nils-herrmann/clean_scirepeval huggingface dataset:
Elicitation for Preferences Single Peaked on Trees

In multiagent systems, we often have a set of agents each of which have a preference ordering over a set of items and one would like to know these preference orderings for various tasks, for example, data analysis, preference aggregation, voting etc. However, we often have a large number of items which makes it impractical to ask the agents for their complete preference ordering. In such scenarios, we usually elicit these agents’ preferences by asking (a hopefully small number of) comparison queries — asking an agent to compare two items. Prior works on preference elicitation focus on unrestricted domain and the domain of single peaked preferences and show that the preferences in single peaked domain can be elicited by much less number of queries compared to unrestricted domain. We extend this line of research and study preference elicitation for single peaked preferences on trees which is a strict superset of the domain of single peaked preferences. We show that the query complexity crucially depends on the number of leaves, the path cover number, and the distance from path of the underlying single peaked tree, whereas the other natural parameters like maximum degree, diameter, pathwidth do not play any direct role in determining query complexity. We then investigate the query complexity for finding a weak Condorcet winner for preferences single peaked on a tree and show that this task has much less query complexity than preference elicitation. Here again we observe that the number of leaves in the underlying single peaked tree and the path cover number of the tree influence the query complexity of the problem.
Impact of Mindfulness-Based Stress Reduction (MBSR) on attention, rumination and resting blood pressure in women with cancer: A waitlist-controlled study

The present study is a waitlist-controlled investigation of the impact of a Mindfulness-Based Stress Reduction (MBSR) program on mindful attentiveness, rumination and blood pressure (BP) in women with cancer. Female post-treatment cancer patients were recruited from the MBSR program waitlist. Participants completed self-report measures of mindfulness and rumination and measured casual BP at home before and after the 8-week MBSR program or waiting period. MBSR group participants demonstrated higher levels of mindful attentiveness and decreased ruminative thinking following the intervention but no difference in BP, when compared to controls. In the MBSR group, decreases in rumination correlated with decreases in SBP and increases in mindful attention. When participants were assigned to “Higher BP” and “Lower BP” conditions based on mean BP values at week 1, “Higher BP” participants in the MBSR group (n = 19) had lower SBP at week 8 relative to the control group (n = 16). A MBSR program may be efficacious in increasing mindful attention and decreasing rumination in women with cancer. Randomized controlled trials are needed to evaluate an impact on clinically elevated BP.
EFFECTS OF MILD DEHYDRATION ON THERMOREGULATION , PERFORMANCE AND MENTAL FATIGUE DURING AN ICE HOCKEY

EFFECTS OF MILD DEHYDRATION ON THERMOREGULATION, PERFORMANCE AND MENTAL FATIGUE DURING AN ICE HOCKEY SCRIMMAGE Mark Edward Linseman Advisor: University of Guelph, 2011 Professor L.L. Spriet This study investigated the effects of progressive dehydration by 1.5-2.0% body mass (BM) (NF) on core temperature (Tc), heart rate (HR), on-ice performance, and mental fatigue during a 70-min scrimmage, compared to maintaining BM with a carbohydrate-electrolyte solution (CES). Compared to CES, Tc was significantly higher throughout the scrimmage in NF. Players in NF had reduced mean skating speed and time at high effort between 30-50 min of the scrimmage. Players in NF committed more puck turnovers and completed a lower percentage of passes in the last 20 min of play. Post-scrimmage shuttle skating time was higher in NF. Hockey fatigue questionnaire total score and Profile of Mood States fatigue score was higher in NF. The results indicate that mild dehydration compared to maintaining BM with a CES resulted in increased Tc, decreased skating and puck handling performance, and increased mental fatigue during an ice hockey scrimmage.
The Recombinant BCG ΔureC::hly Vaccine Targets the AIM2 Inflammasome to Induce Autophagy and Inflammation.

The recombinant BCG ΔureC::hly (rBCG) vaccine candidate induces improved protection against tuberculosis over parental BCG (pBCG) in preclinical studies and has successfully completed a phase 2a clinical trial. However, the mechanisms responsible for the superior vaccine efficacy of rBCG are still incompletely understood. Here, we investigated the underlying biological mechanisms elicited by the rBCG vaccine candidate relevant to its protective efficacy.



THP-1 macrophages were infected with pBCG or rBCG, and inflammasome activation and autophagy were evaluated. In addition, mice were vaccinated with pBCG or rBCG, and gene expression in the draining lymph nodes was analyzed by microarray at day 1 after vaccination.



BCG-derived DNA was detected in the cytosol of rBCG-infected macrophages. rBCG infection was associated with enhanced absent in melanoma 2 (AIM2) inflammasome activation, increased activation of caspases and production of interleukin (IL)-1β and IL-18, as well as induction of AIM2-dependent and stimulator of interferon genes (STING)-dependent autophagy. Similarly, mice vaccinated with rBCG showed early increased expression of Il-1β, Il-18, and Tmem173 (transmembrane protein 173; also known as STING).



rBCG stimulates AIM2 inflammasome activation and autophagy, suggesting that these cell-autonomous functions should be exploited for improved vaccine design.
cw2vec: Learning Chinese Word Embeddings with Stroke n-gram Information

We propose cw2vec, a novel method for learning Chinese word embeddings. It is based on our observation that exploiting stroke-level information is crucial for improving the learning of Chinese word embeddings. Specifically, we design a minimalist approach to exploit such features, by using stroke n-grams, which capture semantic and morphological level information of Chinese words. Through qualitative analysis, we demonstrate that our model is able to extract semantic information that cannot be captured by existing methods. Empirical results on the word similarity, word analogy, text classification and named entity recognition tasks show that the proposed approach consistently outperforms state-of-the-art approaches such as word-based word2vec and GloVe, character-based CWE, component-based JWE and pixel-based GWE.
User Personalized Satisfaction Prediction via Multiple Instance Deep Learning

Community-based question answering(CQA) services have arisen as a popular knowledge sharing pattern for netizens. With abundant interactions among users, individuals are capable of obtaining satisfactory information. However, it is not effective for users to attain answers within minutes. Users have to check the progress over time until the satisfying answers submitted. We address this problem as a user personalized satisfaction prediction task. Existing methods usually exploit manual feature selection. It is not desirable as it requires careful design and is labor intensive. In this paper, we settle this issue by developing a new multiple instance deep learning framework. Specifically, in our settings, each question follows a weakly supervised learning (multiple instance learning) assumption, where its obtained answers can be regarded as instance sets and we define the question resolved with at least one satisfactory answer. We thus design an efficient framework exploiting multiple instance learning property with deep learning tactic to model the question-answer pairs relevance and rank the asker’s satisfaction possibility. Extensive experiments on large-scale datasets from Stack Exchange demonstrate the feasibility of our proposed framework in predicting askers personalized satisfaction. Our framework can be extended to numerous applications such as UI satisfaction Prediction, multi-armed bandit problem, expert finding and so on.
A Consensual Linear Opinion Pool

An important question when eliciting opinions from experts is how to aggregate the reported opinions. In this paper, we propose a pooling method to aggregate expert opinions. Intuitively, it works as if the experts were continuously updating their opinions in order to accommodate the expertise of others. Each updated opinion takes the form of a linear opinion pool, where the weight that an expert assigns to a peer’s opinion is inversely related to the distance between their opinions. In other words, experts are assumed to prefer opinions that are close to their own opinions. We prove that such an updating process leads to consensus, i.e., the experts all converge towards the same opinion. Further, we show that if rational experts are rewarded using the quadratic scoring rule, then the assumption that they prefer opinions that are close to their own opinions follows naturally. We empirically demonstrate the efficacy of the proposed method using real-world data.
Citation based plagiarism detection: a new approach to identify plagiarized work language independently

This paper describes a new approach towards detecting plagiarism and scientific documents that have been read but not cited. In contrast to existing approaches, which analyze documents' words but ignore their citations, this approach is based on citation analysis and allows duplicate and plagiarism detection even if a document has been paraphrased or translated, since the relative position of citations remains similar. Although this approach allows in many cases the detection of plagiarized work that could not be detected automatically with the traditional approaches, it should be considered as an extension rather than a substitute. Whereas the known text analysis methods can detect copied or, to a certain degree, modified passages, the proposed approach requires longer passages with at least two citations in order to create a digital fingerprint.
Equalizer Design and Complexity for Digital Coherent Receivers

Digital signal processing has completely changed the way optical communication systems work during recent years. In combination with coherent demodulation, it enables compensation of optical distortions that seemed impossible only a few years ago. However, at high bit rates, this comes at the price of complex processing circuits and high power consumption. In order to translate theoretic concepts into economically viable products, careful design of the digital signal processing algorithms is needed. In this paper, we give an overview of digital equalization algorithms for coherent receivers and derive expressions for their complexity. We compare single-carrier and multicarrier approaches, and investigate blind equalizer adaptation as well as training-symbol-based algorithms. We examine tradeoffs between parameters like sampling rate and tracking speed that are important for algorithm design and practical implementation.
Cannabis use in palliative care - an examination of the evidence and the implications for nurses.

Examine the pharmaceutical qualities of cannabis including a historical overview of cannabis use. Discuss the use of cannabis as a clinical intervention for people experiencing palliative care, including those with life-threatening chronic illness such as multiple sclerosis and motor neurone disease [amyotrophic lateral sclerosis] in the UK.



The non-medicinal use of cannabis has been well documented in the media. There is a growing scientific literature on the benefits of cannabis in symptom management in cancer care. Service users, nurses and carers need to be aware of the implications for care and treatment if cannabis is being used medicinally.



A comprehensive literature review.



Literature searches were made of databases from 1996 using the term cannabis and the combination terms of cannabis and palliative care; symptom management; cancer; oncology; chronic illness; motor neurone disease/amyotrophic lateral sclerosis; and multiple sclerosis. Internet material provided for service users searching for information about the medicinal use of cannabis was also examined.



The literature on the use of cannabis in health care repeatedly refers to changes for users that may be equated with improvement in quality of life as an outcome of its use. This has led to increased use of cannabis by these service users. However, the cannabis used is usually obtained illegally and can have consequences for those who choose to use it for its therapeutic value and for nurses who are providing care.


 TO CLINICAL PRACTICE
Questions and dilemmas are raised concerning the role of the nurse when caring and supporting a person making therapeutic use of cannabis.
An infrastructure for real-time population health assessment and monitoring

real-time population health assessment and monitoring D. L. Buckeridge M. Izadi A. Shaban-Nejad L. Mondor C. Jauvin L. Dubé Y. Jang R. Tamblyn The fragmented nature of population health information is a barrier to public health practice. Despite repeated demands by policymakers, administrators, and practitioners to develop information systems that provide a coherent view of population health status, there has been limited progress toward developing such an infrastructure. We are creating an informatics platform for describing and monitoring the health status of a defined population by integrating multiple clinical and administrative data sources. This infrastructure, which involves a population health record, is designed to enable development of detailed portraits of population health, facilitate monitoring of population health indicators, enable evaluation of interventions, and provide clinicians and patients with population context to assist diagnostic and therapeutic decision-making. In addition to supporting public health professionals, clinicians, and the public, we are designing the infrastructure to provide a platform for public health informatics research. This early report presents the requirements and architecture for the infrastructure and describes the initial implementation of the population health record, focusing on indicators of chronic diseases related to obesity.
Necrotising fasciitis: a life-threatening complication of acupuncture in a patient with diabetes mellitus.

Acupuncture is used for some conditions as an alternative to medication or surgical intervention. Several complications had been reported, and they are generally due to physical injury by the needle or transmission of diseases. We report a case of life-threatening necrotising fasciitis that developed after acupuncture treatment for osteoarthritis of the knee in a 55-year-old diabetic woman. She presented with multiple discharging sinuses over the right knee. As the patient did not respond to intravenous antibiotics, extensive debridement was performed. She made a good recovery. Since many old diabetic patients with degenerative joint diseases may consider this mode of treatment, guidelines on cleanliness and sterility of this procedure should be developed and practiced.
An Automated Hierarchical Framework for Player Recognition in Sports Image

The recognition of player in the soccer game is a challenging task due to the continuous variation in the position, view, orientation and distance of the players as well as the camera. In order to resolve this problem, the player's identification number (which is printed on their jersey) is recognized and based on the number, players are identified. This paper proposes a noble Optical Character Recognition (OCR) system that automatically extracts and recognizes the player's jersey number in the image. A hierarchical computational framework is introduced which uses high and low-level vision features of the image to identify the player. While following the hierarchical approach a parsing tree is constructed by segmenting the image into snippets based on different algorithms. The entire parsing tree is divided into 4 levels: Level 1 deals with the playfield detection and shot classification, Level 2 tackles the player localization and extraction, Level 3 covers the player's number extraction and shape restoration, and Level 4 recognizes the player's number. The proposed OCR system has consistently shown outstanding results in terms of efficiency, effectiveness, and robustness over a large soccer dataset.
Trends in esophageal and esophagogastric junction cancer research from 2007 to 2016

This study aimed to analyze the scientific outputs of esophageal and esophagogastric junction (EGJ) cancer and construct a model to quantitatively and qualitatively evaluate pertinent publications from the past decade.



Publications from 2007 to 2016 were retrieved from the Web of Science Core Collection database. Microsoft Excel 2016 (Redmond, WA) and the CiteSpace (Drexel University, Philadelphia, PA) software were used to analyze publication outcomes, journals, countries, institutions, authors, research areas, and research frontiers.



A total of 12,978 publications on esophageal and EGJ cancer were identified published until March 23, 2017.  Esophageal squamous cell carcinoma ranked the first in research hotspots, and preoperative chemotherapy/chemoradiotherapy ranked the first in research frontiers.



The annual number of publications steadily increased in the past decade. A considerable number of papers were published in journals with high impact factor. Many Chinese institutions engaged in esophageal and EGJ cancer research but significant collaborations among them were not noted.  A, Van Hagen P, Cunningham D, and Enzinger PC were identified as good candidates for research collaboration. Neoadjuvant therapy and genome-wide association study in esophageal and EGJ cancer research should be closely observed.
A literature review on Software-Defined Networking (SDN) research topics, challenges and solutions

Cloud computing data centers are becoming increasingly popular for the provisioning of computing resources. In the past, most of the research works focused on the effective use of the computational and storage resources by employing the Virtualization technology. Network automation and virtualization of data center LAN and WAN were not the primary focus. Recently, a key emerging trend in Cloud computing is that the core systems infrastructure, including compute resources, storage and networking, is increasingly becoming Software-Defined. In particular, instead of being limited by the physical infrastructure, applications and platforms will be able to specify their fine-grained needs, thus precisely defining the virtual environment in which they wish to run. Software-Defined Networking (SDN) plays an important role in paving the way for effectively virtualizing and managing the network resources in an on demand manner. Still, many research challenges remain: how to achieve network Quality of Service (QoS), optimal load balancing, scalability, and security. Hence, it is the main objective of this article to survey the current research work and describes the ongoing efforts to address these challenging issues.
IOT based controlling of hybrid energy system using ESP8266

In this paper, authors have focused on controlling of hybrid energy system using IOT. There is various combination of energy and all of them are alternative to each other like solar energy, wind energy, bio fuel, fuel cell, etc. But the need of controlling of hybrid energy system arises when it is installed for domestic or commercial purpose. At this point IOT plays an important role in controlling system. The main criteria being switching between the two sources of energy i.e. solar and wind energy without any inconvenience through a website using ESP8266 Wi-Fi module. The data is transmitted wirelessly through website to ESP8266 module which controls the sources of energy. The transmitted data is controlled remotely using IOT. This enables user to have flexible control mechanism remotely through a secured internet web connection. This system helps the user to control the sources of energy, manually and remotely using smart phone or personal computer. This system is very efficient, cheaper and flexible in operation.
Tenofovir versus Placebo to Prevent Perinatal Transmission of Hepatitis B.

Pregnant women with an elevated viral load of hepatitis B virus (HBV) have a risk of transmitting infection to their infants, despite the infants' receiving hepatitis B immune globulin.



In this multicenter, double-blind clinical trial performed in Thailand, we randomly assigned hepatitis B e antigen (HBeAg)-positive pregnant women with an alanine aminotransferase level of 60 IU or less per liter to receive tenofovir disoproxil fumarate (TDF) or placebo from 28 weeks of gestation to 2 months post partum. Infants received hepatitis B immune globulin at birth and hepatitis B vaccine at birth and at 1, 2, 4, and 6 months. The primary end point was a hepatitis B surface antigen (HBsAg)-positive status in the infant, confirmed by the HBV DNA level at 6 months of age. We calculated that a sample of 328 women would provide the trial with 90% power to detect a difference of at least 9 percentage points in the transmission rate (expected rate, 3% in the TDF group vs. 12% in the placebo group).



From January 2013 to August 2015, we enrolled 331 women; 168 women were randomly assigned to the TDF group and 163 to the placebo group. At enrollment, the median gestational age was 28.3 weeks, and the median HBV DNA level was 8.0 log10 IU per milliliter. Among 322 deliveries (97% of the participants), there were 319 singleton births, two twin pairs, and one stillborn infant. The median time from birth to administration of hepatitis B immune globulin was 1.3 hours, and the median time from birth to administration of hepatitis B vaccine was 1.2 hours. In the primary analysis, none of the 147 infants (0%; 95% confidence interval [CI], 0 to 2) in the TDF group were infected, as compared with 3 of 147 (2%; 95% CI, 0 to 6) in the placebo group (P=0.12). The rate of adverse events did not differ significantly between groups. The incidence of a maternal alanine aminotransferase level of more than 300 IU per liter after discontinuation of the trial regimen was 6% in the TDF group and 3% in the placebo group (P=0.29).



In a setting in which the rate of mother-to-child HBV transmission was low with the administration of hepatitis B immune globulin and hepatitis B vaccine in infants born to HBeAg-positive mothers, the additional maternal use of TDF did not result in a significantly lower rate of transmission. (Funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development; ClinicalTrials.gov number, NCT01745822 .).
Mobileflow: Toward software-defined mobile networks

Mobile carrier networks follow an architecture where network elements and their interfaces are defined in detail through standardization, but provide limited ways to develop new network features once deployed. In recent years we have witnessed rapid growth in over-the-top mobile applications and a 10-fold increase in subscriber traffic while ground-breaking network innovation took a back seat. We argue that carrier networks can benefit from advances in computer science and pertinent technology trends by incorporating a new way of thinking in their current toolbox. This article introduces a blueprint for implementing current as well as future network architectures based on a software-defined networking approach. Our architecture enables operators to capitalize on a flow-based forwarding model and fosters a rich environment for innovation inside the mobile network. In this article, we validate this concept in our wireless network research laboratory, demonstrate the programmability and flexibility of the architecture, and provide implementation and experimentation details.