Miracle-dz/UniFAR-FTUs huggingface dataset:
Corruption, Government Effectiveness and Human Development
in Sub-Saharan Africa

Aside economic factors causing low human development which have been extensively studied in literature, the implications of high level of corruption and weak governance prevalent in sub- Saharan African (SSA) countries have not been explored. The study assessed the effects of corruption, government effectiveness and their joint effect on human development in SSA. Data collected on thirty-seven (37) countries within the period of 2005 to 2018 were analyzed using system Generalized Method of Moment which was most suitable for the dataset. Results indicated that lagged human development index (P<0.01), government effectiveness (P<0.05), economic growth rate (P<0.1) and government health spending (P<0.1) had significant positive effect on human development while corruption and its interaction with government effectiveness did not. The results of Arrelano-Bond test of first order autocorrelation and second order autocorrelation of error term as well as the Sargan test and Hansen J test for validity of instrumental variables confirmed the validity of the model. The robustness of the estimation was established as the coefficient of the lagged dependent variable fell between the values in the fixed effect and pooled ordinary least square regression. The study recommended retraining and reorientation of government employees towards the mindset of effective service delivery and strong political will to achieve it, diversification of SSA economies alongside other growth stimulating policies such as reduced lending interest rate on loans meant for the real sector, improvement in the ease of doing business, improved funding of the health sector and proper monitoring of activities in the public service by concerned agencies to curb corruption where it is present.
Development of a Reduced Primary Reference Fuel Mechanism for Internal Combustion Engine Combustion Simulations

A reduced PRF mechanism was proposed for combustion simulations of PRF and diesel/gasoline fuels based on the latest LLNL mechanism. The reduced PRF mechanism consists of 73 species and 296 reactions. The major reaction pathways of the detailed mechanism were mostly retained in the reduced mechanism, which ensures its predictive capability, the ability to be extended to other fuels, and the high computational efficiency of the reduced mechanism. The important reaction pathways and reactions in the reduced mechanism are identified and discussed. Furthermore, the reaction rates of two reactions, HO2 + OH = HO2 + O2 and HO2 + HO2 = H2O2 + O2, in the hydrogen submechanism are discussed and updated. The reduced mechanism was validated with measured ignition delays, laminar flame speeds, premixed flame species concentrations, jet stirred reactor and shock tube species profiles, and PRF fuel HCCI and PPCI combustion and diesel/gasoline direct injection spray combustion data. The reduced mechanism predicts well t.
Contact Line Friction in Liquid–Liquid Displacement on Hydrophobic Surfaces

The dynamics of a receding water front displaced by (a) an immiscible droplet of dodecane and (b) an air bubble on smooth thiol and silane coated substrates has been investigated. For velocities below 0.02 m/s, the three phase contact line motion is captured by the molecular kinetic theory. The corresponding wetting parameters show a dependence on surface hydrophobicity, irrespective of the substrate chemistry. The contact line frictions for both liquid–liquid and liquid–vapor systems are directly compared by using an existing approach and a new model that adds the contributions of the individual fluid viscosities. For both systems, the contact line friction increases with the affinity of the fluids for the substrate. Three phase contact line motion occurs via the concerted movement of clusters of molecules or contact line segments, rather than through individual molecular displacements.
The Application of Gratitude Group Program to Increase Quality of Life Among Indonesian Elderly in Residential Home X Jakarta

The aim of this study is to determine the impact of gratitude group program on enhancing the quality of life of the elderly living in residential home. Living in residential home can make the elderly feel alianated and limited in doing activities related to their family members or friends. What they feel and perceive can affect their quality of life. According to WHO (1996), quality of life is the individual's perception of their position in life according to the cultural context and value systems in which they live and in relation to their goals, expectations, standards and concerns. One of the techniques to enhance the quality of life is to be grateful. Grateful experiences and expressions can help individuals build personal and interpersonal resources to deal effectively with stress and difficulties. Total subject in this study were 12 people. The research method used was quasi-experimental with randomized matched two-group design. The sampling technique used nonprobability sampling, purposive sampling. Data was analyzed using Wilcoxon signed-Rank Test with SPSS 16.00 for Windows. The results showed that score of the elderly quality of life increase significantly in experimental group with gratitude group program (Z = -2.226, p = 0.026 < 0.05) than in control group without any treatment (Z = -0.946 p = 0.344 > 0.05).
THE COMPARISON OF PLASMA MALONDIALDEHYDE LEVELS AMONG OSTEOPOROTIC AND NON-OSTEOPOROTIC POSTMENOPAUSAL WOMEN

Introduction: Osteoporosis is a bone metabolic disorder due to decreased of bone matrix and minerals. Oxidative stress refered as an elevation of reactive oxygen species (ROS) in the cells causing structural damages and functional loss, is contributed in the process of osteoporosis, but its association still in controversy. Herewith we report the comparison of the plasma malondialdehyde (MDA) levels, one of oxidative stress markers among osteoporotic postmenopausal women and without osteoporosis. Methods: An observational analytic study with cross-sectional approach among 40 postmenopausal women, grouped into two groups, osteoporosis (n=20) and non-osteoporosis (n=20) based on bone mineral density (BMD) score. The plasma MDA levels were measured from venous blood using ELISA. The difference between plasma MDA levels among both groups was analyzed using an independent T-test. Results: The characteristics of demography and clinic among both groups are relatively similar. However, there is a difference in the body weight and BMI. Furthermore, there is no significant differences of MDA levels between the two groups (292,03±61,02ng/ml for group with osteoporosis, and 315,25±73,86ng/ml for non-osteoporosis, p=0,286). Conclusions: There is no significant difference in plasma MDA levels among osteoporosis and non-osteoporosis postmenopausal women.
Study of electrical properties and estimation of average mobility and diffusion coefficients in several insulating liquids by dielectric spectroscopy

Electrical properties of cyclohexane, a pure mineral oil, a mineral oil with additive and a silicon oil are studied in thefrequency range of 10−2 – 105 Hz. The paper reviews theoretical and practical basics for wide range dielectric spectroscopymeasurements and puts into focus a method for estimating ionic mobility and diffusion coefficients in insulating liquidsvia data issued from low frequency spectra. Results obtained at different temperatures are presented and discussed.DOI : 10.34343/ijpest.2020. 14.e03006
A New Form of Financial Contagion: COVID-19 and Stock Market Responses

The COVID-19 pandemic has induced a different and more severe version of the contagion phenomenon. In this study, we examine the influence of the COVID-19 pandemic on six different stock markets. Empirical analyses are conducted for four different time intervals to reveal the effect of the COVID-19 pandemic. The modified ICSS test shows that the pandemic has led to structural breaks in the volatility of stock indexes. While break dates intensify around February 19–21, 2020 in most of the markets, for the Chinese stock market, the break appears approximately three weeks earlier, on January 30, 2020. The DCC-MVGARCH and DCC-MVFIGARCH models illustrate the effect of the COVID-19 pandemic on dynamic conditional correlations. According to the changes in unconditional correlation coefficients, although the relationship of the Chinese and Turkish stock markets weakens across 2005 to 2019, it displays a 20% rise following the pandemic. Some other market pairs also show soaring correlation coefficients, although these increases are lower, at approximately 10%.
High-dimensional Statistical Learning Techniques for Time-varying Limit Order Book Networks

This paper provides statistical learning techniques for determining the full own-price market impact and the relevance and effect of cross-price and cross-asset spillover channels from intraday transactions data. The novel tools allow extracting comprehensive information contained in the limit order books (LOB) and quantify their impacts on the size and structure of price interdependencies across stocks. For correct empirical network determination of such dynamic liquidity price effects even in small portfolios, we require high-dimensional statistical learning methods with an integrated general bootstrap procedure. We document the importance of LOB liquidity network spillovers even for a small blue-chip NASDAQ portfolio.
Inverse spin Hall effect in metallic heterostructures

The inverse spin Hall effect (ISHE) arises from spin dependent scattering. It signifies a conversion of a longitudinal spin current into a transversal charge current. This enables spin current sensors using conventional charge-based electronics leveraging advances in technology, e.g., towards the development of magnetization based universal memory concepts, and a fundamental understanding of physical properties of spin-dependent scattering. From an experimental point of view this PhD-thesis is placed in the greater context of magnetization dynamics. In metallic heterostructures consisting of atleast one ferromagnetic and one normal metal (non-magnetic) layer, a precessing magnetization in the ferromagnetic layer may facilitate a pure spin current across the interface into the normal metal (NM). The spin current generated by this so-called spin pumping effect is converted into a charge current by ISHE in NM. In steady-state this corresponds to a voltage drop along the normal metal which relates directly back to the amount of spin dependent scattering in NM and which is retained in one single parameter characterizing the material, the spin Hall angle. In this PhD-thesis this kind of experiment is used for the quest for materials which feature large spin Hall angles. To this end it is one of the central concerns to characterize and ultimately exclude all possible parasitic voltages, which naturally arise in an experimental setup towards magnetization dynamics. The main parasitic voltages in this respect are the ones caused by spin rectification due to anisotropic magnetoresistance in the ferromagnetic layer and the ones caused by electromagnetic induction in the measurement circuit. Ruling out these effects comprehensive and reliable estimations of the spin Hall angles for platinum, gold and of the alloys of both materials are conducted. Furthermore, the experimental approach of using a combination of spin pumping and ISHE is used to investigate the oscillating nature of spin currents which naturally result from spin pumping. This eventually leads to the observation of the ac-ISHE in platinum measuring voltages in the GHz-regime. This observation uncovers the interesting field of ac-spintronics.
A novel magnetic field generating machine with a wide range of tunable parameters to study in vitro cells

Background Extremely low-frequency magnetic field (ELF-MF) significantly induces apoptosis in cancer cells. To study the biological effects of the ELF-MF on tumor cells, we have designed and constructed a new exposure system that provides a uniform magnetic field with negligible temperature fluctuations during the exposure. Additionally, it provides ideal physiological conditions for live cells inside the incubator. This ELF-MF exposure system eliminates several limitations and disadvantages of other low frequency magnetic field systems; it generates a magnetic field with a frequency of 0 to 70 Hz with a maximum magnetic flux density of 150 mT. Methods The capabilities of the setup were examined using a 1 Hz, 100 mT magnetic field, at various exposure times, to induce apoptosis-mediated cell death in the MC4-L2 cell line. After exposure, apoptosis was assessed by flow cytometry. Results A biphasic response was observed in cells exposed to ELF-MF: at first a decreasing apoptotic rate during 2-12 hours exposure time was detected, after which apoptosis gradually increased during 24-120 hours of exposure. Conclusions We show that ELF-MF exposure with a frequency of 1 Hz and intensity of 100 mT induces apoptosis in MC4-L2 cancer cells in a time-dependent manner. These results show the significance of the long term studies of the ELF exposure effects.
Differences in soil evaporation between row and interrow positions in furrowed agricultural fields

Although large‐scale center pivot sprinkler irrigation has replaced surface irrigation in many locations, the agricultural practice of growing crops in furrows remains common. Still, how the presence of elevated soil rows under sprinkler irrigation influences evaporation losses remains unclear, even while quantifying nonproductive water losses becomes increasingly important for informing new water conservation and irrigation strategies. In this study at the Hermiston Agricultural Research and Extension Center in Hermiston, OR, soil evaporation from the row and interrow positions within potato (Solanum tuberosum L.) fields of contrasting irrigation timing (daytime vs. nighttime) was estimated based on hydrogen and oxygen isotope ratios. Samples collected throughout the 2016 growing season were analyzed and used to calculate soil evaporation (E) losses relative to applied irrigation (I). On average, row positions were more enriched in heavy isotopes than interrow positions, indicating that the evaporated fraction of applied irrigation (E/I) depends on the position. Within the day‐irrigated field, the estimated (mean ± standard deviation) E/I ratios determined from both stable isotopes for May, July, and September were 18 ± 8%, 10 ± 3%, and 19 ± 5% for row and 15 ± 6%, 7 ± 2%, and 12 ± 4% for interrow samples. Within the night‐irrigated field during these same months, the E/I ratios were 13 ± 12%, 16 ± 7%, and 13 ± 5% for row and 12 ± 7%, 9 ± 2%, and 6 ± 2% for interrow samples, respectively. For these fields, these results reveal that there is more evaporation from row, as compared with interrow, positions. Therefore, management practices for water conservation should account for larger nonproductive evaporation from within rows in order to minimize evaporative losses.
Searching for Needles in the Cosmic Haystack

Searching for Needles in the Cosmic Haystack by Thomas Ryan Devine Doctor of Philosophy in Computer Science West Virginia University Katerina Goseva-Popstojanova, Ph.D., Chair Searching for pulsar signals in radio astronomy data sets is a difficult task. The data sets are extremely large, approaching the petabyte scale, and are growing larger as instruments become more advanced. Big Data brings with it big challenges. Processing the data to identify candidate pulsar signals is computationally expensive and must utilize parallelism to be scalable. Labeling benchmarks for supervised classification is costly. To compound the problem, pulsar signals are very rare, e.g., only 0.05% of the instances in one data set represent pulsars. Furthermore, there are many different approaches to candidate classification with no consensus on a best practice. This dissertation is focused on identifying and classifying radio pulsar candidates from single pulse searches. First, to identify and classify Dispersed Pulse Groups (DPGs), we developed a supervised machine learning approach that consists of RAPID (a novel peak identification algorithm), feature extraction, and supervised machine learning classification. We tested six algorithms for classification with four imbalance treatments. Results showed that classifiers with imbalance treatments had higher recall values. Overall, classifiers using multiclass RandomForests combined with Synthetic Majority Oversampling TEchnique (SMOTE) were the most efficient; they identified additional known pulsars not in the benchmark, with less false positives than other classifiers. Second, we developed a parallel single pulse identification method, D-RAPID, and introduced a novel automated multiclass labeling (ALM) technique that we combined with feature selection to improve execution performance. D-RAPID improved execution performance over RAPID by a factor of 5. We also showed that the combination of ALM and feature selection sped up the execution performance of RandomForest by 54% on average with less than a 2% average reduction in classification performance. Finally, we proposed CoDRIFt, a novel classification algorithm that is distributed for scalability and employs semi-supervised learning to leverage unlabeled data to inform classification. We evaluated and compared CoDRIFt to eleven other classifiers. The results showed that CoDRIFt excelled at classifying candidates in imbalanced benchmarks with a majority of non-pulsar signals (>95%). Furthermore, CoDRIFt models created with very limited sets of labeled data (as few as 22 labeled minority class instances) were able to achieve high recall (mean = 0.98). In comparison to the other algorithms trained on similar sets, CoDRIFt outperformed them all, with recall 2.9% higher than the next best classifier and a 35% average improvement over all eleven classifiers. CoDRIFt is customizable for other problem domains with very large, imbalanced data sets, such as fraud detection and cyber attack detection.
Portfolio optimization for jump-diffusion risky assets with regime switching: A time-consistent approach

In this paper, an optimal portfolio selection problem with mean-variance utility is considered for a financial market consisting of one risk-free asset and two risky assets, whose price processes are modulated by jump-diffusion model, the two jump number processes are correlated through a common shock, and the Brownian motions are supposed to be dependent. Moreover, it is assumed that not only the risk aversion coefficient but also the market parameters such as the appreciation and volatility rates as well as the jump amplitude depend on a Markov chain with finite states. In addition, short selling is supposed to be prohibited. Using the technique of stochastic control theory and the corresponding extended Hamilton-Jacobi-Bellman equation, the explicit expressions of the optimal strategies and value function are obtained within a game theoretic framework, and the existence and uniqueness of the solutions are proved as well. In the end, some numerical examples are presented to show the impact of the parameters on the optimal strategies, and some further discussions on the case of \begin{document}$ n\geq 3 $\end{document} risky assets are given to demonstrate the important effect of the correlation coefficient of the Brownian motions on the optimal results.
How are Emotional and Physical Demands Associated with Job Dissatisfaction? Moderated by Marital Status

Although there has been extensive research on job satisfaction, the theoretical possibilities may be limited. In general, most of the research focuses only on job-demand factors. However, this study focuses on the emotional and physical demands on job satisfaction. Using the 5th wave of IFLS data, this study aims to determine the effect of marital status upon the relationship between emotional and physical demands on employee satisfaction in Indonesia. The results of research from 19,395 Indonesian employees show that marital status is a mediator in the relationship between emotional and physical demands on job satisfaction. The findings suggest that marital status underpins negative outcomes of emotional and physical demands on job satisfaction in Indonesia. Additionally, the present study found that gender differences affect job satisfaction. Traditional role values and gender concepts are discussed. demand; physical demands; marital status
Klotho inhibits H2O2‐induced oxidative stress and apoptosis in periodontal ligament stem cells by regulating UCP2 expression

Periodontitis, a human chronic inflammatory disease, has affected the lives of millions of individuals. Periodontal ligament stem cells (PDLSCs), derived from the periodontal ligament, exhibit tissue specificity and impaired differentiation ability and are closely associated with tissue regeneration in periodontitis. Klotho, a single‐pass transmembrane protein, has been reported to positively affect H2O2‐induced oxidative stress and inflammation in PDLSCs. The ultimate damage of oxidative stress stimulation in PDLSCs was cell apoptosis, which was also the major lesion in periodontitis. Thus, the present study aimed to figure out the effect of klotho on H2O2‐injured PDLSCs and its underlying mechanism to provide new therapeutic targets in periodontitis. The expression of klotho and uncoupling protein 2 (UCP2) was investigated in the gingival tissues, gingival crevicular fluid (GCF), and periodontal ligament stem cells (PDLSCs) in patients with chronic periodontitis. Then, under klotho treatment, oxidative stress was evaluated by measuring SOD and GSH‐PX levels. Cell apoptosis and cell necrosis were also detected by measuring the cell death‐relevant proteins, including Caspase‐3, BAX, Bcl, MLKL, RIP1, and RIP3. Finally, a rescue assay was performed by inhibiting the expression of UCP2. The results showed that klotho and UCP2 were downregulated in patients with chronic periodontitis. In addition, klotho upregulated the production of UCP2 in H2O2‐treated PDLSCs. Klotho inhibited H2O2‐induced oxidative stress and cellular loss in PDLSCs, moreover, the rescue assay suggested that UCP2 knockdown suppressed the effects of klotho on PDLSCs. In conclusion, this study showed that klotho inhibits H2O2‐induced oxidative stress and apoptosis in PDLSCs by regulating UCP2 expression. This novel discovery might provide a potential target for chronic periodontitis treatment.