Search results for: Recruitment and Selection

Authors: Maryam Monazzah, Ronak Samadpour, Mehdi Nasr-esfahani, Fatemeh Qalavand, Marziye Motamedi

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Bipolaris sorokiniana, and Heterodera filipjevi, are important wheat diseases that lead to yield losses worldwide. Identifying novel resistant sources helps us combat these devastating diseases. In this study, we studied the role of Cre3 gene and antioxidant enzymes in the immune responses of wheat genotypes to H. filipjevi and B. sorokiniana. Therefore, real-time PCR analysis using Cre3 gene marker, a resistant gene to cereal cyst nematodes, was conducted on leaves and roots, along with changes ‎in the activity of antioxidant enzymes, peroxidase, and catalase. Enzyme activity assay was performed on roots attacked by nematode and in leaves infected with Bipolaris. Wheat accessions including “Bam” (resistant), “Parsi” (moderately-resistant), “Azar2”, “Ohadi”, “Homa” (highly-susceptible) were previously screened against both stresses under greenhouse and field conditions. Results showed that Cre3 expression against cyst nematodes was significantly higher in resistant cultivars compared to susceptible cultivars. Cre3 was used in marker-assisted selection programs to identify genotypes carrying resistant genes to cyst nematodes. Interestingly, Cre3 was also up-regulated in both tissues of resistant cultivars to B. sorokiniana. Therefore, Cre3 in wheat similarly modulates immunity against B. sorokiniana and might be one of the central components of the induced immune system in wheat. The activity of antioxidant enzymes also indicated the highest increase in resistant genotypes upon both stresses that subsequently neutralize oxidative stress in tissues and decrease damage. Further studies on these resistance components may help us gain insight into the molecular basis of resistance and shed new light on the interaction and overlap between different forms of stress.

Keywords: Bipolaris sorokiniana, Heterodera filipjevi, resistant gene expression, wheat

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Authors: Othman E. Othman, Hassan R. Darwish, Amira M. Nowier

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Lactoferrin (LF) is a multifunctional protein involved in economically production traits like milk protein composition and skeletal structure in small ruminants including sheep and goat. So, LF gene - with its genetic polymorphisms associated with production traits - is considered a candidate genetic marker used in marker-assisted selection in goats. This study aimed to identify the different alleles and genotypes of this gene in three Egyptian goat breeds using PCR-SSCP (polymerase chain reaction-single-strand conformation polymorphism) and DNA sequencing. Genomic DNA was extracted from 120 animals belonging to Barki, Zaraibi, and Damascus goat breeds. Using specific primers, PCR amplified 247-bp fragments from exon 2 of LF goat gene. The PCR products were subjected to Single-Strand Conformation Polymorphism (SSCP) technique. The results showed the presence of two genotypes GG and AG in the tested animals. The frequencies of both genotypes varied among the three tested breeds with the highest frequencies of GG genotype in all tested goat breeds. The sequence analysis of PCR products representing these two detected genotypes declared the presence of an SNP (single nucleotide polymorphisms) substitution (G/A) among G and A alleles of this gene. The association between different LF genotypes and milk composition as well as body measurement was estimated. The comparison showed that the animals possess AG genotypes are superior over those with GG genotypes for different parameters of milk protein compositions and skeletal structures. This finding declared that allele A of LF gene is considered the promising marker for the productive traits in goat. In conclusion, the Egyptian goat breeds will be needed to enhance their milk protein composition and growth trait parameters through the increasing of allele A frequency in their herds depending on the superior production traits of this allele in goats.

Keywords: lLactoferrin gene, PCR-SSCP, SNPs, Egyptian goat

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Authors: Zewdneh Zana Zate

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The study focuses on the evolutionary and ecological genomics of both wild and cultivated Coffea arabica L. at its center of origin, Ethiopia, aiming to uncover how this vital species may withstand future climate changes. Utilizing bioclimatic models, we project the future distribution of Arabica under varied climate scenarios for 2050 and 2080, identifying potential conservation zones and immediate risk areas. Through whole-genome resequencing of accessions from Ethiopian gene banks, this research assesses genetic diversity and divergence between wild and cultivated populations. It explores relationships, demographic histories, and potential hybridization events among Coffea arabica accessions to better understand the species' origins and its connection to parental species. This genomic analysis also seeks to detect signs of natural or artificial selection across populations. Integrating these genomic discoveries with ecological data, the study evaluates the current and future ecological and genomic vulnerabilities of wild Coffea arabica, emphasizing necessary adaptations for survival. We have identified key genomic regions linked to environmental stress tolerance, which could be crucial for breeding more resilient Arabica varieties. Additionally, our ecological modeling predicted a contraction of suitable habitats, urging immediate conservation actions in identified key areas. This research not only elucidates the evolutionary history and adaptive strategies of Arabica but also informs conservation priorities and breeding strategies to enhance resilience to climate change. By synthesizing genomic and ecological insights, we provide a robust framework for developing effective management strategies aimed at sustaining Coffea arabica, a species of profound global importance, in its native habitat under evolving climatic conditions.

Keywords: coffea arabica, climate change adaptation, conservation strategies, genomic resilience

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Authors: Abisuga Oluwayemisi Adebola, Kerri Akiwowo, Deon de Beer, Kobus Van Der Walt

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The convergence of additive manufacturing (AM) and traditional textile dyeing techniques has initiated innovative possibilities for improving the visual application and customization potential of 3D-printed polymer objects. Textile dyeing techniques have progressed to transform fabrics with vibrant colours and complex patterns over centuries. The layer-by-layer deposition characteristic of AM necessitates adaptations in dye application methods to ensure even colour penetration across complex surfaces. Compatibility between dye formulations and polymer matrices influences colour uptake and stability, demanding careful selection and testing of dyes for optimal results. This study investigates the development interaction between these areas, revealing the challenges and opportunities of applying textile dyeing methods to colour 3D-printed polymer materials. The method explores three innovative approaches to colour the 3D-printed polymer object: (a) Additive Manufacturing of a Prototype, (b) the traditional dyebath method, and (c) the contemporary digital sublimation technique. The results show that the layer lines inherent to AM interact with dyes differently and affect the visual outcome compared to traditional textile fibers. Skillful manipulation of textile dyeing methods and dye type used for this research reduced the appearance of these lines to achieve consistency and desirable colour outcomes. In conclusion, integrating textile dyeing techniques into colouring 3D-printed polymer materials connects historical craftsmanship with innovative manufacturing. Overcoming challenges of colour distribution, compatibility, and layer line management requires a holistic approach that blends the technical consistency of AM with the artistic sensitivity of textile dyeing. Hence, applying textile dyeing methods to 3D-printed polymers opens new dimensions of aesthetic and functional possibilities.

Keywords: polymer, 3D-printing, sublimation, textile, dyeing, additive manufacturing

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Authors: M. Hirani, M. Devine, O. Obisesan, C. Bryant

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Introduction: The use of four or more implants to support a fixed prosthesis in the edentulous mandible is well documented, with high levels of clinical outcomes recorded. Despite this, the use of three implant-supported fixed prostheses offers the potential to deliver a more cost-effective method of oral rehabilitation in the lower arch, an important consideration given that edentulism is most prevalent in low-income subpopulations. The purpose of this study aimed to evaluate the implant and prosthetic survival rate, changes in marginal bone level, and patient satisfaction associated with a three-implant-supported fixed prosthesis for rehabilitation of the edentulous mandible over a follow-up period of at least one year. Methods: A comprehensive literature search was performed to evaluate studies that met the selection criteria. The information extracted included the study design and population, participant demographics, observation period, loading protocol, and the number of implants placed together with the required outcome measures. Mean values and standard deviations (SD) were calculated using SPSS® (IBM Corporation, New York, USA), and the level of statistical significance across all comparative studies described was set at P < 0.05. Results: The eligible studies included a total of 1968 implants that were placed in 652 patients. The subjects ranged in age from 33-89 years, with a mean of 63.2 years. The mean cumulative implant and prosthetic survival rates were 95.5% and 96.2%, respectively, over a mean follow-up period of 3.25 years. The mean marginal bone loss recorded was 1.04 mm, and high patient satisfaction rates were reported across the studies. Conclusion: Current evidence suggests that a three implant-supported fixed prosthesis for the edentulous mandible is a successful treatment strategy presenting high implant and prosthetic survival rates over the short-to-medium term. Further well-designed controlled clinical trials are required to evaluate longer-term outcomes, with supplemental data correlating implant dimensions and prosthetic design.

Keywords: implants, mandible, fixed, prosthesis

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Authors: Thiago Spilborghs Bueno Meyer, Plinio Thomaz Aquino Junior

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Through speech, which privileges the functional and interactive nature of the text, it is possible to ascertain the spatiotemporal circumstances, the conditions of production and reception of the discourse, the explicit purposes such as informing, explaining, convincing, etc. These conditions allow bringing the interaction between humans closer to the human-robot interaction, making it natural and sensitive to information. However, it is not enough to understand what is said; it is necessary to recognize emotions for the desired interaction. The validity of the use of neural networks for feature selection and emotion recognition was verified. For this purpose, it is proposed the use of neural networks and comparison of models, such as recurrent neural networks and deep neural networks, in order to carry out the classification of emotions through speech signals to verify the quality of recognition. It is expected to enable the implementation of robots in a domestic environment, such as the HERA robot from the RoboFEI@Home team, which focuses on autonomous service robots for the domestic environment. Tests were performed using only the Mel-Frequency Cepstral Coefficients, as well as tests with several characteristics of Delta-MFCC, spectral contrast, and the Mel spectrogram. To carry out the training, validation and testing of the neural networks, the eNTERFACE’05 database was used, which has 42 speakers from 14 different nationalities speaking the English language. The data from the chosen database are videos that, for use in neural networks, were converted into audios. It was found as a result, a classification of 51,969% of correct answers when using the deep neural network, when the use of the recurrent neural network was verified, with the classification with accuracy equal to 44.09%. The results are more accurate when only the Mel-Frequency Cepstral Coefficients are used for the classification, using the classifier with the deep neural network, and in only one case, it is possible to observe a greater accuracy by the recurrent neural network, which occurs in the use of various features and setting 73 for batch size and 100 training epochs.

Keywords: emotion recognition, speech, deep learning, human-robot interaction, neural networks

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Authors: Husam Mohammed Saleh Alziyadi

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The drilling fluid has a significant impact on drilling efficiency. Drilling fluids have several functions which make them most important within the drilling process, such as lubricating and cooling the drill bit, removing cuttings from down of hole, preventing formation damage, suspending drill bit cuttings, , and also removing permeable formation as a result, the flow of fluid into the formation process is delayed. In the oil and gas sector, unconventional shale reserves have been a central player in meeting world energy demands. Oil-based drilling fluids (OBM) are generally favored for drilling shale plays due to negligible chemical interactions. Nevertheless, the industry has been inspired by strict environmental regulations to design water-based drilling fluids (WBM) capable of regulating shale-water interactions to boost their efficiency. However, traditional additives are too large to plug the micro-fractures and nanopores of the shale. Recently, nanotechnology in the oil and gas industries has shown a lot of promise, especially with drilling fluids based on nanoparticles. Nanotechnology has already made a huge contribution to technical developments in the energy sector. In the drilling industry, nanotechnology can make revolutionary changes. Nanotechnology creates nanomaterials with many attractive properties that can play an important role in improving the consistency of mud cake, reducing friction, preventing differential pipe sticking, preserving the stability of the borehole, protecting reservoirs, and improving the recovery of oil and gas. The selection of suitable nanomaterials should be based on the shale formation characteristics intended for drilling. The size, concentration, and stability of the NPs are three more important considerations. The effects of the environment are highly sensitive to these materials, such as changes in ionic strength, temperature, or pH, all of which occur under downhole conditions. This review paper focused on the previous research and recent development of environmentally friendly drilling fluids according to the regulatory environment and cost challenges.

Keywords: nanotechnology, WBM, Drilling Fluid, nanofluids

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Authors: Wade Ghribi, Abdelmoty M. Ahmed, Ahmed Said Badawy, Belgacem Bouallegue

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In higher education institutions, the most pressing priority is to improve student performance and retention. Large volumes of student data are used in Educational Data Mining techniques to find new hidden information from students' learning behavior, particularly to uncover the early symptom of at-risk pupils. On the other hand, data with noise, outliers, and irrelevant information may provide incorrect conclusions. By identifying features of students' data that have the potential to improve performance prediction results, comparing and identifying the most appropriate ensemble learning technique after preprocessing the data, and optimizing the hyperparameters, this paper aims to develop a reliable students' performance prediction model for Higher Education Institutions. Data was gathered from two different systems: a student information system and an e-learning system for undergraduate students in the College of Computer Science of a Saudi Arabian State University. The cases of 4413 students were used in this article. The process includes data collection, data integration, data preprocessing (such as cleaning, normalization, and transformation), feature selection, pattern extraction, and, finally, model optimization and assessment. Random Forest, Bagging, Stacking, Majority Vote, and two types of Boosting techniques, AdaBoost and XGBoost, are ensemble learning approaches, whereas Decision Tree, Support Vector Machine, and Artificial Neural Network are supervised learning techniques. Hyperparameters for ensemble learning systems will be fine-tuned to provide enhanced performance and optimal output. The findings imply that combining features of students' behavior from e-learning and students' information systems using Majority Vote produced better outcomes than the other ensemble techniques.

Keywords: educational data mining, student performance prediction, e-learning, classification, ensemble learning, higher education

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Authors: Maria Do Carmo Baracho De Alencar, Marciene Campos Fialho, Maria Do Carmo Vitório Ramos

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The subjects affected by Repetitive Strain Injury/Work Related Musculoskeletal Disorder (RSI/WRMSD) face an everyday life marked by pain, feelings of worthlessness and incapacity caused by the disease, and aggravated often because of discrimination society. Aim: To investigate the experiences and feelings of workers affected by RSI/WRMSD in removal from work situations and to understand the repercussions on mental health. Methods: Clinical records of workers were consulted, opened from July 1, 2014, to July 1, 2015, at the Reference Center for Worker's Health, in Santos city-SP. Selection of workers affected by RSI /WRMSD and who had experienced the removal from work situation due to the disease, and invitation to participate in the study. Semi-structured and individual interviews were carried out based on a pre-elaborated script, and for thematic content analysis. Results: Of a total of 502 medical records, 157 were selected, and of these, 18 workers participated in the interviews, both gender, most of them with low education level, aged between 35 and 56 years, and from different professions. Diseases affected several physical body regions and some workers had more than one body region affected by chronic pain. In the testimonies emerged the psychic suffering by the process of illness at work, fear of dismissal, invisibility of pain, in medical expertise attendance, by the incapacity to perform tasks that were easily achievable, with feelings of uselessness, revolt, and injustice, among others. Conclusion: The workers need to be readapted to new life situations, and the study promotes reflections on the need for more interdisciplinary actions and of the Psychology to the workers affected by RSI/ WRMSD.

Keywords: repetitive strain injury, cumulative trauma disorder, absence from work, mental health, occupational health

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Authors: Javier Ascanio Villabona, Brayan Eduardo Tarazona Romero, Camilo Leonardo Sandoval Rodriguez, Arly Dario Rincon, Omar Lengerke Perez

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Efficient energy consumption in the housing sector in relation to refrigeration is a concern in the construction and rehabilitation of houses in tropical areas. Thermal comfort is aggravated by heat gain on the roof surface by heat gains. Thus, in the group of passive cooling techniques, one of the practices and technologies in solar control that provide improvements in comfortable conditions are thermal insulation or geometric changes of the roofs. On the other hand, methods with reflection and radiation are the methods used to decrease heat gain by facilitating the removal of excess heat inside a building to maintain a comfortable environment. Since the potential of these techniques varies in different climatic zones, their application in different zones should be examined. This research is based on the experimental study of a prototype of a roof radiator as a method of passive cooling in homes, which was developed through an experimental research methodology making measurements in a prototype built by means of the paradigm of appropriate technology, with the aim of establishing an initial behavior of the internal temperature resulting from the climate of the external environment. As a starting point, a selection matrix was made to identify the typologies of passive cooling systems to model the system and its subsequent implementation, establishing its constructive characteristics. Step followed by the measurement of the climatic variables (outside the prototype) and microclimatic variables (inside the prototype) to obtain a database to be analyzed. As a final result, the decrease in temperature that occurs inside the chamber with respect to the outside temperature was evidenced. likewise, a linearity in its behavior in relation to the variations of the climatic variables.

Keywords: appropriate technology, enveloping, energy efficiency, passive cooling

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Authors: Emmanuel Abayomi Rotimi

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Context: Rabbits production plays important role in increasing animal protein supply in Nigeria. Rabbit production provides a cheap, affordable, and healthy source of meat. The growth of animals involves an increase in body weight, which can change the conformation of various parts of the body. Live weight and linear measurements are indicators of growth rate in rabbits and other farm animals. Aims: This study aimed to define the body dimensions of New Zealand rabbits and also to investigate the morphometric traits variables that contribute to body conformation by the use of principal component analysis (PCA). Methods: Data were obtained from 80 New Zealand rabbits (40 bucks and 40 does) raised in Livestock Teaching and Research Farm, Federal University Dutsinma. Data were taken on body weight (BWT), body length (BL), ear length (EL), tail length (TL), heart girth (HG) and abdominal circumference (AC). Data collected were subjected to multivariate analysis using SPSS 20.0 statistical package. Key results: The descriptive statistics showed that the mean BWT, BL, EL, TL, HG, and AC were 0.91kg, 27.34cm, 10.24cm, 8.35cm, 19.55cm and 21.30cm respectively. Sex showed significant (P<0.05) effect on all the variables examined, with higher values recorded for does. The phenotypic correlation coefficient values (r) between the morphometric traits were all positive and ranged from r = 0.406 (between EL and BL) to r = 0.909 (between AC and HG). HG is the most correlated with BWT (r = 0.786). The principal component analysis with variance maximizing orthogonal rotation was used to extract the components. Two principal components (PCs) from the factor analysis of morphometric traits explained about 80.42% of the total variance. PC1 accounted for 64.46% while PC2 accounted for 15.97% of the total variances. Three variables, representing body conformation, loaded highest in PC1. PC1 had the highest contribution (64.46%) to the total variance, and it is regarded as body conformation traits. Conclusions: This component could be used as selection criteria for improving body weight of rabbits.

Keywords: conformation, multicollinearity, multivariate, rabbits and principal component analysis

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Authors: Juan A. Ferriz-Papi, Allan L. Nantel, Talib E. Butt

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Buildings are thought to consume about 50% of the total energy in the UK. The use stage in a building life cycle has the largest energy consumption, although different assessments are showing that the construction can equal several years of maintenance and operations. The selection of materials with lower embodied energy is very important to reduce this consumption. For this reason, timber is one adequate material due to its low embodied energy and the capacity to be used as carbon storage. The use of timber in the construction industry is very significant. Sawn wood, for example, is one of the top 5 construction materials consumed in the UK according to National Statistics. Embodied energy for building products considers the energy consumed in extraction and production stages. However, it is not the same consideration if this product is produced locally as when considering the resource produced further afield. Transport is a very relevant matter that profoundly influences in the results of embodied energy. The case of timber use in the UK is important because the balance between imports and exports is far negative, industry consuming more imported timber than produced. Nearly 80% of sawn softwood used in construction is imported. The imports-exports deficit for sawn wood accounted for more than 180 million pounds during the first four-month period of 2016. More than 85% of these imports come from Europe (83% from the EU). The aim of this study is to analyze climate change impact due to transport for timber products consumed in the UK. An approximate estimation of energy consumed and carbon emissions are calculated considering the timber product’s import origin. The results are compared to the total consumption of each product, estimating the impact of transport on the final embodied energy and carbon emissions. The analysis of these results can help deduce that one big challenge for climate change is the reduction of external dependency, with the associated improvement of internal production of timber products. A study of different types of timber products produced in the UK and abroad is developed to understand the possibilities for this country to improve sustainability and self-management. Reuse and recycle possibilities are also considered.

Keywords: embodied energy, climate change, CO2 emissions, timber, transport

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Authors: Seyi Olalekan Olawuyi, Abbyssiania Mushunje

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The potential benefits of agricultural production to improve the welfare condition of smallholder farmers in developing countries is no more a news because it has been widely documented. Yet majority of these farming households suffer from shortfall in production output to meet both the consumption needs and market demand which adversely affects output market participation and by extension welfare condition. Therefore, this study investigated the impacts of output market participation on households’ welfare of cassava-based farmers in Oyo State, Nigeria. Multistage sampling technique was used to select 324 sample size used for this study. The findings from the data obtained and analyzed through composite score and crosstab analysis revealed that there is varying degree of output market participation among the farmers which also translate to the observed welfare profile differentials in the study area. The probit model analysis with respect to the selection equation identified gender of household head, household size, access to remittance, off-farm income and ownership of farmland as significant drivers of output market participation in the study area. Furthermore, the treatment effect model of the welfare equation and propensity score matching (PSM) technique were used as robust checks; and the findings attest to the fact that, complimentarily with other significant variables highlighted in this study, output market participation indeed has a significant impact on farming households’ welfare. As policy implication inferences, the study recommends female active inclusiveness and empowerment in farming activities, birth control strategies, secondary income smoothing activities and discouragement of land fragmentation habits, to boost productivity and output market participation, which by extension can significantly improve farming households’ welfare.

Keywords: Cassava market participation, households' welfare, propensity score matching, treatment effect model

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Authors: Shringika Soni, Utkarsh Jain, Nidhi Chauhan

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Aptamers are recently discovered ~80-100 bp long artificial oligonucleotides that not only demonstrated their applications in therapeutics; it is tremendously used in diagnostic and sensing application to detect different biomarkers and drugs. Synthesizing aptamers for proteins or genomic template is comparatively feasible in laboratory, but drugs or other chemical target based aptamers require major specification and proper optimization and validation. One has to optimize all selection, amplification, and characterization steps of the end product, which is extremely time-consuming. Therefore, we performed asymmetric PCR (polymerase chain reaction) for random oligonucleotides pool synthesis, and further use them in Systematic evolution of ligands by exponential enrichment (SELEX) for anti-psychotic drugs based aptamers synthesis. Anti-psychotic drugs are major tranquilizers to control psychosis for proper cognitive functions. Though their low medical use, their misuse may lead to severe medical condition as addiction and can promote crime in social and economical impact. In this work, we have approached the in-vitro SELEX method for ssDNA synthesis for anti-psychotic drugs (in this case ‘target’) based aptamer synthesis. The study was performed in three stages, where first stage included synthesis of random oligonucleotides pool via asymmetric PCR where end product was analyzed with electrophoresis and purified for further stages. The purified oligonucleotide pool was incubated in SELEX buffer, and further partition was performed in the next stage to obtain target specific aptamers. The isolated oligonucleotides are characterized and quantified after each round of partition, and significant results were obtained. After the repetitive partition and amplification steps of target-specific oligonucleotides, final stage included sequencing of end product. We can confirm the specific sequence for anti-psychoactive drugs, which will be further used in diagnostic application in clinical and forensic set-up.

Keywords: anti-psychotic drugs, aptamer, biosensor, ssDNA, SELEX

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Authors: Ambra Giovannelli, Erika Maria Archilei

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The electrical power consumption related to refrigeration systems is evaluated to be in the order of 15% of the total electricity consumption worldwide. For this reason, in the last years several energy saving techniques have been suggested to reduce the power demand of refrigeration and air conditioning plants. The research work deals with the development of an innovative internal power recovery system for industrial cryogenic cooling plants. Such system is based on a Compressor-Expander Group (CEG). Both the expander and the compressor have been designed starting from automotive turbocharging components, strongly modified to take refrigerant fluid properties and specific system requirements into consideration. A preliminary choice of the machines (radial compressors and expanders) among existing components available on the market was realised according to the rules of the similarity theory. Once the expander was selected, it was strongly modified and performance verified by means of steady-state 3D CFD simulations. This paper focuses the attention on the development of the second CEG main component: the compressor. Once the preliminary selection has been done, the compressor geometry has been modified to take the new boundary conditions into account. In particular, the impeller has been machined to address the required total enthalpy increase. Such evaluation has been carried out by means of a simplified 1D model. Moreover, a vaneless diffuser has been added, modifying the shape of casing rear and front disks. To verify the performance of the modified compressor geometry and suggest improvements, a numerical fluid dynamic model has been set up and the commercial Ansys-CFX software has been used to perform steady-state 3D simulations. In this work, all the numerical results will be shown, highlighting critical aspects and suggesting further developments to increase compressor performance and flexibility.

Keywords: vapour compression systems, energy saving, refrigeration plant, organic fluids, centrifugal compressor

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Authors: Azadeh Razzagh Shoar, Hassan Sadeghi Naeini

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There is little doubt that concepts such as space and place have become more common considering that human beings have grown more apart and more than having contact with each other, they are in contact with objects, spaces, and places. Cafés, as a third place which is neither home nor workplace, have attracted these authors’ interests, who are industrial and interior designers. There has been much research on providing suitable cafés, customer behavior, and criteria for spatial sense. However, little research has been carried out on consumerism, desire for variety, and their relationship with changing places, and specifically cafes in term of interior design. In fact, customer’s sense of place has mostly been overlooked. In this case study, authors conducted to challenge the desire for variety and consumerism as well as investigating the addictive factors in cafés. From the designers’ point of view and by collecting data through observing and interviewing café managers, this study investigates and analyzes the customers in two cafes located in a commercial building in northern Tehran (a part of city with above average economic conditions). Since these two cafés are at the same level in terms of interior and spatial design, the question is raised as to why customers patronize the newly built café despite their loyalty to the older café. This study aims to investigate and find the criteria based on the sense of space (café) in a consumerist society, a world where consumption is a myth. Going to cafés in a larger scale than a product can show a selection and finally who you are, where you go, which brand of coffee you prefer, and what time of the day you would like to have your coffee. The results show that since people spend time in cafés more than any other third place, the interaction they have with their environment is more than anything else, and they are consumers of time and place more than coffee or any other product. Also, if there is a sense of consumerism and variety, it is mostly for the place rather than coffee and other products. To satisfy this sense, individuals go to a new place (the new café). It can be easily observed that this sense overshadows the sense of efficiency, design, facilities and all important factor for a café.

Keywords: place, cafe, consumerist society, consumerism, desire for variety

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Authors: Rabbya Ashrafi, Mohammad Tarikul Islam , Al-Amin Bhuiyan, Aminur Rahman

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Injury is the leading killer of children in Bangladesh. Anchal (community crèche) is an effective intervention to prevent injuries among children under 5. Through the SoLiD project, 1,600 Anchals are in place in three sub-districts in Bangladesh. The objectives of the Anchal are to provide supervision and early childhood development stimulations (ECD) to the children. A locally trained caregiver supervises 20-25 children, 9 to 59 months old, from 9 a.m. to 1 p.m., six days a week. Although it was found effective, during its implementation phase several challenges were noticed. To identify challenges and means to overcome those to improve the Anchal activities. In-depth interviews were conducted with Anchal caregivers, their supervisors, and trainers. Focus group discussions were conducted with the mothers of the Anchal children. The study was conducted in the Manohardi sub-district in November 2015. Decay of knowledge and skills after 2-3 months of training, lack of formal certification and inappropriate selection of women as Anchal caregivers, and enrollment of small children (less than 12 months) were the important challenges. The reluctance of parents to send children to the Anchal at the proper time, failure to engage children in various ECD activities, ineffective conduction of parents and community leaders meeting by the Anchal caregivers, insufficient accommodation, and poor supply of logistics for children were also the important challenges. The suggestion for improvement was to recruit caregivers as per standard criteria, provide them refreshers training at three months intervals, train them on effective conduction of parents and community leaders meetings, provide a formal certificate, and ensure regular supply of logistics. The identified challenges are needed to be addressed by utilizing the suggestions obtained from the IDIs and FGDs to make the Anchal intervention more effective in preventing childhood injuries.

Keywords: comunity crech, earlychildhood development, measures for improvement, childhood injury

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Authors: Maysam Mard-Soltani, Mohamad Javad Rasaee, Saeed Khalili, Abdol Karim Sheikhi, Mehdi Hedayati

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Production of specific antibody responses against hTSH is a cumbersome process due to the high identity between the hTSH and the other members of the glycoprotein hormone family (FSH, LH and HCG) and the high identity between the human hTSH and host animals for antibody production. Therefore, two polyclonal antibodies were purified against two recombinant proteins. Four possible ELISA tests were designed based on these antibodies. These ELISA tests were checked against hTSH and other glycoprotein hormones, and their sensitivity and specificity were assessed. Bioinformatics tools were used to analyze the immunological properties. After the immunogen region selection from hTSH protein, c terminal of B hTSH was selected and applied. Two recombinant genes, with these cut pieces (first: two repeats of C terminal of B hTSH, second: tetanous toxin+B hTSH C terminal), were designed and sub-cloned into the pET32a expression vector. Standard methods were used for protein expression, purification, and verification. Thereafter, immunizations of the white New Zealand rabbits were performed and the serums of them were used for antibody titration, purification and characterization. Then, four ELISA tests based on two antibodies were employed to assess the hTSH and other glycoprotein hormones. The results of these assessments were compared with standard amounts. The obtained results indicated that the desired antigens were successfully designed, sub-cloned, expressed, confirmed and used for in vivo immunization. The raised antibodies were capable of specific and sensitive hTSH detection, while the cross reactivity with the other members of the glycoprotein hormone family was minimum. Among the four designed tests, the test in which the antibody against first protein was used as capture antibody, and the antibody against second protein was used as detector antibody did not show any hook effect up to 50 miu/l. Both proteins have the ability to induce highly sensitive and specific antibody responses against the hTSH. One of the antibody combinations of these antibodies has the highest sensitivity and specificity in hTSH detection.

Keywords: hTSH, bioinformatics, protein expression, cross reactivity

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Authors: Mohd Sabri Minhat, Nurul Adilla Mohd Subha

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The 1MWth PUSPATI TRIGA Reactor (RTP) in Malaysia Nuclear Agency has been operating more than 35 years. The existing core power control is using conventional controller known as Feedback Control Algorithm (FCA). It is technically challenging to keep the core power output always stable and operating within acceptable error bands for the safety demand of the RTP. Currently, the system could be considered unsatisfactory with power tracking performance, yet there is still significant room for improvement. Hence, a new design core power control is very important to improve the current performance in tracking and regulating reactor power by controlling the movement of control rods that suit the demand of highly sensitive of nuclear reactor power control. In this paper, the proposed Model Predictive Control (MPC) law was applied to control the core power. The model for core power control was based on mathematical models of the reactor core, MPC, and control rods selection algorithm. The mathematical models of the reactor core were based on point kinetics model, thermal hydraulic models, and reactivity models. The proposed MPC was presented in a transfer function model of the reactor core according to perturbations theory. The transfer function model-based predictive control (TFMPC) was developed to design the core power control with predictions based on a T-filter towards the real-time implementation of MPC on hardware. This paper introduces the sensitivity functions for TFMPC feedback loop to reduce the impact on the input actuation signal and demonstrates the behaviour of TFMPC in term of disturbance and noise rejections. The comparisons of both tracking and regulating performance between the conventional controller and TFMPC were made using MATLAB and analysed. In conclusion, the proposed TFMPC has satisfactory performance in tracking and regulating core power for controlling nuclear reactor with high reliability and safety.

Keywords: core power control, model predictive control, PUSPATI TRIGA reactor, TFMPC

Procedia PDF Downloads 240

Authors: Nureni Amoo, Sunday Aroge, Oluranti Akintola, Hakeem Olujide, Ibrahim Alabi

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This study investigated the optimum landfill site in Osogbo so as to identify suitable solid waste dumpsite for proper waste management in the capital city. Despite an increase in alternative techniques for disposing of waste, landfilling remains the primary means of waste disposal. These changes in attitudes in many parts of the world have been supported by changes in laws and policies regarding the environment and waste disposal. Selecting the most suitable site for landfill can avoid any ecological and socio-economic effects. The increase in industrial and economic development, along with the increase of population growth in Osogbo town, generates a tremendous amount of solid waste within the region. Factors such as the scarcity of land, the lifespan of the landfill, and environmental considerations warrant that the scientific and fundamental studies are carried out in determining the suitability of a landfill site. The analysis of spatial data and consideration of regulations and accepted criteria are part of the important elements in the site selection. This paper presents a multi-criteria decision-making method using geographic information system (GIS) with the integration of the fuzzy logic multi-criteria decision making (FMCDM) technique for landfill suitability site evaluation. By using the fuzzy logic method (classification of suitable areas in the range of 0 to 1 scale), the superposing of the information layers related to drainage, soil, land use/land cover, slope, land use, and geology maps were performed in the study. Based on the result obtained in this study, five (5) potential sites are suitable for the construction of a landfill are proposed, two of which belong to the most suitable zone, and the existing waste disposal site belonged to the unsuitable zone.

Keywords: fuzzy logic multi-criteria decision making, geographic information system, landfill, suitable site, waste disposal

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Authors: Salah A. Aly, Mohammed A. Ibrahim, Mostafa M. khttab

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The amount of construction and demolition (C&D) waste has increased considerably over the last few decades. From the viewpoint of environmental preservation and effective utilization of resources, crushing C&D concrete waste to produce coarse aggregate (CA) with different replacement percentage for the production of new concrete is one common means for achieving a more environment-friendly concrete. In the study presented herein, the investigation was conducted in two phases. In the first phase, the selection of the materials was carried out and the physical, mechanical and chemical characteristics of these materials were evaluated. Different concrete mixes were designed. The investigation parameter was Recycled Concrete Aggregate (RCA) ratios. The mechanical properties of all mixes were evaluated based on compressive strength and workability results. Accordingly, two mixes have been chosen to be used in the next phase. In the second phase, the study of the structural behavior of the concrete beams was developed. Sixteen beams were casted to investigate the effect of RCA ratios, the shear span to depth ratios and the effect of different locations and reinforcement of openings on the shear behavior of the tested specimens. All these beams were designed to fail in shear. Test results of the compressive strength of concrete indicated that, replacement of natural aggregate by up to 50% recycled concrete aggregates in mixtures with 350 Kg/m3 cement content led to increase of concrete compressive strength. Moreover, the tensile strength and the modulus of elasticity of the specimens with RCA have very close values to those with natural aggregates. The ultimate shear strength of beams with RCA is very close to those with natural aggregates indicating the possibility of using RCA as partial replacement to produce structural concrete elements. The validity of both the Egyptian Code for the design and implementation of Concrete Structures (ECCS) 203-2007 and American Concrete Institute (ACI) 318-2011Codes for estimating the shear strength of the tested RCA beams was investigated. It was found that the codes procedures gives conservative estimates for shear strength.

Keywords: construction and demolition (C&D) waste, coarse aggregate (CA), recycled coarse aggregates (RCA), opening

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Authors: Beata Bilska, Marzena Tomaszewska, Danuta Kolozyn-Krajewska

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Food loss and food waste are a global problem of the modern economy. The research undertaken aimed to analyze how food is handled in catering establishments when it comes to food waste and to demonstrate the main ways of management with foods/dishes not served to consumers. A survey study was conducted from January to June 2019. The selection of catering establishments participating in the study was deliberate. The study included establishments located only in Mazowieckie Voivodeship (Poland). Forty-two completed questionnaires were collected. In some questions, answers were based on a 5-point scale of 1 to 5 (from "always" / "every day" to "never"). The survey also included closed questions with a suggested cafeteria of answers. The respondents stated that in their workplaces, dishes served cold and hot ready meals are discarded every day or almost every day (23.7% and 20.5% of answers respectively). A procedure most frequently used for dealing with dishes not served to consumers on a given day is their storage at a cool temperature until the following day. In the research, 1/5 of respondents admitted that consumers "always" or "usually" leave uneaten meals on their plates, and over 41% "sometimes" do so. It was found additionally that food not used in the foodservice sector is most often thrown into a public container for rubbish. Most often thrown into the public container (with communal trash) were: expired products (80.0%), plate waste (80.0%) and inedible products (fruit and vegetable peels, eggshells) (77.5%). Most frequently into the container dedicated only to food waste were thrown out used deep-frying oil (62.5%). 10% of respondents indicated that inedible products in their workplaces are allocated for animal feeds. Food waste in the foodservice sector remains an insufficiently studied issue, as owners of these objects are often unwilling to disclose data about the subject. Incorrect ways of management with foods not served to consumers were observed. There is a need to develop educational activities for employees and management in the context of food waste management in the foodservice sector.

Keywords: food waste, inedible products, plate waste, used deep-frying oil

Procedia PDF Downloads 125

Authors: Efe Çukur

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This study aims to discuss and compare i) widespread and generic design, particularly industrial design education in relation to the specific needs of the automotive/transportation industry, and ii) an automotive/transportation design education model within and under to provide the conditions of design education and automotive industry, especially in Turkey and T.R.N.C. The automotive industry is the 11th largest in the world ($1.51 trillion). One of the most important departments in this industry, along with sales, marketing and engineering, is the design department. The automotive industry is known as the locomotive industry, but there is a non-automotive design department on the academic side of Turkey. This suggestion; includes the presentation of a program proposal that meets the needs of the industry for Turkey and T.R.N.C., the second largest automobile manufacturing country in Europe. On the education side, industrial design education has become a generic title. Automotive design studios are divided into several subgroups. Even in the higher graduate education, the automotive design departments get their subgroups like exterior design and interior design. Transportation design, which is a subfield of industrial design, is offered as higher education in transportation design departments, particularly in America and Europe. In these departments, the curriculum is shaped to the needs of the sectors. Higher education transportation design programs began in the mid-20th century. Until those high education programs...Until these high education programs, the industry has adapted architectures and engineers for designer workloads. Still today transportation design graduates are not the majority of the design studios. The content of the study is an in-depth comparison of these institutions and how the requirements, demands of the industry are met in this regard and revealed. Some of the institutions are selected from Europe and US. To be analyzed under the headings of staff, courses, syllabus, University-Industry collaboration, and location selection. The study includes short, mid, and long term proposals and a hypothesis for discussion. In short, the study will not only provide a wide comparative scope of information on generic and specialized aspects of design education in different countries but also propose a higher education model for automotive / transportation design with solid data of requirements, methodology, and structure regarding learning outcomes, and especially industry cooperation.

Keywords: design education, automotive - transportation design programs, transportation design, automotive industry in Turkey /T.R.N.C., automotive design education in Turkey /T.R.N.C.

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Authors: Manuel A. Alonso-Tarajano, Roberto Mosca, Patrick Aloy

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Protein kinases participate in a myriad of cellular processes of major biomedical interest. The in vivo substrate specificity of these enzymes is a process determined by several factors, and despite several years of research on the topic, is still far from being totally understood. In the present work, we have quantified the contributions to the kinase substrate specificity of i) the phosphorylation sites and their surrounding residues in the sequence and of ii) the association of kinases to adaptor or scaffold proteins. We have used position-specific scoring matrices (PSSMs), to represent the stretches of sequences phosphorylated by 93 families of kinases. We have found negative correlations between the number of sequences from which a PSSM is generated and the statistical significance and the performance of that PSSM. Using a subset of 22 statistically significant PSSMs, we have identified specificity determinant residues (SDRs) for 86% of the corresponding kinase families. Our results suggest that different SDRs can function as positive or negative elements of substrate recognition by the different families of kinases. Additionally, we have found that human proteins with known function as adaptors or scaffolds (kAS) tend to interact with a significantly large fraction of the substrates of the kinases to which they associate. Based on this characteristic we have identified a set of 279 potential adaptors/scaffolds (pAS) for human kinases, which is enriched in Pfam domains and functional terms tightly related to the proposed function. Moreover, our results show that for 74.6% of the kinase– pAS association found, the pAS colocalize with the substrates of the kinases they are associated to. Finally, we have found evidence suggesting that the association of kinases to adaptors and scaffolds, may contribute significantly to diminish the in vivo substrate crossed- specificity of protein kinases. In general, our results indicate the relevance of several SDRs for both the positive and negative selection of phosphorylation sites by kinase families and also suggest that the association of kinases to pAS proteins may be an important factor for the localization of the enzymes with their set of substrates.

Keywords: kinase, phosphorylation, substrate specificity, adaptors, scaffolds, cellular colocalization

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Authors: Halimatus Sakdiah Minhat, Hamizah Sulaiman

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Introduction: Old age is commonly link with menopause among women. The main purpose of this study is to explore the views of middle-aged women and its association with menopause. Methods: Qualitative interviews in the form of focus group discussions (FGD) were conducted among women aged between 35 and 59 years old living in urban localities in two different states in Malaysia. Selection of respondents were conducted using the maximum variation sampling, focussing on five age categories which are between 35 to 39, 40 to 44, 45 to 49, 50 to 54 and 55 to 59 years old. Each FGD involved 5 to 7 respondents and lasted for 1 to 2 hours each. The content of the interviews were recorded, transcribed verbatim after each interview before the next focus group discussion is conducted. Field notes of reflexive observations were recorded by the rapporteur. Individual transcripts were analysed using standard methods of qualitative thematic analysis. The material was read through twice and later coded. The codes were further collapsed into several key themes related to perceptions towards menopause among the respondents. Results: A total number of 36 middle-aged women were consented for the interviews. The contents of the interviews revealed that younger women tend to associate menopause with being old, which were dominated by the younger aged categories of less than 50 years old. Majority of the respondents linked menopause with end of woman’s reproductive capacity or inability to give birth, lethargic or endless feeling of tiredness and insomnia, emotional instability or having more sensitive feelings and also the beginning of many health problems such as osteoarthritis which they perceived very synonyms with being old. Conclusion: The findings of this study indirectly reflect the negative views towards menopause among the middle-aged women in Malaysia. Being residents in the urban areas equipped with advanced technology and health information, do not exclude them from having negative views about menopause. However, this is a qualitative study which only focussing on age ranges, regardless of their socioeconomic and demographic background, which make further studies on related issues are necessaries. The fact that it was a qualitative interview, the findings could not be generalised and only specific to the targeted population.

Keywords: Menopause, Middle-aged women, old, Malaysia

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Authors: Rohini Hariharan, Yazhini R, Bhamidipati Naga Shrikarti

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In the realm of cricket, particularly within the context of the Indian Premier League (IPL), the ability to predict team scores accurately holds significant importance for both cricket enthusiasts and stakeholders alike. This paper presents a comprehensive study on IPL score prediction utilizing various machine learning algorithms, including Support Vector Machines (SVM), XGBoost, Multiple Regression, Linear Regression, K-nearest neighbors (KNN), and Random Forest. Through meticulous data preprocessing, feature engineering, and model selection, we aimed to develop a robust predictive framework capable of forecasting team scores with high precision. Our experimentation involved the analysis of historical IPL match data encompassing diverse match and player statistics. Leveraging this data, we employed state-of-the-art machine learning techniques to train and evaluate the performance of each model. Notably, Multiple Regression emerged as the top-performing algorithm, achieving an impressive accuracy of 77.19% and a precision of 54.05% (within a threshold of +/- 10 runs). This research contributes to the advancement of sports analytics by demonstrating the efficacy of machine learning in predicting IPL team scores. The findings underscore the potential of advanced predictive modeling techniques to provide valuable insights for cricket enthusiasts, team management, and betting agencies. Additionally, this study serves as a benchmark for future research endeavors aimed at enhancing the accuracy and interpretability of IPL score prediction models.

Keywords: indian premier league (IPL), cricket, score prediction, machine learning, support vector machines (SVM), xgboost, multiple regression, linear regression, k-nearest neighbors (KNN), random forest, sports analytics

Procedia PDF Downloads 50

Authors: Altilio Rosa, Chirico Francesco, Foglia Goffredo

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In recent years, the number of Unmanned Aerial Vehicles (UAVs) has significantly increased. The rapid development of commercial and recreational drones makes them an important part of our society. Despite the growing list of their applications, these vehicles pose a huge threat to civil and military installations: detection, classification and neutralization of such flying objects become an urgent need. Radar is an effective remote sensing tool for detecting and tracking flying objects, but scenarios characterized by the presence of a high number of tracks related to flying birds make especially challenging the drone detection task: operator PPI is cluttered with a huge number of potential threats and his reaction time can be severely affected. Flying birds compared to UAVs show similar velocity, RADAR cross-section and, in general, similar characteristics. Building from the absence of a single feature that is able to distinguish UAVs and birds, this paper uses a multiple features approach where an original feature selection technique is developed to feed binary classifiers trained to distinguish birds and UAVs. RADAR tracks acquired on the field and related to different UAVs and birds performing various trajectories were used to extract specifically designed target movement-related features based on velocity, trajectory and signal strength. An optimization strategy based on a genetic algorithm is also introduced to select the optimal subset of features and to estimate the performance of several classification algorithms (Neural network, SVM, Logistic regression…) both in terms of the number of selected features and misclassification error. Results show that the proposed methods are able to reduce the dimension of the data space and to remove almost all non-drone false targets with a suitable classification accuracy (higher than 95%).

Keywords: birds, classification, machine learning, UAVs

Procedia PDF Downloads 218

Authors: Aniketh Ravukutam, Rajath Rao M., Pradyumna S. A.

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In the past few decades there has been great advancement in use of aerodynamics in cars. Now its use has been evident from commercial cars to race cars for achieving higher speeds, stability and efficiency. This paper focusses on studying the effects of aerodynamics in Formula Student car. These cars weigh around 200kgs with an average speed of 60kmph. With increasing competition every year, developing a competitive car is a herculean task. The race track comprises mostly of tight corners and little or no straights thus testing the car’s cornering capabilities. Higher cornering speeds can be achieved by increasing traction at the tires. Studying the aerodynamics helps in achieving higher traction without much addition in overall weight of car. The main focus is to develop an aerodynamic package involving front wing, under tray and body to obtain an optimum value of down force. The initial process involves the detail study of geometrical constraints mentioned in the rule book and calculating the limiting value of drag as per the engine specifications. The successive steps involve conduction of various iterations in ANSYS for selection of airfoils, deciding the number of elements, designing the nose for low drag, channelizing the flow under the body and obtain an optimum value of down force within the limits defined in the initial process. The final step involves design of model using these results in Virtual environment called OptimumLap® for detailed study of performance with and without the presence of aerodynamics. The CFD analysis results showed an overall down force of 377.44N with a drag of 164.08N. The corresponding parameters of the last model were applied in OptimumLap® and an improvement of 3.5 seconds in lap times was observed.

Keywords: aerodynamics, formula student, traction, front wing, undertray, body, rule book, drag, down force, virtual environment, computational fluid dynamics (CFD)

Procedia PDF Downloads 239

Authors: James Ladzekpo

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Background: The urgent need to identify new pharmacological targets for diabetes treatment and prevention has been amplified by the disease's extensive impact on individuals and healthcare systems. A deeper insight into the biological underpinnings of diabetes is crucial for the creation of therapeutic strategies aimed at these biological processes. Current predictive models based on genetic variations fall short of accurately forecasting diabetes. Objectives: Our study aims to pinpoint key epigenetic factors that predispose individuals to diabetes. These factors will inform the development of an advanced predictive model that estimates diabetes risk from genetic profiles, utilizing state-of-the-art statistical and data mining methods. Methodology: We have implemented a recursive feature elimination with cross-validation using the support vector machine (SVM) approach for refined feature selection. Building on this, we developed six machine learning models, including logistic regression, k-Nearest Neighbors (k-NN), Naive Bayes, Random Forest, Gradient Boosting, and Multilayer Perceptron Neural Network, to evaluate their performance. Findings: The Gradient Boosting Classifier excelled, achieving a median recall of 92.17% and outstanding metrics such as area under the receiver operating characteristics curve (AUC) with a median of 68%, alongside median accuracy and precision scores of 76%. Through our machine learning analysis, we identified 31 genes significantly associated with diabetes traits, highlighting their potential as biomarkers and targets for diabetes management strategies. Conclusion: Particularly noteworthy were the Gradient Boosting Classifier and Multilayer Perceptron Neural Network, which demonstrated potential in diabetes outcome prediction. We recommend future investigations to incorporate larger cohorts and a wider array of predictive variables to enhance the models' predictive capabilities.

Keywords: diabetes, machine learning, prediction, biomarkers

Procedia PDF Downloads 53

Authors: A. Čelan, M. Ćosić, D. Rušić, N. Kuzmanić

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Conducting crystallization in an agitated vessel requires a proper selection of mixing parameters that would result in a production of crystals of specific properties. In dual impeller systems, which are characterized by a more complex hydrodynamics due to the possible fluid flow interactions, revealing a clear link between mixing parameters and crystallization kinetics is still an open issue. The aim of this work is to establish this connection by investigating how fluid flow patterns, generated by two impellers mounted on the same shaft, reflect on metastable zone width of borax decahydrate, one of the most important parameters of the crystallization process. Investigation was carried out in a 15-dm³ bench scale batch cooling crystallizer with an aspect ratio (H/T) equal to 1.3. For this reason, two radial straight blade turbines (4-SBT) were used for agitation. Experiments were conducted at different impeller spacings at the state of complete suspension. During the process of an unseeded batch cooling crystallization, solution temperature and supersaturation were continuously monitored what enabled a determination of the metastable zone width. Hydrodynamic conditions in the vessel achieved at different impeller spacings investigated were analyzed in detail. This was done firstly by measuring the mixing time required to attain the desired level of homogeneity. Secondly, fluid flow patterns generated in a described dual impeller system were both photographed and simulated by VisiMix Turbulent software. Also, a comparison of these two visualization methods was performed. Experimentally obtained results showed that metastable zone width is definitely affected by the hydrodynamics in the crystallizer. This means that this crystallization parameter can be controlled not only by adjusting the saturation temperature or cooling rate, as is usually done, but also by choosing a suitable impeller spacing that will result in a formation of crystals of wanted size distribution.

Keywords: dual impeller crystallizer, fluid flow pattern, metastable zone width, mixing time, radial impeller

Procedia PDF Downloads 195