nils-herrmann/clean_scirepeval huggingface dataset:
A one year proprioceptive exercise programme reduces the incidence of falls in community dwelling elderly people: A before after non randomised intervention study.
Venue: Maturitas

The risk of falls increases with age. Balance alteration and polypharmacy are independent contributors to an increased risk of falls.  The primary aim was to assess whether a proprioceptive exercise programme reduces the incidence of falls. A secondary aim was to assess the association between drugs and falls.  This was a before after non randomised intervention study.  The study recruited independent and cognitively intact community dwelling people aged over 69 years, from December 2012 to May 2014.  The intervention was done by a nurse and consisted of a monthly supervised group session of proprioceptive training for 1 year, supplemented by a home diary exercise. Daily medication was reviewed.  We included 572 subjects (63.3% women) mean age 76.1+ 3.9 years. The mean number of drugs prescribed at the start of the study was 4.7+ 3.0and 353 of the participants (61.7% were taking four or more drugs a day. The elderly who fell were more dependent in their activities of daily living (Barthel index) and their balance was worse (determined using the Tinetti scale) as were their results on a cognitive scale (the MEC) After the intervention, an increase in self perceived quality of life (EQ5D) was reported. The incidence of falls was reduced from 37.5% in the 12 months prior to the intervention to 25.7% in the 12 months after the intervention. During the follow up, beta blocker use was associated with an increased incidence of falls (OR=2.05; 95%IC: 1.24 3.39; p=0.005) In contrast, antiplatelet/anticoagulation drugs were associated with a lower risk of falls (OR=0.7; 95%IC: 0.55 0.88; p=0.003)  The proprioceptive exercise programme reduced the incidence of falls in community dwelling older people. Multiple drug use was an independent predictor of an increased risk of falls, and specific drug groups were associated with falls.
The effects of a life goal setting technique in a preventive care program for frail community dwelling older people: a cluster nonrandomized controlled trial
Venue: BMC Geriatrics

BackgroundFrailty among older people is associated with an increased risk of needing care. There have been many reports on preventive care programs for frail older people, but few have shown positive effects on disability prevention. Physical exercise programs for frail older people affect elements such as physical fitness and balance, but are less effective for disability outcomes and are not followed up in the longer term. We developed a life goal setting technique (LGST) Our objective was to determine the effect of a LGST plus standard preventive care program for community dwelling frail older people.MethodsWe used a cluster nonrandomized controlled trial with seven intervention and nine matched control groups, with baseline assessment and follow up at 3, 6, and 9 months. Participants were 176 frail older people, aged 65 years or over, living in the community in Izumi, Osaka, Japan. All participants attended regular 120 min preventive care exercise classes each week, over 3 months. They also received oral care and nutrition education. The intervention groups alone received life goal setting support. We assessed outcomes longitudinally, comparing pre intervention with follow up. The primary outcome measure was health improvement according to the Japanese Ministry of Health, Labour and Welfare's "Kihon Checklist" for assessment of frailty and quality of life (QOL) analyzed with a two way ANOVA and post test comparison. Secondary outcomes included physical functions and assessment of life goals.ResultsThe improvement on the Kihon Checklist for the intervention group was approximately 60 from baseline to 9 months follow up; the control group improved by approximately 40 The difference between groups was significant at 3 month (p 0.043) and 6 month (p 0.015) follow ups but not at 9 month (p 0.098) follow up. Analysis of QOL yielded a significant time x group interaction effect (p 0.022) The effect was significant at 3 months in the intervention group, but at no time in the control group. 3 month exercise program helped to decrease frailty and improve QOL in frail older people, and the addition of LGST increased its effectiveness. The LGST is a feasible and promising intervention for reducing risk of needing care.
Implementation of LMS algorithm for system identification
Venue: 2016 International Conference on Signal and Information Processing (IConSIP)

An adaptive filter is a digital filter that self adjusts its transfer function according to an optimizing algorithm which is most frequently Least Mean Square (LMS) algorithm. Due to the complexity of adaptive filtering most digital filters are FIR filter. There are numerous applications of adaptive filters like noise cancellations, echo cancellation, system identification, inverse system modeling, adaptive beam forming etc. In this research article, adaptive LMS algorithm has been used for unknown system identification. The system identification is a category of adaptive filtering which find its numerous applications in diverse field like communication, image processing, speech processing etc.
Clinical Profile of Dengue Fever in Children: A Study from Southern Odisha, India
Venue: Scientifica

In India, dengue epidemics are becoming more frequent (WHO, 2008) The majority of dengue viral infections are self limiting, but complications may cause high morbidity and mortality.  To assess the clinical profile of the dengue infection in children less than 14 years of age and to evaluate the outcomes of dengue fever from September 2013 to August 2015 at the Pediatric Department of Maharaja Krishna Chandra Gajapati Medical College, the largest tertiary care hospital of southern Odisha.  A total of 97 cases were classified into 84 (86.59% nonsevere and 13 (13.40% severe dengue cases. The most common age of presentation was above 11 yrs. The mean age of admission was 8.7 yrs. The most common presenting symptom was fever seen in 100% and hepatomegaly (43.8% the most common physical finding. Gastrointestinal bleeding was markedly seen in severe dengue (76.9% Elevation in aspartate transaminase (SGOT) was found in 47.42% and thrombocytopenia in 27.5% The correlation between hepatomegaly and elevated SGOT was significant (P value 0.0346) Case fatality rate (CFR) was 1.03% The mean duration of hospitalisation was 3.8 days.  In children, if symptoms like fever, pain, rashes, and vomiting are associated with hepatomegaly and elevated SGOT in context of low TPC, a strong possibility of dengue fever is present, especially in an epidemic setting. Early suspicion and effective management can reduce the severity.
On the Widely Differing Effects of Free Trade Agreements: Lessons from Twenty Years of Trade Integration

We develop a novel two stage methodology that allows us to study the empirical determinants of the ex post effects of past free trade agreements (FTAs) as well as obtain ex ante predictions for the effects of future FTAs. We first identify 908 unique estimates of the effects of FTAs on different trading pairs for the years 1986 2006. We then employ these estimates as our dependent variable in a "second stage" characterizing the heterogeneity in these effects. Interestingly, most of this heterogeneity 2/3) occurs within FTAs (rather than across different FTAs) with asymmetric effects within pairs (on exports vs. imports) also playing a important role. We offer several intuitive explanations for these variations. Even with the same agreement, FTA effects are weaker for more distant pairs and for pairs with otherwise high levels of ex ante trade frictions. The effects of new FTAs are similarly weaker for pairs with existing agreements already in place. In addition, we are able to relate asymmetries in FTA effects to each country's ability to influence the other's terms of trade. Out of sample predictions incorporating these insights enable us to predict direction specific effects of future FTAs between any pair of countries. A simulation of the general equilibrium effects of TTIP demonstrates the importance of our methods.
Shifting journalistic roles in democratic transitions: Lessons from Egypt

While in the case of the Arab Spring the focus of research and debate was very much on the role of social media in enabling political change both during the uprisings and in their immediate aftermath, the impact of traditional national mass media and journalism on framing this political change has been less addressed. In this article, we investigate the role of Egyptian journalists in shaping Egypt's complex and fast moving political transition. Based on a thematic analysis of in depth interviews and a conceptual framework building on Christians et al.'s normative roles of the media, it can be concluded that the monitorial and facilitative roles, which were prevalent in the early stages of the post Mubarak era, were quickly overturned in favor of a radical and collaborative role. Egyptian journalists working in private media thus demonized their political adversaries, mainly the Islamists, transforming this political 'other' into the ultimate enemy. At the same time, the new military regime was being revered and celebrated. This arguably contributed to further destabilize the fragile transition to democracy. It is furthermore concluded that for democracy to succeed in an Egyptian context, antagonistic political conflicts need to be transformed into agonistic ones both at the level of political culture and media culture.
Towards a cognitive learning formulation of youth anxiety: A narrative review of theory and evidence and implications for treatment.
Venue: Clinical psychology review

The tendency to disproportionately allocate attention to threat stimuli, to evaluate ambiguous or benign situations as overly threatening, and to exhibit overgeneralised and indiscriminate conditioned fear responses to threat and safe stimuli are hallmark clinical correlates of pathological anxiety. Investigation of these processes in children and adolescents suggests that anxiety related differences increase with age, and that the specific conditions under which anxious children differ from non anxious peers are poorly understood. Furthermore, research on cognitive biases and fear conditioning in anxious children and adolescents has progressed as quite distinct lines of investigation. Greater integration of key tenets from each perspective could advance knowledge and provide new directions for improving treatments. The purpose of this paper is threefold. First, we provide a qualitative review of the key principles from cognitive and conditioning theories of anxiety and the associated empirical research, including the underlying neurophysiological basis of these processes in anxious children and adolescents, in order to delineate the conditions under which anxiety specific differences in threat related cognitive biases and overgeneralised conditioned fear manifest in children and adolescents. Second, we synthesize these theoretical and empirical insights to propose a cognitive learning formulation of anxiety in children and adolescents. We propose that conditioning and cognitive factors linked to differences in engagement of underlying neural circuits across development contribute to an internal representation of a wide range of stimuli as threatening, to which anxious children and adolescents adopt maladaptive attention regulation patterns of predominantly threat monitoring or threat avoidance. These maladaptive attention regulation patterns differentiate anxious children and adolescents in terms of predominantly high cognitive distress (e.g. worry and rumination) and high behavioural avoidance respectively. Third, we consider the clinical implications of the cognitive learning formulation for understanding outcomes from current treatments and provide suggestions for improving treatment outcomes.
The I 2 R NWPU NTU Text to Speech System at Blizzard Challenge 2016

In this paper, we introduce a trajectory tiling method guided by deep neural networks (DNNs) for text to speech (TTS) which is the entry to Blizzard Challenge 2016 by I2R NWPU NTU team. We build a deep bidirectional LSTM (DBLSTM) based network to predict the phoneme level duration and frame level acoustic parameters. After the acoustic parameters are predicted, the best units are selected from the database using a trajectory tiling method. Experiments demonstrate that, under the DBLSTM framework, the context information of a phoneme extracted in text processing will help the duration prediction, while not help the acoustic modeling. The results of subjective evaluation are also discussed.
Geodesic Witten diagrams with an external spinning field

We explore AdS/CFT correspondence between geodesic Witten diagrams and conformal blocks (conformal partial waves) with an external symmetric traceless tensor field. We derive an expression for the conformal partial wave with an external spin 1 field and show that this expression is equivalent to the amplitude of the geodesic Witten diagram. We also show the equivalence by using conformal Casimir equation in embedding formalism. Furthermore, we extend the construction of the amplitude of the geodesic Witten diagram to an external arbitrary symmetric traceless tensor field. We show our construction agrees with the known result of the conformal partial waves.
Optimal market making

Market makers provide liquidity to other market participants: they propose prices at which they stand ready to buy and sell a wide variety of assets. They face a complex optimization problem with both static and dynamic components. They need indeed to propose bid and offer/ask prices in an optimal way for making money out of the difference between these two prices (their bid ask spread) Since they seldom buy and sell simultaneously, and therefore hold long and/or short inventories, they also need to mitigate the risk associated with price changes and subsequently skew their quotes dynamically. In this paper, (i) we propose a general modelling framework which generalizes (and reconciles) the various modelling approaches proposed in the literature since the publication of the seminal paper 'High frequency trading in a limit order book' by Avellaneda and Stoikov, (ii) we prove new general results on the existence and the characterization of optimal market making strategies, (iii) we obtain new closed form approximations for the optimal quotes, (iv) we extend the modelling framework to the case of multi asset market making and we obtain general closed form approximations for the optimal quotes of a multi asset market maker, and (v) we show how the model can be used in practice in the specific (and original) case of two credit indices.
SHIVA a web application for drug resistance and tropism testing in HIV
Venue: BMC Bioinformatics

BackgroundDrug resistance testing is mandatory in antiretroviral therapy in human immunodeficiency virus (HIV) infected patients for successful treatment. The emergence of resistances against antiretroviral agents remains the major obstacle in inhibition of viral replication and thus to control infection. Due to the high mutation rate the virus is able to adapt rapidly under drug pressure leading to the evolution of resistant variants and finally to therapy failure.ResultsWe developed a web service for drug resistance prediction of commonly used drugs in antiretroviral therapy, i.e. protease inhibitors (PIs) reverse transcriptase inhibitors (NRTIs and NNRTIs) and integrase inhibitors (INIs) but also for the novel drug class of maturation inhibitors. Furthermore, co receptor tropism (CCR5 or CXCR4) can be predicted as well, which is essential for treatment with entry inhibitors, such as Maraviroc. Currently, SHIVA provides 24 prediction models for several drug classes. SHIVA can be used with single RNA/DNA or amino acid sequences, but also with large amounts of next generation sequencing data and allows prediction of a user specified selection of drugs simultaneously. Prediction results are provided as clinical reports which are sent via email to the user.ConclusionsSHIVA represents a novel high performing alternative for hitherto developed drug resistance testing approaches able to process data derived from next generation sequencing technologies. SHIVA is publicly available via a user friendly web interface.
Usage of ferrocement jacketing for strengthening of damaged unreinforced masonry (URM) walls

In this paper, it is presented the usage of ferrocement jacketing technique as an effective method to improve structural performance of unreinforced masonry panels. Nine diagonal compression tests were conducted on plain, pre cracked repaired and reinforced masonry panels on six specimen with nominal dimensions of 1.2 x 1.2 x 0.25 m, built and tested in laboratory. The results of the diagonal compression tests were compared in terms of increase in shear strength, drift and the mode of failure. Additionally, finite element modelling using discrete micro modelling and non linear analyses were performed using midas FX+ for DIANA 9.6 commercial software to simulate the behavior of plain and reinforced panels. As a result, it was observed that ferrocement jacketing made a considerable improvement in shear strength and deformation capacity for both, repaired and reinforced masonry panels.
Strategically supported cooperation in dynamic games with coalition structures

The problem of strategic stability of long range cooperative agreements in dynamic games with coalition structures is investigated. Based on imputation distribution procedures, a general theoretical framework of the differential game with a coalition structure is proposed. A few assumptions about the deviation instant for a coalition are made concerning the behavior of a group of many individuals in certain dynamic environments. From these, the time consistent cooperative agreement can be strategically supported by e Nash or strong e Nash equilibria. While in games in the extensive form with perfect information, it is somewhat surprising that without the assumptions of deviation instant for a coalition, Nash or strong Nash equilibria can be constructed.
Knowledge of extraction from trained neural network by using decision tree
Venue: 2016 2nd International Conference on Science in Information Technology (ICSITech)

Inside the sets of data, hidden knowledge can be acquired by using neural network. These knowledge are described within topology, using activation function and connection weight at hidden neurons and output neurons. Is hardly to be understanding since neural networks act as a black box. The black box problem can be solved by extracting knowledge (rule) from trained neural network. Thus, the aim of this paper is to extract valuable information from trained neural networks using decision. Further, the Levenberg Marquardt algorithm was applied to training 30 networks for each datasets, using learning parameters and basis weights differences. As the number of hidden neurons increase, mean squared error and mean absolute percentage error decrease, and more time they need to deal with the dataset, that is result of investigation from neural network architectures. Decision tree induction generally performs better in knowledge extraction result with accuracy and precision level from 84.07 to 93.17 percent. The extracted rule can be used to explaining the process of the neural network systems and also can be applied in other systems like expert systems.
SolveDB: Integrating Optimization Problem Solvers Into SQL Databases
Venue: SSDBM

Many real world decision problems involve solving optimization problems based on data in an SQL database. Traditionally, solving such problems requires combining a DBMS with optimization software packages for each required class of problems (e.g. linear and constraint programming) leading to workflows that are cumbersome, complex, inefficient, and error prone. In this paper, we present SolveDB a DBMS for optimization applications. SolveDB supports solvers for different problem classes and offers seamless data management and optimization problem solving in a pure SQL based setting. This allows for much simpler and more effective solutions of database based optimization problems. SolveDB is based on the 3 level ANSI/SPARC architecture and allows formulating, solving, and analysing solutions of optimization problems using a single so called solve query. SolveDB provides (1) an SQL based syntax for optimization problems, (2) an extensible infrastructure for integrating different solvers, and (3) query optimization techniques to achieve the best execution performance and/or result quality. Extensive experiments with the PostgreSQL based implementation show that SolveDB is a versatile tool offering much higher developer productivity and order of magnitude better performance for specification complex and data intensive problems.
A JIT Compilation Based Unified SQL Query Optimization System
Venue: 2016 6th International Conference on IT Convergence and Security (ICITCS)

In memory databases are gaining attention as a solution to efficiently support SQL queries on large volume of data, as main memories are becoming cheaper and grow in size. However, their query performance is not well improved on modern hardware with faster CPUs, registers and caches due to the limitation of the classical iterator style query processing model. We propose a unified SQL query optimization system using JIT compilation of OLTP, OLAP, and Stored Procedure workloads for enhanced performance on modern hardware.
Effect of transformational leadership on strategic human resource management and firm success of Toyota's dealer in Thailand

This study investigates effect of transformational leadership on strategic human resource management and firm success of Toyota's dealer in Thailand. Following to the existing literature, transformational leadership is an origin of strategic human resource management that leads to firm success. Therefore, transformational leadership in the dimension of intellectual stimulation is important to create strategic human resource management for the success of firms. The sample of 400 Toyota's dealer businesses in Thailand and statistics used are tested by ordinary least squared regression. Furthermore, response bias, validity and reliability were examined by researcher. These results reveal that intellectual stimulation has significant positive effect on strategic human resource management. Furthermore, intellectual stimulation and inspirational motivation still have has significant relate to firm success by themselves also. Then, strategic human resource management has significant positive effect on firm success respectively. Subsequently, managerial and theoretical contributions, and suggestions for further research are presented.
A regulatory perspective on missing data in the aftermath of the NRC report.
Venue: Statistics in medicine

The issuance of a report in 2010 by the National Research Council (NRC) of the National Academy of Sciences entitled 'The Prevention and Treatment of Missing Data in Clinical Trials, commissioned by the US Food and Drug Administration, had an immediate impact on the way that statisticians and clinical researchers in both industry and regulatory agencies think about the missing data problem. We believe that there is currently great potential to improve study quality and interpretability by reducing the amount of missing data through changes in trial design and conduct and by planning and conducting analyses that better account for the missing information. Here, we describe our view on some of the recommendations in the report and suggest ways in which these recommendations can be incorporated into new or ongoing clinical trials in order to improve their chance of success.  This article is a U.S. Government work and is in the public domain in the USA.