nils-herrmann/clean_scirepeval huggingface dataset:
Rationale and methods of an Evaluation of the Effectiveness of the Community Paramedicine at Home (CP@home) program for frequent users of emergency medical services in multiple Ontario regions: a study protocol for a randomized controlled trial
Venue: Trials
Year: 2019

BackgroundFrequent users of emergency medical services for issues that could be more appropriately managed through non urgent care deplete the limited resources of the health care system. Community paramedicine is an emerging field that extends the role of paramedics beyond the traditional emergency response. The goal of the current study is to evaluate the impact of a community paramedicine home visit intervention with frequent users on reducing ambulance calls, hospital visits, and admissions. The study will also provide a cross sectional description of the characteristics of frequent users of emergency medical services. open label, pragmatic, randomized controlled trial with parallel intervention and control groups will be conducted in four paramedic services in Ontario. The sample size has been calculated as 261 per group for a 25% reduction in ambulance calls. Eligible participants will be frequent callers (three or more calls in 6 months) individuals who call for at least one lift assist, or individuals referred to the program by a paramedic. Individuals will be randomly allocated to receive either the Community Paramedicine at Home (CP@home) program intervention or their usual care (control) Intervention participants will receive up to three visits from a community paramedic, who will conduct health risk assessments, provide health promotion and education, provide referrals to local resources, and fax reports back to the family physician. Data will be collected from administrative databases (e.g. paramedic services) a custom CP@home program database, participant surveys, and key informant interviews. An intention to treat analysis will be conducted, including descriptive statistics and multi level modeling to find factors predictive of primary and secondary outcomes. A thematic analysis will be used to analyze the qualitative outcomes. An economic analysis will consider the cost effectiveness of the program.DiscussionCP@home has the potential to reduce the health care system burden significantly by targeting current frequent users of emergency medical services. By targeting this population, CP@home aims to decrease ambulance calls and emergency department visits, reducing health care costs and improving the quality of life of a vulnerable population. If successful, CP@home will inform the development of community paramedicine policies and the expanding role of paramedics in regions across Canada.
Flint for Safer Smart Contracts
Venue: ArXiv
Year: 2019

The Ethereum blockchain platform supports the execution of decentralised applications or smart contracts. These typically hold and transfer digital currency to other parties on the platform; however, they have been subject to numerous attacks due to the unintentional introduction of bugs. Over a billion dollars worth of currency has been stolen since its release in July 2015. As smart contracts cannot be updated after deployment, it is imperative that the programming language supports the development of robust contracts. We propose Flint, a new statically typed programming language specifically designed for writing robust smart contracts. Flint's features enforce the writing of safe and predictable code. To encourage good practices, we introduce protection blocks. Protection blocks restrict who can run code and when (using typestate) it can be executed. To prevent vulnerabilities relating to the unintentional loss of currency, Flint Asset traits provide safe atomic operations, ensuring the state of contracts is always consistent. Writes to state are restricted, simplifying reasoning about smart contracts.
Charge Simulation Based Electric Field Analysis and Electrical Tree Propagation Model with Defects in 10 kV XLPE Cable Joint
Year: 2019

The most severe partial discharges and main insulation failures of 10 kV cross linked polyethylene cables occur at the joint due to defects caused by various factors during the manufacturing and installation processes. The electric field distortion is analyzed as the indicator by the charge simulation method to identify four typical defects (air void, water film, metal debris, and metal needle) This charge simulation method is combined with random walk theory to describe the stochastic process of electrical tree growth around the defects with an analysis of the charge accumulation process. The results illustrate that the electrical trees around the metal debris and needle are more likely to approach the cable core and cause main insulation failure compared with other types of the defects because the vertical field vector to the cable core is significantly larger than the field vectors to other directions during the tree propagation process with conductive defects. The electric field was measured around the cable joint surface and compared with the simulation results to validate the calculation model and the measurement method. The air void and water film defects are difficult to detect when their sizes are less than 5 mm3 because the field distortions caused by the air void and water film are relatively small and might be concealed by interference. The proposed electric field analysis focuses on the electric field distortion in the cable joint, which is the original cause of the insulation material breakdown. This method identifies the defect and predicts the electrical tree growth in the cable joint simultaneously. It requires no directly attached or embedded sensors to impact the cable joint structure and maintains the power transmission during the detection process.
Regulating Recommending: Motivations, Considerations, and Principles
Venue: Eur. J. Law Technol.
Year: 2019

Internet regulation and 'online harms' are matters of much political and regulatory attention. This debate is beset by issues, including defining 'online harms' respecting freedom of expression, and others. While much of this debate has focused on content hosted by online platforms, comparatively little attention has been paid to the central role of algorithmic personalisation or 'recommending' by platforms in content dissemination in online environments and the problems to which this contributes. Focusing on recommender systems, i.e. the mechanism by which content is recommended by platforms, provides an alternative regulatory approach that avoids many of the pitfalls with addressing the hosting of content itself. This paper therefore explores motivations and considerations for regulating the use of recommender systems by online platforms. In doing so, this paper establishes a typology of online recommending, sets out various problems and consequences of recommending, and argues that recommending content is not one of the three activities for which information society service providers are afforded liability protections under the E Commerce Directive. To address the identified problems and fill this legal gap, this paper proposes some principles for future regulation, and discusses approaches to oversight and compliance that could work with these principles.
Impacts of COVID 19 on ecology and evolutionary biology faculty in the United States
Venue: Ecological applications a publication of the Ecological Society of America
Year: 2020

We surveyed ecologists and evolutionary biologists in American Universities to understand how they are coping with the COVID 19 pandemic. Female respondents, assistant professors, and those who care for at least one child or teenager, were significantly more dissatisfied with their work life balance during this pandemic than others, and further expected these negative impacts to be long lived. Online teaching support, relaxed expectations on publications, the possibility of pausing the tenure clock, and an acknowledgment of "no business as usual" by administrators were thought to be effective policies in mitigating these negative impacts. This survey serves as a manifesto to what our professional community is currently experiencing, and should be used to inform academic policies directed at improving faculty productivity and welfare.
Application of chemicals for enhancing lipid production in microalgae a short review.
Venue: Bioresource technology
Year: 2019

Microalgae have attracted great attention as a promising sustainable resource for biofuel production. In studies aiming to improve lipid accumulation, many key enzymes involved in lipid biosynthesis were identified and confirmed, but genetic engineering remains a challenge in most species of microalgae. In an alternative approach, various chemical modulators can be used to directly regulate the lipid biosynthesis pathway, with similar effects to gene overexpression and interference approaches, including improving the precursor supply and blocking competing pathways. The produced lipid can be protected from being converted into other metabolites by the chemicals such as lipase inhibitors. In addition, a few chemicals were also demonstrated to greatly influence cell growth and lipid accumulation by indirect regulation of the lipid biosynthesis pathway, such as increasing cell permeability or regulating oxidative stress. Thus, adding chemical modulators can be a useful alternative strategy for improving lipid accumulation in large scale cultivation of microalgae.
Weighted domain adaptation networks for machinery fault diagnosis
Year: 2021

Intelligent fault diagnosis of machines has received much attention in this big data era. Most reported models are constructed under the assumption that the training and testing data are from the same distribution. However, data distribution will shift due to working condition changes, posing challenges on the performance of intelligent models. This study considers the case that out of many known working conditions with labeled historical data, the model is to be used under another unlabelled target working condition. A multiple source domain adaptation method is proposed to learn fault discriminative but working condition invariant features from raw vibration signals. Different known working conditions will be assigned with different weights, on the basis of their distributional similarities to the target working condition. Two case studies are carried out to validate the effectiveness of the proposed method, respectively on rotating speed changes and load level changes.
Books in the Time of Screens: The Reading Habits of Slovenian Students
Year: 2020

This research paper brings up the question of recreational reading habits among the generation of university students that were born after 1990 and grew up in a digital environment. The paper focuses on their self reported reading habits. The students belong to two disciplinary domains (humanities and social sciences) at the University of Ljubljana, Slovenia. A significant number of them were pre service teachers. The research was conducted on a non random sample of 429 students. Data were gathered using a printed questionnaire that included assessment scales of students' reading habits. These data were compared with data gathered in the online reading habits survey of the general Slovenian population that took place in autumn 2019 on a sample of 1000 participants, demographically representing Slovene general population. The key finding was that university students read more than members of the general population do, but still less than would be expected of future educators who will introduce book reading to pupils as the number of non readers in student population was higher than expected. In addition, the data revealed that practically all students were able to read in at least one foreign language (predominantly in English) what is significantly higher than in general population. The paper indicates a few reasons for such outcomes and addresses the question of why recreational book reading matters in educational settings.
Touching your words Why braille reading is special
Year: 2019

Reading, while usually done through vision, can also be done through touch using the braille system. Research on the differences between these two modalities is needed to distinguish between modalitydependent and modality independent processes. This has theoretical implications regarding the improvement of our understanding of reading in general, and also practical implications: it may be useful to develop tools and strategies to better teach and learn braille, an essential skill to navigate the world for those visually impaired. Here, we describe two recent papers showing both similarities and differences between these two modalities.
Recruitment and retention strategies for an urban adolescent study: Lessons learned from a multi center study of community based asthma self management intervention for adolescents.
Venue: Journal of adolescence
Year: 2018

Intervention studies with urban adolescents and families affected by asthma are critical to improving the disproportionate morbidity in this population. Community based recruitment and retention strategies in a multi site longitudinal project evaluating an asthma self management intervention for adolescents are presented. Successful recruitment strategies depended on the geographic and cultural characteristics of each study site. Partnering with providers and groups known to the target population and in person contact with target population were found effective. Flexibility accommodating modified and new approaches, securing multiple contacts and repeating mailings as well as capitalizing on the benefits of subject payment was critical to achieving long term subject engagement of 85% in the study. Ongoing monitoring and adjustment of recruitment and retention strategies is recommended.
A transfer convolutional neural network for fault diagnosis based on ResNet 50
Venue: Neural Computing and Applications
Year: 2019

With the rapid development of smart manufacturing, data driven fault diagnosis has attracted increasing attentions. As one of the most popular methods applied in fault diagnosis, deep learning (DL) has achieved remarkable results. However, due to the fact that the volume of labeled samples is small in fault diagnosis, the depths of DL models for fault diagnosis are shallow compared with convolutional neural network in other areas (including ImageNet) which limits their final prediction accuracies. In this research, a new TCNN(ResNet 50) with the depth of 51 convolutional layers is proposed for fault diagnosis. By combining with transfer learning, TCNN(ResNet 50) applies ResNet 50 trained on ImageNet as feature extractor for fault diagnosis. Firstly, a signal to image method is developed to convert time domain fault signals to RGB images format as the input datatype of ResNet 50. Then, a new structure of TCNN(ResNet 50) is proposed. Finally, the proposed TCNN(ResNet 50) has been tested on three datasets, including bearing damage dataset provided by KAT datacenter, motor bearing dataset provided by Case Western Reserve University (CWRU) and self priming centrifugal pump dataset. It achieved state of the art results. The prediction accuracies of TCNN(ResNet 50) are as high as 98.95% 0.0074, 99.99% 0 and 99.20% 0, which demonstrates that TCNN(ResNet 50) outperforms other DL models and traditional methods.
Mapping Time: Illustrated by Minard's Map of Napoleon's Russian Campaign of 1812
Year: 2014

Maps tell time 1 Napoleon's Russian campaign, About Gerrit Janz Kraak 2 Minard's map 2.1 The map, About Minard 2.2 Minard's work 2.3 Mapping 1812 As a historical event Inspired by Minard Curiosities 3 Time 3.1 What about time? 3.2 Types of time 3.3 Events and change 3.4 Questions and time 3.5 Temporal data visualization and time space 4 Maps, data, and design 4.1 Map basics 4.2 Map data analysis 4.3 Map design 5 Maps and time 5.1 Map narrative 5.2 Expressing change Change from object perspective Change from attribute perspective Change from location perspective Change and Minard's representation of Napoleon's Russian campaign Change and the map background 5.3 Change in a single map, Flow line maps, Cartograms, Space time cube, A third dimension 5.4 Change in a series of maps 5.5 Change in animation 6 Maps and temporal exploration 6.1 From presentation to exploration, Mapping environment, Representation, Design guidelines, Visualization strategies 6.2 Exploring, Reviewing Napoleon's battle record, What happened at the crossing of the Berezina River? 7 Reflection References Credits Index
Cryptochromes Mediated Inhibition of the CRL4Cop1 Complex Assembly Defines an Evolutionary Conserved Signaling Mechanism
Venue: Current Biology
Year: 2019

In plants, cryptochromes are photoreceptors that negatively regulate the ubiquitin ligase CRL4Cop1. In mammals, cryptochromes are core components of the circadian clock and repressors of the glucocorticoid receptor (GR) Moreover, mammalian cryptochromes lost their ability to interact with Cop1, suggesting that they are unable to inhibit CRL4Cop1. Contrary to this assumption, we found that mammalian cryptochromes are also negative regulators of CRL4Cop1, and through this mechanism, they repress the GR transcriptional network both in cultured cells and in the mouse liver. Mechanistically, cryptochromes inactivate Cop1 by interacting with Det1, a subunit of the mammalian CRL4Cop1 complex that is not present in other CRL4s. Through this interaction, the ability of Cop1 to join the CRL4 complex is inhibited; therefore, its substrates accumulate. Thus, the interaction between cryptochromes and Det1 in mammals mirrors the interaction between cryptochromes and Cop1 in planta, pointing to a common ancestor in which the cryptochromes Cop1 axis originated.
Improving Postgraduate Students' Scientific Literacy and Research Ability Using Workshops: Evidence from a Chinese University Theory, Achievements and Reflection
Venue: DEStech Transactions on Economics, Business and Management
Year: 2019

Postgraduate education bears the dual mission of "high end talent supply" and "scientific and technological innovation" Whether there is a matching scientific literacy and spirit is one of the important criteria for evaluating the teaching quality of postgraduate students and their universities. With the specific design and implementation of the short term workshop and the investigation and research, this paper observes and analyzes the performance of the new postgraduate s of the school of business administration of a university in Shandong Province in the six week workshop, and then discusses how to use this education mode to improve the scientific literacy and research ability of the postgraduate students. The research results show that the workshop, which combines academic lectures and individual and team research exercises, is of practical significance for improving the scientific literacy of postgraduate students. It is also suggested that colleges and universities should refer to the theoretical and practical value of the model and rationally adopt the workshop model to optimize postgraduate
How Generational Theory Can Improve Teaching: Strategies for Working with the "Millennials" ESSAYS
Year: 2008

This article applies recent writing on the "Millennial Generation" to a range of pedagogical issues. Born between 1982 and 2003 and also known as Generation Y, the Millennials have been hailed as a new "Great Generation." According to William Strauss and Neil Howe, they display ambition, confidence, optimism, and a capacity for high level cooperative work. At the same time, they measure high on scales of stress, conventionality, and over reliance on parents. This internally complex set of traits calls for a variety of nuanced pedagogies, including balancing students' need for overall clarity with their sense of competence in co designing key aspects of their educational experience. Incorporating a wide range of generational studies, including the latest (2008) publications in this area, the authors offer a variety of teaching strategies, some arising out of their own primary research.
Weighing up the Effects of Working Memory and Cognitive Abilities in CLIL Learning
Year: 2019

In an era of globalization, multilingualism is no longer the exception but the rule. To fully promote the commnicative and functional development of multilingual learners, different educational programs at school have been implemented in the past few years. The study presented here is a contribution in this direction, by investigating the linguistic development in a second foreign language (L3 English) of students who were exposed to asymmetric input exposure in this and another non native language. This other language was the L2 (German) which the learners (n= 50, 11 13 years old) were studying in a CLIL context together with the native languages of the participants (Spanish and Catalan) Within such a context, the purpose of the study is two fold. On the one hand, it attempts to investigate the linguistic attainment in the L3, measured in terms of various dimensions of writing performance in a composition task, namely, fluency, accuracy, structural complexity and lexical complexity. On the other hand, the study aimed at exploring the contribution of various components of working memory (short term memory and attention switching) to performance in these linguistic dimensions. The results suggest that individual differences in storage capacity and in capability for attention and task switching had an effect on the accuracy of the learners' performance, and to a lesser extent, also lexical complexity. Moreover, it was found that in general, attentional abilities had a greater impact than memory. These results are discussed in light of previous findings, while proposing directions for further investigation in the field.
Planning with Exploration: Addressing Dynamics Bottleneck in Model based Reinforcement Learning
Venue: ArXiv
Year: 2020

Model based reinforcement learning is a framework in which an agent learns an environment model, makes planning and decision making in this model, and finally interacts with the real environment. Model based reinforcement learning has high sample efficiency compared with model free reinforcement learning, and shows great potential in the real world application. However, model based reinforcement learning has been plagued by dynamics bottleneck. Dynamics bottleneck is the phenomenon that when the timestep to interact with the environment increases, the reward of the agent falls into the local optimum instead of increasing. In this paper, we analyze and explain how the coupling relationship between model and policy causes the dynamics bottleneck and shows improving the exploration ability of the agent can alleviate this issue. We then propose a new planning algorithm called Maximum Entropy Cross Entropy Method (MECEM) MECEM can improve the agent's exploration ability by maximizing the distribution of action entropy in the planning process. We conduct experiments on fourteen well recognized benchmark environments such as HalfCheetah, Ant and Swimmer. The results verify that our approach obtains the state of the art performance on eleven benchmark environments and can effectively alleviate dynamics bottleneck on HalfCheetah, Ant and Walker2D.