Search results for: random matrix theory

Authors: Fulufhelo Amanda Doboro, Kgomotso Sebeko, Stephen Njiro, Moritz Van Vuuren

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Ovine herpesvirus 2 (OvHV-2) genome obtained from the lymphopblastoid cell line of a BJ1035 cow was recently sequenced in the United States of America (USA). Information on the sequences of OvHV-2 genes obtained from South African strains from bovine or other African countries and molecular characterization of OvHV-2 is not documented. Present investigation provides information on the nucleotide and derived amino acid sequences and genetic diversity of Ov 7, Ov 8 ex2, ORF 27 and ORF 73 genes, of these genes from OvHV-2 strains circulating in South Africa. Gene-specific primers were designed and used for PCR of DNA extracted from 42 bovine blood samples that previously tested positive for OvHV-2. The expected PCR products of 495 bp, 253 bp, 890 bp and 1632 bp respectively for Ov 7, Ov 8 ex2, ORF 27 and ORF 73 genes were sequenced and multiple sequence analysis done on the selected regions of the sequenced PCR products. Two genotypes for ORF 27 and ORF 73 gene sequences, and three genotypes for Ov 7 and Ov 8 ex2 gene sequences were identified, and similar groupings for the derived amino acid sequences were obtained for each gene. Nucleotide and amino acid sequence variations that led to the identification of the different genotypes included SNPs, deletions and insertions. Sequence analysis of Ov 7 and ORF 27 genes revealed variations that distinguished between sequences from SA and reference OvHV-2 strains. The implication of geographic origin among SA sequences was difficult to evaluate because of random distribution of genotypes in the different provinces, for each gene. However, socio-economic factors such as migration of people with animals, or transportation of animals for agricultural or business use from one province to another are most likely to be responsible for this observation. The sequence variations observed in this study have no impact on the antibody binding activities of glycoproteins encoded by Ov 7, Ov 8 ex2 and ORF 27 genes, as determined by prediction of the presence of B cell epitopes using BepiPred 1.0. The findings of this study will be used for selection of gene candidates for the development of diagnostic assays and vaccine development as well.

Keywords: amino acid, genetic diversity, genes, nucleotide

Procedia PDF Downloads 469

Authors: Esra Topcuoglu, Seyhmus Baloglu

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This research investigates the effects of online hotel sales promotion fit (SP fit) on traveler purchase intention (PI) and word-of-mouth (WOM). It examines these relationships based on the need for cognition (NFC), intention to travel (TI), promotional attractiveness (PA), and demographics within resource matching theory (RMT). One factor (SP: Fit presence for monetary and nonmonetary vs. Fit absence for monetary and nonmonetary) design was employed to test the effects of SP fit on traveler behaviors. Data collection was conducted from 300 subjects through Qualtrics. One-way MANOVA was performed to test the main effects of SP fit, and PROCESS simple moderation test for the interaction effects. Results revealed promotional fit increased the effectiveness of monetary and nonmonetary sales promotions. “F&B discount card at the hotel” was the most preferred deal. Fit absence for monetary sales promotion (MSP) and fit presence for nonmonetary sales promotion (NMSP) yielded significant results. The participants were involved in their intention to travel and perceptions of promotional attractiveness to value the promotions.

Keywords: need for cognition, promotional attractiveness, sales promotion fit, travel intention

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Authors: Wenyang Wan

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The study of urban land use and landscape pattern is the current hotspot in the fields of planning and design, ecology, etc., which is of great significance for the construction of the overall humanistic ecosystem of the city and optimization of the urban spatial structure. Banan District, as the main part of the eastern eco-city planning of Chongqing Municipality, is a high ground for highlighting the ecological characteristics of Chongqing, realizing effective transformation of ecological value, and promoting the integrated development of urban and rural areas. The analytical methods of land use transfer matrix (GIS) and landscape pattern index (Fragstats) were used to study the characteristics and laws of the evolution of land use landscape pattern in Banan District from 2000 to 2020, which provide some reference value for Banan District to alleviate the ecological contradiction of landscape. The results of the study show that ① Banan District is rich in land use types, of which the area of cultivated land will still account for 57.15% of the total area of the landscape until 2020, accounting for an absolute advantage in land use structure of Banan District; ② From 2000 to 2020, land use conversion in Banan District is characterized as Cropland > woodland > grassland > shrubland > built-up land > water bodies > wetlands, with cropland converted to built-up land being the largest; ③ From 2000 to 2020, the landscape elements of Banan District were distributed in a balanced way, and the landscape types were rich and diversified, but due to the influence of human interference, it also presented the characteristics that the shape of the landscape elements tended to be irregular, and the dominant patches were distributed in a scattered manner, and the patches had poor connectivity. It is recommended that in future regional ecological construction, the layout should be rationally optimized, the relationship between landscape components should be coordinated, the connectivity between landscape patches should be strengthened, and the degree of landscape fragmentation should be reduced.

Keywords: land use transfer, landscape pattern evolution, GIS and Fragstats, Banan district

Procedia PDF Downloads 53

Authors: Chukwuemeka Daniel Ezeliora, Chukwuebuka Lawrence Ezeliora

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The research focused on the appraisal of impact strength on mild steel cladding weld metal geometry. Over the years, poor welding has resulted in failures in engineering components, poor material quality, the collapse of welded materials, and failures in material strength. This is as a result of poor selection and combination of welding input process parameters. The application of the Tungsten Inert Gas (TIG) welding method with weld specimen of length 60; width 40, and thickness of 10 was used for the experiment. A butt joint method was prepared for the welding, and tungsten inert gas welding process was used to perform the twenty (20) experimental runs. A response surface methodology was used to model and to analyze the system. For an adequate polynomial approximation, the experimental design was used to collect the data. The key parameters considered in this work are welding current, gas flow rate, welding speed, and voltage. The range of the input process parameters was selected from the literature and the design. The steps followed to achieve the experimental design and results is the use of response surface method (RSM) implemented in central composite design (CCD) to generate the design matrix, to obtain quadratic model, and evaluate the interactions in the factors as well as optimizing the factors and the response. The result expresses that the best impact strength of the mild steel cladding weld metal geometry is 115.419 Joules. However, it was observed that the result of the input factors is; current 180.4 amp, voltage 23.99 volt, welding speed 142.7 mm.s and gas flow rate 10.8 lit/min as the optimum of the input process parameters. The optimal solution gives a guide for optimal impact strength of the weldment when welding with tungsten inert gas (TIG) under study.

Keywords: mild steel, impact strength, response surface, bead geometry, welding

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Authors: Fathiah Mohamed Zuki, Robert George Edyvean

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Electrostatic interaction energy (∆EEDL) is a part of the Extended Derjaguin-Landau-Verwey-Overbeek (XDLVO) theory, which, together with van der Waals (∆EVDW) and acid base (∆EAB) interaction energies, has been extensively used to investigate the initial adhesion of bacteria to surfaces. Electrostatic or electrical double layer interaction energy is considerably affected by surface potential, however it cannot be determined experimentally and is usually replaced by zeta (ζ) potential via electrophoretic mobility. This paper focuses on the effect of ionic concentration as a function of pH and the effect of mineral grain size on ζ potential. It was found that both ionic strength and mineral grain size play a major role in determining the value of ζ potential for the adhesion of P. putida to hematite and quartz surfaces. Higher ζ potential values lead to higher electrostatic interaction energies and eventually to higher total XDLVO interaction energy resulting in bacterial repulsion.

Keywords: XDLVO, electrostatic interaction energy, zeta potential, P. putida, mineral

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Authors: Mohammed Saleh Lahmdi, Hassan Obeid Alfadly

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This study explores an optimality-theoretic account of Indian loanwords in Hadhrami Arabic (henceforth HA), a variety of Arabic spoken in Hadhramout Province in the coastal areas and Hadhramout Valley. The purpose of this paper is to find out how the phonological forms of Indian loanwords can be accounted for from an OT standpoint. To achieve this purpose, two main instruments were implemented: participant observation and interview. The sample of this study was selected carefully with certain characteristics by judgment sampling consisting of eleven informants. An ethnographic qualitative approach was employed to find out the phonological articulations that the researcher encountered during the implementation. Many phonological processes are used and several markedness and faithfulness constraints have been interacted in conflict in order to choose the optimal form of Hadhrami realisations. The findings of the study confirm that the Hadhrami syllable structure prevails over the donor language, i.e., the Indian (mainly Urdu) language. Specifically, markedness constraints dominate faithfulness ones when most of the Indian loanwords are incorporated into HA.

Keywords: linguistic borrowing, optimality theory, Hadhrami Arabic, loanword, phonological processes

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Authors: Ebraheem Al-Jouri, Youssef Abu-Ahmad, Ramasamy Srinivasan

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The parasitoid, Diadegma semiclausum (Hymenoptera: Ichneumonidae) is one of the most effective exotic parasitoids of diamondback moth (DBM), Plutella xylostella in the lowland areas of Homs, Syria. Molecular evolution studies are useful tools to shed light on the molecular bases of insect geographical spread and adaptation to new hosts and environment and for designing better control strategies. In this study, molecular evolution analysis was performed based on the 42 nuclear internal transcribed spacer-2 (ITS2) sequences representing the D. semiclausum and eight other Diadegma spp. from Syria and worldwide. Possible recombination events were identified by RDP4 program. Four potential recombinants of the American D. insulare and D. fenestrale (Jeju) were detected. After detecting and removing recombinant sequences, the ratio of non-synonymous (dN) to synonymous (dS) substitutions per site (dN/dS=ɷ) has been used to identify codon positions involved in adaptive processes. Bayesian techniques were applied to detect selective pressures at a codon level by using five different approaches including: fixed effects likelihood (FEL), internal fixed effects likelihood (IFEL), random effects method (REL), mixed effects model of evolution (MEME) and Program analysis of maximum liklehood (PAML). Among the 40 positively selected amino acids (aa) that differed significantly between clades of Diadegma species, three aa under positive selection were only identified in D. semiclausum. Additionally, all D. semiclausum branches tree were highly found under episodic diversifying selection (EDS) at p≤0.05. Our study provide evidence that both recombination and positive selection have contributed to the molecular diversity of Diadegma spp. and highlights the significant contribution of D. semiclausum in adaptive evolution and influence the fitness in the DBM parasitoid.

Keywords: diadegma sp, DBM, ITS2, phylogeny, recombination, dN/dS, evolution, positive selection

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Authors: Richard Ren

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Air pollution is a serious danger to international well-being and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.

Keywords: air quality prediction, air pollution, artificial intelligence, machine learning algorithms

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Authors: Jan Henrik Wosnitza

Abstract:

The logistic regression has developed into a standard approach for estimating conditional probabilities in a wide range of applications including credit risk prediction. The article at hand contributes to the current literature on logistic regression fourfold: First, it is demonstrated that the binary logistic regression automatically meets its model assumptions under very general conditions. This result explains, at least in part, the logistic regression's popularity. Second, the requirement of homoscedasticity in the context of binary logistic regression is theoretically substantiated. The variances among the groups of defaulted and non-defaulted obligors have to be the same across the level of the aggregated default indicators in order to achieve linear logits. Third, this article sheds some light on the question why nonlinear logits might be superior to linear logits in case of a small amount of data. Fourth, an innovative methodology for estimating correlations between obligor-specific log-odds is proposed. In order to crystallize the key ideas, this paper focuses on the example of credit risk prediction. However, the results presented in this paper can easily be transferred to any other field of application.

Keywords: correlation, credit risk estimation, default correlation, homoscedasticity, logistic regression, nonlinear logistic regression

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Authors: Van Truong Pham

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Background: Self-management was described as a potential strategy for blood pressure control in patients with hypertension. However, the effects of self-management interventions on blood pressure, self-efficacy, medication adherence, and body mass index (BMI) in older adults with hypertension have not been systematically evaluated. We evaluated the effects of self-management interventions on systolic blood pressure (SBP) and diastolic blood pressure (DBP), self-efficacy, medication adherence, and BMI in hypertensive older adults. Methods: We followed the recommended guidelines of preferred reporting items for systematic reviews and meta-analyses. Searches in electronic databases including CINAHL, Cochrane Library, Embase, Ovid-Medline, PubMed, Scopus, Web of Science, and other sources were performed to include all relevant studies up to April 2019. Studies selection, data extraction, and quality assessment were performed by two reviewers independently. We summarized intervention effects as Hedges' g values and 95% confidence intervals (CI) using a random-effects model. Data were analyzed using Comprehensive Meta-Analysis software 2.0. Results: Twelve randomized controlled trials met our inclusion criteria. The results revealed that self-management interventions significantly improved blood pressure control, self-efficacy, medication adherence, whereas the effect of self-management on BMI was not significant in older adult patients with hypertension. The following Hedges' g (effect size) values were obtained: SBP, -0.34 (95% CI, -0.51 to -0.17, p < 0.001); DBP, -0.18 (95% CI, -0.30 to -0.05, p < 0.001); self-efficacy, 0.93 (95%CI, 0.50 to 1.36, p < 0.001); medication adherence, 1.72 (95%CI, 0.44 to 3.00, p=0.008); and BMI, -0.57 (95%CI, -1.62 to 0.48, p = 0.286). Conclusions: Self-management interventions significantly improved blood pressure control, self-efficacy, and medication adherence. However, the effects of self-management on obesity control were not supported by the evidence. Healthcare providers should implement self-management interventions to strengthen patients' role in managing their health care.

Keywords: self-management, meta-analysis, blood pressure control, self-efficacy, medication adherence, body mass index

Procedia PDF Downloads 105

Authors: Anuoluwapo S. Taiwo, David S. Ayre, Morteza Khorami, Sameer S. Rahatekar

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This investigation aims to characterize the effect of Corn Cob (CC), an agricultural waste, for potential use as a filler material, reducing cement in natural fibre-reinforced cement composite boards used for building applications in low-cost housing estates in developing countries. The corn cob is readily and abundantly available in many West African States. However, this agricultural waste product has not been put to any effective use. Hence, the objective of the current research is to convert this massive agro-waste resource into a potential material for use as filler materials reducing cement contents in fibre-cement board production. Kraft pulp fibre-reinforced cement composite boards were developed with the incorporation of the corn cob powder at varying percentages of 1 – 4% as filler materials to reduce the cement content, using a laboratory-simulated vacuum de-watering process. The mechanical properties of the developed cement boards were characterized through a three-point bending test, while the fractured morphology of the cement boards was examined through a Scanning Electron Microscope (SEM). Results revealed that the flexural strength of the composite board improved significantly with an optimum enhancement of 39% when compared to the reference sample without corn cob replacement, however, the flexural behaviour (ductility) of the composite board was slightly affected by the addition of the corn cob powder at higher percentage. SEM observation of the fractured surfaces revealed good bonding at the fibre-matrix interface as well as a ductile-to-brittle fracture mechanism. Overall, the composite board incorporated with 2% corn cob powder as filler materials had the optimum properties which satisfied the minimum requirements of relevant standards for fibre cement flat sheets.

Keywords: agricultural waste, building applications, fibre-cement board, kraft pulp fibre, sustainability

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Authors: Aleksandar Hatzivelkos

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The term ”compromise” is mostly used casually within the social choice theory. It is usually used as a mere result of the social choice function, and this omits its deeper meaning and ramifications. This paper is based on a mathematical model for the description of a compromise as a version of the Sorites paradox. It introduces a formal definition of d-measure of divergence from a compromise and models a notion of compromise that is often used only colloquially. Such a model for vagueness phenomenon, which lies at the core of the notion of compromise enables the introduction of new mathematical structures. In order to maximize compromise, different methods can be used. In this paper, we explore properties of a social welfare function TdM (from Total d-Measure), which is defined as a function which minimizes the total sum of d-measures of divergence over all possible linear orderings. We prove that TdM satisfy strict Pareto principle and behaves well asymptotically. Furthermore, we show that for certain domain restrictions, TdM satisfy positive responsiveness and IIIA (intense independence of irrelevant alternatives) thus being equivalent to Borda count on such domain restriction. This result gives new opportunities in social choice, especially when there is an emphasis on compromise in the decision-making process.

Keywords: borda count, compromise, measure of divergence, minimization

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Authors: Izian Idris, Melissa Ha, Mikkay Wong

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Social media marketing, including influencer marketing, is an ongoing phenomenon, and most companies as well as industries, are finding it crucial to implement social media marketing in their marketing strategies. However, social media influencer marketing still needs to be explored, and further research on this area needs to be carried out to fully understand the importance of social media influencer marketing in impacting consumer purchase decisions. Influencer endorsement has become a trend to grab users’ attention these days. Thus, the aim of this research paper is to explore the attributes of social media influencers/influencer as the endorser that impact consumer purchase intentions. The attributes that will be investigated include attitude homophily, physical attractiveness, and social attractiveness. Following this, the elaboration likelihood model from the theory of persuasion is implemented in this research to further examine the influence of social media influencer attributes on consumer purchase intentions. This study will be able to help marketers, businesses, and researchers understand the attributes of social media influencers as endorsers that will impact consumer purchase intentions and allow businesses to enhance their strategies to better cater to their target market.

Keywords: influencer, endorsement, consumer purchase, social media

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Authors: Adedayo Racheal Agbonna

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The rising level of graduate unemployment in Nigeria has brought about the introduction of entrepreneurship education as a career option for self–reliance and self-employment. Sequel to this, it is important to have an understanding of the determining factors of entrepreneurial intention. Therefore this research empirically investigated the influence of entrepreneurship education on entrepreneurial intention of undergraduate students of selected universities in Ogun State, Nigeria. The study is significant to researchers, university policy makers, and the government. Survey research design was adopted in the study. The population consisted of 17,659 final year undergraduate students universities in Ogun State. The study adopted stratified and random sampling technique. The table of sample size determination was used to determine the sample size for this study at 95% confidence level and 5% margin error to arrive at a sample size of 1877 respondents. The elements of population were 400 level students of the selected universities. A structured questionnaire titled 'Entrepreneurship Education and students’ Entrepreneurial intention' was administered. The result of the reliability test had the following values 0.716, 0.907 and 0.949 for infrastructure, perceived university support, and entrepreneurial intention respectively. In the same vein, from the construct validity test, the following values were obtained 0.711, 0.663 and 0.759 for infrastructure, perceived university support and entrepreneurial intention respectively. Findings of this study revealed that each of the entrepreneurship education variables significantly affected intention University infrastructure B= -1.200, R²=0.679, F (₁,₁₈₇₅) = 3958.345, P < 0.05) Perceived University Support B= -1.027, R²=0.502, F(₁,₁₈₇₅) = 1924.612, P < 0.05). The perception of respondents in public university and private university on entrepreneurship education have a statistically significant difference [F(₁,₁₈₇₅) = 134.614, p < 0.05) α F(₁,₁₈₇₅) = 363.439]. The study concluded that entrepreneurship education positively influenced entrepreneurial intention of undergraduate students in Ogun State, Nigeria. Also, university infrastructure and perceived university support have negative and significant effect on entrepreneurial intention. The study recommended that to promote entrepreneurial intention of university undergraduate students, infrastructures and the university support that can arouse entrepreneurial intention of students should be put in place.

Keywords: entrepreneurship education, entrepreneurial intention, perceived university support, university infrastructure

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Authors: S. Archsana, Vajira Balasuriya

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In Trincomalee of Sri Lanka, a post-conflict area, resettlement projects and policy initiatives are taking place to improve the wealth of the rural communities through promoting economic activities by way of encouraging the rural women to opt to commence and operate Micro and Small Scale (MSS) businesses. This study attempts to identify the manner in which the institutional environment could facilitate these MSS businesses owned and operated by women in the rural environment. The respondents of this study are the beneficiaries of the Divi Neguma Development Training Program (DNDTP); a project designed to aid women owned MSS businesses, in Trincomalee district. 96 women business operators, who had obtained financing facilities from the DNDTP, are taken as the sample based on fixed interval random sampling method. The study reveals that primary challenges encountered by 82% of the women business operators are lack of initial capital followed by 71% initial market finding and 35% access to technology. The low level of education and language barriers are the constraints in accessing support agencies/service providers. Institutional support; specifically management and marketing services, have a significant relationship with wealth augmentation. Institutional support at the setting-up stage of businesses are thin whereas terms and conditions of the finance facilities are perceived as ‘too challenging’. Although diversification enhances wealth of the rural women business operators, assistance from the institutional framework to prepare financial reports that are required for business expansion is skinny. The study further reveals that institutional support is very much weak in terms of providing access to new technology and identifying new market networks. A mechanism that could facilitate the institutional framework to support the rural women business operators to access new technology and untapped market segments, and assistance in preparation of legal and financial documentation is recommended.

Keywords: business facilitation, institutional support, rural women business operators, wealth augmentation

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Authors: Kashifa Khalid

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This study aims to analyze the loss of identity and its impact on one’s life in ‘The Last White Man’ by Mohsin Hamid. The theory of Alienation Effect by Bertolt Brecht has been applied to the text as Hamid offers the readers a unique perspective, alluding to significant themes like identity, race and death. The aspects of defamiliarization align impeccably with the plot, as existence and the corresponding concept of identity seem to have dissolved into utter chaos. This extends from the unexplained transformation to the way the entire world unravels from its general norm into a dystopian mayhem. The characters, starting with the protagonist Anders, have lost their center. One’s own self transforms into the ‘other’, and the struggle is to get refamiliarized with one’s own self. Alienation and isolation only rise as the construct of race and identity is taken apart brick by brick, ironically at its own pace as many new realities are blown to bits. The inseparable relationship between identity and grief under the ever-looming cloud of ‘death’ is studied in detail. The theoretical framework and thematic aspects harmonize in accordance with the writing style put forth by Hamid, tying all the loose ends together.

Keywords: lost identity, post-apocalyptic world, chaos, alienation

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Authors: Asrat M.Belachew, Tiago Pereira, Institute of Mathematics, Computer Sciences, Avenida Trabalhador São Carlense, 400, São Carlos, 13566-590, Brazil

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Infectious diseases are among the most prominent threats to human beings. They cause morbidity and mortality to an individual and collapse the social, economic, and political systems of the whole world collectively. Mathematical models are fundamental tools and provide a comprehensive understanding of how infectious diseases spread and designing the control strategy to mitigate infectious diseases from the host population. Modeling the spread of infectious diseases using a compartmental model of inhomogeneous populations is good in terms of complexity. However, in the real world, there is a situation that accounts for heterogeneity, such as ages, locations, and contact patterns of the population which are ignored in a homogeneous setting. In this work, we study how classical an SEIR infectious disease spreading of the compartmental model can be extended by incorporating the mobility of population between heterogeneous cities during an outbreak of infectious disease. We have formulated an SEIR multi-cities epidemic spreading model using a system of 4k ordinary differential equations to describe the disease transmission dynamics in k-cities during the day and night. We have shownthat the model is epidemiologically (i.e., variables have biological interpretation) and mathematically (i.e., a unique bounded solution exists all the time) well-posed. We constructed the next-generation matrix (NGM) for the model and calculated the basic reproduction number R0for SEIR-epidemic spreading model with cities mobility. R0of the disease depends on the spectral radius mobility operator, and it is a threshold between asymptotic stability of the disease-free equilibrium and disease persistence. Using the eigenvalue perturbation theorem, we showed that sending a fraction of the population between cities decreases the reproduction number of diseases in interconnected cities. As a result, disease transmissiondecreases in the population.

Keywords: SEIR-model, mathematical model, city mobility, epidemic spreading

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Authors: Sheikh Omar Sillah

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Introduction: Monitoring is an important means of ensuring the smooth implementation and quality of clinical trials. For many years, traditional site monitoring approaches have been critical in detecting data errors but not optimal in identifying fabricated and implanted data as well as non-random data distributions that may significantly invalidate study results. The objective of this paper was to provide recommendations based on best statistical monitoring practices for detecting data-integrity issues suggestive of fabrication and implantation early in the study conduct to allow implementation of meaningful corrective and preventive actions. Methodology: Electronic bibliographic databases (Medline, Embase, PubMed, Scopus, and Web of Science) were used for the literature search, and both qualitative and quantitative studies were sought. Search results were uploaded into Eppi-Reviewer Software, and only publications written in the English language from 2012 were included in the review. Gray literature not considered to present reproducible methods was excluded. Results: A total of 18 peer-reviewed publications were included in the review. The publications demonstrated that traditional site monitoring techniques are not efficient in detecting data anomalies. By specifying project-specific parameters such as laboratory reference range values, visit schedules, etc., with appropriate interactive data monitoring, statistical monitoring can offer early signals of data anomalies to study teams. The review further revealed that statistical monitoring is useful to identify unusual data patterns that might be revealing issues that could impact data integrity or may potentially impact study participants' safety. However, subjective measures may not be good candidates for statistical monitoring. Conclusion: The statistical monitoring approach requires a combination of education, training, and experience sufficient to implement its principles in detecting data anomalies for the statistical aspects of a clinical trial.

Keywords: statistical monitoring, data anomalies, clinical trials, traditional monitoring

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Authors: Chen Zheng, Lin Zhou, Bao Xie, Xiao Du, Nianbin Shao

Abstract:

Power generated by large-scale photovoltaic plants (LSPVPs) is usually transmitted to the grid through several transformers and long distance overhead lines. Impedance of transformers and transmission lines results in complex interactions between the plant and the grid and among different inverters. In accordance with the topological structure of LSPV in reality, an equivalent model containing different inverters was built and then interactions between the plant and the grid and among different inverters were studied. Based on the vector composition principle of voltage at the point of common coupling (PCC), the mathematic function of PCC voltage in regard to the total power and grid impedance was deduced, from which the uttermost total power to guarantee the system stable is obtained. Taking the influence of different inverters numbers and the length of transmission lines to the system stability into account, the stability criterion of LSPV containing different inverters was derived. The result of simulation validated the theory analysis in the paper.

Keywords: LSPVPs, stability analysis, grid impedance, different types of inverter, PCC voltage

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Authors: F. V. Matta, C. M. Donnelly, M. B. Jaafar, N. I. Ward

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‘Yerba Mate’ (Ilex paraguariensis) is a native plant from South America with the main producers being Argentina and Brazil. ‘Mate’ is widely consumed in Argentina, Brazil, Uruguay and Paraguay. The most popular format is as an infusion made from dried leaves of a traditional cup, roasted material in tea bags or iced tea infusions. There are many alleged health benefits resulted from mate consumption, even though there is a lack of conclusive research published in the international literature. The main objective of this study was to develop and evaluate the sample preparation and instrumental analysis stages involved in the determination of trace elements in yerba mate using inductively coupled plasma mass spectrometry (ICP-MS). Specific details on the methods of sample digestion, validation of the ICP-MS analysis especially for polyatomic ion correction and matrix effects associated with the complex medium of mate will be presented. More importantly, mate produced in Brazil and Argentina, is subject to different soil conditions, methods of cultivation and production, especially for loose leaves and tea bags. The highest concentrations for loose mate leaf were for (mg/kg, dry weight): aluminium (253.6 – 506.9 for Brazil (Bra), 230.0 – 541.8 for Argentina (Arg), respectively), manganese (378.3 – 762.6 Bra; 440.8 – 879.9 Arg), iron (32.5 – 85.7 Bra; 28.2 – 132.9 Arg), zinc (28.2 – 91.1 Bra; 39.1 – 92.3 Arg), nickel (2.2 – 4.3 Bra; 2.9 – 10.8 Arg) and copper (4.8 – 9.1 Bra; 4.3 – 9.2 Arg), with lower levels of chromium, cobalt, selenium, molybdenum, cadmium, lead and arsenic. Elemental levels of mate leaf consumed in tea bags were found to be higher, mainly due to only using leaf material (as opposed to leaf and twig for loose packed product). Further implications of the way of consuming yerba mate will be presented, including different infusion methods in Brazil and Argentina. This research provides for the first time an extensive evaluation of mate products from both countries and the possible implications of specific trace elements, especially Mn, Fe, Se, Cu and Zn and the various health claims of consuming yerba mate.

Keywords: beverage analysis, ICP-MS, trace elements, yerba mate

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Authors: Tasanee Satthapong

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The purpose of the study was to determine the relationship between learning style preferences, teaching style preferences, and learning with happiness of college students who were majors in five different academic areas at the Suansunandha Rajabhat University in Thailand. The selected participants were 729 students 1st year-5th year in Faculty of Education from Thai teaching, early childhood education, math and science teaching, and English teaching majors. The research instruments are the Grasha and Riechmann learning and teaching styles survey and the students’ happiness in learning survey, based on learning with happiness theory initiated by the Office of the National Education Commission. The results of this study: 1) The most students’ learning styles were participant style, followed by collaborative style, and independent style 2) Most students’ happiness in learning in all subjects areas were at the moderate level: Early Childhood Education subject had the highest scores, while Math subject was at the least scores. 3) No different of student’s happiness in learning were found between students who has learning styles that match and not match to teachers’ teaching styles.

Keywords: learning style, teaching style, learning with happiness

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Authors: Giovana Perini-Loureiro

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The purpose of this research was to identify whether the nominalizations terminating in -TION in the academic discourse of native English speakers contain the arguments required by their input verbs. In the perspective of functional linguistics, ideational metaphors, with nominalization as their most pervasive realization, are lexically dense, and therefore frequent in formal texts. Ideational metaphors allow the academic genre to instantiate objectification, de-personalization, and the ability to construct a chain of arguments. The valence of those nouns present in nominalizations tends to maintain the same elements of the valence from its original verbs, but these arguments are not always expressed. The initial hypothesis was that these arguments would also be present alongside the nominalizations, through anaphora or cataphora. In this study, a qualitative analysis of the occurrences of the five more frequent nominalized terminations in -TION in academic texts was accomplished, and thus a verification of the occurrences of the arguments required by the original verbs. The assembling of the concordance lines was done through COCA (Corpus of Contemporary American English). After identifying the five most frequent nominalizations (attention, action, participation, instruction, intervention), the concordance lines were selected at random to be analyzed, assuring the representativeness and reliability of the sample. It was possible to verify, in all the analyzed instances, the presence of arguments. In most instances, the arguments were not expressed, but recoverable, either in the context or in the shared knowledge among the interactants. It was concluded that the realizations of the arguments which were not expressed alongside the nominalizations are part of a continuum, starting from the immediate context with anaphora and cataphora; up to a knowledge shared outside the text, such as specific area knowledge. The study also has implications for the teaching of academic writing, especially with regards to the impact of nominalizations on the thematic and informational flow of the text. Grammatical metaphors are essential to academic writing, hence acknowledging the occurrence of its arguments is paramount to achieve linguistic awareness and the writing prestige required by the academy.

Keywords: corpus, functional linguistics, grammatical metaphors, nominalizations, academic English

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Authors: Riki H. Patel, Arpan Desai, Trushit Upadhyaya, Shobhit K. Patel

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The micro strip antennas area has seen some inventive work in recent years and is now one of the most dynamic fields of antenna theory. A novel and simple printed wideband monopole antenna is presented. Printed on a single dielectric substrate and easily fed by using a 50 ohm microstip line, low-profile antenna structure with two parallel S-shaped meandered line of same size. In this research, S–form micro strip patch antenna is designed from measuring the prototypes of the proposed antenna one available bands with 10db return loss bandwidths of about GPS application (GPS L2 1490 MHz) and covering the 1400 to 1580 MHz frequency band at 1.5 GHz The simulated results for main parameters such as return loss, impedance bandwidth, radiation patterns and gains are also discussed herein. The modeling study shows that such antennas, in simplicity design and supply, and can satisfy GPS application. Two parallel slots are incorporated to disturb the surface flow path, introducing local inductive effect. This antenna is fed by a coaxial feeding tube.

Keywords: bandwidth, electrically small antenna, microstrip, patch antenna, GPS

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Authors: Yousfi Abdelkader, Chaker Abdelkader, Bot Youcef

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This article proposes a five-level shunt active power filter for power quality improvement using a interval type-2 fuzzy logic controller (IT2 FLC). The reference compensating current is extracted using the P-Q theory. The majority of works previously reported are based on two-level inverters with a conventional Proportional integral (PI) controller, which requires rigorous mathematical modeling of the system. In this paper, a IT2 FLC controlled five-level active power filter is proposed to overcome the problem associated with PI controller. The IT2 FLC algorithm is applied for controlling the DC-side capacitor voltage as well as the harmonic currents of the five-level active power filter. The active power filter with a IT2 FLC is simulated in MATLAB Simulink environment. The simulated response shows that the proposed shunt active power filter controller has produced a sinusoidal supply current with low harmonic distortion and in phase with the source voltage.

Keywords: power quality, shunt active power filter, interval type-2 fuzzy logic controller (T2FL), multilevel inverter

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Authors: Sara D. Garduno-Diaz, Ramona Milcheva, Chanyu Xu

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Women’s reproductive stages (pre-pregnancy, pregnancy, and lactation) represent a time of higher micronutrient needs. With a healthy food selection as the first path of choice to cover these increased needs, tandem micronutrient supplementation is often required. Because pregnancy and lactation should be treated with care, all supplements consumed should be of quality ingredients and manufactured through controlled processes. This work describes the process followed for the development of plant-based multiple micronutrient supplements aimed at addressing the growing demand for natural ingredients of non-animal origin. A list of key nutrients for inclusion was prioritized, followed by the identification and selection of qualified raw ingredient providers. Nutrient absorption into the food matrix was carried out through natural processes. The outcome is a new line of products meeting the set criteria of being gluten and lactose-free, suitable for vegans/vegetarians, and without artificial conservatives. In addition, each product provides the consumer with 10 vitamins, 6 inorganic nutrients, 1 source of essential fatty acids, and 1 source of phytonutrients each (maca, moringa, and chlorella). Each raw material, as well as the final product, was submitted to microbiological control three-fold (in-house and external). The final micronutrient mix was then tested for human factor contamination, pesticides, total aerobic microbial count, total yeast count, and total mold count. The product was created with the aim of meeting product standards for the European Union, as well as specific requirements for the German market in the food and pharma fields. The results presented here reach the point of introduction of the newly developed product to the market, with acceptability and effectiveness results to be published at a later date.

Keywords: fertility, lactation, organic, pregnancy, vegetarian

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Authors: Rushi Tan, Yilun Xu, Xiaohui Wang

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The restrained construction zoning, an important part in the urban master plan, is a necessary planning tool to control the city sprawl, to guarantee the reservation implementation of the various types of protective elements, and to realize the storage of the essential urban spatial resources. Simultaneously, owing to the diverse constitutes of restrained construction area and the various stakeholders involved in, its planning requires an overall consideration of all elements from the perspective of coordination, balance and practicability to deal with the problems and conflicts in this process. Taking Yangzijin Ecological Restrained Construction Area in Yangzhou as an example, this study analyzes all the potential actors, agencies and stakeholders in this restrained construction area, as well as the relevant conflicts between each other. Besides, this study tries to build up a planning procedure based on the framework of governance theory, and proposes a possible planning method that combines "rigidity" and "flexibility" to protect the ecological limitation boundary, to take every interest into account, and to promote economic development in a harmonious society.

Keywords: restrained construction area, governance, stakeholder, flexible stratagem, China

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Authors: H. Loumi-Fergane, A. Belaidi

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The problem of symmetries in field theory has been analyzed using geometric frameworks, such as the multisymplectic models by using in particular the multivector field formalism. In this paper, we expand the vector fields associated to infinitesimal symmetries which give rise to invariant quantities as Noether currents for classical field theories and relativistic mechanic using the multisymplectic geometry where the Poincaré-Cartan form has thus been greatly simplified using the Second Order Partial Differential Equation (SOPDE) for multi-vector fields verifying Euler equations. These symmetries have been classified naturally according to the construction of the fiber bundle used.  In this work, unlike other works using the analytical method, our geometric model has allowed us firstly to distinguish the angular moments of the gauge field obtained during different transformations while these moments are gathered in a single expression and are obtained during a rotation in the Minkowsky space. Secondly, no conditions are imposed on the Lagrangian of the mechanics with respect to its dependence in time and in qⁱ, the currents obtained naturally from the transformations are respectively the energy and the momentum of the system.

Keywords: conservation laws, field theories, multisymplectic geometry, relativistic mechanics

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Authors: Claudia Borges Colcerniani

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The paper is about a qualitative study whose main objective is to know how labor, as a Brazilian constitutionally established social right, can promote the social inclusion of female heads of one-parent families in a situation of poverty. The participants are six women, mothers, and workers living in Rocinha, a community located in the city of Rio de Janeiro, RJ, Brazil. According to the Brazilian Federal Constitution, social rights are based on the idea that socioeconomic inequalities should not limit or eliminate civil and political rights. In this perspective, labor can be a way to reach social justice, according to the theory of Nancy Fraser, the theoretical framework adopted in this research. Data were collected through socioeconomic questionnaires, and semi-structured interviews applied individually. The results analysis was made using the content analysis/categorical content analysis, according to Bardin's perspective. The results indicate that labor (as a social right) is considered, by the interviewed women, as an opportunity for social inclusion when there are the characteristics of the formality in accordance with the international labor regulations (Decent Work - International Labour Organization/United Nations).

Keywords: female labor, social justice, inclusion, women, decent work

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Authors: Sabita Mahapatra

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‘Going green’ has been an emerging issue worldwide driving companies to continuously enhance their green capabilities and implement innovative green practices to protect the environment and improve business performance. Green has become a contemporary business environmental issue. The resource advantage theory is adopted in the present study to observe the impact of marketing orientation and green innovation practices on environmental and firm’s performance. The small and medium firms compared to large firms have different approach towards market orientation as a strategic tool. The present study proposes a conceptual framework regarding the impact of market orientation on environmental and firm’s performance through green innovation practices in the context of small and medium scale industries (SMEs). The propositions developed in the present paper would provide scope for future research study to validate the conceptual framework in the emerging economy like India.

Keywords: market orientation, green innovation practices, environment performance, corporate performance, emerging market

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Authors: Sadia Arshad

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The new coronavirus disease or COVID-19 still poses an alarming situation around the world. Modeling based on the derivative of fractional order is relatively important to capture real-world problems and to analyze the realistic situation of the proposed model. Weproposed a mathematical model for the investigation of COVID-19 dynamics in a generalized fractional framework. The new model is formulated in the Caputo sense and employs a nonlinear time-varying transmission rate. The existence and uniqueness solutions of the fractional order derivative have been studied using the fixed-point theory. The associated dynamical behaviors are discussed in terms of equilibrium, stability, and basic reproduction number. For the purpose of numerical implementation, an effcient approximation scheme is also employed to solve the fractional COVID-19 model. Numerical simulations are reported for various fractional orders, and simulation results are compared with a real case of COVID-19 pandemic. According to the comparative results with real data, we find the best value of fractional orderand justify the use of the fractional concept in the mathematical modelling, for the new fractional modelsimulates the reality more accurately than the other classical frameworks.

Keywords: fractional calculus, modeling, stability, numerical solution

Procedia PDF Downloads 86