nils-herrmann/clean_scirepeval huggingface dataset:
Developing graduate employability skills and attributes: curriculum enhancement through work integrated learning
Year: 2017

Work integrated learning (WIL) is considered a key strategy for promoting graduate employability. Graduate employability is a complex concept, one which has broadened in recent years to encapsulate a diverse range of skills, attributes, and other measures such as networks, professional identity and active citizenship. This special issue presents recent scholarship on WIL and employability, addressing the question of how WIL contributes to enhancing employability outcomes for students and graduates. The importance of embedding WIL experiences in the curriculum so they are effectively supported by appropriate pedagogical strategies is emphasized, as well as the provision of quality assessment to support employability outcomes. Such supports, while critical, have resourcing implications for higher education, including impacts on staff workload which also need to be considered. Employability is considered in relation to the related construct of employment outcomes, pointing to ways in which these two perspectives can be better integrated. Recommendations are made for future research.
Parallel WaveNet: Fast High Fidelity Speech Synthesis
Venue: ICML
Year: 2018

The recently developed WaveNet architecture is the current state of the art in realistic speech synthesis, consistently rated as more natural sounding for many different languages than any previous system. However, because WaveNet relies on sequential generation of one audio sample at a time, it is poorly suited to today's massively parallel computers, and therefore hard to deploy in a real time production setting. This paper introduces Probability Density Distillation, a new method for training a parallel feed forward network from a trained WaveNet with no significant difference in quality. The resulting system is capable of generating high fidelity speech samples at more than 20 times faster than real time, and is deployed online by Google Assistant, including serving multiple English and Japanese voices.
Breast Cancer Disease Prediction With Recurrent Neural Networks (RNN)
Year: 2020

Cancer is a collaborative amalgamation of diseases that involves abnormal increase in cell growth with the potential of occupying and attacking the entire body. According to studies, breast cancer most likely occurs in women and it has become the second biggest cause of female death. Due to its widespread penetration and significance, many researchers have analyzed the phenomenon and further studies are still required to reach an optimum outcome. This study applies deep learning technique in conjunction with Recurrent Neural Networks (RNN) to predict the formation of breast cancer disease so that doctors will perform the diagnosis more properly. To assess the efficiency of the proposed method, breast cancer data belonging to UC Irvine repository were used. Precision, recall, accuracy, and f1 score of the proposed method showed good scores and the proposed technique performed well.
Spatial clustering of time series via mixture of autoregressions models and Markov random fields
Year: 2016

Time series data arise in many medical and biological imaging scenarios. In such images, a time series is obtained at each of a large number of spatially dependent data units. It is interesting to organize these data into model based clusters. A two stage procedure is proposed. In stage 1, a mixture of autoregressions (MoAR) model is used to marginally cluster the data. The MoAR model is fitted using maximum marginal likelihood (MMaL) estimation via a minorization maximization (MM) algorithm. In stage 2, a Markov random field (MRF) model induces a spatial structure onto the stage 1 clustering. The MRF model is fitted using maximum pseudolikelihood (MPL) estimation via an MM algorithm. Both the MMaL and MPL estimators are proved to be consistent. Numerical properties are established for both MM algorithms. A simulation study demonstrates the performance of the two stage procedure. An application to the segmentation of a zebrafish brain calcium image is presented.
A Depth Video based Human Detection and Activity Recognition using Multi features and Embedded Hidden Markov Models for Health Care Monitoring Systems
Venue: Int. J. Interact. Multim. Artif. Intell.
Year: 2017

Increase in number of elderly people who are living independently needs especial care in the form of healthcare monitoring systems. Recent advancements in depth video technologies have made human activity recognition (HAR) realizable for elderly healthcare applications. In this paper, a depth video based novel method for HAR is presented using robust multi features and embedded Hidden Markov Models (HMMs) to recognize daily life activities of elderly people living alone in indoor environment such as smart homes. In the proposed HAR framework, initially, depth maps are analyzed by temporal motion identification method to segment human silhouettes from noisy background and compute depth silhouette area for each activity to track human movements in a scene. Several representative features, including invariant, multi view differentiation and spatiotemporal body joints features were fused together to explore gradient orientation change, intensity differentiation, temporal variation and local motion of specific body parts. Then, these features are processed by the dynamics of their respective class and learned, modeled, trained and recognized with specific embedded HMM having active feature values. Furthermore, we construct a new online human activity dataset by a depth sensor to evaluate the proposed features. Our experiments on three depth datasets demonstrated that the proposed multi features are efficient and robust over the state of the art features for human action and activity recognition.
A learning framework for temporal recommendation without explicit iterative optimization
Venue: Appl. Soft Comput.
Year: 2018

Pushing accurate and prompt recommendations to diverse users is an on going key challenge for researchers in studying recommender systems, which is also known as temporal recommendation. Thereby, modeling to capture every single user's preference dynamically and accurately is the core. In this work, we propose a hybrid model to exploit user's periodical feature for his/her behaviors over time such as purchasing on line goods which essentially can reflect one's preference on some types of items. An outstanding merit of the proposed model is that, in contrast to traditional model based methods, it is free of explicit iterative optimization process. Meanwhile, we introduce an improved Markov state computing method to perform temporal recommendation on three real movie rating data sets which obtains a systematic improvement in computational efficiency compared with traditional model based approaches and moreover, it is better than neighborhood based collaborative filtering methods and the state of the art temporal recommendation models with respect to the results of recommendation accuracy. In addition, further analyses verify that the proposed learning framework has the capacity in capturing user's personalized preference from a perspective of temporal dynamics.
The Role of Sleep in Learning and Memory
Year: 2014

1048 (2001) 294 Science Pierre Maquet The Role of Sleep in Learning and Memory This copy is for your personal, non commercial use only. clicking here. colleagues, clients, or customers by you can order high quality copies for your If you wish to distribute this article to others here. following the guidelines can be obtained by Permission to republish or repurpose articles or portions of articles February 10, 2014 www.sciencemag.org (this information is current as of The following resources related to this article are available online at http:/www.sciencemag.org/content/294/5544/1048.full.html version of this article at: including high resolution figures, can be found in the online Updated information and services, 252 article(s) on the ISI Web of Science cited by This article has been http:/www.sciencemag.org/content/294/5544/1048.full.html#related urls 67 articles hosted by HighWire Press; see: cited by This article has been http:/www.sciencemag.org/cgi/collection/neuroscience Neuroscience subject collections: This article appears in the following
Group Intervention for Adolescent Anxiety and Depression: Outcomes of a Randomized Trial with Adolescents in Kenya.
Venue: Behavior therapy
Year: 2020

Youth mental health interventions in low resource communities may benefit from including empirically supported elements, using stigma free content, and using trained lay providers. We developed and evaluated such an intervention, targeting adolescent depression and anxiety in Kenya, where mental health care is limited by social stigma and a paucity of providers. Kenyan adolescents (N 51, ages 14 17, 60.78% female) from a school in an urban slum in Nairobi with self reported moderate to severe symptoms of depression or anxiety were randomized to the 4 week "Shamiri" "thrive" group intervention or a study skills control intervention of equal duration. The Shamiri intervention included growth mindset, gratitude, and value affirmation exercises. The content was delivered by recent high school graduates (ages 17 21, 60% male) trained as lay providers. Participants met in school once a week in groups of 9 12 youths (average group size 10) Compared to the study skills control, Shamiri produced greater reductions in adolescent depression symptoms (p .038; d .32) and anxiety symptoms (p .039; d .54) from baseline to 4 week follow up, and greater improvements in academic performance (p .034; d .32) from the school term before versus after the intervention. There were no effects on overall social support or perceived control, but the Shamiri group showed larger increases in perceived social support from friends (p .028, d .71) This appears to be the first report that a brief, lay provider delivered, community based intervention may reduce internalizing symptoms and improve academic outcomes in high symptom adolescents in Sub Saharan Africa. Larger replications with extended follow ups will help gauge the strength and durability of these effects.
The Evaluation of Pharmacy Strategic Plan in Past 2013 2016 and Forecasting of New Vision 2030 at Ministry of Health in Saudi Arabia
Year: 2018

To explore the outcomes of strategic plan implementations in past 2013 2016 and to update the pharmacy strategic plan based on new Saudi vision 2030.  It is a cross sectional follow up, monitor, and forecasting of General Administration of the pharmaceutical care strategic plan in 2016 2020. The authors review all six strategic plan, seventeen initiatives, and eighty three projects. The Assessment from the baseline before applying the strategic plan 2013 to 2016 at MOH hospitals and primary care centers. The new updating of a strategic plan based new vision of Ministry of Health and Saudi vision 2030 and correlate with them accordingly.  The total project of past strategic plan was 84 projects. The total number of fully implemented projects were at hospital 29 (34.5% projects, and primary care centers were 19 (22.6% projects. The total number of some implemented programs at the hospital was 28 33.33% while at primary care centers were 26 (30.95% projects. The total number not implemented at hospitals were 25 29.76% while at primary care centers were 36 42.85% The total number of new projects added to the new plan was seven, and a total number of deleted projects was one. The total number of projects with new strategic plan vision 2030 were ninety projects.  The last pharmacy strategic plan at Ministry of Health organization was beneficial during 2013 2016. Several programs implemented for the first time. That is including but not limited to stewardship of antimicrobial program, pain management program, and medication safety program. The new updating pharmacy strategic plan compatible and support the Ministry of Health and Kingdom of Saudi Arabia new strategic plan with new vision 2030.  Pharmacy, Strategic plan, Forecasting, Vision 2030, Ministry of Health, Saudi Arabia.
Upframing Service Design and Innovation for Research Impact
Year: 2018

Service design and innovation are receiving greater attention from the service research community because they play crucial roles in creating new forms of value cocreation with customers, organizations, and societal actors in general. Service innovation involves a new process or service offering that creates value for one or more actors in a service network. Service design brings new service ideas to life through a human centered and holistic design thinking approach. However, service design and innovation build on dispersed multidisciplinary contributions that are still poorly understood. The special issue that follows offers important contributions through the examination of service design and innovation literature, the links between service design and innovation, the role of customers in service design and innovation, and service design and innovation for well being. Building on these contributions, this article develops a future research agenda in three areas: (1) reinforcing and expanding the foundations of service design and innovation by integrating multiple perspectives and methods; (2) advancing service design and innovation by improving the connection between the two areas, deepening actor involvement, and leveraging the role of technology; and (3) upframing service design and innovation to strengthen research impact by innovating complex value networks and service ecosystems and by building a cornerstone for transformative service research.
The role of radiology in diagnostic error: a medical malpractice claims review
Venue: Diagnosis
Year: 2017

Just as radiologic studies allow us to see past the surface to the vulnerable and broken parts of the human body, medical malpractice claims help us see past the surface of medical errors to the deeper vulnerabilities and potentially broken aspects of our healthcare delivery system. And just as the insights we gain through radiologic studies provide focus for a treatment plan for healing, so too can the analysis of malpractice claims provide insights to improve the delivery of safe patient care. We review 1325 coded claims where Radiology was the primary service provider to better understand the problems leading to patient harm, and the opportunities most likely to improve diagnostic care in the future.
An Attitude Strength and Self Perception Framework Regarding the Bi directional Relationship of Job Satisfaction with Extra Role and In Role Behavior: The Doubly Moderating Role of Work Centrality
Venue: Front. Psychol.
Year: 2016

Studies have identified variables either moderating the extent to which job satisfaction predicts work behavior or moderating the reverse impact of work behavior on job satisfaction. Based on an attitude strength and self perception framework, we argue that certain variables may moderate both the predictive utility of job satisfaction for work behavior and the impact of work behavior on job satisfaction. Specifically focusing on work centrality, we hold that high work centrality renders job satisfaction a strong job attitude, whereas low work centrality renders job satisfaction a weak job attitude. Hence, the predictive utility of job satisfaction for both extra role behavior and in role behavior should be higher the more work is central to employees. In contrast, the influence of extra role behavior, but not of in role behavior, on job satisfaction should be higher the less work is central to employees. Results of a two wave study (N 176) were in line with these predictions. We discuss further variables that may play a similar role for the bi directional relationship between job satisfaction and work behavior.
3D Printed Capacitive Pressure Sensing Sole for Anthropomorphic Robots
Venue: 2021 IEEE International Conference on Flexible and Printable Sensors and Systems (FLEPS)
Year: 2021

This paper presents a newly designed, 3D printed pressure sensitive sole to obtain the tactile sensing data from humanoid foot during standing or walking. The device was tested for high amounts of pressure that are typical during walking of an anthropomorphic robot. The capacitive pressure sensor embedded in the sole was obtained by 3D printing of the conductive flexible electrodes and a two part rubber as the dielectric with microbubbles to increase the sensitivity. The 3D printed sensor was fabricated simultaneously with its packaging to increase its durability. The sensor was tested both for static and dynamic conditions and the average sensitivity was found to be 0.0004 KPa 1. The proof of concept device showed good response when it was stepped upon thus proving its applicability for applications with large load or pressures.
Model Pengendalian Internal Berbasis Sarbanes Oxley Act dan Keandalan Pelaporan Keuangan (Studi Internal Audit Pada Perusahaan Publik di Indonesia)
Year: 2016

This study focus on internal control application based on the Sarbanes Oxley Act. The research objective is to examine the impact of Sarbanes Oxley Act implementation and the financial reporting reliability toward audit quality and audit opinion. The research is conducted on public companies implementing Sarbanes Oxley Act in Indonesia. The internal audit section in the companies are used as respondents. Based on questionnaires distributed, there were 35 samples of public companies used in this research. This study employs WarpPLS to handle the SEM model in testing the hypotheses and multigroup analysis to conduct the sensitivity analysis. The research's results showed that application of Sarbanes Oxley Act based internal control and financial reporting reliability are positively affect the audit opinions and directly influence the audit quality. However, the independent auditor's opinion is not a moderating variables between other variables. The research results are expected to be used as considerations by the companies in implementation of Sarbanes Oxley Act based internal control.
Refeeding syndrome is associated with increased mortality in malnourished medical inpatients
Venue: Medicine
Year: 2020

Whether the occurrence of refeeding syndrome (RFS) a metabolic condition characterized by electrolyte shifts after initiation of nutritional therapy, has a negative impact on clinical outcomes remains ill defined. We prospectively investigated a subgroup of patients included in a multicentre, nutritional trial (EFFORT) for the occurrence of RFS.  In this secondary analysis of a randomized controlled trial investigating the effects of nutritional support in malnourished medical inpatients, we prospectively screened patients for RFS and classified them as "RFS confirmed" and "RFS not confirmed" based on predefined criteria (i.e. electrolyte shifts, clinical symptoms, clinical context, and patient history) We assessed associations of RFS and mortality within 180 days (primary endpoint) and other secondary endpoints using multivariable regression analysis.  Among 967 included patients, RFS was confirmed in 141 (14.6% patients. Compared to patients with no evidence for RFS, patients with confirmed RFS had significantly increased 180 days mortality rates (42/141 (29.8% vs 181/826 (21.9% adjusted odds ratio (OR) 1.53 (95% CI 1.02 to 2.29) P .05) Patients with RFS also had an increased risk for ICU admission (6/141 (4.3% vs 13/826 (1.6% adjusted OR 2.71 (95% CI 1.01 to 7.27) P .05) and longer mean length of hospital stays (10.5 6.9 vs 9.0 6.6 days, adjusted difference 1.57 days (95% CI 0.38 2.75) P .01)  A relevant proportion of medical inpatients with malnutrition develop features of RFS upon hospital admission, which is associated with long term mortality and other adverse clinical outcomes. Further studies are needed to develop preventive strategies for RFS in this patient population.
A COMPLEXIDADE DO RACISMO ESTRUTURAL: REDUCAO DE TRABALHADORES A CONDICAO ANALOGA A DE ESCRAVOS COMO CONTINUISMO DO SISTEMA ECONOMICO ESCRAVOCRATA
Year: 2020

The objective is to discern the bases of structural racism in Brazil, in order to understand why contemporary slave labor in Brazil must be faced from this logic, in the scope that if its mitigation occurs in a sustainable way. Methodology is qualitative, based on the nuances of the bibliographic and documentary review. Structural racism is perceived as the causal source of the normalization of the practice of reducing workers to the condition analogous to that of slaves and the reproduction and flowering of the practice, with the need for staggered modification of actions involving institutional and educational public policies.
Analysis of Bidirectional DC DC converter with Wide Voltage Gain for charging of Electric Vehicle
Venue: 2021 7th International Conference on Electrical Energy Systems (ICEES)
Year: 2021

In Electric Vehicles (EVs) a bidirectional converter is incorporated since the power flow will be in reverse direction while regenerative braking and by collecting this power, effective operation can be achieved. In this paper, description of Bidirectional DC DC converter has given with high voltage gain, continuous current conduction at both ports and good steady state response. The converter topology includes three MOSFET switches, two inductors and four capacitors. Moreover, efficiency of converter is increased by decreasing switching losses. This is applicable in Electric vehicles, Distribution Generation, Energy Storage Units and Micro grids. The proposed converter is designed for 1.5kW and 400V. The designed converter can be compared with conventional converters in terms of Voltage Gain and the steady state response to highlight the exclusiveness of the proposed converter.
Association between targeted somatic mutation (TSM) signatures and HGS OvCa progression
Venue: Cancer medicine
Year: 2016

Evidence already exists that the activation induced cytidine deaminase (AID/APOBEC) and the adenosine deaminase (ADAR) families of enzymes are implicated as powerful mutagens in oncogenic processes in many somatic tissues. Each deaminase is identified by the DNA or RNA nucleotide sequence "motif" surrounding the nucleotide targeted for deamination. The primary objective of this study is to develop an in silico approach to identify nucleotide sequence changes of the target motifs of key deaminases during oncogenesis. If successful, a secondary objective is to investigate if such changes are associated with disease progression indicators that include disease stage and progression free survival time. Using a discovery cohort of 194 high grade serous ovarian adenocarcinoma (HGS OvCa) exomes, the results confirm the ability of the novel in silico approach used to identify changes in the preferred target motifs for AID, APOBEC3G, APOBEC3B, and ADAR1 during oncogenesis. Using this approach, a set of new cancer progression associated signatures (C PASs) were identified. Furthermore, it was found that the C PAS identified can be used to differentiate between the cohort of patients that remained progression free for longer than 60 months, from those in which disease progressed within 60 months (sensitivity 95% specificity 90% The spectrum of outcomes observed here could provide a foundation for future clinical assessment of susceptibility variants in ovarian, and several other cancers as disease progresses. The ability of the in silico methodology used to identify changes in deaminase motifs during oncogenesis also suggests new links between immune system function and tumorigenesis.