nils-herrmann/clean_scirepeval huggingface dataset:
Blockchain in operations management and manufacturing: Potential and barriers
Venue: Comput. Ind. Eng.
Year: 2020

Transparency, visibility, and disintermediation are some of the prospects of the aspiring blockchain technology in the business to business context. The digital transformation and Industry 4.0 trends also facilitate blockchain applications in operations management (OM) and manufacturing. However, scientific contributions and successful industrial applications in this area are still scarce and mainly at a proof of concept stage. The empirical research in this article is based on an expert interview study to uncover and analyse the potential and barriers to the adoption of blockchain technology in OM and manufacturing from within the industry. Semi structured interviews with industry experts are employed to elaborate on promising practices for the industry to efficiently promote blockchain adoption and meaningful research directions for scholars. Findings include unexplored potential regarding distributed production networks and collaboration, expected evolutionary steps of IoT, disintermediation leading to new business models like tokenisation, and short term rather than long term relationships. Current barriers include staff difficulties, legal uncertainties, missing infrastructure and standardisation, and unclear governance structures. Improving smart contract security and interoperability of private and public protocols will enable further dissemination of the technology. Managers and academic scholars can address these findings and new propositions of this study in future application development and implementation.
Suicide risk among 1.3 million veterans who were on active duty during the Iraq and Afghanistan wars.
Venue: Annals of epidemiology
Year: 2015

We conducted a retrospective cohort mortality study to determine the postservice suicide risk of recent wartime veterans comparing them with the US general population as well as comparing deployed veterans to nondeployed veterans.  Veterans were identified from the Defense Manpower Data Center records, and deployment to Iraq or Afghanistan war zone was determined from the Contingency Tracking System. Vital status of 317,581 deployed and 964,493 nondeployed veterans was followed from the time of discharge to December 31, 2009. Underlying causes of death were obtained from the National Death Index Plus.  Based on 9353 deaths (deployed, 1650; nondeployed, 7703) of which 1868 were suicide deaths (351; 1517) both veteran cohorts had 24% to 25% lower mortality risk from all causes combined but had 41% to 61% higher risk of suicide relative to the US general population. However, the suicide risk was not associated with a history of deployment to the war zone. After controlling for age, sex, race, marital status, branch of service, and rank, deployed veterans showed a lower risk of suicide compared with nondeployed veterans (hazard ratio, 0.84; 95% confidence interval, 0.75 0.95) Multiple deployments were not associated with the excess suicide risk among deployed veterans (hazard ratio, 1.00; 95% confidence interval, 0.79 1.28) CONCLUSIONS Veterans exhibit significantly higher suicide risk compared with the US general population. However, deployment to the Iraq or Afghanistan war, by itself, was not associated with the excess suicide risk.
Chiral de Rham complex on the upper half plane and modular forms.
Year: 2020

For any congruence subgroup \Gamma$ we study the vertex operator algebra \Omega^{ch}\mathbb H,\Gamma) constructed from the \Gamma$ invariant global sections of the chiral de Rham complex on the upper half plane, which are holomorphic at all the cusps. We introduce an $SL(2,\mathbb R) invariant filtration on the global sections and show that the \Gamma$ invariants on the graded algebra is isomorphic to certain copies of modular forms. We also give an explicit formula for the lifting of modular forms to \Omega^{ch}\mathbb H,\Gamma) and compute the character formula of \Omega^{ch}\mathbb H,\Gamma) Furthermore, we show that the vertex algebra structure modifies the Rankin Cohen bracket, and the modified bracket becomes non zero between constant modular forms involving the Eisenstein series.
Improved synthesis of graphene oxide.
Venue: ACS nano
Year: 2010

An improved method for the preparation of graphene oxide (GO) is described. Currently, Hummers' method  and performing the reaction in a 9:1 mixture of H(2)SO(4)/H(3)PO(4) improves the efficiency of the oxidation process. This improved method provides a greater amount of hydrophilic oxidized graphene material as compared to Hummers' method or Hummers' method with additional KMnO(4) Moreover, even though the GO produced by our method is more oxidized than that prepared by Hummers' method, when both are reduced in the same chamber with hydrazine, chemically converted graphene (CCG) produced from this new method is equivalent in its electrical conductivity. In contrast to Hummers' method, the new method does not generate toxic gas and the temperature is easily controlled. This improved synthesis of GO may be important for large scale production of GO as well as the construction of devices composed of the subsequent CCG.
A highly accurate interatomic potential for LaMnO3 perovskites with temperature dependence of structure and thermal properties
Year: 2021

ABO3 type perovskites LaMnO3 is a colossal magnetoresistance material that undergoes an orthorhombic rhombohedral phase transition as the temperature increases. Phase transition determines its structural properties and thermal conductivity that are important in industrial application. Structural transition is reflected mainly in Mn O bond lengths and Mn O Mn angles between MnO6 octahedrons for Jahn Teller effect during this progress and traditional born mayer (BM) model has difficulty in description of structural distortion and thermal properties. In this paper, a new classic interatomic potential model for LaMnO3 was developed within the framework of bond valence (BV) theory. First principles and intelligent optimization algorithm were used to fit the parameters, enabling the study of temperature dependent structures by accurate large scale molecular dynamics (MD) simulations. Calculated structural distortions by our model and thermal properties calculated with equilibrium molecular dynamics (EMD) method accorded with the experimental values within a reasonable error, and had higher accuracy than traditional born mayer model. These results provided further insight about temperature depended phase transition and further performance mining of LaMnO3. Most importantly, our potential model showed better accuracy than traditional potential model and is applicable for all crystal materials with perovskite structures.
Deep Learning Algorithm Classifies Heartbeat Events Based on Electrocardiogram Signals
Venue: Frontiers in Physiology
Year: 2020

Cardiovascular diseases (CVDs) have become the number 1 threat to human health. Their numerous complications mean that many countries remain unable to prevent the rapid growth of such diseases, although significant health resources have been invested toward their prevention and management. Electrocardiogram (ECG) is the most important non invasive physiological signal for CVD screening and diagnosis. For exploring the heartbeat event classification model using single or multiple lead ECG signals, we proposed a novel deep learning algorithm and conducted a systemic comparison based on the different methods and databases. This new approach aims to improve accuracy and reduce training time by combining the convolutional neural network (CNN) with the bidirectional long short term memory (BiLSTM) To our knowledge, this approach has not been investigated to date. In this study, Database I with single lead ECG and Database II with 12 lead ECG were used to explore a practical and viable heartbeat event classification model. An evolutionary neural system approach (Method I) and a deep learning approach (Method II) that combines CNN with BiLSTM network were compared and evaluated in processing heartbeat event classification. Overall, Method I achieved slightly better performance than Method II. However, Method I took, on average, 28.3 h to train the model, whereas Method II needed only 1 h.  II achieved an accuracy of 80, 82.6, and 85% compared with the China Physiological Signal Challenge 2018, PhysioNet Challenge 2017, and Massachusetts Institute of Technology Beth Israel Hospital (MIT BIH) Arrhythmia datasets, respectively. These results are impressive compared with the performance of state of the art algorithms used for the same purpose.
Saving Face: Shared Experience and Dialogue on Social Touch, in Playful Smart Public Space
Venue: Making Smart Cities More Playable
Year: 2019

Can shared experience and dialogue on social touch be orchestrated in playful smart public spaces? In smart city public spaces, in which physical and virtual realities are currently merging, new forms of social connections, interfaces and experiences are being explored. Within art practice, such new connections include new forms of affective social communication with additional social and sensorial connections to enable and enhance empathic, intimate experience in playful smart public space. This chapter explores a novel design for shared intimate experience of playful social touch in three orchestrations of 'Saving Face' in different cultural and geographical environments of smart city (semi public spaces, in Beijing, Utrecht, Dessau Berlin. These orchestrations are purposefully designed to create a radically unfamiliar sensory synthesis to disrupt the perception of 'who sees and who is being seen, who touches and who is being touched' Participants playfully 'touch themselves and feel being touched, to connect with others on a screen' All three orchestrations show that shared experience and dialogue on social touch can be mediated by playful smart cities technologies in public spaces, but rely on design of mediated, intimate and exposed forms of 'self touch for social touch' ambivalent relations, exposure of dialogue and hosting.
Hybrid metal organic nanoflowers and their application in biotechnology and medicine.
Venue: Colloids and surfaces. B, Biointerfaces
Year: 2019

Nanoflowers new nanostructures have aroused the interest of scientists due to the topographic features of nanolayers, the special location of which allows a higher surface to volume ratio compared to classic spherical nanoparticles, which significantly increases the efficiency of surface reactions for nanoflowers. The main purpose of these types of nanomaterials is their use as enzyme stabilizers. To facilitate the functioning of enzymes under different conditions, organic inorganic hybrid nanomaterials have been developed, the name of which indicates that all components of inorganic nanoparticles are associated with organic materials. These nanoparticles have many promising applications in catalysis, as biosensors, and for drug delivery. Organic inorganic hybrid nanoflowers have led to the development of a new branch of chemistry the chemistry of hybrid nanomaterials in which research is rapidly developing. Thus, studying organic inorganic hybrid nanocrystals can lead to creative new solutions in the field of chemistry of enzyme systems and the rapid development of bionanomaterials and new biotechnology industries. Present review focuses on wide biomedical applications of nanoflowers including biocatalysis, detection of substances, electrochemical biosensors based on nanoflowers, photosensitizers, drug and gene carriers and detection of various diseases, photothermal and other treatments. It will be interesting for wide range of scientists focusing in topic of new kinds of nanoparticles.
Reservoir computing based on laser subject to optoelectronic feedback
Venue: 2020 International Conference Laser Optics (ICLO)
Year: 2020

We study delay based photonic reservoir computing using a semiconductor laser with an optoelectronic feedback. We investigate the connection between the bifurcation landscape of this system with the computational performance of the reservoir. Specifically, there are multiple Hopf bifurcation branches possessing the parity asymmetry with relation to the feedback sign. We observe the corresponding difference in the normalized means square error (NMSE) values using the prediction on the chaotic Santa Fe time series as a benchmark.
Defining Psychometric Variables Related to Use of Autonomous Vehicles
Venue: Transportation Research Record: Journal of the Transportation Research Board
Year: 2019

With the goal of understanding autonomous vehicle (AV) adoption and use behavior, numerous behavioral studies and surveys have included variables intended to capture individuals' perceptions of and attitudes toward AVs. However, the selection of questions to measure these psychometric variables appears to be ad hoc and, in many cases, arbitrary. In contrast, this study defines psychometric latent variables (LVs) that are related to the adoption and use of AVs and develops a set of questions to reliably measure them. By considering three psychological concepts (norms, perceptions, and attitudes) and nine qualitative utility constructs that influence individuals' travel behavior, this study defines a comprehensive list of LVs and identifier questions to support their construction. A factor analysis of a nationwide n 347 sample was used to obtain a minimum set of relevant LVs and questions to measure them. Ultimately, the factor analysis resulted in a final set of nine LVs specified by 44 questions (four or five questions for each LV) The final set of questions may be used by researchers or survey organizations interested in studying future trends of demand and adoption for AVs or other emerging transportation modes. The approach used in this study may also be employed in other contexts to define psychometric variables of interest and the questions needed to reliably measure them.
Effects of Continuous Cropping of Sweet Potato on the Fungal Community Structure in Rhizospheric Soil
Venue: Front. Microbiol.
Year: 2019

Soil microorganisms play an important role in the ecosystem, and have a certain relationship with the continuous cropping obstacles, which are common with sweet potato. However, there are few reports on the effects of continuous cropping of sweet potato on the microbial community structure in the rhizospheric soil. Here, we investigated the effects of continuous cropping of sweet potato on the fungal community structure in rhizospheric soil, in order to provide theoretical basis for prevention and control of continuous cropping obstacles. This study used X18 and Y138 varieties as experimental materials. Soil samples were collected during the early period of planting and harvest in two consecutive years, and fungi were analyzed using Illumina Miseq. Results showed that the fungi diversity and richness in rhizospheric soil of X18 and Y138 were significantly increased after continuous cropping; the most dominant fungi phylum was Ascomycota, which decreased significantly after continuous cropping. In addition, the content of beneficial fungi such as Chaetomium was reduced, while that of harmful fungi such as Verticillium, Fusarium, and Colletotrichum were increased. The composition of X18 and Y138 fungal community in the same sampling period after continuous cropping was similar, although that of the same sweet potato variety significantly differed with the sampling period. Overall, our results indicate that continuous cropping alters the fungal community structure of the sweet potato rhizospheric soil, such that the content of beneficial fungi decrease, while that of harmful fungi increase, thereby increasing soil borne diseases and reducing the yield and quality of sweet potato. Furthermore, these effects are different for different sweet potato varieties. Thus, during actual production, attention should be paid to maintain the stability of sweet potato rhizospheric soil micro ecology through rotation or application of microbial fertilizers and soil amendments to alleviate continuous cropping obstacles.
Visualizing Wikipedia using t SNE
Year: 2014

This paper presents an approach on visualizing high dimensional data of Wikipedia. Visualizing data is an important and well studied problem. Visualizing highdimensional data can viewed as a dimensionality reduction problem. Over the past few decades many techniques have been proposed for linear and nonlinear dimensionality reduction. In this paper we use one such non linear dimensionality reduction technique called tDistributed Stochastic Neighbor Embedding and specifically the version using Barnes Hut algorithm for approximation. We also show that using semantic role labels as features for dimensionality reduction, we are able to visualize well clustered data with clusters containing similar data.
Empirical Research in REBT Theory and Practice
Year: 2019

The theory of REBT was developed by Ellis (1962, 1994) being seen by many in the field as the first form of CBT (e.g. Hollon DiGiuseppe, 2010) and as a major contributor to the cognitive revolution in psychology and psychotherapy (David, 2015) First labeled Rational Therapy, it was renamed Rational Emotive Therapy before receiving the current name: Rational Emotive Behavior Therapy (David, 2015) In a personal communication to one of the chapter's authors (Dr. David) Albert Ellis (2005) would have liked to finally name it Cognitive Affective Behavior Therapy.
Population Based Study of the Influence of the COVID 19 Pandemic on Hand Hygiene Behaviors Polish Adolescents' COVID 19 Experience (PLACE 19) Study
Year: 2020

Due to the COVID 19 pandemic, the World Health Organization and other major authorities recommend frequent hand washing and applying proper hand hygiene procedures as one of the cheapest, easiest, and most important ways to prevent the spread of a virus. For adolescents it is especially important as it should become for them a lifelong habit. The aim of the study was to assess the hand hygiene behaviors during the COVID 19 pandemic in a national Polish sample of secondary school adolescents and to verify the influence of the COVID 19 pandemic on those behaviors. The study was conducted in April 2020 in a national sample of 2323 secondary school students recruited based on secondary school sampling procedure (random quota sampling with quotas for voivodeships) The hand hygiene behaviors that were assessed included: frequency of washing hands, reasons for not washing hands, circumstances of washing hands, and procedure of handwashing. Participants were asked each question twice for the current period of the COVID 19 pandemic and for the period before the COVID 19 issue. The declared frequency of washing hands during the COVID 19 pandemic was significantly higher than before (p 0.0001) as the majority of respondents declared doing it 6 15 times a day (58.4% while before the pandemic, it was 3 10 times a day (68.1% The share of respondents declaring washing their hands always while it would be needed was significantly higher for the period during the COVID 19 pandemic (54.8% than it was for the period before (35.6% p 0.0001) and there was a lower share of respondents declaring various reasons for not washing hands. For the majority of circumstances of washing hands, including those associated with meals, personal hygiene, leaving home, socializing, health, and household chores, the share of respondents declaring always washing their hands was significantly higher for the period during the COVID 19 pandemic than for the period before (p 0.0001) For the majority of steps of handwashing procedure, the share of respondents declaring including them always was significantly higher for the period during the COVID 19 pandemic than for the period before (p 0.0001) but a higher share declared not wearing a watch and bracelet (p 0.0006) and rings (p 0.0129) It was concluded that during the COVID 19 pandemic all the assessed hand hygiene behaviors of Polish adolescents were improved, compared with those before, but hand hygiene education is still necessary.
Recommendations for participation in competitive and leisure time sport in athletes with cardiomyopathies, myocarditis, and pericarditis: position statement of the Sport Cardiology Section of the European Association of Preventive Cardiology (EAPC)
Venue: European heart journal
Year: 2019

Myocardial diseases are associated with an increased risk of potentially fatal cardiac arrhythmias and sudden cardiac death/cardiac arrest during exercise, including hypertrophic cardiomyopathy, dilated cardiomyopathy, left ventricular non compaction, arrhythmogenic cardiomyopathy, and myo pericarditis. Practicing cardiologists and sport physicians are required to identify high risk individuals harbouring these cardiac diseases in a timely fashion in the setting of preparticipation screening or medical consultation and provide appropriate advice regarding the participation in competitive sport activities and/or regular exercise programmes. Many asymptomatic (or mildly symptomatic) patients with cardiomyopathies aspire to participate in leisure time and amateur sport activities to take advantage of the multiple benefits of a physically active lifestyle. In 2005, The European Society of Cardiology (ESC) published recommendations for participation in competitive sport in athletes with cardiomyopathies and myo pericarditis. One decade on, these recommendations are partly obsolete given the evolving knowledge of the diagnosis, management and treatment of cardiomyopathies and myo pericarditis. The present document, therefore, aims to offer a comprehensive overview of the most updated recommendations for practicing cardiologists and sport physicians managing athletes with cardiomyopathies and myo pericarditis and provides pragmatic advice for safe participation in competitive sport at professional and amateur level, as well as in a variety of recreational physical activities.
Simulation Based Decision Support System for Economical Supply Chain Management of Rebar
Year: 2007

The economics of a materials management system is defined by the size of the shipments, the scheduling strategy that allows contractors to handle uncertainty and variability in the supply chain, and the timing of the shipments, which in turn depend on the environment in which the project is taking place. This study presents a simulation based decision support system to assist contractors in selecting the most economical rebar management system prior to the start of construction by recommending lot sizes (large, small) a scheduling strategy (optimistic, neutral, pessimistic) and buffer sizes (large, medium, small) given the conditions of the project. This model is of benefit to contractors and researchers because it generates the probable cost of inventory of 18 alternative rebar management systems ranging from just in case (JIC) to just in time (JIT) and including different variations in between. It allows contractors to select the alternative with least cost of inventory at the planning stages of a project. The simulation model was tested by using actual data obtained from a trade center project in Istanbul, Turkey. As expected, the test indicated that JIC was the most economical rebar management system in a case study conducted in a developing country, as it generated a savings of 4.8% over JIT.