Miracle-dz/UniFAR-FTUs huggingface dataset:
Primary prophylaxis of variceal hemorrhage: a randomized controlled trial comparing band ligation, propranolol, and isosorbide mononitrate.

BACKGROUND & AIMS This randomized controlled trial compared variceal band ligation (VBL), propranolol (PPL), and isosorbide-5-mononitrate (ISMN) in the prevention of first esophageal variceal bleed. METHODS Over a 6-year period, 172 patients with cirrhosis, grade II or III esophageal varices that had never bled, were recruited; 44 into VBL, 66 into PPL, and 62 into ISMN. Baseline patient characteristics: age, 55 +/- 11 years; Child-Pugh score, 8 +/- 2; 65% alcohol-induced cirrhosis; follow-up period, 19.7 +/- 17.6 months (range, 0.13-72.1 months), were comparable in the 3 groups. RESULTS On intention-to-treat analysis, variceal bleeding occurred in 7% of patients randomized to VBL, 14% to PPL, and 23% to ISMN. The 2-year actuarial risks for first variceal bleed were 6.2% (95% confidence interval [CI], 0.0%-15.0%) for VBL, 19.4% (95% CI, 0.1%-32.4%) for PPL, and 27.7% (95% CI, 14.2%-41.2%) for ISMN. A significant number of patients reported side effects with drug treatment (45% PPL and 42% ISMN vs. 2% VBL; P = 0.00), resulting in withdrawal from treatment in 30% of PPL and 21% of ISMN patients. There were no statistically significant differences in mortality rates in the 3 groups. In as-treated analysis, there was a statistically significant difference in actuarial risk for bleeding at 2 years between VBL and ISMN (7.5%, 95% CI, 2.5%-10.6% vs. 33.0%, 95% CI, 15%-49%, respectively, log rank test P = 0.03) but not between VBL and PPL. CONCLUSIONS VBL was equivalent to PPL and superior to ISMN in preventing first variceal bleed. The side-effect profile for pharmacotherapy was considerable.
Optimum Energy Allocation for Cooperative Networks with Differential Modulation

The development of relay transmissions have recently attracted increasing interests in wireless communications since they provide cooperative diversity gains by forming virtual antenna arrays. In such relay networks, optimum energy allocation is critical to enhance their performance and efficiency. However, existing works on performance analysis and optimization mainly focus on single-relay systems. In this paper, an upper bound of the error performance is derived with arbitrary number of relays. Based on this bound, we then develop the optimum energy allocation schemes that minimize the average system error. Equally attractive is that our investigation is tailored for differential modulations, which bypass the channel estimation at the receiver and are particularly suitable for wireless relay networks. The performance improvement of the optimized systems over the un-optimized ones is confirmed by analytical and simulated comparisons
Discriminative stimulus effects of flumazenil: perceptual masking by baclofen, and lack of substitution with gamma-hydroxybutyrate and its precursors 1,4-butanediol and gamma-butyrolactone

Pigeons trained to discriminate 0.1 mg/kg flumazenil, proposed as an in-vivo model to study interactions with diazepam-insensitive &ggr;-aminobutyric acid (GABA)A receptors, were tested with various GABAergic and non-GABAergic compounds. As a result of its pharmacological selectivity, the model was suitable for further examining previously reported flumazenil-like effects of &ggr;-hydroxybutyrate (GHB). Flumazenil and the GABAA negative modulator Ro 15-4513 produced 82–100% flumazenil-appropriate responding. Diazepam and the direct-acting GABAA agonists muscimol and 4,5,6,7-tetrahydroisoxazolo[5,4–c]pyridine-3-ol (THIP) produced 38–64% flumazenil-appropriate responding. GHB, its precursors 1,4-butanediol (1,4-BD) and &ggr;-butyrolactone (GBL), and the GABAB agonists baclofen and SKF97541 produced 0–24% flumazenil-appropriate responding. Baclofen shifted the flumazenil dose–response curve to the right and down, possibly involving perceptual masking of the discriminative stimulus effects of flumazenil by agonist activity at GABAB receptors. These masking effects of baclofen were blocked by the GABAB antagonist CGP35348. When CGP35348 was given together with GHB to block its GABAB agonist effects, GHB did not produce flumazenil-appropriate responding. Conceivably, effects of GHB at non-GABAB receptors (e.g. diazepam-sensitive GABAA receptors and GHB receptors) may interfere with the expression of its flumazenil-like discriminative stimulus effects. The asymmetric substitution between GHB and flumazenil is consistent with the hypothesis that the discriminative stimulus effects of GHB consist of several components, not all of which are mimicked by flumazenil.
Decreasing errors in pediatric continuous intravenous infusions*

Objective: To evaluate the effect of a Web-based calculator and decision-support system on infusion ordering errors and to estimate error frequency in pharmacy infusion preparation. Design: Data on ordering error frequency and typology were collected before and after implementation of an online infusion ordering system. Data on pharmacy preparation errors of infusions were collected. Setting: A children's hospital at an academic medical center. Patients: None. Data were abstracted from infusion orders. Interventions: Introduction of a voluntary-use Web-based calculator into infusion ordering workflow. Observation only. Main Outcome measures: Number and type of errors in handwritten and calculator-generated orders. Number and type of errors in pharmacy infusion preparation. Results: Before calculator deployment, 129 sequential handwritten infusion orders were collected over 5 weeks. After deployment, of 162 sequential infusion orders, 88% (142) were calculator-generated. Calculator-generated infusion orders contained 83% fewer (p < .001) orders containing one or more errors than handwritten orders. Calculator-generated orders contained no high-risk errors (incorrect decimal, dose, or unit of measure) when compared with handwritten orders and were associated with fewer pharmacy interventions. In 118 sequential pharmacy infusion preparations over 4 wks, there were no errors observed. Conclusion: A Web-based calculator reduced significantly the total number of errors and eliminated all high-risk errors in the prescribing process for continuous pediatric infusions. With no observed errors in pharmacy preparation, this study provides data to support the use of computerized ordering as an independent safe and viable method for ordering continuous pediatric infusions.
HIGHLIGHTED TOPIC Hypoxia 2015 Oxygen tension, H 2 S, and NO bioavailability: is there an interaction?

Oxygen H 2 S, and NO bioavailability: is there an interaction? J Appl Physiol 263–270, 2016. doi:10.1152/japplphysiol.00365. 2015. —Molecu-lar oxygen (O 2 ) is an essential component for survival and development. Variation in O 2 levels leads to changes in molecular signaling and ultimately affects the physiological functions of many organisms. Nitric oxide (NO) and hydrogen sulﬁde (H 2 S) are two gaseous cellular signaling molecules that play key roles in several physiological functions involved in maintaining vascular homeostasis including vasodilation, anti-inﬂammation, and vascular growth. Apart from the aforemen- tioned functions, NO and H 2 S are believed to mediate hypoxic responses and serve as O 2 chemosensors in biological systems. In this literature review, we brieﬂy discuss NO and H 2 S and their roles during hypoxia.
A Decentralized Consensus Algorithm via LMI-Based Model Predictive Control and Primal Decomposition

This paper proposes a decentralized model predictive control method for solving an optimal consensus problem, where a system consists of networked multiple subsystems and the states of all the subsystems converge to a common point. The problem is formulated as a convex optimization problem involving linear matrix inequalities, and then is solved by using an incremental subgradient method based on primal decomposition. In the proposed scheme, the state feedback matrix for each subsystem is computed at each time in a decentralized way. It is shown that the states of all the subsystems asymptotically converge by the proposed method if the optimization problem is feasible at the initial time. A numerical example is given to show the effectiveness of the proposed method.
Hindu Arabic character recognition using mathematical morphology

Presentation of a novel decision tree based method to improve the ability of hand written character recognition using mathematical morphology. For this paper, classification of hand written digits is done into two groups: one with blob and another without blob. This paper proposes the recognition of digits using certain features that can distinguish one digit from the other.
Classification of Tree Species in a Diverse African Agroforestry Landscape Using Imaging Spectroscopy and Laser Scanning

Airborne imaging spectroscopy (IS) and laser scanning (ALS) have been explored widely for tree species classification during the past decades. However, African agroforestry areas, where a few exotic tree species are dominant and many native species occur less frequently, have not yet been studied. Obtaining maps of tree species would provide useful information for the characterization of agroforestry systems and detecting invasive species. Our objective was to study tree species classification in a diverse tropical landscape using IS and ALS data at the tree crown level, with primary interest in the exotic tree species. We performed multiple analyses based on different IS and ALS feature sets, identified important features using feature selection, and evaluated the impact of combining the two data sources. Given that a high number of tree species with limited sample size (499 samples for 31 species) was expected to limit the classification accuracy, we tested different approaches to group the species based on the frequency of their occurrence and Jeffries–Matusita (JM) distance. Surface reflectance at wavelengths between 400–450 nm and 750–800 nm, and height to crown width ratio, were identified as important features. Nonetheless, a selection of minimum noise fraction (MNF) transformed reflectance bands showed superior performance. Support vector machine classifier performed slightly better than the random forest classifier, but the improvement was not statistically significant for the best performing feature set. The highest F1-scores were achieved when each of the species was classified separately against a mixed group of all other species, which makes this approach suitable for invasive species detection. Our results are valuable for organizations working on biodiversity conservation and improving agroforestry practices, as we showed how the non-native Eucalyptus spp. , Acacia mearnsii and Grevillea robusta (mean F1-scores 76%, 79% and 89%, respectively) trees can be mapped with good accuracy. We also found a group of six fruit bearing trees using JM distance, which was classified with mean F1-score of 65%. This was a useful finding, as these species could not be classified with acceptable accuracy individually, while they all share common economic and ecological importance.
A behavior change program to increase outings delivered during therapy to stroke survivors by community rehabilitation teams: The Out-and-About trial

Background Australian guidelines recommend that outdoor mobility be addressed to increase participation after stroke. Aim To investigate the efficacy of the Out-and-About program at increasing outings delivered during therapy by community teams, and outings taken by stroke survivors in real life. Method Cluster-randomized trial involving 22 community teams providing stroke rehabilitation. Experimental teams received the Out-and-About program (a behavior change program comprising a training workshop with barrier identification and booster session, printed educational materials, audit, and feedback). Control teams received printed clinical guidelines only. The primary outcome was the percentage of stroke survivors receiving four or more outings during therapy. Secondary outcomes included the number of outings received by stroke survivors during therapy and undertaken in real life. Results At 12 months after implementation of the behavior change program, 9% of audited experimental group stroke survivors received four or more outings during therapy compared with 5% in the control group (adjusted risk difference 4%, 95% CI − 9 to 17, p = 0.54). They received 1.1 (SD 0.9) outings during therapy compared with 0.6 (SD 1.0) in the control group (adjusted mean difference 0.5, 95% CI − 0.4 to 1.4; p = 0.26). After six months of rehabilitation, observed experimental group stroke survivors took 9.0 (SD 3.0) outings per week in real life compared with 7.4 (SD 4.0) in the control group (adjusted mean difference 0.5, 95% CI − 1.8 to 2.8; p = 0.63). Conclusion The Out-and-About program did not change team or stroke survivor behavior.
Partition-Based Coverage Metrics and Type-Guided Search in Concolic Testing for JavaScript Applications

JavaScript extends its uses from client-side web applications to mobile applications, but testing JavaScript applications is not yet satisfactory. Researchers have not spent much attention on testing JavaScript programs, and existing coverage metrics and testing mechanisms for C and Java may not be applicable to JavaScript because of its extremely dynamic semantics without any compile-time checks. Because, in JavaScript, any variable may have any kinds of types during evaluation, and because varying types change program execution flows, testing JavaScript programs requires more cases to cover different execution flows. Thus, test cases with 100% coverage levels in terms of the existing coverage metrics for statically typed languages may miss faults in JavaScript. Moreover, existing search strategies for statically typed languages may not exercise increased test requirements by dynamic languages effectively. In this paper, we identify JavaScript characteristics that make thorough testing of JavaScript programs more difficult than testing C and Java programs. To address such characteristics, we propose new partition-based coverage metrics that expose implicit execution flows using varying types. To generate test cases satisfying the coverage metrics effectively, we develop type-guided search strategies for concolic testing using program analysis results. We evaluate the new coverage metrics and search strategies for concolic testing with open-source web applications, and the preliminary experimental results show that their practical uses in JavaScript testing are promising.
The Ability of Criminal Law to Produce Gender Equality: Judicial Discourses in the Swedish Criminal Legal System

The main aim of the Swedish Women’s Peace reform in 1998 was to enhance criminal legal protection for women exposed to violence in heterosexual relationships and to promote gender equality. However, these ambitions risk being contravened in a masculinist criminal legal system. One problem concerns how the victim is constructed in criminal legal cases. The author argues that moral balancing and discourses of responsibility and guilt in Swedish cases constrain the agency possible for women and suggest that a more comprehensive policy in Sweden must be developed to include violent men, their agency, and their responsibility for the violence.
Evolutionary coalitional games in network selection

The widespread use of heterogeneous wireless technologies, their integration, advent of multi-mode terminals, and the envisioned user (service) centricity enable users to get associated with the best available networks according to user preferences and application specific requirements. When it comes to user-centric network selection, operators with the view to increasing their user-pool may offer different incentives to the users to motivate them form coalitions. In this paper, we present a novel approach of coalition network selection. We use evolutionary game-theory to model this problem. We also examine fully distributed algorithms for global optima in network selection games. Then, the problem of dynamic network formation and evolutionary coalitional games in network selection networks are investigated. This article also points out the open research issues, new interests and developments in this interdisciplinary field.
Subcortical ischaemic changes in young hypertensive patients: frequency, effect on cognitive performance and relationship with markers of endothelial and haemostatic activation

Information on subcortical ischaemic changes (SIC) in young hypertensive patients is scarce. We evaluated the frequency of SIC at magnetic resonance imaging (MRI), the possible effect on cognition of these patients, and the role of plasma markers known as indicators of endothelial and haemostatic activation. Inclusion criteria were age ≤54 years, hypertension for at least 2 years and absence of cerebrovascular disease or other conditions possibly related to SIC. Patients with SIC at MRI and two control groups (matched for age, sex and education) of hypertensive patients without SIC and non‐hypertensive healthy subjects underwent an extensive neuropsychological examination and evaluation of plasma markers. Amongst the 200 patients evaluated, 50 (25%) showed SIC at MRI. Mean age was 48.4 ± 4.8 years. Compared with both control groups, hypertensive patients with SIC performed significantly worse in general cognition, attention, memory and executive functions. Moreover, they showed significantly more often increased levels of all plasma markers compared with healthy controls, and of von Willebrand factor (vWF) compared with both control groups (P < 0.001). In young hypertensive patients SIC are frequent, related to a worse cognitive performance and endothelial dysfunction. Our findings suggest vWF as marker of end‐organ damage, underscoring the relevance of treating hypertension at younger age.
Gestational diabetes mellitus and interpregnancy weight change: A population-based cohort study

Background Being overweight is an important risk factor for Gestational Diabetes Mellitus (GDM), but the underlying mechanisms are not understood. Weight change between pregnancies has been suggested to be an independent mechanism behind GDM. We assessed the risk for GDM in second pregnancy by change in Body Mass Index (BMI) from first to second pregnancy and whether BMI and gestational weight gain modified the risk. Methods and findings In this observational cohort, we included 24,198 mothers and their 2 first pregnancies in data from the Medical Birth Registry of Norway (2006–2014). Weight change, defined as prepregnant BMI in second pregnancy minus prepregnant BMI in first pregnancy, was divided into 6 categories by units BMI (kilo/square meter). Relative risk (RR) estimates were obtained by general linear models for the binary family and adjusted for maternal age at second delivery, country of birth, education, smoking in pregnancy, interpregnancy interval, and year of second birth. Analyses were stratified by BMI (first pregnancy) and gestational weight gain (second pregnancy). Compared to women with stable BMI (−1 to 1), women who gained weight between pregnancies had higher risk of GDM—gaining 1 to 2 units: adjusted RR 2.0 (95% CI 1.5 to 2.7), 2 to 4 units: RR 2.6 (2.0 to 3.5), and ≥4 units: RR 5.4 (4.0 to 7.4). Risk increased significantly both for women with BMI below and above 25 at first pregnancy, although it increased more for the former group. A limitation in our study was the limited data on BMI in 2 pregnancies. Conclusions The risk of GDM increased with increasing weight gain from first to second pregnancy, and more strongly among women with BMI < 25 in first pregnancy. Our results suggest weight change as a metabolic mechanism behind the increased risk of GDM, thus weight change should be acknowledged as an independent factor for screening GDM in clinical guidelines. Promoting healthy weight from preconception through the postpartum period should be a target.
Multiple fuzzy c-means clustering algorithm in medical diagnosis.

BACKGROUND In recent years, the use of the fuzzy c-means (FCM) clustering techniques in medical diagnosis has steadily increased, because of its effectiveness in recognizing systems in the medical database to help medical experts diagnosing diseases. However, its performance is highly dependent on the randomly initialized cluster centroids which may allow the diagnosis to be trapped into the problem of the local optimum. OBJECTIVE This paper proposes a multiple fuzzy c-means (MFCM) algorithm for medical diagnosis. METHODS The new method optimizes the initial optimizing cluster centers by comparing the Euclidean distance between patient data. Further, this paper assigns a set of weights to the features of a certain disease to equalize their difference influence as a substitute for data normalization. RESULTS The performance of proposed MFCM algorithm was demonstrated through dividing complex primary headache data into Migraine, Tension-Type Headache (TTH), Trigeminal Autonomic Cephalalgias (TACs) and other primary headache disorders. In addition the superiority of MFCM algorithm was proven by comparing analytical results with other state-of-the-art clustering methods. CONCLUSIONS This MFCM method has shown a new application in medical diagnosis.
Tags Are Related: Measurement of Semantic Relatedness Based on Folksonomy Network

Folksonomy and tagging systems, which allow users to interactively annotate a pool of shared resources using descriptive tags, have enjoyed phenomenal success in recent years. The concepts are organized as a map in human mind, however, the tags in folksonomy, which reflect users' collaborative cognition on information, are isolated with current approach. What we do in this paper is to estimate the semantic relatedness among tags in folksonomy: whether tags are related from semantic view, rather than isolated? We introduce different algorithms to form networks of folksonomy, connecting tags by users collaborative tagging, or by resource context. Then we perform multiple measures of semantic relatedness on folksonomy networks to investigate semantic information within them. The result shows that the connections between tags have relatively strong semantic relatedness, and the relatedness decreases dramatically as the distance between tags increases. What we find in this paper could provide useful visions in designing future folksonomy-based systems, constructing semantic web in current state of the Internet, and developing natural language processing applications.