Miracle-dz/UniFAR-FTUs huggingface dataset:
The Relation Between Economic Growth and Foreign Direct Investment During the Economic Crisis in the European Union

The goal of this research is to investigate the relationship between economic growth and foreign direct investment inflows in the European Union (EU-28) in the period of the recent economic crisis. Panel data approach and Bayesian techniques are employed to solve the problem of a short set of data (2008–2014). The panel data approaches (panel vector-autoregressive model and Bayesian random effect models) identified a reciprocal and positive relationship between FDI and economic growth in EU-28 starting with 2008. The individual approach based on Bayesian linear regressions identified this tendency as being specific for most of the EU-28 countries. However, there are some countries for which higher FDI did not generate economic growth and some countries where higher GDP did not attract more FDI and FDI did not bring economic growth. According to cluster analysis, the disparities among countries regarding the FDI distribution according to GDP growth and GDP rate distribution according to FDI diminished in 2014 compared to 2008. The basic conclusion is that on overall in the European Union there was a reciprocal relationship between economic growth and FDI since the beginning of the crisis with a tendency of reducing disparities between countries in attracting FDI.
Efficient Discovery of Temporal Inclusion Dependencies in Wikipedia Tables

Inclusion dependencies (INDs) demand that the value set that appears in one attribute is contained in the value set that appears in a different attribute. The automatic discovery of INDs in static data is a well-researched topic with many use-cases, such as foreign key discovery. However, data is usually not static, in fact data changes frequently, especially on Wikipedia. The availability of change data allows us to take a fresh look at the discovery of INDs in Wikipedia tables, by taking into account not only the current state of a dataset, but also its past versions. In this work, we formally define the concept of temporal INDs (tINDs) and introduce several relaxations, allowing for the discovery of tINDs in dirty data. We present an efficient index structure for unary tIND search that returns all valid tINDs for a user query in 63 milliseconds on average, allowing users to interactively explore tIND relationships in Wikipedia tables. Furthermore, we can use our index to discover the set of all valid tINDs between 1.3 million attributes from Wikipedia tables in less than three hours. Finally, we show empirically, that tIND discovery can help to find genuine INDs much more reliably than IND discovery on static data.
Tracking network state from combined SCADA and synchronized phasor measurements

Initiated by the authors' previous work on state reconstruction from a limited number of synchrophasors [1], this paper goes one step further by exploring the possibility to track the network state using both SCADA and synchronized phasor measurements. When a SCADA measurement is received, it is used in the next state reconstruction; otherwise, it is replaced by a pseudo-measurement stemming from the previous state reconstruction. The approach resorts to a standard weighted least squares formulation and Hachtel's augmented matrix method. State reconstruction is intended to be used at a much higher rate than classical state estimation, for instance every second. It has been validated using simulated measurements obtained from detailed time simulation.
Initializing Bayesian Hyperparameter Optimization via Meta-Learning

Model selection and hyperparameter optimization is crucial in applying machine learning to a novel dataset. Recently, a subcommunity of machine learning has focused on solving this problem with Sequential Model-based Bayesian Optimization (SMBO), demonstrating substantial successes in many applications. However, for computationally expensive algorithms the overhead of hyperparameter optimization can still be prohibitive. In this paper we mimic a strategy human domain experts use: speed up optimization by starting from promising configurations that performed well on similar datasets. The resulting initialization technique integrates naturally into the generic SMBO framework and can be trivially applied to any SMBO method. To validate our approach, we perform extensive experiments with two established SMBO frameworks (Spearmint and SMAC) with complementary strengths; optimizing two machine learning frameworks on 57 datasets. Our initialization procedure yields mild improvements for low-dimensional hyperparameter optimization and substantially improves the state of the art for the more complex combined algorithm selection and hyperparameter optimization problem.
ANALGESIC AND ANTI INFLAMMATORY ACTIVITIES OF THE ETHANOLIC EXTRACT OF THE MUSHROOM GANODERMA APPLANATUM

Objective: The ethanolic extract of the mushroom, Ganoderma applanatum was investigated for the presence of secondary metabolites, anti-inflammatory and analgesic activities. Material and Methods: The extract was subjected to phytochemical screening for the identification of secondary metabolites. Using intraperitoneal doses of 150, 300, 600 and 1200 mg/kg body weight, in vivo anti-inflammatory screening was carried out in rats using the rat paw oedema test while analgesic activity of the extract was done in mice using the hot plate test. Results: The study shows that the extract has an LD50 of 3273 mg/kg and the presence of anthraquinones, flavonoids and steroids. Saponins and tannins were absent. Dose and time dependent suppression of egg-white induced oedema in the rat paw test was observed, with maximum percentage suppression occurring at 600mg/kg (59.2%). The extract also significantly prolonged the reaction time in mice to noxious thermal stimuli. Conclusion: Ganoderma applanatum has potential as a source of useful analgesic and anti-inflammatory principles.
On the duration and intensity of cumulative advantage competitions

Network growth can be framed as a competition for edges among nodes in the network. As with various other social and physical systems, skill (fitness) and luck (random chance) act as fundamental forces driving competition dynamics. In the context of networks, cumulative advantage (CA)—the rich-get-richer effect—is seen as a driving principle governing the edge accumulation process. However, competitions coupled with CA exhibit non-trivial behavior and little is formally known about duration and intensity of CA competitions. By isolating two nodes in an ideal CA competition, we provide a mathematical understanding of how CA exacerbates the role of luck in detriment of skill. We show, for instance, that when nodes start with few edges, an early stroke of luck can place the less skilled in the lead for an extremely long period of time, a phenomenon we call ‘struggle of the fittest’. We prove that duration of a simple skill and luck competition model exhibit power-law tails when CA is present, regardless of skill difference, which is in sharp contrast to the exponential tails when fitness is distinct but CA is absent. We also prove that competition intensity is always upper bounded by an exponential tail, irrespective of CA and skills. Thus, CA competitions can be extremely long (infinite mean, depending on fitness ratio) but almost never very intense. The theoretical results are corroborated by extensive numerical simulations. Our findings have important implications to competitions not only among nodes in networks but also in contexts that leverage socio-physical models embodying CA competitions.
Thickening in the somatosensory cortex of patients with migraine

Objective: To examine morphologic changes in the somatosensory cortex (SSC) of patients with migraine. Methods: Cortical thickness of the SSC of patients with migraine was measured in vivo and compared with age- and sex-matched healthy subjects. The cohort was composed of 24 patients with migraine, subdivided into 12 patients who had migraine with aura, 12 patients who had migraine without aura, and 12 controls. Group and individual analyses were performed in the SSC and shown as average maps of significant changes in cortical thickness. Results: Migraineurs had on average thicker SSCs than the control group. The most significant thickness changes were noticed in the caudal SSC, where the trigeminal area, including head and face, is somatotopically represented. Conclusions: Our findings indicate the presence of interictal structural changes in the somatosensory cortex (SSC) of migraineurs. The SSC plays a crucial role in the noxious and nonnoxious somatosensory processing. Thickening in the SSC is in line with diffusional abnormalities observed in the subcortical trigeminal somatosensory pathway of the same migraine cohort in a previous study. Repetitive migraine attacks may lead to, or be the result of, neuroplastic changes in cortical and subcortical structures of the trigeminal somatosensory system.
Genome-Wide Association Study in BRCA1 Mutation Carriers Identifies Novel Loci Associated with Breast and Ovarian Cancer Risk

BRCA1-associated breast and ovarian cancer risks can be modified by common genetic variants. To identify further cancer risk-modifying loci, we performed a multi-stage GWAS of 11,705 BRCA1 carriers (of whom 5,920 were diagnosed with breast and 1,839 were diagnosed with ovarian cancer), with a further replication in an additional sample of 2,646 BRCA1 carriers. We identified a novel breast cancer risk modifier locus at 1q32 for BRCA1 carriers (rs2290854, P = 2.7×10−8, HR = 1.14, 95% CI: 1.09–1.20). In addition, we identified two novel ovarian cancer risk modifier loci: 17q21.31 (rs17631303, P = 1.4×10−8, HR = 1.27, 95% CI: 1.17–1.38) and 4q32.3 (rs4691139, P = 3.4×10−8, HR = 1.20, 95% CI: 1.17–1.38). The 4q32.3 locus was not associated with ovarian cancer risk in the general population or BRCA2 carriers, suggesting a BRCA1-specific association. The 17q21.31 locus was also associated with ovarian cancer risk in 8,211 BRCA2 carriers (P = 2×10−4). These loci may lead to an improved understanding of the etiology of breast and ovarian tumors in BRCA1 carriers. Based on the joint distribution of the known BRCA1 breast cancer risk-modifying loci, we estimated that the breast cancer lifetime risks for the 5% of BRCA1 carriers at lowest risk are 28%–50% compared to 81%–100% for the 5% at highest risk. Similarly, based on the known ovarian cancer risk-modifying loci, the 5% of BRCA1 carriers at lowest risk have an estimated lifetime risk of developing ovarian cancer of 28% or lower, whereas the 5% at highest risk will have a risk of 63% or higher. Such differences in risk may have important implications for risk prediction and clinical management for BRCA1 carriers.
Influence of knowledge, training and experience of observers on the reliability of anthropometric measurements in children

Objective : To elucidate the impact of the observer's level of technical knowledge, training and experience with measuring height and triceps skinfold thickness on the reliability of these measurements in children. Despite of instructions and encouraging careful measurements, these factors may significantly affect measurements and lead to interpretation difficulties, especially of short term growth data. Subjects and methods : A cross-sectional study was designed in which 18 children, aged 2-7 years, were measured in duplo by 12 observers with different backgrounds and levels of experience, protocol knowledge and protocol training. The main outcome measures, precision and accuracy, were expressed as technical error of measurement (TEM) and average bias (AB) in comparison with an expert anthropometrist. Results : As expected, the best educated and most experienced observers scored the best precision and accuracy. By ranking analysis and multiple regressions we learned that precision and accuracy in measuring height and triceps skinfold thickness are mainly predicted by allround knowledge of the measurement protocol (p< 0.05) and the years of experience (p< 0.05). A practical training course of only a few hours does not seem to improve reliability significantly. Conclusion : To get a more reliable insight in growth of a child it is important to be aware of the influence on measurement outcome values of protocol knowledge and years of experience. Growth studies should use detailed anthropometric standardization protocols and train people to acquire better insight into these protocols.
Backbone colorings along perfect matchings

Given a graph $G=(V,E)$ and a spanning subgraph $H$ of $G$ (the backbone of $G$), a backbone coloring for $G$ and $H$ is a proper vertex coloring $V\rightarrow \{1,2,\ldots\}$ of $G$ in which the colors assigned to adjacent vertices in $H$ differ by at least two. In a recent paper, backbone colorings were introduced and studied in cases were the backbone is either a spanning tree or a spanning path. Here we study the case where the backbone is a perfect matching. We show that for perfect matching backbones of $G$ the number of colors needed for a backbone coloring of $G$ can roughly differ by a multiplicative factor of at most $\frac{4}{3}$ from the chromatic number $\chi(G)$. We show that the computational complexity of the problem ``Given a graph $G$ with a perfect matching $M$, and an integer $\ell$, is there a backbone coloring for $G$ and $M$ with at most $\ell$ colors? '' jumps from polynomial to NP-complete between $\ell=3$ and $\ell=4$. Finally, we consider the case where $G$ is a planar graph.
Evaluation of Diffusion Models for Flood Routing

A study has been conducted to define the range of conditions with respect to hydrographs and channels encountered by SCS engineers in flood plain/flood control projects and to test two diffusion flood routing models against a benchmark full dynamic routing model. A total of 340 routing tests were performed. The accuracies of predicting peak discharge, peak area, time of peaks, and correlation of hydrograph shapes were analyzed and related to nondimensional parameters that describe the range of field conditions. Both diffusion models were found to satisfy accuracy criteria for over 80 per cent of the SCS field conditions. The variable parameter diffusion model provides greater accuracy only in retaining the shape of the hydrographs.
Determining Possible and Necessary Winners under Common Voting Rules Given Partial Orders

Usually a voting rule or correspondence requires agents to give their preferences as linear orders. However, in some cases it is impractical for an agent to give a linear order over all the alternatives. It has been suggested to let agents submit partial orders instead. Then, given a profile of partial orders and a candidate c, two important questions arise: first, is c guaranteed to win, and second, is it still possible for c to win? These are the necessary winner and possible winner problems, respectively. We consider the setting where the number of alternatives is unbounded and the votes are unweighted. We prove that for Copeland, maximin, Bucklin, and ranked pairs, the possible winner problem is NP-complete; also, we give a sufficient condition on scoring rules for the possible winner problem to be NP-complete (Borda satisfies this condition). We also prove that for Copeland and ranked pairs, the necessary winner problem is coNP-complete. All the hardness results hold even when the number of undetermined pairs in each vote is no more than a constant. We also present polynomial-time algorithms for the necessary winner problem for scoring rules, maximin, and Bucklin.
Antibiotic Prescribing among Pediatric Inpatients with Potential Infections in Two Private Sector Hospitals in Central India

Introduction Infectious diseases are one of the major causes of child mortality in India. Pediatric patients are commonly prescribed antibiotics for non-bacterial infections. Monitoring of local antibiotic prescribing with respect to the diagnosis is necessary to improve the prescribing practices. The aim of the study was to describe antibiotic prescribing for potential infections among patients admitted in pediatric departments in two private sector hospitals; one teaching (TH) and one non-teaching (NTH) in Central India. Methods Data from all patients admitted at the pediatric departments of both study hospitals was collected manually, for 3 years (2008–2011) using a customized form. Data from inpatients aged 0–18 years, diagnosed with; acute gastroenteritis (AGE), respiratory tract infections, enteric fever, viral fever or unspecified fever were focused for analysis. Antibiotic prescriptions were analysed using the WHO Anatomical Therapeutic Chemical (ATC) classification system and defined daily doses (DDDs). Adherence to the Indian Academy of Pediatrics list of essential medicines (IAP-LEM) was investigated. P-values <0.05 were considered significant. Results Oftotal6, 825 inpatients admitted at two pediatric departments, 510 patients from the TH and 2,479from the NTH were selected based on the assigned potential infectious diagnoses. Of these, 224 patients (44%) at the TH and 2,088 (84%) at the NTH were prescribed at least one antibiotic during hospital stay (odds ratio-0.69, 95%confidence interval-0.52 to 0.93; p<0.001). Patients with AGE, viral- and enteric fever were frequently prescribed antibiotics at both hospitals, yet higher proportion were prescribed antibiotics at the NTH compared to the TH. Broad-spectrum antibiotics were the most commonly prescribed antibiotic class in both hospitals, namely third generation cephalosporins, J01DD (69%) at the TH, and new fixed dose combinations of antibiotics J01R (FDCs, 42%) at the NTH. At the TH, 37% of the antibiotic prescriptions were comprised of antibiotics listed in the IAP-LEM, compared to 24% at the NTH (p<0.05). Conclusions Broad-spectrum antibiotics were prescribed frequently in both hospitals also for the un-indicated conditions such as viral fever and enteric fever. At the NTH, new FDCs were more frequently prescribed and adherence to the IAP-LEM was substantially lower at the NTH compared to the TH. The results demonstrate need to develop diagnosis-specific prescribing guidelines to facilitate rational use of antibiotics and implement antibiotic stewardship program.
Towards breaking the Ω-bias degeneracy in density—velocity comparisons

I derive a second-order local relation between the redshift-space mass density field and the real-space velocity field. This relation can be useful for comparisons between the cosmic density and peculiar velocity fields, for a number of reasons. First, relating the real-space velocity directly to the redshift-space density enables one to avoid the Ω-dependent reconstruction of the density field in real space. Secondly, the reconstruction of the three-dimensional velocity field in redshift space, questionable because of its vorticity, is also unnecessary. Finally, a similar relation between the galaxy density field and the velocity field offers a way to break the Ω-bias degeneracy in density–velocity comparisons, when combined with an additional measurement of the redshift-space galaxy skewness. I derive the latter relation under the assumption of non-linear but local bias; accounting for stochasticity of bias is left for further study.
Adaptive blind noise suppression in some speech processing applications

In many applications of speech processing the noise reveals some specific features. Although the noise could be quite broadband, there are a limited number of dominant frequencies, which carry the most of its energy. This fact implies the usage of narrow-band notch filters that must be adaptive in order to track the changes in noise characteristics. A method and a system for noise suppression are developed. The method uses adaptive notch filters based on second-order Gray-Markel lattice structure. The main advantages of the proposed system are that it has very low computational complexity, is stable in the process of adaptation, and has a short time of adaptation. Under comparable SNR improvement, the proposed method adjusts only 3 coefficients against 250-450 for the conventional adaptive noise cancellation systems. A framework for a speech recognition system that uses the proposed method is suggested.
On the carapacial ridge in turtle embryos: its developmental origin, function and the chelonian body plan

The chelonian carapace is composed of dorsolaterally expanded ribs; an evolutionary change in the rib-patterning program is assumed to be related to this novelty. Turtle embryos exhibit a longitudinal ridge called the carapacial ridge (CR) on the flank, and its histological resemblance to the apical ectodermal ridge of the limb bud implies its inductive activity in the unique patterning of the ribs. We studied the Chinese soft-shelled turtle, Pelodiscus sinensis, and confirmed by labeling with a lipophilic dye, DiI, that the CR contains the somite-derived dermis and that it is a unique structure among amniotes. Using electroporation of a dominant-negative form of LEF-1, the CR-specific gene, we showed that CR-specific genes function in the growth and maintenance of the CR. Microcauterization or implantation of the CR did not change the dorsoventral pattern of the ribs, and only their fan-shaped pattern was arrested by CR removal. We conclude that the CR is a true embryonic novelty among amniotes and, because of the specific expression of regulatory genes, it functions in the marginal growth of the carapacial primordium, thereby inducing the fan-shaped arrangement of the ribs.
Large-Scale Calcium Waves Traveling through Astrocytic Networks In Vivo

Macroscopic changes in cerebral blood flow, such as those captured by functional imaging of the brain, require highly organized, large-scale dynamics of astrocytes, glial cells that interact with both neuronal and cerebrovascular networks. However, astrocyte activity has been studied mainly at the level of individual cells, and information regarding their collective behavior is lacking. In this work, we monitored calcium activity simultaneously from hundreds of mouse hippocampal astrocytes in vivo and found that almost all astrocytes participated en masse in regenerative waves that propagated from cell to cell (referred to here as “glissandi”). Glissandi emerged depending on the neuronal activity and accompanied a reduction in infraslow fluctuations of local field potentials and a decrease in the flow of red blood cells. This novel phenomenon was heretofore overlooked, probably because of the high vulnerability of astrocytes to light damage; glissandi occurred only when observed at much lower laser intensities than previously used.
Motivated explanation

Although motivation is a well-established field of study in its own right, and has been fruitfully studied in connection with attribution theory and belief formation under the heading of “motivated thinking,” its powerful and pervasive influence on specifically explanatory processes is less well explored. Where one has a strong motivation to understand some event correctly, one is thereby motivated to adhere as best one can to normative or “epistemic” criteria for correct or accurate explanation, even if one does not consciously formulate or apply such criteria. By contrast, many of our motivations to explain introduce bias into the processes involved in generating, evaluating, or giving explanations. Non-epistemic explanatory motivations, or following Kunda's usage, “directional” motivations, include self-justification, resolution of cognitive dissonance, deliberate deception, teaching, and many more. Some of these motivations lead to the relaxation or violation of epistemic norms; others enhance epistemic motivation, so that one engages in more careful and thorough generational and evaluative processes. We propose that “real life” explanatory processes are often constrained by multiple goals, epistemic and directional, where these goals may mutually reinforce one another or may conflict, and where our explanations emerge as a matter of weighing and satisfying those goals. We review emerging evidence from psychology and neuroscience to support this framework and to elucidate the central role of motivation in human thought and explanation.