nils-herrmann/clean_scirepeval huggingface dataset:
Principal change leadership competencies and teacher attitudes toward change: the mediating effects of teacher change beliefs
Year: 2018

This study investigates the relationship between Principal Change Leadership Competencies, Teacher Change Beliefs and Teacher Attitudes toward Change. A total of 936 teachers from 47 High Performing Secondary Schools in Malaysia completed the survey. Structural equation modelling was applied to test the models. Firstly, the results showed that Principal Change Leadership Competencies was significantly related to Teacher Change Beliefs and implied that if school principals equipped themselves with sufficient Principal Change Leadership Competencies, Teacher Change Beliefs can certainly be enhanced. Secondly, Teacher Change Beliefs was significantly related to Teacher Attitudes toward Change whereby the stronger the Teacher Change Beliefs, the greater the enhancement of Teacher Attitudes toward Change. Thirdly, Teacher Change Beliefs was indeed a total mediator in the relationship of Principal Change Leadership Competencies and Teacher Attitudes toward Change. Put simply, via Teacher Change Beliefs, the impact of Principal Change Leadership Competencies on Teacher Attitudes toward Change was relatively strong as Teacher Change Beliefs greatly facilitated the influence of Principal Change Leadership Competencies on Teacher Attitudes toward Change. Thus, in depth enhancing Teacher Change Beliefs is one of the effective ways to increase the likelihood of teachers to embrace change. Fourthly, Principal Change Leadership Competencies was more influential than teachers' self influence in enhancing Teacher Attitudes toward Change. Therefore, concerted effort must be given to prioritize the continuous development of principal change leadership in effective change management. The study encourages a fresh look at change leadership development and ultimately alters the traditional approach of school principals in managing change.
Sampling based algorithms for optimal motion planning using process algebra specifications
Venue: 2014 IEEE International Conference on Robotics and Automation (ICRA)
Year: 2014

This paper investigates motion planning using formal language specifications for dynamical systems with differential constraints. In particular, we focus on process algebra as a language to specify complex task specifications motivated by autonomous electric vehicles operating in a mobility on demand scenario. We use ideas from sampling based motion planning algorithms to incrementally construct a finite abstraction of the dynamical system as a Kripke structure. Given a task specification expressed as a process graph, we use model checking techniques to construct a weighted product graph of the specification with the Kripke structure. We then devise an algorithm that provably converges to the optimal trajectory of the dynamical system that satisfies the task specification as the number of the states in the Kripke structure goes to infinity. The algorithm is demonstrated in simulation experiments, viz. charging the electric car at a busy charging station and scheduling pick ups and drop offs of passengers.
CAR T Cell Therapy for Solid Tumors.
Venue: Annual review of medicine
Year: 2017

The field of cancer immunotherapy has been re energized by the application of chimeric antigen receptor (CAR) T cell therapy in cancers. These CAR T cells are engineered to express synthetic receptors that redirect polyclonal T cells to surface antigens for subsequent tumor elimination. Many CARs are designed with elements that augment T cell persistence and activity. To date, CAR T cells have demonstrated tremendous success in eradicating hematologic malignancies (e.g. CD19 CARs in leukemias) However, this success has yet to be extrapolated to solid tumors, and the reasons for this are being actively investigated. We characterize some of the challenges that CAR T cells have to surmount in the solid tumor microenvironment and new approaches that are being considered to overcome these hurdles.
Conceptualising the framework for effectiveness of customer value co creation in service innovation
Year: 2018

The involvement of customers as co creators in new service innovation is increasingly being suggested as a successful strategy to improve the success rate of new services. Value in use is a central theme for the service dominant logic because the customer is always a co creator of value. Co creation involves customer engagement in the creation of offerings through ideation, design and development. The objective of this paper is to develop the framework for successful development and implementation of customer value co creation process in service innovation. Based on literature review, three phases of value co creation have been developed. First, motivation for customer value co creation is one of the important aspects to consider by a service firm. Extrinsic and intrinsic motivations play a key role for customer motivation to participate. Second, customers' role in value creation process have greater been developed. Customer experience during interaction becomes central to the value creation process. Customer participation in value creation process is divided into two parts: participation behaviour and citizenship behaviour. Third, criteria for superior value co creation process have been developed. This research brings the framework that motivation for value co creation creates positive impact on value co creation process, which in turn leads to generate positive value co creation experience.
The Preparation towards Asean Exchange Link between Malaysia Stock Market and Asia Countries Macroeconomics Variables Interdependency
Year: 2011

When Asean countries discuss the Asean Exchage link this includes the initiatives to assess and rank ASEAN public listed companies against international corporate governance standards, harmonized standards relating to disclosure for cross border offerings, facilitate cross border offerings of products and the establishment of the ASEAN Exchange link. With this development, we try to investigate the interaction between stock prices and macroeconomic variables in Asia countries (Malaysia, Indonesia, Thailand, Singapore, China, India, South Korea, Japan and Taiwan) with reference to the United States market as a benchmark to view the sensitivity and the interdependacy of our stock market to other Asia countries macroeconomics variables. The methodology used are cointegration, Vector Error Correction Model (VECM) and Sensitivity Analysis to determine the interactions between variables. The data is quarterly data for the period of January 1990 to December 2007. Our findings show that Malaysian stock market is more integrated with other Asia Countries economics variables after the financial crisis 1997. This situation arise because of more economics project cooperation and merger between Asia countries companies to strengthen the business foundations. However, too much independent will jeopardise our stock market from speculation activities, to reduce this risk we use sensitivity analysis to test the level of sensitiveness of the variables testes to our stock market and found out that only stock price and exchange rate of other Asia Countries have the most impact to our stock markets.
Intelligent sentiment analysis approach using edge computing based deep learning technique
Venue: Softw. Pract. Exp.
Year: 2020

Sentiment analysis and opinion mining has become a major tool for collecting information from customer reviews on user sentiments and emotions, especially for online video streaming services and social networks. The increasing use of smartphones has popularized subscription to various streaming services that provide streaming media and video on demand. These applications offer a gateway to analyze user reviews by introducing sentiment analysis in the mobile environment. Online user reviews can hold a lot of useful information and help predict user interests. Analysis of user reviews can provide substantive information for business processing. Sentiment classification of these reviews is a commonly used analysis technique. Usually, these reviews are given in a text format, with every word in each considered a feature, so selection should focus on optimal features from all available features present in the reviews. This study employs machine learning algorithms to extract the best features from the training review data set. Then, the selected features are fed into the convolutional neural network and other fully connected layers for further processing. The proposed approach is evaluated with the standard evaluation metrics, such as precision, accuracy, recall, and f measure, using three distinct benchmark data sets: polarity, Rotten Tomatoes, and IMDb. This work has also employed a pretrained sentiment analysis model over an Android application framework to classify reviews on a Smartphone without the need for any cloud or server side API.
Methanol Synthesis from CO2 Hydrogenation
Venue: ChemCatChem
Year: 2019

In the future we will be phasing out the use of fossil fuels in favour of more sustainable forms of energy, especially solar derived forms such as hydroelectric, wind and photovoltaic. However, due to the variable nature of the latter sources which depend on time of day, and season of the year, we also need to have a way of storing such energy at peak production times for use in times of low production. One way to do this is to convert such energy into chemical energy, and the principal way considered at present is the production of hydrogen. Although this may be achieved directly in the future via photocatalytic water splitting, at present it is electrolytic production which dominates thinking. In turn, it may well be important to store this hydrogen in an energy dense liquid form such as methanol or ammonia. In this brief review it is emphasised that CO2 is the microscopic carbon source for current industrial methanol synthesis, operating through the surface formate intermediate, although when using CO in the feed, it is CO which is hydrogenated at the global scale. However, methanol can be produced from pure CO2 and hydrogen using conventional and novel types of catalysts. Examples of such processes, and of a demonstrator plant in construction, are given, which utilize CO2 (which would otherwise enter the atmosphere directly) and hydrogen which can be produced in a sustainable manner. This is a fast evolving area of science and new ideas and processes will be developed in the near future.
The arginine deiminase pathway of koji bacteria is involved in ethyl carbamate precursor production in soy sauce.
Venue: FEMS microbiology letters
Year: 2014

Ethyl carbamate (EC) is a group 2A carcinogen generated from a few precursors in many fermented foods and alcoholic beverages. Citrulline, urea, carbamoyl phosphate, and ethanol are common precursors detected in fermented foods. In this study, citrulline was proved to be the main EC precursor in soy sauce, which was found to be accumulated in moromi mash period and correlated with the utilization of arginine by koji bacteria. Six koji isolates belonging to three genera were identified to be able to accumulate citrulline via the arginine deiminase (ADI) pathway. Among these strains, only Pediococcus acidilactici retained high activities in synthesis and accumulation of citrulline in the presence of high concentration of sodium chloride. These results suggested that P. acidilactici is responsible for the accumulation of citrulline, one of the EC precursors, in the process of soy sauce fermentation.
What factors explain anti Muslim prejudice? An assessment of the effects of Muslim population size, institutional characteristics and immigration related media claims
Venue: Journal of Ethnic and Migration Studies
Year: 2019

What factors explain majority members' anti Muslim prejudice? This is an increasingly important question to ask, but to date only relatively few studies have sought to provide answers from a cross national comparative perspective. This study aims to help fill this gap. Using data from the seventh round of the European Social Survey (ESS) linked with country level characteristics, our results indicate that (a) a larger Muslim population size, (b) more liberal immigrant integration policies and (c) greater state support of religion are all associated with lower levels of majority members' negative attitudes towards Muslim immigration our indicator of anti Muslim prejudice. Such attitudes, however, prove to be unrelated to (d) cross national differences in the frequency of negative immigration related news reports as measured by the ESS media claims data. Collectively, these findings bring us one important step closer towards a better understanding of interethnic relations between majority members and Muslim immigrants in European host societies.
Indian Religion and Western Yoga Practice
Year: 2011

Yoga has become a very recognizable feature of Western culture. Almost every person who has taken a yoga class can tell you that yoga originated in India. However, contemporary North American yoga focused on postures and physical practice departs considerably from "classical" yoga in India. The various yoga styles and yoga studios in North America differ with respect to their relationship to the history and tradition of yoga. My thesis seeks to understand the different ways that Indian religion "Indian ness" and religiosity are expressed in yoga classes and among yoga practitioners. This thesis is a case study conducted in Montreal carried out at three studios representing three styles that one could find in almost every major North American city: Sattva Yoga Shala (Ashtanga Vinyasa Yoga) Moksha Yoga Montreal (hot yoga) and Centre de Yoga Iyengar de Montreal (Iyengar Yoga) At each studio I interviewed teachers and students to discover their experiences with yoga, their beliefs about benefits from practicing yoga, as well as their knowledge and relation to the tradition of yoga. Indian religious elements are present to varying degrees in North American yoga classes but both teachers and students appreciate these aspects as pleasant exoticisms that are basically inessential to their yoga practice. At the same time, students and teachers may be prone to projecting non Indian spiritual ideas onto their yoga practice, which enhances its significance for them.
False Impression: Medicine Says Medicare Report Inflates Success of Quality Program.
Venue: Texas medicine
Year: 2019

High participation, "significant strides," overwhelming success. That was the picture the Centers for Medicare Medicaid Services painted in a March report on the first year of the Quality Payment Program. But a closer look by the Texas Medical Association raises serious doubts about CMS' numbers, transparency, and cheerleading so much so that TMA and seven other state medical associations are asking the agency to rescind the report.
Mechanical characterization of FDM 3D printing of continuous carbon fiber reinforced PLA composites
Venue: Composites Part B: Engineering
Year: 2019

Additive manufacturing of fiber reinforced composites is of great interest in various industrial applications. In this study, an innovative extruder is designed and manufactured for fused deposition modeling (FDM) 3D printers in order to produce continuous fiber reinforced thermoplastic (CFRT) composites. There are some challenges along this way such as making tension in fiber, fiber surface preparation, printing temperature and feed rate to produce a composite part with good quality. These challenges are discussed in detail. The main advantage of this extruder is that it can be mounted on the available FDM 3D printers and consequently there is no need to design a new chassis. In order to assess the quality of products, standard tensile and three point bending specimens made of pure poly lactic acid (PLA) and carbon fiber reinforced PLA are printed and tested under quasi static loading. Experimental results show significant improvements of tensile and bending properties of PLA. Morphological analysis is also conducted to study the bonding between the carbon fiber and PLA.
Chronic non puerperal uterine inversion due to submucosal fibroid: a rare case report
Year: 2020

Uterine inversion is a rare clinical condition with only a few cases of chronic non puerperal inversion of uterus quoted in the literature. On an average a gynaecologist may only see one case in their lifetime. Uterine infection is described as a part of the uterus indenting towards and eventually prolapsing through the dilated cervix resulting in uterus being turned inside out. It is categorized as puerperal and non puerperal complication Acute puerperal uterine inversion occurs within 24 hours of birth, sub acute inversion occurs after 24 hours and within 4 weeks, chronic occurs after 4 weeks. Surgery for inverted uterus is technically difficult and poses a great challenge for the surgeon. Authors are reporting a case of chronic non puerperal uterine inversion due to benign submucous fundal uterine fibroid in 50 year old multiparous women who had correction of anaemia followed by vaginal hysterectomy.
Utilising Information Foraging Theory for User Interaction with Image Query Auto Completion
Venue: ECIR
Year: 2020

Query Auto completion (QAC) is a prominently used feature in search engines, where user interaction with such explicit feature is facilitated by the possible automatic suggestion of queries based on a prefix typed by the user. Existing QAC models have pursued a little on user interaction and cannot capture a user's information need (IN) context. In this work, we devise a new task of QAC applied on an image for estimating patch (one of the key components of Information Foraging Theory) probabilities for query suggestion. Our work supports query completion by extending a user query prefix (one or two characters) to a complete query utilising a foraging based probabilistic patch selection model. We present iBERT, to fine tune the BERT (Bidirectional Encoder Representations from Transformers) model, which leverages combined textual image queries for a solution to image QAC by computing probabilities of a large set of image patches. The reflected patch probabilities are used for selection while being agnostic to changing information need or contextual mechanisms. Experimental results show that query auto completion using both natural language queries and images is more effective than using only language level queries. Also, our fine tuned iBERT model allows to efficiently rank patches in the image.
Multi Touch in the Air: Device Free Finger Tracking and Gesture Recognition via COTS RFID
Venue: IEEE INFOCOM 2018 IEEE Conference on Computer Communications
Year: 2018

Recently, gesture recognition has gained considerable attention in emerging applications (e.g. AR/VR systems) to provide a better user experience for human computer interaction. Existing solutions usually recognize the gestures based on wearable sensors or specialized signals (e.g. WiFi, acoustic and visible light) but they are either incurring high energy consumption or susceptible to the ambient environment, which prevents them from efficiently sensing the fine grained finger movements. In this paper, we present RF finger, a device free system based on Commercial Off The Shelf (COTS) RFID, which leverages a tag array on a letter size paper to sense the fine grained finger movements performed in front of the paper. Particularly, we focus on two kinds of sensing modes: finger tracking recovers the moving trace of finger writings; multi touch gesture recognition identifies the multi touch gestures involving multiple fingers. Specifically, we build a theoretical model to extract the fine grained reflection feature from the raw RF signal, which describes the finger influence on the tag array in cm level resolution. For the finger tracking, we leverage K Nearest Neighbors (KNN) to pinpoint the finger position relying on the fine grained reflection features, and obtain a smoothed trace via Kalman filter. Additionally, we construct the reflection image of each multi touch gesture from the reflection features by regarding the multiple fingers as a whole. Finally, we use a Convolutional Neural Network (CNN) to identify the multi touch gestures based on the images. Extensive experiments validate that RF finger can achieve as high as 88% and 92% accuracy for finger tracking and multi touch gesture recognition, respectively.
Cancer stem cells: current status and evolving complexities.
Venue: Cell stem cell
Year: 2012

The cancer stem cell (CSC) model has been established as a cellular mechanism that contributes to phenotypic and functional heterogeneity in diverse cancer types. Recent observations, however, have highlighted many complexities and challenges: the CSC phenotype can vary substantially between patients, tumors may harbor multiple phenotypically or genetically distinct CSCs, metastatic CSCs can evolve from primary CSCs, and tumor cells may undergo reversible phenotypic changes. Although the CSC concept will have clinical relevance in specific cases, accumulating evidence suggests that it will be imperative to target all CSC subsets within the tumor to prevent relapse.
Systeme de connaissance expert dedie a la recherche translationnelle dans les maladies rares
Year: 2016

Environ 6000 a 8000 maladies rares differentes existent aujourd'hui, affectant environ 6 a 8% de la population mondiale. La grande majorite d'entre elles correspond a des maladies genetiques, pour lesquelles il n'existe pas de traitement curatif. La revolution genomique a augmente l'espoir d'obtenir des traitements specifiques du defaut genetique pour de nombreuses maladies. Dans ces conditions, le traitement et l'analyse des donnees ne sont pas triviaux et s'eloignent de la simple routine.Cette these rapporte la creation de Saut d'exon, capables d'aider les chercheurs et les cliniciens a identifier les mutations responsables de certaines maladies et developper de nouvelles strategies therapeutiques. Ainsi, les systemes Human Splicing Finder et UMD Predictor permettent respectivement de predire l'effet d'une mutation sur l'epissage et la fonction de la proteine. Ils ont ete valides grace a des jeux de donnees de reference et/ou issus de la litterature, et peuvent aider les cliniciens a annoter correctement les variations de signification inconnue. De plus, cette these propose deux outils a visees therapeutiques Skip E, un outil d'identification des AON candidats a la therapie par saut d'exon, et NR Analyser, un systeme de prediction des codons de terminaison prematures candidats a la therapie par translecture des codons stop.Ces differents systemes s'integrent dans un projet plus global dedie a la recherche translationnelle. Par ces deux volets, predictif et therapeutique, cette these s'inscrit dans une strategie de recherche en adequation avec les objectifs du Consortium International pour la Recherche contre les Maladies Rares, l'IRDiRC.