Miracle-dz/UniFAR-FTUs huggingface dataset:
Change in non-alcoholic beverage sales following a 10-pence levy on sugar-sweetened beverages within a national chain of restaurants in the UK: interrupted time series analysis of a natural experiment

Background This study evaluates changes in sales of non-alcoholic beverages in Jamie’s Italian, a national chain of commercial restaurants in the UK, following the introduction of a £0.10 per-beverage levy on sugar-sweetened beverages (SSBs) and supporting activity including beverage menu redesign, new products and establishment of a children’s health fund from levy proceeds. Methods We used an interrupted time series design to quantify changes in sales of non-alcoholic beverages 12 weeks and 6 months after implementation of the levy, using itemised electronic point of sale data. Main outcomes were number of SSBs and other non-alcoholic beverages sold per customer. Linear regression and multilevel random effects models, adjusting for seasonality and clustering, were used to investigate changes in SSB sales across all restaurants (n=37) and by tertiles of baseline restaurant SSB sales per customer. Results Compared with the prelevy period, the number of SSBs sold per customer declined by 11.0% (−17.3% to −4.3%) at 12 weeks and 9.3% (−15.2% to −3.2%) at 6 months. For non-levied beverages, sales per customer of children’s fruit juice declined by 34.7% (−55.3% to −4.3%) at 12 weeks and 9.9% (−16.8% to −2.4%) at 6 months. At 6 months, sales per customer of fruit juice increased by 21.8% (14.0% to 30.2%) but sales of diet cola (−7.3%; −11.7% to −2.8%) and bottled waters (−6.5%; −11.0% to −1.7%) declined. Changes in sales were only observed in restaurants in the medium and high tertiles of baseline SSB sales per customer. Conclusions Introduction of a £0.10 levy on SSBs alongside complementary activities is associated with declines in SSB sales per customer in the short and medium term, particularly in restaurants with higher baseline sales of SSBs.
A new clinical decision support tool for improving the adequacy of anticoagulant therapy and reducing the incidence of stroke in nonvalvular atrial fibrillation

Introduction: Atrial fibrillation (AF) is the most common cardiac arrhythmia and increases the risk of ischemic stroke 4 to 5-fold. The first choice of anticoagulant therapy (AT) is the vitamin K antagonist (VKA). Contraindication to VKA or poor control of the International Normalized Ratio leads to the administration of direct-acting oral anticoagulants. There is a trend toward inadequate AT in nonvalvular AF (NVAF) patients. Aim: To evaluate the impact of the implementation of a decision support tool linked to the digital clinical history on the adequacy of AT, the incidence of complications, and the mortality in patients with NVAF in primary care centers (PCCs) of the Catalan Institute of Health (ICS). Methods and analysis: Randomized clinical trial in 287 PCCs, formed by 2 groups (intervention and control). Population: patients controlled in PCCs, diagnosed with NVAF 1 year before the implementation of the decision support tool and with VKA treatment over a minimum of 1 year. A simple randomization method will be performed at a sector level. The decision support tool will be available for 1 year. The time in therapeutic range (TTR) will be available in the digital clinical history only to professionals of the intervention group. The information system for primary care research development database will be used for the data extraction. Statistical analysis will be done at 3 time points: before the implementation of the tool, at 1 year, and at 2 years after the beginning of the intervention. Multilevel (patient and professional levels) logistic regression models will be used to estimate the effect of the intervention. Ethics and dissemination: This study protocol was approved by the Ethical Committee of Clinical Investigation of the Institut Universitari d’Investigació en Atenció Primària Jordi Gol (code P17/091). Articles will be published in scientific journals. Trial registration: Clinical-Trials.gov: NCT03367325.
Efecto del pre-procesamiento en la detección automática de plagio para PAN 2014 y PAN 2015

Resumen. Dentro de la detección automática de plagio, el alineamiento de texto en [1] lo define como el descubrimiento de fragmentos similares de texto entre dos documentos. La cual puede utilizarse en: detección de plagio, identificación de autoría, detección de reúso de texto, recuperación de información, entre muchas otras. El pre-procesamiento consta de diversas técnicas que se aplica en la mayoría de las tareas del Procesamiento del Lenguaje Natural (PLN), en este caso, las heurísticas presentadas son tomadas de los trabajos [1] y [2] de las mejores participaciones en la competencia internacional de detección automática de plagio PAN 2014 y PAN 2015 en la sub-tarea alineamiento de texto monolingüe, con la finalidad de conocer el efecto que tiene la eliminación de stopwords y el uso o no de stemming en las heurísticas antes mencionadas, que son técnicas dentro del pre-procesamiento.
Comprehensive Mapping of Common Immunodominant Epitopes in the West Nile Virus Nonstructural Protein 1 Recognized by Avian Antibody Responses

West Nile virus (WNV) is a mosquito-borne flavivirus that primarily infects birds but occasionally infects humans and horses. Certain species of birds, including crows, house sparrows, geese, blue jays and ravens, are considered highly susceptible hosts to WNV. The nonstructural protein 1 (NS1) of WNV can elicit protective immune responses, including NS1-reactive antibodies, during infection of animals. The antigenicity of NS1 suggests that NS1-reactive antibodies could provide a basis for serological diagnostic reagents. To further define serological reagents for diagnostic use, the antigenic sites in NS1 that are targeted by host immune responses need to be identified and the potential diagnostic value of individual antigenic sites also needs to be defined. The present study describes comprehensive mapping of common immunodominant linear B-cell epitopes in the WNV NS1 using avian WNV NS1 antisera. We screened antisera from chickens, ducks and geese immunized with purified NS1 for reactivity against 35 partially overlapping peptides covering the entire WNV NS1. This study identified twelve, nine and six peptide epitopes recognized by chicken, duck and goose antibody responses, respectively. Three epitopes (NS1-3, 14 and 24) were recognized by antibodies elicited by immunization in all three avian species tested. We also found that NS1-3 and 24 were WNV-specific epitopes, whereas the NS1-14 epitope was conserved among the Japanese encephalitis virus (JEV) serocomplex viruses based on the reactivity of avian WNV NS1 antisera against polypeptides derived from the NS1 sequences of viruses of the JEV serocomplex. Further analysis showed that the three common polypeptide epitopes were not recognized by antibodies in Avian Influenza Virus (AIV), Newcastle Disease Virus (NDV), Duck Plague Virus (DPV) and Goose Parvovirus (GPV) antisera. The knowledge and reagents generated in this study have potential applications in differential diagnostic approaches and subunit vaccines development for WNV and other viruses of the JEV serocomplex.
Peripheral Autoantigen Induces Regulatory T Cells that Prevent Autoimmunity

Previous studies have shown that autoimmune thyroiditis can be induced in normal laboratory rats after thymectomy and split dose γ-irradiation. Development of disease can be prevented by reconstitution of PVG rats shortly after their final irradiation with either peripheral CD4+CD45RC− T cells or CD4+CD8− thymocytes from syngeneic donors. Although the activity of both populations is known to depend on the activities of endogenously produced interleukin 4 and transforming growth factor β, implying a common mechanism, the issue of antigen specificity of the cells involved has not yet been addressed. In this study, we show that the regulatory T cells that prevent autoimmune thyroiditis are generated in vivo only when the relevant autoantigen is also present. Peripheral CD4+ T cells, from rats whose thyroids were ablated in utero by treatment with 131I, were unable to prevent disease development upon adoptive transfer into thymectomized and irradiated recipients. This regulatory deficit is specific for thyroid autoimmunity, since CD4+ T cells from 131I-treated PVG.RT1u rats were as effective as those from normal donors at preventing diabetes in thymectomized and irradiated PVG.RT1u rats. Significantly, in contrast to the peripheral CD4+ T cells, CD4+CD8− thymocytes from 131I-treated PVG donors were still able to prevent thyroiditis upon adoptive transfer. Taken together, these data indicate that it is the peripheral autoantigen itself that stimulates the generation of the appropriate regulatory cells from thymic emigrant precursors.
Development of the 25-item National Eye Institute Visual Function Questionnaire.

OBJECTIVE To develop and test the psychometric properties of a 25-item version of the National Eye Institute Visual Function Questionnaire (NEI VFQ-25). DESIGN Prospective observational cohort study of persons with 1 of 5 chronic eye diseases or low vision who were scheduled for nonurgent visits in ophthalmology practices and a reference sample of persons without eye disease. SETTING Eleven university-based ophthalmology practices and the NEI Clinical Center. PATIENTS Eligible participants had to have 1 of the following eye conditions: age-related cataracts, age-related macular degeneration, diabetic retinopathy, primary open-angle glaucoma, cytomegalovirus retinitis, or low vision from any cause. Seven of the 12 sites also enrolled persons in a reference sample. Reference sample participants had no evidence of underlying eye disease but were scheduled for either screening eye examinations or correction of refractive error. All eligible persons had to be 21 years or older, English speaking, and cognitively able to give informed consent and participate in a health status interview. MEASUREMENTS AND MAIN RESULTS To provide the data needed to create the NEI VFQ-25, all subjects completed an interview that included the 51-item NEI VFQ. Estimates of internal consistency indicate that the subscales of the NEI VFQ-25 are reliable. The validity of the NEI VFQ-25 is supported by high correlations between the short- and long-form versions of the measure, observed between-group differences in scores for persons with different eye diseases of varying severity, and the moderate-to-high correlations between the NEI VFQ-25 subscales that have the most to do with central vision and measured visual acuity. CONCLUSIONS The reliability and validity of the NEI VFQ-25 are comparable to those of the 51-item NEI VFQ field test version of the survey. This shorter version will be more feasible in settings such as clinical trials where interview length is a critical consideration. In addition, preliminary analyses indicate that the psychometric properties of the NEI VFQ-25 are robust for the eye conditions studied; this suggests that the measure will provide reproducible and valid data when used across multiple conditions of varying severity.
FACTS: A Framework for Fault-Tolerant Composition of Transactional Web Services

Along with the standardization of Web services composition language and the widespread acceptance of composition technologies, Web services composition is becoming an efficient and cost-effective way to develop modern business applications. As Web services are inherently unreliable, how to deliver reliable Web services composition over unreliable Web services is a significant and challenging problem. In this paper, we propose FACTS, a framework for fault-tolerant composition of transactional Web services. We identify a set of high-level exception handling strategies and a new taxonomy of transactional Web services to devise a fault-tolerant mechanism that combines exception handling and transaction techniques. We also devise a specification module and a verification module to assist service designers to construct fault-handling logic conveniently and correctly. Furthermore, we design an implementation module to automatically implement fault-handling logic in WS-BPEL. A case study demonstrates the viability of our framework and experimental results show that FACTS can improve fault tolerance of composite services with acceptable overheads.
Controlled dimerization of insulin-like growth factor-1 and insulin receptors reveals shared and distinct activities of holo and hybrid receptors

Breast cancer development and progression are influenced by insulin-like growth factor receptor 1 (IGF1R) and insulin receptor (InsR) signaling, which drive cancer phenotypes such as cell growth, proliferation, and migration. IGF1R and InsR form IGF1R/InsR hybrid receptors (HybRs) consisting of one molecule of IGF1R and one molecule of InsR. The specific signaling and functions of HybR are largely unknown, as HybR is activated by both IGF1 and insulin, and no cellular system expresses HybR in the absence of holo-IGF1R or holo-InsR. Here we studied the role of HybR by constructing inducible chimeric receptors and compared HybR signaling with that of holo-IGF1R and holo-InsR. We cloned chemically inducible chimeric IGF1R and InsR constructs consisting of the extracellular domains of the p75 nerve growth factor receptor fused to the intracellular β subunit of IGF1R or InsR and a dimerization domain. Dimerization with the drugs AP20187 or AP21967 allowed specific and independent activation of holo-IGF1R, holo-InsR, or HybR, resulting in activation of the PI3K pathway. Holo-IGF1R and HybR both promoted cell proliferation and glucose uptake, whereas holo-InsR only promoted glucose uptake, and only holo-IGF1R showed anti-apoptotic effects. We also found that the three receptors differentially regulated gene expression: holo-IGF1R and HybR up-regulated EGR3; holo-InsR specifically down-regulated JUN and BCL2L1; holo-InsR down-regulated but HybR up-regulated HK2; and HybR specifically up-regulated FHL2, ITGA6, and PCK2. Our findings suggest that, when expressed and activated in mammary epithelial cells, HybR acts in a manner similar to IGF1R and support further investigation of the role of HybR in breast cancer.
Electromagnetically Induced Transparency in a Silicon Self-Coupled Optical Waveguide

We investigate the resonance property of a self-coupled optical waveguide (SCOW) with four coupling points. Under a special condition that the two outer couplers are in weak coupling and the two inner couplers are in strong coupling, an implicit standing-wave resonance mode is formed inside the SCOW structure. As the resonance is feedback coupled via an S-shape bus waveguide, electromagnetically induced transparency (EIT)-like resonance features are observed in the output transmission spectrum. The SCOW resonator is analyzed using the coupled mode theory and finite-difference time-domain simulation. The device is experimentally demonstrated on the silicon-on-insulator platform. The measurement results overall agree well with the theoretical calculation. The EIT-like peak can be tuned by a thermo-optic phase shifter made of a NIN-type silicon resistor integrated in the feedback waveguide. The results point to new ways of creating on-chip optical analog of the EIT phenomenon that can be utilized for various optical signal processing applications.
Detection of Behavior Change in People with Depression

Major Depressive Disorder (MDD) is the most common mental health disorder and remains a leading cause of disability and lost productivity with huge costs for society. MDD has high rates of relapse and recurrence, and it has strong correlations with feelings of low social support and disrupted sleep. However, MDD is also commonly misdiagnosed by primary care providers, which leads to delayed treatment and unnecessary suffering. Changes in technology now make it possible to cheaply and effectively monitor social and sleep behaviors, offering the potential of early detection of the onset of MDD. We report on the design of Big Black Dog, a smartphone-based system for gathering data about social and sleep behaviors. We also report on the results of a pilot evaluation to understand the feasibility of gathering and using data from smartphones for inferring the onset of depression.
Distributed Seeking of Nash Equilibria With Applications to Mobile Sensor Networks

We consider the problem of distributed convergence to a Nash equilibrium in a noncooperative game where the players generate their actions based only on online measurements of their individual cost functions, corrupted with additive measurement noise. Exact analytical forms and/or parameters of the cost functions, as well as the current actions of the players may be unknown. Additionally, the players' actions are subject to linear dynamic constraints. We propose an algorithm based on discrete-time stochastic extremum seeking using sinusoidal perturbations and prove its almost sure convergence to a Nash equilibrium. We show how the proposed algorithm can be applied to solving coordination problems in mobile sensor networks, where motion dynamics of the players can be modeled as: 1) single integrators (velocity-actuated vehicles), 2) double integrators (force-actuated vehicles), and 3) unicycles (a kinematic model with nonholonomic constraints). Examples are given in which the cost functions are selected such that the problems of connectivity control, formation control, rendezvous and coverage control are solved in an adaptive and distributed way. The methodology is illustrated through simulations.
Unsupervised aspect level sentiment analysis using Ant Clustering and Self-organizing Maps

We present an approach for aspect based opinion mining, which uses an unsupervised neural network as the opinion classifier. To identify the aspects, we use the Ant Clustering Algorithm. It is able to group similar sentences into clusters and then to extract from each cluster one different aspect of the opinion target object. The neural model used for sentiment analysis is an extension of the Growing Hierarchical Self-organizing Maps. In our aspect based sentiment analysis method, we assume that different sentences in a product review refer to the different aspects of the reviewed product. We use the Growing Hierarchical Self-organizing Maps in order to classify the review sentences. This way we determine whether the various aspects of the target entity (e.g. a product) are opinionated with positive or negative sentiment in the review sentences. We classify the sentences against a domain specific tree-like ontological taxonomy of aspects and (positive/ negative) opinions associated with the aspects. As a consequence, we really classify the sentiment polarity about the different aspects of the target object, as expressed in the sentences. Moreover, being based on a classification against an ontology of aspects, our approach is semantic oriented, where the aspects themselves are also defined semantically. The approach proposed has been tested on a collection of product reviews, more exactly reviews about photo cameras.
Protein Interaction and Na/K-ATPase-Mediated Signal Transduction

The Na/K-ATPase (NKA), or Na pump, is a member of the P-type ATPase superfamily. In addition to pumping ions across cell membrane, it is engaged in assembly of multiple protein complexes in the plasma membrane. This assembly allows NKA to perform many non-pumping functions including signal transduction that are important for animal physiology and disease progression. This article will focus on the role of protein interaction in NKA-mediated signal transduction, and its potential utility as target for developing new therapeutics.
The Management of Peri-implant Breakdown Around Functioning Osseointegrated Dental Implants.

Peri-implant tissue breakdown can be the result of microbial action as well as of biomechanical and occlusal overload. The long-term goal of the treatment of peri-implant breakdown is to arrest the progression of the disease and to achieve a maintainable site for the patient. Peri-implant bony defects around functioning implants can be treated with either non-surgical or surgical (resective or regenerative) techniques. Bone regeneration is possible in selected peri-implant bony defects of functioning implants if appropriate surgical techniques are utilized and the etiologic cause is eradicated. J Periodontol 1993; 64:1176-1183.
How Can Researchers Tell Whether Someone Has a False Memory? Coding Strategies in Autobiographical False-Memory Research: A Reply to Wade, Garry, and Pezdek (2018)

Research on autobiographical false memories requires a method of classifying memories. But how do researchers know whether to classify a memory as false? Recently, a “mega-analysis” of false-memory studies was conducted in an attempt to apply a universal coding strategy. It was published by a number of senior researchers in the field of false memory (Scoboria et al., 2017) and involved the recoding and reanalysis of the transcripts from eight false-memory studies. According to Scoboria et al., a mega-analysis was conducted rather than a more typical meta-analysis because “given the variation in coding schemes across studies, meta-analysis is not an appropriate approach for combining data from memory implantation studies” (p. 149). This shows that coding strategies vary widely in false-memory studies. One such variation is the topic of a recent Commentary by Wade, Garry, and Pezdek (2018), who prepared a critique of the coding strategy applied in Shaw and Porter (2015). Wade et al. criticized Shaw and Porter for not differentiating between false memories and false beliefs. Further, they reported evidence that when this distinction was made, the percentage of participants classified as having false memories was considerably lower than the percentage reported by Shaw and Porter. Two methodological disagreements are apparent from this debate. The first is disagreement as to the operational and theoretical definition of false memory. The second involves the particular methodology by which participants should be classified as having false memories. I will address both of these disagreements in turn.
Improvement of Disease Prediction and Modeling through the Use of Meteorological Ensembles: Human Plague in Uganda

Climate and weather influence the occurrence, distribution, and incidence of infectious diseases, particularly those caused by vector-borne or zoonotic pathogens. Thus, models based on meteorological data have helped predict when and where human cases are most likely to occur. Such knowledge aids in targeting limited prevention and control resources and may ultimately reduce the burden of diseases. Paradoxically, localities where such models could yield the greatest benefits, such as tropical regions where morbidity and mortality caused by vector-borne diseases is greatest, often lack high-quality in situ local meteorological data. Satellite- and model-based gridded climate datasets can be used to approximate local meteorological conditions in data-sparse regions, however their accuracy varies. Here we investigate how the selection of a particular dataset can influence the outcomes of disease forecasting models. Our model system focuses on plague (Yersinia pestis infection) in the West Nile region of Uganda. The majority of recent human cases have been reported from East Africa and Madagascar, where meteorological observations are sparse and topography yields complex weather patterns. Using an ensemble of meteorological datasets and model-averaging techniques we find that the number of suspected cases in the West Nile region was negatively associated with dry season rainfall (December-February) and positively with rainfall prior to the plague season. We demonstrate that ensembles of available meteorological datasets can be used to quantify climatic uncertainty and minimize its impacts on infectious disease models. These methods are particularly valuable in regions with sparse observational networks and high morbidity and mortality from vector-borne diseases.