Miracle-dz/UniFAR-FTUs huggingface dataset:
A Coupled Finite Difference Material Point Method andIts Application in Explosion Simulation

The material point method (MPM) discretizes the material domain by a set of particles, and has showed advantages over the mesh-based methods for many challenging problems associated with large deformation. However, at the same time, it requires more computational resource and has difficulties to construct high order scheme when simulating the fluid in high explosive (HE) explosion problems. A coupled finite difference material point (CFDMP) method is proposed through a bridge region to combine the advantages of the finite difference method (FDM) and MPM. It solves a 3D HE explosion and its interaction with the surrounding structures by dividing the problem domain into FDM region and MPM region in space. FDM is employed to simulate the region where the detonation products disperse into the surrounding air, while the FSI region is simulated by MPM. A bridging region is employed to exchange the information. In the bridge region, MPM provides the boundary condition for FDM region by mapping the variables from MPM background grid nodes to FDM fictitious points, while FDM provides the boundary condition for MPM region by mapping the variables from FDM cell-centre points to MPM interface grid nodes. The transportation between the two computational regions is implemented by moving particles in the bridge region. Numerical results are in good agreement with those of theoretical solutions, empirical formula and experiments. No obvious interface effect are observed in the bridge region in numerical tests.
NOVEL BROADBAND TERAHERTZ NEGATIVE REFRACTIVE INDEX METAMATERIALS: ANALYSIS AND EXPERIMENT

Broadband planar and non-planar negative refractive index (NRI) metamaterial (MTM) designs consisting of a periodically arranged split ring resonator and wire structures are developed in the terahertz (THz) frequency regime using the Finite-Difference Time- Domain (FDTD) method. The novel MTM designs generate a broad negative index of refraction (NIR) passband approximately two and a half times higher than those of the conventional SRR/wire structures, by using the same dimensions. Numerical simulations of wedge- and triangle-shaped metamaterials are used to prove the negative refractive index of the models. The fabricated MTMs exhibit passband characteristics which are in good agreement with the model results. The parametric studies of correlated factors further support these outcomes.
Optimal Alarm Systems for Count Processes

In many phenomena described by stochastic processes, the implementation of an alarm system becomes fundamental to predict the occurrence of future events. In this work we develop an alarm system to predict whether a count process will upcross a certain level and give an alarm whenever the upcrossing level is predicted. We consider count models with parameters being functions of covariates of interest and varying on time. This article presents classical and Bayesian methodology for producing optimal alarm systems. Both methodologies are illustrated and their performance compared through a simulation study. The work finishes with an empirical application to a set of data concerning the number of sunspot on the surface of the sun.
MetaReg: Towards Domain Generalization using Meta-Regularization

Training models that generalize to new domains at test time is a problem of fundamental importance in machine learning. In this work, we encode this notion of domain generalization using a novel regularization function. We pose the problem of finding such a regularization function in a Learning to Learn (or) meta-learning framework. The objective of domain generalization is explicitly modeled by learning a regularizer that makes the model trained on one domain to perform well on another domain. Experimental validations on computer vision and natural language datasets indicate that our method can learn regularizers that achieve good cross-domain generalization.
New sol-gel formulations to increase the barrier effect of a protective coating against the corrosion and wear of galvanized steel

This study proposes a new pretreatment method that uses alkoxide precursors with a plasticizing agent; the purpose of this study is to improve the electrochemical and mechanical properties of a galvanized steel surface. Galvanized steel was covered with a hybrid film obtained from a sol that consisted of two alkoxide precursors, 3 - (trimethoxysilylpropyl) methacrylate (TMSM) and tetraethoxysilane (TEOS), with nitrate cerium in a concentration of 0.01 M and a polyethylene glycol (PEG) plasticizer. The hybrid coatings were obtained by dip-coating method with various concentrations of plasticizer (0, 20, 40 and 60 g.L-1). The hybrid films were analyzed by scanning electron microscopy (SEM), profilometry, contact angle measurements, a tribometer with the type-setting ball on the plate and electrochemical tests. The addition of the plasticizer into the hybrid films improves the corrosion resistance behavior compared to the sample without the plasticizer. The addition of 20 g.L-1 of plasticizer showed the best performance in the electrochemical tests. The mechanical behavior results indicated that higher PEG concentrations resulted in films with enhanced durability.
Provable Variational Inference for Constrained Log-Submodular Models

Submodular maximization problems appear in several areas of machine learning and data science, as many useful modelling concepts such as diversity and coverage satisfy this natural diminishing returns property. Because the data defining these functions, as well as the decisions made with the computed solutions, are subject to statistical noise and randomness, it is arguably necessary to go beyond computing a single approximate optimum and quantify its inherent uncertainty. To this end, we define a rich class of probabilistic models associated with constrained submodular maximization problems. These capture log-submodular dependencies of arbitrary order between the variables, but also satisfy hard combinatorial constraints. Namely, the variables are assumed to take on one of — possibly exponentially many — set of states, which form the bases of a matroid. To perform inference in these models we design novel variational inference algorithms, which carefully leverage the combinatorial and probabilistic properties of these objects. In addition to providing completely tractable and well-understood variational approximations, our approach results in the minimization of a convex upper bound on the log-partition function. The bound can be efficiently evaluated using greedy algorithms and optimized using any first-order method. Moreover, for the case of facility location and weighted coverage functions, we prove the first constant factor guarantee in this setting — an efficiently certifiable e/(e-1) approximation of the log-partition function. Finally, we empirically demonstrate the effectiveness of our approach on several instances.
Antagonistic potential of selected fungal and bacterial biocontrol agents against Colletotrichum truncatum of soybean seeds

Ten fungal and bacterial biocontrol agents (BCAs) were evaluated in vitro for their antagonistic potential against Colletotrichum truncatum isolated from soybean seeds. Two fungal BCAs namely Trichoderma virens isolate UPM23 and Trichoderma harzianum isolate UPM40 and a bacterial BCA namely Pseudomonas aeruginosa isolate UPM13B8 strongly inhibited the growth of C. truncatum based on high PIRG values in dual culture and culture filtrate tests. Studies on the mechanism of action using mycoparasitism technique and antibiosis observed under light microscope revealed that T. virens and T. harzianum inhibited the growth of C. truncatum by coiling and penetration into the hyphae. Consequently, the hyphae of C. truncatum became malformed and swollen. Pseudomonas aeruginosa also caused mycelial malformation; the mycelia turned vacuoled and swollen in or at tips of hyphae. Pseudomonas aeruginosa gave the highest PIRG value in the culture filtrate test, suggesting that antibiosis could be the main mechanism of antagonism. No inhibitory effect was observed on soybean seeds and seedlings when the seeds were artificially inoculated with T. virens, T. harzianum and P. aeruginosa. On the contrary, T. virens and T. harzianum were found to enhance seed germination and seedling establishment, while P. aeruginosa enhanced fresh and dry weights of seedlings.
The Effect of Strength Training and Consumption of Glutamine Supplement on GH/IGF1 Axis

Physical activity and diet are factors that influence the body's structure. The purpose of this study was to compare the effects of four weeks of resistance training, and glutamine supplement consumption on growth hormone (GH), and Insulin-like growth factor 1 (IGF-1) Axis. 40 amateur male bodybuilders, participated in this study. They were randomly divided into four equal groups, Resistance (R), Glutamine (G), Resistance with Glutamine (RG), and Control (C). The R group was assigned to a four week resistance training program, three times/week, three sets of 10 exercises with 6-10 repetitions, at the 80-95% 1RM (One Repetition Maximum), with 120 seconds rest between sets), G group is consuming l-glutamine (0.1 g/kg-1/day-1), RG group resistance training with consuming L-glutamine, and C group continued their normal lifestyle without exercise training. GH, IGF1, IGFBP-III plasma levels were measured before and after the protocol. One-way ANOVA indicated significant change in GH, IGF, and IGFBP-III between the four groups, and the Tukey test demonstrated significant increase in GH, IGF1, IGFBP-III plasma levels in R, and RG group. Based upon these findings, we concluded that resistance training at 80-95% 1RM intensity, and resistance training along with oral glutamine shows significantly increase secretion of GH, IGF-1, and IGFBP-III in amateur males, but the addition of oral glutamine to the exercise program did not show significant difference in GH, IGF-1, and IGFBP-III.
Pitfalls in the European Enlargement Process: Financial Instability and Real Divergence

Many of the EU accession countries have announced that they will not only try to enter the EU as quickly as possible but also to adopt the euro at an early date. This is justified by the effort to avoid the danger of financial instability in the period prior to euro-introduction. However, by trying to avoid this danger, the CEECCs, at least the (economically, institutionally and technologically) less developed, may run into another danger or pitfall, namely of real divergence (or very slow real convergence). The paper investigates these dangers or pitfalls. It argues that for some accession countries the costs of entry at an early date may be very high, and that there may also be negative spillovers for the other accession countries and for the EU core countries.
BEŞ FAKTÖR KİŞİLİK ÖZELLİKLERİ İLE İŞ PERFORMANSI ARASINDAKİ İLİŞKİLER: BEŞ YILDIZLI OTELLER ÜZERİNE BİR UYGULAMA

The main purpose of this study is to investigate the relationship between five factor personality traits and job performance levels of five-star hotel employees. In addition to this, it is also a sub-objective to examine the relationships between the demographic characteristics of the employees and five factor personality traits and job performance levels. In the study, 372 employees from 73 fivestar hotels in Alanya were consulted. Survey technique was used to collect data. As a result of the research, it was determined that there were statistically significant relationships between the five factor personality traits and job performance of the employees. Also, it was concluded that the five factor personality traits and job performance levels of the employees differ significantly according to the demographic characteristics of the employees.
Hitting a moving target: inhibition of the nuclear export receptor XPO1/CRM1 as a therapeutic approach in cancer

Cellular homeostasis crucially relies on the correct nucleocytoplasmic distribution of a vast number of proteins and RNA molecules, which are shuttled in and out of the nucleus by specialized transport receptors. The nuclear export receptor XPO1, also called CRM1, mediates the translocation of hundreds of proteins and several classes of RNA to the cytoplasm, and thus regulates critical signaling pathways and cellular functions. The normal function of XPO1 appears to be often disrupted in malignant cells due to gene mutations or, most commonly, aberrant overexpression. Due to its important physiological roles and its frequent alteration in human tumors, XPO1 is a promising target for cancer therapy. XPO1 inhibitors have undergone extensive testing as therapeutic agents in preclinical models of cancer, with promising results. One of these inhibitors, Selinexor, is currently being evaluated in multiple clinical trials of different types of solid tumors and hematological malignancies. Here, we review several key aspects of XPO1 function, as well as the mechanisms that may lead to its alteration in cancer, and provide an update on the status of XPO1 inhibitors being developed as drugs for cancer therapy, including the definitive results of the first clinical trials with Selinexor that have been recently published.
Attribute extraction and classification using rough sets on a lymphoma dataset

In this paper, we describe a rough sets approach to classification and attribute extraction of a small biomedical dataset. The dataset contains 148 entries with 19 attributes on patients that were suspected to have a lymphoma. Our primary goal was to be able to create a set of rules that allow the prediction of the decision class based on the values of relevant attributes. Our preliminary study of this dataset indicated that seven of the 19 attributes were predictive in this dataset. Our classification accuracy was approximately 85%, with a high sensitivity and specificity. In addition to the promising classification results, rough sets provided a means of dimensionality reduction and rule generation.
Technology Transferring Performance of Chinese Universities: Insights from Patent Licensing Data

This paper had collected the patent licensing documents of all Chinese universities and made a comprehensive study on licensing performance. With a whole set of data from SIPO, the exact licensing frequency number and licensing propensity number of Chinese universities had been obtained for the first time. On average, 16.03 patents (6%) per university had been licensed out to the industry, which is much lower than expectations. The frequency of licensing, propensity of licensing, number of partners (licensees), number of patent stocks, local-transfer ratio and the distribution of licensing frequency in terms of university-firm distance had been obtained in details. Five hypotheses had been made to discover the variances in university licensing performance. With the ANOVA technique, five hypotheses had been confirmed within the dataset, which had revealed a significant effect of patent stocks, local economic performance, central government support, existence of TTO and local government administration on university licensing performance.
Incidence and Risk Factors of Twin Pregnancy at Jimma University Specialized Hospital, Southwest Ethiopia

Background: The incidence of twin pregnancy is increasing all over the world because of assisted reproductive technology or spontaneously as a result of numerous risk factors. It is associated with increased risk of maternal and neonatal complications both in the developed and developing countries, which in turn increase financial, emotional, personal and social costs to the twins themselves and their families. Thus, determining its magnitude and identifying the risk factors are crucial for possible prevention and better interventions. Method: Hospital-based prospective and case-control studies were conducted. To determine the incidence of twin pregnancy, all the 3812 deliveries conducted from December 01, 2012 to November 30, 2013 at Jimma University Specialized Hospital were followed from the time of admission to labor ward to the expulsion of fetus. To identify the risk factors for twin pregnancies, all 144 twin deliveries happened were taken as cases and 288 controls were randomly selected from the 3668 single ton-deliveries happened, with the ratio of 1:2. All the necessary data were collected by interviewing mothers, for both the cases and controls, by using structured questionnaire. The data were analyzed by using SPSS for windows version 20.0. Multivariate logistic regression analysis was done to identify risk factors for twin pregnancy. Odds ratios with 95% confidence intervals were used as measure of associations. Results: From 3812 deliveries conducted in the year period, 144 were twins making an incidence of 37.7 per 1000 deliveries. Family history of twinning (OR=9.16, 95% CI: 4.73, 17.74), oral contraceptive pill use prior to pregnancy (OR=2.14, 95% CI: 1.12, 4.08), household monthly income of 50-100 USD (OR=1.94, 95% CI: 1.08, 3.50) and >100 USD (OR=2.18, 95% CI: 1.10, 4.33) were found to increase the risk of twin pregnancy significantly. Conclusion: The study found high incidence of twin pregnancy. Family history of twinning, household income of ≥50 USD and oral contraceptive use prior to pregnancy were identified as risk factors for twin pregnancy. Mothers with identified risk factors should be targeted by nearby health facility in order to make the diagnosis of twin pregnancy earlier so that complications can be picked earlier and managed.
The Impact of Structured Input and Consciousness Raising Tasks on the Acquisition of Implicit and Explicit Knowledge of EFL Learners

During the past decades, the distinction between implicit and explicit knowledge and how they could be developed through instruction have always been controversial issues for cognitive psychologists and second language acquisition (SLA) researchers. The present study was aimed at investigating the effects of two different input-based tasks (Structured Input and Consciousness Raising) on the acquisition of implicit and explicit knowledge of English active causative structure by EFL learners. Seventy three female English language learners participated in this study. Participants were divided into two experimental groups, one was provided with structured input activities and the other with consciousness raising activities. The participants’ implicit and explicit knowledge of the target structure was assessed through Timed Grammaticality Judgment and Untimed Grammaticality Judgment respectively before and after the treatment. The results of Paired and Independent Samples t-test analyses revealed that both C-R tasks and SI tasks resulted in the acquisition of both implicit and explicit knowledge, with C-R having more significant impact on the explicit knowledge. The findings provided indirect positive support for the interface hypothesis.
Comparative Analysis of Antihistamines and Nonsteroidal Anti-inflammatory Drugs (NSAIDs): Properties, Structure and Prediction of New Potential Drugs

Aims: To determine the molecular properties of common antihistamines and non-steroidal antiinflammatory agents (NSAIDs). To identify interrelationships among these two groups of drugs utilizing pattern recognition methods and statistical analysis. Study Design: After determination of molecular properties, values thereof are examined using pattern recognition methods and other numerical analysis for underlying relationships and similarities. Place and Duration of Study: Durham Science Center, University of Nebraska, Omaha, Nebraska from September 2016 to January 2017. Methodology: Thirty compounds were identified as antihistamines and 27 compounds identified as NSAIDs. Properties such as Log P, molecular weight, polar surface area, etc. are determined. Molecular properties are compared applying methods such as K-means cluster analysis, nearest neighbor joining, box plots, and statistical analysis in order to determine trends and underlying Original Research Article Bartzatt; JAMPS, 12(3): 1-18, 2017; Article no.JAMPS. 32695 2 relationships. Pattern recognition techniques allow elucidation of underlying similarities. Results: The molecular properties of all 57 drugs are tabulated for comparison and numerical analysis. Evaluation by Kruskal-Wallis test and one-way ANOVA indicated that antihistamines and NSAIDs’ values of Log P have equal medians and equal means. However, values of polar surface area (PSA) and number of rotatable bonds for these two groups do not have equal means and medians. Box plots indicated that Log P, PSA, and molecular weight values have significant overlap in range. Neighbor-joining method showed which drugs are most similar to each other. Kmeans cluster analysis also divided these 57 drugs into six groups of highest similarity. Principal coordinates analysis (PCoA) with 95% ellipses indicated all but four of the drugs fall within a 95% confidence region. Multiple regression analysis generated mathematical relationship for prediction of new drugs. Conclusion: These two groups of drugs show compelling similarities. PCoA showed all but four of 57 drugs come within a 95% confidence ellipsis. Neighbor joining and K-means cluster analysis showed drugs having similarities between the two groups.
Commercial Lending and Distance: Evidence from Community Reinvestment Act Data

A number of large banking organizations have substantially broadened the distances at which they are willing to extend commercial loans, but there is also evidence to suggest that this has occurred primarily at the high side of the distribution of lending distances. In this paper, we employ a new source of data to examine the relationship between lending decisions and distance between lender and borrower for that part of the distance distribution where, arguably, most of the competitive interactions among lenders still occur.We report three basic findings: (1) distance operates as a deterrent to lending, even within areas traditionally defined as local markets, (2) distance is more of a deterrent for small banks than for larger organizations, even within these areas, and (3) for those commercial loans made within areas currently treated by regulators as markets, distance has not been declining in importance. Indeed, a preponderance of the evidence suggests that it is becoming, if anything, more of a factor. Possible explanations and policy implications are discussed.
Effects of the colonial cyanobacterium Trichodesmium spp. on bacterial activity

We measured rates of particulate and dissolved primary production (DOCp) as well as bacterial production (BP) in order to determine the effect of freshly produced photosynthates on heterotrophic bacteria. During a 1 mo study carried out on samples from the southwestern lagoon of New Caledonia, we observed 2 different phytoplanktonic communities. The first was a mixed com- munity, dominated by diatoms and with a low abundance of Trichodesmium spp. (10% total phyto- plankton cells) and the second community was dominated by Trichodesmium spp. (up to 98% total phytoplankton cells). Chlorophyll a normalised total (particulate + dissolved) primary production rates were twice as high in the mixed community compared to the Trichodesmium spp. dominated community. The percentage of extracellular release (PER), calculated as the percentage of DOCp divided by total primary production (TOCp), reached 8% in the mixed community; in contrast, rates were much lower in the Trichodesmium spp. community and remained close to 1%. In terms of BP, activities were higher in the mixed community and were generally higher in light incubations than in the dark. In contrast, in the Trichodesmium spp. dominated community, bacterial activity was much lower and decreased with increasing Trichodesmium spp. abundance. This decrease in bacterial activity could not be explained by a decrease in bacterial abundance. This suggests that the propor- tion of active bacteria was much lower during the Trichodesmium spp. bloom.