Search results for: township level

Authors: Hsiao-Wen Hsu

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It is generally believed that the teacher’s use of motivational strategies can enhance student motivation, especially in a place like Taiwan where teacher usually dominates student EFL learning. However, only little empirical studies support this claim. This study examined the connection between teachers’ use of motivational teaching practice and observed student motivated behavior in rural junior high schools in Taiwan. The use of motivational strategies by 12 teachers in five recognized rural junior high schools was investigated observed using a classroom observation instrument, the Motivation Orientation of Language Teaching. Meanwhile, post-lesson teacher evaluations accomplished by both the researcher and the teacher were functioning as part of the measure of teacher motivational practice. The data collected through observation scheme follows the real-time coding principle to examine observable teacher motivational practice and learner motivated behaviors. The results support the previous research findings that teachers’ use of motivational strategies is associated with the student motivated behaviors as well as the students’ level of motivation regarding English learning.

Keywords: English learning, motivational strategies, student motivation, teacher motivational practices

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Authors: Chunye Gong, Ming Tie, Jie Liu, Weimin Bao, Xinbiao Gan, Shengguo Li, Bo Yang, Xuguang Chen, Tiaojie Xiao, Yang Sun

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Large-scale CFD simulation relies on high-performance parallel computing, and the load balance is the key role which affects the parallel efficiency. This paper focuses on the load-balancing problem of parallel CFD simulation with structured mesh. A mathematical model for this load-balancing problem is presented. The genetic algorithm, fitness computing, two-level code are designed. Optimal selector, robust operator, and local optimization operator are designed. The properties of the presented genetic algorithm are discussed in-depth. The effects of optimal selector, robust operator, and local optimization operator are proved by experiments. The experimental results of different test sets, DLR-F4, and aircraft design applications show the presented load-balancing algorithm is robust, quickly converged, and is useful in real engineering problems.

Keywords: genetic algorithm, load-balancing algorithm, optimal variation, local optimization

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Authors: Van-Thuan Tran, Minh-Khai Nguyen, Geum-Bae Cho

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Recently, multilevel inverters have become more attractive for researchers due to low total harmonic distortion (THD) in the output voltage and low electromagnetic interference (EMI). This paper proposes a single-phase cascaded H-bridge quasi switched boost inverter (CHB-qSBI) for renewable energy sources applications. The proposed inverter has the advantage over the cascaded H-bridge quasi-Z-source inverter (CHB-qZSI) in reducing two capacitors and two inductors. As a result, cost, weight, and size are reduced. Furthermore, the dc-link voltage of each module is controlled by individual shoot-through duty cycle to get the same values. Therefore, the proposed inverter solves the imbalance problem of dc-link voltage in traditional CHB inverter. This paper shows the operating principles and analysis of the single-phase cascaded H-bridge quasi switched boost inverter. Also, a control strategy for the proposed inverter is shown. Experimental and simulation results are shown to verify the operating principle of the proposed inverter.

Keywords: renewable energy sources, cascaded h-bridge inverter, quasi switched boost inverter, quasi z-source inverter, multilevel inverter

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Authors: Dimitra Das, Anuradha Mitra, Kalyan Kumar Chattopadhyay

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Organic polymers, constructed from light elements like carbon, hydrogen, nitrogen, oxygen, sulphur, and boron atoms, are the emergent class of non-toxic, metal-free, environmental benign advanced materials. Covalent triazine-based polymers with a functional triazine group are significant class of organic materials due to their remarkable stability arising out of strong covalent bonds. They can conventionally form hydrogen bonds, favour π–π contacts, and they were recently revealed to be involved in interesting anion–π interactions. The present work mainly focuses upon the development of a single-crystalline, highly cross-linked triazine-based nitrogen-rich organic polymer with nanodendritic morphology and significant thermal stability. The polymer has been synthesized through hydrothermal treatment of melamine and ethylene glycol resulting in cross-polymerization via condensation-polymerization reaction. The crystal structure of the polymer has been evaluated by employing Rietveld whole profile fitting method. The polymer has been found to be composed of monoclinic melamine having space group P21/a. A detailed insight into the chemical structure of the as synthesized polymer has been elucidated by Fourier Transform Infrared Spectroscopy (FTIR) and Raman spectroscopic analysis. X-Ray Photoelectron Spectroscopic (XPS) analysis has also been carried out for further understanding of the different types of linkages required to create the backbone of the polymer. The unique rod-like morphology of the triazine based polymer has been revealed from the images obtained from Field Emission Scanning Electron Microscopy (FESEM) and Transmission Electron Microscopy (TEM). Interestingly, this polymer has been found to selectively detect mercury (Hg²⁺) ions at an extremely low concentration through fluorescent quenching with detection limit as low as 0.03 ppb. The high toxicity of mercury ions (Hg²⁺) arise from its strong affinity towards the sulphur atoms of biological building blocks. Even a trace quantity of this metal is dangerous for human health. Furthermore, owing to its small ionic radius and high solvation energy, Hg²⁺ ions remain encapsulated by water molecules making its detection a challenging task. There are some existing reports on fluorescent-based heavy metal ion sensors using covalent organic frameworks (COFs) but reports on mercury sensing using triazine based polymers are rather undeveloped. Thus, the importance of ultra-trace detection of Hg²⁺ ions with high level of selectivity and sensitivity has contemporary significance. A plausible sensing phenomenon by the polymer has been proposed to understand the applicability of the material as a potential sensor. The impressive sensitivity of the polymer sample towards Hg²⁺ is the very first report in the field of highly crystalline triazine based polymers (without the introduction of any sulphur groups or functionalization) towards mercury ion detection through photoluminescence quenching technique. This crystalline metal-free organic polymer being cheap, non-toxic and scalable has current relevance and could be a promising candidate for Hg²⁺ ion sensing at commercial level.

Keywords: fluorescence quenching , mercury ion sensing, single-crystalline, triazine-based polymer

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Authors: Wooyoung Jung, Ghang Lee

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This paper paper reports the worldwide status of building information modeling (BIM) adoption from the perspectives of the engagement level, the Hype Cycle model, the technology diffusion model, and BIM-uses. An online survey was distributed, and 156 experts from six continents responded. Overall, North America was the most advanced continent, followed by Oceania and Europe. Countries in Asia perceived their phase mainly as slope of enlightenment (mature) in the Hype Cycle model. In the technology diffusion model, the main BIM-users worldwide were “early majority” (third phase), but those in the Middle East/Africa and South America were “early adopters” (second phase). In addition, the more advanced the country, the more number of BIM services employed in general. In summary, North America, Europe, Oceania, and Asia were advancing rapidly toward the mature stage of BIM, whereas the Middle East/Africa and South America were still in the early phase. The simple indexes used in this study may be used to track the worldwide status of BIM adoption in long-term surveys.

Keywords: BIM adoption, BIM services, hype cycle model, technology diffusion model

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Authors: Firas A. Al Laban, Mohamed Chabi, Sammani Danwawu Abdullahi

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There are a real needs to integrate types of Open Educational Resources (OER) with an intelligent system to extract information and knowledge in the semantic searching level. Those needs raised because most of current learning standard adopted web based learning and the e-learning systems does not always serve all educational goals. Semantic Web systems provide educators, students, and researchers with intelligent queries based on a semantic knowledge management learning system. An ontology-based learning system is an advanced system, where ontology plays the core of the semantic web in a smart learning environment. The objective of this paper is to discuss the potentials of ontologies and mapping different kinds of ontologies; heterogeneous or homogenous to manage and control different types of Open Educational Resources. The important contribution of this research is to approach a methodology uses logical rules and conceptual relations to map between ontologies of different educational resources. We expect from this methodology to establish for an intelligent educational system supporting student tutoring, self and lifelong learning system.

Keywords: knowledge management systems, ontologies, semantic web, open educational resources

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Authors: Nino Grigolaia

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Introduction: The article discusses the experience of the EU in the social field, analyzes the peculiarities of the functioning of the social system in Georgia, and reveals the priority and importance of social policy. Methodology: Different research methods are applied in the presented paper. There are used induction, deduction, analysis, synthesis, analogy, correlation, and statistical observation methodologies in the work. Main Findings: Based on the analysis of social security reforms in Georgia, the main systematic problems are detected, the recommendations on social security system components, integration of the social security field in the unified insurance system, the formation of the national social system, perfection of the legislative, regulatory framework of social protection, adoption of foreign experience are developed in the article. Conclusion: The article concludes that the social protection system in Georgia is at an early stage of development, with the significant impact of factors such as high level of unemployment, low pensions, a large number of families living under the poverty line, and other ones. Accordingly, it is well-established that the study of the social security problem in Georgia is still actual. Based on the analysis, appropriate suggestions in the field of social security are made, and relevant recommendations are proposed.

Keywords: social security, social system, social policy, social security models

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Authors: Austin Belfiori, Kevin Rinek, Zach Barcroft, Jennifer Berglind

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Diet influences the composition of the gut microbiota and host's health. Disruption of the balance among the microbiota, epithelial cells, and resident immune cells in the intestine is involved in the pathogenesis of inflammatory bowel disease (IBD). To study the role of gut microbiota in intestinal inflammation, the microbiome of control mice (C57BL6) given a gluten-containing standard diet versus C57BL6 mice given the gluten-free (GF) feed (n=10 in each group) was examined. All mice received the 3% DSS for 5 days. Throughout the study, feces were collected and processed for DNA extraction and MiSeq Illumina sequencing of V4 region of bacterial 16S rRNA gene. Alpha and beta diversities and compositional differences at phylum and genus levels were determined in intestinal microbiota. The mice receiving the GF diet showed a significantly increased abundance of Firmicutes and a decrease of Bacteroides and Lactobacillus at phylum level. Therefore, the gluten free diet led to reductions in beneficial gut bacteria populations. These findings indicate a role of wheat gluten in dysbiosis of the intestinal microbiota.

Keywords: gluten, colitis, microbiota, DSS, dextran sulphate sodium

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Authors: Dong Wook Lee, Seung Hyun Kim, Jeongho Oh

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With the strengthened regulation on the mandatory use of recycled aggregate, development of construction materials using recycled aggregate has recently increased. This study aimed to secure the performance of asphalt concrete mixture by developing recycled-modified asphalt using recycled basalt aggregate from the Jeju area. The strength of the basalt aggregate from the Jeju area used in this study was similar to that of general aggregate, while the specific surface area was larger due to the development of pores. Modified asphalt was developed using a general aggregate-recycled aggregate ratio of 7:3, and the results indicated that the Marshall stability increased by 27% compared to that of asphalt concrete mixture using only general aggregate, and the flow values showed similar levels. Also, the indirect tensile strength increased by 79%, and the toughness increased by more than 100%. In addition, the TSR for examining moisture resistance was 0.95 indicating that the reduction in the indirect tensile strength due to moisture was very low (5% level), and the developed recycled-modified asphalt could satisfy all the quality standards of asphalt concrete mixture.

Keywords: asphalt concrete mixture, performance grade, recycled basalt aggregate, recycled-modified asphalt

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Authors: Zhiming Ye, Dejiang Wang, Huiling Zhao

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Development of the technology demands a higher-level research on the mechanical behavior of materials. Structural members made of bi-modulus materials have different elastic modulus when they are under tension and compression. The stress and strain states of the point effect on the elastic modulus and Poisson ratio of every point in the bi-modulus material body. Accompanied by the uncertainty and nonlinearity of the elastic constitutive relation is the complicated nonlinear problem of the bi-modulus members. In this paper, the small displacement and large displacement finite element method for the bi-modulus members have been proposed. Displacement nonlinearity is considered in the elastic constitutive equation. Mechanical behavior of slender bi-modulus beam-column under different boundary conditions and loading patterns has been simulated by the proposed method. The influence factors on the ultimate bearing capacity of slender beam and columns have been studied. The results show that as the ratio of tensile modulus to compressive modulus increases, the error of the simulation employing the same elastic modulus theory exceeds the engineering permissible error.

Keywords: bi-modulus, ultimate capacity, beam-column, nonlinearity

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Authors: Cavidan Yakupoglu, Kurt Rohloff

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In this study, we aim to provide a novel parameter selection model for the BFVrns scheme, which is one of the prominent FHE schemes. Parameter selection in lattice-based FHE schemes is a practical challenges for experts or non-experts. Towards a solution to this problem, we introduce a hybrid principles-based approach that combines theoretical with experimental analyses. To begin, we use regression analysis to examine the parameters on the performance and security. The fact that the FHE parameters induce different behaviors on performance, security and Ciphertext Expansion Factor (CEF) that makes the process of parameter selection more challenging. To address this issue, We use a multi-objective optimization algorithm to select the optimum parameter set for performance, CEF and security at the same time. As a result of this optimization, we get an improved parameter set for better performance at a given security level by ensuring correctness and security against lattice attacks by providing at least 128-bit security. Our result enables average ~ 5x smaller CEF and mostly better performance in comparison to the parameter sets given in [1]. This approach can be considered a semiautomated parameter selection. These studies are conducted using the PALISADE homomorphic encryption library, which is a well-known HE library. The abstract goes here.

Keywords: lattice cryptography, fully homomorphic encryption, parameter selection, LWE, RLWE

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Authors: Endang Jati Mat Sahid, Hussain Ali Bekhet

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Robust economic growth, increasing population, and personal consumption are the main drivers for the rapid increase of energy demand in Malaysia. Increasing demand has compounded the issue of national energy security due to over-dependence on fossil fuel, depleting indigenous domestic conventional energy resources which in turns has increased the country’s energy import dependence. In order to improve its energy security, Malaysia has seriously embarked on a renewable energy journey. Many initiatives on renewable energy have been introduced in the past decade. These strategies have resulted in the exploding growth of renewable energy deployment in Malaysia. Therefore, this study investigated the impact of renewable energy deployment on energy security. Secondary data was used to calculate the energy security indicators. The study also compared the results of applying different energy security indicators namely availability, applicability, affordability and acceptability dimension of energy resources. The evaluation shows that Malaysia will experience slight improvement in availability and acceptability dimension of energy security. This study suggests that energy security level could be further enhanced by efficient utilization of energy, reducing carbon content of energy and facilitating low-carbon industries.

Keywords: energy policy, energy security, Malaysia, renewable energy

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Authors: Vani Singhal, Jitendra Parmar, Satyendra Singh Chouhan

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Unseen class discovery has now become an important part of a machine-learning algorithm to judge new classes. Unseen classes are the classes on which the machine learning model is not trained on. With the advancement in technology and AI replacing humans, the amount of data has increased to the next level. So while implementing a model on real-world examples, we come across unseen new classes. Our aim is to find the number of unseen classes by using a hierarchical-based active learning algorithm. The algorithm is based on hierarchical clustering as well as active sampling. The number of clusters that we will get in the end will give the number of unseen classes. The total clusters will also contain some clusters that have unseen classes. Instead of first discovering unseen classes and then finding their number, we directly calculated the number by applying the algorithm. The dataset used is for intent classification. The target data is the intent of the corresponding query. We conclude that when the machine learning model will encounter real-world data, it will automatically find the number of unseen classes. In the future, our next work would be to label these unseen classes correctly.

Keywords: active sampling, hierarchical clustering, open world learning, unseen class discovery

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Authors: Abdullah Ali H. Ahmadini, Firoz Ahmad, Intekhab Alam

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Geometric programming problem (GPP) is a well-known non-linear optimization problem having a wide range of applications in many engineering problems. The structure of GPP is quite dynamic and easily fit to the various decision-making processes. The aim of this paper is to highlight the bounded solution method for GPP with special reference to variation among right-hand side parameters. Thus this paper is taken the advantage of two-level mathematical programming problems and determines the solution of the objective function in a specified interval called lower and upper bounds. The beauty of the proposed bounded solution method is that it does not require sensitivity analyses of the obtained optimal solution. The value of the objective function is directly calculated under varying parameters. To show the validity and applicability of the proposed method, a numerical example is presented. The system reliability optimization problem is also illustrated and found that the value of the objective function lies between the range of lower and upper bounds, respectively. At last, conclusions and future research are depicted based on the discussed work.

Keywords: varying parameters, geometric programming problem, bounded solution method, system reliability optimization

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Authors: Aniedi A. Udo, Magnus U. Igboekwe, Rasaaq Bello, Francis D. Eyenaka, Michael C. Ohakwere-Eze

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Groundwater vulnerability to pollution was assessed in Akwa Ibom State, Southern Nigeria, with the aim of locating areas with high potentials for resource contamination, especially due to anthropogenic influence. The electrical resistivity method was utilized in the collection of the initial field data. Additional data input, which included depth to static water level, drilled well log data, aquifer recharge data, percentage slope, as well as soil information, were sourced from secondary sources. The initial field data were interpreted both manually and with computer modeling to provide information on the geoelectric properties of the subsurface. Interpreted results together with the secondary data were used to develop the DRASTIC thematic maps. A vulnerability assessment was performed using the DRASTIC model in a GIS environment and areas with high vulnerability which needed immediate attention was clearly mapped out and presented using an aquifer vulnerability map. The model was subjected to validation and the rate of validity was 73% within the area of study.

Keywords: groundwater, vulnerability, DRASTIC model, pollution

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Authors: Mehrdad Shahrbanozadeh, Gholam Abbas Barani, Saeed Shojaee

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In this study, a finite element (Seep3D model) and an artificial neural network (ANN) model were developed to simulate flow through dam foundation. Seep3D model is capable of simulating three-dimensional flow through a heterogeneous and anisotropic, saturated and unsaturated porous media. Flow through the Shahid Abbaspour dam foundation has been used as a case study. The FEM with 24960 triangular elements and 28707 nodes applied to model flow through foundation of this dam. The FEM being made denser in the neighborhood of the curtain screen. The ANN model developed for Shahid Abbaspour dam is a feedforward four layer network employing the sigmoid function as an activator and the back-propagation algorithm for the network learning. The water level elevations of the upstream and downstream of the dam have been used as input variables and the piezometric heads as the target outputs in the ANN model. The two models are calibrated and verified using the Shahid Abbaspour’s dam piezometric data. Results of the models were compared with those measured by the piezometers which are in good agreement. The model results also revealed that the ANN model performed as good as and in some cases better than the FEM.

Keywords: seepage, dam foundation, finite element method, neural network, seep 3D model

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Authors: Tarek Abdel Azim Ahmed, Eman Sarhan Shaker

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This research aims to explore how well the extended model of internet commerce adoption (eMICA) model is often used to determine the extent of internet commerce adoption in the travel agencies sector in both Egypt and Kingdom of Saudi Arabia (KSA). The web content analysis method was used to analyze the level of adoption of Egyptian travel agencies and Saudi travel agencies according to data immensely available on their websites. Therefore, each site was categorized according to the phases and levels proposed. In order to achieve this, 120 websites were evaluated by the two authors over a three-month period, from August to October 2020, and then categorized according to the phases and levels of (eMICA). The results show that there are deficiencies in the application of the eMICA model by both KSA and Egyptian travel agencies, generally, updating their websites, the absence of quality certification, offering secure online payment, virtual tours, and videos using Flash animation. In general, the Egyptian companies slightly outperformed the KSA ones in applying eMICA model.

Keywords: e-commerce, internet marketing, eMICA, travel agencies, websites

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Authors: Mahta Eskandarnejad

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The aim of this paper was to compare physical activity and mental toughness in the staff and students of the University of Tabriz. 615 people participated in this study and filled demographic questionnaire, mental thoughness48 (MTQ48) questionnaire and habitual physical activity questionnaire (Baecke physical activity questionnaire). The research sample included 355 students and 260 staff (615 questionnaires). For analyzing hypotheses MANOVA, correlation and independent t-test were used. Based on the result; some subscales of mental toughness and physical activity were significantly related. The result showed the significant correlation between mental toughness and physical activity in student and no significant correlation in staff. Students were significantly physically more active than staff, and mental toughness was higher in staff. There was no difference in mental toughness variable between active participants (active staff and student). The results of this study showed that mental toughness could influence the way a person cope with living conditions. It is expected that mental toughness changes can lead to changing in levels of physical activity. It should be noted that the other variables should not be ignored.

Keywords: Baecke physical activity questionnaire, mental toughness, physical activity, university staff, university student

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Authors: Keerthi S. Shetty, Annappa Basava

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In recent years, modelling of biological systems represented by biochemical reactions has become increasingly important in Systems Biology. Biological systems represented by biochemical reactions are highly stochastic in nature. Probabilistic model is often used to describe such systems. One of the main challenges in Systems biology is to combine absolute experimental data into probabilistic model. This challenge arises because (1) some molecules may be present in relatively small quantities, (2) there is a switching between individual elements present in the system, and (3) the process is inherently stochastic on the level at which observations are made. In this paper, we describe a novel idea of combining absolute experimental data into probabilistic model using tool R2. Through a case study of the Transcription Process in Prokaryotes we explain how biological systems can be written as probabilistic program to combine experimental data into the model. The model developed is then analysed in terms of intrinsic noise and exact sampling of switching times between individual elements in the system. We have mainly concentrated on inferring number of genes in ON and OFF states from experimental data.

Keywords: systems biology, probabilistic model, inference, biology, model

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Authors: Sanjay Kumar Srivastava, Rajesh Srivastava

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Human resource is the key point of success of any economy. From the past few decades, policies started to move in the route of expanding inclusive education with effective involvement of government.Governments of developing nations are generating policies for educational upliftment. Applying educational policies, the motive of the government is to maintain and develop the effective human resource within a society. The attention of the government includes primary education to higher education. It also involves professional training programmes related to every discipline. The aim of this paper is to find out the government policies in terms of expenditure and achievements for inclusive education to develop human resources in developing countries. A case of Indian experience has been taken into consideration. This approach generates a picture as to how India is enriching its educational system for human resource development and this research study will be useful for the policy makers to determine the appropriate level of overall spending of government and achievements in the education system for human resource development. Analytical research methodology has been adopted.

Keywords: government policies, inclusive education, National Educational Policy, NCERT

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Authors: Farzad Jalilian, Mehdi Mirzaei Alavijeh, Fazel Zinat Motlagh

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Social support is an important benchmark of health for people in avoidance conditions. The main goal of this study was to determine the three kinds of social support (family, friend and other significant) to drug cessation among male addicts, in Kermanshah, the west of Iran. This cross-sectional study was conducted among 132 addicts, randomly selected to participate voluntarily in the study. Data were collected from conduct interviews based on standard questionnaire and analyzed by using SPSS-18 at 95% significance level. The majority of addicts were young (Mean: 30.4 years), and with little education. Opium (36.4%), Crack (21.2%), and Methamphetamine (12.9%) were the predominant drugs. Inabilities to reject the offer and having addict friends are the most often reasons for drug usage. Almost, 18.9% reported history of drug injection. 43.2% of the participants already did drug cessation at least once. Logistic regression showed the family support (OR = 1.110), age (OR = 1.106) and drug use initiation age (OR = 0.918) was predicting drug cessation. Our result showed; family support is a more important effect among types of social support in drug cessation. It seems that providing educational program to addict’s families for more support of patients at drug cessation can be beneficial.

Keywords: drug cessation, family support, drug use, initiation age

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Authors: Akshita Bhardwaj

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Keratinase is an enzyme obtained from extracellular sources that is involved in biodegradation of keratin. It is a member of a group of proteases that can break down keratin into amino acids. Keratinases are produced only in the presence of substrate that contain keratin. It attacked the disulfide bond of substrate and involve in keratin degradation. Human hair, feathers, animal hard tissues, horns, claws, and hooves all contain keratin.. It exists in two form alpha keratin (found in soft tissues) and beta keratin (found in hard tissue). By taking part in the degradation of keratin, keratinases derived from microbial sources, often referred to as microbial keratinases, are important in the process of turning wastes containing keratin into products with added value. Chicken feathers contain high level of keratin protein content than other sources and became a suitable protein source. Keratinase production occurs at near alkaline pH and thermophilic temperatures. The bioprocessing of keratinous waste benefits greatly from the use of keratinases. Additionally, it lessens the issue caused by poultry excrement. The use of feather meal, along with keratinase, improves the digestion of proteins and amino acids.

Keywords: mili litre (ml), micro litre (Ul), TCA - trichloroacetic acid, OD - optical density

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Authors: M. D. Saeed, S. O. Oladeji

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The level of cobalt was determined in wastewater and vegetable (carrot, lettuce, onion, spinach, cabbage, tomato and okro) samples collected on seasonal basis from December, 2012 to September 2014 along Kubanni stream channels in Zaria. The results showed cobalt concentrations in wastewater were in the range of 3.77 – 15.20 mg/L for the year 2013 and 4.74 – 15.20 mg/L in 2014 while the vegetable had concentrations in the range of 1.25 – 8.75 mg/Kg for the year 2013 and 2.76 – 12.45 mg/Kg in 2014. Statistical analysis revealed a significant difference in cobalt levels across the locations for wastewater and vegetables whereas seasons (harmattan, dry and rainy) showed no significant difference in wastewater and vegetables analyzed. Pearson correlation revealed substantial (r = 0.726) relationship between cobalt levels in wastewater for the year 2013 and 2014 likewise, substantial (r = 0.750) relationship was also obtained for vegetables cultivated in 2013 and 2014 respectively. Cobalt concentrations obtained in this study was higher than Maximum Contaminant Levels set by Standard Organization such as W.H.O. and F.A.O. for wastewater; however, vegetables indicated no contamination with cobalt metal.

Keywords: cobalt, concentration, wastewater, vegetable

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Authors: Leah Plocharczyk, Matthew Conner

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This paper analyzes the relatively new trend of PSE programs which seek to provide education, vocational training, and a college experience to individuals with an intellectual and developmental disability (IDD). Specifically, the paper examines the degree of interaction between PSE programs and the libraries of their college campuses. Using ThinkCollege, a clearinghouse and advocate for PSE programs, the researchers identified 293 programs throughout the country. These were all contacted with an email survey asking them about the nature of their involvement, if any, with the academic libraries on their campus. Where indicated by the responses, the libraries of PSE programs were contacted for additional information about their programming. Responses to the survey questions were tabulated and analyzed quantitatively. Written comments were analyzed for themes which were then tabulated. This paper presents the results of this study. They show obvious preferences for library programming, such as group formal instruction, individual liaisons, embedded reference, and various instructional designs. These are discussed in terms of special education principles of mainstreaming, level of restriction, training demands and cost effectiveness. The work serves as a foundation for best practices that can advance the field.

Keywords: disability studies, instructional design, universal design for learning, assessment methodology

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Authors: Xia Chen, Yulan Wang

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purpose: To compare the accuracy of Haigis, SRK/T, T2, Holladay 1, Hoffer Q, Barrett Universal II, Emmetropia Verifying Optical (EVO) and Kane for intraocular lens power calculation in patients with axial length (AL) ≥ 28 mm. Methods: In this retrospective single-center study, 50 eyes of 41 patients with AL ≥ 28 mm that underwent uneventful cataract surgery were enrolled. The actual postoperative refractive results were compared to the predicted refraction calculated with different formulas (Haigis, SRK/T, T2, Holladay 1, Hoffer Q, Barrett Universal II, EVO and Kane). The mean absolute prediction errors (MAE) 1 month postoperatively were compared. Results: The MAE of different formulas were as follows: Haigis (0.509), SRK/T (0.705), T2 (0.999), Holladay 1 (0.714), Hoffer Q (0.583), Barrett Universal II (0.552), EVO (0.463) and Kane (0.441). No significant difference was found among the different formulas (P = .122). The Kane and EVO formulas achieved the lowest level of mean prediction error (PE) and median absolute error (MedAE) (p < 0.05). Conclusion: The Kane and EVO formulas had a better success rate than others in predicting IOL power in high myopic eyes with AL longer than 28 mm in this study.

Keywords: cataract, power calculation formulas, intraocular lens, long axial length

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Authors: Kehinde Damilola Ilesanmi, Dev Datt Tewari

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South Africa is in its post-industrial era moving from the primary and secondary sector to the tertiary sector. The study investigated the impact of the disaggregated energy consumption (coal, oil, and electricity) on the primary, secondary and tertiary sectors of the economy between 1980 and 2012 in South Africa. Using vector error correction model, it was established that South Africa is an energy dependent economy, and that energy (especially electricity and oil) is a limiting factor of growth. This implies that implementation of energy conservation policies may hamper economic growth. Output growth is significantly outpacing energy supply, which has necessitated load shedding. To meet up the excess energy demand, there is a need to increase the generating capacity which will necessitate increased investment in the electricity sector as well as strategic steps to increase oil production. There is also need to explore more renewable energy sources, in order to meet the growing energy demand without compromising growth and environmental sustainability. Policy makers should also pursue energy efficiency policies especially at sectoral level of the economy.

Keywords: causality, economic growth, energy consumption, hypothesis, sectoral output

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Authors: M. Velana, G. Rinkenauer

Abstract:

Nowadays, nurses are facing unprecedented amounts of pressure due to the ongoing global health demands. Work-related stress can cause a high physical and psychological workload, which can lead, in turn, to burnout. On the physiological level, stress triggers an initial activation of the sympathetic nervous and adrenomedullary systems resulting in increases in cardiac activity. Furthermore, activation of the hypothalamus-pituitary-adrenal axis provokes endocrine and immune changes leading to the release of cortisol and cytokines in an effort to re-establish body balance. Based on the current state of the literature, it has been identified that resilience and mindfulness exercises among nurses can effectively decrease stress and improve mood. However, it is still unknown what relaxation techniques would be suitable for and to what extent would be effective to decrease psychophysiological arousal deriving from either a physiological or a psychological stressor. Moreover, although cardiac activity and cortisol are promising candidates to examine the effectiveness of relaxation to reduce stress, it still remains to shed light on the role of cytokines in this process so as to thoroughly understand the body’s response to stress and to relaxation. Therefore, the main aim of the present study is to develop a comprehensive experimental paradigm and assess different relaxation techniques, namely progressive muscle relaxation and a mindfulness exercise originating from cognitive therapy by means of biofeedback, under highly controlled laboratory conditions. An experimental between-subject design will be employed, where 120 participants will be randomized either to a physiological or a psychological stress-related experiment. Particularly, the cold pressor test refers to a procedure in which the participants have to immerse their non-dominant hands into ice water (2-3 °C) for 3 min. The participants are requested to keep their hands in the water throughout the whole duration. However, they can immediately terminate the test in case it would be barely tolerable. A pre-test anticipation phase and a post-stress period of 3 min, respectively, are planned. The Trier Social Stress Test will be employed to induce psychological stress. During this laboratory stressor, the participants are instructed to give a 5-min speech in front of a committee of communication specialists. Before the main task, there is a 10-min anticipation period. Subsequently, participants are requested to perform an unexpected arithmetic task. After stress exposure, the participants will perform one of the relaxation exercises (treatment condition) or watch a neutral video (control condition). Electrocardiography, salivary samples, and self-report will be collected at different time points. The preliminary results deriving from the pilot study showed that the aforementioned paradigm could effectively induce stress reactions and that relaxation might decrease the impact of stress exposure. It is of utmost importance to assess how the human body responds under different stressors and relaxation exercises so that an evidence-based intervention could be transferred in a clinical setting to improve nurses’ general health. Based on suggestive future laboratory findings, the research group plans to conduct a pilot-level randomized study to decrease stress and promote well-being among nurses who work in the stress-riddled environment of a hospital located in Northern Germany.

Keywords: nurses, psychophysiology, relaxation, stress

Procedia PDF Downloads 97

Authors: Simonida S. Djuric, Timea I. Hajnal Jafari, Dragana R. Stamenov

Abstract:

The use of plant growth promoting fungi (PGPF) has significantly increased in the last decade mostly due to their multi-level properties, and their expected success as biofertilizers in agriculture. Beneficial fungi with broad-host range undergo long-term interactions with a large variety of plants thereby playing a significant role in managed ecosystems and in the adaptation of crops to global climate changes. Trichoderma spp. are promising fungi toward the development of sustainable agriculture. The aim of our experiment was to investigate the effect of seed inoculation of sunflower, maize, soybean, paprika, melon, and watermelon seeds with Trichoderma sp. on early seed germination energy and initial growth of the plant. The seed inoculation with Trichoderma sp. increased the seedling emergence from 7, 85% in melon to 156,70% in watermelon. The inoculation had the best effect on initial growth of maize shoot (+23,80%) and soybean root (+106,30%). The different response of seed and young plants on Trichoderma sp. inoculation implicate the need for future investigations of successful inoculation systems and modes of their integration in sustainable agriculture production systems.

Keywords: initial growth, inoculation, seedling, Trichoderma sp.

Procedia PDF Downloads 229

Authors: Alessandro Marzucchini, Yie Sue Chua, Andrew Lian, Richard Shonn Mills

Abstract:

A unique, fast and easy installed inter-module connection named Candle-Loc was developed and applied in several high-rise steel and reinforced concrete modular buildings in Singapore and Hong Kong, China. However, its effect on the global behaviour of modular buildings in high seismic zones was not studied. Therefore, the design concept and the structural performance of each component in this connection was investigated through analytical approach. Response spectrum, linear time-history, and nonlinear time-history analyses were conducted to investigate the effects of the different joint models of the Candle-Loc in the global analysis of high-rise buildings under high seismic loads. It is found that it is important to assess the level of plasticity developed in the inter-module connection under high seismic loads. The ductility of the lateral force resisting system influences the amount of load taken by the inter-module connections.

Keywords: high-rise, inter-module connection, nonlinear, seismic, time-history analysis

Procedia PDF Downloads 149

Authors: Jean Marie Tshimula, Atsushi Togashi

Abstract:

We develop a data-science approach for providing an interactive visualization and predictive models to find insights into the projects' historical data in order for stakeholders understand some unseen opportunities in the African market that might escape them behind the online project portfolio of the African Development Bank. This machine learning-based web application identifies the market trend of the fastest growing economies across the continent as well skyrocketing sectors which have a significant impact on the future of business in Africa. Owing to this, the approach is tailored to predict where the investment needs are the most required. Moreover, we create a corpus that includes the descriptions of over more than 1,200 projects that approximately cover 14 sectors designed for some of 53 African countries. Then, we sift out this large amount of semi-structured data for extracting tiny details susceptible to contain some directions to follow. In the light of the foregoing, we have applied the combination of Latent Dirichlet Allocation and Random Forests at the level of the analysis module of our methodology to highlight the most relevant topics that investors may focus on for investing in Africa.

Keywords: machine learning, topic modeling, natural language processing, big data

Procedia PDF Downloads 159