Miracle-dz/UniFAR-FTUs huggingface dataset:
To what extent are patients with migraine able to predict attacks?

Purpose Premonitory symptoms (PSs) of migraine are those that precede pain in a migraine attack. Previous studies suggest that treatment during this phase may prevent the onset of pain; however, this approach requires that patients be able to recognize their PSs. Our objectives were to evaluate patients’ actual ability to predict migraine attacks based on their PSs and analyze whether good predictors meet any characteristic profile. Patients and methods This prospective, observational study included patients with migraine with and without aura. Patients’ baseline characteristics were recorded. During a 2-month follow-up period, patients used a mobile application to record what they believed to be PSs and later to record the onset of pain, if this occurred. When a migraine attack ended, patients had to complete a form on the characteristics of the episode (including the presence of PSs not identified prior to the attack). Results Fifty patients were initially selected. A final total of 34 patients were analyzed, recording 229 attacks. Of whom, 158 (69%) were accompanied by PSs and were recorded prior to the pain onset in 63 (27.5%) cases. A total of 67.6% of the patients were able to predict at least one attack, but only 35.3% were good predictors (>50% of attacks). There were only 11 cases in which a patient erroneously reported their PSs (positive predictive value: 85.1%). Good predictors were not differentiated by any specific clinical characteristic. However, a range of symptoms were particularly predictive; these included photophobia, drowsiness, yawning, increased thirst, and blurred vision. Conclusion A large majority of patients with migraine experienced a PS and were able to predict at least one attack. Besides, only a small percentage of patients were considered as good predictors; however, they could not be characterized by any specific profile. Nonetheless, when patients with migraine believed that they were experiencing PSs, they were frequently correct.
Feed-Net: Fully End-to-End Dehazing

This paper proposes an image dehazing model built with a fully convolutional neural network (CNN), called Fully End-to-End Dehazing Network (FEED-Net). In contrast to estimate the transmission map and the atmospheric light separately as most previous deep learning methods, FEED-Net recovers the hazy-free image directly from a hazy image via a light-weight CNN. In addition, we introduce contextual information into dehazing via dilated convolution and use dense skip connection for feature fusion, which makes end-to-end dehazing possible. Experimental results show our method outperforms the state-of-the-art algorithms on both synthetic dataset and real-world images.
Cross-Version Defect Prediction using Cross-Project Defect Prediction Approaches: Does it work?

Background: Specifying and removing defects before release deserve extra cost for the success of software projects. Long-running projects experience multiple releases, and it is a natural choice to adopt cross-version defect prediction (CVDP) that uses information from older versions. A past study shows that feeding multi older versions data may have a positive influence on the performance. The study also suggests that cross-project defect prediction (CPDP) may fit the situation but one CPDP approach was only examined. Aims: To investigate whether feeding multiple older versions data is effective for CVDP using CPDP approaches. The investigation also involves performance comparisons of the CPDP approaches under CVDP situation. Method: We chose a style of replication of the comparative study on CPDP approaches by Herbold et al. under CVDP situation. Results: Feeding multiple older versions had a positive effect for more than a half CPDP approaches. However, almost all of the CPDP approaches did not perform significantly better than a simple rule-based prediction. Although the best CPDP approach could work better than it and with-in project defect prediction, we found no effect of feeding multiple older versions for it. Conclusions: Feeding multiple older versions could improve CPDP approaches under CVDP situation. However, it did not work for the best CPDP approach in the study.
GMOD: a dynamic GPU memory overflow detector

Rich thread-level parallelism in GPU has motivated co-running GPU kernels on a single GPU. However, when GPU kernels co-run, it is possible that a kernel can leverage buffer overflow to attack another kernel running on the same GPU. There is very limited work aiming to detect buffer overflow for GPU. The existing work has either large performance overhead or limited capability to detect buffer overflow. In this paper, we introduce GMOD, a runtime software system that detects GPU buffer overflow. GMOD performs always-on monitoring on dynamically allocated buffers based on a canary-based design. GMOD introduces a set of byte arrays to store buffer information for buffer overflow detection. To enable high performance, GMOD introduces several techniques, such as lock-free accesses to the byte arrays, delayed memory free for high performance memory free, and efficient memory reallocation and garbage collection for the byte arrays. Our experiments show that GMOD is capable of detecting buffer overflows at runtime and has small runtime overhead (2.9% on average and up to 9.1%).
Embedded Fatigue Detection Using Convolutional Neural Networks with Mobile Integration

Fatigued or drowsy drivers pose a significant risk of causing life-threatening accidents. Yet, many sleep-deprived drivers are behind the wheels exposing lives to danger. In this paper, we propose a low-cost and real-time embedded system for fatigue detection using convolutional neural networks (CNN). Our system starts by spatially processing the video signal using a real-time face detection algorithm to establish a region of interest and reduce computations. The video signal comes from a camera module mounted on the car dashboard connected to an embedded Linux board set to monitor the driver's eyes. Detected faces are then passed to an optimized fatigue recognition CNN binary classifier to detect the event of fatigued or normal driving. When temporally persistent fatigue is detected, alerts are sent to the driver's smart phone, and to possibly others, for prevention measures to be taken before accidents happen. Our testing shows that the system can robustly detect fatigue and can effectively be deployed to address the problem.
Women’s sanitation practices in informal settlements: A multi-level analysis of factors influencing utilisation in Nairobi, Kenya

ABSTRACT For decades, countries throughout the world have failed to meet sanitation-related development goals. Access to safe sanitation is undeniably linked to improved health outcomes; yet, 2.4 billion people, globally, still lack access. The persistent failure to meet sanitation goals suggests that our understanding of the factors that influence sustainable sanitation access and utilisation is incomplete. Despite growing availability of toilets in informal settlements, there is evidence that women, in particular, may adopt other strategies for managing their sanitation needs. Empirical data documenting the motivations underlying such practices in sub-Saharan Africa are limited. This study uses cross-sectional data collected in 2016 from women in Mathare Valley Informal Settlement in Nairobi, Kenya. Boosted and logistic regressions were used to investigate which factors were associated with women’s common sanitation patterns. Lack of privacy and insecurity at toilets and neighbourhood disorganisation emerged as important factors – particularly for women who reported regularly using buckets or plastic bags for urination/defecation. These findings suggest that availability of toilets may not be enough to eliminate sanitation-related health risks in informal settlements. Future interventions may need to address other barriers to sanitation access if sustainable gains in this important public health area are to be achieved.
Percutaneous Left Atrial Appendage Occlusion for the Prevention of Stroke in Patients with Atrial Fibrillation: Review and Critical Appraisal

The authors review the current status of percutaneous left atrial appendage (LAA) occlusion therapy in patients with atrial fibrillation with the goal to prevent ischemic stroke and systemic embolism and to reduce oral anticoagulation associated bleeding. While we cover the historical and also surgical background, and all tested devices, the main focus rests on the single currently U.S. Food and Drug Administration (FDA) approved LAA occluder, the WATCHMAN device, and its approval process. The authors also give a critical appraisal beyond the review of mere facts, trying to put the current data into perspective.
Proposal for a New TNM Stage based on the 7th and 8th American Joint Committee on Cancer pTNM Staging Classification for Gastric Cancer

Background: The 8th edition of the American Joint Committee on Cancer (AJCC) staging system for gastric cancer incorporated several new changes. We aimed to assess the comparative prognostic values of the 7th and 8th AJCC pTNM staging systems in patients with gastric cancer (GC), and accordingly, to put forward a refined staging classification. Methods: The SEER database was queried to identify GC patients between 2004 and 2009. GC patients from Sun Yat-sen University Cancer Center (SYSUCC) were used as external validation data. The Kaplan-Meier method and Cox proportional hazards regression models were used to analyze cause-specific survival (CSS). The prognostic performance of different staging schemes was assessed using the concordance index (c-index), Akaike's information criterion (AIC), and likelihood ratio χ2 test. Results: In the SEER cohort, stage migration occurred in 8.74% of patients. Survival analysis showed that it was better to treat T4bN0M0 + T4aN2M0 as stage IIIB and T4bN3bM0 as stage IV. Based on this, we established a new staging system which exhibited a superior c-index (0.7501) to the 7th and 8th AJCC staging systems (0.7498 and 0.7500, respectively). The new staging system also outperformed the 7th and 8th AJCC staging systems in terms of AIC and the likelihood ratio χ2 test. The predictive superiority of the new staging system remained valid in the SYSUCC database. Conclusions: We demonstrated that some stage modifications in the 8th AJCC pathologic staging were unnecessary. Therefore we established a new staging system, which was superior to the 7th and 8th staging systems.
Genetic risk score based on fat mass and obesity-associated, transmembrane protein 18 and fibronectin type III domain containing 5 polymorphisms is associated with anthropometric characteristics in South Brazilian children and adolescents

Abstract The prevalence of childhood obesity has increased worldwide. Although it is considered a polygenic inheritance disease, little is known about its susceptibility when the additive effect is considered. The aim of this study is to investigate whether the genetic risk score (GRS) based on previously associated obesity polymorphisms (SNP) rs9939609 (fat mass and obesity-associated (FTO)), rs6548238 (transmembrane protein 18 (TMEM18)) and rs16835198 (fibronectin type III domain containing 5 (FNDC5)) could serve as a predictor for anthropometric characteristics in a sample of Brazilian children and adolescents. This is a cross-sectional study with 1471 children and adolescents aged 6–17 years. BMI, waist circumference (WC) and percentage of body fat and metabolic parameters were verified. In all, three SNP were genotyped by TaqMan™ allelic discrimination. The metabolic and anthropometric parameters were compared between the genotypes, and the unweighted and weighted GRS (GRS and wGRS, respectively) were created to test the additive effect of these genetic polymorphisms on anthropometric parameters. The prevalence of overweight plus obesity was 41 %. Significant associations were identified for FTO rs9939609, TMEM18 rs6548238 and FNDC5 rs16835198 and for GRS and wGRS with anthropometric phenotypes. The higher score of wGRS was associated with obesity (OR: 2·65, 95 % CI 1·40, 5·04, P=0·003) and with greater WC (OR: 2·91, 95 % CI 1·57, 5·40, P=0·001). Our results suggest that these genetic variants contribute to obesity susceptibility in children and adolescents and reinforce the idea that the additive effect may be useful to elucidate the genetic component of obesity.
CUB360: Exploiting Cross-Users Behaviors for Viewport Prediction in 360 Video Adaptive Streaming

To ensure 360-degree video's continuous playback and reduce the bandwidth waste, predicting user's future fixation is indispensable. However, existing methods concentrate either on user's motion information or content information. None of them consider users watching behaviors' inconsistency which embodies user's attention distribution more explicitly. So in this paper, we exploit Cross-Users Behaviors for viewport prediction in 360-degree video adaptive streaming, namely CUB360, trying to concurrently consider user's personalized information and cross-users behaviors information to predict future viewport. Besides, we use a QoE-driven framework to optimize existing video streaming approaches and propose a general algorithm aiming at solving the NP problem at a low complexity. Extensive experimental results over real datasets demonstrate that compared with traditional adaptive streaming method, our proposal can significantly boost the prediction accuracy by 20.2% absolutely and 48.1 % relatively. Besides, the mean quality can get 30.28% gain while quality variance can be reduced by 29.89%.
Blind, Adaptive and Robust Flow Segmentation in Datacenters

To optimize routing of flows in datacenters, SDN controllers receive a packet-in message whenever a new flow appears in the network. Unfortunately, flow arrival rates can peak to millions per second, impairing the ability of controllers to treat them on time. Flow scheduling copes with such sheer numbers by segmenting the traffic between elephant and mice flows and by treating elephant flows in priority, as they disrupt short lived TCP flows and create bottlenecks. We propose a learning algorithm called SOFIA and able to perform optimal online flow segmentation. Our solution, based on stochastic approximation techniques, is implemented at the switch level and updated by the controller, with minimal signaling over the control channel. SOFIA is blind, i.e., it is oblivious to the flow size distribution. It is also adaptive, since it can track traffic variations over time. We prove its convergence properties and its message complexity. Moreover, we specialize our solution to be robust to traffic classification errors. Extensive numerical experiments characterize the performance of our approach in vitro. Finally, results of the implementation in a real OpenFlow controller demonstrate the viability of SOFIA as a solution in production environments.
Does the medical literature remain inadequately described despite having reporting guidelines for 21 years? – A systematic review of reviews: an update

Purpose Reporting guidelines (eg, Consolidated Standards of Reporting Trials [CONSORT] statement) are intended to improve reporting standards and enhance the transparency and reproducibility of research findings. Despite accessibility of such guidelines, researchers are not required to adhere to them. Our goal was to determine the current status of reporting quality in the medical literature and examine whether adherence of reporting guidelines has improved since the inception of reporting guidelines. Materials and methods Eight reporting guidelines, such as CONSORT, Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), STrengthening the Reporting of OBservational studies in Epidemiology (STROBE), Quality of Reporting of Meta-analysis (QUOROM), STAndards for Reporting of Diagnostic accuracy (STARD), Animal Research: Reporting In Vivo Experiments (ARRIVE), Consolidated Health Economic Evaluation Reporting Standards (CHEERS), and Meta-analysis of Observational Studies in Epidemiology (MOOSE) were examined. Our inclusion criteria included reviews published between January 1996 to September 2016 which investigated the adherence to reporting guidelines in the literature that addressed clinical trials, systematic reviews, observational studies, meta-analysis, diagnostic accuracy, economic evaluations, and preclinical animal studies that were in English. All reviews were found on Web of Science, Excerpta Medical Database (EMBASE), MEDLINE, and Cumulative Index to Nursing and Allied Health Literature (CINAHL). Results Among the general searching of 26,819 studies by using the designed searching method, 124 studies were included post screening. We found that 87.9% of the included studies reported suboptimal adherence to reporting guidelines. Factors associated with poor adherence included non-pharmacological interventions, year of publication, and trials concluding with significant results. Improved adherence was associated with better study designs such as allocation concealment, random sequence, large sample sizes, adequately powered studies, multiple authorships, and being published in journals endorsing guidelines. Conclusion We conclude that the level of adherence to reporting guidelines remains suboptimal. Endorsement of reporting guidelines by journals is important and recommended.
Information failures and catastrophes: What can we learn by linking information studies and disaster research?

The genesis and context of disasters and mishaps raise a set of topics that are of interest for Information Studies; namely, the contributions of information failures as precursors to, as opposed to outcomes of, disasters. There is much to be learned by relating the research in three key areas: disasters, information use environments and behaviours, and culture (i.e., cultural knowledge, and information, safety, and organizational cultures). Patient safety failures in hospitals provide both a timely context and practical examples to illustrate these connections. This paper highlights the linkages and raises questions for information professionals and for future research.
Facilitators and barriers to HIV testing among Asians in the United States: a systematic review

ABSTRACT Asians have the highest rate of undiagnosed HIV in the United States. Limited research on factors implicated in HIV testing among this population presents a barrier to monitoring and addressing HIV testing disparities. To examine predictors of HIV testing among Asians in the United States, a systematic search of articles published from January 1997 to December 2017 was conducted using four electronic databases, including Medline, PubMed, PsycINFO, and Web of Science. Twenty-two articles were included according to predefined inclusion criteria: peer-reviewed, published in English, took place in the United States, included participants at least 18 years of age, reported data specifically on Asians or Asian subgroups, and assessed HIV testing. Included studies were assessed by methodological quality scoring. Individual-level factors such as HIV knowledge and HIV risk perceptions were commonly reported facilitators of HIV testing. Studies placed less attention on community, institutional, or structural level factors predicting HIV testing. Sorely warranted are high quality, longitudinal studies that examine HIV testing among Asians in the United States. Multi-level theoretical frameworks that examine HIV testing among Asians with attention to ethnic subgroups are needed to improve understanding of HIV testing and to develop targeted testing interventions.
Imaging findings in spinal sarcoidosis: a report of 18 cases and review of the current literature

Purpose Spinal sarcoidosis, referring to involvement of the spine in sarcoidosis, is relatively rare and may mimic other neurological disease affecting the spine. The authors present a clinic radiological review of 18 spinal sarcoidosis patients who presented to a tertiary hospital, with emphasis on initial imaging and radiological response to treatment. Materials and methods We retrospectively reviewed our departmental imaging archives over a 15-year period and found 49 cases of neurosarcoidosis out of which 18 patients had spinal magnetic resonance imaging. Results Approximately 72% (13/18) of the neurosarcoidosis patients showed some form of spinal involvement. The clinical, epidemiological and imaging data were reviewed for these 13 patients at presentation and follow-up. The findings on magnetic resonance imaging included leptomeningeal enhancement (61%), pachymeningeal (23%), intramedullary enhancing lesions (38%) and bony involvement (15%). The cervical segment was most frequently involved followed by the thoracic segment. Involvement was often long segment (4.2 spinal segments) with proclivity for the dorsal cord. Mean follow-up was 23.2 months. A complete or near-complete radiological response occurred in 66% while partial response was seen in 25% patients. Four patients had isolated central nervous system involvement including one with isolated spinal cord involvement. On diffusion-weighted imaging, the apparent diffusion coefficient of intramedullary lesions was increased compared to normal-appearing cord on baseline and subsequent follow-up scans. Conclusions Spinal sarcoidosis was previously considered uncommon but is being increasingly recognized with widespread use of magnetic resonance imaging. Proclivity for dorsal surface involvement is characteristic, although not necessarily pathognomonic. Also, quantitative diffusion studies may serve as a biomarker for the disease activity and parenchymal injury.
Father 2 Son: The Impact of African American Father–Son Sexual Communication on African American Adolescent Sons’ Sexual Behaviors

Parent–child sexual communication has been associated with reducing adolescent sexual risk behaviors. Limited research on parent–child sexual communication has been conducted on African American (AA) adolescent males who are at increased risk of sexually transmitted infections (STIs) including HIV/AIDS. The purpose of this research was to examine AA father–son sexual communication and the effect of contextual factors on the sexual risk behaviors. The final sample consisted of 96 AA adolescent males, ages 16–21 years. Structural equation modeling was used to examine the variables of interest (neighborhood characteristics, father–son closeness and connectedness, father–son communication, sexual permissiveness, condom attitudes, sexual risk behaviors). A path model was developed and tested. Results demonstrated that AA father–son closeness and connectedness were related to father–son communication. AA father–son communication was negatively related to sons’ permissiveness and positively related to condom attitudes. Sons’ permissiveness positively predicted their sexual risk behaviors. AA sons’ condom attitudes did not negatively or positively predict their sexual risk behaviors. The findings from this study demonstrate that AA father–son communication is an important factor in decreasing AA adolescent males’ sexual risk behaviors and HIV risk.