Miracle-dz/UniFAR-FTUs huggingface dataset:
FlameDB: A Key-Value Store With Grouped Level Structure and Heterogeneous Bloom Filter

Key-value (KV) stores are widely used to provide much higher read and write throughput than traditional SQL databases. In particular, LSM-tree based KV store is popular with many applications since it could eliminate random writes and thus provides good write performance. However, the data residing in external storage are compacted from time to time, which takes a large amount of I/O resources and degrades the system performance. In this paper, we propose FlameDB, which leverages grouped level structure (GLS) to mitigate the compaction overhead. Besides dividing the whole storage space into multiple components as in LSM-tree, GLS further divides each component into multiple groups and compacts all KV items in a component as a group of the next component. Besides, we also propose a heterogeneous bloom filter (HEBF) scheme which assigns more bits to the bloom filters in upper components. With HEBF, the false positive rate of a bloom filter in upper components become smaller, and this scheme reduces the expected number of I/Os to read a KV item from the external storage with a given memory usage. Our experiments show that FlameDB saves about 75% I/O during compaction, so it improves the write throughput by about four times. Meanwhile, the read performance is also slightly improved by deploying HEBF.
Interaction between quinoline yellow and human serum albumin: spectroscopic, chemometric and molecular docking studies.

BACKGROUND Quinoline yellow (QY), a synthetic colourant widely used in the food industry, has caused extensive concerns because of its potentially harmful effects on human health. In the present work, the interactions between QY and human serum albumin (HSA) were characterized by multiple spectroscopic methods, a chemometric algorithm, and molecular modelling studies. RESULTS The concentration profiles and pure spectra obtained for the components (QY, HSA and QY-HSA complex) from analyses of the expanded UV-visible absorption data matrices by multivariate curve resolution alternating least squares confirmed the QY-HSA interaction process. QY quenched the fluorescence of HSA through formation of a QY-HSA complex that was stabilized by moderate affinity. Hydrophobic forces and hydrogen bonding play major roles in the binding of QY to HSA. Site-specific marker-induced displacement results suggest that QY binds to subdomain IIA of HSA. This was corroborated by the molecular docking results. Decreases in HSA surface hydrophobicity and free sulfhydryl group content indicate that QY causes a contraction of the peptide strand in HSA, hiding the hydrophobic patches of the protein. Analyses by UV-visible absorption, circular dichroism, and three-dimensional fluorescence spectroscopy found that QY causes microenvironmental perturbations around the fluorophores and secondary structure changes in HSA. CONCLUSION This work shows that QY binds to HSA, affecting its structural and functional properties, and provides new insights into the binding mechanism and a comprehensive understanding of the toxicity of QY to biological processes. © 2018 Society of Chemical Industry.
Peperomia at SemEval-2018 Task 2: Vector Similarity Based Approach for Emoji Prediction

This paper describes our participation in SemEval 2018 Task 2: Multilingual Emoji Prediction, in which participants are asked to predict a tweet’s most associated emoji from 20 emojis. Instead of regarding it as a 20-class classification problem we regard it as a text similarity problem. We propose a vector similarity based approach for this task. First the distributed representation (tweet vector) for each tweet is generated, then the similarity between this tweet vector and each emoji’s embedding is evaluated. The most similar emoji is chosen as the predicted label. Experimental results show that our approach performs comparably with the classification approach and shows its advantage in classifying emojis with similar semantic meaning.
Improving Scheduling Efficiency of Hadoop YARN Using AFSA Algorithm

Apache Hadoop is one of the most popular MapReduce framework for parallel processing of large data sets. As the job scheduler and resource manager, YARN plays a very important role. Schedulers on YARN are designed to minimize the makespan of MapReduce jobs. The performance of a scheduler in YARN depends not only on whether the resource capacity of the working nodes are fully utilized, but also on the dependencies among those tasks. Therefore it is very difficult to achieve an optimal solution. This paper proposes a new Hadoop YARN scheduling algorithm. The algorithm formalizes the problem as a multiple knapsack problem which takes into consideration of the resource cost and time cost of each task as well as the dependency between different tasks. Artificial Fish Swarm Algorithm is adopted to solve the knapsack optimization problem. The algorithm was implemented as a pluggable scheduler on the most recent version of Hadoop YARN and evaluated with several MapReduce benchmarks. The experimental results show that our scheduler could effectively reduce the makespan of Hadoop jobs by 30% compared with some existing scheduling policies.
INAOE-UPV at SemEval-2018 Task 3: An Ensemble Approach for Irony Detection in Twitter

This paper describes an ensemble approach to the SemEval-2018 Task 3. The proposed method is composed of two renowned methods in text classification together with a novel approach for capturing ironic content by exploiting a tailored lexicon for irony detection. We experimented with different ensemble settings. The obtained results show that our method has a good performance for detecting the presence of ironic content in Twitter.
Implementing a Glass Fracture Module in the BRANZFIRE Zone Model

A glass fracture routine has been successfully implemented in the BRANZFIRE zone model, based largely on the heat transfer model developed by Sincaglia and Barnett and the fracture criterion of Pagni and Joshi. A second implementation of the model has been successfully created as a spreadsheet. The zone model implementation has been compared against an existing glass fracture model, BREAK1 and against a series of experiments. This model has been found to predict fracture times consistent with BREAK1 over a range of simulations. Fracture time predictions have also compared well with experimental results. A Monte Carlo based sensitivity analysis found that fracture strength was the most important input variable, though this is largely attributable to the large standard deviation of the probability distribution used for this input.
Theoretical study of the role of the tip in enhancing the sensitivity of differential conductance tunneling spectroscopy on magnetic surfaces

Based on a simple model for spin-polarized scanning tunneling spectroscopy (SP-STS), we study how tip magnetization and electronic structure affects the differential conductance (dI/dV ) tunneling spectrum of an Fe(001) surface. We take into account energy dependence of the vacuum decay of electron states and tip electronic structure either using an ideal model or based on ab initio electronic structure calculation. In the STS approach, topographic and magnetic contributions to dI/dV can clearly be distinguished and analyzed separately. Our results suggest that the sensitivity of STS on a magnetic sample can be tuned and even enhanced by choosing the appropriate magnetic tip and bias set point, and the effect is governed by the effective spin polarization.
Effects of dams on downstream molluscan predator-prey interactions in the Colorado River estuary

Effects of dams on downstream molluscan predator-prey interactions in the Colorado River estuary Authors Jansen A. Smith (jas933@cornell.edu) John C. Handley (handley@priweb.org) Gregory P. Dietl (gpd3@cornell.edu) Affiliations 1. Department of Earth and Atmospheric Sciences, Cornell University, Ithaca, NY 14853; 2. Paleontological Research Institution, Ithaca, NY, 14850 Corresponding Author Jansen Smith, jas933@cornell.edu; telephone: 608-498-2331; fax: 607-273-6620
Usability and Learnability of RxUniverse, an Enterprise-Wide App Prescribing Platform Used in an Academic Tertiary Care Hospital

The objective of this study was to assess the usability of RxUniverse, a novel platform that enables health care providers to directly disseminate proven, evidence-based mobile health apps to patients. Among five pilot clinical sites, 40 physicians and front-line providers were trained on the RxUniverse platform. They were educated on the platform's functionality and instructed how to prescribe apps to their patients. The well-validated System Usability Score (SUS) was used to assess the usability of the platform. The adoption goal was set as 100 prescriptions of relevant apps within an 8-week pilot period. Within the pilot period, over 2000 apps were prescribed. Nineteen responses were received from the System Usability Score survey, and the platform received a usability score of 84.2, which is in the 96th percentile across all systems. The pilot study outcomes demonstrate the high adoption and usability of the RxUniverse platform.
Lyb3b at SemEval-2018 Task 12: Ensemble-based Deep Learning Models for Argument Reasoning Comprehension Task

Reasoning is a crucial part of natural language argumentation. In order to comprehend an argument, we have to reconstruct and analyze its reasoning. In this task, given a natural language argument with a reason and a claim, the goal is to choose the correct implicit reasoning from two options, in order to form a reasonable structure of (Reason, Warrant, Claim). Our approach is to build distributed word embedding of reason, warrant and claim respectively, meanwhile, we use a series of frameworks such as CNN model, LSTM model, GRU with attention model and biLSTM with attention model for processing word vector. Finally, ensemble mechanism is used to integrate the results of each framework to improve the final accuracy. Experiments demonstrate superior performance of ensemble mechanism compared to each separate framework. We are the 11th in official results, the final model can reach a 0.568 accuracy rate on the test dataset.
Validation of “Wound QoL” Hebrew version disease‐specific questionnaire for patients with lower extremity ulcerations

The slow healing process and high recurrence rate of lower extremity ulcerations (LEU) impose a considerable medical and economic burden and affect quality of life (QoL). Analyses of LEU‐related QoL in Israel are limited due to lack of a validated Hebrew disease‐specific evaluation instrument. The aim of this study was to validate the disease‐specific Hebrew “Wound QoL” questionnaire. The validation of the “Wound QoL” disease‐specific instrument, translated from English to Hebrew, was based on a comparison with the valid Hebrew version of the SF12v.2 health‐related questionnaire. The convenience sample for the “Wound QoL” validation (n = 32) was obtained from patient populations in the Maccabi Health Services’ outpatient clinics at the northern and southern parts of Israel. The study was conducted between June and September 2017. Face/construct validity was accepted by specialists’ consensus. Internal consistency assessed by Cronbach's α was . 893. Concurrent validity reflected by Pearson's correlations between the tools was in the range of 0.830 to 0.950. The Wound QoL Hebrew version is a valid and reliable instrument suitable for implementation in an Israeli cultural environment.
ESTIMATION OF TIGER DENSITIES IN INDIA USING PHOTOGRAPHIC CAPTURES AND RECAPTURES

The tiger (Panthera tigris) is an endangered, large felid whose demographic status is poorly known across its distributional range in Asia. Previously applied methods for estimating tiger abundance, using total counts based on tracks, have proved unreliable. Lack of reliable data on tiger densities not only has constrained our ability to understand the ecological factors shaping communities of large, solitary felids, but also has undermined the effective conservation of these animals. In this paper, we describe the use of a field method proposed by Karanth (1995), which combines camera-trap photography, to identify individual tigers, with theoretically well-founded capture-recapture models. We developed a sampling design for camera-trapping and used the approach to estimate tiger population size and density in four representative tiger habitats in different parts of India. The field method worked well and provided data suitable for analysis using closed capture-recapture models. The results suggest the potential for applying this methodology to rigorously estimate abundances, survival rates, and other population parameters for tigers and other low-density, secretive animal species in which individuals can be identified based on natural markings. Estimated probabilities of photo-capturing tigers present in the study sites ranged from
Cross-Domain Review Helpfulness Prediction Based on Convolutional Neural Networks with Auxiliary Domain Discriminators

With the growing amount of reviews in e-commerce websites, it is critical to assess the helpfulness of reviews and recommend them accordingly to consumers. Recent studies on review helpfulness require plenty of labeled samples for each domain/category of interests. However, such an approach based on close-world assumption is not always practical, especially for domains with limited reviews or the “out-of-vocabulary” problem. Therefore, we propose a convolutional neural network (CNN) based model which leverages both word-level and character-based representations. To transfer knowledge between domains, we further extend our model to jointly model different domains with auxiliary domain discriminators. On the Amazon product review dataset, our approach significantly outperforms the state of the art in terms of both accuracy and cross-domain robustness.
Long-surface-wave instability in dense granular flows

In this paper we present an experimental study of the long-surface-wave instability that can develop when a granular material flows down a rough inclined plane. The threshold and the dispersion relation of the instability are precisely measured by imposing a controlled perturbation at the entrance of the flow and measuring its evolution down the slope. The results are compared with the prediction of a linear stability analysis conducted in the framework of the depth-averaged or Saint-Venant equations. We show that when the friction law proposed in Pouliquen (1999a) is introduced in the Saint-Venant equations, the theory is able to predict quantitatively the stability threshold and the phase velocity of the waves but fails in predicting the observed cutoff frequency. The instability is shown to be of the same nature as the long-wave instability observed in classical fluids but with characteristics that can dramatically differ due to the specificity of the granular rheology.
A study on the role of small intestinal bacterial overgrowth in patients with functional dyspepsia

Background: Functional dyspepsia (FD) accounts for majority of dyspepsia. Before labeling them as FD, a bunch of investigations to be done to rule out organic cause. Small intestinal bacterial overgrowth (SIBO) which is one of the cause for dyspepsia is not commonly sought and always neglected among physicians. So we aimed to study the frequency of SIBO in patients with dyspeptic symptoms and whether to include investigations to diagnose SIBO in the algorithm of approach to dyspepsia. Materials and methods: We consecutively enrolled 50 newly diagnosed functional dyspepsia patients based on Rome III criteria and 50 healthy controls in this study. They underwent glucose hydrogen breath test (GHBT) after overnight fasting. Results: In the cases with FD, 6 (12%) subjects were found to have positive GHBT and diagnosed as SIBO, whereas in the controls 2 (4%) had positive GHBT with no statistical significant difference among groups with a P value of 0.140. In the cases with FD, the most common subtype was post prandial distress syndrome (46%), followed by epigastric pain syndrome (36%) and mixed type Sabarinathan Ramanathan, Premkumar Karunakaran, Kani Shaikh Mohamed, Ratnakar Kini, Pugazhendhi Thangavel, Murali Ananthavadivelu, Mohammed Ali, Rabindranath Eswaran, Thinakar Mani, Chandrashekar Patil. A study on the role of small intestinal bacterial overgrowth in patients with functional dyspepsia. IAIM, 2017; 4(5): 88-97. Page 89 (18%). Patients with SIBO were treated with rifaximin 1200 mg/day in divided doses for 10 days. GHBT was repeated after 4 weeks and found to be normalized in all cases. Conclusion: SIBO should be considered before making a diagnosis of FD. GHBT is a simple noninvasive method to diagnose SIBO. One could avoid taking unnecessary drugs by timely diagnosis of SIBO in patients with dyspepsia.
A new boundary element technique without domain integrals for elastoplastic solids

A simple idea is proposed to solve boundary value problems for elastoplastic solids via boundary elements, namely, to use the Green's functions corresponding to both the loading and unloading branches of the tangent constitutive operator to solve for plastic and elastic regions, respectively. In this way, domain integrals are completely avoided in the boundary integral equations. Though a discretization of the region where plastic flow occurs still remains necessary to account for the inhomogeneity of plastic deformation, the elastoplastic analysis reduces, in essence, to a straightforward adaptation of techniques valid for anisotropic linear elastic constitutive equations (the loading branch of the elastoplastic constitutive operator may be viewed formally as a type of anisotropic elastic law). Numerical examples, using J2‐flow theory with linear hardening, demonstrate that the proposed method retains all the advantages related to boundary element formulations, is stable and performs well.
BAHS: A Bandwidth-Aware Heterogeneous Scheduling Approach for SDN-Based Cluster Systems

Software Defined Networking(SDN) is a novel network architecture proposed by Stanford in 2008, which decouples control plane and data plane separately. SDN comes with logically centralized view of the whole network status and flexible control of packet switching, providing more possibilities of manipulating network in large-scale cloud systems. Scheduling algorithms impact the network performance significantly, especially for SDN-based cluster systems. However, finding an appropriate scheduling algorithm for heterogeneous network environments is an NP problem, where Quality-of-Service(QoS) needs to be ensured efficiently in these systems. Existing solutions rarely take into account of fine-grained bandwidth information and the lack of global network information also reasons why bandwidth is not widely used in scheduling. ,,,, ,,,, To address this problem, we proposed a new scheduling approach called BAHS, which is a comprehensive scheduling approach built in SDN environment. The main idea of BAHS is choosing proper tasks and their corresponding paths with the lowest interference. To estimate potential path conflicts, BAHS incorporates the state-of-the-art solution such as Dynamic Online Routing Algorithm(DORA). To demonstrate the effectiveness of our proposed approach, we conduct several simulations based on Mininet. Compared to previous approaches, BAHS improves the completion time and local rate of all tasks with QoS guarantee by up to 14.49% and 12.76%, respectively.
Shared and Distinct Features of Human Milk and Infant Stool Viromes

Infants acquire many of their microbes from their mothers during the birth process. The acquisition of these microbes is believed to be critical in the development of the infant immune system. Bacteria also are transmitted to the infant through breastfeeding, and help to form the microbiome of the infant gastrointestinal (GI) tract; it is unknown whether viruses in human milk serve to establish an infant GI virome. We examined the virome contents of milk and infant stool in a cohort of mother-infant pairs to discern whether milk viruses colonize the infant GI tract. We observed greater viral alpha diversity in milk than in infant stool, similar to the trend we found for bacterial communities from both sites. When comparing beta diversity, viral communities were mostly distinguishable between milk and infant stool, but each was quite distinct from adult stool, urine, and salivary viromes. There were significant differences in viral families in the infant stool (abundant bacteriophages from the family Siphoviridae) compared to milk (abundant bacteriophages from the family Myoviridae), which may reflect significant differences in the bacterial families identified from both sites. Despite the differences in viral taxonomy, we identified a significant number of shared viruses in the milk and stool from all mother-infant pairs. Because of the significant proportion of bacteriophages transmitted in these mother-infant pairs, we believe the transmission of milk phages to the infant GI tract may help to shape the infant GI microbiome.
Determining the validity and reliability of measuring scale for entrepreneurship in sport

The present study aims to measure the entrepreneurship of graduate students of physical education. In so doing, a 75-item entrepreneurship questionnaire was implemented on 300 last semester bachelor students of Physical Education and Sport Sciences in Azad and State universities of Tehran province, Iran. This scale consists of twelve subscales including responsibility, opportunity, confidence, seeking opportunity, progress motivation, risk tolerance, perseverance, need to progress, creativity, intelligence, assertiveness and decision- making and 75 items with statements on entrepreneurship in sport. Face and content validity [expert's opinions], structure [exploratory and confirmatory factor analysis] were used to validate questionnaire and Cronbach's alpha method [0.90] was used for making the questionnaire reliable. The results revealed that for entrepreneurial tool in sport, the priority of areas is: responsibility, chance, confidence, seeking opportunity, progress motivation, risk tolerance, perseverance, need to progress, creativity, intelligence, assertiveness and making-decision, respectively. It is necessary to do an action for recognizing the features, status and importance of entrepreneurs' works because entrepreneurship is the main factor of creativity and innovation. Without a doubt, studying characteristics of entrepreneurs and designing and constructing an instrument for identifying and supporting them are important.