nils-herrmann/clean_scirepeval huggingface dataset:
Activity recognition based on inertial sensors for Ambient Assisted Living
Venue: 2016 19th International Conference on Information Fusion (FUSION)

Ambient Assisted Living (AAL) aims to create innovative technical solutions and services to support independent living among older adults, improve their quality of life and reduce the costs associated with health and social care. AAL systems provide health monitoring through sensor based technologies to preserve health and functional ability and facilitate social support for the ageing population. Human activity recognition (HAR) is an enabler for the development of robust AAL solutions, especially in safety critical environments. Therefore, HAR models applied within this domain (e.g. for fall detection or for providing contextual information to caregivers) need to be accurate to assist in developing reliable support systems. In this paper, we evaluate three machine learning algorithms, namely Support Vector Machine (SVM) a hybrid of Hidden Markov Models (HMM) and SVM (SVM HMM) and Artificial Neural Networks (ANNs) applied on a dataset collected between the elderly and their caregiver counterparts. Detected activities will later serve as inputs to a bidirectional activity awareness system for increasing social connectedness. Results show high classification performances for all three algorithms. Specifically, the SVM HMM hybrid demonstrates the best classification performance. In addition to this, we make our dataset publicly available for use by the machine learning community.
A semantic graph based approach on interest extraction from user generated texts in social media
Venue: 2016 International Conference on Data Mining and Advanced Computing (SAPIENCE)

Micro blogs and social networking websites have become a platform for self expression. They reflect the thoughts, ideas and opinions of people on various subjects. Analyzing these texts to find the main topics mentioned in them is a fine method for targeted marketing. Targeted marketing involves identifying potential clients who might be interested in particular products or services and marketing them to these clients. Examples of targeted marketing include recommender systems and targeted advertising. Identifying the personal interests of users is a major factor that determines the quality of such systems. Commonly used techniques monitor online behavior of users like purchase histories, product views etc. or explicitly collect the user's interests through surveys and rating systems. However there have been only a few attempts to use user generated texts as a source for analyzing personal interests and preferences. This paper proposes a semantic graph based method to identify the likes and interests of users by analyzing their twitter feeds. It also put forward the design for a recommender system that can work along with the proposed interest extraction method. This method is purely based on the texts that a user leaves in a particular social network website or a micro blog. Unlike the other conventional methods there is no need to track the user activity on the Internet or conduct exclusive surveys and ratings to collect explicit ideas from the user.
Identifying Platform Effects in Social Media Data
Venue: ICWSM

Even when external researchers have access to social media data, they are not privy to decisions that went into platform design including the measurement and testing that goes into deploying new platform features, such as recommender systems, seeking to shape user behavior towards desirable ends. Finding ways to identify platform effects is thus important both for generalizing findings, as well as understanding the nature of platform usage. One approach is to find temporal data covering the introduction of a new feature; observing differences in behavior before and after allow us to estimate the effect of the change. We investigate platform effects using two such datasets, the Netflix Prize dataset and the Facebook New Orleans data, in which we observe seeming discontinuities in user behavior but that we know or suspect are the result of a change in platform design. For the Netflix Prize, we estimate user ratings changing by an average of about 3% after the change, and in Facebook New Orleans, we find that the introduction of the 'People You May Know' feature locally nearly doubled the average number of edges added daily, and increased by 63% the average proportion of triangles created by each new edge. Our work empirically verifies several previously expressed theoretical concerns, and gives insight into the magnitude and variety of platform effects.
A Quantitative Examination of School Leadership and Response to Intervention

This study sought to provide educational researchers, policy makers, and professionals with quantitative data on the status of RTI implementation, as well as on which leadership behaviors have been associated with successful implementation. School psychologists and other RTI professionals rated their schools on RTI implementation using the RTI Essential Components Integrity Rubric and rated their school principals on leadership style using the Multifactor Leadership Questionnaire 5X. Descriptive data indicate that while schools have made progress, they have fallen far short of having fully implemented the RTI model. Multiple regression analysis identified transformational leadership as the predictive factor for RTI implementation, highlighting the importance of effective school leadership for this model.
An evaluation of underlying mechanisms for "fishing down marine food webs"
Venue: Acta Oceanologica Sinica

Since the concept of "fishing down marine food webs" was first proposed in 1998, mean trophic level of fisheries landings (MTL) has become one of the most widely used indicators to assess the impacts of fishing on the integrity of marine ecosystem and guide the policy development by many management agencies. Recent studies suggest that understanding underlying causes for changes in MTL is vital for an appropriate use of MTL as an indicator of fishery sustainability. Based on the landing data compiled by Food and Agriculture Organization (FAO) and trophic information of relevant species in Fishbase, we evaluated MTL trends in 14 FAO fishing areas and analyzed catches of upper and lower trophic level groups under different trends of MTL and found that both the cases of a recovered MTL trend and a generally increasing MTL trend could be accompanied by decreasing catches of lower trophic level species. Further, community structure and exploitation history should be considered in using MTL after excluding species with trophic levels lower than 3.25 to distinguish "fishingthrough" from "fishing down" We conclude that MTL used as an indicator to measure fishery sustainability can benefit from a full consideration of both upper and lower trophic level species and masking effects of community structure and exploitation history.
Current state of Linked Data in digital libraries
Venue: J. Inf. Sci.

The Semantic Web encourages institutions, including libraries, to collect, link and share their data across the Web in order to ease its processing by machines to get better queries and results. Linked Data technologies enable us to connect related data on the Web using the principles outlined by Tim Berners Lee in 2006. Digital libraries have great potential to exchange and disseminate data linked to external resources using Linked Data. In this paper, a study about the current uses of Linked Data in digital libraries, including the most important implementations around the world, is presented. The study focuses on selected vocabularies and ontologies, benefits and problems encountered in implementing Linked Data in digital libraries. In addition, it also identifies and discusses specific challenges that digital libraries face, offering suggestions for ways in which libraries can contribute to the Semantic Web. The study uses an adapted methodology for literature review, to find data available to answer research questions. It is based on the information found in the library websites recommended by W3C Library Linked Data Incubator Group in 2011, and scientific publications from Google Scholar, Scopus, ACM and Springer from the last 5 years. The selected libraries for the study are the National Library of France, the Europeana Library, the Library of Congress of the USA, the British Library and the National Library of Spain. In this paper, we outline the best practices found in each experience and identify gaps and future trends.
Discover Digital Libraries: Theory and Practice

Discover Digital Libraries: Theory and Practice is a book that integrates both research and practice concerning digital library development, use, preservation, and evaluation. The combination of current research and practical guidelines is a unique strength of this book. The authors bring in depth expertise on different digital library issues and synthesize theoretical and practical perspectives relevant to researchers, practitioners, and students. The book presents a comprehensive overview of the different approaches and tools for digital library development, including discussions of the social and legal issues associated with digital libraries. Readers will find current research and the best practices of digital libraries, providing both US and international perspectives on the development of digital libraries and their components, including collection, digitization, metadata, interface design, sustainability, preservation, retrieval, and evaluation of digital libraries. Offers an overview of digital libraries and the conceptual and practical understanding of digital libraries Presents the lifecycle of digital library design, use, preservation and evaluation, including collection development, digitization of static and multimedia resources, metadata, digital library development and interface design, digital information searching, digital preservation, and digital library evaluation Synthesizes current research and the best practices of digital libraries, providing both US and international perspectives on the development of digital libraries Introduces new developments in the area of digital libraries, such as large scale digital libraries, social media applications in digital libraries, multilingual digital libraries, digital curation, linked data, rapid capture, guidelines for the digitization of multimedia resources Highlights the impact, challenges, suggestions for overcoming these challenges, and trends of present and future development of digital libraries Offers a comprehensive bibliography for each chapter
Towards Cyberphysical Digital Libraries: Integrating IoT Smart Objects into Digital Libraries
Venue: Management of Cyber Physical Objects in the Future Internet of Things

Digital libraries are distributed software infrastructures that aim at collecting, managing, preserving, and using digital objects (or resources) for the long term, and providing specialized services on such resources to its users. Service provision should be of measurable quality and performed according to codified policies. Currently, modern digital libraries include a wide range of conventional digital objects: text document, image, audio, video, software, etc. In the emerging domain of the Internet of Things (IoT) cyberphysical smart objects (or simply smart objects) will play a central role in providing new (smart) services to both humans and machines. It is therefore challenging to include smart objects, the newest type of digital objects, into digital libraries as novel first class objects to be collected, managed, and preserved. However, their inclusion poses critical issues to address and many research challenges to deal with. This paper aims at paving the way towards such a novel inclusion that will enable effective discovery, management and querying of smart objects, so establishing cyberphysical digital libraries. In particular, our approach is based on a metadata model purposely defined to describe all the cyberphysical characteristics (geophysical, functional, and non functional) of smart objects. The metadata model is then used for a seamless integration of smart objects into digital libraries compliant with the digital library reference model proposed by the DL.org community. The proposed approach is also exemplified through a simple yet effective case study.
Understanding research students' behavioural intention in the adoption of digital libraries

The purpose of this study is to investigate the factors that influence the adoption of Higher Education Commission (HEC) National Digital Library among research students in different universities of Pakistan.  The study framework was based on technology acceptance model (TAM) A sample of Pakistani university students completed the questionnaire measuring the effects of extraneous stimuli through cognitive responses on adoption of the HEC digital library. To test the research hypotheses, multiple regression analysis was used.  The findings revealed that: cognitive responses predicted students' intention of using HEC digital library; extraneous variables significantly influenced cognitive responses; system characteristics directly influenced usefulness and ease of use; interface characteristics directly influenced cognitive responses; and individual differences significantly affected the ease of use. Similarly, system quality was identified with the highest direct effect on usefulness, whereas navigation had the highest influence on easy use of the HEC digital library of Pakistan. In addition, usefulness was explored with the highest effect on intention to use the HEC digital library of Pakistan. The findings revealed that individual behaviours influence the use of digital libraries which imply that acceptance of an information system (IS) involve cognitive idiosyncrasies. Findings of the study are useful for Pakistani academic librarians to enhance adoption and usability of the HEC digital library of Pakistan. The study extended cross cultural validation of TAM and explored how that Pakistani university students utilize HEC digital library.  These findings have significant implications for librarians in developing countries, such as to evaluate usability of digital libraries from individuals' perspective, create awareness, customize users' interface and train students in navigational techniques. It may also facilitate librarians to improve their current levels of library assistance and emphasize the usefulness of digital libraries towards academic excellence. The findings equally suggest that individual behaviours influence the use of digital libraries because acceptance of an information system involves cognitive idiosyncrasies. This study explored all possible links between the study constructs and emphasized that findings are useful to enhance the adoption and usability of digital library in the developing countries.  This study is the first attempt that empirically assessed the adoption of digital libraries in terms of Pakistani research students. The study validated TAM in the context of Pakistani university librarianship that extended the cross cultural validation of TAM. Furthermore, the study focused on real constructs instead of dummy variables and predicted significant effects on acceptance and rejection of digital libraries.
Effect of external loads on damage detection of rubber toughened nanocomposites using carbon nanotubes sensory network

Multiwalled carbon nanotubes of 0.2% weight fraction are used as a sensory network for detecting and characterizing the damage of particulate epoxy composites under shear loading conditions. Three different weight fractions of carboxyl terminated butadiene acrylonitrile copolymer rubber [10 parts per hundred of epoxy resin (phr) 20 phr, and 30 phr] are used for toughening a thermoset epoxy composite. The electrical response of the specimens is measured, nearest the central shearing plane, using a four circumferential ring probe technique in conjunction with a high resolution data acquisition system. A collection of the electromechanical response results are reported with respect to the shear strain. The resistance changes observed under shear loading are related to nonlinear deformation mechanisms, void initiation, and growth around rubber particulate. With increasing rubber content, the strength of the material decreases and a greater drop in resistance is recorded as a result of decreased distance between neighboring carbon nanotubes (CNTs) due to declustering and straightening of molecular chains of host matrix. In the end, a comparison for 30 phr composites under shear loading with that of tensile and compression loading conditions is presented. For initial deformation, there is no change in resistance under shear loading condition; however, the significant resistance change can be noticed under both tension and compression. The specimen under shear loading conditions experiences smaller decrease in resistance when compared with both tension and compression. However, the decrease in resistance is higher for compression due to higher decrease in distance between neighboring CNTs.  2014.
Can grain growers and agronomists identify common leaf diseases and biosecurity threats in grain crops? An Australian example

The Australian grains industry relies upon growers and agronomists to be aware of pests and diseases in their crops and to notify their local State Department of Agriculture when they suspect an incursion of a high priority pest (HPP) This raises the question "Are growers and agronomists, within the Australian grains industry, able to meet this expectation?" A training needs analysis was undertaken to determine the capacity of growers and agronomists to identify three endemic diseases (powdery mildew in barley, stripe rust in wheat and blackleg in canola) in their crops. Their knowledge of the top four biosecurity threats to the Australian grains industry (Karnal bunt, Khapra beetle, barley stripe rust and Russian wheat aphid) was also determined. Benchmarks for successfully identifying these diseases were set beforehand at 70% of growers and 80% of agronomists; participants' ability to identify these endemic diseases in crops met these benchmarks. However, their ability to recognise blackleg in canola was significantly lower than for the two cereal foliar diseases. There was a significant correlation of region with these capabilities, with a greater proportion of participants in Western Australia (WA) recognising powdery mildew in barley than in Eastern Australia (EA) In contrast, a greater proportion of participants in EA were able to identify stripe rust of wheat than in WA. The education levels of participants corresponded with their ability to identify blackleg in canola. Participants' knowledge and awareness of symptoms and signs associated with the top four biosecurity threats were well below expectations; fewer than half of the participants answered questions on these four HPPs. Gender, age and educational level did not correlate with the participants' knowledge and awareness of the four HPPs with the exception of Karnal bunt. Participants with a higher level of education had significantly more knowledge of symptoms associated with Karnal bunt than did participants with lower levels of education. The use of diagnostic services by the grains industry participants is a vital component of general surveillance. This survey showed that use of these services by growers was significantly lower than by agronomists. Awareness of the National Exotic Plant Pest Hotline and GrainGuard was significantly lower than other diagnostic services for both growers and agronomists. Diagnostic services need to be promoted further to increase awareness and use by growers and agronomists. Correct diagnosis of disease and pest symptoms is vital for the biosecurity of the grains industry.
A technical guide to tDCS, and related non invasive brain stimulation tools
Venue: Clinical Neurophysiology

Transcranial electrical stimulation (tES) including transcranial direct and alternating current stimulation (tDCS, tACS) are non invasive brain stimulation techniques increasingly used for modulation of central nervous system excitability in humans. Here we address methodological issues required for tES application. This review covers technical aspects of tES, as well as applications like exploration of brain physiology, modelling approaches, tES in cognitive neurosciences, and interventional approaches. It aims to help the reader to appropriately design and conduct studies involving these brain stimulation techniques, understand limitations and avoid shortcomings, which might hamper the scientific rigor and potential applications in the clinical domain.
Saponin determination, expression analysis and functional characterization of saponin biosynthetic genes in Chenopodium quinoa leaves.
Venue: Plant science an international journal of experimental plant biology

Quinoa (Chenopodium quinoa Willd. is a highly nutritious pseudocereal with an outstanding protein, vitamin, mineral and nutraceutical content. The leaves, flowers and seed coat of quinoa contain triterpenoid saponins, which impart bitterness to the grain and make them unpalatable without postharvest removal of the saponins. In this study, we quantified saponin content in quinoa leaves from Ecuadorian sweet and bitter genotypes and assessed the expression of saponin biosynthetic genes in leaf samples elicited with methyl jasmonate. We found saponin accumulation in leaves after MeJA treatment in both ecotypes tested. As no reference genes were available to perform qPCR in quinoa, we mined publicly available RNA Seq data for orthologs of 22 genes known to be stably expressed in Arabidopsis thaliana using geNorm, NormFinder and BestKeeper algorithms. The quinoa ortholog of At2g28390 (Monensin Sensitivity 1, MON1) was stably expressed and chosen as a suitable reference gene for qPCR analysis. Candidate saponin biosynthesis genes were screened in the quinoa RNA Seq data and subsequent functional characterization in yeast led to the identification of CqbAS1, CqCYP716A78 and CqCYP716A79. These genes were found to be induced by MeJA, suggesting this phytohormone might also modulate saponin biosynthesis in quinoa leaves. Knowledge of the saponin biosynthesis and its regulation in quinoa may aid the further development of sweet cultivars that do not require postharvest processing.