Miracle-dz/UniFAR-FTUs huggingface dataset:
The Variability of Outcomes Used in Efficacy and Effectiveness Trials of Alcohol Brief Interventions: A Systematic Review.

OBJECTIVE The purpose of this study was to characterize recent alcohol brief intervention (ABI) efficacy and effectiveness trials, summarize outcomes, and show how variability in outcomes and reporting compromises the evidence base. METHOD A systematic review and narrative synthesis of articles from 10 databases were undertaken (January 2000-November 2017); study selection represented recent, readily available publications. The National Institute of Care Excellence (NICE) Public Health Guideline 24 (Alcohol use disorders: prevention) informed ABI definitions. The review was conducted using Centre for Reviews and Dissemination (CRD) guidance and pre-registered on PROSPERO (CRD42016047185). Seven a priori specified domains were used to classify outcomes: biomarkers, alcohol-related outcomes, economic factors/resource use, health measures, life impact, intervention factors, and psychological/behavioral factors. RESULTS The search identified 405 trials from 401 eligible papers. In 405 trials, 2,641 separate outcomes were measured in approximately 1,560 different ways. The most common outcomes used were the number of drinks consumed in a week and frequency of heavy episodic drinking. Biomarkers were least frequently used. The most common primary outcome was weekly drinks. By trial type, the most frequent outcome in efficacy and effectiveness trials was frequency of heavy drinking. CONCLUSIONS Consumption outcomes predominated; however, no single outcome was found in all trials. This comprehensive outcome map and methodological detail on ABI effectiveness and efficacy trials can aid decision making in future trials. There was a diversity of instruments, time points, and outcome descriptions in methods and results sections. Compliance with reporting guidance would support data synthesis and improve trial quality. This review establishes the need for a core outcome set (COS)/minimum data standard and supports the Outcome Reporting in Brief Interventions: Alcohol initiative (ORBITAL) to improve standards in the ABI field through a COS for effectiveness and efficacy randomized trials.
Rheological and kinetic studies of low density polyetyhlene (LDPE) – chitosan biocomposite film

The amount of plastic waste has always increased over the years and caused many problems in the environment because of its poor degradation rate characteristics. Recently, the interest in biodegradable polymer to substitute these synthetic plastic materials has been increased. Biocomposite materials have better biodegradability rate and can be utilized for several applications, such as packaging, agriculture, biomedical and healthcare. Chitosan as natural polymer that has good biodegradability can be combined with low density polyethylene (LDPE) to improve its mechanical properties. The LDPE-chitosan biocomposites were made by mixing chitosan and LDPE with maleic anhydride as compatibilizer and perbutyl Z as an initiator. In this study, the decomposition kinetic and thermal behavior of low density polyethylene (LDPE)-chitosan biocomposites were investigated by thermogravimetric analysis (TGA). The residual weight of biocomposites after decomposition process was analyzed. The samples were heated in the range of temperature from 25 °C to 500 °C and at different heating rates of 5, 10, 15, 20 °C/min, respectively. The result shows that activation energy decreased along with the increasing of chitosan concentration. This result indicates that the LDPE-chitosan biocomposite is a promising candidate for substitution of synthetic plastic.
The Development and Validation of the Practicing Faith Survey

We introduce a new instrument, called the Practicing Faith Survey (PFS), to assess faith formation among students in K-12 Christian schools. We begin by describing the conceptual and theological background of the PFS, underscoring the ways it differs from existing instruments of faith formation because of its particular focus on Christian practice within the context of learning and the vocation of the student. We then describe the procedures behind developing the PFS and its five domains: Intellectual, Relational, Introspective, Beneficent, and Formational Practices. We then provide evidence of validity and reliability based on a pilot study that involved 1,200 US and Australian Christian school students in fifth through 12th grades. We conclude with recommendations about how Christian school educators, students, and parents can use the PFS in practice.
Analysis of multi‐input multi‐output transactions in the Bitcoin network

Distinct transactions among different and unrelated users are combined together to create a single Bitcoin transaction (mixing transaction) to obfuscate the relationships among the actual participants (more specifically, the wallet addresses used for the transactions). We consider multi‐input multi‐output transactions with at least two inputs and three outputs as proxy, to analyze four characteristic periods of ∼50 days each, representing periods before the introduction of mixing, in its early days, during its growth, and after the volume of such multi‐input multi‐output transactions became more or less stabile. Structural properties and characteristics of the transaction and wallet address networks are computed and compared, through standard tools, but also via the introduction of two novel techniques that provide indicators of mixing‐like behaviors: (1) an entropy characterization to detect abnormally uniform inputs and/or outputs and (2) a connected component analysis of subgraphs formed by only multi‐input multi‐output transactions (showing cascades of such transactions). The contributions of this exploratory Bitcoin network analysis paper can thus be seen as two‐fold. At a macroscopic level, the growth and stabilization periods are shown to stand out with respect to most considered metrics, while at a microscopic level, chains of multi‐input multi‐output transactions, and transactions with outlier behavior in terms of input/output entropies are identified for further investigation.
RETRACTED ARTICLE: A Robust Face Emotion Recognition Approach through Optimized SIFT Features and Adaptive Deep Belief Neural Network

We, the Editor and Publisher of Journal of Applied Security Research, have retracted the following article: Yenumaladoddi Jayasimha & R. Venkata Siva Reddy, A Robust Face Emotion Recognition Approach through Optimized SIFT Features and Adaptive Deep Belief Neural Network, Journal of Applied Security Research, 2019, DOI: 10.1080/19361610.2019. 1656471. This article contains extensive and continuous content similarity across all sections with the previously published article: Yenumaladoddi Jayasimha & R. Venkata Siva Reddy (2019) A robust face emotion recognition approach through optimized SIFT features and adaptive deep belief neural network, Intelligent Design Technologies, 13.3, 379–390. DOI: 10.3233/IDT-190022. The substantial similarity between the articles is not acknowledged. Following a request by the corresponding author to withdraw this article from Journal of Applied Security research, we discovered the previously published article. We contacted the corresponding author multiple times but have received no response. Therefore, we have determined that retracting this article is the best course of action. We have been informed in our decision-making by our policy on publishing ethics and integrity and the COPE guidelines on retractions. The retracted article will remain online to maintain the scholarly record, but it will be digitally watermarked on each page as “Retracted. ”
El Niño forecasting based on the global atmospheric oscillation

The predictability of El Niño and La Niña is investigated. In this case, the recently discovered so‐called global atmospheric oscillation (GAO) is considered. Assuming GAO to be the main mode of short‐term climatic variability, this study defines an index that characterizes the dynamics and relationships of the extratropical components of the GAO and El Niño – Southern Oscillation (ENSO). Due to the general propagation of the GAO's spatial structure from west to east, another index – predictor of ENSO is defined. The cross‐wavelet analysis between both of these indices and the Oceanic Niño Index (ONI) is performed. This analysis reveals a range of timescales within which the closest relationship between the GAO and ONI takes place. Using this relationship, it is possible to predict El Niño and La Niña with a lead‐time of approximately 12 months.
A Realist Perspective on Bayesian Cognitive Science

Bayesian cognitive science constructs detailed mathematical models of perception, motor control, and many other psychological domains. The models postulate mental activity that approximately conforms to Bayesian norms. Often, the postulated activity is subpersonal. I defend a realist stance towards Bayesian cognitive science. Bayesian models vary widely in their scientific merit, but many are well-confirmed and explanatorily superior to non-Bayesian alternatives. We have good reason to believe that these models are approximately true. I argue that realism about Bayesian cognitive science offers significant explanatory advantages over a rival instrumentalist view, on which Bayesian models are predictive tools that we should not construe even semi-literally. §1. Bayesian modeling of the mind Bayesian decision theory is a mathematical framework for modeling inference and decision-making under uncertain conditions. It has two central notions: subjective probability (or credence), which reflects the degree to which an agent believes that a state of affairs obtains; and utility, which reflects the degree to which an agent desires an outcome. At the heart of the framework lie norms governing credence and utility: The probability calculus axioms constrain how to allocate credence at any moment. Conditionalization dictates how to reallocate credence in light of new evidence.
From Off-Label to Repurposed Drug in Non-Oncological Rare Diseases: Definition and State of the Art in Selected EU Countries

Introduction Almost 8,000 rare diseases exist worldwide, affecting approximately 350 million people. Nevertheless, only 5% receive a specific authorized or licensed treatment. The need for effective and rapidly available therapies is still unmet for many patients. Objective The objective is to define repurposing versus off-label drugs, and to evaluate pathways of repurposed drugs for rare non-oncological diseases in Italy, France, England, and Spain (the EU4 countries). Methods This original paper is based on 3 research activities: (i) a nonsystematic literature research; (ii) a questionnaire-based survey to regulatory experts; and (iii) research on approval timelines and therapy prices of repurposed non-oncology orphan drugs. Official approval dates in England are not available if the National Institute for Health and Care Excellence does not appraise the products. Results Only France provides a specific adaptive pathway from off-label to repurposed drugs. Pricing and reimbursement assessment for the drug samples varied across the EU4 countries: time-to-market for repurposed drugs versus new drugs is longer in all analyzed countries; that is, 979 days versus 462 days in Italy, 502 days versus 350 days in France, and 624 versus 378 days in Spain. Repurposed drugs have higher success rates from development to approval than novel drugs (30% vs. 11%). Small- and medium-sized enterprises owned 9 of 12 repurposed non-oncology orphan drugs, of which only 4 were reimbursed in all EU4 countries. Prices were more homogeneous across EU4 although the reimbursement rates were different. Conclusions Drug repurposing represents a great opportunity to treat rare non-oncological diseases. However, a more homogenous assessment across EU4 could ensure reimbursement and prices high enough to reward organizations investing in this field.
The complete chloroplast genome of Pertya phylicoides (Asteraceae, Pertyeae): a shurby endemic species from China

Abstract This study was the first report about complete chloroplast genome of Pertya phylicoides (Asteraceae: Pertyeae), a critically shurby plant. The complete chloroplast genome of Pertya phylicoides was 153,379 bp in length and a typical circular structure, which comprises a pair of inverted repeat (IR) region of 25,191 bp divided by a large single-copy (LSC) region of 84,535 bp and a small single-copy (SSC) region of 18,462 bp. The general GC content was 37.6% in the whole sequence, whereas corresponding values of 35.6%, 31.2%, and 43.1% in the LSC, SSC, and IR regions, respectively. The whole genome contained 113 unique genes, including 79 protein-coding genes, 4 ribosomal RNA genes, and 30 tRNA genes. The phylogenetic hypotheses obtained based on the analyses of 21 cp genomes indicates Pertya phylicoides was supported as a sister group to the tribe Carduoideae.
A Study on the Correlation between Employment Status and Quality of Life in Secondary School Children

Abstract This descriptive study aimed to investigate the correlation between employment status and quality oflife in secondary school children. The study sample included 450 students aged between 13-15 years, attendingsecondary schools in Fethiye, Mugla. The Sociodemographic Data Form and Pediatric Quality of Life InventoryAdolescent Form were used for data collection. The study results indicated that students who were not employedhad higher levels of academic success. Employed students had lower scores of psychosocial health and schoolfunctionality subdimensions in comparison to those who were not employed, which was found to be statisticallysignificant. As regards to durations of employment, there was also a statistically significant difference betweenphysical health, psychosocial health, social functionality, school functionality scores and total score averages Itwas found out the students with lower income levels had lower levels of quality of life.
The United States of America’s interlocked information industry: An examination into seven U.S. media sectors’ boards of directors

ABSTRACT This research explores the interfirm interlock networks that currently exist among publicly traded media conglomerates operating in the United States of America. Directorship information was gathered from annual reports and definitive proxy reports filed with the U.S. Securities and Exchange Commission for 68 media conglomerates across seven media sectors for year ending 2018. This investigation applies social resource theory to assess the social networks formed by interfirm interlocks among media conglomerates and how such network structures address environmental uncertainty. Results indicate that not all alliances are mutually beneficial and those that are more resource-dependent endure negative cooptation effects. Moreover, today’s financial interlocks look very different than they did at the turn of the century. This research discusses how these changes in interfirm interlocks have resulted in directorship wars. Practical implications are discussed.
Supervised machine learning in multiple sclerosis: applications to clinically isolated syndromes

Multiple sclerosis (MS) is an inflammatory, demyelinating disease that can cause various neurological symptoms. The first episode of this disease is called a clinically isolated syndrome (CIS) and leads to the diagnosis of MS in the majority of patients in the long-term. Fast conversion from CIS to MS is associated with higher disability and more severe disease progression so that it is of high clinical interest to identify risk patients that will convert to MS within a short time. Several risk factors for conversion have been identified but they can only be applied on cohort levels. In this thesis we provide an overview of supervised machine learning approaches that can be used to distinguish individual CIS-stable patients from those who will experience a second attack within one to five years and consequently will be diagnosed with clinically definite MS. This classification is based on information available at baseline derived from routine MRI scans and complemented by clinical information such as lesion masks, age, gender, disability and CIS type of onset. We introduce the classification landscape, an overview of supervised classification studies with respect to their method and task complexity, and show that our experiments cover a large range of feature complexities in this landscape for the rather complex task of outcome prediction in CIS patients. We show that low-level voxel-based information such as tissue density of grey and white matter are not informative and lead to inconclusive results, whereas the introduction of high-level features such as lesion load, age, gender or disability improves accuracies to 71.4 % and 68 % at one- and three-year follow-up respectively in a single-centre data set. Finally, we propose a recursive feature elimination method that is able to identify specific regions that are relevant with respect to disease progression in MS and achieves accuracies of 73.9 % and 74.3 % at one- and three-year follow-up respectively even in a multi-centre setting.
The Role of Myofascial Pain and Fibromyalgia on Pain and Disability of the Computer Users with Cumulative Trauma Disorders

Abstract Objectives: We hypothesized that Cumulative Trauma Disorders (CTD) is common in computer workers and computer workers with CTD will have more FFS and MPS than those without. We further hypothesized that those with CTD and FS or MPS will have greater disability than those without. Methods: 170 computer users and 55 age, sex and body mass index matched healthy controls were included in the study. Pain assessment was made by visual analog scale. The presence of FS was evaluated using 2010 ACR classification criteria. The existence of MPS was evaluated using specific diagnostic criteria. In order to measure the general disability levels of the participants, Quick DASH Score (QDS) was used, besides to measure their disability levels during work, Quick DASH Work Score (QDWS) was used. Results: 114 (69%) of the computer users had CTD. The presence of MPS and FS in CTD group was significantly higher than the non-CTD group and controls (p < 0.001, p < 0.001). QDS and QDWS were significantly higher in CTD group (p < 0.01–p < 0.05). Statistically significant increases were found in pain score, QDS and QDWS in CTD group with FS and MPS (p < 0.05–p < 0.001). Conclusions: We observed that CTD is common in computer users and determined that the existence of fibromyalgia and MPS are found to be serious risk factors for disability in computer users with CTD. We believe that treatment of FS and MPS have great importance in the treatment and more importantly in the prevention of this clinic entity which can cause serious pain, disability and workforce loss.
A SYSTEMATIC REVIEW OF KAP-O FRAMEWORK FOR DIABETES

A majority of diabetes self-management programs have been shown to improve knowledge, attitude, practice, and health care outcomes. However, in the literature the underlying causal mechanisms for the improvement attributable to health education interventions have not been systematically explored, especially to show how diabetes educational intervention may affect diabetes care outcomes. The purpose of this scientific review is to identify the underlying causal mechanisms responsible for improved knowledge, attitude, preventive practice and outcomes, so that educational interventions can be tailored efficiently and effectively to patients who are most likely to benefit from self-care management. The review examines multiple causes of the variation in each of the clinical or health outcomes such as glycated hemoglobin (A1C), low-density lipoprotein cholesterol (LDLC), functional capacity (FC), and poor perceived health (PPH). We include behavioral theories relevant to changing diabetes patients’ behaviors: 1) the health belief model, 2) the theory of planned behavior, 3) social cognitive theory, 4) the trans-theoretical model of stages of change, and 5) the patient empowerment model. These theories seek to identify the determinants or predictors of health behavior and change. Future research on diabetes care could be benefited from employing information technology and self-monitoring devices.
Effect of GHRM Practices on Work Performance: The Mediatory Role of Green Lifestyle

Purpose–This research seeks to determine the effect of Green Human Resource Management (GHRM) on work performance by the mediatory role of the green lifestyle of staff from different sectors in Pakistan and possible engorgement of GHRM to the lifestyle of staff. Design/Methodology/Approach–Structural equation Model (SEM) and exploratory factor assessment were used to examine the relation of factors. A survey was allocated to three hundred (300) participants who were randomly chosen for this research from different private sectors. Findings–This research demonstrates that the GHRM application affects the lifestyle of an employee as well as the efficiency of their work. It indicates that by focusing on GHRM, organizations can contribute to the setting and retain the excellent performance of staff as well. Research Limitations/Implications–Taking into account the location of the research; it was limited to Pakistani sectors. The research was also restricted to sectors that are certified ISO14001, aimed at that certification. Also, the surveys have not been disseminated by age groups and gender. Therefore, researchers are enthusiastic to further investigate the impacts of these variables on other factors. Practical Implications–This research may promote the use of GHRM methods in the workplace by human resources professionals to motivate staff to engage in utilizing available recourses smartly and effectively.
Evaluating the Stability of Double Emulsions—A Review of the Measurement Techniques for the Systematic Investigation of Instability Mechanisms

Double emulsions are very promising for various applications in pharmaceutics, cosmetics, and food. Despite lots of published research, only a few products have successfully been marketed due to immense stability problems. This review describes approaches on how to characterize the stability of double emulsions. The measurement methods are used to investigate the influence of the ingredients or the process on the stability, as well as of the environmental conditions during storage. The described techniques are applied either to double emulsions themselves or to model systems. The presented analysis methods are based on microscopy, rheology, light scattering, marker detection, and differential scanning calorimetry. Many methods for the characterization of double emulsions focus only on the release of the inner water phase or of a marker encapsulated therein. Analysis methods for a specific application rarely give information on the actual mechanism, leading to double emulsion breakage. In contrast, model systems such as simple emulsions, microfluidic emulsions, or single-drop experiments allow for a systematic investigation of diffusion and coalescence between the individual phases. They also give information on the order of magnitude in which they contribute to the failure of the overall system. This review gives an overview of various methods for the characterization of double emulsion stability, describing the underlying assumptions and the information gained. With this review, we intend to assist in the development of stable double emulsion-based products.