Miracle-dz/UniFAR-FTUs huggingface dataset:
Novel variant in the KAT6B gene associated with Say Barber Biesecker Young Simpson

Introduction Say-Barber-Biesecker-Young-Simpson (SBBYSS) (OMIM #603736) and genitopatellar (GPS) (OMIM #606170) syndromes are two distinct clinical entities caused by pathogenic/likely pathogenic (P/LP) variants in the KAT6B gene (Campeau et al., 2012; Clayton-Smith et al., 2011). Overlapping features include global developmental delay, intellectual disability, hypotonia, genital abnormalities, congenital heart defects, dental anomalies, hearing loss and thyroid anomalies (Young and Simpson, 1987; Zhang et al., 2020). SBBYSS is characterized by a set of facial dysmorphisms typically described as a mask-like facial appearance (blepharophimosis and palpebral ptosis), external auditory canal malformations and/or stenosis with or without hearing loss, dacryostenosis, optic atrophy or hypoplasia, respiratory distress, palate abnormalities and long thumbs and/or great toes among other features.
THE AUTECOLOGY OF THE MEADOW THISTLE (Cirsium dissectum L. Hill) ON DEVON RHoS PASTURES, WITH PARTICULAR REFERENCE TO THE EFFECT OF MAJOR ENVIRONMENTAL VARIABLES ON THE POPULATION DYNAMICS

The autecology of the meadow thistle (Cirsium dissectum L. Hill) on Devon Rhos pastures, with particular reference to the effect of major environmental variables on the population dynamics John Ross Semi-natural wet grassland communities are rapidly disappearing from the farmed landscape. Protection of remaining areas and restoration of degraded areas has become a priority with organisations concerned with the conservation ofbiodiversity in the U.K. The research described in this thesis provides an insight into the community dynamics of one particularly rare plant community, the Cirsio-Molinietum fen meadow (NVC M24). This was achieved by examining the autecology of Cirsium dissectum, one of the key indicator species of this community. The habitat environment where C. dissectum is present was characterised at eight Devon M24 locations and ten non-M24 locations. This revealed a particularly unique suite of environmental conditions. Soil water content was found to be relatively high with little seasonal fluctuation. Mineral nutrient status was characterised by particularly low phosphorus, below optimal nitrogen, ample calcium and potassium and a soil pH which was only mildly acid. The physiological characteristics of C. dissectum were determined by a series of controlled experiments. The species exhibited a high water requirement but was relatively tolerant of drought stress and prolonged dehydration. It was demonstrated that C. dissectum is well adapted to a low phosphorus environment, is tolerant of nitrogen levels considered below optimum for many plants and is relatively tolerant of shade. It can also ' recover from partial or total defoliation in a relatively short period of time without any loss in plant mass or carbohydrate reserves. From the physiological characteristics, it was concluded that C. dissectum conforms to the "stress-tolerant competitor" functional type. It was also concluded that the decline of the species is directly related to loss of habitat as a result of its degree of specialism and specific niche requirement. The implications for management of existing sites and restoration of degraded sites is discussed and an outline model of appropriate management actions is presented. ,. ·Copyright Statement This copy·ofthe thesis has been supplied on conditioO! that anyoneiwho consults it is · understoodito:recogiliseithat its;copyright rests. with :its author, and that·no! quotation from' the thesis and.no:ilifotmation:derivedfrom itmay be published.without,the;a\]thor's[pnor 'consent. List of contents List of tables List of figures List of plates Acknowledgements Author's declaration Chapter 1 Introduction and Research Rationale 1.1 Background 1.2 Ecological Rationale 1.3 M24 Habitat description 1.4 A Review of C. dissectum 1.5 Theoretical Plant: Environment Relationships 1.6 Overall Project Aims and Objectives Page
ACUPOINT TRANSCUTANEOUS ELECTRICAL NERVE STIMULATION IN HOSPITALIZED COPD PATIENTS WITH SEVERE DYSPNOEA: STUDY PROTOCOL FOR A RANDOMIZED CONTROLED TRIAL

Background Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) is a major cause of hospital admissions and dyspnoea is its main symptom. Some studies have concluded that a new modality of acupuncture called Acupuncture transcutaneous nerve stimulation (acuTENS) could reduce dyspnoea in COPD patients by increasing beta-endorphin levels, however those trials have mainly been conducted on patients with stable condition. This study aims to determinate if the administration of acuTENS can reduce dyspnoea in patients hospitalized for AECOPD. Methods A multicentric randomized control trial with patient- and assessor-blinded will be conducted. A sample of 60 patients will be randomised to receive 45 minutes of either real acuTENS or sham acuTENS treatment once a day during 5 consecutive days. The trial will be conducted at the “Hospital del Mar” of Barcelona (Spain) and the “Hospital Sant Joan de Déu de Manresa” in Manresa (Spain). The Borg scale at baseline, and day 1 to 5 will be the primary outcome. Secondary outcomes will be the duration of the hospitalization, quantity of drugs administrated, expiratory peck flow adverse effects and mortality and readmissions at 3 months. Discussion AcuTENS is non-pharmacological, non-invasive and cheap intervention. This trial will help to understand acuTENS potential role in the treatment of AECOPD.
Sur visual cortex Molecular mechanisms of experience-dependent plasticity in

(314 articles) neuroscience Articles on similar topics can be found in the following collections Email alerting service here right-hand corner of the article or click Receive free email alerts when new articles cite this article-sign up in the box at the top A remarkable amount of our current knowledge of mechanisms underlying experience-dependent plasticity during cortical development comes from study of the mammalian visual cortex. Recent advances in high-resolution cellular imaging, combined with genetic manipulations in mice, novel fluorescent recombinant probes, and large-scale screens of gene expression, have revealed multiple molecular mechanisms that underlie structural and functional plasticity in visual cortex. We situate these mechanisms in the context of a new conceptual framework of feed-forward and feedback regulation for understanding how neurons of the visual cortex reorganize their connections in response to changes in sensory inputs. Such conceptual advances have important implications for understanding not only normal development but also pathological conditions that afflict the central nervous system. 1. INTRODUCTION Plasticity—the ability of the brain to reorganize its connections structurally and functionally in response to changes in sensory experience—is fundamental for the development of neuronal circuitry in central brain structures and for enabling the brain to adapt to its environment. Experience-dependent plasticity embodies the developmental history of the organism and matches neuronal circuits to the nature of inputs to enable appropriate information processing. Importantly, this experience-driven synaptic organization serves as a scaffold for subsequent reorganization underlying learning and memory. Indeed, many of the mechanisms that are involved in developmental plasticity are the forebears of later mechanisms of learning and memory during adulthood in various brain regions. Furthermore, understanding the mechanisms involved in the development and plasticity of connections is important not only for understanding the formation of neural circuitry but also for specifying possible deviations from a common developmental plan, and hence the aetiology of developmental brain disorders. The visual cortex has long been a proving ground for the study of experience-dependent plasticity because visual experience can be easily manipulated and the consequences of manipulations can be readily measured at the anatomical, physiological and molecular levels. Although the maturation of visual system
Bayesian estimation of simultaneous equation model with lagged endogenous variables and first order serially correlated errors

Most simultaneous equation models involve the inclusion of lagged endogenous and/or exogenous variables and sometimes it may be misleading to assume that the errors are normally distributed when in reality they exhibit functional formsthat are not normal especially in practical situations. The classical methods of estimating parameters of simultaneous equation models are usually affected by the presence of autocorrelation among the error terms. Unfortunately, in practice the form of correlation between the pairs of the random deviates is unknown.In this paper classical and Bayesian methods for the estimation of simultaneous equation model withlagged endogenous variables and first order serially correlated errors are considered. The smallsample properties of the methods at different levels of correlation for ρ = 0.2, 0.5 and 0.8are compared.Better parameter estimates were produced by the Bayesian estimator with smaller standard errors compared to the classical method. The standard deviations of the Bayesian estimator are consistently better than those of the OLS estimator for the sample sizes considered. For example, the standard deviations of the Bayesian for b14 (the coefficient of the lagged endogenous variable,y 1t-1) when ρ = 0.2 at N = 10, 15, 20 and 25 were 0.07712781, 0.05433923, 0.03230012 and 0.03177252 respectively while those of OLS were 0.0784732, 0.4718914, 0.05701936 and 1.31422868. However, when ρ = 0.8, the standard deviations were 0.0548055, 0.03860254, 0.02572899 and 0.02126175 for Bayesian and 0.0562190, 0.03882345, 0.053676 and 0.0315632 for OLS. Interestingly, notice that even at high correlation level, the estimates produced by the Bayesian method are closer to the parameter values and the standard deviations decrease as the sample size increases. Hence, the Bayesian estimation method might be a better choice when lagged endogenous variables are included in a simultaneous equation model with auto-correlated disturbances since it appeared to give better results compared to the classical approach.Keywords: Bayesian estimation, Lagged endogenous variables, Simultaneous equations, Monte-Carlo Simulation, First-order autoregressive process.
District characteristics and the representational relationship

Districts are intermediary legislative institutions that structure the relationship between constituents and legislatures. Situated between citizens and their elected representatives, districts mediate citizen-legislator interaction, and may have widereaching effects on the representational relationship. By creating a political community, defining its interests by delineating its scale and boundaries, and structuring interaction between constituents and their elected representatives, districts shape the representational relationship. District characteristics alter the representational experience for constituents with very real consequences for trust in government, evaluations of legislative institutions and representatives, perceptions of responsiveness, and the degree and type of constituent-legislator communication. Three district characteristics are examined: the population size of legislative districts (constituency size), the shape of district boundaries (geographical compactness, and the extent to which district boundaries follow pre-existing political subdivision boundaries (boundary coterminousness). Using Census data and GIS, measures of these characteristics are created for every state legislative and congressional district (post-2000 redistricting) in the United States. These characteristics are combined with public opinion data to test for their influence on attitudes toward government, legislative institutions, and legislators, as well as with data on the closeness of the representational relationship. The findings suggest constituency size is an important determinant of evaluations of government, institutions, and legislators at both the state and congressional level. The geographical districting principles of compactness and coterminousness influence the
Comparative scanning electron microscopy of third‐instar Hypoderma spp. (Diptera: Oestridae)

Scanning electron microscope study of third‐instar larvae of four species of Hypoderma revealed differences among species in the pattern of spination, spine morphology and morphology of the spiracular plates. These observations identify characters that enable the differentiation of Hypoderma actaeon and H. diana, parasitizing red deer (Cervus elaphus) in Europe, and provide additional characters for differentiating H. bovis and H. lineatum parasitizing cattle.
Statistical methods for resolving poor uncertainty quantification in machine learning interatomic potentials

Machine learning interatomic potentials (MLIPs) are promising surrogates for quantum mechanics evaluations in ab-initio molecular dynamics simulations due to their ability to reproduce the energy and force landscape within chemical accuracy at four orders of magnitude less cost. While developing uncertainty quantification (UQ) tools for MLIPs is critical to build production MLIP datasets using active learning, only limited progress has been made and the most robust method, ensembling, still shows low correlation between high error and high uncertainty predictions. Here we develop a rigorous method rooted in statistics for determining an error cutoff that distinguishes regions of high and low UQ performance. The statistical cutoff illuminates that a main cause of the poor UQ performance is due to the machine learning model already describing the entire dataset and not having any datapoints with error greater than the statistical error distribution. Second, we extend the statistical analysis to create an interpretable connection between the error and uncertainty distributions to predict an uncertainty cutoff separating high and low errors. We showcase the statistical cutoff in active learning benchmarks on two datasets of varying chemical complexity for three common UQ methods: ensembling, sparse Gaussian processes, and latent distance metrics and compare them to the true error and random sampling, showing that the statistical cutoff is generalizable to a variety of different UQ methods and protocols and performs similarly to using the true error. Importantly, we conclude that utilizing this uncertainty cutoff enables using significantly lower cost uncertainty quantification tools such as sparse gaussian processes and latent distances compared to ensembling approaches for generating MLIP datasets at a fraction of the cost.
Flexible Handover with Real-Time Robust Dynamic Grasp Trajectory Generation

In recent years, there has been a significant effort dedicated to developing efficient, robust, and general human-to-robot handover systems. However, the area of flexible handover in the context of complex and continuous objects' motion remains relatively unexplored. In this work, we propose an approach for effective and robust flexible handover, which enables the robot to grasp moving objects with flexible motion trajectories with a high success rate. The key innovation of our approach is the generation of real-time robust grasp trajec-tories. We also design a future grasp prediction algorithm to enhance the system's adaptability to dynamic handover scenes. We conduct one-motion handover experiments and motion-continuous handover experiments on our novel benchmark that includes 31 diverse household objects. The system we have developed allows users to move and rotate objects in their hands within a relatively large range. The success rate of the robot grasping such moving objects is 78.15 % over the entire household object benchmark.
RecXplainer: Amortized Attribute-based Personalized Explanations for Recommender Systems

Recommender systems influence many of our interactions in the digital world -- impacting how we shop for clothes, sorting what we see when browsing YouTube or TikTok, and determining which restaurants and hotels we are shown when using hospitality platforms. Modern recommender systems are large, opaque models trained on a mixture of proprietary and open-source datasets. Naturally, issues of trust arise on both the developer and user side: is the system working correctly, and why did a user receive (or not receive) a particular recommendation? Providing an explanation alongside a recommendation alleviates some of these concerns. The status quo for auxiliary recommender system feedback is either user-specific explanations (e.g.,"users who bought item B also bought item A") or item-specific explanations (e.g.,"we are recommending item A because you watched/bought item B"). However, users bring personalized context into their search experience, valuing an item as a function of that item's attributes and their own personal preferences. In this work, we propose RecXplainer, a novel method for generating fine-grained explanations based on a user's preferences over the attributes of recommended items. We evaluate RecXplainer on five real-world and large-scale recommendation datasets using five different kinds of recommender systems to demonstrate the efficacy of RecXplainer in capturing users' preferences over item attributes and using them to explain recommendations. We also compare RecXplainer to five baselines and show RecXplainer's exceptional performance on ten metrics.
VARIABLE MESSAGE SIGNS : THE FRENCH APPROACH IN THE EUROPEAN CONTEXT

This paper describes a technical guide on variable message signs (VMS) which has been published. The guide presents the different types of traffic signs, the areas in which they are used and emphasizes the necessity of integrating VMS into an overall approach. The guide emphasizes the necessity of an in-depth analysis before deciding to implement VMS.
Computational Lower Bounds for Graphon Estimation via Low-degree Polynomials

Graphon estimation has been one of the most fundamental problems in network analysis and has received considerable attention in the past decade. From the statistical perspective, the minimax error rate of graphon estimation has been established by Gao et al (2015) for both stochastic block model (SBM) and nonparametric graphon estimation. The statistical optimal estimators are based on constrained least squares and have computational complexity exponential in the dimension. From the computational perspective, the best-known polynomial-time estimator is based on universal singular value thresholding (USVT), but it can only achieve a much slower estimation error rate than the minimax one. It is natural to wonder if such a gap is essential. The computational optimality of the USVT or the existence of a computational barrier in graphon estimation has been a long-standing open problem. In this work, we take the first step towards it and provide rigorous evidence for the computational barrier in graphon estimation via low-degree polynomials. Specifically, in both SBM and nonparametric graphon estimation, we show that for low-degree polynomial estimators, their estimation error rates cannot be significantly better than that of the USVT under a wide range of parameter regimes. Our results are proved based on the recent development of low-degree polynomials by Schramm and Wein (2022), while we overcome a few key challenges in applying it to the general graphon estimation problem. By leveraging our main results, we also provide a computational lower bound on the clustering error for community detection in SBM with a growing number of communities and this yields a new piece of evidence for the conjectured Kesten-Stigum threshold for efficient community recovery.
Polarized Speech on Online Platforms

While political polarization has increased as measured through surveys, currently we lack comprehensive, longitudinal, and ecologically valid measurement of the polarization of online political speech that spans social media platforms. Using language models, we analyze ~2.5 billion comments on Reddit and Twitter across ~1.7 million accounts from 2007-2023 and find that polarized speech has been rising on both platforms since their inception, with outgroup polarization levels higher on Twitter than Reddit. On Twitter, while U.S. politicians on the left have been consistently more polarized than everyday users, politicians on the right experienced the highest growth in polarization, overtaking journalists, media, and everyday users over the past four years. Today, politicians, the group listened to the most for their political rhetoric, are far more polarized than everyday users. Additionally, while polarized speech is typically lower for accounts with more followers, right-leaning political influencers are an exception to this trend, which may influence perceptions of polarization on the left versus the right. Polarization is more diffuse across users on Twitter than on Reddit, where it is localized to a few communities. Polarization also varies by topic, with right-leaning users twice as likely to use polarized rhetoric about immigration as left-leaning users while left-leaning users are somewhat more likely to be polarized around healthcare. Our large-scale analysis reveals previously unknown patterns of polarization across platforms, groups, and topics that will help us better contextualize polarized content and potentially intervene to reduce it.
Decomposing random regular graphs into stars

We study $k$-star decompositions, that is, partitions of the edge set into disjoint stars with $k$ edges, in the uniformly random $d$-regular graph model $\mathcal{G}_{n,d}$. We prove an existence result for such decompositions for all $d,k$ such that $d/2<k \leq d/2 + \max\{1,\frac{1}{6}\log d\}$. More generally, we give a sufficient existence condition that can be checked numerically for any given values of $d$ and $k$. Complementary negative results are obtained using the independence ratio of random regular graphs. Our results establish an existence threshold for $k$-star decompositions in $\mathcal{G}_{n,d}$ for all $d\leq 100$ and $k>d/2$, and strongly suggest the a.a. s. existence of such decompositions is equivalent to the a.a. s. existence of independent sets of size $(2k-d)n/(2k)$, subject to the necessary divisibility conditions on the number of vertices. For smaller values of $k$, the connection between $k$-star decompositions and $\beta$-orientations allows us to apply results of Thomassen (2012) and Lov\'asz, Thomassen, Wu and Zhang (2013). We prove that random $d$-regular graphs satisfy their assumptions with high probability, thus establishing a.a. s. existence of $k$-star decompositions (i) when $2k^2+k\leq d$, and (ii) when $k$ is odd and $k<d/2$.