nils-herrmann/clean_scirepeval huggingface dataset:
On weighted balanced loss function under the Esscher principle and credibility premiums

This paper focuses on weighted balanced loss function under the Esscher principle (WBLF) of which we explore the modern practice of credibility theory and we generalize credibility premiums by using the WBLF. We obtain a distribution free approach under the WBLF and the Esscher premium by using a minimization technique. Also, we discuss the consistency of the credibility premium generated by this distribution free approach.
Omnichannel Fashion Retail and Channel Integration: The Case of Department Stores

The evolution from single channel to multichannel retailing is explained by the need to overcome existing format limitations such as the size of store, expansion in new markets through electronic channels, increasing sales by cross channel interactions and gaining valuable insight into consumer behaviour through the Internet. The aim of this chapter is to explain the development and implementation of omnichannel retailing and to demonstrate its experiential touchpoints in department stores. Case study approach is adopted to look at the development of omichannel integration and retail touchpoints in two iconing department stores: Harrods and Selfridges. Different strategies are identified and implications of each are discussed with relevant recommendations for retail practitioners.
Transient Noise Reduction in Cochlear Implant Users: a Multi Band Approach
Venue: Audiology research

A previously tested transient noise reduction (TNR) algorithm for cochlear implant (CI) users was modified to detect and attenuate transients independently across multiple frequency bands. Since speech and transient noise are often spectrally distinct, we hypothesized that benefits in speech intelligibility can be achieved over the earlier single band design. Fifteen experienced CI users (49 to 72 years) were tested unilaterally using pre processed stimuli delivered directly to a speech processor. Speech intelligibility in transient and soft stationary noise, subjective sound quality and the recognition of warning signals was investigated in three processing conditions: no TNR (TNRoff) single band TNR (TNRsgl) and multi band TNR (TNRmult) Notably, TNRmult improved speech reception thresholds (SRTs) in cafeteria noise and office noise by up to 3 dB over both TNRoff and TNRsgl, and yielded higher comfort and clarity ratings in cafeteria noise. Our results indicate that multi band transient noise reduction may be advantageous compared to a single band approach, and reveal a substantial overall potential for TNR to improve speech perception and listening comfort in CI users.
Preliminary Study on the Impact of Literature Curation in a Model Organism Database on Article Citation Rates
Venue: D Lib Mag.

Literature curation by model organism databases (MODs) results in the interconnection of papers, genes, gene functions, and other experimentally supported biological information, and aims to make research data more discoverable and accessible to the research community. That said, there is a paucity of quantitative data about if and how literature curation affects access and reuse of the curated data. One potential measure of data reuse is the citation rate of the article used in curation. If articles and their corresponding data are easier to find, then we might expect that curated articles would exhibit different citation profiles when compared to articles that are not curated. That is, what are the effects of having scholarly articles curated by MODs on their citation rates? To address this question we have been comparing the citation behavior of different groups of articles and asking the following questions: (1) given a collection of 'similar' articles about Arabidopsis, is there a difference in the citation numbers between articles that have been curated in TAIR (The Arabidopsis Information Resource) and ones that have not, (2) for articles annotated in TAIR, is there a difference in the citation behavior before vs. after curation and, (3) is there a difference in citation behavior between Arabidopsis articles added to TAIR's database and those that are not in TAIR? Our data indicate that curated articles do have a different citation profile than non curated articles that appears to result from increased visibility in TAIR. We believe data of this type could be used to quantify the impact of literature curation on data reuse and may also be useful for MODs and funders seeking incentives for community literature curation. This project is a research partnership between TAIR and Elsevier Labs.
Software Analysis for the Web: Achievements and Prospects
Venue: 2016 IEEE 23rd International Conference on Software Analysis, Evolution, and Reengineering (SANER)

The web has had a significant impact on our lives. A technology that was initially created for sharing documents across the network has evolved into a strong medium for developing and distributing software applications. In this paper, we first provide a concise overview of the evolution of the web itself. We then focus on some of the main industrial and research achievements in software analysis and testing techniques geared toward web apps, in the past two decades. We discuss static, dynamic, and hybrid analyses approaches, software testing and test adequacy techniques, as well as techniques that help developers write, analyze and maintain their code. Finally, we present some of the current and future challenges and research opportunities ahead in this field.
Analytic Behavior and Trust Building in Visual Analytics
Venue: EuroVis

Visual Analytics (VA) is a collaborative process between human and computer, where analysts are performing numerous interactions and reasoning activities. This paper presents our current progress in developing a note taking environment (NTE) that can be plugged to any VA system. The NTE supports the analysis process on the one hand, and captures user interactions on the other hand. Our aim is to integrate human lower (exploration) with higher (verification) level analytic processes and to investigate those together related to further human factors, such as trust building. We conducted a user study to collect and investigate analytic provenance data. Our early results reveal that analysis strategies and trust building are very individual. However, we were able to identify significant correlations between trust levels and interactions of particular participants.
A Survey Paper on different Clustering techniques for Collaborative Filtering for services recommendation

Collaborative filtering (CF) is a technique commonly used to build personalized recommendations on the Web. Some popular websites that make use of the collaborative filtering technology include Amazon, Netflix, iTunes, IMDB. Data sparseness is the most important issue in CF. Data sparseness causes the system difficulty in determining the nearest neighbours of the target user accurately. Clustering can solve the problem of data sparseness. Grouping a set of physical or abstract objects into classes of similar objects, this process is called as clustering. This paper presents the methods to generate recommendations using clusteringbased collaborative filtering approach.  Clustering, Collaborative filtering, Nearest Neighbours, Data sparseness, Personalised recommendations.
A survey of active learning in collaborative filtering recommender systems
Venue: Comput. Sci. Rev.

In collaborative filtering recommender systems user's preferences are expressed as ratings for items, and each additional rating extends the knowledge of the system and affects the system's recommendation accuracy. In general, the more ratings are elicited from the users, the more effective the recommendations are. However, the usefulness of each rating may vary significantly, i.e. different ratings may bring a different amount and type of information about the user's tastes. Hence, specific techniques, which are defined as "active learning strategies" can be used to selectively choose the items to be presented to the user for rating. In fact, an active learning strategy identifies and adopts criteria for obtaining data that better reflects users' preferences and enables to generate better recommendations.So far, a variety of active learning strategies have been proposed in the literature. In this article, we survey recent strategies by grouping them with respect to two distinct dimensions: personalization, i.e. whether the system selected items are different for different users or not, and, hybridization, i.e. whether active learning is guided by a single criterion (heuristic) or by multiple criteria. In addition, we present a comprehensive overview of the evaluation methods and metrics that have been employed by the research community in order to test active learning strategies for collaborative filtering. Finally, we compare the surveyed strategies and provide guidelines for their usage in recommender systems.
Noncontact Monitoring of Blood Oxygen Saturation Using Camera and Dual Wavelength Imaging System
Venue: IEEE Transactions on Biomedical Engineering

We present a noncontact method to monitor blood oxygen saturation (SpO2) The method uses a CMOS camera with a trigger control to allow recording of photoplethysmography (PPG) signals alternatively at two particular wavelengths, and determines the SpO2 from the measured ratios of the pulsatile to the nonpulsatile components of the PPG signals at these wavelengths. The signal to noise ratio (SNR) of the SpO2 value depends on the choice of the wavelengths. We found that the combination of orange (l 611 nm) and near infrared (l 880 nm) provides the best SNR for the noncontact video based detection method. This combination is different from that used in traditional contact based SpO2 measurement since the PPG signal strengths and camera quantum efficiencies at these wavelengths are more amenable to SpO2 measurement using a noncontact method. We also conducted a small pilot study to validate the noncontact method over an SpO2 range of 83% 98% This study results are consistent with those measured using a reference contact SpO2 device (r 0.936, p 0.001) The presented method is particularly suitable for tracking one's health and wellness at home under free living conditions, and for those who cannot use traditional contact based PPG devices.
The role of nurse education in improving patient outcomes and patient satisfaction with nursing care: A multiple case study of nursing teams in three hospitals across Ireland and Germany.

International large scale research has found that nurse education at degree level contributes to reduced mortality and failure to rescue rates. The influences of hospital and national contexts and of different types of nurse education levels towards improved patient care seem often overlooked.  The aim of this study was to explore the role of nurse education in improving patient outcomes and patient satisfaction with nursing care, taking into account different types of nurse education levels within different hospital based and country specific contexts. The objectives were: (1) to explore and compare nurse education levels, hospital and nurse structures, care processes and patient related outcomes for selected nursing teams from the Irish and German arms of the RN4CAST project (2) to explore factors other than nurse education affecting patient outcomes, including country specific factors.  A multiple case study design was utilised to conduct an in depth exploration of the findings generated from the Irish and German arms of the RN4CAST (Nurse Forecasting: Human Resources Planning in Nursing) project. Three nursing teams, with different proportions of degree (pre registration, post registration and international degree) and apprenticeship trained nurses working in hospitals in Ireland and Germany were selected. Data were explored and compared based on Donabedian's (2005) Structure Process Outcome model for health care practice. Patient outcomes included falls with injury, medication errors and pressure ulcers developed after admission. Patients rated nurse communication, pain control and discharge information provided.  Findings suggest that degree level education, and type of degree, play a role in improving patient related outcomes. The team with both degree and apprenticeship trained nurses reported the best patient outcomes, which were also attributed to better working conditions and lower levels of hospital bed occupancy. Country specific factors such as nurse to patient ratios and skill mix further affected the care provided by the nursing teams.  This study provides new insights into the role of nurse education in improving patient related outcomes. It also provides new information about hospital based and country specific contexts, within which nurses with different educational backgrounds provide care.
Multi person Tracking by Multicut and Deep Matching
Venue: ECCV Workshops

In Tang et al. (2015) we proposed a graph based formulation that links and clusters person hypotheses over time by solving a minimum cost subgraph multicut problem. In this paper, we modify and extend Tang et al. (2015) in three ways: (1) We introduce a novel local pairwise feature based on local appearance matching that is robust to partial occlusion and camera motion. (2) We perform extensive experiments to compare different pairwise potentials and to analyze the robustness of the tracking formulation. (3) We consider a plain multicut problem and remove outlying clusters from its solution. This allows us to employ an efficient primal feasible optimization algorithm that is not applicable to the subgraph multicut problem of Tang et al. (2015) Unlike the branch and cut algorithm used there, this efficient algorithm used here is applicable to long videos and many detections. Together with the novel pairwise feature, it eliminates the need for the intermediate tracklet representation of Tang et al. (2015) We demonstrate the effectiveness of our overall approach on the MOT16 benchmark (Milan et al. 2016) achieving state of art performance.
MiR 150 Controls B Cell Differentiation by Targeting the Transcription Factor c Myb
Venue: Cell

MiR 150 is a microRNA (miRNA) specifically expressed in mature lymphocytes, but not their progenitors. A top predicted target of miR 150 is c Myb, a transcription factor controlling multiple steps of lymphocyte development. Combining loss and gain of function gene targeting approaches for miR 150 with conditional and partial ablation of c Myb, we show that miR 150 indeed controls c Myb expression in vivo in a dose dependent manner over a narrow range of miRNA and c Myb concentrations and that this dramatically affects lymphocyte development and response. Our results identify a key transcription factor as a critical target of a stage specifically expressed miRNA in lymphocytes and suggest that this and perhaps other miRNAs have evolved to control the expression of just a few critical target proteins in particular cellular contexts.
Anti inflammatory and Anti oxidative Effects of Dexpanthenol on Lipopolysaccharide Induced Acute Lung Injury in Mice
Venue: Inflammation

The aim of this study is to investigate the effects of dexpanthenol in a model of acute lung injury (ALI) induced by lipopolysaccharides (LPS) Lung injury was induced by exposure to atomized LPS. Mice were randomly divided into four groups: control group; Dxp (500 mg/kg) group; LPS group; LPS Dxp (500 mg/kg) group. The effects of dexpanthenol on LPS induced neutrophil recruitment, cytokine levels, total protein concentration, myeloperoxidase (MPO) malondialdehyde (MDA) superoxide dismutase (SOD) and glutathione (GSH) contents were examined. Additionally, lung tissue was examined by histology to investigate the changes in pathology in the presence and absence of dexpanthenol. In LPS challenged mice, dexpanthenol significantly improved lung edema. Dexpanthenol also markedly inhibited the LPS induced neutrophiles influx, protein leakage, and release of TNF a and IL 6 in bronchoalveolar lavage fluid (BALF) Furthermore, dexpanthenol attenuated MPO activity and MDA contents and increased SOD and GSH activity in the LPS challenged lung tissue. These data suggest that dexpanthenol protects mice from LPS induced acute lung injury by its anti inflammatory and anti oxidative activities.
Dexpanthenol therapy reduces lung damage in a hyperoxic lung injury in neonatal rats
Venue: The journal of maternal fetal neonatal medicine the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians

Dexpanthenol (Dxp) plays a major role in cellular defense and in repair systems against oxidative stress and inflammatory response and it has not yet been evaluated in treatment of bronchopulmonary dysplasia (BPD) We tested the hypothesis that proposes whether Dxp decreases the severity of lung injury in an animal model of BPD.  Forty rat pups were divided into four groups: control, control Dxp, hyperoxia and hyperoxia Dxp. All animals were processed for lung histology and tissue analysis. The degree of lung inflammation, oxidative and antioxidant capacity was assessed from lung homogenates.  Lung injury score and alveol diameter increased in the hyperoxia group (p 0.001) Median level of malondialdehyde, total oxidant status and oxidative stress indexes was significantly higher in the hyperoxia group compared to the other groups. The median superoxide dismutase activity in the hyperoxia group was notably less than those of control Dxp and hyperoxia Dxp groups (p 0.01) Similarly, lung catalase, glutathione (GSH) peroxidase and reduced GSH activities in the hyperoxia group were significantly lower than other groups. Furthermore, the hyperoxia Dxp group had lower tumor necrosis factor a and interleukin 1b median levels compared to the hyperoxia group (p 0.007)  Dxp treatment results in less emphysematous change as well as decrease in inflammation and oxidative stress markers in an animal model of BPD.
Deep Learning Approach for Arabic Named Entity Recognition
Venue: CICLing

Inspired by recent work in Deep Learning that have achieved excellent performance on difficult problems such as computer vision and speech recognition, we introduce a simple and fast model for Arabic named entity recognition based on Deep Neural Networks (DNNs) Named Entity Recognition (NER) is the task of classifying or labelling atomic elements in the text into categories such as Person, Location or Organization. The unique characteristics and the complexity of the Arabic language make the extraction of named entities a challenging task. Most state of the art systems use a combination of various Machine Learning algorithms or rely on handcrafted engineering features and the output of other NLP tasks such as part of speech (POS) tagging, text chunking, prefixes and suffixes as well as a large gazetteer. In this paper, we present an Arabic NER system based on DNNs that automatically learns features from data. The experimental results show that our approach outperforms the model based on Conditional Random Fields by 12.36 points in F measure. Moreover, our model outperforms the state of the art by 5.18 points in Precision and gets very close results in F measure. Most importantly, our system can be easily extended to recognize other named entities without any additional rules or handcrafted engineering features.
Transformation of teacher practice using mobile technology with one to one classes: M learning pedagogical approaches
Venue: Br. J. Educ. Technol.

The rapid global uptake of mobile technology is reflected in pioneering New Zealand schools. Teachers of classes where each student uses a mobile device were surveyed on how frequently they use various mobile learning activities and asked to describe the new pedagogical opportunities it offers. The teachers' m learning pedagogical approaches and the extent of transformation were considered. This study finds the main use of mobile technology is to enhance learning with task activities and information access; however, innovative content production is also common. The opportunities for pedagogical transformation that collaborative learning offers appear to be partially realised, but the potential for situative learning using authentic contexts and experts seems to be largely unrealised. Presently, transformative pedagogical approaches are not prevalent despite collaborative inquiry and situative approaches with authentic contexts being linked to developing higher order thinking and fostering future focused skills, which are a key focus for educators. The use of one to one mobile technology in the classroom is a new educational practice with significant potential. This study provides a snapshot to contribute to building the necessary body of work on m learning pedagogical transformation.
Employees' acceptance of mobile technology in a workplace: An empirical study using SEM and fsQCA

This study aims to analyze the antecedent conditions of work performance including performance expectancy, facilitating conditions, social influence, and which combination of them better leads to higher levels of performance when using mobile technology in the workplace. With an extended theoretical framework of UTAUT, this study undertook a survey of employees from various industrial categories in Taiwan. The data were analyzed by structural equation model (SEM) and fuzzy set qualitative comparative analysis (fsQCA) to understand the statistical associations and the set relations of the conjunctions and conditions. Using a sample of 692 employees, the results support all four hypotheses and support the structural model built in this study. The findings suggested that using mobile technology in the workplace positively influenced employees' perceived improvement of work performance and that the performance expectancy also affected work performance improvement. Finally, facilitating conditions and social influence significantly affected mobile technology usage behavior.
Parent Scaffolding of Young Children When Engaged with Mobile Technology
Venue: Front. Psychol.

Shared parent child experiences while engaged with an iPadTM were examined to determine if and then how parents interact with their children when using mobile digital devices. In total, 104 parent child dyads participated in an observation session where parent child interactions using the touchscreen tablet device were video recorded in order to observe first hand the supports and exchanges between parent and child (age range 46.21 75.9 months) Results indicate that parents provide a great deal of support to their children while interacting with the touchscreen tablet device including verbal, emotional verbal, physical and emotional physical supports. The types of support offered did not differ as a function of parent gender or experience with mobile devices (users versus non users) Overall, parents rated their own experience engaging with the touchscreen tablet and that of their child's positively. Additional survey measures assessed parents' perceptions of their child's technology use and attitudes regarding optimal ages and conditions for introducing and using technology. Most parents indicated a preference for very early introduction to mobile technologies. Implications of these findings are discussed.