Miracle-dz/UniFAR-FTUs huggingface dataset:
Alternative Global – Local Shrinkage Priors Using Hypergeometric – Beta Mixtures

This paper introduces an approach to estimation in possibly sparse data sets using shrinkage priors based upon the class of hypergeometric-beta distributions. These widely applicable priors turn out to be a four-parameter generalization of the beta family, and are pseudo-conjugate: they cannot themselves be expressed in closed form, but they do yield tractable moments and marginal likelihoods when used as priors for the mean of a normal distribution. These priors are useful in situations where standard priors are inappropriate or ill-behaved. Non-Bayesians will find these priors useful for generating easily computable shrinkage estimators that have excellent risk properties. Bayesians will find them useful for generating computationally tractable priors for a variance parameter. We illustrate the use of these priors on a variety of global and local shrinkage problems, and we prove a theorem that characterizes their risk proprieties when used for estimation of a normal mean under a quadratic loss function.
Reducing radiation exposure from survey CT scans.

OBJECTIVE The purpose of this study was to focus attention on the technique factors commonly used in survey CT scans (e.g., scout, topogram, or pilot scans) to measure the radiation exposure from typical survey CT scans, to compare their exposure to that of typical chest radiographs, and to explore methods for radiation exposure reduction. MATERIALS AND METHODS The default survey CT scans on 21 CT scanners, representing three different vendors and 11 different models, were investigated. Exposure measurements were obtained with an ion chamber at isocenter and adjusted to be consistent with standard chest radiographic exposure measurement methods (single posterior-anterior projection). These entrance exposures were compared with those of typical chest radiographs, for which the mean for average-sized adults is 16 mR (4.1 x 10(-6) C/kg). RESULTS The entrance exposures of the default survey CT scans ranged from 3.2 to 74.7 mR (0.8 to 19.3 x 10(-6) C/kg), which is equivalent to approximately 0.2 to 4.7 chest radiographs. By changing the default scan parameters from 120 kVp to 80 kVp and the tube position from 0 degrees (tube above table) to 180 degrees (tube below table), the entrance exposure for the survey CT scan was reduced to less than that of one chest radiograph for all CT scanners. CONCLUSION For institutions at which the interpreting radiologists do not rely heavily on the appearance of the survey CT image, we recommend adjusting the technique parameters (kilovoltage and X-ray tube position) to decrease radiation exposure, especially for vulnerable patient populations such as children and young women.
Optimal caliper widths for propensity-score matching when estimating differences in means and differences in proportions in observational studies

In a study comparing the effects of two treatments, the propensity score is the probability of assignment to one treatment conditional on a subject's measured baseline covariates. Propensity‐score matching is increasingly being used to estimate the effects of exposures using observational data. In the most common implementation of propensity‐score matching, pairs of treated and untreated subjects are formed whose propensity scores differ by at most a pre‐specified amount (the caliper width). There has been a little research into the optimal caliper width. We conducted an extensive series of Monte Carlo simulations to determine the optimal caliper width for estimating differences in means (for continuous outcomes) and risk differences (for binary outcomes). When estimating differences in means or risk differences, we recommend that researchers match on the logit of the propensity score using calipers of width equal to 0.2 of the standard deviation of the logit of the propensity score. When at least some of the covariates were continuous, then either this value, or one close to it, minimized the mean square error of the resultant estimated treatment effect. It also eliminated at least 98% of the bias in the crude estimator, and it resulted in confidence intervals with approximately the correct coverage rates. Furthermore, the empirical type I error rate was approximately correct. When all of the covariates were binary, then the choice of caliper width had a much smaller impact on the performance of estimation of risk differences and differences in means. Copyright © 2010 John Wiley & Sons, Ltd.
Trust- and clustering-based authentication services in mobile ad hoc networks

A mobile ad hoc network is a kind of wireless communication network that does not rely on a fixed infrastructure and is lack of any centralized control. These characteristics make it vulnerable to security attack, so protecting the security of the network is essential. Like many distributed systems, security in ad hoc networks widely relies on the use of key management mechanisms. However, traditional key management systems are not appropriate for them. We aim at providing a secure and distributed authentication service in ad hoc networks. We propose a secure public key authentication service based on our trust model and network model to prevent nodes from obtaining false public keys of the others when there are malicious nodes in the network. We perform an overall evaluation of our proposed approach by simulations. The experimental results indicate clear advantages of our approach in providing effective security in mobile ad hoc networks.
Self-cancellation of multiple frequency offsets in OFDM systems

In this paper, we propose a method to compensate the effects of multiple carrier frequency offsets for orthogonal frequency division multiplexing (OFDM) systems when the received signals come from two spatially separated transmitters. The scheme estimates a proper compensation value with previously estimated carrier frequency offsets caused by the two transmitters. And then compensates the received time domain signal by using it, which results in self-cancellation of the interchannel interference should be introduced by frequency offsets1.
Space-efficient data structures for Top-k completion

Virtually every modern search application, either desktop, web, or mobile, features some kind of query auto-completion. In its basic form, the problem consists in retrieving from a string set a small number of completions, i.e. strings beginning with a given prefix, that have the highest scores according to some static ranking. In this paper, we focus on the case where the string set is so large that compression is needed to fit the data structure in memory. This is a compelling case for web search engines and social networks, where it is necessary to index hundreds of millions of distinct queries to guarantee a reasonable coverage; and for mobile devices, where the amount of memory is limited. We present three different trie-based data structures to address this problem, each one with different space/time/complexity trade-offs. Experiments on large-scale datasets show that it is possible to compress the string sets, including the scores, down to spaces competitive with the gzip'ed data, while supporting efficient retrieval of completions at about a microsecond per completion.
Tunnel Propagation of Postshock Activations as a Hypothesis for Fibrillation Induction and Isoelectric Window

Comprehensive understanding of the ventricular response to shocks is the approach most likely to succeed in reducing defibrillation threshold. We propose a new theory of shock-induced arrhythmogenesis that unifies all known aspects of the response of the heart to monophasic (MS) and biphasic (BS) shocks. The central hypothesis is that submerged “tunnel” propagation of postshock activations through shock-induced intramural excitable areas underlies fibrillation induction and the existence of isoelectric window. We conducted simulations of fibrillation induction using a realistic bidomain model of rabbit ventricles. Following pacing, MS and BS of various strengths/timings were delivered. The results demonstrated that, during the isoelectric window, an activation originated deep within the ventricular wall, arising from virtual electrodes; it then propagated fully intramurally through an excitable tunnel induced by the shock, until it emerged onto the epicardium, becoming the earliest-propagated postshock activation. Differences in shock outcomes for MS and BS were found to stem from the narrower BS intramural postshock excitable area, often resulting in conduction block, and the difference in the mechanisms of origin of the postshock activations, namely intramural virtual electrode–induced phase singularity for MS and virtual electrode–induced propagated graded response for BS. This study provides a novel analysis of the 3D mechanisms underlying the origin of postshock activations in the process of fibrillation induction by MS and BS and the existence of isoelectric window. The tunnel propagation hypothesis could open a new avenue for interventions exploration to achieve significantly lower defibrillation threshold.
Centrality-as-Relevance: Support Sets and Similarity as Geometric Proximity

In automatic summarization, centrality-as-relevance means that the most important content of an information source, or a collection of information sources, corresponds to the most central passages, considering a representation where such notion makes sense (graph, spatial, etc.). We assess the main paradigms, and introduce a new centrality-based relevance model for automatic summarization that relies on the use of support sets to better estimate the relevant content. Geometric proximity is used to compute semantic relatedness. Centrality (relevance) is determined by considering the whole input source (and not only local information), and by taking into account the existence of minor topics or lateral subjects in the information sources to be summarized. The method consists in creating, for each passage of the input source, a support set consisting only of the most semantically related passages. Then, the determination of the most relevant content is achieved by selecting the passages that occur in the largest number of support sets. This model produces extractive summaries that are generic, and language- and domainindependent. Thorough automatic evaluation shows that the method achieves state-of-the art performance, both in written text, and automatically transcribed speech summarization, including when compared to considerably more complex approaches.
On the Shared Control of an EMG-Controlled Prosthetic Hand: Analysis of User–Prosthesis Interaction

An anthropomorphic underactuated prosthetic hand, endowed with position and force sensors and controlled by means of myoelectric commands, is used to perform experiments of hierarchical shared control. Three different hierarchical control strategies combined with a vibrotactile feedback system have been developed and tested by able-bodied subjects through grasping tasks used in activities of daily living (ADLs). The first goal is to find a good tradeoff between good grasping capabilities and low attention required by the user to complete grasping tasks, without addressing advanced algorithm for electromyographic processing. The second goal is to understand whether a vibrotactile feedback system is subjectively or objectively useful and how it changes users' performance. Experiments showed that users were able to successfully operate the device in the three control strategies, and that the grasp success increased with more interactive control. Practice has proven that when too much effort is required, subjects do not do their best, preferring, instead, a less-interactive control strategy. Moreover, the experiments showed that when grasping tasks are performed under visual control, the enhanced proprioception offered by a vibrotactile system is practically not exploited. Nevertheless, in subjective opinion, feedback seems to be quite important.
Learning dynamic features with neural networks for phoneme recognition

Dynamic features such as delta and delta-delta of basic acoustic features have long been used in various speech applications and give satisfactory performance. The explicit physical meaning and simplicity of dynamic features clearly compound their prevalence. In this paper, we propose a new framework with neural network to learn the alternatives of traditional delta and higher order differences. Instead of embracing the interpretability and simplicity, our framework is able to learn a new transformation that simulates what differences do but is more relevant to a specific task such as phoneme recognition. We determine the best way to learn such a new transformation among several most probable alternatives. Our experiments indicate that dynamic features obtained with transformation learned this way are better than traditional differences in both frame classification and phoneme recognition. The improvement of performance is even clearer when higher-order of differences are applied.
Contour map matching for event detection in sensor networks

Many sensor network applications, such as object tracking and disaster monitoring, require effective techniques for event detection. In this paper, we propose a novel event detection mechanism based on matching the contour maps of in-network sensory data distribution. Our key observation is that events in sensor networks can be abstracted into spatio-temporal patterns of sensory data and that pattern matching can be done efficiently through contour map matching. Therefore, we propose simple SQL extensions to allow users to specify common types of events as patterns in contour maps and study energy-efficient techniques of contour map construction and maintenance for our pattern-based event detection. Our experiments with synthetic workloads derived from a real-world coal mine surveillance application validate the effectiveness and efficiency of our approach.
Histone Deacetylase 3 Binds to and Regulates the Multifunctional Transcription Factor TFII-I*

Histone deacetylase 3 (HDAC3) is one of four members of the human class I histone deacetylases that are implicated in transcriptional repression through deacetylation of acetyllysines in amino-terminal tails of core histones. In an immunoaffinity purification using anti-HDAC3, transcription factor TFII-I copurified with HDAC3. Specificity of the HDAC3-TFII-I interaction was confirmed by coimmunoprecipitation of epitope-tagged proteins, GST pull-down assays, and protein colocalization with indirect immunofluorescence. An anti-TFII-I immunoprecipitate contained histone deacetylase enzymatic activity. Mutational analyses revealed that the carboxyl-terminal of HDAC3 (residues 373–401) and residues 363–606 of TFII-I were required for the HDAC3-TFII-I interaction. Transcriptional activation by TFII-I was severely reduced by overexpression of HDAC3. These results suggest that HDAC3 modulates some of the functions of TFII-I and provides a link between histone deacetylase and a multifunctional transcriptional activator.
Comparison of alternative models for personality disorders, II: 6-, 8- and 10-year follow-up

Background Several conceptual models have been considered for the assessment of personality pathology in DSM-5. This study sought to extend our previous findings to compare the long-term predictive validity of three such models: the Five-Factor Model (FFM), the Schedule for Nonadaptive and Adaptive Personality (SNAP), and DSM-IV personality disorders (PDs). Method An inception cohort from the Collaborative Longitudinal Personality Disorder Study (CLPS) was followed for 10 years. Baseline data were used to predict long-term outcomes, including functioning, Axis I psychopathology, and medication use. Results Each model was significantly valid, predicting a host of important clinical outcomes. Lower-order elements of the FFM system were not more valid than higher-order factors, and DSM-IV diagnostic categories were less valid than dimensional symptom counts. Approaches that integrate normative traits and personality pathology proved to be most predictive, as the SNAP, a system that integrates normal and pathological traits, generally showed the largest validity coefficients overall, and the DSM-IV PD syndromes and FFM traits tended to provide substantial incremental information relative to one another. Conclusions DSM-5 PD assessment should involve an integration of personality traits with characteristic features of PDs.
Spatio-Temporal Topic Modeling in Mobile Social Media for Location Recommendation

Mobile networks enable users to post on social media services (e.g., Twitter) from anywhere and anytime. This new phenomenon led to the emergence of a new line of work of mining the behavior of mobile users taking into account the spatio-temporal aspects of their engagement with online social media. In this paper, we address the problem of recommending the right locations to users at the right time. We claim to propose the first comprehensive model, called STT (Spatio-Temporal Topic), to capture the spatio-temporal aspects of user check-ins in a single probabilistic model for location recommendation. Our proposed generative model does not only captures spatio-temporal aspects of check-ins, but also profiles users. We conduct experiments on real life data sets from Twitter, Go Walla, and Bright kite. We evaluate the effectiveness of STT by evaluating the accuracy of location recommendation. The experimental results show that STT achieves better performance than the state-of-the-art models in the areas of recommender systems as well as topic modeling.
Energy Efficient User Association for Cloud Radio Access Networks

Cloud radio access network (C-RAN) and massive multiple-input multiple-output (MIMO) are recognized as two key technologies for the fifth-generation mobile networks. In this paper, we consider the energy efficiency-based user association problem in massive MIMO empowered C-RAN, where multiple antennae are clustered at each remote radio head (RRH). We first obtain the deterministic equivalent expression of the energy efficiency, and then propose three user association algorithms, named nearest-based user association (NBUA), single-candidate RRH user association (SCRUA), and multi-candidate RRHs user association (MCRUA), respectively. In NBUA and SCRUA, each user is associated with only one RRH, and in MCRUA, multiple RRHs can serve the same user. In our algorithms, the impact of the power consumption of fronthaul links and antennas is considered by allowing inefficient RRHs to be turned into sleep mode. We provide the numerical comparisons of the proposed algorithms and a state-of-the-art baseline, which associates each user with the nearest RRH. The results show that our proposed algorithms achieve higher energy efficiency than the baseline algorithm. The proposed MCRUA algorithm achieves a good balance between spectral and energy efficiency, and the performance gain is more significant when the number of users is large.
Budget Analyses of Precipitation and Energetics Associated with Torrential Rainfall Events over Zhejiang, Fujian and Jiangxi

Four cases of heavy rainfall over Zhejiang, Fujian and Jiangxi during mid-June are simulated by the two-dimensional (2D) cloud-resolving model using the large-scale forcing data derived from the 6-hourly ERA-Interim data set. The simulations are used to conduct budget analysis of precipitation and energetics associated with the development of torrential rainfall. Surface rainfall is dominated by water vapor convergence (QWVF) in water vapor related surface rainfall budget and heat divergence (SHF) in thermally related surface rain budget. The high linear correlation coefficients between water vapor related precipitation efficiency (PEWV) and heat related precipitation efficiency (PEH) stem from the statistical similarities between QWVF and SHF . The diurnal variations of surface rainfall correspond to the upward motions. An energy conversion efficiency is defined as the ratio of perturbation kinetic-energy to convective available potential energy to measure how efficiently the secondary circulations develop under the consumption of the convective available potential energy. The diurnal variations of energy conversion efficiency generally are in phase with the rainfall, indicating importance of interaction between dynamics and water vapor in build-up of rainfall peaks. (Citation: Yang, X., and X. Li, 2018: Budget analyses of precipitation and energetics associated with torrential rainfall events over Zhejiang, Fujian and Jiangxi. SOLA, 14, 185−191, doi: 10.2151/sola.2018-033.)
In silico analysis of potential structural and functional significance of human breast cancer gene BRCA2 sequence variants found in 5’ untranslated region

Background and Purpose: BRCA1 and BRCA2 are major hereditary breast/ovarian cancer predisposing genes and their mutations increase the risk of developing cancer. Genetic testing of these two genes is nowadays commonly performed but almost half of found genetics alterations are declared as variants of unknown clinical significance. Interpretation of these unclassified variants is the major concern for BRCA genes. The aim of this study is to investigate potential structural and functional significance of sequence variants found in 5’ untranslated region (UTR) of BRCA2 gene. Materials and Methods: Consensus secondary structure of BRCA2 5’ UTR was built based on nucleotide sequences from four different species. We collected all found human BRCA2 5’ UTR variants and explored their potentials effects by folding human BRCA2 5’ UTR including one of each variant, using consensus structure as a constraint. If constrained folding results in a structure that is very different from the consensus one, this may indicate that this particular sequence variant could have potential functional impact.
Axiomatization and Measurement of Quasi-Hyperbolic Discounting

This article provides an axiomatic characterization of quasi-hyperbolic discounting and a more general class of semi-hyperbolic preferences. We impose consistency restrictions directly on the intertemporal trade-offs by relying on what we call â€œannuity compensations. â€ Our axiomatization leads naturally to an experimental design that disentangles discounting from the elasticity of intertemporal substitution. In a pilot experiment we use the partial identification approach to estimate bounds for the distributions of discount factors in the subject pool. Consistent with previous studies, we find evidence for both present and future bias.