Miracle-dz/UniFAR-FTUs huggingface dataset:
One- And Two-year Outcomes of Treating Preschool Children with Autism with a Qigong Massage Protocol: An Observational Follow-along Study

Background: Randomized controlled trials have repeatedly demonstrated that treatment with a five-month qigong massage protocol significantly reduces the severity of autism. The treatment protocol is known as Qigong Sensory Training (QST) autism massage and is given daily by parents and weekly by therapists for five months. Treatment reduces the tactile abnormalities that are universal in young children with autism and results in improved social skills, language and behavior. At five months, tactile abnormalities are reduced by 1/2, autistic behavior is reduced by 1/3, autism severity is reduced by 16%, and 6% of children have moved off the spectrum. What has not yet been done is to measure outcomes with longer-term treatment. This observational study investigates outcomes with up to 24 months of treatment. Methods: 75 children entered this observational study upon completion of five months of treatment with the QST protocol. They received daily parent treatment and monthly therapist treatment for the balance of the first year, and daily parent treatment without therapist support for the second year. Sequential evaluations were conducted at baseline (n=75), five months (n=75), 12 months (n=67) and 24 months (n=31). Results: Continued treatment resulted in continued improvement. At 12 and 24 months, mean tactile responses normalized by 57% and 72%, with 24% and 32% falling into the normal range; mean autism severity decreased by 27% and 44%, with 12% and 26% of children moving out of autistic range. Conclusions: Results demonstrated that longer-term treatment resulted in resolution of tactile impairment and continued improvement of social skills, language and behavior. The rate of coming off the spectrum (1 in 4 children by year-2) was far higher than the natural history of ASD would predict. Results support earlier recommendations to treat tactile abnormalities at the time of autism diagnosis in order to improve autism outcomes.
Brain-Computer Interface for a Prosthetic Hand Using Local Machine Control and Haptic Feedback

A brain-computer interface (BCI) uses electrophysiological measures of brain function to enable individuals to communicate with the external world, bypassing normal neuromuscular pathways. While it has been suggested that this control can be applied for neuroprostheses, few studies have demonstrated practical BCI control of a prosthetic device. In this paper, an electroencephalogram (EEG)-based motor imagery BCI is presented to control movement of a prosthetic hand. The hand was instrumented with force and angle sensors to provide haptic feedback and local machine control. Using this system, subjects demonstrated the ability to control the prosthetic's grasping force with accuracy comparable to an EMG-based control scheme. Further work is necessary to improve the integration of BCI control strategies with prostheses.
Measures of physical performance and risk for progressive and catastrophic disability: results from the Women's Health and Aging Study.

BACKGROUND Physical performance measures can predict incident disability, but little research has assessed and compared how these measures predict progressive and rapid-onset (catastrophic) disability. The authors evaluated the ability of upper and lower extremity performance measures to predict progressive and catastrophic disability in activities of daily living (ADL), mobility, and upper extremity function. METHODS The incidence of progressive and catastrophic disability was assessed semiannually during a 3-year period in 884 women participating in the Women's Health and Aging Study I. Four-meter walking speed, balance, and chair stands tests were used to evaluate lower extremity function. The putting-on-blouse test, the Purdue pegboard test, and grip strength were used to assess upper extremity function. Summary performance scores (SPS) for the lower and upper extremities were calculated. Among participants in whom disability developed, those who reported no difficulty in the previous year were defined as cases of catastrophic disability, and those who previously reported little or some difficulty were considered to be cases of progressive disability. Cox proportional hazard regression analyses were used to evaluate the association of performance measures and time to incident disability. The predictive ability of performance measures was compared using receiver-operator characteristic curves. RESULTS All lower and upper extremity measures, with the exception of grip strength, significantly predicted the onset of progressive ADL disability, but only walking speed was significantly associated with the onset of catastrophic ADL disability. The chair stands test, walking speed, and the lower extremity SPS were significantly associated with the onset of both progressive and catastrophic mobility disability. Only lower extremity individual tests and SPS significantly predicted the onset of both progressive and catastrophic upper extremity disability. The receiver-operator characteristic curves for ADL and mobility disability showed that all performance measures evaluated had a greater predictive ability for progressive than for catastrophic incident disability. This finding was not consistent for upper extremity disability. The areas under the curve for walking speed and lower extremity SPS were very similar, ranging from 0.58 to 0.81 and from 0.57 to 0.85, and the predictive ability of these two measures was the greatest for all disability outcomes assessed. CONCLUSION Physical performance measures of lower extremity and, in particular, walking speed and lower extremity SPS are valuable tools to predict different forms of disability, especially those with a progressive onset.
Virtual reality immersion method of distraction to control experimental ischemic pain.

BACKGROUND Virtual reality immersion has been advocated as a new effective adjunct to drugs for pain control. The attenuation of pain perception and unpleasantness has been attributed to the patient's attention being diverted from the real, external environment through immersion in a virtual environment transmitted by an interactive 3-D software computer program via a VR helmet. OBJECTIVES To investigate whether VR immersion can extend the amount of time subjects can tolerate ischemic tourniquet pain. METHODS The study group comprised 20 healthy adult volunteers. The pain was induced by an inflated blood pressure cuff during two separate, counterbalanced, randomized experimental conditions for each subject: one with VR and the control without VR exposure. The VR equipment consisted of a standard computer, a lightweight helmet and an interactive software game. RESULTS Tolerance time to ischemia was significantly longer for VR conditions than for those without (P < 0.001). Visual Analogue Scale (0-10) ratings were recorded for pain intensity, pain unpleasantness, and the time spent thinking about pain. Affective distress ratings of unpleasantness and of time spent thinking about pain were significantly lower during VR as compared with the control condition (P< 0.003 and 0.001 respectively). CONCLUSIONS The VR method in pain control was shown to be beneficial. The relatively inexpensive equipment will facilitate the use of VR immersion in clinical situations. Future research is necessary to establish the optimal selection of clinical patients appropriate for VR pain therapy and the type of software required according to age, gender, personality, and cultural factors.
Dimensionality of Scandinavian river flow regimes

A river flow regime describes an average seasonal behaviour of river flow, usually representing a set of long-term monthly mean values. Seasonal patterns of flow can be regular, repeating in principle the same pattern from year to year, or irregular, i.e. alternating between a couple of different regime types during individual years. By tradition, a river flow regime has been considered as a static characteristic that does not change in large temporal scale, yet this may be an oversimplification with regard to constantly changing environmental conditions. Such a "static" description of a flow regime, based on long-term mean values is in discrepancy with the dynamic character of the system described. The dimension of this system in terms of fractal and intrinsic dimensions has been investigated on an example of Scandinavian runoff series by different methods: from a simple graphic method to determine the fractal dimension to empirical orthogonal function (EOF) and entropy-based aggregation to outline the number of patterns necessary for representing the regimes of different intrinsic dimension of a set of point data. The series studied demonstrated a variety of fractal and intrinsic dimensions that were well in agreement with the stability character of the investigated regime types. The less stable the regime, the higher were its fractal and intrinsic dimensions and the number of variables required for its description. Structure dimensionnelle des regimes d'ecoulements des rivieres
Progressive multifocal leukoencephalopathy and natalizumab--unforeseen consequences.

In this issue of the Journal, there are reports describing in detail three patients in whom progressive multifocal leukoencephalopathy (PML) developed during treatment with natalizumab, a humanized monoclonal antibody against α4 integrins.1–3 These patients were among 3000 who had participated in clinical trials of natalizumab for the treatment of multiple sclerosis or Crohn's disease. PML is a deadly opportunistic infection of the central nervous system (CNS) for which there is no specific treatment. It is caused by reactivation of a clinically latent JC polyomavirus infection. This virus infects and destroys oligodendrocytes, leading to multifocal areas of demyelination and .
Energy Efficient Algorithm for Congestion Control in Wireless Sensor Networks

—Wireless routing is an area of research which is being focused mainly for congestion avoidance and security. Various routing protocols and techniques are being included in wireless network and making it an area for further research. The need is increasing more due to invention and adaption of wireless communication devices for wireless communication. This work is focusing on security over multicast routing and simulations are being proposed to show the improved packet delivery ration, end to end delay and reduced packet drop rate for Ad hoc On Demand Distance Vector (AODV) routing protocol. Attacks are being avoided proactively by including changes in the basic implementation of AODV routing protocol. This work proposes a communication algorithm for WSN networks so that the congestion will be reduced and in turn energy will be utilized efficiently.
Imaging Radio-Frequency Power Distributions by an EBG Absorber

A thin electromagnetic band-gap (EBG) absorber is employed to capture the 2-d image of radio-frequency (RF) power distribution. The EBG absorber consists of an array of mushroom unit cells formed on a thin dielectric substrate with a metal backplane, and lumped resistors interconnecting the surface patches of the mushrooms. Around the resonance frequency at which the EBG structure acts as a high-impedance surface, the RF power incident on the surface is absorbed by the lumped resistors which are matched with the incident wave impedance. By detecting directly the amounts of power consumed by the individual resistors, an “RF power imager” can be constructed which captures the 2-d distribution of the RF power illuminating the EBG surface, where polarization discrimination is possible. The resonance (i.e., absorption) frequency is made tunable by adding varactor diodes in parallel with the lumped resistors. The EBG absorber tunable in the frequency range of 700 MHz–2.7 GHz is designed and fabricated, and its performance is evaluated by an equivalent-circuit analysis, simulation and measurement. It is shown that the small resistance of the varactors have a considerable effect on the absorption performance. RF power distributions radiated from a dipole antenna are successfully measured by a matrix of sensitive power detectors installed on the backside of the absorber. Using such an RF power imager, the power distributions of even impulsive RF signals and/or noises can be captured and visualized in situ and in real-time, while the electromagnetic environment is almost undisturbed by the EBG absorber. key words: EBG, absorber, RF power distribution, measurement, imaging
Classification of children with voice impairments using deep neural networks

This paper presents the deep neural networks to classification of children with voice impairments from speech signals. In the analysis of speech signals, 6,373 static acoustic features are extracted from many kinds of low-level-descriptors and functionals. To reduce the variability of extracted features, two-dimensional normalizations are applied to smooth the interspeaker and inter-feature mismatch using the feature warping approach. Then, the feature selection is used to explore the discriminative and low-dimensional representation based on techniques of principal component analysis and linear discriminant analysis. In such representation, the robust features are obtained by eliminating noise features via subspace projection. Finally, the deep neural networks are adopted to classify the children with voice impairments. We conclude that deep neural networks with the proposed feature normalization and selection can significantly contribute to the robustness of recognition in practical application scenarios. We have achieved an UAR of 60.9% for the four-way diagnosis classification on the development set. This is a relative improvement of 16.2% to the official baseline by using our single system.
Disease, predation and demography: Assessing the impacts of bovine tuberculosis on African buffalo by monitoring at individual and population levels

Summary 1. Understanding the effects of disease is critical to determining appropriate management responses, but estimating those effects in wildlife species is challenging. We used bovine tuberculosis (BTB) in the African buffalo Syncerus caffer population of Kruger National Park, South Africa, as a case study to highlight the issues associated with estimating chronic disease effects in a long-lived host. 2. We used known and radiocollared buffalo, aerial census data, and a natural gradient in pathogen prevalence to investigate if: (i) at the individual level, BTB infection reduces reproduction; (ii) BTB infection increases vulnerability to predation; and (iii) at the population level, increased BTB prevalence causes reduced population growth. 3. There was only a marginal reduction in calving success associated with BTB infection, as indexed by the probability of sighting a known adult female with or without a calf ( P = 0·065). 4. Since 1991, BTB prevalence increased from 27 to 45% in the southern region and from 4 to 28% in the central region of Kruger National Park. The prevalence in the northern regions was only 1·5% in 1998. Buffalo population growth rates, however, were neither statistically different among regions nor declining over time. 5. Lions Panthera leo did not appear to preferentially kill test-positive buffalo. The best (Akaike’s Information Criterion corrected for small sample size) AIC c model with BTB as a covariate [exp( β ) = 0·49; 95% CI = (0·24‐1·02)] suggested that the mortality hazard for positive individuals was no greater than for test-negative individuals. 6. Synthesis and applications . Test accuracy, time-varying disease status, and movement among populations are some of the issues that make the detection of chronic disease impacts challenging. For these reasons, the demographic impacts of bovine tuberculosis in the Kruger National Park remain undetectable despite 6 years of study on known individuals and 40 years of population counts. However, the rainfall and forage conditions during this study were relatively good and the impacts of many chronic diseases may be a non-linear function of environmental conditions such that they are only detectable in stressful periods.
GMASS ultradeep spectroscopy of galaxies at z $\mathsf{\sim2}$ - III. The emergence of the color bimodality at z $\mathsf{\sim2}$

Aims. The aim of this work is to study the evolution of the rest-frame color distribution of galaxies with the redshift, in particular in the critical interval $1.4 Methods. We combined ultradeep spectroscopy from the GMASS project ( Galaxy Mass Assembly ultradeep Spectroscopic Survey ) with GOODS multi-band photometry (from optical to mid-infrared) to study a sample of 1021 galaxies up to m (4.5 μ m) = 23. Results. We find that the distribution of galaxies in the $(U-B)$ color vs. stellar mass plane is bimodal up to at least redshift $z=2$. We define a “mass complete” sample of galaxies residing on the red sequence, selecting objects with $\log(M/M_{\odot})>10.1$, and we study their morphological and spectro-photometric properties. We show that the contribution to this sample of early-type galaxies, defined as galaxies with a spheroidal morphology and no star formation, decreases from 60-70% at $z 2$ we still find red galaxies in the mass complete sample, even if the bimodality is not seen any more. About 25% of these red galaxies at $z>2$ are passively evolving, with the bulk of their stars formed at redshift $z>3$.
Journal of Multidisciplinary Healthcare Dovepress Evaluation of the Antipsychotic Medication Review Process at Four Long-term Facilities in Alberta

you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms Purpose: The goal of this evaluation was to understand how four long-term care (LTC) facilities in Alberta have implemented medication reviews for the Appropriate Use of Antipsy-chotics (AUA) initiative. We aimed to determine how interprofessional (IP) collaboration was incorporated in the antipsychotic medication reviews and how the reviews had been sustained. Methods: Four LTC facilities in Alberta participated in this evaluation. We conducted semis-tructured interviews with 18 facility staff and observed one antipsychotic medication review at each facility. We analyzed data according to the following key components that we identified as relevant to the antipsychotic medication reviews: the structure of the reviews, IP interactions between the staff members, and strategies for sustaining the reviews. Results: The duration of antipsychotic medication reviews ranged from 1 to 1.5 hours. The number of professions in attendance ranged from 3 to 9; a pharmacist led the review at two sites, while a registered nurse led the review at one site and a nurse practitioner at the remaining site. The number of residents discussed during the review ranged from 6 to 20. The process at some facilities was highly IP, demonstrating each of the six IP competencies. Other facilities conducted the review in a less IP manner due to challenges of physician involvement and staff workload, particularly of health care aides. Facilities that had an nurse practitioner on site were more efficient with the process of implementing recommendations resulting from the medication reviews. Conclusion: The LTC facilities were successful in implementing the medication review process and the process seemed to be sustainable. A few challenges were observed in the implementation process at two facilities. IP practice moved forward the goals of the AUA initiative to reduce the inappropriate use of antipsychotics.
Utility-Oriented Matching: A New Research Direction for Case-Based Reasoning

Case-Based Reasoning research has reached a state where a large number of basic problems seems to be “solved”. However, techniques originally developed for CBR applications are being applied in systems that are not CBR systems in the original meaning of the word. This paper wants to extend the traditional view of CBR to overcome its former limitations, to open new fields of research, and to open new application areas. This is achieved by generalizing the classical similarity measure to a utility measure that does not depend on problem descriptions taken from experience any more.
Why Do Firms Hold Cash ? Evidence from Demographic Demand Shifts 1

We study why companies hold cash by exploring shifts in demand induced by demographics. These shifts generate exogenous variations both on the precautionary motive and the free cash problem. We find that firms increase their cash holdings in advance of high demand growth. Consistent with the precautionary motive, this relation is stronger for financially constrained firms. Additionally, we find that firms decrease their cash holdings when facing low forecasted demand growth. Consistent with an adjustment to reduce the free cash problem this relation is stronger for firms with stronger governance, lower debt, and in low concentration industries.
Multiresolution Techniques for the Simplification of Triangular and Tetrahedral Meshes

We study the simplification of triangular and tetrahedral meshes using techniques based on successive edge collapses, as well as the exploitation of the generated multiple levels of detail for the effective processing of the models. Regarding triangular meshes, we present a method for the construction of progressive hulls, by suitable edge collapses; we use the generated hulls for the acceleration of intersection tests between the initial mesh and a line. Regarding tetrahedral meshes, we simplify meshes with associated vector fields; we construct progressive tetrahedral meshes by taking into account, while collapsing edges, both the geometry of the mesh and the associated field. Finally, we present an efficient algorithm for computing ray-tetrahedron intersection, which exploits Plücker coordinates to accelerate computations; this algorithm may be used for the efficient processing of progressive tetrahedral meshes.
Multi-modal Multi-label Semantic Indexing of Images Using Unlabeled Data

Automatic image annotation (AIA) refers to the association of words to whole images which is considered as a promising and effective approach to bridge the semantic gap between low-level visual features and high-level semantic concepts. In this paper, we formulate the task of image annotation as a multi-label multi class semantic image classification problem and propose a simple yet effective algorithm: hybrid self-learning with alternating space between uni-modality and bi-modality, which integrate multi-label boosting with asymmetric binary SVM-based active learning into a joint hierarchical classification framework to perform cross-modal image annotation by incorporating unlabeled images. We conducted experiments on a medium-sized image collection including about 15000 images from Corel Stock Photo CDs. The experimental results demonstrated that our proposed method can enhance a given annotation model by using unlabeled images to some extent, showing the effectiveness of the proposed algorithm and the feasibility of unlabeled data to help the annotation accuracy.