nils-herrmann/clean_scirepeval huggingface dataset:
Intellectual capital and corporate governance: an evaluation of Oman's financial sector companies
Year: 2020

The purpose of this study is to empirically investigate the relationship between intellectual capital and corporate governance of Oman's financial sector companies. Intellectual capital has been found to successfully contribute to the economic wealth creation of firms in germane literature. Unfortunately, financial statements do not necessarily capture and reflect the contributions of intellectual capital, thereby leading to an information asymmetry between companies and users of financial statements. The research also investigates the relationship between corporate governance and intellectual capital efficiency across various financial subsectors.,Data are collected from annual reports available on Muscat Securities Market for 31 listed financial sector companies for the period 2012 to 2016 and analyzed using a multiple regression model. Intellectual capital is measured using Pulic's efficiency measure of value added intellectual coefficient (VAIC) Corporate governance individual components such as board characteristics, audit committee characteristics and ownership structure are presented as independent variables.,The findings suggest that board size and frequency of audit committee meetings have a significant association with the intellectual capital efficiency of Oman's financial sector. VAIC and human capital efficiency of banks are also significantly influenced by most of the corporate governance mechanisms; however, other subsectors do not report such findings. Corporate governance of banks in comparison to other subsectors effectively engages in utilizing the potential of intellectual capital efficiency. Agency theory and resource dependency theory find limited support as a result of this study. The GMM results are not robust to the alternative instruments.,The sample size is small as the study is limited to the listed financial sector of Oman. Future studies can be extended to include all of Oman's or GCC's listed companies. Additionally, the intellectual capital is measured using the construct of VAIC which suffers some limitations and can be overcome using other tools such as content analysis.,The findings of this study suggest that Oman's regulators can create an awareness strategy on highlighting the importance of intellectual capital for companies (board of directors and managers) investors, debtors and creditors. Further, Oman's Capital Market Authority and Muscat Securities Market need to strengthen the regulations related to intellectual capital.,This study extends intellectual capital and corporate governance literature by presenting the research outcome for Oman's financial sector. It is useful for Oman's financial sector companies to direct corporate governance measures for driving value creation of firms through the management of intellectual capital efficiency.
NAVIG: Guidance system for the visually impaired using virtual augmented reality
Year: 2012

Finding ones way to an unknown destination, navigating complex routes, finding inanimate objects; these are all tasks that can be challenging for the visually impaired. The project NAVIG (Navigation Assisted by artificial VIsion and GNSS) is directed towards increasing the autonomy of visually impaired users in known and unknown environments, exterior and interior, large scale and small scale, through a combination of a Global Navigation Satellite System (GNSS) and rapid visual recognition with which the precise position of the user can be determined. Relying on geographical databases and visually identified objects, the user is guided to his or her desired destination through spatialized semantic audio rendering, always maintained in the head centered reference frame. This paper presents the overall project design and architecture of the NAVIG system. In addition, details of the new type of detection and localization device are presented in relation to guidance directives developed through participative design with potential users and educators for the visually impaired. A fundamental concept in this project is the belief that this type of assistive device is able to solve one of the major problems faced by the visually impaired: their difficulty in localizing specific objects.
Mean shift least squares model averaging
Year: 2019

This paper proposes a new estimator for selecting weights to average over least squares estimates obtained from a set of models. Our proposed estimator builds on the Mallows model average (MMA) estimator of Hansen (2007) but, unlike MMA, simultaneously controls for location bias and regression error through a common constant. We show that our proposed estimator the mean shift Mallows model average (MSA) estimator is asymptotically optimal to the original MMA estimator in terms of mean squared error. A simulation study is presented, where we show that our proposed estimator uniformly outperforms the MMA estimator.
k Carrageenan derived carbon dots for highly selective and sensitive detection of Fe3+ and oxytetracycline
Venue: Journal of Materials Science
Year: 2020

Carbon dots (CDs) have received increasing attention as fluorescence sensors for the detection of different metal ions and organic small molecules. In this work, k carrageenan (k Carr) derived carbon dots (C CDs) were synthesized via a facile hydrothermal treatment with k Carr as a carbon source. The produced C CDs exhibited a high fluorescence with fluorescent quantum yield up to 20.6% and excellent fluorescent stability under diverse conditions (UV radiation, pH value and ionic strength) Then, the C CDs were utilized as dual functional sensing probe to detect both Fe3+ and oxytetracycline (Otc) The fluorescence intensity of C CDs was selectively quenched by Fe3+ in sharp contrast to dozens of other metal ions like Al3+ Ba2+ Ca2+ Co2+ Mg2+ Pb2+ Na+ Hg2+ Ni2+ Zn2+ Cd2+ and Cu2+ Coincidentally, this fluorescence could also be selectively quenched by Otc, entirely distinct from related physiological molecules like glycine, ammonium hydroxide, glucose, urea. The prepared C CDs could be used for label free sensitive and selective fluorescent detector for Fe3+ in a wide concentration range of 0 500 mM with a detection limit of 0.21 mM and for Otc as well in the range of 0 100 uM with a detection limit of 0.05 uM. Moreover, the fluorescent C CDs were successfully used for Fe3+ and Otc detection in some real samples, suggesting great application potential in fluorescence sensing of trace metal elements and antibiotics.
Synthesis, in vitro a glucosidase inhibition, antioxidant, in vivo antidiabetic and molecular docking studies of pyrrolidine 2,5 dione and thiazolidine 2,4 dione derivatives.
Venue: Bioorganic chemistry
Year: 2019

a Glucosidase is considered as a therapeutic target for the treatment of type 2 diabetes mellitus (DM2) In current study, we synthesized pyrrolidine 2,5 dione (succinimide) and thiazolidine 2,4 dione derivatives and evaluated for their ability to inhibit a Glucosidase. Pyrrolidine 2,5 dione derivatives (11a o) showed moderate to poor a glucosidase inhibition. Compound 11o with the IC50 value of 28.3 0.28 uM emerged as a good inhibitor of a glucosidase. Thiazolidine 2,4 dione and dihydropyrimidine (TZD DHPM) hybrids (22a c) showed excellent inhibitory activities. The most active compound 22a displayed IC50 value of 0.98 0.008 uM. Other two compounds of this series also showed activity in low micromolar range. The in vivo antidiabetic study of three compounds 11n, 11o and 22a were also determined using alloxan induced diabetes mice model. Compounds 11o and 22a showed significant hypoglycemic effect compared to the reference drug. In vivo acute toxicity study showed the safety of these selected compounds. In silico docking studies were carried out to rationalize the in vitro results. The binding modes and bioassay results of TZD DHPM hybrids showed that interactions with important residues appeared significant for high potency.
The impact of engineering students' performance in the first three years on their graduation result using educational data mining
Venue: Heliyon
Year: 2019

Research studies on educational data mining are on the increase due to the benefits obtained from the knowledge acquired from machine learning processes which help to improve decision making processes in higher institutions of learning. In this study, predictive analysis was carried out to determine the extent to which the fifth year and final Cumulative Grade Point Average (CGPA) of engineering students in a Nigerian University can be determined using the program of study, the year of entry and the Grade Point Average (GPA) for the first three years of study as inputs into a Konstanz Information Miner (KNIME) based data mining model. Six data mining algorithms were considered, and a maximum accuracy of 89.15% was achieved. The result was verified using both linear and pure quadratic regression models, and R2 values of 0.955 and 0.957 were recorded for both cases. This creates an opportunity for identifying students that may graduate with poor results or may not graduate at all, so that early intervention may be deployed.
Leaders' Emotional Intelligence and Employee Retention: Mediation of Job Satisfaction in the Hospitality Industry
Venue: International Journal of Financial Research
Year: 2019

The present study has catered to one of the major issues faced by organizations across the globe, employee retention. Therein, the study attempted to examine the relationship of leaders' emotional intelligence with employee retention. In parallel, the study also tested to underline if job satisfaction could mediate this relationship. Through targeting non managerial employees working in the four and five star hotels in Jordan, the present study sampled 380 employees from the 56 hotels. Through using structural equation modelling approach via Smart PLS 2.0 M3, the present study found significant relationship between leaders' emotional intelligence and employee retention hence suggesting that leaders' emotional awareness and management of employees whilst enriching their emotional expression and skills can significantly help boost employee retention. Accordingly, the study also reported significant mediation of job satisfaction in the relationship between leaders' emotional intelligence and employee retention. The study has reported that leaders' emotional intelligence can induce sense of belongingness leading to enhance job satisfaction which further results in harnessing employee retention. The study forwards notable implications for practice and scope for future studies in light of the findings.
Classifying and Characterizing Query Intent
Venue: ECIR
Year: 2009

Understanding the intent underlying users' queries may help personalize search results and improve user satisfaction. In this paper, we develop a methodology for using ad clickthrough logs, query specific information, and the content of search engine result pages to study characteristics of query intents, specially commercial intent. The findings of our study suggest that ad clickthrough features, query features, and the content of search engine result pages are together effective in detecting query intent. We also study the effect of query type and the number of displayed ads on the average clickthrough rate. As a practical application of our work, we show that modeling query intent can improve the accuracy of predicting ad clickthrough for previously unseen queries.
Design of a state of the art reporting system and process improvement for reporting of high complexity single antigen bead data for transplant patients to the electronic medical record
Venue: BMJ open quality
Year: 2020

The UCLA Immunogenetics Center is an Immunogenetics and Histocompatibility laboratory that performs testing for multiple transplant programmes within and outside of UCLA. The single antigen bead (SAB) test is a high complexity luminex bead test used to assess pretransplant and post transplant patients for the presence of pathogenic human leucocyte antigen donor specific antibody associated with allograft rejection. Efficient reporting of the SAB test has been difficult as data analysis and reports are generated in the laboratory information system (LIS) and uploaded to the electronic medical record (EMR) as PDFs. To solve this, we recently developed a state of the art reporting workflow allowing discrete reporting of SAB data (antibody specificity, mean fluorescent intensity and interpretative comments) from the LIS HistoTrac to UCLA Health System's EMR EPIC:CareConnect. However, a proportion of tests did not report to the EMR appropriately. Baseline system performance data evaluated over a 10 week period showed that ~4.5/100 tests resulted in EPIC as 'preliminary result' or 'in process' instead of 'final result' with only common cause variation. Quality improvement methods were employed to improve the process with the SMART Aim of reporting 100% of tests as 'final result' Pareto analysis identified two errors accounting for 79% of common system level failures status errors and interface errors. We hypothesised that addressing the status error would reduce or eliminate the interface errors. We used the Model For Improvement to test a reprogramming intervention. Status and interface errors were completely resolved through the process improvement. Continuous monitoring revealed a system level shift with only ~1.9/100 tests resulting inappropriately. Through the audit process, the remaining common system level failures were identified and resolved. Therefore, 100% of tests result to EPIC as 'final result' The study demonstrates that high complexity SAB bead data can be efficiently reported EPIC:CareConnect from HistoTrac as discrete data.
Short term effects of prescribed burning in Mediterranean pine plantations on surface runoff, soil erosion and water quality of runoff.
Venue: The Science of the total environment
Year: 2019

Fires are a complex phenomenon that may generate a chain of responses and processes that affect each part of the ecosystem. Thus, it is important to understand the magnitude of the impacts of fire on soil properties and the response of plants to this disturbance. For the moment, few studies have examined the effects of prescribed fire on large plots in afforested pine plantations in Mediterranean ecosystems. To fill this gap, the effects of a prescribed fire on runoff, soil erosion, and water quality for approximately one year after burning have been evaluated in pine plantations in south eastern Spain. We constructed six erosion plots in the control area and six erosion plots in the burned area that were 4 m long and 2 m wide, immediately after the prescribed fire. Runoff, soil erosion and runoff water quality were studied after each rainy event in all plots. Our results reveal that prescribed fire did not significantly affect runoff and soil erosion when low intensity precipitations occur at pine plantations. In relation to water quality, water turbidity, salinity, pH, organic matter content and ionic substances concentrations increased immediately after prescribed burn, nevertheless these changes disappeared over time. We can conclude that prescribed fire can be a useful tool for fuel reduction in Mediterranean pine plantations without wide and long term impacts to soil losses, or water quality.
Headspace gas chromatographic fingerprints to discriminate and classify counterfeit medicines.
Venue: Talanta
Year: 2014

Counterfeit medicines are a global threat to public health. These pharmaceuticals are not subjected to quality control and therefore their safety, quality and efficacy cannot be guaranteed. Today, the safety evaluation of counterfeit medicines is mainly based on the identification and quantification of the active substances present. However, the analysis of potential toxic secondary components, like residual solvents, becomes more important. Assessment of residual solvent content and chemometric analysis of fingerprints might be useful in the discrimination between genuine and counterfeit pharmaceuticals. Moreover, the fingerprint approach might also contribute in the evaluation of the health risks different types of counterfeit medicines pose. In this study a number of genuine and counterfeit Viagra((r) and Cialis((r) samples were analyzed for residual solvent content using headspace GC MS. The obtained chromatograms were used as fingerprints and analyzed using different chemometric techniques: Principal Component Analysis, Projection Pursuit, Classification and Regression Trees and Soft Independent Modelling of Class Analogy. It was tested whether these techniques can distinguish genuine pharmaceuticals from counterfeit ones and if distinct types of counterfeits could be differentiated based on health risks. This chemometric analysis showed that for both data sets PCA clearly discriminated between genuine and counterfeit drugs, and SIMCA generated the best predictive models. This technique not only resulted in a 100% correct classification rate for the discrimination between genuine and counterfeit medicines, the classification of the counterfeit samples was also superior compared to CART. This study shows that chemometric analysis of headspace GC impurity fingerprints allows to distinguish between genuine and counterfeit medicines and to differentiate between groups of counterfeit products based on the public health risks they pose.
Relationships between dough thermomechanical parameters and physical and sensory properties of gluten free bread texture during storage
Year: 2020

This study aimed to evaluate the effects of rice flour (RF) replacement with chickpea flour (CF) and their combinations with psyllium (PSY) on dough thermomechanical parameters by analyzing their relationship with the quality features of instrumental and sensory texture of gluten free bread (GFB) during storage. Bread samples were evaluated for crumb moisture and firmness, texture profile analysis, texture acceptability, overall liking, and descriptive profile during 7 days of storage. The data were evaluated using regression vector (RV) coefficients and multiple factor analysis (MFA) The RV coefficients showed a high correlation among the data, and the sum between the two dimensions of MFA explained 96.58% of the total variation. Replacing RF by CF decreased the tendency for starch gelatinization, gel stability, and retrogradation, as well as the hardening rate, favoring acceptance of GFB, which was described as soft and fresh during the 7 days of storage. Adding PSY increased dough initial consistency, which explains the increased cohesiveness and springiness aspects that inhibited bread crumbling during storage. The results indicate a promising use of Mixolab analysis to predict GFB quality and acceptability during 7 days of storage.
Chasing the White "WHALE" A Case Study in Using iPads to Promote Active Learning
Year: 2016

In order to encourage more active learning in the library classroom, the college librarians at the Tidewater Community College/City of Virginia Beach Joint Use Library turned one of their library instruction classrooms into a dynamic and flexible space using movable seating and iPads. This article explores the reasons for making such a change, the benefits of doing so, how the new classroom has affected librarians' teaching methods, and gives specific information about apps used for class activities.
The Effectiveness of a Proposed Internet Based Collaborative Tasks Program in Developing EFL Speaking Skills among Egyptian University Level Students
Venue: CDELT Occasional Papers in the Development of English Education
Year: 2019

Occasional Papers Vol. 66(A) (April 2019) Occasional Papers Vol. 66(A) (April 2019) ISSN 1110 2721 The Effectiveness of a Proposed InternetBased Collaborative Tasks Program in Developing EFL Speaking Skills among Egyptian University Level Students Ebtihal A. Helal, Ph.D. TEFL Lecturer Faculty of Languages, October Modern Sciences Arts University Abstract: The aim of the current study was to help EFL first year intensive English course students at October Modern Sciences Arts University develop the necessary speaking sub skills through a proposed Internetbased collaborative tasks program. These tasks included (1) watching, retelling and commenting on online digital stories, (2) watching online videos on argumentative topics and having debates based on these videos and (3) using different internet sources to give group multi media presentations highlighting the causes, effects and possible solutions of varied problems. The study followed the quasiexperimental pretestposttest one group design. The study group consisted of thirty students who were randomly selected for the purpose of the current study. The experimental group was taught by the researcher throughout the Spring Semester of the academic year 20172018 according to the proposed program. The study tools included a checklist for determining the necessary speaking sub skills, a pre/postspeaking test, an analytical rubric for marking the students' oral performance on the pre posttest and the proposed program. Comparing the pre posttest speaking performance of the study group indicated that there were statistically significant differences between the pretest and posttest scores in favour of the posttest scores. Therefore, it was concluded that the proposed program proved to be effective in developing the study group students' overall speaking performance as well as in developing each speaking sub skill.
Sensorless Indirect Field Oriented Control of Single sided Linear Induction Motor With a Novel Sliding Mode MRAS Speed Estimator
Year: 2015

This paper proposes a new sliding mode control (SMC) based model reference adaptive system (MRAS) for sensorless indirect field oriented control (IFOC) of a single sided linear induction motor (SLIM) The operation of MRAS speed estimators dramatically depends on adaptation mechanism. Fixed gain PI controller is conventionally used for this purpose which may fail to estimate the speed correctly in different condition such as variation in the machine parameters. In this paper, PI controller is replaced by SMC based adaptation mechanism. One of the major problems of SMC is high frequency chattering due to switching control function. In order to alleviate this problem, a new switching control function is presented. The SMC parameters are tuned using an off line method through chaotic optimization algorithm (COA) because no design criterion is given to provide these values. The operation of sliding mode MRAS speed estimators (SM MRAS) is validated by numerical simulation. The simulation results confirm the efficiency of proposed adaptation mechanism.
A Survey on Recent Advancements for AI Enabled Radiomics in Neuro Oncology
Venue: RNO AI@MICCAI
Year: 2019

Artificial intelligence (AI) enabled radiomics has evolved immensely especially in the field of oncology. Radiomics provide assistancein diagnosis of cancer, planning of treatment strategy, and predictionof survival. Radiomics in neuro oncology has progressed significantly inthe recent past. Deep learning has outperformed conventional machinelearning methods in most image based applications. Convolutional neu ral networks (CNNs) have seen some popularity in radiomics, since theydo not require hand crafted features and can automatically extract fea tures during the learning process. In this regard, it is observed that CNNbased radiomics could provide state of the art results in neuro oncology,similar to the recent success of such methods in a wide spectrum ofmedical image analysis applications. Herein we present a review of the most recent best practices and establish the future trends for AI enabled radiomics in neuro oncology.