The Implementation of Recruitment and Selection in Civil Service Institutions of Oromia National Regional State, Ethiopia

Ethiopia is known as a country with thousands of years of government structure. In contrast, the modern civil service structure is only about one hundred years old.It was established in 1907 during the reign of Emperor Menelik. However, for almost fifty-five years, there was no legal system that uniformly governed the newly established civil service institutions. In 1962, the first civil service law was enacted with the aim of establishing meritocratic, efficient and effective civil service structure governed by specified rules and procedures. Despite the initiative to improve the civil service and the new laws, the civil service failed to achieve its objectives. After 1991, the current government took initiative to reform the civil service procedures including the human resource management system. The issue of recruitment and selection was one of the components of HRM reform that aimed to achieve a merit-based system. Studies revealed, however, that the implementation process was not going well. This article assesses the implementation of the recruitment and selection process in civil service institutions of Oromia National Regional State. Accordingly, the findings reveal that though the government showed commitment in developing a system that properly guides the process of recruitment and selection, the implementation process is not on track to achieve the desired merit-based system in the civil service sector of the region

Africa In An Age Of Globalization

The global markets continue to grow in developing countries. Global markets have created new businesses and provided opportunities for global employers and individuals in developing countries. Through globalization of economies, jobs have been created which reduce unemployment rates. However, economic growth rates in Africa have been lagged behind other developing countries. This paper examines the importance of global business to Africa. Also, this study explores how African countries can strengthen their macroeconomic policies and structural reforms in order to achieve globalization of their economies. In addition, this study evaluates the current state and future direction of globalization in Africa

The Impact of Credit Risk Management on Financial Performance of Commercial Banks –Evidence from Eritrea

This study focuses on the impact of credit risk management on the performance of commercial banks in Eritrea. The main indicators used in this study are Return on Assets (ROA), Non-performing Loans Ratio (NPLR), Capital Adequacy Ratio (CAR), Loan and Advances Ratio (LAR) and Loan Loss Provision Ratio (LLPR). The researches collects data from Commercial Bank of Eritrea and Housing and Commerce Bank of Eritrea from 1998 to 2015. Descriptive and panel data regression analysis are used in order to test the relationship between the four indicators and the performance of commercial banks in Eritrea. The findings show that credit risk management is inversely associated with bank performance. The nonperforming loan, and loan and advances ratios significantly and negatively affected performance of the commercial banks. The result indicates that loan and advances ratio are negative but statistically insignificant. There is a positive relationship between CAR and ROA.  The significant positive relationship between loan loss provision and commercial banks performance in this study could indicate the presence of potential earning management activities by bank managers. Keywords: Performance, Credit risk management, Commercial Banks, Eritre

A Glance at Tropical Operations and Tropical Linear Algebra

The tropical semiring is ℝ ∪ {∞} with the operations x ⊕ y = min{x, y}, x ⊕ ∞ = ∞ ⊕ x = x, x ⊙ y = x + y, x ⊙ ∞ = ∞ ⊙ y = ∞. This paper explores how ideas from classical algebra and linear algebra over the real numbers such as polynomials, roots of polynomials, lines, matrices and matrix operations, determinants, eigen values and eigen vectors would appear in tropical mathematics. It uses numerous computed examples to illustrate these concepts and explores the relationship between certain tropical matrices and graph theory, using this to provide proofs of some tropical computations

Modeling Financial Swaps and Geophysical data Using the Barndorff-Nielsen and Shephard Model

This dissertation uses Barndoff-Nielsen and Shephard (BN-S) models to model swap, a type of financial derivative, and analyze geophysical data for estimation of major earthquakes. From empirical observation of the stock market activity and earthquake occurrence, we observe that the distributions have high kurtosis and right skewness. Consequently, such data cannot be captured by stochastic models driven by a Wiener process. Non-Gaussian processes of Ornstein-Uhlenbeck type are one of the most significant candidates for being the building blocks of models of financial economics. These models offer the possibility of capturing important distributional deviations from Gaussianity and thus these are more practical models of dependence structures. Introduced by Barndorff-Nielsen and Shephard these processes are not only convenient to model volatility in financial market, but have an independent interest for modeling stationary time series of various kinds. For the financial data we use BN-S models to price the arbitrage-free value of volatility, variance, covariance, and correlation swap. Such swaps are used in financial markets for volatility hedging and speculation. We use the S&P500 and NASDAQ index for parameter estimation and numerical analysis. We show that with this model the error estimation in fitting the delivery price is much less than the existing models with comparable parameters. For any given time interval, the earthquake magnitude data have three main properties: (1) magnitude is a non-negative stationary stochastic process; (2) for any finite interval of time there are only finite number of jumps; (3) the sample path of the magnitude of an earthquake consists of upward jumps (significant earthquake) and a gradual decrease (aftershocks). For such geophysical data we specifically use Gamma Ornstein Uhlenbeck processes driven by a Levy process to estimate a major earthquake in a certain region in California. Rigorous regression analysis is provided, and based on that, first-passage times are computed for different sets of data. Both applications demonstrate the significance of BN-S models to phenomena that follow non-Gaussian distributions

Population pharmacokinetic modelling for dose optimization of esomeprazole to treat early-onset preeclampsia

Rationale Esomeprazole is a proton pump inhibitor with preclinical efficacy data showing it lowers concentrations of soluble fms like tyrosine kinase 1 (sFlt-1) and soluble endoglin (sEng), pathognomonic biomarkers identified in preeclampsia. A randomized controlled trial, Preeclampsia Intervention with Esomeprazole (PIE) trial, was conducted in South African women diagnosed with early-onset preeclampsia to investigate efficacy, but it found no change in clinical outcome or biomarker concentrations. It was hypothesized that the 40 mg daily oral dose was not enough to achieve therapeutic exposure. This study investigated the pharmacokinetics of esomeprazole in patients with early- onset preeclampsia with the aim to optimize the dose for future clinical trials. Methods Pharmacokinetic data from ten pregnant patients with early-onset preeclampsia from the PIE trial, median (range) age 30 (21-43) years, weight 98.8 (56-126) kg, and gestational age 29 (26- 31) weeks, were included for model development. In addition, pharmacokinetic data from non- pregnant healthy volunteers consisted of a pooled dataset of 26 male and female subjects, median (range) age of 21 (18-27) years and weight 69 (54-89) kg, who received 40 mg esomeprazole daily. Analysis of the pharmacokinetic data in pregnant patients was performed using nonlinear mixed-effects modelling with allometric scaling on clearance (CL) and volume of distribution (Vd). Metabolite to parent area under the time-concentration curve (AUCsulf/AUCeso and AUChyd/AUCeso) ratios were compared between pregnant and non-pregnant to assess metabolic changes in pregnancy. Simulations were performed with the model to determine the nonlinear increase in AUC with higher doses and with repeated dosing in the pregnant patients. Simulation results were compared with the preclinical target unbound concentration (0.917 mg/L) and preclinical target unbound AUC0-24 (9.29 mg·h/L). Results A one compartment pharmacokinetic model with first-order elimination and transit compartment absorption best described the data. Model estimated apparent CL and apparent Vd (95% CI) were 19.2 (14.2-26) L/h and 44.2 (29.9-56.6) L, respectively. Median AUCsulf/AUCeso (IQR) for pregnant patients, 2.00 (1.35-2.61) , was significantly higher than that for non-pregnant subjects on day1, 0.700 (0.636-1.00) , and day5, 1.18 (0.981- 1.58) . Median AUChyd/AUCeso (IQR) for pregnant patients, 0.0543 (0.0500-0.0914) , was not significantly different from that of non-pregnant subjects on day5, 0.0777 (0.0569-0.108) but lower than that of non-pregnant subjects on day1, 0.188 (0.156- 0.227). Simulation results showed that predicted steady state unbound Cmax is between 0.0949 and 0.398 mg/L while the predicted unbound AUC0-24 in pregnant patients with the highest dose of esomeprazole used clinically, i.e.120 mg BID, is between 0.696 and 2.92 mg·h/L. Discussion/Conclusion Model estimated CL/F and Vd/F are higher than values previously reported by other population pharmacokinetic models. AUCm/AUCp comparisons showed that esomeprazole metabolism in pregnancy appears to have shifted to the CYP3A4 pathway. This means that the nonlinear AUC increase expected with dose escalation and with repeated dosing are not as significant as in nonpregnant. Simulations indicate that pregnant patients are unlikely to achieve the target concentration and exposure with the highest dose of esomeprazole registered. Further research is necessary to determine the target site of action of esomeprazole in preeclampsia, and the pharmacokinetic metric that correlates with efficacy

Predicting suicide risk from online postings in Reddit : the UGent-IDLab submission to the CLPysch 2019 Shared Task A

This paper describes IDLab’s text classification systems submitted to Task A as part of the CLPsych 2019 shared task. The aim of this shared task was to develop automated systems that predict the degree of suicide risk of people based on their posts on Reddit. Bag-of-words features, emotion features and post level predictions are used to derive user-level predictions. Linear models and ensembles of these models are used to predict final scores. We find that predicting fine-grained risk levels is much more difficult than flagging potentially at-risk users. Furthermore, we do not find clear added value from building richer ensembles compared to simple baselines, given the available training data and the nature of the prediction task