nils-herrmann/clean_scirepeval huggingface dataset:
LexToPlus: A Thai Lexeme Tokenization and Normalization Tool

The increasing popularity of social media has a large impact on the evolution of language usage. The evolution includes the transformation of some existing terms to enhance the expression of the writer’s emotion and feeling. Text processing tasks on social media texts have become much more challenging. In this paper, we propose LexToPlus, a Thai lexeme tokenizer with term normalization process. LexToPlus is designed to handle the intentional errors caused by the repeated characters at the end of words. LexToPlus is a dictionary-based parser which detects existing terms in a dictionary. Unknown tokens with repeated characters are merged and removed. We performed statistical analysis and evaluated the performance of the proposed approach by using a Twitter corpus. The experimental results show that the proposed algorithm yields an accuracy of 96.3% on a test data set. The errors are mostly caused by the out-ofvocabulary problem which can be solved by adding newly found terms into the dictionary.
Montmorillonite : An efficient , heterogeneous and green catalyst for organic synthesis

Reactions of organic molecules on Montmorillonite c lay mineral have been investigated from various asp ects. These include catalytic reactions for organic synthesis, chemical evolution, the mechanism of humus-formatio n, and environmental problems. Catalysis by clay minerals has attracted much interest recently, and many repo rts including the catalysis by synthetic or modified cl ays have been published. In this review, we will li mit the review to organic reactions using Montmorillonite clay as cat alyst.
Human-Computer Interaction

Offering training programs to their employees is one of the necessary tasks that managers must comply with. Training is done mainly to provide upto-date knowledge or to convey to staff the objectives, history, corporate name, functions of the organization’s areas, processes, laws, norms or policies that must be fulfilled. Although there are a lot of methods, models or tools that are useful for this purpose, many companies face with some common problems like employee’s motivation and high costs in terms of money and time. In an effort to solve this problem, new trends have emerged in the last few years, in particular strategies related to games, such as serious games and gamification, whose success has been demonstrated by numerous researchers. According to the above, we present a systematic literature review of the different approaches that have used games or their elements, using the procedure suggested by Cooper, on this matter, ending with about the positive and negative findings.
Biologics in juvenile idiopathic arthritis: a narrative review

In the past years, pediatric rheumatology has seen a revolution in the treatments for rheumatic diseases, particularly juvenile idiopathic arthritis. Even if nonsteroidal anti-inflammatory drugs (NSAID), intra-articular corticosteroids (IAC) injections, and methotrexate remain the mainstay of the treatment for JIA patients, in aggressive disease, these treatments may be not sufficient to reach disease remission and to prevent long-term disability. Comprehension of immunological mechanisms involved in the pathogenesis of the diseases allowed to conceive new drugs targeting specific steps of the immune response. Several cytokines, like TNF alpha and IL-1, represent a very interesting target for biologic therapies. Due to the efficacy of these therapies, nowadays, “disease remission” in pediatric rheumatology is more and more frequent, especially in juvenile idiopathic arthritis patients, and the long-term outcomes have been significantly improved. Crucial to these advancements have been multicenter controlled clinical trials and long-term safety monitoring.  Research in pediatric rheumatology has resulted in dramatic advances in diseases management. Biologic treatments have improved physical and functional outcomes and quality of life of patients with rheumatic disease.  • NSAID, intra-articular injection of corticoids, and methotrexate are the mainstay in treatment of JIA. • In aggressive JIA, these treatments may be not sufficient to reach disease remission and to prevent long term disability.  • In recent years, management of JIA has significantly improved with the development of biologic therapies that allowed children with arthritis to reach a normal growth and to achieve a good long-term functional outcome.
Full-duplex wireless based on a small-form-factor analog self-interference canceller: demo

A demonstration of a real-time full-duplex wireless link is presented, in which a pair of full-duplex transceivers perform simultaneous transmission and reception on the same frequency channel. A full-duplex transceiver is composed of a custom-designed small-form-factor analog self-interference canceller, and a digital self-interference cancellation implementation is integrated with the National Instruments Universal Software Radio Peripheral (USRP). An adaptive analog self-interference canceller tuning mechanism adjusts to environmental changes. We demonstrate the practicality and robustness of the full-duplex wireless link through the National Instruments LabVIEW interface.
Neural Responses to Ingroup and Outgroup Members' Suffering Predict Individual Differences in Costly Helping

Little is known about the neurobiological mechanisms underlying prosocial decisions and how they are modulated by social factors such as perceived group membership. The present study investigates the neural processes preceding the willingness to engage in costly helping toward ingroup and outgroup members. Soccer fans witnessed a fan of their favorite team (ingroup member) or of a rival team (outgroup member) experience pain. They were subsequently able to choose to help the other by enduring physical pain themselves to reduce the other's pain. Helping the ingroup member was best predicted by anterior insula activation when seeing him suffer and by associated self-reports of empathic concern. In contrast, not helping the outgroup member was best predicted by nucleus accumbens activation and the degree of negative evaluation of the other. We conclude that empathy-related insula activation can motivate costly helping, whereas an antagonistic signal in nucleus accumbens reduces the propensity to help.
Deep Survey on Sentiment Analysis and Opinion Mining on Social Networking Sites and E-Commerce Website

Due to Evolution of internet and social media, every internet user expresses his opinion and views on the web. These views are both regarding day-to-day transaction and international issues as well. W ith the rapid growth of web technology internet has become the place for online learning and exchange ideas also. With this informat ion other users make up their mind about a particular service, product or organization. This gives birth to a huge opinion data available online in the form of on -line rev iew site, twitter, face book and personal blogs etc. This paper focuses on review of Opinion mining and sentiment analysis as it is the process of examining the text (opin ion or review) about a topic written in a natural language and classify them as positive, negative or neutral based on the humans sentiments involved in it. In this paper we have reviewed papers of last ten years to bring the research done in the field of sentiment analysis at a common platfo rm. It includes sentiment analysis tools, levels of sentiment analysis, its challenges a nd issues thus it will be very useful for the new researchers to have all information at a g lance.
Factors influencing the immunogenicity of therapeutic proteins.

Several diseases and disorders are treatable with therapeutic proteins, but some of these products may induce an immune response, especially when administered as multiple doses over prolonged periods. Antibodies are created by classical immune reactions or by the breakdown of immune tolerance; the latter is characteristic of human homologue products. Many factors influence the immunogenicity of proteins, including structural features (sequence variation and glycosylation), storage conditions (denaturation, or aggregation caused by oxidation), contaminants or impurities in the preparation, dose and length of treatment, as well as the route of administration, appropriate formulation and the genetic characteristics of patients. The clinical manifestations of antibodies directed against a given protein may include loss of efficacy, neutralization of the natural counterpart and general immune system effects (including allergy, anaphylaxis or serum sickness). An upsurge in the incidence of antibody-mediated pure red cell aplasia (PRCA) among patients taking one particular formulation of recombinant human erythropoietin (epoetin-alpha, marketed as Eprex(R)/Erypo(R); Johnson & Johnson) in Europe caused widespread concern. The PRCA upsurge coincided with removal of human serum albumin from epoetin-alpha in 1998 and its replacement with glycine and polysorbate 80. Although the immunogenic potential of this particular product may have been enhanced by the way the product was stored, handled and administered, it should be noted that the subcutaneous route of administration does not confer immunogenicity per se. The possible role of micelle (polysorbate 80 plus epoetin-alpha) formation in the PRCA upsurge with Eprex is currently being investigated.
A Hybrid Approach for Predicting Aging-Related Failures of Software Systems

Software aging is a chronic process that is hidden under system monitoring until a system failure occurs. Aging related failures (ARFs) are the result of a variety of complex factors. Therefore, how to precisely predict the ARFs for a running software system is a challenge problem. Previous studies typically predict ARFs by means of predicting the time to resource exhaustion (TTE), which adopts resource data as aging indicators to predict when the resource data achieve the preset threshold. However, the practical effect of prior approaches are far from satisfactory due to lack of effective aging indicators and difficult to set accurate threshold. In this paper, we propose a hybrid approach, which combines model and measurements to construct a probabilistic aging indicator. The aging indicator is a multifactorial aging indicator that is more effective than traditional ones. Moreover, the hybrid approach is threshold-free in ARFs prediction. We evaluate the hybrid approach in Data caching system and Media streaming system, the results show that the hybrid approach can achieve high precision and recall for ARFs prediction. Compared to previous approaches, our approach increases the prediction precision and recall significantly.
(1-uv)-constacyclic Codes over (𝔽p + U𝔽p + V𝔽p + Uv𝔽p)

Constacyclic codes are an important class of linear codes in coding theory. Many optimal linear codes are directly derived from constacyclic codes. In this paper, (1 − uv)-constacyclic codes over the local ring Fp + uFp + vFp + uvFp are studied. It is proved that the image of a (1 − uv)constacyclic code of length n over Fp + uFp + vFp + uvFp under a Gray map is a distance invariant quasi-cyclic code of index p and length pn over Fp. Several examples of optimal linear codes over Fp from (1 − uv)-constacyclic codes over Fp + uFp + vFp + uvFp are given.
A 500-W high efficiency LDMOS classical three-way Doherty amplifier for base-station applications

A 500W classical three-way Doherty power amplifier (DPA) with LDMOS devices at 1.8GHz is presented. Optimized device ratio is selected to achieve maximum efficiency as well as linearity. With a simple passive input driving network implementation, the demonstrator exhibits more than 55% efficiency with 9.9PAR WCDMA signal from 1805MHz-1880MHz. It can be linearized at -60dBc level with 20MHz LTE signal at an average output power of 49dBm.
Porting an AUTOSAR-compliant operating system to a high performance embedded platform

Automotive embedded systems are going through a major change, both in terms of how they are used and in terms of software and hardware architecture. Much more powerful and rapidly evolvable hardware is expected, paralleled by an accelerating development rate of the control software. To meet these challenges, a software standard, AUTOSAR, is gaining ground in the automotive field. In this work, experiences from porting AUTOSAR to a high performance embedded system, Raspberry Pi, are collected. The goal is both to present experience on the process of AUTOSAR porting and to create an AUTOSAR implementation on a cheap and widely accessible hardware platform, making AUTOSAR available for researchers and students.
Cryptographic Currencies Crash Course (C4): Tutorial

”Bitcoin is a rare case where practice seems to be ahead of theory.” Joseph Bonneau et al.  This tutorial aims to further close the gap between IT security research and the area of cryptographic currencies and block chains. We will describe and refer to Bitcoin as an example throughout the tutorial, as it is the most prominent representative of a such a system. It also is a good reference to discuss the underlying block chain mechanics which are the foundation of various altcoins (e.g. Namecoin) and other derived systems. In this tutorial, the topic of cryptographic currencies is solely addressed from a technical IT security point-of-view. Therefore we do not cover any legal, sociological, financial and economical aspects. The tutorial is designed for participants with a solid IT security background but will not assume any prior knowledge on cryptographic currencies. Thus, we will quickly advance our discussion into core aspects of this field.
Blockchain: Distributed Event-based Processing in a Data-Centric World: Extended Abstract

Usage of Blockchain is expanding from the initial focus on crypto-currencies towards applications to support a broad range of collaborative activies amongst businesses, organizations, and individuals. There are two broad levels of Blockchain: the foundation level relates to encryption, consensus algorithms, and support for a single (logical) data store that is shared by all participants; and the "smart contract" level that enables developers and business-level users to specify the data, logic, and behavior that collaborations should follow. The smart contracts are programs that are fundamentally event driven, data-centric, and support the activity of a distributed set of stakeholders situated across multiple organizations. This raises an array of research challenges in areas including language and solution design, interoperation across smart contracts, and verification.
Single-Phase Hybrid Switched-Capacitor Voltage-Doubler SEPIC PFC Rectifiers

In this paper, the switched-capacitor concept is extended to the voltage-doubler discontinuous conduction mode SEPIC rectifier. As a result, a set of single-phase hybrid SEPIC power factor correction rectifiers able to provide lower voltage stress on the semiconductors and/or higher static gain, which can be easily increased with additional switched-capacitor cells, is proposed. Hence, these rectifiers could be employed in applications that require higher output voltage. In addition, the converters provide a high power factor and a reduced total harmonic distortion in the input current. The topology employs a three-state switch, and three different implementations are described, two being bridgeless versions, which can provide gains in relation to efficiency. The structures and the topological states, a theoretical analysis in steady state, a dynamic model for control, and a design example are reported herein. Furthermore, a prototype with specifications of 1000-W output power, 220-V input voltage, 800-V output voltage, and 50-kHz switching frequency was designed in order to verify the theoretical analysis.
Robot-assisted stereotactic laser ablation in medically intractable epilepsy: operative technique.

Stereotactic laser ablation offers an advantage over open surgical procedures for treatment of epileptic foci, tumors, and other brain pathology. Robot-assisted stereotactic laser ablation could offer an accurate, efficient, minimally invasive, and safe method for placement of an ablation catheter into the target.



To determine the feasibility of placement of a stereotactic laser ablation catheter into a brain lesion with the use of robotic assistance, via a safe, accurate, efficient, and minimally invasive manner.



A laser ablation catheter (Visualase, Inc) was placed by using robotic guidance (ROSA, Medtech Surgical, Inc) under general anesthesia into a localized epileptogenic periventricular heterotopic lesion in a 19-year-old woman with 10-year refractory focal seizure history. The laser applicator (1.65 mm diameter) position was confirmed by using magnetic resonance imaging (MRI). Ablation using the Visualase system was performed under multiplanar imaging with real-time thermal imaging and treatment estimates in each plane. A postablation MRI sequence (T1 postgadolinium contrast injection) was used to immediately confirm the ablation.



MRI showed accurate skin entry point and trajectory, with the applicator advanced to the lesion's distal boundary. Ablation was accomplished in less than 3 minutes of heating. The overall procedure, from time of skin incision to end of last ablation, was approximately 90 minutes. After confirmation of proper lesioning by using a T1 contrast-enhanced MRI, the applicator was removed, and the incision was closed using a single stitch. No hemorrhage or other untoward complication was visualized. The patient awoke without any complication, was observed overnight after admitting to a regular floor bed, and was discharged to home the following day.



This technique, using a combination of Visualase laser ablation, ROSA robot, and intraoperative MRI, facilitated a safe, efficacious, efficient, and minimally invasive approach that could be used for placement of 1 or multiple electrodes in the future.
Dynamic Object Flow Analysis

The behavior of an object-oriented software system is notoriously hard to understand from the source code alone. The main reason is the large gap between the program’s static structure and its actual runtime behavior. Features inherent to object-orientation, like object aliasing and late binding, — while providing a high degree of expressiveness to model an application domain — make programs hard to understand, maintain, and analyze. Complementary to static analysis, dynamic analysis can help to close this gap by investigating the properties of a running program. The state of the art in dynamic analysis focuses on investigating runtime control flow and structures of object graphs, but a thorough analysis of how objects are passed through a system is missing. Tracking how object references are transferred, however, is essential to analyze the dependencies introduced by object aliasing. In this dissertation we propose Object Flow Analysis, our approach to track object flow by explicitly representing object references and reference transfer. Object Flow Analysis provides an effective and original way of analyzing and runtime monitoring dependencies introduced by object aliasing. To validate Object Flow Analysis, we propose three different reverse engineering applications that, based on Object Flow Analysis, reason about aliasing dependencies in object-oriented programs. Yet Object Flow Analysis extends beyond traditional reverse engineering applications. A key contribution of our work is that we advance the state of the art in backin-time debugging by proposing and providing an implementation of the concept of Object Flow Analysis in a high-level language virtual machine.
Privacy preserving string comparisons based on Levenshtein distance

Alice and Bob possess strings x and y of length m and n respectively and want to compute the Levenshtein distance L(x, y) between the strings under privacy and communication constraints. The Levenshtein distance, or edit distance, has a dynamic programming formulation that solves a series of minimum-finding problems. Based on this formulation, there are known symmetric privacy-preserving protocols for the computation of L(x, y), in which the two parties incur equal protocol overhead. In this work, we propose an asymmetric two-party protocol in which a lightweight client Bob with a string y interacts with a single powerful server Alice containing string x in its database. We present a privacy-preserving minimum-finding protocol based on semantically secure homomorphic functions and additive secret sharing. This protocol is executed repeatedly, to enable private computation of the edit distance. Our protocol supports arbitrary finite insertion/deletion costs and a variety of substitution costs. While Alice requires similar effort as in previous approaches, the advantage is that Bob incurs far fewer ciphertext operations and transmissions, making the protocol well-suited for client-server querying applications.
Object recognition based on critical nodes

In recent decades, the need for efficient and effective image search from large databases has increased. In this paper, we present a novel shape matching framework based on structures common to similar shapes. After representing shapes as medial axis graphs, in which nodes show skeleton points and edges connect nearby points, we determine the critical nodes connecting or representing a shape’s different parts. By using the shortest path distance from each skeleton (node) to each of the critical nodes, we effectively retrieve shapes similar to a given query through a transportation-based distance function. To improve the effectiveness of the proposed approach, we employ a unified framework that takes advantage of the feature representation of the proposed algorithm and the classification capability of a supervised machine learning algorithm. A set of shape retrieval experiments including a comparison with several well-known approaches demonstrate the proposed algorithm’s efficacy and perturbation experiments show its robustness.
GLOBAL PRODUCTION NETWORKS AND THE ANALYSIS OF ECONOMIC DEVELOPMENT

This article outlines a framework for the analysis of economic integration and its relation to the asymmetries of economic and social development. Consciously breaking with state-centric forms of social science, it argues for a research agenda that is more adequate to the exigencies and consequences of globalisation than has traditionally been the case in 'development studies'. Drawing on earlier attempts to analyse the crossborder activities of firms, their spatial configurations and developmental consequences, the article moves beyond these by proposing the framework of the 'global production network' (GPN). It explores the conceptual elements involved in this framework in some detail and then turns to sketch a stylised example of a GPN. The article concludes with a brief indication of the benefits that could be delivered be research informed by GPN analysis.
Extrasensory perception: odorant and taste receptors beyond the nose and mouth.

G protein-coupled receptors (GPCRs) represent the largest family of transmembrane receptors and are prime therapeutic targets. The odorant and taste receptors account for over half of the GPCR repertoire, yet they are generally excluded from large-scale, drug candidate analyses. Accumulating molecular evidence indicates that the odorant and taste receptors are widely expressed throughout the body and functional beyond the oronasal cavity - with roles including nutrient sensing, autophagy, muscle regeneration, regulation of gut motility, protective airway reflexes, bronchodilation, and respiratory disease. Given this expanding array of actions, the restricted perception of these GPCRs as mere mediators of smell and taste is outdated. Moreover, delineation of the precise actions of odorant and taste GPCRs continues to be hampered by the relative paucity of selective and specific experimental tools, as well as the lack of defined receptor pharmacology. In this review, we summarize the evidence for expression and function of odorant and taste receptors in tissues beyond the nose and mouth, and we highlight their broad potential in physiology and pathophysiology.