nils-herrmann/clean_scirepeval huggingface dataset:
The three Es of cancer immunoediting.

After a century of controversy, the notion that the immune system regulates cancer development is experiencing a new resurgence. An overwhelming amount of data from animal models--together with compelling data from human patients--indicate that a functional cancer immunosurveillance process indeed exists that acts as an extrinsic tumor suppressor. However, it has also become clear that the immune system can facilitate tumor progression, at least in part, by sculpting the immunogenic phenotype of tumors as they develop. The recognition that immunity plays a dual role in the complex interactions between tumors and the host prompted a refinement of the cancer immunosurveillance hypothesis into one termed "cancer immunoediting." In this review, we summarize the history of the cancer immunosurveillance controversy and discuss its resolution and evolution into the three Es of cancer immunoediting--elimination, equilibrium, and escape.
TransmiR: a transcription factor–microRNA regulation database

MicroRNAs (miRNAs) regulate gene expression at the posttranscriptional level and are therefore important cellular components. As is true for protein-coding genes, the transcription of miRNAs is regulated by transcription factors (TFs), an important class of gene regulators that act at the transcriptional level. The correct regulation of miRNAs by TFs is critical, and increasing evidence indicates that aberrant regulation of miRNAs by TFs can cause phenotypic variations and diseases. Therefore, a TF-miRNA regulation database would be helpful for understanding the mechanisms by which TFs regulate miRNAs and understanding their contribution to diseases. In this study, we manually surveyed approximately 5000 reports in the literature and identified 243 TF-miRNA regulatory relationships, which were supported experimentally from 86 publications. We used these data to build a TF-miRNA regulatory database (TransmiR, http://cmbi.bjmu.edu.cn/transmir), which contains 82 TFs and 100 miRNAs with 243 regulatory pairs between TFs and miRNAs. In addition, we included references to the published literature (PubMed ID) information about the organism in which the relationship was found, whether the TFs and miRNAs are involved with tumors, miRNA function annotation and miRNA-associated disease annotation. TransmiR provides a user-friendly interface by which interested parties can easily retrieve TF-miRNA regulatory pairs by searching for either a miRNA or a TF.
Survey of Text Classification Technique and Compare Classifier

Huge amount data on the internet are in unstructured texts can‟t simply be used for further processing by computer , therefore specific processing method and algorithm require to extract useful pattern. Text mining is process to extract information from the unstructured data. Text classification is task of automatically sorting set of document into categories from predefined set. A major difficulty of text classification is high dimensionality of feature space. Feature selection method used for dimension reduction. This paper describe about text classification process, compare various classifier and also discuss feature selection method for solving problem of high dimensional data and application of text classification.
Design of ZnO microvaristor end corona protection for electrical machines

For the stator winding of electrical machines, end corona protection arrangements including semi-conductive microvaristor lacquers are analyzed using finite element method (FEM) simulations. Those materials feature nonlinear resistive properties depending on the local electric field. Hence, electroquasistatic FEM simulations considering capacitive and nonlinear resistive material behavior are performed. End corona protection arrangements using semi-conductive materials are compared. The resulting voltage distributions, tangential electric fields and ohmic losses are presented.
On the Design of Pulsed Sources and Spread Compensation in Finite-Difference Time-Domain Electromagnetic Simulations

This paper first describes the phenomenon of Gaussian pulse spread due to numerical dispersion in the finite-difference time-domain (FDTD) method for electromagnetic computation. This effect is undesired, as it reduces the precision with which multipath pulses can be resolved in the time domain. The quantification of the pulse spread is thus useful to evaluate the accuracy of pulsed FDTD simulations. Then, using a linear approximation to the numerical phase delay, a formula to predict the pulse duration is developed. Later, this formula is used to design a Gaussian source that keeps the spread of numerical pulses bounded in wideband FDTD. Finally, the developed model and the approximation are validated via simulations.
2015 Korean Guidelines for the Management of Dyslipidemia: Executive Summary (English Translation)

February 11, 2016 / Revision Received: April 6, 2016 / Accepted: April 12, 2016 Correspondence: Chee Jeong Kim, MD, Division of Cardiology, Department of Internal Medicine, Chung-Ang University College of Medicine, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Korea / Tel: 82-2-6299-1398 / Fax: 82-2-822-2769 / E-mail: cjkim@cau.ac.kr * This guideline is translated from “J Lipid Atheroscler 2015;4(1):61-92”.  Full list of Committee information is available at the end of this article. • The authors have no financial conflicts of interest.
Twitter data analysis for studying communities of practice in the media industry

Today, more and more physical communities of practice, a concept that describes a group of people that share a passion and interact regularly at events to exchange knowledge, utilize social media, such as Twitter. Brotaru, for instance, is such a physical community of practice for media professionals in Brussels. It is a monthly meet-up of videogame developers in various locations in Brussels. Furthermore, Twitter becomes widely acknowledged as important instrument for learning and community formation in the virtual world. But, do these communities of practice use Twitter only to promote their physical activities of learning? Or, are the activities of the physical communities further extended into the virtual world meaning that virtual communities of practice emerge from them? This article suggests a novel mixed-methods approach based on qualitative and quantitative data to measure the role of Twitter for physical communities of practice. The method applies different statistical measures and analysis on harvested Twitter data and additionally brings two of the most used methods in Twitter analysis together, social network analysis and text data analysis (a.k.a., content analysis). Four different communities of practice in Brussels’ media industry and their activities and followers on Twitter have been analysed. The findings showed that the activities of the communities of practice extend into the Twitter sphere as the online communities are characterised by (1) a shared domain, (2) a lively community and (3) shared practices. The analysis further revealed that Twitter offers three main opportunities for the activities of communities of practice: it offers geographical extension; it gives temporal autonomy; and, it can be used to diversify the practices.
Ranking with Deep Neural Networks

The task of ranking is crucial in information retrieval. With the advent of the Big Data age, new challenges have arisen for the field. Deep neural architectures are capable of learning complex functions, and capture the underlying representation of the data more effectively. In this work, ranking is reduced to a classification problem and deep neural architectures are used for this task. A dynamic, pointwise approach is used to learn a ranking function, which outperforms the existing ranking algorithms. We introduce three architectures for the task, our primary objective being to identify architectures which produce good results, and to provide intuitions behind their usefulness. The inputs to the models are hand-crafted features provided in the datasets. The outputs are relevance levels. Further, we also explore the idea as to whether the semantic grouping of handcrafted features aids deep learning models in our task.
A syntactic language model based on incremental CCG parsing

Syntactically-enriched language models (parsers) constitute a promising component in applications such as machine translation and speech-recognition. To maintain a useful level of accuracy, existing parsers are non-incremental and must span a combinatorially growing space of possible structures as every input word is processed. This prohibits their incorporation into standard linear-time decoders. In this paper, we present an incremental, linear-time dependency parser based on Combinatory Categorial Grammar (CCG) and classification techniques. We devise a deterministic transform of CCG-bank canonical derivations into incremental ones, and train our parser on this data. We discover that a cascaded, incremental version provides an appealing balance between efficiency and accuracy.
Multiple assignment scheme for sharing secret

In a secret sharing scheme, a datumd is broken into shadows which are shared by a set of trustees. The family {P′⊆P:P′ can reconstructd} is called the access structure of the scheme. A (k, n)-threshold scheme is a secret sharing scheme having the access structure {P′⊆P: |P′|≥k}. In this paper, by observing a simple set-theoretic property of an access structure, we propose its mathematical definition. Then we verify the definition by proving that every family satisfying the definition is realized by assigning two more shadows of a threshold scheme to trustees.
Light Field Occlusion Removal

We present a novel method for detecting occlusions and in-painting unknown areas of a light field photograph, based on previous work in obstruction-free photography and light field completion. An initial guess at separating the occluder from the rest of the photograph is computed by aligning backgrounds of the images and using this information to generate an occlusion mask. The masked pixels are then synthesized using a patch-based texture synthesis algorithm, with the median image as the source of each patch.
The group of epidermal nevus syndromes Part I. Well defined phenotypes.

The epidermal nevus syndromes represent a group of distinct disorders that can be distinguished by the type of associated epidermal nevus and by the criterion of presence or absence of heritability. Well defined syndromes characterized by organoid epidermal nevi include Schimmelpenning syndrome, phacomatosis pigmentokeratotica, nevus comedonicus syndrome, angora hair nevus syndrome, and Becker nevus syndrome. The molecular basis of these disorders has so far not been identified. By contrast, the group of syndromes characterized by keratinocytic nevi comprises three phenotypes with a known molecular etiology in the form of CHILD (congenital hemidysplasia with ichthyosiform nevus and limb defects) syndrome, type 2 segmental Cowden disease, and fibroblast growth factor receptor 3 epidermal nevus syndrome (García-Hafner-Happle syndrome), whereas Proteus syndrome is still of unknown origin. From this overview, it is clear that a specific type of these disorders cannot be classified by the name "epidermal nevus syndrome" nor by the terms "organoid nevus syndrome" or "keratinocytic nevus syndrome."



After completing this learning activity, participants should be able to distinguish nine different epidermal nevus syndromes by their characteristic features, understand the practical significance of avoiding terms like "epidermal nevus syndrome" or "keratinocytic nevus syndrome" to define any specific entity within this group of disorders, and differentiate between nonhereditary traits and those bearing a genetic risk because of either Mendelian or non-Mendelian inheritance.
Extending Patchmatch Stereo to Multiple-View Case by Using Neighboring Images

Multiple-view stereo reconstruction is a key step in image-based 3D acquisition and patchmatch based method is suited for large scale scene reconstruction. In this paper we extend the two-view patchmatch stereo to multiple-view in the multiple-view stereo pipeline. The key of the proposed method is to select multiple suitable neighboring images for a reference image, compute the depth-maps and merge the depth-maps. Experimental results on benchmark data sets demonstrate the accuracy and efficiency of the proposed method.
Aligning Product Categories using Anchor Products

E-commerce sites group similar products into categories, and these categories are further organized in a taxonomy. Since different sites have different products and cater to a variety of shoppers, the taxonomies differ both in the categorization of products and the textual representation used for these categories. In this paper, we propose a technique to align categories across sites, which is useful information to have in product graphs. We use breadcrumbs present on the product pages to infer a site’s taxonomy. We generate a list of candidate category pairs for alignment using anchor products products present in two or more sites. We use multiple similarity and distance metrics to compare these candidates. To generate the final set of alignments, we propose a model that combines these metrics with a set of structural constraints. The model is based on probabilistic soft logic (PSL), a scalable probabilistic programming framework. We run experiments on data extracted from Amazon, Ebay, Staples and Target, and show that the distance metric based on products, and the use of PSL to combine various metrics and structural constraints lead to improved alignments.
Blockchain Based DNS and PKI Solutions

Domain name systems and certificate authority systems may have security and trust problems in their implementation. This article summarizes how these systems work and what the implementation problems may be. There are blockchain-based decentralized solutions that claim to overcome those problems. We provide a brief explanation on how blockchain systems work, and their strengths are explained. DNS security challenges are given. Blockchain-based DNS solutions are classified and described in detail according to their services. The advantages and feasibility of these implementations are discussed. Last but not least, the possibility of the decentralized Internet is questioned.
Adapting RFID Technology for Implementation of a New Birth Record in Jordanian Hospitals

This paper introduces a new integrated clinical record in Jordan using the RFID technology, where currently no clinical report links antenatal, birth and postnatal care for women. As a result no continuity of information is provided to clinicians nor are there national statistics on trends, or performance of hospitals around birth. The paper is based on a study conducted in the Jordanian Ministry of Health, the maternity wards and registration departments of three hospitals in Jordan and in the Maternal Child Health Centers located near these hospitals . Lack of active follow-up to ensure the best service for antenatal, birth and postnatal care for women is the main problem. An RFID model for managing the clinical record for maternal child was proposed. The model is valuable to policy makers and program implementers in strengthening implementation of programs and activities to improve maternal child care services. The statistics yielded from the proposed RFID model is of particular importance to help fulfill this need. The proposed maternal child management system is expected to control the health care cost, improve the care quality, and provide a comprehensive strategy for restructuring maternal child care delivery system.
The effects of recommendations’ presentation on persuasion and satisfaction in a movie recommender system

The explosive growth of Internet applications and content, during the last decade, has revealed an increasing need for information filtering and recommendation. Most research in the area of recommendation systems has focused on designing and implementing efficient algorithms that provide accurate recommendations. However, the selection of appropriate recommendation content and the presentation of information are equally important in creating successful recommender applications. This paper addresses issues related to the presentation of recommendations in the movies domain. The current work reviews previous research approaches and popular recommender systems, and focuses on user persuasion and satisfaction. In our experiments, we compare different presentation methods in terms of recommendations’ organization in a list (i.e. top N-items list and structured overview) and recommendation modality (i.e. simple text, combination of text and image, and combination of text and video). The most efficient presentation methods, regarding user persuasion and satisfaction, proved to be the “structured overview” and the “text and video” interfaces, while a strong positive correlation was also found between user satisfaction and persuasion in all experimental conditions.
A 14-b 12-MS/s CMOS pipeline ADC with over 100-dB SFDR

A 1.8-V 14-b 12-MS/s pseudo-differential pipeline analog-to-digital converter (ADC) using a passive capacitor error-averaging technique and a nested CMOS gain-boosting technique is described. The converter is optimized for low-voltage low-power applications by applying an optimum stage-scaling algorithm at the architectural level and an opamp and comparator sharing technique at the circuit level. Prototyped in a 0.18-/spl mu/m 6M-1P CMOS process, this converter achieves a peak signal-to-noise plus distortion ratio (SNDR) of 75.5 dB and a 103-dB spurious-free dynamic range (SFDR) without trimming, calibration, or dithering. With a 1-MHz analog input, the maximum differential nonlinearity is 0.47 LSB and the maximum integral nonlinearity is 0.54 LSB. The large analog bandwidth of the front-end sample-and-hold circuit is achieved using bootstrapped thin-oxide transistors as switches, resulting in an SFDR of 97 dB when a 40-MHz full-scale input is digitized. The ADC occupies an active area of 10 mm/sup 2/ and dissipates 98 mW.
An interference-aware 5.8GHz wake-up radio for ETCS

Wake-up radios have been a popular transceiver architecture in recent years for battery-powered applications such as wireless body area networks (WBANs) , wireless sensor networks (WSNs) , and even electronic toll collection systems (ETCS) . The most important consideration in implementing a wake-up receiver (WuRX) is low power dissipation while maximizing sensitivity. Because of this requirement of very low power, WuRX are usually designed by a simple RF envelope detector (RFED) consisting of Schottky diodes [1,3] or MOSFETs in the weak inversion region  without active filtering or amplification of the input signal. Therefore, the performance of the RFED itself is critical for attaining good sensitivity of the WuRX. Moreover, the poor filtering of the input signal renders the WuRX vulnerable to interferers from nearby terminals with high transmit power such as mobile phones and WiFi devices, and this can result in false wake-ups . Although the RFED has very low power, a false wake-up will increase the power consumption of the wake-up radio as it will enable the power-hungry main transceiver.
Mental disorders stigma in the media: review of studies on production, content, and influences.

This article analyzes two decades of research regarding the mass media's role in shaping, perpetuating, and reducing the stigma of mental illness. It concentrates on three broad areas common in media inquiry: production, representation, and audiences. The analysis reveals that descriptions of mental illness and the mentally ill are distorted due to inaccuracies, exaggerations, or misinformation. The ill are presented not only as peculiar and different, but also as dangerous. Thus, the media perpetuate misconceptions and stigma. Especially prominent is the absence of agreed-upon definitions of "mental illness," as well as the lack of research on the inter-relationships in audience studies between portrayals in the media and social perceptions. The analysis concludes with suggestions for further research on mass media's inter-relationships with mental illness.
Tree Stem Diameter Estimation from Mobile Laser Scanning Using Line-Wise Intensity-Based Clustering

Diameter at breast height has been estimated from mobile laser scanning using a new set of methods. A 2D laser scanner was mounted facing forward, tilted nine degrees downwards, on a car. The trajectory was recorded using inertial navigation and visual SLAM (simultaneous localization and mapping). The laser scanner data, the trajectory and the orientation were used to calculate a 3D point cloud. Clusters representing trees were extracted line-wise to reduce the effects of uncertainty in the positioning system. The intensity of the laser echoes was used to filter out unreliable echoes only grazing a stem. The movement was used to obtain measurements from a larger part of the stem, and multiple lines from different views were used for the circle fit. Two trigonometric methods and two circle fit methods were tested. The best results with bias 2.3% (6 mm) and root mean squared error 14% (37 mm) were acquired with the circle fit on multiple 2D projected clusters. The method was evaluated compared to field data at five test areas with approximately 300 caliper-measured trees within a 10-m working range. The results show that this method is viable for stem measurements from a moving vehicle, for example a forest harvester.
Crime , Deterrence , and Right-to-Carry Concealed

Using cross-sectional time-series data for U.S. counties from 1977 to 1992, we find that allowing citizens to carry concealed weapons deters violent crimes and it appears to produce no increase in accidental deaths. If those states which did not have right-to-carry concealed gun provisions had adopted them in 1992, approximately 1,570 murders; 4,177 rapes; and over 60,000 aggravate assaults would have been avoided yearly. On the other hand, consistent with the notion of criminals responding to incentives, we find criminals substituting into property crimes involving stealth and where the probabilities of contact between the criminal and the victim are minimal. The largest population counties where the deterrence effect on violent crimes is greatest are where the substitution effect into property crimes is highest. Concealed handguns also have their greatest deterrent effect in the highest crime counties. Higher arrest and conviction rates consistently and dramatically reduce the crime rate. Consistent with other recent work (Lott, 1992b), the results imply that increasing the arrest rate, independent of the probability of eventual conviction, imposes a significant penalty on criminals. The estimated annual gain from allowing concealed handguns is at least $6.214 billion.
Phase Mapper: Accelerating Materials Discovery with AI

uted to the discovery and characterization of new materials. The discovery of semiconductors laid the foundation for modern electronics, while the formulation of new molecules allows us to treat diseases previously thought incurable. Looking into the future, some of the largest problems facing humanity now are likely to be solved by the discovery of new materials. In this article, we explore the techniques materials scientists are using and show how our novel artificial intelligence system, Phase-Mapper, allows materials scientists to quickly solve material systems to infer their underlying crystal structures and has led to the discovery of new solar light absorbers.