nils-herrmann/clean_scirepeval huggingface dataset:
Emotion-focused family therapy for eating disorders in children and adolescents.

Family-based therapy (FBT) is regarded as best practice for the treatment of eating disorders in children and adolescents. In FBT, parents play a vital role in bringing their child or adolescent to health; however, a significant minority of families do not respond to this treatment. This paper introduces a new model whereby FBT is enhanced by integrating emotion-focused therapy (EFT) principles and techniques with the aims of helping parents to support their child's refeeding and interruption of symptoms. Parents are also supported to become their child's 'emotion coach'; and to process any emotional 'blocks' that may interfere with their ability to take charge of recovery. A parent testimonial is presented to illustrate the integration of the theory and techniques of EFT in the FBT model. EFFT (Emotion-Focused Family Therapy) is a promising model of therapy for those families who require a more intense treatment to bring about recovery of an eating disorder.



More intense therapeutic models exist for treatment-resistant eating disorders in children and adolescents. Emotion is a powerful healing tool in families struggling with an eating disorder. Working with parent's emotions and emotional reactions to their child's struggles has the potential to improve child outcomes.
A Low-Profile Metamaterial Loaded Antenna Array With Anti-Interference and Polarization Reconfigurable Characteristics

A low-profile metamaterial loaded antenna array with anti-interference and polarization reconfigurable features is proposed for base-station communication. Owing to the dual notches etched on the radiating electric dipoles, an impedance bandwidth of 75.6% ranging from 1.68 to 3.72 GHz with a notch band from 2.38 to 2.55 GHz can be achieved. By employing the metamaterial loadings that are arranged in the center of the magnetic dipole, the thickness of the proposed antenna can be decreased from 28 to 20 mm. Furthermore, a serial feeding network that consists of several Wilkinson power dividers and phase shifters is introduced to attain the conversion between dual-linear polarization and triple-circular polarization. Hence, the antenna could meet the demand of the future 5G intelligent application.
Legal Translation and Translation Theory : a Receiver-oriented Approach

In this age of globalization, the need for competent legal translators is greater than ever. This perhaps explains the growing interest in legal translation not only by linguists but also by lawyers, the latter especially over the past 10 years (cf. Berteloot, 1999:101). Although Berteloot maintains that lawyers analyze the subject matter from a different perspective, she advises her colleagues also to take account of contributions by linguists (ibid.). I assume this includes translation theory as well. In the past, both linguists and lawyers have attempted to apply theories of general translation to legal texts, such as Catford’s concept of situation equivalence (Kielar, 1977:33), Nida’s theory of formal correspondence (Weisflog, ); also in Weisflog 1996:35), and, more recently, Vermeer’s skopos theory (see Madsen’s, 1997:17-26). While some legal translators seem content to apply principles of general translation theory (Koutsivitis, 1988:37), others dispute the usefulness of translation theory for legal translation (Weston, 1991:1). The latter view is not surprising since special methods and techniques are required in legal translation, a fact confirmed by Bocquet, who recognizes the importance of establishing a theory or at least a theoretical framework that is practice oriented (1994). By analyzing legal translation as an act of communication in the mechanism of the law, my book New Approach to Legal Translation (1997) attempts to provide a theoretical basis for legal translation within the framework of modern translation theory.
Mining the peanut gallery: opinion extraction and semantic classification of product reviews

The web contains a wealth of product reviews, but sifting through them is a daunting task. Ideally, an opinion mining tool would process a set of search results for a given item, generating a list of product attributes (quality, features, etc.) and aggregating opinions about each of them (poor, mixed, good). We begin by identifying the unique properties of this problem and develop a method for automatically distinguishing between positive and negative reviews. Our classifier draws on information retrieval techniques for feature extraction and scoring, and the results for various metrics and heuristics vary depending on the testing situation. The best methods work as well as or better than traditional machine learning. When operating on individual sentences collected from web searches, performance is limited due to noise and ambiguity. But in the context of a complete web-based tool and aided by a simple method for grouping sentences into attributes, the results are qualitatively quite useful.
A GPU-based parallel slicer for 3D printing

Mesh slicing is one of the most common operations in additive manufacturing (AM). However, the computing burden for such an application is usually very heavy, especially when dealing with large models. Nowadays the graphics processing units (GPU) have abundant resources and it is reasonable to utilize the computing power of GPU for mesh slicing. In the paper, we propose a parallel implementation of the slicing algorithm using GPU. We test the GPU-accelerated slicer on several models and obtain a speedup factor of about 30 when dealing with large models, compared with the CPU implementation. Results show the power of GPU on the mesh slicing problem. In the future, we will extend our work and standardize the slicing process.
Metal Artifact Reduction in CT: Where Are We After Four Decades?

Methods to overcome metal artifacts in computed tomography (CT) images have been researched and developed for nearly 40 years. When X-rays pass through a metal object, depending on its size and density, different physical effects will negatively affect the measurements, most notably beam hardening, scatter, noise, and the non-linear partial volume effect. These phenomena severely degrade image quality and hinder the diagnostic power and treatment outcomes in many clinical applications. In this paper, we first review the fundamental causes of metal artifacts, categorize metal object types, and present recent trends in the CT metal artifact reduction (MAR) literature. To improve image quality and recover information about underlying structures, many methods and correction algorithms have been proposed and tested. We comprehensively review and categorize these methods into six different classes of MAR: metal implant optimization, improvements to the data acquisition process, data correction based on physics models, modifications to the reconstruction algorithm (projection completion and iterative reconstruction), and image-based post-processing. The primary goals of this paper are to identify the strengths and limitations of individual MAR methods and overall classes, and establish a relationship between types of metal objects and the classes that most effectively overcome their artifacts. The main challenges for the field of MAR continue to be cases with large, dense metal implants, as well as cases with multiple metal objects in the field of view. Severe photon starvation is difficult to compensate for with only software corrections. Hence, the future of MAR seems to be headed toward a combined approach of improving the acquisition process with dual-energy CT, higher energy X-rays, or photon-counting detectors, along with advanced reconstruction approaches. Additional outlooks are addressed, including the need for a standardized evaluation system to compare MAR methods.
Two algorithms for the Student-Project Allocation problem

We study the Student-Project Allocation problem (SPA), a generalisation of the classical Hospitals / Residents problem (HR). An instance of SPA involves a set of students, projects and lecturers. Each project is offered by a unique lecturer, and both projects and lecturers have capacity constraints. Students have preferences over projects, whilst lecturers have preferences over students. We present two optimal linear-time algorithms for allocating students to projects, subject to the preference and capacity constraints. In particular, each algorithm finds a stable matching of students to projects. Here, the concept of stability generalises the stability definition in the HR context. The stable matching produced by the first algorithm is simultaneously best-possible for all students, whilst the one produced by the second algorithm is simultaneously best-possible for all lecturers. We also prove some structural results concerning the set of stable matchings in a given instance of SPA. The SPA problem model that we consider is very general and has applications to a range of different contexts besides student-project allocation.
Efficient Subgraph Isomorphism Detection: A Decomposition Approach

ÐGraphs are a powerful and universal data structure useful in various subfields of science and engineering. In this paper, we propose a new algorithm for subgraph isomorphism detection from a set of a priori known model graphs to an input graph that is given online. The new approach is based on a compact representation of the model graphs that is computed offline. Subgraphs that appear multiple times within the same or within different model graphs are represented only once, thus reducing the computational effort to detect them in an input graph. In the extreme case where all model graphs are highly similar, the run-time of the new algorithm becomes independent of the number of model graphs. Both a theoretical complexity analysis and practical experiments characterizing the performance of the new approach will be given. Index TermsÐGraph matching, graph isomorphism, subgraph isomorphism, preprocessing.
Sneak-Path Testing of Crossbar-Based Nonvolatile Random Access Memories

Emerging nonvolatile memory (NVM) technologies, such as resistive random access memories (RRAM) and phase-change memories (PCM), are an attractive option for future memory architectures due to their nonvolatility, high density, and low-power operation. Notwithstanding these advantages, they are prone to high defect densities due to the nondeterministic nature of the nanoscale fabrication. We examine the fault models and propose an efficient testing technique to test crossbar-based NVMs. The typical approach to testing memories entails testing one memory element at a time. This is time consuming and does not scale for the dense, RRAM or PCM-based memories. We propose a testing scheme based on “sneak-path sensing” to efficiently detect faults in the memory. The testing scheme uses sneak paths inherent in crossbar memories, to test multiple memory elements at the same time, thereby reducing testing time. We designed the design-for-test support necessary to control the number of sneak paths that are concurrently enabled; this helps control the power consumed during test. The proposed scheme enables and leverages sneak paths during test mode, while still maintaining a sneak path free crossbar during normal operation.
Automatic keyphrase extraction from scientific articles

This paper describes the organization and results of the automatic keyphrase extraction task held at the workshop on Semantic Evaluation 2010 (SemEval-2010). The keyphrase extraction task was specifically geared towards scientific articles. Systems were automatically evaluated by matching their extracted keyphrases against those assigned by the authors as well as the readers to the same documents. We outline the task, present the overall ranking of the submitted systems, and discuss the improvements to the state-of-the-art in keyphrase extraction.
A semi-supervised deep fuzzy C-mean clustering for two classes classification

Deep Fuzzy C-Means algorithm is applied to determine veiled structure in the data set. It is commonly used when data boundaries are not clearly defined and extra parameters are needed to reduce the statistical closeness. In this paper, we propose a semi-supervised deep fuzzy C-Means algorithm that accommodates this intangibility. It is applicable to machine learning methodology that relies on algorithmic flow for dynamic data. With statistical data provided in the form of a collection of numerical data set of two classes, namely labeled and unlabeled, the semi-supervised deep fuzzy c-means clustering provides a comparison and solution for a given data set. The clustering approach looks at membership functions for fuzziness. The proposed framework for semi-supervised data set finds supervised data and segregates it from unsupervised data. Here, the term "deep" defines the proximity in space, which is used to improve precision along the centers. The membership function for each cluster is used to gauge the closeness between the unlabeled and labeled data set. The dependency of our algorithm's performance on control parameters helps us determine the variability of the clustering technique. Our simulation result shows that semi-supervised deep fuzzy-c algorithm performs better than previously studied semi-supervised clustering algorithms.
Integration of Distributed Enterprise Applications: A Survey

Many industrial enterprises acquire disparate systems and applications over the years. The need to integrate these different systems and applications is often prominent for satisfying business requirements and needs. In an effort to help researchers in industrial informatics understand the state-of-the-art of the enterprise application integration, we examined the architectures and technologies for integrating distributed enterprise applications, illustrated their strengths and weaknesses, and identified research trends and opportunities in this increasingly important area.
High-Efficiency-Isolated Single-Input Multiple-Output Bidirectional Converter

This study presents a high-efficiency-isolated single-input multiple-output bidirectional (HISMB) converter for a power storage system. According to the power management, the proposed HISMB converter can operate at a step-up state (energy release) and a step-down state (energy storage). At the step-up state, it can boost the voltage of a low-voltage input power source to a high-voltage-side dc bus and middle-voltage terminals. When the high-voltage-side dc bus has excess energy, one can reversely transmit the energy. The high-voltage dc bus can take as the main power, and middle-voltage output terminals can supply powers for individual middle-voltage dc loads or to charge auxiliary power sources (e.g., battery modules). In this study, a coupled-inductor-based HISMB converter accomplishes the bidirectional power control with the properties of voltage clamping and soft switching, and the corresponding device specifications are adequately designed. As a result, the energy of the leakage inductor of the coupled inductor can be recycled and released to the high-voltage-side dc bus and auxiliary power sources, and the voltage stresses on power switches can be greatly reduced. Moreover, the switching losses can be significantly decreased because of all power switches with zero-voltage-switching features. Therefore, the objectives of high-efficiency power conversion, electric isolation, bidirectional energy transmission, and various output voltage with different levels can be obtained. The effectiveness of the proposed HISMB converter is verified by experimental results of a kW-level prototype in practical applications.
What Motivates People to Purchase Digital Items on Virtual Community Websites? The Desire for Online Self-Presentation

T sale of digital items, such as avatars and decorative objects, is becoming an important source of revenue for virtual community (VC) websites. However, some websites are unable to leverage this source of revenue, and there is a corresponding lack of understanding about what motivates people to purchase digital items in VCs. To explain the phenomenon, we develop a model based on the theory of self-presentation. The model proposes that the desire for online self-presentation is a key driver for such purchases. We also hypothesize that the social influence factors of online self-presentation norms and VC involvement as well as personal control in the form of online presentation self-efficacy are antecedents of the desire for online self-presentation. The model was validated by using survey data collected from Cyworld (N = 217) and Habbo (N = 197), two online social network communities that have been pioneers in the sale of digital items. This work contributes to our understanding of the purchase of digital items by extending the theory of self-presentation and adds to the broader line of research on online identity. It also lends insights into how VC providers can tap this source of revenue.
The red ear syndrome: an auriculo-autonomic cephalgia.

CLINICAL HISTORY A 54-year-old white female was seen with a 10-year history of episodes of a burning sensation of the left ear. The episodes are preceded by nausea and a hot feeling for about 15 seconds and then the left ear becomes visibly red for an average of about 1 hour, with a range from about 30 minutes to 2 hours. About once every 2 years, she would have a flurry of episodes occurring over about a 1-month period during which she would average about five episodes with a range of 1 to 6. There was also an 18-year history of migraine without aura occurring about once a year. At the age of 36 years, she developed left-sided pulsatile tinnitus. A cerebral arteriogram revealed a proximal left internal carotid artery occlusion of uncertain etiology after extensive testing. An MRI scan at the age of 45 years was normal. Neurological examination was normal. A carotid ultrasound study demonstrated complete occlusion of the left internal carotid artery and a normal right. Question.—What is the diagnosis?
Thoracodorsal artery perforator (TAP) type I V-Y advancement flap in axillary hidradenitis suppurativa.

Hidradenitis suppurativa is a chronic debilitating disease. Surgical removal of all apocrine glands in the affected region is the definitive treatment. The resulting wound may either be left to heal secondarily or closed primarily. Secondary healing in the axilla may cause contractures and stiffening of the shoulder. Primary healing requires direct closure, split-skin grafting or local flap application. Direct closure is associated with a high incidence of recurrence compared to skin grafting or flaps. Local flap cover is the ideal method of wound closure after excision of the glands. We have used a thoracodorsal artery perforator (TAP) V-Y advancement flap (type I) to achieve closure as a single-stage procedure successfully in four cases. It is a single stage procedure capable of closing large axillary defects whilst preserving the axillary contour.
On the Malleability of Bitcoin Transactions

We study the problem of malleability of Bitcoin transactions. Our first two contributions can be summarized as follows: (i) we perform practical experiments on Bitcoin that show that it is very easy to maul Bitcoin transactions with high probability, and (ii) we analyze the behavior of the popular Bitcoin wallets in the situation when their transactions are mauled; we conclude that most of them are to some extend not able to handle this situation correctly. The contributions in points (i) and (ii) are experimental. We also address a more theoretical problem of protecting the Bitcoin distributed contracts against the “malleability” attacks. It is well-known that malleability can pose serious problems in some of those contracts. It concerns mostly the protocols which use a “refund” transaction to withdraw a financial deposit in case the other party interrupts the protocol. Our third contribution is as follows: (iii) we show a general method for dealing with the transaction malleability in Bitcoin contracts. In short: this is achieved by creating a malleability-resilient “refund” transaction which does not require any modification of the Bitcoin protocol.
Haunted House / Haunted Heroine : Female Gothic Closets in “ The Yellow Wallpaper ”

Concluding his provocative 1989 essay delineating how Charlotte Perkins Gilman’s “The Yellow Wallpaper” functions as a Gothic allegory, Greg Johnson describes Gilman’s achievement as yet awaiting its “due recognition” and her compelling short story as being “[s]till under-read, still haunting the margins of the American literary canon” (530). Working from the premise that Gilman’s tale “adroitly and at times parodically employs Gothic conventions to present an allegory of literary imagination unbinding the social, domestic, and psychological confinements of a nineteenth-century woman writer,” Johnson provides a fairly satisfactory general overview of “The Yellow Wallpaper” as a Gothic production (522). Despite the disputable claim that Gilman’s story functions, in part, as a Gothic parody, he correctly identifies and aptly elucidates several of the most familiar Gothic themes at work in this study— specifically “confinement and rebellion, forbidden desire and ‘irrational’ fear”—alongside such traditional Gothic elements as “the distraught heroine, the forbidding mansion, and the powerfully repressive male antagonist” (522). Johnson ultimately overlooks,
To bathe or not to bathe with chlorhexidine gluconate: is it time to take a stand for preadmission bathing and cleansing?

any health care facilities have incorporated an antiseptic skin cleansing protocol, often referred to as preoperative bathing and cleansing, to reduce the endogenous microbial burden on the skin of patients undergoing elective surgery, with the aim of reducing the risk of surgical site infections (SSIs). According to a recent study by Injean et al, 91% of all facilities that perform coronary artery bypass surgery in California have a standardized preoperative bathing and cleansing protocol for patients. Historically, this practice has been endorsed by national and international organizations, such as the Hospital Infection Control Practice Advisory Committee and the Centers for Disease Control and Prevention, the Association for Professionals in Infection Control and Epidemiology (APIC), AORN, the Institute for Healthcare Improvement (IHI), and the National Institute for Health and Care Excellence (NICE), which recommend bathing and/or cleansing with an antiseptic agent before surgery as a component of a broader strategy to reduce SSIs. The 2008 Society for Healthcare Epidemiology of America (SHEA)/ Infectious Diseases Society of America (IDSA)/Surgical Infection Society (SIS) strategies to prevent SSIs in acute care hospitals declined to recommend a specific application policy regarding selection of an antiseptic agent for preoperative bathing but acknowledged that the (maximal) antiseptic benefits of chlorhexidine gluconate (CHG) are dependent on achieving adequate skin surface concentrations.
Blockchain-Based PKI Solutions for IoT

Traditionally, a Certification Authority (CA) is required to sign, manage, verify and revoke public key certificates. Multiple CAs together form the CA-based Public Key Infrastructure (PKI). The use of a PKI forces one to place trust in the CAs, which have proven to be a single point-of-failure on multiple occasions. Blockchain has emerged as a transformational technology that replaces centralized trusted third parties with a decentralized, publicly verifiable, peer-to-peer data store which maintains data integrity among nodes through various consensus protocols. In this paper, we deploy three blockchain-based alternatives to the CA-based PKI for supporting IoT devices, based on Emercoin Name Value Service (NVS), smart contracts by Ethereum blockchain, and Ethereum Light Sync client. We compare these approaches with CA-based PKI and show that they are much more efficient in terms of computational and storage requirements in addition to providing a more robust and scalable PKI.