Miracle-dz/UniFAR-FTUs huggingface dataset:
Risk classifications of aquatic non-native species: Application of contemporary European assessment protocols in different biogeographical settings

Non-native species can cause negative impacts when they become invasive. This study entails a comparison of risk classifications for 25 aquatic non-native species using various European risk identification protocols. For 72% of the species assessed, risk classifications were dissimilar between countries. The pair-wise comparison of Freshwater Fish Invasiveness Scoring Kit (FISK) scores of in total 28 fish species from the UK, Flanders (Belgium) and Belarus resulted in a higher correlation for scores of Flanders- Belarus than that of Flanders-UK and Belarus-UK. We conclude that different risk classifications may occur due to differences in (1) national assessment protocols, (2) species-environment matches in various biogeographical regions, and (3) data availability and expert judgement. European standardisation of risk assessment protocols, performance of biogeographical region specific risk classifications and further research on key factors for invasiveness of aquatic ecosystems are recommended.
Long-term effectiveness and safety of sirolimus drug-eluting stents

The root cause of coronary artery disease is atherosclerosis, ie, intraluminal narrowing (stenosis) of the arteries that supply blood to tissues of the heart. The introduction of the drug-eluting stent over the past decade has revolutionized the field of interventional cardiology. It is used extensively in clinical practice for the treatment of coronary artery disease. The first drug-eluting stent to receive US Food and Drug Administration approval was the sirolimus-eluting stent. Recently, two other stent analogs of sirolimus were approved, ie, the zotarolimus-eluting stent and the everolimus-eluting stent. However, concern has arisen in recent years about the long-term safety and efficacy of drug-eluting stents, due to the occurrence of late adverse clinical events, such as stent thrombosis. This review focuses on clinical studies that have been performed with the sirolimus-eluting stent or its analogs. We discuss the pharmacology, safety, and various therapeutic options that exist when choosing stents for coronary artery disease. Our aim is to provide a thorough review of the long-term efficacy and safety of sirolimus drug-eluting stents, and also to discuss currently approved and promising investigational drug-eluting stents, in an effort to provide insight into how these stents are currently evolving and generate further investigation in this area.
A statistical approach for predicting grassland degradation in disturbance-driven landscapes

The relationship between fire and long-term trends in tallgrass prairie vegetation was assessed at Fort Riley and Konza Prairie Biological Station (KPBS) in Kansas. Linear trends of surface greenness were previously estimated using BFAST and MODIS MOD13Q1 NDVI composite images from 2001 to 2010. To explain trends, fire frequency and seasonality (fire regime) was determined and each site was divided into spatial strata using administrative or management units. Generalized linear models (GLM) were used to explain trends by fire regime and/or stratification. Spatialized versions of GLMs were also computed address unexplained spatial components. Non-spatial models for FRK showed fire regime explained only 4% of trends compared to strata (7-26%). At KPBS, fire regime and spatial stratification explained 14% and 39%, respectively. At both sites, improvements in performance were minimal using both fire and strata as explanatory variables. Model spatialization resulted in a 5% improvement at FRK, but with weak spatial structure in the residuals, and was not necessary at KPBS as the existing stratification most of the spatial structure in model residuals. All models at KPBS performed better for each explanatory variable and combination tested. Fire has only a marginal effect on vegetation trends at FRK despite its widespread use as a grassland management tool to improve vegetation health, and explains much more of the trends at KPBS. Analysis of predictors from spatial models with existing stratification yielded an approach with fewer strata but similar performance and may provide insight about additional explanatory variables omitted from this analysis.
Global systems approach to bacterial physiology: protein responders to stress and starvation

For over a century microbial physiologists have been studying how bacteria adapt and grow in their environment. A tremendous amount of information has been obtained by two quite different approaches. One approach studies how the bacterium as a biological system competes with other bacterial species for the limiting nutrient supply [1-4] and also how ~ s,o~rvives deleterious environmental conditions [2-5]. Another approach studies the individual enzymes necessary for the cell to survive or compete successfully in its environment and how the individual genes for these enzymes are regulated (for example, see [6,7]). A more recent strategy, the global systems approach, has been developed which helps to link these two classical approaches by allowing the investigator to study the response of many genes/ proteins simultaneously. By this strategy one identifies the sets of genes/proteins which respond to an environmental condition and then uncovers the regulatory elements that unite these sets of genes. / proteins. For some multigene systems this approach has helped to elucidate in molecular terms
Control of late apoptotic events by the p38 stress kinase in l‐glutamine‐deprived mouse hybridoma cells

l‐Glutamine (Gln) starvation rapidly triggers apoptosis in Sp2/0‐Ag14 (Sp2/0) murine hybridoma cells. Here, we report on the role played by the stress‐activated kinase p38 mitogen‐activated protein kinase (MAPK) in this process. p38 activation was detected 2 h after Gln withdrawal and, although treatment with the p38 inhibitor SB203580 did not prevent caspase activation in Gln‐starved cells, it reduced the occurrence of both nuclear condensation/fragmentation and apoptotic body formation. Similarly, transfection of Sp2/0 cells with a dominant negative p38 MAPK reduced the incidence of nuclear pyknosis and apoptotic body formation following 2 h of Gln starvation. Gln withdrawal‐induced apoptosis was blocked by the overexpression of the anti‐apoptotic protein Bcl‐xL or by the caspase inhibitor Z‐VAD‐fmk. Interestingly, Bcl‐xL expression inhibited p38 activation, but Z‐VAD‐fmk treatment did not, indicating that activation of this MAPK occurs downstream of mitochondrial dysfunction and is independent of caspases. Moreover, the anti‐oxidant N‐acetyl‐l‐cysteine prevented p38 phosphorylation, showing that p38 activation is triggered by an oxidative stress. Altogether, our findings indicate that p38 MAPK does not contribute to the induction of apoptosis in Gln‐starved Sp2/0 cells. Rather, Gln withdrawal leads to mitochondrial dysfunction, causing an oxidative stress and p38 activation, the latter contributing to the formation of late morphological features of apoptotic Sp2/0 cells. Copyright © 2012 John Wiley & Sons, Ltd.
Hybrid recommenders: incorporating metadata awareness into latent factor models

This paper proposes a hybrid recommender algorithm which integrates a set of different user's inputs into a unified and generic latent factor model to improve prediction accuracy. The technique can exploit users' demographics, such as age, gender and occupation, along with implicit feedback and items' metadata. Depending on the personal information from users, the recommender selects content whose subject is semantically related to their interests. The method was evaluated in the MovieLens dataset and compared against other approaches reported in the literature. The results show the effectiveness of incorporating metadata awareness into a latent factor model.
A study with pharyngeal and esophageal 24‐hour pH–impedance monitoring in patients with laryngopharyngeal symptoms refractory to proton pump inhibitors

The role of gastroesophageal reflux in chronic laryngeal symptoms is difficult to establish. The aim of this study was to characterize pharyngeal and esophageal pH–impedance reflux patterns in a group of patients with suspected laryngopharyngeal reflux and to determine predictive factors of response to proton pump inhibitors.
Surgical Risks Associated with the Management of Grade I and II Brain Arteriovenous Malformations

OBJECTIVEGrade I and II arteriovenous malformations (AVMs) have been considered safe to resect. However, unoperated low-grade AVMs have not been considered in previously reported series. The aim of this study was to examine all cases, both operated and unoperated, to identify any characteristics of low-grade AVMs that comprise a subgroup that might pose a relatively higher risk. METHODSA prospectively enrolled AVM database included 237 patients in Spetzler-Martin Grade I or II. These patients were analyzed on the basis of demographic characteristics, angiographic and magnetic resonance imaging features, clinical presentation, method of treatment, and outcome. RESULTSSurgery was performed in 220 patients in Spetzler-Martin Grade I or II. Seventeen patients did not undergo treatment because of poor neurological condition (six patients), patient refusal (nine patients), and perceived surgical difficulty (AVM size approaching 3 cm adjacent to Broca’s area) (two patients). The overall surgical morbidity rate was 0.9%, and the mortality rate was 0.5%. Adverse outcomes occurred in 1 (0.6%) of 180 patients with AVMs located away from eloquent cortex and in 2 (5%) of 40 patients with AVMs adjacent to eloquent cortex. None of 28 surgical patients with deep venous drainage had an adverse outcome. All 219 patients who survived surgery underwent postoperative angiography that confirmed cure. No postoperative hemorrhage has occurred in 1143 patient-years of follow-up (mean follow-up, 5.3 yr). CONCLUSIONWhen considering adverse outcome in the surgical series of Grade I and II AVMs alone, no statistical difference between non-eloquently located AVMs (0.6%) and eloquently located AVMs (5% adverse outcome) can be detected. However, consideration of all Grade I and II AVMs, both surgical and nonsurgical, may prove that a difference in outcome exists between these two groups masked by case selection. Generalization of the chances of adverse outcomes to all Grade I and II AVMs (both operated and unoperated) suggests that the risk of performing surgery on noneloquent brain in our series was 0.6% and that in eloquent brain could have been as high as 9.5%, had all such patients undergone surgery.
A new UPS topology employing a PFC boost rectifier cascaded high-frequency tri-port converter

A new uninterruptible power supply (UPS) topology using the high-frequency tri-port UPS technique is proposed which presents the advantages of no-break power, low cost, input unity power factor, high power density, and high power conversion efficiency. Through the proposed circuit configuration, charging concept, and control strategy, the battery management is easily obtained by controlling the output voltage of the power-factor-correction (PFC) converter, which results in no additional power device being required for charging. The implementing circuit of the charging method is submitted to perform the two-stage charging, constant current charging, and constant voltage charging. The proposed technologies can be applied to the switching power supply with built-in UPS function featuring a low-cost solution for computer equipment, Finally, an experimental AC online UPS is built to verify the proposed concept, analysis, and control strategy.
Learning cross-regional dependence of EEG with convolutional neural networks for emotion classification

Electroencephalography (EEG) has received much attention because it provides comprehensive information of human perception and is relatively spaceand costeffective compared with the other functional brain imaging methods. In this paper, we present an approach to model undirected and directed cross-regional dependence of EEG signals with convolutional neural networks (CNNs). It considers the brain connectivity that measures simultaneous activation of different brain regions. Furthermore, the spatial arrangement of EEG electrodes is examined. We verify the effectiveness of the method for EEG-based emotion recognition.
Power-leveling as an effect of group model building

The influence of power is a relatively unexplored area within group model building assessment studies. In this paper we explore the effect of group model building on the use of power by participants in modeling sessions, by applying social exchange theory to the communicative exchange process. According to this theory, differences in power between two participants influence their behavior: the larger the power differences between the two participants the less likely they are to interact and vice versa. In general, this behavior is not helpful in designing optimal solutions. It is hypothesized that group model building helps to reduce the use of power by participants compered to regular meetings, we refer to this effect as power-leveling. If our assumption holds, this may explain why group model building is helpful in designing better solutions. This research is conducted in a field setting at the Dutch Health Care Insurance Board, where regular meetings and group model building meetings are studied. The results indicate that the assumption of power-leveling as an effect of group model building seems to hold. Further research is however required to strengthen these findings.
INAUGURAL ARTICLE by a Recently Elected Academy Member:How Christians reconcile their personal political views and the teachings of their faith: Projection as a means of dissonance reduction

The present study explores the dramatic projection of one's own views onto those of Jesus among conservative and liberal American Christians. In a large-scale survey, the relevant views that each group attributed to a contemporary Jesus differed almost as much as their own views. Despite such dissonance-reducing projection, however, conservatives acknowledged the relevant discrepancy with regard to “fellowship” issues (e.g., taxation to reduce economic inequality and treatment of immigrants) and liberals acknowledged the relevant discrepancy with regard to “morality” issues (e.g., abortion and gay marriage). However, conservatives also claimed that a contemporary Jesus would be even more conservative than themselves on the former issues whereas liberals claimed that Jesus would be even more liberal than themselves on the latter issues. Further reducing potential dissonance, liberal and conservative Christians differed markedly in the types of issues they claimed to be more central to their faith. A concluding discussion considers the relationship between individual motivational processes and more social processes that may underlie the present findings, as well as implications for contemporary social and political conflict.
Hidden tree Markov networks: Deep and wide learning for structured data

The paper introduces the Hidden Tree Markov Network (HTN), a neuro-probabilistic hybrid fusing the representation power of generative models for trees with the incremental and discriminative learning capabilities of neural networks. We put forward a modular architecture in which multiple generative models of limited complexity are trained to learn structural feature detectors whose outputs are then combined and integrated by neural layers at a later stage. In this respect, the model is both deep, thanks to the unfolding of the generative models on the input structures, as well as wide, given the potentially large number of generative modules that can be trained in parallel. Experimental results show that the proposed approach can outperform state-of-the-art syntactic kernels as well as generative kernels built on the same probabilistic model as the HTN.
Acute physiological and perceptual responses to wearing additional clothing while cycling outdoors in a temperate environment:A practical method to increase the heat load

ABSTRACT This investigation assessed the acute physiological and perceptual responses to wearing additional clothing during outdoor cycling to determine if this strategy could increase the heat load while training in temperate environments. Seven male cyclists (age: 32 ± 13 y, height: 179 ± 10 cm, body mass: 74 ± 10 kg, body fat percentage: 10.3 ± 1.0%) completed 2 randomized outdoor (∼17°C and ∼82% RH), 80 min cycling sessions at moderate-hard intensities (CR10 RPE = 3–5). They wore spandex shorts and a short sleeve top (CON) or additional clothing including full-length spandex pants and a ‘winter’ cycling jacket and gloves (AC). Core temperature, heart rate, sweat rate, thermal sensation and thermal comfort were measured across the trials. Moderate increases were observed in AC vs. CON for the change in mean core temperature (0.4 ± 0.3°C, effect size, ES = 1.16 ± 0.55), change in maximum core temperature (0.5 ± 0.3°C, ES = 1.07 ± 0.48) and sweat rate (0.24 ± 0.16 L.h−1, ES = 1.04 ± 0.59). A small increase in mean heart rate (3 ± 3 bpm, ES = 0.32 ± 0.28) was observed as well as a ‘very likely’ (percentage difference = 22.4 ± 7.1) and ‘most likely’ (percentage difference = 42.9 ± 11.9) increase in thermal sensation and thermal comfort, respectively, in AC vs. CON. Dressing in additional clothing while cycling outdoors in a temperate environment increased physiological strain and sensations of warmth and discomfort. Training in additional clothing during outdoor cycling represents a practical alternative to increasing the heat load of a training session.
Web-Based Education in Systems-Based Practice

Methods: We enrolled 276 medical students and 417 residents in the fields of surgery, medicine, obstetricsgynecology, and emergency medicine in a 9-week randomized, controlled, crossover educational trial. Participants were asked to sequentially complete validated Web-based modules on patient safety and the US health care system. The primary outcome measure was performance on a 26-item validated online test administered before, between, and after the participants completed the modules. Results: Six hundred forty (92.4%) of the 693 enrollees participated in the study; 512 (80.0%) of the participants completed all 3 tests. Participants’ test scores improved significantly after completion of the first module (P .001). Overall learning from the 9-week Web-based program, as measured by the increase in scores (posttest scores minus pretest scores), was 16 percentage points (95% confidence interval, 14-17 percentage points; P .001) in public safety topics and 22 percentage points (95% confidence interval, 20-23 percentage points; P .001) in US health care system topics.
Collecting Telemetry Data Privately

The collection and analysis of telemetry data from users' devices is routinely performed by many software companies. Telemetry collection leads to improved user experience but poses significant risks to users' privacy. Locally differentially private (LDP) algorithms have recently emerged as the main tool that allows data collectors to estimate various population statistics, while preserving privacy. The guarantees provided by such algorithms are typically very strong for a single round of telemetry collection, but degrade rapidly when telemetry is collected regularly. In particular, existing LDP algorithms are not suitable for repeated collection of counter data such as daily app usage statistics. In this paper, we develop new LDP mechanisms geared towards repeated collection of counter data, with formal privacy guarantees even after being executed for an arbitrarily long period of time. For two basic analytical tasks, mean estimation and histogram estimation, our LDP mechanisms for repeated data collection provide estimates with comparable or even the same accuracy as existing single-round LDP collection mechanisms. We conduct empirical evaluation on real-world counter datasets to verify our theoretical results. Our mechanisms have been deployed by Microsoft to collect telemetry across millions of devices.
Involvement of Machine Learning for Breast Cancer Image Classification: A Survey

Breast cancer is one of the largest causes of women's death in the world today. Advance engineering of natural image classification techniques and Artificial Intelligence methods has largely been used for the breast-image classification task. The involvement of digital image classification allows the doctor and the physicians a second opinion, and it saves the doctors' and physicians' time. Despite the various publications on breast image classification, very few review papers are available which provide a detailed description of breast cancer image classification techniques, feature extraction and selection procedures, classification measuring parameterizations, and image classification findings. We have put a special emphasis on the Convolutional Neural Network (CNN) method for breast image classification. Along with the CNN method we have also described the involvement of the conventional Neural Network (NN), Logic Based classifiers such as the Random Forest (RF) algorithm, Support Vector Machines (SVM), Bayesian methods, and a few of the semisupervised and unsupervised methods which have been used for breast image classification.
Design for Slenderness in Concrete Columns Internally Reinforced with Fiber-Reinforced Polymer Bars

In spite of their successful introduction into the construction market, widespread acceptance of fiber-reinforced polymer (FRP) reinforcement by the engineering community depends on timely development of design guidelines and specifications. Many properties can influence the slenderness of FRP reinforced concrete (RC) columns. In this paper, a rational method is developed for the analysis of slender FRP-RC columns. A detailed parametric study is also carried out. This study recommends reducing the current slenderness limit of 22 to 17 for FRP-RC columns bent in single curvature. It is also shown that the moment magnification method can be extended to FRP-RC columns. The current stiffness formulas, and the stiffness reduction factor, however, need to be adjusted either as sole functions of modular ratio or as functions of both modular ratio and eccentricity ratio.
Shape memory behavior of Ni-rich NiTi foam with different porosity percentages

The shape memory properties of Ni50.6Ti49. 4 alloy having porosity levels of 36%, 55%, and 60% such as recoverable and irrecoverable strain levels, transformation temperatures, and thermal hysteresis are determined from isobaric cooling–heating experiments. High recoverable strain up to 4.5% and almost no irrecoverable strain against up to 100 MPa of applied stress levels are observed due to the high strength of the sintered 36% porous Ni50.6Ti49. 4 alloy. More interestingly, thermal hysteresis under constant stress levels for this sample is notably very low. Furthermore, as the porosity percentage increases from 36% to 55% and 60%, the recoverable strain levels under low constant stress levels increases. Additionally, since the strength of the 60% porous NiTi alloy decreases, it fractures at a relatively lower stress level.