Miracle-dz/UniFAR-FTUs huggingface dataset:
The Europeanization of Eastern Europe: the external incentives model revisited

ABSTRACT The External Incentives Model (EIM) was designed to explain the Europeanization of the Central and Eastern European countries (CEECs) through the EU’s accession conditionality. This article asks how relevant the model remains beyond its original context. We examine recent data and research on the EU’s impact in two additional contexts: post-accession developments in the CEECs and the Southeast European countries currently in the accession process. We find that the model generally accounts well for the variation in Europeanization across domains and countries. More specifically, the credibility of incentives stands out as a crucial condition for the success of EU conditionality. At the same time, we note omissions and limitations of the original model: first, the model works with highly abstract conditions that require contextual specification to render them more meaningful and better testable. Second, the EIM starts from generally favourable, but underspecified, background conditions.
Ovarian Microcystic Stromal Tumor: Report of A New Entity with Immunohistochemical and Ultrastructural Studies

Abstract Microcystic stromal tumor is a recently described rare subtype of ovarian tumor for which there has been no previously reported ultrastructural study. We report a case with the characteristic histological and immunohistochemical features and the first ultrastructural study. The immunohistochemical findings of strong and diffuse nuclear staining for beta catenin and P27 are suggestive of dysregulation of more than one genetic pathway. The ultrastructural findings are supportive of the previous postulation of an ovarian stromal origin of the neoplastic cells.
PANCREATIC CANCER RISK FACTORS : A SUMMARY REVIEW OF METAANALYTICAL AND PROSPECTIVE COHORT STUDIES PART 1 . COFFEE AND TEA CONSUMPTION

Pancreatic cancer (PC) is one of the top 5 causes of mortality from cancer. The role of dietary factors in the etiology of PC is unclear. We reviewed some meta-analytical or pooled reports dealing with the association between coff ee (C) and tea (T) consumption and PC risk. C components can have anticarcinogenic eff ect: meta-analysis by Dong (2011) confi rmed, that pooled relative risk (RR) of PC in high C lovers comparing with non/lowest C drinkers was 0.68 (95% CI 0.51–0.84). But in the “US NIH-AARP Diet and Health Study” (2015) after adjustment for smoking, PC risk were not signifi cant: never C drinkers compared with C drinkers≥6 cups per day (cpd) HR1.24 (0.93–1.65). In the European Prospective Investigation (2013) neither C, nor T were also associated with PC risk, but the previous Italian multicenter study (1995) was demonstrated, that ingestion of >3 cpd lead to signifi cantly increased PC risk (odds ratio (OR) 2.53; 1.53–4.18). A meta-analysis by Zeng (2014) indicate, that green T consumption >2 cpd (OR0.95, 0.85–1.06) was not associated with PC risk. However, the subgroup analysis of diff erent countries in meta-analysis by Chen (2014) showed a statistical decrease in PC risk by high T consumption in a Chinese population (Risk ratio=0.76, 0.59–0.98). Nevertheless meta-analysis, pooled and case-control PANCREATIC CANCER RISK FACTORS: A SUMMARY REVIEW OF METAANALYTICAL AND PROSPECTIVE COHORT STUDIES PART 1. COFFEE AND TEA CONSUMPTION Grigorieva I. N.1, 2 1 Research Institutе of Internal and Preventive Medicine — Branch of Federal State Budget Scientefi c Institution The Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences (Novosibirsk, Russia) 2 National Research State University (Novosibirsk, Russia)
Linking genetic diversity and temporal fluctuations in population abundance of the introduced feral cat (Felis silvestris catus) on the Kerguelen archipelago

Linking temporal variations of genetic diversity, including allelic richness and heterozygosity, and spatio‐temporal fluctuations in population abundance has emerged as an important tool for understanding demographic and evolutionary processes in natural populations. This so‐called genetic monitoring was conducted across 12 consecutive years (1996–2007) at three sites for the feral cat, introduced onto the Kerguelen archipelago fifty years ago. Temporal changes in allelic richness and heterozygosity at 18 microsatellite DNA loci were compared with temporal changes in the adult population abundance index, obtained by typical demographic monitoring. No association was found at the island spatial scale, but we observed an association between genetic diversity and adult population indices from year to year within each study site. More particularly, the magnitude of successive increases or decreases in the adult population abundance index appeared to be the major factor linking the trajectories of genetic diversity and adult population abundance indices. Natal dispersal and/or local recruitment, both facilitated by high juvenile survival when the adult population size is small, is proposed as the major demographic processes contributing to such an observed pattern. Finally, we suggested avoiding the use of the harmonic mean as an estimator of long‐term population size to study the relationships between demographic fluctuations and heterozygosity in populations characterized by strong multiannual density fluctuations.
Macroeconomic Variables and In-Migration in Malaysia ’ s Developed States

Nowadays, in-migration is one of the important phenomena that affects urbanisation and development in the destination area. Indirectly, it will cause the rapid growth of the population, leads to overcrowding, competition for jobs, unemployment, poverty and the formation of new towns in the destination area especially urban areas. However, for rural destination areas, in-migration of professionals is important to stimulate economic growth. Hence, the objective of this study is to forecast and analyze the effect of macroeconomic variables on in-migration into developed states in Malaysia. Using the annual time series data from 1980 to 2012, Autoregression Distributed Lag (ARDL) and Grangercausality test were conducted. The findings have found that long run and short run relationships exist between inmigration and macroeconomic factors for developed states. The forecasting until year 2020 expects that in-migration will increase in Perak and Penang. Investment factors that are concentrated in the developed states also affect the population’s decision to migrate especially in Kuala Lumpur and Selangor. To promote the economic growth, foreign direct investment and domestic investment for development sector should be intensified to improve household incomes in the region. Besides, Perak and Selangor need to improve the existing policies to ensure that there is an increase in foreign direct investment and domestic investment.
Capital Structure and Hedging Demand with Incomplete Markets∗

In this paper we study the role played by hedging demand in shaping firms’ capital structure. We develop and study a general equilibrium model with production and incomplete markets where households differ in their risk–sharing needs. Valuemaximizing firms cater to these different needs when choosing their leverage, their size, and possibly the risk profile of their production technology. We find that as the demand for hedging increases, firms issue more debt and destine only part of the greater proceeds to investment – the remainder going to shareholders. How much more debt, depends on the availability of competing risk-sharing instruments, such as (government–issued) risk–free debt and derivatives. When the capital structure is jointly shaped by hedging demand and agency – in the form of an asset–substitution problem – the greater risk induced by asymmetric information has countervailing effects on debt: On the one hand, debt is reduced to nudge shareholders into choosing lower risk. This is the standard asset substitution effect. On the other hand, however, the greater risk in production affects the state prices and calls for more debt.
9-2014 Verifying and Validating Multirobot Missions

We have developed an approach that can be used by mission designers to determine whether or not a performance guarantee for their mission software, when carried out under the uncertain conditions of a real-world environment, will hold within a threshold probability. In this paper we demonstrate its utility for verifying multirobot missions, in particular a bounding overwatch mission.
Decreased Growth Velocity Before IDDM Onset

Diabetes can retard growth. Growth was studied prospectively in 12 nondiabetic identical twins aged <14 yr and in their co-twins with insulin-dependent diabetes mellitus (IDDM) to determine whether changes in growth occur before the onset of IDDM. Seven of the 12 nondiabetic twins subsequently developed IDDM; the remainder are now unlikely to become diabetic. A significantly reduced growth velocity was observed more frequently in the nondiabetic twins (7 of 12) than in their diabetic co-twins (1 of 12; P = 0.03). Of the 7 nondiabetic twins who were prediabetic, 6 had a reduction in growth velocity to below the 3rd percentile before the onset of diabetes compared with 1 of their diabetic co-twins (P = 0.03). However, only 1 of the 5 nondiabetic twins who did not develop diabetes showed a reduction in growth velocity. The nadir of growth in the twins who developed diabetes occurred a mean of 1.2 yr before diagnosis (range 0.3–2.3 yr). All 7 of the prediabetic twins had islet cell antibodies when first seen, and 3 had them before they showed either decreased growth velocity or impaired glucose tolerance. In 4 prediabetic twins, the decreased growth preceded impaired glucose tolerance. The prediabetic twins tested had lower testosterone or estradiol levels at the time they showed decreased growth than their diabetic twins. We conclude that decreased growth velocity is an early sensitive marker of IDDM.
Development of a dual tactile pattern presentation device using in MRI environment

We have developed a novel tactile pattern presentation device to assess tactile cognitive function by active, passive and dual touch. The device is magnetic resonance imaging (MRI) compatible and can serve to investigate the underlying neural mechanisms of tactile pattern discrimination. The primary components of the system are one disk for pattern presentation (DPP) driven by an ultrasonic motor, one set of fingers position control unit and one reaction key pad. In order to evaluate the performance of the presentation device, two functional MRI tasks were executed. First, we used MRI-Phantom to test the practicability of the tactile pattern presentation device. Second, we designed a tactile raised line cognitive task with five young subjects to investigate the brain activity areas concerning tactile shape cognition by dual touch. The results suggested that this device to be unaffected by the magnetic field, and the brain imaging results were consistent with previous neuroimaging study. The most significantly of present study is that the device provides a powerful means of investigating neural mechanisms of perception and cognitive function for touch discrimination.
Increasing trust in fully automated driving: route indication on an augmented reality head-up display

Cooperative, intelligent transportation systems (C-ITSs) have capabilities far beyond what human drivers can achieve. For instance, intelligent systems that plan the exact trajectories of vehicles could increase throughput at intersections, allowing vehicles to pass with high speed and without any need for traffic lights. It is imaginable that C-ITS will manage traffic in fully automated driving (FAD). However, the unpredictable behavior patterns of the automated vehicle (AV) are also likely to make the occupants feel uncomfortable. FAD systems operate based on a vast amount of information. As this information is potentially invisible to individuals, the question is if users trust FAD systems. We hypothesize that users experiencing such scenarios would demand system feedback to anticipate upcoming system decisions and maneuvers. Therefore, we evaluated five augmented reality (AR) user interface (UI) concepts aiming to increase system transparency in a user study (N = 30) in a driving simulation in virtual reality (VR). Our results support the assumption that feedback about the system state (in the form of route information) significantly increases trust in AVs. As trust is highly subjective, we propose to provide experience-based route visualization systems in FAD to meet individuals' needs.
Eight novel mutations in SPG4 in a large sample of patients with hereditary spastic paraplegia.

BACKGROUND Hereditary spastic paraplegia (HSP) is a group of genetically heterogeneous disorders characterized by progressive spasticity of the lower limbs. Mutations in the SPG4 gene, which encodes spastin protein, are responsible for up to 45% of autosomal dominant cases. OBJECTIVE To search for disease-causing mutations in a large series of Italian patients with HSP. DESIGN Samples of DNA were analyzed by direct sequencing of all exons in SPG4. Samples from a subset of patients were also analyzed by direct sequencing of all exons in SPG3A, SPG6, SPG10, and SPG13. SETTING Molecular testing facility in Italy. PATIENTS Sixty unrelated Italian patients with pure (n = 50) and complicated (n = 10) HSP. MAIN OUTCOME MEASURES Mutations in SPG4, SPG3A, SPG6, SPG10, and SPG13. RESULTS We identified 12 different mutations, 8 of which were novel, in 13 patients. No mutations of any of the other HSP genes tested were found in 15 patients with sporadic pure HSP who did not have mutations in the SPG4 gene. CONCLUSIONS The overall rate of mutation in the SPG4 gene within our sample was 22%, rising to 26% when only patients with pure HSP were considered. The negative result obtained in 15 patients without mutations in SPG4 in whom 4 other genes were analyzed (SPG3A, SPG6, SPG10, and SPG13) indicate that these genes are not frequently mutated in sporadic pure HSP.
Fit Fly: A Case Study on Interconnect Innovation through Parallel Simulation

To meet the demand for exascale-level performance from high-performance computing (HPC) interconnects, many system architects are turning to simulation results for accurate and reliable predictions of the performance of prospective technologies. Testing full-scale networks with a variety of benchmarking tools, including synthetic workloads and application traces, can give crucial insight into what ideas are most promising without needing to physically construct a test network. While flexible, however, this approach is extremely compute time intensive. We address this time complexity challenge through the use of large-scale, optimistic parallel simulation that ultimately leads to faster HPC network architecture innovations. In this paper we demonstrate this innovation capability through a real-world network design case study. Specifically, we have simulated and compared four extreme-scale interconnects: Dragonfly, Megafly, Slim Fly, and a new dual-rail-dual-plane variation of the Slim Fly network topology. We present this new variant of Slim Fly, dubbed Fit Fly, to show how interconnect innovation and evaluation---beyond what is possible through analytic methods---can be achieved through parallel simulation. We validate and compare the model with various network designs using the CODES interconnect simulation framework. By running large-scale simulations in a parallel environment, we are able to quickly generate reliable performance results that can help network designers break ground on the next generation of high-performance network designs.
Social Trait Information in Deep Convolutional Neural Networks Trained for Face Identification

Faces provide information about a person's identity, as well as their sex, age, and ethnicity. People also infer social and personality traits from the face - judgments that can have important societal and personal consequences. In recent years, deep convolutional neural networks (DCNNs) have proven adept at representing the identity of a face from images that vary widely in viewpoint, illumination, expression, and appearance. These algorithms are modeled on the primate visual cortex and consist of multiple processing layers of simulated neurons. Here, we examined whether a DCNN trained for face identification also retains a representation of the information in faces that supports social-trait inferences. Participants rated male and female faces on a diverse set of 18 personality traits. Linear classifiers were trained with cross validation to predict human-assigned trait ratings from the 512 dimensional representations of faces that emerged at the top-layer of a DCNN trained for face identification. The network was trained with 494,414 images of 10,575 identities and consisted of seven layers and 19.8 million parameters. The top-level DCNN features produced by the network predicted the human-assigned social trait profiles with good accuracy. Human-assigned ratings for the individual traits were also predicted accurately. We conclude that the face representations that emerge from DCNNs retain facial information that goes beyond the strict limits of their training.
Pro-inflammatory cytokines: a possible relationship with dialytic adequacy and serum albumin in peritoneal dialysis patients

Background Inflammation and serum albumin concentration are both important predictors of survival in patients treated with peritoneal dialysis (PD). Furthermore, systemic and local inflammatory mediators may induce structural and functional alterations in the peritoneal membrane, thus interfering with dialysis adequacy. PD adequacy is monitored primarily by indices of small solute clearance, such as Kt/V urea and weekly creatinine clearance (wCc). The aim of this study was to investigate the possible relationship between pro-inflammatory cytokines, such as interleukin-6 (IL-6) and interleukin-1β (IL-1β), and serum albumin and C-reactive protein (CRP). Moreover, the relationship between IL-6 and IL-1β and PD adequacy has been analysed. Methods We enrolled 46 stable PD patients undergoing maintenance PD for a minimum of 3 months. Plasma levels of serum albumin, high-sensitivity (hs)-CRP, IL-6 and IL-1β were measured in all patients. We used weekly Kt/V urea and wCc to monitor PD adequacy. Daily urine volume was measured in all patients. Results The median values of serum albumin, hs-CRP, IL-6 and IL-1β showed no significant differences between continuous ambulatory PD and automated PD patients. IL-6 levels showed a positive correlation with hs-CRP levels (P < 0.001) and a negative correlation with serum albumin concentration (P = 0.01). There was no statistically significant relationship between IL-1β and hs-CRP or serum albumin concentrations. Subsequently, PD patients were divided into two groups based on Kt/V urea value. PD patients with Kt/V ≤1.7 had significantly higher IL-6 levels compared with PD patients with Kt/V >1.7 (P = 0.015). No statistically significant relationship between IL-6 and wCc was observed. There was no significant difference in IL-1β levels between PD patients with Kt/V ≤1.7 and with Kt/V >1.7 [median (interquartile range) 0.82 (0.88–5.2) versus 1.82 (0.95–2.7)]. There was no significant difference in IL-6 and IL-1β levels in PD patients with and without residual diuresis (P = 0.32 and P = 0.77, respectively). Conclusion Our data suggest a possible relationship between serum IL-6 levels and serum albumin and hs-CRP in PD patients. Furthermore, IL-6 seems to be higher in patients with lower Kt/V, thus suggesting a possible use of this inflammatory biomarker in PD adequacy monitoring.
Stock Price Pattern Prediction Based on Complex Network and Machine Learning

Complex networks in stock market and stock price volatility pattern prediction are the important issues in stock price research. Previous studies have used historical information regarding a single stock to predict the future trend of the stock’s price, seldom considering comovement among stocks in the same market. In this study, in order to extract the information about relation stocks for prediction, we try to combine the complex network method with machine learning to predict stock price patterns. Firstly, we propose a new pattern network construction method for multivariate stock time series. The price volatility combination patterns of the Standard & Poor’s 500 Index (S&P 500), the NASDAQ Composite Index (NASDAQ), and the Dow Jones Industrial Average (DJIA) are transformed into directed weighted networks. It is found that network topology characteristics, such as average degree centrality, average strength, average shortest path length, and closeness centrality, can identify periods of sharp fluctuations in the stock market. Next, the topology characteristic variables for each combination symbolic pattern are used as the input variables for K-nearest neighbors (KNN) and support vector machine (SVM) algorithms to predict the next-day volatility patterns of a single stock. The results show that the optimal models corresponding to the two algorithms can be found through cross-validation and search methods, respectively. The prediction accuracy rates for the three indexes in relation to the testing data set are greater than 70%. In general, the prediction ability of SVM algorithms is better than that of KNN algorithms.
Mercury Isotope Fractionation in the Subsurface of a Hg(II) Chloride-Contaminated Industrial Legacy Site

To understand the transformations of mercury (Hg) species in the subsurface of a HgCl2-contaminated former industrial site in southwest Germany, Hg isotope analysis was combined with an investigation of Hg forms by a four-step sequential extraction protocol (SEP) and pyrolytic thermodesorption. Data from two soil cores revealed that the initial HgCl2 was partly reduced to metallic Hg(0) and that Hg forms of different mobility and oxidation state coexist in the subsurface. The most contaminated sample (K2-8, 802 mg kg–1 Hg) had a bulk δ202Hg value of around −0.43 ± 0.06‰ (2SD), similar to published average values for industrial Hg sources. Other sample signatures varied significantly with depth and between SEP pools. The most Hg-rich samples contained mixtures of Hg(0) and Hg(II) phases, and the water-extractable, mobile Hg pool exhibited heavy δ202Hg values of up to +0.18‰. Sequential water extracts revealed slow dissolution kinetics of mobile Hg pools, continuously releasing isotopically heavy Hg into solution. This was further corroborated by heavy δ202Hg values of groundwater samples. Our results demonstrate that the Hg isotope signature of an industrial contamination source can be significantly altered during the transformations of Hg species in the subsurface, which complicates source tracing applications but offers the possibility of using Hg isotopes as process tracers in contaminated subsurface systems.
DETECTION AND CHEMOTHERAPY OF Balantidium coli IN BUFFALOES AROUND LAHORE, PAKISTAN

A study was conducted for the detection of Balantidium coli and to determine the comparative efficacy of ampicillin, secnidazole and neem seeds (Melia Azadarch linn) against balantidiosis in buffaloes around Lahore. A total of two hundred buffaloes were examined coprologically. Of those, 40 were found positive (20%), twenty-four buffaloes having balantidiosis were selected for chemotherapeutic trials and were divided into four equal groups. The efficacy of drugs was determined on the basis of disappearance of clinical signs and reduction of cysts/trophozoites in faeces. It was concluded that secnidazole (Dysen forte) is the drug of choice for the treatment of bovine balantidiosis.