21].
\n
At 1000 m depth, sunlight is no longer strong enough to allow fishes to see in and that depth by definition corresponds to the beginning of the bathypelagic zone [30]. The latter is the aphotic zone where no sunlight is available [30] and complete homogeneity in terms of the light environment occurs in all directions [4, 31]. Here, light from above does not possess much relevance for the impoverished faunal assemblages present and the only source of photic stimulation, in contrast to that of the mesopelagic zone, is bioluminescence [3, 30]. Consequently, there is a drop in the number of bioluminescent species and individuals from that in the mesopelagic zone [2]. Even deeper living abyssal fishes, phylogenetically related to bathypelagic or mesopelagic luminous species, are not bioluminescent (e.g. macrourids) [4, 12].
\n
It is not surprising that the majority of all bioluminescent fishes are oceanic and pelagic [33], as there are no structures blocking the path of the light in this environment, it seems to be optimal for the realization of many of the roles bioluminescence can ultimately be involved in [30, 37]. On the other hand, some benthopelagic species that are not known as vertical migrators possess ventral luminescence (e.g. morid species). These are puzzling cases of bioluminescence and its possible role [2], because emitting ventral light close to the bottom does not fulfil the purpose of camouflage. In fact, it may cause a reflection by the substrate and expose the fish [21]; however, there may be advantages too, which have not been looked into like, for instance, diverting attention and misguiding potential predators to the reflection rather than its originator. Coastal and benthic fishes more often employ bacterial luminescence while the pelagic species possess mostly intrinsic bioluminescence [2, 33, 39].
\n
Diel vertical migrations are common among mesopelagic fishes [40] but are also known from some species of epipelagic [4, 41] and bathypelagic fish [4, 21]. These migrations do not always involve all taxa present [15] or genders in the same population and may vary geographically and seasonally. Generally speaking, the diel vertical migrant approaches surface waters at night to feed on zooplankton or other migrants when diurnally hunting visual predators are less active. The vertical movements of these individuals provide an important source of carbon (and other nutrients) to the deeper layers of the ocean [4].
\n
\n
4. Bioluminescence purposes in fishes
\n
4.1. Light organs and control
\n
Despite the extensive diversity of luminous organs in fishes, the basic structure is rather uniform [37] irrespective of whether we deal with photocytes or bacterial symbionts (Figure 2). The photogenic mass is situated at the centre and is associated with an external lens. An internal reflector is enclosed by a pigmented layer. Innervation of blood capillaries is also a common feature [2, 37]. Bacterial light organs usually possess an opening to exterior allowing the release of excess bacterial cells to the environment [42]. Photophores, with the exception of those in neoscopelids, are closed [2, 4].
\n
The majority of the bioluminescent fishes have luminous tissues capable of generating light by themselves, but others maintain a culture of luminous symbiotic bacteria in their light organs [4, 39, 43]. The light organs of the species with symbiotic bacteria possess ducts in which they culture extracellular luminous bacteria [39]. In most cases, these bacteria are species like Photobacterium, but Aliivibrio fischeri and possibly Vibrio harveyi can also be found as symbionts in light organs of some luminous fishes [42]. Intrinsically luminescent fish possess photocytes with Cypridina luciferin and coelenterazine. Cypridina luciferin is only used by coastal fishes of the families Batrachoididae, Pempheridae and Apogonidae while coelenterazine has been suggested to occur in Stomiiformes, Myctophiformes and Platytroctidae [44]. The remainder of intrinsically bioluminescent fishes may belong to coelenterazine or unknown luciferin types.
\n
A pigmented layer of cells surrounds the light organs internally to absorb stray light [2]. Below the light organ, there usually is a layer of cells with a reflecting material that redirects the light towards the lens [45]. Some species lack reflectors [20, 21], and in others, the reflectors may not be present in all types of luminous tissues, as stomiids [46]. In fishes with indirect bioluminescence, the reflector is located above the ventral diffusive tissues (see Figure 3) instead of being inside the light organ [47]. Reflectors affect the emission spectra in some fishes, as in alepocephalids, and myctophids that lack pigmented lenses in front of the light organ [48, 49]. When the light produced by the photogenic chamber is emitted to the outside of the photophores, it passes through the lens [45], whose pigments filter the emitted light and adjust its spectrum to match that of the downwelling light [3, 48]. Some fishes like the monocentrids lack lenses. In the case of Cleidopus gloriamaris, a red-orange skin tissue external to the light organ alters the spectrum of the light emission [12].
\n
Figure 2.
Schematic representation of the general structure of light organs in fishes. External side with light emission and internal side with blood capillaries and nerve supply. Matrix represents the space between the photogenic chamber and other structures. The right half of the photogenic chamber represents an intrinsic light organ with photocytes. The left half of the photogenic chamber represents a symbiotic light organ with transverse section of tubules filled with luminous bacteria.
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Fishes with luminous symbiotic bacteria emit light continuously, but may have some control over the light by chromatophores [34] and nutrient supply to the bacteria [34, 43, 45]. Shutters are tissue patches with chromatophores that can partially or totally cover the light organs and are under muscular control [41, 50]. These shutters are different across genera of the same family and may occlude internal organs as in leiognathids and Siphamia or may be restricted to external organs as in anomalopids [41, 50, 51]. It is suggested that anglerfishes possess a similar mechanism to control the light emission from the escae [41]. Skin chromophores can be used to control light emissions in bioluminescent fishes with internal bacterial symbiotic organs (leiognathids [50], pempherids [47], acropomatids [19], evermannelids [2]) or externally (Gadiformes [52], Trachichtidae [12]), and bacterial symbionts in the lower jaw organs as in monocentrids [34]. There are some exceptions like Opisthoproctus, which may regulate light with ventral scale movements [2] and thaumatichthyids [41] and Cleidopus gloriamaris [12] that have light organs inside the mouth closing it to block the light emission. Leiognathids use branchiostegals to control their light emissions [53], and according to the observations of one of the authors (Yuichi Oba), the pigmented pelvic fins of Chlorophthalmus may serve the same purpose. The regulation of bacterial luciferase by oxygen and ion supply from the blood has been stated as a possibility, but there are no clear conclusions on this [39]. Observations by Meyer-Rochow [43] on Anomalops katoptron have shown that their bacterial light organs become successively dimmer when the fish starves.
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Figure 3.
Light organs in fishes per family. Intrinsic bioluminescence in blue and symbiotic in green. The light organs are represented in coloured bands or circles delimited by a black outline. Blur coloured forms represent internal bioluminescence through diffusive tissues. aUsed in cases that bioluminescent emissions and organs are very similar between families of the same order.b Crane [101] also found luminescence in skin samples of the ventral surface of the fish. Images are representative for the families and are not on scale. Same references used for bioluminescence in Figure 1 plus [10, 13, 15, 95]. Source of drawings: Food and Agriculture Organization of the United Nations [15, 26, 96, 102–105]. Reproduced with permission.
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Neural light emission control of intrinsic bioluminescence occurs in sharks [54], Stomiiformes [46, 55], myctophids, Porichthys [55] as well as alepocephalids [49] and proceeds through neurons in scopelarchids [56] and other coastal fishes besides Porichthys [33]. Neurons may be able to individually regulate light outputs of single photophores as in myctophids [55]. However, blood supply has also been suggested to be involved, at least in the control of the linophrynid’s intrinsically luminous barbels [41].
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Exceptions are platytroctids, which excrete luminous liquids; a process that invokes muscular control [2, 41]. In some anglerfishes, the liquid may not actually be secreted by the Escae, but from small symbiotic luminous bulbs (the so-called caruncles) that in the family Ceratiidae are dorso-posteriorly positioned from the escae [14].
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Luminous organs are predominantly ventral [21, 37] (Figure 3) but some light tissues can be dorsal, as in the escae of anglerfishes and photophores in dalatiid sharks. Some fishes have buccal light organs like in the apogonids Siphamia spp. [18], the myctophid genus Neoscopelus [20] and thaumatichthyids and Cleidopus. Light organs are present in or on the heads of some fish especially deep-sea species like alepocephalids [57], platytroctids [13], myctophids, stomiids, and the chiasmodontid Pseudoscopelus [58], but also the shallow-water anomalopids and monocentrids [12]. Apart from these organs, there are other types of luminous tissues in fishes. Besides the ‘normal’ photophores, i.e. primary photophores, some species also possess secondary photophores that are smaller and of less complex structure [57]. These small photophores are then, rarely with some degree of preference, distributed all over the body of the fish, cf. platytroctids, alepocephalids, myctophids and stomiids [13, 15, 57]. Myctophids possess caudal glands that usually present sexual dimorphism [2] and glandular light organs can also be found in the Stomiiformes [2, 46] and dalatiid species [8]. Luminous tissue with a similar structure to photophores can be found in the body of myctophids [2] and stomiids [46] and barbels, while luminous mucus clinging to teeth was seen in some stomiids [20] and anglerfishes [2]. Some studies suggest the existence of bioluminescent skin in Himantolophus azurlucens and Cryptopsaras couesii [41].
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The intensity of light emission in fishes can vary individually depending on the type of organ, depth and function (see further). Nevertheless, it seems that intensity is higher in coastal and shallow rather than mesopelagic, deep water species. Light spectra of the emitted lights usually peak in the blue-green, but are to some extent variable mostly in relation to depth. Coastal and epipelagic fishes produce light principally in the green and meso- and bathypelagic in the blue [3, 4, 33]. A rare case is the red light emission of some stomiids. Regarding angular distribution, bioluminescence starts to exceed downwelling light in the lower mesopelagic zone. At that depth, luminescence signals change from a ventral direction to a point-light scenario with bioluminescence emitted in all directions. The angle of the light emitted by an individual depends on the position of the light organ and its reflector in the body of the fish [2, 48], on the kind of transmission tissue involved and the body position of the light-emitting fish in the water column [37, 50]. Some shallow-water fishes like anomalopids and leiognathids can control the angle of the emitted lights [41, 50]. The light emitted also depends on the trophic level and nutritive state of the fish [43] and whether the light-emitting individual is looking at a conspecific side by side in a school, or, for example, prey above or a predator below.
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4.2. Functions of light organs and likely roles of the emitted lights
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A bioluminescent signal is defined by its intensity, spectral peak(s), temporal and spatial characteristics [3]. To what extent the degree of polarization, if any, plays a role has never been examined. The same luminous tissue may serve multiple kinds of functions, and the locations of the light organs are generally related to the roles the emitted lights are expected to play. The light generated can be used by a fish to communicate with its congeners, attract prey or avoid and startle predators. The range of functions of biological light is less complex in the coastal species than that in the deep water species, but even in the former, the emitted light has a variety of different biological roles.
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4.2.1. Intraspecific communication
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Fishes use light signals for intraspecific recognition, schooling and mating. Some fishes possess species-specific structures that purely on account of their placement and position may also assist specific recognition, as the photophore patterns in myctophids apparently do [59]. As aggregations of bioluminescent fishes help confusing predators, light emission may also assist school-forming species of etmopterids [10, 54], chlorophthalmids and macrourids [60].
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A role in reproduction seems to be the part of the bioluminescence repertoire of at least some luminescent fishes including leiognathids, with their complex system of controlled light emission, and stomids [2, 3]. Light organs are sexually dimorphic in some species of Gazza, Secutor and Leiognathus, and courtship behaviours using light signals have been observed in these fishes [61].
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4.2.2. Interspecific communication
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Some fishes use luminous organs located in or on the head to illuminate their surroundings, in search of prey and to detect predators. The bright headlights of anomalopids illuminate their surroundings, help them to avoid predators [62] and allow them to spot zooplankton [35]. Luminescence may be used for illumination in alepocephalids and macrourids in search of prey on the seafloor [30].
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Many fish seem to attract their prey with bioluminescent lures. The escae of anglerfishes have been suggested to mimic faecal pellets with luminous bacteria [32]. Monocentrids have been assumed to attract prey with their light organs [53], but the cephalic photophores of Diaphus may be used to stun preys with bright flashes [1]. Malacosteus niger has small greenish light-emitting spots near its mouth and larger red light-emitting patches below its eyes. It is believed that the small greenish lights attract prey and the red light, invisible to most deep water organisms, is used by the fish to visually detect the approach of the unsuspecting prey in order to seize it when sufficiently close [2, 30, 48, 63].
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Bioluminescent fishes can also use their lights in various ways to distract predators and avoid to be seen by them. Counterillumination is widespread and particularly common in the mesopelagic species, which emit light ventrally to match the downwelling light from above. In that way these often strongly laterally compressed species become camouflaged and almost invisible as silhouettes to the eyes of a predator below [37, 50]. This notion of the use of bioluminescence is strongly supported by biological and ecological facts. Photophores tend to be larger in the species of mesopelagic fishes occurring at shallower depths [2, 4], but the intensity of the ventral light emission from some fishes may change according to the light they find themselves in as from leiognathids [50] and myctophids [64]. Extraocular photophores in Stomiiformes, myctophids [2] and sharks [65] are located in optimal positions for comparisons of the downwelling sunlight with their own light in order to adjust it, a scenario that has also been suggested for apogonids [51]. Counterillumination appears to be of importance to the vast majority of luminous shallow water [33, 35] and mesopelagic teleosts [4, 21, 57] and sharks [66]. Whether the control of the matching luminescence involves eyes and ocular feedback or whether the light organs and cells within them are able to independently and directly regulate photic output of the light organ are questions yet to be answered.
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Aposematism is a likely reason for the bioluminescent dorsal spines in etmopterids [67]. Aposematism is one of the proposed functions for bioluminescence in Porichthys as these species possess venomous dorsal spines [2]. When a possible predator is close by and ready to attack, other methods have to be used for luminous fishes to escape. One possible strategy for prey to evade a predator’s attack is to emit a brief and blindingly bright flash of light right before changing its swimming direction. This has been suggested for the post-orbital photophores of anomalopids [62] and stomiids [4]. As most of the predators of these fishes have eyes adapted to dim light, very bright flashes may have a temporary effect of rendering them incapable of vision [32, 33]. In addition to the species already mentioned, this survival strategy also seems to be employed in cases of the brief and bright flashes of leiognathids [53], the cephalic photophores in Diaphus [1] and the caudal organs of various myctophids [2]. A very similar defence has been proposed in cases in which a bioluminescent liquid is secreted into the water, acting as a luminous smokescreen and confusing the predator while the prey escapes [4]. Luminous liquids or mucoid secretions are produced in the ‘shoulder organ’ of platytroctids [57], the gill slits of the epigonid Florenciella [2], the anal gland of the macrourid Malacocephalus [21] and the escae and caruncles of some anglerfishes [21, 41].
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4.2.3. Unreported functions
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For the bioluminescence in several families of fish, no particular reason for the biological light is known (Table 1). Nevertheless, most of these unreported cases deserve some attention. As for the majority of other pelagic species, counterillumination is probably the most important function in Somniosidae, Evermannelidae, Microstomatidae, Phosichthyidae, Epigonidae and Howellidae as well as in some other families of the same order. Eurypharyngidae may use their luminescence as a lure to attract food items as with members of Saccopharyngidae. The fact that bioluminescence characteristics exhibit considerable similarities within the families of the order Gadiformes may be used as evidence that functions suggested for Macrouridae can apply equally to Moridae and Merlucciidae.
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5. Vision in bioluminescent fishes
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Figure 4.
Schematic representations of the eye structure in fishes. (A) Camera-eye representing light entering the eye (1) and refracted by the lens focused on the retina (2). (B) Front-view of a left tubular eye in the head of a fish. (C) Basic retinal structure by cell layers.
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Light enters the eye through the cornea (Figure 4), passes the pupil and is refracted by the lens and focussed on the retina. Photons are absorbed by pigments in the photoreceptor cells, transformed into synaptic signals, the latter being transmitted through interneurons to the retinal ganglion cells [30, 68, 69]. The axons of these cells are grouped together and form the optic nerve which passes the visual information to the optic areas in the brain [70]. The basic structure of the eye in fish conforms to that of other vertebrates, but there are features that differ, depending on the life style of the fish involved (predator or prey) and on the photic environment [3], i.e. essentially the epipelagic and mesopelagic zones, in which the fish eyes are supposed to operate [30]. The most obvious differences in the structure and function of the fish eye accompany differences in the light intensities prevailing along the depth gradient of the oceanic zones. The majority of the bioluminescent species inhabit deeper waters and their vision is adapted to dim light conditions [30]. The luminescent crepuscular or nocturnal epipelagic fishes [33, 34, 39] have photoreceptors that, too, are mainly adapted to function under low light conditions [68, 70, 71].
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5.1. Eye (structure, size and position)
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There are no bioluminescent fishes with degenerated eyes and all possess binocular vision [3]. Epipelagic [4, 33] and mesopelagic fishes [30] inhabit environments that can be reached by sunlight and they usually possess large laterally positioned eyes. In contrast, the aphotic bathypelagic species often have smaller eyes [4, 30]. The majority of the bioluminescent fishes have typical single lens, camera-type eyes, but some mesopelagic fishes possess tubular eyes. The latter are cylindrical eyes located at the top of the head and on account of their position allow the fish to distinguish silhouettes against downwelling sunlight. In these eyes, their binocular overlap provides high quantum capture, and accessory retinae and additional visual structures allow them to also detect a certain amount of light coming from lateral and ventral regions [68].
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5.2. Lens, pupils and gaps
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Fish lenses present little spherical aberration and a gradient of refractive index with the highest value in the centre guarantees that the focus of the light is sharp [4]. Lens transparency helps sensitivity [3], but lens pigments may influence the colour of the light reaching the retina [36]. Large pupils corresponding to wide apertures allow the admission of more photons, increasing visual sensitivity [30]. Aphakic gaps can enhance sensitivity by allowing light capture from specific oblique areas of the visual field [3, 4]. Such gaps are more commonly rostrally placed and extend binocular frontal vision in the lateral eyes. Light passing through gaps may get focussed in specialized retinal areas [30, 31, 72].
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5.3. Tapeta
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Animals that live in dim environments often possess tapeta lucida, which consist of a reflective layer positioned behind the photoreceptors acting as a mirror [30, 71]. This layer reflects the photons that are not captured by the photoreceptors, sending them back to the photoreceptors [68] and doubling quantum capture success; thus improving the sensitivity of the eye [31]. The spectral reflection peak of the tapetal regions in some fish species is thought to coincide with the absorption peaks of the visual pigments in the photoreceptors of the fish, but in some cases specific tapetal areas reflect spectrally different light thereby fulfilling specific visual tasks [36, 72].
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5.4. Retina
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Photoreceptor cells are responsible for the perception of light and their anatomical and ultrastructural make up, organization, dimensions, density, and distribution, and visual pigment is what has to match the behavioural visual tasks required of them by their owners in the specific photic habitats [69]. Like other vertebrates, fishes have two anatomically distinguishable types of photoreceptors. Cones, of which physiologically different two, three or more kinds with non-identical peak spectral sensitivities may be present, perceive different colours under conditions of bright light. Contrary to cones, rods are monochromatic photoreceptors, but provide the fish with high sensitive vision under low levels of light [36]. Cones occur in some bioluminescent fishes but are often reduced in total number and/or size even in the shallow-water species [60, 68, 70, 71, 73, 74]. Deep-sea fishes have mostly pure rod retinas of high cell density, for there is little need for them to be able to distinguish colours. For them the priority is to possess high sensitivity in a blue-light dominated nearly monochromatic dim, almost dark environment. High sensitivity of the rods is achieved by longer and wider cells. Sensitivity is also enhanced when rods are arranged in groups or are arranged in multi-layers called banks [30].
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The differences in function between rods and cones are due to different kinds of photopigments in the visual cells. Rods possess either rhodopsin, a visual pigment with maximum absorbance at short wavelength (chemically a retinaldehyde, retinal 1 or vitamin A1-based compound) or porphyropsin (i.e. chemically a 3,4-dehydroretinal, retinal 2 or vitamin A2-based compound) [36]. Deep-sea fishes usually have high concentrations of rhodopsin giving the fish broad sensitivity to blue-green wavelengths [69]. However, some deep-sea fish have rod types containing different wavelength-sensitive rhodopsins or in addition may also have porphyropsins, the latter with longer-wavelength peak absorbances. The variety of receptor types and the development of banked retinas to increase absolute sensitivity can provide deep-water fish with the potential to make use of a wide range of photic stimuli [36, 75].
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The density of retinal ganglion cells and, in particular, the ratios between receptors to ganglion cells define visual acuity and sensitivity. A high ratio of rods to retinal ganglion cells is indicative of high absolute sensitivity, while a low ratio would favour acuity. Most of the deep-water fishes possess unspecialized retinae and retinal cell ratios typical of sensitivity improvement [30, 31]. However, even so slight regional enhancements of acuity may be found in some species [68, 76].
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Retinal specializations are regions of concentric increases in visual cell densities that enhance the visual sensitivity (rods) or acuity (retinal ganglion cells). These specializations seem to be related to visual behavioural tasks [72, 76]. In bioluminescent fishes, areae centralis and foveas can usually be identified as areas with higher visual acuity than the rest of the retina [30, 68], but it is possible that such specialized retinal regions change during the lifetime of a fish [77].
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6. Evolution of bioluminescence and vision
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The eyes of bioluminescent fishes evolved as adaptations to a dim light environment, in which bioluminescence provided important visual stimuli to perceive predators, prey items and mates. The fact that the bioluminescence in these species shares optical properties with the light pervading the environment the fish inhabit indicates the role selective pressures must have played [4]. Nevertheless, one cannot discount the idea that light emission and reception together represent a mutual and progressive adaptation [3].
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In fishes, the adaptation of rhodopsin pigments to dim-light vision occurred in 12 separate occasions, suggesting that dim-light vision was a subject to considerable adaptive evolution [5]. In deep-sea fishes, these pigments were already shifted and adapted to the same visual environment as today in the Early Triassic. This shift was an adaptation to maximize the quantum capture of the dim sunlight and the biologically generated light in the deeper water of the sea. Along the way, convergent evolution seemed to have occurred with regard to rhodopsins of deep-sea fishes for adaptation to specific light regimes. This would explain the variation of wavelength sensitivities in these fishes, some adapted to specific bioluminescence peaks [75, 78]. Diversity in the pigmentation of the lenses of deep-water fishes suggests that it too has been the subject of separate evolutionary events a number of times [36]. Much later than vision, and assumed to have happened from the Early Cretaceous to the Late Cenozoic, bioluminescence appears to have evolved in teleosts [17]. A total of 27 independent occurrences are regarded to have left representatives in the marine teleosts assemblage, appearing first in the Stomiiformes [17]. Bioluminescence in the three closely related families containing luminescent species of sharks is also thought to have evolved from a common ancestor during the Cretaceous [9, 10, 17]. Bioluminescent patterns could have contributed to speciation in fishes [9, 11].
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6.1. Bioluminescence evolution
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An exposure to different light regimes powerfully influences the type of bioluminescence characteristics in the species of different habitats. This can express itself through different spectral emission peaks and intensities of the biologically generated lights matching the photic environment of a species’ habitat. The angle and direction of the emitted light are also subject to evolutionary pressures as most of luminescence glows ventrally in epipelagic and mesopelagic zones [2, 21, 33], where traces of sunlight from above are still discernible. No light from above, on the other hand, reaches the bathypelagic zone where the bioluminescent species exhibit a reduction in the number and sizes of photophores [2]. A good example of this tendency is the bathypelagic myctophids of the genus Taaningichthys, in which only the deepest living species, T. paurolychnus [79], lacks photophores (but still possesses caudal glands) [15].
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6.1.1. Functions
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Bioluminescence plays major roles in the ecology of the luminescent fish species. The evolutionary history of bioluminescence in fishes shows that the ability to generate light arose dozens of times in unrelated clades [17] and yet, the basic structure of the light organs is nearly the same in all cases, independent of substrate, position and functions of the organ [20, 37]: counterillumination seems an excellent example. Fishes developed different ways to hide their silhouette from predators, using their ventral light emission. Some species make use of rows of photophores for that purpose, whereas others use indirect luminescence, but each case arose repeatedly and independently during evolution [17, 21].
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An example of different structures employed in counterillumination can be seen in shallow-water species. In that environment, all the fishes use an indirect form of bioluminescence for camouflage with the exception of Porichthys, sciaenids and C. dussumieri that have photophores for that purpose [2, 33]. Different photogenic origins (i.e. symbiotic and intrinsic) may have led to the evolution of counterillumination, and some excellent examples are those that involve indirect bioluminescence. Some shallow (e.g. pempherids) and deep-water (e.g. Cocorella atrata) fishes use intrinsic light organs for indirect ventral bioluminescence, but the majority of species with this kind of light emission are employing symbiotic bacteria [2, 19, 39]. This divergence of photogenic origins can also be observed within apogonids [2]. Ventral luminescence in diel vertical migrants must also have come under selective pressures to conceal the silhouettes of the migrants from predators, when ascending into shallower and more illuminated waters [21, 37]. It is also conceivable that light signals in interspecific schools of diel vertical migrants play a role in keeping individuals together [3]. Although we focussed on counterillumination, there are other less well studied examples of structures of photogenic as well as non-photogenic origins serving identical functions in bioluminescent fishes. What immediately comes to mind are the symbiotic lures in anomalopids [53] and ceratiids [14] and the intrinsic barbels of stomiids [4] and photophores in sharks [8].
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6.1.2. Acquisition
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Whether we deal with cases of intrinsic or symbiotic bioluminescence in fishes, the acquisition of the bioluminescence must have appeared at some point in the evolutionary history. It is still not clear how and when this happened, but based on some widely accepted suggestions the process behind it is thought to have involved the higher availability of luminous bacteria in coastal areas as a cause for the widespread use of symbiotic bacteria in the bioluminescence of fishes inhabiting seashore-near habitats [80]. Similar kinds of constraints could have acted upon the Cypridina luciferin containing species of intrinsic luminous fish. These fishes are coastal species [33, 44] and the ostracods, which produce Cypridina luciferin, Vargula and Cypridina are benthic species and seem to inhabit mainly coastal and shallow waters [81–83]. It is well established that fishes like apogonids, pempherids and Porichthys have obtained the Cypridina luciferin from ostracods they ingested [18, 47, 84]. As there are no records that fish can synthesize coelenterazine, dietary acquisition seems a plausible scenario. This suggestion is supported by the widespread occurrence of coelenterazine also in luminous mid-water fishes and the fact that this substance is most abundant in the tissues of the digestive tracts of these fishes [85].
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On the other hand, we have the symbiotic luminous fishes, in which light-producing bacteria are responsible for the bioluminescent capacity of the host. In return, the host provides protection, a place to grow, nutrition and oxygen to the bacteria [42]. This symbiotic relation could have started with facultative luminous bacteria in the gut of fishes (e.g. leiognathids), evolving into the obligatory symbiosis we now witness in anglerfishes and anomalopids [39, 41]. Hosts are ecologically dependent on the bacterial light and ‘host family-bacterial specificity‘ seems to be the trend [42]. However, contrary to what had been believed for decades, nowadays coevolution between facultative symbiont and the host fish species is regarded as an unlikely scenario [41] as different fish host the same bacterial species and different species of bacteria can be co-symbionts of fish species. Moreover, evolutionary divergence in the bacterial species is unrelated to that of the host species [86]. Nevertheless, the absence of non-luminous bacteria in the organs indicates that some selection must have taken place [42] and associations could have arisen (or been bolstered) through environmental factors like the depth that the metamorphosing larvae inhabit. Support for this notion comes from Photobacterium leiognathi and Photobacterium mandapamensis found in organs of fishes that inhabit warmer and shallower waters and Photobacterium kishitanii that is found in deeper and colder waters [39, 42, 86].
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6.2. Visual adaptation to bioluminescence
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Vision in fishes evolved primarily as an adaptation to light intensity changes to extended or point sources in the near and far field of vision and secondarily to species-specific ecological needs [30, 31]. Bioluminescence has, to a large extent, affected the evolution of the optical system in luminescent fishes, which is obvious when one compares the eyes of fishes inhabiting the mesopelagic and bathypelagic realms. In the mesopelagic zone, animals use counterillumination to match the dim background light [36] and under such conditions fish evolved certain adaptations like tubular eyes [68], yellow lenses and retinae with banked receptor cells. In terms of their function, such eyes had to be sensitive, able to distinguish small spectral discrepancies from background light and to detect camouflaged prey [36]. For bathypelagic fishes, on the other hand, the only light sources available to them would have been of bioluminescent origins, restricting the range of their visual adaptational possibilities [31]. The bathypelagic species therefore tend to have larger aphakic gaps than mesopelagic species even within the same genus [3, 68]. As food is scarce at these greater depths, fishes living there evolved less energetically expensive small eyes [4]. Nevertheless, these fishes do possess eyes with visual acuities capable of distinguishing point-source bioluminescence. Moreover, the eyes of the bathypelagic bioluminescent species show overall fewer regressed features than the eyes of the non-luminescent bathypelagic species do, indicating that the former rely more on vision than the latter. There are even some bottom-dwelling deep-sea fishes that have severely degenerated eyes ,which are likely to detect no more than the presence or absence of bioluminescence of perhaps invertebrates in the seabed [31].
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The types of visual pigments [5] and the balance between visual acuity and sensitivity are the results of millennia of selective pressures stemming from the diverse light regimes and visual tasks fishes had to contend with [4]. Visual pigments evolved primarily to light from the sun, perhaps to guide specimens to darker regions and shelters away from the light or to seek illuminated areas, but in deep-sea fishes photopigments seem to be much more attuned to bioluminescence spectra [4, 6, 30, 36]. The eyes of most of the deep-water species have high concentrations of rhodopsin giving them a broad sensitivity to the blue-green range of the spectrum [69], comprising wavelengths that seem ideally suitable for perceiving bioluminescence emissions of prey, predators and conspecifics [6]. Potential colour vision in some deep-sea fishes may be an adaptation to identify species by differences in their bioluminescence hues [69, 75].
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7. Ontogeny of bioluminescence and vision
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7.1. Metamorphosis of eye and luminous tissues
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During larval metamorphosis in fishes, the eyes change in shape, size, structure and even location [27]. The best examples among bioluminescent species are the tubular eyes, which are formed from laterally placed camera-type eyes in the larvae that become tubular in shape and migrate dorsally during metamorphosis. The lens remains unchanged but the retina suffers many alterations [87]. Retinae in larvae of the deep-water species, whether or not luminescent, are poorly specialized and vision, generally, is much less developed than in adults [88]. Almost all fish larvae have pure-cone retinae that are totally or partially substituted by rods during metamorphosis. The only exceptions in bioluminescent fish larvae are Saccopharyngiformes and Lumiconger arafura, in which pure rod retinae are the rule. In retinae with rod multilayers, the number of banks increases throughout development [68, 87, 88].
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Photophores are formed during metamorphosis of a fish [22, 27, 87] and some are then already functional [2]. The luminous organs of symbiotic fishes also develop during larval metamorphosis [39]. This is the case of other luminous tissues too, as for example, the caruncles of ceratiids [41] and the caudal glands of myctophids [27]. Furthermore, the barbels of stomiids seem to arise during metamorphosis [27] and continue to elaborate throughout the fish’s development [4].
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The acquisition of the photogenic substrate in fishes is not well known. The luminous organs of symbiotic fishes start to develop prior to their being colonized by bacteria. Colonization occurs during metamorphosis and it seems that each new generation of fish needs to acquire its symbiont afresh from the environment. The larvae of the shallow-water species are spatially close to adults, which suggests that bacteria may be released from the adult light organ and transferred to the young [39]. This does not seem to apply to the deep-sea species as the larvae are planktonic and hundreds of metres away from the adults. In these cases, it was suggested that larvae are infected when they migrate to coastal areas where luminous bacteria are more abundant [42, 80]. For ceratioids, the secretory cells that are common only in young fish may liberate pheromones to attract the right bacterial symbiotic species [41]. In intrinsic species, maternal transference of Cypridina luciferin was observed in Porichthys [84]. The same mechanism was suggested to apply to other teleosts and etmopterid sharks [89, 90].
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7.2. Ecology and ontogeny: vision and bioluminescence in young fishes
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Most symbiotic and intrinsically bioluminescent fishes have epipelagic larvae that will inhabit mid- or deep-waters as adults [4, 12, 15, 22, 26, 39]. During this ontogenic vertical migration to deeper waters, the visual habitat changes to an increasingly dim and monochromatic light scenario. These changes in the light environment require the modifications of the fish’s photoreceptive as well as luminescent structures (described above) to coincide with the larvae undergoing metamorphosis. The migration to deeper waters and the metamorphic changes previous to the habitat change are believed to be completed in a relatively short time [87]. The development of rods and the changes in photoreceptor arrangements prepare the metamorphosing larvae to a life as a juvenile or adult in an environment where superior visual sensitivity is paramount. The transformations provide the young fish with visual capabilities for recognizing conspecifics, forming schools, engaging in predation and tracking and evading predator advances. In multi-layered retinae, a greater development of banks appears to coincide with the greater depths juvenile fish seek to spend their lives in as adults. In shark species, a metamorphosis similar to that seen in teleost is not present and the ontogenesis of photogenic organs or eyes in bioluminescent sharks has not been studied in much detail [68, 87].
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In teleosts, the development of luminous organs is also affected by the changes in the photic environment and the behaviour of the young fishes. In some Stomiiformes and myctophids, the early development of cephalic photophores suggests that they are used to lure crustacean prey at night [22]. The more common scenario is that in the species whose larvae occur in dimly illuminated waters, photophores develop on the body first [2, 22, 91] and then gradually become functional as the migration to deeper water proceeds [22]. Larvae tend to develop photophores earlier in the species that inhabit deeper water as adults. For juveniles, light emission changes during growth and maturation [22]; ventral luminescence develops rapidly during that phase of the life of many teleosts [2, 4, 12, 52]. Ventral photophores also appear to be more developed in juvenile etmopterid sharks that inhabit shallower depths than the adults [8]. Considered together, these observations highlight the importance of counterillumination in young fishes while they migrate to deeper waters [2, 22].
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Not only do photophores and light organs change in relation to a fish’s developmental stage, the role or roles bioluminescence is to play in the life of a fish may also change with age. This has been suggested for etmopterid sharks as ventral patterns of photophores used for mating and schooling are more developed in adults [8, 92]. Photophores of young platytroctids are horizontally placed on the body and are probably used to illuminate prey, while distracting predators. These photophores, however, do acquire more vertical positions as the ontogenic development proceeds [13] and this very likely implies a similar explanation to that seen in scopelarchids in which luminescence is limited to the adults [2]. In both cases, the use of the ventral lights only in adults is strong evidence for its function as counterillumination devices to help camouflage silhouettes of larger adult bodies.
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\n
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8. Visual ecology
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Considering bioluminescence as a means for communication and vision may help us understand its origins in fishes. Luminous species exhibit adaptations for a wide range of visual tasks [30] as light organs are multi-purpose and in most cases their predators and preys are also bioluminescent [2, 30]. Most bioluminescent signals are of rather low intensity, but bioluminescent fishes frequently possess rod-dominated retinae, conferring to them high visual absolute sensitivity [68, 70, 71] allowing them to perceive even very dim lights.
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8.1. Bioluminescence detection
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The optical characteristics, i.e. ‘quality and quantity’ of the light emitted by the vast majority of mid and deep-water luminescent species of fish relate to the downwelling light of their habitats. Vision accompanies this tendency. All of the luminescent species, whether shallow or deep-water fishes, possess eyes with at least some visual overlap, i.e. binocular vision, and that enhances sensitivity to and detection of distant point sources in dimly lit environments [68]. Bioluminescent fishes, moreover, frequently exhibit large pupils, which help them to detect bioluminescent flashes against a wider background [30]. The visual pigments present in the eyes of deep-sea bioluminescent fishes seem to be perfectly adapted to the bioluminescence spectra they encounter [2, 6, 30, 36].
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Additionally to these more general adaptations, bioluminescent fishes evolved numerous visual particularities in order to improve detection of bioluminescence signals. Large eyes in epipelagic and in particular mesopelagic species admit greater amounts of photons, banked photoreceptors further improve the photon yield and efficient tapeta permit an at least twofold photon catch. Such adaptations are critically important if sensitivity improvement in order to use bioluminescence is the goal. Different spatial relation of aphakic gaps, retinal specializations and tapeta are particularly well developed among the myctophid species [72] and luminous sharks [65]. Most deep-sea fishes can detect bioluminescence signals up to 30 m away [6, 48]. Some are even able to see bioluminescence up to 51 m as in bathypelagic fishes [21]. Bioluminescent bathypelagic fishes possess small eyes with wide pupils, rostral aphakic gaps and acute foveas. Although these eyes are less sensitive than those of the mesopelagic species, their resolving power is better and they seem perfectly adapted to spot point sources of biological lights in their environment. Contrary to non-luminescent bathypelagic fishes, the eyes of the luminous species are not widely separated, aiding them in distances estimation [31, 68].
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8.2. Intraspecific communication
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In many bioluminescent fish species, their luminescence seems to play a role in communication between conspecifics. The eyes of these species are by necessity optimally adapted to their own bioluminescence. In shallow-water species, anomalopids seem to have eyes and retinae adapted to their own lights [74] and the visual pigments of Porichthys are also a good match to the emission spectrum in this species [73].
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In deeper species, the eyes of Chlorophthalmus, with yellow tainted lenses and a specialized retina with some cones seem specifically adapted to their own blue-green light emissions [60]. Myctophids also possess visual pigments adapted to the spectra of their own light emissions [6]. Most male anglerfishes possess relatively large laterally positioned eyes with aphakic gaps [14] and long rods for heightened absolute sensitivity, adaptations that may be linked to the use of the female’s esca to attract the attention of a male [3]. The genera Malacosteus, Photostomias and Aristostomias possess sub-ocular photophores, which emit red-light used as a ‘private waveband’. These species evolved long-wavelength pigments in their rods and possessed tapeta and lenses that allow them to see their own red light [36].
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Dalatiid sharks do not school, contrary to etmopterids [10]. In bioluminescent sharks, only the etmopterids seem to use their light emissions for intraspecific purposes, specifically the lateral patterns of the photophores [8, 92]. These patterns are more nasal and temporal in Etmopterus lucifer and seem to be detected by specific sensitive and acute zones in the nasal and temporal areas of the retina of this species [65].
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8.3. Hunting
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The use of bioluminescence in the context of food procurement in luminescent fishes is common. Photic lures to attract prey are one of the better known examples of luminous hunting devices. In order to be seen by and attract prey, the light tissue of the predator needs to be brighter than the background and has to be located in a visible place of the predator body, preferably the head and near the mouth [21]. Indeed, the most luminous structures of fishes that are likely to act as lures are easily spotted and emit an intense light, as the escae of anglerfishes [41], the barbels of stomiids [4] and the head organs of anomalopids [33], monocentrids [12] and Diaphus [1]. Most of their prey organisms possess highly sensitive eyes [30], so that the perception by them of the lights emitted by the photic lures is not an issue.
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Some luminous fishes use their light to illuminate their surroundings, helping them in the search and seizure of prey, as suggested for anomalopids [35, 62] and Diaphus [1]. The same is possible for the benthopelagic deep-sea fishes, as alepocephalids and macrourids, that have uncommonly well-developed eyes, which might serve them to search for prey with their ventrally aimed luminescence [31].
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It is common for bioluminescent fishes to prey on other luminous organisms. A good indication of this is the acquisition of Cypridina luciferin by fish through the consumption of luminous ostracods [18, 33] and the high amount of coelenterazine in the digestive tissues of bioluminescent fishes [85]. The eyes of these predators, exhibit characteristics that help them perceive the bioluminescence of their prey. The highly sensitive retinae of fishes like myctophids, ensures that light from prey reaching them over relative long distances, i.e. several metres, is registered [72, 76]. Luminous sharks have retinal specializations, aphakic gaps and tapeta that also seem to be used for the detection of luminescent prey. In the specific case of the dalatiid Squaliolus aliae, the shortwave sensitive pigments in its retina seem to be more adapted to prey emitting blue-luminescence [65].
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The fact that the prey of luminous fishes is frequently bioluminescent can create problems for the predator as most prey may employ counterillumination for concealment [4]. Bioluminescent fishes therefore appear to have evolved visual mechanisms allowing them to distinguish light emissions of prey from the downwelling surrounding lights. Most of the predators seeking to capture fish that employ counterillumination have large eyes that can disrupt the prey’s counterillumination at close range [32]. Other species have evolved tubular eyes which possess acute retinal areas [30] perfect to detect at greater distances even silhouettes camouflaged through counterillumination [21, 46] and diverticula and accessory retinae to detect lateral luminescent stimuli [3, 31]. Some predators use yellow eye lenses to cut-off blue spectra, and to recognize the minimal green mismatches revealing the luminous silhouettes of prey [36]. Aphakic gaps ‘lined‘ with retinal specializations of photoreceptor and ganglion cells as in myctophids may further help detecting counterilluminated prey [72, 76]. The enhancement of binocular resolution by foveas in deep-sea fish may also aid in breaking luminescent camouflages [68]. Different visual pigments and banks in rods that potentiate colour vision in deep-sea fishes are probably involved in breaking counterillumination [36, 75] and the translucent skin area above the eyes in etmopterid sharks may filter the spectra of luminescent prey, thereby compromising the camouflage of the latter [65].
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8.4. Predator avoidance
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One of the major functions of bioluminescence is defence [4, 33]. It is therefore not surprising to see such a vast number of different self-protective mechanisms in luminescent fishes. The trick is to avoid being seen by predators and in the case that has already happened, to deceive the predator and ‘to go on the run’. The method of defence as well as vision of the predator and prey is always involved. We already stated the possibility for the predators to be luminous and that the eyes of bioluminescent fishes serving as prey are sufficiently sensitive to detect the predator. Curiously, except for the purpose of camouflage, smaller species tend to produce faster and shorter flashes than the larger predators [93]. This seems a strategy to reduce the risk to be accepted by a predator. A predator cannot afford the effort and risk of checking out every single flash it encounters, so that the predator would probably use the size and duration of a flash it encounters in deciding whether pursuit is worthwhile and the emitter of the luminescence is large or small [32].
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The spectrum of a luminescent species’ light used in counterillumination is not always a perfect match of the downwelling light [30]. This is not a problem for the deep-sea species as most of their predators do not possess colour vision [4, 48] and intensity rather than spectral matching is most important and apparently within the capability of most species that employ counterillumination concealment [4, 30, 32, 64]. On the other hand, epipelagic predators of bioluminescent fish have eyes more capable than those of deeper waters [94] to disrupt counterillumination [33]. The majority of coastal luminescent fishes exhibit internal light organs providing them a kind of disruptive luminescence that is more effective in turbid and dynamic near-shore waters than the uniform glow [33, 50] of deep-water species that live in more homogeneous and optically transparent photic environment [4].
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Since both nocturnal predators of shallow-water bioluminescent fishes [94] and deep water predators [30] possess highly sensitive eyes, luminescent ‘smokescreens‘ and very bright, brief flashes can temporarily confuse or even blind a predator and allow potential prey to flee [33].
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Bioluminescence is not always straightforward and what seems to be an advantage can become a disadvantage under certain conditions. The ‘private waveband‘ of the red light in stomiids seems an outstanding evolutionary trait for a predator, but some prey like scopelarchids [69], gonostomatids [75] and myctophids [6] have retinae with additional long-wave sensitive photopigments enabling the potential prey to see the stomiids red light. Fishes with ‘head lamps’ to illuminate the surroundings may be coastal and nocturnal or midwater inhabitants. Their bright emissions may be an advantage to pick up prey, but they are also a disadvantage as predators can easily spot these fishes and be attracted to them [12, 32, 33]. Nevertheless, the risks of that happening appear to be reduced as these species feed in schools from which predators usually find it more difficult to focus on an individual fish and seize it [12, 33, 94]. Moreover, the luminescent anomalopid also can rapidly and repeatedly occlude their lights [35, 41, 43].
\n
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9. Final remarks
\n
9.1. Methodology
\n
To understand the inter-relationship between vision and bioluminescence in luminescent species, detailed information on eyes and light organs of these animals is paramount. Spectral properties and intensities of the emitted lights, development, organization, structure and function of photophores as well as photoreceptors have to be studied and behavioural correlates need to be identified. None of that is easy; accessibility is difficult, measurements of the light emissions in luminescent fishes can be a tricky undertaking (especially for deep-sea teleosts and sharks) and when caught, these animals are more than often moribund and in most cases have to be stimulated to glow. This is possible using electricity and/or certain chemicals [34, 55]. The intensity and spectra of such induced light emissions can be measured using a spectrometer and a photo detector, but the data may not exactly reveal their properties in the way the fish use their luminescence in their natural environment. The angle of the light emissions depends on the light organ’s position on the body and the internal angle of the organ, both analysable to a fair degree of accuracy using histological techniques [46]. Chemical analyses of the chemical compounds involved in the generation of the biological light would help understand the underlying mechanism involved, but control of the light emissions, whether direct by the photophores themselves, through nervous signals or hormonal mediators requires living, healthy specimens.
\n
Anatomical details of the eye, cell topography, photoreceptor cell types, cell ultrastructures and distributions as well as certain visual parameters can be gleaned from histological investigations, but while functional parameters like sensitivity, acuity, angular acceptance, etc. can to some extent be deduced from the anatomical details, electrophysiological techniques or the use of microspectrophotometry must be the methods of choice when it comes to functional questions. Spectral sensitivity peaks of the visual pigments obtained spectrophotometrically or electrophysiologically ought to be connected with chemical analyses of the photopigments involved and opsin gene analyses [36]. Chemical and optical studies like refractive indices, focal lengths, etc. on the dioptric structures of the fish eye ought to complement the other investigations so that predictions can be made on the way a fish uses its eyes.
\n
Evolutional studies of vision receive support from investigations on the mutagenesis of the visual pigments [5] and genetics of nuclear and mitochondrial gene fragments can also be used in studies on phylogenetic relationships between species [17]. Often lacking first-hand direct observational evidence of vision/luminescence interactions in the natural environment, the next best approach would involve realistic analyses of the underwater transmission of bioluminescence in specific cases and ecological modelling, based on the information available [48].
\n
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9.2. Future prospects
\n
Communication by light is a subject of considerable interest to ethologists and ecologists, chemists, geneticists, anatomists, physiologist, opticians and vision researchers. Biotechnologists, too, become increasingly interested in bioluminescence generally and communication by light in particular. For the comparative zoologist it is important to realize that behaviour exhibited by individual luminescent fish in captivity may not be the same as that in the fish’s natural environment. This is even more important to keep in mind when interpreting the induced light emissions obtained from nearly dead deep-sea species. Moreover, vision and bioluminescence are only part of a bigger picture. There is evidence that pineal photoreceptors support light perception and are even involved in light output regulation in deep-sea fish [64]. Therefore in analyses of the ecological role, i.e. overall biological significance that bioluminescence plays, we must not ignore the fact that other sense organs like, for instance the lateral line system, semicircular canals, otoliths, chemo, electro and magnetoreceptors, etc. may also be involved [4].
\n
Regarding the eco-ethological roles of the relationship between bioluminescence and vision, some questions have been answered but many more remain to be solved. Remotely operated underwater vehicles (ROVs) can be expected to help in this task and should provide new in vivo insights into the various eco-ethological roles of bioluminescence while advances in genetic techniques can be expected to shed further light onto the phylogeny and evolution of these ‘brightest creatures of the animal world’.
\n
\n
\n
Acknowledgments
\n
The authors are grateful to the Food and Agriculture Organization of the United Nations for the authorization of the drawings in Figure 4 and Dr. Hayato Tanaka for the information on luminous ostracods.
\n
\n',keywords:"bioluminescence, light, sea, eye, vision, fish",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/52465.pdf",chapterXML:"https://mts.intechopen.com/source/xml/52465.xml",downloadPdfUrl:"/chapter/pdf-download/52465",previewPdfUrl:"/chapter/pdf-preview/52465",totalDownloads:1816,totalViews:721,totalCrossrefCites:11,totalDimensionsCites:15,totalAltmetricsMentions:0,impactScore:5,impactScorePercentile:93,impactScoreQuartile:4,hasAltmetrics:0,dateSubmitted:"March 2nd 2016",dateReviewed:"August 26th 2016",datePrePublished:null,datePublished:"November 10th 2016",dateFinished:"September 27th 2016",readingETA:"0",abstract:"What shaped the evolution of vision in fish more than anything else is the need to see, be it to avoid obstacles or find shelters, and recognize conspecifics, predators and prey. However, for vision to be effective, sufficient light has to be available. While there is no shortage of light in shallow water depths, at least during the day, the situation for species occurring at greater depths is a different one: they live in an environment where sunlight does not reach, but which nevertheless, is not totally devoid of light. Numerous marine organisms, including fishes of at least 46 families, possess the ability to ‘bioluminesce’, i.e. they can produce biological light. This chapter focuses on the interaction between bioluminescence and specific photoreceptor adaptations in fishes to detect the biological light.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/52465",risUrl:"/chapter/ris/52465",book:{id:"5348",slug:"luminescence-an-outlook-on-the-phenomena-and-their-applications"},signatures:"José Paitio, Yuichi Oba and Victor Benno Meyer-Rochow",authors:[{id:"185998",title:"Dr.",name:"Yuichi",middleName:null,surname:"Oba",fullName:"Yuichi Oba",slug:"yuichi-oba",email:"oba@agr.nagoya-u.ac.jp",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"Nagoya University",institutionURL:null,country:{name:"Japan"}}},{id:"186175",title:"Dr.",name:"Jose Rui",middleName:null,surname:"Lima Paitio",fullName:"Jose Rui Lima Paitio",slug:"jose-rui-lima-paitio",email:"josepaitio@ua.pt",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"202747",title:"Dr.",name:"Victor B.",middleName:null,surname:"Meyer-Rochow",fullName:"Victor B. Meyer-Rochow",slug:"victor-b.-meyer-rochow",email:"meyrow@gmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Taxonomy of luminous fishes",level:"1"},{id:"sec_2_2",title:"2.1. Dubious species",level:"2"},{id:"sec_4",title:"3. Habitat dispersal of luminous fishes",level:"1"},{id:"sec_5",title:"4. Bioluminescence purposes in fishes",level:"1"},{id:"sec_5_2",title:"4.1. Light organs and control",level:"2"},{id:"sec_6_2",title:"4.2. Functions of light organs and likely roles of the emitted lights",level:"2"},{id:"sec_6_3",title:"4.2.1. Intraspecific communication",level:"3"},{id:"sec_7_3",title:"4.2.2. Interspecific communication",level:"3"},{id:"sec_8_3",title:"4.2.3. Unreported functions",level:"3"},{id:"sec_11",title:"5. Vision in bioluminescent fishes",level:"1"},{id:"sec_11_2",title:"5.1. Eye (structure, size and position)",level:"2"},{id:"sec_12_2",title:"5.2. Lens, pupils and gaps",level:"2"},{id:"sec_13_2",title:"5.3. Tapeta",level:"2"},{id:"sec_14_2",title:"5.4. Retina",level:"2"},{id:"sec_16",title:"6. Evolution of bioluminescence and vision",level:"1"},{id:"sec_16_2",title:"6.1. Bioluminescence evolution",level:"2"},{id:"sec_16_3",title:"6.1.1. Functions",level:"3"},{id:"sec_17_3",title:"6.1.2. Acquisition",level:"3"},{id:"sec_19_2",title:"6.2. Visual adaptation to bioluminescence",level:"2"},{id:"sec_21",title:"7. Ontogeny of bioluminescence and vision",level:"1"},{id:"sec_21_2",title:"7.1. Metamorphosis of eye and luminous tissues",level:"2"},{id:"sec_22_2",title:"7.2. Ecology and ontogeny: vision and bioluminescence in young fishes",level:"2"},{id:"sec_24",title:"8. Visual ecology",level:"1"},{id:"sec_24_2",title:"8.1. Bioluminescence detection",level:"2"},{id:"sec_25_2",title:"8.2. Intraspecific communication",level:"2"},{id:"sec_26_2",title:"8.3. Hunting",level:"2"},{id:"sec_27_2",title:"8.4. Predator avoidance",level:"2"},{id:"sec_29",title:"9. Final remarks",level:"1"},{id:"sec_29_2",title:"9.1. Methodology",level:"2"},{id:"sec_30_2",title:"9.2. Future prospects",level:"2"},{id:"sec_32",title:"Acknowledgments",level:"1"}],chapterReferences:[{id:"B1",body:'Haddock SHD, Moline MA, Case JF. Bioluminescence in the sea. Annual Review of Marine Science. 2010;2:443–493. DOI: 10.1146/annurev-marine-120308-081028.'},{id:"B2",body:'Herring PJ, Morin JG. Bioluminescence in fishes. In: Herring PJ, editor. Bioluminescence in Action. London: Academic Press; 1978. pp.273–329.'},{id:"B3",body:'Nicol JA. Bioluminescence and vision. In: Herring PJ, editor. Bioluminescence in Action. London: Academic Press; 1978. pp. 367–408.'},{id:"B4",body:' Herring P. The Biology of the Deep Ocean. New York: Oxford University Press Inc.; 2002. 314 p.'},{id:"B5",body:'Yokoyama S. Evolution of dim-light and color vision pigments. 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FAO Species Identification Guide for Fishery Purposes. The Living Marine Resources of the Western Central Pacific. Volume 2: Cephalopods, crustaceans, holothurians and sharks. Rome: Food and Agriculture Organization of the United Nations; 1998. pp. 687–1406.'},{id:"B103",body:'Carpenter KE, Niem VH, editors. FAO Species Identification Guide for Fishery Purposes. The Living Marine Resources of the Western Central Pacific. Volume 6: Bony Fishes Part 4 (Labridae to Latimeriidae), Estuarine Crocodiles, Sea Turtles, Sea Snakes and Marine Mammals. Rome: Food and Agriculture Organization of the United Nations; 2001. pp. 3391–4218 p.'},{id:"B104",body:'Carpenter KE, editor. FAO Species Identification Guide for Fishery Purposes. The Living Marine Resources of the Western Central Atlantic. Volume 2: Bony Fishes Part 1 (Acipenseridae to Grammatidae). Rome: Food and Agriculture Organization of the United Nation and American Society of Ichthyologists and Herpetologists. Special Publication Number 5; 2002. pp. 601–1374.'},{id:"B105",body:'Carpenter KE, editor. FAO Species Identification Guide for Fishery Purposes. The Living Marine Resources of the Western Central Atlantic. Volume 3: Bony Fishes Part 2 (Opistognathidae to Molidae), sea turtles and marine mammals. Rome: Food and Agriculture Organization of the United Nation and American Society of Ichthyologists and Herpetologists. Special Publication Number 5; 2002. pp. 1375–2127 .'},{id:"B106",body:'Sasaki K. Phylogeny of the family Sciaenidae, with notes on its zoogeography (Teleostei, Perciformes). Memoirs of the Faculty of Fisheries Hokkaido University. 1989;36(1–2):1–138.'}],footnotes:[],contributors:[{corresp:null,contributorFullName:"José Paitio",address:null,affiliation:'
Deparment of Environmental Biology, Chubu University, Kasugai, Japan
Department of Genetics and Physiology, Oulu University, Finland
Research Institute of Luminous Organisms, Hachijojima, Japan
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1. Introduction
Maintenance of railway tracks is essential for the safe operation of trains. Railway operators conduct track inspections using track geometry cars and track maintenance crews. However, regional railway operators, who carry fewer passengers, often lack the personnel and funds to conduct adequate track inspections. The monitoring of railway track geometry from an in-service vehicle has become increasingly attractive over the past decade [1].
To address this problem, a system that can monitor the track condition inexpensively and frequently using a device incorporating sensors and a global navigation satellite system (GNSS) unit, which is installed on in-service trains, has been developed [2, 3]. The system calculates root mean square (RMS) values from the vertical acceleration, lateral acceleration, and roll angular velocity of the car body. To select sites for repair, we adopt the method of prioritizing sites with the highest numerical values.
The acceleration RMS is closely related to the general health of the track [4]. In Ref. [5], RMS values are used to identify track irregularities for longitudinal level, alignment, cross-level. However, monitoring based on RMS values alone is not sufficient. Without frequency information, it is difficult to identify the type of track fault. Furthermore, since the amount of data generated by constant measurement is enormous, it is necessary to automate the analysis in order to monitor and predict the track condition efficiently.
In this study, we propose a method to classify the types of track faults automatically by means of machine learning, using a CNN trained on images created via a CWT from the vibration acceleration on the time-frequency plane. A continuous wavelet transform (CWT) is a transformation technique that emphasizes certain portions of the waveform by suppressing other portions as it proceeds by multiplying a target waveform using a mother wavelet [6]. A convolutional neural network (CNN) is a class of deep neural networks. It is widely used for image recognition.
To verify the effectiveness of the algorithm we developed, we first describe the results of simulating the vibration of a car body when passing over a faulty track. Next, we describe the results of diagnosing track faults from the vertical vibration acceleration data of a car body measured by a regional railway.
2. Literature review of track condition monitoring using machine learning techniques
It should be necessary for railway operators to control track irregularity, such as vertical rail profiles, lateral alignment, gauge, cross-level, twist (depicted in Figure 1) properly. Track irregularities cause vehicle vibrations that degrade the rider’s comfort and increase the risk of derailments. Track irregularities are strongly correlated with vehicle vibrations. Thus, it can be possible to estimate general trends of the track condition by analyzing vehicle vibrations.
Figure 1.
Track structure and irregularities.
Although track geometry measurement systems using in-service vehicles are becoming increasingly attractive around the world [2, 7, 8, 9], the repeated checking of the same track provides the information regarding track geometry degradation, which can be fed back to the track maintenance section for taking essential actions. The use of vehicle responses in the track geometry assessment process allows identifying of critical defects, which could not have been identified from geometry parameters, and thus, improve the maintenance operations.
Tsunashima et al. proposed techniques of condition monitoring of railway tracks based on time-frequency analysis [10]. They compared the performance of Hilbert-Huang transforms (HHT) and CWT for identifying track faults from car body vibration. It is shown that the feature of track fault can be identified in time-frequency plane.
Tsunashima proposed a classifier based on a machine learning technique for identifying track faults automatically from measured car body vibration [5]. It is shown that the degradation of track can be classified in the feature space consisting of car body vibration RMS.
Faghih-Roohi et al. proposed a deep convolutional neural network for the analysis of image data for the detection of rail surface defects [11]. They explored the efficiency of the proposed deep convolutional neural network for the detection and classification of rail surface defects.
Zheng et al. proposed a multi-object detection method based on a deep convolutional neural network that can achieve non-destructive detection of rail surface and fastener defects [12]. A defect detection model based on Mask R-CNN and ResNet framework was utilized to detect the surface defects.
Jin et al. proposed a machine learning framework based on wavelet scattering networks and neural networks for identifying railhead defects [13].
Alvarenga et al. proposed an embedded system for online detection and location of rails defects based on eddy current [14]. They proposed a new method to interpret eddy current signals by analyzing their wavelet transforms through a convolutional neural network.
3. Effect of track faults on time-frequency plane
3.1 Overview of the simulation
When a train runs on a track, vibrations that correspond to the track geometry are generated [15, 16]. Therefore, in this study, to verify the relationship between the type of track fault and the car body vibration acceleration, and to evaluate the effectiveness of time-frequency analysis in detecting track faults, we simulated the occurrence of track faults, calculated the vertical vibration acceleration of the car body, and then applied a CWT, a method of time-frequency analysis, to the results.
3.2 Continuous wavelet transform (CWT)
A CWT is a method that simultaneously detects the frequency and time characteristics of an unsteady signal, by comparing the original signal with dilated and translated versions of a small wavelike function called the mother wavelet. Using this method, it is possible to view the amplitude and frequency information of the vibration acceleration as an image. In this study, we used the Morlet wavelet, which offers a relatively good balance between localization of time and frequency, as the mother wavelet [17] (see Appendix A).
This technique is well suited for analyzing unsteady signals, such as xt those that exhibit sudden variation, and is defined as follows:
Wψab=∫−∞∞1aψ∗t−baxtdt,E1
where, variables a and b correspond to the dilatation and location parameters, respectively, they translate the mother wavelet ψt by a time shift b in time, and by 1/a in frequency. indicates the complex conjugate of ψ.
3.3 Vehicle model used in the simulation
The vehicle model used in the simulation is shown in Figure 2 [10]. The vehicle model consists of a total of seven rigid bodies: one car body, two bogies, and four wheelsets. The car body and bogie were assigned two degrees of freedom (DOF) for bounce and pitch, and the wheelset was assigned one DOF for the bounce. The vehicle’s parameters were obtained from measurement data from a regional railway vehicle equipped with an onboard sensing device.
Figure 2.
Vehicle model [10].
3.4 Simulation conditions
In the simulation, the vehicle model was run at 60 [km/h] for 500 [m], and the results were output for the section between 100 [m] and 350 [m]. We set rail joint faults (joint depressions) at 4 points; otherwise, the track was assumed to be straight. To set the rail joint faults, we used the function model shown in Figure 3 [18].
Figure 3.
Track fault model.
The geometry of the modeled track are represented by
y=Ae−12xk2,E2
and
y2=12xk2−A.E3
The track geometry used in the simulation is shown in Figure 4. At the 150 [m] and 200 [m] points, we set depths of A=15mm and 30mm, respectively, to simulate joint depressions, which are depressions in the top surface of the railhead that occur at track joints.
Figure 4.
Track geometry with different faults.
In both cases, we set the depression length k=83.5mm. For comparison, at the 250 [m] and 300 [m] points, we set a gentler dip in track geometry by setting depths of A=15mm and 30mm, respectively, but with length k=1670mm. The values of A and k were determined with reference to generally occurring track displacement. The car body vibration acceleration was assumed to occur directly above the center of the front bogie of the vehicle model. The simulation was performed at a sampling frequency of 200 [Hz].
3.5 Simulation results
The simulated vertical vibration acceleration of the car body is shown in Figure 5a. The figure shows that characteristic vibrations corresponding to the track geometry are generated at the points where the track faults were set. Figure 5b shows the result of the CWT of the simulated vertical vibration acceleration. The color bar indicates the magnitude of the amplitude in the time-frequency plane.
Figure 5.
Simulated car body vertical acceleration and its CWT image.
At 150 [m] and 200 [m], the points where the joint depressions were simulated, vibrations in the frequency band of 15–30 [Hz] were detected due to the impulse-like track geometry, and variations depending on depth A can be seen in the CWT images. In addition, at 250 [m] and 300 [m], the points where gentler dips in the track geometry were set, vibrations in the frequency band of 0–5 [Hz] were detected, and variations depending on depth A can be seen in the CWT images. These results demonstrate that the CWT images are effective for identifying track faults, since the features of the CWT images change markedly depending on the type and level of degradation.
4. Monitoring the condition of railway track using a convolutional neural network
4.1 Track condition monitoring system
Figure 6 shows the track condition monitoring system developed and applied for regional railway lines in Japan [2].
Figure 6.
Track condition monitoring system [2].
Accelerometers and rate gyros in the onboard sensing device measure the car body vibration. A GNSS receiver detects the location and speed of the train. Collected data are transmitted to the data server in the monitoring center continuously via a mobile phone network.
The diagnostic software analyses the collected data and results are fed back to the railway operators through online channels via tablet computers. The diagnostic results are used to facilitate the maintenance work of railway operators.
Convolutional neural networks are a method used in the field of machine learning called deep learning and are particularly suitable for image recognition. In this study, we examined the effectiveness of classifying longitudinal level irregularities and joint depressions automatically, using a diagnostic algorithm, we constructed based on a convolutional neural network trained on CWT images generated from vertical vibration acceleration data from a car body. The diagnostic procedure is shown in Figure 7.
Figure 7.
Diagnostic procedure.
5. Identification of the condition of railway track using vertical vibration acceleration data measured from an actual car body
5.1 Overview of diagnosis
The car body’s vertical acceleration with track faults was collected in a regional railway line using the track condition monitoring system. The input data for the classifier consists of vertical vibration acceleration measurements from an onboard sensing device in a car body, which are then converted into images using a CWT. Figure 8 shows an example of converting the measurements into a CWT image.
Figure 8.
Measured car-body vertical acceleration and its CWT image.
The vibration characteristics of the joint depression at the distance of 25.82 [km] appear in the 10–30 [Hz] frequency range. The vibration characteristics of the longitudinal level irregularities around 25.95 [km] appear in the 0–5 [Hz] frequency range.
5.2 Images used for training and evaluation
In this study, we investigated the following three types of diagnoses:
Classification of images into three types: longitudinal level irregularity, joint depression, and normal.
Classification of the degradation level of longitudinal level irregularity into normal, medium, and large.
Classification of the degradation level of joint depression into normal, medium, and large.
Examples of images used for each task are shown in Figures 9–11. The images were created with an aspect ratio of 1:1 (150 × 150 pixels), which is optimal for training.
Figure 9.
CWT images of faulty track.
Figure 10.
CWT images of the different levels of a degraded track (track irregularity).
Figure 11.
CWT images of the different levels of a degraded track (joint depression).
For diagnosing the level of degradation of longitudinal level irregularities, in cases where the one-side amplitude of the vibration acceleration was normal, images of car body acceleration of 0–0.5m/s2 were used. To diagnose medium degradation, images of 0.8–1.2m/s2 were used, and to diagnose large degradation, images of 1.5m/s2 or greater were used.
For diagnosing the level of degradation of joint depressions, in cases where the one-side amplitude of the vibration acceleration was normal, images of body acceleration of 0 to were used. To diagnose medium degradation, images of 2.5–3.5m/s2 were used, and to diagnose large degradation, images of 4.5m/s2 or greater were used.
5.3 Identification of longitudinal level irregularities and joint depressions
5.3.1 Configuration of the trained convolutional neural network
We prepared a total of 300 images: 100 normal images, 100 images with a longitudinal level irregularity, and 100 images with a joint depression. We set aside 80% of the images for training and 20% for evaluation as shown in Figure 9.
Figure 12 shows the configuration of the trained convolutional neural network (see Appendix B). In the figure, the name of the process and the size (vertical × horizontal × channels) before processing are indicated above each layer, and the size after processing is indicated below the layer.
Figure 12.
Network configuration.
The Convolution layer applies the convolution operation to the image, representing it in matrix form; the Max pooling layer performs information compression; the Affine layer combines information from different layers, and the Output layer outputs a set of probabilities indicating how well the image matches the three types of training image data. The number of training sessions was set to 50.
5.3.2 Diagnosis results
Figure 13 shows the results of using images for evaluation to discriminate longitudinal level irregularity track faults versus joint depression track faults versus normal track. The overall accuracy rate was 98.3%, demonstrating that convolutional neural networks are effective for the classification of track faults.
Figure 13.
Detection accuracy for the type of track fault.
5.4 Identification of the degradation level of longitudinal level irregularities
5.4.1 Configuration of the trained convolutional neural network
In order to classify the degradation level of longitudinal level irregularities into three types: normal, medium, and large, we prepared a total of 300 images: 100 normal, 100 medium, and 100 large. We set aside 80% of the images for training and 20% for evaluation. The network configuration and the number of training sessions were the same as in Section 5.3.
5.4.2 Diagnosis results
Detection results using the trained model are shown in Figure 14. The overall accuracy rate was 98.3%, demonstrating that the level of longitudinal level irregularity can be classified with high accuracy into normal, medium, and large.
Figure 14.
Detection accuracy for the different levels of a degraded track (track irregularity).
5.5 Classification of the degradation level of joint depression
5.5.1 Configuration of the trained convolutional neural network
In order to classify the degradation level of joint depression into three types: normal, medium, and large, we prepared a total of 300 images: 100 normal, 100 medium, and 100 large. We set aside 80% of the images for training and 20% for evaluation. The network configuration and the number of training sessions were the same as in Section 5.3.
5.5.2 Diagnosis results
Detection results using the trained model are shown in Figure 15. Some incorrect diagnoses were made in the images of normal and medium joint depression. However, the overall accuracy was 96.7%, which was sufficient to classify the level of joint depression, demonstrating that the diagnostic algorithm we developed is effective for the diagnosis of joint depression.
Figure 15.
Detection accuracy for the different levels of a degraded track (joint depression).
6. Investigation of CWT images that were diagnosed incorrectly
Figure 16 shows an example of an image that was diagnosed incorrectly. The right side of Figure 16a was diagnosed as normal, even though it shows joint depression. Conversely, the left side of Figure 16a shows an image that was diagnosed correctly as a joint depression. Comparing those, the feature representing the joint depression is extremely small in the incorrectly diagnosed image. This reveals that an incorrect diagnosis can occur when the features are extremely small.
Figure 16.
CWT images that were diagnosed incorrectly.
The right side of Figure 16b was diagnosed as normal, even though it shows a large track irregularity. Conversely, the left side of Figure 16b shows an image that was diagnosed correctly as a large track irregularity. The reason for the incorrect diagnosis was that the large amplitude of the vertical acceleration, shown in red color, was appeared at the bottom of the CWT image.
7. Conclusion
In this study, we proposed a method to classify the type and level of track faults automatically using a convolutional neural network trained on car body vibration acceleration measurements converted into images using a CWT, a well-known method of time-frequency analysis. The algorithm we developed was used to perform the diagnosis of track conditions on actual measurements.
The results demonstrated that it is possible to diagnose the type and level of degradation of track faults with high accuracy.
In future work, we plan to improve the algorithm to estimate the locations of track faults accurately in actual measurements and monitor the condition of railway tracks in more detail.
Acknowledgments
This research was funded by Nihon University Research Grant for Social Implementation (19-006) (2019). We would like to thank Editage (www.editage.jp) for English language editing.
Conflict of interest
The authors declare no conflict of interest.
A CWT is a method that simultaneously detects the frequency and time characteristics of an unsteady signal, by comparing the original signal with dilated and translated versions of a small wavelike function called the mother wavelet. The CWT computes the inner products of a continuous signal with a set of continuous wavelets according to the following equation
Wψab=∫−∞∞1aψ∗t−baxtdt,EA1
where, variables a and b correspond to the dilatation and location parameters, respectively, they translate the mother wavelet ψt by a time shift b in time, and by 1/a in frequency. ψ∗ indicates the complex conjugate of ψ.
In this study, we used the real-valued Morlet wavelet (Figure 17) as the mother wavelet ψt.
Figure 17.
Real-valued Morlet wavelet.
ψt=e−t22cos5t.EA2
A Convolutional Neural Network (CNN) is a well-known deep learning architecture. There are numerous variants of CNN architectures. The basic components of CNN consist of convolutional layer, pooling layer, and fully-connected layers [19].
B.1 Convolution Layer
The objective of the convolution operation is to extract the significant features from the input image. The convolution layer is composed of several convolution kernels which are used to compute different feature maps. The feature maps are generated by the convolution operation with the filter that acts as the feature extractor as follows.
I2xy=∑j=−NN∑i=−NNFijI1x−iy−j.EA3
where I1xy: pixel value of input image at xy, I2xy: pixel value of output image at xy, Fij: filter coefficient.
B.2 Pooling layer
The Pooling layer is responsible for reducing the spatial size of the feature maps. This is to decrease the computational power required to process the data through size reduction. It is useful for extracting dominant features. There are two types of Pooling: Max Pooling and Average Pooling. Max Pooling returns the maximum value from the portion of the image. On the other hand, Average Pooling returns the average value. In this study, Max Pooling were used. Figure 18 shows the example of the Max Pooling operation.
Figure 18.
Max pooling.
B.3 Activation function
Rectified linear unit (ReLU) is one of the most famous activation functions. In this study, the following function is used to adjust the output of the Pooling Layer.
y=0x≤0xx>0EB1
where x is the input of the activation function. The simple operation of the activation function makes the faster computation than sigmoid or hyperbolic tangent functions.
Softmax function defined by
yi=exi∑k=1nexki=12⋯n,EB2
was used in output layer. Where n indicates the number of classification.
B.4 Fully connected layer
In fully connected layers, the neuron applies a linear transformation to the input vector through a weights matrix. In this study, an Affine transformation was used in fully connected layer.
B.5 Loss function
The loss function is the function that computes the distance between the current output of the algorithm and the expected output. In this study, we employed the categorical cross-entropy, which is well suited to classification tasks.
Abbreviations
CWT
continuous wavelet transform
RMS
root mean square
CNN
convolutional neural network
HHT
Hilbert–Huang transform
GNSS
global navigation satellite system
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Railway Research. London: IntechOpen; 2015. p. 145. DOI: 10.5772/61077'},{id:"B3",body:'Mori H, Ohno H, Tsunashima H, Saito Y. Development of compact size onboard device for condition monitoring of railway tracks. Journal of Mechanical Systems for Transportation and Logistics. 2013;6(2):142-149. DOI: 10.1299/jmtl.6.142'},{id:"B4",body:'Vinberg EM, Martin M, Firdaus AH, Tang Y, Qazizadeh A. Railway Applications of Condition Monitoring. Stockholm, Sweden: KTH Royal Institute of Technology; 2018. p. 147. DOI: 10.13140/RG.2.2.35912.62729'},{id:"B5",body:'Tsunashima H. Condition monitoring of railway tracks from car-body vibration using a machine learning technique. Applied Sciences. 2019;9(13):2734. DOI: 10.3390/app9132734'},{id:"B6",body:'Daubechies I. Ten Lectures on Wavelets. Society for Industrial and Applied Mathematics: Philadelphia, Pennsylvania, United States. 1992. p. 441 DOI: 10.1137/1.9781611970104'},{id:"B7",body:'Weston P, Ling C, Goodman C, Roberts C, Li P, Goodall R. Monitoring vertical track irregularity from in-service railway vehicles. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit. 2007;221:75-88. DOI: 10.1243/0954409JRRT65'},{id:"B8",body:'Weston P, Ling C, Goodman C, Roberts C, Li P, Goodall R. Monitoring lateral track irregularity from in-service railway vehicles. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit. 2007;221:89-100. DOI: 10.1243/0954409JRRT64'},{id:"B9",body:'Wei X, Liu F, Jia L. Urban rail track condition monitoring based on in-service vehicle acceleration measurements. Measurement. 2016;80:217-228. DOI: 10.1016/j.measurement.2015.11.033'},{id:"B10",body:'Tsunashima H, Hirose R. Condition monitoring of railway track from car-body vibration using time–frequency analysis. Vehicle System Dynamics. 2020;1:1-18. DOI: 10.1080/00423114.2020.1850808'},{id:"B11",body:'Faghih-Roohi S, Hajizadeh S, Nunez A, Babuska R, De Schutter B. Deep convolutional neural networks for detection of rail surface defects. In: Proceedings of the 2016 International Joint Conference on Neural Networks. Vancouver, Canada: IJCNN; 2016. pp. 2584-2589'},{id:"B12",body:'Zheng D, Li L, Zheng S, Chai X, Zhao S, Tong Q, et al. A defect detection method for rail surface and fasteners based on deep convolutional neural network. Hindawi, Computational Intelligence and Neuroscience. 2021;2565500:15. DOI: 10.1155/2021/2565500'},{id:"B13",body:'Jin Y. Wavelet scattering and neural networks for railhead defect identification. Materials. 1957;2021:14. DOI: 10.3390/ma14081957'},{id:"B14",body:'Alvarenga TA, Carvalho AL, Honorio LM, Cerqueira AS, Filho LMA, Nobrega RA. Detection and classification system for rail surface defects based on Eddy current. Sensors. 2021;21:7937. DOI: 10.3390/s21237937'},{id:"B15",body:'Kraft S, Causse J, Coudert F. Vehicle response based track geometry assessment using multi-body simulation. Vehicle System Dynamics. 2018;56(2):190-220. DOI: 10.1080/00423114.2017.1359418'},{id:"B16",body:'Karis T, Berg M, Stichel S, Li M, Thomas D, Dirks B. Correlation of track irregularities and vehicle responses based on measured data. Vehicle System Dynamics. 2018;56(6):967-981. DOI: 10.1080/00423114.2017.1403634'},{id:"B17",body:'Le T. Use of the Morlet mother wavelet in the frequency-scale domain decomposition technique for the modal identification of ambient vibration responses. Mechanical Systems and Signal Processing. 2017;95:488-505. DOI: 10.1016/j.ymssp.2017.03.045'},{id:"B18",body:'Garg V, Dukkipati R. Dynamics of Railway Vehicle Systems. Cambridge, Massachusetts: Academic Press; 1984. p. 407'},{id:"B19",body:'Gu J, Wang Z, Kuen J, Ma L, Shahroudy A, Shuai B, et al. Recent advances in convolutional neural networks. Pattern Recognition. 2018;77:354-377. 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Many researches have been conducted to determine the best control method for vortex flow in pump sumps so that the pump lifespan can be maximized. In this study, a vortex control principle designed to minimize the impact of submerged vortex flow in pump sump on major pump components is presented. This principle employs a device called the plate type floor splitter which serves the function of eliminating vortices formed on the sump floor and reduces the intensity of swirling motion in the intake flow. A pump sump model was built to carry out the study by installing a floor splitter plate sample under the pump suction inlet and the corresponding parameters used to quantify the swirl intensity known as the swirl angle was measured. Procedures for the measurement were conducted based on ANSI/HI 9.8-2018 standard. A numerical simulation was performed to study the flow in a full-scale pump sump. The results showed that the installation of floor splitter plate can eliminate vortices efficiently and reduce swirl angle significantly. 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This chapter focuses on investigating the commonly used manufacturing technologies and process chain for the prototyping and mass production of microfluidic chips. The rapid prototyping technologies comprising of PDMS casting, micro machining, and 3D-printing are firstly detailed with some important research findings. Scaling up the production process chain for microfluidic chips are discussed and summarized with the perspectives of tooling technology, replication, and bonding technologies, where the primary working mechanism, technical advantages and limitations of each process method are presented. Finally, conclusions and future perspectives are given. Overall, this chapter demonstrates how to select the processing materials and methods to meet practical requirements for microfluidic chip batch production. 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One of the most plausible applications of nanotechnology is to produce nanoparticles of high thermal conductivity and mixing with the base fluids that transfer energy forming what is called nanofluids. Adding of nanoparticles to the base fluid shows a remarkable enhancement of the thermal properties of the base properties. Nanotechnology has greatly improved the science of heat transfer by improving the properties of the energy-transmitting fluids. A high heat transfer could be obtained through the creation of innovative fluid (nanofluids). This also reduces the size of heat transfer equipment and saves energy.",book:{id:"8887",slug:"thermophysical-properties-of-complex-materials",title:"Thermophysical Properties of Complex Materials",fullTitle:"Thermophysical Properties of Complex Materials"},signatures:"Mahmoud Salem Ahmed",authors:null}],onlineFirstChaptersFilter:{topicId:"157",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:8,limit:8,total:0},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:90,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:104,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:32,numberOfPublishedChapters:319,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:12,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:141,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:133,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!0},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:113,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:107,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:5,numberOfOpenTopics:1,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!0},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:0,numberOfPublishedChapters:16,numberOfOpenTopics:5,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}},{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. 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\r\n\tTransforming our World: the 2030 Agenda for Sustainable Development endorsed by United Nations and 193 Member States, came into effect on Jan 1, 2016, to guide decision making and actions to the year 2030 and beyond. Central to this Agenda are 17 Goals, 169 associated targets and over 230 indicators that are reviewed annually. The vision envisaged in the implementation of the SDGs is centered on the five Ps: People, Planet, Prosperity, Peace and Partnership. This call for renewed focused efforts ensure we have a safe and healthy planet for current and future generations.
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\r\n\t2. Health and Wellbeing focusing on SDG 3 on Good Health and Wellbeing and SDG 6 on Clean Water and Sanitation
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\r\n\t3. Inclusivity and Social Equality involving SDG 4 on Quality Education, SDG 5 on Gender Equality, and SDG 16 on Peace, Justice and Strong Institutions
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\r\n\t4. Climate Change and Environmental Sustainability comprising SDG 13 on Climate Action, SDG 14 on Life Below Water, and SDG 15 on Life on Land
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\r\n\t5. Urban Planning and Environmental Management embracing SDG 7 on Affordable Clean Energy, SDG 9 on Industry, Innovation and Infrastructure, and SDG 11 on Sustainable Cities and Communities.
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\r\n\tThe series also seeks to support the use of cross cutting SDGs, as many of the goals listed above, targets and indicators are all interconnected to impact our lives and the decisions we make on a daily basis, making them impossible to tie to a single topic.
",coverUrl:"https://cdn.intechopen.com/series/covers/24.jpg",latestPublicationDate:"July 5th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:0,editor:{id:"262440",title:"Prof.",name:"Usha",middleName:null,surname:"Iyer-Raniga",slug:"usha-iyer-raniga",fullName:"Usha Iyer-Raniga",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRYSXQA4/Profile_Picture_2022-02-28T13:55:36.jpeg",biography:"Usha Iyer-Raniga is a professor in the School of Property and Construction Management at RMIT University. Usha co-leads the One Planet Network’s Sustainable Buildings and Construction Programme (SBC), a United Nations 10 Year Framework of Programmes on Sustainable Consumption and Production (UN 10FYP SCP) aligned with Sustainable Development Goal 12. The work also directly impacts SDG 11 on Sustainable Cities and Communities. She completed her undergraduate degree as an architect before obtaining her Masters degree from Canada and her Doctorate in Australia. Usha has been a keynote speaker as well as an invited speaker at national and international conferences, seminars and workshops. Her teaching experience includes teaching in Asian countries. She has advised Austrade, APEC, national, state and local governments. She serves as a reviewer and a member of the scientific committee for national and international refereed journals and refereed conferences. She is on the editorial board for refereed journals and has worked on Special Issues. Usha has served and continues to serve on the Boards of several not-for-profit organisations and she has also served as panel judge for a number of awards including the Premiers Sustainability Award in Victoria and the International Green Gown Awards. Usha has published over 100 publications, including research and consulting reports. Her publications cover a wide range of scientific and technical research publications that include edited books, book chapters, refereed journals, refereed conference papers and reports for local, state and federal government clients. She has also produced podcasts for various organisations and participated in media interviews. She has received state, national and international funding worth over USD $25 million. Usha has been awarded the Quarterly Franklin Membership by London Journals Press (UK). Her biography has been included in the Marquis Who's Who in the World® 2018, 2016 (33rd Edition), along with approximately 55,000 of the most accomplished men and women from around the world, including luminaries as U.N. Secretary-General Ban Ki-moon. 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Initial biochemical studies have been exclusively analytic: dissecting, purifying, and examining individual components of a biological system; in the apt words of Efraim Racker (1913 –1991), “Don’t waste clean thinking on dirty enzymes.” Today, however, biochemistry is becoming more agglomerative and comprehensive, setting out to integrate and describe entirely particular biological systems. The ‘big data’ metabolomics can define the complement of small molecules, e.g., in a soil or biofilm sample; proteomics can distinguish all the comprising proteins, e.g., serum; metagenomics can identify all the genes in a complex environment, e.g., the bovine rumen. This Biochemistry Series will address the current research on biomolecules and the emerging trends with great promise.",coverUrl:"https://cdn.intechopen.com/series/covers/11.jpg",latestPublicationDate:"June 29th, 2022",hasOnlineFirst:!0,numberOfOpenTopics:4,numberOfPublishedChapters:318,numberOfPublishedBooks:32,editor:{id:"31610",title:"Dr.",name:"Miroslav",middleName:null,surname:"Blumenberg",fullName:"Miroslav Blumenberg",profilePictureURL:"https://mts.intechopen.com/storage/users/31610/images/system/31610.jpg",biography:"Miroslav Blumenberg, Ph.D., was born in Subotica and received his BSc in Belgrade, Yugoslavia. He completed his Ph.D. at MIT in Organic Chemistry; he followed up his Ph.D. with two postdoctoral study periods at Stanford University. Since 1983, he has been a faculty member of the RO Perelman Department of Dermatology, NYU School of Medicine, where he is codirector of a training grant in cutaneous biology. Dr. Blumenberg’s research is focused on the epidermis, expression of keratin genes, transcription profiling, keratinocyte differentiation, inflammatory diseases and cancers, and most recently the effects of the microbiome on the skin. He has published more than 100 peer-reviewed research articles and graduated numerous Ph.D. and postdoctoral students.",institutionString:null,institution:{name:"New York University Langone Medical Center",institutionURL:null,country:{name:"United States of America"}}},subseries:[{id:"14",title:"Cell and Molecular Biology",keywords:"Omics (Transcriptomics; Proteomics; Metabolomics), Molecular Biology, Cell Biology, Signal Transduction and Regulation, Cell Growth and Differentiation, Apoptosis, Necroptosis, Ferroptosis, Autophagy, Cell Cycle, Macromolecules and Complexes, Gene Expression",scope:"The Cell and Molecular Biology topic within the IntechOpen Biochemistry Series aims to rapidly publish contributions on all aspects of cell and molecular biology, including aspects related to biochemical and genetic research (not only in humans but all living beings). We encourage the submission of manuscripts that provide novel and mechanistic insights that report significant advances in the fields. Topics include, but are not limited to: Advanced techniques of cellular and molecular biology (Molecular methodologies, imaging techniques, and bioinformatics); Biological activities at the molecular level; Biological processes of cell functions, cell division, senescence, maintenance, and cell death; Biomolecules interactions; Cancer; Cell biology; Chemical biology; Computational biology; Cytochemistry; Developmental biology; Disease mechanisms and therapeutics; DNA, and RNA metabolism; Gene functions, genetics, and genomics; Genetics; Immunology; Medical microbiology; Molecular biology; Molecular genetics; Molecular processes of cell and organelle dynamics; Neuroscience; Protein biosynthesis, degradation, and functions; Regulation of molecular interactions in a cell; Signalling networks and system biology; Structural biology; Virology and microbiology.",annualVolume:11410,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/14.jpg",editor:{id:"165627",title:"Dr.",name:"Rosa María",middleName:null,surname:"Martínez-Espinosa",fullName:"Rosa María Martínez-Espinosa",profilePictureURL:"https://mts.intechopen.com/storage/users/165627/images/system/165627.jpeg",institutionString:null,institution:{name:"University of Alicante",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"79367",title:"Dr.",name:"Ana Isabel",middleName:null,surname:"Flores",fullName:"Ana Isabel Flores",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRpIOQA0/Profile_Picture_1632418099564",institutionString:null,institution:{name:"Hospital Universitario 12 De Octubre",institutionURL:null,country:{name:"Spain"}}},{id:"328234",title:"Ph.D.",name:"Christian",middleName:null,surname:"Palavecino",fullName:"Christian Palavecino",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000030DhEhQAK/Profile_Picture_1628835318625",institutionString:null,institution:{name:"Central University of Chile",institutionURL:null,country:{name:"Chile"}}},{id:"186585",title:"Dr.",name:"Francisco Javier",middleName:null,surname:"Martin-Romero",fullName:"Francisco Javier Martin-Romero",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSB3HQAW/Profile_Picture_1631258137641",institutionString:null,institution:{name:"University of Extremadura",institutionURL:null,country:{name:"Spain"}}}]},{id:"15",title:"Chemical Biology",keywords:"Phenolic Compounds, Essential Oils, Modification of Biomolecules, Glycobiology, Combinatorial Chemistry, Therapeutic peptides, Enzyme Inhibitors",scope:"Chemical biology spans the fields of chemistry and biology involving the application of biological and chemical molecules and techniques. In recent years, the application of chemistry to biological molecules has gained significant interest in medicinal and pharmacological studies. This topic will be devoted to understanding the interplay between biomolecules and chemical compounds, their structure and function, and their potential applications in related fields. Being a part of the biochemistry discipline, the ideas and concepts that have emerged from Chemical Biology have affected other related areas. This topic will closely deal with all emerging trends in this discipline.",annualVolume:11411,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/15.jpg",editor:{id:"441442",title:"Dr.",name:"Şükrü",middleName:null,surname:"Beydemir",fullName:"Şükrü Beydemir",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003GsUoIQAV/Profile_Picture_1634557147521",institutionString:null,institution:{name:"Anadolu University",institutionURL:null,country:{name:"Turkey"}}},editorTwo:{id:"13652",title:"Prof.",name:"Deniz",middleName:null,surname:"Ekinci",fullName:"Deniz Ekinci",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYLT1QAO/Profile_Picture_1634557223079",institutionString:null,institution:{name:"Ondokuz Mayıs University",institutionURL:null,country:{name:"Turkey"}}},editorThree:null,editorialBoard:[{id:"219081",title:"Dr.",name:"Abdulsamed",middleName:null,surname:"Kükürt",fullName:"Abdulsamed Kükürt",profilePictureURL:"https://mts.intechopen.com/storage/users/219081/images/system/219081.png",institutionString:null,institution:{name:"Kafkas University",institutionURL:null,country:{name:"Turkey"}}},{id:"241413",title:"Dr.",name:"Azhar",middleName:null,surname:"Rasul",fullName:"Azhar Rasul",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRT1oQAG/Profile_Picture_1635251978933",institutionString:null,institution:{name:"Government College University, Faisalabad",institutionURL:null,country:{name:"Pakistan"}}},{id:"178316",title:"Ph.D.",name:"Sergey",middleName:null,surname:"Sedykh",fullName:"Sergey Sedykh",profilePictureURL:"https://mts.intechopen.com/storage/users/178316/images/system/178316.jfif",institutionString:null,institution:{name:"Novosibirsk State University",institutionURL:null,country:{name:"Russia"}}}]},{id:"17",title:"Metabolism",keywords:"Biomolecules Metabolism, Energy Metabolism, Metabolic Pathways, Key Metabolic Enzymes, Metabolic Adaptation",scope:"Metabolism is frequently defined in biochemistry textbooks as the overall process that allows living systems to acquire and use the free energy they need for their vital functions or the chemical processes that occur within a living organism to maintain life. Behind these definitions are hidden all the aspects of normal and pathological functioning of all processes that the topic ‘Metabolism’ will cover within the Biochemistry Series. Thus all studies on metabolism will be considered for publication.",annualVolume:11413,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/17.jpg",editor:{id:"138626",title:"Dr.",name:"Yannis",middleName:null,surname:"Karamanos",fullName:"Yannis Karamanos",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002g6Jv2QAE/Profile_Picture_1629356660984",institutionString:null,institution:{name:"Artois University",institutionURL:null,country:{name:"France"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"243049",title:"Dr.",name:"Anca",middleName:null,surname:"Pantea Stoian",fullName:"Anca Pantea Stoian",profilePictureURL:"https://mts.intechopen.com/storage/users/243049/images/system/243049.jpg",institutionString:null,institution:{name:"Carol Davila University of Medicine and Pharmacy",institutionURL:null,country:{name:"Romania"}}},{id:"203824",title:"Dr.",name:"Attilio",middleName:null,surname:"Rigotti",fullName:"Attilio Rigotti",profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institutionString:null,institution:{name:"Pontifical Catholic University of Chile",institutionURL:null,country:{name:"Chile"}}},{id:"300470",title:"Dr.",name:"Yanfei (Jacob)",middleName:null,surname:"Qi",fullName:"Yanfei (Jacob) Qi",profilePictureURL:"https://mts.intechopen.com/storage/users/300470/images/system/300470.jpg",institutionString:null,institution:{name:"Centenary Institute of Cancer Medicine and Cell Biology",institutionURL:null,country:{name:"Australia"}}}]},{id:"18",title:"Proteomics",keywords:"Mono- and Two-Dimensional Gel Electrophoresis (1-and 2-DE), Liquid Chromatography (LC), Mass Spectrometry/Tandem Mass Spectrometry (MS; MS/MS), Proteins",scope:"With the recognition that the human genome cannot provide answers to the etiology of a disorder, changes in the proteins expressed by a genome became a focus in research. Thus proteomics, an area of research that detects all protein forms expressed in an organism, including splice isoforms and post-translational modifications, is more suitable than genomics for a comprehensive understanding of the biochemical processes that govern life. The most common proteomics applications are currently in the clinical field for the identification, in a variety of biological matrices, of biomarkers for diagnosis and therapeutic intervention of disorders. From the comparison of proteomic profiles of control and disease or different physiological states, which may emerge, changes in protein expression can provide new insights into the roles played by some proteins in human pathologies. Understanding how proteins function and interact with each other is another goal of proteomics that makes this approach even more intriguing. Specialized technology and expertise are required to assess the proteome of any biological sample. Currently, proteomics relies mainly on mass spectrometry (MS) combined with electrophoretic (1 or 2-DE-MS) and/or chromatographic techniques (LC-MS/MS). MS is an excellent tool that has gained popularity in proteomics because of its ability to gather a complex body of information such as cataloging protein expression, identifying protein modification sites, and defining protein interactions. The Proteomics topic aims to attract contributions on all aspects of MS-based proteomics that, by pushing the boundaries of MS capabilities, may address biological problems that have not been resolved yet.",annualVolume:11414,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/18.jpg",editor:{id:"200689",title:"Prof.",name:"Paolo",middleName:null,surname:"Iadarola",fullName:"Paolo Iadarola",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSCl8QAG/Profile_Picture_1623568118342",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorTwo:{id:"201414",title:"Dr.",name:"Simona",middleName:null,surname:"Viglio",fullName:"Simona Viglio",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRKDHQA4/Profile_Picture_1630402531487",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorThree:null,editorialBoard:[{id:"72288",title:"Dr.",name:"Arli Aditya",middleName:null,surname:"Parikesit",fullName:"Arli Aditya Parikesit",profilePictureURL:"https://mts.intechopen.com/storage/users/72288/images/system/72288.jpg",institutionString:null,institution:{name:"Indonesia International Institute for Life Sciences",institutionURL:null,country:{name:"Indonesia"}}},{id:"40928",title:"Dr.",name:"Cesar",middleName:null,surname:"Lopez-Camarillo",fullName:"Cesar Lopez-Camarillo",profilePictureURL:"https://mts.intechopen.com/storage/users/40928/images/3884_n.png",institutionString:null,institution:{name:"Universidad Autónoma de la Ciudad de México",institutionURL:null,country:{name:"Mexico"}}},{id:"81926",title:"Dr.",name:"Shymaa",middleName:null,surname:"Enany",fullName:"Shymaa Enany",profilePictureURL:"https://mts.intechopen.com/storage/users/81926/images/system/81926.png",institutionString:"Suez Canal University",institution:{name:"Suez Canal University",institutionURL:null,country:{name:"Egypt"}}}]}]}},libraryRecommendation:{success:null,errors:{},institutions:[]},route:{name:"chapter.detail",path:"/chapters/52465",hash:"",query:{},params:{id:"52465"},fullPath:"/chapters/52465",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)}()