Impact of organic farming on biodiversity based on the literature review.
\r\n\tThe purpose of this book is to provide the readers with an understanding of the characteristics of the crisis itself, recognize the wide range and multi-layer of the crisis from a real situation, give ideas on how to minimize the damage, and find ways to increase resilience in the future. To adapt to the rapidly and diversely changing world, the necessary experience and appropriate management for all kinds of crisis issues will be discussed as well. At the same time, it is intended to suggest elements such as verified scientific and empirical knowledge and applicable technologies; more effective risk management operation; modeling of the risks, manuals, management plans, and strategies.
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In last several decades agriculture has been oriented towards industrial and extremely intensive farming practices, aimed at ensuring enough food for the human population, a goal that was not achieved. These types of farming practices also caused several negative environmental impacts such as decreasing biodiversity, including the farm bird index, where a decline has been observed in Slovenia since 2008. Many farms intensified their activities and became highly mechanized, whilst those unable to do so became increasingly marginalized and were sometimes forced to abandon their land, causing equally devastating consequences for biodiversity [1]. Today, it is globally imperative that the growing demand for food be met in a manner that is socially equitable and ecologically sustainable over the long term. It is possible to design farming systems that are equally productive and that maintain or enhance the provisioning of ecosystem services (i.e., biodiversity, soil quality, nutrient management, water-holding capacity, control of weeds, diseases and pests, pollination services, carbon sequestration, energy efficiency and reducing global warming potential, as well as resistance and resilience to climate change and crop productivity) and thus agroecosystem resilience and sustainability [2].
Organic agriculture refers to a farming system that enhances soil fertility by maximizing the efficient use of local resources, while foregoing the use of agrochemicals, genetically modified organisms and the many synthetic compounds used as food additives. The high quality of organic food and its added value relies on a number of farming practices based on ecological cycles, and aims at minimizing the environmental impact of the food industry, preserving the long term sustainability of soil and reducing to a minimum the use of non-renewable resources [3].
Organic farming practices have been promoted as reducing the environmental impacts of agriculture. The results of meta-analysis of studies that compare the environmental impacts of organic and conventional farming in Europe show that organic farming practices generally have positive impacts on the environment per unit of area, but not necessarily per product unit. Significant differences between the two farming systems include soil organic matter content, nitrogen leaching, nitrous oxide emissions per unit of field area, energy use and land use. Most of the studies that compared biodiversity in organic and conventional farming demonstrated lower environmental impacts from organic farming [4]. Furthermore, organic farming appears to perform better than conventional farming and also provides other important environmental advantages such as halting the use of harmful chemicals and their spread in the environment and along the trophic chain, and reducing water use [3]. A life cycle analysis approach calculating the ecological footprint of different productions systems confirmed, respectively, 8.5 and 5.9 times better environmental performance of organic farming practices, compared to their conventional counterparts in winter wheat and spelt production [5].
Biodiversity loss and the degradation of ecosystems have important implications for the environment and are costly for society as a whole [6]. In Europe, loss of plant biodiversity is primarily reflected in the decline of many species of plants and in the disappearing of local and old plant varieties. In 2011, the European Parliament adopted the European Union (EU) Biodiversity Strategy to 2020 with aim of preventing biodiversity loss and the degradation of ecosystems. The strategy includes combating invasive alien species that jeopardize biodiversity and aims also at enhancing the positive contribution of European agriculture, forest and fishery sectors to biodiversity conservation and sustainable use, and to increase by 2020 the EUs contribution to drawing attention to global biodiversity loss [1]. The World Trade Organization notes a crop variety loss of 75% during the past 100 years, even of 90% in the EU. Only 17% of species and habitats assessed under the Habitats Directive have been deemed to be in good status and the degradation and loss of natural capital is jeopardizing efforts for attaining the EUs biodiversity and climate change objectives [7, 4], which did not reach its 2010 biodiversity target [1].
Organic farming is a production method that preserves or even enrich biodiversity at the field level, at the farm level and in the ecosystem as per its regulatory demands, where the objectives of organic farming in EU regulation 834/2007 is noted thus: that organic farming shall pursue to establish a sustainable management system for agriculture with respect to nature\'s systems and cycles, and sustain and enhance the health of soil, water, plants and animals and the balance between them, and to contribute to a high level of biological diversity [5]. Organic farming systems generally harbour larger floral and faunal biodiversity, more so than conventional systems; however, when properly managed, the latter can also improve biodiversity. Importantly, the landscape surrounding farmed land also appears to have the potential to enhance biodiversity in agricultural areas [3]. However, the benefits of organic farming to biodiversity in agriculture landscapes are still being discussed.
Agrobiodiversity is an important aspect of biodiversity that is directly influenced by different production methods, especially at the field level. It can also supply several ecosystem services to agriculture, thus reducing environmental externalities and the need for off-farm inputs. Organic farming is considered an environmentally-friendly agriculture practice and a holistic approach encompassing several demands and bans from a regulatory point of view [8], and receives primarily from European countries additional agri-environmental payments for ecosystem services, including biodiversity. In some countries, payments are available as single biodiversity measures (i.e., hedgerows, insectary strips, crop rotation, or the retention of semi-natural areas) in agri-environmental programmes that are also aimed at conventional agriculture.
The aim of this paper is to establish whether organic farming fulfils the promise of protecting biodiversity better than conventional farming, based on the review of recent publications emphasizing the importance of precisely quantifying the effect of organic vs. conventional farming. Additional to an extensive review, data from the University of Maribor regarding the effects of different production systems on the earthworm population [9] and the biodiversity of weed species from field experiments in the north east of Slovenia [10] were compared with other findings.
The reader is kindly referred to previously mentioned sources [5, 9, 10, 36] for a detailed description of differences between farming systems. For a better general understanding, some details are explained. Earthworms were collected in October 2009, 2010 and 2011 using a mustard aqueous solution as a non-toxic irritant that drove deep burrowing earthworm species to the surface [11]. After measurements were taken, earthworms were returned back to the soil. Analyses were carried out using the Statgraphics Centurion XV statistical program [12]. The biodiversity of weed species [9] was measured using two methods: (i) above-ground weed population sampling; (ii) seedbank sampling. The size of the weed seedbank was determined within the 0 to 0.2 m soil layer of each plot using the greenhouse emergence method [13]. The in situ number of the above-ground weed population per m2 was measured at the end of June or at the beginning of July 2009, 2010 and 2011, after mechanical control and the use of herbicides. Weeds were counted in four 0.25 m2 quadrates randomly located in the centre of each plot, parallel to the working direction of machinery. The weed species were determined when a 2/3 population was at the stages of 2 to 3 true leaves and 1/3 was at the stages of 4 to 5 true leaves. Species diversity was calculated for both seedbank and weed communities using H’ [14].
Results of several research studies and published scientific articles showed that organic farming benefits to the environment, including biodiversity. Comparison of biodiversity in organic and conventional farms has shown that organic farming generally had positive impacts on many species [15]. Results of meta-analyses that compared biodiversity in organic and conventional farms found that organic farms generally have 30% higher species richness and 50% higher abundance of organisms than conventional farms. However, there are wide variations between different studies, which have to be discussed; for example, 16% of studies found a negative effect of organic farming on species richness. Additionally, it was also found that the effect of organic farming on species richness was larger for intensively managed landscapes than for diverse landscapes with many non-crop biotopes [16]. In 327 out of 396 relevant results [17], a higher degree of biodiversity in organic farming was found when compared to conventional farming. In 56 papers (14 %), no difference was verified and in 13 contributions (3%), organic farming yielded less biodiversity (seven of them for soil invertebrates). Significantly, the positive effect of organic farming on biodiversity compared to conventional farming was noticed in 80% of cases; in 16%, differences were unclear and less biodiversity was found in 4% of comparisons (Table 1).
\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t
Rahmann [17] | \n\t\t\t343 | \n\t\t\t10 | \n\t\t\t327 | \n\t\t\t56 | \n\t\t\t13 | \n\t\t
Hole et al. [15] | \n\t\t\t76 | \n\t\t\t9 | \n\t\t\t66 | \n\t\t\t25 | \n\t\t\t8 | \n\t\t
Pfiffner [18] | \n\t\t\t44 | \n\t\t\t7 | \n\t\t\t49 | \n\t\t\t5 | \n\t\t\t1 | \n\t\t
Sum | \n\t\t\t\n\t\t\t | \n\t\t\t | 442 | \n\t\t\t86 | \n\t\t\t22 | \n\t\t
Share (%) | \n\t\t\t\n\t\t\t | \n\t\t\t | 80 | \n\t\t\t16 | \n\t\t\t4 | \n\t\t
Impact of organic farming on biodiversity based on the literature review.
1 Multiple citations of used studies are possible due to different conclusions for different species or multiple answers; 2 biodiversity indicators i.e., flora, weeds, soil biota, earthworms, pollinators, birds, etc.
On average, organic farming increased species richness by about 30%. This result has been robust over the past 30 years of published studies. Organic farming had a greater effect on biodiversity as the percentage of arable fields of the landscape increased, that is, it is higher in intensively farmed regions [19]. Thus, it may be concluded that organic farming produces more biodiversity. Research gaps still exist for the understanding of functional biodiversity and ecosystem impact, which comprise soil biota, landscape (ecosystem and habitat) and genetic biodiversity on agricultural land in natural habitats [17]. The majority of current studies are from Northern and Western Europe and North American agriculture practices, while other regions with large areas of organic farming have been poorly investigated. Comparison between paired organic and conventional fields in India assessed a wide range of taxa (plants, soil microbes, earthworms, butterflies, dragonflies and other arthropods, reptiles, molluscs, amphibians/frogs and birds) trough different methods that showed similar trends. Habitat area, composition and management of organic fields were likely to favour higher levels of biodiversity by supporting higher numbers of species, dominance and abundance across most taxa. Organic fields are systems that are less dependent on external inputs to restore and rejuvenate the environment, resulting in higher biodiversity that promotes higher sustainable production on a long-term basis [20]. The effects of time since conversion to organic farming on species richness and abundance have been poorly researched. Plant and butterfly species richness was 20% higher on organic farms and butterfly abundance was about 60% higher, compared to conventional farms. Time since conversion to organic farming affected butterfly abundance gradually over a 25-year period, resulting in a 100% increase; however, no effect was found on plant or butterfly species richness, indicating that the main effect took place immediately after the conversion to organic farming [21].
Three recent multiregional studies from Europe have also demonstrated the negative effects of both agricultural intensification (increased use of synthetic fertilizers and pesticides combined with the reduced use of diversified farming system techniques) and landscape simplification on components of biodiversity [2]. The EU Biodiversity Strategy to 2020 also focuses on sustainable farming and forestry as the focus of one of six targets in the form of improving the integration of biodiversity conservation into key policies for agriculture and forestry. Combined, these two sectors include almost 72% of land in the EU and play a major role in Europe’s biodiversity [1].
Crop rotation brings biodiversity in the time scale. It is mandatory on organic farms and is stated as a method to maintain and increase the fertility and biological activity of the soil, and means the prevention of damage caused by pests, diseases and weeds [8]. Due to more diverse crop rotation and the use of green manure and intercroppings on organic farms, there is also greater biodiversity. Furthermore, using domestic populations of seed varieties preserves biodiversity, but the production of alternative crops (rare, underutilized, disregarded, neglected or new) increase biodiversity at the filed level [22].
The biodiversity of weed communities in agro-ecosystems provides several valuable ecological functions [23]. Conventional and integrated production systems tend to be similar in both intensity of management and within-field biodiversity, but organic production tends to support greater density, species number and biological diversity in comparison with other investigated production systems [24]. At the field level, species richness was the greatest on organic farms where there was a greater abundance of weeds [24-27, 31; organic production system had the highest biodiversity of weed species [28-31]. Organic agricultural practices yielded more weed species in root crops, red clover/grass mixtures and in winter triticale. Weed species richness was reduced in red clover/grass stands, while root crops and spring barley undersown with red clover and grasses decreased weed species diversity, which is also important for achieving higher yields in an organic production system. The species composition and in particular the quantitative structure of weeds were affected more by crop species and cultivation regime, compared to different agriculture practices (organic vs. integrated). Weed communities of crops grown using organic and integrated farming systems were more similar in terms of species composition than quantitative structure [30].
The maintenance of a diverse weed community is one step towards the sustainability of an agro-ecosystem through improved nutrient cycling and pest control, improved soil chemical and physical properties, and the reduction of soil erosion. An important aspect in the evaluation of the environmental impact of production systems is the biodiversity index for weed species (Table 2). Using the Shannon-Weaver diversity index for weeds of different production systems (conventional, integrated, organic) growing white cabbage and red beet showed that the biodiversity index was significantly higher in organic systems (0.86 in organic vs. 0.66 in conventional systems for cabbage and 0.81 in organic vs. 0.59 in conventional for red beet). Using ecological footprint calculation for the evaluation of different production systems showed that organic farming had the lowest impact on the environment. In the case of white cabbage and red beet production, ratio in ecological footprint between organic and conventional production was 1 to 3.5 [10].
The emerged weed flora is more affected by recent agrochemical inputs than the seedbank, which is buffered by the persistence of weed seeds in the soil. The seedbank is more strongly influenced by soil characteristics, such as the percentage organic carbon and percentage total nitrogen than by management [26]. The same weed species were in the seedbank and at field counted as germinated weeds, totalling 29 weed species in the survey (Table 2). The accumulated number of observed species pooled over fields was highest in the organic production of white cabbage and red beet, with 29 and 28 species, respectively. Within the conventional crop rotations, 18 species were observed in the cabbage field and 17 in the red beets field, while 20 and 19 were observed in the integrated crop rotation for cabbage and red beets. The differences in the number of weed species between conventional and integrated fields for cabbage were not significantly different; however, the difference when comparing organic and conventional fields was significantly different for both vegetables. For red beet, differences among all production systems were significant, which is contrary to the findings of [30], where weed communities of crops grown under organic and integrated farming systems were similar with regard to species composition but not quantitative structure. Different farming practices (described as organic, integrated and conventional) appeared to exert selection pressure on the species composition of the seedbank, building up different communities under the three farming systems over time [26]. These effects were scale dependent. At a within-field scale, species richness was greatest in organic farms, where there was a greater abundance of weeds; this was similar to our results and those of many others [24-31]. These results suggest that weed species diversity can be promoted by using organic cropping practices [31].
\n\t\t\t | \n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t | ||
\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t
Control Conventional Organic Integrated Biodynamic | \n\t\t\t0.38d 0.66c 0.86a 0.74b - | \n\t\t\t14c 18b 29a 20b - | \n\t\t\t0.32d 0.59c 0.81a 0.64b - | \n\t\t\t13c 17b 28a 19b - | \n\t\t\t11.58b 11.25b 22.41a 13.00b 24.00a | \n\t\t
Shannon-Weaver diversity index (H\') and the frequency of occurrence (O) of weed species from the 30 species present in white cabbage and red beet in different production systems [10],3 and the influence on earthworm population [9, 36].
a-d Mean values followed by different letters within a column are significantly different (Duncan, α=0.05)
Organic farming systems are generally associated with increased biological activity and increased below-ground biodiversity. The main impacts on biological fertility do not result from the systems per se, but are related to the amount and quality of the soil organic matter that is used in the farming system, as well as the disruptions of soil habitat using different tillage tools. Even within the constraints of organic farming practices, it is possible for farmers to make changes to management practices using less tillage, which will tend to improved soil biological quality [32]. An important part of soil biodiversity is arbuscular mycorrhizal fungi, which can provide several benefits to plants and ecosystems. Organic farming enhances arbuscular mycorrhizal fungi, communities of which are similar in organically managed fields and in semi-natural species-rich grasslands; however, significantly less communities are found in conventionally managed fields. Their richness increased significantly over time since conversion to organic agriculture [33]. Soil microorganisms and other parts of soil biota including earthworms are also important drivers of soil fertility. Organic farming is based on the principle of the maintenance and enhancement of soil life and natural soil fertility, soil stability and soil biodiversity for preventing and combating soil compaction and soil erosion, and for the nourishing of plants primarily through the soil ecosystem [8]. Furthermore, our research results investigating the number and mass of earthworms as an indicator of soil biodiversity confirmed the effects of different production systems (conventional, integrated, organic, biodynamic) on the population of earthworms following the harvesting of different crops [9].
The studied production systems significantly influenced total earthworm population (Table 2) and small earthworms [36]. Both were shown to be higher in number in the biodynamic and organic production systems compared to the control, conventional and integrated production systems. When compared to control plots, as well as those managed without fertilizers and plant protection agents, there were roughly 2.7 and 2.5 times more small earthworms in biodynamic and organic production systems, respectively. In the same manner, the total earthworm population in the biodynamic production system was 207% and in the organic production system, 193% of this was counted for the control treatments. Similarly, the beneficial effect of organic farming on earthworms has been emphasized by other investigations [34, 35]. The abundance of earthworms, as well as their total body mass, was affected by plant species occurring in crop rotation. Oil pumpkins were revealed to have a beneficial effect on earthworms. There was also a significant production system and plant species interaction concerning the population of small earthworms [36]. In addition to a production system, tillage is also a major driver for altering communities of earthworms and microorganisms in arable soils. The use of reduced tillage provides an approach for eco-intensification by enhancing inherent soil biota functions in organic arable farming [37].
Biodiversity, as one of the most important ecosystem services of organic farming, is firmly connected to biocontrol and pollination services [2]. While the field of organic crop production has increased globally, the potential interactions between pest management in organic and conventionally managed systems have to date received little attention [38]. Organic agriculture improves biodiversity at the field level, but potential interactions with the surrounding landscape and the potential effects on ecosystem services are less well known. Predation of aphids was the highest in organic fields in mixed landscapes and lower in more uniform surroundings. The results of comparing 153 farms from five countries showed that organic agriculture improved the biodiversity of plants and birds in all landscapes, but only in more diverse surroundings did it improve the potential for biological control. Contradictory results showed the necessity for taking into consideration production methods (organic vs. conventional) and regional landscape complexity for developing agri-environmental schemes for the future [39]. Organic farming is one of the most successful agri environmental schemes, as humans benefit from high quality food and farmers from higher prices for their products; additionally, this approach often successfully protects biodiversity. Based on the assessment of 30 triticale fields (15 organic vs. 15 conventional) and the comparison of five conventional fields that were treated with insecticides and 10 non-treated conventional fields, it was found out that organic fields had five times higher plant species richness and about 20 times higher pollinator species richness compared to conventional fields. In contrast, the abundance of cereal aphids was five times lower in organic fields, while predator abundances were three times higher and predator-prey ratios 20 times higher in organic fields, indicating a significantly higher potential for biological pest control in organic fields [40]. Aphid density was also significantly lower in organic wheat fields compared to conventional fields, based on the assessment of 216 wheat fields during a two-year study [41]. Another positive impact of crop genetic diversity where wheat is concerned was found on below (collembola) and aboveground arthropod (spiders and predatory carbides) diversity at the field scale, which may be the result of a wider variety of food resources or more complex crop architecture. Increasing crop genetic diversity can therefore be an easy-to-implement scheme for benefiting farmland biodiversity [42].
Despite decades of European policy to ban harmful pesticides, the negative effects of pesticides on wild plant and animal species are nonetheless present and can be observed through losses pertaining to biodiversity. Chemical pesticides minimize opportunities for biological pest control. If there is an aim for biodiversity to be restored in Europe, opportunities should be created for crop production utilizing biodiversity-based ecosystem services such as biological pest control; what is needed is a Europe-wide shift towards farming employing the minimal use of pesticides over large areas, not only on organic farming areas [43]. Insecticide treatment in conventional fields had only a short-term effect on aphid densities, while later in the season, aphid abundances were even higher and predator abundances lower in treated compared to untreated conventional fields. Preventative insecticide application in conventional fields has only short-term effects on aphid densities but long-term negative effects on biological pest control. Therefore, conventional farmers should restrict insecticide applications to situations where thresholds for pest densities have been reached. Organic farming increases biodiversity, including important functional groups like plants, pollinators and predators, which in turn enhance natural pest control [40].
Biodiversity supplies multiple ecosystem services to agriculture. In addition to the potential for biological pest control, pollination problems are a topic now also being addressed in EU agriculture policy [43]. Declines in insect-pollinated plants and their pollinators have been reported as a result of agricultural intensification [44]. Reducing farming intensity with conventionally managed leys does not seem to be as effective as organic farming for delivering crop pollination services [45]. The abundance of pollinators was more than 100 times higher on organic fields. Plant and pollinator species richness, as well as predator abundances and predator-prey ratios, were higher at field edges compared to field centres, highlighting the importance of field edges for ecosystem services [40].
Pollination systems within intensive grassland communities may be different from those in arable systems. Results from comparing plant community composition among 10 pairs of organic and conventional dairy farms indicate that organic management increases plant richness in field centres, but that landscape complexity exerts a strong influence on both organic and conventional field edges. Insect-pollinated forb richness showed positive relationships to landscape complexity, reflecting what has been documented for bees and other pollinators [44].
Hedges provide important nesting, feeding and sheltering sites for birds in agricultural areas, while organic farming also enhances the environments of farmland birds [15, 18, 46]. However, little is known about how the interaction of (the amount of) hedges and variables pertaining to the organic management of the landscape scale affects birds. Birds were surveyed in the fields and in the adjoining hedges on conventional and organic winter wheat fields and meadows. More bird species occurred in organic than in conventional fields, regardless of land-use type. Hedge length had a much stronger effect on bird richness than organic farming practice. The interaction of landscape complexity and hedge length was found to be connected. Hedge length enhanced bird richness only in the case of simple landscapes. In more complex landscapes, the local effect of hedge length levelled off, because bird richness was high even without local hedges. Adding hedges or introducing organic farming practices should be primarily promoted in simple landscapes, where it particularly makes a difference for biodiversity [46].
The effect of organic farming differs depending on the scale of uptake of a particular landscape. The local effect of organic farming was found to be consistently strong, with higher diversity in borders adjoining organic fields, most likely due to the lack of herbicides used on organically managed farmland. In addition to the proportion of semi-natural habitat, which is important for farmland biodiversity, the management practice of cropland can also influence diversity in semi-natural habitats. Forb richness, which was evaluated as an agri-environmental indicator for biodiversity was also higher within borders situated in landscapes with a high proportion of organic land, irrespective of local management; this was possibly as a result of the dispersal of primarily annual plant species from the organically managed fields into the borders (mass effect). Farming practice at a local and a landscape scale can independently influence plant species richness, indicating that organic farming can also influence diversity at larger spatial scales, as well as outside organically managed land [47]. Organic farming enhances species richness and the abundance of many common taxa, but its effects are often species specific, as well as trait or context dependant. Landscape enhances or reduces the positive effects of organic farming, or acts through interactions where the surrounding landscape affects biodiversity differently on organic and conventional farms [48].
Around the world, small farms are those that practice high-diversity agriculture. Small farmers often choose to cultivate several varieties of the same crop; additionally and perhaps more importantly, different farmers in a given locality often cultivate different varieties. On the other hand large farms usually sow a single variety over a wide area [49]. Small farms may in this way have an indirect, positive effect on biodiversity, since these farms normally have smaller land parcels and thus more field edges, which are relatively species-rich. Although the average organic farm is bigger in the EU than its conventional counterparts [50] and in some cases is “conventionalized”, organic farming is nonetheless generally viewed as small farms. The world\'s majority of food is produced by smallholder farmers who grow over 70% of all our food. Organic farming on small farms leads to an increase in food production and to greater benefits for the ecosystem by improving soil organic matter, reducing erosion and increasing biodiversity. At the same time, organic farming also allows farmers to receive higher prices for their value-added produce and provide them with opportunities to export to markets niche [51]. The report of a study focusing on farming systems in Africa showed that it is possible to set broad priorities for agricultural intensification based on the organic principles of health, ecology, fairness and caring for the earth. Ecological principles and technologies can be used to support farmers in obtaining food security and improving their livelihoods without destroying the local indigenous biodiversity [52].
Agricultural intensification has caused significant declines in biodiversity, while the profound intensification of European agricultural practices in the past number of decades continues. This is due to decreasing crop diversity, simplification of cropping methods, the use of fertilizers and pesticides and the homogenization of landscapes, all of which have negative effects on biodiversity in agricultural areas. Agricultural management practices can have a substantial positive impact on the conservation of the EUs wild flora and fauna. Agri-environmental schemes including organic farming are thought to benefit biodiversity. Agri-environmental payments are part of Common agriculture policy, which promotes the multifunctional role of farming as a provider of food products and a steward of diverse landscapes, as well as the cultural and natural heritage of rural areas. Furthermore, in the future, according to the EU regulation 1305/2013, each member state has to introduce agri-environmental measures for enhancing biodiversity and the preservation of high nature value farming and forestry systems [53]. Ecosystem services payments must be based on a standardized and transparent assessment of the goods and services provided. This is especially relevant in the context of EU agri-environmental programmes, but also for organic-food companies that foster environmental services on their contractor farms [54].
Agri-environmental schemes have been introduced to minimize the effects of agricultural intensification and enhance farmland biodiversity, but evaluations have produced inconsistent results [47]. Biodiversity is in different countries supported by different measures (i.e., strips and hedges, crop rotation, autochthone varieties, Nature 2000 measures), as is organic farming, which enhances the species richness and abundance of above and below soil taxa [15-20]. Traditional farming contributes to the safeguarding of certain natural or semi-natural habitats. Many valuable habitats and the presence of species have a direct interdependence with agriculture (e.g., many bird species nest and feed on farmland). Two major changes have contributed to upsetting the delicate balance between agriculture and biodiversity: (i) specialization and intensification of certain production methods (such as the use of more chemicals and heavy machinery); (ii) marginalization or abandonment of traditional land management, a key factor in preserving certain habitats and site-specific biodiversity. In some EU member states, land abandonment and the withdrawal of traditional management may become a threat to biodiversity on farmland. Therefore, preventing these processes is a key action for halting the loss of biodiversity. The Common agricultural policy addresses the preservation of habitats and biodiversity by specific rural development measures targeted at the preservation of habitats and biodiversity (agri-environmental and Nature 2000 payments), as well as requirements included in the scope of cross compliance for birds and habitats [55].
Agri-environmental payments to farmers for the conversion from conventional to organic farming or remaining inorganic should encourage them to participate in schemes, thereby responding to the increasing demand by society for the use of environmentally-friendly farm practices and also for high standards of animal welfare, as is the case in organic farming. In order to increase synergy in biodiversity and the benefits delivered by the organic farming, other measures should also be promoted and supported among organic farmers in order to cover larger areas or other protected areas, e.g., Nature 2000 [53].
In agricultural landscapes, farmers have a large impact on biodiversity through the management decisions and agricultural practices that are used on their farms. Farmers\' perceptions of biodiversity and its different values influence their willingness to apply biodiversity-friendly farming practices. Organic and conventional farmers\' perceptions of the different values of biodiversity were analysed across three European countries. Farmers\' perceptions of biodiversity were strongly connected to their everyday lives and linked to farming practices. In addition to recognizing the importance of variety, species and habitat diversity, farmers also acknowledged wider landscape processes and attached value to the complexity of ecological systems. It was found that organic farmers tended to have a more complex and philosophical approach to biodiversity, with little differences being observed between these farmers; conventional farmers, on the other hand, exhibited more differences among themselves. Furthermore, ethical and social values were important for all farmers, but economic value was more important for conventional farmers, which has an impact on their behaviour [56].
Based on a survey among organic and conventional farmers, it was concluded that they had similar attitudes to farming results and to the environment; however, organic farmers were better informed about environmental issues and carried out more environmentally-friendly practices and behaviours. More biodiversity was found on environmentally-friendly orientated farms and less on high production-orientated farms. Organic farmers with more positive attitudes to the environment and who were better informed about environmental topics had higher biodiversity on their farms compared to others. Although there were disparities between attitudes and actual behaviours in relation to the environment among organic farmers sharing similar attitudes to conventional farmers, they were more prepared to inform themselves about and carry out environmentally-friendly farming. Results of the comparison study showed that biodiversity benefitted more from organic farming and environmentally- oriented farmers, and that there is an important link between farmers\' environmental attitudes and knowledge and the beneficial effects of organic farming on biodiversity [57].
Farmers strongly acknowledged ethical and social biodiversity values. This suggests that soft policy tools can also foster biodiverse-sensitive farming methods that are complementary to mainstream monetary incentives [55]. As farmers receive a majority of agri-environmental payments, they can be more involved in data generation and conservation management. Farm size is very important in terms of the amount of payments that are provided per hectare and for improving biodiversity on a bigger scale. A standardized model for measuring on-farm biodiversity does not yet exist in practice. Performance indicators should be focused on and farmers should be included in generating this information. A framework is needed for assessment of the results and for management measures that can be employed on farms. Another requirement is ease of application, which encompasses the simplicity of gathering input data and its clarity to those farmers who will apply it [54]. Conservation-oriented thinking and better environmental education among farmers should be encouraged for those who already participate in an agri-environmental scheme and even more so amongst newcomers. In this way, the benefits of the agri-environmental schemes for the environment can be maximized [57].
An open source farm assessment system was prepared for the assessment of biodiversity including biotopes, species, biotope connectivity and the influence of land use. Interviews with the test farmers showed that the assessment methods can be implemented on farms and that they were understood by farmers [54].
The analysed data showed that in the past decades, the specialization and intensification of agriculture production methods have had negative effects on biodiversity. The future holds the challenge of designing more sustainable farming systems that are productive and maintain or enhance the provision of ecosystem services, including biodiversity. The significantly positive effect of organic farming on biodiversity compared to conventional farming was noticed in 80% of cases; in 16%, differences were unclear and less biodiversity was found in 4% of comparisons [15, 17, 18], where seven to 10 biodiversity indicators were taken into account. Small farms in particular may have an indirect positive effect on biodiversity. These farms generally have smaller land parcels and thus more field edges, which are relatively species-rich.
We can conclude that the benefits of organic farming on biodiversity are as follows:
Organic farming increased species richness by about 30% and had a greater effect on biodiversity, as the percentage of the landscape consisting of arable fields increased. It was found that organic fields had up to five times higher plant species richness compared to conventional fields. For example, plant and butterfly species richness was up to 20% higher on organic farms and butterfly abundance was about 60% higher. After the conversion from conventional to organic farming abundance of butterflies was increased for 100%. Organic farming enhanced arbuscular mycorrhizal fungi and its communities. This was similar in organically managed fields and in semi-natural species rich grasslands, but significantly fewer communities were found in conventionally managed fields. Their richness increased significantly over time from the point of a conversion to organic agriculture.
The occurrence of weed species was significantly higher in the organic production of white cabbage and red beet compared to integrated and conventional production. The biodiversity index was significantly higher in organic production compared to the conventional method, 0.86 vs. 0.66 for cabbages and 0.81 vs. 0.59 for red beets. Conventional and integrated production systems tended to be similar both in terms of the intensity of management and regarding within-field biodiversity; however, organic production tended to support greater density, species number and biological diversity compared to other investigated production systems.
Earthworms were more abundant on organically managed fields. In organic and biodynamic farming plots, the number of earthworms was on average two times higher compared to integrated, conventional and control plots.
Biodiversity as one of the most important ecosystem services of organic farming is firmly connected to biocontrol and pollination services, which are enhanced when using no or less chemicals. The abundance of cereal aphids was five times lower in organic fields, while predator abundances were 20 times higher in organic fields, indicating a significantly higher potential for biological pest control in organic fields. Organic fields had 20 times higher pollinator species richness compared to conventional fields. Pollinators and predator abundance was higher at field edges compared to field centres, highlighting the importance of field edges for ecosystem services. Edges provide important nesting, feeding and sheltering sites for birds in agricultural areas. Thus, organic farming enhances farmland birds.
Overall, organic agriculture appears to perform better than conventional farming and provides important environmental advantages such as halting the use of harmful chemicals and their spread in the environment and along the trophic chain, reducing water use, as well as reducing carbon and ecological footprints. As we have underscored, organic farming fulfils the promise to protect biodiversity better than conventional farming. However, in the European commission document, The EU Biodiversity Strategy to 2020 [1], organic farming is not even mentioned, while in the European Parliament resolution regarding the strategy [6], organic farming is mentioned only once in the context of a call for a strengthening of Pillar II and for drastic improvements to the environmental focus of that pillar, and to the effectiveness of its agri-environmental measures. Supporting farmers to convert their properties to organic land and to maintain organic farming within the scope of agri-environmental schemes as a part of Common agriculture policy can have a significant impact on biodiversity as a result of management decisions farmers apply to their agricultural land.
The results presented in this paper are in part an output of the national research project J4-9532: "The quality of food dependent on the agricultural production method", funded by the Ministry of Higher Education, Science and Technology of the Republic of Slovenia and Slovenian Research Agency.
Since the Federal legalization of cannabis medicines in Australia in 2016, cannabis has rapidly moved from being a recreational drug to a medicinal product. While it shows great therapeutic promise, one of the issues faced by clinicians in prescribing cannabis is the limited information available from high quality clinical trials across a broad range of indications. In order to generate this evidence, collaboration and sharing of knowledge between all stakeholders will be required to progress quality clinical trials of cannabis medicines. This paper discusses several issues that investigators have found when designing clinical studies using cannabis medicines as investigational products. These include cannabis medicine selection according to the indication(s) being studied, dosage form, dose range, drug-drug interactions, regulatory considerations, purchase and supply, purity and consistency of plant-based products, and industry engagement.
Over 120 phytocannabinoids have been identified in Cannabis sativa L. that have a diverse range of molecular targets [1]. Consideration of the type of cannabinoid and its pharmacokinetics and pharmacodynamics is important when selecting products for clinical trials [2]. To date, research has focused heavily on cannabidiol (CBD) and ∆-9-tetrahydrocannabinol (THC). Cannabis medicine clinical trials can be located on clinical trial registries, such as the Australian New Zealand Clinical Trials Registry (ANZCTR), ClinicalTrials.gov and WHO International Clinical Trials Registry Platform (ICTRP) [3, 4, 5]. The selection of cannabis medicines for a particular indication in the context of a clinical trial requires researchers to consider several different factors.
Some trials have investigated a combination of cannabinoids. For example, in palliative care [6] and glioblastoma [7], THC and CBD have been trialed in the ratios of 1:1 and 4:1, respectively. Trials of CBD alone have been conducted in anxiety and schizophrenia [8] and refractory epilepsy (Dravet syndrome and Lennox-Gastaut syndrome) [9]. Nabiximols, an oral spray containing roughly equal parts CBD and THC and marketed under the trade name Sativex, has been studied in spasticity in multiple sclerosis [10], cannabis dependence [11], and neuropathic pain [12]. Dronabinol, an entirely synthetic form of THC has been trialed for anorexia and weight loss in patients with acquired immune deficiency syndrome [13] while dronabinol and nabilone, also a synthetic cannabinoid that is similar to THC but appears to be more potent, have both been studied in treatment-refractory chemotherapy-induced nausea and vomiting [14]. Dementia studies have trialed THC, dronabinol, and nabilone [15].
These are only a few examples of numerous trials for different clinical indications and disease states. Many of these studies have had mixed results suggesting that proposed clinical trials, especially for diseases not already studied will require a thorough examination of in vitro and preclinical work to inform the selection of the cannabinoid formulation most appropriate for the disease under study.
To this end, there is an abundance of in vitro and in vivo studies being conducted on a variety of cannabinoids and in different formulations that over time, will help identify the principal components required of a cannabinoid for the disease being targeted [1]. As always, a detailed literature search is essential.
Several factors need to be considered when selecting a cannabis medicine for use in a clinical trial. Key features include the age of the patient cohort where participants may have limited dexterity in handling certain formulations, likely comorbid conditions that may affect drug absorption, and manufacturers\' ability to create a placebo that looks, tastes, and smells the same as the investigational product.
Several different dosage formulations can be selected. Table 1 describes the potential advantages and disadvantages of common dosage forms of cannabis medicines that may be considered for use in a clinical trial. Less common dosage forms such as rectal, vaginal, and intravenous are not discussed as they are generally less practical forms for a clinical trial in comparison with the forms discussed below [16].
Route of delivery | Dosage Form | Advantages | Disadvantages |
---|---|---|---|
Inhaled | Smoked or vaporized |
| |
Sublingual | Sprays, oils, tinctures, wafer |
|
|
Oral | Capsules, tablets, oils, tinctures |
|
|
Topical | Creams, patches |
|
Advantages and disadvantages of common dosage forms of Cannabis medicines when used in a clinical trial setting.
Currently, dosing information is only available for approved cannabis medicines, dronabinol, nabilone, nabiximols and Epidiolex (CBD). For unregistered cannabis medicines, there is no precise dosing recommendation. Pharmacokinetic variability of cannabinoids is very high both among and between cohorts and hence, dosing is highly individualized and dependant on the patient’s condition [21, 22]. Generally, the approach for cannabis dosing is to start low and go slow. The patient should be started on a low dose and gradually titrated until a therapeutic effect without any undesired side effect is achieved [23, 24, 25, 26].
Most patients take oral cannabis medicines 2–3 times per day. Epidiolex, a cannabis-derived form of CBD, is taken twice daily with a starting dose of 5 mg/kg/day up to a maximum dose of 20 mg/kg/day [27], while nabiximols is taken as 4 to 8 sprays/day (1 spray is equivalent to 2.7 mg THC and 2.5 mg CBD) up to a maximum of 12 sprays/day [28]. Frequency is dependent on the duration of action, which is in the order of 3–4 hours for inhaled products and 8–12 hours for oral products.
THC-dominant products can be taken at bedtime for days 1–2 to minimize undesirable daytime side effects such as dizziness or drowsiness and encourage tolerance of doses beginning at 2.5 mg of THC. If the dose is tolerated, the dosing can be doubled every 1–2 days until any undesired side effect(s) are experienced. In this event, patients are advised to revert to their previous dose [23].
CBD dominant products can be used at higher concentrations than THC products because they produce fewer adverse effects. Doses of CBD between 1 and 50 mg/kg/day improve psychotic symptoms, seizures, and anxiety [29]. An average CBD dose of 15 mg/kg/day showed positive significant reductions of seizure while CBD between 150 and 600 mg/day produced therapeutic effects in social anxiety disorder and insomnia. The maximum tolerated dose for CBD in humans is 1500 mg/day [30]. This data shows that CBD-dominant products have a higher therapeutic index than THC-dominant products. Patients are advised to keep a journal of their cannabis medicine dosing together with a record of their symptoms to aid in determining the optimal CBD dose for their particular condition.
There is variable evidence indicating other drugs interact with cannabis medicines, ranging from hypothetical concepts to documented clinical trial evidence [31, 32]. Interactions among drugs is particularly relevant in trials where a variety of pharmacologic products is being investigated. Drug-drug interactions may increase the active concentration of cannabinoids, enhancing the possibility of adverse effects, or they may decrease cannabinoid concentrations, compromising their physiologic effects [33]. The converse effect might be expected from the competing drug.
Examples of drug-drug interactions include blood pressure-lowering medications, warfarin [33], antiepileptic drugs (e.g. clobazam) [34], and central nervous system depressant medications, including opioids and benzodiazepines [35]. Researchers should keep in mind that drug-drug interactions can occur with cannabis medicines.
Clinical trials place stringent demands upon the availability of precise and reproducible formulations of the medicines under study. Unfortunately, the quality and consistency of supply of many cannabis medicines are not of a standard that would facilitate their use in most clinical trials. Indeed, while plant genetics can be tightly regulated through cloning techniques to minimize variability amongst cannabis plants, multiple factors can still alter the phytochemical profile of plant-based medicines, including environmental factors, time of harvest, manufacturing processes and storage conditions (reviewed in [36]). In Australia, to overcome this the Therapeutic Goods Administration (TGA) has introduced guidelines for cannabis medicines and more recently the U.S. Food and Drug Administration (FDA) has also introduced guidelines [37, 38]. Cannabis medicines used in clinical trials must align with the existing framework for the use of medications in clinical trials, and meet the requirements for human use of cannabis medicines set by the local regulator e.g. FDA, European Medicines Agency (EMA), TGA [39, 40, 41]. Local pharmaceutical, prescribing and holding regulations, approvals, and requirements for labelling, transport, and storage of investigational medicinal product for use in a clinical trial must also be confirmed prior to selecting and purchasing a product for a clinical trial [42, 43, 44].
Australia’s TGA approves the use of medicines in a clinical trial through their Clinical Trial Notification (CTN) scheme [41, 45]. Prescribed cannabis medicines must conform to Therapeutic Goods Orders No. 93 (Standard for Medicinal Cannabis) (TGO 93) and TGO 100 (Microbiological quality of medicinal cannabis products), among others [37, 46, 47]. Adherence to Good Manufacturing Process (GMP), and to federal and state pharmacy regulations, policies, and their respective drugs and poisons legislation is required [48, 49, 50, 51, 52]. Where the manufacture of cannabis medicine products will form part of a clinical trial, a license authorising manufacture for clinical trial use must be in place between the manufacturer and the TGA [44, 53].
Following product feasibility, risk review, and final selection, supply contracts should be developed for the purchase of the product(s) for the clinical trial, to document agreed requirements, roles, and responsibilities including:
Formulation (dose, volume, and form)
Packaging and labeling requirements (if required) must comply with Pharmaceutical Inspection Convention and Pharmaceutical Inspection Co-operative Scheme (PIC/S) Annex 13 [43, 44]
Consistency of supply (i.e. volume, consistency and purity of product supplied across the duration of the clinical trial) with an agreement to provide certificates of analysis with each batch to ensure purity and consistency in phytochemical profile
Availability of stock
Cost
Any regulatory fees, import permits as required, shipping costs
Insurance and indemnity
Access to data if appropriate (this may be an ethics committee decision)
Pharmacovigilance reporting responsibilities
Confirmation that all products under trial will meet and be maintained in compliance with International Conference for Harmonisation of technical requirements for pharmaceuticals for human use Good Clinical Practice (ICH- GCP) R6E2 requirements
An essential consideration of any cannabis clinical trial is the stability of the cannabis medicines and the robustness both of their supply chain and the methods used to assess their stability [54]. It is imperative that any medication under study is available via a reliable and continuous supply for the duration of the study and for any ethically approved post-study period. This is particularly important when utilizing plant-based sources that can have inherent variability compared to chemically-synthesized medicines of mainstream pharmaceutical products.
As the legal production of GMP-certified cannabis medicines that are suitable for clinical trials is limited to certain countries, securing appropriate supply may involve transportation across international and state borders. Export and import logistics, licensing, permits, and quarantine requirements may be a consideration to ensure adequate supply in a timely manner for the trial.
A diverse stakeholder cohort underpins all clinical trials. In cannabis research, most stakeholders—clinicians, researchers, regulatory bodies, and the medicinal cannabis industry—support the need for robust clinical evidence that informs the use of cannabis derived therapeutics. In Australia as in other countries, cooperation amongst stakeholders is essential to ensure the challenges associated with a complex regulatory environment are appropriately addressed. Furthermore, stakeholders have the responsibility of managing industry expectations and delivering a level of patient recruitment that leads to successful clinical trials as well as fostering more efficient and effective collaborations.
A lack of global consistency on quality standards presents a different challenge. Establishing collaborations and implementing common agreements with local industry provides a framework to share knowledge especially when accessing the GMP cannabis medicines produced in Australia. Moreover, importation of products for clinical trials requires authorization, first from the country to which the product will be imported and subsequently from the country from which the product will be exported. Industry stakeholders may be highly responsive and supportive, but response timelines of regulators on both ends of the importing process can be prolonged and unreliable and may impact continuity of supply for longer-term trials. In addition, the requirement to comply with local standards that are geographically specific and often unique to cannabis medicines, means that the supplier must be both willing and capable of meeting those standards. In practical terms, this requirement can constrain a research team to source cannabis medicines only from companies with an established local operation with experience in the current regulations. Without this experience the impost of ensuring compliance shall fall either on the supplier or the research project and is likely to be cost-prohibitive.
The design of clinical trials for cannabis medicines is a complex process. Before embarking on a clinical trial, researchers need to have a clear understanding of the potential therapeutic benefit cannabis medicines may have. This understanding will inform the selection of cannabis product, the formulation of the product and the dose to be tested. Researchers must also be aware of regulations that are applicable where the research is to be undertaken as well as regulations that may be imposed at the source of the cannabis product. The phytochemical consistency of plant-derived products can be solidified with further research and may assist the approval of additional botanical products to the cannabis medicines market, increasing options for clinicians and patients, as plant-based products may be preferred to chemically-synthesized or bioengineered medicines [55]. Importantly, collaborations with industry are key to the successful outcome of cannabis medicines clinical trials. Without significant investment and sponsorship of clinical trials, the ability to generate quality data will be limited and the evidence for cannabis medicines to be registered as therapeutics lacking. Collaborations between researchers, industry and regulators, working together in sharing knowledge will generate high quality cannabis medicines research.
We would like to thank the members of the Australian Centre for Cannabinoid Clinical and Research Excellence (ACRE) Guidance Writing Group for Clinical Trials in Cannabinoids: Selection, Purchase and Supply of Cannabis Medicines as Study Drugs in Clinical Trials members Prof Janet Hardy (Mater Cancer Care Centre) and A/Prof Phillip Good (Mater Cancer Care Centre) for their contribution to the development of this paper.
Author Disclosure Statement
Dr Peter Galettis, Dr Rachel Galettis and Mrs Courtney Hill are part of the Australian Centre for Cannabinoid Clinical and Research Excellence (ACRE), which is funded through the National Health and Medical Research Council’s Centres of Research Excellence Program. ACRE also receives funding through NSW Health’s Clinical Cannabis Medicines Program.
John Barlow is a consultant to Applied Cannabis Research.
Jaroslav Boublik is Chief Science Officer of LeafCann Group Pty Ltd, a privately held Australian federally licensed medicinal cannabis production company.
Myfanwy Graham is funded through NSW Health’s Clinical Cannabis Medicines Program.
Melinda Thompson is an alternate board member for the Medicinal Cannabis Industry Australia (MCIA)
Aaron Wong is Primary Investigator in a medicinal cannabis trial which is funded by the Victorian Cancer Agency.
SC, JSa, JS, PM, RR, LT, KW, & BZ – No competing financial interests exist
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Delac received his B.Sc.E.E. degree in 2003 and is currentlypursuing a Ph.D. degree at the University of Zagreb, Faculty of Electrical Engineering andComputing. His current research interests are digital image analysis, pattern recognition andbiometrics.",institutionString:null,institution:{name:"University of Zagreb",country:{name:"Croatia"}}},{id:"557",title:"Dr.",name:"Andon",middleName:"Venelinov",surname:"Topalov",slug:"andon-topalov",fullName:"Andon Topalov",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/557/images/1927_n.jpg",biography:"Dr. Andon V. Topalov received the MSc degree in Control Engineering from the Faculty of Information Systems, Technologies, and Automation at Moscow State University of Civil Engineering (MGGU) in 1979. He then received his PhD degree in Control Engineering from the Department of Automation and Remote Control at Moscow State Mining University (MGSU), Moscow, in 1984. 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Given their increasing integration with corporate networks, in which the industry 4.0 is the most recent driving force, new uncertainties, not only from the tangible physical world, but also from a cyber space perspective, are brought into play. In order to improve the overall resilience of a cyber-physical system, this work proposes a framework based on a distributed middleware that integrates a multiagent topology, where each agent is responsible for coordinating and executing specific tasks. In this framework, both physical and cyber vulnerabilities alike are considered, and the achievement of a correct state awareness and minimum levels of acceptable operation, in response to physical or malicious disturbances, are guaranteed. Experimental results collected with an IPv6-based simulator comprising several distributed computational devices and heterogeneous communication networks show the relevance and inherent benefits of this approach.",book:{id:"5996",slug:"multi-agent-systems",title:"Multi-agent Systems",fullTitle:"Multi-agent Systems"},signatures:"Fábio Emanuel Pais Januário, Joaquim Leitão, Alberto Cardoso and\nPaulo Gil",authors:[{id:"202364",title:"Ph.D. Student",name:"Fábio",middleName:null,surname:"Januário",slug:"fabio-januario",fullName:"Fábio Januário"},{id:"203414",title:"Prof.",name:"Alberto",middleName:null,surname:"Cardoso",slug:"alberto-cardoso",fullName:"Alberto Cardoso"},{id:"203415",title:"Prof.",name:"Paulo",middleName:null,surname:"Gil",slug:"paulo-gil",fullName:"Paulo Gil"},{id:"206481",title:"MSc.",name:"Joaquim",middleName:null,surname:"Leitão",slug:"joaquim-leitao",fullName:"Joaquim Leitão"}]},{id:"56014",doi:"10.5772/intechopen.69352",title:"Robust Adaptive Cooperative Control for Formation-Tracking Problem in a Network of Non-Affine Nonlinear Agents",slug:"robust-adaptive-cooperative-control-for-formation-tracking-problem-in-a-network-of-non-affine-nonlin",totalDownloads:1510,totalCrossrefCites:2,totalDimensionsCites:4,abstract:"In this chapter, a decentralized cooperative control protocol is proposed with application to any network of agents with non-affine nonlinear multi-input-multi-output (MIMO) dynamics. Here, the main purpose of cooperative control protocol is to track a time-variant reference trajectory while maintaining a desired formation. The reference trajectory is defined to a leader, which has at least one information connection with one of the agents in the network. The design procedure includes a robust adaptive law for estimating the unknown nonlinear terms of each agent’s dynamics in a model-free format, that is, without the use of any regressors. Moreover, an observer is designed to have an approximation on the values of control parameters for the leader at the agents without connection to the leader. The entire design procedure is analysed successfully for the stability using Lyapunov stability theorem. Finally, the simulation results for the application of the proposed method on a network of nonholonomic wheeled mobile robots (WMR) are presented. Desirable leader-following tracking and geometric formation control performance have been successfully demonstrated through simulated group of wheeled mobile robots.",book:{id:"5996",slug:"multi-agent-systems",title:"Multi-agent Systems",fullTitle:"Multi-agent Systems"},signatures:"Muhammad Nasiruddin bin Mahyuddin and Ali Safaei",authors:[{id:"204129",title:"Dr.",name:"Muhammad Nasiruddin",middleName:null,surname:"Mahyuddin",slug:"muhammad-nasiruddin-mahyuddin",fullName:"Muhammad Nasiruddin Mahyuddin"},{id:"206489",title:"Mr.",name:"Ali",middleName:null,surname:"Safaei",slug:"ali-safaei",fullName:"Ali Safaei"}]},{id:"56255",doi:"10.5772/intechopen.69844",title:"Time Critical Mass Evacuation Simulation Combining A Multi- Agent System and High-Performance Computing",slug:"time-critical-mass-evacuation-simulation-combining-a-multi-agent-system-and-high-performance-computi",totalDownloads:1395,totalCrossrefCites:1,totalDimensionsCites:1,abstract:"This chapter presents an application of multi-agent systems to simulate tsunami-triggered mass evacuations of large urban areas. The main objective is to quantitatively evaluate various strategies to accelerate evacuation in case of a tsunami with a short arrival time, taking most influential factors into account. Considering the large number of lives in fatal danger, instead of widely used simple agents in 1D networks, we use a high-resolution model of environment and complex agents so that wide range of influencing factors can be taken into account. A brief description of the multi-agent system is provided using a mathematical framework as means to easily and unambiguously refer to the main components of the system. The environment of the multi-agent system, which mimics the physical world of evacuees, is modelled as a hybrid of a high-resolution grid and a graph connecting traversable spaces. This hybrid of raster and vector data structures enables modelling large domain in a scalable manner. The agents, which mimic the heterogeneous crowd of evacuees, are composed of different combinations of basic constituent functions for modelling interaction with each other and environment, decision-making, etc. The results of tuning and validating of constituent functions for pedestrian-pedestrian, car-car and car-pedestrian interactions are presented. A scalable high-performance computing (HPC) extension to address the high-computational demand of complex agents and high-resolution model of environment is briefly explained. Finally, demonstrative applications that highlight the need for including sub-meter details in the environment, different modes of evacuation and behavioural differences are presented.",book:{id:"5996",slug:"multi-agent-systems",title:"Multi-agent Systems",fullTitle:"Multi-agent Systems"},signatures:"Leonel Aguilar, Maddegedara Lalith and Muneo Hori",authors:[{id:"203530",title:"Prof.",name:"Maddgedara",middleName:null,surname:"Lalith",slug:"maddgedara-lalith",fullName:"Maddgedara Lalith"},{id:"204168",title:"Dr.",name:"Leonel",middleName:null,surname:"Aguilar",slug:"leonel-aguilar",fullName:"Leonel Aguilar"},{id:"204169",title:"Prof.",name:"Muneo",middleName:null,surname:"Hori",slug:"muneo-hori",fullName:"Muneo Hori"}]},{id:"56327",doi:"10.5772/intechopen.69845",title:"Motion Coordination Problems with Collision Avoidance for Multi-Agent Systems",slug:"motion-coordination-problems-with-collision-avoidance-for-multi-agent-systems",totalDownloads:1395,totalCrossrefCites:1,totalDimensionsCites:1,abstract:"This chapter studies the collision avoidance problem in the motion coordination control strategies for multi-agent systems. The proposed control strategies are decentralised, since agents have no global knowledge of the goal to achieve, knowing only the position and velocity of some agents. These control strategies allow a set of mobile agents achieve formations, formation tracking and containment. For the collision avoidance, we add a repulsive vector field of the unstable focus type to the motion coordination control strategies. We use formation graphs to represent interactions between agents. The results are presented for the front points of differential-drive mobile robots. The theoretical results are verified by numerical simulation.",book:{id:"5996",slug:"multi-agent-systems",title:"Multi-agent Systems",fullTitle:"Multi-agent Systems"},signatures:"Jesús Santiaguillo-Salinas and Eduardo Aranda-Bricaire",authors:[{id:"16943",title:"Prof.",name:"Eduardo",middleName:null,surname:"Aranda-Bricaire",slug:"eduardo-aranda-bricaire",fullName:"Eduardo Aranda-Bricaire"},{id:"204125",title:"Ph.D.",name:"Jesús",middleName:null,surname:"Santiaguillo-Salinas",slug:"jesus-santiaguillo-salinas",fullName:"Jesús Santiaguillo-Salinas"}]}],mostDownloadedChaptersLast30Days:[{id:"56573",title:"Introductory Chapter: Multi-Agent Systems",slug:"introductory-chapter-multi-agent-systems",totalDownloads:2389,totalCrossrefCites:4,totalDimensionsCites:9,abstract:null,book:{id:"5996",slug:"multi-agent-systems",title:"Multi-agent Systems",fullTitle:"Multi-agent Systems"},signatures:"Jorge Rocha, Inês Boavida-Portugal and Eduardo Gomes",authors:[{id:"145918",title:"Ph.D.",name:"Jorge",middleName:null,surname:"Rocha",slug:"jorge-rocha",fullName:"Jorge Rocha"},{id:"214969",title:"Prof.",name:"Inês",middleName:null,surname:"Boavida-Portugal",slug:"ines-boavida-portugal",fullName:"Inês Boavida-Portugal"},{id:"214971",title:"MSc.",name:"Eduardo",middleName:null,surname:"Gomes",slug:"eduardo-gomes",fullName:"Eduardo Gomes"}]},{id:"55920",title:"Hybrid Architecture to Support Context‐Aware Systems",slug:"hybrid-architecture-to-support-context-aware-systems",totalDownloads:1626,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"Any system that is said to be context‐aware is capable of monitoring continuously the surrounding environment, that is, capable of prompt reaction to events and changing conditions of the environment. The main objective of a context‐aware system is to be continuously recognizing the state of the environment and the users present, in order to adjust the environment to an ideal state and to provide personalized information and services to users considering the user profile. In this chapter, we describe an architecture that relies on the incorporation of intelligent multi‐agent systems (MAS), sensor networks, mobile sensors, actuators, Web services and ontologies. We describe the interaction of these technologies into the architecture aiming at facilitating the construction of context‐aware systems.",book:{id:"5996",slug:"multi-agent-systems",title:"Multi-agent Systems",fullTitle:"Multi-agent Systems"},signatures:"Maricela Bravo, José A. Reyes‐Ortiz, Leonardo Sánchez‐Martínez\nand Roberto A. Alcántara‐Ramírez",authors:[{id:"204084",title:"Dr.",name:"Maricela",middleName:null,surname:"Bravo",slug:"maricela-bravo",fullName:"Maricela Bravo"},{id:"204085",title:"Dr.",name:"Alejandro",middleName:null,surname:"Reyes",slug:"alejandro-reyes",fullName:"Alejandro Reyes"},{id:"204086",title:"Dr.",name:"Leonardo",middleName:null,surname:"Sánchez",slug:"leonardo-sanchez",fullName:"Leonardo Sánchez"},{id:"204087",title:"MSc.",name:"Roberto",middleName:null,surname:"Alcántara-Ramírez",slug:"roberto-alcantara-ramirez",fullName:"Roberto Alcántara-Ramírez"}]},{id:"56184",title:"Multiagent Systems in Automotive Applications",slug:"multiagent-systems-in-automotive-applications",totalDownloads:1759,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"The multiagent systems have proved to be a useful tool in the design of solutions to problems of distributed nature. In a distributed system, it is possible that the data, the control actions or even both, be distributed. The concept of agent is a suitable notion for capturing situations where the global knowledge about the status of a system is complex or even impossible to acquire in a single entity. In automotive applications, there exist a great number of scenarios of distributed nature, such as the traffic coordination, routes load balancing problems, traffic negotiation among the infrastructure and cars, to mention a few. Even more, the autonomous driving features of the new generation of cars will require the new methods of car to car communication, car to infrastructure negotiation, and even infrastructure to infrastructure communication. This chapter proposes the application of multiagent system techniques to some problems in the automotive field.",book:{id:"5996",slug:"multi-agent-systems",title:"Multi-agent Systems",fullTitle:"Multi-agent Systems"},signatures:"Raul Campos‐Rodriguez, Luis Gonzalez‐Jimenez, Francisco\nCervantes‐Alvarez, Francisco Amezcua‐Garcia and Miguel\nFernandez‐Garcia",authors:[{id:"178524",title:"Dr.",name:"Raul",middleName:null,surname:"Campos-Rodriguez",slug:"raul-campos-rodriguez",fullName:"Raul Campos-Rodriguez"},{id:"204584",title:"Dr.",name:"Francisco",middleName:null,surname:"Cervantes Alvarez",slug:"francisco-cervantes-alvarez",fullName:"Francisco Cervantes Alvarez"},{id:"204586",title:"Mr.",name:"Francisco",middleName:null,surname:"Amezcua Garcia",slug:"francisco-amezcua-garcia",fullName:"Francisco Amezcua Garcia"},{id:"204587",title:"BSc.",name:"Miguel",middleName:null,surname:"Fernandez Garcia",slug:"miguel-fernandez-garcia",fullName:"Miguel Fernandez Garcia"},{id:"207383",title:"Dr.",name:"Luis",middleName:null,surname:"Gonzalez-Jimenez",slug:"luis-gonzalez-jimenez",fullName:"Luis Gonzalez-Jimenez"}]},{id:"56297",title:"Multiagent System for Image Mining",slug:"multiagent-system-for-image-mining",totalDownloads:1363,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"The overdone growth, wide availability, and demands for remote sensing databases combined with human limits to analyze such huge datasets lead to a need to investigate tools, techniques, methodologies, and theories capable of assisting humans at extracting knowledge. Image mining arises as a solution to extract implicit knowledge intelligently and semiautomatically or other patterns not explicitly stored in the huge image databases. However, spatial databases are among the ones with the fastest growth due to the volume of spatial information produced many times a day, demanding the investigation of other means for knowledge extraction. Multiagent systems are composed of multiple computing elements known as agents that interact to pursuit their goals. Agents have been used to explore information in the distributed, open, large, and heterogeneous platforms. Agent mining is a potential technology that studies ways of interaction and integration between data mining and agents. This area brought advances to the technologies involved such as theories, methodologies, and solutions to solve relevant issues more precisely, accurately and faster. AgentGeo is evidence of this, a multiagent system of satellite image mining that, promotes advances in the state of the art of agent mining, since it relevant functions to extract knowledge from spatial databases.",book:{id:"5996",slug:"multi-agent-systems",title:"Multi-agent Systems",fullTitle:"Multi-agent Systems"},signatures:"Nicksson Ckayo Arrais de Freitas and Marcelino Pereira dos Santos\nSilva",authors:[{id:"203201",title:"B.Sc.",name:"Nicksson",middleName:"Ckayo Arrais",surname:"De Freitas",slug:"nicksson-de-freitas",fullName:"Nicksson De Freitas"},{id:"203204",title:"Dr.",name:"Marcelino",middleName:null,surname:"Silva",slug:"marcelino-silva",fullName:"Marcelino Silva"}]},{id:"56255",title:"Time Critical Mass Evacuation Simulation Combining A Multi- Agent System and High-Performance Computing",slug:"time-critical-mass-evacuation-simulation-combining-a-multi-agent-system-and-high-performance-computi",totalDownloads:1393,totalCrossrefCites:1,totalDimensionsCites:1,abstract:"This chapter presents an application of multi-agent systems to simulate tsunami-triggered mass evacuations of large urban areas. The main objective is to quantitatively evaluate various strategies to accelerate evacuation in case of a tsunami with a short arrival time, taking most influential factors into account. Considering the large number of lives in fatal danger, instead of widely used simple agents in 1D networks, we use a high-resolution model of environment and complex agents so that wide range of influencing factors can be taken into account. A brief description of the multi-agent system is provided using a mathematical framework as means to easily and unambiguously refer to the main components of the system. The environment of the multi-agent system, which mimics the physical world of evacuees, is modelled as a hybrid of a high-resolution grid and a graph connecting traversable spaces. This hybrid of raster and vector data structures enables modelling large domain in a scalable manner. The agents, which mimic the heterogeneous crowd of evacuees, are composed of different combinations of basic constituent functions for modelling interaction with each other and environment, decision-making, etc. The results of tuning and validating of constituent functions for pedestrian-pedestrian, car-car and car-pedestrian interactions are presented. A scalable high-performance computing (HPC) extension to address the high-computational demand of complex agents and high-resolution model of environment is briefly explained. Finally, demonstrative applications that highlight the need for including sub-meter details in the environment, different modes of evacuation and behavioural differences are presented.",book:{id:"5996",slug:"multi-agent-systems",title:"Multi-agent Systems",fullTitle:"Multi-agent Systems"},signatures:"Leonel Aguilar, Maddegedara Lalith and Muneo Hori",authors:[{id:"203530",title:"Prof.",name:"Maddgedara",middleName:null,surname:"Lalith",slug:"maddgedara-lalith",fullName:"Maddgedara Lalith"},{id:"204168",title:"Dr.",name:"Leonel",middleName:null,surname:"Aguilar",slug:"leonel-aguilar",fullName:"Leonel Aguilar"},{id:"204169",title:"Prof.",name:"Muneo",middleName:null,surname:"Hori",slug:"muneo-hori",fullName:"Muneo Hori"}]}],onlineFirstChaptersFilter:{topicId:"526",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:89,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:318,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:15,numberOfOpenTopics:5,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. The whole process of submitting an article and editing of the submitted article goes extremely smooth and fast, the number of reads and downloads of chapters is high, and the contributions are also frequently cited.",author:{id:"55578",name:"Antonio",surname:"Jurado-Navas",institutionString:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",slug:"antonio-jurado-navas",institution:{id:"720",name:"University of Malaga",country:{id:null,name:"Spain"}}}},{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"}}}}]},series:{item:{id:"14",title:"Artificial Intelligence",doi:"10.5772/intechopen.79920",issn:"2633-1403",scope:"Artificial Intelligence (AI) is a rapidly developing multidisciplinary research area that aims to solve increasingly complex problems. In today's highly integrated world, AI promises to become a robust and powerful means for obtaining solutions to previously unsolvable problems. This Series is intended for researchers and students alike interested in this fascinating field and its many applications.",coverUrl:"https://cdn.intechopen.com/series/covers/14.jpg",latestPublicationDate:"June 11th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:9,editor:{id:"218714",title:"Prof.",name:"Andries",middleName:null,surname:"Engelbrecht",slug:"andries-engelbrecht",fullName:"Andries Engelbrecht",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRNR8QAO/Profile_Picture_1622640468300",biography:"Andries Engelbrecht received the Masters and PhD degrees in Computer Science from the University of Stellenbosch, South Africa, in 1994 and 1999 respectively. He is currently appointed as the Voigt Chair in Data Science in the Department of Industrial Engineering, with a joint appointment as Professor in the Computer Science Division, Stellenbosch University. Prior to his appointment at Stellenbosch University, he has been at the University of Pretoria, Department of Computer Science (1998-2018), where he was appointed as South Africa Research Chair in Artifical Intelligence (2007-2018), the head of the Department of Computer Science (2008-2017), and Director of the Institute for Big Data and Data Science (2017-2018). In addition to a number of research articles, he has written two books, Computational Intelligence: An Introduction and Fundamentals of Computational Swarm Intelligence.",institutionString:null,institution:{name:"Stellenbosch University",institutionURL:null,country:{name:"South Africa"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:6,paginationItems:[{id:"22",title:"Applied Intelligence",coverUrl:"https://cdn.intechopen.com/series_topics/covers/22.jpg",isOpenForSubmission:!0,editor:{id:"27170",title:"Prof.",name:"Carlos",middleName:"M.",surname:"Travieso-Gonzalez",slug:"carlos-travieso-gonzalez",fullName:"Carlos Travieso-Gonzalez",profilePictureURL:"https://mts.intechopen.com/storage/users/27170/images/system/27170.jpeg",biography:"Carlos M. Travieso-González received his MSc degree in Telecommunication Engineering at Polytechnic University of Catalonia (UPC), Spain in 1997, and his Ph.D. degree in 2002 at the University of Las Palmas de Gran Canaria (ULPGC-Spain). He is a full professor of signal processing and pattern recognition and is head of the Signals and Communications Department at ULPGC, teaching from 2001 on subjects on signal processing and learning theory. His research lines are biometrics, biomedical signals and images, data mining, classification system, signal and image processing, machine learning, and environmental intelligence. He has researched in 52 international and Spanish research projects, some of them as head researcher. He is co-author of 4 books, co-editor of 27 proceedings books, guest editor for 8 JCR-ISI international journals, and up to 24 book chapters. He has over 450 papers published in international journals and conferences (81 of them indexed on JCR – ISI - Web of Science). He has published seven patents in the Spanish Patent and Trademark Office. He has been a supervisor on 8 Ph.D. theses (11 more are under supervision), and 130 master theses. He is the founder of The IEEE IWOBI conference series and the president of its Steering Committee, as well as the founder of both the InnoEducaTIC and APPIS conference series. He is an evaluator of project proposals for the European Union (H2020), Medical Research Council (MRC, UK), Spanish Government (ANECA, Spain), Research National Agency (ANR, France), DAAD (Germany), Argentinian Government, and the Colombian Institutions. He has been a reviewer in different indexed international journals (<70) and conferences (<250) since 2001. He has been a member of the IASTED Technical Committee on Image Processing from 2007 and a member of the IASTED Technical Committee on Artificial Intelligence and Expert Systems from 2011. \n\nHe has held the general chair position for the following: ACM-APPIS (2020, 2021), IEEE-IWOBI (2019, 2020 and 2020), A PPIS (2018, 2019), IEEE-IWOBI (2014, 2015, 2017, 2018), InnoEducaTIC (2014, 2017), IEEE-INES (2013), NoLISP (2011), JRBP (2012), and IEEE-ICCST (2005)\n\nHe is an associate editor of the Computational Intelligence and Neuroscience Journal (Hindawi – Q2 JCR-ISI). He was vice dean from 2004 to 2010 in the Higher Technical School of Telecommunication Engineers at ULPGC and the vice dean of Graduate and Postgraduate Studies from March 2013 to November 2017. He won the “Catedra Telefonica” Awards in Modality of Knowledge Transfer, 2017, 2018, and 2019 editions, and awards in Modality of COVID Research in 2020.\n\nPublic References:\nResearcher ID http://www.researcherid.com/rid/N-5967-2014\nORCID https://orcid.org/0000-0002-4621-2768 \nScopus Author ID https://www.scopus.com/authid/detail.uri?authorId=6602376272\nScholar Google https://scholar.google.es/citations?user=G1ks9nIAAAAJ&hl=en \nResearchGate https://www.researchgate.net/profile/Carlos_Travieso",institutionString:null,institution:{name:"University of Las Palmas de Gran Canaria",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"23",title:"Computational Neuroscience",coverUrl:"https://cdn.intechopen.com/series_topics/covers/23.jpg",isOpenForSubmission:!0,editor:{id:"14004",title:"Dr.",name:"Magnus",middleName:null,surname:"Johnsson",slug:"magnus-johnsson",fullName:"Magnus Johnsson",profilePictureURL:"https://mts.intechopen.com/storage/users/14004/images/system/14004.png",biography:"Dr Magnus Johnsson is a cross-disciplinary scientist, lecturer, scientific editor and AI/machine learning consultant from Sweden. \n\nHe is currently at Malmö University in Sweden, but also held positions at Lund University in Sweden and at Moscow Engineering Physics Institute. \nHe holds editorial positions at several international scientific journals and has served as a scientific editor for books and special journal issues. \nHis research interests are wide and include, but are not limited to, autonomous systems, computer modeling, artificial neural networks, artificial intelligence, cognitive neuroscience, cognitive robotics, cognitive architectures, cognitive aids and the philosophy of mind. \n\nDr. Johnsson has experience from working in the industry and he has a keen interest in the application of neural networks and artificial intelligence to fields like industry, finance, and medicine. \n\nWeb page: www.magnusjohnsson.se",institutionString:null,institution:{name:"Malmö University",institutionURL:null,country:{name:"Sweden"}}},editorTwo:null,editorThree:null},{id:"24",title:"Computer Vision",coverUrl:"https://cdn.intechopen.com/series_topics/covers/24.jpg",isOpenForSubmission:!0,editor:{id:"294154",title:"Prof.",name:"George",middleName:null,surname:"Papakostas",slug:"george-papakostas",fullName:"George Papakostas",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002hYaGbQAK/Profile_Picture_1624519712088",biography:"George A. Papakostas has received a diploma in Electrical and Computer Engineering in 1999 and the M.Sc. and Ph.D. degrees in Electrical and Computer Engineering in 2002 and 2007, respectively, from the Democritus University of Thrace (DUTH), Greece. Dr. Papakostas serves as a Tenured Full Professor at the Department of Computer Science, International Hellenic University, Greece. Dr. Papakostas has 10 years of experience in large-scale systems design as a senior software engineer and technical manager, and 20 years of research experience in the field of Artificial Intelligence. Currently, he is the Head of the “Visual Computing” division of HUman-MAchines INteraction Laboratory (HUMAIN-Lab) and the Director of the MPhil program “Advanced Technologies in Informatics and Computers” hosted by the Department of Computer Science, International Hellenic University. He has (co)authored more than 150 publications in indexed journals, international conferences and book chapters, 1 book (in Greek), 3 edited books, and 5 journal special issues. His publications have more than 2100 citations with h-index 27 (GoogleScholar). His research interests include computer/machine vision, machine learning, pattern recognition, computational intelligence. \nDr. Papakostas served as a reviewer in numerous journals, as a program\ncommittee member in international conferences and he is a member of the IAENG, MIR Labs, EUCogIII, INSTICC and the Technical Chamber of Greece (TEE).",institutionString:null,institution:{name:"International Hellenic University",institutionURL:null,country:{name:"Greece"}}},editorTwo:null,editorThree:null},{id:"25",title:"Evolutionary Computation",coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",isOpenForSubmission:!0,editor:{id:"136112",title:"Dr.",name:"Sebastian",middleName:null,surname:"Ventura Soto",slug:"sebastian-ventura-soto",fullName:"Sebastian Ventura Soto",profilePictureURL:"https://mts.intechopen.com/storage/users/136112/images/system/136112.png",biography:"Sebastian Ventura is a Spanish researcher, a full professor with the Department of Computer Science and Numerical Analysis, University of Córdoba. Dr Ventura also holds the positions of Affiliated Professor at Virginia Commonwealth University (Richmond, USA) and Distinguished Adjunct Professor at King Abdulaziz University (Jeddah, Saudi Arabia). Additionally, he is deputy director of the Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI) and heads the Knowledge Discovery and Intelligent Systems Research Laboratory. He has published more than ten books and over 300 articles in journals and scientific conferences. Currently, his work has received over 18,000 citations according to Google Scholar, including more than 2200 citations in 2020. In the last five years, he has published more than 60 papers in international journals indexed in the JCR (around 70% of them belonging to first quartile journals) and he has edited some Springer books “Supervised Descriptive Pattern Mining” (2018), “Multiple Instance Learning - Foundations and Algorithms” (2016), and “Pattern Mining with Evolutionary Algorithms” (2016). He has also been involved in more than 20 research projects supported by the Spanish and Andalusian governments and the European Union. He currently belongs to the editorial board of PeerJ Computer Science, Information Fusion and Engineering Applications of Artificial Intelligence journals, being also associate editor of Applied Computational Intelligence and Soft Computing and IEEE Transactions on Cybernetics. Finally, he is editor-in-chief of Progress in Artificial Intelligence. He is a Senior Member of the IEEE Computer, the IEEE Computational Intelligence, and the IEEE Systems, Man, and Cybernetics Societies, and the Association of Computing Machinery (ACM). Finally, his main research interests include data science, computational intelligence, and their applications.",institutionString:null,institution:{name:"University of Córdoba",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"26",title:"Machine Learning and Data Mining",coverUrl:"https://cdn.intechopen.com/series_topics/covers/26.jpg",isOpenForSubmission:!0,editor:{id:"24555",title:"Dr.",name:"Marco Antonio",middleName:null,surname:"Aceves Fernandez",slug:"marco-antonio-aceves-fernandez",fullName:"Marco Antonio Aceves Fernandez",profilePictureURL:"https://mts.intechopen.com/storage/users/24555/images/system/24555.jpg",biography:"Dr. Marco Antonio Aceves Fernandez obtained his B.Sc. (Eng.) in Telematics from the Universidad de Colima, Mexico. He obtained both his M.Sc. and Ph.D. from the University of Liverpool, England, in the field of Intelligent Systems. He is a full professor at the Universidad Autonoma de Queretaro, Mexico, and a member of the National System of Researchers (SNI) since 2009. Dr. Aceves Fernandez has published more than 80 research papers as well as a number of book chapters and congress papers. He has contributed in more than 20 funded research projects, both academic and industrial, in the area of artificial intelligence, ranging from environmental, biomedical, automotive, aviation, consumer, and robotics to other applications. He is also a honorary president at the National Association of Embedded Systems (AMESE), a senior member of the IEEE, and a board member of many institutions. His research interests include intelligent and embedded systems.",institutionString:"Universidad Autonoma de Queretaro",institution:{name:"Autonomous University of Queretaro",institutionURL:null,country:{name:"Mexico"}}},editorTwo:null,editorThree:null},{id:"27",title:"Multi-Agent Systems",coverUrl:"https://cdn.intechopen.com/series_topics/covers/27.jpg",isOpenForSubmission:!0,editor:{id:"148497",title:"Dr.",name:"Mehmet",middleName:"Emin",surname:"Aydin",slug:"mehmet-aydin",fullName:"Mehmet Aydin",profilePictureURL:"https://mts.intechopen.com/storage/users/148497/images/system/148497.jpg",biography:"Dr. Mehmet Emin Aydin is a Senior Lecturer with the Department of Computer Science and Creative Technology, the University of the West of England, Bristol, UK. His research interests include swarm intelligence, parallel and distributed metaheuristics, machine learning, intelligent agents and multi-agent systems, resource planning, scheduling and optimization, combinatorial optimization. Dr. Aydin is currently a Fellow of Higher Education Academy, UK, a member of EPSRC College, a senior member of IEEE and a senior member of ACM. In addition to being a member of advisory committees of many international conferences, he is an Editorial Board Member of various peer-reviewed international journals. He has served as guest editor for a number of special issues of peer-reviewed international journals.",institutionString:null,institution:{name:"University of the West of England",institutionURL:null,country:{name:"United Kingdom"}}},editorTwo:null,editorThree:null}]},overviewPageOFChapters:{paginationCount:19,paginationItems:[{id:"82196",title:"Multi-Features Assisted Age Invariant Face Recognition and Retrieval Using CNN with Scale Invariant Heat Kernel Signature",doi:"10.5772/intechopen.104944",signatures:"Kamarajugadda Kishore Kumar and Movva Pavani",slug:"multi-features-assisted-age-invariant-face-recognition-and-retrieval-using-cnn-with-scale-invariant-",totalDownloads:6,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Pattern Recognition - New Insights",coverURL:"https://cdn.intechopen.com/books/images_new/11442.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}},{id:"82063",title:"Evaluating Similarities and Differences between Machine Learning and Traditional Statistical Modeling in Healthcare Analytics",doi:"10.5772/intechopen.105116",signatures:"Michele Bennett, Ewa J. Kleczyk, Karin Hayes and Rajesh Mehta",slug:"evaluating-similarities-and-differences-between-machine-learning-and-traditional-statistical-modelin",totalDownloads:6,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Machine Learning and Data Mining - Annual Volume 2022",coverURL:"https://cdn.intechopen.com/books/images_new/11422.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}},{id:"81791",title:"Self-Supervised Contrastive Representation Learning in Computer Vision",doi:"10.5772/intechopen.104785",signatures:"Yalin Bastanlar and Semih Orhan",slug:"self-supervised-contrastive-representation-learning-in-computer-vision",totalDownloads:30,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Pattern Recognition - New Insights",coverURL:"https://cdn.intechopen.com/books/images_new/11442.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}},{id:"79345",title:"Application of Jump Diffusion Models in Insurance Claim Estimation",doi:"10.5772/intechopen.99853",signatures:"Leonard Mushunje, Chiedza Elvina Mashiri, Edina Chandiwana and Maxwell Mashasha",slug:"application-of-jump-diffusion-models-in-insurance-claim-estimation-1",totalDownloads:10,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Data Clustering",coverURL:"https://cdn.intechopen.com/books/images_new/10820.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}}]},overviewPagePublishedBooks:{paginationCount:9,paginationItems:[{type:"book",id:"7723",title:"Artificial Intelligence",subtitle:"Applications in Medicine and Biology",coverURL:"https://cdn.intechopen.com/books/images_new/7723.jpg",slug:"artificial-intelligence-applications-in-medicine-and-biology",publishedDate:"July 31st 2019",editedByType:"Edited by",bookSignature:"Marco Antonio Aceves-Fernandez",hash:"a3852659e727f95c98c740ed98146011",volumeInSeries:1,fullTitle:"Artificial Intelligence - Applications in Medicine and Biology",editors:[{id:"24555",title:"Dr.",name:"Marco Antonio",middleName:null,surname:"Aceves Fernandez",slug:"marco-antonio-aceves-fernandez",fullName:"Marco Antonio Aceves Fernandez",profilePictureURL:"https://mts.intechopen.com/storage/users/24555/images/system/24555.jpg",biography:"Dr. Marco Antonio Aceves Fernandez obtained his B.Sc. (Eng.) in Telematics from the Universidad de Colima, Mexico. He obtained both his M.Sc. and Ph.D. from the University of Liverpool, England, in the field of Intelligent Systems. He is a full professor at the Universidad Autonoma de Queretaro, Mexico, and a member of the National System of Researchers (SNI) since 2009. Dr. Aceves Fernandez has published more than 80 research papers as well as a number of book chapters and congress papers. He has contributed in more than 20 funded research projects, both academic and industrial, in the area of artificial intelligence, ranging from environmental, biomedical, automotive, aviation, consumer, and robotics to other applications. He is also a honorary president at the National Association of Embedded Systems (AMESE), a senior member of the IEEE, and a board member of many institutions. 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He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. 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He has been reviewer for several publications of the Optical Society of America\\'s including Photonics Technology Letters and Applied Optics.\n\nPersonal Interests\nThese include motor cycling in a very relaxed manner and performing martial arts.",institutionString:null,institution:{name:"Charité",country:{name:"Germany"}}},{id:"341622",title:"Ph.D.",name:"Eduardo",middleName:null,surname:"Rojas Alvarez",slug:"eduardo-rojas-alvarez",fullName:"Eduardo Rojas Alvarez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/341622/images/15892_n.jpg",biography:null,institutionString:null,institution:{name:"University of Cuenca",country:{name:"Ecuador"}}},{id:"215610",title:"Prof.",name:"Muhammad",middleName:null,surname:"Sarfraz",slug:"muhammad-sarfraz",fullName:"Muhammad Sarfraz",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/215610/images/system/215610.jpeg",biography:"Muhammad Sarfraz is a professor in the Department of Information Science, Kuwait University. His research interests include computer graphics, computer vision, image processing, machine learning, pattern recognition, soft computing, data science, intelligent systems, information technology, and information systems. Prof. Sarfraz has been a keynote/invited speaker on various platforms around the globe. He has advised various students for their MSc and Ph.D. theses. He has published more than 400 publications as books, journal articles, and conference papers. He is a member of various professional societies and a chair and member of the International Advisory Committees and Organizing Committees of various international conferences. Prof. Sarfraz is also an editor-in-chief and editor of various international journals.",institutionString:"Kuwait University",institution:{name:"Kuwait University",country:{name:"Kuwait"}}},{id:"32650",title:"Prof.",name:"Lukas",middleName:"Willem",surname:"Snyman",slug:"lukas-snyman",fullName:"Lukas Snyman",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/32650/images/4136_n.jpg",biography:"Lukas Willem Snyman received his basic education at primary and high schools in South Africa, Eastern Cape. He enrolled at today's Nelson Metropolitan University and graduated from this university with a BSc in Physics and Mathematics, B.Sc Honors in Physics, MSc in Semiconductor Physics, and a Ph.D. in Semiconductor Physics in 1987. After his studies, he chose an academic career and devoted his energy to the teaching of physics to first, second, and third-year students. After positions as a lecturer at the University of Port Elizabeth, he accepted a position as Associate Professor at the University of Pretoria, South Africa.\r\n\r\nIn 1992, he motivates the concept of 'television and computer-based education” as means to reach large student numbers with only the best of teaching expertise and publishes an article on the concept in the SA Journal of Higher Education of 1993 (and later in 2003). The University of Pretoria subsequently approved a series of test projects on the concept with outreach to Mamelodi and Eerste Rust in 1993. In 1994, the University established a 'Unit for Telematic Education ' as a support section for multiple faculties at the University of Pretoria. In subsequent years, the concept of 'telematic education” subsequently becomes well established in academic circles in South Africa, grew in popularity, and is adopted by many universities and colleges throughout South Africa as a medium of enhancing education and training, as a method to reaching out to far out communities, and as a means to enhance study from the home environment.\r\n\r\nProfessor Snyman in subsequent years pursued research in semiconductor physics, semiconductor devices, microelectronics, and optoelectronics.\r\n\r\nIn 2000 he joined the TUT as a full professor. Here served for a period as head of the Department of Electronic Engineering. Here he makes contributions to solar energy development, microwave and optoelectronic device development, silicon photonics, as well as contributions to new mobile telecommunication systems and network planning in SA.\r\n\r\nCurrently, he teaches electronics and telecommunications at the TUT to audiences ranging from first-year students to Ph.D. level.\r\n\r\nFor his research in the field of 'Silicon Photonics” since 1990, he has published (as author and co-author) about thirty internationally reviewed articles in scientific journals, contributed to more than forty international conferences, about 25 South African provisional patents (as inventor and co-inventor), 8 PCT international patent applications until now. Of these, two USA patents applications, two European Patents, two Korean patents, and ten SA patents have been granted. A further 4 USA patents, 5 European patents, 3 Korean patents, 3 Chinese patents, and 3 Japanese patents are currently under consideration.\r\n\r\nRecently he has also published an extensive scholarly chapter in an internet open access book on 'Integrating Microphotonic Systems and MOEMS into standard Silicon CMOS Integrated circuitry”.\r\n\r\nFurthermore, Professor Snyman recently steered a new initiative at the TUT by introducing a 'Laboratory for Innovative Electronic Systems ' at the Department of Electrical Engineering. The model of this laboratory or center is to primarily combine outputs as achieved by high-level research with lower-level system development and entrepreneurship in a technical university environment. Students are allocated to projects at different levels with PhDs and Master students allocated to the generation of new knowledge and new technologies, while students at the diploma and Baccalaureus level are allocated to electronic systems development with a direct and a near application for application in industry or the commercial and public sectors in South Africa.\r\n\r\nProfessor Snyman received the WIRSAM Award of 1983 and the WIRSAM Award in 1985 in South Africa for best research papers by a young scientist at two international conferences on electron microscopy in South Africa. He subsequently received the SA Microelectronics Award for the best dissertation emanating from studies executed at a South African university in the field of Physics and Microelectronics in South Africa in 1987. In October of 2011, Professor Snyman received the prestigious Institutional Award for 'Innovator of the Year” for 2010 at the Tshwane University of Technology, South Africa. This award was based on the number of patents recognized and granted by local and international institutions as well as for his contributions concerning innovation at the TUT.",institutionString:null,institution:{name:"University of South Africa",country:{name:"South Africa"}}},{id:"317279",title:"Mr.",name:"Ali",middleName:"Usama",surname:"Syed",slug:"ali-syed",fullName:"Ali Syed",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/317279/images/16024_n.png",biography:"A creative, talented, and innovative young professional who is dedicated, well organized, and capable research fellow with two years of experience in graduate-level research, published in engineering journals and book, with related expertise in Bio-robotics, equally passionate about the aesthetics of the mechanical and electronic system, obtained expertise in the use of MS Office, MATLAB, SolidWorks, LabVIEW, Proteus, Fusion 360, having a grasp on python, C++ and assembly language, possess proven ability in acquiring research grants, previous appointments with social and educational societies with experience in administration, current affiliations with IEEE and Web of Science, a confident presenter at conferences and teacher in classrooms, able to explain complex information to audiences of all levels.",institutionString:null,institution:{name:"Air University",country:{name:"Pakistan"}}},{id:"75526",title:"Ph.D.",name:"Zihni Onur",middleName:null,surname:"Uygun",slug:"zihni-onur-uygun",fullName:"Zihni Onur Uygun",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/75526/images/12_n.jpg",biography:"My undergraduate education and my Master of Science educations at Ege University and at Çanakkale Onsekiz Mart University have given me a firm foundation in Biochemistry, Analytical Chemistry, Biosensors, Bioelectronics, Physical Chemistry and Medicine. After obtaining my degree as a MSc in analytical chemistry, I started working as a research assistant in Ege University Medical Faculty in 2014. In parallel, I enrolled to the MSc program at the Department of Medical Biochemistry at Ege University to gain deeper knowledge on medical and biochemical sciences as well as clinical chemistry in 2014. In my PhD I deeply researched on biosensors and bioelectronics and finished in 2020. Now I have eleven SCI-Expanded Index published papers, 6 international book chapters, referee assignments for different SCIE journals, one international patent pending, several international awards, projects and bursaries. In parallel to my research assistant position at Ege University Medical Faculty, Department of Medical Biochemistry, in April 2016, I also founded a Start-Up Company (Denosens Biotechnology LTD) by the support of The Scientific and Technological Research Council of Turkey. Currently, I am also working as a CEO in Denosens Biotechnology. The main purposes of the company, which carries out R&D as a research center, are to develop new generation biosensors and sensors for both point-of-care diagnostics; such as glucose, lactate, cholesterol and cancer biomarker detections. My specific experimental and instrumental skills are Biochemistry, Biosensor, Analytical Chemistry, Electrochemistry, Mobile phone based point-of-care diagnostic device, POCTs and Patient interface designs, HPLC, Tandem Mass Spectrometry, Spectrophotometry, ELISA.",institutionString:null,institution:{name:"Ege University",country:{name:"Turkey"}}},{id:"267434",title:"Dr.",name:"Rohit",middleName:null,surname:"Raja",slug:"rohit-raja",fullName:"Rohit Raja",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/267434/images/system/267434.jpg",biography:"Dr. Rohit Raja received Ph.D. in Computer Science and Engineering from Dr. CVRAMAN University in 2016. His main research interest includes Face recognition and Identification, Digital Image Processing, Signal Processing, and Networking. Presently he is working as Associate Professor in IT Department, Guru Ghasidas Vishwavidyalaya (A Central University), Bilaspur (CG), India. He has authored several Journal and Conference Papers. He has good Academics & Research experience in various areas of CSE and IT. He has filed and successfully published 27 Patents. He has received many time invitations to be a Guest at IEEE Conferences. He has published 100 research papers in various International/National Journals (including IEEE, Springer, etc.) and Proceedings of the reputed International/ National Conferences (including Springer and IEEE). He has been nominated to the board of editors/reviewers of many peer-reviewed and refereed Journals (including IEEE, Springer).",institutionString:"Guru Ghasidas Vishwavidyalaya",institution:{name:"Guru Ghasidas Vishwavidyalaya",country:{name:"India"}}},{id:"246502",title:"Dr.",name:"Jaya T.",middleName:"T",surname:"Varkey",slug:"jaya-t.-varkey",fullName:"Jaya T. Varkey",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/246502/images/11160_n.jpg",biography:"Jaya T. Varkey, PhD, graduated with a degree in Chemistry from Cochin University of Science and Technology, Kerala, India. She obtained a PhD in Chemistry from the School of Chemical Sciences, Mahatma Gandhi University, Kerala, India, and completed a post-doctoral fellowship at the University of Minnesota, USA. She is a research guide at Mahatma Gandhi University and Associate Professor in Chemistry, St. Teresa’s College, Kochi, Kerala, India.\nDr. Varkey received a National Young Scientist award from the Indian Science Congress (1995), a UGC Research award (2016–2018), an Indian National Science Academy (INSA) Visiting Scientist award (2018–2019), and a Best Innovative Faculty award from the All India Association for Christian Higher Education (AIACHE) (2019). She Hashas received the Sr. Mary Cecil prize for best research paper three times. She was also awarded a start-up to develop a tea bag water filter. \nDr. Varkey has published two international books and twenty-seven international journal publications. She is an editorial board member for five international journals.",institutionString:"St. Teresa’s College",institution:null},{id:"250668",title:"Dr.",name:"Ali",middleName:null,surname:"Nabipour Chakoli",slug:"ali-nabipour-chakoli",fullName:"Ali Nabipour Chakoli",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/250668/images/system/250668.jpg",biography:"Academic Qualification:\r\n•\tPhD in Materials Physics and Chemistry, From: Sep. 2006, to: Sep. 2010, School of Materials Science and Engineering, Harbin Institute of Technology, Thesis: Structure and Shape Memory Effect of Functionalized MWCNTs/poly (L-lactide-co-ε-caprolactone) Nanocomposites. Supervisor: Prof. Wei Cai,\r\n•\tM.Sc in Applied Physics, From: 1996, to: 1998, Faculty of Physics & Nuclear Science, Amirkabir Uni. of Technology, Tehran, Iran, Thesis: Determination of Boron in Micro alloy Steels with solid state nuclear track detectors by neutron induced auto radiography, Supervisors: Dr. M. Hosseini Ashrafi and Dr. A. Hosseini.\r\n•\tB.Sc. in Applied Physics, From: 1991, to: 1996, Faculty of Physics & Nuclear Science, Amirkabir Uni. of Technology, Tehran, Iran, Thesis: Design of shielding for Am-Be neutron sources for In Vivo neutron activation analysis, Supervisor: Dr. M. Hosseini Ashrafi.\r\n\r\nResearch Experiences:\r\n1.\tNanomaterials, Carbon Nanotubes, Graphene: Synthesis, Functionalization and Characterization,\r\n2.\tMWCNTs/Polymer Composites: Fabrication and Characterization, \r\n3.\tShape Memory Polymers, Biodegradable Polymers, ORC, Collagen,\r\n4.\tMaterials Analysis and Characterizations: TEM, SEM, XPS, FT-IR, Raman, DSC, DMA, TGA, XRD, GPC, Fluoroscopy, \r\n5.\tInteraction of Radiation with Mater, Nuclear Safety and Security, NDT(RT),\r\n6.\tRadiation Detectors, Calibration (SSDL),\r\n7.\tCompleted IAEA e-learning Courses:\r\nNuclear Security (15 Modules),\r\nNuclear Safety:\r\nTSA 2: Regulatory Protection in Occupational Exposure,\r\nTips & Tricks: Radiation Protection in Radiography,\r\nSafety and Quality in Radiotherapy,\r\nCourse on Sealed Radioactive Sources,\r\nCourse on Fundamentals of Environmental Remediation,\r\nCourse on Planning for Environmental Remediation,\r\nKnowledge Management Orientation Course,\r\nFood Irradiation - Technology, Applications and Good Practices,\r\nEmployment:\r\nFrom 2010 to now: Academic staff, Nuclear Science and Technology Research Institute, Kargar Shomali, Tehran, Iran, P.O. Box: 14395-836.\r\nFrom 1997 to 2006: Expert of Materials Analysis and Characterization. Research Center of Agriculture and Medicine. Rajaeeshahr, Karaj, Iran, P. O. Box: 31585-498.",institutionString:"Atomic Energy Organization of Iran",institution:{name:"Atomic Energy Organization of Iran",country:{name:"Iran"}}},{id:"248279",title:"Dr.",name:"Monika",middleName:"Elzbieta",surname:"Machoy",slug:"monika-machoy",fullName:"Monika Machoy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/248279/images/system/248279.jpeg",biography:"Monika Elżbieta Machoy, MD, graduated with distinction from the Faculty of Medicine and Dentistry at the Pomeranian Medical University in 2009, defended her PhD thesis with summa cum laude in 2016 and is currently employed as a researcher at the Department of Orthodontics of the Pomeranian Medical University. She expanded her professional knowledge during a one-year scholarship program at the Ernst Moritz Arndt University in Greifswald, Germany and during a three-year internship at the Technical University in Dresden, Germany. She has been a speaker at numerous orthodontic conferences, among others, American Association of Orthodontics, European Orthodontic Symposium and numerous conferences of the Polish Orthodontic Society. She conducts research focusing on the effect of orthodontic treatment on dental and periodontal tissues and the causes of pain in orthodontic patients.",institutionString:"Pomeranian Medical University",institution:{name:"Pomeranian Medical University",country:{name:"Poland"}}},{id:"252743",title:"Prof.",name:"Aswini",middleName:"Kumar",surname:"Kar",slug:"aswini-kar",fullName:"Aswini Kar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/252743/images/10381_n.jpg",biography:"uploaded in cv",institutionString:null,institution:{name:"KIIT University",country:{name:"India"}}},{id:"204256",title:"Dr.",name:"Anil",middleName:"Kumar",surname:"Kumar Sahu",slug:"anil-kumar-sahu",fullName:"Anil Kumar Sahu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/204256/images/14201_n.jpg",biography:"I have nearly 11 years of research and teaching experience. I have done my master degree from University Institute of Pharmacy, Pt. Ravi Shankar Shukla University, Raipur, Chhattisgarh India. I have published 16 review and research articles in international and national journals and published 4 chapters in IntechOpen, the world’s leading publisher of Open access books. I have presented many papers at national and international conferences. I have received research award from Indian Drug Manufacturers Association in year 2015. My research interest extends from novel lymphatic drug delivery systems, oral delivery system for herbal bioactive to formulation optimization.",institutionString:null,institution:{name:"Chhattisgarh Swami Vivekanand Technical University",country:{name:"India"}}},{id:"253468",title:"Dr.",name:"Mariusz",middleName:null,surname:"Marzec",slug:"mariusz-marzec",fullName:"Mariusz Marzec",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/253468/images/system/253468.png",biography:"An assistant professor at Department of Biomedical Computer Systems, at Institute of Computer Science, Silesian University in Katowice. Scientific interests: computer analysis and processing of images, biomedical images, databases and programming languages. He is an author and co-author of scientific publications covering analysis and processing of biomedical images and development of database systems.",institutionString:"University of Silesia",institution:null},{id:"212432",title:"Prof.",name:"Hadi",middleName:null,surname:"Mohammadi",slug:"hadi-mohammadi",fullName:"Hadi Mohammadi",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/212432/images/system/212432.jpeg",biography:"Dr. Hadi Mohammadi is a biomedical engineer with hands-on experience in the design and development of many engineering structures and medical devices through various projects that he has been involved in over the past twenty years. Dr. Mohammadi received his BSc. and MSc. degrees in Mechanical Engineering from Sharif University of Technology, Tehran, Iran, and his PhD. degree in Biomedical Engineering (biomaterials) from the University of Western Ontario. He was a postdoctoral trainee for almost four years at University of Calgary and Harvard Medical School. He is an industry innovator having created the technology to produce lifelike synthetic platforms that can be used for the simulation of almost all cardiovascular reconstructive surgeries. He’s been heavily involved in the design and development of cardiovascular devices and technology for the past 10 years. He is currently an Assistant Professor with the University of British Colombia, Canada.",institutionString:"University of British Columbia",institution:{name:"University of British Columbia",country:{name:"Canada"}}},{id:"254463",title:"Prof.",name:"Haisheng",middleName:null,surname:"Yang",slug:"haisheng-yang",fullName:"Haisheng Yang",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/254463/images/system/254463.jpeg",biography:"Haisheng Yang, Ph.D., Professor and Director of the Department of Biomedical Engineering, College of Life Science and Bioengineering, Beijing University of Technology. He received his Ph.D. degree in Mechanics/Biomechanics from Harbin Institute of Technology (jointly with University of California, Berkeley). Afterwards, he worked as a Postdoctoral Research Associate in the Purdue Musculoskeletal Biology and Mechanics Lab at the Department of Basic Medical Sciences, Purdue University, USA. He also conducted research in the Research Centre of Shriners Hospitals for Children-Canada at McGill University, Canada. Dr. Yang has over 10 years research experience in orthopaedic biomechanics and mechanobiology of bone adaptation and regeneration. He earned an award from Beijing Overseas Talents Aggregation program in 2017 and serves as Beijing Distinguished Professor.",institutionString:null,institution:{name:"Beijing University of Technology",country:{name:"China"}}},{id:"89721",title:"Dr.",name:"Mehmet",middleName:"Cuneyt",surname:"Ozmen",slug:"mehmet-ozmen",fullName:"Mehmet Ozmen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/89721/images/7289_n.jpg",biography:null,institutionString:null,institution:{name:"Gazi University",country:{name:"Turkey"}}},{id:"242893",title:"Ph.D. Student",name:"Joaquim",middleName:null,surname:"De Moura",slug:"joaquim-de-moura",fullName:"Joaquim De Moura",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/242893/images/7133_n.jpg",biography:"Joaquim de Moura received his degree in Computer Engineering in 2014 from the University of A Coruña (Spain). In 2016, he received his M.Sc degree in Computer Engineering from the same university. He is currently pursuing his Ph.D degree in Computer Science in a collaborative project between ophthalmology centers in Galicia and the University of A Coruña. His research interests include computer vision, machine learning algorithms and analysis and medical imaging processing of various kinds.",institutionString:null,institution:{name:"University of A Coruña",country:{name:"Spain"}}},{id:"294334",title:"B.Sc.",name:"Marc",middleName:null,surname:"Bruggeman",slug:"marc-bruggeman",fullName:"Marc Bruggeman",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/294334/images/8242_n.jpg",biography:"Chemical engineer graduate, with a passion for material science and specific interest in polymers - their near infinite applications intrigue me. \n\nI plan to continue my scientific career in the field of polymeric biomaterials as I am fascinated by intelligent, bioactive and biomimetic materials for use in both consumer and medical applications.",institutionString:null,institution:null},{id:"255757",title:"Dr.",name:"Igor",middleName:"Victorovich",surname:"Lakhno",slug:"igor-lakhno",fullName:"Igor Lakhno",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/255757/images/system/255757.jpg",biography:"Igor Victorovich Lakhno was born in 1971 in Kharkiv (Ukraine). \nMD – 1994, Kharkiv National Medical Univesity.\nOb&Gyn; – 1997, master courses in Kharkiv Medical Academy of Postgraduate Education.\nPh.D. – 1999, Kharkiv National Medical Univesity.\nDSC – 2019, PL Shupik National Academy of Postgraduate Education \nProfessor – 2021, Department of Obstetrics and Gynecology of VN Karazin Kharkiv National University\nHead of Department – 2021, Department of Perinatology, Obstetrics and gynecology of Kharkiv Medical Academy of Postgraduate Education\nIgor Lakhno has been graduated from international training courses on reproductive medicine and family planning held at Debrecen University (Hungary) in 1997. Since 1998 Lakhno Igor has worked as an associate professor in the department of obstetrics and gynecology of VN Karazin National University and an associate professor of the perinatology, obstetrics, and gynecology department of Kharkiv Medical Academy of Postgraduate Education. Since June 2019 he’s been a professor in the department of obstetrics and gynecology of VN Karazin National University and a professor of the perinatology, obstetrics, and gynecology department. He’s affiliated with Kharkiv Medical Academy of Postgraduate Education as a Head of Department from November 2021. Igor Lakhno has participated in several international projects on fetal non-invasive electrocardiography (with Dr. J. A. Behar (Technion), Prof. D. Hoyer (Jena University), and José Alejandro Díaz Méndez (National Institute of Astrophysics, Optics, and Electronics, Mexico). He’s an author of about 200 printed works and there are 31 of them in Scopus or Web of Science databases. Igor Lakhno is a member of the Editorial Board of Reproductive Health of Woman, Emergency Medicine, and Technology Transfer Innovative Solutions in Medicine (Estonia). He is a medical Editor of “Z turbotoyu pro zhinku”. Igor Lakhno is a reviewer of the Journal of Obstetrics and Gynaecology (Taylor and Francis), British Journal of Obstetrics and Gynecology (Wiley), Informatics in Medicine Unlocked (Elsevier), The Journal of Obstetrics and Gynecology Research (Wiley), Endocrine, Metabolic & Immune Disorders-Drug Targets (Bentham Open), The Open Biomedical Engineering Journal (Bentham Open), etc. He’s defended a dissertation for a DSc degree “Pre-eclampsia: prediction, prevention, and treatment”. Three years ago Igor Lakhno has participated in a training course on innovative technologies in medical education at Lublin Medical University (Poland). Lakhno Igor has participated as a speaker in several international conferences and congresses (International Conference on Biological Oscillations April 10th-14th 2016, Lancaster, UK, The 9th conference of the European Study Group on Cardiovascular Oscillations). His main scientific interests: are obstetrics, women’s health, fetal medicine, and cardiovascular medicine. \nIgor Lakhno is a consultant at Kharkiv municipal perinatal center. He’s graduated from training courses on endoscopy in gynecology. He has 28 years of practical experience in the field.",institutionString:null,institution:null},{id:"244950",title:"Dr.",name:"Salvatore",middleName:null,surname:"Di Lauro",slug:"salvatore-di-lauro",fullName:"Salvatore Di Lauro",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0030O00002bSF1HQAW/ProfilePicture%202021-12-20%2014%3A54%3A14.482",biography:"Name:\n\tSALVATORE DI LAURO\nAddress:\n\tHospital Clínico Universitario Valladolid\nAvda Ramón y Cajal 3\n47005, Valladolid\nSpain\nPhone number: \nFax\nE-mail:\n\t+34 983420000 ext 292\n+34 983420084\nsadilauro@live.it\nDate and place of Birth:\nID Number\nMedical Licence \nLanguages\t09-05-1985. Villaricca (Italy)\n\nY1281863H\n474707061\nItalian (native language)\nSpanish (read, written, spoken)\nEnglish (read, written, spoken)\nPortuguese (read, spoken)\nFrench (read)\n\t\t\nCurrent position (title and company)\tDate (Year)\nVitreo-Retinal consultant in ophthalmology. Hospital Clinico Universitario Valladolid. Sacyl. National Health System.\nVitreo-Retinal consultant in ophthalmology. Instituto Oftalmologico Recoletas. Red Hospitalaria Recoletas. Private practise.\t2017-today\n\n2019-today\n\t\n\t\nEducation (High school, university and postgraduate training > 3 months)\tDate (Year)\nDegree in Medicine and Surgery. University of Neaples 'Federico II”\nResident in Opthalmology. Hospital Clinico Universitario Valladolid\nMaster in Vitreo-Retina. IOBA. University of Valladolid\nFellow of the European Board of Ophthalmology. Paris\nMaster in Research in Ophthalmology. University of Valladolid\t2003-2009\n2012-2016\n2016-2017\n2016\n2012-2013\n\t\nEmployments (company and positions)\tDate (Year)\nResident in Ophthalmology. Hospital Clinico Universitario Valladolid. Sacyl.\nFellow in Vitreo-Retina. IOBA. University of Valladolid\nVitreo-Retinal consultant in ophthalmology. Hospital Clinico Universitario Valladolid. Sacyl. National Health System.\nVitreo-Retinal consultant in ophthalmology. Instituto Oftalmologico Recoletas. Red Hospitalaria Recoletas. \n\t2012-2016\n2016-2017\n2017-today\n\n2019-Today\n\n\n\t\nClinical Research Experience (tasks and role)\tDate (Year)\nAssociated investigator\n\n' FIS PI20/00740: DESARROLLO DE UNA CALCULADORA DE RIESGO DE\nAPARICION DE RETINOPATIA DIABETICA BASADA EN TECNICAS DE IMAGEN MULTIMODAL EN PACIENTES DIABETICOS TIPO 1. Grant by: Ministerio de Ciencia e Innovacion \n\n' (BIO/VA23/14) Estudio clínico multicéntrico y prospectivo para validar dos\nbiomarcadores ubicados en los genes p53 y MDM2 en la predicción de los resultados funcionales de la cirugía del desprendimiento de retina regmatógeno. Grant by: Gerencia Regional de Salud de la Junta de Castilla y León.\n' Estudio multicéntrico, aleatorizado, con enmascaramiento doble, en 2 grupos\nparalelos y de 52 semanas de duración para comparar la eficacia, seguridad e inmunogenicidad de SOK583A1 respecto a Eylea® en pacientes con degeneración macular neovascular asociada a la edad' (CSOK583A12301; N.EUDRA: 2019-004838-41; FASE III). Grant by Hexal AG\n\n' Estudio de fase III, aleatorizado, doble ciego, con grupos paralelos, multicéntrico para comparar la eficacia y la seguridad de QL1205 frente a Lucentis® en pacientes con degeneración macular neovascular asociada a la edad. (EUDRACT: 2018-004486-13). Grant by Qilu Pharmaceutical Co\n\n' Estudio NEUTON: Ensayo clinico en fase IV para evaluar la eficacia de aflibercept en pacientes Naive con Edema MacUlar secundario a Oclusion de Vena CenTral de la Retina (OVCR) en regimen de tratamientO iNdividualizado Treat and Extend (TAE)”, (2014-000975-21). Grant by Fundacion Retinaplus\n\n' Evaluación de la seguridad y bioactividad de anillos de tensión capsular en conejo. Proyecto Procusens. Grant by AJL, S.A.\n\n'Estudio epidemiológico, prospectivo, multicéntrico y abierto\\npara valorar la frecuencia de la conjuntivitis adenovírica diagnosticada mediante el test AdenoPlus®\\nTest en pacientes enfermos de conjuntivitis aguda”\\n. National, multicenter study. Grant by: NICOX.\n\nEuropean multicentric trial: 'Evaluation of clinical outcomes following the use of Systane Hydration in patients with dry eye”. Study Phase 4. Grant by: Alcon Labs'\n\nVLPs Injection and Activation in a Rabbit Model of Uveal Melanoma. Grant by Aura Bioscience\n\nUpdating and characterization of a rabbit model of uveal melanoma. Grant by Aura Bioscience\n\nEnsayo clínico en fase IV para evaluar las variantes genéticas de la vía del VEGF como biomarcadores de eficacia del tratamiento con aflibercept en pacientes con degeneración macular asociada a la edad (DMAE) neovascular. Estudio BIOIMAGE. IMO-AFLI-2013-01\n\nEstudio In-Eye:Ensayo clínico en fase IV, abierto, aleatorizado, de 2 brazos,\nmulticçentrico y de 12 meses de duración, para evaluar la eficacia y seguridad de un régimen de PRN flexible individualizado de 'esperar y extender' versus un régimen PRN según criterios de estabilización mediante evaluaciones mensuales de inyecciones intravítreas de ranibizumab 0,5 mg en pacientes naive con neovascularización coriodea secunaria a la degeneración macular relacionada con la edad. CP: CRFB002AES03T\n\nTREND: Estudio Fase IIIb multicéntrico, randomizado, de 12 meses de\nseguimiento con evaluador de la agudeza visual enmascarado, para evaluar la eficacia y la seguridad de ranibizumab 0.5mg en un régimen de tratar y extender comparado con un régimen mensual, en pacientes con degeneración macular neovascular asociada a la edad. CP: CRFB002A2411 Código Eudra CT:\n2013-002626-23\n\n\n\nPublications\t\n\n2021\n\n\n\n\n2015\n\n\n\n\n2021\n\n\n\n\n\n2021\n\n\n\n\n2015\n\n\n\n\n2015\n\n\n2014\n\n\n\n\n2015-16\n\n\n\n2015\n\n\n2014\n\n\n2014\n\n\n\n\n2014\n\n\n\n\n\n\n\n2014\n\nJose Carlos Pastor; Jimena Rojas; Salvador Pastor-Idoate; Salvatore Di Lauro; Lucia Gonzalez-Buendia; Santiago Delgado-Tirado. Proliferative vitreoretinopathy: A new concept of disease pathogenesis and practical\nconsequences. Progress in Retinal and Eye Research. 51, pp. 125 - 155. 03/2016. DOI: 10.1016/j.preteyeres.2015.07.005\n\n\nLabrador-Velandia S; Alonso-Alonso ML; Di Lauro S; García-Gutierrez MT; Srivastava GK; Pastor JC; Fernandez-Bueno I. Mesenchymal stem cells provide paracrine neuroprotective resources that delay degeneration of co-cultured organotypic neuroretinal cultures.Experimental Eye Research. 185, 17/05/2019. DOI: 10.1016/j.exer.2019.05.011\n\nSalvatore Di Lauro; Maria Teresa Garcia Gutierrez; Ivan Fernandez Bueno. Quantification of pigment epithelium-derived factor (PEDF) in an ex vivo coculture of retinal pigment epithelium cells and neuroretina.\nJournal of Allbiosolution. 2019. ISSN 2605-3535\n\nSonia Labrador Velandia; Salvatore Di Lauro; Alonso-Alonso ML; Tabera Bartolomé S; Srivastava GK; Pastor JC; Fernandez-Bueno I. Biocompatibility of intravitreal injection of human mesenchymal stem cells in immunocompetent rabbits. Graefe's archive for clinical and experimental ophthalmology. 256 - 1, pp. 125 - 134. 01/2018. DOI: 10.1007/s00417-017-3842-3\n\n\nSalvatore Di Lauro, David Rodriguez-Crespo, Manuel J Gayoso, Maria T Garcia-Gutierrez, J Carlos Pastor, Girish K Srivastava, Ivan Fernandez-Bueno. A novel coculture model of porcine central neuroretina explants and retinal pigment epithelium cells. Molecular Vision. 2016 - 22, pp. 243 - 253. 01/2016.\n\nSalvatore Di Lauro. Classifications for Proliferative Vitreoretinopathy ({PVR}): An Analysis of Their Use in Publications over the Last 15 Years. Journal of Ophthalmology. 2016, pp. 1 - 6. 01/2016. DOI: 10.1155/2016/7807596\n\nSalvatore Di Lauro; Rosa Maria Coco; Rosa Maria Sanabria; Enrique Rodriguez de la Rua; Jose Carlos Pastor. Loss of Visual Acuity after Successful Surgery for Macula-On Rhegmatogenous Retinal Detachment in a Prospective Multicentre Study. Journal of Ophthalmology. 2015:821864, 2015. DOI: 10.1155/2015/821864\n\nIvan Fernandez-Bueno; Salvatore Di Lauro; Ivan Alvarez; Jose Carlos Lopez; Maria Teresa Garcia-Gutierrez; Itziar Fernandez; Eva Larra; Jose Carlos Pastor. Safety and Biocompatibility of a New High-Density Polyethylene-Based\nSpherical Integrated Porous Orbital Implant: An Experimental Study in Rabbits. Journal of Ophthalmology. 2015:904096, 2015. DOI: 10.1155/2015/904096\n\nPastor JC; Pastor-Idoate S; Rodríguez-Hernandez I; Rojas J; Fernandez I; Gonzalez-Buendia L; Di Lauro S; Gonzalez-Sarmiento R. Genetics of PVR and RD. Ophthalmologica. 232 - Suppl 1, pp. 28 - 29. 2014\n\nRodriguez-Crespo D; Di Lauro S; Singh AK; Garcia-Gutierrez MT; Garrosa M; Pastor JC; Fernandez-Bueno I; Srivastava GK. Triple-layered mixed co-culture model of RPE cells with neuroretina for evaluating the neuroprotective effects of adipose-MSCs. Cell Tissue Res. 358 - 3, pp. 705 - 716. 2014.\nDOI: 10.1007/s00441-014-1987-5\n\nCarlo De Werra; Salvatore Condurro; Salvatore Tramontano; Mario Perone; Ivana Donzelli; Salvatore Di Lauro; Massimo Di Giuseppe; Rosa Di Micco; Annalisa Pascariello; Antonio Pastore; Giorgio Diamantis; Giuseppe Galloro. Hydatid disease of the liver: thirty years of surgical experience.Chirurgia italiana. 59 - 5, pp. 611 - 636.\n(Italia): 2007. ISSN 0009-4773\n\nChapters in books\n\t\n' Salvador Pastor Idoate; Salvatore Di Lauro; Jose Carlos Pastor Jimeno. PVR: Pathogenesis, Histopathology and Classification. Proliferative Vitreoretinopathy with Small Gauge Vitrectomy. Springer, 2018. ISBN 978-3-319-78445-8\nDOI: 10.1007/978-3-319-78446-5_2. \n\n' Salvatore Di Lauro; Maria Isabel Lopez Galvez. Quistes vítreos en una mujer joven. Problemas diagnósticos en patología retinocoroidea. Sociedad Española de Retina-Vitreo. 2018.\n\n' Salvatore Di Lauro; Salvador Pastor Idoate; Jose Carlos Pastor Jimeno. iOCT in PVR management. OCT Applications in Opthalmology. pp. 1 - 8. INTECH, 2018. DOI: 10.5772/intechopen.78774.\n\n' Rosa Coco Martin; Salvatore Di Lauro; Salvador Pastor Idoate; Jose Carlos Pastor. amponadores, manipuladores y tinciones en la cirugía del traumatismo ocular.Trauma Ocular. Ponencia de la SEO 2018..\n\n' LOPEZ GALVEZ; DI LAURO; CRESPO. OCT angiografia y complicaciones retinianas de la diabetes. PONENCIA SEO 2021, CAPITULO 20. (España): 2021.\n\n' Múltiples desprendimientos neurosensoriales bilaterales en paciente joven. Enfermedades Degenerativas De Retina Y Coroides. SERV 04/2016. \n' González-Buendía L; Di Lauro S; Pastor-Idoate S; Pastor Jimeno JC. Vitreorretinopatía proliferante (VRP) e inflamación: LA INFLAMACIÓN in «INMUNOMODULADORES Y ANTIINFLAMATORIOS: MÁS ALLÁ DE LOS CORTICOIDES. 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