Search results for: climatic variables

Authors: K. A. Bindu, T. V. Raja, P. M. Rojan, A. Siby

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The multivariate path coefficient approach was employed to study the effects of various production and reproduction traits on the slaughter body weight of rabbits. Information on 562 rabbits maintained at the university rabbit farm attached to the Centre for Advanced Studies in Animal Genetics, and Breeding, Kerala Veterinary and Animal Sciences University, Kerala State, India was utilized. The manifest variables used in the study were age and weight of dam, birth weight, litter size at birth and weaning, weight at first, second and third months. The linear multiple regression analysis was performed by keeping the slaughter weight as the dependent variable and the remaining as independent variables. The model explained 48.60 percentage of the total variation present in the market weight of the rabbits. Even though the model used was significant, the standardized beta coefficients for the independent variables viz., age and weight of the dam, birth weight and litter sizes at birth and weaning were less than one indicating their negligible influence on the slaughter weight. However, the standardized beta coefficient of the second-month body weight was maximum followed by the first-month weight indicating their major role on the market weight. All the other factors influence indirectly only through these two variables. Hence it was concluded that the slaughter body weight can be predicted using the first and second-month body weights. The principal components were also developed so as to achieve more accuracy in the prediction of market weight of rabbits.

Keywords: component analysis, multivariate, slaughter, regression

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Authors: Adji Achmad Rinaldo Fernandes

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Path analysis is an analytical technique to study the causal relationship between independent and dependent variables. In this study, the integration of Clusters in the Ward Linkage method was used in a variety of clusters with path analysis. The variables used are character (x₁), capacity (x₂), capital (x₃), collateral (x₄), and condition of economy (x₄) to on time pay (y₂) through the variable willingness to pay (y₁). The purpose of this study was to compare the Ward Linkage method cluster integration in various clusters with path analysis to classify willingness to pay (y₁). The data used are primary data from questionnaires filled out by customers of Bank X, using purposive sampling. The measurement method used is the average score method. The results showed that the Ward linkage method cluster integration with path analysis on 2 clusters is the best method, by comparing the coefficient of determination. Variable character (x₁), capacity (x₂), capital (x₃), collateral (x₄), and condition of economy (x₅) to on time pay (y₂) through willingness to pay (y₁) can be explained by 58.3%, while the remaining 41.7% is explained by variables outside the model.

Keywords: cluster integration, linkage, path analysis, compliant paying behavior

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Authors: S. Pushkar, O. Verbitsky

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Currently, green rating systems are mainly utilized for correctly sizing mechanical and electrical systems, which have short lifetime expectancies. In these systems, passive solar and bio-climatic architecture, which have long lifetime expectancies, are neglected. Urban rating systems consider buildings and services in addition to neighborhoods and public transportation as integral parts of the built environment. The main goal of this study was to develop a more consistent point allocation system for urban building standards by using six different lifetime shearing layers: Site, Structure, Skin, Services, Space, and Stuff, each reflecting distinct environmental damages. This shearing-layer concept was applied to internationally well-known rating systems: Leadership in Energy and Environmental Design (LEED) for Neighborhood Development, BRE Environmental Assessment Method (BREEAM) for Communities, and Comprehensive Assessment System for Building Environmental Efficiency (CASBEE) for Urban Development. The results showed that LEED for Neighborhood Development and BREEAM for Communities focused on long-lifetime-expectancy building designs, whereas CASBEE for Urban Development gave equal importance to the Building and Service Layers. Moreover, although this rating system was applied using a building-scale assessment, “Urban Area + Buildings” focuses on a short-lifetime-expectancy system design, neglecting to improve the architectural design by considering bio-climatic and passive solar aspects.

Keywords: green rating system, urban community, sustainable design, standardization, shearing-layer concept, passive solar architecture

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Authors: Claudineia Brazil, Elison Eduardo Jardim Bierhals, Luciane Teresa Salvi, Rafael Haag

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Renewable energy sources are dependent on climatic variability, so for adequate energy planning, observations of the meteorological variables are required, preferably representing long-period series. Despite the scientific and technological advances that meteorological measurement systems have undergone in the last decades, there is still a considerable lack of meteorological observations that form series of long periods. The reanalysis is a system of assimilation of data prepared using general atmospheric circulation models, based on the combination of data collected at surface stations, ocean buoys, satellites and radiosondes, allowing the production of long period data, for a wide gamma. The third generation of reanalysis data emerged in 2010, among them is the Climate Forecast System Reanalysis (CFSR) developed by the National Centers for Environmental Prediction (NCEP), these data have a spatial resolution of 0.50 x 0.50. In order to overcome these difficulties, it aims to evaluate the performance of solar radiation estimation through alternative data bases, such as data from Reanalysis and from meteorological satellites that satisfactorily meet the absence of observations of solar radiation at global and/or regional level. The results of the analysis of the solar radiation data indicated that the reanalysis data of the CFSR model presented a good performance in relation to the observed data, with determination coefficient around 0.90. Therefore, it is concluded that these data have the potential to be used as an alternative source in locations with no seasons or long series of solar radiation, important for the evaluation of solar energy potential.

Keywords: climate, reanalysis, renewable energy, solar radiation

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Authors: Gizem Akcan, Erdinc Ozturk

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The purpose of the study was to determine some psychosocial variables that predict dissociation in university students. These psychosocial variables were perceived childhood trauma, alexithymia, and gender. 150 (75 males, 75 females) university students (bachelor, master and postgraduate) were enrolled in this study. They were chosen from universities in Istanbul at the education year of 2016-2017. Dissociative Experiences Scale (DES), Childhood Trauma Questionnaire (CTQ) and Toronto Alexithymia Scale were used to assess related variables. Demographic Information Form was given to students in order to have their demographic information. Frequency Distribution, Linear Regression Analysis, and t-test analysis were used for statistical analysis. Childhood trauma and alexithymia were found to have predictive value on dissociation among university students. However, physical abuse, physical neglect and emotional neglect sub dimensions of childhood trauma and externally-oriented thinking sub dimension of alexithymia did not have predictive value on dissociation. Moreover, there was no significant difference between males and females in terms of dissociation scores of participants.

Keywords: childhood trauma, dissociation, alexithymia, gender

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Authors: Arcady Ponosov

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A novel mathematical approach is suggested, which facilitates a compressed representation and efficient validation of parameter-rich ordinary differential equation models describing the dynamics of complex, especially biology-related, systems and which is based on identification of the system's latent variables. In particular, an efficient parameter estimation method for the compressed non-linear dynamical systems is developed. The method is applied to the so-called 'power-law systems' being non-linear differential equations typically used in Biochemical System Theory.

Keywords: generalized law of mass action, metamodels, principal components, synergetic systems

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Authors: Saeed Yazdani, Shahrbanoo Bagheri, Sepideh Nikravesh

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Considering the importance and scarcity of water resources, the efficient management of water resources is of great importance. Adoption of modern irrigation technology is considered to be a key of increasing the efficiency of water used in agriculture. Policy makers have implemented several ways to induce the adoption of new irrigation technology. The empirical studies show that farmers are reluctant to utilize the use of new irrigation methods. This study aims to assess factors affecting on farmer’s decision on the application of water saving technologies with emphasize on crop price variation and water sources. A Logit model was employed to examine the impact of different variables on use of water saving technology. The required data gathered from a sample of 204 farmers in the year 2012. The results indicate that different variables such as crop price variability, water supply source, high-value crops, farm size, income, education, membership in cooperatives have a positive effect and variables such as age and number of plots have a negative impact on the probability of adopting modern water saving technologies.

Keywords: irrigation, water, water saving technology, scarcity

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Authors: Taisiia Gorshkova

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Since the 1980s, spatial correlation models have been used more often to model regional indicators. An increasingly popular method for studying regional indicators is modeling taking into account spatial relationships between objects that are part of the same economic zone. In 2000s the new class of model – spatial vector autoregressions was developed. The main difference between standard and spatial vector autoregressions is that in the spatial VAR (SpVAR), the values of indicators at time t may depend on the values of explanatory variables at the same time t in neighboring regions and on the values of explanatory variables at time t-k in neighboring regions. Thus, VAR is a special case of SpVAR in the absence of spatial lags, and the spatial panel data model is a special case of spatial VAR in the absence of time lags. Two specifications of SpVAR were applied to Russian regional data for 2000-2017. The values of GRP and regional CPI are used as endogenous variables. The lags of GRP, CPI and the unemployment rate were used as explanatory variables. For comparison purposes, the standard VAR without spatial correlation was used as “naïve” model. In the first specification of SpVAR the unemployment rate and the values of depending variables, GRP and CPI, in neighboring regions at the same moment of time t were included in equations for GRP and CPI respectively. To account for the values of indicators in neighboring regions, the adjacency weight matrix is used, in which regions with a common sea or land border are assigned a value of 1, and the rest - 0. In the second specification the values of depending variables in neighboring regions at the moment of time t were replaced by these values in the previous time moment t-1. According to the results obtained, when inflation and GRP of neighbors are added into the model both inflation and GRP are significantly affected by their previous values, and inflation is also positively affected by an increase in unemployment in the previous period and negatively affected by an increase in GRP in the previous period, which corresponds to economic theory. GRP is not affected by either the inflation lag or the unemployment lag. When the model takes into account lagged values of GRP and inflation in neighboring regions, the results of inflation modeling are practically unchanged: all indicators except the unemployment lag are significant at a 5% significance level. For GRP, in turn, GRP lags in neighboring regions also become significant at a 5% significance level. For both spatial and “naïve” VARs the RMSE were calculated. The minimum RMSE are obtained via SpVAR with lagged explanatory variables. Thus, according to the results of the study, it can be concluded that SpVARs can accurately model both the actual values of macro indicators (particularly CPI and GRP) and the general situation in the regions

Keywords: forecasting, regional data, spatial econometrics, vector autoregression

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Authors: Sayantan Khanra, Rojers P. Joseph

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Background and Significance: This study is aimed at analyzing the role of demographic and service quality variables in the adoption and diffusion of e-government services among the users in India. The study proposes to examine the users' perception about e-Government services and investigate the key variables that are most salient to the Indian populace. Description of the Basic Methodologies: The methodology to be adopted in this study is Hierarchical Regression Analysis, which will help in exploring the impact of the demographic variables and the quality dimensions on the willingness to use e-government services in two steps. First, the impact of demographic variables on the willingness to use e-government services is to be examined. In the second step, quality dimensions would be used as inputs to the model for explaining variance in excess of prior contribution by the demographic variables. Present Status: Our study is in the data collection stage in collaboration with a highly reliable, authentic and adequate source of user data. Assuming that the population of the study comprises all the Internet users in India, a massive sample size of more than 10,000 random respondents is being approached. Data is being collected using an online survey questionnaire. A pilot survey has already been carried out to refine the questionnaire with inputs from an expert in management information systems and a small group of users of e-government services in India. The first three questions in the survey pertain to the Internet usage pattern of a respondent and probe whether the person has used e-government services. If the respondent confirms that he/she has used e-government services, then an aggregate of 15 indicators are used to measure the quality dimensions under consideration and the willingness of the respondent to use e-government services, on a five-point Likert scale. If the respondent reports that he/she has not used e-government services, then a few optional questions are asked to understand the reason(s) behind the same. Last four questions in the survey are dedicated to collect data related to the demographic variables. An indication of the Major Findings: Based on the extensive literature review carried out to develop several propositions; a research model is prescribed to start with. A major outcome expected at the completion of the study is the development of a research model that would help to understand the relationship involving the demographic variables and service quality dimensions, and the willingness to adopt e-government services, particularly in an emerging economy like India. Concluding Statement: Governments of emerging economies and other relevant agencies can use the findings from the study in designing, updating, and promoting e-government services to enhance public participation, which in turn, would help to improve efficiency, convenience, engagement, and transparency in implementing these services.

Keywords: adoption and diffusion of e-government services, demographic variables, hierarchical regression analysis, service quality dimensions

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Authors: Zahid Ahmad, Samia Yousaf

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The main purpose of this study is to evaluate and assess the financial position, operating performance, and recent outlook of the companies. This study investigates the impact of capital structure, dividend policy and sustainability on the value of firms of textile spinning sector of Pakistan which is listed on Pakistan stock exchange. The panel data technique has been applied to this group of textile sector which is textile spinning. This study covers the last ten years of time period. All the data related to the variables have been collected from the annual reports and financial statements of the textile sector firms. There are differently related determinants to measure the capital structure which are fixed assets turnover ratio, debt ratio, equity ratio, debt to equity ratio, assets tangibility, and shareholder’s equity. Dividend policy is being measured by two determinants which are earning per share (EPS) and dividend payout ratio. Sustainability is being measured by three suitable factors which are sales growth, gross profit margin ratio and firm size. These are three independent variables and their determinants of this study. Value of firm is measured through the return on asset (ROA). Capital structure is at the top of the list among all the three variables. According to the results of this research work, somewhere all the three variables generates positive and significant effect on the firm’s performance and its growth.

Keywords: capital structure, dividend policy, panel data, sustainability

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Authors: Bensaid A., Mostephaoui T., Nedjai R.

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Climatic factors are the subject of considerable research, both methodologically and instrumentally. Under the effect of climate change, the approach to climate parameters with precision remains one of the main objectives of the scientific community. This is from the perspective of assessing climate change and its repercussions on humans and the environment. However, many regions of the world suffer from a severe lack of reliable instruments that can make up for this deficit. Alternatively, the use of empirical methods becomes the only way to assess certain parameters that can act as climate indicators. Several scientific methods are used for the evaluation of evapotranspiration which leads to its evaluation either directly at the level of the climatic stations or by empirical methods. All these methods make a point approach and, in no case, allow the spatial variation of this parameter. We, therefore, propose in this paper the use of three sources of information (network of weather stations of Meteo France, World Databases, and Moodis satellite images) to evaluate spatial evapotranspiration (ETP) using the Turc method. This first step will reflect the degree of relevance of the indirect (satellite) methods and their generalization to sites without stations. The spatial variation representation of this parameter using the geographical information system (GIS) accounts for the heterogeneity of the behaviour of this parameter. This heterogeneity is due to the influence of site morphological factors and will make it possible to appreciate the role of certain topographic and hydrological parameters. A phase of predicting the evolution over the medium and long term of evapotranspiration under the effect of climate change by the application of the Intergovernmental Panel on Climate Change (IPCC) scenarios gives a realistic overview as to the contribution of aquatic systems to the scale of the region.

Keywords: climate change, ETP, MODIS, GIEC scenarios

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Authors: Mohsen Amiri

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This study aimed at investigating the relationship between familial functioning, child characteristics, demographic variables and parenting stress and mental health among parents of children with mental disabilities. 200 parents (130 mothers and 70 fathers) were studied and they completed the Parenting Stress Index, General Health Questionnaire, Family Assessment Device and demographic questionnaires for parents and children. Data were analyzed using correlation and regression analysis. Regression analysis showed that child characteristics, familial functioning and parents demographic factors could predict 8, 4 and 17 percent of variance in parental stress and 3.6, 16 and 10 percent of variance in mental health, respectively. Familial functioning, child characteristics and parental demographic variables correlated with mental health and parental stress and could predict them.

Keywords: parenting stress, mental health, mentally disabled children, familial functioning, demographic variables

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Authors: Bakari Mohammed

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Sports performance and achievements have been the avenue through which great nations of the world exhibit their supremacy over others through sports development strategy. Effective sports development, therefore, requires variables like sports policy, sports funding, sports programme, sports facilities and sponsorship. The extent to what these variables are met shall no doubt affects the effectiveness of any sports development. Two distinguishing features of the Nigerian sports system are its central organization and its employment for specific socio-political objectives, it is against this backdrop that this paper will x-ray the politicization of sports which parallels sports development in the enhanced role of sports and in contrast with developed nations system and management.

Keywords: sport development, sport policy, personnel, program, facilities, funding, sponsorship

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Authors: Ali Hesari, Arezoo Esmaeeli

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Regarding to dramatic changes of fertility and higher order births during recent decades in Iran, access to knowledge about affecting factors on different birth orders has crucial importance. In this study, According to hierarchical structure of many of social sciences data and the effect of variables of different levels of social phenomena that determine different birth orders in 365 days ending to 1390 census have been explored by multilevel approach. In this paper, 2% individual row data for 1390 census is analyzed by HLM software. Three different hierarchical linear regression models are estimated for data analysis of the first and second, third, fourth and more birth order. Research results displays different outcomes for three models. Individual level variables entered in equation are; region of residence (rural/urban), age, educational level and labor participation status and province level variable is GDP per capita. Results show that individual level variables have different effects in these three models and in second level we have different random and fixed effects in these models.

Keywords: fertility, birth order, hierarchical approach, fixe effects, random effects

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Authors: Jafar Akbari, Masoud Rismanchian, Samira Ramezani

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Purpose: The photocatalytic degradation of pollutants is a novel technology with various advantages such as high efficiency and energy saving. In this research, the effects of operational variables on the photocatalytic efficiency of TiO₂ coated on nickel foam in the removal of toluene from the simulated indoor air have been investigated. Methods: TiO₂ film were prepared via the sol-gel method and coated on nickel foam. The characteristics and morphology were found using XRD, SEM, and BET technique. Then, the effects of relative humidity, UV-A intensity, the initial toluene concentration, TiO₂ loading, and the air circulation velocity on the photocatalytic degradation rate have been evaluated. Results: The optimal degradation of toluene has been achieved with loading 4.35 g TiO2 on the foam, 30% RH, 5.4 µW.cm−2 UV-A intensity, and 20 ppm initial concentration in the air circulation velocity of 0.15 fpm. Conclusion: The changes of toluene photocatalytic degradation rate have been studied at various times. Also, the kinetic behavior of toluene photocatalytic degradation has been investigated using Langmuir-Hinshelwood (L-H) model.

Keywords: photocatalytic degradation, operational variables, tio₂, nickel foam, gaseous toluene, nanotechnology

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Authors: Guilhermina Torrao

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An extensive number of studies have been conducted to determine the factors which influence crash injury risk (CIR); however, uncertainties inherent to selected variables have been neglected. A review of existing literature is required to not only obtain an overview of the variables and measures but also ascertain the implications when comparing studies without a systematic view of variable taxonomy. Therefore, the aim of this literature review is to examine and report on peer-reviewed studies in the field of crash analysis and to understand the implications of broad variations in variable selection in CIR analysis. The objective of this study is to demonstrate the variance in variable selection and classification when modeling injury risk involving occupants of light vehicles by presenting an analytical review of the literature. Based on data collected from 64 journal publications reported over the past 21 years, the analytical review discusses the variables selected by each study across an organized list of predictors for CIR analysis and provides a better understanding of the contribution of accident and vehicle factors to injuries acquired by occupants of light vehicles. A cross-comparison analysis demonstrates that almost half the studies (48%) did not consider vehicle design specifications (e.g., vehicle weight), whereas, for those that did, the vehicle age/model year was the most selected explanatory variable used by 41% of the literature studies. For those studies that included speed risk factor in their analyses, the majority (64%) used the legal speed limit data as a ‘proxy’ of vehicle speed at the moment of a crash, imposing limitations for CIR analysis and modeling. Despite the proven efficiency of airbags in minimizing injury impact following a crash, only 22% of studies included airbag deployment data. A major contribution of this study is to highlight the uncertainty linked to explanatory variable selection and identify opportunities for improvements when performing future studies in the field of road injuries.

Keywords: crash, exploratory, injury, risk, variables, vehicle

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Authors: Bok Yae Chung, Eun Hee Oh

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Breast cancer patients require more nutritional interventions than others. However, a few studies have attempted to assess the overall nutritional status, to reduce body weight and BMI by improving diet, and to improve the prognosis of cancer for breast cancer patients. The purpose of this study was to evaluate the effect of diet intervention in the breast cancer patients through meta-analysis. For the study purpose, 16 studies were selected by using PubMed, ScienceDirect, ProQuest and CINAHL. Meta-analysis was performed using a random-effects model, and the effect size on outcome variables in breast cancer was calculated. The effect size for outcome variables of diet intervention was a large effect size. For heterogeneity, moderator analysis was performed using intervention type and intervention duration. All moderators did not significant difference. Diet intervention has significant positive effects on outcome variables in breast cancer. As a result, it is suggested that the timing of the intervention should be no more than six months, but a strategy for sustaining long-term intervention effects should be added if nutritional intervention is to be administered for breast cancer patients in the future.

Keywords: breast cancer, diet, mete-analysis, intervention

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Authors: Derya Yucel, Nigar Angın, Dürdane Mart, Meltem Turkeri, Volkan Catalkaya, Celal Yucel

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Chickpea (Cicer arietinum L.) is one of the important legumes widely grown for dietery proteins in semi-arid Mediteranean climatic conditions. To evaluate the genetic diversity with improved heat and drought tolerance capacity in chickpea, thirty-four selected chickpea genotypes were tested under different field-growing conditions (rainfed winter sowing, irrigated-late sowing and rainfed-late sowing) in 2015 growing season. A factorial experiment in randomized complete block design with 3 reps was conducted at the Eastern Mediterranean Research Institute Adana, Turkey. Based on grain yields under different growing conditions, several indices were calculated to identify economically higher-yielding chickpea genotypes with greater heat and drought tolerance capacity. Average across chickpea genotypes, the values of tolerance index, mean productivity, yield index, yield stability index, stress tolerance index, stress susceptibility index, and geometric mean productivity were ranged between 1.1 to 218, 38 to 202, 0.3 to 1.7, 0.2 to 1, 0.1 to 1.2, 0.02 to 1.4, and 36 to 170 for drought stress and 3 to 54, 23 to 118, 0.3 to 1.7, 0.4 to 0.9, 0.2 to 2, 0.2to 2.3, and 23 to 118 for heat stress, respectively. There were highly significant differences observed among the tested chickpea genotypes response to drought and heat stresses. Among the chickpea genotypes, the Aksu, Arda, Çakır, F4 09 (X 05 TH 21-16189), FLIP 03-108 were identified with a higher drought and heat tolerance capacity. Based on our field studies, it is suggested that the drought and heat tolerance indicators of plants can be used by breeders to select stress-resistant economically productive chickpea genotypes suitable to grow under Mediteranean climatic conditions.

Keywords: irrigation, rainfed, stress susceptibility, tolerance indice

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Authors: Vandana Maurya

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Positive psychological capital is the key contributor to the competitive advantage of the organizations. Moreover, work engagement and sense of humor are also positive notions and are able to facilitate positive workplace behaviour but the mechanism behind these relationships are not well understood. The purpose of this study was to examine the relationships among work engagement, sense of humor and outcome variables (organizational citizenship behaviour and ethical performance) as well as investigating how psychological capital (PsyCap) mediates the relationships between work engagement, sense of humor and the outcome variables among healthcare professionals. A cross-sectional survey was conducted on healthcare professionals (n= 240). Data were collected using questionnaires which includes Utrecht Work Engagement Scale (UWES), Multi-dimensional Sense of Humor Scale (MSHS), Psychological Capital Questionnaire (PCQ), Organizational Citizenship Behavior Questionnaire, and Ethical Performance Scale (EPS). The results of the regression analyses showed that work engagement and sense of humor both positively predicted the outcome variables. Mediation analysis reveals that psychological capital mediates the relationship between predictor and outcome variables. The study recommends that the framework presented in this study can be an important tool for managers to enhance their employees’ psychological capital by increasing their levels of work engagement and sense of humor. In turn, psychological capital could be a positive resource for employees to dealing more ethically and enhancing more positive workplace behaviour.

Keywords: ethical performance, humor, organizational citizenship behavior, PsyCap, work engagement

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Authors: Jiahua Zhang, Qing Chang, Fengmei Yao

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Studying on the response of vegetation phenology to climate change at different temporal and spatial scales is important for understanding and predicting future terrestrial ecosystem dynamics andthe adaptation of ecosystems to global change. In this study, the Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) dataset and climate data were used to analyze the dynamics of grassland phenology as well as their correlation with climatic factors in different eco-geographic regions and elevation units across the Tibetan Plateau. The results showed that during 2003–2012, the start of the grassland greening season (SOS) appeared later while the end of the growing season (EOS) appeared earlier following the plateau’s precipitation and heat gradients from southeast to northwest. The multi-year mean value of SOS showed differences between various eco-geographic regions and was significantly impacted by average elevation and regional average precipitation during spring. Regional mean differences for EOS were mainly regulated by mean temperature during autumn. Changes in trends of SOS in the central and eastern eco-geographic regions were coupled to the mean temperature during spring, advancing by about 7d/°C. However, in the two southwestern eco-geographic regions, SOS was delayed significantly due to the impact of spring precipitation. The results also showed that the SOS occurred later with increasing elevation, as expected, with a delay rate of 0.66 d/100m. For 2003–2012, SOS showed an advancing trend in low-elevation areas, but a delayed trend in high-elevation areas, while EOS was delayed in low-elevation areas, but advanced in high-elevation areas. Grassland SOS and EOS changes may be influenced by a variety of other environmental factors in each eco-geographic region.

Keywords: grassland, phenology, MODIS, eco-geographic regions, elevation, climatic factors, Tibetan Plateau

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Authors: K. D. Mroczek

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In the study presented institutional context is discussed in terms of companies’ entry mode choice. In contrary to many previous analyses, instead of using one or two aggregated variables, a set of eleven determinants is used to establish equity and non-equity internationalization friendly conditions. Based on secondary data, 140 countries are analysed and grouped into clusters revealing similar framework. The range of the economies explored is wide as it covers all regions distinguished by The World Bank. The results can prove a useful alternative for operationalization of institutional variables in further research concerning entry modes or strategic management in international markets.

Keywords: clustering, entry mode choice, institutional environment, transaction costs

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Authors: Umeora Chukwunonso Obiefuna

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The private sector in housing provision continually take steps towards addressing part of the problem of cushioning the effect of the housing shortage in Nigeria by establishing housing estates since the government alone cannot provide housing for everyone. This research examined and reported findings from research conducted on the state of repair of buildings in private housing estates in Enugu metropolis, Enugu state Nigeria. The objectives of the study were to examine the physical conditions of the building fabrics and appraise the performance of infrastructural services provided in the buildings. The questionnaire was used as a research instrument to elicit data from respondents. Stratified sampling of the estates based on building type was adopted as a sampling method for this study. Findings from the research show that the state of repair of most buildings require minor repairs to make them fit for habitation and sound to ensure the well-being of the residents. In addition, four independent variables from the nine independent variables investigated significantly explained residual variation in the dependent variable - state of repair of the buildings in the study area. These variables are: Average Monthly Income of Residents (AMIR), Length of Stay of the Residents in the estates (LSY), Type of Wall Finishes on the buildings (TWF), and Time Taken to Respond to Resident’s complaints by the estate managers (TTRC). With this, the linear model was established for predicting the state of repair of buildings in private housing estates in the study area. This would assist in identifying variables that are lucid in predicting the state of repair of the buildings.

Keywords: building, housing estate, private, repair

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Authors: Jorge Anibal Restrepo Morales, Sonia Martín Gómez

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A model based on a logical framework was developed to quantify SMEs' internationalization capacity. To do so, linguistic variables, such as human talent, infrastructure, innovation strategies, FTAs, marketing strategies, finance, etc. were integrated. It is argued that a company’s management of international markets depends on internal factors, especially capabilities and resources available. This study considers internal factors as the biggest business challenge because they force companies to develop an adequate set of capabilities. At this stage, importance and strategic relevance have to be defined in order to build competitive advantages. A fuzzy inference system is proposed to model the resources, skills, and capabilities that determine the success of internationalization. Data: 157 linguistic variables were used. These variables were defined by international trade entrepreneurs, experts, consultants, and researchers. Using expert judgment, the variables were condensed into18 factors that explain SMEs’ export capacity. The proposed model is applied by means of a case study of the textile and clothing cluster in Medellin, Colombia. In the model implementation, a general index of 28.2 was obtained for internationalization capabilities. The result confirms that the sector’s current capabilities and resources are not sufficient for a successful integration into the international market. The model specifies the factors and variables, which need to be worked on in order to improve export capability. In the case of textile companies, the lack of a continuous recording of information stands out. Likewise, there are very few studies directed towards developing long-term plans, and., there is little consistency in exports criteria. This method emerges as an innovative management tool linked to internal organizational spheres and their different abilities.

Keywords: business strategy, exports, internationalization, fuzzy set methods

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Authors: Carolina Aparicio-Fernández, Alejandro Vilar Abad, Mar Cañada Soriano, Jose-Luis Vivancos

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The building sector is responsible for 40% of the total energy consumption in the European Union (EU). Thus, implementation of strategies for quantifying and reducing buildings energy consumption is indispensable for reaching the EU’s carbon neutrality and energy efficiency goals. Each Member State has transposed the European Directives according to its own peculiarities: existing technical legislation, constructive solutions, climatic zones, etc. Therefore, in accordance with the Energy Performance of Buildings Directive, Member States have developed different Energy Performance Certificate schemes, using proposed energy simulation software-tool for each national or regional area. Energy Performance Certificates provide a powerful and comprehensive information to predict, analyze and improve the energy demand of new and existing buildings. Energy simulation software and databases allow a better understanding of the current constructive reality of the European building stock. However, Energy Performance Certificates still have to face several issues to consider them as a reliable and global source of information since different calculation tools are used that do not allow the connection between them. In this document, TRNSYS (TRaNsient System Simulation program) software is used to calculate the energy demand of a building, and it is compared with the energy labeling obtained with Spanish Official software-tools. We demonstrate the possibility of using not official software-tools to calculate the Energy Performance Certificate. Thus, this approach could be used throughout the EU and compare the results in all possible cases proposed by the EU Member States. To implement the simulations, an isolated single-family house with different construction solutions is considered. The results are obtained for every climatic zone of the Spanish Technical Building Code.

Keywords: energy demand, energy performance certificate EPBD, trnsys, buildings

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Authors: M. Arifuzzaman, H. S. Kim

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Multiple sets of variables associated with expanded perlite particle consolidation in foam manufacturing were analyzed to develop a model for predicting perlite foam density. The consolidation of perlite particles based on the flotation method and compaction involves numerous variables leading to the final perlite foam density. The variables include binder content, compaction ratio, perlite particle size, various perlite particle densities and porosities, and various volumes of perlite at different stages of process. The developed model was found to be useful not only for prediction of foam density but also for optimization between compaction ratio and binder content to achieve a desired density. Experimental verification was conducted using a range of foam densities (0.15–0.5 g/cm3) produced with a range of compaction ratios (1.5-3.5), a range of sodium silicate contents (0.05–0.35 g/ml) in dilution, a range of expanded perlite particle sizes (1-4 mm), and various perlite densities (such as skeletal, material, bulk, and envelope densities). A close agreement between predictions and experimental results was found.

Keywords: expanded perlite, flotation method, foam density, model, prediction, sodium silicate

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Authors: Ravinder Singh, Pratima Syal

Abstract:

Background: The rising prevalence and incidence of Acute Pancreatitis (AP) and its associated metabolic variables known as metabolic syndrome (MetS) are common medical conditions with catastrophic consequences and substantial treatment costs. The correlation between MetS and AP, as well as their impact on Health Related Quality of Life (HRQoL) is uncertain, and because there are so few published studies, further research is needed. As a result, we planned this study to determine the relationship between MetS components impact on HRQoL in AP patients. Patients and Methods: A prospective, observational study involving the recruitment of patients with AP with and without MetS was carried out in tertiary care hospital of North India. Patients were classified with AP if they were diagnosed with two or more components of the following criteria, abdominal pain, serum amylase and lipase levels two or more times normal, imaging trans-abdominal ultrasound, computed tomography, or magnetic resonance. The National Cholesterol Education Program–Adult Treatment Panel III (NCEP-ATP III) criterion was used to diagnose the MetS. The various socio-demographic variables were also taken into consideration for the calculation of statistical significance (P≤.05) in AP patients. Finally, the correlation between AP and MetS, along with their impact on HRQoL was assessed using Student's t test, Pearson Correlation Coefficient, and Short Form-36 (SF-36). Results: AP with MetS (n = 100) and AP without MetS (n = 100) patients were divided into two groups. Gender, Age, Educational Status, Tobacco use, Body Mass Index (B.M.I), and Waist Hip Ratio (W.H.R) were the socio-demographic parameters found to be statistically significant (P≤.05) in AP patients with MetS. Also, all the metabolic variables were also found to statistically significant (P≤.05) and found to be increased in patients with AP with MetS as compared to AP without MetS except HDL levels. Using the SF-36 form, a greater significant decline was observed in physical component summary (PCS) and mental component summary (MCS) in patients with AP with MetS as compared to patients without MetS (P≤.05). Furthermore, a negative association between all metabolic variables with the exception of HDL, and AP was found to be producing deterioration in PCS and MCS. Conclusion: The study demonstrated that patients with AP with MetS had a worse overall HRQOL than patients with AP without MetS due to number of socio-demographic and metabolic variables having direct correlation impacting physical and mental health of patients.

Keywords: metabolic disorers, QOL, cost effectiveness, pancreatitis

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Authors: Karim Hajjar, Luis Lillo, Diego Martinez, Manuel Hermosilla, Nicholas Risko

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Objectives: This study examines the relationship between universal health coverage (UCH) and the burden of emergency diseases at a global level. Methods: Data on Disability-Adjusted Life Years (DALYs) from emergency conditions were extracted from the Institute for Health Metrics and Evaluation (IHME) database for the years 2015 and 2019. Data on UHC, measured using two variables, 1) coverage of essential health services and 2) proportion of population spending more than 10% of household income on out-of-pocket health care expenditure, was extracted from the World Bank Database for years preceding our outcome of interest. Linear regression was performed, analyzing the effect of the UHC variables on the DALYs of emergency diseases, controlling for other variables. Results: A total of 133 countries were included. 44.4% of the analyzed countries had coverage of essential health services index of at least 70/100, and 35.3% had at least 10% of their population spend greater than 10% of their household income on healthcare. For every point increase in the coverage of essential health services index, there was a 13-point reduction in DALYs of emergency medical diseases (95% CI -16, -11). Conversely, for every percent decrease in the population with large household expenditure on healthcare, there was a 0.48 increase in DALYs of emergency medical diseases (95% CI -5.6, 4.7). Conclusions: After adjusting for multiple variables, an increase in coverage of essential health services was significantly associated with improvement in DALYs for emergency conditions. There was, however, no association between catastrophic health expenditure and DALYs.

Keywords: emergency medicine, universal healthcare, global health, health economics

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Authors: N. A. Mokhtar, A. G. Hussin, Y. Z. Zubairi

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This paper proposes a new simultaneous simple linear functional relationship model by assuming equal error variances. We derive the maximum likelihood estimate of the parameters in the simultaneous model and the covariance. We show by simulation study the small bias values of the parameters suggest the suitability of the estimation method. As an illustration, the proposed simultaneous model is applied to real data of the wind direction and wave direction measured by two different instruments.

Keywords: simultaneous linear functional relationship model, Fisher information matrix, parameter estimation, circular variables

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Authors: Khuram Nawaz Sadozai, Sonia

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The agriculture sector is deemed more vulnerable to climate change as its variation can directly affect the crop’s productivity, but farmers’ adaptation strategies play a vital role in climate change-agriculture relationship. Therefore, this research has been undertaken to assess the Climate Change impact on wheat productivity and farmers’ adaptability strategies in Khyber Pakhtunkhwa province, Pakistan. The panel dataset was analyzed to gauge the impact of changing climate variables (i.e., temperature, rainfall, and humidity) on wheat productivity from 1985 to 2015. Amid the study period, the fixed effect estimates confirmed an inverse relationship of temperature and rainfall on the wheat yield. The impact of temperature is observed to be detrimental as compared to the rainfall, causing 0.07 units reduction in the production of wheat with 1C upsurge in temperature. On the flip side, humidity revealed a positive association with the wheat productivity by confirming that high humidity could be beneficial to the production of the crop over time. Thus, this study ensures significant nexus between agricultural production and climatic parameters. However, the farming community in the underlying study area has limited knowledge about the adaptation strategies to lessen the detrimental impact of changing climate on crop yield. It is recommended that farmers should be well equipped with training and advanced agricultural management practices under the realm of climate change. Moreover, innovative technologies pertinent to the agriculture system should be encouraged to handle the challenges arising due to variations in climate factors.

Keywords: climate change, fixed effect model, panel data, wheat productivity

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Authors: Adji Achmad Rinaldo Fernandes

Abstract:

Path analysis tests the relationship between variables through cause and effect. Before conducting further tests on path analysis, the assumption of linearity must be met. If the shape of the relationship is not linear and the shape of the curve is unknown, then use a nonparametric approach, one of which is a truncated spline. The purpose of this study is to estimate the function and get the best model on the nonparametric truncated spline path of linear, quadratic, and cubic orders with 1 and 2-knot points and determine the significance of the best function estimator in modeling farmer loyalty through the jackknife resampling method. This study uses secondary data through questionnaires to farmers in Sumbawa Regency who use SP-36 subsidized fertilizer products as many as 100 respondents. Based on the results of the analysis, it is known that the best-truncated spline nonparametric path model is the quadratic order of 2 knots with a coefficient of determination of 85.50%; the significance of the best-truncated spline nonparametric path estimator shows that all exogenous variables have a significant effect on endogenous variables.

Keywords: nonparametric path analysis, farmer loyalty, jackknife resampling, truncated spline

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