Miracle-dz/UniFAR-FTUs huggingface dataset:
Spatio–Temporal Edge Service Placement: A Bandit Learning Approach

Shared edge computing platforms deployed at the radio access network are expected to significantly improve the quality-of-service delivered by application service providers (ASPs) in a flexible and economic way. However, placing edge service in every possible edge site by an ASP is practically infeasible due to the ASP’s prohibitive budget requirement. In this paper, we investigate the edge service placement problem of an ASP under a limited budget, where the ASP dynamically rents computing/storage resources in edge sites to host its applications in close proximity to end users. Since the benefit of placing edge service in a specific site is usually unknown to the ASP a priori, optimal placement decisions must be made while learning this benefit. We pose this problem as a novel combinatorial contextual bandit learning problem. It is “combinatorial” because only a limited number of edge sites can be rented to provide the edge service given the ASP’s budget. It is “contextual” because we utilize user context information to enable finer-grained learning and decision-making. To solve this problem and optimize the edge computing performance, we propose SEEN, a Spatial-temporal Edge sErvice placemeNt algorithm. Furthermore, SEEN is extended to scenarios with overlapping service coverage by incorporating a disjunctively constrained knapsack problem. In both cases, we prove that our algorithm achieves a sublinear regret bound when it is compared with an Oracle algorithm that knows the exact benefit information. Simulations are carried out on a real-world dataset, whose results show that SEEN significantly outperforms benchmark solutions.
Tobacco smoke exposure is an independent predictor of vitamin D deficiency in US children

Importance The role of tobacco-smoke exposure on serum vitamin D concentration in US pediatric population is not known. We hypothesized that tobacco smoke exposure would increase the prevalence of vitamin D deficiency in US children. Methods Representative national data were accessed from the National Health and Nutrition Examination Survey (NHANES) 2009–2010 databank on 2,263 subjects of ages 3 to 17 years. Subjects were categorized into two groups based on their age: children, if <10 years; and youth if 10 to 17 years. Descriptive and multiple logistic regression analyses were conducted to determine the effect of serum cotinine-verified tobacco smoke exposure on vitamin D status after controlling for key sociodemographic confounders. Vitamin D deficiency was defined as 25(OH)D <20 ng/mL, insufficiency as 25(OH)D of 20–29.9 ng/mL, and sufficiency as 25(OH)D of ≥30 ng/mL. Tobacco smoke exposure status was defined by serum cotinine concentration as follows: unexposed and non-smoking (<0.05 ng/mL) and exposed (passive and active smokers combined) (≥0.05ng/mL). Specifically, passive and active smoking were defined as cotinine of 0.05–10 ng/mL, and ≥10ng/mL respectively. Results The prevalence of second-hand smoke exposure was 42.0% (95%CI, 36.7%-47.5%); while the prevalence of active smoking among teenagers was 9.0% (95%CI, 6.2%-12.5%). Vitamin D deficiency occurred at a frequency of 15.1% in children unexposed to tobacco smoke, 20.9% in children exposed to passive tobacco smoke, and 18.0% among actively smoking youth (p<0.001). Tobacco smoke exposure independently predicted vitamin D deficiency after controlling for age, sex, race, BMI, maternal education, and family socio-economic status (OR:1.50; 95%CI, 1.14–1.85, p = 0.002). Conclusions This analysis of a nationwide database reports that tobacco smoke exposure is an independent predictor of vitamin D deficiency in US children.
Protocol for Fecal Microbiota Transplantation in Inflammatory Bowel Disease: A Systematic Review and Meta-Analysis

Background Fecal microbiota transplantation (FMT) is an emerging treatment approach for inflammatory bowel disease (IBD). The donor selection, the separation of fecal bacteria, the frequency of FMT, the way of infusion, the long-term safety, and efficacy are still uncertain. Aim To further study the efficacy and safety and protocol of FMT for IBD. Methods A systematic review and meta-analysis were conducted until February, 2018. Clinical remission was established as the primary outcome. Results A total of 596 paediatric and adult IBD patients were enrolled, and 459 patients received FMT therapy. 28.8% (132/459) patients achieved clinical remission during follow-up. 53% (241/459) patients achieved clinical response. The pooled estimated clinical remission for ulcerative colitis (UC) was 21% (95% CI: 8%-37%) and 30% (95% CI: 11%-52%) for Crohn's disease (CD), both with a risk of heterogeneity; 10% (95% CI: 0%-43%) for paediatric UC; 26% (95% CI: 10%-48%) for adult UC; 45% for paediatric CD (95% CI: 24%-66%); 22% (95% CI: 3%-52%) for adult CD. Meta-analysis of cohort studies showed that moderate-severe IBD patients could achieve more significant remission from FMT than mild-moderate patients (P=0.037). Delivery route has no impact on the efficacy of FMT in UC and CD. Based on current available evidence, a trend was observed towards higher clinical remission rate of frozen stool FMT than that of fresh stool for UC, while there was no significant difference between fresh and frozen FMT for CD. The optimal donor stool for FMT is still uncertain. Meta-analysis of RCTs showed that FMT treatment achieved significantly higher clinical remission rate than placebo for UC (28% versus 9%, P=0.0003). Conclusion FMT is an effective and safe therapy for both paediatric and adult IBD; fresh or frozen donor stool, delivery route, and antibiotic pretreatment or not have no impact on the efficacy of FMT in IBD. FMT might be a potential rescue therapy and even an initial standardized therapy for IBD. However, few data exist on long-term safety and efficacy and further validation is needed.
Multimodal prediction of the audience's impression in political debates

Debates are popular among politicians, journalists and scholars because they are a useful way to foster discussion and argumentation about relevant matters. In these discussions, people try to give a good impression (the immediate effect produced in the mind after a stimulus) by showcasing good skills in oratory and argumentation. We investigate this issue by using data gathered from an audience watching a national election debate and measuring the impression that politicians were giving during it. We then model a multimodal approach for automatically predicting their impression and analyze what modalities are the most important ones for this task. Our results show that the vision modality brings the best results and that fusing modalities at the feature-level is beneficial depending on the setup. The dataset is made publicly available to the community for further research on this topic.
Healthy Volunteers’ Perceptions of the Benefits of Their Participation in Phase I Clinical Trials

Other than the financial motivations for enrolling in Phase I trials, research on how healthy volunteers perceive the benefits of their trial participation is scant. Using qualitative interviews conducted with 178 U.S. healthy volunteers enrolled in Phase I trials, we investigated how participants described the benefits of their study involvement, including, but not limited to, the financial compensation, and we analyzed how these perceptions varied based on participants’ sociodemographic characteristics and clinical trial history. We found that participants detailed economic, societal, and noneconomic personal benefits. We also found differences in participants’ perceived benefits based on gender, age, ethnicity, educational attainment, employment status, and number of clinical trials completed. Our study indicates that many healthy volunteers believe they gain more than just the financial compensation when they accept the risks of Phase I participation.
Camera Model Identification Using Convolutional Neural Networks

Source camera identification is the process of determining which camera or model has been used to capture an image. In recent years, there has been a rapid growth of research interest in the domain of forensics. In the current work, we describe our Deep Learning approach to the camera detection task of 10 cameras as a part of the Camera Model Identification Challenge hosted by Kaggle.com where our team finished 2nd out of 582 teams with the accuracy on the unseen data of 98%. Augmentations that allowed a stay robust against transformations. A number of experiments are carried out on datasets collected by organizers and scraped from the web.
Defunctioning ileostomy and mechanical bowel preparation may contribute to development of low anterior resection syndrome

Introduction Laparoscopic surgery is an approved technique in colorectal cancer treatment. Functional and quality-of-life studies have revealed significant changes in faecal continence. Aim To assess the incidence and risk factors of low anterior resection syndrome (LARS) in patients undergoing rectal resections for cancer. Material and methods We enrolled patients undergoing rectal resections in a general surgery department of a university hospital. The primary outcomes were the Jorge-Wexner scale and the LARS score 6 months after the end of treatment. The secondary outcomes were the risk factors for LARS development. Results Fifty-six patients were included; 15 (26%) developed major LARS and 10 (18%) had minor LARS at 6 months. In univariate analysis the risk factors were: preoperative radiotherapy (p < 0.001, OR = 11.9, 95% CI: 2.98–47.48); shorter distance of the tumour from the anal verge (p = 0.001, OR = 0.69, 95% CI: 0.55–0.86); bowel preparation (p = 0.01, OR = 6.27, 95% CI: 1.51–26.07); low anterior rectal resection (p = 0.01, OR = 17.07, 95% CI: 1.86–156.83); and protective ileostomy (p = 0.001, OR = 15.97, 95% CI: 4.07–61.92). The risk factors for a higher Jorge-Wexner score in univariate analysis were greater diameter of tumour (p = 0.035), radiotherapy (p = 0.001), shorter distance from the anal verge (p = 0.002), bowel preparation (p = 0.042), low anterior rectal (LAR) (p = 0.01), ileostomy (p = 0.001), perioperative complications (p = 0.032), and readmission within 30 days (p = 0.034). In the multivariate analysis, readmissions and perioperative complications were significant. Conclusions In addition to typically described risk factors, two new ones have been identified. Mechanical bowel preparation and defunctioning ileostomy may also contribute to LARS development. However, due to the limitations of this study our observations require further confirmation in future trials.
Aging and Attention: Meaningfulness May Be More Important Than Valence

Studies on socioemotional selectivity theory have found that compared with younger adults, older adults are more likely to (a) prefer to interact with emotionally close social partners and (b) show preferential cognitive processing of positive relative to negative stimuli. To integrate these 2 lines of findings, this study examined attention toward emotional (positive and negative) facial expressions of experimentally manipulated emotionally close versus nonclose targets among younger and older adults. Compared with younger adults, older adults gazed more at facial expressions of emotionally close than nonclose targets, regardless of valence. This age difference occurred to a greater extent among those who endorsed eudaimonic goals more.
Quality assessment in general practice: diagnosis and antibiotic treatment of acute respiratory tract infections

Abstract Objective: To investigate areas in need of quality improvement within the diagnostic process and antibiotic treatment of acute respiratory tract infections (RTIs) in Danish general practice by using quality indicators (QIs). Design and setting: During a 4-week period in winter 2017, a prospective registration of patients diagnosed with RTIs was conducted in general practice in two regions of Denmark. Subjects: Throughout the registration period each patient with symptoms of an RTI was registered. Information about age, symptoms and findings, duration of symptoms, the use and result of clinical tests, allergy towards penicillin, referral to secondary care and the antibiotic given were recorded. Main outcome measures: Values and acceptable ranges for QIs focusing on the diagnostic process, the decision to prescribe antibiotics and the choice of antibiotics for patients with RTIs. Results: Regarding the diagnostic process nearly all QIs for patients diagnosed with acute pharyngotonsillitis and pneumonia fell within the acceptable range. Contrarily, the diagnostic QIs for patients with acute otitis media and acute rhinosinusitis were outside the acceptable range. All indicators designed to measure overuse of antibiotics were outside the acceptable range and nearly all indicators assessing if patients were sufficiently treated fell within the acceptable range. QIs assessing use of the recommended type of antibiotic were only within the acceptable range for patients diagnosed with acute pharyngotonsillitis. Conclusion: The findings indicate an overuse of antibiotics for RTIs in Danish general practice. Especially management of acute rhinosinusitis and acute bronchitis should be targeted in future quality improvement projects. KEY POINTS: To improve antibiotic prescribing in general practice it is important to focus on both the diagnostic process and the prescribing patterns. The findings indicate an overuse of antibiotics for acute respiratory tract infections in Danish general practice. Especially the diagnostic process and antibiotic prescribing patterns for acute rhinosinusitis and acute bronchitis could benefit from future quality improvement interventions.
Increased Functional Brain Network Efficiency During Audiovisual Temporal Asynchrony Integration Task in Aging

Audiovisual integration significantly changes over the lifespan, but age-related functional connectivity in audiovisual temporal asynchrony integration tasks remains underexplored. In the present study, electroencephalograms (EEGs) of 27 young adults (22–25 years) and 25 old adults (61–76 years) were recorded during an audiovisual temporal asynchrony integration task with seven conditions [auditory (A), visual (V), AV, A50V, A100V, V50A and V100A]. We calculated the phase lag index (PLI)-weighted connectivity networks modulated by the audiovisual tasks and found that the PLI connections showed obvious dynamic changes after stimulus onset. In the theta (4–7 Hz) and alpha (8–13 Hz) bands, the AV and V50A conditions induced stronger functional connections and higher global and local efficiencies, reflecting a stronger audiovisual integration effect, which was attributed to the auditory information arriving at the primary auditory cortex earlier than the visual information reaching the primary visual cortex. Importantly, the functional connectivity and network efficiencies of old adults revealed higher global and local efficiencies and higher degree in both the theta and alpha bands. These larger network efficiencies indicated that old adults might experience more difficulties in attention and cognitive control during the audiovisual integration task with temporal asynchrony than young adults. There were significant associations between network efficiencies and peak time of integration only in young adults. We propose that an audiovisual task with multiple conditions might arouse the appropriate attention in young adults but would lead to a ceiling effect in old adults. Our findings provide new insights into the network topography of old adults during audiovisual integration and highlight higher functional connectivity and network efficiencies due to greater cognitive demand.
MMCF: Multimodal Collaborative Filtering for Automatic Playlist Continuation

Automatic playlist continuation (APC) is a common task of music recommender systems, enabling the automatic discovery of tracks that fit into a given playlist. To recommend a coherent list of tracks to users, it is important to capture the underlying characteristics of a playlist. Unfortunately, existing recommender models suffer from several problems: (1) They tend to misinterpret tracks that appear rarely in a playlist (popularity bias) (2) they cannot extend user's playlist that consists of very few tracks (cold-start problem), and (3) they neglect the context of a playlist such as the sequence of tracks or playlist title (context-aware continuation). This year's ACM RecSys Challenge'18 aimed to find new solutions to tackle these problems. In this paper, we propose a multimodal collaborative filtering model to deal effectively with diverse data. This consists of two components: (1) an autoencoder using both the playlist and its categorical contents and (2) a character-level convolutional neural network using the playlist title only. By simultaneously analyzing the playlist and the categorical contents, our model successfully addresses the cold-start and popularity bias problems. In addition, we consider the context of a playlist by utilizing its title, thus enhancing the prediction of well-suited tracks. In the challenge, our team "hello world! " was ranked the 2nd place, scoring 0.224, 0.394, and 1.928 for the three evaluation metrics, respectively. Our implementation code is publicly available at https://github.com/hojinYang/spotify_recSys_challenge_2018.
Pathophysiology of Placenta Accreta Spectrum Disorders: A Review of Current Findings

Current findings continue to support the concept of a biologically defective decidua rather than a primarily abnormally invasive trophoblast. Prior cesarean sections increase the risk of placenta previa and both adherent and invasive placenta accreta, suggesting that the endometrial/decidual defect following the iatrogenic creation of a uterine myometrium scar has an adverse effect on early implantation. Preferential attachment of the blastocyst to scar tissue facilitates abnormally deep invasion of trophoblastic cells and interactions with the radial and arcuate arteries. Subsequent high velocity maternal arterial inflow into the placenta creates large lacunae, destroying the normal cotyledonary arrangement of the villi.
Candida albicans biofilm–induced vesicles confer drug resistance through matrix biogenesis

Cells from all kingdoms of life produce extracellular vesicles (EVs). Their cargo is protected from the environment by the surrounding lipid bilayer. EVs from many organisms have been shown to function in cell–cell communication, relaying signals that impact metazoan development, microbial quorum sensing, and pathogenic host–microbe interactions. Here, we have investigated the production and functional activities of EVs in a surface-associated microbial community or biofilm of the fungal pathogen Candida albicans. Crowded communities like biofilms are a context in which EVs are likely to function. Biofilms are noteworthy because they are encased in an extracellular polymeric matrix and because biofilm cells exhibit extreme tolerance to antimicrobial compounds. We found that biofilm EVs are distinct from those produced by free-living planktonic cells and display strong parallels in composition to biofilm matrix material. The functions of biofilm EVs were delineated with a panel of mutants defective in orthologs of endosomal sorting complexes required for transport (ESCRT) subunits, which are required for normal EV production in diverse eukaryotes. Most ESCRT-defective mutations caused reduced biofilm EV production, reduced matrix polysaccharide levels, and greatly increased sensitivity to the antifungal drug fluconazole. Matrix accumulation and drug hypersensitivity of ESCRT mutants were reversed by addition of wild-type (WT) biofilm EVs. Vesicle complementation showed that biofilm EV function derives from specific cargo proteins. Our studies indicate that C. albicans biofilm EVs have a pivotal role in matrix production and biofilm drug resistance. Biofilm matrix synthesis is a community enterprise; prior studies of mixed cell biofilms have demonstrated extracellular complementation. Therefore, EVs function not only in cell–cell communication but also in the sharing of microbial community resources.
Diffusivities and Atomic Mobilities in bcc Ti-Mo-Zr Alloys

β-type (with bcc structure) titanium alloys have been widely used as artificial implants in the medical field due to their favorable properties. Among them, Ti-Mo alloy attracted numerous interests as metallic biomaterials. Understanding of kinetic characteristics of Ti alloys is critical to understand and manipulate the phase transformation and microstructure evolution during homogenization and precipitation. In this work, diffusion couple technique was employed to investigate the diffusion behaviors in bcc Ti-Mo-Zr alloys. The diffusion couples were prepared and annealed at 1373 K for 72 h and 1473 K for 48 h, respectively. The composition-distance profiles were obtained via electron probe micro-analysis (EPMA). The chemical diffusion coefficients and impurity diffusion coefficients were extracted via the Whittle-Green method and Hall method. The obtained diffusion coefficients were assessed to develop a self-consistent atomic mobility database of bcc phase in Ti-Mo-Zr system. The calculated diffusion coefficients were compared with the experimental results. They showed good agreement. Simulations were implemented by Dictra Module in Thermo-Calc software. The predicted composition-distance profiles, inter-diffusion flux, and diffusion paths are consistent with experimental data, confirming the accuracy of the database.
Moving Object Detection in Complex Scene Using Spatiotemporal Structured-Sparse RPCA

Moving object detection is a fundamental step in various computer vision applications. Robust principal component analysis (RPCA)-based methods have often been employed for this task. However, the performance of these methods deteriorates in the presence of dynamic background scenes, camera jitter, camouflaged moving objects, and/or variations in illumination. It is because of an underlying assumption that the elements in the sparse component are mutually independent, and thus the spatiotemporal structure of the moving objects is lost. To address this issue, we propose a spatiotemporal structured sparse RPCA algorithm for moving objects detection, where we impose spatial and temporal regularization on the sparse component in the form of graph Laplacians. Each Laplacian corresponds to a multi-feature graph constructed over superpixels in the input matrix. We enforce the sparse component to act as eigenvectors of the spatial and temporal graph Laplacians while minimizing the RPCA objective function. These constraints incorporate a spatiotemporal subspace structure within the sparse component. Thus, we obtain a novel objective function for separating moving objects in the presence of complex backgrounds. The proposed objective function is solved using a linearized alternating direction method of multipliers based batch optimization. Moreover, we also propose an online optimization algorithm for real-time applications. We evaluated both the batch and online solutions using six publicly available data sets that included most of the aforementioned challenges. Our experiments demonstrated the superior performance of the proposed algorithms compared with the current state-of-the-art methods.