Search results for: forest regeneration

Authors: T. Garba, Y. Y. Babanyara, M. Isah, A. K. Muktari, R. Y. Abdullahi

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The increased in demand of fuel wood for heating, cooking and sometimes bakery has continued to exert appreciable impact on natural vegetation. This study focus on the use of multi-temporal data from land sat TM of 1986, land sat EMT of 1999 and lands sat ETM of 2006 to investigate the changes of Natural Vegetation resulting from charcoal production activities. The three images were classified based on bare soil, built up areas, cultivated land, and natural vegetation, Rock out crop and water bodies. From the classified images Land sat TM of 1986 it shows natural vegetation of the study area to be 308,941.48 hectares equivalent to 50% of the area it then reduces to 278,061.21 which is 42.92% in 1999 it again depreciated to 199,647.81 in 2006 equivalent to 30.83% of the area. Consequently cultivated continue increasing from 259,346.80 hectares (42%) in 1986 to 312,966.27 hectares (48.3%) in 1999 and then to 341.719.92 hectares (52.78%). These show that within the span of 20 years (1986 to 2006) the natural vegetation is depreciated by 119,293.81 hectares. This implies that if the menace is not control the natural might likely be lost in another twenty years. This is because forest cleared for charcoal production is normally converted to farmland. The study therefore concluded that there is the need for alternatives source of domestic energy such as the use of biomass which can easily be accessible and affordable to people. In addition, the study recommended that there should be strong policies enforcement for the protection forest reserved.

Keywords: charcoal, classification, data, images, land use, natural vegetation

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Authors: Rachel Danielson, Brendan Bohannan, S.M. Tsai, Kyle Meyer, Jorge L.M. Rodrigues

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The Amazon Rainforest is a global diversity hotspot and crucial carbon sink, but approximately 20% of its total extent has been deforested- primarily for the establishment of cattle pasture. Understanding the impact of this large-scale disturbance on soil microbial community composition and activity is crucial in understanding potentially consequential shifts in nutrient or greenhouse gas cycling, as well as adding to the body of knowledge concerning how these complex communities respond to human disturbance. In this study, surface soils (0-10cm) were collected from three forests and three 45-year-old pastures in Rondonia, Brazil (the Amazon state with the greatest rate of forest destruction) in order to determine the impact of forest conversion on microbial communities involved in nitrogen fixation. Soil chemical and physical parameters were paired with measurements of microbial activity and genetic profiles to determine how community composition and process rates relate to environmental conditions. Measuring both the natural abundance of 15N in total soil N, as well as incorporation of enriched 15N2 under incubation has revealed that conversion of primary forest to cattle pasture results in a significant increase in the rate of nitrogen fixation by free-living diazotrophs. Quantification of nifH gene copy numbers (an essential subunit encoding the nitrogenase enzyme) correspondingly reveals a significant increase of genes in pasture compared to forest soils. Additionally, genetic sequencing of both nifH genes and transcripts shows a significant increase in the diversity of the present and metabolically active diazotrophs within the soil community. Levels of both organic and inorganic nitrogen tend to be lower in pastures compared to forests, with ammonium rather than nitrate as the dominant inorganic form. However, no significant or consistent differences in total, extractable, permanganate-oxidizable, or loss-on-ignition carbon are present between the two land-use types. Forest conversion is associated with a 0.5- 1.0 unit pH increase, but concentrations of many biologically relevant nutrients such as phosphorus do not increase consistently. Increases in free-living diazotrophic community abundance and activity appear to be related to shifts in carbon to nitrogen pool ratios. Furthermore, there may be an important impact of transient, low molecular weight plant-root-derived organic carbon on free-living diazotroph communities not captured in this study. Preliminary analysis of nitrogenase gene variant composition using NovoSeq metagenomic sequencing indicates that conversion of forest to pasture may significantly enrich vanadium-based nitrogenases. This indication is complemented by a significant decrease in available soil molybdenum. Very little is known about the ecology of diazotrophs utilizing vanadium-based nitrogenases, so further analysis may reveal important environmental conditions favoring their abundance and diversity in soil systems. Taken together, the results of this study indicate a significant change in nitrogen cycling and diazotroph community composition with the conversion of the Amazon Rainforest. This may have important implications for the sustainability of cattle pastures once established since nitrogen is a crucial nutrient for forage grass productivity.

Keywords: free-living diazotrophs, land use change, metagenomic sequencing, nitrogen fixation

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Authors: Ekramul Hoque, Zinat Ara Eakut Zarin, Ershad Ali

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The growth and development of explants is governed by the effect of nutrient medium. Ammonium nitrate (NH4NO3) as a major salt of stock solution-1 for the preparation of tissue culture medium. But, it has several demerits on human civilization. It is use for the preparation of bomb and other destructive activities. Hence, it is totally ban in our country. A new chemical was identified as a substitute of ammonium nitrate. The concentrations of the other ingredients of major and minor salt were modified from the MS medium. The formulation of new medium is totally different from the MS nutrient composition. The most widely use MS medium composition was used as first check treatment and MS powder (Duchefa Biocheme, The Netherland) was used as second check treatment. The experiments were carried out at the Department of Biotechnology, Sher-e-Bangla Agricultural University, Dhaka, Bangladesh. Two potato varieties viz. Diamant and Asterix were used as experimental materials. The regeneration potentiality of potato onto new medium was best as compare with the two check treatments. The traits -node number, leaf number, shoot length, root lengths were highest in new medium. The plantlets were healthy, robust and strong as compare to plantlets regenerated from check treatments. Three subsequent sub-cultures were made in the new medium to observe the growth pattern of plantlet. It was also showed the best performance in all the parameter under studied. The regenerated plantlet produced good quality minituber under field condition. Hence, it is concluded that, a new plant tissue culture medium as discovered from the Department of Biotechnology, Sher-e-Bangla Agricultural University, Dhaka, Bangladesh under the leadership of Professor Dr. Md. Ekramul Hoque.

Keywords: new medium, potato, regeneration, ammonium nitrate

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Authors: Farid Khosravikia, Patricia Clayton

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The main objective of this work is to evaluate the advantages and disadvantages of various machine learning techniques in two key steps of seismic hazard and risk assessment of different types of structures. The first step is the development of ground-motion models, which are used for forecasting ground-motion intensity measures (IM) given source characteristics, source-to-site distance, and local site condition for future events. IMs such as peak ground acceleration and velocity (PGA and PGV, respectively) as well as 5% damped elastic pseudospectral accelerations at different periods (PSA), are indicators of the strength of shaking at the ground surface. Typically, linear regression-based models, with pre-defined equations and coefficients, are used in ground motion prediction. However, due to the restrictions of the linear regression methods, such models may not capture more complex nonlinear behaviors that exist in the data. Thus, this study comparatively investigates potential benefits from employing other machine learning techniques as statistical method in ground motion prediction such as Artificial Neural Network, Random Forest, and Support Vector Machine. The results indicate the algorithms satisfy some physically sound characteristics such as magnitude scaling distance dependency without requiring pre-defined equations or coefficients. Moreover, it is shown that, when sufficient data is available, all the alternative algorithms tend to provide more accurate estimates compared to the conventional linear regression-based method, and particularly, Random Forest outperforms the other algorithms. However, the conventional method is a better tool when limited data is available. Second, it is investigated how machine learning techniques could be beneficial for developing probabilistic seismic demand models (PSDMs), which provide the relationship between the structural demand responses (e.g., component deformations, accelerations, internal forces, etc.) and the ground motion IMs. In the risk framework, such models are used to develop fragility curves estimating exceeding probability of damage for pre-defined limit states, and therefore, control the reliability of the predictions in the risk assessment. In this study, machine learning algorithms like artificial neural network, random forest, and support vector machine are adopted and trained on the demand parameters to derive PSDMs for them. It is observed that such models can provide more accurate estimates of prediction in relatively shorter about of time compared to conventional methods. Moreover, they can be used for sensitivity analysis of fragility curves with respect to many modeling parameters without necessarily requiring more intense numerical response-history analysis.

Keywords: artificial neural network, machine learning, random forest, seismic risk analysis, seismic hazard analysis, support vector machine

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Authors: Zafer Yüce, Paşa Yayla, Alev Taşkın

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There are heaps of analytical methods to estimate the crack growth life of a component. Soft computing methods have an increasing trend in predicting fatigue life. Their ability to build complex relationships and capability to handle huge amounts of data are motivating researchers and industry professionals to employ them for challenging problems. This study focuses on soft computing methods, especially random forest regressors and artificial neural networks with hyperparameter optimization algorithms such as grid search and random grid search, to estimate the crack growth life of an aircraft wing splice joint under variable amplitude loading. TensorFlow and Scikit-learn libraries of Python are used to build the machine learning models for this study. The material considered in this work is 7050-T7451 aluminum, which is commonly preferred as a structural element in the aerospace industry, and regarding the crack type; corner crack is used. A finite element model is built for the joint to calculate fastener loads and stresses on the structure. Since finite element model results are validated with analytical calculations, findings of the finite element model are fed to AFGROW software to calculate analytical crack growth lives. Based on Fighter Aircraft Loading Standard for Fatigue (FALSTAFF), 90 unique fatigue loading spectra are developed for various load levels, and then, these spectrums are utilized as inputs to the artificial neural network and random forest regression models for predicting crack growth life. Finally, the crack growth life predictions of the machine learning models are compared with analytical calculations. According to the findings, a good correlation is observed between analytical and predicted crack growth lives.

Keywords: aircraft, fatigue, joint, life, optimization, prediction.

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Authors: Priyanka Yadav, Umesh Bnasal, Yashvinder Kumar

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The placenta is an important structure that provides oxygen and nutrients to the growing fetus in utero. It is usually thrown away after birth, but it has a therapeutic role in the regeneration of tissue. It is covered by the amniotic membrane, which can be easily separated into the amnion layer and the chorion layer—the amnion layer act as a biofilm for the healing of burn wound and non-healing ulcers. The freshly collected membrane has stem cells, cytokines, growth factors, and anti-inflammatory properties, which act as a biofilm for the healing of wounds. It functions as a barrier and prevents heat and water loss and also protects from bacterial contamination, thus supporting the healing process. The application of Amnion membranes has been successfully used for wound and reconstructive purposes for decades. It is a very cheap and easy process and has shown superior results to allograft and xenograft. However, there are very few case reports of amnion membrane grafting in newborns; we intend to highlight its therapeutic importance in burn injuries in newborns. We present a case of 9 days old male neonate who presented to the neonatal unit of Maulana Azad Medical College with a complaint of fluid-filled blisters and burns wound on the body for six days. He was born outside the hospital at 38 weeks of gestation to a 24-year-old primigravida mother by vaginal delivery. The presentation was cephalic and the amniotic fluid was clear. His birth weight was 2800 gm and APGAR scores were 7 and 8 at 1 and 5 minutes, respectively. His anthropometry was appropriate for gestational age. He developed respiratory distress after birth requiring oxygen support by nasal prongs for three days. On the day of life three, he developed blisters on his body, starting from than face then over the back and perineal region. At a presentation on the day of life nine, he had blisters and necrotic wound on the right side of the face, back, right shoulder and genitalia, affecting 60% of body surface area with full-thickness loss of skin. He was started on intravenous antibiotics and fluid therapy. Pus culture grew Pseudomonas aeuroginosa, for which culture-specific antibiotics were started. Plastic surgery reference was taken and regular wound dressing was done with antiseptics. He had a storming course during the hospital stay. On the day of life 35 when the baby was hemodynamically stable, amnion membrane grafting was done on the wound site; for the grafting, fresh amnion membrane was removed under sterile conditions from the placenta obtained by caesarean section. It was then transported to the plastic surgery unit in half an hour in a sterile fluid where the graft was applied over the infant’s wound. The amnion membrane grafting was done twice in two weeks for covering the whole wound area. After successful uptake of amnion membrane, skin from the thigh region was autografted over the whole wound area by Meek technique in a single setting. The uptake of autograft was excellent and most of the areas were healed. In some areas, there was patchy regeneration of skin so dressing was continued. The infant was discharged after three months of hospital stay and was later followed up in the plastic surgery unit of the hospital.

Keywords: amnion membrane grafting, autograft, meek technique, newborn, regeneration of skin

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Authors: John Wangui, Charles Gachene, Stephen Mureithi, Boniface Kiteme

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Land use changes caused by demographic, natural variability, economic, technological and policy factors affect the goods and services derived from an ecosystem. In the past few decades, Lake Ol Bolossat catchment in Nyandarua County Kenya has been facing challenges of land cover changes threatening its capacity to perform ecosystems functions and adversely affecting communities and ecosystems downstream. This study assessed land cover changes in the catchment for a period of twenty eight years (from 1986 to 2014). Analysis of three Landsat images i.e. L5 TM 1986, L5 TM 1995 and L8 OLI/TIRS 2014 was done using ERDAS 9.2 software. The results show that dense forest, cropland and area under water increased by 27%, 29% and 3% respectively. On the other hand, open forest, dense grassland, open grassland, bushland and shrubland decreased by 3%, 3%, 11%, 26% and 1% respectively during the period under assessment. The lake was noted to have increased due to siltation caused by soil erosion causing a reduction in Lake’s depth and consequently causing temporary flooding of the wetland. The study concludes that the catchment is under high demographic pressure which would lead to resource use conflicts and therefore formulation of mitigation measures is highly recommended.

Keywords: land cover, land use change, land degradation, Nyandarua, Remote sensing

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Authors: Sakshi Yadav, Sushila Shekhawat

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This study addresses different types of points of view as seen in nature documentary films with the help of three eco documentaries, and it would be significant in understanding the role of the narrative point of view as a tool for showing and telling in documentaries. Narrative analysis of a film forms an essential aspect of the discourse of scholarship in film studies. Narration is the chain of events occurring in time and space. The notion of narrative provides the idea of coherence and wholeness to the story. There are various components that the narration carries, one of which is the perspective or point of view. The narrator plays the role of a mediator between the film and the audience; thus, his perspective influences the way the audience interprets the film. Feature films have been analyzed through narrative points of view; however, this research intends to conduct it from the angle of a nature documentary film. The study will examine narrative viewpoints unique to nature documentary films using three ecological documentary films-The Cove (2009), Tale of a forest (2012), and Before the flood (2016). This research will apply the framework of narrative theory and will investigate the impact of the different types of narrative points of view, as each portrays the human-nature relationship from a different standpoint, and it will also study the effect that the narrative point of view has on the mode of these eco documentaries.

Keywords: ecodocumentary, narrative, human-nature relationship, point of view

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Authors: Julius Niba Fon, Jean Hude E. Moudingo

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Mangrove ecosystems in Cameroon are valuable both in services and functions as they play host to carbon sinks, fishery breeding grounds and natural coastal barriers against storms. In addition to the globally important biodiversity that they contain, they also contribute to local livelihoods. Despite these appraisals, a reduction of about 30 % over a 25 years period due to anthropogenic and natural actions has been recorded. The key drivers influencing mangrove change include population growth, climate change, economic and political trends and upstream habitat use. Reversing the trend of mangrove loss and growing vulnerability of coastal peoples requires a real commitment by the government to develop and implement robust level policies. It has been observed in Cameroon that special ecosystems like mangroves are insufficiently addressed by forestry and/or environment programs. Given these facts, the Food Agriculture Organization (FAO) in partnership with the Government of Cameroon and other development actors have put in place the project for sustainable community-based management and conservation of mangrove ecosystems in Cameroon. The aim is to address two issues notably the present weak institutional and legal framework for mangrove management, and the unrestricted and unsustainable harvesting of mangrove resources. Civil society organizations like the Cameroon Wildlife Conservation Society, Cameroon Ecology and Organization for the Environment and Development have been working to reduce the deforestation and degradation trend of Cameroon mangroves and also bringing the mangrove agenda to the fore in national and international arenas. Following a desktop approach, we found out that in situ and ex situ initiatives on mangrove management and conservation exist on propagation of improved fish smoke ovens to reduce fuel wood consumption, mangrove forest regeneration, shrimps farming and mangrove protected areas management. The evidence generated from the field experiences are inputs for processes of improving the legal and institutional framework for mangrove management in Cameroon, such as the elaboration of norms for mangroves management engaged by the government.

Keywords: mangrove ecosystem, legal and institutional framework, climate change, civil society organizations

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Authors: Anjali Chouksey, Riya Nimje, Jahanvi Saraf

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Online transactions have increased dramatically in this new ‘social-distancing’ era. With online transactions, Fraud in online payments has also increased significantly. Frauds are a significant problem in various industries like insurance companies, baking, etc. These frauds include leaking sensitive information related to the credit card, which can be easily misused. Due to the government also pushing online transactions, E-commerce is on a boom. But due to increasing frauds in online payments, these E-commerce industries are suffering a great loss of trust from their customers. These companies are finding credit card fraud to be a big problem. People have started using online payment options and thus are becoming easy targets of credit card fraud. In this research paper, we will be discussing machine learning algorithms. We have used a decision tree, XGBOOST, k-nearest neighbour, logistic-regression, random forest, and SVM on a dataset in which there are transactions done online mode using credit cards. We will test all these algorithms for detecting fraud cases using the confusion matrix, F1 score, and calculating the accuracy score for each model to identify which algorithm can be used in detecting frauds.

Keywords: machine learning, fraud detection, artificial intelligence, decision tree, k nearest neighbour, random forest, XGBOOST, logistic regression, support vector machine

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Authors: Aishwarya Ravindra Fursule, Shruti Kshirsagar

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In the intersection of artificial intelligence and human-centered computing, this paper delves into speech emotion recognition (SER). It presents a comparative analysis of machine learning models such as K-Nearest Neighbors (KNN),logistic regression, support vector machines (SVM), decision trees, ensemble classifiers, and random forests, applied to SER. The research employs four datasets: Crema D, SAVEE, TESS, and RAVDESS. It focuses on extracting salient audio signal features like Zero Crossing Rate (ZCR), Chroma_stft, Mel Frequency Cepstral Coefficients (MFCC), root mean square (RMS) value, and MelSpectogram. These features are used to train and evaluate the models’ ability to recognize eight types of emotions from speech: happy, sad, neutral, angry, calm, disgust, fear, and surprise. Among the models, the Random Forest algorithm demonstrated superior performance, achieving approximately 79% accuracy. This suggests its suitability for SER within the parameters of this study. The research contributes to SER by showcasing the effectiveness of various machine learning algorithms and feature extraction techniques. The findings hold promise for the development of more precise emotion recognition systems in the future. This abstract provides a succinct overview of the paper’s content, methods, and results.

Keywords: comparison, ML classifiers, KNN, decision tree, SVM, random forest, logistic regression, ensemble classifiers

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Authors: Shinta Holdsworth, Jan Axmacher, Darren J. Mann

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Beetles represent the most diverse insect taxon, and they contribute significantly to a wide range of vital ecological functions. Examples include decomposition by bark beetles, nitrogen recycling and dung processing by dung beetles or pest control by predatory ground beetles. Nonetheless, research into the distribution patterns, species richness and functional diversity of beetles particularly from tropical regions remains extremely limited. In our research, we aim to investigate the distribution and diversity patterns of beetles and the roles they play in small tropical island ecosystems in the Kepulauan Seribu Marine National Park and on Java. Our research furthermore provides insights into the effects anthropogenic activities have on the assemblage composition and diversity of beetles on the small islands. We recorded a substantial number of highly abundant small island species, including a substantial number of unique small island species across the study area, highlighting these islands’ potential importance for the regional conservation of genetic resources. The highly varied patterns observed in relation to the use of different trapping types - pitfall traps and flight interception traps (FITs) - underscores the need for complementary trapping strategies that combine multiple methods for beetle community surveys in tropical islands. The significant impacts of human activities have on the small island beetle faunas were also highlighted in our research. More island beetle species encountered in settlement than forest areas shows clear trend of positive links between anthropogenic activities and the overall beetle species richness. However, undisturbed forests harboured a high number of unique species, also in comparison to disturbed forests. Finally, our study suggests that, with regards to different feeding guilds, the diversity of herbivorous beetles on islands is strongly affected by the different levels of forest cover encountered.

Keywords: beetle diversity, forest disturbance, island biogeography, island settlement

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Authors: Xiao-Yin Liu, Liang-Xue Zhou

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Traumatic brain injury (TBI), as a kind of nerve trauma caused by an external force, affects people all over the world and is a global public health problem. Although there are various clinical treatments for brain injury, including surgery, drug therapy, and rehabilitation therapy, the therapeutic effect is very limited. To improve the therapeutic effect of TBI, scaffolds combined with exosomes are a promising but challenging method for TBI repair. In this study, we examined whether a novel 3D-printed collagen/chitosan scaffold/exosomes derived from neural stem cells (NSCs) pretreated with insulin growth factor-1 (IGF-I) scaffolds (3D-CC-INExos) could be used to improve TBI repair and functional recovery after TBI. Our results showed that composite scaffolds of collagen-, chitosan- and exosomes derived from NSCs pretreated with IGF-I (INExos) could continuously release the exosomes for two weeks. In the rat TBI model, 3D-CC-INExos scaffold transplantation significantly improved motor and cognitive function after TBI, as assessed by the Morris water maze test and modified neurological severity scores. In addition, immunofluorescence staining and transmission electron microscopy showed that the recovery of damaged nerve tissue in the injured area was significantly improved by 3D-CC-INExos implantation. In conclusion, our data suggest that 3D-CC-INExos might provide a potential strategy for the treatment of TBI and lay a solid foundation for clinical translation.

Keywords: traumatic brain injury, exosomes, insulin growth factor-1, neural stem cells, collagen, chitosan, 3D printing, neural regeneration, angiogenesis, functional recovery

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Authors: Rikson Gultom

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Hate Speech and Abusive language on social media is difficult to detect, usually, it is detected after it becomes viral in cyberspace, of course, it is too late for prevention. An early detection system that has a fairly good accuracy is needed so that it can reduce conflicts that occur in society caused by postings on social media that attack individuals, groups, and governments in Indonesia. The purpose of this study is to find an early detection model on Twitter social media using machine learning that has high accuracy from several machine learning methods studied. In this study, the support vector machine (SVM), Naïve Bayes (NB), and Random Forest Decision Tree (RFDT) methods were compared with the Support Vector machine with genetic algorithm (SVM-GA), Nave Bayes with genetic algorithm (NB-GA), and Random Forest Decision Tree with Genetic Algorithm (RFDT-GA). The study produced a comparison table for the accuracy of the hate speech and abusive language detection model, and presented it in the form of a graph of the accuracy of the six algorithms developed based on the Indonesian-language Twitter dataset, and concluded the best model with the highest accuracy.

Keywords: abusive language, hate speech, machine learning, optimization, social media

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Authors: Chondrogianni Dimitra, Yorgos J. Stephanedes

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The impact of the economic crisis, coupled with the aging of the city's old core, is reflected in central Athens. Public and private users, residents, employees, visitors desire the quality upgrading of abandoned buildings and public spaces through environmental upgrading and sustainable mobility, and promotion of the international metropolitan character of the city. In the study, a strategy for reshaping the character and function of the historic Athenian triangle is proposed, aiming at its economic, environmental, and social sustainable development through feasible, meaningful, and non-landscaping solutions of low cost and high positive impact. Sustainable mobility is the main principle in re-planning the study area and transforming it into a “Low Pollution and Limited Vehicle Traffic Zone” is the main strategy. Τhe proposed measures include the development of pedestrian mobility networks by expanding the pedestrian roads and limited-traffic routes, of bicycle networks based on the approved Metropolitan Bicycle Route of Athens, of public transportation networks with new lines of electric mini-buses, and of new regulations for vehicle mobility in the historic triangle. In addition, complementary actions are proposed regarding the provision of Wi-Fi on fixed track media, development of applications that facilitate combined travel and provide real-time data, integration of micromobility (roller skates, Segway, Hoverboard), and its enhancement as a flexible means of personal mobility, and development of car-sharing, ride-sharing and dynamic carpooling initiatives.

Keywords: regeneration plans, sustainable mobility, environmental upgrading, athens historical triangle

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Authors: Shashi Mehta, Krishan Kumar Yadav

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This paper presents an overview of issues pertaining to the conservation of the natural environment and factors affecting the coexistence of the forest, wildlife and people. As forests and wildlife together create the basis for economic, cultural and recreational spaces for overall well-being and life-support systems, the adverse impacts of increasing consumerism are only too evident. The IUCN predicts extinction of 41% of all amphibians and 26% of mammals. The major causes behind this threatened extinction are Deforestation, Dysfunctional governance, Climate Change, Pollution and Cataclysmic phenomena. Thus the intrinsic relationship between natural resources and wildlife needs to be understood in totality, not only for the eco-system but for humanity at large. To demonstrate this, forest areas in the Aravalis- the oldest mountain ranges of Asia—falling in the States of Haryana and Rajasthan, have been taken up for study. The Aravalis are characterized by extreme climatic conditions and dry deciduous forest cover on intermittent scattered hills. Extending across the districts of Gurgaon, Faridabad, Mewat, Mahendergarh, Rewari and Bhiwani, these ranges - with village common land on which the entire economy of the rural settlements depends - fall in the state of Haryana. Aravali ranges with diverse fauna and flora near Alwar town of state of Rajasthan also form part of NCR. Once, rich in biodiversity, the Aravalis played an important role in the sustainable co-existence of forest and people. However, with the advent of industrialization and unregulated urbanization, these ranges are facing deforestation, degradation and denudation. The causes are twofold, i.e. the need of the poor and the greed of the rich. People living in and around the Aravalis are mainly poor and eke out a living by rearing live-stock. With shrinking commons, they depend entirely upon these hills for grazing, fuel, NTFP, medicinal plants and even drinking water. But at the same time, the pressure of indiscriminate urbanization and industrialization in these hills fulfils the demands of the rich and powerful in collusion with Government agencies. The functionaries of federal and State Governments play largely a negative role supporting commercial interests. Additionally, planting of a non- indigenous species like prosopis juliflora across the ranges has resulted in the extinction of almost all the indigenous species. The wildlife in the area is also threatened because of the lack of safe corridors and suitable habitat. In this scenario, the participatory role of different stakeholders such as NGOs, civil society and local community in the management of forests becomes crucial not only for conservation but also for the economic wellbeing of the local people. Exclusion of villagers from protection and conservation efforts - be it designing, implementing or monitoring and evaluating could prove counterproductive. A strategy needs to be evolved, wherein Government agencies be made responsible by putting relevant legislation in place along with nurturing and promoting the traditional wisdom and ethics of local communities in the protection and conservation of forests and wild life in the Aravali ranges of States of Haryana and Rajasthan of the National Capital Region, Delhi.

Keywords: deforestation, ecosystem, governance, urbanization

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Authors: Mahmut Sozmen, Alparslan Kadir Devrim, Yonca Betil Kabak, Tuba Devrim

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Acute myocardial infarction is the leading cause of deaths in the worldwide. Mature cardiomyocytes do not have the ability to regenerate instead fibrous tissue proliferate and granulation tissue to fill out. Periostin is an extracellular matrix protein from fasciclin family and it plays an important role in the cell adhesion, migration, and growth of the organism. Periostin prevents apoptosis while stimulating cardiomyocytes. The main objective of this project is to investigate the effects of the recombinant murine periostin peptide administration for the cardiomyocyte regeneration in a rat model of acute myocardial infarction. The experiment was performed on 84 male rats (6 months old) in 4 group each contains 21 rats. Saline applied subcutaneously (1 ml/kg) two times with 24 hours intervals to the rats in control group (Group 1). Recombinant periostin peptide (1 μg/kg) dissolved in saline applied intraperitoneally in group 2 on 1, 3, 7, 14 and 21. days on same dates in group 4. Isoproterenol dissolved in saline applied intraperitoneally (85mg/kg/day) two times with 24 hours intervals to the groups 3 and 4. Rats in group 4 further received recombinant periostin peptide (1 μg/kg) dissolved in saline intraperitoneally starting one day after the final isoproterenol administration on days 1, 3, 7, 14 and 21. Following the final application of periostin rats continued to feed routinely with pelleted chow and water ad libitum for further seven days. At the end of 7th day rats sacrificed, blood and heart tissue samples collected for the immunohistochemical and biochemical analysis. Angiogenesis in response to tissue damage, is a highly dynamic process regulated by signals from the surrounding extracellular matrix and blood serum. In this project, VEGF, ANGPT, bFGF, TGFβ are the key factors that contribute to cardiomyocyte regeneration were investigated. Additionally, the relationship between mitosis and apoptosis (Bcl-2, Bax, PCNA, Ki-67, Phopho-Histone H3), cell cycle activators and inhibitors (Cyclin D1, D2, A2, Cdc2), the origin of regenerating cells (cKit and CD45) were examined. Present results revealed that periostin stimulated cardiomyocye cell-cycle re-entry in both normal and MCA damaged cardiomyocytes and increased angiogenesis. Thus, periostin contributes to cardiomyocyte regeneration during the healing period following myocardial infarction which provides a better understanding of its role of this mechanism, improving recovery rates and it is expected to contribute the lack of literature on this subject. Acknowledgement: This project was financially supported by Turkish Scientific Research Council- Agriculture, Forestry and Veterinary Research Support Group (TUBİTAK-TOVAG; Project No: 114O734), Ankara, TURKEY.

Keywords: cardiotoxicity, immunohistochemistry, isoproterenol, periostin

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Authors: Titinan Pothong, Prasit Wangpakapattanawong, Stephen Elliott

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Shifting cultivation is an indigenous agricultural practice among upland people and has long been one of the major land-use systems in Southeast Asia. As a result, fallows and secondary forests have come to cover a large part of the region. However, they are increasingly being replaced by monocultures, such as corn cultivation. This is believed to be a main driver of deforestation and forest degradation, and one of the reasons behind the recurring winter smog crisis in Thailand and around Southeast Asia. Accurate biomass estimation of trees is important to quantify valuable carbon stocks and changes to these stocks in case of land use change. However, presently, Thailand lacks proper tools and optimal equations to quantify its carbon stocks, especially for secondary evergreen forests, including fallow areas after shifting cultivation and smaller trees with a diameter at breast height (DBH) of less than 5 cm. Developing new allometric equations to estimate biomass is urgently needed to accurately estimate and manage carbon storage in tropical secondary forests. This study established new equations using a destructive method at three study sites: approximately 50-year-old secondary forest, 4-year-old fallow, and 7-year-old fallow. Tree biomass was collected by harvesting 136 individual trees (including coppiced trees) from 23 species, with a DBH ranging from 1 to 31 cm. Oven-dried samples were sent for carbon analysis. Wood density was calculated from disk samples and samples collected with an increment borer from 79 species, including 35 species currently missing from the Global Wood Densities database. Several models were developed, showing that aboveground biomass (AGB) was strongly related to DBH, height (H), and wood density (WD). Including WD in the model was found to improve the accuracy of the AGB estimation. This study provides insights for reforestation management, and can be used to prepare baseline data for Thailand’s carbon stocks for the REDD+ and other carbon trading schemes. These may provide monetary incentives to stop illegal logging and deforestation for monoculture.

Keywords: aboveground biomass, allometric equation, carbon stock, secondary forest

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Authors: Urvi Panwar, Kanchan Mishra, Kanjaksha Ghosh, ShankerLal Kothari

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Background: Day-by-day the increasing prevalence of neurodegenerative diseases have become a global issue to manage them by medical sciences. The adult neural stem cells are rare and require an invasive and painful procedure to obtain it from central nervous system. Mesenchymal stem cell (MSCs) therapies have shown remarkable application in treatment of various cell injuries and cell loss. MSCs can be derived from various sources like adult tissues, human bone marrow, umbilical cord blood and cord tissue. MSCs have similar proliferation and differentiation capability, but the human umbilical cord-derived mesenchymal stem cells (hUCMSCs) are proved to be more beneficial with respect to cell procurement, differentiation to other cells, preservation, and transplantation. Material and method: Human umbilical cord is easily obtainable and non-controversial comparative to bone marrow and other adult tissues. The umbilical cord can be collected after delivery of baby, and its tissue can be cultured using explant culture method. Cell culture medium such as DMEMF12+10% FBS and DMEMF12+Neural growth factors (bFGF, human noggin, B27) with antibiotics (Streptomycin/Gentamycin) were used to culture and differentiate mesenchymal stem cells into neural cells, respectively. The characterisations of MSCs were done with Flow Cytometer for surface markers CD90, CD73 and CD105 and colony forming unit assay. The differentiated various neural cells will be characterised by fluorescence markers for neurons, astrocytes, and oligodendrocytes; quantitative PCR for genes Nestin and NeuroD1 and Western blotting technique for gap43 protein. Result and discussion: The high quality and number of MSCs were isolated from human umbilical cord via explant culture method. The obtained MSCs were differentiated into neural cells like neurons, astrocytes and oligodendrocytes. The differentiated neural cells can be used to treat neural injuries and neural cell loss by delivering cells by non-invasive administration via cerebrospinal fluid (CSF) or blood. Moreover, the MSCs can also be directly delivered to different injured sites where they differentiate into neural cells. Therefore, human umbilical cord is demonstrated to be an inexpensive and easily available source for MSCs. Moreover, the hUCMSCs can be a potential source for neural cell therapies and neural cell regeneration for neural cell injuries and neural cell loss. This new way of research will be helpful to treat and manage neural cell damages and neurodegenerative diseases like Alzheimer and Parkinson. Still the study has a long way to go but it is a promising approach for many neural disorders for which at present no satisfactory management is available.

Keywords: bone marrow, cell therapy, explant culture method, flow cytometer, human umbilical cord, mesenchymal stem cells, neurodegenerative diseases, neuroprotective, regeneration

Procedia PDF Downloads 182

Authors: Simon Grossemy, Peggy P. Y. Chan, Pauline M. Doran

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Nerve tissue engineering is the main field of research aimed at finding an alternative to autografts as a treatment for nerve injuries. Scaffolds are used as a support to enhance nerve regeneration. In order to successfully design novel scaffolds and in vitro cell culture systems, a deep understanding of the factors affecting nerve regeneration processes is needed. Physical and biological parameters associated with the culture environment have been identified as potentially influential in nerve cell differentiation, including electrical stimulation, exposure to extracellular-matrix (ECM) proteins, dynamic medium conditions and co-culture with glial cells. The mechanisms involved in driving the cell to differentiation in the presence of these factors are poorly understood; the complexity of each of them raises the possibility that they may strongly influence each other. Some questions that arise in investigating nerve regeneration include: What are the best protein coatings to promote neural cell attachment? Is the scaffold design suitable for providing all the required factors combined? What is the influence of dynamic stimulation on cell viability and differentiation? In order to study these effects, scaffolds adaptable to bioreactor culture conditions were designed to allow electrical stimulation of cells exposed to ECM proteins, all within a dynamic medium environment. Gold coatings were used to make the surface of viscose rayon microfiber scaffolds (VRMS) conductive, and poly-L-lysine (PLL) and laminin (LN) surface coatings were used to mimic the ECM environment and allow the attachment of rat PC12 neural cells. The robustness of the coatings was analyzed by surface resistivity measurements, scanning electron microscope (SEM) observation and immunocytochemistry. Cell attachment to protein coatings of PLL, LN and PLL+LN was studied using DNA quantification with Hoechst. The double coating of PLL+LN was selected based on high levels of PC12 cell attachment and the reported advantages of laminin for neural differentiation. The underlying gold coatings were shown to be biocompatible using cell proliferation and live/dead staining assays. Coatings exhibiting stable properties over time under dynamic fluid conditions were developed; indeed, cell attachment and the conductive power of the scaffolds were maintained over 2 weeks of bioreactor operation. These scaffolds are promising research tools for understanding complex neural cell behavior. They have been used to investigate major factors in the physical culture environment that affect nerve cell viability and differentiation, including electrical stimulation, bioreactor hydrodynamic conditions, and combinations of these parameters. The cell and tissue differentiation response was evaluated using DNA quantification, immunocytochemistry, RT-qPCR and functional analyses.

Keywords: bioreactor, electrical stimulation, nerve differentiation, PC12 cells, scaffold

Procedia PDF Downloads 219

Authors: Marizia Roberta Rasoanandrasana, Hery Lisy Tiana. Ranarijaona, Herintsitohaina Razakamanarivo, Eric Delaitre, Nandrianina Ramifehiarivo

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Madagascar is one of the producer’s countries of world's fine cocoa. Cocoa-based agroforestry systems (CBAS) plays a very important economic role for over 75% of the population in the north of Madagascar, the island's main cocoa-producing area. It is also viewed as a key factor in the deforestation of local protected areas. It is therefore urgent to establish a compromise between cocoa production and forest conservation in this region which is difficult due to a lack of accurate cocoa agro-systems data. In order to fill these gaps and to response to these socio-economic and environmental concerns, this study aims to describe CBAS by providing precise data on their characteristics and to establish a typology. To achieve this, 150 farms were surveyed and observed to characterize CBAS based on 11 agronomic and 6 socio-economic data. Also, 30 representative plots of CBAS among the 150 farms were inventoried for providing accurate ecological data (6 variables) as an additional data for the typology determination. The results showed that Madagascar’s CBAS systems are generally extensive and practiced by smallholders. Four types of cocoa-based agroforestry system were identified, with significant differences between the following variables: yield, planting age, cocoa density, density of associated trees, preceding crop, associated crops, Shannon-Wiener indices and species richness in the upper stratum. Type 1 is characterized by old systems (>45 years) with low crop density (425 cocoa trees/ha), installed after conversion of crops other than coffee (> 50%) and giving low yields (427 kg/ha/year). Type 2 consists of simple agroforestry systems (no associated crop 0%), fairly young (20 years) with low density of associated trees (77 trees/ha) and low species diversity (H'=1.17). Type 3 is characterized by high crop density (778 trees/ha and 175 trees/ha for cocoa and associated trees respectively) and a medium level of species diversity (H'=1.74, 8 species). Type 4 is particularly characterized by orchard regeneration method involving replanting and tree lopping (100%). Analysis of the potential of these four types has identified Type 4 as a promising practice for sustainable agriculture.

Keywords: conservation, practices, productivity, protect areas, smallholder, trade-off, typology

Procedia PDF Downloads 73

Authors: Hager Elsheikh

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Context: Pancreatitis is a condition characterized by inflammation in the pancreas, which can lead to serious complications if untreated. Both acute and chronic pancreatitis are associated with immune reactions and fibrosis, which further damage the pancreas. The type 2 immune response, primarily driven by alternative activated macrophages (AAMs), plays a significant role in the development of fibrosis. The IL-4/STAT6 pathway is a crucial signaling pathway for the activation of M2 macrophages. Pancreatic fibrosis is induced by dysregulated inflammatory responses and can result in the autodigestion and necrosis of pancreatic acinar cells. Research Aim: The aim of this study is to investigate the impact of STAT6, a crucial molecule in the IL-4/STAT6 pathway, on the severity and development of fibrosis during acute and chronic pancreatitis. The research also aims to understand the influence of the JAK/STAT6 signaling pathway on the balance between fibrosis and regeneration in the presence of different macrophage populations. Methodology: The research utilizes murine models of acute and chronic pancreatitis induced by cerulean injection. Animal models will be employed to study the effect of STAT6 knockout on disease severity and fibrosis. Isolation of acinar cells and cell culture techniques will be used to assess the impact of different macrophage populations on wound healing and regeneration. Various techniques such as PCR, histology, immunofluorescence, and transcriptomics will be employed to analyze the tissues and cells. Findings: The research aims to provide insights into the mechanisms underlying tissue fibrosis and wound healing during acute and chronic pancreatitis. By investigating the influence of the JAK/STAT6 signaling pathway and different macrophage populations, the study aims to understand their impact on tissue fibrosis, disease severity, and pancreatic regeneration. Theoretical Importance: This research contributes to our understanding of the role of specific signaling pathways, macrophage polarization, and the type 2 immune response in pancreatitis. It provides insights into the molecular mechanisms underlying tissue fibrosis and the potential for targeted therapies. Data Collection and Analysis Procedures: Data will be collected through the use of murine models, isolation and culture of acinar cells, and various experimental techniques such as PCR, histology, immunofluorescence, and transcriptomics. Data will be analyzed using appropriate statistical methods and techniques, and the findings will be interpreted in the context of the research objectives. Conclusion: By investigating the mechanisms of tissue fibrosis and wound healing during acute and chronic pancreatitis, this research aims to enhance our understanding of the disease progression and potential therapeutic targets. The findings have theoretical importance in expanding our knowledge of pancreatic fibrosis and the role of macrophage polarization in the context of the type 2 immune response.

Keywords: immunity in chronic diseases, pancreatitis, macrophages, immune response

Procedia PDF Downloads 18

Authors: Muhtasim Shafi Kader, Fizar Ahmed, Annesha Acharjee

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Machine learning and data mining are crucial in health care, as well as medical information and detection. Machine learning approaches are now being utilized to improve awareness of a variety of critical health issues, including diabetes detection, neuron cell tumor diagnosis, COVID 19 identification, and so on. Parkinson’s disease is basically a disease for our senior citizens in Bangladesh. Parkinson's Disease indications often seem progressive and get worst with time. People got affected trouble walking and communicating with the condition advances. Patients can also have psychological and social vagaries, nap problems, hopelessness, reminiscence loss, and weariness. Parkinson's disease can happen in both men and women. Though men are affected by the illness at a proportion that is around partial of them are women. In this research, we have to get out the accurate ML algorithm to find out the disease with a predictable dataset and the model of the following machine learning classifiers. Therefore, nine ML classifiers are secondhand to portion study to use machine learning approaches like as follows, Naive Bayes, Adaptive Boosting, Bagging Classifier, Decision Tree Classifier, Random Forest classifier, XBG Classifier, K Nearest Neighbor Classifier, Support Vector Machine Classifier, and Gradient Boosting Classifier are used.

Keywords: naive bayes, adaptive boosting, bagging classifier, decision tree classifier, random forest classifier, XBG classifier, k nearest neighbor classifier, support vector classifier, gradient boosting classifier

Procedia PDF Downloads 110

Authors: Akmez Nabeerasool, Michaelis Massaros, Nigel Brown, David Sanderson, David Parocki, Charlotte Thompson, Mike Lodge, Mikael Khan

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The provision of clean and safe drinking water is of paramount importance and is a basic human need. Water scarcity coupled with tightening of regulations and the inability of current treatment technologies to deal with emerging contaminants and Pharmaceuticals and personal care products means that alternative treatment technologies that are viable and cost effective are required in order to meet demand and regulations for clean water supplies. Logistically, the application of water treatment in rural areas presents unique challenges due to the decentralisation of abstraction points arising from low population density and the resultant lack of infrastructure as well as the need to treat water at the site of use. This makes it costly to centralise treatment facilities and hence provide potable water direct to the consumer. Furthermore, across the UK there are segments of the population that rely on a private water supply which means that the owner or user(s) of these supplies, which can serve one household to hundreds, are responsible for the maintenance. The treatment of these private water supply falls on the private owners, and it is imperative that a chemical free technological solution that can operate unattended and does not produce any waste is employed. Arvia’s patented advanced oxidation technology combines the advantages of adsorption and electrochemical regeneration within a single unit; the Organics Destruction Cell (ODC). The ODC uniquely uses a combination of adsorption and electrochemical regeneration to destroy organics. Key to this innovative process is an alternative approach to adsorption. The conventional approach is to use high capacity adsorbents (e.g. activated carbons with high porosities and surface areas) that are excellent adsorbents, but require complex and costly regeneration. Arvia’s technology uses a patent protected adsorbent, Nyex™, which is a non-porous, highly conductive, graphite based adsorbent material that enables it to act as both the adsorbent and as a 3D electrode. Adsorbed organics are oxidised and the surface of the Nyex™ is regenerated in-situ for further adsorption without interruption or replacement. Treated water flows from the bottom of the cell where it can either be re-used or safely discharged. Arvia™ Technology Ltd. has trialled the application of its tertiary water treatment technology in treating reservoir water abstracted near Glasgow, Scotland, with promising results. Several other pilot plants have also been successfully deployed at various locations in the UK showing the suitability and effectiveness of the technology in removing recalcitrant organics (including pharmaceuticals, steroids and hormones), COD and colour.

Keywords: Arvia™ process, adsorption, water treatment, electrochemical oxidation

Procedia PDF Downloads 242

Authors: Antonio Munar-Frau, Sascha Klismoch, Manfred Schmolz, Federico Hernandez-Alfaro, Jordi Caballe-Serrano

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Introduction: Biocompatibility of biomaterials has been proposed as one of the main criteria for treatment success. For guided bone regeneration (GBR), barrier membranes present a conflict given the number of origins and modifications of these materials. The biologic response to biomaterials is orchestrated by a series of events leading to the integration or rejection of the biomaterial, posing questions such as if a longer occlusive property may trigger an inflammatory reaction. Whole blood cultures are a solution to study the immune response to drugs or biomaterials during the first 24-48 hours. The aim of this study is to determine the early immune response of different origins and chemical modifications of barrier membranes. Materials & Methods: 5 different widely used barrier membranes were included in this study: Acellular dermal matrix (AlloDerm, LifeCell®), Porcine Peritoneum (BioGide, Geistlich Pharma®), Porcine Pericardium (Jason, Botiss Biomaterials GmbH®), Porcine Cross-linked collagen (Ossix Plus, Datum Dental®) and d-PTFE (Cytoplast TXT, Osteogenics Biomedical®). Blood samples were extracted from 3 different healthy donors and incubated with the different samples of barrier membranes for 24 hours. After the incubation time, serum samples were obtained and analyzed by means of biocompatibility assays taking into account 42 markers. Results: In an early stage of the inflammatory response, the Acellular dermal matrix, porcine peritoneum and porcine cross-linked collagen expressed similar patterns of cytokine expression with a great manifestation of ENA 78. Porcine pericardium and d-PTFE presented similar cytokine activation, especially for MMP-3 and MMP-9, although other cytokines were highlighted with lower expression. For the later immune response, Porcine peritoneum and acellular dermal matrix MCP-1 and IL-15 were evident. Porcine pericardium, porcine cross-linked collagen and d-PTFE presented a high expression of IL-16 and lower manifestation of other cytokines. Different behaviors depending on an earlier or later stage of the inflammation process were observed. Barrier membrane inflammatory expression does not only differ depending on the origin, variables such as treatment of the collagen and polymers may also have a great impact on the cytokine expression of the studied barrier membranes during inflammation. Conclusions: Surface treatment and modifications might affect the biocompatibility of the membranes, as different cytokine expressions were evidently depending on the origin of the biomaterial. This study is only a brushstroke regarding the biocompatibility of materials, as it is one of the pioneer studies for ex vivo barrier membranes assays. Studies regarding surface modification are needed in order to clarify mystifications of barrier membrane science.

Keywords: biomaterials, bone regeneration, biocompatibility, inflammation

Procedia PDF Downloads 140

Authors: Samira Bensoltane, Smina Ait Hamlet, Samti Meriem, Semmasel Asma

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Living organisms in the soil are subject to regular fluctuations of abiotic parameters, as well as a chemical contamination of the environment due to human activities. They are subject to multiple stressors they face. The aim of our work was to study the effects of insecticide: thiamethoxam (neonicotinoid), and the potential reversibility of the effects by an antioxidant: ginger on a bioindicator species in ecotoxicology, the land snail Helix aspersa. The effects were studied by a targeted cell approach of evaluating the effect of these molecules on tissue and cellular aspect of hepatopancreas through histological study. Treatment with thiamethoxam concentrations 10, 20, and 40 mg/l shows signs of inflammation even at low concentrations and from the 5th day of treatment. Histological examination of the hepatopancreas of snails treated with thiamethoxam showed significant changes from the lowest concentrations tested , note intertubular connective tissue enlargement, necrosis deferent types of cells (cells with calcium , digestive, excretory) , also damage acini, alteration of the apical membrane and lysis of the basement membrane in a dose- dependent manner. After 10 days of treatment and with 40 mg/l, the same changes were observed with a very advanced degeneration of the wall of the member that could be confused with the cell debris. For cons, the histological study of the hepatopancreas in Helix aspersa treated with ginger for a period of 15 days after stopping treatment with thiamethoxam has shown a partial regeneration of hepatopancreatic tissue snails treated with all concentrations of thiamethoxam and especially in the intertubular connective tissue of the wall and hepatopancreatic digestive tubules. Finally, we can conclude that monitoring the effect of the insecticide thiamethoxam showed significant alterations, however, treatment with ginger shows regeneration of damaged cells themselves much sharper at low concentration (10 mg/L).

Keywords: Helix aspersa, insecticides, thiamethoxam, ginger, hepatopancreas

Procedia PDF Downloads 197

Authors: Krishang Surapaneni

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The goal of this project is to determine how to predict important aspects of options, including the ask price. We want to compare different machine learning models to learn the best model and the best hyperparameters for that model for this purpose and data set. Option pricing is a relatively new field, and it can be very complicated and intimidating, especially to inexperienced people, so we want to create a machine learning model that can predict important aspects of an option stock, which can aid in future research. We tested multiple different models and experimented with hyperparameter tuning, trying to find some of the best parameters for a machine-learning model. We tested three different models: a Random Forest Regressor, a linear regressor, and an MLP (multi-layer perceptron) regressor. The most important feature in this experiment is the ask price; this is what we were trying to predict. In the field of stock pricing prediction, there is a large potential for error, so we are unable to determine the accuracy of the models based on if they predict the pricing perfectly. Due to this factor, we determined the accuracy of the model by finding the average percentage difference between the predicted and actual values. We tested the accuracy of the machine learning models by comparing the actual results in the testing data and the predictions made by the models. The linear regression model performed worst, with an average percentage error of 17.46%. The MLP regressor had an average percentage error of 11.45%, and the random forest regressor had an average percentage error of 7.42%

Keywords: finance, linear regression model, machine learning model, neural network, stock price

Procedia PDF Downloads 60

Authors: Carlos Amnael Orozco-Diaz, Robert David Moorehead, Gwendolen Reilly, Fiona Gilchrist, Cheryl Ann Miller

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The current gold-standard for maxillofacial reconstruction surgery (MRS) utilizes auto-grafted cancellous bone as a filler. This study was aimed towards developing a polylactic-acid/hydroxyapatite (PLA-HA) composite suitable for fused-deposition 3D printing. Functionalization of the polymer through the addition of HA was directed to promoting bone-regeneration properties so that the material can rival the performance of cancellous bone grafts in terms of bone-lesion repair. This kind of composite enables the production of MRS implants based off 3D-reconstructions from image studies – namely computed tomography – for anatomically-correct fitting. The present study encompassed in-vitro degradation and in-vitro biocompatibility profiling for 3D-printed PLA and PLA-HA composites. PLA filament (Verbatim Co.) and Captal S hydroxyapatite micro-scale HA powder (Plasma Biotal Ltd) were used to produce PLA-HA composites at 5, 10, and 20%-by-weight HA concentration. These were extruded into 3D-printing filament, and processed in a BFB-3000 3D-Printer (3D Systems Co.) into tensile specimens, and were mechanically challenged as per ASTM D638-03. Furthermore, tensile specimens were subjected to accelerated degradation in phosphate-buffered saline solution at 70°C for 23 days, as per ISO-10993-13-2010. This included monitoring of mass loss (through dry-weighing), crystallinity (through thermogravimetric analysis/differential thermal analysis), molecular weight (through gel-permeation chromatography), and tensile strength. In-vitro biocompatibility analysis included cell-viability and extracellular matrix deposition, which were performed both on flat surfaces and on 3D-constructs – both produced through 3D-printing. Discs of 1 cm in diameter and cubic 3D-meshes of 1 cm3 were 3D printed in PLA and PLA-HA composites (n = 6). The samples were seeded with 5000 MG-63 osteosarcoma-like cells, with cell viability extrapolated throughout 21 days via resazurin reduction assays. As evidence of osteogenicity, collagen and calcium deposition were indirectly estimated through Sirius Red staining and Alizarin Red staining respectively. Results have shown that 3D printed PLA loses structural integrity as early as the first day of accelerated degradation, which was significantly faster than the literature suggests. This was reflected in the loss of tensile strength down to untestable brittleness. During degradation, mass loss, molecular weight, and crystallinity behaved similarly to results found in similar studies for PLA. All composite versions and pure PLA were found to perform equivalent to tissue-culture plastic (TCP) in supporting the seeded-cell population. Significant differences (p = 0.05) were found on collagen deposition for higher HA concentrations, with composite samples performing better than pure PLA and TCP. Additionally, per-cell-calcium deposition on the 3D-meshes was significantly lower when comparing 3D-meshes to discs of the same material (p = 0.05). These results support the idea that 3D-printable PLA-HA composites are a viable resorbable material for artificial grafts for bone-regeneration. Degradation data suggests that 3D-printing of these materials – as opposed to other manufacturing methods – might result in faster resorption than currently-used PLA implants.

Keywords: bone regeneration implants, 3D-printing, in vitro testing, biocompatibility, polymer degradation, polymer-ceramic composites

Procedia PDF Downloads 138

Authors: Viacheslav Shkuratskyy, Aminu Bello Usman, Michael O’Dea, Saifur Rahman Sabuj

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This paper examines relationships between solar activity and earthquakes; it applied machine learning techniques: K-nearest neighbour, support vector regression, random forest regression, and long short-term memory network. Data from the SILSO World Data Center, the NOAA National Center, the GOES satellite, NASA OMNIWeb, and the United States Geological Survey were used for the experiment. The 23rd and 24th solar cycles, daily sunspot number, solar wind velocity, proton density, and proton temperature were all included in the dataset. The study also examined sunspots, solar wind, and solar flares, which all reflect solar activity and earthquake frequency distribution by magnitude and depth. The findings showed that the long short-term memory network model predicts earthquakes more correctly than the other models applied in the study, and solar activity is more likely to affect earthquakes of lower magnitude and shallow depth than earthquakes of magnitude 5.5 or larger with intermediate depth and deep depth.

Keywords: k-nearest neighbour, support vector regression, random forest regression, long short-term memory network, earthquakes, solar activity, sunspot number, solar wind, solar flares

Procedia PDF Downloads 53

Authors: Sayyed Benyamin Alavi, Giovanni Cerri, Leila Chennaoui, Ambra Giovannelli, Stefano Mazzoni

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Primary energy consumption and emissions of pollutants (including CO2) sustainability call to search methodologies to lower power absorption for unit of a given product. Cool production plants based on vapour compression are widely used for many applications: air conditioning, food conservation, domestic refrigerators and freezers, special industrial processes, etc. In the field of cool production, the amount of Yearly Consumed Primary Energy is enormous, thus, saving some percentage of it, leads to big worldwide impact in the energy consumption and related energy sustainability. Among various techniques to reduce power required by a Vapour Compression Cool Production Plant (VCCPP), the technique based on Power Regeneration by means of Internal Direct Cycle (IDC) will be considered in this paper. Power produced by IDC reduces power need for unit of produced Cool Power by the VCCPP. The paper contains basic concepts that lead to develop IDCs and the proposed options to use the IDC Power. Among various selections for using turbo machines, Best Economically Available Technologies (BEATs) have been explored. Based on vehicle engine turbochargers, they have been taken into consideration for this application. According to BEAT Database and similarity rules, the best turbo machine selection leads to the minimum nominal power required by VCCPP Main Compressor. Results obtained installing the prototype in “ad hoc” designed test bench will be discussed and compared with the expected performance. Forecasts for the upgrading VCCPP, various applications will be given and discussed. 4-6% saving is expected for air conditioning cooling plants and 15-22% is expected for cryogenic plants.

Keywords: Refrigeration Plant, Vapour Pressure Amplifier, Compressor, Expander, Turbine, Turbomachinery Selection, Power Saving

Procedia PDF Downloads 409