Search results for: genome scale metabolic model

Authors: Jialin Ma, Jia Meng

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Genomic features, the genome-based coordinates, are commonly used for the representation of biological features such as genes, RNA transcripts and transcription factor binding sites. For the analysis of RNA-related genomic features, such as RNA modification sites, a common task is to correlate these features with transcript components (5'UTR, CDS, 3'UTR) to explore their distribution characteristics in terms of transcriptomic coordinates, e.g., to examine whether a specific type of biological feature is enriched near transcription start sites. Existing approaches for performing these tasks involve the manipulation of a gene database, conversion from genome-based coordinate to transcript-based coordinate, and visualization methods that are capable of showing RNA transcript components and distribution of the features. These steps are complicated and time consuming, and this is especially true for researchers who are not familiar with relevant tools. To overcome this obstacle, we develop a dedicated web app TARF, which represents web toolkit for annotating RNA-related genomic features. TARF web tool intends to provide a web-based way to easily annotate and visualize RNA-related genomic features. Once a user has uploaded the features with BED format and specified a built-in transcript database or uploaded a customized gene database with GTF format, the tool could fulfill its three main functions. First, it adds annotation on gene and RNA transcript components. For every features provided by the user, the overlapping with RNA transcript components are identified, and the information is combined in one table which is available for copy and download. Summary statistics about ambiguous belongings are also carried out. Second, the tool provides a convenient visualization method of the features on single gene/transcript level. For the selected gene, the tool shows the features with gene model on genome-based view, and also maps the features to transcript-based coordinate and show the distribution against one single spliced RNA transcript. Third, a global transcriptomic view of the genomic features is generated utilizing the Guitar R/Bioconductor package. The distribution of features on RNA transcripts are normalized with respect to RNA transcript landmarks and the enrichment of the features on different RNA transcript components is demonstrated. We tested the newly developed TARF toolkit with 3 different types of genomics features related to chromatin H3K4me3, RNA N6-methyladenosine (m6A) and RNA 5-methylcytosine (m5C), which are obtained from ChIP-Seq, MeRIP-Seq and RNA BS-Seq data, respectively. TARF successfully revealed their respective distribution characteristics, i.e. H3K4me3, m6A and m5C are enriched near transcription starting sites, stop codons and 5’UTRs, respectively. Overall, TARF is a useful web toolkit for annotation and visualization of RNA-related genomic features, and should help simplify the analysis of various RNA-related genomic features, especially those related RNA modifications.

Keywords: RNA-related genomic features, annotation, visualization, web server

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Authors: Ryan Dale B. Elnar

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This study developed a multidimensional need assessment scale for college students called The University of Mindanao Needs Assessment Scale (UMNAS). Although there are context-specific instruments measuring the needs of clinical and non-clinical samples, literature reveals no standardized scales to measure the needs of the college students thus a four-phase item development process was initiated to support its content validity. Comprising seven broad facets namely spiritual-moral, intrapersonal, socio-personal, psycho-emotional, cognitive, physical and sexual, a pyramid model of college needs was deconstructed through FGD sample to support the literature review. Using various construct validity procedures, the model was further tested using a total of 881 Filipino college samples. The result of the study revealed evidences of the reliability and validity of the UMNAS. The reliability indices range from .929-.933. Exploratory and confirmatory factor analyses revealed a one-factor-six-dimensional instrument to measure the needs of the college students. Using multivariate regression analysis, year level and course are found predictors of students’ needs. Content analysis attested the usefulness of the instrument to diagnose students’ personal and academic issues and concerns in conjunction with other measures. The norming process includes 1728 students from the different colleges of the University of Mindanao. Further validation is recommended to establish a national norm for the instrument.

Keywords: needs assessment scale, validity, factor analysis, college students

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Authors: Pui Shan Wong, Kosuke Tashiro, Satoru Kuhara, Sachiyo Aburatani

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Functional genomics and gene regulation inference has readily expanded our knowledge and understanding of gene interactions with regards to expression regulation. With the advancement of transcriptome sequencing in time-series comes the ability to study the sequential changes of the transcriptome. This method presented here works to augment existing regulation networks accumulated in literature with transcriptome data gathered from time-series experiments to construct a sequential representation of transcription factor activity. This method is applied on a time-series RNA-Seq data set from Escherichia coli as it transitions from growth to stationary phase over five hours. Investigations are conducted on the various metabolic activities in gene regulation processes by taking advantage of the correlation between regulatory gene pairs to examine their activity on a dynamic network. Especially, the changes in metabolic activity during phase transition are analyzed with focus on the pagP gene as well as other associated transcription factors. The visualization of the sequential transcriptional activity is used to describe the change in metabolic pathway activity originating from the pagP transcription factor, phoP. The results show a shift from amino acid and nucleic acid metabolism, to energy metabolism during the transition to stationary phase in E. coli.

Keywords: Escherichia coli, gene regulation, network, time-series

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Authors: Santiago Silva de Andrade

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In recent decades, Marx's ecological theory of the value-form and the theory of metabolic rift have represented fundamental methodological innovations for social scientists interested in environmental transformations and their relationships with the development of the capital system. However, among Latin American environmental historians, such theoretical and methodological instruments have been used infrequently and very cautiously. This investigation aims to demonstrate how the concepts of metabolic rift and ecological value-form are important for understanding the environmental, economic and social transformations in the Amazon region between the second half of the 19th century and the end of the 20th century. Such transformations manifested themselves mainly in two dimensions: the first concerns the link between the manufacture of tropical substances for export and scientific developments in the fields of botany, chemistry and agriculture. This link was constituted as a set of social, intellectual and economic relations that condition each other, configuring an asymmetrical field of exchanges and connections between the demands of the industrialized world - personified in scientists, naturalists, businesspeople and bureaucrats - and the agencies of local social actors, such as indigenous people, riverside dwellers and quilombolas; the second dimension concerns the imperative link between the historical development of the capitalist world-system and the restructuring of the natural world, its landscapes, biomes and social relations, notably in peripheral colonial areas. The environmental effects of capitalist globalization were not only seen in the degradation of exploited environments, although this has been, until today, its most immediate and noticeable aspect. There was also, in territories subject to the logic of market accumulation, the reformulation of patterns of authority and institutional architectures, such as property systems, political jurisdictions, rights and social contracts, as a result of the expansion of commodity frontiers between the 16th and 21st centuries. . This entire set of transformations produced impacts on the ecological landscape of the Amazon. This demonstrates the need to investigate the histories of local configurations of power, spatial and ecological - with their institutions and social actors - and their role in structuring the capitalist world-system , under the lens of the ecological theory of value-form and metabolic rift.

Keywords: amazon, ecology, form-value, metabolic rift

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Authors: Ellie Fini, Mahour Parast, Daniel Oldham, Shahrzad Hosseinnezhad

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This paper investigates the relationship between molecular species of four different bio-based adhesives (made from Swine Manure, Miscanthus Pellet, Corn Stover, and Wood Pellet) and their rheological behavior before and after they undergo extensive oxidative aging. To study the effect of oxidative aging on the chemical structure of bio-adhesives, Infrared Attenuated Total Reflectance Spectroscopy (Fourier transform infrared) was utilised. In addition, a Drop Shape Analyser, Rotational Viscometer, and Dynamic Shear Rheometer were used to evaluate the surface properties and rheological behaviour of each bio-adhesive. Overall, bio-adhesives were found to be significantly different in terms of their ageing characteristics. Accordingly, their surface and rheological properties were found to be ranked differently before and after ageing. The results showed that the bio-adhesive from swine manure is less susceptible to aging compared to plant-based bio-oils. This can be further attributed to the chemical structure and the high lipid contents of the bio-adhesive from swine manure, making it less affected by oxidative ageing.

Keywords: bio-adhesive, rheology, bio-mass, material genome

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Authors: Shane D. Inder, Mehrdad Khamooshi

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Efficient energy storage is a crucial factor in facilitating the uptake of renewable energy resources. Among the many options available for energy storage systems required to balance imbalanced supply and demand cycles, compressed air energy storage (CAES) is a proven technology in grid-scale applications. This paper reviews the current state of micro scale CAES technology and describes a micro-scale advanced adiabatic CAES (A-CAES) system, where heat generated during compression is stored for use in the discharge phase. It will also describe a thermodynamic model, developed in EES (Engineering Equation Solver) to evaluate the performance and critical parameters of the discharge phase of the proposed system. Three configurations are explained including: single turbine without preheater, two turbines with preheaters, and three turbines with preheaters. It is shown that the micro-scale A-CAES is highly dependent upon key parameters including; regulator pressure, air pressure and volume, thermal energy storage temperature and flow rate and the number of turbines. It was found that a micro-scale AA-CAES, when optimized with an appropriate configuration, could deliver energy input to output efficiency of up to 70%.

Keywords: CAES, adiabatic compressed air energy storage, expansion phase, micro generation, thermodynamic

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Authors: Adeline Fontvieille, Hugo Parent-Roberge, Marie-France Langlois, Tamas Fulop, Michel Pavic, Eleonor Riesco

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Introduction: Total lean body mass is reduced during cancer treatment. This loss is called cancer cachexia and is accompanied by a progressive loss of fat mass. In older adults, these body composition changes can have a larger impact on metabolic health, physical autonomy, and cancer survival. Although currently untreatable, exercise training could reduce these effects. Hence, the objective of this pilot study is to investigate if 12 weeks of exercise training during cancer treatment can mitigate the loss of muscle mass and fat mass in older adults. Methods: A total of 40 older adults (65-80 years) with an ongoing treatment for a curable cancer are currently recruited and randomised in two groups: 1) Combined training (EX, n=20) and 2) Control group (CON, n=20). All variables are measured before and after 12 weeks of intervention: Anthropometry (weight, height, body mass index), body composition (total fat mass, visceral adipose tissue, total and appendicular muscle mass; DXA), metabolic profile (HDL-C and LDL-C, triglycerides, glucose and insulin levels). Results: Preliminary analyses revealed no impact of exercise training on appendicular muscle mass (p=0,31) and fat mass (p=0,31). Furthermore, total body weight, waist circumference, HDL-cholesterol, LDL-cholesterol, glucose and insulin levels remained unchanged (all p ≥ 0.79) after 12 weeks of training. However, statistical analyses revealed that triglyceride levels slightly increased (p=0.03), irrespective of the group. Conclusion: Preliminary analyses did not reveal any impact of aerobic and resistance exercise training on body composition in oncogeriatric patients. Furthermore, exercise training seems not efficient to prevent the cancer treatment-related triglyceride levels increase.

Keywords: muscle mass, fat mass, metabolic profile, combined training, aging, cancer

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Authors: Han-Qin Zheng, Yi-Fan Chiang-Hsieh, Chia-Hung Chien, Wen-Chi Chang

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As the most important non-vascular plants, algae have many research applications, including high species diversity, biofuel sources, adsorption of heavy metals and, following processing, health supplements. With the increasing availability of next-generation sequencing (NGS) data for algae genomes and transcriptomes, an integrated resource for retrieving gene expression data and metabolic pathway is essential for functional analysis and systems biology in algae. However, gene expression profiles and biological pathways are displayed separately in current resources, and making it impossible to search current databases directly to identify the cellular response mechanisms. Therefore, this work develops a novel AlgaePath database to retrieve gene expression profiles efficiently under various conditions in numerous metabolic pathways. AlgaePath, a web-based database, integrates gene information, biological pathways, and next-generation sequencing (NGS) datasets in Chlamydomonasreinhardtii and Neodesmus sp. UTEX 2219-4. Users can identify gene expression profiles and pathway information by using five query pages (i.e. Gene Search, Pathway Search, Differentially Expressed Genes (DEGs) Search, Gene Group Analysis, and Co-Expression Analysis). The gene expression data of 45 and 4 samples can be obtained directly on pathway maps in C. reinhardtii and Neodesmus sp. UTEX 2219-4, respectively. Genes that are differentially expressed between two conditions can be identified in Folds Search. Furthermore, the Gene Group Analysis of AlgaePath includes pathway enrichment analysis, and can easily compare the gene expression profiles of functionally related genes in a map. Finally, Co-Expression Analysis provides co-expressed transcripts of a target gene. The analysis results provide a valuable reference for designing further experiments and elucidating critical mechanisms from high-throughput data. More than an effective interface to clarify the transcript response mechanisms in different metabolic pathways under various conditions, AlgaePath is also a data mining system to identify critical mechanisms based on high-throughput sequencing.

Keywords: next-generation sequencing (NGS), algae, transcriptome, metabolic pathway, co-expression

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Authors: Hafiz Arbab Sakandar

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Time-restricted intermittent fasting (TRIF) impacts host’s physiology and health. Plenty of health benefits have been reported for TRIF in animal models. However, limited studies have been conducted on humans especially in underdeveloped economies. Here, we designed a study to investigate the impact of TRIF/Ramadan fasting (16:8) on the modulation of gut-microbiome structure, metabolic pathways, and predicted metabolites and explored the correlation among them at different time points (during and after the month of Ramadan) in Pakistani Expats living in China. We observed different trends of Shannon-Wiener index in different subjects; however, all subjects showed substantial change in bacterial diversity with the progression of TRIF. Moreover, the changes in gut microbial structure by the end of TRIF were higher vis-a-vis in the beginning, significant difference was observed among individuals. Additionally, metabolic pathways analysis revealed that amino acid, carbohydrate and energy metabolism, glycan biosynthesis metabolism of cofactors and vitamins were significantly affected by TRIF. Pyridoxamine, glutamate, citrulline, arachidonic acid, and short chain fatty acid showed substantial difference at different time points based on the predicted metabolism. In conclusion, these results contribute to further our understanding about the key relationship among, dietary intervention (TRIF), gut microbiome structure and function. The preliminary results from study demonstrate significant potential for elucidating the mechanisms underlying gut microbiome stability and enhancing the effectiveness of microbiome-tailored interventions among the Pakistani populace. Nonetheless, extensive, and rigorous large-scale research on the Pakistani population is necessary to expound on the association between diet, gut microbiome, and overall health.

Keywords: gut microbiome, health, fasting, functionality

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Authors: Chamilani Nikapitiya, Mahanama De Zoysa, Jehee Lee

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Most of the bacterial diseases are associated with high mortalities in aquaculture species and causing huge economic losses. Different approaches have been taken to prevent or control of bacterial diseases including use of vaccines, probiotics, chemotherapy, water quality management, etc. Antibiotics are widely applying as chemotherapy to control bacterial diseases, however, it has been shown that frequent use of antibiotics is favored to develop multi-drug resistance bacteria. Therefore, phages and phage encoded lytic proteins are known to be one of the most promising alternatives for antibiotics to avoid the emergence of antibiotic-resistant bacteria. We isolated and characterized the two lytic phages, namely pAh-1 and pAs-1 against pathogenic Aeromonas hydrophila and Aeromonas salmonicida, respectively. Morphological characteristics were analyzed by Transmission electron microscopy (TEM) and host strain specificities were tested with Aeromonas and other closely related bacterial strains. TEM analysis revealed that both pAh-1 and pAsm-1 are composed of an icosahedral head and a segmented tail, and we suggest that, they are new members of Myoviridae family. Genome sizes of isolated phages were estimated by restriction enzyme digestion of genomic DNA using selected endonucleases followed by agarose gel electrophoresis. Estimated genome size of pAh-1 and pAs-1 were approximately 64 Kbp and 120 Kbp, respectively. Both pAh-1 and pAs-1 have shown narrow host specificity. Moreover, protective effects of phage therapy against fish pathogenic A. hydrophila were investigated in zebrafish model. The survival rate was 40% higher when zebrafish received intra-peritoneal injection (i.p.) of pAh-1 were simultaneously challenge A. hydrophila (2 x 106 CFU/fish) compared to that without phage treatment. Overall results suggest that both pAh-1 and pAs-1 can be used as a potential phage therapy to control Aeromonas infections in aquaculture.

Keywords: Aeromonas infections, antibiotic resistance, bacteriophage, bio-control, lytic phage

Procedia PDF Downloads 179

Authors: Turki J. Alharbi, Jencia Wong, Dennis Yue, Tania P. Markovic, Julie Hetherington, Ted Wu, Belinda Brooks, Radhika Seimon, Alice Gibson, Stephanie L. Silviera, Amanda Sainsbury, Tanya J. Little

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Fasting has been practiced for centuries and is incorporated into the practices of different religions including Islam, whose followers intermittently fast throughout the month of Ramadan. Thus, Ramadan presents a unique model of prolonged intermittent fasting (IF). Despite a growing body of evidence for a cardio-metabolic and endocrine benefit of IF, detailed studies of the effects of IF on these indices in type 2 diabetes are scarce. We studied 5 subjects with type 2 diabetes (T2DM) and 7 healthy controls (C) at baseline (pre), and in the last week of Ramadan (post). Fasting circulating levels of glucose, HbA1c and lipids, as well as body composition (with DXA) and resting energy expenditure (REE) were measured. Plasma gut hormone levels and appetite responses to a mixed meal were also studied. Data are means±SEM. Ramadan decreased total fat mass (-907±92 g, p=0.001) and trunk fat (-778±190 g, p=0.014) in T2DM but not in controls, without any reductions in lean mass or REE. There was a trend towards a decline in plasma FFA in both groups. Ramadan had no effect on body weight, glycemia, blood pressure, or plasma lipids in either group. In T2DM only, the area under the curve for post-meal plasma ghrelin concentrations increased after Ramadan (pre:6632±1737 vs. post:9025±2518 pg/ml.min-1, p=0.045). Despite this increase in orexigenic ghrelin, subjective appetite scores were not altered by Ramadan. Meal-induced plasma concentrations of the satiety hormone pancreatic polypeptide did not change during Ramadan, but were higher in T2DM compared to controls (post: C: 23486±6677 vs. T2DM: 62193±6880 pg/ml.min-1, p=0.003. In conclusion, Ramadan, as a model for IF appears to have more favourable effects on body composition in T2DM, without adverse effects on metabolic control or subjective appetite. These data suggest that IF may be particularly beneficial in T2DM as a nutritional intervention. Larger studies are warranted.

Keywords: type 2 diabetes, obesity, intermittent fasting, appetite regulating hormones

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Authors: Pratiksha Dubey, Praveen Singh, Shantanu Sen Gupta, Anand K. Bachhawat

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5-oxoproline (pyroglutamic acid) is a cyclic lactam of glutamic acid. In the cell, it can be produced by several different pathways and is metabolized into glutamate with the help of the 5-oxoprolinase enzyme (OPLAH or OXP1). The inhibition of 5-oxoprolinase enzyme in mammals was found to result in heart failure and is thought to be a consequence of oxidative stress [1]. To analyze the consequences of 5-oxoproline accumulation more clearly, we are generating models for 5-oxoproline accumulation in yeast. The 5-oxoproline accumulation model in yeast is being developed by two different strategies. The first one is by overexpression of the mouse  -glutamylcyclotransferase enzyme. It degrades -glu-met dipeptide into 5-oxoproline and methionine taken by the cell from the medium. The second strategy is by providing high concentration of 5-oxoproline externally to the yeast cells. The intracellular 5-oxoproline levels in both models are being evaluated. In addition, the metabolic and cellular consequences are being investigated.

Keywords: 5-oxoproline, pyroglutamic acid, yeast, genetics

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Authors: Mohamed Hafid, Marcel Lacroix

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This study aimed at developing an inverse heat transfer approach for predicting the time-varying freezing front and the temperature distribution of tumors during cryosurgery. Using a temperature probe pressed against the layer of tumor, the inverse approach is able to predict simultaneously the metabolic heat generation and the blood perfusion rate of the tumor. Once these parameters are predicted, the temperature-field and time-varying freezing fronts are determined with the direct model. The direct model rests on one-dimensional Pennes bioheat equation. The phase change problem is handled with the enthalpy method. The Levenberg-Marquardt Method (LMM) combined to the Broyden Method (BM) is used to solve the inverse model. The effect (a) of the thermal properties of the diseased tissues; (b) of the initial guesses for the unknown thermal properties; (c) of the data capture frequency; and (d) of the noise on the recorded temperatures is examined. It is shown that the proposed inverse approach remains accurate for all the cases investigated.

Keywords: cryosurgery, inverse heat transfer, Levenberg-Marquardt method, thermal properties, Pennes model, enthalpy method

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Authors: Weiyao Zhu, Qian Qi, Ming Yue, Dongxu Ma

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Due to the nano-micro pore structures and the massive multi-stage multi-cluster hydraulic fracturing in shale gas reservoirs, the multi-scale seepage flows are much more complicated than in most other conventional reservoirs, and are crucial for the economic development of shale gas. In this study, a new multi-scale non-linear flow model was established and simplified, based on different diffusion and slip correction coefficients. Due to the fact that different flow laws existed between the fracture network and matrix zone, a three-zone composite model was proposed. Then, according to the conformal transformation combined with the law of equivalent percolation resistance, the productivity equation of a horizontal fractured well, with consideration given to diffusion, slip, desorption, and absorption, was built. Also, an analytic solution was derived, and the interference of the multi-cluster fractures was analyzed. The results indicated that the diffusion of the shale gas was mainly in the transition and Fick diffusion regions. The matrix permeability was found to be influenced by slippage and diffusion, which was determined by the pore pressure and diameter according to the Knudsen number. It was determined that, with the increased half-lengths of the fracture clusters, flow conductivity of the fractures, and permeability of the fracture network, the productivity of the fractured well also increased. Meanwhile, with the increased number of fractures, the distance between the fractures decreased, and the productivity slowly increased due to the mutual interference of the fractures. In regard to the fractured horizontal wells, the free gas was found to majorly contribute to the productivity, while the contribution of the desorption increased with the increased pressure differences.

Keywords: multi-scale, fracture network, composite model, productivity

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Authors: Areej Al-Khabbaz, Swapna Goerge, Majedah Abdul-Rasoul

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Introduction: The most prevalent periodontal disease among children is gingivitis, and it usually becomes more severe in adolescence. A number of intervention studies suggested that resolution of periodontal inflammation can improve metabolic control in patients diagnosed with diabetes mellitus. Aim: to assess the effect of non-surgical periodontal therapy on glycemic control of children diagnosed with diabetes mellitus. Method: Twenty-eight children diagnosed with diabetes mellitus were recruited with established diagnosis diabetes for at least 1 year. Informed consent and child assent form were obtained from children and parents prior to enrolment. The dental examination for the participants was performed on the same week directly following their annual medical assessment. All patients had their glycosylated hemoglobin (HbA1c%) test one week prior to their annual medical and dental visit and 3 months following non-surgical periodontal therapy. All patients received a comprehensive periodontal examination The periodontal assessment included clinical attachment loss, bleeding on probing, plaque score, plaque index and gingival index. All patients were referred for non-surgical periodontal therapy, which included oral hygiene instruction and motivation followed by supra-gingival and subg-ingival scaling using ultrasonic and hand instruments. Statistical Analysis: Data were entered and analyzed using the Statistical Package for Social Science software (SPSS, Chicago, USA), version 18. Statistical analysis of clinical findings was performed to detect differences between the two groups in term of periodontal findings and HbA1c%. Binary logistic regression analysis was performed in order to examine which factors were significant in multivariate analysis after adjusting for confounding between effects. The regression model used the dependent variable ‘Improved glycemic control’, and the independent variables entered in the model were plaque index, gingival index, bleeding %, plaque Statistical significance was set at p < 0.05. Result: A total of 28 children. The mean age of the participants was 13.3±1.92 years. The study participants were divided into two groups; Compliant group (received dental scaling) and non-complaints group (received oral hygiene instructions only). No statistical difference was found between compliant and non-compliant group in age, gender distribution, oral hygiene practice and the level of diabetes control. There was a significant difference between compliant and non-compliant group in term of improvement of HBa1c before and after periodontal therapy. Mean gingival index was the only significant variable associated with improved glycemic control level. In conclusion, this study has demonstrated that non-surgical mechanical periodontal therapy can improve HbA1c% control. The result of this study confirmed that children with diabetes mellitus who are compliant to dental care and have routine professional scaling may have better metabolic control compared to diabetic children who are erratic with dental care.

Keywords: children, diabetes, metabolic control, periodontal therapy

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Authors: A. Ghanbari Mardasi, N. Wu, C. Wu

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In this study, a spatial wavelet-based crack localization technique for a thick beam is presented. Wavelet scale in spatial wavelet transformation is optimized to enhance crack detection sensitivity. A windowing function is also employed to erase the edge effect of the wavelet transformation, which enables the method to detect and localize cracks near the beam/measurement boundaries. Theoretical model and vibration analysis considering the crack effect are first proposed and performed in MATLAB based on the Timoshenko beam model. Gabor wavelet family is applied to the beam vibration mode shapes derived from the theoretical beam model to magnify the crack effect so as to locate the crack. Relative wavelet coefficient is obtained for sensitivity analysis by comparing the coefficient values at different positions of the beam with the lowest value in the intact area of the beam. Afterward, the optimal wavelet scale corresponding to the highest relative wavelet coefficient at the crack position is obtained for each vibration mode, through numerical simulations. The same procedure is performed for cracks with different sizes and positions in order to find the optimal scale range for the Gabor wavelet family. Finally, Hanning window is applied to different vibration mode shapes in order to overcome the edge effect problem of wavelet transformation and its effect on the localization of crack close to the measurement boundaries. Comparison of the wavelet coefficients distribution of windowed and initial mode shapes demonstrates that window function eases the identification of the cracks close to the boundaries.

Keywords: edge effect, scale optimization, small crack locating, spatial wavelet

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Authors: Salma M. Wakil

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Advances in the field of genetics overwhelmed detecting large number of inherited disorders at the molecular level and directed to the development of innovative technologies. These innovations have led to gene sequencing, prenatal mutation detection, pre-implantation genetic diagnosis; population based carrier screening and genome wide analyses using microarrays. Microarrays are widely used in establishing clinical and diagnostic setup for genetic anomalies at a massive level, with the advent of cytoscan molecular karyotyping as a clinical utility card for detecting chromosomal aberrations with high coverage across the entire human genome. Unlike a regular karyotype that relies on the microscopic inspection of chromosomes, molecular karyotyping with cytoscan constructs virtual chromosomes based on the copy number analysis of DNA which improves its resolution by 100-fold. We have been investigating a large number of patients with Developmental Delay and Intellectual disability with this platform for establishing micro syndrome deletions and have detected number of novel CNV’s in the Arabian population with the clinical relevance.

Keywords: microarrays, molecular karyotyping, developmental delay, genetics

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Authors: Les Paul Valdez, Rowena Manzarate, Joseph Carl Lunizo, Mary Thereze Mabaquiao, Mary Deo Luigi Mabunay

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Background: Across the literature, varying definitions of successful aging can be found. As a result, several determinants have been associated with successful aging. However, there is a paucity of literature exploring the relationship between successful aging and factors such as spiritual experience, gerotranscendence, and social engagement. Objective: Thus, this study purports to ascertain the relationship between and among spiritual experience, gerotranscendence, social engagement and successful aging. Methods: The Daily Spiritual Experience Scale (DSES), Social Engagement Scale (SES), Gerotranscendence Scale Revised (GS-R) and Expectations Regarding Aging (ERA) were fielded to 349 incarcerated elderly to measure spiritual experience, social engagement, gerotranscendence and successful aging respectively. Data was analyzed using Structural Equation Modelling through AMOS 21. The hypothesized model was evaluated using the goodness of fit and parsimony indices. Results: Social engagement (β= .179, p=.128) and spiritual experience (β= .375, p=.262) contribute to successful aging through the mediating effect of gerotranscendence (β= .973, p=.718). Conclusion: Today more than ever, healthcare providers in penal institutions are challenged to ensure that incarcerated elderly are socially and spiritually engaged; and have high levels of gerotranscendence.

Keywords: elderly, Filipino, gerotranscendence, social engagement, spiritual experience, successful aging

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Authors: Dino Carpentras, Alejandro Dinkelberg, Michael Quayle

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Within agent-based modeling, opinion dynamics is the field that focuses on modeling people's opinions. In this prolific field, most of the literature is dedicated to the exploration of the two 'degrees of freedom' and how they impact the model’s properties (e.g., the average final opinion, the number of final clusters, etc.). These degrees of freedom are (1) the interaction rule, which determines how agents update their own opinion, and (2) the network topology, which defines the possible interaction among agents. In this work, we show that the third degree of freedom exists. This can be used to change a model's output up to 100% of its initial value or to transform two models (both from the literature) into each other. Since opinion dynamics models are representations of the real world, it is fundamental to understand how people’s opinions can be measured. Even for abstract models (i.e., not intended for the fitting of real-world data), it is important to understand if the way of numerically representing opinions is unique; and, if this is not the case, how the model dynamics would change by using different representations. The process of measuring opinions is non-trivial as it requires transforming real-world opinion (e.g., supporting most of the liberal ideals) to a number. Such a process is usually not discussed in opinion dynamics literature, but it has been intensively studied in a subfield of psychology called psychometrics. In psychometrics, opinion scales can be converted into each other, similarly to how meters can be converted to feet. Indeed, psychometrics routinely uses both linear and non-linear transformations of opinion scales. Here, we analyze how this transformation affects opinion dynamics models. We analyze this effect by using mathematical modeling and then validating our analysis with agent-based simulations. Firstly, we study the case of perfect scales. In this way, we show that scale transformations affect the model’s dynamics up to a qualitative level. This means that if two researchers use the same opinion dynamics model and even the same dataset, they could make totally different predictions just because they followed different renormalization processes. A similar situation appears if two different scales are used to measure opinions even on the same population. This effect may be as strong as providing an uncertainty of 100% on the simulation’s output (i.e., all results are possible). Still, by using perfect scales, we show that scales transformations can be used to perfectly transform one model to another. We test this using two models from the standard literature. Finally, we test the effect of scale transformation in the case of finite precision using a 7-points Likert scale. In this way, we show how a relatively small-scale transformation introduces both changes at the qualitative level (i.e., the most shared opinion at the end of the simulation) and in the number of opinion clusters. Thus, scale transformation appears to be a third degree of freedom of opinion dynamics models. This result deeply impacts both theoretical research on models' properties and on the application of models on real-world data.

Keywords: degrees of freedom, empirical validation, opinion scale, opinion dynamics

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Authors: Paul J. McKay

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Large-scale genome-wide association studies (GWAS) investigating genetic contributions to sexual orientation and gender identity are largely lacking and may reduce stigma experienced in the LGBTQ+ community by providing an underlying biological explanation for queerness. While there is a growing consensus within the scientific community that genetic makeup contributes – at least in part – to sexual orientation and gender identity, there is a marked lack of genomics research exploring polygenic contributions to queerness. Based on recent (2019) findings from a large-scale GWAS investigating the genetic architecture of same-sex sexual behavior, and various additional peer-reviewed publications detailing novel insights into the molecular mechanisms of sexual orientation and gender identity, we hypothesize that sexual orientation and gender identity are complex, multifactorial, and polygenic; meaning that many genetic factors contribute to these phenomena, and environmental factors play a possible role through epigenetic modulation. In recent years, large-scale GWAS studies have been paramount to our modern understanding of many other complex human traits, such as in the case of autism spectrum disorder (ASD). Despite possible benefits of such research, including reduced stigma towards queer people, improved outcomes for LGBTQ+ in familial, socio-cultural, and political contexts, and improved access to healthcare (particularly for trans populations); important risks and considerations remain surrounding this type of research. To mitigate possibilities such as invalidation of the queer identities of existing LGBTQ+ individuals, genetic discrimination, or the possibility of euthanasia of embryos with a genetic predisposition to queerness (through reproductive technologies like IVF and/or gene-editing in utero), we propose a community-engaged research (CER) framework which emphasizes the privacy and confidentiality of research participants. Importantly, the historical legacy of scientific research attempting to pathologize queerness (in particular, falsely equating gender variance to mental illness) must be acknowledged to ensure any future research conducted in this realm does not propagate notions of homophobia, transphobia or stigma against queer people. Ultimately, in a world where same-sex sexual activity is criminalized in 69 UN member states, with 67 of these states imposing imprisonment, 8 imposing public flogging, 6 (Brunei, Iran, Mauritania, Nigeria, Saudi Arabia, Yemen) invoking the death penalty, and another 5 (Afghanistan, Pakistan, Qatar, Somalia, United Arab Emirates) possibly invoking the death penalty, the importance of this research cannot be understated, as finding a biological basis for queerness would directly oppose the harmful rhetoric that “being LGBTQ+ is a choice.” Anti-trans legislation is similarly widespread: In the United States in 2022 alone (as of Oct. 13), 155 anti-trans bills have been introduced preventing trans girls and women from playing on female sports teams, barring trans youth from using bathrooms and locker rooms that align with their gender identity, banning access to gender affirming medical care (e.g., hormone-replacement therapy, gender-affirming surgeries), and imposing legal restrictions on name changes. Understanding that a general lack of knowledge about the biological basis of queerness may be a contributing factor to the societal stigma faced by gender and sexual orientation minorities, we propose the initiation of large-scale GWAS studies investigating the genetic basis of gender identity and sexual orientation.

Keywords: genome-wide association studies (GWAS), sexual and gender minorities (SGM), polygenicity, community-engaged research (CER)

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Authors: Eric Beyegue, Boris Azantza, Judith Laure Ngondi, Julius E. Oben

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Background: Insulin resistance (IR) and oxidative stress are associated with obesity, diabetes mellitus, and other cardio metabolic disorders. The aim of this study was to investigate the effect of Coula edulis extracts (CEE) on insulin resistance and oxidative stress markers in high-fat/high sucrose diet-induced insulin resistance in rats. Materials and Methods: Thirty male rats were divided into 6 groups of 5 rats each fed, received daily oral administration of CE extracts for 8 weeks as follows: Group 1 or negative control group, fed with standard diet (SD); Group 2 fed with high-fat/high sucrose diet (HFHS) only; Group3 fed with HFHS + CEAq 200; Group 4 fed with HFHS + CEAq 400; Group 5 fed with HFHS + CEEt 200; Group 6 fed with HFHS + CEEt 400. At the end of the experiment (8 weeks), animals were sacrificed plasma lipid profile, glucose, insulin, oxidative marker and digestive enzyme activities were measured. The homeostasis model assessment for insulin resistance (HOMA-IR) was determined. Results: Feedings with HFHS significantly (p < 0.01) induced plasma hyperglycaemia, hyperinsulinaemia, increased triglyceride, total cholesterol, and low-density lipoprotein levels, decreased high-density lipoprotein levels, alterations of α amylase, and glucose-6-phosphatase activities, and oxidative stress. Daily oral administration with CEE for eight weeks after insulin resistance induction had a hypolipidaemic action, antioxidative activities and modulated metabolic markers. Ethanolic extract at the higher dose had the best effect on body weight gain and insulin resistance, whereas aqueous extract showed the better activity on hyperlipidemia. Conclusion: These results suggest that CEAq and CEEt at 400mg/kg are promising complementary supplements that can be used to protect better from metabolic disorders associated with HFHS.

Keywords: Coula edulis Baill, high-fat / high sucrose diet, insulin resistance, oxidative stress

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Authors: Ho-Won Jung, Donghun Lee, Hyung-Jin Kim

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Predictive analytics (data analysis) uses a subset of measurements (the features, predictor, or independent variable) to predict another measurement (the outcome, target, or dependent variable) on a single person or unit. It applies empirical methods in statistics, operations research, and machine learning to predict the future, or otherwise unknown events or outcome on a single or person or unit, based on patterns in data. Most analyses of metabolic syndrome are not predictive analytics but statistical explanatory studies that build a proposed model (theory building) and then validate metabolic syndrome predictors hypothesized (theory testing). A proposed theoretical model forms with causal hypotheses that specify how and why certain empirical phenomena occur. Predictive analytics and explanatory modeling have their own territories in analysis. However, predictive analytics can perform vital roles in explanatory studies, i.e., scientific activities such as theory building, theory testing, and relevance assessment. In the context, this study is to demonstrate how to use our predictive analytics to support theory building (i.e., hypothesis generation). For the purpose, this study utilized a big data predictive analytics platform TM based on a co-occurrence graph. The co-occurrence graph is depicted with nodes (e.g., items in a basket) and arcs (direct connections between two nodes), where items in a basket are fully connected. A cluster is a collection of fully connected items, where the specific group of items has co-occurred in several rows in a data set. Clusters can be ranked using importance metrics, such as node size (number of items), frequency, surprise (observed frequency vs. expected), among others. The size of a graph can be represented by the numbers of nodes and arcs. Since the size of a co-occurrence graph does not depend directly on the number of observations (transactions), huge amounts of transactions can be represented and processed efficiently. For a demonstration, a total of 13,254 metabolic syndrome training data is plugged into the analytics platform to generate rules (potential hypotheses). Each observation includes 31 predictors, for example, associated with sociodemographic, habits, and activities. Some are intentionally included to get predictive analytics insights on variable selection such as cancer examination, house type, and vaccination. The platform automatically generates plausible hypotheses (rules) without statistical modeling. Then the rules are validated with an external testing dataset including 4,090 observations. Results as a kind of inductive reasoning show potential hypotheses extracted as a set of association rules. Most statistical models generate just one estimated equation. On the other hand, a set of rules (many estimated equations from a statistical perspective) in this study may imply heterogeneity in a population (i.e., different subpopulations with unique features are aggregated). Next step of theory development, i.e., theory testing, statistically tests whether a proposed theoretical model is a plausible explanation of a phenomenon interested in. If hypotheses generated are tested statistically with several thousand observations, most of the variables will become significant as the p-values approach zero. Thus, theory validation needs statistical methods utilizing a part of observations such as bootstrap resampling with an appropriate sample size.

Keywords: explanatory modeling, metabolic syndrome, predictive analytics, theory building

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Authors: András Farkas, István Molnár, Jan Vrána, Veronika Burešová, Petr Cápal, András Cseh, Márta Molnár-Láng, Jaroslav Doležel

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Species of Aegilops played a central role in the evolution of wheat and are sources of traits related to yield quality and tolerance against biotic and abiotic stresses. These wild genes and alleles are desirable to use in crop improvement programs via introgressive hybridization. However, the success of chromosome mediated gene transfer to wheat are hampered by the pour knowledge on the genome structure of Aegilops relative to wheat and by the low number of cost-effective molecular markers specific for Aegilops chromosomes. The COS markers specific for genes conserved throughout evolution in both sequence and copy number between Triticeae/Aegilops taxa and define orthologous regions, thus enabling the comparison of regions on the chromosomes of related species. The present study compared individual chromosomes of Aegilops umbellulata (UU), Ae. comosa (MM), Ae. speltoides (SS) and Ae. caudata (CC) purified by flourescent labelling with oligonucleotid SSR repeats and biparametric flow cytometry with wheat by identifying orthologous chromosomal regions by COS markers. The linear order of bin-mapped COS markers along the wheat D chromosomes was identified by the use of chromosome-specific sequence data and virtual gene order. Syntenic regions of wheat identifying genome rearrangements differentiating the U, M, S or C genomes from the D genome of wheat were detected. The conserved orthologous set markers assigned to Aegilops chromosomes promise to accelerate gene introgression by facilitating the identification of alien chromatin. The syntenic relationships between the Aegilops species and wheat will facilitate the targeted development of new markers specific for U, M, S and C genomic regions and will contribute to the understanding of molecular processes related to the evolution of Aegilops.

Keywords: Aegilops, cos-markers, flow-sorting, wheat

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Authors: Irina M. Kolesnikova, Andrey M. Gaponov, Sergey A. Roumiantsev, Tatiana V. Grigoryeva, Alexander V. Laikov, Alexander V. Shestopalov

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Background. Neuropathy is a common complication of obesity. In this regard, the content of neurotrophins in such patients is of particular interest. Neurotrophins are the proteins that regulate neuron survival and neuroplasticity and include brain-derived neurotrophic factor (BDNF) and nerve growth factor (NGF). However, the risk of complications depends on the metabolic type of obesity. Metabolically unhealthy obesity (MUHO) is associated with a high risk of complications, while this is not the case with metabolically healthy obesity (MHO). Therefore, the aim of our work was to study the effect of the obesity metabolic type on serum neurotrophins levels. Patients, materials, methods. The study included 134 healthy donors and 104 obese patients. Depending on the metabolic type of obesity, the obese patients were divided into subgroups with MHO (n=40) and MUHO (n=55). In the blood serum, the concentration of BDNF and NGF was determined. In addition, the content of adipokines (leptin, asprosin, resistin, adiponectin), myokines (irisin, myostatin, osteocrin), indicators of carbohydrate, and lipid metabolism were measured. Correlation analysis revealed the relationship between the studied parameters. Results. We found that serum BDNF concentration was not different between obese patients and healthy donors, regardless of obesity metabolic type. At the same time, in obese patients, there was a decrease in serum NGF level versus control. A similar trend was characteristic of both MHO and MUHO. However, MUHO patients had a higher NGF level than MHO patients. The literature indicates that obesity is associated with an increase in the plasma concentration of NGF. It can be assumed that in obesity, there is a violation of NGF storage in platelets, which accelerates neurotrophin degradation. We found that BDNF concentration correlated with irisin levels in MUHO patients. Healthy donors had a weak association between NGF and VEGF levels. No such association was found in obese patients, but there was an association between NGF and leptin concentrations. In MHO, the concentration of NHF correlated with the content of leptin, irisin, osteocrin, insulin, and the HOMA-IR index. But in MUHO patients, we found only the relationship between NGF and adipokines (leptin, asprosin). It can be assumed that in patients with MHO, the replenishment of serum NGF occurs under the influence of muscle and adipose tissue. In the MUHO patients only the effect of adipose tissue on NGF was observed. Conclusion. Obesity, regardless of metabolic type, is associated with a decrease in serum NGF concentration. We showed that muscle and adipose tissues make a significant contribution to the serum NGF pool in the MHO patients. In MUHO there is no effect of muscle on the NGF level, but the effect of adipose tissue remains.

Keywords: neurotrophins, nerve growth factor, NGF, brain-derived neurotrophic factor, BDNF, obesity, metabolically healthy obesity, metabolically unhealthy obesity

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Authors: Givi Kupatadze

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Backward economies are facing a challenge of achieving sustainable high economic growth rate. Dominant growth models represent a roadmap in framing economic development strategy. This paper examines a relevance of the dominant growth models for backward economies. Cobb-Douglas production function, the Harrod-Domar model of economic growth, the Solow growth model and general formula of gross domestic product are examined to undertake a comprehensive study of the dominant growth models. Deductive research method allows to uncover major weaknesses of the dominant growth models and to come up with practical implications for economic development strategy. The key finding of the paper shows, contrary to what used to be taught by textbooks of economics, that constant returns to scale property of the dominant growth models are a mere coincidence and its generalization over space and time can be regarded as one of the most unfortunate mistakes in the whole field of political economy. The major suggestion of the paper for backward economies is that understanding and considering taxonomy of economic activities based on increasing and diminishing returns to scale represent a cornerstone of successful economic development strategy.

Keywords: backward economies, constant returns to scale, dominant growth models, taxonomy of economic activities

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Authors: Irvan Adhin Cholilie, Susinggih Wijana, Yusron Sugiarto

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The aim of this research is to compare the results of black grass jelly produced using laboratory scale and double scale. In this research, the production from the laboratory scale is using ingredients of 1 kg black grass jelly added with 5 liters of water, while the double scale is using 5 kg black grass jelly and 75 liters of water. The results of organoleptic tests performed by 30 panelists (general) to the sample gels of grass black powder produced from both of laboratory and double scale are not different significantly in color, odor, flavor, and texture. Proximate test results conducted in both of grass black jelly powder produced in laboratory scale and double scale also have no significant differences in all parameters. Grass black jelly powder from double scale contains water, carbohydrate, crude fiber, and yield in the amount of 12,25 %; 43,7 %; 5,89 %; and 16,28 % respectively. The results of the energy efficiency analysis by boiling, draining, evaporation, drying, and milling processes are 85,11 %; 76,97 %; 99,64 %; 99,99% and 99,39% respectively. The utility needs including water needs for each batch amounted 0.1 m3 and cost Rp 220,5 per batch, the electricity needs for each batch is 20.01 kWh and cost Rp 18569.28 per batch, and LPG needs for each batch is 30 kg costed Rp 234,000.00 so that the total cost spent for the process is Rp 252,789.78 .

Keywords: black grass jelly, powder, mass balance, energy balance, cost

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Authors: Peter Adly Hamdy Fahmy

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The aim of the study was to examine the effects of a physical education program on student learning by combining the teaching of personal and social responsibility (TPSR) with a physical education model and TPSR with a traditional teaching model, these learning outcomes involving self-learning. -Study. Athletic performance, enthusiasm for sport, group cohesion, sense of responsibility and game performance. The participants were 3 secondary school physical education teachers and 6 physical education classes, 133 participants with students from the experimental group with 75 students and the control group with 58 students, and each teacher taught the experimental group and the control group for 16 weeks. The research methods used surveys, interviews and focus group meetings. Research instruments included the Personal and Social Responsibility Questionnaire, Sports Enthusiasm Scale, Group Cohesion Scale, Sports Self-Efficacy Scale, and Game Performance Assessment Tool. Multivariate analyzes of covariance and repeated measures ANOVA were used to examine differences in student learning outcomes between combining the TPSR with a physical education model and the TPSR with a traditional teaching model. The research findings are as follows: 1) The TPSR sports education model can improve students' learning outcomes, including sports self-efficacy, game performance, sports enthusiasm, team cohesion, group awareness and responsibility. 2) A traditional teaching model with TPSR could improve student learning outcomes, including sports self-efficacy, responsibility, and game performance. 3) The sports education model with TPSR could improve learning outcomes more than the traditional teaching model with TPSR, including sports self-efficacy, sports enthusiasm, responsibility and game performance. 4) Based on qualitative data on teachers' and students' learning experience, the physical education model with TPSR significantly improves learning motivation, group interaction and sense of play. The results suggest that physical education with TPSR could further improve learning outcomes in the physical education program. On the other hand, the hybrid model curriculum projects TPSR - Physical Education and TPSR - Traditional Education are good curriculum projects for moral character education that can be used in school physics.

Keywords: approach competencies, physical, education, teachers employment, graduate, physical education and sport sciences, SWOT analysis character education, sport season, game performance, sport competence

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Authors: Poonam Yadav, Dong Bok Lee

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Isothermal oxidation at 800°C for 50h and Cyclic oxidation at 600°C and 800°C for 40h of Pure Ti and Ti64 were performed in a muffle furnace. In Cyclic oxidation, massive scale spallation occurred, and the oxide scale cracks and peels off were observed at high temperature, it represents oxide scale that formed during cyclic oxidation was spalled out owing to stresses due to thermal shock generated during repetitive oxidation and subsequent cooling. The thickness of scale is larger in cyclic oxidation than the isothermal case. This is due to inward diffusion of oxygen through oxide scales and/or pores and cracks in cyclic oxidation.

Keywords: cyclic, diffusion, isothermal, cyclic

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Authors: Ophir Nave

Abstract:

In our research, we present the concept of singularly perturbed vector field (SPVF) method, and its application to thermal explosion of diesel spray combustion. Given a system of governing equations, which consist of hidden Multi-scale variables, the SPVF method transfer and decompose such system to fast and slow singularly perturbed subsystems (SPS). The SPVF method enables us to understand the complex system, and simplify the calculations. Later powerful analytical, numerical and asymptotic methods (e.g method of integral (invariant) manifold (MIM), the homotopy analysis method (HAM) etc.) can be applied to each subsystem. We compare the results obtained by the methods of integral invariant manifold and SPVF apply to spray droplets combustion model. The research deals with the development of an innovative method for extracting fast and slow variables in physical mathematical models. The method that we developed called singular perturbed vector field. This method based on a numerical algorithm applied to global quasi linearization applied to given physical model. The SPVF method applied successfully to combustion processes. Our results were compared to experimentally results. The SPVF is a general numerical and asymptotical method that reveals the hierarchy (multi-scale system) of a given system.

Keywords: polydisperse spray, model reduction, asymptotic analysis, multi-scale systems

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Authors: Zahra Bahadoran, Parvin Mirmiran, Hanieh-Sadat Ejtahed, Maryam Tohidi, Fereidoun Azizi

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Background and Aim: Broccoli sprouts, rich source of bioactive compounds specially sulforaphane (SFN), have unique functional properties. This study was conducted to investigate the possible treatment effects of high-SFN broccoli sprouts powder on metabolic and liver disorders in rats fed with high-fructose corn syrup. Methods: Thirty-two male wistar rats, pretreated with an eight-week high-fructose diet (water containing 30% fructose), were randomly allocated into three groups: Baseline control (BC), control (C) (normal diet), and BSP-diet (normal diet+5% BSP). The duration of the study was 6 weeks. Biochemical measurements, liver weight and triglyceride content were evaluated and histopathological examination of liver was performed. Results: After 6-weeks, the liver weight was significantly lower in BSP group compared to controls (13.4 g vs. 11.4 g, P<0.05). After 6 weeks, a significant decrease was observed in fasting serum glucose, total cholesterol and triglyceride levels in both experimental groups (P<0.05). Compared to controls, serum levels of HDL-C were significantly higher in BSP group. The liver TG content in BSP compared to control group was lower (14.6 vs. 16.4 mg/mg tissue). The hepatic levels of alanine aminotransferase, aspartate aminotransferase and γ-glutamyl transferase had not considerable changes in the groups after the intervention period but the level of alkaline phosphatase significantly decreased in BSP group (P<0.05). The histopathological examination of liver confirmed a decrease lobular and portal inflammation and ballooning in BSP group compared to control. Conclusion: High-SFN broccoli sprouts powder has beneficials effect on metabolic and liver changes-induced by high fructose corn syrup.

Keywords: broccoli sprouts, metabolic disorders, fatty liver, food science

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