nils-herrmann/clean_scirepeval huggingface dataset:
Observational registry of sorafenib use in clinical practice across Child Pugh subgroups: The GIDEON study.
Venue: Journal of hepatology

GIDEON (Global Investigation of therapeutic DEcisions in hepatocellular carcinoma and Of its treatment with sorafeNib) is a prospective, observational registry study evaluating the safety of sorafenib and treatment practices in hepatocellular carcinoma patients. This large global database allowed for assessment of the use and tolerability of sorafenib in patients with liver dysfunction.  Baseline characteristics and medical/treatment history were collected in patients for whom a decision to treat with sorafenib had been made. Adverse event, dosing, and outcomes data were collected during follow up.  In the overall safety population (n=3202) 1968 patients (61% had Child Pugh A status and 666 (21% had Child Pugh B. The majority of Child Pugh A (72% and Child Pugh B (70% patients received an initial sorafenib dose of 800mg, consistent with the label, and dose reduction rates were 40% and 29% respectively. The type and incidence of adverse events were generally consistent across Child Pugh subgroups. The incidence of drug related adverse events leading to discontinuation was similar between Child Pugh A and Child Pugh B patients (17% and 21% In the intent to treat population (n=3213) median overall survival (months [95% confidence interval] was longer in Child Pugh A patients (13.6 [12.8 14.7] compared with Child Pugh B patients (5.2 [4.6 6.3]  In clinical practice, the safety profile of sorafenib appeared to be consistent across Child Pugh A and Child Pugh B patients. Findings suggest sorafenib may be safely used in some Child Pugh B patients and indicate the importance of careful patient evaluation when making treatment decisions.  The GIDEON (Global Investigation of therapeutic DEcisions in hepatocellular carcinoma and Of its treatment with sorafeNib) study is a large prospective registry of patients with liver cancer who were treated with sorafenib. The aims were to evaluate the safety and tolerability of sorafenib among those in which the liver was not functioning properly. The study showed that the safety profile of sorafenib was consistent across patients with preserved liver function and those in which the liver was not functioning properly, and therefore, suggesting that sorafenib may be a valid treatment for some patients with liver impairment.
Automatic Text Classification in Information retrieval: A Survey
Venue: ICoICT 2016

Improvement in information retrieval performance relates to the accessibility, selection and management of large amounts of information on web that usually expressed as textual data and supervised machine learning approach is an important source of tool for automating information retrieval task. This paper provides a review of supervised machine learning approaches of text classification for information retrieval and present a comparative study of supervised machine learning algorithms namely Naive Bayes (NB) Support vector machine (SVM) K nearest neighbor (KNN) and decision tree (DT) We used WEKA (Weikato Environment for Knowledge Analysis) tool to evaluate these four algorithms through a series of experiments. In WEKA Sequential Minimum Optimization (SMO) represents Support vector machine (SVM) classifier, IBK represents K nearest neighbour and J48 version of Decision Tree is used. The result concludes that the performance of the algorithms depends on the characteristics of the datasets.
Entropy, topological transitivity, and dimensional properties of unique $q$ expansions

Let $M$ be a positive integer and $q \in(1,M+1] We consider expansions of real numbers in base $q$ over the alphabet {0,\ldots, M\ In particular, we study the set \mathcal{U}_{q} of real numbers with a unique $q$ expansion, and the set \mathbf{U}_q$ of corresponding sequences. It was shown in (Komornik et al, 2017 H$ which associates to each $q\in(1, M+1] the topological entropy of \mathcal{U}_q$ is a Devil's staircase. In this paper we explicitly determine the plateaus of $H$ and characterize the bifurcation set \mathcal E$ of $q$'s where the function $H$ is not locally constant. Moreover, we show that \mathcal E$ is a Cantor set of full Hausdorff dimension. We also investigate the topological transitivity of a naturally occurring subshift \mathbf{V}_q, \sigma) which has a close connection with open dynamical systems. Finally, we prove that the Hausdorff dimension and box dimension of \mathcal{U}_q$ coincide for all $q\in(1,M+1]
Determinants of Leadership Style in Big Five Personality Dimensions

This study addresses the inconsistency of contemporary literature on defining the link between leadership styles and personality traits. The plethora of literature on personality traits has culminated into symbolic big five personality dimensions but there is still a dearth of research on developing representative leadership styles despite the perennial fascination with the subject. Absence of an unequivocal model for developing representative styles in conjunction with the use of several non mutually exclusive existing leadership styles has created a discrepancy in developing a coherent link between leadership and personality. This study sums up 39 different styles of leadership into five distinct representative styles on the basis of similar theoretical underpinnings and common characteristics to explore how each of these five representative leadership style relates to personality dimensions proposed by big five model.
Initiating and utilizing shared leadership in teams: The role of leader humility, team proactive personality, and team performance capability.
Venue: The Journal of applied psychology

The present study was designed to produce novel theoretical insight regarding how leader humility and team member characteristics foster the conditions that promote shared leadership and when shared leadership relates to team effectiveness. Drawing on social information processing theory and adaptive leadership theory, we propose that leader humility facilitates shared leadership by promoting leadership claiming and leadership granting interactions among team members. We also apply dominance complementary theory to propose that team proactive personality strengthens the impact of leader humility on shared leadership. Finally, we predict that shared leadership will be most strongly related to team performance when team members have high levels of task related competence. Using a sample composed of 62 Taiwanese professional work teams, we find support for our proposed hypothesized model. The theoretical and practical implications of these results for team leadership, humility, team composition, and shared leadership are discussed.
Ensemble of deep neural networks using acoustic environment classification for statistical model based voice activity detection
Venue: Comput. Speech Lang.

In this paper, we investigate the ensemble of deep neural networks (DNNs) by using an acoustic environment classification (AEC) technique for the statistical model based voice activity detection (VAD) From an investigation of the statistical model based VAD, it is known that the traditional decision rule is based on the geometric mean of the likelihood ratio or the support vector machine (SVM) which is a shallow model with zero or one hidden layer. Since the shallow models cannot take an advantage of the diversity of the space distribution of features, in the training step, we basically build the multiple DNNs according the different noise types by employing the parameters of the statistical model based VAD algorithm. In addition, the separate DNN is designed for the AEC algorithm in order to choose the best DNN for each noise. In the on line noise aware VAD step, the AEC is first performed on a frame by frame basis using the separate DNN so the a posteriori probabilities to identify noise are obtained. Once the probabilities are achieved for each noise, the environmental knowledge is contributed to allow us to combine the speech presence probabilities which are derived from the ensemble of the DNNs trained for the individual noise. Our approach for VAD was evaluated in terms of objective measures and showed significant improvement compared to the conventional algorithm.
Nonparametric catchment clustering using the data depth function

The clustering of catchments is important for prediction in ungauged basins, model parameterization and watershed development and management. The aim of this study is to explore a new measure of similarity among catchments, using a data depth function and comparing it with catchment clustering indices based on flow and physical characteristics. A cluster analysis was performed for each similarity measure using the affinity propagation clustering algorithm. We evaluated the similarity measure based on depth depth plots (DD plots) as a basis for transferring parameter sets of a hydrological model between catchments. A case study was developed with 21 catchments in a diverse New Zealand region. Results show that clustering based on the depth depth measure is dissimilar to clustering on catchment characteristics, flow, or flow indices. A hydrological model was calibrated for the 21 catchments and the transferability of model parameters among similar catchments was tested within and between clusters defined by each clustering method. The mean model performance for parameters transferred within a group always outperformed those from outside the group. The DD plot based method was found to produce the best in group performance and second highest difference between in group and out group performance.
Long Term Sustainable Sustainability in Luxury. Where Else?

We live in a world impacted by economic growth drivers of decreasing natural resources and increasing population. A shift toward a sustainable mindset does not seem a choice but a necessity. In today's extremely competitive luxury industry, sustainability seems like a paradox. The fashion and luxury business is producing more products, at a faster pace and change of seasons and constantly looking at decreasing costs. Many companies have moved production to Asia, especially to the more economically poorer nations. Is the demand of "sustainable luxury" enough for brands to consciously shift focus and change existing commercial production processes, do they realize the shift and awareness of the new customer who cares, and is it easy and practical to move toward "green" luxury? The purpose of this chapter is to explore the past and current intersections of sustainable luxury and draw a conclusion on its future. We take examples of luxury brands integrating themselves to sustainability. From understanding the production cycles, poor working conditions to how consumers are attracted to sustainable brands, we aim to help counter current challenges. Our methodology is comprised of qualitative data collected from various industry sources and interviews. The intent is to unravel the future of sustainable luxury with a lens on the manufacturing, packaging, and marketing efforts of a wide selection of luxury companies with different company turnovers. This chapter touches on a wide range of perspectives on the topic, including industry, designer, and retail, outlining a range of best practice strategies toward greater sustainability, while also acknowledging the complexity of the subject and its challenges, and the importance of the fashion and textile industries to livelihoods and business in general. The chapter specifically aims to put luxury and sustainability in the context of consumers and brands, understanding each through theoretical evidences from costly signaling theory, mimetic desire, pro environmental values as well as practical phenomenon. Specific focus is given to the following: (1) Materials exclusive to luxury industry from exotic skins, high quality tanned leather to furs, (2) Working conditions in manufacturing facilities, (3) Educating the customers, (4) Made in Europe versus developing countries, (5) Influence of technology in engaging with consumer on sustainability, (6) Evolution of business models that put transparency at the heart of emerging brands, (7) ROI, innovation, and luxury. The everlasting paradigm, (8) Emerging countries have also a great niche to boost, (9) Goodwill and know how: sustainable by essence, (10) Branding the innovative sustainable way and new business models.
Measurements of Dielectric Parameters of Aviation Fuel at X Band Frequencies Using Cavity Perturbation Technique

Real and imaginary parts of complex permittivity of Aviation Turbine Kerosine (Hydro fined) JetA 1 and Aviation Turbine Kerosine (Copper Sweetened) JetA 1 are measured over the wide frequency range 8 12 GHz using X band rectangular cavity resonator. The measurement technique uses the cavity perturbation technique. The fuel sample is filled in thin capillary tube of low loss material. It is then inserted through a sample hole at the centre of the broader side of the waveguide cavity resonator. The sample shifts the resonance frequency. The resonance frequency and shift in resonance frequency are measured using PNA Network Analyzer (AT E8362C) Validity of present measurement technique has been checked by measuring the dielectric properties of well known dielectric materials (Plexiglas) Due to lack of experimental data in literature on dielectric parameters of Aviation fuels, it would be of great interest for the community to find its dielectric properties over wider frequency range. In addition the estimation of measurement error associated with this technique is also discussed.
Multiplexed, Patterned Paper Immunoassay for Detection of Malaria and Dengue Fever.
Venue: Analytical chemistry

Multiplex assays detect the presence of more than one analyte in a sample. For diagnostic applications, multiplexed tests save healthcare providers time and resources by performing many assays in parallel, minimizing the amount of sample needed and improving the quality of information acquired regarding the health status of a patient. These advantages are of particular importance for those diseases that present with general, overlapping symptoms, which makes presumptive treatments inaccurate and may put the patient at risk. For example, malaria and dengue fever are febrile illnesses transmitted through mosquito bites, and these common features make it difficult to obtain an accurate diagnosis by symptoms alone. In this manuscript, we describe the development of a multiplexed, patterned paper immunoassay for the detection of biomarkers of malaria and dengue fever: malaria HRP2, malaria pLDH, and dengue NS1 type 2. In areas coendemic for malaria and dengue fever, this assay could be used as a rapid, point of care diagnostic to determine the cause of a fever of unknown origin. The reagents required for each paper based immunoassay are separated spatially within a three dimensional device architecture, which allows the experimental conditions to be adjusted independently for each assay. We demonstrate the analytical performances of paper based assays for each biomarker and we show that there is no significant difference in performance between the multiplexed immunoassay and those immunoassays performed in singleplex. Additionally, we spiked individual analytes into lysed human blood to demonstrate specificity in a clinically relevant sample matrix. Our results suggest multiplex paper based devices can be an essential component of diagnostic assays used at the point of care.
Computation offloading frameworks in mobile cloud computing a survey
Venue: 2016 IEEE International Conference on Current Trends in Advanced Computing (ICCTAC)

Mobile devices are characterized by limited and non scalable resources such as low processing power, insufficient primary memory and short battery life. Resource intensive applications such as augmented reality, artificial intelligence, artificial vision, object tracking, image processing and natural language processing are becoming popular. These applications are unable to execute effectively on resource constraint mobile devices. In the last few years considerable research has been done on Mobile Cloud Computing to extend the capabilities of mobile devices. Various models and frameworks have been proposed to offload resource intensive components of applications to cloud for efficient execution. This paper surveys recent computation offloading frameworks to determine and analyze the factors which affect the wide acceptance of these frameworks.
Estimating the Effective Population Size from Temporal Allele Frequency Changes in Experimental Evolution
Venue: Genetics

The effective population size (Ne) is a major factor determining allele frequency changes in natural and experimental populations. Temporal methods provide a powerful and simple approach to estimate short term Ne. They use allele frequency shifts between temporal samples to calculate the standardized variance, which is directly related to Ne. Here we focus on experimental evolution studies that often rely on repeated sequencing of samples in pools (Pool seq) Pool seq is cost effective and often outperforms individual based sequencing in estimating allele frequencies, but it is associated with atypical sampling properties: Additional to sampling individuals, sequencing DNA in pools leads to a second round of sampling, which increases the variance of allele frequency estimates. We propose a new estimator of Ne, which relies on allele frequency changes in temporal data and corrects for the variance in both sampling steps. In simulations, we obtain accurate Ne estimates, as long as the drift variance is not too small compared to the sampling and sequencing variance. In addition to genome wide Ne estimates, we extend our method using a recursive partitioning approach to estimate Ne locally along the chromosome. Since the type I error is controlled, our method permits the identification of genomic regions that differ significantly in their Ne estimates. We present an application to Pool seq data from experimental evolution with Drosophila and provide recommendations for whole genome data. The estimator is computationally efficient and available as an R package at https:/github.com/ThomasTaus/Nest.
A new compression technique for surveillance videos: Evaluation using new dataset
Venue: 2016 Sixth International Conference on Digital Information and Communication Technology and its Applications (DICTAP)

Traditional video surveillance takes a huge amount of space storage. Recording everything captured by a surveillance camera consumes the storage devices used by the system. Extracting useful and meaningful information from surveillance videos is a time consuming process due to the long time of the recorded videos. These drawbacks limit the effectiveness of traditional video surveillance systems. In this paper, we propose and elaborate on a compression method which investigates the fact that surveillance videos may last for a long time with no changes in the scene it monitors. Using this fact, a new compression technique that reduces the size of the videos dramatically was developed. We also present a dataset for low quality surveillance videos which can be used by researchers for applying different algorithms and techniques in the field of surveillance videos.
Throughput Maximization for UAV Enabled Mobile Relaying Systems
Venue: IEEE Transactions on Communications

In this paper, we consider a novel mobile relaying technique, where the relay nodes are mounted on unmanned aerial vehicles (UAVs) and hence are capable of moving at high speed. Compared with conventional static relaying, mobile relaying offers a new degree of freedom for performance enhancement via careful relay trajectory design. We study the throughput maximization problem in mobile relaying systems by optimizing the source/relay transmit power along with the relay trajectory, subject to practical mobility constraints (on the UAV's speed and initial/final relay locations) as well as the information causality constraint at the relay. It is shown that for the fixed relay trajectory, the throughput optimal source/relay power allocations over time follow a "staircase" water filling structure, with non increasing and non decreasing water levels at the source and relay, respectively. On the other hand, with given power allocations, the throughput can be further improved by optimizing the UAV's trajectory via successive convex optimization. An iterative algorithm is thus proposed to optimize the power allocations and relay trajectory alternately. Furthermore, for the special case with free initial and final relay locations, the jointly optimal power allocation and relay trajectory are derived. Numerical results show that by optimizing the trajectory of the relay and power allocations adaptive to its induced channel variation, mobile relaying is able to achieve significant throughput gains over the conventional static relaying.
Endoxifen, a New Treatment Option for Mania: A Double Blind, Active Controlled Trial Demonstrates the Antimanic Efficacy of Endoxifen
Venue: Clinical and translational science

The protein kinase C (PKC) signaling system plays a role in mood disorders and PKC inhibitors such as endoxifen may be an innovative medicine for bipolar disorder (BP) patients. In this study we show for the first time the antimanic properties of endoxifen in patients with bipolar I disorder (BPD I) with current manic or mixed episode. In a double blind, active controlled study, 84 subjects with BPD I were randomly assigned to receive endoxifen (4 mg/day or 8 mg/day) or divalproex in a 2:1 ratio. Patients orally administered 4 mg/day or 8 mg/day endoxifen showed significant improvement in mania assessed by the Young Mania Rating Scale as early as 4 days. The effect remained significant throughout the 21 day period. At study end point, response rates were 44.44% and 64.29% at 4 mg/day and 8 mg/day of endoxifen treatment, respectively. Thus, endoxifen has been shown as a promising novel antimanic or mood stabilizing agent.
Impact of Intra group Conflict on Group Performance moderating Role of Cultural Diversity

In the present study, a model was developed to describe relationships between impacts of intra group conflict on group performance moderating role of cultural diversity. Data from 170 employees working in teams of GSM cellular companies located in Pakistan support our hypothesis. Data was analyzed through SPSS. Findings indicated that intragroup conflict had direct negative effects on group performance effectiveness. Furthermore, our findings suggest that reducing intragroup conflict and providing team members with the abilities to manage conflict effectively is a way to increase group performance and implement strategies to decrease a stressful work environment and increase team building activities. At the end, conclusion, limitations, and future research directions are also discussed.
Liking, wanting, and the incentive sensitization theory of addiction.
Venue: The American psychologist

Rewards are both "liked" and "wanted," and those 2 words seem almost interchangeable. However, the brain circuitry that mediates the psychological process of "wanting" a particular reward is dissociable from circuitry that mediates the degree to which it is "liked." Incentive salience or "wanting," a form of motivation, is generated by large and robust neural systems that include mesolimbic dopamine. By comparison, "liking," or the actual pleasurable impact of reward consumption, is mediated by smaller and fragile neural systems, and is not dependent on dopamine. The incentive sensitization theory posits the essence of drug addiction to be excessive amplification specifically of psychological "wanting," especially triggered by cues, without necessarily an amplification of "liking." This is because of long lasting changes in dopamine related motivation systems of susceptible individuals, called "neural sensitization." A quarter century after its proposal, evidence has continued to grow in support the incentive sensitization theory. Further, its scope is now expanding to include diverse behavioral addictions and other psychopathologies.