Search results for: statistical machine translation

Authors: Muhammad Shafi’U Adamu

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This study examined the effects of two groups of Cognitive Behavioral Therapies (CBT) which, includes Cognitive Restructuring (CB) and Rational Emotive Behavioral Therapy (REBT), on the Psychological Distress of awaiting-trial Inmates in Correctional Centers in North-West Nigeria. The study had four specific objectives, four research questions, and four null hypotheses. The study used a quasi-experimental design that involved pre-test and post-test. The population comprised of all 7,962 awaiting-trial inmates in correctional centers in North-west Nigeria. 131 awaiting trial inmates from three intact Correctional Centers were randomly selected using the census technique. The respondents were sampled and randomly put into 3 groups (CR, REBT and Control). Kessler Psychological Distress Scale (K10) was adapted for data collection in the study. The instrument was validated by experts and subjected to a pilot study using Cronbach's Alpha with a reliability coefficient of 0.772. Each group received treatment for 8 consecutive weeks (60 minutes/week). Data collected from the field were subjected to descriptive statistics of mean, standard deviation and mean difference to answer the research questions. Inferential statistics of ANOVA and independent sample t-test were used to test the null hypotheses at P≤ 0.05 level of significance. Results in the study revealed that there was no significant difference among the pre-treatment mean scores of experimental and control groups. Statistical evidence also showed a significant difference among the mean scores of the three groups, and thus, results of the Post Hoc multiple-comparison test indicated the posttreatment reduction of psychological distress in the awaiting-trial inmates. Documented output also showed a significant difference between the post-treatment psychologically distressed mean scores of male and female awaiting-trial inmates, but there was no difference in those exposed to REBT. The research recommends that a standardized structured CBT counseling technique treatment should be designed for correctional centers across Nigeria, and CBT counseling techniques could be used in the treatment of PD in both correctional and clinical settings.

Keywords: awaiting-trial inmates, cognitive restructuring, correctional centers, rational emotive behavioral therapy

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Authors: B. Mohammadi, A. Riazati, P. Soltan Sanjari, S. Azimbeik

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The ever-increasing development of civic demands on one hand; and the urban constrains for newly establish of infrastructures, on the other hand, perforce the engineering committees to apply non-conflicting methods in order to optimize the results. One of these optimized procedures to establish the main sewerage networks is the pipe jacking and micro-tunneling method. The raw information and researches are based on the experiments of the slurry micro-tunneling project of the Tehran main sewerage network that it has executed by the KAYSON co. The 4985 meters route of the mentioned project that is located nearby the Azadi square and the most vital arteries of Tehran is faced to 45% physical progress nowadays. The boring machine is made by the Herrenknecht and the diameter of the using concrete-polymer pipes are 1600 and 1800 millimeters. Placing and excavating several shafts on the ground and direct Tunnel boring between the axes of issued shafts is one of the requirements of the micro-tunneling. Considering the stream of the ground located shafts should care the hydraulic circumstances, civic conditions, site geography, traffic cautions and etc. The profile length has to convert to many shortened segment lines so the generated angle between the segments will be based in the manhole centers. Each segment line between two continues drive and receive the shaft, displays the jack location, driving angle and the path straight, thus, the diversity of issued angle causes the variety of jack positioning in the shaft. The jacking frame fixing conditions and it's associated dynamic load direction produces various patterns of Stress and Strain distribution and creating fatigues in the shaft wall and the soil surrounded the shaft. This pattern diversification makes the shaft wall transformed, unbalanced subsidence and alteration in the pipe jacking Stress Contour. This research is based on experiments of the Tehran's west sewerage plan and the numerical analysis the interaction of the soil around the shaft, shaft walls and the Jacking frame direction and finally, the suitable or unsuitable location of the pipe jacking shaft will be determined.

Keywords: underground structure, micro-tunneling, fatigue analysis, dynamic-soil–structure interaction, underground water, finite element analysis

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Authors: Nareshkumar Harale, B. B. Meshram

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The continued exponential growth of successful cyber intrusions against today’s businesses has made it abundantly clear that traditional perimeter security measures are no longer adequate and effective. We evolved the network trust architecture from trust-untrust to Zero-Trust, With Zero Trust, essential security capabilities are deployed in a way that provides policy enforcement and protection for all users, devices, applications, data resources, and the communications traffic between them, regardless of their location. Information exchange over the Internet, in spite of inclusion of advanced security controls, is always under innovative, inventive and prone to cyberattacks. TCP/IP protocol stack, the adapted standard for communication over network, suffers from inherent design vulnerabilities such as communication and session management protocols, routing protocols and security protocols are the major cause of major attacks. With the explosion of cyber security threats, such as viruses, worms, rootkits, malwares, Denial of Service attacks, accomplishing efficient and effective intrusion detection and prevention is become crucial and challenging too. In this paper, we propose a design and analysis model for next generation network intrusion detection and protection system as part of layered security strategy. The proposed system design provides intrusion detection for wide range of attacks with layered architecture and framework. The proposed network intrusion classification framework deals with cyberattacks on standard TCP/IP protocol, routing protocols and security protocols. It thereby forms the basis for detection of attack classes and applies signature based matching for known cyberattacks and data mining based machine learning approaches for unknown cyberattacks. Our proposed implemented software can effectively detect attacks even when malicious connections are hidden within normal events. The unsupervised learning algorithm applied to network audit data trails results in unknown intrusion detection. Association rule mining algorithms generate new rules from collected audit trail data resulting in increased intrusion prevention though integrated firewall systems. Intrusion response mechanisms can be initiated in real-time thereby minimizing the impact of network intrusions. Finally, we have shown that our approach can be validated and how the analysis results can be used for detecting and protection from the new network anomalies.

Keywords: network intrusion detection, network intrusion prevention, association rule mining, system analysis and design

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Authors: Tassadit Issaadi Hamitouche, Nicolas Gillard, Jean Petit, Valerie Lavaste, Celine Mayousse

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Water is a fundamental resource for the industry. It is taken from the environment either from municipal distribution networks or from various natural water sources such as the sea, ocean, rivers, aquifers, etc. Once used, water is discharged into the environment, reprocessed at the plant or treatment plants. These withdrawals and discharges have a direct impact on natural water resources. These impacts can apply to the quantity of water available, the quality of the water used, or to impacts that are more complex to measure and less direct, such as the health of the population downstream from the watercourse, for example. Based on the analysis of data (meteorological, river characteristics, physicochemical substances), we wish to predict water stress episodes and anticipate prefectoral decrees, which can impact the performance of plants and propose improvement solutions, help industrialists in their choice of location for a new plant, visualize possible interactions between companies to optimize exchanges and encourage the pooling of water treatment solutions, and set up circular economies around the issue of water. The development of a system for the collection, processing, and use of data related to water resources requires the functional constraints specific to the latter to be made explicit. Thus the system will have to be able to store a large amount of data from sensors (which is the main type of data in plants and their environment). In addition, manufacturers need to have 'near-real-time' processing of information in order to be able to make the best decisions (to be rapidly notified of an event that would have a significant impact on water resources). Finally, the visualization of data must be adapted to its temporal and geographical dimensions. In this study, we set up an infrastructure centered on the TICK application stack (for Telegraf, InfluxDB, Chronograf, and Kapacitor), which is a set of loosely coupled but tightly integrated open source projects designed to manage huge amounts of time-stamped information. The software architecture is coupled with the cross-industry standard process for data mining (CRISP-DM) data mining methodology. The robust architecture and the methodology used have demonstrated their effectiveness on the study case of learning the level of a river with a 7-day horizon. The management of water and the activities within the plants -which depend on this resource- should be considerably improved thanks, on the one hand, to the learning that allows the anticipation of periods of water stress, and on the other hand, to the information system that is able to warn decision-makers with alerts created from the formalization of prefectoral decrees.

Keywords: data mining, industry, machine Learning, shortage, water resources

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Authors: Som Pal Baliyan

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Dairy enterprise has been a major source of employment and income generation in most of the economies worldwide. Botswana government has also identified dairy as one of the agricultural sectors towards diversification of the mineral dependent economy of the country. The huge gap between local demand and supply of milk and milk products indicated that there are not only constraints but also; opportunities exist in this sub sector of agriculture. Therefore, this study was an attempt to identify constraints and opportunities in dairy production industry in Botswana. The possible ways to mitigate the constraints were also identified. The findings should assist the stakeholders especially, policy makers in the formulation of effective policies for the growth of dairy sector in the country. This quantitative study adopted a survey research design. A final survey followed by a pilot survey was conducted for data collection. The purpose of the pilot survey was to collect basic information on the nature and extent of the constraints, opportunities and ways to mitigate the constraints in dairy production. Based on the information from pilot survey, a four point Likert’s scale type questionnaire was constructed, validated and tested for its reliability. The data for the final survey were collected from purposively selected twenty five dairy farms. The descriptive statistical tools were employed to analyze data. Among the twelve constraints identified; high feed costs, feed shortage and availability, lack of technical support, lack of skilled manpower, high prevalence of pests and diseases and, lack of dairy related technologies were the six major constraints in dairy production. Grain feed production, roughage feed production, manufacturing of dairy feed, establishment of milk processing industry and, development of transportation systems were the five major opportunities among the eight opportunities identified. Increasing production of animal feed locally, increasing roughage feed production locally, provision of subsidy on animal feed, easy access to sufficient financial support, training of the farmers and, effective control of pests and diseases were identified as the six major ways to mitigate the constraints. It was recommended that the identified constraints and opportunities as well as the ways to mitigate the constraints need to be carefully considered by the stakeholders especially, policy makers during the formulation and implementation of the policies for the development of dairy sector in Botswana.

Keywords: dairy enterprise, milk production, opportunities, production constraints

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Authors: Siddharth Jain, Abhenil Mittal, Surendra Kumar Sharma

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Background: With its recent emergence and re-emergence, dengue has become a major international public health concern, imposing significant financial burden especially in developing countries. Despite aggressive control measures in place, India experienced one of its largest outbreaks in 2015 with Delhi being most severely affected. There is a lack of reliable predictors of disease severity and mortality in dengue. The present study was carried out to identify these predictors during the 2015 outbreak. Methods: This prospective observational study conducted at an apex tertiary care center in Delhi, India included confirmed adult dengue patients admitted between August-November 2015. Patient demographics, clinical details, and laboratory findings were recorded in a predesigned proforma. Appropriate statistical tests were used to summarize and compare the clinical and laboratory characteristics and derive predictors of mortality and severe disease, while developing a clinical risk score for mortality. Serotype analysis was also done for 75 representative samples to identify the dominant serotypes. Results: Data of 369 patients were analyzed (mean age 30.9 years; 67% males). Of these, 198 (54%) patients had dengue fever, 125 (34%) had dengue hemorrhagic fever (DHF Grade 1,2)and 46 (12%) developed dengue shock syndrome (DSS). Twenty two (6%) patients died. Late presentation to the hospital (≥5 days after onset) and dyspnoea at rest were identified as independent predictors of severe disease. Age ≥ 24 years, dyspnoea at rest and altered sensorium were identified as independent predictors of mortality. A clinical risk score was developed (12*age + 14*sensorium + 10*dyspnoea) which, if ≥ 22, predicted mortality with a high sensitivity (81.8%) and specificity (79.2%). The predominant serotypes in Delhi (2015) were DENV-2 and DENV-4. Conclusion: Age ≥ 24 years, dyspnoea at rest and altered sensorium were identified as independent predictors of mortality. Platelet counts did not determine the outcome in dengue patients. Timely referral/access to health care is important. Development and use of validated predictors of disease severity and simple clinical risk scores, which can be applied in all healthcare settings, can help minimize mortality and morbidity, especially in resource limited settings.

Keywords: dengue, mortality, predictors, severity

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Authors: Marion G. Ben-Jacob, David Wang

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There is a mathematics requirement for entry level college and university students, especially those who plan to study STEM (Science, Technology, Engineering and Mathematics). Most of them take College Algebra, and to continue their studies, they need to succeed in this course. Different pedagogical strategies are employed to promote the success of our students. There is, of course, the Traditional Method of teaching- lecture, examples, problems for students to solve. The Emporium Model, another pedagogical approach, replaces traditional lectures with a learning resource center model featuring interactive software and on-demand personalized assistance. This presentation will compare these two methods of pedagogy and the study done with its results on this comparison. Math is the foundation for science, technology, and engineering. Its work is generally used in STEM to find patterns in data. These patterns can be used to test relationships, draw general conclusions about data, and model the real world. In STEM, solutions to problems are analyzed, reasoned, and interpreted using math abilities in a assortment of real-world scenarios. This presentation will examine specific examples of how math is used in the different STEM disciplines. Math becomes practical in science when it is used to model natural and artificial experiments to identify a problem and develop a solution for it. As we analyze data, we are using math to find the statistical correlation between the cause of an effect. Scientists who use math include the following: data scientists, scientists, biologists and geologists. Without math, most technology would not be possible. Math is the basis of binary, and without programming, you just have the hardware. Addition, subtraction, multiplication, and division is also used in almost every program written. Mathematical algorithms are inherent in software as well. Mechanical engineers analyze scientific data to design robots by applying math and using the software. Electrical engineers use math to help design and test electrical equipment. They also use math when creating computer simulations and designing new products. Chemical engineers often use mathematics in the lab. Advanced computer software is used to aid in their research and production processes to model theoretical synthesis techniques and properties of chemical compounds. Mathematics mastery is crucial for success in the STEM disciplines. Pedagogical research on formative strategies and necessary topics to be covered are essential.

Keywords: emporium model, mathematics, pedagogy, STEM

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Authors: Benedicta Asante, Brenna Bath, Olugbenga Adebayo, Catherine Trask

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Background: Waste Collection Workers’ (WCWs) activities contribute greatly to the recycling sector and are an important component of the waste management industry. As the recycling sector evolves, reports of injuries and fatal accidents in the industry demand notice particularly common and debilitating musculoskeletal disorders such as low back pain (LBP). WCWs are likely exposed to diverse work-related hazards that could contribute to LBP. However, to our knowledge there has never been a systematic review or other synthesis of LBP findings within this workforce. The aim of this systematic review was to determine the prevalence and risk factors of LBP among WCWs. Method: A comprehensive search was conducted in Ovid Medline, EMBASE, and Global Health e-publications with search term categories ‘low back pain’ and ‘waste collection workers’. Articles were screened at title, abstract, and full-text stages by two reviewers. Data were extracted on study design, sampling strategy, socio-demographic, geographical region, and exposure definition, definition of LBP, risk factors, response rate, statistical techniques, and LBP prevalence. Risk of bias (ROB) was assessed based on Hoy Damien’s ROB scale. Results: The search of three databases generated 79 studies. Thirty-two studies met the study inclusion criteria for both title and abstract; thirteen full-text articles met the study criteria at the full-text stage. Seven articles (54%) reported prevalence within 12 months of LBP between 42-82% among WCW. The major risk factors for LBP among WCW included: awkward posture; lifting; pulling; pushing; repetitive motions; work duration; and physical loads. Summary data and syntheses of findings was presented in trend-lines and tables to establish the several prevalence periods based on age and region distribution. Public health implications: LBP is a major occupational hazard among WCWs. In light of these risks and future growth in this industry, further research should focus on more detail ergonomic exposure assessment and LBP prevention efforts.

Keywords: low back pain, scavenger, waste collection workers, waste pickers

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Authors: Sahar El Kasmi, Ayoub Aziz, Saadia Lharti, Mohammed El Janati, Boubker Boukili, Nacer El Motawakil, Mayom Chol Luka Awan

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Two types of geomaterials (Red Triassic clay from the Maaziz region and Yellow Pliocene clay from the Akrach region) were used to create different mixtures for the fabrication of ceramic bricks. This study investigated the influence of the Pliocene clay on the overall composition and mechanical properties of the Triassic clay. The red Triassic clay, sourced from Maaziz, underwent various mechanical processes and treatments to facilitate its transformation into ceramic bricks for construction. The triassic clay was subjected to a drying chamber and a heating chamber at 100°C to remove moisture. Subsequently, the dried clay samples were processed using a Planetary Babs ll Mill to reduce particle size and improve homogeneity. The resulting clay material was sieved, and the fine particles below 100 mm were collected for further analysis. In parallel, the Miocene marl obtained from the Akrach region was fragmented into finer particles and subjected to similar drying, grinding, and sieving procedures as the triassic clay. The two clay samples are then amalgamated and homogenized in different proportions. Precise measurements were taken using a weighing balance, and mixtures of 90%, 80%, and 70% Triassic clay with 10%, 20%, and 30% yellow clay were prepared, respectively. To evaluate the impact of Pliocene marl on the composition, the prepared clay mixtures were spread evenly and treated with a water modifier to enhance plasticity. The clay was then molded using a brick-making machine, and the initial manipulation process was observed. Additional batches were prepared with incremental amounts of Pliocene marl to further investigate its effect on the fracture behavior of the clay, specifically their resistance. The molded clay bricks were subjected to compression tests to measure their strength and resistance to deformation. Additional tests, such as water absorption tests, were also conducted to assess the overall performance of the ceramic bricks fabricated from the different clay mixtures. The results were analyzed to determine the influence of the Pliocene marl on the strength and durability of the Triassic clay bricks. The results indicated that the incorporation of Pliocene clay reduced the fracture of the triassic clay, with a noticeable reduction observed at 10% addition. No fractures were observed when 20% and 30% of yellow clay are added. These findings suggested that yellow clay can enhance the mechanical properties and structural integrity of red clay-based products.

Keywords: triassic clay, pliocene clay, mineralogical composition, geo-materials, ceramics, akach region, maaziz region, morocco.

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Authors: Vrinda Hari Ankolekar, Anne D. Souza, Mamatha Hosapatna

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Introduction: Precise anatomical assessment of femoral neck anteversion (FNA) and the neck shaft angles (NSA) would be essential in diagnosing the pathological conditions involving hip joint and its ligaments. FNA of greater than 20 degrees is considered excessive femoral anteversion, whereas a torsion angle of fewer than 10 degrees is considered femoral retroversion. Excessive femoral torsion is not uncommon and has been associated with certain neurologic and orthopedic conditions. The enlargement and maturation of the hip joint increases at the 20th week of gestation and the NSA ranges from 135- 140◦ at birth. Material and methods: 48 femurs were tagged according to the GA and two photographs for each femur were taken using Nikon digital camera. Each femur was kept on a horizontal hard desk and end on an image of the upper end was taken for the estimation of FNA and a photograph in a perpendicular plane was taken to calculate the NSA. The images were transferred to the computer and were stored in TIFF format. Microsoft Paint software was used to mark the points and Image J software was used to calculate the angles digitally. 1. Calculation of FNA: The midpoint of the femoral head and the neck were marked and a line was drawn joining these two points. The angle made by this line with the horizontal plane was measured as FNA. 2. Calculation of NSA: The midpoint of the femoral head and the neck were marked and a line was drawn joining these two points. A vertical line was drawn passing through the tip of the greater trochanter to the inter-condylar notch. The angle formed by these lines was calculated as NSA. Results: The paired t-test for the inter-observer variability showed no significant difference between the values of two observers. (FNA: t=-1.06 and p=0.31; NSA: t=-0.09 and p=0.9). The FNA ranged from 17.08º to 33.97 º on right and 17.32 º to 45.08 º on left. The NSA ranged from 139.33 º to 124.91 º on right and 143.98 º to 123.8 º on left. Unpaired t-test was applied to compare the mean angles between the second and third trimesters which did not show any statistical significance. This shows that the FNA and NSA of femur did not vary significantly during the third trimester. The FNA and NSA were correlated with the GA using Pearson’s correlation. FNA appeared to increase with the GA (r=0.5) but the increase was not statistically significant. A decrease in the NSA was also noted with the GA (r=-0.3) which was also statistically not significant. Conclusion: The present study evaluates the FNA and NSA of the femur in fetuses and correlates their development with the GA during second and third trimesters. The FNA and NSA did not vary significantly during the third trimester.

Keywords: anteversion, coxa antetorsa, femoral torsion, femur neck shaft angle

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Authors: Jeremy Jenrette, Z. Y. C. Liu, Pranav Chimote, Edward Fox, Trevor Hastie, Francesco Ferretti

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Suitable shark conservation depends on well-informed population assessments. Direct methods such as scientific surveys and fisheries monitoring are adequate for defining population statuses, but species-specific indices of abundance and distribution coming from these sources are rare for most shark species. We can rapidly fill these information gaps by boosting media-based remote monitoring efforts with machine learning and automation. We created a database of shark images by sourcing 24,546 images covering 219 species of sharks from the web application spark pulse and the social network Instagram. We used object detection to extract shark features and inflate this database to 53,345 images. We packaged object-detection and image classification models into a Shark Detector bundle. We developed the Shark Detector to recognize and classify sharks from videos and images using transfer learning and convolutional neural networks (CNNs). We applied these models to common data-generation approaches of sharks: boosting training datasets, processing baited remote camera footage and online videos, and data-mining Instagram. We examined the accuracy of each model and tested genus and species prediction correctness as a result of training data quantity. The Shark Detector located sharks in baited remote footage and YouTube videos with an average accuracy of 89\%, and classified located subjects to the species level with 69\% accuracy (n =\ eight species). The Shark Detector sorted heterogeneous datasets of images sourced from Instagram with 91\% accuracy and classified species with 70\% accuracy (n =\ 17 species). Data-mining Instagram can inflate training datasets and increase the Shark Detector’s accuracy as well as facilitate archiving of historical and novel shark observations. Base accuracy of genus prediction was 68\% across 25 genera. The average base accuracy of species prediction within each genus class was 85\%. The Shark Detector can classify 45 species. All data-generation methods were processed without manual interaction. As media-based remote monitoring strives to dominate methods for observing sharks in nature, we developed an open-source Shark Detector to facilitate common identification applications. Prediction accuracy of the software pipeline increases as more images are added to the training dataset. We provide public access to the software on our GitHub page.

Keywords: classification, data mining, Instagram, remote monitoring, sharks

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Authors: Emilio A. Berny-Brandt, Sonia E. Ruiz

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Steel tubular towers serving as support structures for large wind turbines are subject to several hundred million stress cycles arising from the turbulent nature of the wind. This causes high-cycle fatigue which can govern tower design. The practice of maintaining the support structure after wind turbines reach its typical 20-year design life have become common, but without quantifying the changes in the reliability on the tower. There are several studies on this topic, but most of them are based on the S-N curve approach using the Miner’s rule damage summation method, the de-facto standard in the wind industry. However, the qualitative nature of Miner’s method makes desirable the use of fracture mechanics to measure the effects of fatigue in the capacity curve of the structure, which is important in order to evaluate the integrity and reliability of these towers. Temporal and spatially varying wind speed time histories are simulated based on power spectral density and coherence functions. Simulations are then applied to a SAP2000 finite element model and step-by-step analysis is used to obtain the stress time histories for a range of representative wind speeds expected during service conditions of the wind turbine. Rainflow method is then used to obtain cycle and stress range information of each of these time histories and a statistical analysis is performed to obtain the distribution parameters of each variable. Monte Carlo simulation is used here to evaluate crack growth over time in the tower base using the Paris-Erdogan equation. A nonlinear static pushover analysis to assess the capacity curve of the structure after a number of years is performed. The capacity curves are then used to evaluate the changes in reliability of a steel tower located in Oaxaca, Mexico, where wind energy facilities are expected to grow in the near future. Results show that fatigue on the tower base can have significant effects on the structural capacity of the wind turbine, especially after the 20-year design life when the crack growth curve starts behaving exponentially.

Keywords: crack growth, fatigue, Monte Carlo simulation, structural reliability, wind turbines

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Authors: Obiajulu Anthony Ugochukwu Nnedum, Bernard Chukwukelue Chine, Jerome Ogochukwu Ezisi

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A notable challenge of organizational citizenship behavior in Nigerian organizations is the prevalence of individualistic work cultures among employees, as this mindset can result in employees being less willing to go beyond their formal job requirements to contribute to the organization overall success. However, the dearth and scarce research on the antecedents of organizational citizenship behavior, such as paternalistic leadership and employee loyalty to supervisors in sub-Saharan African cultures such as Nigeria, motivated the current study to take a deep investigation into the moderating role of employee loyalty to supervisor on the relationship between paternalistic leadership and organizational citizenship behavior. The relevance of the current study ensures that when employees are loyal to their paternalistic leaders who show care and support, they are more likely to exhibit organizational citizenship behavior. The current study employed a sample size of four hundred and twenty participants (one hundred and five managers and three hundred and five subordinates) from eleven large organizations randomly selected through lucky dip from twenty-two large organizations from the directory of the Chamber of Commerce and Industry in Anambra state, south-eastern Nigeria. Also, a twelve-item organizational citizenship behavior scale, a thirty-nine-item paternalistic leadership scale, and a six-item loyalty to supervisor scale were employed for the collection of data for the current study. Adopting a one manager/Leader by triad subordinates cross-sectional survey design, Hayes process micro model and statistical package for social sciences (SPSS) version twenty-five, the findings from the result of the analysis of the hypotheses demonstrated that loyalty to supervisor moderated the relationship between paternalistic leadership and organizational citizenship behavior-conscientiousness. Also, the findings from the result revealed that loyalty to the supervisor moderated the relationship between authoritative leadership and organizational citizenship behavior identification. Furthermore, the findings from the result showed that loyalty to the supervisor moderated the relationship between moral leadership and organizational citizenship behavior. Accordingly, the result from the analysis implies that when employees are loyal to their supervisors, they are more likely to exhibit organizational citizenship behavior by going above and beyond their formal job requirements, as this loyalty can be fostered through a paternalistic leadership style that emphasizes a supportive and caring relationship between supervisors and subordinates.

Keywords: authoritative leadership, moral leadership, loyalty to supervisor, organizational citizenship behavior

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Authors: Timothy Quinn, Ronald Croce, Aliaksandr Leuchanka, Justin Walker

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Many endurance athletes train at or just below an intensity associated with their lactate threshold (LT) and often the heart rate (HR) that these athletes use for their LT are above their true LT-HR measured in a laboratory. Training above their true LT-HR may lead to overtraining and injury. Few athletes have the capability of measuring their LT in a laboratory and rely on perception to guide them, as accurate field tests to determine LT are limited. Therefore, the purpose of this study was to determine if an 8-minute field test could accurately define the HR associated with LT as measured in the laboratory. On Day 1, fifteen male runners (mean±SD; age, 27.8±4.1 years; height, 177.9±7.1 cm; body mass, 72.3±6.2 kg; body fat, 8.3±3.1%) performed a discontinuous treadmill LT/maximal oxygen consumption (LT/VO2max) test using a portable metabolic gas analyzer (Cosmed K4b2) and a lactate analyzer (Analox GL5). The LT (and associated HR) was determined using the 1/+1 method, where blood lactate increased by 1 mMol•L-1 over baseline followed by an additional 1 mMol•L-1 increase. Days 2 and 3 were randomized, and the athletes performed either an 8-minute run on the treadmill (TM) or on a 160-m indoor track (TR) in an effort to cover as much distance as possible while maintaining a high intensity throughout the entire 8 minutes. VO2, HR, ventilation (VE), and respiratory exchange ratio (RER) were measured using the Cosmed system, and rating of perceived exertion (RPE; 6-20 scale) was recorded every minute. All variables were averaged over the 8 minutes. The total distance covered over the 8 minutes was measured in both conditions. At the completion of the 8-minute runs, blood lactate was measured. Paired sample t-tests and pairwise Pearson correlations were computed to determine the relationship between variables measured in the field tests versus those obtained in the laboratory at LT. An alpha level of <0.05 was required for statistical significance. The HR (mean +SD) during the TM (167+9 bpm) and TR (172+9 bpm) tests were strongly correlated to the HR measured during the laboratory LT (169+11 bpm) test (r=0.68; p<0.03 and r=0.88; p<0.001, respectively). Blood lactate values during the TM and TR tests were not different from each other but were strongly correlated with the laboratory LT (r=0.73; p<0.04 and r=0.66; p<0.05, respectively). VE (Lmin-1) was significantly greater during the TR (134.8+11.4 Lmin-1) as compared to the TM (123.3+16.2 Lmin-1) with moderately strong correlations to the laboratory threshold values (r=0.38; p=0.27 and r=0.58; p=0.06, respectively). VO2 was higher during TR (51.4 mlkg-1min-1) compared to TM (47.4 mlkg-1min-1) with correlations of 0.33 (p=0.35) and 0.48 (p=0.13), respectively to threshold values. Total distance run was significantly greater during the TR (2331.6+180.9 m) as compared to the TM (2177.0+232.6 m), but they were strongly correlated with each other (r=0.82; p<0.002). These results suggest that an 8-minute running field test can accurately predict the HR associated with the LT and may be a simple test that athletes and coaches could implement to aid in training techniques.

Keywords: blood lactate, heart rate, running, training

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Authors: Hameed Ullah, Shujaul Mulk Khan, Zahid Ullah, Zeeshan Ahmad Sadia Jahangir, Abdullah, Amin Ur Rahman, Muhammad Suliman, Dost Muhammad

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The interrelationship between vegetation and abiotic variables inside an ecosystem is one of the main jobs of plant scientists. This study was designed to investigate the vegetation structure and species diversity along with the environmental variables in the Yakhtangay hill district Shangla of the Himalayan Mountain series Pakistan by using multivariate statistical analysis. Quadrat’s method was used and a total of 171 Quadrats were laid down 57 for Tree, Shrubs and Herbs, respectively, to analyze the phytosociological attributes of the vegetation. The vegetation of the selected area was classified into different Life and leaf-forms according to Raunkiaer classification, while PCORD software version 5 was used to classify the vegetation into different plants communities by Two-way indicator species Analysis (TWINSPAN). The CANOCCO version 4.5 was used for DCA and CCA analysis to find out variation directories of vegetation with different environmental variables. A total of 114 plants species belonging to 45 different families was investigated inside the area. The Rosaceae (12 species) was the dominant family followed by Poaceae (10 species) and then Asteraceae (7 species). Monocots were more dominant than Dicots and Angiosperms were more dominant than Gymnosperms. Among the life forms the Hemicryptophytes and Nanophanerophytes were dominant, followed by Therophytes, while among the leaf forms Microphylls were dominant, followed by Leptophylls. It is concluded that among the edaphic factors such as soil pH, the concentration of soil organic matter, Calcium Carbonates concentration in soil, soil EC, soil TDS, and physiographic factors such as Altitude and slope are affecting the structure of vegetation, species composition and species diversity at the significant level with p-value ≤0.05. The Vegetation of the selected area was classified into four major plants communities and the indicator species for each community was recorded. Classification of plants into 4 different communities based upon edaphic gradients favors the individualistic hypothesis. Indicator Species Analysis (ISA) shows the indicators of the study area are mostly indicators to the Himalayan or moist temperate ecosystem, furthermore, these indicators could be considered for micro-habitat conservation and respective ecosystem management plans.

Keywords: species richness, edaphic gradients, canonical correspondence analysis (CCA), TWCA

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Authors: Swati Gautam, Amita Jain, Shyampyari Jaiswar

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Objective: To elucidate the role of (ApaI&TaqI) VDR gene polymorphism in the pathogenesis of female genital tuberculosis (FGTB) cases. Background: Female genital TB represents about 15-20% of total extra-pulmonary TB (EPTB). Female subjects with vitamin D deficiency have been shown to be at higher risk of pulmonary TB as well as FGTB. In same context few functional polymorphism in vitamin D receptor (VDR) gene has been considered as an important genetic risk factor that modulate the development of FGTB. Therefore we aimed, to elucidate the role of (ApaI&TaqI) VDR gene polymorphism in the pathogenesis of FGTB. Study design: Case-Control study. Sample size: Cases (60) and Controls (60). Study site: Department of Obstetrics & Gynecology & Department of Microbiology, K.G.M.U. Lucknow, (UP). Inclusion criteria: Cases: Women with age group 20-35 years, premenstrual endometrial aspiration collected and included in the study, those were positive with acid-fast bacilli (AFB)/ TB-PCR/ LJ culture/ liquid culture. Controls: Women with age group 20-35 years having no history of ATT and all test negative for TB recruited as control. Exclusion criteria: -Women with endometriosis, polycystic ovaries (PCOD), positive on Chlamydia & gonorrhea, already on anti-tubercular therapy (ATT) excluded. Materials and Methods: Blood samples were collected in EDTA tubes from cases and controls stored at -20ºC. Genomic DNA extraction was carried out by salting-out method. Genotyping of VDR gene (ApaI&TaqI) polymorphism was performed by using single amplification refractory mutation system (ARMS) PCR technique. PCR products were analyzed by electrophoresis on 2% agarose gel. Statistical analysis was done by SPSS16.3 software & computing odds ratio (OR) with 95% CI. Results: Increased risk of female genital tuberculosis was observed in AA genotype (OR =1.1419-6.212 95% CI, P*<0.036) and A allele (OR =1.255-3.518, 95% CI, P* < 0.006) in FGTB as compared to controls. Moreover A allele was found more frequent in FGTB patients. No significant difference was observed in TaqI gene polymorphism of VDR gene. Conclusion: The ApaI polymorphism is significantly associated with etiology of FGTB and plays an important role as a genetic risk factor in FGTB women.

Keywords: ARMS, ATT, EPTB, FGTB, VDR

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Authors: Kevin De Castro Cogle, Mirian Kubo, Maria Anastasiadi, Fady Mohareb, Claire Rossi

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Background: The bioaccessibility of bioactive compounds is a critical determinant of the nutritional quality of various food products. Despite its importance, there is a limited number of comprehensive studies aimed at assessing how the composition of a food matrix influences the bioaccessibility of a compound of interest. This knowledge gap has prompted a growing need to investigate the intricate relationship between food matrix formulations and the bioaccessibility of bioactive compounds. One such class of bioactive compounds that has attracted considerable attention is curcuminoids. These naturally occurring phytochemicals, extracted from the roots of Curcuma longa, have gained popularity owing to their purported health benefits and also well known for their poor bioaccessibility Project aim: The primary objective of this research project is to systematically assess the influence of matrix composition on the bioaccessibility of curcuminoids. Additionally, this study aimed to develop a series of predictive models for bioaccessibility, providing valuable insights for optimising the formula for functional foods and provide more descriptive nutritional information to potential consumers. Methods: Food formulations enriched with curcuminoids were subjected to in vitro digestion simulation, and their bioaccessibility was characterized with chromatographic and spectrophotometric techniques. The resulting data served as the foundation for the development of predictive models capable of estimating bioaccessibility based on specific physicochemical properties of the food matrices. Results: One striking finding of this study was the strong correlation observed between the concentration of macronutrients within the food formulations and the bioaccessibility of curcuminoids. In fact, macronutrient content emerged as a very informative explanatory variable of bioaccessibility and was used, alongside other variables, as predictors in a Bayesian hierarchical model that predicted curcuminoid bioaccessibility accurately (optimisation performance of 0.97 R2) for the majority of cross-validated test formulations (LOOCV of 0.92 R2). These preliminary results open the door to further exploration, enabling researchers to investigate a broader spectrum of food matrix types and additional properties that may influence bioaccessibility. Conclusions: This research sheds light on the intricate interplay between food matrix composition and the bioaccessibility of curcuminoids. This study lays a foundation for future investigations, offering a promising avenue for advancing our understanding of bioactive compound bioaccessibility and its implications for the food industry and informed consumer choices.

Keywords: bioactive bioaccessibility, food formulation, food matrix, machine learning, probabilistic modelling

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Authors: Mohammad Khazaei, Reza Rostami, Hassan Gharayagh Zandi, Ruhollah Basatnia, Mahboubeh Ghayour Najafabadi

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Introduction: This study delves into the influence of diverse interventions on brain functional connectivity among young male basketball players. Given the significance of understanding how interventions affect cognitive functions in athletes, particularly in the context of basketball, this research contributes to the growing body of knowledge in sports neuroscience. Methods: Three distinct groups were selected for comprehensive investigation: the Motivational Interview Group, Placebo Consumption Group, and Ritalin Consumption Group. The study involved assessing brain functional connectivity using various frequency bands (Delta, Theta, Alpha, Beta1, Beta2, Gamma, and Total Band) before and after the interventions. The participants were subjected to specific interventions corresponding to their assigned groups. Results: The findings revealed substantial differences in brain functional connectivity across the studied groups. The Motivational Interview Group exhibited optimal outcomes in PLI (Total Band) connectivity. The Placebo Consumption Group demonstrated a marked impact on PLV (Alpha) connectivity, and the Ritalin Consumption Group experienced a considerable enhancement in imCoh (Total Band) connectivity. Discussion: The observed variations in brain functional connectivity underscore the nuanced effects of different interventions on young male basketball players. The enhanced connectivity in specific frequency bands suggests potential cognitive and performance improvements. Notably, the Motivational Interview and Placebo Consumption groups displayed unique patterns, emphasizing the multifaceted nature of interventions. These findings contribute to the understanding of tailored interventions for optimizing cognitive functions in young male basketball players. Conclusion: This study provides valuable insights into the intricate relationship between interventions and brain functional connectivity in young male basketball players. Further research with expanded sample sizes and more sophisticated statistical analyses is recommended to corroborate and expand upon these initial findings. The implications of this study extend to the broader field of sports neuroscience, aiding in the development of targeted interventions for athletes in various disciplines.

Keywords: electroencephalography, Ritalin, Placebo effect, motivational interview

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Authors: Joseph Fitoussi, Mohammadali Shirinbayan, Abbas Tcharkhtchi

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Due to material flow during processing, short fiber reinforced composites structures obtained by injection or compression molding generally present strong spatial microstructure variation. On the other hand, quasi-static, dynamic, and fatigue behavior of these materials are highly dependent on microstructure parameters such as fiber orientation distribution. Indeed, because of complex damage mechanisms, SFRC structures design is a key challenge for safety and reliability. In this paper, we propose a micromechanical model allowing prediction of damage behavior of real structures as a function of microstructure spatial distribution. To this aim, a statistical damage criterion including strain rate and fatigue effect at the local scale is introduced into a Mori and Tanaka model. A critical local damage state is identified, allowing fatigue life prediction. Moreover, the multi-scale model is coupled with an experimental intrinsic link between damage under monotonic loading and fatigue life in order to build an abacus giving Tsai-Wu failure criterion parameters as a function of microstructure and targeted fatigue life. On the other hand, the micromechanical damage model gives access to the evolution of the anisotropic stiffness tensor of SFRC submitted to complex thermomechanical loading, including quasi-static, dynamic, and cyclic loading with temperature and amplitude variations. Then, the latter is used to fill out microstructure dependent material cards in finite element analysis for design optimization in the case of complex loading history. The proposed methodology is illustrated in the case of a real automotive component made of sheet molding compound (PSA 3008 tailgate). The obtained results emphasize how the proposed micromechanical methodology opens a new path for the automotive industry to lighten vehicle bodies and thereby save energy and reduce gas emission.

Keywords: short fiber reinforced composite, structural design, damage, micromechanical modelling, fatigue, strain rate effect

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Authors: S. Agarwal, A. Rani

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Catechol is a natural polyphenolic compound that widely exists in higher plants such as teas, vegetables, fruits, tobaccos, and some traditional Chinese medicines. The fly ash-based zeolites are capable of absorbing a wide range of pollutants. But the process of zeolite synthesis is time-consuming and requires technical setups by the industries. The marketed costs of zeolites are quite high restricting its use by small-scale industries for the removal of phenolic compounds. The present research proposes a simple method of alkaline treatment of FA to produce an effective adsorbent for catechol removal from wastewater. The experimental parameter such as pH, temperature, initial concentration and adsorbent dose on the removal of catechol were studied in batch reactor. For this purpose the adsorbent materials were mixed with aqueous solutions containing catechol ranging in 50 – 200 mg/L initial concentrations and then shaken continuously in a thermostatic Orbital Incubator Shaker at 30 ± 0.1 °C for 24 h. The samples were withdrawn from the shaker at predetermined time interval and separated by centrifugation (Centrifuge machine MBL-20) at 2000 rpm for 4 min. to yield a clear supernatant for analysis of the equilibrium concentrations of the solutes. The concentrations were measured with Double Beam UV/Visible spectrophotometer (model Spectrscan UV 2600/02) at the wavelength of 275 nm for catechol. In the present study, the use of low-cost adsorbent (BTFA) derived from coal fly ash (FA), has been investigated as a substitute of expensive methods for the sequestration of catechol. The FA and BTFA adsorbents were well characterized by XRF, FE-SEM with EDX, FTIR, and surface area and porosity measurement which proves the chemical constituents, functional groups and morphology of the adsorbents. The catechol adsorption capacities of synthesized BTFA and native material were determined. The adsorption was slightly increased with an increase in pH value. The monolayer adsorption capacities of FA and BTFA for catechol were 100 mg g⁻¹ and 333.33 mg g⁻¹ respectively, and maximum adsorption occurs within 60 minutes for both adsorbents used in this test. The equilibrium data are fitted by Freundlich isotherm found on the basis of error analysis (RMSE, SSE, and χ²). Adsorption was found to be spontaneous and exothermic on the basis of thermodynamic parameters (ΔG°, ΔS°, and ΔH°). Pseudo-second-order kinetic model better fitted the data for both FA and BTFA. BTFA showed large adsorptive characteristics, high separation selectivity, and excellent recyclability than FA. These findings indicate that BTFA could be employed as an effective and inexpensive adsorbent for the removal of catechol from wastewater.

Keywords: catechol, fly ash, isotherms, kinetics, thermodynamic parameters

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Authors: Karina I. Hidas, Csaba Németh, Anna Visy, Judit Csonka, László Friedrich, Ildikó Cs. Nyulas-Zeke

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Egg yolk is a popular ingredient in the food industry due to its gelling, emulsifying, colouring, and coagulating properties. Because of the heat sensitivity of proteins, egg yolk can only be heat treated at low temperatures, so its shelf life, even with the addition of a preservative, is only a few weeks. Freezing can increase the shelf life of liquid egg yolk up to 1 year, but it undergoes gelling below -6 ° C, which is an irreversible phenomenon. The degree of gelation depends on the time and temperature of freezing and is influenced by the process of thawing. Therefore, in our experiment, we examined egg yolks thawed in different ways. In this study, unpasteurized, industrially broken, separated, and homogenized liquid egg yolk was used. Freshly produced samples were frozen in plastic containers at -18°C in a laboratory freezer. Frozen storage was performed for 90 days. Samples were analysed at day zero (unfrozen) and after frozen storage for 1, 7, 14, 30, 60 and 90 days. Samples were thawed in two ways (at 5°C for 24 hours and 30°C for 3 hours) before testing. Calorimetric properties were examined by differential scanning calorimetry, where heat flow curves were recorded. Denaturation enthalpy values were calculated by fitting a linear baseline, and denaturation temperature values were evaluated. Besides, dry matter content of samples was measured by the oven method with drying at 105°C to constant weight. For statistical analysis two-way ANOVA (α = 0.05) was employed, where thawing mode and freezing time were the fixed factors. Denaturation enthalpy values decreased from 1.1 to 0.47 at the end of the storage experiment, which represents a reduction of about 60%. The effect of freezing time was significant on these values, already the enthalpy of samples stored frozen for 1 day was significantly reduced. However, the mode of thawing did not significantly affect the denaturation enthalpy of the samples, and no interaction was seen between the two factors. The denaturation temperature and dry matter content did not change significantly either during the freezing period or during the defrosting mode. Results of our study show that slow freezing and frozen storage at -18°C greatly reduces the amount of protein that can be denatured in egg yolk, indicating that the proteins have been subjected to aggregation, denaturation or other protein conversions regardless of how they were thawed.

Keywords: denaturation enthalpy, differential scanning calorimetry, liquid egg yolk, slow freezing

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Authors: C. Zimmermann, E. Lackner, M. Ebner

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Massive Open Online Courses (MOOCs) are increasingly popular learning hubs that are boasting considerable participant numbers, innovative technical features, and a multitude of instructional resources. Still, there is a high level of evidence showing that almost all MOOCs suffer from a declining frequency of participant activity and fairly low completion rates. In this paper, we would like to share the lessons learned in implementing several design patterns that have been suggested in order to foster participant activity. Our conclusions are based on experiences with the ‘Dr. Internet’ MOOC, which was created as an xMOOC to raise awareness for a more critical approach to online health information: participants had to diagnose medical case studies. There is a growing body of recommendations (based on Learning Analytics results from earlier xMOOCs) as to how the decline in participant activity can be alleviated. One promising focus in this regard is instructional design patterns, since they have a tremendous influence on the learner’s motivation, which in turn is a crucial trigger of learning processes. Since Medieval Age storytelling, micro-learning units and specific comprehensible, narrative structures were chosen to animate the audience to follow narration. Hence, MOOC participants are not likely to abandon a course or information channel when their curiosity is kept at a continuously high level. Critical aspects that warrant consideration in this regard include shorter course duration, a narrative structure with suspense peaks (according to the ‘storytelling’ approach), and a course schedule that is diversified and stimulating, yet easy to follow. All of these criteria have been observed within the design of the Dr. Internet MOOC: 1) the standard eight week course duration was shortened down to six weeks, 2) all six case studies had a special quiz format and a corresponding resolution video which was made available in the subsequent week, 3) two out of six case studies were split up in serial video sequences to be presented over the span of two weeks, and 4) the videos were generally scheduled in a less predictable sequence. However, the statistical results from the first run of the MOOC do not indicate any strong influences on the retention rate, so we conclude with some suggestions as to why this might be and what aspects need further consideration.

Keywords: case study, Dr. internet, experience, MOOCs, design patterns

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Authors: Rio Hirakawa, Christian Gundlach, Sven Hartwig

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In recent years, the use of aluminium has further expanded and is expected to replace steel in the future as vehicles become lighter and more recyclable in order to reduce greenhouse gas (GHG) emissions and improve fuel economy. In line with this, structures and components are becoming increasingly multi-material, with different materials, including aluminium, being used in combination to improve mechanical utility and performance. A common method of assembling dissimilar materials is mechanical fastening, but it has several drawbacks, such as increased manufacturing processes and the influence of substrate-specific mechanical properties. Adhesive bonding and fusion bonding are methods that overcome the above disadvantages. In these two joining methods, surface pre-treatment of the substrate is always necessary to ensure the strength and durability of the joint. Previous studies have shown that laser surface treatment improves the strength and durability of the joint. Yan et al. showed that laser surface treatment of aluminium alloys changes α-Al2O3 in the oxide layer to γ-Al2O3. As γ-Al2O3 has a large specific surface area, is very porous and chemically active, laser-treated aluminium surfaces are expected to undergo physico-chemical changes over time and adsorb moisture and organic substances from the air or storage atmosphere. The impurities accumulated on the laser-treated surface may be released at the adhesive and bonding interface by the heat input to the bonding system during the joining phase, affecting the strength and durability of the joint. However, only a few studies have discussed the effect of such storage periods on laser-treated surfaces. This paper, therefore, investigates the ageing of laser-treated aluminium alloy surfaces through thermal analysis, electrochemical analysis and microstructural observations.AlMg3 of 0.5 mm and 1.5 mm thickness was cut using a water-jet cutting machine, cleaned and degreased with isopropanol and surface pre-treated with a pulsed fibre laser at 1060 nm wavelength, 70 W maximum power and 55 kHz repetition frequency. The aluminium surface was then analysed using SEM, thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy (FTIR) and cyclic voltammetry (CV) after storage in air for various periods ranging from one day to several months TGA and FTIR analysed impurities adsorbed on the aluminium surface, while CV revealed changes in the true electrochemically active surface area. SEM also revealed visual changes on the treated surface. In summary, the changes in the laser-treated aluminium surface with storage time were investigated, and the final results were used to determine the appropriate storage period.

Keywords: laser surface treatment, pre-treatment, adhesion, bonding, corrosion, durability, dissimilar material interface, automotive, aluminium alloys

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Authors: Faizul Azly Abd Dzubir, Muhammad F. Othman

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Conventional structural health monitoring approach for mechanical equipment uses inspection data from Non-Destructive Testing (NDT) during plant shut down window and fitness for service evaluation to estimate the integrity of the equipment that is prone to crack damage. Yet, this forecast is fraught with uncertainty because it is often based on assumptions of future operational parameters, and the prediction is not continuous or online. Advanced Diagnostic and Prognostic Technology (ADaPT) uses Acoustic Emission (AE) technology and a stochastic prognostic model to provide real-time monitoring and prediction of mechanical defects or cracks. The forecast can help the plant authority handle their cracked equipment before it ruptures, causing an unscheduled shutdown of the facility. The ADaPT employs process historical data trending, finite element analysis, fitness for service, and probabilistic statistical analysis to develop a prediction model for crack initiation and growth due to mechanical damage. The prediction model is combined with live equipment operating data for real-time prediction of the remaining life span owing to fracture. ADaPT was devised at a hot combined feed exchanger (HCFE) that had suffered creep crack damage. The ADaPT tool predicts the initiation of a crack at the top weldment area by April 2019. During the shutdown window in April 2019, a crack was discovered and repaired. Furthermore, ADaPT successfully advised the plant owner to run at full capacity and improve output by up to 7% by April 2019. ADaPT was also used on a coke drum that had extensive fatigue cracking. The initial cracks are declared safe with ADaPT, with remaining crack lifetimes extended another five (5) months, just in time for another planned facility downtime to execute repair. The prediction model, when combined with plant information data, allows plant operators to continuously monitor crack propagation caused by mechanical damage for improved maintenance planning and to avoid costly shutdowns to repair immediately.

Keywords: mechanical damage, cracks, continuous monitoring tool, remaining life, acoustic emission, prognostic model

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Authors: Piret Pernik

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Based on strategic, operational, and technical analysis of the ongoing armed conflict in Ukraine, this paper will examine the opportunities and risks of using small commercial drones (dual-use unmanned aerial vehicles, UAV) for military purposes. The paper discusses the opportunities and risks in the information domain, encompassing both cyber and electromagnetic interference and attacks. The paper will draw conclusions on a possible strategic impact to the battlefield outcomes in the modern armed conflicts by the widespread use of dual-use UAVs. This article will contribute to filling the gap in the literature by examining based on empirical data cyberattacks and electromagnetic interference. Today, more than one hundred states and non-state actors possess UAVs ranging from low cost commodity models, widely are dual-use, available and affordable to anyone, to high-cost combat UAVs (UCAV) with lethal kinetic strike capabilities, which can be enhanced with Artificial Intelligence (AI) and Machine Learning (ML). Dual-use UAVs have been used by various actors for intelligence, reconnaissance, surveillance, situational awareness, geolocation, and kinetic targeting. Thus they function as force multipliers enabling kinetic and electronic warfare attacks and provide comparative and asymmetric operational and tactical advances. Some go as far as argue that automated (or semi-automated) systems can change the character of warfare, while others observe that the use of small drones has not changed the balance of power or battlefield outcomes. UAVs give considerable opportunities for commanders, for example, because they can be operated without GPS navigation, makes them less vulnerable and dependent on satellite communications. They can and have been used to conduct cyberattacks, electromagnetic interference, and kinetic attacks. However, they are highly vulnerable to those attacks themselves. So far, strategic studies, literature, and expert commentary have overlooked cybersecurity and electronic interference dimension of the use of dual use UAVs. The studies that link technical analysis of opportunities and risks with strategic battlefield outcomes is missing. It is expected that dual use commercial UAV proliferation in armed and hybrid conflicts will continue and accelerate in the future. Therefore, it is important to understand specific opportunities and risks related to the crowdsourced use of dual-use UAVs, which can have kinetic effects. Technical countermeasures to protect UAVs differ depending on a type of UAV (small, midsize, large, stealth combat), and this paper will offer a unique analysis of small UAVs both from the view of opportunities and risks for commanders and other actors in armed conflict.

Keywords: dual-use technology, cyber attacks, electromagnetic warfare, case studies of cyberattacks in armed conflicts

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Authors: Hritik Bhattarai

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Land use and land cover play a crucial role in preserving and managing Earth's natural resources. Various factors, such as economic, demographic, social, cultural, technological, and environmental processes, contribute to changes in land use and land cover (LULC). Rupandehi District is significantly influenced by a combination of driving forces, including its geographical location, rapid population growth, economic opportunities, globalization, tourism activities, and political events. Urbanization and urban growth in the region have been occurring in an unplanned manner, with internal migration and natural population growth being the primary contributors. Internal migration, particularly from neighboring districts in the higher and lower Himalayan regions, has been high, leading to increased population growth and density. This study utilizes geospatial technology, specifically geographic information system (GIS), to analyze and illustrate the land cover and land use changes in the Rupandehi district for the years 2009 and 2019, using freely available Landsat images. The identified land cover categories include built-up area, cropland, Das-Gaja, forest, grassland, other woodland, riverbed, and water. The statistical analysis of the data over the 10-year period (2009-2019) reveals significant percentage changes in LULC. Notably, Das-Gaja shows a minimal change of 99.9%, while water and forest exhibit increases of 34.5% and 98.6%, respectively. Riverbed and built-up areas experience changes of 95.3% and 39.6%, respectively. Cropland and grassland, however, show concerning decreases of 102.6% and 140.0%, respectively. Other woodland also indicates a change of 50.6%. The most noteworthy trends are the substantial increase in water areas and built-up areas, leading to the degradation of agricultural and open spaces. This emphasizes the urgent need for effective urban planning activities to ensure the development of a sustainable city. While Das-Gaja seems unaffected, the decreasing trends in cropland and grassland, accompanied by the increasing built-up areas, are unsatisfactory. It is imperative for relevant authorities to be aware of these trends and implement proactive measures for sustainable urban development.

Keywords: land use and land cover, geospatial, urbanization, geographic information system, sustainable urban development

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Authors: Vincent Andrew Cappellano

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In the early phases of critical infrastructure system design, translating distributed computing requirements to an architecture has risk given the multitude of approaches (e.g., cloud, edge, fog). In many systems, a single requirement for system uptime / availability is used to encompass the system’s intended operations. However, when architected systems may perform to those availability requirements only during normal operations and not during component failure, or during outages caused by adversary attacks on critical infrastructure (e.g., physical, cyber). System designers lack a structured method to evaluate availability requirements against candidate system architectures through deep degradation scenarios (i.e., normal ops all the way down to significant damage of communications or physical nodes). This increases risk of poor selection of a candidate architecture due to the absence of insight into true performance for systems that must operate as a piece of critical infrastructure. This research effort proposes a process to analyze critical infrastructure system availability requirements and a candidate set of systems architectures, producing a metric assessing these architectures over a spectrum of degradations to aid in selecting appropriate resilient architectures. To accomplish this effort, a set of simulation and evaluation efforts are undertaken that will process, in an automated way, a set of sample requirements into a set of potential architectures where system functions and capabilities are distributed across nodes. Nodes and links will have specific characteristics and based on sampled requirements, contribute to the overall system functionality, such that as they are impacted/degraded, the impacted functional availability of a system can be determined. A machine learning reinforcement-based agent will structurally impact the nodes, links, and characteristics (e.g., bandwidth, latency) of a given architecture to provide an assessment of system functional uptime/availability under these scenarios. By varying the intensity of the attack and related aspects, we can create a structured method of evaluating the performance of candidate architectures against each other to create a metric rating its resilience to these attack types/strategies. Through multiple simulation iterations, sufficient data will exist to compare this availability metric, and an architectural recommendation against the baseline requirements, in comparison to existing multi-factor computing architectural selection processes. It is intended that this additional data will create an improvement in the matching of resilient critical infrastructure system requirements to the correct architectures and implementations that will support improved operation during times of system degradation due to failures and infrastructure attacks.

Keywords: architecture, resiliency, availability, cyber-attack

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Authors: Rangrong Yoksan, Amporn Sane, Nattaporn Khanoonkon, Chanakorn Yokesahachart, Narumol Noivoil, Khanh Minh Dang

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Polylactic acid (PLA) is the most commercially available bio-based and biodegradable plastic at present. PLA has been used in plastic related industries including single-used containers, disposable and environmentally friendly packaging owing to its renewability, compostability, biodegradability, and safety. Although PLA demonstrates reasonably good optical, physical, mechanical, and barrier properties comparable to the existing petroleum-based plastics, its brittleness and mold shrinkage as well as its price are the points to be concerned for the production of rigid and semi-rigid packaging. Blending PLA with other bio-based polymers including thermoplastic starch (TPS) is an alternative not only to achieve a complete bio-based plastic, but also to reduce the brittleness, shrinkage during molding and production cost of the PLA-based products. TPS is a material produced mainly from starch which is cheap, renewable, biodegradable, compostable, and non-toxic. It is commonly prepared by a plasticization of starch under applying heat and shear force. Although glycerol has been reported as one of the most plasticizers used for preparing TPS, its migration caused the surface stickiness of the TPS products. In some cases, mixed plasticizers or natural fibers have been applied to impede the retrogradation of starch or reduce the migration of glycerol. The introduction of fibers into TPS-based materials could reinforce the polymer matrix as well. Therefore, the objective of the present research is to study the effect of starch type (i.e. native starch and phosphate starch), plasticizer type (i.e. glycerol and xylitol with a weight ratio of glycerol to xylitol of 100:0, 75:25, 50:50, 25:75, and 0:100), and fiber content (i.e. in the range of 1-25 % wt) on properties of PLA/TPS blend and composite. PLA/TPS blends and composites were prepared using a twin-screw extruder and then converted into dumbbell-shaped specimens using an injection molding machine. The PLA/TPS blends prepared by using phosphate starch showed higher tensile strength and stiffness than the blends prepared by using the native one. In contrast, the blends from native starch exhibited higher extensibility and heat distortion temperature (HDT) than those from the modified starch. Increasing xylitol content resulted in enhanced tensile strength, stiffness, and water resistance, but decreased extensibility and HDT of the PLA/TPS blend. Tensile properties and hydrophobicity of the blend could be improved by incorporating silane treated-jute fibers.

Keywords: polylactic acid, thermoplastic starch, Jute fiber, composite, blend

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Authors: Ali Showail Ali Alasmari

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Introduction: Cataract is the loss of transparency of the lens inside the eye. It is the most common cause of visual loss and blindness worldwide. This study provides a systemic review of the recent findings on the association of vitamin D, and vitamin B12, and their possible role in preventing cataracts in senile (S) and diabetic mellitus (DM) patient groups. Objective: This study was intended to establish and investigate if there is any role between vitamin D and vitamin B12? Secondly, the connection between serum level of vitamin D and vitamin B12 in cataract incidence senile (s) vs. diabetic mellitus (DM) cataract patient groups. Furthermore, to evaluate and analyze cataract occurrence regarding vitamin D and vitamin B12 levels with other risk factors. Finally, to evaluate lens opacities pre and post treatment with vitamin D and vitaminB12 linked to age and visual acuity loss in both senile(S) and diabetic mellitus (DM) cataract patients’ groups. Methods: This study conducted at the ophthalmology clinic at Muhyail General Hospital. Select a prospective case-control to study the effect of vitamin D and Vit B12 on senile(S) cataracts that caused by age and diabetic mellitus (DM)cataract patients; then we compare these two groups. This study prospectively enrolled a total of 50 samples, 25 with senile cataract and 25 with diabetic cataract, from ophthalmology clinic at Muhyail General Hospital. Measuring 25-hydroxy vitamin D and vitamin B12 level concentrations in the assigned samples. Analyses were performed using SAS (statistical analysis software) program. Results: The most important finding in this study was that the senile(s) cataract patients’ group greatly benefited by the combination therapy of vitamin D, and Vitamin B12 reached (28.5±1.50 and 521.1±21.10) respectively; on the contrary, the diabetic cataract patient group hardly shows any significant improvement (21.5 ± 1.00 and 197.2 ± 7.20) respectively. This is because of the Metformin, the first line drug for treating diabetes, has been reported to potentially decrease vitamin B-12 status. This epigenetic modification was correlated with the diabetic mellitus (DM) cataract patients’ group not responding. Vitamin B12 deficiency also leads to an impairment of the conversion of methylmalonyl-CoA to succinyl-CoA, which has been associated with insulin resistance. There was no significant difference between the age, body mass index (BMI), the mean of Vit-D pre-treatments, and the mean values of Hemoglobin A1C of both senile (S) and diabetic mellitus (DM) cataract patient groups. On other hand, there was a highly significant difference between the mean values of glucose levels in both senile (S) and diabetic mellitus (DM) cataract patient groups. Conclusion: Here we conclude that diabetic mellitus (DM) cataract patient group hardly benefited from this combination therapy vitamin D and vitamin B12; on the other hand senile patient group (s) benefited a lot from the therapy.

Keywords: cataract patients, senile, diabetes mellitus, vitamin B12, vitamin D, Muhyail General Hospital, Saudi Arabia

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Authors: Konstantin Nefedev, Petr Andriushchenko

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Usually under the frustrated magnetics, it understands such materials, in which ones the interaction between located magnetic moments or spins has competing character, and can not to be satisfied simultaneously. The most well-known and simplest example of the frustrated system is antiferromagnetic Ising model on the triangle. Physically, the existence of frustrations means, that one cannot select all three pairs of spins anti-parallel in the basic unit of the triangle. In physics of the interacting particle systems, the vector models are used, which are constructed on the base of the pair-interaction law. Each pair interaction energy between one-component vectors can take two opposite in sign values, excluding the case of zero. Mathematically, the existence of frustrations in system means that it is impossible to have all negative energies of pair interactions in the Hamiltonian even in the ground state (lowest energy). In fact, the frustration is the excitation, which leaves in system, when thermodynamics does not work, i.e. at the temperature absolute zero. The origin of the frustration is the presence at least of one ''unsatisfied'' pair of interacted spins (magnetic moments). The minimal relative quantity of these excitations (relative quantity of frustrations in ground state) can be used as parameter of frustration. If the energy of the ground state is Egs, and summary energy of all energy of pair interactions taken with a positive sign is Emax, that proposed frustration parameter pf takes values from the interval [0,1] and it is defined as pf=(Egs+Emax)/2Emax. For antiferromagnetic Ising model on the triangle pf=1/3. We calculated the parameters of frustration in thermodynamic limit for different 2D periodical structures of Ising dipoles, which were on the ribs of the lattice and interact by means of the long-range dipolar interaction. For the honeycomb lattice pf=0.3415, triangular - pf=0.2468, kagome - pf=0.1644. All dependencies of frustration parameter from 1/N obey to the linear law. The given frustration parameter allows to consider the thermodynamics of all magnetic systems from united point of view and to compare the different lattice systems of interacting particle in the frame of vector models. This parameter can be the fundamental characteristic of frustrated systems. It has no dependence from temperature and thermodynamic states, in which ones the system can be found, such as spin ice, spin glass, spin liquid or even spin snow. It shows us the minimal relative quantity of excitations, which ones can exist in system at T=0.

Keywords: frustrations, parameter of order, statistical physics, magnetism

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