nils-herrmann/clean_scirepeval huggingface dataset:
If We Could Go Back in Time. On the Use of 'Unnatural' Time and Ordering in Dataflow Models
Venue: Principles of Modeling
Year: 2018

Model based design methods have become common practice for the design, analysis, and synthesis of embedded and cyber physical systems. Different models of computation are used (for example state based models, dataflow models, differential equations, hybrid models) In real time and cyber physical systems it is common to incorporate in such models some representation of time, physical, logical or otherwise. We are used to time progressing in forward direction. This assumption is built into the very definition of many of our favorite models of computation. Execution times or delays are usually non negative. Time stamps usually increase monotonically. Tasks can depend on past activations of other tasks, but not on future activations. Tasks are temporally causal. In this paper we explore the possibilities and the potential benefits of liberating our models from these assumptions, allowing time go backward in our models. We will use the dataflow model of computation for our exploration and show that there are potential benefits to negative execution times, negative delays on channels, and non monotone events in event traces.
Fabrication and finite element analysis of stereolithographic 3D printed microneedles for transdermal delivery of model dyes across human skin in vitro.
Venue: European journal of pharmaceutical sciences official journal of the European Federation for Pharmaceutical Sciences
Year: 2019

This research aimed to manufacture and evaluate in vitro 3D printed microneedles for transdermal drug delivery. Firstly, microneedle arrays were fabricated using a polymer based material. Subsequently, these arrays were tested for their mechanical strength applying axial load along their length, while prediction of the buckling load was performed using widely known arithmetic models. Additionally, the force required to pierce human skin was calculated in order to verify that microneedles insert human skin without buckling or fracturing. Finite Element Analysis (FEA) was used to simulate the insertion process and complement the experimental findings. Furthermore, permeation studies were carried out in order to compare diffusion of two model dyes with different molecular weight namely; FITC Dextran (M.W.:4000 Da) and calcein (M.W.:622.54 Da) across full thickness human skin in vitro before and after skin treatment with microneedles. Finally, visualization studies enabled illustration of microneedle perforation sites. The results showed that the manufactured 3D printed microneedle arrays penetrate sufficiently human skin and can significantly enhance the transport of the dyes across human skin.
Effects of Educational Program on MERS Corona Virus Among Nurses Students at Jazan University 1439 2017
Year: 2018

The Middle Eastern Respiratory Syndrome Corona Virus (MERSCoV) firstly discovered among people living in Saudi Arabia.aim of study is to The aim of the study is to evaluate the effectiveness of Educational Program on MERS Corona Virus among nurses students at Jazan University 1439 2017 among nurses student at Sabia University College.
An Efficient Hybrid RSS AoA Localization for 3D Wireless Sensor Networks
Venue: Sensors
Year: 2019

Wireless sensor networks (WSNs) enable many applications such as intelligent control, prediction, tracking, and other communication network services, which are integrated into many technologies of the Internet of Things. The conventional localization frameworks may not function well in practical environments since they were designed either for two dimensional space only, or have high computational costs, or are sensitive to measurement errors. In order to build an accurate and efficient localization scheme, we consider in this paper a hybrid received signal strength and angle of arrival localization in three dimensional WSNs, where sensors are randomly deployed with the transmit power and the path loss exponent unknown. Moreover, in order to avoid the difficulty of solving the conventional maximum likelihood estimator due to its non convex and highly complex natures, we derive a weighted least squares estimate to estimate jointly the location of the unknown node and the two aforementioned channel components through some suitable approximations. Simulation results confirm the effectiveness of the proposed method.
Confidence limits, error bars and method comparison in molecular modeling. Part 1: The calculation of confidence intervals
Venue: Journal of Computer Aided Molecular Design
Year: 2014

Computational chemistry is a largely empirical field that makes predictions with substantial uncertainty. And yet the use of standard statistical methods to quantify this uncertainty is often absent from published reports. This article covers the basics of confidence interval estimation for molecular modeling using classical statistics. Alternate approaches such as non parametric statistics and bootstrapping are discussed.
The Correlation Research Between Express Company Service Quality And Undergraduate Customer Satisfaction Degree Based On SERVQUAL Model
Year: 2016

How to improve the service quality of express company in the internet plus era have already become a hot topic among the academic circles and business circles. The college students group is one of the primary groups with online shopping habit. The development projects on special services for undergraduate groups have benefit to assure the customer interests during the online shopping. In order to comprehend express company service condition to undergraduate customer group, this essay propose five dimensions of express service quality based on the classic SERVQUAL model, and make hypotheses on the correlation between them and the undergraduate customer satisfaction degree. After the investigation on the undergraduate group and statistic analysis through SPSS software, get the following conclusion. The tangibility, reliability, responsiveness and empathy of express service quality have significant effect to undergraduate customer satisfaction degree. According to this, the express should enhance the service quality as soon as possible, establish the deliver system centered on the benefits of undergraduate customers to encourage them make online shopping; what's more, the express company should pay more attention to develop the terminal deliver system and supervision strength of undergraduate market; the last but not the least, the express company should efficiently handle the complaints of undergraduate customer.
Camp Counseling and the Development and Transfer of Workforce Skills: The Perspective of Ohio 4 H Camp Counselor Alumni
Year: 2007

Recent research shows that camp counselors, including those in 4 H, benefit from the experience by developing important life skills. However, because research regarding the perception of workforce skill development in this context has yielded inconsistent findings, the present study used focus groups to examine 4 H camp counselor alumni perceptions about the skills gained and transfer of these skills to other settings. Overall, 4 H camp counselor alumni thought their experience was fun and enjoyable, yet challenging. They believed they developed important life and workforce skills. Not only did alumni learn these skills, but the skills transferred beyond the camp setting. Leadership was noted as the skill most frequently applied to other contexts. Alumni believed that their counseling experiences had both indirect and direct impacts on their career choice. This study suggests many practical applications for those who work with camp programs.
Normal and inverse magnetocaloric effect in colossal magnetoresistive electron doped manganites R0.15Ca0.85MnO3 (R Y, Gd and Dy)
Venue: Journal of Magnetism and Magnetic Materials
Year: 2019

Magnetic, magnetocaloric and electrical transport properties of polycrystalline R0.15Ca0.85MnO3 (R Y, Gd and Dy) manganites (Orthorhombic, Pnma) have been studied. Magnetization measured in 5 kOe field reveals antiferromagnetic transition at 111 K, 119 K and 112 K (TN) respectively in R0.15Ca0.85MnO3 (R Y, Gd and Dy) Magnetization in the ordered state undergoes field induced transition and at 2 K, in 140 kOe field, the magnetic moment values are 1.5 mB/f.u. 2.8 mB/f.u. and 2.7 mB/f.u. respectively for R0.15Ca0.85MnO3 (R Y, Gd and Dy) samples. While the electrical resistivity above TN shows non adiabatic, small polaron hopping behavior, the resistivity value increases rapidly below TN. Hysteresis is observed around TN between field cooled cooling (FCC) and field cooled warming (FCW) magnetization data in 100 Oe and also between the cooling and warming data of zero field electrical resistivity. Electrical resistivity exhibits a metal to insulator like transition at TN in applied magnetic fields of 50 kOe and above. Colossal, negative magnetoresistance of ~82% 85% and 76% is observed at 50 K in 50 kOe field in R0.15Ca0.85MnO3 (R Y, Gd and Dy) manganites. Magnetocaloric effect (MCE) is estimated in terms of isothermal magnetic entropy change (DSm) and inverse MCE +DSm) is observed in the antiferromagnetically ordered state. The DSm changes sign for field changes greater than the metamagnetic critical magnetic field (Hc) Sign changing MCE signifies the evolution of underlying mixed magnetic interactions in these systems with variations in magnetic field and temperature.
THE ROLE OF KNOWLEDGE MANAGEMENT IN ACHIEVING SUSTAINABLE COMPETITIVE ADVANTAGE IN BUSINESS
Year: 2017

Companies are struggling to gain sustainable competitive advantage in order to survive among aggressive huge competitors. To achieve that, companies must know how to create, share and use the knowledge through the company and aligning it to the company strategy and process as well. Besides, managers have to realize which knowledge strategy should be chose to improve the company's activities to gain sustainable competitive advantage. This is a case study that attempt to demonstrate how companies use organizational knowledge and knowledge management to gain sustaining competitive advantage. Knowledge Management Networking Value chain theory has been applyied to explain how the value of a knowledge network increases as the number of the members increases in Toyota. Explaining strategies that Toyota adopted to create and transfer knowledge to subsidiaries abroad in order to give a chance to local markets to create knowledge in foreign markets. In the end of this study, it can be determine how knowledge management concept is a necessary tool to gain competitive advantage for the companies especially automotive industry. KeywordsKnowledge Management, Competitive Advantage, Organizational Knowledge, Knowledge Creation, Knowledge Sharing.
Adaptive graph regularized fixed rank representation for subspace segmentation
Venue: Pattern Analysis and Applications
Year: 2019

Low rank representation (LRR) has shown its great power in subspace segmentation tasks. However, by using matrix factorization skill, fixed rank representation dominates LRR in many subspace segmentation applications. In this paper, based on the depth analyses on fixed rank representation (FRR) we propose a new graph regularized FRR method which is termed adaptive graph regularized fixed rank representation (AGFRR) Different from the existing methods which use the original data set to build the graph regularizer for a reconstruction coefficient matrix, AGFRR uses one of the matrix factor of a reconstruction matrix to construct the graph regularizer for the reconstruction matrix itself. We claim that the constructed graph regularizer can discover the manifold structure of a given data set more faithfully. Hence, AGFRR is more suitable for revealing the nonlinear subspace structures of data sets than FRR. Moreover, an optimization algorithm for solving AGFRR problem is also provided. Finally, the subspace segmentation experiments on both synthetic and real world data sets show that AGFRR is superior to the existing LRR and FRR related algorithms.
Preventing occupational stress in healthcare workers
Year: 2018

The National Institute for Occupational Safety and Health (NIOSH) defines occupational stress as "the harmful physical and emotional responses that occur when the requirements of the job do not match the capabilities, resources, or needs of the worker" (NIOSH, 2008) Healthcare workers have been identified as being at high risk for occupational or work related stress due to exposure to stressors at work. For example, in the United Kingdom, the healthcare sector has the highest estimated prevalence of work related stress (Health and Safety Executive, 2013) This stress is a consequence of organizational factors and a mismatch between demands, skills, and social support at work, or any combination of these. Factors that have been shown to increase the risk of stress include increasing workload, emotional response to contact with suffering and dying patients and organizational problems and conflict (McNeely, 2005; Payne&FirthCozens, 1987) A European survey on working conditions revealed that the healthcare sector rated highest on two significant causes of stress: hiding ones' own emotions and adverse social behavior (Eurofound, 2012) The consequences of occupational stress on healthcare workers include severe distress, burnout, or psychosomatic diseases and a corresponding decline in quality of life and their quality of care or service provision (Weinberg and Creed, 2000) There is also an economic impact of occupational stress on healthcare organizations through increased rates of absenteeism and turnover (Jacobson et al. 1996;  2005) and compensation claims (Williamson, 1994) Three strategies to combat occupational stress are acknowledged (Ruotsalainen, Verbeek, Marine, Serra, 2015) First, cognitive behavioral training (CBT) provides new ways for the person to feel, think, and act in stressful situations. Second, mental or physical relaxation techniques work by diverting attention away from unpleasant and stressful thoughts and feelings and help to foster resilience in the person. Third, organizational interventions, in which work practices are adjusted to match and make better use of workers' capabilities, help to prevent stressful events from occurring.
Loop based conic multivariate adaptive regression splines is a novel method for advanced construction of complex biological networks
Venue: Eur. J. Oper. Res.
Year: 2018

The Gaussian Graphical Model (GGM) and its Bayesian alternative, called, the Gaussian copula graphical model (GCGM) are two widely used approaches to construct the undirected networks of biological systems. They define the interactions between species by using the conditional dependencies of the multivariate normality assumption. However, when the system's dimension is high, the performance of the model becomes computationally demanding, and, particularly, the accuracy of GGM decreases when the observations are far from normality. Here, we suggest a Conic Multivariate Adaptive Regression Splines (CMARS) as an alternative to GGM and GCGM to ameliorate both problems. CMARS is a modified version of the Multivariate Adaptive Regression Spline, a well known modeling approaches used in Operational Research (OR) to represent biological, environmental, and economic data. The main benefit of this model is its compatibility with high dimensional and correlated measurements of serious nonlinearity, which allows for a wide field of application. We adapted CMARS to describe biological systems and called it "LCMARS" due to its loop based description. We then applied LCMARS to simulated and real datasets, and LCMARS produced more accurate results compared to GGM and GCGM. Hereby, the ability to use LCMARS in the description of biological networks has the potential to open up new avenues in the application of OR to computational biology and bioinformatics, and can thus help us better understanding complex diseases like cancer and hepatitis.
Does Parental Involvement Matter for Students' Mental Health in Middle School?
Venue: School psychology
Year: 2019

Middle school is a risky period, marked by increased peer victimization, and the onset of several mental disorders, including suicidal thoughts and behaviors (STBs) Parental involvement is critical to students' well being; however, few studies have examined the role of parental involvement among middle school students or its effect on their mental health. This study examined the effects of perceived parental involvement and victimization on adolescents' mental health difficulties (MHDs) and STBs. We also investigated whether these effects varied across demographic groups, and whether perceived parental involvement buffers the relationship between victimization and students' mental health outcomes. The sample consisted of 301,628 students (50.7% female) from 615 middle schools (Grades 6 to 8) in Georgia (United States) Hierarchical linear modeling showed that higher student level perceived parental involvement was related to fewer MHDs (b 0.20) and STBs (b 0.10) and higher school level perceived parental involvement was related to fewer STBs (b 0.11) However, higher student level (b 0.25, 0.08) and school level (b 0.37, 0.10) traditional victimization were associated with more MHDs and STBs. Student level perceived parental involvement was also more positively related to MHDs and STBs for 6th (b 0.06, 0.04) and 7th graders (b 0.03, 0.02) than for 8th graders, and it was more negatively related to MHDs (b 0.24) and STBs (b 0.13) for girls than for boys. Perceived parental involvement also moderated the relationships among traditional victimization, cyber victimization MHDs, and STBs. Implications are discussed relating to how schools can promote parental involvement and student mental health.
Echo State networks and Neural network Ensembles to predict Sunspots activity
Venue: ESANN
Year: 2009

Echo state networks (ESN) and ensembles of neural networks are developed for the prediction of the monthly sunspots series. Through numerical evaluation on this benchmark data set it has been shown that the feedback ESN models outperform feedforward MLP. Furthermore, it is shown that median fusion lead to robust predictors, and even can improve the prediction accuracy of the best individual predictors.
Responses to work intensification: does generation matter?
Year: 2012

Work intensification can be an organisational tool to increase the productivity of an existing workforce. We investigate employee reactions to three levels of sustained extensive work intensification (long work hours over two consecutive time periods) of the two most prevalent generational groups in the labour market: Generation X and Baby Boomers. Boomers have been characterised as 'workaholics' who 'live to work' while Gen Xers are 'slackers' who 'work to live' We investigate, using a nationally representative sample of employees, whether these generational differences in work attitudes impact employee reactions (measured by employee reports of job satisfaction and work life balance) to sustained extensive work intensification. The results show that perceptions of job satisfaction and work life balance are reduced by sustained extensive work intensification but the differences between the two generations are minimal, suggesting that organisations do not need to tailor their employment practices to fit the work values of different generations.
Electronic Mobile Devices, Transformative Pedagogy and Learning: Higher Education and Changing Times in Kenya
Venue: Journal of Educational and Social Research
Year: 2019

The Fourth Industrial requires new concepts and skills to be acquired by learners at various levels. This has led to a new breed of learners joining our education institutions at various levels with prerequisite knowledge on technology which can be harnessed for learning and teaching purposes. This scenario has generated a lot of interest and more research on how first the process of knowledge acquisition is changing. There is excited attention among researchers, educators, education commentators and stakeholders on this aspect of learning. The new generations of techno savvy leaners joining institutions are a challenge to the old pedagogy of teaching. These young generations are creating a digital gap between the old ways of teaching and learning to new approaches in education. The nature of the generation change needs to bring some reforms in education especially in higher education in Kenya where electronic mobile devices penetration has escalated for the last ten years. This research paper, highlights issues around use of electronic mobile devices for knowledge acquisition purposes which if well utilized can aid the education systems in most African Countries in terms of access, affordability, ease of use and leaners wide interaction and independent study. The old pedagogy of the teacher being the absolute source of information is being transformed by the use of an array of emerging devices like Smartphone, ipads, laptops and others which are readily available to the leaner's. The study was carried out among undergraduate and postgraduate students at the University of Nairobi, Kenya between 2016 to 2018.The researchers found out that, electronic mobile devices are with the students for ease of use. The study also found out that, some of leaners in higher institutions of learning are not well informed on how to utilize the mobile devices for learning purposes hence most of the time they are used for other purposes not related to learning. In general, most countries in Africa have tried to invest on internet connectivity, ICT Infrastructure, capacity building among others structure which can also be leveraged for Education needs.
Addressing Fairness, Bias, and Appropriate Use of Artificial Intelligence and Machine Learning in Global Health
Venue: Frontiers in Artificial Intelligence
Year: 2020

In Low and Middle Income Countries (LMICs) machine learning (ML) and artificial intelligence (AI) offer attractive solutions to address the shortage of health care resources and improve the capacity of the local health care infrastructure. However, AI and ML should also be used cautiously, due to potential issues of fairness and algorithmic bias that may arise if not applied properly. Furthermore, populations in LMICs can be particularly vulnerable to bias and fairness in AI algorithms, due to a lack of technical capacity, existing social bias against minority groups, and a lack of legal protections. In order to address the need for better guidance within the context of global health, we describe three basic criteria (Appropriateness, Fairness, and Bias) that can be used to help evaluate the use of machine learning and AI systems: 1) APPROPRIATENESS is the process of deciding how the algorithm should be used in the local context, and properly matching the machine learning model to the target population; 2) BIAS is a systematic tendency in a model to favor one demographic group vs another, which can be mitigated but can lead to unfairness; and 3) FAIRNESS involves examining the impact on various demographic groups and choosing one of several mathematical definitions of group fairness that will adequately satisfy the desired set of legal, cultural, and ethical requirements. Finally, we illustrate how these principles can be applied using a case study of machine learning applied to the diagnosis and screening of pulmonary disease in Pune, India. We hope that these methods and principles can help guide researchers and organizations working in global health who are considering the use of machine learning and artificial intelligence.