Search results for: explanatory factor analysis

Authors: Peter J. Fusco, Dave M. Mathew, Chris Mathew, Kenneth H. Levy, Kathryn S. Varghese, Stephanie Salazar-Restrepo, Serena M. Mathew, Sofia Khaja, Eamon Vega, Mia Polizzi, Alyssa Mullane, Adham Ahmed

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Background: Laparoscopic (LS) removal of neuroblastomas in children has been reported to offer favorable outcomes compared to the conventional open thoracotomy (OT) procedure. Critical perioperative measures such as blood loss, operative time, length of stay, and time to postoperative chemotherapy have all supported laparoscopic use rather than its more invasive counterpart. Herein, a pairwise meta-analysis was performed comparing perioperative outcomes between LS and OT in thoracoabdominal neuroblastoma cases. Methods: A comprehensive literature search was performed on PubMed, Ovid EMBASE, and Scopus databases to identify studies comparing the outcomes of pediatric patients with thoracoabdominal neuroblastomas undergoing resection via OT or LS. After deduplication, 4,227 studies were identified and subjected to initial title screening with exclusion and inclusion criteria to ensure relevance. When studies contained overlapping cohorts, only the larger series were included. Primary outcomes include estimated blood loss (EBL), hospital length of stay (LOS), and mortality, while secondary outcomes were tumor recurrence, post-operative complications, and operation length. The “meta” and “metafor” packages were used in R, version 4.0.2, to pool risk ratios (RR) or standardized mean differences (SMD) in addition to their 95% confidence intervals in the random effects model via the Mantel-Haenszel method. Heterogeneity between studies was assessed using the I² test, while publication bias was assessed via funnel plot. Results: The pooled analysis included 209 patients from 5 studies (141 OT, 68 LS). Of the included studies, 2 originated from the United States, 1 from Toronto, 1 from China, and 1was from a Japanese center. Mean age between study cohorts ranged from 2.4 to 5.3 years old, with female patients occupying between 30.8% to 50% of the study populations. No statistically significant difference was found between the two groups for LOS (SMD -1.02; p=0.083), mortality (RR 0.30; p=0.251), recurrence(RR 0.31; p=0.162), post-operative complications (RR 0.73; p=0.732), or operation length (SMD -0.07; p=0.648). Of note, LS appeared to be protective in the analysis for EBL, although it did not reach statistical significance (SMD -0.4174; p= 0.051). Conclusion: Despite promising literature assessing LS removal of pediatric neuroblastomas, results showed it was non-superior to OT for any explored perioperative outcomes. Given the limited comparative data on the subject, it is evident that randomized trials are necessary to further the efficacy of the conclusions reached.

Keywords: laparoscopy, neuroblastoma, thoracoabdominal, thoracotomy

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Authors: Bitewulign Mekonnen

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Context: This scientific paper focuses on the use of near-infrared (NIR) spectroscopy to determine glucose concentration in aqueous solutions accurately and rapidly. The study compares six different machine learning methods for predicting glucose concentration and also explores the development of a deep learning model for classifying NIR spectra. The objective is to optimize the detection model and improve the accuracy of glucose prediction. This research is important because it provides a comprehensive analysis of various machine-learning techniques for estimating aqueous glucose concentrations. Research Aim: The aim of this study is to compare and evaluate different machine-learning methods for predicting glucose concentration from NIR spectra. Additionally, the study aims to develop and assess a deep-learning model for classifying NIR spectra. Methodology: The research methodology involves the use of machine learning and deep learning techniques. Six machine learning regression models, including support vector machine regression, partial least squares regression, extra tree regression, random forest regression, extreme gradient boosting, and principal component analysis-neural network, are employed to predict glucose concentration. The NIR spectra data is randomly divided into train and test sets, and the process is repeated ten times to increase generalization ability. In addition, a convolutional neural network is developed for classifying NIR spectra. Findings: The study reveals that the SVMR, ETR, and PCA-NN models exhibit excellent performance in predicting glucose concentration, with correlation coefficients (R) > 0.99 and determination coefficients (R²)> 0.985. The deep learning model achieves high macro-averaging scores for precision, recall, and F1-measure. These findings demonstrate the effectiveness of machine learning and deep learning methods in optimizing the detection model and improving glucose prediction accuracy. Theoretical Importance: This research contributes to the field by providing a comprehensive analysis of various machine-learning techniques for estimating glucose concentrations from NIR spectra. It also explores the use of deep learning for the classification of indistinguishable NIR spectra. The findings highlight the potential of machine learning and deep learning in enhancing the prediction accuracy of glucose-relevant features. Data Collection and Analysis Procedures: The NIR spectra and corresponding references for glucose concentration are measured in increments of 20 mg/dl. The data is randomly divided into train and test sets, and the models are evaluated using regression analysis and classification metrics. The performance of each model is assessed based on correlation coefficients, determination coefficients, precision, recall, and F1-measure. Question Addressed: The study addresses the question of whether machine learning and deep learning methods can optimize the detection model and improve the accuracy of glucose prediction from NIR spectra. Conclusion: The research demonstrates that machine learning and deep learning methods can effectively predict glucose concentration from NIR spectra. The SVMR, ETR, and PCA-NN models exhibit superior performance, while the deep learning model achieves high classification scores. These findings suggest that machine learning and deep learning techniques can be used to improve the prediction accuracy of glucose-relevant features. Further research is needed to explore their clinical utility in analyzing complex matrices, such as blood glucose levels.

Keywords: machine learning, signal processing, near-infrared spectroscopy, support vector machine, neural network

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Authors: Mia Françoise

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This report aims to develop a strategy for assisting short-term investors to benefit from the current economic climate in South Africa by utilizing technical analysis techniques and predictive analytics. As part of this research, value investing and technical analysis principles will be combined to maximize returns for South African investors while optimizing volatility. As an emerging market, South Africa offers many opportunities for high growth in sectors where other developed countries cannot grow at the same rate. Investing in South African companies with significant growth potential can be extremely rewarding. Although the risk involved is more significant in countries with less developed markets and infrastructure, there is more room for growth in these countries. According to recent research, the offshore market is expected to outperform the local market over the long term; however, short-term investments in the local market will likely be more profitable, as the Johannesburg Stock Exchange is predicted to outperform the S&P500 over the short term. The instabilities in the economy contribute to increased market volatility, which can benefit investors if appropriately utilized. Price prediction and portfolio optimization comprise the two primary components of this methodology. As part of this process, statistics and other predictive modeling techniques will be used to predict the future performance of stocks listed on the Johannesburg Stock Exchange. Following predictive data analysis, Modern Portfolio Theory, based on Markowitz's Mean-Variance Theorem, will be applied to optimize the allocation of assets within an investment portfolio. By combining different assets within an investment portfolio, this optimization method produces a portfolio with an optimal ratio of expected risk to expected return. This methodology aims to provide a short-term investment with a stock portfolio that offers the best risk-to-return profile for stocks listed on the JSE by combining price prediction and portfolio optimization.

Keywords: financial stocks, optimized asset allocation, prediction modelling, South Africa

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Authors: S. J. Yune, S. Y. Lee, S. J. Im, B. S. Kam, S. Y. Baek

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This study aimed to determine the reliability of clinical performance assessments, having been emphasized by ability-based education, and professors overall assessment methods. We addressed the following problems: First, we try to find out whether there is a difference in what we consider to be the main variables affecting the clinical performance test according to the evaluator’s working period and the number of evaluation experience. Second, we examined the relationship among the global rating score (G), analytic global rating score (Gc), and the sum of the analytical checklists (C). What are the main factors affecting clinical performance assessments in relation to the numbers of times the evaluator had administered evaluations and the length of their working period service? What is the relationship between overall assessment score and analytic checklist score? How does analytic global rating with 6 components in OSCE and 4 components in sub-domains (Gc) CPX: aseptic practice, precision, systemic approach, proficiency, successfulness, and attitude overall assessment score and task-specific analytic checklist score sum (C) affect the professor’s overall global rating assessment score (G)? We studied 75 professors who attended a 2016 Bugyeoung Consortium clinical skills performances test evaluating third and fourth year medical students at the Pusan National University Medical school in South Korea (39 prof. in OSCE, 36 prof. in CPX; all consented to participate in our study). Each evaluator used 3 forms; a task-specific analytic checklist, subsequent analytic global rating scale with sub-6 domains, and overall global scale. After the evaluation, the professors responded to the questionnaire on the important factors of clinical performance assessment. The data were analyzed by frequency analysis, correlation analysis, and hierarchical regression analysis using SPSS 21.0. Their understanding of overall assessment was analyzed by dividing the subjects into groups based on experiences. As a result, they considered ‘precision’ most important in overall OSCE assessment, and ‘precise accuracy physical examination’, ‘systemic approaches to taking patient history’, and ‘diagnostic skill capability’ in overall CPX assessment. For OSCE, there was no clear difference of opinion about the main factors, but there was for CPX. Analytic global rating scale score, overall rating scale score, and analytic checklist score had meaningful mutual correlations. According to the regression analysis results, task-specific checklist score sum had the greatest effect on overall global rating. professors regarded task-specific analytic checklist total score sum as best reflecting overall OSCE test score, followed by aseptic practice, precision, systemic approach, proficiency, successfulness, and attitude on a subsequent analytic global rating scale. For CPX, subsequent analytic global rating scale score, overall global rating scale score, and task-specific checklist score had meaningful mutual correlations. These findings support explanations for validity of professors’ global rating in clinical performance assessment.

Keywords: global rating, clinical performance assessment, medical education, analytic checklist

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Authors: Iman Janghorban Esfahani

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Due to the increased use of irrigation in agriculture, the importance and need for highly reliable water pumping systems have significantly increased. The pumping of the groundwater is essential to provide water for both drip and furrow irrigation to increase the agricultural yield, especially in arid regions that suffer from scarcities of surface water. The most common irrigation pumping systems (IPS) consume conventional energies through the use of electric motors and generators or connecting to the electricity grid. Due to the shortage and transportation difficulties of fossil fuels, and unreliable access to the electricity grid, especially in the rural areas, and the adverse environmental impacts of fossil fuel usage, such as greenhouse gas (GHG) emissions, the need for renewable energy sources such as photovoltaic systems (PVS) as an alternative way of powering irrigation pumping systems is urgent. Integration of the photovoltaic systems with irrigation pumping systems as the Photovoltaic Powered-Irrigation Pumping System (PVP-IPS) can avoid fossil fuel dependency and the subsequent greenhouse gas emissions, as well as ultimately lower energy costs and improve efficiency, which made PVP-IPS systems as an environmentally and economically efficient solution for agriculture irrigation in every region. The greatest problem faced by integration of PVP with IPS systems is matching the intermittence of the energy supply with the dynamic water demand. The best solution to overcome the intermittence is to incorporate a storage system into the PVP-IPS to provide water-on-demand as a highly reliable stand-alone irrigation pumping system. The water storage tank (WST) is the most common storage device for PVP-IPS systems. In the integrated PVP-IPS with a water storage tank (PVP-IPS-WST), a water storage tank stores the water pumped by the IPS in excess of the water demand and then delivers it when demands are high. The Freshwater pinch analysis (FWaPA) as an alternative to mathematical modeling was used by other researchers for retrofitting the off-grid battery less photovoltaic-powered reverse osmosis system. However, the Freshwater pinch analysis has not been used to integrate the photovoltaic systems with irrigation pumping system with water storage tanks. In this study, FWaPA graphical and numerical tools were used for retrofitting an existing PVP-IPS system located in Salahadin, Republic of Iraq. The plant includes a 5 kW submersible water pump and 7.5 kW solar PV system. The Freshwater Composite Curve as the graphical tool and Freashwater Storage Cascade Table as the numerical tool were constructed to determine the minimum required outsourced water during operation, optimal amount of delivered electricity to the water pump, and optimal size of the water storage tank for one-year operation data. The results of implementing the FWaPA on the case study show that the PVP-IPS system with a WST as the reliable system can reduce outsourced water by 95.41% compare to the PVP-IPS system without storage tank.

Keywords: irrigation, photovoltaic, pinch analysis, pumping, solar energy

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Authors: H. Nikzad, S. Yoshitomi

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This study investigates and develops the structural optimization method. The effect of size constraints on practical solution of reinforced concrete (RC) building structure with shear wall is proposed. Cross-sections of beam and column, and thickness of shear wall are considered as design variables. The objective function to be minimized is total cost of the structure by using a simple and efficient automated MATLAB platform structural optimization methodology. With modification of mathematical formulations, the result is compared with optimal solution without size constraints. The most suitable combination of section sizes is selected as for the final design application based on linear static analysis. The findings of this study show that defining higher value of upper bound of sectional sizes significantly affects optimal solution, and defining of size constraints play a vital role in finding of global and practical solution during optimization procedures. The result and effectiveness of proposed method confirm the ability and efficiency of optimal solutions for 3D RC shear wall-frame structure.

Keywords: structural optimization, linear static analysis, ETABS, MATLAB, RC shear wall-frame structures

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Authors: Abhay Asthana, Gyati Shilakari Asthana

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It’s the patient compliance and stability in combination with controlled drug delivery and biocompatibility that forms the core feature in present research and development of sustained biodegradable patch formulation intended for wound healing. The aim was to impart sustained degradation, sterile formulation, significant folding endurance, elasticity, biodegradability, bio-acceptability and strength. The optimized formulation was developed using component including polymers including Hydroxypropyl methyl cellulose, Ethylcellulose, and Gelatin, and Citric Acid PEG Citric acid (CPEGC) triblock dendrimers and active Curcumin. Polymeric mixture dissolved in geometric order in suitable medium through continuous stirring under ambient conditions. With continued stirring Curcumin was added with aid of DCM and Methanol in optimized ratio to get homogenous dispersion. The dispersion was sonicated with optimum frequency and for given time and later casted to form a patch form. All steps were carried out under under strict aseptic conditions. The formulations obtained in the acceptable working range were decided based on thickness, uniformity of drug content, smooth texture and flexibility and brittleness. The patch kept on stability using butter paper in sterile pack displayed folding endurance in range of 20 to 23 times without any evidence of crack in an optimized formulation at room temperature (RT) (24 ± 2°C). The patch displayed acceptable parameters after stability study conducted in refrigerated conditions (8±0.2°C) and at RT (24 ± 2°C) upto 90 days. Further, no significant changes were observed in critical parameters such as elasticity, biodegradability, drug release and drug content during stability study conducted at RT 24±2°C for 45 and 90 days. The drug content was in range 95 to 102%, moisture content didn’t exceeded 19.2% and patch passed the content uniformity test. Percentage cumulative drug release was found to be 80% in 12h and matched the biodegradation rate as drug release with correlation factor R2>0.9. The biodegradable patch based formulation developed shows promising results in terms of stability and release profiles.

Keywords: sustained biodegradation, wound healing, polymers, stability

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Authors: Evans Iyamu

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Genes encoding hydrophobins play distinct roles at different stages of the life cycle of fungi, and they foster hyphal attachment to surfaces. The hydrophobin Sc4 is known to provide a hydrophobic membrane lining of the gas channels within Schizophyllum commune fruiting bodies. Here, we cultivated non-fruiting, monokaryotic S. commune 12-43 on glass surfaces that could be verified by micrography. Differential gene expression profiling of nine hydrophobin genes and the hydrophobin-like sc15 gene by quantitative PCR showed significant up-regulation of sc4 when S. commune was attached to glass surfaces, also confirmed with RNA-Seq data analysis. Another silicate, namely quartz sand, was investigated, and induction of sc4 was seen as well. The up-regulation of the hydrophobin gene sc4 may indicate involvement in S. commune hyphal attachment to glass as well as quartz surfaces. We propose that the covering of hyphae by Sc4 allows for direct interaction with the hydrophobic surfaces of silicates and that differential functions of specific hydrophobin genes depend on the surface interface involved. This study could help with the clarification of the biological functions of hydrophobins in natural surroundings, including hydrophobic surface attachment. Therefore, the analysis of growth on glass serves as a basis for understanding S. commune interaction with glass surfaces while providing the possibility to visualize the interaction microscopically.

Keywords: hydrophobin, structured glass surfaces, differential gene expression, quartz sand

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Authors: Vita Strazdina, Aleksandrs Jemeljanovs, Vita Sterna

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Not all proteins have the same nutritional value, since protein quality strongly depends on its amino acid composition and digestibility. The meat of game animals could be a high protein source because of its well-balanced essential amino acids composition. Investigations about biochemical composition of game meat such as wild boar (Sus scrofa scrofa), roe deer (Capreolus capreolus) and beaver (Castor fiber) are not very much. Therefore, the aim of the investigation was evaluate protein composition of game meat hunted in Latvia. The biochemical analysis, evaluation of connective tissue and essential amino acids in meat samples were done, the amino acids score were calculate. Results of analysis showed that protein content 20.88-22.05% of all types of meat samples is not different statistically. The content of connective tissue from 1.3% in roe deer till 1.5% in beaver meat allowed classified game animal as high quality meat. The sum of essential amino acids in game meat samples were determined 7.05–8.26g100g-1. Roe deer meat has highest protein content and lowest content of connective tissues among game meat hunted in Latvia. Concluded that amino acid score for limiting amino acids phenylalanine and tyrosine is high and shows high biological value of game meat.

Keywords: dietic product, game meat, amino acids, scores

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Authors: Kimberly Samaha

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In order to attract new types of investors into the emerging Bio-Economy, new methodologies to analyze investment risk are needed. The Bio-Hub Ecosystem model was developed to address a critical area of concern within the global energy market regarding the use of biomass as a feedstock for power plants. This study looked at repurposing existing biomass-energy plants into Circular Zero-Waste Bio-Hub Ecosystems. A Bio-Hub model that first targets a ‘whole-tree’ approach and then looks at the circular economics of co-hosting diverse industries (wood processing, aquaculture, agriculture) in the vicinity of the Biomass Power Plants facilities. This study modeled the economics and risk strategies of cradle-to-cradle linkages to incorporate the value-chain effects on capital/operational expenditures and investment risk reductions using a proprietary techno-economic model that incorporates investment risk scenarios utilizing the Monte Carlo methodology. The study calculated the sequential increases in profitability for each additional co-host on an operating forestry-based biomass energy plant in West Enfield, Maine. Phase I starts with the base-line of forestry biomass to electricity only and was built up in stages to include co-hosts of a greenhouse and a land-based shrimp farm. Phase I incorporates CO2 and heat waste streams from the operating power plant in an analysis of lowering and stabilizing the operating costs of the agriculture and aquaculture co-hosts. Phase II analysis incorporated a jet-fuel biorefinery and its secondary slip-stream of biochar which would be developed into two additional bio-products: 1) A soil amendment compost for agriculture and 2) A biochar effluent filter for the aquaculture. The second part of the study applied the Monte Carlo risk methodology to illustrate how co-location derisks investment in an integrated Bio-Hub versus individual investments in stand-alone projects of energy, agriculture or aquaculture. The analyzed scenarios compared reductions in both Capital and Operating Expenditures, which stabilizes profits and reduces the investment risk associated with projects in energy, agriculture, and aquaculture. The major findings of this techno-economic modeling using the Monte Carlo technique resulted in the masterplan for the first Bio-Hub to be built in West Enfield, Maine. In 2018, the site was designated as an economic opportunity zone as part of a Federal Program, which allows for Capital Gains tax benefits for investments on the site. Bioenergy facilities are currently at a critical juncture where they have an opportunity to be repurposed into efficient, profitable and socially responsible investments, or be idled and scrapped. The Bio-hub Ecosystems techno-economic analysis model is a critical model to expedite new standards for investments in circular zero-waste projects. Profitable projects will expedite adoption and advance the critical transition from the current ‘take-make-dispose’ paradigm inherent in the energy, forestry and food industries to a more sustainable Bio-Economy paradigm that supports local and rural communities.

Keywords: bio-economy, investment risk, circular design, economic modelling

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Authors: Youn Young Shim, Ji Hye Kim, Jae Youl Cho, Martin J. T. Reaney

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Flaxseed (Linum usitatissimum L.) is gaining popularity in the food industry as a superfood due to its health-promoting properties. The flax plant synthesizes an array of biologically active cyclic peptides or linusorbs (LOs, a.k.a. cyclolinopeptides) from three or more ribosome-derived precursors. [1–9-NαC]-linusorb B3 and [1–9-NαC]-linusorb B2, suppress immunity, induce apoptosis in human epithelial cancer cell line (Calu-3) cells, and inhibit T-cell proliferation, but the mechanism of LOs action is unknown. Using gene expression analysis in nematode cultures and human cancer cell lines, we have observed that LOs exert their activity, in part, through induction of apoptosis. Specific LOs’ properties include: 1) distribution throughout the body after flaxseed consumption; 2) induce heat shock protein (HSP) 70A production as an indicator of stress and address the issue in Caenorhabditis elegans (exposure of nematode cultures to [1–9-NαC]-linusorb B3 induced a 30% increase in production of the HSP 70A protein); 3) induce apoptosis in Calu-3 cells; and 4) modulate regulatory genes in microarray analysis. These diverse activities indicate that LOs might induce apoptosis in cancer cells or act as versatile platforms to deliver a variety of biologically active molecules for cancer therapy.

Keywords: flaxseed, linusorb, cyclic peptide, orbitides, heat shock protein, apoptosis, anti-cancer

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Authors: Syed Masood Hussain

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An effective control method, including system-level control and pulse width modulation for quasi-Z-source cascade multilevel inverter (qZS-CMI) based grid-tie photovoltaic (PV) power system is proposed. The system-level control achieves the grid-tie current injection, independent maximum power point tracking (MPPT) for separate PV panels, and dc-link voltage balance for all quasi-Z-source H-bridge inverter (qZS-HBI) modules. A recent upsurge in the study of photovoltaic (PV) power generation emerges, since they directly convert the solar radiation into electric power without hampering the environment. However, the stochastic fluctuation of solar power is inconsistent with the desired stable power injected to the grid, owing to variations of solar irradiation and temperature. To fully exploit the solar energy, extracting the PV panels’ maximum power and feeding them into grids at unity power factor become the most important. The contributions have been made by the cascade multilevel inverter (CMI). Nevertheless, the H-bridge inverter (HBI) module lacks boost function so that the inverter KVA rating requirement has to be increased twice with a PV voltage range of 1:2; and the different PV panel output voltages result in imbalanced dc-link voltages. However, each HBI module is a two-stage inverter, and many extra dc–dc converters not only increase the complexity of the power circuit and control and the system cost, but also decrease the efficiency. Recently, the Z-source/quasi-Z-source cascade multilevel inverter (ZS/qZS-CMI)-based PV systems were proposed. They possess the advantages of both traditional CMI and Z-source topologies. In order to properly operate the ZS/qZS-CMI, the power injection, independent control of dc-link voltages, and the pulse width modulation (PWM) are necessary. The main contributions of this paper include: 1) a novel multilevel space vector modulation (SVM) technique for the single phase qZS-CMI is proposed, which is implemented without additional resources; 2) a grid-connected control for the qZS-CMI based PV system is proposed, where the all PV panel voltage references from their independent MPPTs are used to control the grid-tie current; the dual-loop dc-link peak voltage control.

Keywords: Quzi-Z source inverter, Photo voltaic power system, space vector modulation, cascade multilevel inverter

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Authors: Nazia Shehzad

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An icebreaker is a facilitation exercise intended to help a group to begin the process of forming themselves into a team. Icebreakers are commonly presented as a game to ‘warm up’ the group by helping the members to get to know each other. They often focus on sharing personal information such as names, hobbies, etc. Challenging icebreakers also have the ability to allow a group to be better prepared to complete its assigned tasks. For example, if the team's objective is to redesign a business process such as Accounts Payable, the icebreaker activity might take the team through a process analysis. The analysis could include the identification of failure points, challenging assumptions, and development of new solutions — all in a simpler and ‘safer’ setting where the team can practice the group dynamics which they will use to solve the assigned problem. Icebreakers help establish a positive environment and provide an opportunity for students to get to know one another and the instructor. Both are critical to the retention and success of students. There are a number of benefits of using ice-breakers activities in the classroom. It reduces both student and instructor anxiety prior to introducing the course, fosters in a powerful way both student-student and faculty-student interactions. It creates an environment where the learner is expected to participate and the instructor is willing to listen, actively engage students from the onset. It conveys the message that the instructor cares about getting to know the students and makes it easier for students to form relationships early in the semester so they can work together both in and out of class.

Keywords: actively engages students, facilitation exercise, faculty- student interactions, group dynamics, warm up

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Authors: Misbah Khan, Jian Wen, Muhammad Asif Shakoori

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The Organic Rankine Cycle (ORC) plays an important role in converting low-temperature heat sources into electrical power by using refrigerants as working fluids. The thermophysical properties of working fluids are essential for designing ORC. HFO-1336mzz(Z) (cis-1,1,1,4,4,4-hexafluoro-2-butene) considered as working fluid and have almost 99% low GWP and relatively same thermophysical properties used as a replacement of HFC-245fa (1,1,1,3,3-pentafluoro-propane). The environmental, safety, healthy and thermophysical properties of HFO-1336mzz(Z) are needed to use it in a practical system. In this paper, Molecular dynamics simulations were used to investigate the Homogeneous condensation, thermophysical and structural properties of HFO-1336mzz(Z) and HFC-245fa. The effect of various temperatures and pressures on thermophysical properties and condensation was extensively investigated. The liquid densities and isobaric heat capacities of this refrigerant was simulated at 273.15K to 353.15K temperatures and pressure0.5-4.0MPa. The simulation outcomes were compared with experimental data to validate our simulation method. The mean square displacement for different temperatures was investigated for dynamical analysis. The variations in potential energies and condensation rate were simulated to get insight into the condensation process. The radial distribution function was simulated at the micro level for structural analysis and revealed that the phase transition of HFO-1336mzz(Z) did not affect the intramolecular structure.

Keywords: homogenous condensation, refrigerants, molecular dynamics simulations, organic rankine cycle

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Authors: Sadia Rafiq, Md. Ashab Siddique Zaki, Ananya Roy

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Mountain cycling is a type of off-road bicycle racing that typically takes place on rocky, arid, or other challenging terrains on specially-made mountain cycles. Professional cyclists race while attempting to stay on their bikes in a variety of locales across the world. For safety measures in mountain cycling, as there we have a high chance of injury in case of tire puncture, it’s a preferable way to use an airless tire instead of a pneumatic tire. As airless tire does not tend to go flat, it needs to be replaced less frequently. The airless tire replaces the pneumatic tire, wheel, and tire system with a single unit. It consists of a stiff hub connected to a shear band by flexible, pliable spokes, which is made of poly-composite and a tread band, all of which work together as a single unit to replace all of the components of a normal radial tire. In this paper, an analysis of airless tires in the mountain cycle is shown along with structure and material study. We will be taking the Honeycomb and Diamond Structure of spokes to compare the deformation in both cases and choose our preferable structure. As we know, the tread and spokes deform with the surface roughness and impact. So, the tire tread thickness and the design of spokes can control how much the tire can distort. Through the simulation, we can come to the conclusion that the diamond structure deforms less than the honeycomb structure. So, the diamond structure is more preferable.

Keywords: airless tire, diamond structure, honeycomb structure, deformation

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Authors: Anita Khadka, Gregory Epiphaniou, Carsten Maple

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There is a dramatic surge in the adoption of machine learning (ML) techniques in many areas, including the nuclear industry (such as fault diagnosis and fuel management in nuclear power plants), autonomous systems (including self-driving vehicles), space systems (space debris recovery, for example), medical surgery, network intrusion detection, malware detection, to name a few. With the application of learning methods in such diverse domains, artificial intelligence (AI) has become a part of everyday modern human life. To date, the predominant focus has been on developing underpinning ML algorithms that can improve accuracy, while factors such as resiliency and robustness of algorithms have been largely overlooked. If an adversarial attack is able to compromise the learning method or data, the consequences can be fatal, especially but not exclusively in safety-critical applications. In this paper, we present an in-depth analysis of five adversarial attacks and three defence methods on a crack detection ML model. Our analysis shows that it can be dangerous to adopt machine learning techniques in security-critical areas such as the nuclear industry without rigorous testing since they may be vulnerable to adversarial attacks. While common defence methods can effectively defend against different attacks, none of the three considered can provide protection against all five adversarial attacks analysed.

Keywords: adversarial machine learning, attacks, defences, nuclear industry, crack detection

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Authors: Hatice Karakoyun, Mustafa Akdag

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This study has been made to examine the attitudes of pre-school teachers towards values education. The study has been made as a general scanning model. The study’s working group contains 108 pre-school teachers who worked in Diyarbakır, Turkey. In this study Values Education Attitude Scale (VEAS), which developed by Yaşaroğlu (2014), was used. In order to analyze the data for sociodemographic structure, percentage and frequency values were examined. The Kolmogorov-Smirnov method was used in determination of the normal distribution of data. During analyzing the data, KolmogorovSimirnov test and the normal curved histograms were examined to determine which statistical analyzes would be applied on the scale and it was found that the distribution was not normal. Thus, the Mann Whitney U analysis technique which is one of the nonparametric statistical analysis techniques were used to test the difference of the scores obtained from the scale in terms of independent variables. According to the analyses, it seems that pre-school teachers’ attitudes toward values education are positive. According to the scale with the highest average, it points out that pre-school teachers think that values education is very important for students’ and children’s future. The variables included in the scale (gender, seniority, age group, education, school type, school place) seem to have no effect on the pre-school teachers’ attitude grades which joined to the study.

Keywords: attitude scale, pedagogy, pre-school teacher, values education

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Authors: Elham Shahrjooi Haghighi

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This research explores how lexical bundles are utilized in writing in the field of linguistics by comparing professional Persian writers with native English writers using corpus-based studies and advanced computational techniques to examine the occurrence and characteristics of lexical bundles in academic writings. The review of literature emphasizes how important lexical bundles are, in organizing discussions and conveying opinions in both spoken and written language contexts across genres and proficiency levels in fields of study. Previous research has indicated that native English writers tend to employ an array and diversity of bundles than non-native writers do; these bundles are essential elements in academic writing. In this study’s methodology section, the research utilizes a corpus-based method to analyze a collection of writings such as research papers and advanced theses at the doctoral and masters’ levels. The examination uncovers variances in the utilization of groupings between writers who are native speakers of Persian and those who are native English speakers with the latter group displaying a greater occurrence and variety, in types of groupings. Furthermore, the research delves into how these groupings contribute to aspects classifying them into categories based on their relevance to research text structure and individuals as outlined in Hyland’s framework. The results show that Persian authors employ phrases and demonstrate distinct structural and functional tendencies in comparison to native English writers. This variation is linked to differing language skills, levels, disciplinary norms and cultural factors. The study also highlights the pedagogical implications of these findings, suggesting that targeted instruction on the use of lexical bundles could enhance the academic writing skills of non-native speakers. In conclusion, this research contributes to the understanding of lexical bundles in academic writing by providing a detailed comparative analysis of their use by Persian and native English writers. The insights from this study have important implications for language education and the development of effective writing strategies for non-native English speakers in academic contexts.

Keywords: lexical bundles, academic writing, comparative analysis, computational techniques

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Authors: Amrin Moger, Martin Mathew, Sagar Bhalerao

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Mass media may be categorized into print and digital, former being the traditional form of reaching the masses to inform and educate on various issues. The Indian print media is more than two centuries old. Its strengths have largely been shaped by its historical experience and, in particular, by its association with the freedom struggle as well as movements for social emancipation, reform, and amelioration. Therefore, it is highly regarded in the Indian society. Persons with disability are part of Indian Society. Persons with Disability have always been looked down upon and not considered as part of the society. People with disabilities were commonly feared, pitied, and neglected. Much of the literature on disability in India has pointed to the importance of the concept of karma in attitudes to disability, with disability perceived either as punishment for misdeeds in the past lives of the PWD, or the wrongdoings of their parents. Some Indian authors consider the passage of the PWD Act as a landmark step in the history of rehabilitation services in India have put it, ‘At a profoundly serious and spiritual level, disability represents divine justice’. The newspaper has to play a role where it changes this attitude of the people. A short comparative content analysis of two English newspapers of Mumbai edition was selected, to analyze the language that is used for reporting disability issues. Software Package for Social Science (SPSS) was used to gather and analyze data.

Keywords: content analysis, disability, newspaper dailies, language

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Authors: Eser Bingül

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The leadership and leaders, also having been a privileged subject of scientific researches in the last century, have become influential in shaping the destiny of the states since the first examples of the warfare history. The issue of leadership, finding a place in the management science, can also be defined as an integration of function within the aspect of leader. In this description, the relationship has come to the foreground which is established between the development of leadership theories and the elements of function which are leader, followers, and condition. While one reason of this analysis in leadership is to keep a lens to the historical background, the main reason has been a questioning the traits and education of leaders who have still affected the nation’s and organization’s fate. The links and analysis established in the definition of leadership have put forward the necessity of solving the unpredictable structure of human nature and behaviors in the focus of leadership approach. On the other hand becoming a model that meets the today’s needs of any system has given a clue that the leaders should turn towards the people. Being aware of this necessity, human-oriented leadership approach aims to gain both followers and their abilities to the system with giving them a deserved esteem and create the team spirit based on mutual trust. Ultimately this approach, with the determined leadership qualities consisting of charisma, ability of communication and trust, will be able to produce the solutions to the instant and long-term problems and uncertainties, derived from the variables of function, for the sake of systems.

Keywords: human nature, leadership, human-oriented approach, social sciences and humanities

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Authors: Arpit Kumar Shrivastava, Subrat Kumar, Rajani Kanta Mohapatra, Priyadarshi Soumyaranjan Sahu

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Computational approaches to predict structure, function and other biological characteristics of proteins are becoming more common in comparison to the traditional methods in drug discovery. Cryptosporidiosis is a major zoonotic diarrheal disease particularly in children, which is caused primarily by Cryptosporidium hominis and Cryptosporidium parvum. Currently, there are no vaccines for cryptosporidiosis and recommended drugs are not effective. With the availability of complete genome sequence of C. hominis, new targets have been recognized for the development of effective and better drugs and/or vaccines. We identified a unique hypothetical epitopic protein in C. hominis genome through BLASTP analysis. A 3D model of the hypothetical protein was generated using I-Tasser server through threading methodology. The quality of the model was validated through Ramachandran plot by PROCHECK server. The functional annotation of the hypothetical protein through DALI server revealed structural similarity with human Transportin 3. Phylogenetic analysis for this hypothetical protein also showed C. hominis hypothetical protein (CUV04613) was the closely related to human transportin 3 protein. The 3D protein model is further subjected to virtual screening study with inhibitors from the Zinc Database by using Dock Blaster software. Docking study reported N-(3-chlorobenzyl) ethane-1,2-diamine as the best inhibitor in terms of docking score. Docking analysis elucidated that Leu 525, Ile 526, Glu 528, Glu 529 are critical residues for ligand–receptor interactions. The molecular dynamic simulation was done to access the reliability of the binding pose of inhibitor and protein complex using GROMACS software at 10ns time point. Trajectories were analyzed at each 2.5 ns time interval, among which, H-bond with LEU-525 and GLY- 530 are significantly present in MD trajectories. Furthermore, antigenic determinants of the protein were determined with the help of DNA Star software. Our study findings showed a great potential in order to provide insights in the development of new drug(s) or vaccine(s) for control as well as prevention of cryptosporidiosis among humans and animals.

Keywords: cryptosporidium hominis, hypothetical protein, molecular docking, molecular dynamics simulation

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Authors: Dalia Perkumiene

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The process of globalization has several unforeseen negative effects on the quality of the environment, including increased pollution, climate change, and the depletion and destruction of natural resources. The impact of these processes makes it difficult to guarantee citizens' rights to a clean environment, and complex legal solutions are needed to implement this right. In order to implement human rights in a clean and safe environment, international legal documents and court rulings are analyzed. It is important to find a balance between the legal context: the right to a clean environment and environmental challenges such as climate change and global warming. Research Methods: The following methods were used in this study: analytical, analysis, and synthesis of scientific literature and legal documents, comparative analysis of legal acts, and generalization. Major Findings: It is difficult to implement the right to a clean, safe and sustainable environment. The successful implementation of this right depends on the application of various complex ideas and rational, not only legal solutions. Legislative measures aim to maximize the implementation of citizens' rights in the face of climate change and other environmental challenges. This area remains problematic, especially in international law. Concluding Statement: The right to a clean environment should allow a person to live in a harmonious system, where environmental factors do not pose a risk to human health and well-being.

Keywords: clean and safe and clean environmen, environmen, persons’ rights, right to a clean and safe and clean environment

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Authors: Sérgio J. Teixeira, João J. Ferreira

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Tourism frequently gets identified as one of the sectors with the greatest potential for expansion on a global scale and hence conveying the importance of attempting to better understand the regional factors of competitiveness prevailing in this sector. This study’s objective essentially strives to provide a mapping of the scientific publications and the intellectual knowledge therein contained while conveying past research trends and identifying potential future lines of research in the fields of regional competitiveness and tourism innovation. This correspondingly deploys a systematic review of the literature in keeping with the bibliometric approach based upon VOSviewer software, with a particular focus on drafting maps for visualising the underlying intellectual structure. This type of analysis encapsulates the number of articles published and their annual number of citations for the period between 1900 and 2016 as registered by the Web of Science database. The results demonstrate how the intellectual structure on regional competitiveness divides essentially into three major categories: regional competitiveness, tourism innovation, and tourism clusters. Thus, the main contribution of this study arises out of identifying the main research trends in this field and the respective shortcomings and specific needs for future scientific research in the field of regional competitiveness and innovation in tourism.

Keywords: regional competitiveness, tourism cluster, bibliometric studies, tourism innovation, systematic review

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Authors: Natia Gavardashvili

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On June 13-14 of 2015, a landslide in village Akhaldaba was formed as a result of the intense rains in the water catch basin of the river Vere. As a result of the landslide movement, freshets and mudflows originated, and unfortunately, there were victims: zoo animals and birds were drawn in the flood and 12 people died due to the flooded motor road. The goal of the study is to give the analysis of the results of the field and scientific research held in 2015-2017 and to generalize them to the water catch basins of the erosive-mudflow rivers of other mountain landscapes of Georgia. By considering the field and scientific works, the main geographic, geological, climatic, hydrological and hydraulic properties of the erosive-mudflow tributaries of the water catch basin of the river Vere were evaluated and the probabilities of mudflow formation by considering relevant risk-factors were identified. The typology of the water catch basins of erosive-mudflow rivers of Georgia was identified on the example of the river Vere based on the field and scientific study, and their genesis, frequency of mudflow formation and volume of the drift material was identified. By using the empirical and theoretical dependencies, the amount of solid admixtures in the mudflow formed in the gorge of the river Jokhona, the right tributary of the river Vere was identified by considering the shape of the stones.

Keywords: water catchment basin, erosion, mudflow, typology

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Authors: Rady A., Elsheshai A., Elsawy M., Nagui R.

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Background and Aim: Metabolic syndrome affect around 20% of general population , authors have incriminated antipsychotics as serious risk factor that may provoke such derangement. The aim of our study is to assess metabolic syndrome in patients presenting psychotic features (delusions and hallucinations) whether schizophrenia or mood disorder and compare results in terms of drug naïf, on medication and healthy control. Subjects and Methods: The study recruited 40 schizophrenic patients, half of them drug naïf and the other half on antipsychotics, 40 patients with mood disorder with psychotic features, half of them drug naïf and the other half on medication, 20 healthy control. Exclusion criteria were put in order to exclude patients having already endocrine or metabolic disorders that my interfere with results obtain to minimize confusion bias. Metabolic syndrome assessed by measuring parameters including weight, body mass index, waist circumference, triglyceride level, HDL, fasting glucose, fasting insulin and insulin resistance Results: No difference was found when comparing drug naïf to those on medication in both schizophrenic and psychotic mood disorder arms, schizophrenic patients whether on medication or drug naïf should difference with control group for fasting glucose, schizophrenic patients on medication also showed difference in insulin resistance compared to control group. On the other hand, patients with psychotic mood disorder whether drug naïf or on medication showed difference from control group for fasting insulin level. Those on medication also differed from control for insulin resistance Conclusion: Our study didn’t reveal difference in metabolic syndrome among patients with psychotic features whether on medication or drug naïf. Only patients with Psychotic features on medication showed insulin resistance. Schizophrenic patients drug naïf or on medication tend to show higher fasting glucose while psychotic mood disorder whether drug naïf or on medication tend to show higher fasting insulin. This study suggest that presence of psychotic features themselves regardless being on medication or not carries a risk for insulin resistance and metabolic syndrome. Limitation: This study is limited by number of participants and larger numbers in future studies should be included in order to extrapolate results. Cohort longitudinal studies are needed in order to evaluate such hypothesis.

Keywords: schizophrenia, metabolic syndrome, psychosis, insulin, resistance

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Authors: Chakkrit Poonpakdee, Jing-Hua Tzen, Ya-Zhen Huang, Yao-Tung Lin

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Potassium (K) is a known macro nutrient and essential element for plant growth. Single leaching and modified sequential extraction schemes have been developed to estimate the relative phase associations of soil samples. The sequential extraction process is a step in analyzing the partitioning of metals affected by environmental conditions, but it is not a tool for estimation of K bioavailability. While, traditional single leaching method has been used to classify K speciation for a long time, it depend on its availability to the plants and use for potash fertilizer recommendation rate. Clay mineral in soil is a factor for controlling soil fertility. The change of the micro-structure of clay minerals during various environment (i.e. swelling or shrinking) is characterized using Transmission X-Ray Microscopy (TXM). The objective of this study are to 1) compare the distribution of K speciation between single leaching and sequential extraction process 2) determined clay particle flocculation structure before/after suspension with K+ using TXM. Four tropical soil samples: farming without K fertilizer (10 years), long term applied K fertilizer (10 years; 168-240 kg K2O ha-1 year-1), red soil (450-500 kg K2O ha-1 year-1) and forest soil were selected. The results showed that the amount of K speciation by single leaching method were high in mineral K, HNO3 K, Non-exchangeable K, NH4OAc K, exchangeable K and water soluble K respectively. Sequential extraction process indicated that most K speciations in soil were associated with residual, organic matter, Fe or Mn oxide and exchangeable fractions and K associate fraction with carbonate was not detected in tropical soil samples. In farming long term applied K fertilizer and red soil were higher exchangeable K than farming long term without K fertilizer and forest soil. The results indicated that one way to increase the available K (water soluble K and exchangeable K) should apply K fertilizer and organic fertilizer for providing available K. The two-dimension of TXM image of clay particles suspension with K+ shows that the aggregation structure of clay mineral closed-void cellular networks. The porous cellular structure of soil aggregates in 1 M KCl solution had large and very larger empty voids than in 0.025 M KCl and deionized water respectively. TXM nanotomography is a new technique can be useful in the field as a tool for better understanding of clay mineral micro-structure.

Keywords: potassium, sequential extraction process, clay mineral, TXM

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Authors: Lebeza Alemu Tenaw, Fei Wan Ngai

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Background: Postpartum depression is the most common mental health disorder that occurs after childbirth, and it is more prevalent among teenage mothers compared to adults. Although there is emerging evidence suggesting psychosocial interventions can decrease postpartum depression, there are no consistent findings regarding the effectiveness of these interventions, especially for teenage mothers. The current review aimed to investigate the effectiveness of psychosocial interventions in preventing postpartum depression among teenage mothers. Methods: The Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) manual was implemented to select articles from online databases. The articles were searched using the Population, Intervention, Control, and Outcome (PICO) model. The quality of the articles was assessed using the Cochrane Collaboration Risk of Bias assessment tool. The statistical analyses were performed using Stata 17, and the effect size was estimated using the standard mean difference score of depression between the intervention and control groups. Heterogeneity between the studies was assessed through the I2 statistic and Q statistic, while the publication bias was evaluated using the asymmetry of the funnel plot and Egger's test. Results: In this systematic review, a total of nine articles were included. While psychosocial interventions demonstrated in reducing the risk of postpartum depression compared to usual maternal care, it is important to note that the mean difference score of depression was significant in only three of the included studies. The overall meta-analysis finding revealed that psychosocial interventions were effective in preventing postpartum depression, with a pooled effect size of -0.5 (95% CI: -0.95, -0.06) during the final time postpartum depression assessment. The heterogeneity level was found to be substantial, with an I2 value of 82.3%. However, no publication bias was observed. Conclusion: The review findings suggest that psychosocial interventions initiated during the late antenatal and early postnatal periods effectively prevent postpartum depression. The interventions were found to be more beneficial during the first three months of the postpartum period. However, this review also highlighted that there is a scarcity of interventional studies conducted in low-income countries, indicating the need for further studies in diverse communities.

Keywords: teenage pregnancy, postpartum depression, review

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Authors: Adewale I. Adeolu, Vivian U. Oleforuh-Okoleh, Sylvester N. Ibe

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Heritability and repeatability estimates are needed for the genetic evaluation of livestock populations and consequently for the purpose of upgrading or improvement. Pooled data on 604 progeny from three consecutive parities of purebred rabbit breeds (Chinchilla, Dutch and New Zealand white) raised in Derived Savanna Zone of Nigeria were used to estimate heritability and repeatability for pre-weaning body weights between 1st and 8th week of age. Traits studied include Individual kit weight at birth (IKWB), 2nd week (IK2W), 4th week (IK4W), 6th week (IK6W) and 8th week (IK8W). Nested random effects analysis of (Co)variances as described by Statistical Analysis System (SAS) were employed in the estimation. Respective heritability estimates from the sire component (h2s) and repeatability (R) as intra-class correlations of repeated measurements from the three parties for IKWB, IK2W, IK4W and IK8W are 0.59±0.24, 0.55±0.24, 0.93±0.31, 0.28±0.17, 0.64±0.26 and 0.12±0.14, 0.05±0.14, 0.58±0.02, 0.60±0.11, 0.20±0.14. Heritability and repeatability (except R for IKWB and IK2W) estimates are moderate to high. In conclusion, since pre-weaning body weights in the present study tended to be moderately to highly heritable and repeatable, improvement of rabbits raised in derived savanna zone can be realized through genetic selection criterions.

Keywords: heritability, nested design, parity, pooled data, repeatability

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Authors: Ananya Gupta, Sangeeta Bhaskar

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Mycobacterium indicus pranii (MIP) is a saprophytic mycobacterium. It is a predecessor of M. avium complex (MAC). Whole genome analysis and growth kinetics studies have placed MIP in between pathogenic and non-pathogenic species. It shares significant antigenic repertoire with M. tuberculosis and have unique immunomodulatory properties. MIP provides better protection than BCG against pulmonary tuberculosis in animal models. Immunization with MIP by aerosol route provides significantly higher protection as compared to immunization by subcutaneous (s.c.) route. However, mechanism behind differential protection has not been studied. In this study, using mice model we have evaluated and compared the M.tb specific immune response in lung compartments (airway lumen / lung interstitium) as well as spleen following MIP immunization via nasal (i.n.) and s.c. route. MIP i.n. vaccination resulted in increased seeding of memory T cells (CD4+ and CD8+ T-cells) in the airway lumen. Frequency of CD4+ T cells expressing Th1 migratory marker (CXCR3) and activation marker (CD69) were also high in airway lumen of MIP i.n. group. Significantly high ex vivo secretion of cytokines- IFN-, IL-12, IL-17 and TNF- from cells of airway luminal spaces provides evidence of antigen-specific lung immune response, besides generating systemic immunity comparable to MIP s.c. group. Analysis of T cell response on per cell basis revealed that antigen specific T-cells of MIP i.n. group were functionally superior as higher percentage of these cells simultaneously secreted IFN-gamma, IL-2 and TNF-alpha cytokines as compared to MIP s.c. group. T-cells secreting more than one of the cytokines simultaneously are believed to have robust effector response and crucial for protection, compared with single cytokine secreting T-cells. Adoptive transfer of airway luminal T-cells from MIP i.n. group into trachea of naive B6 mice revealed that MIP induced CD8 T-cells play crucial role in providing long term protection. Thus the study demonstrates that MIP intranasal vaccination induces M.tb specific memory T-cells in the airway lumen that results in an early and robust recall response against M.tb infection.

Keywords: airway lumen, Mycobacterium indicus pranii, Th1 migratory markers, vaccination

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Authors: Bahman Ghaderi, Hedayat Hosseini, Parviz Kafche

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The role of knowledge management processes in achieving the strategic goals of organizations is crucial. To this end, understanding the relationship between knowledge management processes and different aspects of strategic thinking (followed by long-term organizational planning) should be considered. This research examines the relationship between each of the five knowledge management processes (creation, storage, transfer, audit, and deployment) with each dimension of strategic thinking (vision, creativity, thinking, communication and analysis) in one of the major sectors of the food industry in Iran. In this research, knowledge management and its dimensions (knowledge acquisition, knowledge storage, knowledge transfer, knowledge auditing, and finally knowledge utilization) as independent variables and strategic thinking and its dimensions (creativity, systematic thinking, vision, strategic analysis, and strategic communication) are considered as the dependent variable. The statistical population of this study consisted of 245 managers and employees of Minoo Food Industrial Group in Tehran. In this study, a simple random sampling method was used, and data were collected by a questionnaire designed by the research team. Data were analyzed using SPSS 21 software. LISERL software is also used for calculating and drawing models and graphs. Among the factors investigated in the present study, knowledge storage with 0.78 had the most effect, and knowledge transfer with 0.62 had the least effect on knowledge management and thus on strategic thinking.

Keywords: knowledge management, strategic thinking, knowledge management processes, food industry

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