Miracle-dz/UniFAR-FTUs huggingface dataset:
Interhospital Comparison of Surgical Site Infection Rates in Orthopedic Surgery

OBJECTIVE To investigate whether comparison by deep or adjusted deep surgical site infection (SSI) rates in orthopedic surgeries are a better basis for feedback to Finnish hospitals than overall SSI rates DESIGN Retrospective cohort study SETTING Hospitals conducting surveillance of hip arthroplasties (HPROs) and knee arthroplasties (KPROs) in the Finnish Hospital Infection Program METHODS We analyzed surveillance data for 73,227 HPROs and 56,860 KPROs performed in 18 hospitals during 1999–2014. For each hospital, the overall, deep, and adjusted deep SSI rates with 95% confidence intervals (CIs) were calculated, and the hospital ranks were simulated in the Bayesian framework. Adjustments were performed using relevant patient and hospital characteristics. The correlation between the median expected hospital ranks in overall versus deep SSI rates and deep vs adjusted deep SSI rates were assessed using Spearman’s correlation coefficient ρ. RESULTS For HPRO, the overall SSI rates ranged from 0.92 to 6.83, the deep SSI rates ranged from 0.34 to 1.86, and the adjusted deep hospital-specific SSI rates ranged from 0.37 to 1.85. For KPRO, the overall SSI rates ranged from 0.71 to 5.03, the deep SSI rates ranged from 0.42 to 1.60, and the adjusted deep hospital-specific SSI rates ranged from 0.56 to 1.55. For both procedures, the 95% CIs of the rates between hospitals largely overlapped; only single outliers were detected. Hospital rank did not correlate between overall and deep SSI rates (HPRO, ρ=0.03; KPRO, ρ=0.40), but a correlation was observed in hospital rank for deep and adjusted deep SSI rates (HPRO, ρ=0.85; KPRO, ρ=0.94). CONCLUSION Deep SSI rates may be a better tool for interhospital comparisons than overall SSI rates. Although the adjustment could lead to fairer hospital ranking, it is not always necessary for feedback. Infect Control Hosp Epidemiol 2017;38:423–429
Systematic model of peripheral inflammation after subarachnoid hemorrhage

Objective: To investigate inflammatory processes after aneurysmal subarachnoid hemorrhage (aSAH) with network models. Methods: This is a retrospective observational study of serum samples from 45 participants with aSAH analyzed at multiple predetermined time points: <24 hours, 24 to 48 hours, 3 to 5 days, and 6 to 8 days after aSAH. Concentrations of cytokines were measured with a 41-plex human immunoassay kit, and the Pearson correlation coefficients between all possible cytokine pairs were computed. Systematic network models were constructed on the basis of correlations between cytokine pairs for all participants and across injury severity. Trends of individual cytokines and correlations between them were examined simultaneously. Results: Network models revealed that systematic inflammatory activity peaks at 24 to 48 hours after the bleed. Individual cytokine levels changed significantly over time, exhibiting increasing, decreasing, and peaking trends. Platelet-derived growth factor (PDGF)-AA, PDGF-AB/BB, soluble CD40 ligand, and tumor necrosis factor-α (TNF-α) increased over time. Colony-stimulating factor (CSF) 3, interleukin (IL)-13, and FMS-like tyrosine kinase 3 ligand decreased over time. IL-6, IL-5, and IL-15 peaked and decreased. Some cytokines with insignificant trends show high correlations with other cytokines and vice versa. Many correlated cytokine clusters, including a platelet-derived factor cluster and an endothelial growth factor cluster, were observed at all times. Participants with higher clinical severity at admission had elevated levels of several proinflammatory and anti-inflammatory cytokines, including IL-6, CCL2, CCL11, CSF3, IL-8, IL-10, CX3CL1, and TNF-α, compared to those with lower clinical severity. Conclusions: Combining reductionist and systematic techniques may lead to a better understanding of the underlying complexities of the inflammatory reaction after aSAH.
Site‐specific treatment outcome in smokers following 12 months of supportive periodontal therapy

Abstract Aim To evaluate the effect of cigarette smoking on periodontal health at patient, tooth, and site levels following supportive therapy. Materials and Methods Eighty chronic periodontitis patients, 40 smokers and 40 non‐smokers, were recruited to a single‐arm clinical trial. Periodontal examinations were performed at baseline (T0), 3 months following active periodontal therapy (T1), and 12 months following supportive periodontal therapy (T2). Smoking status was validated measuring serum cotinine levels. Probing depth (PD) ≥ 5 mm with bleeding on probing (BoP) was defined as the primary outcome. Logistic regression analyses adjusted for clustered observations of patients, teeth, and sites and mixed effects models were employed to analyse the data. Results All clinical parameters improved from T0 to T2 (p < 0.001), whereas PD, bleeding index (BI), and plaque index (PI) increased from T1 to T2 in smokers and non‐smokers (p < 0.001). An overall negative effect of smoking was revealed at T2 (OR = 2.78, CI: 1.49, 5.18, p < 0.001), with the most pronounced effect at maxillary single‐rooted teeth (OR = 5.08, CI: 2.01, 12.78, p < 0.001). At the patient level, less variation in treatment outcome was detected within smokers (ICC = 0.137) compared with non‐smokers (ICC = 0.051). Conclusion Smoking has a negative effect on periodontal health following 12 months of supportive therapy, in particular at maxillary single‐rooted teeth.
Passive Fault-Tolerance Management in Component-Based Embedded Systems

It is imperative to accept that failures can and will occur even in meticulously designed distributed systems and to design proper measures to counter those failures. Passive replication minimizes resource consumption by only activating redundant replicas in case of failures, as typically, providing and applying state updates is less resource demanding than requesting execution. However, most existing solutions for passive fault tolerance are usually designed and configured at design time, explicitly and statically identifying the most critical components and their number of replicas, lacking the needed flexibility to handle the runtime dynamics of distributed component-based embedded systems. This paper proposes a cost-effective adaptive fault tolerance solution with a significant lower overhead compared to a strict active redundancy-based approach, achieving a high error coverage with a minimum amount of redundancy. The activation of passive replicas is coordinated through a feedback-based coordination model that reduces the complexity of the needed interactions among components until a new collective global service solution is determined, hence improving the overall maintainability and robustness of the system.
Experimental study of dilute spray combustion

Liquid fuels are the primary energy source in a wide range of applications including industrial and residential furnaces, internal combustion engines and propulsion systems. Pollutant emission reduction is currently one of the major constraints for the design of the next generation combustion chamber. Spray combustion involves many complex physical phenomena including atomization, dispersion, evaporation and combustion, which generally take place simultaneously or within very small regions in the combustion chambers. Although numerical simulation is a valuable tool to tackle these different interactions between liquid and gas phases, the method needs to be validated through reliable experimental studies. Therefore, accurate experimental data on flame structure and on liquid and gas properties along the evaporation and combustion steps are needed and are still challenging. A joint effort between numerical and experimental teams is necessary to meet tomorrow's energy challenges and opportunities. The complexity of the real aeronautical configurations implies to study the effect of local properties in flame dynamics on a canonical configuration, which presents the essential feature of very well defined boundary conditions. This work, carried out within the framework of the ANR TIMBER project, aims to improve the understanding of two-phase flow combustion, as well as to produce an efficient and original database for the validation of the models used in LES.
Long‐term efficacy and tolerability of azilsartan medoxomil/chlorthalidone vs olmesartan medoxomil/hydrochlorothiazide in chronic kidney disease

An open‐label, long‐term study evaluated safety and tolerability of azilsartan medoxomil/chlorthalidone (AZL‐M/CLD) vs olmesartan/hydrochlorothiazide (OLM/HCTZ) in hypertensive participants with stage 3 chronic kidney disease. Initial therapy was AZL‐M/CLD 20/12.5 mg (n = 77) or OLM/HCTZ 20/12.5 mg (n = 76), but could be up‐titrated (AZL‐M/CLD to 40/25 mg; OLM/HCTZ to 40/25 mg [US] or 20/25 mg [Europe]) with other agents added during weeks 4‐52. Primary endpoint was proportion of participants with ≥ 1 adverse event (AE) through week 52. Baseline demographics were similar. AEs did not differ between groups (88.3%, AZL‐M/CLD vs 76.3%, OLM/HCTZ; P = .058). AZL‐M/CLD showed greater systolic BP reductions after initial dosing (P = .037) but not during long‐term follow‐up (P = .588). A greater proportion of participants up‐titrated to the highest dose with OLM/HCTZ (48.7%) vs AZL‐M/CLD (29.9%) (P = .021) and were taking additional antihypertensive medications (26.3% vs 16.9%). Both AZL‐M/CLD and OLM/HCTZ showed similar efficacy and tolerability.
Image de-fencing with hyperspectral camera

The main idea of image de-fencing refers to removing fence-like obstacles in the image and recovering the image. In this paper, rather than using a common RGB camera, we propose a novel image de-fencing algorithm with the help of a hyperspectral camera. Our algorithm consists of two phases: (1) automatically finding the location of the fence in the image, (2) image inpainting to reveal a fence-free image. With a hyperspectral camera, hundreds of images of the same scene under different wavelengths can be obtained instantly. By exploiting the spectral information of different positions in the scene with these hyperspectral images, the location of the fence can be distinguished from other objects. Then the fence can be removed and the image can be recovered with a novel image inpainting algorithm based on an approximate near-neighbor search method. Experiments demonstrate that our algorithm achieves considerable performance for the image de-fencing problem.
Motivators and barriers to HIV testing among street-based female sex workers in St. Petersburg, Russia

ABSTRACT Female sex workers are particularly susceptible to HIV-infection in Russia. However, a dearth of information exists on their utilisation of HIV services. A mixed-methods, cross-sectional study was conducted to examine motivators and barriers to HIV testing among street-based sex workers in St. Petersburg, Russia. The health belief model was the theoretical framework for the study. Twenty-nine sex workers participated in in-depth interviews, and 139 sex workers completed interviewer-administered surveys between February and September 2009. Barriers to getting an HIV test were fear of learning the results, worrying that other people would think they were sick, and the distance needed to travel to obtain services. Motivators for getting tested were protecting others from infection, wanting to know one's status and getting treatment if diagnosed. Logistic regression analysis demonstrated that knowing people living with HIV [aOR = 6.75, 95% CI (1.11, 41.10)] and length of time since start of injection drug use [aOR = 0.30, 95% CI (0.09, 0.97)] were significantly associated with recently getting tested. These results are important to consider when developing public health interventions to help female sex workers in Russia learn their HIV status and get linked to care and treatment services if needed.
Carbon nanotube buckypaper reinforced polymer composites: a review

This review provides valuable information about the general characteristics, processing conditions and physical properties of carbon nanotube buckypaper (BP) and its polymer composites. Vacuum filtration is the most common technique used for manufacturing BP, since the carbon nanotubes are dispersed in aqueous solution with the aid of surfactant. Previous works have reported that mechanical properties of BP prepared by vacuum filtration technique are relatively weak. On the other hand, the incorporation of polymer materials in those nanostructures revealed a significant improvement in their mechanical behavior, since the impregnation between matrix and BP is optimized. Electrical conductivity of BP/polymer composites can reach values as high as 2000 S/m, which are several orders of magnitude greater than traditional CNT/polymer composites. Also, BP can improve remarkably the thermal stability of polymer matrices, opening new perspectives to use this material in fire retardant applications.
Accelerating Recurrent Neural Networks: A Memory-Efficient Approach

Recurrent neural networks (RNNs) have achieved the state-of-the-art performance on various sequence learning tasks due to their powerful sequence modeling capability. However, RNNs usually require a large number of parameters and high computational complexity. Hence, it is quite challenging to implement complex RNNs on embedded devices with stringent memory and latency requirement. In this paper, we first present a novel hybrid compression method for a widely used RNN variant, long–short term memory (LSTM), to tackle these implementation challenges. By properly using circulant matrices, forward nonlinear function approximation, and efficient quantization schemes with a retrain-based training strategy, the proposed compression method can reduce more than 95% of memory usage with negligible accuracy loss when verified under language modeling and speech recognition tasks. An efficient scalable parallel hardware architecture is then proposed for the compressed LSTM. With an innovative chessboard division method for matrix–vector multiplications, the parallelism of the proposed hardware architecture can be freely chosen under certain latency requirement. Specifically, for the circulant matrix–vector multiplications employed in the compressed LSTM, the circulant matrices are judiciously reorganized to fit in with the chessboard division and minimize the number of memory accesses required for the matrix multiplications. The proposed architecture is modeled using register transfer language (RTL) and synthesized under the TSMC 90-nm CMOS technology. With 518.5-kB on-chip memory, we are able to process a $512 \times 512$ compressed LSTM in 1.71 $\mu {{{\text{s}}}}$ , corresponding to 2.46 TOPS on the uncompressed one, at a cost of 30.77-mm2 chip area. The implementation results demonstrate that the proposed design can achieve significantly high flexibility and area efficiency, which satisfies many real-time applications on embedded devices. It is worth mentioning that the memory-efficient approach of accelerating LSTM developed in this paper is also applicable to other RNN variants.
Coping strategies among conflict-affected adults in low- and middle-income countries: A systematic literature review

ABSTRACT Mental health is recognised as a key issue for populations affected by conflict. The aim of this systematic literature review is to examine coping strategies among conflict-affected civilians in low- and middle-income countries. The objectives were to examine (1) the types of coping strategies used by conflict-affected civilians; (2) factors influencing coping strategies; (3) relationships between coping strategies and mental health outcomes. A database search was conducted on May 13, 2014. Qualitative and quantitative studies that report on coping strategies used by adult conflict-affected civilians in LMICs were included, yielding 50 articles. Coping strategies were organised into a typology of problem-solving, support seeking, escape-avoidance, distraction, and positive cognitive restructuring domains. Support-seeking, positive cognitive restructuring, and problem-solving domains were the most frequently reported coping domains across the articles. Significant factors influencing coping included gender and exposure to trauma. The relationship between coping and mental health outcomes was nuanced. The diverse findings reported across the studies reflect the variety of contexts from which the samples are drawn, the range of coping typologies, and differing methodological approaches to exploring coping and mental health. Context-specific studies are needed in order to capture the social and cultural influences on coping and mental health.
Regression based landmark estimation and multi-feature fusion for visual speech recognition

Visual speech recognition also known as lipreading can improve robustness of automatic acoustic speech recognition especially under noisy environments. However, it remains a challenging topic considering the variety of speaking characteristics and confusion between visual speech features. In this paper, we propose an automatic lipreading method by using a new lip tracking method and multiple visual information fusion to tackle the problem. First, a method of face landmark estimation based on regression is employed for lip detection, based on which a geometric-based shape invariant feature (SIF) is put forward. Moreover, it can also be applied to the removal of the non-speaking utterance. Then the motion interchange patterns and spatial-temporal descriptors are also adopted to describe the lip information, where the Bayes combination strategy is applied. The proposed method is explored on three benchmark data sets: Avletters2, OuluVS and PKUVS. Experimental results demonstrate promising results and show effectiveness of the proposed approach.
Coordinated Beamforming for Multi-Cell MIMO-NOMA

In this letter, two novel coordinated beamforming techniques are developed to enhance the performance of non-orthogonal multiple access combined with multiple-input multiple-output communication in the presence of inter-cell interference. The proposed schemes successfully deal with inter-cell interference, and increase the cell-edge users’ throughput, which in turn improves user fairness. In addition, they increase the number of served users, which makes them suitable for 5G networks where massive connectivity and higher spectral efficiency are required. Numerical results confirm the effectiveness of the proposed algorithms.
Self-reported physical activity and major adverse events in patients with atrial fibrillation: a report from the EURObservational Research Programme Pilot Survey on Atrial Fibrillation (EORP-AF) General Registry

Aims Physical activity is protective against cardiovascular (CV) events, both in general population and in high-risk CV cohorts. However, the relationship between physical activity with major adverse outcomes in atrial fibrillation (AF) is not well-established. Our aim was to analyse this relationship in a 'real-world' AF population. Second, we investigated the influence of physical activity on arrhythmia progression. Methods and Results We studied all patients enrolled in the EURObservational Research Programme on AF (EORP-AF) Pilot Survey. Physical activity was defined as 'none', 'occasional', 'regular', and 'intense', based on patient self-reporting. Data on physical activity were available for 2442 patients: 38.9% reported none, 34.7% occasional, 21.7% regular, and 4.7% intense physical activity. Prevalence of the principal CV risk factors progressively decreased from none to intense physical activity. Lower rates of CV death, all-cause death, and composite outcomes were found in AF patients who reported regular and intense physical activity (P < 0.0001). Increasing physical activity was inversely associated with CV death/any thromboembolic event (TE)/bleeding in the whole cohort, irrespective of gender, paroxysmal AF, elderly age, or high stroke risk. Any level of physical activity intensity was significantly associated with lower risk of CV death/any TE/bleeding at 1-year follow-up. Physical activity was not significantly associated with arrhythmia progression. Conclusion Atrial fibrillation patients taking regular exercise were associated with a lower risk of all-cause death, even when we considered various subgroups, including gender, elderly age, symptomatic status, and stroke risk class. Efforts to increase physical activity among AF patients may improve outcomes in these patients.
Reducing interpolant circuit size by ad-hoc logic synthesis and SAT-based weakening

We address the problem of reducing the size of Craig interpolants used in SAT-based Model Checking. Craig interpolants are AND-OR circuits, generated by post-processing refutation proofs of SAT solvers. Whereas it is well known that interpolants are highly redundant, their compaction is typically tackled by reducing the proof graph and/or by exploiting standard logic synthesis techniques. Furthermore, strengthening and weakening have been studied as an option to control interpolant quality. In this paper we propose two interpolant compaction techniques: (1) A set of ad-hoc logic synthesis functions that, revisiting known logic synthesis approaches, specifically address speed and scalability. Though general and not restricted to interpolants, these techniques target the main sources of redundancy in interpolant circuits. (2) An interpolant weakening technique, where the UNSAT core extracted from an additional SAT query is used to obtain a gate-level abstraction of the interpolant. The abstraction introduces fresh new variables at gate cuts that must be quantified out in order to obtain a valid interpolant. We show how to efficiently quantify them out, by working on an NNF representation of the circuit. The paper includes an experimental evaluation, showing the benefits of the proposed techniques, on a set of benchmark interpolants arising from both hardware and software model checking problems.