Miracle-dz/UniFAR-FTUs huggingface dataset:
International Journal of Science and Business

This paper study the location determinants of FDI inflow in Sudan, the study applied multivariate time series, Vector auto-regression using time-series data of 1980-2018. Variable include; market size, infrastructure, inflation rate, Debt, Dummy of investment incentive, and Terms of Trade openness. The empirical results revealed that there is a short-run causality relationship running from independents variable to FDI as specified in the study. Also, GDP, External debt, investment incentive, and inflation are important location determinants of FDI inflows to Sudan. The Granger Causality shows Uni-directional causality running from GDP, Inflation, TOP, inflation, and Dummy investment incentives to FDI. These results were consistent with the short-run vector autoregression results. Therefore for a country to be declared as attractive by MNC, it means that the above factors have to be significant, since the variable for infrastructure and terms of trade openness are insignificant, investors would choose to neglect Sudan. The outcome shows that GDP is a very important variable in determining the location choice of FDI. This suggests that authorities need to take into account factors that hamper the growth of the economy given its importance in attracting FDI inflows. Finally, Sudan should implements policies to encourage a fast-growing economy by improving its debt service payment, infrastructure, and its terms of trade openness and international cooperation. IJSB Accepted 21 June 2020 Published 22 June 2020 DOI: 10.5281/zenodo.3903279
Combustion Engine Test Bed System Identification Under the Presence of Cyclic Disturbances

In this article, a new approach for combustion engine test bed system identification is presented. Modern engine test beds are used to reduce development time by utilizing them for hardware-in-the-loop tests. For highly accurate and close-to-reality tests, model-based controllers are deployed, which rely on precise models of the test bed. Hereby, the main challenge is the unknown, cyclic disturbance of the engine due to compression and combustion of the air-fuel mixture. These disturbances also occur when the throttle is kept at zero and have a big impact on the measurements. Therefore, parameter estimation is strongly impeded. A method for dealing with these disturbances and embed them into the identification procedure in a two-step fashion is presented in this contribution. Further advantages of this new approach are that a physical model is obtained, but prior knowledge of parameters is not necessary. Moreover, disassembling of the test bed to perform separate parameter estimation is not needed and hence, the time consumption of the procedure is kept low. Experimental results on a 4-cylinder diesel engine test bed prove the feasibility and effectiveness of the proposed concepts.
A neutrosophic clinical decision-making system for cardiovascular diseases risk analysis

Cardiovascular diseases are the leading cause of death worldwide. Early diagnosis of heart disease can reduce this large number of deaths so that treatment can be carried out. Many decision-making systems have been developed, but they are too complex for medical professionals. To target these objectives, we develop an explainable neutrosophic clinical decision-making system for the timely diagnose of cardiovascular disease risk. We make our system transparent and easy to understand with the help of explainable artificial intelligence techniques so that medical professionals can easily adopt this system. Our system is taking thirtyfive symptoms as input parameters, which are, gender, age, genetic disposition, smoking, blood pressure, cholesterol, diabetes, body mass index, depression, unhealthy diet, metabolic disorder, physical inactivity, pre-eclampsia, rheumatoid arthritis, coffee consumption, pregnancy, rubella, drugs, tobacco, alcohol, heart defect, previous surgery/injury, thyroid, sleep apnea, atrial fibrillation, heart history, infection, homocysteine level, pericardial cysts, marfan syndrome, syphilis, inflammation, clots, cancer, and electrolyte imbalance and finds out the risk of coronary artery disease, cardiomyopathy, congenital heart disease, heart attack, heart arrhythmia, peripheral artery disease, aortic disease, pericardial disease, deep vein thrombosis, heart valve disease, and heart failure. There are five main modules of the system, which are neutrosophication, knowledge base, inference engine, de-neutrosophication, and explainability. To demonstrate the complete working of our system, we design an algorithm and calculates its time complexity. We also present a new de-neutrosophication formula, and give comparison of our the results with existing methods.
A novel lattice Boltzmann method for treatment of multicomponent convection, diffusion, and reaction phenomena in multiphase systems

approved: Goran N. Jovanovic In this work, a multicomponent lattice Boltzmann model is developed for the simulation of multiphase mixing, reactions, and separations processes. This model is unique in that diffusive mass transfer of a component in the model is driven by gradients of chemical potential. This fundamentally correct description of diffusion accurately captures the mass transfer in both single phase and multiple phase cases, making the model very versatile. To validate the model, analysis was performed at three levels: the component level, the phase level, and the systems level. At the component level, the accuracy of the mass and momentum transfer in the model was determined analytically and verified numerically. At the phase level, the chemical equilibrium and interface behavior in multiphase fluids was analyzed. Finally, at the systems level, the model was used to simulate a multiphase separations device used in the production of biodiesel. Copyright by James Muirhead Parker September 26, 2008 All Rights Reserved A Novel Lattice Boltzmann Method for Treatment of Multicomponent Convection, Diffusion, and Reaction Phenomena in Multiphase Systems by James Muirhead Parker A DISSERTATION submitted to Oregon State University in partial fulfillment of the requirements for the degree of Doctor of Philosophy Presented September 26, 2008 Commencement June 2009 Doctor of Philosophy dissertation of James Muirhead Parker presented on September 26, 2008.
Late Holocene environmental reconstructions using pollen: from morphological spectra to stable isotopes

Pollen are widespread and abundant microspores that are resistant against decay. Their frequent appearance in climate archives gives the opportunity to study vegetation cover changes and past environmental characteristics. Morphology-based pollen analysis focus on the taxonomic identification of pollen grains extracted out of sediment cores or other archives. The prime advantage of this approach is a worldwide applicability enabling temperature and precipitation reconstructions through quantitative methods. Stable isotope analysis is another approach using pollen in climate studies. Due to the immediate physiological responses of plants to environmental change, isotope values of pollen potentially provide high-resolution palaeoclimate information. Because this method for studying environmental changes is still in the need of a general assessment of its spectrum of applicability and limitations, this thesis focusses mainly on preliminary investigations of species-specific pollen-isotope variability and applicability in environmental studies. A case study of climate and vegetation reconstruction on the north-eastern QinghaiTibetan Plateau using classical morphology-based palynology is included in this dissertation as a first research topic. Pollen assemblages extracted out of the Daotang Pond record reveal environmental changes over the last 1200 years. The Medieval Warm Period occurred on the Qinghai-Tibetan Plateau between CE 850 and 1400. This climate anomaly was accompanied by regular East Asian Summer Monsoon penetrations and moisture input from the eastern lowland. Dry spells with diminished precipitation during the Medieval Warm Period are detectable out of the deposited pollen assemblages, but they have not been as severe as reported from other regions on the Qinghai-Tibetan Plateau. This is most likely caused by a humid micro-climate in the vicinity of the Qinghai Lake drainage basin. Features of the Little Ice Age (CE 1450 to 1950) can also be traced by analysing the pollen assemblages of the samples. Although the Little Ice Age is characterized by a weakened East Asian Summer Monsoon, the pollen record does not display a particularly dry environment during this time period, probably due to generally lower temperatures and diminished evapotranspiration. However, long distance transport of pollen is known
Analysis Of High Quality Agarwood Oil Chemical Compounds By Means Of Spme/Gc-Ms And Z-Score Technique

Currently, the grading of the agarwood oil to the high and low quality is done using manually such as human trained grader. It was performed based on the agarwood oil physical properties such as human experience and perception and the oil colour, odor and long lasting aroma. Several researchers found that chemical profiles of the oil should be utilized to overcome the problem facing by manual techniques i.e. human nose cannot tolerate with the many oils at the same time, so that accurate result can be obtained in grading the agarwood oil. The analysis involved of SPME/GC-MS and Z-score techniques have been proposed in this study to analyze the chemical compounds especially from the high quality samples of agarwood oil (Aquilariamalaccensis) from Malaysia. Two SPME fibers were used such as divinylbenzene-carboxen-polydimethylsiloxane (DVB-CAR-PDMS) and polydimethylsiloxane (PDMS) in extracting the oils’ compound under three different sampling temperature conditions such as 40˚C, 60˚C and 80˚C. The chemical compounds extracted by SPME/GC-MS were analyzed. The chemical compounds as identified by Z-score as significant compounds were discussed before the conclusion is made. It was found that 10-epi-ϒeudesmol, aromadendrane, β-agarofuran, α-agarofuran and ϒ-eudesmol were highlighted as significant for high quality agarwood oil and can be used as a marker compounds in classifying the agarwood oil.
Higher order assembling of the mycobacterial essential polar growth factor DivIVA/Wag31

How proteins localize at the pole remains an enigma. DivIVA/Wag31, which is an essential pole organizing protein in mycobacteria, can assemble at the negatively curved side of the membrane at the growing pole to form a higher order structural scaffold for maintaining cellular morphology and localizing various target proteins for cell-wall biogenesis. A single-site phosphorylation in Wag31 is linked to the regulation of peptidoglycan biosynthesis for optimal mycobacterial growth. The structural organization of polar scaffold formed by coiled-coil rich Wag31, which is a target for anti-tubercular agent amino-pyrimidine sulfonamide, remains to be determined. Here, we report biophysical characterizations of a phospho-mimetic (T73E) and a phospho-ablative (T73A) form of mycobacterial Wag31 using circular dichroism, small angle solution X-ray scattering and atomic force microscopy. While data obtained from both variants of Wag31 in solution states suggested formation of alpha-helical, large, elongated particles, their structural organizations were different. Atomic force microscopic images of Wag31 indicate polymer formation, with occasional curving, sharp bending and branching. Observed structural features in this first view of the polymeric forms of Wag31 suggest a basis for higher order network scaffold formation for polar protein localization.
Survey of Knowledge Graph Approaches and Applications

: With the advent of the era of big data, knowledge engineering has received extensive attention. How to extract useful knowledge from massive data is the key to big data analysis. Knowledge graph technology is an important part of artificial intelligence, which provides a method to extract structured knowledge from massive texts and images, and has broad application prospects. The knowledge base with semantic processing capability and open interconnection ability can be used to generate application value in intelligent information services such as intelligent search, intelligent question answering and personalized recommendation. Although knowledge graph has been applied to various systems, the basic theory and application technology still need further research. On the basis of comprehensively expounding the definition and architecture of knowledge graph, this paper reviews the key technologies of knowledge graph construction, including the research progress of four core technologies such as knowledge extraction technology, knowledge representation technology, knowledge fusion technology and knowledge reasoning technology, as well as some typical applications. Finally, the future development direction and challenges of the knowledge graph are prospected.
Eco-evolutionary partitioning metrics: a practical guide for biologists

It is well-known that ecological and evolutionary processes can occur on similar time scales resulting in eco-evolutionary dynamics. One of the main questions in eco-evolutionary dynamics involves the assessment of the relative contribution of evolution, ecology and their interaction in the eco-evolutionary change under study. This has led to the development of several methods aimed to quantify the contributions of ecology and evolution to observed trait change, here referred to as eco-evolutionary partitioning metrics. This study provides an overview on currently-used partitioning metrics with a focus on methods that can quantify evolutionary and non-evolutionary contributions to population and community trait change. I highlight key differences between these metrics found in previous studies. Additionally, I also provide a detailed comparison between the ‘Geber’ method and the reaction norm approach. Next, I provide a guideline for researchers to assess which metrics are best suited for their data, give an overview on the type of data needed for these metrics, and how this data can be collected with a focus on community data.
ECOLOGICAL CHARACTERISTICS AND HABITAT PREFERENCES OF OSTRACODA (CRUSTACEA) WITH A NEW BISEXUAL POPULATION RECORD (MUĞLA, TURKEY)

In order to compare the ecological characteristics of non-marine ostracods with different reproductive modes, 68 sites including 11 different habitat types were examined in the province of Muğla during July of 2014. A total of 28 taxa were found and 11 of them were new reports for Muğla. Sexual populations of Psychrodromus olivaceus and P. fontinalis were encountered from the same sampling site. Males of the latter species were reported for the first time from Turkey. The female/male ratio of these species was higher at low altitudes while it was about the same at medium altitudes. Numbers of species in sexual and/or parthenogenetic populations with/without swimming setae and individuals in natural and artificial habitats did not show significant difference (P > 0.05). Troughs were described as the richest habitats for ostracods. The first two axes of Canonical Correspondence Analysis explained 66.2% of the relationships between species and environmental variables when the water temperature was the most effective factor on species composition (P < 0.01). Results suggest that type of reproductive modes did not show significant relationship with species distribution among different water bodies. Hence, it seems distribution of species is most probably affected by several biotic and abiotic factors.
A comparative study of biomarker gene selection methods in presence of outliers

The main purpose of gene expression data analysis is to identify the biomarker genes by comparing the gene expression levels between two different groups or conditions. There are several methods to select biomarker genes and many comparative studies have been performed to select the appropriate method. However, they did not consider the problems of outliers in their data sets though it is very essential to select the method from robustness point of view due to outliers may occur in the different steps of the gene expression data generating process. In this paper, it is evaluated the performance among five popular statistical biomarker gene selection methods viz. T-test, SAM, LIMMA, KW and FCROS using both simulated and real gene expression data sets in absence and presence of outliers. In the simulated data analysis, it was demonstrated the performance of these methods in terms of different performance measures such as TPR, TNR, FPR, FNR and AUC and based on these measures, it was found that in absence of outliers, for both small-and-large sample cases all the methods perform almost similar. Whereas, in presence of outliers, for small-sample case only the FCROS method perform well than other methods. From a real colon cancer data analysis, it was elucidated that FCROS method identified additional 59 genes that were not detected by the other methods and most of them belongs to the different cancer related pathways.J. bio-sci. 25: 9-16, 2017
EPfuzzer: Improving Hybrid Fuzzing with Hardest-to-reach Branch Prioritization

Hybrid fuzzing which combines fuzzing and concolic execution, has proved its ability to achieve higher code coverage and therefore find more bugs. However, current hybrid fuzzers usually suffer from inefficiency and poor scalability when applied to complex, real-world program testing. We observed that the performance bottleneck is the inefficient cooperation between the fuzzer and concolic executor and the slow symbolic emulation. In this paper, we propose a novel solution named EPfuzzer to improve hybrid fuzzing. EPfuzzer implements two key ideas: 1) only the hardest-to-reach branch will be prioritized for concolic execution to avoid generating uninteresting inputs; and 2) only input bytes relevant to the target branch to be flipped will be symbolized to reduce the overhead of the symbolic emulation. With these optimizations, EPfuzzer can be efficiently targeted to the hardest-to-reach branch. We evaluated EPfuzzer with three sets of programs: five real-world applications and two popular benchmarks (LAVA-M and the Google Fuzzer Test Suite). The evaluation results showed that EPfuzzer was much more efficient and scalable than the state-of-the-art concolic execution engine (QSYM). EPfuzzer was able to find more bugs and achieve better code coverage. In addition, we discovered seven previously unknown security bugs in five real-world programs and reported them to the vendors.
Implications of Rewards and Punishments for Content Generations by Key Opinion Leaders

: Nowadays, e-commerce platforms have increasingly relied on contents generated by key opinion leaders to engage customers and drive product sales. To stay on top of the growth, e-commerce content platforms have introduced rewards and punishments policies to ensure content quality. However, effectiveness has remained less clear. Besides, there is a dearth of research that focuses on such performance-based output control in the extant platform governance and user-generated content (UGC) literature. In this study, based on the reinforcement theory and UGC literature, we investigate the effects of monetary rewards and punishments on the quantity and quality of contents generated by KOLs in the e-commerce content platform context. Using data collected from JD WeChat Shopping Circle, we empirically testified our hypotheses. Our results indicate that punishments significantly increase the quantity and quality of content generated by KOLs. Monetary rewards only have significantly positive effects on the quality of KOLs' generated content. Nevertheless, the magnitude of the effects of monetary rewards is larger compared with that of punishments. Theoretical and practical implications are discussed.
Direct Generation of OAM Mode-Group and Its Application in LoS-MIMO System

A partial slotted curved waveguide leaky-wave antenna which can directly generate orbital angular momentum (OAM) mode-groups (MG) with high equivalent OAM order <inline-formula> <tex-math notation="LaTeX">$l_{e}=\pm 40$ </tex-math></inline-formula> at 60 GHz is proposed in this letter. This partial arc slotted antenna is designed based on the circular traveling-wave antenna which can generate a single mode conventional OAM wave, so it can be termed as a partial arc transmitting (PAT) scheme compared with the full <inline-formula> <tex-math notation="LaTeX">$2\pi $ </tex-math></inline-formula> aperture slotting of the circular traveling-wave antenna. The full-wave simulation results show that the generated OAM MGs present a high gain beam with a helical phase distribution. Thus it can be used in a MG based line-of-sight (LoS) multiple-in-multiple-out system (MG-MIMO), whose performance is numerically analyzed. These MGs can improve the signal-to-noise ratio (SNR) and decrease the spatial correlation of sub-channels, thereby the MG-MIMO has a better performance in terms of capacity or BER than conventional MIMO.