Search results for: early exercise

Authors: Amber Lim, Ted Ruffman

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A vast amount of research evidence indicates that children develop social attitudes that are similar to those of their parents. When using general measures of social attitudes, such as social dominance orientation (SDO), right-wing authoritarianism (RWA), and prejudice, studies show that parents' and children’s attitudes were correlated. However, the mechanisms behind the intergenerational transmission of attitudes remain largely unexplained. Since it was speculated that the origins of RWA could be traced back to one’s relationship with their parents, the aim of this study was to assess how parents’ social attitudes and parenting behavior are related to children’s social development. One line of research suggests that the different ways in which authoritarian and authoritative parents reason with their children may impact Theory of Mind (ToM) development. That is, inductive discipline (e.g., emphasising how the child’s actions affect others) facilitates empathy and ToM development. Conversely, past evidence shows that children have poorer ToM development when parents enforce rules without explanation. Thus, this study addresses the question of how parent behavior plays a role in the gradual acquisition of a ToM and social attitudes. Seventy parents reported their social attitudes, parenting behavior, and their child’s mental state and non-mental state vocabulary. Their children were given ToM and perspective-taking tasks, along with a friend choice task to measure racial bias and anti-fat bias. As hypothesised, parents’ use of inductive reasoning correlated with children’s performance on Theory of Mind tasks. Mothers’ inductive reasoning facilitated children’s acquisition of mental state vocabulary. Parents’ autonomy granting was associated with improved mental state vocabulary. Authoritarian parenting traits such as verbal hostility were linked to children’s racial bias. These findings highlight the importance of parent-child discussion in shaping children’s social understanding.

Keywords: parenting style, prejudice, social attitudes, social understanding, theory of mind

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Authors: I. Boroňová, J.Bernasovská, J. Kľoc, Z. Tomková, E. Petrejčíková, D. Gabriková, S. Mačeková

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Osteoporosis is a complex health disease characterized by low bone mineral density, which is determined by an interaction of genetics with metabolic and environmental factors. Current research in genetics of osteoporosis is focused on identification of responsible genes and polymorphisms. TNFRSF11B gene plays a key role in bone remodeling. The aim of this study was to investigate the genotype and allele distribution of A163G (rs3102735) osteoprotegerin gene promoter and G1181C (rs2073618) osteoprotegerin first exon polymorphisms in the group of 180 unrelated postmenopausal women with diagnosed osteoporosis and 180 normal controls. Genomic DNA was isolated from peripheral blood leukocytes using standard methodology. Genotyping for presence of different polymorphisms was performed using the Custom Taqman®SNP Genotyping assays. Hardy-Weinberg equilibrium was tested for each SNP in the groups of participants using the chi-square (χ2) test. The distribution of investigated genotypes in the group of patients with osteoporosis were as follows: AA (66.7%), AG (32.2%), GG (1.1%) for A163G polymorphism; GG (19.4%), CG (44.4%), CC (36.1%) for G1181C polymorphism. The distribution of genotypes in normal controls were follows: AA (71.1%), AG (26.1%), GG (2.8%) for A163G polymorphism; GG (22.2%), CG (48.9%), CC (28.9%) for G1181C polymorphism. In A163G polymorphism the variant G allele was more common among patients with osteoporosis: 17.2% versus 15.8% in normal controls. Also, in G1181C polymorphism the phenomenon of more frequent occurrence of C allele in the group of patients with osteoporosis was observed (58.3% versus 53.3%). Genotype and allele distributions showed no significant differences (A163G: χ2=0.270, p=0.605; χ2=0.250, p=0.616; G1181C: χ2= 1.730, p=0.188; χ2=1.820, p=0.177). Our results represents an initial study, further studies of more numerous file and associations studies will be carried out. Knowing the distribution of genotypes is important for assessing the impact of these polymorphisms on various parameters associated with osteoporosis. Screening for identification of “at-risk” women likely to develop osteoporosis and initiating subsequent early intervention appears to be most effective strategy to substantially reduce the risks of osteoporosis.

Keywords: osteoporosis, real-time PCR method, SNP polymorphisms

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Authors: Pradakshina Sharma, Jagriti Narang

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Due to the critical significance in the early identification of infectious diseases, electrochemical sensors have garnered considerable interest. Here, we develop a detection platform for the chikungunya virus by rationally implementing the extremely high charge-transfer efficiency of a ternary nanocomposite of graphene oxide, silver, and gold (G/Ag/Au) (CHIKV). Because paper is an inexpensive substrate and can be produced in large quantities, the use of electrochemical paper analytical device (EPAD) origami further enhances the sensor's appealing qualities. A cost-effective platform for point-of-care diagnostics is provided by paper-based testing. These types of sensors are referred to as eco-designed analytical tools due to their efficient production, usage of the eco-friendly substrate, and potential to reduce waste management after measuring by incinerating the sensor. In this research, the paper's foldability property has been used to develop and create 3D multifaceted biosensors that can specifically detect the CHIKVX-ray diffraction, scanning electron microscopy, UV-vis spectroscopy, and transmission electron microscopy (TEM) were used to characterize the produced nanoparticles. In this work, aptamers are used since they are thought to be a unique and sensitive tool for use in rapid diagnostic methods. Cyclic voltammetry (CV) and linear sweep voltammetry (LSV), which were both validated with a potentiostat, were used to measure the analytical response of the biosensor. The target CHIKV antigen was hybridized with using the aptamer-modified electrode as a signal modulation platform, and its presence was determined by a decline in the current produced by its interaction with an anionic mediator, Methylene Blue (MB). Additionally, a detection limit of 1ng/ml and a broad linear range of 1ng/ml-10µg/ml for the CHIKV antigen were reported.

Keywords: biosensors, ePAD, arboviral infections, point of care

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Authors: Beatriz Lafuente Alcázar, Yash Wani, Amit J. Nimunkar

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Cardiovascular Diseases (CVDs) are the leading cause of death globally, and around 80% of sudden cardiac deaths are due to arrhythmias or irregular heartbeats. The majority of these pathologies are revealed by either short-term or long-term alterations in the electrocardiogram (ECG) morphology. The ECG is the main diagnostic tool in cardiology. It is a non-invasive, pain free procedure that measures the heart’s electrical activity and that allows the detecting of abnormal rhythms and underlying conditions. A cardiologist can diagnose a wide range of pathologies based on ECG’s form alterations, but the human interpretation is subjective and it is contingent to error. Moreover, ECG records can be quite prolonged in time, which can further complicate visual diagnosis, and deeply retard disease detection. In this context, deep learning methods have risen as a promising strategy to extract relevant features and eliminate individual subjectivity in ECG analysis. They facilitate the computation of large sets of data and can provide early and precise diagnoses. Therefore, the cardiology field is one of the areas that can most benefit from the implementation of deep learning algorithms. In the present study, a deep learning algorithm is trained following a novel approach, using a combination of different databases as the training set. The goal of the algorithm is to achieve the detection of R-peaks in ECG signals. Its performance is further evaluated in ECG signals with different origins and features to test the model’s ability to generalize its outcomes. Performance of the model for detection of R-peaks for clean and noisy ECGs is presented. The model is able to detect R-peaks in the presence of various types of noise, and when presented with data, it has not been trained. It is expected that this approach will increase the effectiveness and capacity of cardiologists to detect divergences in the normal cardiac activity of their patients.

Keywords: arrhythmia, deep learning, electrocardiogram, machine learning, R-peaks

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Authors: Wen Hsin Hsu, Pin Lin

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Objective: Thirst discomfort is the most common yet often overlooked symptom in patients in the intensive care unit (ICU), with an incidence rate of 69.8%. If not properly cared for, it can easily lead to irritability, affect sleep quality, and increase the incidence of delirium, thereby extending the length of hospital stay. Research points out that the sensation of coldness is an effective strategy to alleviate thirst. Using a combined care approach for thirst can prolong the sensation of coldness in the mouth and reduce thirst discomfort. Therefore, it needs to be further analyzed and its effectiveness reviewed. Methods: This study uses systematic literature review and meta-analysis methodologies and searched databases including PubMed, MEDLINE, EMBASE, Cochrane, CINAHL, and two Chinese databases (CEPS and CJTD) based on keywords. JBI was used to appraise the quality of the literature. RevMen 5.4 software package was used, and Fix Effect Model was applied for data analysis. We selected experimental articles, including those in English and Chinese, that met the inclusion and exclusion criteria. Three research articles were included in total, with a sample size of 416 people. Two were randomized controlled trials, and one was a quasi-experimental design. Results: The results show that the combined care for thirst, which includes ice water spray or oral swab wipes, menthol mouthwash, and lip balm, can significantly relieve thirst intensity MD=-1.36 (3 studies, 95% CI (-1.77, -0.95), p <0.001) and thirst distress MD=-0.71 (2 studies, 95% CI (-1.32, -0.10), p =0.02). Therefore, it is recommended that medical staff identify high-risk groups for thirst early on. Implications for Practice: For patients who cannot eat orally, providing combined care for thirst can increase oral comfort and improve the quality of care.

Keywords: thirst bundle care, intensive care units, meta-analysis, ice water spray, menthol

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Authors: Tan Lay Cheng (Cheryl), Low Huiqi

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Background: All children learn at different pace. Individualized learning is an approach that tailors to the individual learning needs of each child. When implementing this approach, educators have to base their lessons on the understanding that all students learn differently and that what works for one student may not work for another. In the current early childhood environment, individualized learning is for children with diverse needs. However, a typical developing child is also able to benefit from individualized learning. This research abstract explores the concept of utilizing DNA-MILE, a patented (in Singapore) DNA-based assessment tool that can be used to measure a variety of factors that can impact learning. The assessment report includes the dominant intelligence of the user or, in this case, the child. From the result, a personalized learning plan that is tailored to each individual student's needs. Methods: A study will be conducted to investigate the effectiveness of DNA-MILE in supporting individualized learning. The study will involve a group of 20 preschoolers who were randomly assigned to either a DNA-MILE-assessed group (experimental group) or a control group. 10 children in each group. The experimental group will receive DNA Mile assessments and personalized learning plans, while the control group will not. The children in the experimental group will be taught using the dominant intelligence (as shown in the DNA-MILE report) to enhance their learning in other domains. The children in the control group will be taught using the curriculum and lesson plan set by their teacher for the whole class. Parents’ and teachers’ interviews will be conducted to provide information about the children before the study and after the study. Results: The results of the study will show the difference in the outcome of the learning, which received DNA Mile assessments and personalized learning plans, significantly outperformed the control group on a variety of measures, including standardized tests, grades, and motivation. Conclusion: The results of this study suggest that DNA Mile can be an effective tool for supporting individualized learning. By providing personalized learning plans, DNA Mile can help to improve learning outcomes for all students.

Keywords: individualized, DNA-MILE, learning, preschool, DNA, multiple intelligence

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Authors: Athanasia Eirini Zarkadi, Despoina Balli, Olga Elpis Kolokitha

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Objective: Impacted maxillary canines are a frequent condition and a common reason for patients seeking orthodontic treatment. Their simultaneous presence with dental anomalies raises a question about their possible connection. The aim of this study was to investigate the association of maxillary impacted canines with dental anomalies. Materials and Methods: Files of 874 patients from an orthodontic private practice in Greece were evaluated for the presence of maxillary impacted canines. From this sample, a group of 97 patients (39 males and 58 females) with at least one impacted maxillary canine were selected and consisted of the study group (canine impaction group) of this study. This group was compared to a control group of 97 patients (42 males and 55 females) that was created by random selection from the initial sample without maxillary canine impaction. The impaction diagnosis was made from the panoramic radiographs and confirmed from the surgery. The association between maxillary canine impaction and dental anomalies was examined with the chi-square test. A classification tree was created to further investigate the relations between impaction and dental anomalies. The reproducibility of diagnoses was assessed by re-examining the records of 25 patients two weeks after the first examination. Results: The found associated anomalies were cone-shaped upper lateral incisors and infraocclusion of deciduous molars. There is a significant increase in the prevalence of 12,4% of distal displacement of the unerupted mandibular second premolar in the canine impaction group compared to the control group that was 7,2%. The classification tree showed that the presence of a cone-shaped maxillary lateral incisor gave rise to the probability of an impacted canine to 83,3%. Conclusions: The presence of cone-shaped maxillary lateral incisors and infraocclusion of deciduous molars can be considered valuable early risk indicators for maxillary canine impaction.

Keywords: cone-shaped maxillary lateral incisors, dental anomalies, impacted canines, infraoccluded deciduous molars

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Authors: Yutong Xu, Wanting Zhang, Jia Wang, Zihan Guo, Weiguang Ma

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Background: The resilience education of intern nursing students has significant implications for the development and improvement of the nursing workforce. The clinical internship period is a critical time for enhancing resilience. Aims: To evaluate the resilience level of Chinese nursing interns and identify the factors affecting resilience early in their careers. Methods: The cross-sectional study design was adopted. From March 2022 to May 2023, 512 nursing interns in tertiary care hospitals were surveyed online with the Connor-Davidson Resilience Scale, the Clinical Learning Environment scale for Nurse, and the Career Adapt-Abilities Scale. Structural equation modeling was used to clarify the relationships among these factors. Indirect effects were tested using bootstrapped Confidence Intervals. Results: The nursing interns showed a moderately high level of resilience[M(SD)=70.15(19.90)]. Gender, scholastic attainment, had a scholarship, career adaptability and clinical learning environment were influencing factors of nursing interns’ resilience. Career adaptability and clinical learning environment positively and directly affected their resilience level (β = 0.58, 0.12, respectively, p＜0.01). career adaptability also positively affected career adaptability (β = 0.26, p < 0.01), and played a fully mediating role in the relationship between clinical learning environment and resilience. Conclusion: Career adaptability can enhance the influence of clinical learning environment on resilience. The promotion of career adaptability and the clinical teaching environment should be the potential strategies for nursing interns to improve their resilience, especially for those female nursing interns with low academic performance. Implications for Nursing Educators Nursing educators should pay attention to the cultivation of nursing students' resilience; for example, by helping them integrate to the clinical learning environment and improving their career adaptability. Reporting Method: The STROBE criteria were used to report the results of the observations critically. Patient or Public Contribution No patient or public contribution.

Keywords: resilience, clinical learning environment, career adaptability, nursing interns

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Authors: Ting Shen, Spyros Konstantopoulos

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During the past three decades, class size effects have been a focal debate in education. The idea of having smaller class is enormously popular among parents, teachers and policy makers. The rationale of its popularity is that small classroom could provide a better learning environment in which there would be more teacher-pupil interaction and more individualized instruction. This early stage benefits would also have a long-term positive effect. It is a common belief that reducing class size may result in increases in student achievement. However, the empirical evidence about class-size effects from experimental or quasi-experimental studies has been mixed overall. This study sheds more light on whether class size reduction impacts reading achievement in eight European countries: Bulgaria, Germany, Hungary, Italy, Lithuania, Romania, Slovakia, and Slovenia. We examine class size effects on reading achievement using national probability samples of fourth graders. All eight European countries had participated in the Progress in International Reading Literacy Study (PIRLS) in 2001, 2006 and 2011. Methodologically, the quasi-experimental method of instrumental variables (IV) has been utilized to facilitate causal inference of class size effects. Overall, the results indicate that class size effects on reading achievement are not significant across countries and years. However, class size effects are evident in Romania where reducing class size increases reading achievement. In contrast, in Germany, increasing class size seems to increase reading achievement. In future work, it would be valuable to evaluate differential class size effects for minority or economically disadvantaged student groups or low- and high-achievers. Replication studies with different samples and in various settings would also be informative. Future research should continue examining class size effects in different age groups and countries using rich international databases.

Keywords: class size, reading achievement, instrumental variables, PIRLS

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Authors: Abdullah Al Farwan, Ya Zhang

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In today’s educational arena, it is critical to understand educational data and be able to evaluate important aspects, particularly data on student achievement. Educational Data Mining (EDM) is a research area that focusing on uncovering patterns and information in data from educational institutions. Teachers, if they are able to predict their students' class performance, can use this information to improve their teaching abilities. It has evolved into valuable knowledge that can be used for a wide range of objectives; for example, a strategic plan can be used to generate high-quality education. Based on previous data, this paper recommends employing data mining techniques to forecast students' final grades. In this study, five data mining methods, Decision Tree, JRip, Naive Bayes, Multi-layer Perceptron, and Random Forest with wrapper feature selection, were used on two datasets relating to Portuguese language and mathematics classes lessons. The results showed the effectiveness of using data mining learning methodologies in predicting student academic success. The classification accuracy achieved with selected algorithms lies in the range of 80-94%. Among all the selected classification algorithms, the lowest accuracy is achieved by the Multi-layer Perceptron algorithm, which is close to 70.45%, and the highest accuracy is achieved by the Random Forest algorithm, which is close to 94.10%. This proposed work can assist educational administrators to identify poor performing students at an early stage and perhaps implement motivational interventions to improve their academic success and prevent educational dropout.

Keywords: classification algorithms, decision tree, feature selection, multi-layer perceptron, Naïve Bayes, random forest, students’ academic performance

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Authors: Faris Elghaish, Sepehr Abrishami, Mark Gaterell, Richard Wise

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The collaboration and integration between all building information management (BIM) processes and tasks are necessary to ensure that all project objectives can be delivered. The literature review has been used to explore the state of the art BIM technologies to manage construction materials as well as the challenges which have faced the construction process using traditional methods. Thus, this paper aims to articulate a framework to integrate traditional material planning methods such as ABC analysis theory (Pareto principle) to analyse and categorise the project materials, as well as using independent material planning methods such as Economic Order Quantity (EOQ) and Fixed Order Point (FOP) into the BIM 4D, and 5D capabilities in order to articulate a dependent material planning cycle into BIM, which relies on the constructability method. Moreover, we build a model to connect between the material planning outputs and the BIM 4D and 5D data to ensure that all project information will be accurately presented throughout integrated and complementary BIM reporting formats. Furthermore, this paper will present a method to integrate between the risk management output and the material management process to ensure that all critical materials are monitored and managed under the all project stages. The paper includes browsers which are proposed to be embedded in any 4D BIM platform in order to predict the EOQ as well as FOP and alarm the user during the construction stage. This enables the planner to check the status of the materials on the site as well as to get alarm when the new order will be requested. Therefore, this will lead to manage all the project information in a single context and avoid missing any information at early design stage. Subsequently, the planner will be capable of building a more reliable 4D schedule by allocating the categorised material with the required EOQ to check the optimum locations for inventory and the temporary construction facilitates.

Keywords: building information management, BIM, economic order quantity, EOQ, fixed order point, FOP, BIM 4D, BIM 5D

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Authors: Sally Ibrahim, Mohamed Hedia, Mohamed Taqi, Mohamed Derbala, Karima Mahmoud, Youssef Ahmed, Sayed Ismail, Mohamed El-Belely

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The identification and quantification of serum microRNA (miRNA) from mares with endometritis might serve as useful and implementable clinical biomarkers for the early diagnosis of endometiritis. Aims of the current study were (I) to study the expression pattern of eca-miR-155, eca-miR-223, eca-miR-17, eca-miR-200a, and eca-miR-205, and (II) to determine the levels of interleukin 6 (IL-6), prostaglandins (PGF₂α and PGE₂), in the serum of Arabian mares with healthy and abnormal uterine status (endometritis). This study was conducted on 80 Arabian mares (4-14 years old). Mares were divided into 48 sub-fertile mares suspected of endometritis and 32 fertile at stud farms. The criteria for mares to be enrolled in the endometritis group were that they had been bred three or more times unsuccessfully in the breeding season or had a history of more than one year of reproductive failure. In addition, two or more of the following criteria on a checklist were present: abnormal clinical findings, transrectal ultrasonographic uterine examination showed abnormal fluid in the uterus (echogenic or ≥2 cm in diameter), positive endometrial cytology; and bacterial and/or fungal growth. Serum samples were collected for measuring IL-6, PGF₂α, and PGE₂ concentrations, as well as serum miRNA isolation and quantitative real-time PCR. Serum concentrations of IL-6, PGE₂, and PGF₂α were higher (P ≤ 0.001) in mares with endometritis compared to the control healthy ones. The expression profile of eca-miR-155, eca-miR-223, eca-miR-17, eca-miR-200a, and eca-miR-205 increased (P≤0.001) in mares with endometritis compared to the control ones. To the best of our knowledge, this is the first study that revealed that serum miRNA and serum inflammatory mediators (IL-6, PGE₂, and PGF₂α) could be used as non-invasive gold standard biomarkers, and therefore might be served as an important additional diagnostic tool for endometritis in Arabian mares. Moreover, estimation of the serum concentrations of serum miRNA, IL-6, PGE₂, and PGF₂α is a promising recommended tool during the breeding soundness examination in mares.

Keywords: Arabian Mares, endometritis, inflammatory mediators, serum miRNA

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Authors: Geovanna dos Santos Romeiro, Polintia Rayza Brito da Silva, Luis Henrique Moura, Izadora Moreira Do Amaral, Marília Vitória Pinto Milhomem

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Introduction: The nose is one of the most likely sites for the appearance of malignancy on the face. This can be associated with its unique position of exposure to environmental damage, lack of photoprotection and because it is an area susceptible to greater sun exposure. It is already known that the most common type of nasal tumor is basal cell carcinoma. Squamous cell carcinoma is less common but considerably more aggressive, with a tendency to grow rapidly and metastasize. Nasal skin cancer can have a good prognosis, regardless of the type of treatment chosen, i.e., surgery, radiotherapy or electrodissection. However, tumors that are not diagnosed and treated quickly can be harmful and have a greater chance of metastasizing. When curative surgery is performed, therapies and reconstructive surgical procedures are usually required. Objective: The objective is to review the literature on nasal skin tumors and their types and specific locations. Forty-four articles published in Pubmed related to the location of skin cancer in the specific nasal areas region were analyzed. Twelve were excluded for being prior to the year 2000, three with inconclusive results, and one with unbiased conclusions. Results and Conclusion: Regarding the prevalence of types of nasal tumors, basal cell carcinoma comprises the majority, occurring predominantly in the ala, tip and root; squamous cell carcinoma, on the other hand, is more common in the lateral borders and columella. Even so, 2 articles report that the prevalence of metastasis has a higher incidence in squamous cell carcinomas. All of this points to the importance of early location, including regions that are often overlooked in the examination if the patient is wearing glasses. This topic needs further investigation for a greater correlation between anatomy and clinical-surgical implications.

Keywords: skin cancer, melanoma, non-melanoma, surgery

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Authors: D. Naranchimeg, G. Ulziisaikhan

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Student dropout problem has not been recently investigated within the Mongolian higher education. A student dropping out is a personal decision, but it may cause unemployment and other social problems including low quality of life because students who are not completed a degree cannot find better-paid jobs. The research aims to determine percentage of at-risk students, and understand reasons for dropouts and to find a way to predict. The study based on the students of the Mongolian National University of Education including its Arkhangai branch school, National University of Mongolia, Mongolian University of Life Sciences, Mongolian University of Science and Technology, Mongolian National University of Medical Science, Ikh Zasag International University, and Dornod University. We conducted the paper survey by method of random sampling and have surveyed about 100 students per university. The margin of error - 4 %, confidence level -90%, and sample size was 846, but we excluded 56 students from this study. Causes for exclusion were missing data on the questionnaire. The survey has totally 17 questions, 4 of which was demographic questions. The survey shows that 1.4% of the students always thought to dropout whereas 61.8% of them thought sometimes. Also, results of the research suggest that students’ dropouts from university do not have relationships with their sex, marital and social status, and peer and faculty climate, whereas it slightly depends on their chosen specialization. Finally, the paper presents the reasons for dropping out provided by the students. The main two reasons for dropouts are personal reasons related with choosing wrong study program, not liking the course they had chosen (50.38%), and financial difficulties (42.66%). These findings reveal the importance of early prevention of dropout where possible, combined with increased attention to high school students in choosing right for them study program, and targeted financial support for those who are at risk.

Keywords: at risk students, dropout, faculty climate, Mongolian universities, peer climate

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Authors: Yongjiang Zhang, Kallol Barai, Umesh R. Hodeghatta, Trang Tran, Vikas Dhiman

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Detecting water stress on crops early and accurately is crucial to minimize its impact. This study aims to measure water stress in wild blueberry crops non-destructively by analyzing proximal hyperspectral data. The data collection took place in the summer growing season of 2022. A drought experiment was conducted on wild blueberries in the randomized block design in the greenhouse, incorporating various genotypes and irrigation treatments. Hyperspectral data ( spectral range: 400-1000 nm) using a handheld spectroradiometer and leaf water potential data using a pressure chamber were collected from wild blueberry plants. Machine learning techniques, including multiple regression analysis and random forest models, were employed to predict leaf water potential (MPa). We explored the optimal wavelength bands for simple differences (RY1-R Y2), simple ratios (RY1/RY2), and normalized differences (|RY1-R Y2|/ (RY1-R Y2)). NDWI ((R857 - R1241)/(R857 + R1241)), SD (R2188 – R2245), and SR (R1752 / R1756) emerged as top predictors for predicting leaf water potential, significantly contributing to the highest model performance. The base learner models achieved an R-squared value of approximately 0.81, indicating their capacity to explain 81% of the variance. Research is underway to develop a neural vegetation index (NVI) that automates the process of index development by searching for specific wavelengths in the space ratio of linear functions of reflectance. The NVI framework could work across species and predict different physiological parameters.

Keywords: hyperspectral reflectance, water potential, spectral indices, machine learning, wild blueberries, optimal bands

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Authors: Peifang Hsieh

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The prevention of child abuse has aroused serious concerns in Taiwan because of the disparity between the increasing amount of reported child abuse cases that doubled over the past decade and the scarcity of social workers. New Taipei city, with the most population in Taiwan and over 70% of its 4 million citizens are migrant families in which the needs of children can be easily neglected due to insufficient support from relatives and communities, sees urgency for a social support system, by preemptively identifying and outreaching high-risk families of child abuse, so as to offer timely assistance and preventive measure to safeguard the welfare of the children. Big data analysis is the inspiration. As it was clear that high-risk families of child abuse have certain characteristics in common, New Taipei city decides to consolidate detailed background information data from departments of social affairs, education, labor, and health (for example considering status of parents’ employment, health, and if they are imprisoned, fugitives or under substance abuse), to cross-reference for accurate and prompt identification of the high-risk families in need. 'The Service Center for High-Risk Families' (SCHF) was established to integrate data cross-departmentally. By utilizing the machine learning 'random forest method' to build a risk prediction model which can early detect families that may very likely to have child abuse occurrence, the SCHF marks high-risk families red, yellow, or green to indicate the urgency for intervention, so as to those families concerned can be provided timely services. The accuracy and recall rates of the above model were 80% and 65%. This prediction model can not only improve the child abuse prevention process by helping social workers differentiate the risk level of newly reported cases, which may further reduce their major workload significantly but also can be referenced for future policy-making.

Keywords: child abuse, high-risk families, big data analysis, risk prediction model

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Authors: Syahrir Andi Mangga, Ipranta

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The geological, paleomagnetic, geochemical and geophysical Investigation in The Sumatra Region has yielded some new data, has stimulated a reassessment of stratigraphy, structure, tectonic evolution and which can show a Sumatra geodynamic model. Sumatra island has in the margin of southwest part of the Eurasia plate in the Sundaland cratonic block and occurred as the amalgamation of allochtonous microplates, continental fragments, Island arc and accrctionary by foreland complex which assembled prior to Tertiary. The allochtonous rocks (terranes), can be divided into 4 (four) Terranes with Paleozoic to Mesosoic in age, had different origin, lithology and are separated by a Suture as main fault with trending NW-SE. The terranes are: the Tigapuluh-Bohorok (East Sumatra block / Sibumasu block), Permo-Carboniferous in age and is characterized by the rock types formed in glacio-marine and was intruded by Late Triassic to Early Jurrasic granitics, occupied in the Eastern part of Sumatra, the paleomagnetic data shown 41° South. Tanjung Karang - Gunung Kasih Terrane, is composed of higher metamorphic rocks and supposed to be pre-Carboniferous in age, covered by Mesozoic sedimentary rocks and were intruded by granitic-dioritic rocks, occupied in the Southern part of Sumatra, the paleomagnetic data shown 19° North. The Kuantan-Duabelas Mountain (West Sumatra block) is occupied by metamorphic, sedimentary and volcanic rocks of Paleozoic - Mesozoic (Carboniferous - Triassic) in age, contains a Cathaysion fauna and flora and are intruded by the Mesozoic granitoid rocks. The terrane occurred in the western part of Sumatra. Meanwhile, the Gumai-Garba (Waloya Terrane) which is occupied by the tectonite/melange, metasediment, carbonate and volcanic rocks of Mesozoic (Jurassic - Cretaceous) in age, are intruted by the Late Cretaceous granitoid rocks, the paleomagnetic data shown 30° - 31° South.

Keywords: tectonostratigraphy, amalgamation, allochtonous, terranes, sumatra

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Authors: William Ramirez-Benavides

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The mite Varroa destructor Anderson & Trueman (Mesostigmata: Varroidae), is an exclusive hematophagous parasite of the Apis honey bees (Apidae: Hymenoptera). The early phoretic female mites have multiple small inactivated oocytes. Consequently, for the initial growth and vitellogenesis of the oocytes, the mother mite must feed on the hemolymph of the host, as a unique food source, by taking intermittently variable number of blood meals: 1. During the phoretic phase, to initiate vitellogenesis of the terminal oocyte, 2. From a freshly capped bee cell with a bee larva, up to the apolysis stage, to complete vitellogenesis and embryogenesis of the terminal oocyte, and 3. From all pupal stages, up to the imago stage, to induce oogenesis and vitellogenesis of the would-be nonembryonic female eggs. Additionally, oogenesis and vitellogenesis expressions in Varroa destructor and other Varroidae varies according to environmental conditions, e.g., chemical attractions produced by the adult bee and larvae, race of bees, sex of the larva, developmental period of the bee larva, food quality and quantity, and superparasitism (several cofoundressess). Also, the feeding stimuli obtained from the host hemolymph, indirectly regulate the reproductive physiology of the mite, by inducing different vitellogenin expressions, the production of a male egg first in the sequence followed by vitellogenesis of the would-be female eggs during the pupal stages. Furthermore, the different uptakes of hemolymph from the host, also indirectly induce the production of the male egg first in the sequence, local mate competition (LMC) and variable adaptive female sex ratios in the broods, especially when superparasitism occurs. Consequently, reproduction in Varroa destructor, and probably in other Varroidae, depends exclusively on feeding in the hemolymph of the bee host, even during the phoretic phase, the prepupal stages and during the pupal stages; and that, the feeding factors are common syndromes in other Varroidae.

Keywords: oogenesis, sex determination, varroa destructor, vitellogenesis

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Authors: Jayanthi Rajendran

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Experience is what makes a man perfect. Though we tend to learn many a different things in life through practice still we need to go an extra mile to gain experience which would be profitable only when it is integrated with regular practice. A clear phenomenal idea is that every teacher is a learner. The centralized idea of this paper would focus on the integrated practices carried out among the students of Jizan University which enhances learning through experiences. Integrated practices like student-directed activities, balanced curriculum, phonological based activities and use of consistent language would enlarge the vision and mission of students to earn experience through learning. Students who receive explicit instruction and guidance could practice the skills and strategies through student-directed activities such as peer tutoring and cooperative learning. The second effective practice is to use consistent language. Consistent language provides students a model for talking about the new concepts which also enables them to communicate without hindrances. Phonological awareness is an important early reading skill for all students. Students generally have phonemic awareness in their home language can often transfer that knowledge to a second language. And also a balanced curriculum requires instruction in all the elements of reading. Reading is the most effective skill when both basic and higher-order skills are included on a daily basis. Computer based reading and listening skills will empower students to understand a language in a better way. English language learners can benefit from sound reading instruction even before they are fully proficient in English as long as the instruction is comprehensible. Thus, if students have to be well equipped in learning they should foreground themselves in various integrated practices through multifarious experience for which teachers are moderators and trainers. This type of learning prepares the students for a constantly changing society which helps them to meet the competitive world around them for better employability fulfilling the vision and mission of the institution.

Keywords: consistent language, employability, phonological awareness, balanced curriculum

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Authors: Dwitya Elvira, Raveinal Masri, Rohayat Bilmahdi

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Human Immunodeficiency Virus (HIV) pandemic increased significantly worldwide. The rise in cases of HIV/AIDS was also followed by an increase in the incidence of opportunistic infection, with tuberculosis being the most opportunistic infection found in HIV/AIDS and the main cause of mortality in HIV/AIDS patients. Diagnosis of tuberculosis in HIV/AIDS patients is often difficult because of the uncommon symptom in HIV/AIDS patients compared to those without the disease. Thus, diagnostic tools are required that are more effective and efficient to diagnose tuberculosis in HIV/AIDS. CXCL-10/IP-10 is a chemokine that binds to the CXCR3 receptor found in HIV/AIDS patients with a weakened immune system. Tuberculosis infection in HIV/AIDS activates chemokine IP-10 in urine, which is used as a marker for diagnosis of infection. The aim of this study was to prove whether IP-10 urine can be a biomarker diagnosis of active lung tuberculosis in HIV-AIDS patients. Design of this study is a cross sectional study involving HIV/AIDS patients with lung tuberculosis as the subject of this study. Forty-seven HIV/AIDS patients with tuberculosis based on clinical and biochemical laboratory were asked to collect urine samples and IP-10/CXCL-10 urine being measured using ELISA method with 18 healthy human urine samples as control. Forty-seven patients diagnosed as HIV/AIDS were included as a subject of this study. HIV/AIDS were more common in male than in women with the percentage in male 85.1% vs. 14.5% of women. In this study, most diagnosed patients were aged 31-40 years old, followed by those 21-30 years, and > 40 years old, with one case diagnosed at age less than 20 years of age. From the result of the urine IP-10 using ELISA method, there was significant increase of the mean value of IP-10 urine in patients with TB-HIV/AIDS co-infection compared to the healthy control with mean 61.05 pg/mL ± 78.01 pg/mL vs. mean 17.2 pg/mL. Based on this research, there was significant increase of urine IP-10/CXCL-10 in active lung tuberculosis with HIV/AIDS compared to the healthy control. From this finding, it is necessary to conduct further research into whether urine IP-10/CXCL-10 plays a significant role in TB-HIV/AIDS co-infection, which can also be used as a biomarker in the early diagnosis of TB-HIV.

Keywords: chemokine, HIV/AIDS, IP-10 urine, tuberculosis

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Authors: Richard Mababu Mukiur

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Leadership is an important drive that plays a key role in the success and development of organizations, particularly in the current context of digital transformation, highly competitivity and globalization. Leaders are persons that hold a dominant and privileged position within an organization, field, or sector of activities and are able to manage, motivate and exercise a high degree of influence over other in order to achieve the institutional goals. They achieve commitment and engagement of others to embrace change, and to make good decisions. Leadership studies in higher education institutions have examined how effective leaders hold their organizations, and also to find approaches which fit best in the organizations context for its better management, transformation and improvement. Moreover, recent studies have highlighted the impact of leadership styles on organizational performance and innovation capacities, since some styles give better results than others. Effective leadership is part of learning process that take place through day-to-day tasks, responsibilities, and experiences that influence the organizational performance, innovation and engagement of employees. The adoption of appropriate leadership styles can improve organization results and encourage learning process, team skills and performance, and employees' motivation and engagement. In the case of case of Information Technology sector, leadership styles are particularly crucial since this sector is leading relevant changes and transformations in the knowledge society. In this context, the main objective of this study is to analyze managers leadership styles with their relation to organizational performance and innovation that may be mediated by learning organization process and demographic variables. Therefore, it was hypothesized that the transformational and transactional leadership will be the main style adopted in Information Technology sector and will influence organizational performance and innovation capacity. A sample of 540 participants from Information technology sector has been determined in order to achieve the objective of this study. The Multifactor Leadership Questionnaire was administered as the principal instrument, Scale of innovation and Learning Organization Questionnaire. Correlations and multiple regression analysis have been used as the main techniques of data analysis. The findings indicate that leadership styles have a relevant impact on organizational performance and innovation capacity. The transformational and transactional leadership are predominant styles in Information technology sector. The effective leadership style tend to be characterized by the capacity of generating and sharing knowledge that improve organization performance and innovation capacity. Managers are adopting and adapting their leadership styles that respond to the new organizational, social and cultural challenges and realities of contemporary society. Managers who encourage innovation, foster learning process, share experience are useful to the organization since they contribute to its development and transformation. Learning process capacity and demographic variables (age, gender, and job tenure) mediate the relationship between leadership styles, innovation capacity and organizational performance. The transformational and transactional leadership tend to enhance the organizational performance due to their significant impact on team-building, employees' engagement and satisfaction. Some practical implications and future lines of research have been proposed.

Keywords: leadership styles, tranformational leadership, organisational performance, organisational innovation

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Authors: Caroline Rocco, Feyza Karasu, Céline Croutxé-Barghorn, Xavier Allonas, Maxime Lecompère, Gérard Riess, Yujing Zhang, Catarina Esteves, Leendert van der Ven, Rolf van Benthem Gijsbertus de With

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Acrylates are widely used in UV-curing technology. Their high reactivity can, however, limit their conversion due to early vitrification. In addition, the free radical photopolymerization is known to be sensitive to oxygen inhibition leading to tacky surfaces. Although epoxides can lead to full polymerization, they are sensitive to humidity and exhibit low polymerization rate. To overcome the intrinsic limitations of both classes of monomers, Interpenetrating Polymer Networks (IPNs) can be synthesized. They consist of at least two cross linked polymers which are permanently entangled. They can be achieved under thermal and/or light induced polymerization in one or two steps approach. IPNs can display homogeneous to heterogeneous morphologies with various degrees of phase separation strongly linked to the monomer miscibility and also synthesis parameters. In this presentation, we synthesize UV-cured methacrylate - epoxide based IPNs with different chemical compositions in order to get a better understanding of their formation and phase separation. Miscibility before and during the photopolymerization, reaction kinetics, as well as mechanical properties and morphology have been investigated. The key parameters controlling the morphology and the phase separation, namely monomer miscibility and synthesis parameters have been identified. By monitoring the stiffness changes on the film surface, atomic force acoustic microscopy (AFAM) gave, in conjunction with polymerization kinetic profiles and thermomechanical properties, explanations and corroborated the miscibility predictions. When varying the methacrylate / epoxide ratio, it was possible to move from a miscible and highly-interpenetrated IPN to a totally immiscible and phase-separated one.

Keywords: investigation of properties and morphology, kinetics, phase separation, UV-cured IPNs

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Authors: Pawan Kumar Gupta, Sumana Ghosh

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Parkinson's Disease (PD) is a long-term neurodegenerative movement disorder of the central nervous system with vast symptoms related to the motor system. The common symptoms of PD are tremor, rigidity, bradykinesia/akinesia, and postural instability, but the clinical symptom includes other motor and non‐motor issues. The motor symptoms of the disease are consequence of death of the neurons in a region of the midbrain known as substantia nigra pars compacta, leading to decreased level of a neurotransmitter known as dopamine. The cause of this neuron death is not clearly known but involves formation of Lewy bodies, an abnormal aggregation or clumping of the protein alpha-synuclein in the neurons. Unfortunately, there is no cure for PD, and the management of this disease is challenging. Therefore, it is critical for a patient to be diagnosed at early stages. A limited choice of drugs is available to improve the symptoms, but those become less and less effective over time. Apart from that, with rapid growth in the field of science and technology, other methods such as multi-area brain stimulation are used to treat patients. In order to develop advanced techniques and to support drug development for treating PD patients, an accurate mathematical model is needed to explain the underlying relationship of dopamine secretion in the brain with the hand tremors. There has been a lot of effort in the past few decades on modeling PD tremors and treatment effects from a computational point of view. These models can effectively save time as well as the cost of drug development for the pharmaceutical industry and be helpful for selecting appropriate treatment mechanisms among all possible options. In this review paper, an effort is made to investigate studies on PD modeling and analysis and to highlight some of the key advances in the field over the past centuries with discussion on the current challenges.

Keywords: Parkinson's disease, deep brain stimulation, tremor, modeling

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Authors: Mdoe Mwajuma Bakari, Mselle Lilian Teddy, Kibusi Stephen Mathew

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Background: Due to the increase of caesarean section (CS), many women are discharge early to their home. Women should be aware on how to take care of themselves at home after CS. Evidence shows non-uniform health education on home care after CS are provided to post CS mothers because of lack of standard home care guideline on home after CS; as existing guidelines explore only care of women in hospital setting, for health care workers. There is a need to develop post CS home care guide; exploring contents of home based care education after CS provided by nurse midwives will inform the development of the guide. Objective: To explore the content of health education provided by nurse midwives to post CS mother about home care after hospital discharge in Dodoma, Tanzania. Methodology: An exploratory qualitative study using in-depth interview was conducted in this study using triangulation of data collection method; where 14 nurse midwives working in maternity unit and 11 post CS mother attending their post-natal clinic were recruited. Content analysis was used to generate themes that describe health education information provided by nurse midwives to post CS mother about home care after hospital discharge. Results: The study found that, nutrition health education, maternal and newborn hygiene care of caesarean wound at home were the component of health education provided to post CS mothers by nurse midwives. Contradicting instruction were found to be provided to post CS mothers. Conclusion: This study reported non-uniform health education provided by the nurse midwives on home care after CS. Despite of the fact that nurse midwives recognizes the need to provide health education to the post CS mothers, there is a need to develop home care guideline as a reference for their education to ensure uniform package of education is provided to post CS mothers in order to improve recovery of post CS mothers from CS.

Keywords: caesarean section, home care, discharge education, homecare after caesarean section

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Authors: Paul Lam, Kevin Wong, Chi Him Chan

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Constant practicing and accurate, immediate feedback are the keys to improving students’ speaking skills. However, traditional oral examination often fails to provide such opportunities to students. The traditional, face-to-face oral assessment is often time consuming – attending the oral needs of one student often leads to the negligence of others. Hence, teachers can only provide limited opportunities and feedback to students. Moreover, students’ incentive to practice is also reduced by their anxiety and shyness in speaking the new language. A mobile app was developed to use artificial intelligence (AI) to provide immediate feedback to students’ speaking performance as an attempt to solve the above-mentioned problems. Firstly, it was thought that online exercises would greatly increase the learning opportunities of students as they can now practice more without the needs of teachers’ presence. Secondly, the automatic feedback provided by the AI would enhance students’ motivation to practice as there is an instant evaluation of their performance. Lastly, students should feel less anxious and shy compared to directly practicing oral in front of teachers. Technically, the program made use of speech-to-text functions to generate feedback to students. To be specific, the software analyzes students’ oral input through certain speech-to-text AI engine and then cleans up the results further to the point that can be compared with the targeted text. The mobile app has invited English teachers for the pilot use and asked for their feedback. Preliminary trials indicated that the approach has limitations. Many of the users’ pronunciation were automatically corrected by the speech recognition function as wise guessing is already integrated into many of such systems. Nevertheless, teachers have confidence that the app can be further improved for accuracy. It has the potential to significantly improve oral drilling by giving students more chances to practice. Moreover, they believe that the success of this mobile app confirms the potential to extend the AI-assisted assessment to other language skills, such as writing, reading, and listening.

Keywords: artificial Intelligence, mobile learning, oral assessment, oral practice, speech-to-text function

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Authors: Maryam Salehi, Gholamreza Bonyadinejad

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The application of agricultural plastic products like mulch, greenhouse covers, and silage films is increasing due to their economic benefits in providing an early and better-quality harvest. In 2015, the 4 million tons (valued a 10.6 million USD) global market for agricultural plastic films was estimated to grow by 5.6% per year through 2030. Despite the short-term benefits provided by plastic products, their long-term sustainability issues and negative impacts on soil health are not well understood. After their removal from the field, some plastic residuals remain in the soil. Plastic residuals in farmlands may fragment to small particles called microplastics (d<5mm). The microplastics' exposure to solar radiation could alter their surface chemistry and make them susceptible to fragmentation. Thus, this study examined the photodegradation of low density polyethylene as the model microplastics that are released to the agriculture farmland. The variation of plastic’s surface chemistry, morphology, and bulk characteristics were studied after accelerated UV-A radiation experiments and sampling from an agricultural field. The Attenuated Total Reflectance Fourier Transform Spectroscopy (ATR-FTIR) and X-ray Photoelectron Spectroscopy (XPS) demonstrated the formation of oxidized surface functional groups onto the microplastics surface due to the photodegradation. The Differential Scanning Calorimetry (DSC) analysis revealed an increased crystallinity for the photodegraded microplastics compared to the new samples. The gel permeation chromatography (GPC) demonstrated the reduced molecular weight for the polymer due to the photodegradation. This study provides an important opportunity to advance understanding of soil pollution. Understanding the plastic residuals’ variations as they are left in the soil is providing a critical piece of information to better estimate the microplastics' impacts on environmental biodiversity, ecosystem sustainability, and food safety.

Keywords: soil health, plastic pollution, sustainability, photodegradation

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Authors: Y. Abdul Aziz, E. L. K. Osafo, S. O. Apori, A. Osman

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A sixteen week trial was conducted at the Research Farm (Technology Village) of the Department of Animal Science, School of Agriculture, University of Cape Coast, Cape Coast, Ghana. This study sought to investigate the effects of Probiotic (RE3) on growth performance, diarrhea incidence and blood parameters of N’dama calves. Sixteen N’dama calves aged 3 months of an average initial weight of 44.2 kg were randomly assigned to one of four dietary treatments according to their body weight, age, and sex. Treatment 1 (T1) serve as a control animal (No RE3 supplementation). Treatment 2 (T2) receives 0.03 ml RE3 per kg body weight. Treatment 3 (T3) receives 0.06 ml RE3 per kg body weight, and Treatment 4 (T4) also receives 0.09 ml RE3 per kg body weight in a Completely Randomize Design (CRD). There were 4 replicates per treatment. The calves were allowed access to feed and water ad libitum. The body weight of the calves was recorded at the start of the experiment and thereafter regularly at two weeks interval. Weighing was done early morning before the calves are allowed to access feed and water and were also observed in their pens for occurrence of diarrhea and faecal scores recorded. Blood samples were obtained from each calf at the end of the study through jugular vein puncture. Supplementation of RE3 to calves had showed a beneficial effect by reducing the incidence of diarrhea. The highest faecal score was recorded in T1 and the least faecal score was recorded in T3. There was significant difference (P < 0.05) in the faecal score between the treatment group and the control after two weeks of the experiment. There was no significant difference (P > 0.05) in the average daily gain of the animals. Hematological and biochemical indices of calves were all within the normal range except in treatments (1, 3 and 4) which recorded high White Blood Cell (WBC) count with no significant difference (P > 0.05).

Keywords: probiotics (RE3), diarrhea incidence, blood parameters, N’dama calves

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Authors: Venkatgiri, Ranganath, L. Nagaraja, B. N. Sagar Pandav, S. M. Usturge, D. Dilipkumar, B. V. Shivprakash, B. Bhagwanthappa, D. Jahangir

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A comparative evaluation of Tramadol and Pentazocine as a pre-emptive analgesic in clinical cases of female dogs undergoing ovariohysterectomy was undertaken during this study. During the study, the following parameters were assessed viz., Rectal temperature (ᵒF), Respiratory rate (breaths/min) and Heart rate (beats/min). Hematological and biochemical parameters viz., total erythrocyte count (TEC) (millions/cmm), hemoglobin (g %), otal leucocytes count (TLC) (thousands/cmm), differential leucocytes count (DLC) (%), serum creatinine (mg/dl), plasma protein (mg/dl), blood glucose (mg/dl) was estimated before the surgery and after administration of general anaesthesia and immediate postoperative periods of 0, 12 and 24 hr respectively. Mean Total Pain Score (MTPS) includes measurement of parameters like posture, vocalization, activity level, response to palpation and agitation at different intervals was calculated before surgery and after administration of general anesthesia and post-operative periods of 1, 2, 4, 6, 12hrs and 24 hrs respectively. Mean Total Pain Score (MTPS) was given for each parameter (Posture, Vocalization, Activity Level, Response to Palpation and Agitation) like 0,1,2,3. (maximum score will be given was 4.). Results were revealed in all three groups including control group. There were significant minor alterations in physiological, hematological and biochemical parameters. MTPS (mean total pain score) were revealed and found a significant alteration when compared with control group. In conclusion, Tramadol found to be a better analgesic and had up to 8hrs of analgesic effect and Pentazocine is superior in post-operative pain management when compared to Tramadol because this group of dogs experienced less surgical stress, consumed less anesthetic dose, they recovered early, and they had less MTPS score.

Keywords: dog, pentazocine, tramadol, ovariohysterectomy

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Authors: Solaine Hachem, Frédéric Bourquin, Dominique Siegert

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The brutal collapse of bridges is mainly due to scour. Indeed, the soil erosion in the riverbed around a pier modifies the embedding conditions of the structure, reduces its overall stiffness and threatens its stability. Hence, finding an efficient technique that allows early scour detection becomes mandatory. Vibration analysis is an indirect method for scour detection that relies on real-time monitoring of the bridge. It tends to indicate the presence of a scour based on its consequences on the stability of the structure and its dynamic response. Most of the research in this field has focused on the dynamic behavior of a single pile and has examined the depth of the scour. In this paper, a bridge is fully modeled with all piles and spans and the scour is represented by a reduction in the foundation's stiffnesses. This work aims to identify the vibration modes sensitive to the rigidity’s loss in the foundations so that their variations can be considered as a scour indicator: the decrease in soil-structure interaction rigidity leads to a decrease in the natural frequencies’ values. By using the first-order perturbation method, the expression of sensitivity, which depends only on the selected vibration modes, is established to determine the deficiency of foundations stiffnesses. The solutions are obtained by using the singular value decomposition method for the regularization of the inverse problem. The propagation of uncertainties is also calculated to verify the efficiency of the inverse problem method. Numerical simulations describing different scenarios of scour are investigated on a simplified model of a real composite steel-concrete bridge located in France. The results of the modal analysis show that the modes corresponding to in-plane and out-of-plane piers vibrations are sensitive to the loss of foundation stiffness. While the deck bending modes are not affected by this damage.

Keywords: bridge’s piers, inverse problems, modal sensitivity, scour detection, vibration analysis

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Authors: Malik Muhammad Arslan, Muneeb Ullah, Dai Shihan, Daniyal Haider, Xiaodong Yang

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Chest X-rays are instrumental in the detection and monitoring of a wide array of diseases, including viral infections such as COVID-19, tuberculosis, pneumonia, lung cancer, and various cardiac and pulmonary conditions. To enhance the accuracy of diagnosis, artificial intelligence (AI) algorithms, particularly deep learning models like Convolutional Neural Networks (CNNs), are employed. However, these deep learning models demand a substantial and varied dataset to attain optimal precision. Generative Adversarial Networks (GANs) can be employed to create new data, thereby supplementing the existing dataset and enhancing the accuracy of deep learning models. Nevertheless, GANs have their limitations, such as issues related to stability, convergence, and the ability to distinguish between authentic and fabricated data. In order to overcome these challenges and advance the detection and classification of CXR normal and abnormal images, this study introduces a distinctive technique known as DCWGAN (Diverse Conditional Wasserstein GAN) for generating synthetic chest X-ray (CXR) images. The study evaluates the effectiveness of this Idiosyncratic DCWGAN technique using the ResNet50 model and compares its results with those obtained using the traditional GAN approach. The findings reveal that the ResNet50 model trained on the DCWGAN-generated dataset outperformed the model trained on the classic GAN-generated dataset. Specifically, the ResNet50 model utilizing DCWGAN synthetic images achieved impressive performance metrics with an accuracy of 0.961, precision of 0.955, recall of 0.970, and F1-Measure of 0.963. These results indicate the promising potential for the early detection of diseases in CXR images using this Inimitable approach.

Keywords: CNN, classification, deep learning, GAN, Resnet50

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