nils-herrmann/clean_scirepeval huggingface dataset:
Validity of administrative database coding for kidney disease: a systematic review.

Information in health administrative databases increasingly guides renal care and policy.



Systematic review of observational studies.



Studies describing the validity of codes for acute kidney injury (AKI) and chronic kidney disease (CKD) in administrative databases operating in any jurisdiction.



After searching 13 medical databases, we included observational studies published from database inception though June 2009 that validated renal diagnostic and procedural codes for AKI or CKD against a reference standard.


INDEX TESTS
Renal diagnostic or procedural administrative data codes.


REFERENCE TESTS
Patient chart review, laboratory values, or data from a high-quality patient registry.



25 studies of 13 databases in 4 countries were included. Validation of diagnostic and procedural codes for AKI was present in 9 studies, and validation for CKD was present in 19 studies. Sensitivity varied across studies and generally was poor (AKI median, 29%; range, 15%-81%; CKD median, 41%; range, 3%-88%). Positive predictive values often were reasonable, but results also were variable (AKI median, 67%; range, 15%-96%; CKD median, 78%; range, 29%-100%). Defining AKI and CKD by only the use of dialysis generally resulted in better code validity. The study characteristic associated with sensitivity in multivariable meta-regression was whether the reference standard used laboratory values (P < 0.001); sensitivity was 39% lower when laboratory values were used (95% CI, 23%-56%).



Missing data in primary studies limited some of the analyses that could be done.



Administrative database analyses have utility, but must be conducted and interpreted judiciously to avoid bias arising from poor code validity.
Modulation of adipokines and cytokines in gestational diabetes and macrosomia.

Not much is known about the implication of adipokines and different cytokines in gestational diabetes mellitus (GDM) and macrosomia. The purpose of this study was to assess the profile of these hormones and cytokines in macrosomic babies, born to gestational diabetic women.



A total of 59 women (age, 19-42 yr) suffering from GDM with their macrosomic babies (4.35 +/- 0.06 kg) and 60 healthy age-matched pregnant women and their newborns (3.22 +/- 0.08 kg) were selected.



Serum adipokines (adiponectin and leptin) were quantified using an obesity-related multiple ELISA microarray kit. The concentrations of serum cytokines were determined by ELISA.



Serum adiponectin levels were decreased, whereas the concentrations of leptin, inflammatory cytokines, such as IL-6 and TNF-alpha, were significantly increased in gestational diabetic mothers compared with control women. The levels of these adipocytokines were diminished in macrosomic babies in comparison with their age-matched control newborns. Serum concentrations of T helper type 1 (Th1) cytokines (IL-2 and interferon-gamma) were decreased, whereas IL-10 levels were significantly enhanced in gestational diabetic mothers compared with control women. Macrosomic children exhibited high levels of Th1 cytokines and low levels of IL-10 compared with control infants. Serum IL-4 levels were not altered between gestational diabetic mothers and control mothers or the macrosomic babies and newborn control babies.



GDM is linked to the down-regulation of adiponectin along with Th1 cytokines and up-regulation of leptin and inflammatory cytokines. Macrosomia was associated with the up-regulation of Th1 cytokines and the down-regulation of the obesity-related agents (IL-6 and TNF-alpha, leptin, and adiponectin).
Coordination theory Coordination Theory : A Ten-Year Retrospective

Since the initial publication in 1994, Coordination Theory (Malone and Crowston, 1994) has been referenced in nearly 300 journal articles, book chapters, conference papers and theses. This chapter will analyze the contribution of this body of research to determine how Coordination Theory has been used for user task analysis and modelling for HCI. Issues that will be addressed include: I) how the theory has been applied; 2) factors that led to the success of the theory; and 3) identification of areas needing further research.
TeamDL at SemEval-2018 Task 8: Cybersecurity Text Analysis using Convolutional Neural Network and Conditional Random Fields

In this paper we present our participation to SemEval-2018 Task 8 subtasks 1 & 2 respectively. We developed Convolution Neural Network system for malware sentence classification (subtask 1) and Conditional Random Fields system for malware token label prediction (subtask 2). We experimented with couple of word embedding strategies, feature sets and achieved competitive performance across the two subtasks. Code is made available at https://bitbucket.org/ vishnumani2009/securenlp
Distance and similarity measures for hesitant fuzzy sets

In this paper, we propose a variety of distance measures for hesitant fuzzy sets, based on which the corresponding similarity measures can be obtained. We investigate the connections of the aforementioned distance measures and further develop a number of hesitant ordered weighted distance measures and hesitant ordered weighted similarity measures. They can alleviate the influence of unduly large (or small) deviations on the aggregation results by assigning them low (or high) weights. Several numerical examples are provided to illustrate these distance and similarity measures.
Digital Business Ecosystem Transformation -- Towards Cloud Integration

Digital business ecosystems are becoming an increasingly popular concept as an open environment for modeling and building interoperable system integration. Business organizations have realized the importance of using standards as a cost-effective method for accelerating business process integration. Small and medium size enterprise (SME) participation in global trade is increasing, however, digital transactions are still at a low level. Cloud integration is expected to offer a cost-effective business model to form an interoperable digital supply chain. By observing the integration models, we can identify the large potential of cloud services to accelerate integration. An industrial case study is conducted. This paper investigates and contributes new knowledge on a how top-down approach by using a digital business ecosystem framework enables business managers to define new user requirements and functionalities for system integration. Through analysis, we identify the current cap of integration design. Using the cloud clustering framework, we identify how the design affects cloud integration services.
University of British Columbia Food System Project: Towards Sustainable and Secure Campus Food Systems

In this profile article, we report what we consider to be a rich learning experience which intertwines pedagogy and research: a process of community-based action research which has initiated a transition towards the sustainability of the University of British Columbia’s (UBC) food system. We call this initiative the UBC Food System Project (UBCFSP). The UBCFSP is a jointly initiated project between the Faculty of Land and Food Systems and the UBC Sustainability Office, and includes nine UBC organizational partners and one collaborator. The project emerged out of the recognition that our global, national, regional, and local food systems are increasingly characterized as socially, ecologically, and economically insecure and unsustainable. As a result, these food systems are experiencing an array of vulnerabilities, particularly those that are demonstrated by profound disruptions in our ecosystem and in a worldwide epidemic of malnutrition. The overall objective of the project is to conduct a campus-wide UBC food system sustainability assessment, where barriers that hinder and opportunities to make transitions towards food system sustainability are being collaboratively identified and implemented. This article is part of a series intending to share the experiences gathered so far through the project. The purpose of this profile is to provide a brief overview of the UBC Food System Project, including the context and significance, both the pedagogical approach and research methods, and some accomplishments to date.
Oversimplification in the study of emotional memory.

This Short Review critically evaluates three hypotheses about the effects of emotion on memory: First, emotion usually enhances memory. Second, when emotion does not enhance memory, this can be understood by the magnitude of physiological arousal elicited, with arousal benefiting memory to a point but then having a detrimental influence. Third, when emotion facilitates the processing of information, this also facilitates the retention of that same information. For each of these hypotheses, we summarize the evidence consistent with it, present counter-evidence suggesting boundary conditions for the effect, and discuss the implications for future research.
The Significant Features of the UNSW-NB15 and the KDD99 Data Sets for Network Intrusion Detection Systems

Because of the increase flow of network traffic and its significance to the provision of ubiquitous services, cyberattacks attempt to compromise the security principles of confidentiality, integrity and availability. A Network Intrusion Detection System (NIDS) monitors and detects cyber-attack patterns over networking environments. Network packets consist of a wide variety of features which negatively affects detection of anomalies. These features include some irrelevant or redundant features which reduce the efficiency of detecting attacks, and increase False Alarm Rate (FAR). In this paper, the feature characteristics of the UNSW-NB15 and KDD99 datasets are examined, and the features of the UNSW-NB15 are replicated to the KDD99 data set to measure their effeciency. We apply An Association Rule Mining algorithm as feature selection to generate the strongest features from the two data sets. Some existing classifiers are utilised to evaluate the complexity in terms of accuracy and FAR. The experimental results show that, the original KDD99 attributes are less efficient than the replicated UNSW-NB15 attributes of the KDD99 data set. However, comparing the two data sets, the accuracy of the KDD99 dataset is better than the UNSW-NB 15 dataset, and the FAR of the KDD99 dataset is lower the UNSWNB 15 dataset.
Decision Trees: An Overview and Their Use in Medicine

In medical decision making (classification, diagnosing, etc.) there are many situations where decision must be made effectively and reliably. Conceptual simple decision making models with the possibility of automatic learning are the most appropriate for performing such tasks. Decision trees are a reliable and effective decision making technique that provide high classification accuracy with a simple representation of gathered knowledge and they have been used in different areas of medical decision making. In the paper we present the basic characteristics of decision trees and the successful alternatives to the traditional induction approach with the emphasis on existing and possible future applications in medicine.
FaceVR: Real-Time Gaze-Aware Facial Reenactment in Virtual Reality

We propose FaceVR, a novel image-based method that enables video teleconferencing in VR based on self-reenactment. State-of-the-art face tracking methods in the VR context are focused on the animation of rigged 3D avatars (Li et al. 2015; Olszewski et al. 2016). Although they achieve good tracking performance, the results look cartoonish and not real. In contrast to these model-based approaches, FaceVR enables VR teleconferencing using an image-based technique that results in nearly photo-realistic outputs. The key component of FaceVR is a robust algorithm to perform real-time facial motion capture of an actor who is wearing a head-mounted display (HMD), as well as a new data-driven approach for eye tracking from monocular videos. Based on reenactment of a prerecorded stereo video of the person without the HMD, FaceVR incorporates photo-realistic re-rendering in real time, thus allowing artificial modifications of face and eye appearances. For instance, we can alter facial expressions or change gaze directions in the prerecorded target video. In a live setup, we apply these newly introduced algorithmic components.
The Close Enough Traveling Salesman Problem: A Discussion of Several Heuristics

The use of radio frequency identification (RFID) allows utility companies to read meters from a distance. Thus a meter reader need not visit every customer on his route, but only get within a certain radius of each customer. In finding an optimal route – one that minimizes the distance the meter reader travels while servicing each customer on his route – this notion of only needing to be close enough changes the meter reading problem from a standard Traveling Salesperson Problem (TSP) into a variant problem: Close Enough TSP (CETSP). As a project for a graduate course in network optimization various heuristics for finding near optimal CETSP solutions were developed by six groups of students. In this paper we survey the heuristics and provide results for a diverse set of sample cases.
A Fractal Model of Mountains with Rivers Przemyslaw Prusinkiewicz and

This paper addresses the long-standing problem of generating fractal mountains with rivers, and presents a partial solution that incorporates a squig-curve model of a river’s course into the midpoint-displacement model for mountains. The method is based on the observation that both models can be expressed by similar context-sensitive rewriting mechanisms. As a result, a mountain landscape with a river can be generated using a single integrated process.
Exploring the taxonomie and associative link between emotion and function for robot sound design

Sound is a medium that conveys functional and emotional information in a form of multilayered streams. With the use of such advantage, robot sound design can open a way for being more efficient communication in human-robot interaction. As the first step of research, we examined how individuals perceived the functional and emotional intention of robot sounds and whether the perceived information from sound is associated with their previous experience with science fiction movies. The sound clips were selected based on the context of the movie scene (i.e., Wall-E, R2-D2, BB8, Transformer) and classified as functional (i.e., platform, monitoring, alerting, feedback) and emotional (i.e., positive, neutral, negative). A total of 12 participants were asked to identify the perceived properties for each of the 30 items. We found that the perceived emotional and functional messages varied from those originally intended and differed by previous experience.
Comparison of the effi cacy and safety of new oral anticoagulants with warfarin in patients with atrial fi brillation : a meta-analysis of randomised trials

We searched Medline from Jan 1, 2009, to Nov 19, 2013, limiting searches to phase 3, randomised trials of patients with atrial fi brillation who were randomised to receive new oral anticoagulants or warfarin, and trials in which both effi cacy and safety outcomes were reported. We did a prespecifi ed meta-analysis of all 71 683 participants included in the RE-LY, ROCKET AF, ARISTOTLE, and ENGAGE AF–TIMI 48 trials. The main outcomes were stroke and systemic embolic events, ischaemic stroke, haemorrhagic stroke, all-cause mortality, myocardial infarction, major bleeding, intracranial haemorrhage, and gastrointestinal bleeding. We calculated relative risks (RRs) and 95% CIs for each outcome. We did subgroup analyses to assess whether diff erences in patient and trial characteristics aff ected outcomes. We used a random-eff ects model to compare pooled outcomes and tested for heterogeneity.
Dialog state tracking, a machine reading approach using a memory-enhanced neural network

In an end-to-end dialog system, the aim of dialog state tracking is to accurately estimate a compact representation of the current dialog status from a sequence of noisy observations produced by the speech recognition and the natural language understanding modules. A state tracking module is primarily meant to act as support for a dialog policy but it can also be used as support for dialog corpus summarization and other kinds of information extraction from transcription of dialogs. From a probabilistic view, this is achieved by maintaining a posterior distribution over hidden dialog states composed, in the simplest case, of a set of context dependent variables. Once a dialog policy is defined, deterministic or learnt, it is in charge of selecting an optimal dialog act given the estimated dialog state and a defined reward function. This paper introduces a novel method of dialog state tracking based on the general paradigm of machine reading and proposes to solve it using a memory-enhanced neural network architecture. We evaluate the proposed approach on the second Dialog State Tracking Challenge (DSTC-2) dataset that has been converted for the occasion in order to fit the relaxed assumption of a machine reading formulation where the true state is only provided at the very end of each dialog instead of providing the state updates at the utterance level. We show that the proposed tracker gives encouraging results. Finally, we propose to extend the DSTC-2 dataset with specific reasoning capabilities requirement like counting, list maintenance, yes-no question answering and indefinite knowledge management.
Spectrum of congenital heart defects and extracardiac malformations associated with chromosomal abnormalities: results of a seven year necropsy study.

To analyse the spectrum of congenital heart malformations, the frequency of extracardiac malformations, and the proportion of chromosome aberrations among fetuses sent for necropsy.



Necropsies were performed on 815 fetuses-448 induced abortions (55%), 220 spontaneous abortions (27%), and 147 stillbirths (18%)-during a seven year period (1991-97) in the department of pathology of the Charité Medical Centre in Berlin. A congenital heart defect was identified in 129 cases (16%). For all 129 fetuses, karyotyping and an ultrasound examination had been performed.



Congenital heart defects were present in 22% of induced abortions (99 cases), 9% of spontaneous abortions (20 cases), and 7% of stillbirths (10 cases). The heart malformations were classified into 13 categories. A fetus with more than one defect was included only in the category of the most serious defect. The malformations in order of frequency were: ventricular septal defect (VSD) (28%), atrioventricular septal defect (AVSD) (16%), hypoplastic left heart (HLH) (16%), double outlet right ventricle (DORV) (12%), coarctation of the aorta (CoA) (6%), transposition of the great arteries (TGA) (4%), aortic valve stenosis (AoVS) (4%), tetralogy of Fallot (TOF) (3%), truncus arteriosus communis (TAC) (3%), pulmonary valve stenosis/pulmonary valve atresia (PaVS/PaVA) (3%), tricuspid atresia (TA) (3%), single ventricle (SV) (1.5%), and atrial septal defect (ASD) (0.5%). The most common congenital heart defects were VSD, AVSD, HLH, and DORV, which made up 72% of all the cases. In 11 cases the heart defect was isolated (no other cardiovascular or extracardiac malformations present), 85 cases (66%) were associated with additional cardiac malformations, 85 cases (66%) were associated with extracardiac malformations, and chromosome anomalies were detected in 43 cases (33%).



Fetal congenital heart malformations are common. These defects are often associated with other cardiovascular and extracardiac malformations, as well as with chromosome anomalies. Complex heart defects such as AVSD, HLH, and DORV are frequent in fetuses, as they often lead to spontaneous abortion or stillbirth or, after prenatal diagnosis, to deliberate termination of pregnancy.
Comparison of transplacental treatment of fetal supraventricular tachyarrhythmias with digoxin, flecainide, and sotalol: results of a nonrandomized multicenter study.

Fetal tachyarrhythmia may result in low cardiac output and death. Consequently, antiarrhythmic treatment is offered in most affected pregnancies. We compared 3 drugs commonly used to control supraventricular tachycardia (SVT) and atrial flutter (AF).



We reviewed 159 consecutive referrals with fetal SVT (n=114) and AF (n=45). Of these, 75 fetuses with SVT and 36 with AF were treated nonrandomly with transplacental flecainide (n=35), sotalol (n=52), or digoxin (n=24) as a first-line agent. Prenatal treatment failure was associated with an incessant versus intermittent arrhythmia pattern (n=85; hazard ratio [HR]=3.1; P<0.001) and, for SVT, with fetal hydrops (n=28; HR=1.8; P=0.04). Atrial flutter had a lower rate of conversion to sinus rhythm before delivery than SVT (HR=2.0; P=0.005). Cardioversion at 5 and 10 days occurred in 50% and 63% of treated SVT cases, respectively, but in only 25% and 41% of treated AF cases. Sotalol was associated with higher rates of prenatal AF termination than digoxin (HR=5.4; P=0.05) or flecainide (HR=7.4; P=0.03). If incessant AF/SVT persisted to day 5 (n=45), median ventricular rates declined more with flecainide (-22%) and digoxin (-13%) than with sotalol (-5%; P<0.001). Flecainide (HR=2.1; P=0.02) and digoxin (HR=2.9; P=0.01) were also associated with a higher rate of conversion of fetal SVT to a normal rhythm over time. No serious drug-related adverse events were observed, but arrhythmia-related mortality was 5%.



Flecainide and digoxin were superior to sotalol in converting SVT to a normal rhythm and in slowing both AF and SVT to better-tolerated ventricular rates and therefore might be considered first to treat significant fetal tachyarrhythmia.
Battery optimization in smartphones for remote health monitoring systems to enhance user adherence

Remote health monitoring (RHM) can help save the cost burden of unhealthy lifestyles. Of increased popularity is the use of smartphones to collect data, measure physical activity, and provide coaching and feedback to users. One challenge with this method is to improve adherence to prescribed medical regimens. In this paper we present a new battery optimization method that increases the battery lifetime of smartphones which monitor physical activity. We designed a system, WANDA-CVD, to test our battery optimization method. The focus of this report describes our in-lab pilot study and a study aimed at reducing cardiovascular disease (CVD) in young women, the Women's Heart Health study. Conclusively, our battery optimization technique improved battery lifetime by 300%. This method also increased participant adherence to the remote health monitoring system in the Women's Heart Health study by 53%.
A Customer Churn Analysis Model in E-business Environment

Today, more and more companies in e-business have acknowledged that their business strategies should focus on identifying those customers who are likely to churn as markets become increasingly saturated. In this paper a new method was put forward to analyze and predict customer churn behavior based on data mining techniques, such as decision tree, clustering, neural network, etc. By collecting a large amount of customer churn questionnaire data, this paper established an e-business customer churn prediction and analysis model, analyzed the related factors which influence customer retention of e-business enterprises, and proposed many corresponding loss control measures.
A deep learning and RSSI based approach for indoor positioning

Indoor positioning and navigation systems are getting popular nowadays. There are different types of products in the way of accuracy, cost and power consumption in the field. Especially in the last couple of years, RSSI (Received Signal Strength Indicator) based positioning algorithms have studied but the results are not sufficient and there is no exact way decided to overcome this problem. In this paper, we will explain a method that combines Deep Learning and BLE (Bluetooth Low Energy) Fingerprinting method to get better accurate results.