nils-herrmann/clean_scirepeval huggingface dataset:
A Detailed Analysis of Big Data Analytics Challenges and Opportunities
Year: 2019

Big data investigation has increased widely in consideration on how it is applied to both the scholarly and industry due to interest in understanding the patterns in massive datasets increments. The Late advancements in sensor systems, digital physical frameworks, and the presence of the Internet of Things have expanded the gathering of data to a tremendous scale. Nonetheless, the data gathered from sensors, internet based life, financial records, and so on are inalienably factual because of commotion, deficiency, and irregularity issues evidence in technology. The investigation of these enormous measures of data requires progressed expository systems for efficiently checking on and foreseeing future approaches using basic leadership techniques. As the sum, assortment, and speed of data increments are subjected to vulnerability, prompting the absence of trust in the subsequent investigation procedure undertaken by experts. In contrast with conventional data systems and stages, Artificial Intelligence (AI) methods (counting machine learning, common language handling, and computational insight) give progressively precise, quicker, and adaptable outcomes in big data examination.
A protocol for an intercomparison of biodiversity and ecosystem services models using harmonized land use and climate scenarios
Year: 2018

To support the assessments of the Intergovernmental Science Policy Platform on Biodiversity and Ecosystem Services (IPBES) the IPBES Expert Group on Scenarios and Models is carrying out an intercomparison of biodiversity and ecosystem services models using harmonized scenarios (BES SIM) The goals of BES SIM are (1) to project the global impacts of land use and climate change on biodiversity and ecosystem services (i.e. nature's contributions to people) over the coming decades, compared to the 20th century, using a set of common metrics at multiple scales, and (2) to identify model uncertainties and research gaps through the comparisons of projected biodiversity and ecosystem services across models. BES SIM uses three scenarios combining specific Shared Socio economic Pathways (SSPs) and Representative Concentration Pathways (RCPs) SSP1xRCP2.6, SSP3xRCP6.0, SSP5xRCP8.6 to explore a wide range of land use change and climate change futures. This paper describes the rationale for scenario selection, the process of harmonizing input data for land use, based on the second phase of the Land Use Harmonization Project (LUH2) and climate, the biodiversity and ecosystem services models used, the core simulations carried out, the harmonization of the model output metrics, and the treatment of uncertainty. The results of this collaborative modeling project will support the ongoing global assessment of IPBES, strengthen ties between IPBES and the Intergovernmental Panel on Climate Change (IPCC) scenarios and modeling processes, advise the Convention on Biological Diversity (CBD) on its development of a post 2020 strategic plans and conservation goals, and inform the development of a new generation of nature centred scenarios.
Kunstliche Intelligenz als Strategie in der Ingenieurgeodasie erste Schritte im Bahnumfeld
Year: 2020

A system for recording train rides for work in the track area is crucial. The usage of Artificial Intelligence contributes to this. In the following article a first approach based on Deep Learning is presented, that automatically detects trains on the base of image data and can lead to more safety in the track area. In addition, a software has been developed that reduces the extensive and work intensive data preparation effort significantly. This article presents the potential and the flexible deployment of Artificial Intelligence in the engineering geodetic domain.  Deep Learning, Convolutional Neural Network, Kunstliche Intelligenz, Zugdetektion, Rottenwarnanlage 1 Anwendungskontext und Motivation Die Ingenieurgeodasie tritt als Dienstleister in einem breiten Domanenspektrum auf. Insbesondere der sichere Umgang mit Prazisionsmessungen, Datenmanagement, Referenzund IT Systemen ist ein massgebliches Alleinstellungsmerkmal der modernen, interdisziplinaren Geodasie. Verfahren der Kunstlichen Intelligenz (KI) beschranken sich gegenwartig nicht mehr nur auf die Softwareindustrie, sondern rucken immer weiter in die unterschiedlichsten Branchen vor. So gewinnt dieses Werkzeug auch im Bereich des geodatischen Arbeitens zunehmend an Bedeutung. Cha et al. (2017) sowie Cha und Wang (2017) prasentieren die Moglichkeit, Risse in Betonbauwerken zu erkennen. Dabei werden Daten aus unbemannten Flugsystemen (UAV) mittels kunstlicher neuronaler Netzwerke (KNN) verarbeitet. In Musella et al. (2019) wird Building Information Modeling (BIM) mit KI zur Erkennung seismischer Schaden an Mansardengebauden verknupft. Das Konsortium >KI meets BIM< in welchem auch der Lehrstuhl Informatik im Bauwesen der Ruhr Universitat Bochum (RUB) vertreten ist, legt einen Forschungsschwerpunkt auf die automatisierte Bauablaufplanung und strebt die Umsetzung mit Hilfe von Laserscannern an.  Bereich des spurgebundenen Baustellen Monitorings gehort auch die Sicherung der Baustellen ( Dazu zahlt u. a. die luckenlose Erfassung und zuverlassige, ortsgerechte Weitergabe von Zugfahrten in den verschiedensten Gefahrensituationen, um dem Baustellenpersonal (Rotte) die rechtzeitige Raumung des Gleisbereichs zu ermoglichen. Ublich ist der Einsatz sogenannter Rottenwarnanlagen, welche von Sicherungspersonal Sakra) beaufsichtigt werden und mit Hilfe mechanischer, induktiver oder elektromagnetischer Sensoren den Zug streckenseitig detektieren, um die Rotte uber akustische und optische Reize zu warnen (Abb. 2) Im folgenden Anwendungsbeispiel soll experimentell KI eingesetzt werden, um in Bilddaten automatisiert Kunstliche Intelligenz als Strategie in der Ingenieurgeodasie erste Schritte im Bahnumfeld Bastian Plass, Kira Zschiesche, Tamer Altinbas, Daniel Karla, Linda Rau und Martin Schluter  Warngeberkette M it fr eu nd lic he r Ge ne hm ig un g de r Un te rn eh m en sg ru pp e Zo lln er
Patologicheskoe ispol'zovanie i zavisimost' ot sotsial'nykh setei analiz s pozitsii fenomenologii addiktivnogo povedeniia
Year: 2020

The article summarizes current foreign and Russian literature regarding the pathological use and dependence on social networks, with an emphasis on similarities and differences of this phenomenon from other types of addictive behavior on the Internet. The confirmation that social media addiction is an independent disorder is presented in the review. The variations of Internet addiction relate primarily to the effects of social interactions. However, at the same time, the similarities with other electronic addictions (for example, to a smartphone, the Internet, network games, etc. have been confirmed in many different studies. The excessive use of social media is often associated with other behavioral addictions, such as food addiction, shopping, gaming, as well as with some other psychological health problems (anxiety, depression, low self esteem, suicidal thoughts, etc. The most frequently mentioned personality factors associated with dependence on social media are increased neuroticism, extroversion, decreased conscientiousness, as well as a tendency to highly emotional communication, sometimes adventurism and a demonstration of posturing and narcissism. The Bergen Social Media Addiction Scale (BSMAS) and the Bergen Facebook Addiction Scale (BFAS) have been developed in Denmark for diagnosing pathological behavior in social networks. Both tests were adapted in many countries and are increasingly used for scientific purposes. These scales presumably will help to clarify the prevalence of this kind of dependence in various age groups and objectify its associations with other types of addictive behavior, mental health disorders, and personality traits.
Chinese Text Sentiment Analysis Utilizing Emotion Degree Lexicon and Fuzzy Semantic Model
Venue: Int. J. Softw. Sci. Comput. Intell.
Year: 2014

Text on the web has become a valuable source for mining and analyzing user opinions on any topic. Non native English speakers heavily support the growing use of Network media especially in Chinese. Many sentiment analysis studies have shown that a polarity lexicon can effectively improve the classification consequences. Social media, where users spontaneously generated content have become important materials for tracking people's opinions and sentiments. Meanwhile, the mathematical models of fuzzy semantics have provided a formal explanation for the fuzzy nature of human language processing. This paper investigated the limitations of traditional sentiment analysis approaches and proposed an effective Chinese sentiment analysis approach based on emotion degree lexicon. Inspired by various social cognitive theories, basic emotion value lexicon and social evidence lexicon were combined to improve sentiment analysis consequences. By using the composite lexicon and fuzzy semantic model, this new sentiment analysis approach obtains significant improvement in Chinese text.
The Best Templates Match Technique For Example Based Machine Translation
Venue: ArXiv
Year: 2014

It has been proved that large scale realistic Knowledge Based Machine Translation applications require acquisition of huge knowledge about language and about the world. This knowledge is encoded in computational grammars, lexicons and domain models. Another approach which avoids the need for collecting and analyzing massive knowledge, is the Example Based approach, which is the topic of this paper. We show through the paper that using Example Based in its native form is not suitable for translating into Arabic. Therefore a modification to the basic approach is presented to improve the accuracy of the translation process. The basic idea of the new approach is to improve the technique by which template based approaches select the appropriate templates.
Frequency of Lucid Dreaming in a Representative German Sample
Venue: Perceptual and motor skills
Year: 2011

Lucid dreams occur when a person is aware that he is dreaming while he is dreaming. In a representative sample of German adults (N 919) 51% of the participants reported that they had experienced a lucid dream at least once. Lucid dream recall was significantly higher in women and negatively correlated with age. However, these effects might be explained by the frequency of dream recall, as there was a correlation of .57 between frequency of dream recall and frequency of lucid dreams. Other sociodemographic variables like education, marital status, or monthly income were not related to lucid dream frequency. Given the relatively high prevalence of lucid dreaming reported in the present study, research on lucid dreams might be pursued in the sleep laboratory to expand the knowledge about sleep, dreaming, and consciousness processes in general.
In vitro role of Rad54 in Rad51 ssDNA filament dependent homology search and synaptic complexes formation
Venue: Nature Communications
Year: 2019

Homologous recombination (HR) uses a homologous template to accurately repair DNA double strand breaks and stalled replication forks to maintain genome stability. During homology search, Rad51 nucleoprotein filaments probe and interact with dsDNA, forming the synaptic complex that is stabilized on a homologous sequence. Strand intertwining leads to the formation of a displacement loop (D loop) In yeast, Rad54 is essential for HR in vivo and required for D loop formation in vitro, but its exact role remains to be fully elucidated. Using electron microscopy to visualize the DNA protein complexes, here we find that Rad54 is crucial for Rad51 mediated synaptic complex formation and homology search. The Rad54 K341R ATPase deficient mutant protein promotes formation of synaptic complexes but not D loops and leads to the accumulation of stable heterologous associations, suggesting that the Rad54 ATPase is involved in preventing non productive intermediates. We propose that Rad51/Rad54 form a functional unit operating in homology search, synaptic complex and D loop formation. Homologous recombination uses a template to accurately repair DNA double strand breaks and stalled replication forks to maintain genome stability. Here authors use electron microscopy to investigate the role of Rad54 in homology search and synaptic complex formation.
A critical analysis of methods used to investigate the cellular uptake and subcellular localization of RNA therapeutics
Venue: Nucleic acids research
Year: 2020

RNA therapeutics are a promising strategy to treat genetic diseases caused by the overexpression or aberrant splicing of a specific protein. The field has seen major strides in the clinical efficacy of this class of molecules, largely due to chemical modifications and delivery strategies that improve nuclease resistance and enhance cell penetration. However, a major obstacle in the development of RNA therapeutics continues to be the imprecise, difficult, and often problematic nature of most methods used to measure cell penetration. Here, we review these methods and clearly distinguish between those that measure total cellular uptake of RNA therapeutics, which includes both productive and non productive uptake, and those that measure cytosolic/nuclear penetration, which represents only productive uptake. We critically analyze the benefits and drawbacks of each method. Finally, we use key examples to illustrate how, despite rigorous experimentation and proper controls, our understanding of the mechanism of gymnotic uptake of RNA therapeutics remains limited by the methods commonly used to analyze RNA delivery.
AHA Scientific Statement Particulate Matter Air Pollution and Cardiovascular Disease An Update to the Scientific Statement From the American Heart Association
Year: 2010

In 2004, the first American Heart Association scientific statement on "Air Pollution and Cardiovascular Disease" concluded that exposure to particulate matter (PM) air pollution contributes to cardiovascular morbidity and mortality. In the interim, numerous studies have expanded our understanding of this association and further elucidated the physiological and molecular mechanisms involved. The main objective of this updated American Heart Association scientific statement is to provide a comprehensive review of the new evidence linking PM exposure with cardiovascular disease, with a specific focus on highlighting the clinical implications for researchers and healthcare providers. The writing group also sought to provide expert consensus opinions on many aspects of the current state of science and updated suggestions for areas of future research. On the basis of the findings of this review, several new conclusions were reached, including the following: Exposure to PM 2.5 m in diameter (PM2.5) over a few hours to weeks can trigger cardiovascular disease related mortality and nonfatal events; longer term exposure (eg, a few years) increases the risk for cardiovascular mortality to an even greater extent than exposures over a few days and reduces life expectancy within more highly exposed segments of the population by several months to a few years; reductions in PM levels are associated with decreases in cardiovascular mortality within a time frame as short as a few years; and many credible pathological mechanisms have been elucidated that lend biological plausibility to these findings. It is the opinion of the writing group that the overall evidence is consistent with a causal relationship between PM2.5 exposure and cardiovascular morbidity and mortality. This body of evidence has grown and been strengthened substantially since the first American Heart Association scientific statement was published. Finally, PM2.5 exposure is deemed a modifiable factor that contributes to cardiovascular morbidity and mortality.
Non destructive discrimination of avocado fruit ripeness using laser Doppler vibrometry
Year: 2020

Consumers increasingly desire ready to eat avocado fruit, yet if supplies fall short of customer expectations, complaints follow, incurring considerable cost and waste. In the avocado sector, wastage due to destructive testing and inaccurate assessment of firmness is significant. The aim of this study was to evaluate whether non destructive laser Doppler vibrometry (LDV) was capable of assessing avocado ripeness. Data were sourced from two trials using preclimacteric imported 'Hass' avocado fruit originating from Chile and Spain, ripened at 12 and 18 degC, respectively. Standard force deformation measurements, and either single or simultaneous dual vibration time signals were recorded during shelf life, and assessed against respiration and non structural carbohydrate content. Resonant frequencies measured from fruit by means of LDV decreased two to four fold during ripening and this corresponded with a concomitant decrease in firmness (253 N 2 N) The capability of the LDV system to non destructively discriminate between ripeness stages was demonstrated.
Using scent actuation for engaging user experiences
Venue: Advances in Computer Entertainment
Year: 2015

The sense of smell (olfaction) has been recognised as an important factor governing our emotions and memory. Nevertheless, it remains the most underexplored sense and is still a relatively new modality in the domain of marketing. While researchers have begun to explore the merits of olfaction as a powerful trigger of memories, its relation with emotions has been largely disregarded and its interplay with other modalities remains largely unknown. In this paper, we explore the use of scent for mobile user experiences and devices with a hardware tele smell device "Scentee" We provide two examples of how Scentee has successfully been used in marketing campaigns.
Agile Requirements Engineering and Software Planning for a Digital Health Platform to Engage the Effects of Isolation Caused by Social Distancing: Case Study
Venue: JMIR public health and surveillance
Year: 2020

Social distancing and shielding measures have been put in place to reduce social interaction and slow the transmission of the coronavirus disease (COVID 19) For older people, self isolation presents particular challenges for mental health and social relationships. As time progresses, continued social distancing could have a compounding impact on these concerns.  This project aims to provide a tool for older people and their families and peers to improve their well being and health during and after regulated social distancing. First, we will evaluate the tool's feasibility, acceptability, and usability to encourage positive nutrition, enhance physical activity, and enable virtual interaction while social distancing. Second, we will be implementing the app to provide an online community to assist families and peer groups in maintaining contact with older people using goal setting. Anonymized data from the app will be aggregated with other real world data sources to develop a machine learning algorithm to improve the identification of patients with COVID 19 and track for real time use by health systems.  Development of this project is occurring at the time of publication, and therefore, a case study design was selected to provide a systematic means of capturing software engineering in progress. The app development framework for software design was based on agile methods. The evaluation of the app's feasibility, acceptability and usability shall be conducted using Public Health England's guidance on evaluating digital health products, Bandura's model of health promotion, the Reach Effectiveness Adoption Implementation Maintenance (RE AIM) framework and the Nonadoption, Abandonment and Challenges to the Scale up, Spread and Suitability (NASSS) framework.  Making use of a pre existing software framework for health behavior change, a proof of concept was developed, and a multistage app development and deployment for the solution was created. Grant submissions to fund the project and study execution have been sought at the time of publication, and prediscovery iteration of the solution has begun. Ethical approval for a feasibility study design is being sought.  This case study lays the foundations for future app development to combat mental and societal issues arising from social distancing measures. The app will be tested and evaluated in future studies to allow continuous improvement of the app. This novel contribution will provide an evidence based exemplar for future app development in the space of social isolation and loneliness.
Concentric compressive behavior of hybrid concrete Stainless Steel Double Skin Tubular Columns incorporating High Performance Concretes
Year: 2020

This paper investigates experimentally and numerically concentric compressive behavior of hybrid concrete Stainless Steel (SS) Double Skin Tubular Columns (DSTCs) employing High Performance Concretes (HPCs) DSTCs can be prefabricated using outer and inner double tubes positioned concentrically sandwiching the concrete core in between. However, the ordinary steel tubes beside the poor mechanical properties of Normal Concrete (NC) may not be appropriate for the environmental attack. This research proposes employing two durable SS tubes sandwiching HPCs in between to gain satisfied performance. Beside NC, three types of HPCs were suggested: Engineered Cementitious Composites (ECC) High Strength Fiber Reinforced Concrete (HSFRC) and High Strength Concrete (HSC) Forty specimens were tested experimentally under axial monotonic compressive loading up to failure. The main variables were: void ratio created by inner tube, concrete core type and vertical stiffeners embedded in the concrete core. Parallel to those implemented experimentally, nonlinear three dimensional Finite Element Models (FEMs) were set up, executed and validated against experimental outcomes generating an accepted model with about 6% error. Results revealed that the studied parameters could significantly enhance the behavior in terms of load displacement response, elastic/plastic appearance, ultimate capacity, and capturing ductile failure mode. Finally, both experimental and numerical results were extended deriving new formula could estimate the ultimate capacity with difference about 12%
Antimicrobial Peptides of Multicellular Organisms: My Perspective.
Venue: Advances in experimental medicine and biology
Year: 2019

Antimicrobial peptides of multicellular organisms were first characterized in the 1980s by investigators who felt that known systems of immunity could not explain what they observed: the resistance to bacterial infection of a Cecropia moth pupa lacking antibodies or lymphocytes (cecropins (Steiner 1981) the potent microbicidal activity of neutrophils from a rabbit (defensins (Selsted et al. 1985) and the healing of a wound on the skin of the African clawed frog without infection in a non sterile aquarium (magainins (Zasloff 1987) Since then AMPs have been discovered in diverse species of fungi, plants, and animals (Seshadri Sundararajan et al. 2012; Fan et al. 2016; Waghu et al. 2016; Wang et al. 2016) It is likely that we will discover that every multicellular organism expresses antimicrobial peptides as a key element of their immune system. Why are antimicrobial peptides so popular in