Miracle-dz/UniFAR-FTUs huggingface dataset:
Morphological aspects of the ovary of Columba livia (Gmelin) (Columbidae, Columbiformes)

The study of the female genital system of Columba livia (Gmelin, 1789) is part of the research on the reproductive biology of Brazilian birds. This work describes the morphological aspects of the ovary of Columba livia, as well as the histological differences observed in the ovarian follicles during the ovocyte maturation process. Ten Columba livia females were studied, whose ovaries had been dissected, fixed in Bouin and Helly solutions, and histologically processed for staining (Hematoxylin-Eosin; Gomori's trichromic and Weigert's technique and Gomori's technique for connective tissue fibers). The ovary has an irregular surface, is located in the abdominal cavity, and relates to the cranial portion of the left kidney and caudal extremity of the left lung. Histological examination shows that the ovary is covered with simple cubical epithelium, underlined by loose connective tissue that continues internally, surrounding the follicles. The ovarian follicles were described, in their different stages of development, with basis on the morphological changes occurring in the ovocyte and in the layers that surround it, in each phase of maturation. Among the follicles, groups lof cells of two distinct types, surrounded by connective tissue, are observable: clear cells with a spherical nucleus, and acidophilic cells with a slightly elongated nucleus. The studies of the ovary of Columba livia reveal histological similarities between this species and Columbina talpacoli (Temminck, 1811), whose ovaries were examined by Ribeiro et al. (1991).
A Personal Privacy Preserving Framework: I Let You Know Who Can See What

The booming of social networks has given rise to a large volume of user-generated contents (UGCs), most of which are free and publicly available. A lot of users' personal aspects can be extracted from these UGCs to facilitate personalized applications as validated by many previous studies. Despite their value, UGCs can place users at high privacy risks, which thus far remains largely untapped. Privacy is defined as the individual's ability to control what information is disclosed, to whom, when and under what circumstances. As people and information both play significant roles, privacy has been elaborated as a boundary regulation process, where individuals regulate interaction with others by altering the openness degree of themselves to others. In this paper, we aim to reduce users' privacy risks on social networks by answering the question of Who Can See What. Towards this goal, we present a novel scheme, comprising of descriptive, predictive and prescriptive components. In particular, we first collect a set of posts and extract a group of privacy-oriented features to describe the posts. We then propose a novel taxonomy-guided multi-task learning model to predict which personal aspects are uncovered by the posts. Lastly, we construct standard guidelines by the user study with 400 users to regularize users' actions for preventing their privacy leakage. Extensive experiments on a real-world dataset well verified our scheme.
Fast Scalable Supervised Hashing

Despite significant progress in supervised hashing, there are three common limitations of existing methods. First, most pioneer methods discretely learn hash codes bit by bit, making the learning procedure rather time-consuming. Second, to reduce the large complexity of the n by n pairwise similarity matrix, most methods apply sampling strategies during training, which inevitably results in information loss and suboptimal performance; some recent methods try to replace the large matrix with a smaller one, but the size is still large. Third, among the methods that leverage the pairwise similarity matrix, most of them only encode the semantic label information in learning the hash codes, failing to fully capture the characteristics of data. In this paper, we present a novel supervised hashing method, called Fast Scalable Supervised Hashing (FSSH), which circumvents the use of the large similarity matrix by introducing a pre-computed intermediate term whose size is independent with the size of training data. Moreover, FSSH can learn the hash codes with not only the semantic information but also the features of data. Extensive experiments on three widely used datasets demonstrate its superiority over several state-of-the-art methods in both accuracy and scalability. Our experiment codes are available at: https://lcbwlx.wixsite. com/fssh.
Implementing 360 video tiled streaming system

The computing power and bandwidth of the current VR are limited when compared to the high-quality VR. To overcome these limits, this study proposes a new viewport dependent streaming method that transmits 360-degree videos using the high efficiency video coding (HEVC) and the scalability extension of HEVC (SHVC). The proposed SHVC and HEVC encoders generate the bitstream that can transmit tiles independently. Therefore, the bitstream generated by the proposed encoder can be extracted in units of tiles. In accordance with what is discussed in the standard, the proposed extractor extracts the bitstream of the tiles corresponding to the viewport. SHVC video bitstream extracted by the proposed methods consist of (i) an SHVC base layer (BL) which represents the entire 360-degree area and (ii) an SHVC enhancement layer (EL) for selective streaming with viewport (region of interest (ROI)) tiles. When the proposed HEVC encoder is used, low and high resolution sequences are separately encoded as the BL and EL of SHVC. By streaming the BL(low resolution) and selective EL(high resolution) tiles with ROI instead of streaming whole high quality 360-degree video, the proposed method can reduce the network bandwidth as well as the computational complexity on the decoder side. Experimental results show more than 47% bandwidth reduction.
Premarket Approval Through the 510(k) Process: Lessons from the Translation Process of Magnetic Resonance Elastography

Innovations in medical imaging technologies have revolutionized medicine and generated examples of rapid translation to the clinic. Magnetic resonance elastography (MRE) is a noninvasive technique to quantify tissue stiffness. In this commentary, key events in the translation of MRE from laboratory into clinical practice are highlighted. We focus on key science and technology, application to chronic liver diseases, key clinical studies, the FDA approval process, and its influence on current and future medical practice. This article is protected by copyright. All rights reserved.
Effects of robot assistive upper extremity rehabilitation on motor and cognitive recovery, the quality of life, and activities of daily living in stroke patients.

OBJECTIVE To evaluate the effects of robotic rehabilitation on upper extremity functions, cognitive development, and activities of daily living in patients with subacute stroke. METHODS This study was set as prospective and controlled. Subjects with subacute stroke were allocated into two groups as the robotic and control groups. All subjects received a conventional rehabilitation program five times a week for 3 weeks. In addition, robotic group received robotic rehabilitation five times a week for 3 weeks (30 minutes per session). RESULTS There were 20 patients in the robotic group (mean age of 63.27 ± 3.88 years) and 15 patients in the control group (mean age of 59.25 ± 8.10 years). Compared with baseline, the Functional independence measure (both motor and cognitive subscale), Fugl-Meyer Assessment Scale, and Motricity Index values did increase in both groups. Change levels of Fugl-Meyer Assessment FMA shoulder/elbow/forearm, and Motricity Index shoulder scores were significantly higher in the robotic group than the control group (p< 0.05). Compared with the baseline, physical component summary scores improved only in the robotic group, yet motor component summary scores improved only in the control group. Although Brunnstrom levels increased in both groups compared with baseline, change levels were similar. CONCLUSION In the light of our results, robotic rehabilitation in addition to the conventional rehabilitation program seems to be effective on improving motor recovery and the quality of life in subacute stroke patients.
Can inspiratory muscle training improve weaning outcomes in difficult to wean patients? A protocol for a randomised controlled trial (IMweanT study)

Introduction Respiratory muscle dysfunction has been associated with failure to wean from mechanical ventilation. It has therefore been hypothesised that these patients might benefit from inspiratory muscle training (IMT). Evidence, however, is thus far limited to data from small, single-centre studies with heterogeneity in inclusion criteria, training modalities and outcomes. The aim of this study is to evaluate the effects of a novel IMT method on weaning outcomes in selected patients with weaning difficulties. Methods This study is designed as a double-blind, parallel-group, randomised controlled superiority trial with 1:1 allocation ratio. Patients with weaning difficulties will be randomly allocated into either an IMT group (intervention) or a sham-IMT group (control). Ninetypatients (45 in each group) will be needed to detect a 28% difference in the proportion of weaning success between groups (estimated difference in primary outcome based on previous studies) with a risk for type I error (α) of 5% and statistical power (1-β) of 80%. Patients will perform four sets of 6–10 breaths daily against an external load using a tapered flow resistive loading device (POWERbreathe KH2, HaB International, UK). Training intensity in the intervention group will be adjusted to the highest tolerable load. The control group will train against a low resistance that will not be modified during the training period. Training will becontinued until patients are successfully weaned or for a maximum duration of 28 days. Pulmonary and respiratory muscle function, weaning duration, duration of mechanical ventilation, ventilator-free days and length of stay in the intensive care unit will be evaluated as secondary outcomes. Χ2 tests and analysis of covariance with adjustments for baseline values of respective outcomesas covariates will be used to compare results after the intervention period between groups. Ethics and dissemination Ethics approval was obtained from the local ethical committee (Ethische Commissie Onderzoek UZ/KU Leuven protocol ID: S60516). Results from this randomised controlled trial will be presented at scientific meetings as abstracts for poster or oral presentations and published in peerreviewed journals. Trial status Enrolment into the study have started in August 2017. Data collection and data analysis are expected to be completed in September 2021. Trial registration number NCT03240263.
Effects of hot air treatment in combination with Pichia guilliermondii on postharvest preservation of peach fruit.

BACKGROUND Antagonistic yeast and hot air treatment are two promising methods for conferring resistance to pathogenic fungi. The study assessed the effectiveness of hot-air treatment (45 °C, 4 h) and antagonistic yeast (Pichia guilliermondii at 108 CFU mL-1 ) alone or in combination on the two major postharvest diseases (Rhizopus stolonifer and Penicillium expansum), as well as the quality and antioxidant parameters in harvested peaches. RESULTS The combination of hot-air treatment and Pichia guilliermondii had notable inhibitory effects on infections in peach fruit wounds. In addition, the individual hot-air treatment or Pichia guilliermondii could improve quality indexes to varying degrees, but the combination of the above two treatments could achieve the highest efficacy. Furthermore, compared with other groups, the combined treatment induced the highest activities of superoxide dismutase and catalase, improved the content of total phenolics and reduced glutathione most obviously. Lastly, the most significant reductions in malondialdehyde content and relative electrical conductivity were observed in the combination-treated fruit. CONCLUSIONS The combined treatment could control fungal diseases, besides delay the decline of quality and antioxidant parameters, so as to achieve the purpose of fresh keeping for harvested peach fruit. © 2018 Society of Chemical Industry.
Heat Shock Causes a Reversible Increase in RNA Polymerase II Occupancy Downstream of mRNA Genes, Consistent with a Global Loss in Transcriptional Termination

Cellular transcriptional programs are tightly controlled but can profoundly change in response to environmental challenges or stress. Here we describe global changes in mammalian RNA polymerase II (Pol II) occupancy at mRNA genes in response to heat shock and after recovery from the stress. ABSTRACT Cellular transcriptional programs are tightly controlled but can profoundly change in response to environmental challenges or stress. Here we describe global changes in mammalian RNA polymerase II (Pol II) occupancy at mRNA genes in response to heat shock and after recovery from the stress. After a short heat shock, Pol II occupancy across thousands of genes decreased, consistent with widespread transcriptional repression, whereas Pol II occupancy increased at a small number of genes in a manner consistent with activation. Most striking, however, was loss of the Pol II peak near the 3′ ends of mRNA genes, coupled to a gain in polymerase occupancy extending tens of kilobases downstream of 3′ ends. Typical patterns of 3′ end occupancy were largely restored 60 min after cells returned to normal growth temperatures. These changes in polymerase occupancy revealed a heat shock-induced loss of normal termination, which was potent, global, and reversible. The occupancy of the termination factor CPSF73 at the 3′ ends of representative genes was reduced after heat shock, suggesting a mechanism for impaired termination. The data support a model in which heat shock induces widespread repression of transcriptional initiation and loss of transcription termination, which reverses as cells return to homeostasis.
Information sharing for a coordination game in fluctuating environments

Collective action dilemmas pervade the social and biological sciences - from human decision-making to bacterial quorum sensing. In these scenarios, individuals sense cues from the environment to adopt a suitable phenotype or change in behavior. However, when cues include signals from other individuals, then the appropriate behavior of each individual is linked. Here, we develop a framework to quantify the influence of information sharing on individual behavior in the context of two player coordination games. In this framework, the environment stochastically switches between two states, and the state determines which one of two actions players must coordinate on. Given a stochastically switching environment, we then consider two versions of the game that differ in the way players acquire information. In the first model, players independently sense private environmental cues, but do not communicate with each other. We find there are two types of strategies that emerge as Nash equilibria and fitness maximizers - players prefer to commit to one particular action when private information is poor, or prefer to employ phenotypic plasticity when it is good. The second model adds an additional layer of communication, where players share social cues as well. When the quality of social information is high, we find the socially optimal strategy is a novel “majority logic” strategy that bases decision-making on social cues. Our game-theoretic approach offers a principled way of investigating the role of communication in group decision-making under uncertain conditions.
Testing the Cluster Hypothesis with Focused and Graded Relevance Judgments

The cluster hypothesis is a fundamental concept in ad hoc retrieval. Heretofore, cluster hypothesis tests were applied to documents using binary relevance judgments. We present novel tests that utilize graded and focused relevance judgments; the latter are markups of relevant text in relevant documents. Empirical exploration reveals that the cluster hypothesis holds not only for documents, but also for passages, as measured by the proposed tests. Furthermore, the hypothesis holds to a higher extent for highly relevant documents and for those that contain a high fraction of relevant text.
Convolutional neural network-based image enhancement for x-ray percutaneous coronary intervention

Abstract. Percutaneous coronary intervention (PCI) uses x-ray images, which may give high radiation dose and high concentrations of contrast media, leading to the risk of radiation-induced injury and nephropathy. These drawbacks can be reduced by using lower doses of x-rays and contrast media, with the disadvantage of noisier PCI images with less contrast. Vessel-edge-preserving convolutional neural networks (CNN) were designed to denoise simulated low x-ray dose PCI images, created by adding artificial noise to high-dose images. Objective functions of the designed CNNs have been optimized to achieve an edge-preserving effect of vessel walls, and the results of the proposed objective functions were evaluated qualitatively and quantitatively. Finally, the proposed CNN-based method was compared with two state-of-the-art denoising methods: K-SVD and block-matching and 3D filtering. The results showed promising performance of the proposed CNN-based method for PCI image enhancement with interesting capabilities of CNNs for real-time denoising and contrast enhancement tasks.
Dissecting FcγR Regulation Through a Multivalent Binding Model

Many immune receptors transduce activation across the plasma membrane through their clustering. With Fcγ receptors, this clustering is driven by binding to antibodies of differing affinities that are in turn bound to multivalent antigen. As a consequence of this activation mechanism, accounting for and rationally manipulating IgG effector function is complicated by, among other factors, differing affinities between FcγR species and changes in the valency of antigen binding. In this study, we show that a model of multivalent receptor-ligand binding can effectively account for the contribution of IgG-FcγR affinity and immune complex valency. This model in turn enables us to make specific predictions about the effect of immune complexes of defined composition. In total, these results enable both rational immune complex design for a desired IgG effector function and the deconvolution of effector function by immune complexes. Summary points Avidity most prominently modulates low-affinity FcγR-immune complex binding A multivalent binding model can quantitatively predict FcγR-immune complex binding Immune complex avidity has an outsized contribution to FcγR multimerizationas compared to binding A binding model deconvoles and predicts the influence of interventions modulating in vivo FcγR-driven effector function
Nonmonotonic recruitment of ventromedial prefrontal cortex during remote memory recall

Systems-level consolidation refers to the time-dependent reorganisation of memory traces in the neocortex, a process in which the ventromedial prefrontal cortex (vmPFC) has been implicated. Capturing the precise temporal evolution of this crucial process in humans has long proved elusive. Here, we used multivariate methods and a longitudinal functional magnetic resonance imaging (fMRI) design to detect, with high granularity, the extent to which autobiographical memories of different ages were represented in vmPFC and how this changed over time. We observed an unexpected time course of vmPFC recruitment during retrieval, rising and falling around an initial peak of 8–12 months, before reengaging for older 2- and 5-year-old memories. This pattern was replicated in 2 independent sets of memories. Moreover, it was further replicated in a follow-up study 8 months later with the same participants and memories, for which the individual memory representations had undergone their hypothesised strengthening or weakening over time. We conclude that the temporal engagement of vmPFC in memory retrieval seems to be nonmonotonic, revealing a complex relationship between systems-level consolidation and prefrontal cortex recruitment that is unaccounted for by current theories.
Letter by Voicu et al Regarding Article, "Derivation and Validation of the CREST Model for Very Early Prediction of Circulatory Etiology Death in Patients Without ST-Segment-Elevation Myocardial Infarction After Cardiac Arrest".

We read with great interest the study by Bascom et al1 regarding the predictors of circulatory failure (CF)-related death after resuscitated cardiac arrest (CA). Identifying patients with CA at high risk of CF-related death is important because circulatory assistance devices, such as venoarterial extracorporeal membrane oxygenation, could improve systemic and cerebral circulation until cardiac contractility and vascular resistance recover, potentially preventing CF-related death in some patients. In 2016, our team published a similar study,2 including out-of-hospital patients with CA without and also with ST-elevation myocardial infarction because these patients may also be at risk of CF-related death and may be potential candidates for …
Default‐mode network dynamics are restricted during high speed discrimination in healthy aging: Associations with neurocognitive status and simulated driving behavior

Numerous daily tasks, including car driving, require fine visuospatial tuning. One such visuospatial ability, speed discrimination, declines with aging but its neural underpinnings remain unknown. In this study, we use fMRI to explore the effect of aging during a high speed discrimination task and its neural underpinnings, along with a complete neuropsychological assessment and a simulated driving evaluation in order to examine how they interact with each other through a multivariate regression approach. Beyond confirming that high speed discrimination performance is diminished in the elderly, we found that this deficit might be partly due to a lack of modulation in the activity and connectivity of the default mode network (DMN) in this age group, as well as an over‐recruitment of frontoparietal and cerebellar regions, possibly as a compensatory mechanism. In addition, younger adults tended to drive at faster speeds, a behavior that was associated to adequate DMN dynamics and executive functioning, an effect that seems to be lost in the elderly. In summary, these results reveal how age‐related declines in fine visuospatial abilities, such as high speed discrimination, were distinctly mediated by DMN functioning, a mechanism also associated to speeding behavior in a driving simulator.