nils-herrmann/clean_scirepeval huggingface dataset:
Combining social network and semantic concept analysis for personalized academic researcher recommendation
Venue: Decis. Support Syst.
Year: 2012

The rapid proliferation of information technologies especially Web 2.0 techniques has changed the fundamental ways how things can be done in many areas, including how researchers could communicate and collaborate with each other. The presence of the sheer volume of researchers and research information on the Web has led to the problem of information overload. There is a pressing need to develop researcher recommendation agents such that users can be provided with personalized recommendations of the researchers they can potentially collaborate with for mutual research benefits. In academic contexts, recommending suitable research partners to researchers can facilitate knowledge discovery and exchange, and ultimately improve the research productivity of researchers. Existing expertise recommendation research usually investigates the expert recommending problem from two independent dimensions, namely, their social relations and expertise information. The main contribution of this paper is that we propose a network based researcher recommendation approach which combines social network analysis and semantic concept analysis in a unified framework to improve the effectiveness of personalized researcher recommendation. The results of our experiment show that the proposed approach significantly outperforms the other baseline methods. Moreover, how our proposed framework can be applied to the real world academic contexts is explained based on a case study.
Global to Village| Global to Village: Grounding Communication Research in Rural China Introduction
Year: 2017

At a time when the academic spotlight focuses on "China's rising" in the metaphorical "global village," this article draws attention to China's real villages. It sets the context for a research agenda foregrounding the relevance of an urban rural relationship perspective for a political economy of communication that has systematically prioritized the labor capital relationship in the development of global capitalism. Starting with a personal biographical account and a reexamination of the place of the rural in scholarship on communication, modernization, and global capitalism, the article proceeds to foreground urban rural relations in understanding the historical trajectory of China's engagement with global capitalism and the role of communication and culture within such a trajectory. It then focuses on Heyang as a digitally networked, globalized, and globalizing Chinese village and introduces Global to Village: Grounding Communication Research in Rural China as both a transnational research project and a pedagogical praxis in global citizenship.
Disaster, Divine Judgment, and Original Sin: Christian Interpretations of Tropical Cyclone Winston and Climate Change in Fiji
Year: 2018

Paradise in the Pacific is often rendered as a natural state where "native" people live in simple harmony without the need for government or state institutions. However, Christian traditions also include paradise not simply as a state of innocence but also as a narrative of salvation history in which paradise is lost through original sin and must be restored through sacrifice and repentance. This article takes recent Fijian Christian interpretations of Tropical Cyclone Winston as a key site in which contested ideologies of Paradise are being reworked. As the idyll of island harmony is disrupted by disaster, Christians have seen Winston as an act of divine judgment and punishment on a sinful people. This essay analyzes how narratives of a sinful nation intersect with contemporary formulations of climate change, disaster, politics, and human agency.
Database Management Systems and Use of Digital Resources in Some Selected Public University Libraries of Bangladesh: An Overview
Year: 2012

This paper Discuses present status of database management practices and use of digital resources of five selected Public University Libraries of Bangladesh. Survey has been carried out on the names of used software, number of databases for the dissemination of library resources with total number of records, subscription of online journals with other digital and electronic resources, number of current/bound journals, computers, CDs and audiovisual materials etc. The objectives, methodology for collection, presentation and analysis of collected data for this study and highlights the meaning, need, main considerations, components and domain of library automation in the context of surveyed libraries also have been described. The development of digital technology combined with the evolution of Internet has prompted significant changes in library services and operations within the last few years. The study tries to focus on the availability of hardware and software in the respective library, examine types and forms of library collections, various house keeping operations, management, services, and library administration etc. It has also put forward some suggestions for the future development of the surveyed libraries. Bangladesh Journal of Library and Information Science Vol.2(1) July 2012 pp.67 78 DOI: http:/dx.doi.org/10.3329/bjlis.v2i1.12923
TRANSFER REVENUES OF RESEARCH AND TECHNOLOGY ORGANIZATIONS (RTOs) IN TIMES OF ECONOMIC CRISIS
Year: 2017

Profit oriented transfer activities have become a center piece of STI policies. There is little understanding tough of how companies facing financial headwind re adjust their knowledge transfer activities in the light of economic downturn. This paper studies influence factors for transfer revenues during the years 2009, 2010 and 2012 in around 1000 Russian Research and Technology Organizations (RTOs) The data shows that in times of crisis, quality related variables like scientific papers, patents or successful application for competitive research funds were no longer positively correlated to transfer revenues. Also recruitment strategies or long standing relationships between customer organizations and RTOs had no influence. The paper concludes that RTOs are in a very weak position if economic outlooks are darkening and require public financial support to maintain their ability to continuously provide their services once until the economy will recovers.
Sustaining the nursing workforce through transformational leadership: a Tasmanian perspective
Year: 2018

To identify strengths and opportunities for transformational leadership (FL) development in the Tasmanian Health Service (THS) nurse and midwife managers (NMMs)  Healthcare organisations face a dwindling nursing workforce by high turnover and ageing. TL is a developmental relationship focused leadership style and offers ways to surmount such challenges based on positive empirical outcomes.  TL was measured using the Multifactor Leadership Questionnaire (MLQ 6S) Responses were analysed with the one way ANO VA to identify any statistically significant associations. Overall MLQ scores.from this study were compared with previous studies undertaken in similar contexts.  NHMs reported TL as their primary leadership style. Statistical significance was found between specific TL elements and NMMs' education, age and gender. The comparison of MLQ scores revealed strengths and development opportunities in the NMMs.  Health organisations may benefit from the practise of TL, informed by empirical measurements of TL using the MLQ, to overcome nursing workforce shortage.
Process Monitoring of Polymer Systems by using Near Infrared Spectroscopy
Year: 2018

Polymers are a very important class of organic materials. Nowadays, polymers have been widely used in many fields due to their specific and excellent properties. They have become increasingly significant in our lives. With the growing demands on the quality of polymer products as well as reduction of costs in production and processing, the fast, accurate and reliable monitoring methods become more and more important. The traditional off line monitoring methods have many limitations, one of which is lag effect. This is mainly because sampling and lab testing can be very time consuming and for some tests a long time is required before the results are obtained. It is obviously that there is a large time gap between sampling and obtaining the results. Meanwhile, the reaction or processing of unknown quality polymer continues. Hence, the sample and end product don't have the same properties, which can result in large amounts of wasted material (Rohe et al. 1999) Another problem is that the sample analysed is small and as a result might not have all the properties that the bulk possessed (Coates et al. 2003) Due to these limitations and problems, the off line measuring methods are clearly unsuitable for the process monitoring. Undoubtedly, it is exciting to observe that the spectroscopic techniques can meet the above demands required by the process monitoring of the polymer systems. The vibrational spectroscopy is ideally suited to qualitative and quantitative analysis of polymers. Moreover, it can also give valuable information at the molecular level about the reactions extent and the products quality. It deserves to be specially noted that Near infrared (NIR) spectroscopy is a promising tool among the spectroscopic techniques. Near infrared spectroscopy lies between the visible and mid infrared regions of the electromagnetic spectrum, whose region extends from about 12,500 4000 cm 1. This region encompasses bands that result from the harmonic overtones of fundamental and combination bands associated with hydrogen atoms, which is why compounds containing CH, OH and NH bonds lend themselves favourably to analysis by NIR spectroscopy. However, NIR spectroscopy is comparatively weaker than mid infrared, and contains molecular structure information seriously overlapped which resulted in the silence of its research in the early stage. The modern earliest analytical applications of NIR spectroscopy were reported in the early 1960's (Butler Norris, 1960; Norris Butler, 1961) Nowadays, NIR spectroscopy
Our Mathematical Universe: My Quest for the Ultimate Nature of Reality
Year: 2014

In Our Mathematical Universe, Max Tegmark, one of the most original physicists at work today, leads us on an astonishing journey to explore the mysteries uncovered by cosmology and to discover the nature of reality. Part history of the cosmos, part intellectual adventure, Our Mathematical Universe travels from the Big Bang to the distant future via parallel worlds, across every possible scale from the sub atomic to the intergalactic showing how mathematics provides the answers to our questions about the world. Where do we come from? What makes the universe the way it is? In essence, why are we here? With dazzling clarity, Max Tegmark ponders these deep mysteries and allows us to grasp the most cutting edge and mind boggling theories of physics. What he proposes is an elegant and fascinating idea: that our physical world not only is described by mathematics, but that it is mathematics. "Our Mathematical Universe is nothing if not impressive. Brilliantly argued and beautifully written, it is never less than thought provoking about the greatest mysteries of our existence" (New York Times) "An amazing ride through the rich landscape of contemporary cosmology..Physics could do with more characters like Tegmark .an imaginative intellect and a charismatic presence" (Clive Cookson, Financial Times Max) Tegmark is author or co author of more than 200 technical papers, twelve of which have been cited more than 500 times. He has featured in dozens of science documentaries, and his work with the SDSS collaboration on galaxy clustering shared the first prize in Science magazine's "Breakthrough of the Year: 2003" He holds a Ph.D from the University of California, Berkeley, and is a physics professor at MIT.
Highly machine washable e textiles with high strain sensitivity and high thermal conduction
Year: 2020

Electronic textiles (e textiles) have attracted great attention due to their promising application in areas like flexible electronics, wearable devices, healthcare and sports. They should be machine washable and have high thermal conduction for heat management. But there are few reports on e textiles with high thermal conductivity. Here, we report highly machine washable e textiles with high strain sensitivity and high thermal conduction. The e textiles are prepared by anchoring carbon nanotubes (CNTs) into non woven fabric (NWF) by nanosoldering and then depositing reduced graphene oxide (rGO) through chemical reduction of graphene oxide (GO) The rGO/CNTs/NWF textiles are highly sensitive to the strain and have a gauge factor of 32.65 at a tensile strain of 1.0% They can detect a subtle strain as low as 0.01% In addition, the rGO and CNTs attached by nanosoldering have good adhesion to NWFs. The e textiles are highly machine washable and can be operated in water for a long time. Moreover, they can have a thermal conductivity of 2.90 W m 1 K 1, much higher than normal textiles. Their applications as wearable sensors for monitoring body motion and blood pulse are also demonstrated.
Research on Risk Measurement in Financial Market Based on GARCH VaR and FHS!a!aAn Example of Chinese Bond Market
Year: 2018

Accurately measuring the risk of bond market is very important for improving the risk management level of bond market and maintaining the stability of the financial system. Taking ChinaBond New Composite Wealth (gross) Index as the research object, this paper selects the closing price from January 1, 2002 to March 30, 2018, establishes the GARCH, EGARCH and GJR GARCH model based on normal distribution and t distribution, and finds out the volatility aggregation and the leverage effect of the bond market. Then, this paper use two methods to measure the risk of the bond market: first, we estimate the value at risk (VaR) of the bond market by the parameter method, using conditional variance estimated by the GARCH models, and we carry out backtesting analysis and the Kupiec failure rate test on measurement accuracy of VaR. The results show that t distribution hypothesis and elimination of autocorrelation of the yield rate can improve the accuracy and robustness of the estimation of the VaR; second, we simulate the future revenue path of the bond market and compare it with the actual loss, using Filtered Historical Simulation (FHS) based on Bootstrap method. The results show that the bond market has leverage effect. The maximum possible loss under extreme conditions can be far greater than the maximum possible revenue. But the estimated VaR under 95% confidence level can predict future risks very well. Finally, according to the conclusion, this paper puts forward some suggestions for regulators and investors from the perspective of risk management.
Association Mining to Identify Microbe Drug Interactions Based on Heterogeneous Network Embedding Representation
Venue: IEEE Journal of Biomedical and Health Informatics
Year: 2021

Accurately identifying microbe drug associations plays a critical role in drug development and precision medicine. Considering that the conventional wet lab method is time consuming, labor intensive and expensive, computational approach is an alternative choice. The increasing availability of numerous biological data provides a great opportunity to systematically understand complex interaction mechanisms between microbes and drugs. However, few computational methods have been developed for microbe drug prediction. In this work, we leverage multiple sources of biomedical data to construct a heterogeneous network for microbes and drugs, including drug drug interactions, microbe microbe interactions and microbe drug associations. And then we propose a novel Heterogeneous Network Embedding Representation framework for Microbe Drug Association prediction, named (HNERMDA) by combining metapath2vec with bipartite network recommendation. In this framework, we introduce metapath2vec, a heterogeneous network representation learning method, to learn low dimensional embedding representations for microbes and drugs. Following that, we further design a bias bipartite network projection recommendation algorithm to improve prediction accuracy. Comprehensive experiments on two datasets, named MDAD and aBiofilm, demonstrated that our model consistently outperformed five baseline methods in three types of cross validations. Case study on two popular drugs (i.e. Ciprofloxacin and Pefloxacin) further validated the effectiveness of our HNERMDA model in inferring potential target microbes for drugs.
Prevalence of Metabolic Syndrome and Its Associated Factors among Health Checkup Examinees in a University Hospital
Year: 2012

The purpose of this study was to estimate the prevalence of metabolic syndrome and determine the distribution of the clustering of the metabolic risk factors, and we wanted to evaluated the related factors in urban areas. 1,388 adults of 30 years and over, not recognized as taking medicines for or having cardiovascular diseases, who underwent health package check up at the health promotion center of a university hospital. All subjects were measured by height, weight, waist circumference, blood pressure and blood chemistry(lipid profile) As a results, the prevalence rates of metabolic syndrome of study subjects were 21.7% and the rates of metabolic risk factors were HDL C, blood pressure, TG, abdominal obesity and FBS in that order. And the factors such influencing on metabolic syndrome as age, BMI, smoking habits, vegetable consumption and family history of the diabetes. Consequently, it is suggested that the evaluation and intervention for lifestyle factors may be needed in order to the risk management of metabolic syndrome.
Structural features of global recycling trade networks and dynamic evolution patterns
Year: 2019

Recycling trade transfers recyclable resources and relevant environmental pressures on a global scale to solve resources limitation problem for some economies and alleviate urgent environment protection pressure for other countries/regions. Correspondingly, recycling trade relationships among economies are changing profoundly with the constant adjustment of economic and environmental policies. Based on complex network approach and top network analysis, this paper aims to comprehensively explore the structural features and their evolutionary patterns of global recycling trade networks from the macro, medium and micro levels by using global multi region input output data. The results are: At the macro level, the depth of global recycling import and export markets has strengthened continuously. The breadth of recycling exports showed a "pre concentration, post diversification" trend, and the import market breath demonstrated an opposite trend. At the medium level, the community structure of the global recycling export market increased rapidly in the early stage and became stable in the medium and late stages, while that of import market rapidly declined in the late stage, which means the import market was more sensitive to relevant policies and economic events. At the individual level, developed economics have been trying to transfer recycling products to developing economies, causing the former dominate global recycling export markets and the latter dominate the import markets. Recycling policies of economies, especially the developing economies have a serious impact on the global recycling trade pattern. Therefore, China's new announcement in 2018 for prohibiting import "foreign waste" will inevitably have a huge impact on the global recycling market.
Gurhan Model for SHRM: Explorative Study
Year: 2020

Various studies explore strategic HRM. Two definitions dominate the theory yet in strategic human resource management (SHRM) Wright and McMahan (1992) and Devanna, Fombrun, and Tichy (1981) Gurhan model benchmarks those models with performance and strategy dimensions. Performance and strategy enable firms to achieve organizational goals. In SHRM definition, HRM contributes to firms' organizational objectives. Third dimension in the model is system. System increases impact of HRM practices on individual and firm performances. To conclude, Gurhan model combines variables of American HRM style: performance, strategy, system.
Plant Disease Identification Using Transfer Learning
Venue: 2021 International Conference on Digital Futures and Transformative Technologies (ICoDT2)
Year: 2021

Early detection and control of plant disease is of vital importance for better yield from crops. Plant disease can be identified from the leaves as the texture, color and spots are different from healthy leaves. Conventional method of observing the leaves require expertise. So development of plant disease detection using Deep Learning techniques such as transfer learning can help the farmers who lack expertise and resources to hire the expert. In this study, ResNet50 with Transfer Learning is used for disease identification of potato, tomato and corn. Performance of ResNet50 is compared with VGG16 and MCNN built and trained from scratch. ResNet50 achieved highest performance of 98.7% for plant disease identification. 16 classes of different plant diseases can be identified in the model. Work can be extended by training model on more classes.
Text Line and Paragraph Segmentation Based on simple Mumford Shah Model
Year: 2009

Text line and Paragraph segmentation in handwritten documents is an important stage in document image processing.The paper presents a new text line and Paragraph segmentation method based on the simple Mumford Shah model.The algorithm is script independent.To enhance the efficiency of text line and paragraph segmentation,firstly,we exploit Gaussian Filter to smooth the text document.Then we use level set algorithm to solve the simple Mumford Shah model.In addition,we use morphing to remove overlaps between neighboring text lines and connect broken ones.Experimental results show using this method can segment document image's target fast and accurately.It's an effective and robust approach for text line and paragraph segmentation with noise,irrespective of edge continuous information and curve initial position.
Predicting Joint Roughness Coefficients Using Fractal Dimension of Rock Joint Profiles
Year: 2012

The Joint Roughness Coefficients, JRC, is presented Barton and Choubey in 1977. A series of different rock joint profiles were reconstructed by means of the independent cut method (Voss, 1988) using the programs written by MATLAB language. The reconstructed joint profiles have different amplitude and roughness. JRC values of the joint profiles were calculated on the basis of an empirical formula founded by Tse Cruden in 1979 using measure interval space 0.5mm on the profiles. The fractal dimension values of the joint profile were calculated by means of stick measuring methods suggested by Xu in 1996. The relationships between JRC and fractal dimension for all joint profiles were analyzed and exist strong correlations. A new empirical equation describing the relationships was established based on nonlinear fitting analysis and can predict JRC values accurately.