Miracle-dz/UniFAR-FTUs huggingface dataset:
An Efficient Algorithm of Context-Clustered Microservice Discovery

Using context1 is helpful to find services that satisfy users' requirements more accurately. In this paper context is classified into service context and user context and an algorithm of context-clustered microservice discovery (ACCMD) is proposed. Firstly, microservices are clustered according to the similarity of service context and a candidate service set is initialized by matching the request with service clusters. Then, according to the similarity of user context, users whoever used and are using the candidate services are clustered and the candidate service set is refined by matching the requester's information with the context of users in these clusters. Finally, Quality of Service (QoS) and requester's preference are used to filter candidate services and the results are inverted indexed and returned to the requester. Comparative experiments show that the ACCMD can increase user suitability of discovery and help filter out microservices quickly.
Long‐term outcome of renal function in children after stem cell transplantation measured by estimated glomerular filtration rate

Stem cell transplantation (SCT) outcomes have improved over the last three decades, with many patients being rescued with this treatment. However, improved outcomes have led to issues with long‐term sequelae. One of these sequelae in children is renal dysfunction, an index of which is estimated using glomerular filtration rate (eGFR).
Game in Two kinds of Situations Based on the Loss Averse Retailer

Based on two kinds of situation which there are non-cooperative advertising and cooperative advertising, we discuss the game between the upstream manufacturer and the downstream retailer when the retailer is loss averse. We obtain the implicit formula for partially optimal decision, in view of the impact of the retailer's loss aversion degree on decision makers, this paper have made a part of the sensitivity analysis, at the same time, we also analyze the variation of all the decision variables with the loss aversion coefficient by numerical examples.
Comparative study in the control of bovine viral diarrhea

Abstract Bovine viral diarrhea virus (BVDV) is an important infectious agent affecting herd productivity and reproduction, and leading to massive economic losses. As such, BVD is the subject of a number of control and eradication schemes globally. The key elements of such schemes are: diagnosis and removal of persistently infected animals from herds; implementation of biosecurity practices aimed at preventing the introduction or re-introduction of BVDV in free herds; and ongoing surveillance to monitor the progress of the program and to detect new infections. The objective of this review is to examine the impact of BVD and the management of the disease in three countries: Scotland, Spain, and Argentina, where BVD control programs are in distinct phases: established, developing, and yet to be initiated. This work also sets out to highlight potential difficulties and formulate recommendations for successful BVD control. It concludes that a systematic, countrywide approach is needed to achieve a sustainable decrease in BVD prevalence. The role of vaccines in control programs is concluded to be a valuable additional biosecurity measure. This study also concludes that there are potential wider benefits to a systematic BVD control program, such as a reduction in antimicrobial use and increases in the competitiveness of the cattle industry.
Visualization of myelinated fiber bundles orientation during brain slice preparation by reflection polarized light microscopy

Polarized light imaging (PLI) enables detecting the orientation of myelinated axon bundles in brain slices at microscopic resolution without histological staining. However, standard PLI requires labor‐intensive procedures such as mounting brain cryosections on slide glasses. We developed an optical system that does not require a mounting procedure for PLI. Specifically, we developed an optical system to perform PLI in reflection mode (rPLI) instead of employing transmitted light as in standard PLI. We integrated this rPLI system with a conventional vibratome slicer whose cutting blade surface is a mirror. This combination allowed PLI measurements directly during the slicing procedure at room temperature. Thus, mounting procedure for PLI is not necessary. As a proof‐of‐concept experiment, a perfusion‐fixed brain of a mouse was embedded in gelatin‐containing agar and cut serially at 40~200 μm intervals. The slicing procedure was temporarily halted after each cut to capture the PLI images of the slice on the reflecting blade surface while the slice was still held up by the agar block. The orientation of the fiber bundle estimated with this method agreed with the results obtained from previous reports. Combination of a popular vibratome slicer and our rPLI system that uses versatile and inexpensive optical components would increase popularity of PLI and facilitates connectome studies at microscopic resolution.
A Distributed Approach for Bitrate Selection in HTTP Adaptive Streaming

Past research has shown that concurrent HTTP adaptive streaming (HAS) players behave selfishly and the resulting competition for shared resources leads to underutilization or oversubscription of the network, presentation quality instability and unfairness among the players, all of which adversely impact the viewer experience. While coordination among the players, as opposed to all being selfish, has its merits and may alleviate some of these issues. A fully distributed architecture is still desirable in many deployments and better reflects the design spirit of HAS. In this study, we focus on and propose a distributed bitrate adaptation scheme for HAS that borrows ideas from consensus and game theory frameworks. Experimental results show that the proposed distributed approach provides significant improvements in terms of viewer experience, presentation quality stability, fairness and network utilization, without using any explicit communication between the players.
Proof of Concept for an Intracochlear Acoustic Receiver for Use in Acute Large Animal Experiments

(1) Background: The measurement of intracochlear sound pressure (ICSP) is relevant to obtain better understanding of the biomechanics of hearing. The goal of this work was a proof of concept of a partially implantable intracochlear acoustic receiver (ICAR) fulfilling all requirements for acute ICSP measurements in a large animal. The ICAR was designed not only to be used in chronic animal experiments but also as a microphone for totally implantable cochlear implants (TICI). (2) Methods: The ICAR concept was based on a commercial MEMS condenser microphone customized with a protective diaphragm that provided a seal and optimized geometry for accessing the cochlea. The ICAR was validated under laboratory conditions and using in-vivo experiments in sheep. (3) Results: For the first time acute ICSP measurements were successfully performed in a live specimen that is representative of the anatomy and physiology of the human. Data obtained are in agreement with published data from cadavers. The surgeons reported high levels of ease of use and satisfaction with the system design. (4) Conclusions: Our results confirm that the developed ICAR can be used to measure ICSP in acute experiments. The next generation of the ICAR will be used in chronic sheep experiments and in TICI.
Joint Object Tracking and Segmentation with Independent Convolutional Neural Networks

Object tracking and segmentation are important research topics in computer vision. They provide the trajectory and boundary of an object based on their appearance and shape features. Most studies on tracking and segmentation focus on encoding methods for the feature of an object. However, the tracking trajectory and segmentation mask are acquired separately, although similar visual information is required for both methods. Therefore, in this paper, we propose a CNN-based joint object tracking and segmentation framework that provides a segmentation mask while improving the performance of object tacker. In our model, the tracking model determines the trajectory of the target object as a bounding box in each frame. Given the bounding box at each frame, the segmentation model predicts a dense mask of the target object in the bounding box. Then, the segmentation mask is used to refine the bounding box for the tracking model. We evaluate the performance of our algorithm on DAVIS benchmark dataset by AUC score and mean IoU. We showed that the performance of original tracker was improved by our proposed framework.
Heterogeneous Neural Attentive Factorization Machine for Rating Prediction

Heterogeneous Information Network(HIN) has been employed in recommender system to represent heterogeneous types of data, and meta path has been proposed to capture semantic relationship among objects. When applying HIN to the recommendation, there are two problems: how to extract features from meta paths and how to properly fuse these features to further improve recommendations. Some recent work has employed deep neural network to learn user and item representation, and attention mechanism has been explored to integrate information for recommendation. Inspired by these work, in this paper, we propose Heterogeneous Neural Attentive Factorization Machine(HNAFM) to solve above problems. Specifically, we first calculate the commuting matrices based on meta paths and use multilayer perceptrons to learn user and item features. A hierarchical attention mechanism is employed to find the meta path that best describes user's preference and item's property. Comprehensive experiments based on real-world datasets demonstrate that the proposed HNAFM significantly outperforms state-of-the-art rating prediction methods.
Ledipasvir and Sofosbuvir in the Treatment of Early Hepatitis C Virus Infection in HIV-Infected Men

Abstract Background Treatment of HIV-infected men during early hepatitis C virus (HCV) infection with interferon results in a higher cure rate with a shorter duration of treatment than during chronic HCV infection. We recently demonstrated that this phenomenon applied to interferon-free treatment as well, curing most participants with short-course sofosbuvir and ribavirin. Due to the significantly higher potency of the ledipasvir/sofosbuvir (LDV/SOF) combination, we hypothesized that we would be more successful in curing early HCV infections using a shorter course of LDV/SOF than that used for treating chronic HCV infections. Methods We performed a prospective, open-label, consecutive case series study of 8 weeks of LDV/SOF in HIV-infected men with early genotype 1 HCV infection. The primary end point was aviremia at least 12 weeks after completion of treatment. Results We treated 25 HIV-infected men with early sexually acquired HCV infection with 8 weeks of LDV/SOF, and all 25 (100%) were cured. Twelve (48%) reported sexualized drug use with methamphetamine. Conclusions Eight weeks of LDV/SOF cured all 25 HIV-infected men with early HCV infection, including those who were actively using drugs. Based on these results, we recommend treatment of newly HCV-infected men during early infection, regardless of drug use, to both take advantage of this 8-week treatment and to decrease further HCV transmission among this group of men.
The impact of Recovery Colleges on mental health staff, services and society

Abstract Aims Recovery Colleges are opening internationally. The evaluation focus has been on outcomes for Recovery College students who use mental health services. However, benefits may also arise for: staff who attend or co-deliver courses; the mental health and social care service hosting the Recovery College; and wider society. A theory-based change model characterising how Recovery Colleges impact at these higher levels is needed for formal evaluation of their impact, and to inform future Recovery College development. The aim of this study was to develop a stratified theory identifying candidate mechanisms of action and outcomes (impact) for Recovery Colleges at staff, services and societal levels. Methods Inductive thematic analysis of 44 publications identified in a systematised review was supplemented by collaborative analysis involving a lived experience advisory panel to develop a preliminary theoretical framework. This was refined through semi-structured interviews with 33 Recovery College stakeholders (service user students, peer/non-peer trainers, managers, community partners, clinicians) in three sites in England. Results Candidate mechanisms of action and outcomes were identified at staff, services and societal levels. At the staff level, experiencing new relationships may change attitudes and associated professional practice. Identified outcomes for staff included: experiencing and valuing co-production; changed perceptions of service users; and increased passion and job motivation. At the services level, Recovery Colleges often develop somewhat separately from their host system, reducing the reach of the college into the host organisation but allowing development of an alternative culture giving experiential learning opportunities to staff around co-production and the role of a peer workforce. At the societal level, partnering with community-based agencies gave other members of the public opportunities for learning alongside people with mental health problems and enabled community agencies to work with people they might not have otherwise. Recovery Colleges also gave opportunities to beneficially impact on community attitudes. Conclusions This study is the first to characterise the mechanisms of action and impact of Recovery Colleges on mental health staff, mental health and social care services, and wider society. The findings suggest that a certain distance is needed in the relationship between the Recovery College and its host organisation if a genuine cultural alternative is to be created. Different strategies are needed depending on what level of impact is intended, and this study can inform decision-making about mechanisms to prioritise. Future research into Recovery Colleges should include contextual evaluation of these higher level impacts, and investigate effectiveness and harms.
Bioactivity, Health Benefits, and Related Molecular Mechanisms of Curcumin: Current Progress, Challenges, and Perspectives

Curcumin is a principal curcuminoid of turmeric (Curcuma longa), which is commonly used as a spice in cooking and a yellow pigment in the food processing industry. Recent studies have demonstrated that curcumin has a variety of biological activities and pharmacological performances, providing protection and promotion of human health. In addition to presenting an overview of the gut metabolism of curcumin, this paper reviews the current research progress on its versatile bioactivity, such as antioxidant, anti-inflammatory, and immune-regulatory activities, and also intensively discusses its health benefits, including the protective or preventive effects on cancers and diabetes, as well as the liver, nervous system, and cardiovascular systems, highlighting the potential molecular mechanisms. Besides, the beneficial effects of curcumin on human are further stated based on clinical trials. Considering that there is still a debate on the beneficial effects of curcumin, we also discuss related challenges and prospects. Overall, curcumin is a promising ingredient of novel functional foods, with protective efficacy in preventing certain diseases. We hope this comprehensive and updated review will be helpful for promoting human-based studies to facilitate its use in human health and diseases in the future.
Sci-Blogger: A Step Towards Automated Science Journalism

Science journalism is the art of conveying a detailed scientific research paper in a form that non-scientists can understand and appreciate while ensuring that its underlying information is conveyed accurately. It plays a crucial role in making scientific content suitable for consumption by the public at large. In this work, we introduce the problem of automating some parts of the science journalism workflow by automatically generating the 'title' of a blog version of a scientific paper. We have built a corpus of $87,328$ pairs of research papers and their corresponding blogs from two science news aggregators and have used it to buildSci ence-Blogger - a pipeline-based architecture consisting of a two-stage mechanism to generate the blog titles. Evaluation using standard metrics indicate viability of the proposed system.
Substantial Differences in the Subgingival Microbiome Measured by 16S Metagenomics According to Periodontitis Status in Older Women

Aging invokes physiological changes, such as immunosenescence and inflammation, that could increase host susceptibility to oral microbiome shifts that enable periodontitis progression in later life. At present, there is a dearth of studies specifically evaluating the oral microbiome and periodontitis in older adults. We used high-throughput untargeted sequencing methods and functional metagenomic analyses to assess and compare the subgingival biofilm of postmenopausal women (mean age 71 years) according to periodontitis status. Subgingival plaque samples were obtained from 15 postmenopausal women with no periodontitis, and from 15 women with severe periodontitis, determined by probing measures. The 16S rRNA gene (V1–V3 region) was sequenced on the 454 FLX platform. The PICRUSt technique was used to provide information on what the potential functional characteristics of microbiota might be in healthy, compared with diseased, periodontium. The subgingival microbiome associated with periodontitis showed clear differences to that associated with health. Of the 464 species identified, 22.8% had elevated abundance in disease, while only 6.3% had elevated abundance in health. Among the 12 most prevalent organisms in periodontitis, one-half have previously been recognized as periodontal pathogens by other investigators. The subgingival microbiome in periodontitis contained genes that could code for specific activities, including microbial mobility, synthesis of endotoxin, and proteolytic degradation. The healthy microbiome included genes that could code for sustaining microbial life, including encoding for transporters, glycolysis, gluconeogenesis, the Krebs cycle, and protein kinases. In the present study on postmenopausal women, aged 60 and older, the subgingival microbiome differed in composition and potential function between those with and without periodontitis. Studies of functional gene expression, such as transcriptomics, are needed to definitively identify the molecules carrying out functions associated with pathogenic subgingival complexes. This, in turn, could lead to identification of targets for enhanced management of periodontitis and, possibly, other diseases, in later life.
Multimodal Continuous Emotion Recognition with Data Augmentation Using Recurrent Neural Networks

This paper presents our effects for Cross-cultural Emotion Sub-challenge in the Audio/Visual Emotion Challenge (AVEC) 2018, whose goal is to predict the level of three emotional dimensions time-continuously in a cross-cultural setup. We extract the emotional features from audio, visual and textual modalities. The state of art regressor for continuous emotion recognition, long short term memory recurrent neural network (LSTM-RNN) is utilized. We augment the training data by replacing the original training samples with shorter overlapping samples extracted from them, thus multiplying the number of training samples and also beneficial to train emotional temporal model with LSTM-RNN. In addition, two strategies are explored to decrease the interlocutor influence to improve the performance. We also compare the performance of feature level fusion and decision level fusion. The experimental results show the efficiency of the proposed method and competitive results are obtained.
Cross-Domain Adversarial Feature Learning for Sketch Re-identification

Under person re-identification (Re-ID), a query photo of the target person is often required for retrieval. However, one is not always guaranteed to have such a photo readily available under a practical forensic setting. In this paper, we define the problem of Sketch Re-ID, which instead of using a photo as input, it initiates the query process using a professional sketch of the target person. This is akin to the traditional problem of forensic facial sketch recognition, yet with the major difference that our sketches are whole-body other than just the face. This problem is challenging because sketches and photos are in two distinct domains. Specifically, a sketch is the abstract description of a person. Besides, person appearance in photos is variational due to camera viewpoint, human pose and occlusion. We address the Sketch Re-ID problem by proposing a cross-domain adversarial feature learning approach to jointly learn the identity features and domain-invariant features. We employ adversarial feature learning to filter low-level interfering features and remain high-level semantic information. We also contribute to the community the first Sketch Re-ID dataset with 200 persons, where each person has one sketch and two photos from different cameras associated. Extensive experiments have been performed on the proposed dataset and other common sketch datasets including CUFSF and QUML-shoe. Results show that the proposed method outperforms the state-of-the-arts.
Early oral switch to linezolid for low-risk patients with Staphylococcus aureus bloodstream infections: a propensity-matched cohort study.

Background Oral switch to linezolid is a promising alternative to standard parenteral therapy (SPT) in Staphylococcus aureus bacteremia (SAB). Methods We conducted a prospective cohort study of all adult cases of SAB between 2013 and 2017 in a Spanish University Hospital. We compared the efﬁcacy, safety, and length of hospital stay of patients receiving SPT and those where SPT was switched to oral linezolid from day 3 to 9 of treatment until completion. We excluded complicated SAB and osteoarticular infections. A k-nearest neighbor algorithm was used for propensity score matching with a 2:1 ratio. Results After propensity score matching we included 45 patients of the linezolid group and 90 patients of the SPT group. Leading SAB-sources were catheter-related (49.6%), unknown origin (20.0%), and skin and soft tissue (17.0%). Patients in the linezolid group had less chronic renal disease (4.4% vs 22.2%). We observed no difference in 90-day relapse between the linezolid group and the SPT group (2.2% vs 4.4% respectively; P=0.87). No statistically significant difference was observed in 30-day all-cause mortality between the linezolid group and the SPT group (2.2% vs 13.3%; P=0.08). The median length of hospital stay after onset was 8 days in the linezolid group and 19 days in the SPT group (P<0.01). No drug-related events leading to discontinuation were noted in the linezolid group. Conclusions Treatment of SAB in selected low-risk patients with an oral switch to linezolid from day 3 to 9 of treatment until completion yielded similar clinical outcomes as SPT, allowing earlier discharge from the hospital.