nils-herrmann/clean_scirepeval huggingface dataset:
La inteligencia emocional como factor amortiguador del burnout academico y potenciador del engagement academico
Year: 2019

Los futuros profesionales de enfermeria requieren de una formacion integral que incluya aspectos teoricos y el desarrollo de habilidades emocionales. Estas ultimas, hacen referencia al desarrollo de la Inteligencia emocional, la cual, segun las investigaciones de la ultima decada, tendria una relacion con un mejor ajuste a las exigencias del medio universitario y/o laboral. El objetivo de esta investigacion fue relacionar los niveles de inteligencia emocional con los niveles del Sindrome de Burnout y Engagement academico en estudiantes de enfermeria de una Universidad del norte del pais, por medio de un estudio cuantitativo, correlacional, no experimental, transversal. La muestra fue de 189 alumnos de enfermeria, de ambos sexos, cursando entre el primer y octavo semestre de la malla academica, donde se realizo un muestreo probabilistico aleatorio. Los resultados evidenciaron correlacion entre los factores de claridad y regulacion emocional con ambos factores de Engagement (predisposicion y satisfaccion) Por otro lado, al correlacionar inteligencia emocional con Burnout academico, se evidencio, que el unico factor que correlaciono con las 3 dimensiones de Burnout fue regulacion emocional. Ademas, se demostro que a mayor claridad emocional menor seria el agotamiento y mayor la realizacion personal. Finalmente, se mostro que mayores niveles de Burnout correlacionaron con menores niveles de satisfaccion con los estudios.
Feedback Based Low Power Soft Error Tolerant Design for Dual Modular Redundancy
Venue: IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Year: 2018

Triple modular redundancy (TMR) which consists of three identical modules and a voting circuit, is a common architecture for soft error tolerance. However, the original TMR suffers from two major drawbacks: the large area overhead and the vulnerability of the voter. In order to overcome these drawbacks, we propose a new complementary dual modular redundancy (CDMR) scheme for mitigating the effect of soft errors. Inspired by the Markov random field (MRF) theory, a two stage voting system is implemented in CDMR, including a first stage optimal MRF structure and a second stage high performance merging unit. The CDMR scheme can reduce the voting circuit area by 20% while saving the area of one redundant module, achieving at least 26% error rate reduction at an ultralow supply voltage of 0.25 V with 8.33% faster timing compared to previous voter designs.
Monocular 3D Head Tracking to Detect Falls of Elderly People
Venue: 2006 International Conference of the IEEE Engineering in Medicine and Biology Society
Year: 2006

Faced with the growing population of seniors, Western societies need to think about new technologies to ensure the safety of elderly people at home. Computer vision provides a good solution for healthcare systems because it allows a specific analysis of people behavior. Moreover, a system based on video surveillance is particularly well adapted to detect falls. We present a new method to detect falls using a single camera. Our approach is based on the 3D trajectory of the head, which allows us to distinguish falls from normal activities using 3D velocities
Authentication Integrity and Confidentiality in Encrypted Outsourced Databases
Year: 2007

In the Encrypted Outsourced Database (EODB) model, organizations outsource their data management to an external Application Service Provider (ASP) The organizations database is then hosted by this ASP. Such an ASP serves mechanisms for receiving and sending encrypted data from and to the outsourced database. One could think of operations like querying, creating or updating. This model extends and combines research issues related to data security: We investigate the problem of ensuring authentication, integrity and confidentiality in an outsourced database. Therefore we explore the applicability of authentication and integrity in outsourced databases and practical techniques for searches on encrypted data and show that the performance will be maintained.
Multipath Cooperative Routing with Efficient Acknowledgement for LEO Satellite Networks
Venue: IEEE Transactions on Mobile Computing
Year: 2019

Multipath routing can significantly improve the network throughput and end to end (e2e) delay. Network coding based multipath routing removes the complicated coordination among multiple paths so that it further enhances data transmission efficiency. Traditional network coding based multipath routing protocols, however, are inefficient for Low Earth Orbit (LEO) satellite networks with the long link delay and regular network topology. Considering these characteristics, in this paper, we first formulate the multipath cooperative routing problem, then propose a Network Coding based Multipath Cooperative Routing (NCMCR) protocol for LEO satellite networks to improve the throughput. We propose source based and destination based multipath cooperative routing algorithms, which deliver different parts of a data flow along multiple link disjoint paths dynamically and cooperatively. Furthermore, we design an efficient No Stop Wait ACK mechanism for our NCMCR protocol to accelerate the data transmission, where a source node continuously sends subsequent batches before it receives ACK messages for the batches sent previously. Under the proposed acknowledgement mechanism, we theoretically analyze the number of coded packets that should be sent and the transmission times of each batch for successfully decoding a batch. NS2 based simulation results demonstrate that our NCMCR outperforms the most related protocols.
Comparison of the level of cognitive processing between case based items and non case based items on the Interuniversity Progress Test of Medicine in the Netherlands
Venue: Journal of educational evaluation for health professions
Year: 2018

It is assumed that case based questions require higher order cognitive processing, whereas questions that are not case based require lower order cognitive processing. In this study, we investigated to what extent case based and non case based questions followed this assumption based on Bloom's taxonomy.  In this article, 4,800 questions from the Interuniversity Progress Test of Medicine were classified based on whether they were case based and on the level of Bloom's taxonomy that they involved. Lower order questions require students to remember or/and have a basic understanding of knowledge. Higher order questions require students to apply, analyze, or/and evaluate. The phi coefficient was calculated to investigate the relationship between whether questions were case based and the required level of cognitive processing.  Our results demonstrated that 98.1% of case based questions required higher level cognitive processing. Of the non case based questions, 33.7% required higher level cognitive processing. The phi coefficient demonstrated a significant, but moderate correlation between the presence of a patient case in a question and its required level of cognitive processing (phi coefficient= 0.55, P< 0.001)  Medical instructors should be aware of the association between item format (case based versus non case based) and the cognitive processes they elicit in order to meet the desired balance in a test, taking the learning objectives and the test difficulty into account.
Is the Emerging Source Citation Index an aid to assess the citation impact in social science and humanities?
Venue: J. Informetrics
Year: 2020

This paper aims to analyze the implications of the Emerging Source Citation Index (ESCI) from Clarivate Analytics, as an assessment tool. Based on the evidence that the ESCI has expanded publication coverage, primarily in the social science and humanities, this study poses the following questions. How much has coverage been expanded by field and subject category? What effect has inclusion had on impact factors? Have they risen significantly in any discipline? Is subscribing to this product worthwhile? Should it be taken into consideration for assessment purposes? The results obtained show that sub fields such as Ethics, Poetry, Cultural Studies or Asian Studies improve their visibility with the inclusion of journals in ESCI. Although at the scientific level, CSEC does not seem to improve the evaluation of impact measurement, this new citation index can provide relevant information for evaluation at the micro and meso level. Since it includes widely cited documents (in both the top 1% and top 10% in many disciplines not indexed in the core collection the use of this source can improve the completeness and quality of the analysis of citations from individual groups or institutions in subfields such as Poetry, Cultural studies or Asian studies. It is advisable to carry out periodic studies to analyse the evolution of the impact since, in disciplines with a reduced production and a low number of citations, the data are very sensitive to variations (especially if they are recent publications)
Efficacy of computed image modification of capsule endoscopy in patients with obscure gastrointestinal bleeding.
Venue: World journal of gastrointestinal endoscopy
Year: 2012

To investigate whether flexible spectral color enhancement (FICE) improves diagnostic yields of capsule endoscopy (CE) for obscure gastro intestinal bleeding (OGIB)  The study subjects consisted of 81 patients. Using FICE, there were three different sets with different wavelengths. Using randomly selected sets of FICE, images of CE were evaluated again by two individuals who were not shown the conventional CE reports and findings. The difference between FICE and conventional imaging was examined.  The overall diagnostic yields in FICE sets 1, 2, 3 and conventional imaging (48.1% were 51.9% 40.7% 51.9% and 48.1% respectively, which showed no statistical difference compared to conventional imaging. The total numbers of detected lesions per examination in FICE imaging and conventional imaging were 2.5 2.1 and 1.8 1.7, respectively, which showed a significant difference (P 0.01) CONCLUSION The diagnostic yield for OGIB is not improved by FICE. However, FICE can detect significantly more small bowel lesions compared to conventional imaging.
Impact of the Global Financial Crisis on China: Empirical Evidence and Policy Implications
Year: 2009

This paper applies a structural vector autoregression analysis to quantify the impact of the global financial crisis on China. It is found that the impact is indeed sizeable: a 1 percent decline in economic growth in the USA, the EU and Japan is likely to lead to a 0.73 percent decline in growth in China. The article discusses whether the current measures of fiscal stimulus are adequate to offset the sharp decline in external demand. Although there is little doubt that the massive fiscal stimulus will largely offset the significant shortfalls in external demand, the current growth pattern in China will be increasingly unsustainable in the long term. China's reform cycles suggest that external shocks are often opportunities for structural reforms. Therefore, the crisis could also be a catalyst for rebalancing China's economic structure so as to return the economy to a sustainable path.
Role of Yoga and Mindfulness in Severe Mental Illnesses: A Narrative Review
Venue: International journal of yoga
Year: 2019

Yoga has its origin from the ancient times. It is an integration of mind, body, and soul. Besides, mindfulness emphasizes focused awareness and accepting the internal experiences without being judgemental. These techniques offer a trending new dimension of treatment in various psychiatric disorders.  We aimed to review the studies on the efficacy of yoga and mindfulness as a treatment modality in severe mental illnesses (SMIs) SMI includes schizophrenia, major depressive disorder (MDD) and bipolar disorder (BD)  We conducted a literature search using PubMed, Google Scholar, and Cochrane Library with the search terms "yoga," "meditation," "breathing exercises," "mindfulness," "schizophrenia spectrum and other psychotic disorders," "depressive disorder," and "bipolar disorder" for the last 10 year period. We also included relevant articles from the cross references.  We found that asanas and pranayama are the most commonly studied forms of yoga for schizophrenia. These studies found a reduction in general psychopathology ratings and an improvement in cognition and functioning. Some studies also found modest benefits in negative and positive symptoms. Mindfulness has not been extensively tried, but the available evidence has shown benefits in improving psychotic symptoms, improving level of functioning, and affect regulation. In MDD, both yoga and mindfulness have demonstrated significant benefit in reducing the severity of depressive symptoms. There is very sparse data with respect to BD.  Both yoga and mindfulness interventions appear to be useful as an adjunct in the treatment of SMI. Studies have shown improvement in the psychopathology, anxiety, cognition, and functioning of patients with schizophrenia. Similarly, both the techniques have been established as an effective adjuvant in MDD. However, more rigorously designed and larger trials may be necessary, specifically for BD.
Are High Interest Loans Predatory? Theory and Evidence from Payday Lending
Year: 2021

It is often argued that people might take on too much high cost debt because they are present focused and/or overoptimistic about how soon they will repay. We measure borrowers' present focus and overoptimism using an experiment with a large payday lender. Although the most inexperienced quartile of borrowers underestimate their likelihood of future borrowing, the more experienced three quartiles predict correctly on average. This finding contrasts sharply with priors we elicited from 103 payday lending and behavioral economics experts, who believed that the average borrower would be highly overoptimistic about getting out of debt. Borrowers are willing to pay a significant premium for an experimental incentive to avoid future borrowing, which we show implies that they perceive themselves to be time inconsistent. We use borrowers' predicted behavior and valuation of the experimental incentive to estimate a model of present focus and naivete. We then use the model to study common payday lending regulations. In our model, banning payday loans reduces welfare relative to existing regulation, while limits on repeat borrowing might increase welfare by inducing faster repayment that is more consistent with long run preferences. Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.
Review of Deep Learning Methods in Robotic Grasp Detection
Year: 2018

For robots to attain more general purpose utility, grasping is a necessary skill to master. Such general purpose robots may use their perception abilities to visually identify grasps for a given object. A grasp describes how a robotic end effector can be arranged to securely grab an object and successfully lift it without slippage. Traditionally, grasp detection requires expert human knowledge to analytically form the task specific algorithm, but this is an arduous and time consuming approach. During the last five years, deep learning methods have enabled significant advancements in robotic vision, natural language processing, and automated driving applications. The successful results of these methods have driven robotics researchers to explore the use of deep learning methods in task generalised robotic applications. This paper reviews the current state of the art in regards to the application of deep learning methods to generalised robotic grasping and discusses how each element of the deep learning approach has improved the overall performance of robotic grasp detection. Several of the most promising approaches are evaluated and the most suitable for real time grasp detection is identified as the one shot detection method. The availability of suitable volumes of appropriate training data is identified as a major obstacle for effective utilisation of the deep learning approaches, and the use of transfer learning techniques is proposed as a potential mechanism to address this. Finally, current trends in the field and future potential research directions are discussed.
Building the Rainbow Nation. A critical analysis of the role of architecture in materializing a post apartheid South African identity
Year: 2012

Soon after apartheid was abolished in 1994, the quest for a new, 'authentic' South African identity resulted in the emergence of the "Rainbow Nation" idea, picturing an equal, multicultural and reconciled society. As architecture is considered a crucial element in the promotion of this Rainbow identity, the country witnessed a remarkable "building boom" with its apogee roughly between 1998 and 2010. Huge investments have been made in state driven projects which place the apartheid memory at the center of the architectural debate mostly museums and memorials. However, the focus of this paper shall lie on another, less highlighted tendency in current architectural practice. This paper demonstrates that, through the construction of urban community services, South African architects attempt to materialize the Rainbow Nation in a way that might be closer to the everyday reality of society.  architecture, post apartheid, Cape Town, South Africa, identity
ConFi: Convolutional Neural Networks Based Indoor Wi Fi Localization Using Channel State Information
Venue: IEEE Access
Year: 2017

As the technique that determines the position of a target device based on wireless measurements, Wi Fi localization is attracting increasing attention due to its numerous applications and the widespread deployment of Wi Fi infrastructure. In this paper, we propose ConFi, the first convolutional neural network (CNN) based Wi Fi localization algorithm. Channel state information (CSI) which contains more position related information than traditional received signal strength, is organized into a time frequency matrix that resembles image and utilized as the feature for localization. The ConFi models localization as a classification problem and addresses it with a five layer CNN that consists of three convolutional layers and two fully connected layers. The ConFi has a training stage and a localization stage. In the training stage, the CSI is collected at a number of reference points (RPs) and used to train the CNN via stochastic gradient descent algorithm. In the localization stage, the CSI of the target device is fed to the CNN and the localization result is calculated as the weighted centroid of the RPs with high output value. Extensive experiments are conducted to select appropriate parameters for the CNN and demonstrate the superior performance of the ConFi over existing methods.
The Behavior of Tip Clearance Flow at Near Stall Condition in a Transonic Axial Compressor Rotor
Year: 2007

It is known that the tip clearance flow is dominant and very important flow phenomena in axial compressor aerodynamics because the tip clearance flow has a great influence on the stability as well as aerodynamic loss of compressors. Our goal is to clarify the behavior of tip clearance flow at near stall condition in a transonic axial compressor rotor (NASA Rotor 37) In the present work, steady and unsteady RANS simulations were performed to investigate vortical flow structures and separated flow field near the tip for several different clearance cases. Boundary layer separation on the casing wall and blade suction surface was investigated in detail for near stall and stall condition. In order to understand such complicated flow field, vortex cores were identified using the critical point theory and a topology of the three dimensional separated and vortical flows was analyzed. In the nominal clearance case, the breakdown of tip leakage vortex has occurred at a near stall operating condition because of the interaction of the vortex with the shock wave, leading to a large blockage and unsteadiness in the rotor tip. On the other hand, the calculation with no clearance suggested that the separation on the suction surface was different from that with the nominal clearance. Since the shock wave induced the boundary layer separation on the blade suction surface in the transonic axial compressor rotor, focal type critical points appeared on the suction surface near the tip at near stall condition.
Regulation of pediatric intensive care unit nurse practitioner practice: A national survey
Venue: Journal of the American Association of Nurse Practitioners
Year: 2018

To describe the extent to which organizational regulation of pediatric intensive care unit (PICU) nurse practitioner (NP) practice and prescriptive authority aligns with state scope of practice (SSOP) regulations, to examine differences between PICU medical directors' and NPs' report of regulation, and to describe organizational level restriction of PICU NP practice.  A 34 item national, quantitative cross sectional descriptive survey of US PICU medical directors and NPs included demographic, institutional characteristics, and PICU NP regulation and role related questions. Invitations to participate were sent between October 2016 and January 2017.  Respondents (n 121, 60 PICU NPs and 61 PICU medical directors) reported that 30% of PICU NPs have additional organizational restrictions beyond their SSOP practice authority and 11% have prescriptive authority regulations that exceed those required by the SSOP regulations. Medical directors and lead NPs showed agreement in reports of NP practice regulation. Variation in organizational level restrictions of privileging, billing, and reporting structure practices were identified.  As more states move to full SSOP regulatory environments, organizational regulation of NP practice can impede attainment of full practice authority. Future research is needed to determine whether variations in regulation of PICU NP practice influence patient outcomes, interdisciplinary collaboration, and NP role actualization.
The impact of advertising self presentation style on customer purchase intention
Venue: Asia Pacific Journal of Marketing and Logistics
Year: 2019

The purpose of this paper is to propose the self presentation styles of advertising influence consumer self image, which in turn influence purchase intention.  Using virtual brands as stimuli in a series of experiments, this study collects data on consumer self image and purchase intention in the conditions of different advertising styles.  While consumer self image mediates the relationship between advertising self presentation style and purchase intention, the consumption situation (public vs private) moderates the relationship between self presentation style, consumer self image and purchase intention. That is, self enhancing advertising promotes customers' ideal self, which in turn increases their purchase intention for publicly consumed products, whereas self deprecating advertising solicits customers' real self, which in turn increases their purchase intention for privately consumed products.  This study informs product/brand managers and marketers of the importance of aligning the self presentation style of advertising with the consumption situation of the product being advertised.  Based on self consistency theory, this study not only finds a relationship between the self presentation style of advertising and purchase intention, but also uncovers the mediating role of self image in this relationship. Furthermore, the relationship chain of "self presentation style of advertising self image purchase intention" is moderated by the consumption situation of the product. This is one of the first studies to explore the intricacies of these relationships.