nils-herrmann/clean_scirepeval huggingface dataset:
The Influence of national innovation system on university industry research collaboration
Year: 2018

University Industry Research Collaboration (UIRC) is one of the key factors for continuous innovation. Existing literature argue that UIRC can be shaped by National Innovation System (NIS) However, empirical evidence that looks into factors of national innovation system that influence UIRC is still lacking. The main goal of this research was to propose a new framework based on system thinking theory by investigating the influence of national innovation system on university industry research collaboration. To achieve this aim, data were collected from research centers at Electrical and Chemical Engineering Departments of five research universities in Malaysia. Data were analyzed quantitatively using Statistical Package for the Social Sciences (SPSS) and Partial Least Squares Structural Equation Modeling (PLS SEM) Whereas, some qualitative data from top management of corresponding industries of research centers were analyzed using NVivo 11. Results from the study revealed that technological infrastructure system, financing system, intellectual property right system, the culture of innovation and education and skills system have some influence on UIRC. Besides that, R&D cooperation, financial support, trustworthy culture, contractual agreement, intellectual capital, knowledge sharing and communication played significant roles as reinforcing factors in the relationship between NIS and UIRC. This study pioneered the application of system thinking theory in university industry link research. In terms of practical contribution, findings from the study may serve as a guideline for policymakers in formulating policies and strategies to strengthen the innovative capabilities of UIRC. The limitations of this study are the non inclusions of Ministry of Higher Education (MOHE) and the Ministry of Science, Technology and Innovation (MOSTI) as significant respondents other than research universities and their collaborated industries. It is recommended that future framework development could be expanded by exploring further factors that might have more effects on UIRC.
The Role of International Framework in Promoting Copyright protection in Cyber space
Year: 2016

The intellectual property is the wealth of nations. The misappropriation and destruction of this property can imbalance the economic infrastructure of the nation. When it comes to the copyright in cyber space, it is very much vulnerable to appropriations, as it would cheaply be reproduced. By introducing uniformity of applications to state laws internationally, the international conventions like Berne Convention, the WIPO Copyright Convention, the TRIPS Agreement, WIIPO Performances and Phonogram Treaty, 1996, have got a great role in Protection of Copyright in Cyber space. Further, USA, UK and European countries have also taken lead in this direction by enacting The Digital Millennium Copyright Act, 1998 (US) Internet and its ability of transmitting works almost at a lightning speed, copyright protection has become increasingly difficult. The problems created by recent technological developments cannot be solved by the decisions of individual countries. With the Internet, copyrighted works remain vulnerable to outside piracy even if protected in the home country. The parallel growth of state laws as well as international treaties can meet the challenges that the law faces in this modern technological era.
A Two Centre Observational Study of Simultaneous Pulse Oximetry and Arterial Oxygen Saturation Recordings in Intensive Care Unit Patients
Venue: Anaesthesia and intensive care
Year: 2018

The influence of variables that might affect the accuracy of pulse oximetry (SpO2) recordings in critically ill patients is not well established. We sought to describe the relationship between paired SpO2/SaO2 (oxygen saturation via arterial blood gas analysis) in adult intensive care unit (ICU) patients and to describe the diagnostic performance of SpO2 in detecting low SaO2 and PaO2. A paired SpO2/SaO2 measurement was obtained from 404 adults in ICU. Measurements were used to calculate bias, precision, and limits of agreement. Associations between bias and variables including vasopressor and inotrope use, capillary refill time, hand temperature, pulse pressure, body temperature, oximeter model, and skin colour were estimated. There was no overall statistically significant bias in paired SpO2/SaO2 measurements; observed limits of agreement were 4.4% However, body temperature, oximeter model, and skin colour, were statistically significantly associated with the degree of bias. SpO2 <89% had a sensitivity of 3/7 (42.9% 95% confidence intervals, CI, 9.9% to 81.6% and a specificity of 344/384 (89.6% 95% CI 86.1% to 92.5% for detecting SaO2 <89% The absence of statistically significant bias in paired SpO2/SaO2 in adult ICU patients provides support for the use of pulse oximetry to titrate oxygen therapy. However, SpO2 recordings alone should be used cautiously when SaO2 recordings of 4.4% higher or lower than the observed SpO2 would be of concern. A range of variables relevant to the critically ill had little or no effect on bias.
Apuntes sobre la locura en el Virreinato del Peru
Venue: Revista de Neuro Psiquiatria
Year: 2019

La locura en el Virreinato del Peru fue explicada tanto en terminos medicos como sobrenaturales. La medicina se baso principalmente en la teoria de los cuatro humores. Para denominar la locura y sus diversas formas de manifestarse se utilizaron terminos tales como falta de juicio, insania, demencia, melancolia, mania y otros, con significados no equivalentes a los actuales. El cuidado de los locos estuvo en manos de los medicos, la familia o los religiosos. La Santa Inquisicion debio determinar si los procesados se encontraban o no en su sano juicio, recurriendo a diferentes estrategias ante los casos dudosos, incluyendo la opinion de los medicos. La psiquiatria surgio en el Peru mucho despues de la era virreinal, y sus intentos para explicar la locura en aquellos tiempos llevaron por un lado a una valiosa recoleccion de informacion, sobre todo por parte de Hermilio Valdizan y Oscar Valdivia Ponce, y por otro lado a la elaboracion de diagnosticos retrospectivos, que ilustran sobre el discurso nosologico de sus expositores. En los ultimos anos las opiniones psiquiatricas sobre el periodo virreinal se han centrado en la figura de Santa Rosa de Lima, llevando a planteamientos variopintos. Los diagnosticos retrospectivos se sustentan en premisas cuestionables, tales como atribuir una naturaleza transhistorica y transcultural a los trastornos mentales y a la idea de normalidad, asi como creer que existen fuentes historicas fidedignas que reflejan la verdad de los hechos.
Deep Interest with Hierarchical Attention Network for Click Through Rate Prediction
Venue: SIGIR
Year: 2020

Deep Interest Network (DIN) is a state of the art model which uses attention mechanism to capture user interests from historical behaviors. User interests intuitively follow a hierarchical pattern such that users generally show interests from a higher level then to a lower level abstraction. Modelling such interest hierarchy in an attention network can fundamentally improve the representation of user behaviors. We therefore propose an improvement over DIN to model arbitrary interest hierarchy: Deep Interest with Hierarchical Attention Network (DHAN) In this model, a multi dimensional hierarchical structure is introduced on the first attention layer which attends to individual item, and the subsequent attention layers in the same dimension attend to higher level hierarchy built on top of the lower corresponding layers. To enable modelling of multiple dimensional hierarchy, an expanding mechanism is introduced to capture one to many hierarchies. This design enables DHAN to attend different importance to different hierarchical abstractions thus can fully capture a user's interests at different dimensions (e.g. category, price or brand) To validate our model, a simplified DHAN is applied to Click Through Rate (CTR) prediction and our experimental results on three public datasets with two levels of one dimensional hierarchy only by category. It shows DHAN's superiority with significant AUC uplift from 12% to 21% over DIN. DHAN is also compared with another state of the art model Deep Interest Evolution Network (DIEN) which models temporal interest. The simplified DHAN also gets slight AUC uplift from 1.0% to 1.7% over DIEN. A potential future work can be combination of DHAN and DIEN to model both temporal and hierarchical interests.
Combination of domain knowledge and deep learning for sentiment analysis of short and informal messages on social media
Venue: Int. J. Comput. Vis. Robotics
Year: 2019

Sentiment analysis has been emerging recently as one of the major natural language processing (NLP) tasks in many applications. Especially, as social media channels (e.g. social networks or forums) have become significant sources for brands to observe user opinions about their products, this task is thus increasingly crucial. However, when applied with real data obtained from social media, we notice that there is a high volume of short and informal messages posted by users on those channels. This kind of data makes the existing works suffer from many difficulties to handle, especially ones using deep learning approaches. In this paper, we propose an approach to handle this problem. This work is extended from our previous work, in which we proposed to combine the typical deep learning technique of Convolutional Neural Networks with domain knowledge. The combination is used for acquiring additional training data augmentation and a more reasonable loss function. In this work, we further improve our architecture by various substantial enhancements, including negation based data augmentation, transfer learning for word embeddings, the combination of word level embeddings and character level embeddings, and using multitask learning technique for attaching domain knowledge rules in the learning process. Those enhancements, specifically aiming to handle short and informal messages, help us to enjoy significant improvement in performance once experimenting on real datasets.
Work Family Conflict Scale: Psychometric Properties of the Italian Version
Venue: SAGE Open
Year: 2019

In literature, there are many instruments for measuring the work family conflict (W F C) The Work Family Conflict Scale (WFCS) is one of the most used tools. This study aimed to evaluate its psychometric properties on a sample of 684 Italian workers (42.1% males, 57.9% females, mean age 45.51 10.91) We also evaluated if there were some demographic differences in the W F C, with relation to gender, the presence of children, and the kind of job (i.e. medical doctors and other health professionals, teachers and researchers, employees, manual workers, self employed workers) We found that the Italian WFCS has good psychometric properties. Moreover, contrary to our hypotheses, males experience higher W F C than females, and the lowest level of W F C characterize doctors and other health professionals. Manual workers and self employed workers seem to be the two job categories that experience the highest level of W F C.
The dry chain: Reducing postharvest losses and improving food safety in humid climates
Year: 2018

Even as increasing populations put pressure on food supplies, about one third of the total food produced for human consumption is wasted, with the majority of loss in developing countries occurring between harvest and the consumer. Controlling product dryness is the most critical factor for maintaining quality in stored non perishable foods. The high relative humidity prevalent in humid climates elevates the moisture content of dried commodities stored in porous woven bags, enabling fungal and insect infestations. Mycotoxins (e.g. aflatoxin) produced by fungi in insufficiently dried food commodities affect 4.5 billion people worldwide. Scope and approach We introduce the term "dry chain" to describe initial dehydration of durable commodities to levels preventing fungal growth followed by storage in moisture proof containers. This is analogous to the "cold chain" in which continuous refrigeration is used to preserve quality in the fresh produce industry. However, in the case of the dry chain, no further equipment or energy input is required to maintain product quality after initial drying as long as the integrity of the storage container is preserved. In some locations/seasons, only packaging is required to implement a "climate smart" dry chain, while in humid conditions, additional drying is required and desiccant based drying methods have unique advantages.  We propose both climate based and drying based approaches to implement the dry chain to minimize mycotoxin accumulation and insect infestations in dry products, reduce food loss, improve food quality, safety and security, and protect public health.
Geosecure O: A Method for Secure Distance Calculation for Travel Mode Detection using Outsourced GPS Trajectory Data
Venue: 2019 IEEE Fifth International Conference on Multimedia Big Data (BigMM)
Year: 2019

Detecting the mode of transportation using multimedia sensory data, such as trajectory data, is an important research problem arising out in many application domains that use location based services (LBS) Due to the large volume, such data is commonly outsourced to third party cloud service providers (CSP) for storage and usage by the LBS providers. The LBS providers typically deploy mode detection algorithms at the CSPs, which leads to continuous tracking of the user's location and raises severe security and privacy concerns among the users. Although many approaches exist in the literature regarding travel mode detection, security, and privacy concerns are not addressed by them. GPS based mode detection algorithms use distance and derived features such as velocity and acceleration. In this paper, we present a method, called GeoSecure O, to securely calculate the distance without revealing the users' location to the LBS provider and utilize it to determine the travel mode. We evaluate the proposed method on the Microsoft GeoLife dataset. Experimental results show that the proposed method not only protects users' location but also achieves an accuracy similar to what is achieved using the data with users' location.
Examining the impact of institutional pressures and green supply chain management practices on firm performance
Year: 2019

With the challenge of ecological business sustainability, concepts like green design, eco friendly products, sustainable technologies and efficient processes have compelled the organizations to adopt change. The purpose of this paper is to focus on understanding the impact of green supply chain (GSC) management practices and institutional pressures on economic and environmental performances of organizations in an unstable developing economy.,Data were collected from the supply chain specialists working in manufacturing firms through a questionnaire. Valid data of 101 respondents were used for analyzing the relationship among the constructs with the help of structural equation modeling.,The result of this study reveals that internal GSC practices and institutional pressure have a negative insignificant impact on economic performance, whereas all the constructs are the significant contributors toward improving environmental performance.,This study will help the supply chain decision makers to make a strategy that is beneficial for improving both economic and environmental dimensions of the performance of a firm.,An environmental management study under a rapidly changing scenario is always helpful to understand the behavior and its impact. This study is very useful and need of a time in the context of any developing country facing an economic and environmental crisis.
Sparse and Dense Linear Algebra for Machine Learning on Parallel RDBMS Using SQL
Venue: Open J. Big Data
Year: 2019

While computational modelling gets more complex and more accurate, its calculation costs have been increasing alike. However, working on big data environments usually involves several steps of massive unfiltered data transmission. In this paper, we continue our work on the PArADISE framework, which enables privacy aware distributed computation of big data scenarios, and present a study on how linear algebra operations can be calculated over parallel relational database systems using SQL. We investigate the ways to improve the computation performance of algebra operations over relational databases and show how using database techniques impacts the computation performance like the use of indexes, choice of schema, query formulation and others. We study the dense and sparse problems of linear algebra over relational databases and show that especially sparse problems can be efficiently computed using SQL. Furthermore, we present a simple but universal technique to improve intra operator parallelism for linear algebra operations in order to support the parallel computation of big data.
MiR 204 down regulation elicited perturbation of a gene target signature common to human cholangiocarcinoma and gastric cancer
Venue: Oncotarget
Year: 2017

There is high need of novel diagnostic and prognostic tools for tumors of the digestive system, such as gastric cancer and cholangiocarcinoma. We recently found that miR 204 was deeply downregulated in gastric cancer tissues. Here we investigated whether this was common to other tumors of the digestive system and whether this elicited a miR 204 dependent gene target signature, diagnostically and therapeutically relevant. Finally, we assessed the contribution of the identified target genes to the cell cycle progression and clonogenicity of gastric cancer and cholangiocarcinoma cell lines.  We employed quantitative PCR and Affymetrix profiling for gene expression studies. In silico analysis aided us to identifying a miR 204 target signature in publicly available databases (TGCA) We employed transient transfection experiments, clonogenic assays and cell cycle profiling to evaluate the biological consequences of miR 204 perturbation.  We identified a novel miR 204 gene target signature perturbed in gastric cancer and in cholangiocarcinoma specimens. We validated its prognostic relevance and mechanistically addressed its biological relevance in GC and CC cell lines.  We suggest that restoring the physiological levels of miR 204 in some gastrointestinal cancers might be exploited therapeutically.
The effectiveness of workplace coaching: A meta analysis of learning and performance outcomes from coaching
Year: 2016

This study presents a meta analysis synthesizing the existing research on the effectiveness of workplace coaching. We exclusively explore workplace coaching provided by internal or external coaches and therefore exclude cases of manager subordinate and peer coaching. We propose a framework of potential outcomes from coaching in organizations, which we examine meta analytically (k 17) Our analyses indicated that coaching had positive effects on organizational outcomes overall (d 0.36) and on specific forms of outcome criteria (skill based d 0.28; affective d 0.51; individual level results d 1.24) We also examined moderation by a number of coaching practice factors (use of multisource feedback; type of coach; coaching format; longevity of coaching) Our analyses of practice moderators indicated a significant moderation of effect size for type of coach (with effects being stronger for internal coaches compared to external coaches) and use of multisource feedback (with the use of multisource feedback resulting in smaller positive effects) We found no moderation of effect size by coaching format (comparing face to face, with blended face to face and e coaching) or duration of coaching (number of sessions or longevity of intervention) The effect sizes give support to the potential utility of coaching in organizations. Implications for coaching research and practice are discussed.
Teachers' Perception on School Health Services
Year: 2018

Teaching health and physical education by qualified teachers can support the promotion of health among school children. In Nepal, school health programme has not been run effectively as health and any subject teachers teach physical education subject. On the other hand, government policy makers and school management does not seem serious about this issue. In this context, the study intends to explore perceptions of teachers on students' health promotion through school health services. This study was based on qualitative research design specifically phenomenological approach. Qualitative data were collected from twelve purposefully selected teachers of six different community schools of Kathmandu using in depth interview technique. The collected data were analyzed by applying thematic approach. The study collected perception of Health and Physical Education (HPE) teachers regarding school health services, health promotive activities, water, sanitation and hygiene that play crucial role to promote healthy behaviour of students. In their perception, school health services should be provided to promote students' health, control the epidemics and communicable diseases and to create healthy school environment. In their perception, child friendly school creates an open learning environment and keeps students mentally sound, creative and well motivated in learning. Based on the findings of the study, it can be concluded that teachers' perception on school health programme is fairly satisfactory. However, their health activities are limited within the classroom practices and theoretical notions included in the textbook. Journal of Health Promotion Vol.6 2008,
Measures of Strength and Jump Performance Can Predict 30 m Sprint Time in Rugby Union Players.
Venue: Journal of strength and conditioning research
Year: 2019

Furlong, L AM, Harrison, AJ, and Jensen, RL. Measures of strength and jump performance can predict 30 m sprint time in Rugby Union players.  2019 Performance and fitness monitoring in Rugby Union often include jumping, sprinting, and strength tests, but repeatability of and relationships between these measures are unclear. The level of interindividual variability in these relationships and their sprint time predictive capabilities are also unknown. This study examined the reliability of, and relationship between, countermovement (CMJJH) squat (SJJH) and rebound (RBJJH) jump heights, rebound jump contact time (RBJCT) estimated 1 repetition maximum back squat relative to body mass (SQBM) and reactive strength index (RSI) to 30 m sprint time of subelite, semiprofessional Rugby Union players. Measurement reliability was very good, with high average intraclass correlation coefficients =0.9) and low coefficient of variation <10.1% All variables were significantly (p 0.01) correlated to each other (r 0.575) except for SQBM (only related to CMJJH, r 0.621) and RBJCT (only related to RSI, r 0.727) SJJH and SQBM were the strongest and most consistent predictors of time to 30 m (R 0.754 0.081; SEE 0.166 0.025) but variability in SEE magnitude was observed across the group during bootstrapping. Cross validation showed a mean difference between actual and predicted 30 m times equivalent to 0.22% of the group average time to 30 m. These results support the importance of multiple aspects of fitness training in Rugby Union players for improving performance in short duration sprinting activities, but highlight the individual nature of their relative importance. Measures of strength and power can be used to predict short sprint performance by the strength and conditioning professional.