Archives-June 2018

The adsorption of mercuric ions (Hg2+) on nano zinc oxide (ZnO-NPs) structure was studied using the Monte Carlo simulation and the density functional theory (DFT) methods. The obtained results have shown that the adsorption process is thermodynamically favorable. The mercuric ions are strongly adsorbed on the ZnO-NPs structures due to the formation of the chemical bonds resulted from the positive overlap between p-orbitals of the adsorbate species and the p-orbitals of the zinc atoms in the structure of ZnO-NPs.

In the dynamic business environment, organizations have implemented Enterprise Resource Planning system solutions to gain competitive advantage and fasten service delivery for value realization. Despite their benefits, ERP solutions have not been fully embraced by SACCOs, and those that have implemented the ERPs are not able to justify the benefits of the investment. Therefore the purpose of the study was to establish the value realizations for SACCO’s after the implementation of Enterprise Resource Planning solutions, Nairobi region. Specific objective included: to establish the levels of ERP implementation and the value realized by SACCOs through ERP implementation. The researcher administered the questionnaires to the respondents randomly on a drop and pick basis. The data collected was expected to give both quantitative and qualitative results and it was analyzed using descriptive and regression model. It was found out that there was a strong relationship between the implementation level and the benefits of the ERP systems to SACCOs. The findings recommended that ERP systems should be implemented for customer relationship management; education, training and mentorship; monitoring and evaluation; and for research and development and for these reason, SACCOs should invest in the ERP systems.

This paper presents a Product recommendation system based on metric analysis of product descriptions. The developed system ranks the catalog of products and offers corresponding items to the user’s request while, at the same time, selecting the most diverse items. An algorithm for ranking is developed. Based on the request, the recommendation system finds the distance from this request to all documents from the collection of data. The request and the collection of data are sets of features. The system ranks the results in accordance with the following rules: minimizes the distance from the query to the relevant results, maximizes the distance from the query to the irrelevant results and maximizes the distance between the relevant query results. For ranking, Heterogeneous Euclidean-Overlap Metric (HEOM) of clothes catalogue items is used. HEOM metric uses different attribute distance functions to measure distances between objects in mixed scales. A dataset of clothes catalogue items is collected. The system, in addition to the basic attributes given as text descriptions of product, uses attributes based on expert description such as fashion, psychological age and attractiveness. The dataset has features of text, linear and nominal scales. The computational experiment shows the effectiveness of the proposed algorithm. The importance of features of the collection of data is defined. A software product demonstrating the recommendation system in action is developed.

Market efficiency depends on several things such as stability, confidence, and the flow of accessible information in any country. Others also caution that one must be aware of social or transactional costs which persons grapple with in cases involving political and market settlements. This has to do with “time”, “money”, and the “effort someone loses” in obtaining what he wants during a controversy in the market or political system. This also entails that people should fight less in order to reduce “friction” instead of contributing to this in public matters. Thus, according to Economists, other costs, including search and information costs, bargaining costs, keeping trade secrets, and policing and enforcement costs, can all potentially add to the cost of procuring something from another party. When elections are encountering numerous problems such as they produce risk and uncertainty, economic success may be greatly hampered. Market transactions could be affected. Elections are very important activities, which help nations to elect their prime leaders and parliamentarians. So whenever problems occur due to risk and uncertainties that are involved, the nation in question could fall into pandemonium, which could lead to anarchy. The purpose of the study was to determine how behavioural and social factors cause certain conditions to prevail as a result of conflicts which result from political elections. The use of comparative method enabled the author to combine theories of neuroscience, psychology, microeconomics tools to investigate conditions that occasion these instabilities in elections. Results show that certain behavioural characteristics emerge that illuminate on how leaders perceive themselves in power that negatively influences the political system. The conclusion is that behavioural economics concepts could be utilised to aid leaders in the Third World to desist from certain tendencies which prevent some good governance principles to function in these societies.

Nitrate contamination of drinking water has become a massive public health concern since excessive nitrate concentrations are found to cause several health disorders. The present study was undertaken to investigate the nitrate levels in the groundwaters of Bellandur during the pre- and post-monsoon periods of 2017, compare the analysis results with the drinking water standards as per the Bureau of Indian standards (BIS) and assess the potential risk to human health by evaluating by using the Hazard Index (HI) with respect to nitrates. This was achieved by subjecting 30 groundwater samples each, collected from the study area, during the pre and post monsoon seasons. The analysis results reveal that 53.33% of the samples contain nitrate in excess of 45 mg/l, the maximum allowable limits of drinking water laid down by BIS. The hazard index (HI) was evaluated by computing the Chronic Daily Intake (CDI). Results reveal that 14 samples in the post-monsoon and 12 samples in the pre-monsoon have a hazard index greater than unity (1), which indicates a high level of risk due to nitrate exposure in the groundwater endangering the respondents due to excessive nitrate concentrations in the groundwater.

Water quality monitoring is fast becoming a topic of utmost importance and concern as it deals the health and health issues faced by people. One of the widely employed approaches in water quality assessment is the Nemerow index method and this approach has been employed in the current study and the groundwater quality of K.R.Puram industrial area in Bangalore, India, has been assessed. The quality evaluation has been done by collecting thirty groundwater samples each, both during the pre-monsoon and post-monsoon periods of the year 2017, in and around the K.R.Puram area and subjecting the samples to a comprehensive physico-chemical analysis. To calculate the Nemerow index, ten critical parameters vital from the health point of view has been considered, namely, pH, calcium, magnesium, total hardness, nitrate, chloride, sulphate, total dissolved solids, fluorides and iron. The NPI analysis carried out for these thirty samples revealed that a whopping 93.33 % of the samples exceeded unity, the upper limit for drinking water. The high value of NPI at these stations is mainly due to the excessive concentrations of total dissolved solids, hardness, nitrate, iron, calcium and chlorides. The analysis reveals that most of the groundwater samples are unfit for drinking purposes, which calls for continuous monitoring of groundwater supplies and to adopt a systematic environment management plan to safeguard against the pollution of drinking water.

The sales force's performance is one of the key issues for companies in today's competitive environment. Sales force is the executive arm of organizations in attracting customers and selling goods or services. All efforts of the various units of the organization are summarized as a result of the sales force's performance. As competition intensifies, the importance of sales force performance has increased. Today's vendors are more than ever a dynamic powerhouse in the world of commerce, and their efforts have a direct impact on diverse and diverse activities. Maintain the company's position in the market, evaluate the status of competitors, and ultimately provide the grounds for success and development of the company. This research attempts to investigate the effect of sales force reputation on customer behavior with an emphasis on the role of empirical value added by sales force. The statistical population of the present study is the employees and customers of Iran Khodro authorized dealers in Isfahan city and the number of samples A total of 390 patients were selected. The research type is applied and the method of the survey is descriptive and the data collection tool is a questionnaire. The data were analyzed using SPSS software and Lisrel software. The results show that the reputation of sales force is influential on economic value, service productivity, service superiority, pleasurable interactions, and the mentioned variables have a positive effect on customer behavior in Iranian car dealerships, and it is suggested that these agents In order to raise the trust of customers, they are more seriously committed to their commitments and are committed to their customers and meet their needs.

Trauma can have long-term effects on the survivors’ mental health. In addition, levels of mental disorders reported among Internally Displaced Persons (IDPs) and refugees globally vary considerably. The disputed 2007 presidential election in Kenya eventually resulted in violence. The survivors were left with heavy psychosocial and economic burdens. Therefore, the aim of this study was to establish the prevalence of depression at baseline among IDPs resident in Maai Mahiu camp after the 2007/8 Post Election Violence (PEV) in Kenya. This study was pretest-posttest quasi-experimental and used purposive sampling to select a sample of 139 respondents out of the target population of 196 households. The respondents gave informed consent and filled out socio-demographic and Beck’s Depression Inventory (BDI-11) questionnaires. Analysis was conducted using SPSS, whereby univariate, bivariate and multivariate statistical tests were done. The findings indicated a high prevalence of Depressive Disorder (DD) at 63.3% among the respondents. These findings are significant for clinical practice and could be used to update strategies and policies governing IDP’s health. Therefore, the study recommended that psychosocial interventions should be provided to the PEV survivors and other vulnerable populations in Kenya to avert their suffering.

Enforcement of competition and consumer protection regime and ensuring fair competition and consumer interest in a free market economy depends, among others, upon the effectiveness of competition and consumer protection organ, which is responsible for enforcing. Existing studies reveal that establishment of competition and consumer protection authorities are the most effective way to implement competition and consumer protection law. Despite Ethiopia’s effort to legislate three times in a decade and improve the structure of competition and consumer protection authority, still, the competition and consumer protection legal regime have gaps that will negatively affect enforcement of competition and consumer protection law. This article mainly focuses on identifying authorities and institutional designs for consumer protection and competition, which have, in one way or another, the powers on competition and the consumer protection regime under Ethiopian trade competition and consumer protection laws. Moreover, it will assess and evaluate the autonomy and main functions of the existing enforcement organ of competition and consumer protection law based on the pertinent provisions of the current legislation of the country. Finally, the article ends up with a short conclusion and recommendations on the matters discussed under the main body of the article.

Climate change and climate variability and financial institutions’ unwillingness to give loans have resulted in many farmers losing confidence in dry land agriculture. Traditional crop insurance methods have also presented challenges due to the risk related to adverse selection and moral hazard resulting in high transaction costs for individual assessment. This study focused on developing a weather index based insurance model that uses artificial neural networks to estimate potential evapotranspiration (ETO) and consequently yield reduction due to moisture stress. Weather data from 2012 to 2015 for Kutsaga area in Harare was used for the study. Seasonal weather data were used as input data to the first model to predict the ETo. The output ETO and effective rainfall data together with the crop factor (Kc), yield reduction factor (Ky), root zone depth (RzD) and root zone moisture (RzM)were used as input data for the second network to compute % yield reduction. Data for maize for the 2012-13 growing season was used for training the network and validating the estimated ETO and % yield reduction. The estimated ETO compared very well with the calculated values with R2 values of above 0.84. The estimated yield reduction % indicated even high accuracies with R2 values of above 0.91. The 2014-2015 growing season resulted in crop loss due to mid-season dry spells and the model predicted a 100% crop loss which means the farmer had to be compensated for the value equivalent to cost of inputs. The model has got potential to be used by insurance companies using weather based data and, with mobile banking transaction costs can be reduced.Climate change and climate variability and financial institutions’ unwillingness to give loans have resulted in many farmers losing confidence in dry land agriculture. Traditional crop insurance methods have also presented challenges due to the risk related to adverse selection and moral hazard resulting in high transaction costs for individual assessment. This study focused on developing a weather index based insurance model that uses artificial neural networks to estimate potential evapotranspiration (ETO) and consequently yield reduction due to moisture stress. Weather data from 2012 to 2015 for Kutsaga area in Harare was used for the study. Seasonal weather data were used as input data to the first model to predict the ETo. The output ETO and effective rainfall data together with the crop factor (Kc), yield reduction factor (Ky), root zone depth (RzD) and root zone moisture (RzM)were used as input data for the second network to compute % yield reduction. Data for maize for the 2012-13 growing season was used for training the network and validating the estimated ETO and % yield reduction. The estimated ETO compared very well with the calculated values with R2 values of above 0.84. The estimated yield reduction % indicated even high accuracies with R2 values of above 0.91. The 2014-2015 growing season resulted in crop loss due to mid-season dry spells and the model predicted a 100% crop loss which means the farmer had to be compensated for the value equivalent to cost of inputs. The model has got potential to be used by insurance companies using weather based data and, with mobile banking transaction costs can be reduced.