Search results for: machine resistance training

Authors: Kevin V. Bui, Richard A. Claytor, Elizabeth M. Priolo, Weihui Li

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Oxygen deprivation masks operate through the use of restricting valves as a means to reduce respiratory flow where flow is inversely proportional to the resistance applied. This produces the same effect as higher altitudes where lower pressure leads to reduced respiratory flow. Both increased resistance with restricting valves and reduce the pressure of higher altitudes make breathing difficultier and force breathing muscles (diaphragm and intercostal muscles) working harder. The process exercises these muscles, improves their strength and results in overall better breathing efficiency. Currently, these oxygen deprivation masks are purely mechanical devices without any electronic sensor to monitor the breathing condition, thus not be able to provide feedback on the breathing effort nor to evaluate the lung function. That is part of the reason that these masks are mainly used for high-level athletes to mimic training in higher altitude conditions, not suitable for patients or customers. The design aims to improve the current method of oxygen deprivation mask to include a larger scope of patients and customers while providing quantitative biometric data that the current design lacks. This will be accomplished by integrating sensors into the mask’s breathing valves along with data acquisition and Bluetooth modules for signal processing and transmission. Early stages of the sensor mask will measure breathing rate as a function of changing the air pressure in the mask, with later iterations providing feedback on flow rate. Data regarding breathing rate will be prudent in determining whether training or therapy is improving breathing function and quantify this improvement.

Keywords: oxygen deprivation mask, lung function, spirometer, Bluetooth

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Authors: Isaac Ali Kwasu, Aje Tokan

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The research was set to design a manually pedal operated water pump to aid water flow technology for irrigation activities for rural farmers. The development was carried out first by a prototype design to guide the fabrication. All items needed for the fabrication were used for the final product. The machine is operated manually by pedaling. This engages all the parts of the machine into active motion. Energy is generated and transfer finally to the pumping unit which is wired with plastic pipes. The pumping unit which is wired with PVC pipes, both linked to the water source and the reservoir respectively. The (rpm) revolution per minute of the machine is approximated at 3130 depending on the pedaling speed of the user. The machine does not have gear arrangement yet can give high (rpm) for effective performance. The pumping performance of the machine is 125 liters in one minute and can sustain small scale irrigation farming activities and to supplement water management system to sustain crop growth.

Keywords: pump, development, manual, flywheel, sprocket, pulley, machine, v belt, chain, hub, pipe, steel, mechanism, irrigation, prototype, fabrication

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Authors: Chung-Yang Chuang, Chi-Lung Chen, Hui-Min Wang, Chang-Jung Chang

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Conductive fiber is the key material for e-textiles and wearable devices. However, the durability of the conductive fiber after the wash process is an important issue for conductive fiber applications in e-textiles. Therefore, it is necessary for conductive fiber with good performance on electrically conductive behavior during the product life cycle. In this research, the PET-based conductive fiber was prepared by silver conductive ink continuous coating. The conductive fiber showed low fiber resistance (10-¹~10Ω/cm), and the conductive behavior still had good performance (fiber resistance:10-¹~10Ω/cm， percentage of fiber resistance change:<60%) after the water wash durability test (AATCC-135， 30 times). This research provides a better solution to resolve the issues of resistance increase after the water wash process due to the damage to the conductive fiber structure.

Keywords: PET, conductive fiber, e-textiles, wearable devices

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Authors: Debjit Ray

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Horizontal gene transfer (HGT) and recombination leads to the emergence of bacterial antibiotic resistance and pathogenic traits. HGT events can be identified by comparing a large number of fully sequenced genomes across a species or genus, define the phylogenetic range of HGT, and find potential sources of new resistance genes. In-depth comparative phylogenomics can also identify subtle genome or plasmid structural changes or mutations associated with phenotypic changes. Comparative phylogenomics requires that accurately sequenced, complete and properly annotated genomes of the organism. Assembling closed genomes requires additional mate-pair reads or “long read” sequencing data to accompany short-read paired-end data. To bring down the cost and time required of producing assembled genomes and annotating genome features that inform drug resistance and pathogenicity, we are analyzing the performance for genome assembly of data from the Illumina NextSeq, which has faster throughput than the Illumina HiSeq (~1-2 days versus ~1 week), and shorter reads (150bp paired-end versus 300bp paired end) but higher capacity (150-400M reads per run versus ~5-15M) compared to the Illumina MiSeq. Bioinformatics improvements are also needed to make rapid, routine production of complete genomes a reality. Modern assemblers such as SPAdes 3.6.0 running on a standard Linux blade are capable in a few hours of converting mixes of reads from different library preps into high-quality assemblies with only a few gaps. Remaining breaks in scaffolds are generally due to repeats (e.g., rRNA genes) are addressed by our software for gap closure techniques, that avoid custom PCR or targeted sequencing. Our goal is to improve the understanding of emergence of pathogenesis using sequencing, comparative genomics, and machine learning analysis of ~1000 pathogen genomes. Machine learning algorithms will be used to digest the diverse features (change in virulence genes, recombination, horizontal gene transfer, patient diagnostics). Temporal data and evolutionary models can thus determine whether the origin of a particular isolate is likely to have been from the environment (could it have evolved from previous isolates). It can be useful for comparing differences in virulence along or across the tree. More intriguing, it can test whether there is a direction to virulence strength. This would open new avenues in the prediction of uncharacterized clinical bugs and multidrug resistance evolution and pathogen emergence.

Keywords: genomics, pathogens, genome assembly, superbugs

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Authors: Martha Salinas, Valkyria Bernal

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Creativity is a possible response to the profound social, economic, and global changes society is living and education is the source to develop this kind of capacity. However, institutional pressures often prevent teachers from engaging in creative teaching practices and make innovation not the main curricular focus when building learning scenarios and experiences. This study proposes and validates the use of a prototype of Educative Video – Capsules from the perspective of teacher training, presenting the different stages of design, the content plan, as well as the influences of its components and characteristics from the perspective of creativity. The paper presents literature findings of the factors that influence the innovative behavior of teachers, the beliefs of teachers about creativity and its nature, as well as the creative pedagogies that have generated better results. The results show that the disposition of teachers towards creative pedagogies improves significantly with the use of a tool that is based on the principles of microlearning and is developed in a non-academic, autonomous, and non-imposed family environment as traditional teacher training processes usually occur.

Keywords: educational innovation, resistance to innovation, creativity, creative pedagogy

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Authors: Senol Dogan, Gunay Karli

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Identification of relevant publications based on a Medline query is time-consuming and error-prone. An all based process has the potential to solve this problem without any manual work. To the best of our knowledge, our study is the first to investigate the ability of machine learning to identify relevant articles accurately. 5 different machine learning algorithms were tested using 23 predictors based on several metadata fields attached to publications. We find that the Boosted model is the best-performing algorithm and its overall accuracy is 96%. In addition, specificity and sensitivity of the algorithm is 97 and 93%, respectively. As a result of the work, we understood that we can apply the same procedure to understand cancer gene expression big data.

Keywords: prediction of publications, machine learning, algorithms, bariatric surgery, comparison of algorithms, boosted, tree, logistic regression, ANN model

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Authors: Cyril Kaplan, Nikola Jajcay

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We developed purely sonic, musical based, highly customizable EEG neurofeedback environment designed to administer a new neurofeedback training protocol. The training protocol concentrates on improving the ability to switch between several mental states characterized by different levels of arousal, each of them correlated to specific brain wave activity patterns in several specific regions of neocortex. This paper describes the neurofeedback training environment we developed and its specificities, thus can be helpful as a manual to guide other neurofeedback users (both researchers and practitioners) interested in our editable open source program (available to download and usage under CC license). Responses and reaction of first trainees that used our environment are presented in this article. Combination of qualitative methods (thematic analysis of neurophenomenological insights of trainees and post-session semi-structured interviews) and quantitative methods (power spectra analysis of EEG recorded during the training) were employed to obtain a multifaceted view on our new training protocol.

Keywords: EEG neurofeedback, mixed methods, self-regulation, switch-between-states training

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Authors: Anthony Okechukwu Ifediniru, Austin Ikechukwu Gbasouzor, Isidore Uche Uju

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This article is centered on the design, analysis, construction, and test of a locally made arc welding machine that operates on 250vac with 8 amp output taps ranging from 60vac to 250vac at a fixed frequency, which is of benefit to urban areas; while considering its cost-effectiveness, strength, portability, and mobility. The welding machine uses a power supply to create an electric arc between an electrode and the metal at the welding point. A current selector coil needed for current selection is connected to the primary winding. Electric power is supplied to the primary winding of its transformer and is transferred to the secondary winding by induction. The voltage and current output of the secondary winding are connected to the output terminal, which is used to carry out welding work. The output current of the machine ranges from 110amps for low current welding to 250amps for high current welding. The machine uses a step-down transformer configuration for stepping down the voltage in order to obtain a high current level for effective welding. The welder can adjust the output current within a certain range. This allows the welder to properly set the output current for the type of welding that is being performed. The constructed arc welding machine was tested by connecting the work piece to it. Since there was no shock or spark from the transformer’s laminated core and was successfully used to join metals, it confirmed and validated the design.

Keywords: AC current, arc welding machine, DC current, transformer, welds

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Authors: Okafor Joan, Nwodo Uchechukwu

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Klebsiella pneumoniae (K. pneumoniae) is a significant pathogen responsible for opportunistic and nosocomial infection. One of the most significant antibiotic resistance mechanisms in K. pneumoniae isolates is efflux pumps. Our current study identified efflux genes (AcrAB, OqxAB, MacAB, and TolC) and regulatory genes (RamR and RarA) in multidrug-resistant (MDR) K. pneumoniae isolated from hospital effluents and investigated their relationship with antibiotic resistance. The sum of 145 K. pneumoniae isolates was established by PCR and screened for antibiotic susceptibility. PCR detected efflux pump genes, and their link with antibiotic resistance was statistically examined. However, 120 (83%) of the confirmed isolated were multidrug-resistant, with the largest percentage of resistance to ampicillin (88.3%) and the weakest rate of resistance to imipenem (5.5%). Resistance to the other antibiotics ranged from 11% to 76.6%. Molecular distribution tests show that AcrA, AcrB, MacA, oqxB oqxA, TolC, MacB were detected in 96.7%, 85%, 76.7%, 70.8%, 55.8%, 39.1%, and 29.1% respectively. However, 14.3% of the isolates harboured all seven genes screened. Efflux pump system AcrAB (83.2%) was the most commonly detected in K. pneumonia isolated across all the antibiotics class-tested. In addition, the frequencies of RamR and RarA were 46.2% and 31.4%, respectively. AcrAB and OqxAB efflux pump genes were significantly associated with fluoroquinolone, beta-lactam, carbapenem, and tetracycline resistance (p<0.05). The high rate of efflux genes in this study demonstrated that this resistance mechanism is the dominant way in K. pneumoniae isolates. Appropriate treatment must be used to reduce and tackle the burden of resistant Klebsiella pneumonia in hospital wastewater effluents.

Keywords: Klebsiella pneumonia, efflux pumps, regulatory genes, multidrug-resistant, hospital, PCR

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Authors: Fuad M. Alkoot

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We aim at highlighting the benefits of classifier systems especially in supporting educational management decisions. The paper aims at using classifiers in an educational application where an outcome is predicted based on given input parameters that represent various conditions at the institute. We present a classifier system that is designed using a limited training set with data for only one semester. The achieved system is able to reach at previously known outcomes accurately. It is also tested on new input parameters representing variations of input conditions to see its prediction on the possible outcome value. Given the supervised expectation of the outcome for the new input we find the system is able to predict the correct outcome. Experiments were conducted on one semester data from two departments only, Switching and Mathematics. Future work on other departments with larger training sets and wider input variations will show additional benefits of classifier systems in supporting the management decisions at an educational institute.

Keywords: machine learning, pattern recognition, classifier design, educational management, outcome estimation

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Authors: Aishatu Ibrahim Birma, Aminu Tukur, Abdulkarim Abbass Gora

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Machine translation plays a vital role in the Field of Natural Language Processing (NLP), breaking down language barriers and enabling communication across diverse communities. In the context of Hausa, a widely spoken language in West Africa, mainly in Nigeria, effective translation systems are essential for enabling seamless communication and promoting cultural exchange. However, due to the unique linguistic characteristics of Hausa, accurate translation remains a challenging task. The research proposes an approach to improving the machine learning translation of Hausa by integrating Named Entity Recognition (NER) techniques. Named entities, such as person names, locations, organizations, and dates, are critical components of a language's structure and meaning. Incorporating NER into the translation process can enhance the quality and accuracy of translations by preserving the integrity of named entities and also maintaining consistency in translating entities (e.g., proper names), and addressing the cultural references specific to Hausa. The NER will be incorporated into Neural Machine Translation (NMT) for the Hausa to English Translation.

Keywords: machine translation, natural language processing (NLP), named entity recognition (NER), neural machine translation (NMT)

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Authors: Nadir Ayrilmis

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Wood and wood-based panels are one of the oldest structural materials used in the construction industry due to their significant advantages such as good mechanical properties, low density, renewable material, low-cost, recycling, etc. However, they burn when exposed to a flame source or high temperatures. This is very important when the wood products are used as structural or hemi-structural materials in the construction industry, furniture industry, so on. For this reason, the fire resistance is demanded property for wood products. They can be impregnated with fire retardants to improve their fire resistance. The most used fire retardants, fire-retardant mechanism, and fire-testing systems, and national and international fire-durability classifications and standard requirements for fire-durability of wood and wood-based panels were given in this study.

Keywords: fire resistance, wood-based panels, cone calorimeter, wood

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Authors: Shima Dehghan

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Aim: imbalance between antioxidant defensive system and increasing production of free radicals caused oxidative stress that can be rolled in cellular damage and occurring some of diseases such as diabetes. The aim of current study was to investigate the effect of eight weeks aerobic training on peroxidant and antioxidants indicators in women with type2 diabetes. Methodology: thirty two inactive women with type 2 diabetes were randomly assigned into four groups: 1. control, 2. Aerobic training, 3. Purslane seed and 4. Aerobic training + Purslane seed groups. Subjects were asked to accomplish eight weeks aerobic training (50 min aerobic exercise, 3 days/week, for to achieve 65-75% maximum of heart rate). Also, subjects in certain groups received purslane seeds for eight weeks. Blood samples were obtained in two sets (one session and after 8 weeks). Data was analyzed using one way ANOVA. A significant difference was accepted at p < 0/05 level. Results: After eight weeks of aerobic training with purslane seeds supplementation, malon dyaldehyde (MDA) concentration in training group were significantly decreased (p < 0/000), but A difference significant was not found in control group. Superoxide dismutase (SOD) and catalase (CAT) concentrations in training group were significantly increased (p < 0/000), while difference significant wasnot found in control group. Conclusion: The finding of the current study indicates that disciplined aerobic training with purslane seeds supplementation can be caused improvement in peroxidant/antioxidant balance in women with type2 diabetes.

Keywords: aerobic training, purslane seed, peroxidant/antioxidant balance, diabetes2

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Authors: Ravija Gunawardana, Banuka Athuraliya

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Machine learning has emerged as a powerful tool for disease diagnosis and prediction. The use of machine learning algorithms has the potential to improve the accuracy of disease prediction, thereby enabling medical professionals to provide more effective and personalized treatments. This study focuses on developing a machine-learning model for disease prediction using symptoms and X-ray images. The importance of this study lies in its potential to assist medical professionals in accurately diagnosing diseases, thereby improving patient outcomes. Respiratory diseases are a significant cause of morbidity and mortality worldwide, and chest X-rays are commonly used in the diagnosis of these diseases. However, accurately interpreting X-ray images requires significant expertise and can be time-consuming, making it difficult to diagnose respiratory diseases in a timely manner. By incorporating machine learning algorithms, we can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The study utilized the Mask R-CNN algorithm, which is a state-of-the-art method for object detection and segmentation in images, to process chest X-ray images. The model was trained and tested on a large dataset of patient information, which included both symptom data and X-ray images. The performance of the model was evaluated using a range of metrics, including accuracy, precision, recall, and F1-score. The results showed that the model achieved an accuracy rate of over 90%, indicating that it was able to accurately detect and segment regions of interest in the X-ray images. In addition to X-ray images, the study also incorporated symptoms as input data for disease prediction. The study used three different classifiers, namely Random Forest, K-Nearest Neighbor and Support Vector Machine, to predict diseases based on symptoms. These classifiers were trained and tested using the same dataset of patient information as the X-ray model. The results showed promising accuracy rates for predicting diseases using symptoms, with the ensemble learning techniques significantly improving the accuracy of disease prediction. The study's findings indicate that the use of machine learning algorithms can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The model developed in this study has the potential to assist medical professionals in diagnosing respiratory diseases more accurately and efficiently. However, it is important to note that the accuracy of the model can be affected by several factors, including the quality of the X-ray images, the size of the dataset used for training, and the complexity of the disease being diagnosed. In conclusion, the study demonstrated the potential of machine learning algorithms for disease prediction using symptoms and X-ray images. The use of these algorithms can improve the accuracy of disease diagnosis, ultimately leading to better patient care. Further research is needed to validate the model's accuracy and effectiveness in a clinical setting and to expand its application to other diseases.

Keywords: K-nearest neighbor, mask R-CNN, random forest, support vector machine

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Authors: Ilknur Tuncer, Nihayet Bizsel

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The scarcity of research in bacterial diversity and antimicrobial resistance in coastal environments as in Turkish coasts leads to difficulties in developing efficient monitoring and management programs. In the present study, biogeochemical analysis of sediments and antimicrobial susceptibility analysis of bacteria in Izmir Bay, eastern Aegean Sea under high anthropogenic pressure were aimed in summer period when anthropogenic input was maximum and at intertidal zone where the first terrigenious contact occurred for aquatic environment. Geochemical content of the intertidal zone of Izmir Bay was firstly illustrated such that total and organic carbon, nitrogen and phosphorus contents were high and the grain size distribution varied as sand and gravel. Bacterial diversity and antibiotic resistance were also firstly given for Izmir Bay. Antimicrobially assayed isolates underlined the multiple resistance in the inner, middle and outer bays with overall 19% high MAR (multiple antibiotic resistance) index. Phylogenetic analysis of 16S rRNA gene sequences indicated that 67 % of isolates belonged to the genus Bacillus and the rest included the families Alteromonadaceae, Bacillaceae, Exiguobacteriaceae, Halomonadaceae, Planococcaceae, and Staphylococcaceae.

Keywords: bacterial phylogeny, multiple antibiotic resistance, 16S rRNA genes, Izmir Bay, Aegean Sea

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Authors: Bergun Meric Bingul, Yezdan Cinel, Murat Son, Cigdem Bulgan, Mensure Aydin

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The aim of this study was to determination of the effects of knee and hip isokinetic performance during the training with the special designed roller-shoes. 30 soccer players participated as subjects and these subjects were divided into 3 groups randomly. Training groups were; with the dynamic training shoes group, without the dynamic training shoes group and control group. Subjects were trained speed strength trainings during 8 weeks (3 days a week and 1 hour a day). 6 exercises were focused on the knee flexors and extensors, also hip adductor and abductor muscles were chosen and performed in 3x30secs at each sets. Control group was not paticipated to the training program. Before and after the training programs knee flexor and extensor muscles and hip abductor and adductor muscles’ peak torques were measured by Biodex III isokinetic dynamometer. Isokinetic strength data were analyzed by using SPSS program. A repeated measures analysis of variance (ANOVA) was used to determine differences among the peak torque values for three groups. The results indicated that soccer players’ peak torque values that the group of using the dynamic training shoes, were found higher. Also, hip adductor and abductor peak torques that the group of using the dynamic training shoes, were obtained better than the other groups. In conclusion, the ground friction forces are an important role of increasing strength. With these shoes, using rollers, soccer players were able to move easily because of the friction forces were reduced and created more range of motion. So, exercises were performed faster than before and strength movements in all angles, it ensured that the active state. This was resulted in a better use of force.

Keywords: isokinetic, soccer, dynamic training shoes, training

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Authors: Iddrisu Ibrahim, Joseph Atia Ayariga, Junhuan Xu, Daniel Abugri, Boakai Robertson, Olufemi S. Ajayi

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The emergence of multidrug resistance poses a huge risk to public health globally. Yet these recalcitrant pathogens continue to rise in incidence rate, with resistance rates significantly outpacing the speed of antibiotic development. This, therefore, presents an aura of related health issues such as untreatable nosocomial infections arising from organ transplants and surgeries, as well as community-acquired infections that are related to people with compromised immunity, e.g., diabetic and HIV patients, etc. There is a global effort to fight multidrug-resistant pathogens spearheaded by the World Health Organization, thus calling for research into novel antimicrobial agents to fight multiple drug resistance. Previously, our laboratory demonstrated that Cannabidiol (CBD) was an effective antimicrobial against Salmonella typhimurium (S. typhimurium). However, we observed resistance development over time. To understand the mechanisms S. typhimurium uses to develop resistance to Cannabidiol (CBD), we studied the abundance of bacteria lipopolysaccharide (LPS) and membrane sterols of both susceptible and resistant S. typhimurium. Using real-time quantitative polymerase chain reaction (RT-qPCR), we also analyzed the expression of selected genes known for aiding resistance development in S. typhimurium. We discovered that there was a significantly higher expression of blaTEM, fimA, fimZ, and integrons in the CBD-resistant bacteria, and these were also accompanied by a shift in abundance in cell surface molecules such as lipopolysaccharide (LPS) and sterols.

Keywords: antimicrobials, resistance, cannabidiol, gram-negative bacteria, integrons, blaTEM, Fim, LPS, ergosterols

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Authors: Ziya Esen, Özgür Duygulu, Nazlı S. Büyükatak

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This study investigates the effects of aging heat treatment on corrosion resistance and mechanical properties of WE43 Magnesium alloy. The heat treatment of alloys was conducted by solutionizing at 525oC for 16 h, followed by aging at 190, 210 and 230oC for up to 48 h. The type and the size of precipitates formed upon aging have influenced both the mechanical properties and corrosion behavior of the alloy. Solutionized alloy displayed the worst corrosion resistance in simulated body fluid, while peak hardness and the best corrosion resistance were observed in the alloy aged at 210oC for 24 h as a result of β’ precipitate formation. Longer aging duration at 210oC decreased the corrosion rate due to the coarsening of the precipitates and formation of precipitate-free zones. The increased corrosion resistance of the peak aged samples was attributed to the slowing down effect of the Mg(OH)₂/MgO corrosion layer by the pinning effect of β’-precipitates.

Keywords: WE43 magnesium alloy, simulated body fluid, corrosion, mechanical properties

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Authors: Alok Kumar Kamal, Vinod Kumar

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The trench gate MOSFET has shown itself as the most appropriate power device for low to medium voltage power applications due to its lowest possible ON resistance among all power semiconductor devices. In this research work a double-epilayer PSGT structure using a thin layer of N+ polysilicon as gate material. The total ON-state resistance (RON) of UMOSFET can be reduced by optimizing the epilayer thickness. The optimized structure of Double-Epilayer exhibits a 25.8% reduction in the ON-state resistance at Vgs=5V and improving the switching characteristics by reducing the Reverse transfer capacitance (Cgd) by 7.4%.

Keywords: Miller-capacitance, double-Epilayer;switching characteristics, power trench MOSFET (U-MOSFET), on-state resistance, blocking voltage

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Authors: Talal Alshammari, Nasser Alshammari, Mohamed Sedky, Chris Howard

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With the widespread adoption of the Internet-connected devices, and with the prevalence of the Internet of Things (IoT) applications, there is an increased interest in machine learning techniques that can provide useful and interesting services in the smart home domain. The areas that machine learning techniques can help advance are varied and ever-evolving. Classifying smart home inhabitants’ Activities of Daily Living (ADLs), is one prominent example. The ability of machine learning technique to find meaningful spatio-temporal relations of high-dimensional data is an important requirement as well. This paper presents a comparative evaluation of state-of-the-art machine learning techniques to classify ADLs in the smart home domain. Forty-two synthetic datasets and two real-world datasets with multiple inhabitants are used to evaluate and compare the performance of the identified machine learning techniques. Our results show significant performance differences between the evaluated techniques. Such as AdaBoost, Cortical Learning Algorithm (CLA), Decision Trees, Hidden Markov Model (HMM), Multi-layer Perceptron (MLP), Structured Perceptron and Support Vector Machines (SVM). Overall, neural network based techniques have shown superiority over the other tested techniques.

Keywords: activities of daily living, classification, internet of things, machine learning, prediction, smart home

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Authors: Mai. M. Toughan, Ahmed A. A. Sallam, Ashraf O. Abd El-Latif

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Termites are eusocial insects that are found on all continents except Antarctica. Termites have serious destructive impact, damaging local huts and crops of poor subsistence. The annual cost of termite damage and its control is determined in the billions globally. In Egypt, most of these damages are due to the subterranean termite species especially the sand termite, P. hypostoma. Pyrethroids became the primary weapon for subterranean termite control, after the use of chlorpyrifos as a soil termiticide was banned. Despite the important role of pyrethroids in termite control, its extensive use in pest control led to the eventual rise of insecticide resistance which may make many of the pyrethroids ineffective. The ability to diagnose the precise mechanism of pyrethroid resistance in any insect species would be the key component of its management at specified location for a specific population. In the present study, detailed toxicological and biochemical studies was conducted on the mechanism of pyrethroid resistance in P. hypostoma. The susceptibility of field populations of P. hypostoma against deltamethrin, α-cypermethrin and ƛ-cyhalothrin was evaluated. The obtained results revealed that the workers of P. hypostoma have developed high resistance level against the tested pyrethroids. Studies carried out through estimation of detoxification enzyme activity indicated that enhanced esterase and cytochrome P450 activities were probably important mechanisms for pyrethroid resistance in field populations. Elevated esterase activity and also additional esterase isozyme were observed in the pyrethroid-resistant populations compared to the susceptible populations. Strong positive correlation between cytochrome P450 activity and pyrethroid resistance was also reported. |Deltamethrin could be recommended as a resistance-breaking pyrethroid that is active against resistant populations of P. hypostoma.

Keywords: Psammotermes hypostoma, pyrethroid resistance, esterase, cytochrome P450

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Authors: Sujay Bisht

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The purpose of the study was to evaluate and find out the effect of Hill interval training on VO₂ MAX among field Hockey players. Thirty male field hockey players were selected from LNIPE, Guwahati who were studied in B.P.Ed course. The selected subjects were aged between 18 to 23 years. The VO₂ MAX was calculated and they were divided into two group. One group (N=15) considered as control group that did not participated in any special training apart from regular scheduled/curriculum and another group (N=15) considered as an experimental group which underwent four week Hill Training program. The selected criterion variable such VO₂ Max was measured by the cooper 12min/run/walk test and scores was recorded in ml/kg/min. The subjects were tested on selected criterion variable such as VO₂ Max prior and immediately after the training program. The pretest and posttest data were evaluate by the Analysis of Covariance (ANCOVA) to find out the significance difference if any between the experimental and control group on selected criterion variable. The level of significance was set at 0.05 level of confidence. After applied ANCOVA it was revealed that there was a significant different among the experimental and control group on VO₂ Max. Finally it was concluded that 4 week of Hill interval training effect the VO₂ max performance of field hockey players.

Keywords: VO₂ max, hill interval training, ANCOVA, experimental group

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Authors: Masoud Baghalian, Musa Arshad

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In order to investigate the effect of foliar application of calcium chloride on the resistance of fruits such as Red and Golden Lebanese apple varieties to blue mold, a split plot experiment in time and space, based on accidental blocks, with three replications under foliar application were done (Control, one in a thousand, two in thousands) and the results of the variance analysis showed that there is a significant difference between the levels of foliar and variety at 5% level and between time, there is significant difference in interaction of variety × time and three way interaction of foliar×variety×time, at 1% level. The highest resistance to the blue mold disease in foliar application was observed at two in thousands calcium (calcium chloride) level.

Keywords: apple, blue mold, foliar calcium, resistance

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Authors: Peng Liu, Chyng Wen Tee, Xiaofei Xu

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This paper integrates machine learning forecasting techniques into the multi-period portfolio optimization framework, enabling dynamic asset allocation based on multiple future periods. We explore both theoretical foundations and practical applications, employing diverse machine learning models for return forecasting. This comprehensive guide demonstrates the superiority of multi-period optimization over single-period approaches, particularly in risk mitigation through strategic rebalancing and enhanced market trend forecasting. Our goal is to promote wider adoption of multi-period optimization, providing insights that can significantly enhance the decision-making capabilities of practitioners and researchers alike.

Keywords: multi-period portfolio optimization, look-ahead constrained optimization, machine learning, sequential decision making

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Authors: Rosa Alin Cristian

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As in any other sports branch, there is also a relationship of dependence between the motor qualities and the technical skills in the sports dance, in the sense that superior performances from a technical, artistic point of view can be obtained only on the basis of a certain level of motor qualities and of the morphological and functional indices of the organism. Starting from the premise that physical training is a basic component of the dancers' training process, determining the efficacy and efficiency of the athletes in training and competitions, its main objectives are to obtain an optimal functional capacity of the body, which is reached through a superior level of development and manifestation of the basic and specific motor qualities, through appropriate values of the morph-functional indices, all against the background of a perfect state of health. We propose in this paper to create an inventory of the motor qualities specific to the sports dance, of their forms of manifestation, to establish some methodical priorities for their development, in order to support the specialists in their attempt to approach the physical training in the most rigorous and efficient way, according to the characteristics of each age category.

Keywords: physical training, motor skills, sports dance, performance

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Authors: Seyed Abolhasan Naeini, Mohammad Mahdi Shojaedin

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Oil leakage from the pipelines and the tanks carrying them, or during oil extraction, could lead to the changes in the characteristics and properties of the soil. In this paper, conducting a series of experimental cyclic triaxial tests, the effects of oil contamination on the liquefaction potential of sandy soils is investigated. The studied specimens are prepared by mixing the Firoozkuh sand with crude oil in 4, 8 and 12 percent by soil dry weight. The results show that the oil contamination up to 8% causes an increase in the soil liquefaction resistance and then with increase in the contamination, the liquefaction resistance decreases.

Keywords: cyclic triaxial test, liquefaction resistance, oil contamination, sandy soil

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Authors: Kishor T. Zingre, Seshadhri Srinivasan

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Energy consumption by the building sector is increasing at an alarming rate throughout the world and leading to more building-related CO₂ emissions into the environment. In buildings, the main contributors to energy consumption are heating, ventilation, and air-conditioning (HVAC) systems, lighting, and electrical appliances. It is hypothesised that the energy efficiency in buildings can be achieved by implementing sustainable technologies such as i) enhancing the thermal resistance of fabric materials for reducing heat gain (in hotter climates) and heat loss (in colder climates), ii) enhancing daylight and lighting system, iii) HVAC system and iv) occupant localization. Energy performance of various sustainable technologies is highly dependent on climatic conditions. This paper investigated the use of machine learning techniques for accurate prediction of air-conditioning energy in seasonal climates. The data required to train the machine learning techniques is obtained using the computational simulations performed on a 3-story commercial building using EnergyPlus program plugged-in with OpenStudio and Google SketchUp. The EnergyPlus model was calibrated against experimental measurements of surface temperatures and heat flux prior to employing for the simulations. It has been observed from the simulations that the performance of sustainable fabric materials (for walls, roof, and windows) such as phase change materials, insulation, cool roof, etc. vary with the climate conditions. Various renewable technologies were also used for the building flat roofs in various climates to investigate the potential for electricity generation. It has been observed that the proposed technique overcomes the shortcomings of existing approaches, such as local linearization or over-simplifying assumptions. In addition, the proposed method can be used for real-time estimation of building air-conditioning energy.

Keywords: building energy efficiency, energyplus, machine learning techniques, seasonal climates

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Authors: Seree Klaengair, Sunpetch Angkititrakul, Dusadee Phongaran, Chaiyaporn Soikum

Abstract:

The objectives of this study is to determine the prevalence and antimicrobial resistance pattern of Salmonella spp. isolated from chickens at slaughterhouses in northeast of Thailand. During 2015-2016, all samples were isolated and identified by ISO 6579:2002. A total of 604 samples of rectal swab were collected and isolated for the presence of Salmonella. Salmonella was detected in 109 of 604 (18.05%) samples. The most prevalent serovars were Salmonella Kentucky (22.94%), Give (20.18%) and Typhimurium (7.34%). In this study, 66.97% of the isolates were resistant to at least one antimicrobial drug and 38.39% were multidrug resistant. The highest resistances were found in nalidixic acid (49.54%), ampicillin (30.28%), tetracycline (27.52%), amoxicillin (26.61%), ciprofloxacin (23.85) and norfloxacin (19.27%). The results showed high prevalence of Salmonella spp. in chickens and antimicrobial resistance patterns. Prevention and control of Salmonella contamination in chickens should be consumer healthy.

Keywords: antimicrobial resistance, Salmonella spp., chicken, slaughterhouse

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Authors: Banaeifar Abdolali, Rahmanimoghadam Neda, Sohyli Shahram

Abstract:

Obesity is an increase in body fat , in addition it has been introduced as a risk factor for the progress of lipid disorders, hypertension, cardiovascular disease and type 2 diabetes (1,2). In recent years, Adipose tissue is now recognized as an endocrine organ that secretes many cytokines such as: interleukin 6, leptin, and visfatin (3). Visfatin is an adipocytokine that release from adiposities. It is unidentified whether training also influences concentrations of visfatin. Purpose: The purpose of this study was to examine the effects of 12 weeks of aerobic training on visfatin levels and lipid profile in obese women. Method: Thirty two obese women (age = 37.8 ± 13.2 years, body mass index = of 39.4 ± 6.4 kg/m2 .) volunteered to participate in a 12-wk exercise program. They were randomly assigned to either a training (n = 16) or control (n = 14) group. The training group exercised for 70 minutes per session, 3 days per week during the 12 week training program. The control group was asked to maintain their normal daily activities. Samples were obtained before and at the end of training program. We use t.paire and independent,test for data analyzes. Results: Exercise training resulted in a decrease in body weight (p < 0.05), percent body fat (% fat) and BMI (p < 0.05), fasting glucose level and visfatin concentration decreased but wasn’t significant (p > 0.05). Also the levels of triglyceride, total cholesterol and low-density lipoprotein cholesterol did not change significantly. Conclution: In conclusion, three month aerobic training program used in this study was very effective for producing significant benefits to body composition and HDL.c but didn’t significant chenging visfatin levels and lipid profile in these obese women.

Keywords: aerobic training, visfatin, lipid profile, women

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Authors: Daniel Botero, Oscar Rubiano, Pedro P. Barragan, Jaime Baron, Leonardo Rodriguez Perdomo, Jaime Rodriguez

Abstract:

In the last decade interval training (IT) has gained importance when is compare with strength training (ST). However, there are few studies analyzing the impact of these training over the autonomic nervous system (ANS). This work has aimed to compare the activity of the autonomic nervous system, when is expose to an IT or ST indoor cycling mode. After approval by the ethics committee, a cross-over clinical trial with 22 healthy participants (age 21 ± 3 years) was implemented. The selection of participants for the groups with sequence force-interval (F-I) and interval-force (I-F) was made randomly with assignation of 11 participants for each group. The temporal series of heart rate was obtained before and after each training using the POLAR TEAM® heart monitor. The evaluation of the ANS was performed with spectral analysis of the heart rate variability (HRV) using the fast Fourier transform (Kubios software). A training of 8 weeks in each sequence (4 weeks with each training) with an intermediate period of two weeks of washout was implemented for each group. The power parameter of the HRV in the low frequency band (LF = 0.04-0.15Hz related to the sympathetic nervous system), high frequency (HF = 0.15-0.4Hz, related to the parasympathetic) and LF/HF (with reference to a modulation of parasympathetic over the sympathetic), were calculated. Afterward, the difference between the parameters before and after was realized. Then, to evaluate statistical differences between each training was implemented the method of Wellek (Wellek and Blettner, 2012, Medicine, 109 (15), 276-81). To determine the difference of effect over parasympathetic when FT and IT are used, the T test is implemented obtaining a T value of 0.73 with p-value ≤ 0.1. For the sympathetic was obtained a T of 0.33 with p ≤ 0.1 and for LF/HF the T was 1.44 with a p ≥ 0.1. Then, the carry over effect was evaluated and was not present. Significant changes over autonomic activity with strength or interval training were not observed. However, a modulation of the parasympathetic over the sympathetic can be observed. Probably, these findings should be explained because the sample is little and/or the time of training was insufficient to generate changes.

Keywords: autonomic nervous, force training, indoor cycling, interval training

Procedia PDF Downloads 225