Miracle-dz/UniFAR-FTUs huggingface dataset:
In-hospital and mid-term clinical outcomes after percutaneous coronary intervention with drug eluting stents

Background and objective-Sirolimus-eluting (SES) and paclitaxel-eluting (PES) stents are first generation drug-eluting stents (DES) used to treat patients with ischemic heart disease. Drug-eluting stents (DES) have reduced the occurrence of restenosis and major adverse cardiac events (MACE) when compared with bare metal stents. Our aim was to assess the safety and mid-term clinical outcomes of stenting with Sirolimus-eluting stents (SES) and paclitaxel-eluting stents (PES) for the treatment of coronary artery disease in our routine practice. Material and methods- The study population consisted of 100 patients who had undergone drug eluting stent implantation. Patients were eligible for enrollment if they had symptomatic coronary artery disease or positive exercise testing, and angiographic evidence of single or multivessel disease with a target lesion stenosis of ≥ 70%. Patients were followed-up for 6 months. The efficacy and safety of the procedure, in-hospital clinical outcome and the occurrence of major adverse cardiac events in the first 6 months were assessed. Statistical analysis was done. Results-All patients survived after stent implantation.1 (1%) patient experienced acute ST elevation myocardial infarction during follow up. Recurrent angina pectoris was observed in 5 (5%) patients (2 stable angina pectoris and 3 unstable angina pectoris). The 6month rate of MACE in our study was 1%. Conclusion-The results of the present study indicate that drug eluting stents could be implanted with a very high success rate and have encouraging mid-term clinical results.
Construction of a Third-Order K-Scheme and Its Application to Financial Models

The author proposes a new discretization method of stochastic differential equations (SDEs) that lies in the framework of K-scheme (Kusuoka approximation, Kusuoka--Lyons--Ninomiya--Victoir method). K-scheme is a higher-order discretization framework for performing weak approximations of SDEs. The Ninomiya--Victoir and Ninomiya--Ninomiya methods are practically feasible discretization methods that belong to the K-scheme class. These are second-order weak discretization methods, and some extrapolations of them have been proposed. The new method proposed herein is a third-order weak discretization method that involves no extrapolation. Polynomials of Gaussian random variables that approximate iterated Wiener integrals play a key role in the new method. In addition, the author discusses the applications of the proposed method to the pricing of derivatives in practically important financial models, achieving the desired theoretical order and computational efficiency.
Barriers to self-management behaviors in college students with food allergies

ABSTRACT Objective: This study examined barriers to engagement in self-management behaviors among food-allergic college students (1) within the frameworks of the health belief model (HBM) and common sense self-regulation model (CS-SRM) and (2) in the context of overall risky behaviors. Participants: Undergraduate college students who reported having a physician-diagnosed food allergy (N = 141). Research was conducted from February 2015 through May 2016. Methods: Participants were recruited from college campuses through email and social media. The frequency of adherence to self-management behaviors was measured along with HBM, CS-SRM, and risk-taking behaviors through a self-report survey. Results: Among all participants, HBM and CS-SRM constructs and Tobacco Use explained 30.6% of the variance in adherence. CS-SRM constructs and Tobacco Use explained 44.8% of the variance for participants with self-injectable epinephrine (SIE). Conclusions: Food-allergic college students demonstrate inconsistent adherence, and interventions designed to improve adherence should take both SIE prescription status and contextual factors into consideration.
Pre-Whaling Genetic Diversity and Population Ecology in Eastern Pacific Gray Whales: Insights from Ancient DNA and Stable Isotopes

Commercial whaling decimated many whale populations, including the eastern Pacific gray whale, but little is known about how population dynamics or ecology differed prior to these removals. Of particular interest is the possibility of a large population decline prior to whaling, as such a decline could explain the ∼5-fold difference between genetic estimates of prior abundance and estimates based on historical records. We analyzed genetic (mitochondrial control region) and isotopic information from modern and prehistoric gray whales using serial coalescent simulations and Bayesian skyline analyses to test for a pre-whaling decline and to examine prehistoric genetic diversity, population dynamics and ecology. Simulations demonstrate that significant genetic differences observed between ancient and modern samples could be caused by a large, recent population bottleneck, roughly concurrent with commercial whaling. Stable isotopes show minimal differences between modern and ancient gray whale foraging ecology. Using rejection-based Approximate Bayesian Computation, we estimate the size of the population bottleneck at its minimum abundance and the pre-bottleneck abundance. Our results agree with previous genetic studies suggesting the historical size of the eastern gray whale population was roughly three to five times its current size.
Association pattern of NO2 and NMHC towards high ozone concentration in klang

Association rules techniques has advantages to discover knowledge such as frequent pattern or infrequent patterns. Therefore, this paper present the discovering of association rules based on data mining technique towards climatological time series data. For this purpose, k-mean clustering technique has been proposed to determine the interval for all variables separately and use Apriori algorithm to find association rule between the variables. The aims of this study is to determine the useful patterns on the high and low concentration of Ozone surrounding Klang areas. The experiment was conducted using hourly ozone dataset collected at Klang station in years 1997 until 2012. The result has found 17 rules which contribute in identifying the behaviour and the pattern of the variables.
Making the Rules of Sports Fairer

The rules of many sports are not fair—they do not ensure that equally skilled competitors have the same probability of winning. As an example, the penalty shootout in soccer, wherein a coin toss determines which team kicks first on all five penalty kicks, gives a substantial advantage to the first-kicking team, both in theory and practice. We show that a so-called Catch-Up Rule for determining the order of kicking would not only make the shootout fairer but also is essentially strategyproof. By contrast, the so-called Standard Rule now used for the tiebreaker in tennis is fair. We briefly consider several other sports, all of which involve scoring a sufficient number of points to win, and show how they could benefit from certain rule changes, which would be straightforward to implement.
Machine Learning for Volcano-Seismic Signals: Challenges and Perspectives

Environmental monitoring is a topic of increasing interest, especially concerning the matter of natural hazards prediction. Regarding volcanic unrest, effective methodologies along with innovative and operational tools are needed to monitor, mitigate, and prevent risks related to volcanic hazards. In general, the current approaches for volcanoes monitoring are mainly based on the manual analysis of various parameters, including gas leaps, deformations measurements, and seismic signals analysis. However, due to the large amount of data acquired by in situ sensors for long-term monitoring, manual inspection is no longer a viable option. As in many big data situations, classic machinelearning approaches are now considered to automatize the analysis of years of recorded signals, thereby enabling monitoring on a larger scale.
Redundancy Techniques for Straggler Mitigation in Distributed Optimization and Learning

Performance of distributed optimization and learning systems is bottlenecked by "straggler" nodes and slow communication links, which significantly delay computation. We propose a distributed optimization framework where the dataset is "encoded" to have an over-complete representation with built-in redundancy, and the straggling nodes in the system are dynamically left out of the computation at every iteration, whose loss is compensated by the embedded redundancy. We show that oblivious application of several popular optimization algorithms on encoded data, including gradient descent, L-BFGS, proximal gradient under data parallelism, and coordinate descent under model parallelism, converge to either approximate or exact solutions of the original problem when stragglers are treated as erasures. These convergence results are deterministic, i.e., they establish sample path convergence for arbitrary sequences of delay patterns or distributions on the nodes, and are independent of the tail behavior of the delay distribution. We demonstrate that equiangular tight frames have desirable properties as encoding matrices, and propose efficient mechanisms for encoding large-scale data. We implement the proposed technique on Amazon EC2 clusters, and demonstrate its performance over several learning problems, including matrix factorization, LASSO, ridge regression and logistic regression, and compare the proposed method with uncoded, asynchronous, and data replication strategies.
A Systematic Review of Diabetes Self-Care Interventions for Older, African American, or Latino Adults

PURPOSE this study system dente and exained published self-care ntetion desgd to *nrv glycenu control or quality of life (QoL) among ole, African Americn or Latino adults. METHODS Six electronic databases were searchecl Eligible publicato were thoe that described an intervnin to change knowledge, belie, or behavior among adults with diabetes who were either older than 55 years, African American, or Latino, and that measured the outcomes ofglyeic control or QoL. RESULTS Twelve studies met the inclusion criteria, of which 8 were rdomized conrlld trials (RCTs). Of the 8 RCTs, i7provd glycemic control was reported in the intervention arm of S RCTs comparedwith the control arm Of the 4 RCTs theat amined QoL, inprd QoL was reported in the idention ann of 1 study Charaaristics of sssid inter dio s ed poor glcmvic control at baseline (AlC>1 1%), adtural or agetaioring the inevto use of group counseling or support, and inzdmt of spouses and adult children. CONCLUSIONS Large-scale cinial trials designed according to aural and age cieria speciic for older Ltins and African Americas uh diabetes are needed to determine hbow best to adess this growing publc heath problem.
Chemotaxis Arrays in Vibrio Species and Their Intracellular Positioning by the ParC/ParP System

Most motile bacteria are able to bias their movement toward more favorable environments or to escape from obnoxious substances by a process called chemotaxis. Chemotaxis depends on a chemosensory system that is able to sense specific environmental signals and generate a behavioral response. ABSTRACT Most motile bacteria are able to bias their movement toward more favorable environments or to escape from obnoxious substances by a process called chemotaxis. Chemotaxis depends on a chemosensory system that is able to sense specific environmental signals and generate a behavioral response. Typically, the signal is transmitted to the bacterial flagellum, ultimately regulating the swimming behavior of individual cells. Chemotaxis is mediated by proteins that assemble into large, highly ordered arrays. It is imperative for successful chemotactic behavior and cellular competitiveness that chemosensory arrays form and localize properly within the cell. Here, we review how chemotaxis arrays form and localize in Vibrio cholerae and Vibrio parahaemolyticus. We focus on how the ParC/ParP system mediates cell cycle-dependent polar localization of chemotaxis arrays and thus ensures proper cell pole development and array inheritance upon cell division.
Assessing the direct and indirect effects of food provisioning and nutrient enrichment on wildlife infectious disease dynamics

Anthropogenic resource supplementation can shape wildlife disease directly by altering the traits and densities of hosts and parasites or indirectly by stimulating prey, competitor or predator species. We first assess the direct epidemiological consequences of supplementation, highlighting the similarities and differences between food provisioning and two widespread forms of nutrient input: agricultural fertilization and aquatic nutrient enrichment. We then review an aquatic disease system and a general model to assess whether predator and competitor species can enhance or overturn the direct effects of enrichment. All forms of supplementation can directly affect epidemics by increasing host population size or altering parasite production within hosts, but food provisioning is most likely to aggregate hosts and increase parasite transmission. However, if predators or competitors increase in response to supplementation, they could alter resource-fuelled outbreaks in focal hosts. We recommend identifying the traits of hosts, parasites or interacting species that best predict epidemiological responses to supplementation and evaluating the relative importance of these direct and indirect mechanisms. Theory and experiments should examine the timing of behavioural, physiological and demographic changes for realistic, variable scenarios of supplementation. A more integrative view of resource supplementation and wildlife disease could yield broadly applicable disease management strategies. This article is part of the theme issue ‘Anthropogenic resource subsidies and host–parasite dynamics in wildlife’.
Paclitaxel Treatment and Proprotein Convertase 1/3 (PC1/3) Knockdown in Macrophages is a Promising Antiglioma Strategy as Revealed by Proteomics and Cytotoxicity Studies*

High grade gliomas are the most common brain tumors in adult. These tumors are characterized by a high infiltration in microglial cells and macrophages. The immunosuppressive tumor environment is known to orient immune cells toward a pro-tumoral and anti-inflammatory phenotype. Therefore, the current challenge for cancer therapy is to find a way to reorient macrophages toward an antitumoral phenotype. Previously, we demonstrated that macrophages secreted antitumoral factors when they were invalidated for the proprotein converstase 1/3 (PC1/3) and treated with LPS. However, achieving an activation of macrophages via LPS/TLR4/Myd88-dependent pathway appears yet unfeasible in cancer patients. On the contrary, the antitumor drug Paclitaxel is also known to activate the TLR4 MyD88-dependent signaling pathway and mimics LPS action. Therefore, we evaluated if PC1/3 knock-down (KD) macrophages could be activated by Paclitaxel and efficient against glioma. We report here that such a treatment of PC1/3 KD macrophages drove to the overexpression of proteins mainly involved in cytoskeleton rearrangement. In support of this finding, we found that these cells exhibited a Ca2+ increase after Paclitaxel treatment. This is indicative of a possible depolymerization of microtubules and may therefore reflect an activation of inflammatory pathways in macrophages. In such a way, we found that PC1/3 KD macrophages displayed a repression of the anti-inflammatory pathway STAT3 and secreted more pro-inflammatory cytokines. Extracellular vesicles isolated from these PC1/3 KD cells inhibited glioma growth. Finally, the supernatant collected from the coculture between glioma cells and PC1/3 KD macrophages contained more antitumoral factors. These findings unravel the potential value of a new therapeutic strategy combining Paclitaxel and PC1/3 inhibition to switch macrophages toward an antitumoral immunophenotype.
A steady-state stomatal model of balanced leaf gas exchange, hydraulics and maximal source–sink flux

Trees must simultaneously balance their CO2 uptake rate via stomata, photosynthesis, the transport rate of sugars and rate of sugar utilization in sinks while maintaining a favourable water and carbon balance. We demonstrate using a numerical model that it is possible to understand stomatal functioning from the viewpoint of maximizing the simultaneous photosynthetic production, phloem transport and sink sugar utilization rate under the limitation that the transpiration-driven hydrostatic pressure gradient sets for those processes. A key feature in our model is that non-stomatal limitations to photosynthesis increase with decreasing leaf water potential and/or increasing leaf sugar concentration and are thus coupled to stomatal conductance. Maximizing the photosynthetic production rate using a numerical steady-state model leads to stomatal behaviour that is able to reproduce the well-known trends of stomatal behaviour in response to, e.g., light, vapour concentration difference, ambient CO2 concentration, soil water status, sink strength and xylem and phloem hydraulic conductance. We show that our results for stomatal behaviour are very similar to the solutions given by the earlier models of stomatal conductance derived solely from gas exchange considerations. Our modelling results also demonstrate how the 'marginal cost of water' in the unified stomatal conductance model and the optimal stomatal model could be related to plant structural and physiological traits, most importantly, the soil-to-leaf hydraulic conductance and soil moisture.
Changes in Body Condition of Hibernating Bats Support the Thrifty Female Hypothesis and Predict Consequences for Populations with White-Nose Syndrome

White-nose syndrome (WNS) is a new disease of bats that has devastated populations in eastern North America. Infection with the fungus, Geomyces destructans, is thought to increase the time bats spend out of torpor during hibernation, leading to starvation. Little is known about hibernation in healthy, free-ranging bats and more data are needed to help predict consequences of WNS. Trade-offs presumably exist between the energetic benefits and physiological/ecological costs of torpor, leading to the prediction that the relative importance of spring energy reserves should affect an individual's use of torpor and depletion of energy reserves during winter. Myotis lucifugus mate during fall and winter but females do not become pregnant until after spring emergence. Thus, female reproductive success depends on spring fat reserves while male reproductive success does not. Consequently, females should be “thrifty” in their use of fat compared to males. We measured body condition index (BCI; mass/forearm length) of 432 M. lucifugus in Manitoba, Canada during the winter of 2009/2010. Bats were captured during the fall mating period (n = 200), early hibernation (n = 125), and late hibernation (n = 128). Adult females entered hibernation with greater fat reserves and consumed those reserves more slowly than adult males and young of the year. Consequently, adult females may be more likely than males or young of the year to survive the disruption of energy balance associated with WNS, although surviving females may not have sufficient reserves to support reproduction.
momentuHMM: R package for generalized hidden Markov models of animal movement

Discrete‐time hidden Markov models (HMMs) have become an immensely popular tool for inferring latent animal behaviours from telemetry data. While movement HMMs typically rely solely on location data (e.g. step length and turning angle), auxiliary biotelemetry and environmental data are powerful and readily‐available resources for incorporating much more ecological and behavioural realism. However, complex movement or observation process models often necessitate custom and computationally demanding HMM model‐fitting techniques that are impractical for most practitioners, and there is a paucity of generalized user‐friendly software available for implementing multivariate HMMs of animal movement. Here, we introduce an open‐source R package, momentuHMM, that addresses many of the deficiencies in existing HMM software. Features include: (1) data pre‐processing and visualization; (2) user‐specified probability distributions for an unlimited number of data streams and latent behaviour states; (3) biased and correlated random walk movement models, including dynamic “activity centres” associated with attractive or repulsive forces; (4) user‐specified design matrices and constraints for covariate modelling of parameters using formulas familiar to most R users; (5) multiple imputation methods that account for measurement error and temporally irregular or missing data; (6) seamless integration of spatio‐temporal covariate raster data; (7) cosinor and spline models for cyclical and other complicated patterns; (8) model checking and selection; and (9) simulation. After providing an overview of the main features of the package, we demonstrate some of the capabilities of momentuHMM using real‐world examples. These include models for cyclical movement patterns of African elephants, foraging trips of northern fur seals, loggerhead turtle movements relative to ocean surface currents, and grey seal movements among three activity centres. momentuHMM considerably extends the capabilities of existing HMM software while accounting for common challenges associated with telemetry data. It therefore facilitates more realistic hypothesis‐driven animal movement analyses that have hitherto been largely inaccessible to non‐statisticians. While motivated by telemetry data, the package can be used for analysing any type of data that is amenable to HMMs. Practitioners interested in additional features are encouraged to contact the authors.
Methylation and Loss of Secreted Frizzled-Related Protein 3 Enhances Melanoma Cell Migration and Invasion

Background Wnt signaling is important in development and can also contribute to the initiation and progression of cancer. The Secreted Frizzled Related Proteins (SFRPs) constitute a family of Wnt modulators, crucial for controlling Wnt signaling. Here we investigate the expression and role of SFRP3 in melanoma. Methodology/Principal Findings We show that SFRP3 mRNA is down-regulated in malignant melanoma tumors as compared to normal/benign tissue. Furthermore, we found that SFRP3 expression was lost in the malignant melanoma cell lines, A2058, HTB63 and A375, but not in the non-transformed melanocyte cell line, Hermes 3A. Methylated CpG rich areas were detected in the SFRP3 gene in melanoma cell lines and their SFRP3 expression could be restored using the demethylating agent, 5′aza-deoxycytidine. Addition of recombinant SFRP3 to melanoma cells had no effect on viable cell numbers, but decreased cell migration and invasion. Wnt5a signaling has been shown to increase the migration and invasion of malignant melanoma cells, and high expression of Wnt5a in melanoma tumors has been connected to a poor prognosis. We found that recombinant SFRP3 could inhibit Wnt5a signaling, and that it inhibited melanoma cell migration and invasion in a Wnt5a-dependent manner. Conclusion/Significance We conclude that SFRP3 functions as a melanoma migration and invasion suppressor by interfering with Wnt5a signaling.