Miracle-dz/UniFAR-FTUs huggingface dataset:
The antiviral restriction factor IFN-induced transmembrane protein 3 prevents cytokine-driven CMV pathogenesis

The antiviral restriction factor IFN-induced transmembrane protein 3 (IFITM3) inhibits cell entry of a number of viruses, and genetic diversity within IFITM3 determines susceptibility to viral disease in humans. Here, we used the murine CMV (MCMV) model of infection to determine that IFITM3 limits herpesvirus-associated pathogenesis without directly preventing virus replication. Instead, IFITM3 promoted antiviral cellular immunity through the restriction of virus-induced lymphopenia, apoptosis-independent NK cell death, and loss of T cells. Viral disease in Ifitm3–/– mice was accompanied by elevated production of cytokines, most notably IL-6. IFITM3 inhibited IL-6 production by myeloid cells in response to replicating and nonreplicating virus as well as following stimulation with the TLR ligands Poly(I:C) and CpG. Although IL-6 promoted virus-specific T cell responses, uncontrolled IL-6 expression in Ifitm3–/– mice triggered the loss of NK cells and subsequently impaired control of MCMV replication. Thus, IFITM3 represents a checkpoint regulator of antiviral immunity that controls cytokine production to restrict viral pathogenesis. These data suggest the utility of cytokine-targeting strategies in the treatment of virus-infected individuals with impaired IFITM3 activity.
Distinct T-cell responses when BCG vaccination is delayed from birth to 6 weeks of age in Ugandan infants.

BACKGROUND In Uganda, the tuberculosis vaccine BCG is administered on the first day of life. Infants delivered at home receive BCG vaccine at their first healthcare facility visit at 6 weeks of age. Our aim was to determine the effect of this delay in BCG vaccination on the induced immune response. METHODS We assessed CD4(+) and CD8(+) T-cell responses with a 12-hour whole-blood intracellular cytokine/cytotoxic marker assay, and with a 6-day proliferation assay. RESULTS We enrolled 92 infants: 50 had received BCG vaccine at birth and 42 at 6 weeks of age. Birth vaccination was associated with (1) greater induction of CD4(+) and CD8(+) T cells expressing either interferon γ (IFN-γ) alone or IFN-γ together with perforin and (2) induction of proliferating cells that had greater capacity to produce IFN-γ, tumor necrosis factor α (TNF-α), and interleukin 2 together, compared with delayed vaccination. CONCLUSIONS Distinct patterns of T-cell induction occurred when BCG vaccine was given at birth and at 6 weeks of age. We propose that this diversity might impact protection against tuberculosis. Our results differ from those of studies of delayed BCG vaccination in South Africa and the Gambia, suggesting that geographical and population heterogeneity may affect the BCG vaccine-induced T-cell response.
Electroencephalography Amplitude Modulation Analysis for Automated Affective Tagging of Music Video Clips

The quantity of music content is rapidly increasing and automated affective tagging of music video clips can enable the development of intelligent retrieval, music recommendation, automatic playlist generators, and music browsing interfaces tuned to the users' current desires, preferences, or affective states. To achieve this goal, the field of affective computing has emerged, in particular the development of so-called affective brain-computer interfaces, which measure the user's affective state directly from measured brain waves using non-invasive tools, such as electroencephalography (EEG). Typically, conventional features extracted from the EEG signal have been used, such as frequency subband powers and/or inter-hemispheric power asymmetry indices. More recently, the coupling between EEG and peripheral physiological signals, such as the galvanic skin response (GSR), have also been proposed. Here, we show the importance of EEG amplitude modulations and propose several new features that measure the amplitude-amplitude cross-frequency coupling per EEG electrode, as well as linear and non-linear connections between multiple electrode pairs. When tested on a publicly available dataset of music video clips tagged with subjective affective ratings, support vector classifiers trained on the proposed features were shown to outperform those trained on conventional benchmark EEG features by as much as 6, 20, 8, and 7% for arousal, valence, dominance and liking, respectively. Moreover, fusion of the proposed features with EEG-GSR coupling features showed to be particularly useful for arousal (feature-level fusion) and liking (decision-level fusion) prediction. Together, these findings show the importance of the proposed features to characterize human affective states during music clip watching.
Increasing Physical Activity Amongst Overweight and Obese Cancer Survivors Using an Alexa-Based Intelligent Agent for Patient Coaching: Protocol for the Physical Activity by Technology Help (PATH) Trial

Background Physical activity has established health benefits, but motivation and adherence remain challenging. Objective We designed and launched a three-arm randomized trial to test artificial intelligence technology solutions to increase daily physical activity in cancer survivors. Methods A single-center, three-arm randomized clinical trial with an allocation ration of 1:1:1: (A) control, in which participants are provided written materials about the benefits of physical activity; (B) text intervention, where participants receive daily motivation from a fully automated, data-driven algorithmic text message via mobile phone (Coachtext); and (C) Voice Assist intervention, where participants are provided with an in-home on demand autonomous Intelligent Agent using data driven Interactive Digital Voice Assist on the Amazon Alexa/Echo (MyCoach). Results The study runs for 5 weeks: a one-week run-in to establish baseline, followed by 4 weeks of intervention. Data for study outcomes is collected automatically through a wearable sensor, and data are transferred in real-time to the study server. The recruitment goal is 42 participants, 14 in each arm. Electronic health records are used to prescreen candidates, with 39 participants recruited to date. Discussion This study aims to investigate the effects of different types of intelligent technology solutions on promoting physical activity in cancer survivors. This innovative approach can easily be expanded and customized to other interventions. Early lessons from our initial participants are helping us develop additional advanced solutions to improve health outcomes. Trial Registration Retrospectively registered on July 10, 2017 at ClinicalTrials.gov: NCT03212079; https://clinicaltrials.gov/ct2/show/NCT03212079 (Archived by WebCite at http://www.webcitation.org/6wgvqjTji)
Carbon fiber reinforced PEEK (APC-2/AS-4) composites for orthopaedic implants

The potential of carbon fiber reinforced polyetheretherketone (APC-2/AS-4) as an orthopaedic implant material was investigated. Preliminary results show that the material is resistant to repeated sterilization by gamma radiation and steam. Moreover, accelerated aging in boiling saline indicates that APC-2 is unlikely to undergo degradation or hydrolysis in the hostile physiological environment. These and the excellent mechanical properties lead to the conclusion that APC-2 merits further investigation as a low stiffness/high strength implant material
The so-called “ good hysterics ” revisited A

Author: Jonas Fuglestved Bakkevig Title of article: “The so-called good hysterics revisited. A study of histrionic personality disorder based on its low prevalence in a large Norwegian psychiatric sample. ” Supervisor I: Anne von der Lippe Supervisor II: Sigmund Karterud Background: To the knowledge of this author, no known studies with equally large sample sizes have shown as low prevalence (0.4%) for histrionic personality disorder (HPD) as that of this one. As a literature review indicates that HPD suffers from low construct validity, this article will shed light on the low prevalence by analyzing the construct validity of HPD. Methods: Data was obtained from twelve different Norwegian day treatment centres, comprising 2289 patients treated for personality disorders. Information on personality disorders was gathered by Structured Clinical Interview for DSM-IV Axis II Diagnoses (SCID-II), in addition to measures on dysfunction, distress and interpersonal problems. The author did not participate in data gathering. Results: Although only 10 (0.4%) patients obtained HPD diagnosis, certain findings aided analysis of construct validity; (1) HPD diagnosis and fulfilment of HPD criteria indicated distress and dysfunction, (2) the HPD criteria were interrelated, but only marginally more related to HPD than to borderline personality disorder and to narcissistic personality disorder diagnoses, and (3) the eight HPD criteria were, by of exploratory and confirmatory factor analysis, divided into two factors. Conclusions: The HPD diagnosis in its current form seems to suffer from low construct validity, with implications for prevalence rates. Different possibilities as to which latent structures underlie the eight HPD criteria are discussed, and a tentative suggestion as to the shared properties between these structures is offered.
Impact of Weight Status on the Onset and Parameters of Puberty: Analysis of Three Representative Cohorts from Central Europe

It is controversial whether obesity in children is associated with earlier onset of puberty and advanced appearance of distinct parameters of pubertal development. To investigate the impact of obesity on markers of the onset and parameters representing stages of puberty, we analyzed auxological parameters and secondary sex characteristics in three representative cohorts of Caucasian children. Body weight, height, peak height velocity and pubertal stages were evaluated in two recent German cohorts (CrescNet and Leipzig Schoolchildren), and a historical Swiss cohort. According to body mass index (BMI), children were classified into three weight groups of lean, overweight, or normal weight with limits defined below -1.28 and above +1.28 BMI SDS. Peak height velocity (PHV) occurred significantly later in lean compared to normal weight children in the CrescNet and Swiss cohort, while there was no difference between obese and normal weight children. There was a trend towards acceleration of parameters of puberty onset and progression in obese children in all three cohorts. Height SDS was significantly higher in obese children compared to normal weight peers, but after completion of pubertal development it was similar in adolescents. The impact of overweight on the acceleration of puberty seems to be slightly stronger in boys. Once girls have reached a critical weight for entering the process of maturation, further increase in body weight does not seem to advance the onset of puberty.
Genetics and Genomics of Acute Neurologic Disorders

&NA; Neurologic diseases and injuries are complex and multifactorial, making risk prediction, targeted treatment modalities, and outcome prognostication difficult and elusive. Genetics and genomics have affected clinical practice in many aspects in medicine, particularly cancer treatment. Advancements in knowledge of genetic and genomic variability in neurologic disease and injury are growing rapidly. Although these data are not yet ready for use in clinical practice, research continues to progress and elucidate information that eventually will provide answers to complex neurologic questions and serve as a platform to provide individualized care plans aimed at improving outcomes. This article provides a focused review of relevant literature on genetics, genomics, and common complex neurologic disease and injury likely to be seen in the acute care setting.
Compressing Graphs and Indexes with Recursive Graph Bisection

Graph reordering is a powerful technique to increase the locality of the representations of graphs, which can be helpful in several applications. We study how the technique can be used to improve compression of graphs and inverted indexes. We extend the recent theoretical model of Chierichetti et al. (KDD 2009) for graph compression, and show how it can be employed for compression-friendly reordering of social networks and web graphs and for assigning document identifiers in inverted indexes. We design and implement a novel theoretically sound reordering algorithm that is based on recursive graph bisection. Our experiments show a significant improvement of the compression rate of graph and indexes over existing heuristics. The new method is relatively simple and allows efficient parallel and distributed implementations, which is demonstrated on graphs with billions of vertices and hundreds of billions of edges.
A General Framework for Covariance Matrix Optimization in MIMO Systems

For multi-input multi-output (MIMO) systems, many transceiver design problems involve the optimization of the covariance matrices of the transmitted signals. Karush-Kuhn-Tucker (KKT) conditions based derivations are the most popular method, and many derivations and results have been reported for different scenarios of MIMO systems. We propose a unified framework in formulating the KKT conditions for general MIMO systems. Based on this framework, the optimal water-filling structure of the transmission covariance matrices are derived rigorously, which is applicable to a wide range of MIMO systems. Our results show that for MIMO systems with various power constraint formulations and objective functions, both the derivation logics and water-filling structures for the optimal covariance matrix solutions are fundamentally the same. Thus, our unified framework and solution reveal the underlying relationships among the different water-filling structures of the covariance matrices. Furthermore, our results provide new solutions to the covariance matrix optimization of many complicated MIMO systems with multiple users and imperfect channel state information (CSI) which were unknown before.
Query suggestions using query-flow graphs

The query-flow graph [Boldi et al., CIKM 2008] is an aggregated representation of the latent querying behavior contained in a query log. Intuitively, in the query-flow graph a directed edge from query <i>q</i><sub><i>i</i></sub> to query <i>q</i><sub><i>j</i></sub> means that the two queries are likely to be part of the same search mission. Any path over the query-flow graph may be seen as a possible search task, whose likelihood is given by the strength of the edges along the path. An edge (<i>q</i><sub><i>i</i></sub>, <i>q<sub>j</sub></i>) is also labelled with some information: e.g., the probability that user moves from <i>q</i><sub><i>i</i></sub> to <i>q</i><sub><i>j</i></sub>, or the type of the transition, for instance, the fact that <i>q</i><sub><i>j</i></sub> is a specialization of <i>q</i><sub><i>i</i></sub>. In this paper we propose, and experimentally study, query recommendations based on short random walks on the query-flow graph. Our experiments show that these methods can match in precision, and often improve, recommendations based on query-click graphs, without using users' clicks. Our experiments also show that it is important to consider transition-type labels on edges for having good quality recommendations. Finally, one feature that we had in mind while devising our methods was that of providing diverse sets of recommendations: the experimentation that we conducted provides encouraging results in this sense.
Mesenteric Lymph Duct Ligation Alleviating Lung Injury in Heatstroke

ABSTRACT To explore the roles of mesenteric lymph on lung injury in heatstroke (HS), HS rat model was prepared in a prewarmed incubator. Vascular endothelium injury biomarkers (circulating endothelial cell [CEC] as well as von Willebrand factor [vWF] and thrombomodulin [TM]), proinflammatory factors (tumor necrosis factor-&agr; [TNF-&agr;], interleukin-1&bgr; [IL-1&bgr;], IL-6, and high mobility group box 1), and coagulant markers (activated partial thromboplastin time, prothrombin time, D-Dimer, and platelet count) were tested in HS and HS with mesenteric lymph duct ligation (LDL) rats. In addition, lung histopathology; arterial blood gas; Evans Blue dye (EBD) and protein lung permeability; intralung inflammatory parameters including bronchoalveolar lavage fluid (BALF) TNF-&agr;, IL-1&bgr;, and IL-6 levels; myeloperoxidase (MPO) activity; and vWF immune staining were analyzed. LDL prolonged HS onset time but not HS survival time. LDL significantly attenuated endothelial cell injury for decreased CEC counts as well as plasma vWF and TM concentrations; downregulated systemic inflammation for decreased plasma TNF-&agr;, IL-1&bgr;, IL-6, and high mobility group box 1 levels; and ameliorated coagulant disorders for decreased activated partial thromboplastin time, prothrombin time, and D-Dimer levels as well as increased platelet counts. LDL also significantly reduced acute lung pathological injury; improved lung function indexes including arterial blood PaO2, pH, PaCO2, and lactic acid; decreased BALF TNF-&agr;, IL-1&bgr;, and IL-6 levels and lung MPO activity; improved EBD and protein lung permeability; and inhibited lung vascular endothelium vWF expression. However, all of these parameters were not recovered to the normal states. In summary, LDL developed protection roles systemically and alleviated lung injury in HS rats which indicated that modulating mesenteric lymph flow may have some potential benefits in HS.
Texture Classification in Extreme Scale Variations Using GANet

Research in texture recognition often concentrates on recognizing textures with intraclass variations, such as illumination, rotation, viewpoint, and small-scale changes. In contrast, in real-world applications, a change in scale can have a dramatic impact on texture appearance to the point of changing completely from one texture category to another. As a result, texture variations due to changes in scale are among the hardest to handle. In this paper, we conduct the first study of classifying textures with extreme variations in scale. To address this issue, we first propose and then reduce scale proposals on the basis of dominant texture patterns. Motivated by the challenges posed by this problem, we propose a new GANet network where we use a genetic algorithm to change the filters in the hidden layers during network training in order to promote the learning of more informative semantic texture patterns. Finally, we adopt a Fisher vector pooling of a convolutional neural network filter bank feature encoder for global texture representation. Because extreme scale variations are not necessarily present in most standard texture databases, to support the proposed extreme-scale aspects of texture understanding, we are developing a new dataset, the extreme scale variation textures (ESVaT), to test the performance of our framework. It is demonstrated that the proposed framework significantly outperforms the gold-standard texture features by more than 10% on ESVaT. We also test the performance of our proposed approach on the KTHTIPS2b and OS datasets and a further dataset synthetically derived from Forrest, showing the superior performance compared with the state-of-the-art.
Chapter 10 Structure And Efficiency Of Timber Markets

Perfect competition has long been the standard by which economists have judged the market’s ability to achieve an efficient social outcome. The competitive process, unfettered by the imperfections discussed below, forges an outcome in which goods and services are produced at their lowest possible cost, and market equilibrium is achieved at the point at which the cost of the last unit supplied just equals its value in use to the demander. This point maximizes the amount of utility that consumers obtain and the profit that producers procure through the existence of the market. Therein lies the appeal of perfect competitive markets. Evidence presented in this chapter suggests that timber markets possess certain structural characteristics that may impede perfectly competitive outcomes and thus warrant further scrutiny. Beyond the general concern about the social costs of any form of imperfect competition, why would a policy maker be particularly concerned about the lack of perfect competition in timber markets? The answer lies in the ability of the market to guide society toward an optimal allocation of resources (labor, capital, land) to forestry and forest-based production. If, for example, lack of competition among buyers were to drive down timber prices, the less profitable timber investments would be, and the less profitable forested land use would be. In principle, a lower price for timber causes less land to be in forest base than would otherwise be the case (Hardie et al. 2000). Not only does this diminish the ability of society’s forests to provide the efficient amount of timber and other marketed forest outputs, it also reduces the production of nonmarket goods and services provided by forests, such as wildlife habitat, watershed protection, aesthetics, and biodiversity. Thus private market imperfections can have public goods consequences.
Tornado: A Practical And Efficient Heterogeneous Programming Framework For Managed Languages

This paper describes our experiences creating Tornado: a practical and efficient heterogeneous programming framework for managed languages. The novel aspect of Tornado is that it turns the programming of heterogeneous systems from an activity predominantly based on a priori knowledge into one based on a posteriori knowledge. Alternatively put, it simply means developers do not need to overcomplicate their code by catering for all possible eventualities. Instead, Tornado provides the ability to specialize each application for a specific system in situ which avoids the need for it to be pre-configured by the developer. To enable this, Tornado employs a sophisticated runtime system that can dynamically configure all aspects of the application - from selecting which parallelization scheme to apply to specifying which accelerators to use. By using this ability, the end-user, and not the developer, can transparently make use of any available multi-/many-core processor or hardware accelerator. To showcase the impact of Tornado, we implement a real-world computer vision application and deploy it across nine accelerators without having to modify the source code or even explicitly re-compile the application. Using dynamic configuration, we show that our implementation can achieve up to 124 frames per second (FPS) - up to 166x speedup over the reference implementation. Finally, our implementation is always within 21% of a hand-written OpenCL version but avoids much of the programming tedium.