Miracle-dz/UniFAR-FTUs huggingface dataset:
A Mobile Serious Games Assessment Tool for People with Motor Impairments

Accessibility is a feature that often is not considered in the design of products or services and video games market is not the exception. Serious games is a category of video games that allows to educate in different areas through fun. They have become an important support tool in the learning process. However, most serious games do not focus on vulnerable groups such as people with motor impairments. On the other hand, the number of mobile serious games has increased with the use of mobile devices. Despite this, accessibility for people with motor impairments has not yet been considered a necessary feature in the development of this type of video games. Some video game developer groups recommend general accessibility guidelines for the design of such applications. However, it has become necessary to formalize, consolidate and analyze these initiatives in order to define a model for evaluating the accessibility of video games for people with motor impairments. This paper presents a compilation and analysis of accessibility guidelines for the development of video games for people with motor impairments. It also proposes a categorization of existing guidelines that allow to evaluate a video game accessibility level. As a case study, these accessibility guidelines are used to assess some mobile serious games and identify their accessibility level for people with motor impairments. We propose an assessment tool for those who wish to develop accessible serious games for people with motor impairments on mobile devices.
Web Service Customization Based on Service Feature Model

Service-oriented Computing (SOC) has become one of the most preferred distributed computing paradigms which utilize services as elements for designing and developing application systems. In SOC, consumers who have different functional and non-functional requirements might consume services offered by various providers. Faced with the increasing number of Web services and the diversity of service consumers' requirements, how to select and customize service models to satisfy consumers' personalized requirements remains an important issue. To this end, we adopt a model-driven development approach to customize services based on service feature modeling (SFM). Since SFM builds upon feature modeling (FM), it inherits the advantages of the latter. Furthermore, it takes into account service consumers' non-functional requirements with the attributes and attributes type that are not considered in the general feature model technique. A prototype shows the feasibility of the proposed approach.
A Unified Framework for Throughput Analysis of Streaming Applications under Memory Constraints

Streaming applications are an important class of applications in real-time embedded systems, which usually run under restricted resource constraints and with real-time requirement. They are often modeled with Synchronous data flow graphs (SDFGs) or Cyclo-Static data flow graphs (CSDFGs) at the design stage. A proper analysis of the models gives a predictable design for a system. In this paper, we focus on the throughput analysis of (C)SDFGs, taking into account memory constraints. Memory related analysis needs to choose a memory abstraction that decides when the space of consumed data is released and when the required space is claimed. Different memory abstractions may lead to different achievable throughputs. The existing techniques, however, consider only a certain abstraction. If a model is implemented according to other abstractions, the analysis result may not truly evaluate the performance of the system. In this paper, we present a novel unified framework for throughput analysis of memory constrained (C)SDFGs for different abstractions, aiming to provide evaluations matching up to the corresponding implementations. Our methods are exact. Experiments are carried out on several models of real streaming applications and hundreds of synthetic graphs to evaluate the effects and performance of our methods.
The Role of the Estrogen Pathway in the Tumor Microenvironment

Estrogen receptors are broadly expressed in many cell types involved in the innate and adaptive immune responses, and differentially regulate the production of cytokines. While both genomic and non-genomic tumor cell promoting mechanisms of estrogen signaling are well characterized in multiple carcinomas including breast, ovarian, and lung, recent investigations have identified a potential immune regulatory role of estrogens in the tumor microenvironment. Tumor immune tolerance is a well-established mediator of oncogenesis, with increasing evidence indicating the importance of the immune response in tumor progression. Immune-based therapies such as antibodies that block checkpoint signals have emerged as exciting therapeutic approaches for cancer treatment, offering durable remissions and prolonged survival. However, only a subset of patients demonstrate clinical response to these agents, prompting efforts to elucidate additional immunosuppressive mechanisms within the tumor microenvironment. Evidence drawn from multiple cancer types, including carcinomas traditionally classified as non-immunogenic, implicate estrogen as a potential mediator of immunosuppression through modulation of protumor responses independent of direct activity on tumor cells. Herein, we review the interplay between estrogen and the tumor microenvironment and the clinical implications of endocrine therapy as a novel treatment strategy within immuno-oncology.
60 GHz circularly polarized dielectric resonator antenna fed by printed ridge gap waveguide

A novel 60 GHz dielectric resonator antenna (DRA) with wide circular polarization bandwidth is presented. The performance of a stair-like rectangular DRA with x-shaped feeding slot, which is fed with a printed ridge gap waveguide (PRGW) is analyzed. The antenna has a 10.9% circularly polarized bandwidth (axial ratio < 3 dB) and 28% matching bandwidth (S11 < −10 dB). The PRGW feeding technology ensures a low loss feeding mechanism with no radiation losses.
Salus: a system for server-aided secure function evaluation

Secure function evaluation (SFE) allows a set of mutually distrustful parties to evaluate a function of their joint inputs without revealing their inputs to each other. SFE has been the focus of active research and recent work suggests that it can be made practical. Unfortunately, current protocols and implementations have inherent limitations that are hard to overcome using standard and practical techniques. Among them are: (1) requiring participants to do work linear in the size of the circuit representation of the function; (2) requiring all parties to do the same amount of work; and (3) not being able to provide complete fairness. A promising approach for overcoming these limitations is to augment the SFE setting with a small set of untrusted servers that have no input to the computation and that receive no output, but that make their computational resources available to the parties. In this model, referred to as server-aided SFE, the goal is to tradeoff the parties' work at the expense of the servers. Motivated by the emergence of public cloud services such as Amazon EC2 and Microsoft Azure, recent work has explored the extent to which server-aided SFE can be achieved with a single server. In this work, we revisit the sever-aided setting from a practical perspective and design single-server-aided SFE protocols that are considerably more efficient than all previously-known protocols. We achieve this in part by introducing several new techniques for garbled-circuit-based protocols, including a new and efficient input-checking mechanism for cut-and-choose and a new pipelining technique that works in the presence of malicious adversaries. Furthermore, we extend the server-aided model to guarantee fairness which is an important property to achieve in practice. Finally, we implement and evaluate our constructions experimentally and show that our protocols (regardless of the number of parties involved) yield implementations that are 4 and 6 times faster than the most optimized two-party SFE implementation when the server is assumed to be malicious and covert, respectively.
Adolescent Internet Use, Social Integration, and Depressive Symptoms: Analysis from a Longitudinal Cohort Survey

Objective: To examine the association between adolescent leisure-time Internet use and social integration in the school context and how this association affects later depressive symptoms among adolescents in Taiwan, using a large nationwide cohort study and the latent growth model (LGM) method. Methods: Data of 3795 students followed from the year 2001 to 2006 in the Taiwan Education Panel Survey were analyzed. Leisure-time Internet use was defined by the hours per week spent on (1) online chatting and (2) online games. School social integration and depressive symptoms were self-reported. We first used an unconditional LGM to estimate the baseline (intercept) and growth (slope) of Internet use. Next, another LGM conditioned with school social integration and depression was conducted. Results: Approximately 10% of the participants reported engaging in online chatting and/or gaming for more than 20 hours per week. Internet use for online chatting showed an increase over time. School social integration was associated with the baseline amount (coefficient = −0.62, p < 0.001) but not the growth of leisure-time Internet use. The trend of Internet use was positively related to depressive symptoms (coefficient = 0.31, p < 0.05) at Wave 4. Conclusion: School social integration was initially associated with decreased leisure-time Internet use among adolescents. The growth of Internet use with time was not explainable by school social integration but had adverse impacts on depression. Reinforcing adolescents' bonding to school may prevent initial leisure-time Internet use. When advising on adolescent Internet use, health care providers should consider their patients' social networks and mental well-being.
KLEE: A Framework for Distributed Top-k Query Algorithms

This paper addresses the efficient processing of top-k queries in wide-area distributed data repositories where the index lists for the attribute values (or text terms) of a query are distributed across a number of data peers and the computational costs include network latency, bandwidth consumption, and local peer work. We present KLEE, a novel algorithmic framework for distributed top-k queries, designed for high performance and flexibility. KLEE makes a strong case for approximate top-k algorithms over widely distributed data sources. It shows how great gains in efficiency can be enjoyed at low result-quality penalties. Further, KLEE affords the query-initiating peer the flexibility to trade-off result quality and expected performance and to trade-off the number of communication phases engaged during query execution versus network bandwidth performance. We have implemented KLEE and related algorithms and conducted a comprehensive performance evaluation. Our evaluation employed real-world and synthetic large, web-data collections, and query benchmarks. Our experimental results show that KLEE can achieve major performance gains in terms of network bandwidth, query response times, and much lighter peer loads, all with small errors in result precision and other result-quality measures.
Single nucleotide polymorphisms in an intergenic chromosome 2q region associated with tissue factor pathway inhibitor plasma levels and venous thromboembolism

Essentials Tissue factor pathway inhibitor (TFPI) regulates the blood coagulation cascade. We replicated previously reported linkage of TFPI plasma levels to the chromosome 2q region. The putative causal locus, rs62187992, was associated with TFPI plasma levels and thrombosis. rs62187992 was marginally associated with TFPI expression in human aortic endothelial cells.
Efficient Privacy-Preserving Authentication Protocol for Vehicular Communications with Trustworthy

In this paper, we introduce an efficient and trustworthy conditional privacy-preserving communication protocol for VANETs based on proxy re-signature. The proposed protocol is characterized by the Trusted Authority (TA) designating the Roadside Units (RSUs) to translate signatures computed by the On-Board Units (OBUs) into one that are valid with respect to TA's public key. In addition, the proposed protocol offers both a priori and a posteriori countermeasures: it can not only provide fast anonymous authentication and privacy tracking, but guarantees message trustworthiness for vehicle-to-vehicle (V2V) communications. Furthermore, it reduces the communication overhead and offers fast message authentication and, low storage requirements. We use extensive analysis to demonstrate the merits of the proposed protocol and to contrast it with previously proposed solutions.
Low-rank matrix completion against missing rows and columns with separable 2-D sparsity priors

Most existing matrix completion approaches assume that entries of matrices are missing at random, which could be violated in practical applications. This paper proposes a novel matrix completion method equipped with Joint Priors of LOw-rank and Separable 2-D Sparsity (JPLOSS) to complete missing rows and columns besides random missing. The underlying matrix is regularized by a low-rank prior, and its rows and columns are regularized by a row and a column dictionary, respectively. An reweighting scheme is incorporated into both the low-rank and sparsity terms to promote the low-rankness and sparseness simultaneously. The proposed model is effectively solved by an alternating direction method under the augmented Lagrangian multiplier framework. Experiments on both synthetic data and real images demonstrate the effectiveness and superiority of the proposed model in completing matrices with missing rows and columns compared with state-of-the-art matrix completion approaches.
Biomedical applications of organosilica nanoparticles toward theranostics

Abstract Nanoparticles for biomedical applications have several advantages as multifunctional agents. Among various types of nanoparticles for biomedical applications, silica nanoparticles have characteristic positioning due to their inherent property. The recent development of silica nanoparticles is creating a new trend in nanomedicine. A novel type of silica nanoparticle, organosilica nanoparticle, is both structurally and functionally different from the common (inorgano)silica nanoparticle. The organosilica nanoparticles are inherent organic-inorganic hybrid nanomaterials. The interior and exterior functionalities of organosilica nanoparticles are useful for their multifunctionalization. Biomedical applications of organosilica nanoparticles are leading to a wide range of nanomedical fields such as basic biomedical investigations and clinical applications. Multifunctionalizations peculiar to organosilica nanoparticles enable the creation of novel imaging systems and therapeutic applications. In this review, I will introduce differences between (inorgano)silica nanoparticles and organosilica nanoparticles, and then focus on biomedical applications of organosilica nanoparticles toward theranostics.
Relationship between tissue Doppler measurements of left ventricular diastolic function and silent brain infarction in patients with non-valvular atrial fibrillation

Aims Left ventricular (LV) diastolic function assessed by tissue Doppler imaging (TDI) is reported to be associated with left atrial (LA) blood stasis in patients with non-valvular atrial fibrillation (AF). This study aimed to evaluate the relationship of diastolic TDI parameters with silent brain infarction (SBI) on brain magnetic resonance imaging (MRI), and in turn the risks of subsequent stroke or dementia, in non-valvular AF patients. Methods and results The study population consisted of 171 neurologically asymptomatic patients with non-valvular AF who underwent transoesophageal echocardiography (TOE) (128 men; mean age, 63 ± 11 years). We measured diastolic TDI parameters by transthoracic echocardiography, and also screened for SBI employing brain MRI. Early transmitral flow velocity (E) and mitral annular velocity by TDI (e') were measured, and E/e' ratios were calculated. An increased tertile of the E/e' ratio was significantly related to high prevalences of LA abnormalities detected by TOE (32% vs. 12% vs. 9%; P =0.002) and SBI on brain MRI (46% vs. 23% vs. 14%; P < 0.001). In multivariate logistic regression analyses after adjustment for age, hypertension, chronic kidney disease, and CHA2DS2-VASc score ≥2, the E/e' ratio ≥12.4 was found to be an independent predictor of the presence of SBI (OR 3.98, 95% CI 1.74-9.07; P = 0.001). Conclusions Impaired LV diastolic function evaluated by increased E/e' ratio was closely associated with the presence of SBI independent of CHA2DS2-VASc score. TDI measurements are non-invasive and useful for risk stratification of the early stage of cerebral damages in patients with non-valvular AF.
Motivational Interviewing and Medication Review in Coronary Heart Disease (MIMeRiC): Protocol for a Randomized Controlled Trial Investigating Effects on Clinical Outcomes, Adherence, and Quality of Life

Background Preventive treatment goals for blood pressure and cholesterol levels continue to be unmet for many coronary patients. The effect of drug treatment depends on both its appropriateness and the patients’ adherence to the treatment regimen. There is a need for adherence interventions that have a measurable effect on clinical outcomes. Objective This study aims to evaluate the effects on treatment goals of an intervention designed to improve patient adherence and treatment quality in secondary prevention of coronary heart disease. A protocol for the prespecified process evaluation of the trial is published separately. Methods The Motivational Interviewing and Medication Review in Coronary heart disease (MIMeRiC) trial is a prospective, randomized, outcomes-blinded trial designed to compare individualized follow-up by a clinical pharmacist using motivational interviewing (MI) and medication review with standard follow-up. Patients were randomized to 2 groups after stratification according to their beliefs about medicines. After standard follow-up at the cardiology clinic, patients in the intervention group are seen individually by a clinical pharmacist 2 to 5 times as required over 7 months, at the clinic. The pharmacist reviews each patient’s medication and uses MI to manage any problems with prescribing and adherence. The primary study outcome is the proportion of patients who have reached the treatment goal for low-density lipoprotein cholesterol by 12 months after discharge. Secondary outcomes are the effects on patient adherence, systolic blood pressure, disease-specific quality of life, and health care use. Results The protocol for this study was approved by the Regional Ethics Committee, Linköping, in 2013. Enrollment started in October 2013 and ended in December 2016 when 417 patients had been included. Follow-up data collection will conclude in March 2018. Publication of the primary and secondary outcome results from the MIMeRiC trial is anticipated in 2019. Conclusions The MIMeRiC trial will assess the effectiveness of an intervention involving medication reviews and individualized support. The results will inform the continued development of support for this large group of patients who use preventive medicines for lifelong treatment. The design of this adherence intervention is based on a theoretical framework and is the first trial of an intervention that uses beliefs about medicines to individualize the intervention protocol. Trial Registration ClinicalTrials.gov NCT02102503; https://clinicaltrials.gov/ct2/show/NCT02102503 (Archived by WebCite at http://www.webcitation.org/6x7iUDohy)
Psychosocial Aspects of Immediate versus Delayed Breast Reconstruction

Background: Only little is known about the psychosocial aspects of breast cancer patients after mastectomy with immediate versus delayed breast reconstruction. Methods: We systematically screened PubMed using the following key words: mastectomy, immediate vs. delayed reconstruction, psychosocial aspects and quality of life. To highlight different psychological outcomes, studies were categorized into those describing: anxiety, depression, body image and satisfaction with the surgical outcome. We also compared patients after mastectomy alone with those undergoing immediate or delayed reconstruction. Results: Methodologies and psychological outcomes varied among the identified studies, making it difficult to compare results. There are contradictory outcomes concerning the psychosocial aspects of breast cancer patients after mastectomy alone compared with those who underwent an immediate or delayed reconstruction following mastectomy. Some studies show that immediate reconstruction after mastectomy had a positive impact on patients' psychological well-being. In contrast, other studies indicated that in the long-term view the compared patient groups were very similar concerning psychosocial aspects. Conclusion: Analyzing different aspects of psychosocial well-being after breast cancer surgery, there might be an advantage in choosing immediate reconstruction, if oncological safety allows it.
Efficient Maintenance of Shortest Distances in Dynamic Graphs

Computing shortest distances is a central task in many domains. The growing number of applications dealing with dynamic graphs calls for incremental algorithms, as it is impractical to recompute shortest distances from scratch every time updates occur. In this paper, we address the problem of maintaining all-pairs shortest distances in dynamic graphs. We propose efficient incremental algorithms to process sequences of edge deletions/insertions/updates and vertex deletions/insertions. The proposed approach relies on some general operators that can be easily “instantiated” both in main memory and on top of different underlying DBMSs. We provide complexity analyses of the proposed algorithms. Experimental results on several real-world datasets show that current main-memory algorithms become soon impractical, disk-based ones are needed for larger graphs, and our approach significantly outperforms state-of-the-art algorithms.
Competence Acquisition Using Simulated Learning Experiences: A Concept Analysis

AIM To report the findings of an analysis of the concept of competence acquisition when determined using simulated learning experiences. BACKGROUND Competence of nursing students prior to entry into practice has been stressed by the Institute of Medicine. Competence can be evaluated via simulation; however, evaluation practices vary among schools of nursing. The link between competence acquisition in simulation and clinical competence has not been determined. METHOD Employing the methodology of Walker and Avant (2011), articles included in this analysis were published in english in peer‐reviewed journals from 2002 to 2012 and contained information on simulation outcomes related to competence. Thirty‐five articles and one text were included in the final analysis. RESULTS Essential elements of competence acquisition identified included authentic environment, demonstration, and evaluation. CONCLUSION Use of a consistent language and framework to evaluate competence acquisition in simulation is recommended, as is future research to test the constructs.
On a Web of Data Streams

: With the growing adoption of IoT and sensor technologies, an enormous amount of data is being produced at a very rapid pace and in different application domains. This sensor data consists mostly of live data streams containing sensor observations, generated in a distributed fashion by multiple heterogeneous infrastructures with minimal or no interoperability. RDF streams emerged as a model to represent data streams