nils-herrmann/clean_scirepeval huggingface dataset:
An inkjet-printed UWB antenna on paper substrate utilizing a novel fractal matching network

In this work, the smallest reported inkjet-printed UWB antenna is proposed that utilizes a fractal matching network to increase the performance of a UWB microstrip monopole. The antenna is inkjet-printed on a paper substrate to demonstrate the ability to produce small and low-cost UWB antennas with inkjet-printing technology which can enable compact, low-cost, and environmentally friendly wireless sensor network.
ResumeNet: A Learning-Based Framework for Automatic Resume Quality Assessment

Recruitment of appropriate people for certain positions is critical for any companies or organizations. Manually screening to select appropriate candidates from large amounts of resumes can be exhausted and time-consuming. However, there is no public tool that can be directly used for automatic resume quality assessment (RQA). This motivates us to develop a method for automatic RQA. Since there is also no public dataset for model training and evaluation, we build a dataset for RQA by collecting around 10K resumes, which are provided by a private resume management company. By investigating the dataset, we identify some factors or features that could be useful to discriminate good resumes from bad ones, e.g., the consistency between different parts of a resume. Then a neural-network model is designed to predict the quality of each resume, where some text processing techniques are incorporated. To deal with the label deficiency issue in the dataset, we propose several variants of the model by either utilizing the pair/triplet-based loss, or introducing some semi-supervised learning technique to make use of the abundant unlabeled data. Both the presented baseline model and its variants are general and easy to implement. Various popular criteria including the receiver operating characteristic (ROC) curve, F-measure and ranking-based average precision (AP) are adopted for model evaluation. We compare the different variants with our baseline model. Since there is no public algorithm for RQA, we further compare our results with those obtained from a website that can score a resume. Experimental results in terms of different criteria demonstrate effectiveness of the proposed method. We foresee that our approach would transform the way of future human resources management.
Enrichr: a comprehensive gene set enrichment analysis web server 2016 update

Enrichment analysis is a popular method for analyzing gene sets generated by genome-wide experiments. Here we present a significant update to one of the tools in this domain called Enrichr. Enrichr currently contains a large collection of diverse gene set libraries available for analysis and download. In total, Enrichr currently contains 180 184 annotated gene sets from 102 gene set libraries. New features have been added to Enrichr including the ability to submit fuzzy sets, upload BED files, improved application programming interface and visualization of the results as clustergrams. Overall, Enrichr is a comprehensive resource for curated gene sets and a search engine that accumulates biological knowledge for further biological discoveries. Enrichr is freely available at: http://amp.pharm.mssm.edu/Enrichr.
PARHELIA: Particle Filter-Based Heart Rate Estimation From Photoplethysmographic Signals During Physical Exercise

The photoplethysmographic (PPG) signal is an important source of information for estimating heart rate (HR). However, the PPG signal could be strongly contaminated by the motion artifact of the subjects, making HR estimation a particularly difficult problem. In this paper, we propose PARHELIA, a PARticle filter-based algorithm for HEart rate estimation using photopLethysmographIc signAls. The proposed method employs a particle filter, and utilizes the simultaneously recorded acceleration signals from a wrist-type sensor, to keep track of multiple HR candidates. This achieves quick recovery from incorrect HR estimations under the strong influence of the MA. Experimental results for a dataset of 12 subjects recorded during fast running showed that the average absolute estimation error was 1.17 beats per minute (BPM) whereas that of the best-known conventional method, JOSS, is 1.28 BPM. Furthermore, the estimation time of PARHELIA is 20 times shorter than JOSS.
Detection of Malicious Transaction in Database Using Log Mining Approach

Data mining is the process of finding correlations in the relational databases. There are different techniques for identifying malicious database transactions. Many existing approaches which profile is SQL query structures and database user activities to detect intrusion, the log mining approach is the automatic discovery for identifying anomalous database transactions. Mining of the Data is very helpful to end users for extracting useful business information from large database. Multi-level and multi-dimensional data mining are employed to discover data item dependency rules, data sequence rules, domain dependency rules, and domain sequence rules from the database log containing legitimate transactions. Database transactions that do not comply with the rules are identified as malicious transactions. The log mining approach can achieve desired true and false positive rates when the confidence and support are set up appropriately. The implemented system incrementally maintain the data dependency rule sets and optimize the performance of the intrusion detection process.
The effects of regular aerobic exercise in adolescent period on hippocampal neuron density, apoptosis and spatial memory

It is known that positive effects of regular aerobic exercise on cognitive functions in humans and also animals; but how to the effects of aerobic exercise in adolescent period is unknown. The present study examined the effects of regular aerobic exercise on spatial memory using the Morris water maze, cell density and apoptosis of hippocampus in adolescent rats. Twenty-two days of age male rats were run on a treadmill for 30 min/session at a speed of 8m/min and 0 degrees slope, five times a week for 8 weeks. The present study showed that exercise induced significant cognitive improvement throughout brain maturation in rats. The number of hippocampal CA1 and CA3 neurons, and gyrus dentatus neurons were significantly increased in the exercised rats. There was no significant difference of CA2 neuron density between exercise and control groups. There was no significantly differences in any groups according to the results of apoptosis that account of TUNEL positive cells. The present results suggest that regular moderate aerobic treadmill exercise benefit in cognitive functions. This result may derive from treadmill exercise-induced increase cell density without altering of apoptosis in the hippocampus and dentate gyrus of adolescent rats.
Object Similarity in Ontologies: A Foundation for Business Intelligence Systems and High-Performance Retrieval

The quantity and complexity of available information is rapidly increasing. This potential information overload challenges the standard information retrieval models, as users find it increasingly difficult to find relevant information. We therefore propose a method that can utilize the potentially valuable knowledge contained in concept models such as ontologies, and thereby assist users in querying, using the terminology of the domain. The primary focus of this dissertation is similarity measures for use in ontology-based information retrieval. We aim at incorporating the information contained in ontologies by choosing a representation formalism where queries and objects in the information base are described using a lattice-algebraic concept language containing expressions that can be directly mapped into the ontology. Similarity between the description of the query and descriptions of the objects is calculated based on a nearness principle derived from the structure and relations of the ontology. This measure is then used to perform ontology-based query expansion. By doing so, we can replace semantic matching from direct reasoning over the ontology with numerical similarity calculation by means of a general aggregation principle The choice of the proposed similarity measure is guided by a set of properties aimed at ensuring the measures accordance with a set of distinctive structural qualities derived from the ontology. We furthermore empirically evaluate the proposed similarity measure by comparing the similarity ratings for pairs of concepts produced by the proposed measure, with the mean similarity ratings produced by humans for the same pairs.
Efficacy of a tetravalent dengue vaccine in children in Latin America.

In light of the increasing rate of dengue infections throughout the world despite vector-control measures, several dengue vaccine candidates are in development.



In a phase 3 efficacy trial of a tetravalent dengue vaccine in five Latin American countries where dengue is endemic, we randomly assigned healthy children between the ages of 9 and 16 years in a 2:1 ratio to receive three injections of recombinant, live, attenuated, tetravalent dengue vaccine (CYD-TDV) or placebo at months 0, 6, and 12 under blinded conditions. The children were then followed for 25 months. The primary outcome was vaccine efficacy against symptomatic, virologically confirmed dengue (VCD), regardless of disease severity or serotype, occurring more than 28 days after the third injection.



A total of 20,869 healthy children received either vaccine or placebo. At baseline, 79.4% of an immunogenicity subgroup of 1944 children had seropositive status for one or more dengue serotypes. In the per-protocol population, there were 176 VCD cases (with 11,793 person-years at risk) in the vaccine group and 221 VCD cases (with 5809 person-years at risk) in the control group, for a vaccine efficacy of 60.8% (95% confidence interval [CI], 52.0 to 68.0). In the intention-to-treat population (those who received at least one injection), vaccine efficacy was 64.7% (95% CI, 58.7 to 69.8). Serotype-specific vaccine efficacy was 50.3% for serotype 1, 42.3% for serotype 2, 74.0% for serotype 3, and 77.7% for serotype 4. Among the severe VCD cases, 1 of 12 was in the vaccine group, for an intention-to-treat vaccine efficacy of 95.5%. Vaccine efficacy against hospitalization for dengue was 80.3%. The safety profile for the CYD-TDV vaccine was similar to that for placebo, with no marked difference in rates of adverse events.



The CYD-TDV dengue vaccine was efficacious against VCD and severe VCD and led to fewer hospitalizations for VCD in five Latin American countries where dengue is endemic.
Towards a better understanding of Burrows's Delta in literary authorship attribution

Burrows’s Delta is the most established measure for stylometric difference in literary authorship attribution. Several improvements on the original Delta have been proposed. However, a recent empirical study showed that none of the proposed variants constitute a major improvement in terms of authorship attribution performance. With this paper, we try to improve our understanding of how and why these text distance measures work for authorship attribution. We evaluate the effects of standardization and vector normalization on the statistical distributions of features and the resulting text clustering quality. Furthermore, we explore supervised selection of discriminant words as a procedure for further improving authorship attribution.
Emerging support for a role of exercise in attention-deficit/hyperactivity disorder intervention planning.

Recent years have seen an expansion of interest in non-pharmacological interventions for attention-deficit/hyperactivity disorder (ADHD). Although considerable treatment development has focused on cognitive training programs, compelling evidence indicates that intense aerobic exercise enhances brain structure and function, and as such, might be beneficial to children with ADHD. This paper reviews evidence for a direct impact of exercise on neural functioning and preliminary evidence that exercise may have positive effects on children with ADHD. At present, data are promising and support the need for further study, but are insufficient to recommend widespread use of such interventions for children with ADHD.
Z-Channel: Scalable and Efficient Scheme in Zerocash

Decentralized ledger-based cryptocurrencies like Bitcoin present a way to construct payment systems without trusted banks. However, the anonymity of Bitcoin is fragile. Many altcoins and protocols are designed to improve Bitcoin on this issue, among which Zerocash is the first fullfledged anonymous ledger-based currency, using zero-knowledge proof, specifically zk-SNARK, to protect privacy. However, Zerocash suffers two problems: poor scalability and low efficiency. In this paper, we address the above issues by constructing a micropayment system in Zerocash called Z-Channel. First, we improve Zerocash to support multisignature and time lock functionalities, and prove that the reconstructed scheme is secure. Then we construct Z-Channel based on the improved Zerocash scheme. Our experiments demonstrate that Z-Channel significantly improves the scalability and reduces the confirmation time for Zerocash payments.
High Power Microstrip GaN-HEMT Switches for Microwave Applications

In this paper the design, fabrication and test of X-band and 2-18 GHz wideband high power SPDT MMIC switches in microstrip GaN technology are presented. Such switches have demonstrated state-of-the-art performances. In particular the X-band switch exhibits 1 dB insertion loss, better than 37 dB isolation and a power handling capability at 9 GHz of better than 39 dBm at 1 dB insertion loss compression point; the wideband switch has an insertion loss lower than 2.2 dB, better than 25 dB isolation and a power handling capability of better than 38 dBm in the entire bandwidth.
Source code retrieval on StackOverflow using LDA

Internet code search is quite popular research area. StackOverflow allows developers to ask and answer questions about code. Previous approach to search code on StackOverflow uses tf-idf method that based on number of occurrences of words to recommend source code. This method has the disadvantage that variable or method identifiers are considered as normal words, even though identifiers are often a combination of two or more words. For example, there is an identifier named “randomString”. In that case, if we search using a keyword “random” the system probably will not recommend “randomString” because both words are different. Concept location can tackle this problem. Concept location has been used widely to obtain the correlation between code with a specific concepts or features. Previous research of concept location only focused on source code's comments, and relation among the objects within the source code. This research proposes a mechanism for finding code on StackOverflow uses Latent Dirichlet Allocation (LDA) using concept location in the preprocessing stage. Questions, answers, and code snippets about Java programming are downloaded from StackOverflow to a local repository. Corpuses are generated by extracting questions, answers and code snippets. Inferencing concept location from source code is created using LDA algorithm. Developers query concepts and then system will recommend source code based on the relevant concepts. The result of the experiment shows that the system is able to recommend source code with 48% average of precision and 58% average of recall.
Dominance and Age in Bilingualism

The present article examines the relationship between age and dominance in bilingual populations. Age in bilingualism is understood as the point in devel10 opment at which second language (L2) acquisition begins and as the chronological age of users of two languages. Age of acquisition (AoA) is a factor in determining which of a bilingual’s two languages is dominant and to what degree, and it, along with age of first language (L1) attrition, may be associated with shifts in dominance from the L1 to the L2. In turn, dominance and chron15 ological age, independently and in interaction with lexical frequency, predict performance on naming tasks. The article also considers the relevance of criticalperiod accounts of the relationships of AoA and age of L1 attrition to L2 dominance, and of usage-based and cognitive-aging accounts of the roles of age and dominance in naming.
Anisotropic Ordering in 1T' Molybdenum and Tungsten Ditelluride Layers Alloyed with Sulfur and Selenium.

Alloying is an effective way to engineer the band-gap structure of two-dimensional transition-metal dichalcogenide materials. Molybdenum and tungsten ditelluride alloyed with sulfur or selenium layers (MX2xTe2(1-x), M = Mo, W and X = S, Se) have a large band-gap tunability from metallic to semiconducting due to the 2H-to-1T' phase transition as controlled by the alloy concentrations, whereas the alloy atom distribution in these two phases remains elusive. Here, combining atomic resolution Z-contrast scanning transmission electron microscopy imaging and density functional theory (DFT), we discovered that anisotropic ordering occurs in the 1T' phase, in sharp contrast to the isotropic alloy behavior in the 2H phase under similar alloy concentration. The anisotropic ordering is presumably due to the anisotropic bonding in the 1T' phase, as further elaborated by DFT calculations. Our results reveal the atomic anisotropic alloyed behavior in 1T' phase layered alloys regardless of their alloy concentration, shining light on fine-tuning their physical properties via engineering the alloyed atomic structure.
An automated method of segmentation for tumor detection by neutrosophic sets and morphological operations using MR images

Brain tumor is the most life undermining sickness and its recognition is the most challenging task for radio logistics by manual detection due to varieties in size, shape and location and sort of tumor. So, detection ought to be quick and precise and can be obtained by automated segmentation methods on MR images. In this paper, neutrosophic sets based segmentation is performed to detect the tumor. MRI is an intense apparatus over CT to analyze the interior segments of the body and the tumor. Tumor is detected and true, false and indeterminacy values of tumor are determined by this technique and the proposed method produce the beholden results.
Formalization and Algebraic Verification of Legal Requirements

This paper outlines the technology of the formalization and verification of legal text documents. A formal model of a legal document is presented as an ordered set of rules. Every rule is presented as a triple containing preand post-conditions, as well as process parts. All rules are ordered in Use Case Maps (UCM) diagrams. Such a formal model can be verified for inconsistency and incompleteness, which are the causes of gaps and ambiguities in legal requirements. Verification is implemented by means of algebraic computation and symbolic modelling. The formalization of legal requirements is performed with the use of an intermediate language. An example of the procedure of registration from the Tax Code of Ukraine is given for the illustration of the algebraic method implemented in the Insertion Modeling System (IMS).
Patient-reported outcomes in cancer care — hearing the patient voice at greater volume

Recording of patient-reported outcomes (PROs) enables direct measurement of the experiences of patients with cancer. In the past decade, the use of PROs has become a prominent topic in health-care innovation; this trend highlights the role of the patient experience as a key measure of health-care quality. Historically, PROs were used solely in the context of research studies, but a growing body of literature supports the feasibility of electronic collection of PROs, yielding reliable data that are sometimes of better quality than clinician-reported data. The incorporation of electronic PRO (ePRO) assessments into standard health-care settings seems to improve the quality of care delivered to patients with cancer. Such efforts, however, have not been widely adopted, owing to the difficulties of integrating PRO-data collection into clinical workflows and electronic medical-record systems. The collection of ePRO data is expected to enhance the quality of care received by patients with cancer; however, for this approach to become routine practice, uniquely trained people, and appropriate policies and analytical solutions need to be implemented. In this Review, we discuss considerations regarding measurements of PROs, implementation challenges, as well as evidence of outcome improvements associated with the use of PROs, focusing on the centrality of PROs as part of 'big-data' initiatives in learning health-care systems.
EPID dosimetry for pretreatment quality assurance with two commercial systems

This study compares the EPID dosimetry algorithms of two commercial systems for pretreatment QA, and analyzes dosimetric measurements made with each system alongside the results obtained with a standard diode array. 126 IMRT fields are examined with both EPID dosimetry systems (EPIDose by Sun Nuclear Corporation, Melbourne FL, and Portal Dosimetry by Varian Medical Systems, Palo Alto CA) and the diode array, MapCHECK (also by Sun Nuclear Corporation). Twenty-six VMAT arcs of varying modulation complexity are examined with the EPIDose and MapCHECK systems. Optimization and commissioning testing of the EPIDose physics model is detailed. Each EPID IMRT QA system is tested for sensitivity to critical TPS beam model errors. Absolute dose gamma evaluation (3%, 3 mm, 10% threshold, global normalization to the maximum measured dose) yields similar results (within 1%-2%) for all three dosimetry modalities, except in the case of off-axis breast tangents. For these off-axis fields, the Portal Dosimetry system does not adequately model EPID response, though a previously-published correction algorithm improves performance. Both MapCHECK and EPIDose are found to yield good results for VMAT QA, though limitations are discussed. Both the Portal Dosimetry and EPIDose algorithms, though distinctly different, yield similar results for the majority of clinical IMRT cases, in close agreement with a standard diode array. Portal dose image prediction may overlook errors in beam modeling beyond the calculation of the actual fluence, while MapCHECK and EPIDose include verification of the dose calculation algorithm, albeit in simplified phantom conditions (and with limited data density in the case of the MapCHECK detector). Unlike the commercial Portal Dosimetry package, the EPIDose algorithm (when sufficiently optimized) allows accurate analysis of EPID response for off-axis, asymmetric fields, and for orthogonal VMAT QA. Other forms of QA are necessary to supplement the limitations of the Portal Vision Dosimetry system.
A Survey of Privacy-Preserving Methods Across Vertically Partitioned Data

The goal of data mining is to extract or “mine” knowledge from large amounts of data. However, data is often collected by several different sites. Privacy, legal and commercial concerns restrict centralized access to this data, thus derailing data mining projects. Recently, there has been growing focus on finding solutions to this problem. Several algorithms have been proposed that do distributed knowledge discovery, while providing guarantees on the non-disclosure of data. Vertical partitioning of data is an important data distribution model often found in real life. Vertical partitioning or heterogeneous distribution implies that different features of the same set of data are collected by different sites. In this chapter we survey some of the methods developed in the literature to mine vertically partitioned data without violating privacy and discuss challenges and complexities specific to vertical partitioning.