Miracle-dz/UniFAR-FTUs huggingface dataset:
Distribution of route requests using dominating-set neighbor elimination in an on-demand routing protocol

The use of dominating-set neighbor elimination as an integral part of the distribution of route requests using the ad hoc on-demand distance vector (AODV) protocol as an example of on-demand routing protocols is investigated. We use detailed simulations to show that simply applying dominant pruning (DP) to the distribution of route requests in AODV results in pruning too many route requests in the presence of mobility and cross-traffic. Accordingly, we introduce several heuristics to compensate the effects of DP and show that the resulting AODV with dominating set heuristics (AODV-DS) has comparable or better delivery ratio, network load, and packet latency than the conventional AODV. AODV-DS exhibits over 70% savings on RREQ traffic than conventional AODV, and in some situations, AODV-DS may have a lower control overhead using Hello packets than conventional AODV without Helios.
Fast Electromagnetic Analysis of MRI Transmit RF Coils Based on Accelerated Integral Equation Methods

A fast frequency domain full-wave electromagnetic simulation method is introduced for the analysis of MRI coils loaded with the realistic human body models. The approach is based on integral equation methods decomposed into two domains: 1) the RF coil array and shield, and 2) the human body region where the load is placed. The analysis of multiple coil designs is accelerated by introducing the precomputed magnetic resonance Green functions (MRGFs), which describe how the particular body model used responds to the incident fields from external sources. These MRGFs, which are precomputed once for a given body model, can be combined with any integral equation solver and reused for the analysis of many coil designs. This approach provides a fast, yet comprehensive, analysis of coil designs, including the port S-parameters and the electromagnetic field distribution within the inhomogeneous body. The method solves the full-wave electromagnetic problem for a head array in few minutes, achieving a speed up of over 150 folds with root mean square errors in the electromagnetic field maps smaller than 0.4% when compared to the unaccelerated integral equation-based solver. This enables the characterization of a large number of RF coil designs in a reasonable time, which is a first step toward an automatic optimization of multiple parameters in the design of transmit arrays, as illustrated in this paper, but also receive arrays.
Evidence-Based Psychotherapy for Eating Disorders

Recommended psychotherapies for treating bulimia nervosa and binge eating disorder have been clearly established, with cognitive-behavioral therapy representing the leading choice. Second line psychotherapies for bulimia nervosa and binge eating disorder are interpersonal psychotherapy, as well as dialectical behavior therapy for bulimia nervosa and behavioral weight loss for binge eating disorder. An urgent need remains for effective and acceptable treatments for anorexia nervosa among adults with the choice of treatment currently informed by an array of psychotherapies with weak efficacy; trends toward high treatment drop out and poor adherence are important issues to resolve. Among children and adolescents with anorexia nervosa, and to some extent bulimia nervosa, family-based treatments that directly target eating are favored. Pharmacotherapy may also be recommended for some individuals with eating disorders, which would be administered by a primary care practitioner or psychiatrist for more severe, c.
T1-Weighted Imaging of the Brain at 3 Tesla Using a 2-Dimensional Spoiled Gradient Echo Technique

Rationale and Objectives:The objective of this study was to evaluate a 2-dimensional spoiled gradient echo (GRE) imaging approach using a very short in-phase TE for routine T1-weighted imaging of the brain at 3 T. Materials and Methods:Patient examinations were compared from a 3 T magnetic resonance (MR) unit located immediately adjacent to a similarly equipped 1.5 T unit. Pre- and postcontrast T1-weighted images were evaluated and compared at 1.5 versus 3 T with a 2-dimensional (2-D) spin echo sequence used at 1.5 T and a 2-D GRE sequence at 3 T. The 2 MR systems used are from the same vendor, use similar 8-channel coils, and use identical gradients. The T1-weighted GRE sequence, used at 3 T, relies on a short TE (2.4 ms) to limit flow-related and susceptibility artifacts. Region-of-interest analysis was performed on 16 different sagittal patient examinations at both field strengths (32 total) and similarly on 10 different pre- and postcontrast axial examinations (40 total). Four blinded neuroradiologists also evaluated these studies. Results:Using an off-midline sagittal slice depicting the caudate nucleus (signal-to-noise ratio [SNR] 163 ± 28 vs. 70 ± 7, 3 T vs. 1.5 T) and corona radiata (SNR 214 ± 35 vs. 82 ± 10), 3 T markedly outperformed 1.5 T in both SNR and contrast-to-noise ratio (CNR) (51 ± 14 vs. 12 ± 5). On axial imaging, despite a reduction in slice thickness (5 to 3 mm) and scan time (5 to 1 minute), there was no significant difference pre- or postcontrast in SNR and CNR comparing 3 and 1.5 T. On blinded film review, 3 T performed slightly better on sagittal scans than 1.5 T in regard to motion artifacts (reduced), gray-white matter differentiation, and overall image quality. On axial scans, 3 T performed markedly better in all 3 categories both pre- and postcontrast. In regard to overall image quality, 3 T was preferred 9:2 precontrast and 4:1 postcontrast. Conclusions:High-quality, thin-section (3-mm) T1-weighted imaging can be readily performed at 3 T using a short TE 2-D GRE technique. This approach offers superior SNR and CNR with reduced motion artifacts and scan time as compared with imaging at 1.5 T and is advocated for routine brain imaging at 3 T. It is robust (used in over 1500 patients to date) and does not experience significant specific absorption ratio limitations, poor tissue contrast, or accentuated motion artifacts like encountered with spin echo T1-weighted imaging at 3 T.
Construction of a quantum Heisenberg group

In this paper, we give a construction of a (C*-algebraic) quantum Heisenberg group. This is done by viewing it as the dual quantum group of the specific non-compact quantum group (A,\Delta) constructed earlier by the author. Our definition of the quantum Heisenberg group is different from the one considered earlier by Van Daele. To establish our object of study as a locally compact quantum group, we also give a discussion on its Haar weight, which is no longer a trace. In the latter part of the paper, we give some additional discussion on the duality mentioned above.
Melatonin promotes development of haploid germ cells from early developing spermatogenic cells of Suffolk sheep under in vitro condition

Promotion of spermatogonial stem cell (SSC) differentiation into functional sperms under in vitro conditions is a great challenge for reproductive physiologists. In this study, we observed that melatonin (10−7 m) supplementation significantly enhanced the cultured SSCs differentiation into haploid germ cells. This was confirmed by the expression of sperm special protein, acrosin. The rate of SSCs differentiation into sperm with melatonin supplementation was 11.85 ± 0.93% which was twofold higher than that in the control. The level of testosterone, the transcriptions of luteinizing hormone receptor (LHR), and the steroidogenic acute regulatory protein (StAR) were upregulated with melatonin treatment. At the early stage of SSCs culture, melatonin suppressed the level of cAMP, while at the later stage, it promoted cAMP production. The similar pattern was observed in testosterone content. Expressions for marker genes of meiosis anaphase, Dnmt3a, and Bcl‐2 were upregulated by melatonin. In contrast, Bax expression was downregulated. Importantly, the in vitro‐generated sperms were functional and they were capable to fertilize oocytes. These fertilized oocytes have successfully developed to the blastula stage.
Concurrent verbal reports on text comprehension: A review

Ericsson and Simon's theoretical framework for verbal reports on cognitive processes is described. Current theories of text comprehension are reviewed to identify Information to which people pay attention during comprehension of text. Predictions for the extent and content of subjects' verbal reports during comprehension are dem ed. In an empincal review of studies in which verbal reports on reading and text comprehension were collected, these predictions are evaluatedt and empincal results are summarized for several categories of studies with different verbd-report procedures. Studies using unconstrained reading are distinguished from studies using sentence-bysentence reading, and studies in which subjects' report on actual thoughts during text comprehension are separated from those in which subjects* comment on their comprehension of texts. Studies of reading aloud and of comprehension of specialized texts, such äs problem descriptions and legal case descriptions, are discussed and related to thegeneralmodelofverbalization of comprehension processes. Concerns and future directions for research on text comprehension with the verbal-report methodology are discussed.
Tree-Structured Modelling of Categorical Predictors in Regression

Generalized linear and additive models are very efficient regression tools but the selection of relevant terms becomes difficult if higher order interactions are needed. In contrast, tree-based methods also known as recursive partitioning are explicitly designed to model a specific form of interaction but with their focus on interaction tend to neglect the main effects. The method proposed here focusses on the main effects of categorical predictors by using tree type methods to obtain clusters. In particular when the predictor has many categories one wants to know which of the categories have to be distinguished with respect to their effect on the response. The tree-structured approach allows to detect clusters of categories that share the same effect while letting other variables, in particular metric variables, have a linear or additive effect on the response. An algorithm for the fitting is proposed and various stopping criteria are evaluated. The preferred stopping criterion is based on p-values representing a conditional inference procedure. In addition, stability of clusters are investigated and the relevance of variables is investigated by bootstrap methods. Several applications show the usefulness of tree-structured clustering and a small simulation study demonstrates that the fitting procedure works well.
Network Traffic Prediction Based on Neural Network

Predicting and modeling network traffic is always an important subject in network capability studying. The aim of this article is to explore a new network model in order to describe and predict the network character accurately. Firstly wavelet neural network is investigated and its disadvantages are analyzed. In order to overcome disadvantages of wavelet neural network, genetic algorithm is used to optimize weight and threshold of neural network. At last, the proposed algorithm is used in network traffic prediction and the results show the proposed scheme has good performance.
Imagining worse than reality: comparing beliefs and intentions between disaster evacuees and survey respondents1

We often credit disasters, and their coverage in the media, with changes in the public perception of risk associated with low-probability, high-consequence events (LPHCs). With a change in perceptions, we also expect changes in beliefs, preferences, and behaviors. Do beliefs and behaviors change in different ways for people who live through these LPHC critical events, as opposed to people who observe them? This study compares hypothetical hurricanes with actual hurricane effects in a survey quasi-experiment. Findings indicate that hypothetical disasters induce stronger reactions than those experienced in the natural world, as Hurricane Katrina bystanders imagine themselves incurring much higher damages, and being much less likely to return to live in their hurricane-damaged homes, than actual Hurricane Katrina evacuees. Ultimately, respondents considering a hypothetical low-probability, high-consequence event exhibit exaggerated beliefs and opposite decisions of those who actually lived through one of these events. Results underline the importance of examining the differences between public perceptions and experiential reality.
Explicit, closed-form performance analysis in fading via new bound on Gaussian Q-function

This paper aims at providing explicit, closed-form solutions to the error probability performance analysis of digital communications over fading channels. This is achieved by first deriving a family of new upper bounds on the Gaussian Q-function Q(x), which is given by a sum of products of the exponential function and c/x where c is a constant. The bounds obtained can be made arbitrarily tight as the number of summation terms increases, and thus, can be used to approximate Q(x) accurately. Their applications to the performance analysis over fading are then presented to highlight the significance of the bounds derived. Both short-term fading and combined short-term and long-term fading are considered. It is shown that the new bounds can lead to better performance than the popular exponential-type upper bounds.
ROOT HAIR DEFECTIVE SIX-LIKE Class I Genes Promote Root Hair Development in the Grass Brachypodium distachyon

Genes encoding ROOT HAIR DEFECTIVE SIX-LIKE (RSL) class I basic helix loop helix proteins are expressed in future root hair cells of the Arabidopsis thaliana root meristem where they positively regulate root hair cell development. Here we show that there are three RSL class I protein coding genes in the Brachypodium distachyon genome, BdRSL1, BdRSL2 and BdRSL3, and each is expressed in developing root hair cells after the asymmetric cell division that forms root hair cells and hairless epidermal cells. Expression of BdRSL class I genes is sufficient for root hair cell development: ectopic overexpression of any of the three RSL class I genes induces the development of root hairs in every cell of the root epidermis. Expression of BdRSL class I genes in root hairless Arabidopsis thaliana root hair defective 6 (Atrhd6) Atrsl1 double mutants, devoid of RSL class I function, restores root hair development indicating that the function of these proteins has been conserved. However, neither AtRSL nor BdRSL class I genes is sufficient for root hair development in A. thaliana. These data demonstrate that the spatial pattern of class I RSL activity can account for the pattern of root hair cell differentiation in B. distachyon. However, the spatial pattern of class I RSL activity cannot account for the spatial pattern of root hair cells in A. thaliana. Taken together these data indicate that that the functions of RSL class I proteins have been conserved among most angiosperms—monocots and eudicots—despite the dramatically different patterns of root hair cell development.
A report of 497 women hospitalized for treatment of bulimia nervosa

Abstract The majority of psychotherapy outcome studies of bulimia nervosa have used outpatient samples. Less is known about the bulimia nervosa patient who requires inpatient treatment. We present data on 497 women treated at an inpatient facility for women with eating disorders along with preliminary 1–3-year follow-up on a subset of the women. Psychometric data suggest that, prior to treatment, the women were of above-average severity in terms of eating disorder and psychiatric symptomatology. Clinically and statistically significant changes in these symptoms were observed during treatment. At follow-up approximately 61% of the women appeared no longer to meet the diagnostic criteria for bulimia nervosa. There was no worsening or further improvement following the first year of follow-up. Results are compared with previous reports of inpatient bulimia nervosa patients.
Reflections on the assessment of outcomes in child care

Measuring the outcomes of social work interventions with children raises complex issues. The instability of intermediate outcomes emphasises the need to undertake regular and carefully timed assessments. Differences in approach and perspective can obscure relationships between evaluations of organisational performance and assessments of outcome for individual children; user perspectives introduce another point of view. Assessing outcomes of family support services raises questions of accountability. Aggregate information about children looked after, collected through the Looking After Children project, should help to establish the chances of certain outcomes being realised, although the influence of some factors may not be easy to explain.
Segmentation of retinal blood vessels based on the second directional derivative and region growing

We present a method for the segmentation of blood vessels in retinal images based upon the second derivative of the intensity image which gives information about its topology and overcomes the problem of image intensity variations. The minimum eigenvalue and the magnitude of its gradient are used as features for a region growing procedure which is defined in two stages. For the first stage, growth is restricted to regions with low gradients, allowing vessels to grow where the values of the minimum eigenvalue lie within a wide interval and allowing rapid growth of background regions outside of the vessel boundaries. For the second stage, in which the borders between classes are defined, the algorithm grows vessel and background classes simultaneously without the gradient restriction.
Real-Time Interactive Reinforcement Learning for Robots

It is our goal to understand the role real-time human interaction can play in machine learning algorithms for robots. In this paper we present Interactive Reinforcement Learning (IRL) as a plausible approach for training human-centric assistive robots by natural interaction. We describe an experimental platform to study IRL, pose questions arising from IRL, and discuss initial observations obtained during the development of our system.
An introduction to the analysis of shotgun metagenomic data

Environmental DNA sequencing has revealed the expansive biodiversity of microorganisms and clarified the relationship between host-associated microbial communities and host phenotype. Shotgun metagenomic DNA sequencing is a relatively new and powerful environmental sequencing approach that provides insight into community biodiversity and function. But, the analysis of metagenomic sequences is complicated due to the complex structure of the data. Fortunately, new tools and data resources have been developed to circumvent these complexities and allow researchers to determine which microbes are present in the community and what they might be doing. This review describes the analytical strategies and specific tools that can be applied to metagenomic data and the considerations and caveats associated with their use. Specifically, it documents how metagenomes can be analyzed to quantify community structure and diversity, assemble novel genomes, identify new taxa and genes, and determine which metabolic pathways are encoded in the community. It also discusses several methods that can be used compare metagenomes to identify taxa and functions that differentiate communities.
Senile dementia of the Alzheimer type

The prevalence of severe dementia in the United States is about 1.3 million cases, of which at least 50 to 60% are of the Alzheimer type. Severe dementia of the Alzheimer type is found rarely in a clearly dominant pattern, although often one or more relatives are affected. Down's syndrome in adults is often associated with Alzheimer changes. The diagnosis is a clinicopathological one; there is a considerable error rate in the clinical diagnosis early in the course of the disease, especially in regard to dementia in depression. The differential diagnosis involves a great many disorders, including multi‐infarct dementia, tumors, subdural hematomas, and others. Physiological aspects of Alzheimer's disease include a diffusely slow electroencephalogram, reduced cerebral blood flow, and particular patterns noted on positron emission tomographic scanning. The latter technique has also demonstrated that oxygen extraction is normal in Alzheimer's disease, thus excluding ischemia from possible pathogenetic factors. Morphological changes, that is, the presence of plaques and tangles, are widely distributed in neocortex, paleocortex, and many deep gray areas down through the pontine tegmentum, but largely exclude the basal ganglia, thalamus, and substantia nigra. Numerous plaques without neocortical tangles are found in many demented persons older than 75 years. A severe loss of large neocortical neurons is characteristic of the disease. The chemical nature of the paired helical filaments that make up the neurofibrillary tangle has not yet been ascertained. Neurons are markedly deficient in the basal forebrain nuclei, and this deficiency may account for the severe diminution of choline acetyltransferase and acetylcholine in the neocortex and palecortex. Muscarinic cholinergic receptors are present in normal amounts. Norepinephrine is reduced in some cases, and somatostatin in most. Substance P is low in severe cases. The etiology of the disorder is unknown and the role of aluminum is disputed. Management of patients with Alzheimer's disease is difficult, and neuroleptics are to be used with great caution because of their side effects. Substrate therapy has not been effective; physostigmine improves memory but is not suitable for general use. Trophic factors, gangliosides, and aluminum chelation are being investigated for use in pharmacological intervention.