Search results for: acceptance of psychological variables

Authors: Yijun Shao, Yan Cheng, Rashmee U. Shah, Charlene R. Weir, Bruce E. Bray, Qing Zeng-Treitler

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Deep neural network (DNN) models are being explored in the clinical domain, following the recent success in other domains such as image recognition. For clinical adoption, outcome prediction models require explanation, but due to the multiple non-linear inner transformations, DNN models are viewed by many as a black box. In this study, we developed a deep neural network model for predicting 1-year mortality of patients who underwent major cardio vascular procedures (MCVPs), using temporal image representation of past medical history as input. The dataset was obtained from the electronic medical data warehouse administered by Veteran Affairs Information and Computing Infrastructure (VINCI). We identified 21,355 veterans who had their first MCVP in 2014. Features for prediction included demographics, diagnoses, procedures, medication orders, hospitalizations, and frailty measures extracted from clinical notes. Temporal variables were created based on the patient history data in the 2-year window prior to the index MCVP. A temporal image was created based on these variables for each individual patient. To generate the explanation for the DNN model, we defined a new concept called impact score, based on the presence/value of clinical conditions’ impact on the predicted outcome. Like (log) odds ratio reported by the logistic regression (LR) model, impact scores are continuous variables intended to shed light on the black box model. For comparison, a logistic regression model was fitted on the same dataset. In our cohort, about 6.8% of patients died within one year. The prediction of the DNN model achieved an area under the curve (AUC) of 78.5% while the LR model achieved an AUC of 74.6%. A strong but not perfect correlation was found between the aggregated impact scores and the log odds ratios (Spearman’s rho = 0.74), which helped validate our explanation.

Keywords: deep neural network, temporal data, prediction, frailty, logistic regression model

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Authors: Aliyu Uthman Abdulkadir

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Insurgent reports in Nigeria have become a recurring focus in the media due to the significance of language choices. This paper investigates these reports with the aim of identifying various pragmatic practices and exploring the role of the media in shaping public perception of insurgency. Three Nigerian newspapers The Punch, This Day, and The Guardian were selected for analysis between December 2022 and January 2023. Five media reports were examined to uncover the pragmatic functions embedded in the discourse. The study reveals that the media employ implicit acts such as exposing, sensitizing, informing, castigating, reprimanding, and shaming to depict insurgent activities in the country. The analysis also highlights how the use of presupposed ideologies enhances the delivery and acceptance of information related to insurgent actions. The study concludes that the media's portrayal of insurgency is often biased, as reflected in the data analysis.

Keywords: insurgency, pragmatic acts, bias, framing, ideoligies

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Authors: Joel Podgorski, Manouchehr Amini, Annette Johnson, Michael Berg

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One-third of the world’s population relies on groundwater for its drinking water. Natural geogenic arsenic and fluoride contaminate ~10% of wells. Prolonged exposure to high levels of arsenic can result in various internal cancers, while high levels of fluoride are responsible for the development of dental and crippling skeletal fluorosis. In poor urban and rural settings, the provision of drinking water free of geogenic contamination can be a major challenge. In order to efficiently apply limited resources in the testing of wells, water resource managers need to know where geogenically contaminated groundwater is likely to occur. The Groundwater Assessment Platform (GAP) fulfills this need by providing state-of-the-art global arsenic and fluoride contamination hazard maps as well as enabling users to create their own groundwater quality models. The global risk models were produced by logistic regression of arsenic and fluoride measurements using predictor variables of various soil, geological and climate parameters. The maps display the probability of encountering concentrations of arsenic or fluoride exceeding the World Health Organization’s (WHO) stipulated concentration limits of 10 µg/L or 1.5 mg/L, respectively. In addition to a reconsideration of the relevant geochemical settings, these second-generation maps represent a great improvement over the previous risk maps due to a significant increase in data quantity and resolution. For example, there is a 10-fold increase in the number of measured data points, and the resolution of predictor variables is generally 60 times greater. These same predictor variable datasets are available on the GAP platform for visualization as well as for use with a modeling tool. The latter requires that users upload their own concentration measurements and select the predictor variables that they wish to incorporate in their models. In addition, users can upload additional predictor variable datasets either as features or coverages. Such models can represent an improvement over the global models already supplied, since (a) users may be able to use their own, more detailed datasets of measured concentrations and (b) the various processes leading to arsenic and fluoride groundwater contamination can be isolated more effectively on a smaller scale, thereby resulting in a more accurate model. All maps, including user-created risk models, can be downloaded as PDFs. There is also the option to share data in a secure environment as well as the possibility to collaborate in a secure environment through the creation of communities. In summary, GAP provides users with the means to reliably and efficiently produce models specific to their region of interest by making available the latest datasets of predictor variables along with the necessary modeling infrastructure.

Keywords: arsenic, fluoride, groundwater contamination, logistic regression

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Authors: Alfred Quarcoo

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The main purpose of this paper is to examine the causal relationship between energy consumption and economic growth in Sub-Saharan Africa using panel data techniques. An annual data on energy consumption and Economic Growth (proxied by real gross domestic product per capita) spanning from 1990 to 2016 from the World bank index database was used. The results of the Augmented Dickey–Fuller unit root test shows that the series for all countries are not stationary at levels. However, the log of economic growth in Benin and Congo become stationary after taking the differences of the data, and log of energy consumption become stationary for all countries and Log of economic growth in Kenya and Zimbabwe were found to be stationary after taking the second differences of the panel series. The findings of the Johansen cointegration test demonstrate that the variables Log of Energy Consumption and Log of economic growth are not co-integrated for the cases of Kenya and Zimbabwe, so no long-run relationship between the variables were established in any country. The Granger causality test indicates that there is a unidirectional causality running from energy use to economic growth in Kenya and no causal linkage between Energy consumption and economic growth in Benin, Congo and Zimbabwe.

Keywords: Cointegration, Granger Causality, Sub-Sahara Africa, World Bank Development Indicators

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Authors: Sendy Ghirardi, Pau Rausell Köster

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The European Commission increasingly pushes cultural policies towards social outcomes and local and regional authorities also call for culture-driven strategies for local development and prosperity and therefore, the measurement of cultural participation becomes increasingly more significant for evidence-based policy-making processes. Cultural participation involves various kinds of social and economic spillovers that combine social and economic objectives of value creation, including social sustainability and respect for human values. Traditionally, from the economic perspective, cultural consumption is measured by the value of financial transactions in purchasing, subscribing to, or renting cultural equipment and content, addressing the market value of cultural products and services. The main sources of data are the household spending survey and merchandise trade survey, among others. However, what characterizes the cultural consumption is that it is linked with the hedonistic and affective dimension rather than the utilitarian one. In fact, nowadays, more and more attention is being paid to the social and psychological dimensions of culture. The aim of this work is to present a comprehensive approach to measure the impacts of cultural participation and cultural users’ behaviour, combining both socio-psychological and economic approaches. The model combines contingent evaluation techniques with the individual characteristic and perception analysis of the cultural experiences to evaluate the cognitive, aesthetic, emotive and social impacts of cultural participation. To investigate the comprehensive approach to measure the impact of the cultural events on individuals, the research has been designed on the basis of prior theoretical development. A deep literature methodology has been done to develop the theoretical model applied to the web platform to measure the impacts of cultural experience on individuals. The developed framework aims to become a democratic tool for evaluating the services that cultural or policy institutions can adopt through the use of an interacting platform that produces big data benefiting academia, cultural management and policies. The Au Culture is a prototype based on an application that can be used on mobile phones or any other digital platform. The development of the AU Culture Platform has been funded by the Valencian Innovation Agency (Government of the Region of Valencia) and it is part of the Horizon 2020 project MESOC.

Keywords: comprehensive approach, cultural participation, economic dimension, socio-psychological dimension

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Authors: Ujunma Nnenna Egbuawa

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Rape or sexual assault is a hideous crime of violence done predominantly to women and occasionally to men. In institutions of higher learning, it’s mostly experienced within or outside the campus environment due to students who are from different backgrounds socially. These students also have been imbibed with conflicting ethical standards, thus act both morally and amoral with respect to their sexual urges. The most affected among these are the female students who live outside the campus environment that is suitable for any immoral activity. These female students that are victims of rape hardly would want to be identified and this has left them as habitual prey to the unsuspecting predators. The socio-cultural setting has also been a contributory factor to the psychological and physical damage these victims face throughout their time of study as female rape victims. This is an empirical study designed to elicit information from students of Federal Polytechnic Nekede Owerri Imo State Nigeria on whether they have been sexually assaulted or raped and how they handled it thereafter. This institution was used as a case study because the provost of this tertiary institution is a woman whose name is Dr( Mrs ) C.U Njoku who has made consented efforts to ensure these rape victims rise above the social stigma associated with it. This rector has also put in some measures to bring about a decline in cases of rape within and outside the campus environment. She also granted the researcher an oral interview on how she has been able to achieve these and the challenges she hitherto faced in the process. Three research questions and a hypothesis guided the study. Samples of 119 students were used and stratification was done for sex, age and the academic level of the students. 14 item questionnaires were used and data generated from the survey were analyzed using percentages. This workshop would engage the participants by investigating some courses that may help in declining the rate of rape cases within a campus. Also, necessary measures that would be taken to help in sensitizing the tertiary institutions in areas that can aid the healing procedures of these victims. The need also for guidance and counseling unit is also a necessity for the psychological survival of these rape victims. As a result, the participants would gain an increased awareness of the influence of rape and sexual assault on campus. There ought to be a paradigm shift in institutions of higher learning in policies, administrative decisions and introduction of courses that will uplift ethical standards in order to bring about a change both locally and globally.

Keywords: institutions, psychological, sexual assault, socio-cultural

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Authors: Aziza S. Al Adhoobi, Amna Al Ruheili, Saud M. Al Jufaili

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This study investigates the potential effects of climate change on the habitat suitability of two Aphaniops species (Teleostei: Aphaniidae) found in the Oman Mountains and the Southwestern Arabian Coast. Aphaniops kruppi, an endemic species, is found in various water bodies such as wadis, springs, aflaj, spring-fed streams, and some coastal backwaters. Aphaniops stoliczkanus, on the other hand, inhabits brackish and freshwater habitats, particularly in the lower parts of wadies and aflaj, and exhibits euryhaline characteristics. Using Maximum Entropy Modeling (MaxEnt) in conjunction with ArcGIS (10.8.2) and CHELSA bioclimatic variables, topographic indices, and other pertinent environmental factors, the study modeled the potential impacts of climate change based on three Representative Concentration Pathways (RCPs 2.6, 7.0, 8.5) for the periods 2011-2040, 2041-2070, and 2071-2100. The model demonstrated exceptional predictive accuracy, achieving AUC values of 0.992 for A. kruppi and 0.983 for A. stoliczkanus. For A. kruppi, the most influential variables were the mean monthly climate moisture index (Cmi_m), the mean diurnal range (Bio2), and the sediment transport index (STI), accounting for 39.9%, 18.3%, and 8.4%, respectively. As for A. stoliczkanus, the key variables were the sediment transport index (STI), stream power index (SPI), and precipitation of the coldest quarter (Bio19), contributing 31%, 20.2%, and 13.3%, respectively. A. kruppi showed an increase in habitat suitability, especially in low and medium suitability areas. By 2071-2100, high suitability areas increased slightly by 0.05% under RCP 2.6, but declined by -0.02% and -0.04% under RCP 7.0 and 8.5, respectively. A. stoliczkanus exhibited a broader range of responses. Under RCP 2.6, all suitability categories increased by 2071-2100, with high suitability areas increasing by 0.01%. However, low and medium suitability areas showed mixed trends under RCP 7.0 and 8.5, with declines of -0.17% and -0.16%, respectively. The study highlights that climatic and topographical factors significantly influence the habitat suitability of Aphaniops species in Oman. Therefore, species-specific conservation strategies are crucial to address the impacts of climate change.

Keywords: Aphaniops kruppi, Aphaniops stoliczkanus, Climate change, Habitat suitability, MaxEnt

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Authors: Sylvia Villarreal, Edna Bravo

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Knowledge management focuses on coordinating technologies, people, processes, and structures to generate a competitive advantage and considering that networks are perceived as mechanisms for knowledge creation and transfer, this research presents the stages and practices related to the creation of knowledge networks. The methodology started with a literature review adapted from the systematic literature review (SLR). The descriptive analysis includes variables such as approach (conceptual or practical), industry, knowledge management processes and mythologies (qualitative or quantitative), etc. The content analysis includes identification of reference cases. These cases were characterized based on variables as scope, creation goal, years, network approach, actors and creation methodology. It was possible to do a comparative analysis to determinate similarities and differences in these cases documented in knowledge network scientific literature. Consequently, it was shown that even the need and impact of knowledge networks in organizations, the initial guidelines for their creation are not documented, so there is not a guide of good practices and lessons learned. The reference cases are from industries as energy, education, creative, automotive and textile. Their common points are the human approach; it is oriented to interactions to facilitate the appropriation of knowledge, explicit and tacit. The stages of every case are analyzed to propose the main successful elements.

Keywords: creation, knowledge management, network, stages

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Authors: Khadija Mushtaq, Muhammad Umar

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The research aims to study the association between job satisfaction, motivation and the five factors of organizational citizenship behavior (i.e. Altruism, Conscientiousness, Sportsmanship, Courtesy and Civic virtue) among Public Sector Employees in Pakistan.In this research Structure Equation Modeling with confirmatory factor analysis was used to test the relationship between two independent and five dependent variables. Data was collected through questionnaire survey from 152 Public Servants Working in Gujrat District-Pakistan in different capacities. Stratified Random Sampling Technique was used to conduct this survey. The results of the study indicate that five factors of OCB have positive significant relation with both motivation and job satisfaction except the relationship of Civic Virtue with Motivation.The research findings implicate that factors other than motivation and job satisfaction may also affect OCB. Likewise, all the five factors of OCB may not be present in all populations. Thus, Managers must concentrate on increasing motivation and job satisfaction to increase OCB. Furthermore, the present research gives a direction to future researchers to use more independent variables (e.g. Culture, leadership, workplace environment, various job attitudes, types of motivation, etc.) on different types of populations with larger sample size in order to find the reasons behind insignificant relationship of civic virtue with Motivation in the research in hand and to generalize the tested model.

Keywords: five factors of organizational citizenship behavior (OCB), motivation, job satisfaction, public sector employees in Pakistan

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Authors: Nurul Yusnita

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Many studies have been developed to help the students to get good achievement in English learning. They can be from the teaching method or psychological ones. One of the psychological studies in educational research is learning style. In some ways, learning style can affect the achievement of the students. This study aimed to examine 4 (four) learning styles and their relations to English achievement among the students learning English in Language Training Center of Universitas Muhammadiyah Yogyakarta (LTC UMY). The method of this study was descriptive analytical. The sample consisted of 39 Accounting students in LTC UMY. The data was collected through questionnaires with Likert-scale. The achievement was obtained from the grade of the students. To analyze the questionnaires and to see the relation between the learning styles and the student achievement, SPSS statistical software of correlational analysis was used. The result showed that both visual and auditory had the same percentage of 35.9% (14 students). 3 students (7.7%) had kinaesthetic learning style and 8 students (20.5%) had visual and auditory ones. Meanwhile, there were 5 students (12.8%) who had visual learning style could increase their grades. Only 1 student (2.5%) who had visual and auditory could improve his grade. Besides grade increase, there were also grade decrease. Students with visual, auditory, visual and auditory, and kinaesthetic learning styles were 3 students (7.7%), 5 students (12%), 4 students (10.2%) and 1 student (2.5%) respectively. In conclusion, there was no significant relationship between learning style and English achievement. Most of the good achievers were the students with visual and auditory learning styles and most of them preferred visual method. The implication is the teachers and material designers could improve their method through visual things to achieve effective English teaching learning.

Keywords: accounting students, English achievement, language training centre, learning styles

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Authors: Fatemeh Rouhi, Hadi Nassiri

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Earning forecast is a key element in economic decisions but there are some situations, such as conflicts of interest in financial reporting, complexity and lack of direct access to information has led to the phenomenon of information asymmetry among individuals within the organization and external investors and creditors that appear. The adverse selection and moral hazard in the investor's decision and allows direct assessment of the difficulties associated with data by users makes. In this regard, the role of trustees in corporate governance disclosure is crystallized that includes controls and procedures to ensure the lack of movement in the interests of the company's management and move in the direction of maximizing shareholder and company value. Therefore, the earning forecast of companies in the capital market and the need to identify factors influencing this study was an attempt to make relationship between moral hazard and corporate governance with earning forecast quality companies operating in the capital market and its impact on Earnings Forecasts quality by the company to be established. Getting inspiring from the theoretical basis of research, two main hypotheses and sub-hypotheses are presented in this study, which have been examined on the basis of available models, and with the use of Panel-Data method, and at the end, the conclusion has been made at the assurance level of 95% according to the meaningfulness of the model and each independent variable. In examining the models, firstly, Chow Test was used to specify either Panel Data method should be used or Pooled method. Following that Housman Test was applied to make use of Random Effects or Fixed Effects. Findings of the study show because most of the variables are positively associated with moral hazard with earnings forecasts quality, with increasing moral hazard, earning forecast quality companies listed on the Tehran Stock Exchange is increasing. Among the variables related to corporate governance, board independence variables have a significant relationship with earnings forecast accuracy and earnings forecast bias but the relationship between board size and earnings forecast quality is not statistically significant.

Keywords: corporate governance, earning forecast quality, moral hazard, financial sciences

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Authors: Raka Aldy Nugraha, Kiwah Andanni, Aditya Indra Pratama, Aswin Guntara

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Background: Torus palatinus is a bony protuberance in the hard palate. Sex and race are considered as influencing factors for the development of torus palatinus. Hence, the objective of this study was to determine the prevalence and characteristics of torus palatinus and its correlation with sex and ethnicity among Western Indonesian Population. Methods: We conducted a descriptive and analytical study employing cross-sectional design in 274 new students of Universitas Indonesia. Data were collected by using consecutive sampling method through questionnaire-filling and direct oral examination. Subject with racial background other than indigenous Indonesian Mongol were excluded from this study. Data were statistically analyzed using chi square test for categorical variables whereas logistic regression model was employed to assess the correlation between variables of interest with prevalence of torus palatinus. Results: Torus palatinus were found in 212 subjects (77.4%), mostly small in size (< 3 mm) and single in number, with percentage of 50.5% and 90.6%, respectively. The prevalence of torus palatinus were significantly higher in women (OR 2.88; 95% CI: 1.53-5.39; p = 0.001), dominated by medium-sized and single tori. There was no significant correlation between ethnicity and the occurrence of torus palatinus among Western Indonesian population. Conclusion: Torus palatinus was prevalent among Western Indonesian population. It showed significant positive correlation with sex, but not with ethnicity.

Keywords: characteristic, ethnicity, Indonesia, mongoloid, prevalence, sex, Torus palatinus

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Authors: Ali Ates, Sadık Ata, Kevser Dincer

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In this study, performance of the driver seat‘s localized cooling and heating in a standard car air conditioning system was experimentally investigated and modeled with Rule-Based Mamdani-Type Fuzzy (RBMTF) modeling technique. Climate function at automobile is an important variable for thermal comfort. In the experimental study localized heating and cooling performances have been examined with the aid of a mechanism established to a vehicle. The equipment’s used in the experimental setup/mechanism have been provided and assembled. During the measurement, the status of the performance level has been determined. Input parameters revolutions per minute and time; output parameters car seat cooling temperature, car back cooling temperature, car seat heating temperature, car back heating temperature were described by RBMTF if-the rules. Numerical parameters of input and output variables were fuzzificated as linguistic variables: Very Very Low (L1), Very Low (L2), Low (L3), Negative Medium (L4), Medium (L5), High (L7), Very High (L8) and Very Very High (L9) linguistic classes. The comparison between experimental data and RBMTF is done by using statistical methods like absolute fraction of variance (R2). The actual values and RBMTF results indicated that RBMTF could be successfully used in standard car air conditioning system.

Keywords: air conditioning system, cooling-heating, RMBTF modelling, car seat

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Authors: S. Bagur, S. Verger, B. Mut

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Early childhood intervention (ECI) is understood as the set of interventions aimed at the child population with developmental disorders or disabilities from 0 to 6 years of age, the family, and the environment. Under the principles of family-centred practices, the members of the family nucleus are direct agents of intervention. Thus, the multidisciplinary team of professionals should work to improve family empowerment and the level of parenting skills. The aim of the present study is to analyse descriptively and differentially the level of parenting skills and family empowerment of parents using ECI services during the foster care phase. There were 135 families participating in the study. Three questionnaires were completed. The results show that the employment situation, the age of the child receiving an intervention, and the number of children in the family nucleus or the professional carrying out the intervention are variables that have a differential impact on different items of empowerment and parenting skills. The results are discussed and future lines of research are proposed, with the understanding that the initial analysis of the variables of empowerment and parenting skills may be predictors for the improvement of child development and family well-being. In addition, it is proposed to identify and analyse professional training in order to be able to adapt early care practices without depending on the discipline of the professional of reference.

Keywords: developmental disabilities, early childhood intervention, family empowerment, parenting skills

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Authors: Sepehr Moradi, Mehdi Asadi Rad

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The aim of this study is to evaluate and compare chest weight of pure and mixed races Kabood 30-day Pigeons to investigate about their sex, race, and some auxiliary variables. In this paper, 62 pieces of pigeons as 31 male and female pairs with equal age are studied randomly. A natural incubation was done from each pair. All produced chickens were slaughtered at 30 days age after 12 hours hunger. Then their chests were weighted by a scale with one gram precision. A covariance analysis was used since there were many auxiliary variables and unequal observations. SAS software was used for statistical analysis. Mean weight of chests in pure race (Kabood-Kabood) with 8 records, 123.8±32.3g and mixed races of Kabood-Namebar, Kabood-Parvazy, Kabood-Tizpar, Namebar-Kabood, Tizpar-Kabood, and Parvazi-Kabood with 8, 8, 6, 12, 10, and 10 records were 139.4±23.5, 7/122±23.8, 124.7±30.1, 50.3±29.3, 51.4±26.4, and 137±28.6 gr, respectively. Mean weight of 30-day chests in male and female sex were 87.3±2.5 and 82.7±2.6g, respectively. Difference chest weight of 30-day chests of Kabood-Kabood race with Kabood-Namebar, Kabood-Parvazi, Tizpar-Kabood, Kabood-Tizpar, Namebar-Kabood and Parvazi-Kabood mixed races was not significant. Effect of sex was also significant in 5% level (P<0.05), but mutual effect of sex and race was not significant. Auxiliary variable of father weight was significant in 1% level (p < 0.01), but auxiliary variable of mother weight was not significant. The results showed that most and least weights belonged to Kabood-Namebar and Namebar-Kabood.

Keywords: squab, Kabood race, 30-day chest weight, pigeons

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Authors: Jason Salim, Zhouyang Lu

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Private sector involvement in Public Private Partnership (PPP) projects may raise public suspicion, as PPP is often mistaken as merely a partnership between private and government agencies without consideration for greater “public” (community). This public marginalization is crucial to be dealt with because undermining opinion of majority may cause problems such as protests and/ or low demand. Game theory approach applied in this paper shows that probability of public acceptance towards a project is affected by overall public’s perception on Private sectors’ possible profit accumulation from the project. On the contrary, goodwill of the government and private coalition alone is not enough to minimize the probability of public opposition towards a PPP project. Additionally, the threat of loss or damage raised from public opposition does not affect the profit-maximization behavior of Private sectors.

Keywords: community satisfaction, game theory, non-cooperative, PPP, public policy

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Authors: Zhaojun Wang, Zongdi Sun, Qinqin Cui, Xingwan Ren

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Based on multivariate statistical analysis theory, this paper uses the principal component analysis method, Mahalanobis distance analysis method and fitting method to establish the photovoltaic health model to evaluate the health of photovoltaic panels. First of all, according to weather conditions, the photovoltaic panel variable data are classified into five categories: sunny, cloudy, rainy, foggy, overcast. The health of photovoltaic panels in these five types of weather is studied. Secondly, a scatterplot of the relationship between the amount of electricity produced by each kind of weather and other variables was plotted. It was found that the amount of electricity generated by photovoltaic panels has a significant nonlinear relationship with time. The fitting method was used to fit the relationship between the amount of weather generated and the time, and the nonlinear equation was obtained. Then, using the principal component analysis method to analyze the independent variables under five kinds of weather conditions, according to the Kaiser-Meyer-Olkin test, it was found that three types of weather such as overcast, foggy, and sunny meet the conditions for factor analysis, while cloudy and rainy weather do not satisfy the conditions for factor analysis. Therefore, through the principal component analysis method, the main components of overcast weather are temperature, AQI, and pm2.5. The main component of foggy weather is temperature, and the main components of sunny weather are temperature, AQI, and pm2.5. Cloudy and rainy weather require analysis of all of their variables, namely temperature, AQI, pm2.5, solar radiation intensity and time. Finally, taking the variable values in sunny weather as observed values, taking the main components of cloudy, foggy, overcast and rainy weather as sample data, the Mahalanobis distances between observed value and these sample values are obtained. A comparative analysis was carried out to compare the degree of deviation of the Mahalanobis distance to determine the health of the photovoltaic panels under different weather conditions. It was found that the weather conditions in which the Mahalanobis distance fluctuations ranged from small to large were: foggy, cloudy, overcast and rainy.

Keywords: fitting, principal component analysis, Mahalanobis distance, SPSS, MATLAB

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Authors: Zbigniew Izdebski, Alicja Kozakiewicz, Maciej Białorudzki, Joanna Mazur

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Work is an extremely important part of everyone's life and affects functioning in daily life. Healthcare workers (HCW) are suffering from negative actions in and out of the workplace, such as harassment, abuse, long working hours, mental suffering, exhaustion, and professional burnout. Staff burnout is detrimental not only in terms of individual employees but also to working with patients and to the healthcare institution as a whole. The purpose of this study was to explore the level of professional burnout among HCW working in medical institutions during the COVID-19 pandemic in Poland. The extent to which selected sociodemographic factors and perceived stress increase the risk of professional burnout was assessed. In addition, the frequency of use of professional psychological help and less formal support groups by HCW in relation to the level of professional burnout was presented. The survey was conducted as part of a larger project on the humanization of medicine and clinical communication from February-April 2022. This study used a self-administered online survey (CAWI) technique and PAPI (pen and paper interview) technique. The BAT-12 scale was used to measure burnout, the PSS-4 scale was used to measure stress, and questions formulated by the research team were also used. For the purpose of analysis, the sample was limited to 2196 HCWs who worked on a daily basis with patients during the COVID-19 pandemic. Frequency distributions were analyzed, and multivariate logistic regression was performed. The mean scores (scores) of job burnout as measured by the BAT-12 scale ranged among the professional groups from 2.15(0.69) to 2.30 (0.69) and remained highest for the nurses' group. The groups differed significantly in levels of burnout (chi-sq=17.719; d.f.=8; p<0.023). In the final model, raised stress most likely increased the risk of burnout (OR=3.88; 95%CI <3.13-3.81>; p<0,001). Other significant predictors of burnout included: traumatic work-related experience (OR=1.91, p<0.001), mobbing (OR=1.83, p<0.001), and a higher workload than before the pandemic (OR=1.41, p=0.002). Only 7% of respondents decided to use various forms of psychological support during the pandemic. HCW experiences challenges in dealing with an unpredictable pandemic. Limited preparedness can lead to physical and psychological problems such as high-stress levels, anxiety, fear, helplessness, hopelessness, anger and stigma. The workload can lead to professional burnout, as well as threaten patient safety.

Keywords: burnout, work, healthcare, healthcare worker, stress

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Authors: Amany Ragab, Nashwa Khairat Abousamra, Omayma Saleh, Asmaa Higazy

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Insulin resistance syndrome has been shown to be associated with many coagulation and fibrinolytic proteins and these associations suggest that some coagulation and fibrinolytic proteins have a role in atherothrombotic disorders. This study was conducted to determine the levels of some of the haemostatic parameters in subjects having metabolic syndrome and to correlate these values with the anthropometric and metabolic variables associated with this syndrome. The study included 46 obese non diabetic subjects of whom 28 subjects(group1) fulfilled the ATP III criteria of the metabolic syndrome and 18 subjects (group2) did not have metabolic syndrome as well as 14 lean subjects (group 3) of matched age and sex as a control group. Clinical and laboratory evaluation of the study groups stressed on anthropometric measurements (weight, height, body mass index, waist circumference, and sagittal abdominal diameter), blood pressure, and laboratory measurements of fasting plasma glucose, fasting insulin, serum lipids, tissue plasminogen activator (t-PA), antithrombin III activity (ATIII), protein C and von Willebrand factor (vWf) antigen. There was significant increase in the concentrations of t-PA and vWf antigens in subjects having metabolic syndrome (group 1) in comparison to the other groups while there were non-significant changes in the levels of protein C antigen and AT III activity. Both t-PA and vWf showed significant correlation with HOMA-IR as a measure of insulin sensitivity. The t-PA showed also significant correlation with most of the variables of metabolic syndrome including waist circumference, BMI, systolic blood pressure, fasting plasma glucose, fasting insulin, and HDL cholesterol. On the other hand, vWf showed significant correlations with fasting plasma glucose, fasting insulin and sagital abdominal diameter, with non-significant correlations with the other variables. Haemostatic and fibrinolytic parameters should be included in the features and characterization of the insulin resistance syndrome. t-PA and vWf antigens concentrations were increased in subjects with metabolic syndrome and correlated with the HOMA-IR measure of insulin sensitivity. Taking into consideration that both t-PA and vWf are mainly released from vascular endothelium, these findings could be an indicator of endothelial dysfunction in that group of subjects.

Keywords: insulin resistance, obesity, metabolic syndrome, coagulation

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Authors: Elżbieta Turska

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Introduction: One of the most difficult times in a person’s life is adolescence. The experiences in this period may shape the future life of this person to a large extent. This is the reason why many young people experience sadness, dejection, hopelessness, sense of worthlessness, as well as losing interest in various activities and social relationships, all of which are often classified as mood disorders. As many as 15-40% adolescents experience depressed moods and for most of them they resolve and are not carried into adulthood. However, (5-6%) of those affected by mood disorders develop the depressive syndrome and as many as (1-3%) develop full-blown clinical depression. Materials: A large questionnaire was given to 2508 students, aged 13–16 years old, and one of its parts was the Burns checklist, i.e. the standard test for identifying depressed mood. The questionnaire asked about many aspects of the student’s life, it included a total of 53 questions, most of which had subquestions. It is important to note that the data suffered from many problems, the most important of which were missing data and collinearity. Aim: In order to identify the correlates of mood disorders we built predictive models which were then trained and validated. Our aim was not to be able to predict which students suffer from mood disorders but rather to explore the factors influencing mood disorders. Methods: The problems with data described above practically excluded using all classical statistical methods. For this reason, we attempted to use the following Artificial Intelligence (AI) methods: classification trees with surrogate variables, random forests and xgboost. All analyses were carried out with the use of the mlr package for the R programming language. Resuts: The predictive model built by classification trees algorithm outperformed the other algorithms by a large margin. As a result, we were able to rank the variables (questions and subquestions from the questionnaire) from the most to least influential as far as protection against mood disorder is concerned. Thirteen out of twenty most important variables reflect the relationships with parents. This seems to be a really significant result both from the cognitive point of view and also from the practical point of view, i.e. as far as interventions to correct mood disorders are concerned.

Keywords: mood disorders, adolescents, family, artificial intelligence

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Authors: Joseph Thomas Eghwerido, Julian I. Mbegbu

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In modelling environment processes, we apply multidisciplinary knowledge to explain, explore and predict the Earth's response to natural human-induced environmental changes. Thus, the analysis of spatial-time ecological and environmental studies, the spatial parameters of interest are always heterogeneous. This often negates the assumption of stationarity. Hence, the dispersion of the transportation of atmospheric pollutants, landscape or topographic effect, weather patterns depends on a good estimate of spatial covariance. The generalized linear mixed model, although linear in the expected value parameters, its likelihood varies nonlinearly as a function of the covariance parameters. As a consequence, computing estimates for a linear mixed model requires the iterative solution of a system of simultaneous nonlinear equations. In other to predict the variables at unsampled locations, we need to know the estimate of the present sampled variables. The geostatistical methods for solving this spatial problem assume covariance stationarity (locally defined covariance) and uniform in space; which is not apparently valid because spatial processes often exhibit nonstationary covariance. Hence, they have globally defined covariance. We shall consider different existing methods of solutions of spatial covariance of a space-time processes at unsampled locations. This stationary covariance changes with locations for multiple time set with some asymptotic properties.

Keywords: parametric, nonstationary, Kernel, Kriging

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Authors: Shahida Mohd Sharif, Norsidah Ujang

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Recent research has shown that many of the urban population in Kuala Lumpur, especially from the lower-income group, suffer from socio-psychological problems. They are reported as experiencing anxiety, depression, and stress, which is made worst by the recent COVID-19 pandemic. Much of the population was forced to observe the Movement Control Order (MCO), which is part of pandemic mitigation measures, pushing them to live in isolation as the new normal. The study finds the need to strategize for a better approach to help these people coping with the socio-psychological condition, especially the population from the lower-income group. In Kuala Lumpur, as part of the Local Agenda 21 programme, the Kuala Lumpur City Hall has introduced Green Initiative: Urban Farming, which among the approaches is the community garden. The local authority promotes the engagement to be capable of improving the social environment of the participants. Research has demonstrated that social interaction within community gardens can help the members improve their socio-psychological conditions. Therefore, the study explores the residents’ experience from low-cost flats participating in the community gardening initiative from a social attachment perspective. The study will utilise semi-structured interviews to collect the participants’ experience with community gardening and how the social interaction exchange between the members' forms and develop their ties and trust. For a context, the low-cost flats are part of the government social housing program (Program Perumahan Rakyat dan Perumahan Awam). Meanwhile, the community gardening initiative (Projek Kebun Kejiranan Bandar LA21 KL) is part of the local authority initiative to address the participants’ social, environmental, and economic issues. The study will conduct thematic analysis on the collected data and use the ATLAS.ti software for data organization and management purposes. The findings could help other researchers and stakeholders understand the social interaction experience within community gardens and its relation to ties and trusts. The findings could shed some light on how the participants could improve their social environment, and its report could provide the local authority with evidence-based documentation.

Keywords: community gardening participation, lower-income population, social attachment, social interaction

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Authors: S. Umar, B. F. Umar

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This study was conducted at Giron Masa village, located 30 km from Yauri town. The study determines the socio-economic factors influencing the use of coping strategies among farmers and herders during post-conflict situation. Simple random sampling was employed to select one hundred respondents (50 farmers and 50 herders) from the study area. Logistic regression analysis (LR) was used to ascertain the socioeconomic variables that influenced the use of the coping strategies. The results of the study shows that age, income, family size and farming experience were individually significant and thus influenced the use of POCS by farmers. Annual income and production system influenced the use of POCS by herders. Age, farm size and farming experience were found to be individually significant in influencing the use of EOCS among farmers. Specifically, years of occupation experience among the herders increased the use of emotion oriented coping strategies among herders. The use of SSCS among farmers was influenced by educational level; farm size and farming experience, while the variables are not collectively significant in influencing the use of SSCS among the herders. The research recommends a need to adopt the strategy of community coping to cope with stress.

Keywords: farmers, herders, conflict, coping strategies

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Authors: Selim M. Khan

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Indoor air quality is strongly influenced by the presence of radioactive radon (222Rn) gas. Indeed, exposure to high 222Rn concentrations is unequivocally linked to DNA damage and lung cancer and is a worsening issue in North American and European built environments, having increased over time within newer housing stocks as a function of as yet unclear variables. Indoor air radon concentration can be influenced by a wide range of environmental, structural, and behavioral factors. As some of these factors are quantitative while others are qualitative, no single statistical model can determine indoor radon level precisely while simultaneously considering all these variables across a complex and highly diverse dataset. The ability of AI- machine (deep) learning to simultaneously analyze multiple quantitative and qualitative features makes it suitable to predict radon with a high degree of precision. Using Canadian and Swedish long-term indoor air radon exposure data, we are using artificial deep neural network models with random weights and polynomial statistical models in MATLAB to assess and predict radon health risk to human as a function of geospatial, human behavioral, and built environmental metrics. Our initial artificial neural network with random weights model run by sigmoid activation tested different combinations of variables and showed the highest prediction accuracy (>96%) within the reasonable iterations. Here, we present details of these emerging methods and discuss strengths and weaknesses compared to the traditional artificial neural network and statistical methods commonly used to predict indoor air quality in different countries. We propose an artificial deep neural network with random weights as a highly effective method for assessing and predicting indoor radon.

Keywords: radon, radiation protection, lung cancer, aI-machine deep learnng, risk assessment, risk prediction, Europe, North America

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Authors: Burcu Guvenek, Duygu Baysal Kurt

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The impact of foreign trade on economic growth has been discussed since the Classical Economists. Today, foreign trade has become more important for the country's economy with the increasing globalization. When it comes to foreign trade, policies which may vary from country to country and from time to time as protectionism or free trade are implemented. In general, the positive effect of foreign trade on economic growth is alleged. However, as studies supporting this general acceptance take place in the economics literature, there are also studies in the opposite direction. In this paper, the impact of foreign trade on economic growth will be investigated with the help of panel data analysis. For this research, 24 OECD countries’ GDP and foreign trade data, including the period of 1990 and 2010, will be used.

Keywords: foreign trade, economic growth, OECD countries, panel data analysis

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Authors: Takashi Shimizu, Tomoaki Hashimoto

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A class of implicit systems is known as a more generalized class of systems than a class of explicit systems. To establish a control method for such a generalized class of systems, we adopt model predictive control method which is a kind of optimal feedback control with a performance index that has a moving initial time and terminal time. However, model predictive control method is inapplicable to systems whose all state variables are not exactly known. In other words, model predictive control method is inapplicable to systems with limited measurable states. In fact, it is usual that the state variables of systems are measured through outputs, hence, only limited parts of them can be used directly. It is also usual that output signals are disturbed by process and sensor noises. Hence, it is important to establish a state estimation method for nonlinear implicit systems with taking the process noise and sensor noise into consideration. To this purpose, we apply the model predictive control method and unscented Kalman filter for solving the optimization and estimation problems of nonlinear implicit systems, respectively. The objective of this study is to establish a model predictive control with unscented Kalman filter for nonlinear implicit systems.

Keywords: optimal control, nonlinear systems, state estimation, Kalman filter

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Authors: Morteza Raei Dehaghi, Seyed Mohammad Mirhashemi

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The current study explored the effect of economic development, financial development and institutional quality on environmental destruction in upper-middle income countries during the time period of 1999-2011. The dependent variable is logarithm of carbon dioxide emissions that can be considered as an index for destruction or quality of the environment given to its effects on the environment. Financial development and institutional development variables as well as some control variables were considered. In order to study cross-sectional correlation among the countries under study, Pesaran and Friz test was used. Since the results of both tests show cross-sectional correlation in the countries under study, seemingly unrelated regression method was utilized for model estimation. The results disclosed that Kuznets’ environmental curve hypothesis is confirmed in upper-middle income countries and also, financial development and institutional quality have a significant effect on environmental quality. The results of this study can be considered by policy makers in countries with different income groups to have access to a growth accompanied by improved environmental quality.

Keywords: economic development, environmental destruction, financial development, institutional development, seemingly unrelated regression

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Authors: Eric S. Parilla, Marc Edward Abadilla

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The study aims to determine the effect of awareness of business students towards cryptocurrencies and the readiness of universities and colleges to accept cryptocurrencies as a medium of exchange, considering the mediation of business students’ attitudes. The research used partial least squares structural equation modeling (PLS-SEM) and deployed a questionnaire attuned to the awareness and attitudes of business students towards cryptocurrencies and readiness and compatibility of use in universities and colleges in Ilocos Norte. The output of the investigation revealed that awareness of business students is not correlated to the readiness of universities and colleges, which means that even though students understand cryptocurrencies, it is not an assurance that universities and colleges are ready to accept them as the medium of exchange. The study proposes that training and seminars for business students and professionals should be conducted to expand understanding and acceptance of cryptocurrencies.

Keywords: cryptocurrencies, awareness, readiness, attitudes

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Authors: Addion Nizori, Mursalin, Dharia Renathe, Lavlinesia, Fitry Tafzi

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Tempoyak was made from fermented durian flesh, which very popular among Jambi people Indonesia. This study aims to isolate and identification of bacteria developed during fermentations, determine physical-chemical properties of Tempoyak as the effect of adding salts at various concentration and the sensory evaluations of Tempoyak produced is also evaluated. The predominant microorganisms present in Tempoyak were Lactobacillus bacteria. The results also showed that the level of salts concentration has a significant effect on pH, lactic acid content, however, not has a significant impact on sensory evaluations. The best results were 3% of adding salts with the product properties of pH 3.64, lactic acid content 3.11% and overall acceptance score is 3.41.

Keywords: Tempoyak, fermented foods, salts, sensory

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Authors: Yogesh C. Sharma, A. Seetharaman

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The decision-making process in humans is a complicated system influenced by a variety of intrinsic and extrinsic factors. Human decisions have a ripple effect on subsequent decisions. In this study, the scope of human decision making is limited to employees. In an organisation, a person makes a variety of decisions from the time they are hired to the time they retire. The goal of this research is to identify various elements that influence decision-making. In addition, the environment in which a decision is made is a significant aspect of the decision-making process. Employees in today's workplace use artificial intelligence (AI) systems for automation and decision augmentation. The impact of AI systems on the decision-making process is examined in this study. This research is designed based on a systematic literature review. Based on gaps in the literature, limitations and the scope of future research have been identified. Based on these findings, a research framework has been designed to identify various factors affecting employee decision making. Employee decision making is influenced by technological advancement, data-driven culture, human trust, decision automation-augmentation, and workplace motivation. Hybrid human-AI systems require the development of new skill sets and organisational design. Employee psychological safety and supportive leadership influences overall job satisfaction.

Keywords: employee decision making, artificial intelligence (AI) environment, human trust, technology innovation, psychological safety

Procedia PDF Downloads 108