Search results for: protein structure classification

Authors: Gulmira Zhakupova, Tamara Tultabayeva, Aknur Muldasheva, Assem Sagandyk

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The development of technology and production of products with increased biological value based on the use of natural food raw materials are important tasks in the policy of the food market of the Republic of Kazakhstan. For Kazakhstan, livestock farming, in particular sheep farming, is the most ancient and developed industry and way of life. The history of the Kazakh people is largely connected with this type of agricultural production, with established traditions using dairy products from sheep's milk. Therefore, the development of new technologies from sheep’s milk remains relevant. In addition, one of the most promising areas for the development of food technology for therapeutic and prophylactic purposes is sheep milk products as a source of protein, immunoglobulins, minerals, vitamins, and other biologically active compounds. This article presents the results of research on the study of milk processing technology. The objective of the study is to study the possibilities of processing sheep milk and its role in human nutrition, as well as the results of research to improve the technology of sheep milk products. The studies were carried out on the basis of sanitary and hygienic requirements for dairy products in accordance with the following test methods. To perform microbiological analysis, we used the method for identifying Salmonella bacteria (Horizontal method for identifying, counting, and serotyping Salmonella) in a certain mass or volume of product. Nutritional value is a complex of properties of food products that meet human physiological needs for energy and basic nutrients. The protein mass fraction was determined by the Kjeldahl method. This method is based on the mineralization of a milk sample with concentrated sulfuric acid in the presence of an oxidizing agent, an inert salt - potassium sulfate, and a catalyst - copper sulfate. In this case, the amino groups of the protein are converted into ammonium sulfate dissolved in sulfuric acid. The vitamin composition was determined by HPLC. To determine the content of mineral substances in the studied samples, the method of atomic absorption spectrophotometry was used. The study identified the technological parameters of sheep milk products and determined the prospects for researching sheep milk products. Microbiological studies were used to determine the safety of the study product. According to the results of the microbiological analysis, no deviations from the norm were identified. This means high safety of the products under study. In terms of nutritional value, the resulting products are high in protein. Data on the positive content of amino acids were also obtained. The results obtained will be used in the food industry and will serve as recommendations for manufacturers.

Keywords: dairy, milk processing, nutrition, colostrum

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Authors: Saeed Ahmed, Muhammad Imran, Yasir Allah Ditta, Shahid Mehmood, Zahid Rasool

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A study was conducted to investigate the effect of different levels of microencapsulated butyric (MEB) on growth performance, gut health and immunity in commercial broiler chickens. In total, 336 day-old Hubbard classic broilers chicks were randomly assigned to 4 dietary treatments (Control, 0.25, 0.35 and 0.45g/kg of butyric acid) under completely randomized design. Each treatment was replicated 3 times with 28 birds in each replicate. Feed intake, body weight gain, feed conversion ratio, intestinal morphology, apparent ileal digestibility of protein and immunity parameters were evaluated. At the end of the experiment (35-d) 3 birds/replicate in each group were randomly selected and slaughtered to collect blood, duodenal samples and ileal digesta. The data were analyzed by using ANOVA technique. The results indicated improved body weight gain (P = 0.0222), feed conversion ratio (P = 0.0056), duodenal villus height (P = 0.0512), AID (P = 0.0098) antibody titer against Newcastle disease improved (P = 0.0326). Treatments remained unresponsive with respect to feed intake (P = 0.9685).

Keywords: butyric acid, broilers, gut health, ileal digestibility

Procedia PDF Downloads 324

Authors: Fabian Nde Fon

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Decolonisation is one of the hottest topics in most African Universities; this is because many researchers focus on research that does not speak to their immediate community. This research looked at postgraduate research projects that can take students to the community to apply the knowledge that they have learned as an attempt to transform their community. In regards to this, an honours project was designed to try and provide a cheaper and continuous source of protein (egg) using amber-link layers and to investigate the potential of the project to promote postgraduate student development and entrepreneurship. Two ban layer production systems were created: (1) Production system one on a Hill (PS-I) and (2) Production system two in a valley, closer to a dam (PS-II) at Nqutshini, Gingindlovu, KwaZulu-Natal Province. Forty point-of-lay (18 weeks old) amber links were bought at Inverness Rearers and divided into PS-I (20), and PS-II (20), and each of the production systems was further divided into two groups of ten (PS-I-1 and PS-II-1 (partially supplemented) and PS-I-2 and PS-II-2 (supplemented with layer mash)) by a random selection. Birds' weights were balanced in each group to avoid bias. The two groups in each production system were caged separately (1.5x1.5m² for ten birds) and in close proximity. Partially supplemented birds received 0.6 kg of layer mash (60g/per bird/day) and kitchen leftovers daily, and supplemented birds were fed 1.2 kg of layer mash (120g/per bird/day). Egg collection was daily after feeding in the morning while was given ad libitium. The eggs were assessed for internal and external quality after weighing before recording. Egg production from fully supplemented birds (PS-I-2 and PS-II-2) was generally higher (P<0.05) than those of PS-I-1 and PS-II-1. The difference in production was only 6% in the valley while on the Hill, it was only 3%. However, some of the birds in the valley showed signs of respiratory infections, which was not observed with those on the Hill. There are no differences in the internal and external qualities of eggs (york colour and egg shell) determined. This implies that both systems were sustainable. It was suggested members in the community living at the valley or Hill can use these hardy layers as a cheaper source of protein and preferable to the partially supplemented systems because it is relatively cheaper. The smallholder farmers are still pursuing the project long after the students graduate; hence the benefit of the project is reciprocal for both the university and the community (entrepreneurship).

Keywords: animal nutrition, ban layer, production, postgraduate curricula, entrepreneurship

Procedia PDF Downloads 114

Authors: Asma Omri, Noureddine Benothman, Sofiane Sayahi, Fethi Tlili, Hichem Besbes

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Cycling, a popular mode of transportation, can also be perilous due to cyclists' vulnerability to collisions with vehicles and obstacles. This paper presents an innovative cyclist safety system based on radar technology designed to offer real-time collision risk warnings to cyclists. The system incorporates a low-power radar sensor affixed to the bicycle and connected to a microcontroller. It leverages radar point cloud detections, a clustering algorithm, and a supervised classifier. These algorithms are optimized for efficiency to run on the TI’s AWR 1843 BOOST radar, utilizing a coarse classification approach distinguishing between cars, trucks, two-wheeled vehicles, and other objects. To enhance the performance of clustering techniques, we propose a 2-Level clustering approach. This approach builds on the state-of-the-art Density-based spatial clustering of applications with noise (DBSCAN). The objective is to first cluster objects based on their velocity, then refine the analysis by clustering based on position. The initial level identifies groups of objects with similar velocities and movement patterns. The subsequent level refines the analysis by considering the spatial distribution of these objects. The clusters obtained from the first level serve as input for the second level of clustering. Our proposed technique surpasses the classical DBSCAN algorithm in terms of geometrical metrics, including homogeneity, completeness, and V-score. Relevant cluster features are extracted and utilized to classify objects using an SVM classifier. Potential obstacles are identified based on their velocity and proximity to the cyclist. To optimize the system, we used the View of Delft dataset for hyperparameter selection and SVM classifier training. The system's performance was assessed using our collected dataset of radar point clouds synchronized with a camera on an Nvidia Jetson Nano board. The radar-based cyclist safety system is a practical solution that can be easily installed on any bicycle and connected to smartphones or other devices, offering real-time feedback and navigation assistance to cyclists. We conducted experiments to validate the system's feasibility, achieving an impressive 85% accuracy in the classification task. This system has the potential to significantly reduce the number of accidents involving cyclists and enhance their safety on the road.

Keywords: 2-level clustering, coarse classification, cyclist safety, warning system based on radar technology

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Authors: Sina Mahdavi

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Background and Objective: Multiple sclerosis (MS) is an inflammatory autoimmune disease of the CNS that affects the myelination process in the central nervous system (CNS). Complex interactions of various "environmental or infectious" factors may act as triggers in autoimmunity and disease progression. The association between viral infections, especially Human Herpesvirus 6 (HHV-6), and MS is one potential cause that is not well understood. In this study, we aim to summarize the available data on HHV-6 infection in MS disease progression. Materials and Methods: For this study, the keywords "Multiple sclerosis", " Human Herpesvirus 6 ", and "central nervous system" in the databases PubMed and Google Scholar between 2017 and 2022 were searched, and 12 articles were chosen, studied, and analyzed. Results: HHV 6 tends towards TCD 4+ lymphocytes and enters the CNS due to the weakening of the blood-brain barrier due to inflammatory damage. Following the observation that the HHV-6 U24 protein has a seven amino acid sequence with myelin basic protein, which is one of the main components of the myelin sheath, it could cause a molecular mimicry mechanism followed by cross-reactivity. Reactivation of HHV-6 in the CNS can cause the release of proinflammatory cytokines, including TNF-α, leading to immune-mediated demyelination in patients with MS. Conclusion: There is a high expression of endogenous retroviruses during the course of MS, which indicates the relationship between HHV-6 and MS, and that this virus can play a role in the development of MS by creating an inflammatory state. Therefore, measures to modulate the expression of HHV-6 may be effective in reducing inflammatory processes in demyelinated areas of MS patients.

Keywords: multiple sclerosis, human herpesvirus 6, central nervous system, autoimmunity

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Authors: Ali Essam El Shazly

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The slum survey of 'Sequina' area in Alexandria details the building rooms of twenty-building samples according to the integral measure of space syntax. The essence of room organization sets the most integrative 'visitor' domain between the 'inhabitant' wings of less integrated 'parent' than the 'children' structure with visual ring of 'balcony' space. Despite the collective real relative asymmetry of 'pheno-type' aggregation, the relative asymmetry of individual layouts reveals 'geno-type' structure of spatial diversity. The multifunction of rooms optimizes the integral structure of graph and visibility merge, which contrasts with the deep tailing structure of distinctive social domains. The most integrative layout inverts the geno-type into freed rooms of shallow 'inhabitant' domain against the off-centered 'visitor' space, while the most segregated layout further restricts the pheno-type through isolated 'visitor' from 'inhabitant' domains across the 'staircase' public domain. The catalyst 'kitchen & living' spaces demonstrate multi-structural dimensions among the various social domains. The former ranges from most exposed central integrity to the most hidden 'motherhood' territories. The latter, however, mostly integrates at centrality or at the further ringy 'childern' domain. The study concludes social structure of spatial integrity for redevelopment, which is determined through the micro-level survey of rooms with integral dimensions.

Keywords: Alexandria, Sequina slum, spatial integration, space syntax

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Authors: Valentina Narvaez Gaitan, Laura Valentina Rodriguez Leguizamon, Ruben Dario Hernandez B.

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This work describes a physiological signal emulation system that uses electromyography (EMG) signals obtained from muscle sensors in the first instance. These signals are used to extract their characteristics to model and emulate specific arm movements. The main objective of this effort is to develop a new biomedical software system capable of generating physiological signals through the use of embedded systems by establishing the characteristics of the acquired signals. The acquisition system used was Biosignals, which contains two EMG electrodes used to acquire signals from the forearm muscles placed on the extensor and flexor muscles. Processing algorithms were implemented to classify the signals generated by the arm muscles when performing specific movements such as wrist flexion extension, palmar grip, and wrist pronation-supination. Matlab software was used to condition and preprocess the signals for subsequent classification. Subsequently, the mathematical modeling of each signal is performed to be generated by the embedded system, with a validation of the accuracy of the obtained signal using the percentage of cross-correlation, obtaining a precision of 96%. The equations are then discretized to be emulated in the embedded system, obtaining a system capable of generating physiological signals according to the characteristics of medical analysis.

Keywords: classification, electromyography, embedded system, emulation, physiological signals

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Authors: A. Kudrev

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The duplex Poly(A)-Poly(U) denaturation in an aqueous solutions in mixtures with the tetracationic MeTMPyP4 (Me = 2H, Zn(II); TMPyP4 is 5,10,15,20-tetrakis(N-methylpyridinium-4-yl)porphyrin), was investigated by monitoring the changes in the UV-Vis absorbance spectrum with increasing temperatures from 20°С to 70°С (рН 7.0, I=0.15M). The absorbance data matrices were analyzed with a versatile chemometric procedure that provides the melting profile (distribution of species) and the pure spectrum for each chemical species present along the heating experiment. As revealed by the increase of Tm, the duplex structure was stabilized by these porphyrins. The values of stabilization temperature ΔTm in the presence of these porphyrins are relatively large, 1.2-8.4 °C, indicating that the porphyrins contribute differently in stabilizing the duplex Poly(A)-Poly(U) structure. Remarkable is the fact that the porphyrin TMPyP4 was less effective in the stabilization of the duplex structure than the metalloporphyrin Zn(X)TMPyP4 which suggests that metallization play an important role in porphyrin-RNA binding. Molecular Dynamics Simulations has been used to illustrate melting of the duplex dsRNA bound with a porphyrin molecule.

Keywords: melting, Poly(A)-Poly(U), TMPyP4, Zn(X)TMPyP4

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Authors: Massimiliano Biagini, Marco Spinsanti, Gabriella De Angelis, Sara Tomei, Ilaria Ferlenghi, Maria Scarselli, Alessia Biolchi, Alessandro Muzzi, Brunella Brunelli, Silvana Savino, Marzia M. Giuliani, Isabel Delany, Paolo Costantino, Rino Rappuoli, Vega Masignani, Nathalie Norais

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The gram-negative bacterium Neisseria meningitidis serogroup B (MenB) is an exclusively human pathogen representing the major cause of meningitides and severe sepsis in infants and children but also in young adults. This pathogen is usually present in the 30% of healthy population that act as a reservoir, spreading it through saliva and respiratory fluids during coughing, sneezing, kissing. Among surface-exposed protein components of this diplococcus, factor H binding protein is a lipoprotein proved to be a protective antigen used as a component of the recently licensed Bexsero vaccine. fHbp is a highly variable meningococcal protein: to reflect its remarkable sequence variability, it has been classified in three variants (or two subfamilies), and with poor cross-protection among the different variants. Furthermore, the level of fHbp expression varies significantly among strains, and this has also been considered an important factor for predicting MenB strain susceptibility to anti-fHbp antisera. Different methods have been used to assess fHbp expression on meningococcal strains, however, all these methods use anti-fHbp antibodies, and for this reason, the results are affected by the different affinity that antibodies can have to different antigenic variants. To overcome the limitations of an antibody-based quantification, we developed a quantitative Mass Spectrometry (MS) approach. Selected Reaction Monitoring (SRM) recently emerged as a powerful MS tool for detecting and quantifying proteins in complex mixtures. SRM is based on the targeted detection of ProteoTypicPeptides (PTPs), which are unique signatures of a protein that can be easily detected and quantified by MS. This approach, proven to be highly sensitive, quantitatively accurate and highly reproducible, was used to quantify the absolute amount of fHbp antigen in total extracts derived from 105 clinical isolates, evenly distributed among the three main variant groups and selected to be representative of the fHbp circulating subvariants around the world. We extended the study at the genetic level investigating the correlation between the differential level of expression and polymorphisms present within the genes and their promoter sequences. The implications of fHbp expression on the susceptibility of the strain to killing by anti-fHbp antisera are also presented. To date this is the first comprehensive fHbp expression profiling in a large panel of Neisseria meningitidis clinical isolates driven by an antibody-independent MS-based methodology, opening the door to new applications in vaccine coverage prediction and reinforcing the molecular understanding of released vaccines.

Keywords: quantitative mass spectrometry, Neisseria meningitidis, vaccines, bexsero, molecular epidemiology

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Authors: Mohamad F. Jamiluddin, Emeline Sarry, Ana Bejanariu, Cécile Bauche

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Introduction: Over 360 million people are chronically infected with hepatitis B virus (HBV), of whom 1 million die each year from HBV-associated liver cirrhosis or hepatocellular carcinoma. Current treatment options for chronic hepatitis B depend on interferon-α (IFNα) or nucleos(t)ide analogs, which control virus replication but rarely eliminate the virus. Treatment with PEG-IFNα leads to a sustained antiviral response in only one third of patients. After withdrawal of the drugs, the rebound of viremia is observed in the majority of patients. Furthermore, the long-term treatment is subsequently associated with the appearance of drug resistant HBV strains that is often the cause of the therapy failure. Among the new therapeutic avenues being developed, therapeutic vaccine aimed at inducing immune responses similar to those found in resolvers is of growing interest. The high prevalence of chronic hepatitis B necessitates the design of better vaccination strategies capable of eliciting broad-spectrum of cell-mediated immunity(CMI) and humoral immune response that can control chronic hepatitis B. Induction of HBV-specific T cells and B cells by therapeutic vaccination may be an innovative strategy to overcome virus persistence. Lentiviral vectors developed and optimized by THERAVECTYS, due to their ability to transduce non-dividing cells, including dendritic cells, and induce CMI response, have demonstrated their effectiveness as vaccination tools. Method: To develop a HBV therapeutic vaccine that can induce a broad but specific immune response, we generated recombinant lentiviral vector carrying IRES(Internal Ribosome Entry Site)-containing bicistronic constructs which allow the coexpression of two vaccine products, namely HBV T- cell epitope vaccine and HBV virus like particle (VLP) vaccine. HBV T-cell epitope vaccine consists of immunodominant cluster of CD4 and CD8 epitopes with spacer in between them and epitopes are derived from HBV surface protein, HBV core, HBV X and polymerase. While HBV VLP vaccine is a HBV core protein based chimeric VLP with surface protein B-cell epitopes displayed. In order to evaluate the immunogenicity, mice were immunized with lentiviral constructs by intramuscular injection. The T cell and antibody immune responses of the two vaccine products were analyzed using IFN-γ ELISpot assay and ELISA respectively to quantify the adaptive response to HBV antigens. Results: Following a single administration in mice, lentiviral construct elicited robust antigen-specific IFN-γ responses to the encoded antigens. The HBV T- cell epitope vaccine demonstrated significantly higher T cell immunogenicity than HBV VLP vaccine. Importantly, we demonstrated by ELISA that antibodies are induced against both HBV surface protein and HBV core protein when mice injected with vaccine construct (p < 0.05). Conclusion: Our results highlight that THERAVECTYS lentiviral vectors may represent a powerful platform for immunization strategy against chronic hepatitis B. Our data suggests the likely importance of Lentiviral vector based novel bicistronic construct for further study, in combination with drugs or as standalone antigens, as a therapeutic lentiviral based HBV vaccines. THERAVECTYS bicistronic HBV vaccine will be further evaluated in animal efficacy studies.

Keywords: chronic hepatitis B, lentiviral vectors, therapeutic vaccine, virus-like particle

Procedia PDF Downloads 335

Authors: Jaime Carpio-García, Elena Blanco-Fernández, Jorge Rodríguez-Hernández, Daniel Castro-Fresno

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Geosynthetic mechanical behavior vs temperature or vs aging has been widely studied independently during the last years, both in laboratory and in outdoor conditions. This paper studies this behavior deeper, considering that geosynthetics have to perform adequately at different outdoor temperatures once they have been subjected to a certain degree of aging, and also considering the different geosynthetic structures made of the same material. This combining effect has been not considered so far, and it is important to ensure the performance of geosynthetics, especially where high temperatures are expected. In order to fill this gap, six commercial geosynthetics with different internal structures made of polypropylene (PP), high density polyethylene (HDPE), bitumen and polyvinyl chloride (PVC), or even a combination of some of them have been mechanically tested at mild temperature (20ºC or 23ºC) and at warm temperature (45ºC) before and after specific exposition to air at standardized high temperature in order to simulate 25 years of aging due to oxidation. Besides, for 45ºC tests, an innovative heating system during test for high deformable specimens is proposed. The influence of the combining effect of aging, structure and temperature in the product behavior have been analyzed and discussed, concluding that internal structure is more influential than aging in the mechanical behavior of a geosynthetic versus temperature.

Keywords: geosynthetics, mechanical behavior, temperature, aging, internal structure

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Authors: Chithra A. V., Somoshree Datta, Sandeep Nithyanandan

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Sign Language Recognition (SLR) is the process of interpreting and translating sign language into spoken or written language using technological systems. It involves recognizing hand gestures, facial expressions, and body movements that makeup sign language communication. The primary goal of SLR is to facilitate communication between hearing- and speech-impaired communities and those who do not understand sign language. Due to the increased awareness and greater recognition of the rights and needs of the hearing- and speech-impaired community, sign language recognition has gained significant importance over the past 10 years. Technological advancements in the fields of Artificial Intelligence and Machine Learning have made it more practical and feasible to create accurate SLR systems. This paper presents a distinct approach to SLR by framing it as a video classification problem using Deep Learning (DL), whereby a combination of Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) has been used. This research targets the integration of sign language recognition into healthcare settings, aiming to improve communication between medical professionals and patients with hearing impairments. The spatial features from each video frame are extracted using a CNN, which captures essential elements such as hand shapes, movements, and facial expressions. These features are then fed into an RNN network that learns the temporal dependencies and patterns inherent in sign language sequences. The INCLUDE dataset has been enhanced with more videos from the healthcare domain and the model is evaluated on the same. Our model achieves 91% accuracy, representing state-of-the-art performance in this domain. The results highlight the effectiveness of treating SLR as a video classification task with the CNN-RNN architecture. This approach not only improves recognition accuracy but also offers a scalable solution for real-time SLR applications, significantly advancing the field of accessible communication technologies.

Keywords: sign language recognition, deep learning, convolution neural network, recurrent neural network

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Authors: Shamshiri Mitra, Abedi Rahim

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This paper investigates corporate investment behavior and its relationship with ownership structure and financial leverage for the listed company of Tehran stock exchange during 2008-2012. The results show that the concentration of ownership has s significant positive effect on corporate investment. The results for the kind of major owners show that institutional ownership had a positive significant effect and state and individual ownership had negative significant effects on the corporate investment but the effect of corporate ownership was not significant. Furthermore the effect of financial leverage was negative and significant.

Keywords: corporate investment behavior, financial leverage, ownership structure corporate investment behavior

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Authors: Heba Abdelmotaal

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This paper explores the impact of the extent of a company's environmental, social, and governance (ESG) disclosure on credit rating and capital structure. The analysis is based on a sample of 202 firms from the 350 FTSE firms over the period of 2008-2013. ESG disclosure score is measured using Proprietary Bloomberg score based on the extent of a company's Environmental, Social, and Governance (ESG) disclosure. The credit rating is measured by The QuiScore, which is a measure of the likelihood that a company will become bankrupt in the twelve months following the date of calculation. The Capital Structure is measured by long term debt ratio. Two hypotheses are test using panel data regression. The results suggested that the higher degree of ESG disclosure leads to better credit rating. There is significant negative relationship between ESG disclosure and the long term debit percentage. The paper includes implications for the transparency which is resulting of the ESG disclosure could support the Monitoring Function. The monitoring role of disclosure is the increasing in the transparency of the credit rating agencies, also it could affect on managers’ actions. This study provides empirical evidence on the material of ESG disclosure on credit ratings changes and the firms’ capital decision making.

Keywords: capital structure, credit rating agencies, ESG disclosure, panel data regression

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Authors: Madushani Rodrigo, Banuka Athuraliya

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In today's world of medical diagnosis and prediction, machine learning stands out as a strong tool, transforming old ways of caring for health. This study analyzes the use of machine learning in the specialized domain of sports medicine, with a focus on the timely and accurate detection of bone fractures in cricket athletes. Failure to identify bone fractures in real time can result in malunion or non-union conditions. To ensure proper treatment and enhance the bone healing process, accurately identifying fracture locations and types is necessary. When interpreting X-ray images, it relies on the expertise and experience of medical professionals in the identification process. Sometimes, radiographic images are of low quality, leading to potential issues. Therefore, it is necessary to have a proper approach to accurately localize and classify fractures in real time. The research has revealed that the optimal approach needs to address the stated problem and employ appropriate radiographic image processing techniques and object detection algorithms. These algorithms should effectively localize and accurately classify all types of fractures with high precision and in a timely manner. In order to overcome the challenges of misidentifying fractures, a distinct model for fracture localization and classification has been implemented. The research also incorporates radiographic image enhancement and preprocessing techniques to overcome the limitations posed by low-quality images. A classification ensemble model has been implemented using ResNet18 and VGG16. In parallel, a fracture segmentation model has been implemented using the enhanced U-Net architecture. Combining the results of these two implemented models, the FracXpert system can accurately localize exact fracture locations along with fracture types from the available 12 different types of fracture patterns, which include avulsion, comminuted, compressed, dislocation, greenstick, hairline, impacted, intraarticular, longitudinal, oblique, pathological, and spiral. This system will generate a confidence score level indicating the degree of confidence in the predicted result. Using ResNet18 and VGG16 architectures, the implemented fracture segmentation model, based on the U-Net architecture, achieved a high accuracy level of 99.94%, demonstrating its precision in identifying fracture locations. Simultaneously, the classification ensemble model achieved an accuracy of 81.0%, showcasing its ability to categorize various fracture patterns, which is instrumental in the fracture treatment process. In conclusion, FracXpert has become a promising ML application in sports medicine, demonstrating its potential to revolutionize fracture detection processes. By leveraging the power of ML algorithms, this study contributes to the advancement of diagnostic capabilities in cricket athlete healthcare, ensuring timely and accurate identification of bone fractures for the best treatment outcomes.

Keywords: multiclass classification, object detection, ResNet18, U-Net, VGG16

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Authors: M. Reyes, R. Sastre, P. Gabana, F. V. Tinaut

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In this work, an optical characterization of the ethanol-air laminar combustion is presented in order to investigate the origin of the instabilities developed during the combustion, the onset of the cellular structure and the laminar burning velocity. Experimental tests of ethanol-air have been developed in an optical cylindrical constant volume combustion bomb equipped with a Schlieren technique to record the flame development and the flame front surface wrinkling. With this procedure, it is possible to obtain the flame radius and characterize the time when the instabilities are visible through the cell's apparition and the cellular structure development. Ethanol is an aliphatic alcohol with interesting characteristics to be used as a fuel in Internal Combustion Engines and can be biologically synthesized from biomass. Laminar burning velocity is an important parameter used in simulations to obtain the turbulent flame speed, whereas the flame front structure and the instabilities developed during the combustion are important to understand the transition to turbulent combustion and characterize the increment in the flame propagation speed in premixed flames. The cellular structure is spontaneously generated by volume forces, diffusional-thermal and hydrodynamic instabilities. Many authors have studied the combustion of ethanol air and mixtures of ethanol with other fuels. However, there is a lack of works that investigate the instabilities and the development of a cellular structure in ethanol flames, a few works as characterized the ethanol-air combustion instabilities in spherical flames. In the present work, a parametrical study is made by varying the fuel/air equivalence ratio (0.8-1.4), initial pressure (0.15-0.3 MPa) and initial temperature (343-373K), using a design of experiments type I-optimal. In reach mixtures, it is possible to distinguish the cellular structure formed by the hydrodynamic effect and by from the thermo-diffusive. Results show that ethanol-air flames tend to stabilize as the equivalence ratio decreases in lean mixtures and develop a cellular structure with the increment of initial pressure and temperature.

Keywords: ethanol, instabilities, premixed combustion, schlieren technique, cellularity

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Authors: Mi-Hye Hwang, Young Min Son, Kichan Lee, Bang-Hun Hyun, Byeong Yeal Jung

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Botulism is a paralytic disease of human beings and animals caused by neurotoxin produced by Clostridium botulinum. The neurotoxins are genetically distinguished into 8 types, A to H. Ingestion of performed toxin, usually types B, C, and D, have been shown to produce diseases in most cases of cattle botulism. Vaccination is the best measure to prevent cattle botulism. However, the commercially available toxoid-based vaccines are difficult and hazardous to produce. We produced recombinant protein using gene of heavy chain domain of botulinum toxin B of which binds to cellular receptor of neuron cells and used as immunogen. In this study, we evaluated the safety and efficacy of botulism vaccine composed of recombinant types B. Safety test was done by National Regulation for Veterinary Biologicals. For efficacy test, female ICR mice (5 weeks old) were subcutaneously injected, intraperitoneally challenged, and examined the survival rates compared with vaccination and non-vaccination group. Mouse survival rate of recombinant types B vaccine was above 80%, while one of non-vaccination group was 0%. A vaccine composed of recombinant types B was safe and efficacious in mouse. Our results suggest that recombinant heavy chain receptor binding domain can be used as an effective vaccine candidate for type B botulism.

Keywords: botulism, livestock, vaccine, recombinant protein, toxin

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Authors: Omar Qaftan

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Earthquakes can cause tremendous loss of human life and can result in severe damage to a several of civil engineering structures especially the tall buildings. The response of a multistory structure subjected to earthquake loading is a complex task, and it requires to be studied by physical and numerical modelling. For many circumstances, the scale models on shaking table may be a more economical option than the similar full-scale tests. A shaking table apparatus is a powerful tool that offers a possibility of understanding the actual behaviour of structural systems under earthquake loading. It is required to use a set of scaling relations to predict the behaviour of the full-scale structure. Selecting the scale factors is the most important steps in the simulation of the prototype into the scaled model. In this paper, the principles of scaling modelling procedure are explained in details, and the simulation of scaled multi-storey concrete structure for dynamic studies is investigated. A procedure for a complete dynamic simulation analysis is investigated experimentally and numerically with a scale factor of 1/50. The frequency domain accounting and lateral displacement for both numerical and experimental scaled models are determined. The procedure allows accounting for the actual dynamic behave of actual size porotype structure and scaled model. The procedure is adapted to determine the effects of the tall multi-storey structure on a raft foundation. Four generated accelerograms were used as inputs for the time history motions which are in complying with EC8. The output results of experimental works expressed regarding displacements and accelerations are compared with those obtained from a conventional fixed-base numerical model. Four-time history was applied in both experimental and numerical models, and they concluded that the experimental has an acceptable output accuracy in compare with the numerical model output. Therefore this modelling methodology is valid and qualified for different shaking table experiments tests.

Keywords: structure, raft, soil, interaction

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Authors: Noor Khan, Hira Waris

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This study was conducted on genetically male tilapia (GMT) fry reared in glass aquarium for three months to examine the synergetic effect of essential amino acids (EAA) supplementation on growth, body composition, and enzyme activities. Fish having average body weight of 16.56 ± 0.42g were fed twice a day on artificial feed (20% crude protein) procured from Oryza Organics (commercial feed) supplemented with EAA; methionine (M) and lysine (L) designated as T1 (0.3%M and 2%L), T2 (0.6%M and 4%L), T3 (0.9%M and 6%L) and control without EAA. Significantly higher growth performance was observed in T1, followed by T2, T3, and control. The results revealed that whole-body dry matter and crude protein were significantly higher (p ≤ 0.05) in T3 (0.9% and 6%) feeding fish, while the crude fat was lower (p ≤ 0.05) in a similar group of fish. Additionally, protease, amylase, and lipase activities were also observed maximum (p ≤ 0.05) in response to T3 than other treatments and control. However, the EAA, especially lysine and methionine, were found significantly higher (p ≤ 0.05) in T1 compared to other treatments. Conclusively, the addition of EAA, methionine, and lysine in the feed not only enhanced the growth performance of GMT fry but also improved body proximate composition and essential amino acid profile.

Keywords: genetically male tilapia, body composition, digestive enzyme activities, amino acid profile

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Authors: Insaf Ajili, Malik Mallem, Jean-Yves Didier

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Human motion recognition has been extensively increased in recent years due to its importance in a wide range of applications, such as human-computer interaction, intelligent surveillance, augmented reality, content-based video compression and retrieval, etc. However, it is still regarded as a challenging task especially in realistic scenarios. It can be seen as a general machine learning problem which requires an effective human motion representation and an efficient learning method. In this work, we introduce a descriptor based on Laban Movement Analysis technique, a formal and universal language for human movement, to capture both quantitative and qualitative aspects of movement. We use Discrete Hidden Markov Model (DHMM) for training and classification motions. We improve the classification algorithm by proposing two DHMMs for each motion class to process the motion sequence in two different directions, forward and backward. Such modification allows avoiding the misclassification that can happen when recognizing similar motions. Two experiments are conducted. In the first one, we evaluate our method on a public dataset, the Microsoft Research Cambridge-12 Kinect gesture data set (MSRC-12) which is a widely used dataset for evaluating action/gesture recognition methods. In the second experiment, we build a dataset composed of 10 gestures(Introduce yourself, waving, Dance, move, turn left, turn right, stop, sit down, increase velocity, decrease velocity) performed by 20 persons. The evaluation of the system includes testing the efficiency of our descriptor vector based on LMA with basic DHMM method and comparing the recognition results of the modified DHMM with the original one. Experiment results demonstrate that our method outperforms most of existing methods that used the MSRC-12 dataset, and a near perfect classification rate in our dataset.

Keywords: human motion recognition, motion representation, Laban Movement Analysis, Discrete Hidden Markov Model

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Authors: Joshua Bradley, Matthew Buns

Abstract:

This study aimed to identify the effect of concurrent nutritional supplementation on soccer performance as players ingested either carbohydrate CHO (52 g of Cytocarb Maltodextrin) or a combined carbohydrate and protein PRO (Muscle Milk Pro Series 17g CHO + 50 g PRO liquid) supplement. Twelve male, junior college soccer players (age: 18 ± 6 years, wt. 73.3 ± 8.6 kg) completed three trials wearing global positioning systems (GPS) to measure total running distance and sprinting distance during soccer simulation games. The first match simulation was a baseline match with no supplementation. One hour prior to the second match, simulation players were randomly assigned to one of two supplemental groups CHO or CHO + PRO. A repeated measures ANOVA with a Greenhouse-Geisser correction revealed a statistically significant increase in the total distance run for the CHO supplementation group in comparison to the CHO + PRO group (10.19 ± .200 km vs. 9.77± .194km, p = .035). Although the total running distance was meaningfully influenced by the supplementation, the pattern of response for total sprinting distance was not influenced by supplementation. There was a decline in sprinting distance and total running distance from first half to second half, both for the control (M = -0.01 km, SD = 0.17) and CHO supplementation group (-0.04 km, SD = .19), although these differences were not statistically meaningful. There was a positive correlation between sprinting distance and total distance, which was statistically significant (r = -.514, n = 36, p = .01) In conclusion, supplementation influenced the pattern of activity and demonstrated between-trial differences.

Keywords: GPS, nutrition, simulation, supplementation

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Authors: Seokyoon Moon, Yun-Ho Ahn, Heejoong Kim, Sujin Hong, Yunseok Lee, Youngjune Park

Abstract:

Gas hydrate is a non-stoichiometric crystalline compound consisting of host water-framework and low molecular weight guest molecules. Small gaseous molecules such as CH₄, CO₂, and N₂ can be captured in the host water framework lattices of the gas hydrate with specific temperature and pressure conditions. The three well-known crystal structures of structure I (sI), structure II (sII), and structure H (sH) are determined by the size and shape of guest molecules. In this study, we measured the phase equilibria of binary (2,2-dimethyl-1-propanol + CO₂, CH₄, N₂) hydrates to explore their fundamental thermodynamic characteristics. We identified the structure of the binary gas hydrate by employing synchrotron high-resolution powder diffraction (HRPD), and the guest distributions in the lattice of gas hydrate were investigated via dispersive Raman and ¹³C solid-state nuclear magnetic resonance (NMR) spectroscopies. The end-to-end distance of 2,2-dimethyl-1-propanol was calculated to be 7.76 Å, which seems difficult to be enclathrated in large cages of sI or sII. However, due to the flexibility of the host water framework, binary hydrates of sI or sII types can be formed with the help of small gas molecule. Also, the synchrotron HRPD patterns revealed that the binary hydrate structure highly depends on the type of help gases; a cubic Fd3m sII hydrate was formed with CH₄ or N₂, and a cubic Pm3n sI hydrate was formed with CO₂. Interestingly, dispersive Raman and ¹³C NMR spectra showed that the unique tuning phenomenon occurred in binary (2,2-dimethyl-1-propanol + CO₂) hydrate. By optimizing the composition of NPA, we can achieve both thermodynamic stability and high CO₂ storage capacity for the practical application to CO₂ capture.

Keywords: clathrate, gas hydrate, neopentyl alcohol, CO₂, tuning phenomenon

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Authors: Alexander Pesin, Denis Pustovoytov, Mikhail Sverdlik

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Materials with ultrafine-grained structure and unique physical and mechanical properties can be obtained by methods of severe plastic deformation, which include processes of asymmetric rolling (AR). Asymmetric rolling is a very effective way to create ultrafine-grained structures of metals and alloys. Since the asymmetric rolling is a continuous process, it has great potential for industrial production of ultrafine-grained structure sheets. Basic principles of asymmetric rolling are described in detail in scientific literature. In this work finite element modeling of asymmetric rolling and metal forming processes in multiroll gauge was performed. Parameters of the processes which allow achieving significant values of shear strain were defined. The results of the study will be useful for the research of the evolution of ultra-fine metal structure in asymmetric rolling.

Keywords: asymmetric rolling, equivalent strain, FEM, multiroll gauge, profile, severe plastic deformation, shear strain, sheet

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Authors: Gadiri Sabiha

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Introduction : IgE-dependent cow's milk protein allergy (APLV) is one of the most common allergies in children and is one of the three most common allergies observed in children under 6 years of age. Its natural evolution is most often towards healing. The objective is to determine the sensitization profile of patients allergic to cow's milk (VL). Material and method :A retrospective study carried out on a pediatric population (age < 12 years) over a period of four years (2018-2021) in the context of a suspected food allergy to cow's milk proteins carried out on 121 children aged between 8 months -12 years The search for specific IgE was carried out by immunodot (EUROLINE Pediatric; EUROIMMUN) test which allows a semi-quantitative determination of specific IgE. Results 36 patients (29.7%) had a cow's milk protein allergy (ALPV) with a slight female predominance (58.33% girls vs 41.66% boys) The main clinical signs were: acute diarrhoea; vomiting; Intense abdominal pain, and cutaneous signs (pruritus/urticaria) with respective frequencies of 72%; 58%; 44% and 19%. The 3 major and specific VL allergens identified were beta-lactoglobulin 59% caseins 51% and alpha-lactalbumin 29.7%, The profile of sensitization to LV varies according to age, in infants before 1 year of anti-casein, IgE are predominant 83.3%, followed by beta-lactoglobulin 66.66% and alpha-lactolbumin 50% Conclusion CMPA is a frequent pathology which ranks among the three most common food allergies in children. This is the first to appear, most often starting in infants under 6 months old.

Keywords: specific Ige, food allergy, cow 's milk, child

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Authors: Dina Fatmawati, Sofia Mubarika, Mae Sri Wahyuningsih

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Chemotherapy for breast cancer is largely ineffective, but innovative combinations of chemotherapeutic agents and natural compounds represent a promising strategy. In our previous study, the combination of Doxorubicin (Dox) and ethanolic extract of Dioscorea esculenta tuber ((EED) was found to have a synergistic effect on T47D human breast cancer cell line. In this study, we investigated the apoptotic effect of the combination on T47D human breast cancer cells and normal fibroblasts cell line and its effects on the expression of Caspase-3 and cleaved poly (ADP-Ribose) Polymerase-1 (cPARP-1) protein. T47D cell lines and fibroblasts cells were treated with the combination of Dox and EED. Apoptotic effect of the combination was determined using flow cytrometry assay. Protein expressions were determined by immunocytochemistry staining. The percentage of apoptotic cells were significantly higher in T47D cell lines (75%) than that of in fibroblast cells (23%). The expression of Caspase 3 (84.53%) and cPARP-1 (83.36%) were significantly higher in the cancer cell lines than those of normal cells. These results indicate that the combination of doxorubicin and Dioscorea esculenta is a promising candidate for the treatment of breast cancer cells.

Keywords: Dioscorea esculenta, Doxorubicin, apoptosis, immunocytochemistry, cancer cells

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Authors: M. Zain, Thaung H. Aung, Naveed Anwar

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During the service life, a structure may experience extreme loading conditions. The current study proposes a new methodology that covers the effect of uncertainty involved in gravity loadings on key structural elements of new and complex structures by emphasizing on a very realistic assumption that allows the 'Performance-Based Assessment' to be executed on the structure against the gravity loadings. The methodology does not require the complete removal of an element, instead, it permits the incremental reduction in the capacity of key structural elements and preserves the same stiffness of the member in each case of capacity loss. To demonstrate the application of the proposed methodology, a 13 story complex structure is selected that comprises of a diverse structural configuration. The results ensure the structural integrity against the applied gravity loadings, as well as the effectiveness of the proposed methodology.

Keywords: force-deformation relationship, gravity loading, incremental capacity reduction, multi-linear plastic link element, SAP2000, stiffness

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Authors: Nandhana Vivek, Bhaskar Gogoi, Ayyavu Mahesh

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Breast cancer metastasis plays a key role in cancer progression and fatality. The present study examines the potential causes of metastasis in breast cancer by investigating the novel interactions between genes and their pathways. The gene expression profile of GSE99394, GSE1246464, and GSE103865 was downloaded from the GEO data repository to analyze the differentially expressed genes (DEGs). Protein-protein interactions, target factor interactions, pathways and gene relationships, and functional enrichment networks were investigated. The proliferation pathway was shown to be highly expressed in breast cancer progression and metastasis in all three datasets. Gene Ontology analysis revealed 11 DEGs as gene targets to control breast cancer metastasis: LYN, DLGAP5, CXCR4, CDC6, NANOG, IFI30, TXP2, AGTR1, MKI67, and FTH1. Upon studying the function, genomic and proteomic data, and pathway involvement of the target genes, DLGAP5 proved to be a promising candidate due to it being highly differentially expressed in all datasets. The study takes a unique perspective on the avenues through which DLGAP5 promotes metastasis. The current investigation helps pave the way in understanding the role DLGAP5 plays in metastasis, which leads to an increased incidence of death among breast cancer patients.

Keywords: genomics, metastasis, microarray, cancer

Procedia PDF Downloads 97

Authors: Bhavini Patel, Aslihan Ugun-Klusek, Ellen Billet

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The two main contributing factors to familial and idiopathic form of Parkinson’s disease (PD) are oxidative stress and altered proteolysis. Monoamine oxidase-A (MAO-A) plays a significant role in redox homeostasis by producing reactive oxygen species (ROS) via deamination of for example, dopamine. The ROS generated induces chemical modification of proteins resulting in altered biological function. The ubiquitin-proteasome system, which consists of three different types or proteolytic activity, namely “chymotrypsin-like” activity (CLA), “trypsin-like” activity (TLA) and “post acidic-like” activity (PLA), is responsible for the degradation of ubiquitinated proteins. Defects in UPS are known to be strongly correlated to PD. Herein, the effect of ROS generated by MAO-A on proteasome activity and the effects of proteasome inhibition on MAO-A protein levels in WT, mock and MAO-A overexpressed (MAO-A+) SHSY5Y neuroblastoma cell lines were investigated. The data in this study report increased proteolytic activity when MAO-A protein levels are significantly increased, in particular CLA and PLA. Additionally, 20S proteasome inhibition induced a decrease in MAO-A levels in WT and mock cells in comparison to MAO-A+ cells in which 20S proteasome inhibition induced increased MAO-A levels to be further increased at 48 hours of inhibition. This study supports the fact that MAO-A could be a potential pharmaceutical target for neuronal protection as data suggests that endogenous MAO-A levels may be essential for modulating cell death and survival.

Keywords: monoamine oxidase, neurodegeneration, Parkinson's disease, proteasome

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Authors: H. Nikzad, S. Yoshitomi

Abstract:

In this paper, an optimization procedure is applied for 3D Reinforced concrete building structure with shear wall.  In the optimization problem, cross sections of beams, columns and shear wall dimensions are considered as design variables and the optimal cross sections can be derived to minimize the total cost of the structure. As for final design application, the most suitable sections are selected to satisfy ACI 318-14 code provision based on static linear analysis. The validity of the method is examined through numerical example of 15 storied 3D RC building with shear wall.  This optimization method is expected to assist in providing a useful reference in design early stage, and to be an effective and powerful tool for structural design of RC shear wall structures.

Keywords: structural optimization, linear static analysis, ETABS, MATLAB, RC moment frame, RC shear wall structures

Procedia PDF Downloads 254

Authors: Hira Lal Gope, Hidekazu Fukai

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The aim of this study is to develop a system which can identify and sort peaberries automatically at low cost for coffee producers in developing countries. In this paper, the focus is on the classification of peaberries and normal coffee beans using image processing and machine learning techniques. The peaberry is not bad and not a normal bean. The peaberry is born in an only single seed, relatively round seed from a coffee cherry instead of the usual flat-sided pair of beans. It has another value and flavor. To make the taste of the coffee better, it is necessary to separate the peaberry and normal bean before green coffee beans roasting. Otherwise, the taste of total beans will be mixed, and it will be bad. In roaster procedure time, all the beans shape, size, and weight must be unique; otherwise, the larger bean will take more time for roasting inside. The peaberry has a different size and different shape even though they have the same weight as normal beans. The peaberry roasts slower than other normal beans. Therefore, neither technique provides a good option to select the peaberries. Defect beans, e.g., sour, broken, black, and fade bean, are easy to check and pick up manually by hand. On the other hand, the peaberry pick up is very difficult even for trained specialists because the shape and color of the peaberry are similar to normal beans. In this study, we use image processing and machine learning techniques to discriminate the normal and peaberry bean as a part of the sorting system. As the first step, we applied Deep Convolutional Neural Networks (CNN) and Support Vector Machine (SVM) as machine learning techniques to discriminate the peaberry and normal bean. As a result, better performance was obtained with CNN than with SVM for the discrimination of the peaberry. The trained artificial neural network with high performance CPU and GPU in this work will be simply installed into the inexpensive and low in calculation Raspberry Pi system. We assume that this system will be used in under developed countries. The study evaluates and compares the feasibility of the methods in terms of accuracy of classification and processing speed.

Keywords: convolutional neural networks, coffee bean, peaberry, sorting, support vector machine

Procedia PDF Downloads 144