Miracle-dz/UniFAR-FTUs huggingface dataset:
An Examination of Women Ex-Offenders With Methadone Histories

Criminal (drug and prostitution) charges, employment levels (weekly hours), recent substance use in the past 6 months, and primary sources of income were examined among a sample (n = 106) of women ex-offenders who had opioid use disorders with and without methadone histories. A general linear model was tested to examine differences in relation to methadone use history. Results from a one-way MANCOVA found that those with methadone histories reported significantly higher levels of drug and prostitution charges than those without any methadone history, but no significant differences in terms of weekly hours of employment or recent substance use were observed between groups. Women ex-offenders with methadone histories reported various sources of income beyond employment, and proportionally, more of these women reported prostitution as a primary source of income. Findings suggest that methadone maintenance treatments are not sufficient in meeting the needs of women ex-offenders.
Automated design strategy for high performance mixed signal circuits

This paper discusses an automated design strategy for high performance mixed signal circuit. The reduction of the number of circuit types is firstly required for the smart automated design and addressing low voltage operation, scalability of power dissipation and performance are strongly recommended to select the circuits. A SAR ADC is reviewed as a strong candidate for the selected core of ADC. A fundamental issue of conventional layout method, place and route are discussed. Advantage of MOM capacitor with pitch aligned layout with regularity is shown. The basic idea for the automated design flow in analog circuit design is proposed.
Neurocognition in individuals at high familial risk of mood disorders with or without subsequent onset of depression

Background Neurocognitive performance deficits have been observed in mood disorder patients and their unaffected relatives and may therefore qualify as endophenotypes. However, the precise time course of neurocognitive deficits has not been studied so that it is unknown whether neurocognitive abnormalities reflect the early effects of familial vulnerability to mood disorders or if they emerge at illness onset. Method A neuropsychological test battery was administered at baseline and after a 2-year follow-up interval in 111 initially unaffected young adults at high familial risk of mood disorders and 93 healthy controls (HC). During the follow-up period, 20 high-risk subjects developed major depressive disorder (HR-MDD), with the remainder remaining well (HR-well). Linear mixed-effects models were used to investigate differences and longitudinal changes in the domains of attentional processing, working memory, verbal learning and memory, and cognitive flexibility. Results Reduced long delay verbal memory and extradimensional set-shifting performance across both time points were found in the HR-well group relative to controls. The HR-MDD group displayed decreased extradimensional set-shifting abilities across both time points as compared with the HC group only. There were no significant performance differences between the two high-risk groups. Conclusions Reduced verbal memory and cognitive flexibility are familial trait markers for vulnerability to mood disorders in individuals with a close family history of bipolar disorder. Both neurocognitive performance deficits appear to be relatively stable over a 2-year time period and do not appear to be linked to the onset of MDD. These findings support their use as stable quantitative endophenotypes for mood disorders.
Getting Down to Details: Using Theories of Cognition and Learning to Inform Tangible User Interface Design

Many researchers have suggested that tangible user interfaces (TUIs) have potential for supporting learning. However, the theories used to explain possible effects are often invoked at a very broad level without explication of specific mechanisms by which the affordances of TUIs may be important for learning processes. Equally problematic, we lack theoretically grounded guidance for TUI designers as to what design choices might have significant impacts on learning and how to make informed choices in this regard. In this paper, we build on previous efforts to address the need for a structure to think about TUI design for learning by constructing the Tangible Learning Design Framework. We first compile a taxonomy of five elements for thinking about the relationships between TUI features, interactions and learning.We then briefly review cognitive, constructivist, embodied, distributed and social perspectives on cognition and learning and match specific theories to the key elements in the taxonomy to determine guidelines for design. In each case, we provide examples from previous work to explicate our guidelines; where empirical work is lacking, we suggest avenues for further research. Together, the taxonomy and guidelines constitute the Tangible Learning Design Framework. The framework advances thinking in the area by highlighting decisions in TUI design important for learning, providing initial guidance for thinking about these decisions through the lenses of theories of cognition and learning, and generating a blueprint for research on testable mechanisms of action by which TUI design can affect learning.
Fast bootstrapping of LVCSR systems with multilingual phoneme sets

In this paper we described an e cient method to bootstrap continuously spoken, large vocabulary speech recognition systems by multilingual phoneme sets. To evaluate this techniques we collected the multilingual database GlobalPhone which currently consists of 9 di erent languages. A multilingual recognizer (MULTI) based on the four languages German, English, Japanese and Spanish was developed to serve as a source system. Likewise this system is very useful for language identi cation and achieves 100% language identi cation rate. Based on the MULTI system we evaluated our bootstrap technique on such completely di erent languages as Chinese, Croatian, and Turkish.
Real-Time Halfway Domain Reconstruction of Motion and Geometry

We present a novel approach for real-time joint reconstruction of 3D scene motion and geometry from binocular stereo videos. Our approach is based on a novel variational halfway-domain scene flow formulation, which allows us to obtain highly accurate spatiotemporal reconstructions of shape and motion. We solve the underlying optimization problem at real-time frame rates using a novel data-parallel robust non-linear optimization strategy. Fast convergence and large displacement flows are achieved by employing a novel hierarchy that stores delta flows between hierarchy levels. High performance is obtained by the introduction of a coarser warp grid that decouples the number of unknowns from the input resolution of the images. We demonstrate our approach in a live setup that is based on two commodity webcams, as well as on publicly available video data. Our extensive experiments and evaluations show that our approach produces high-quality dense reconstructions of 3D geometry and scene flow at real-time frame rates, and compares favorably to the state of the art.
Human spermatozoa contain multiple targets for protein S‐nitrosylation: An alternative mechanism of the modulation of sperm function by nitric oxide?

Nitric oxide (NO) enhances human sperm motility and capacitation associated with increased protein phosphorylation. NO activates soluble guanylyl cyclase, but can also modify protein function covalently via S‐nitrosylation of cysteine. Remarkably, this mechanism remains unexplored in sperm although they depend on post‐translational protein modification to achieve changes in function required for fertilisation. Our objective was to identify targets for S‐nitrosylation in human sperm. Spermatozoa were incubated with NO donors and S‐nitrosylated proteins were identified using the biotin switch assay and a proteomic approach using MS/MS. 240 S‐nitrosylated proteins were detected in sperm incubated with S‐nitroso‐glutathione. Minimal levels were observed in glutathione or untreated samples. Proteins identified consistently based on multiple peptides included established targets for S‐nitrosylation in other cells e.g. tubulin, GST and HSPs but also novel targets including A‐kinase anchoring protein (AKAP) types 3 and 4, voltage‐dependent anion‐selective channel protein 3 and semenogelin 1 and 2. In situ localisation revealed S‐nitrosylated targets on the postacrosomal region of the head and throughout the flagellum. Potential targets for S‐nitrosylation in human sperm include physiologically significant proteins not previously reported in other cells. Their identification will provide novel insight into the mechanism of action of NO in spermatozoa.
A low-complexity power-efficient synchronization scheme for wireless communication system

This paper presents a low-cost power-efficient scheme and circuitry for synchronizing in a wireless communication system. By reusing the over-sampling circuitry for frame-synchronization of the wireless system, we can achieve bit synchronization without using PLL CDR Architecture. The over-sampling circuitry is turned-on periodically to achieve low-power. The scheme has been used and verified in a low-power baseband IC. The only overhead is just some logic gates to add-on for the system. The chip is fabricated using Chartered 0. 18µm CMOS process and total baseband area is just 300µm × 300µm. The whole chip area with analogue modulator/demodulator is only 2000µm × 2000µm.
Evaluating a Robust Parser for Italian

Evaluation of performance of a NLP system is crucially related to the evaluation of the core parsing component. Large scale evaluation is thus required to fully measure the quality of the underlying grammatical description and the robustness and speed of the parser. The evaluation of performances requires the availability of large sets of sentences where syntactic information (possibly on a theory free basis) has been manually annotated. Since existing corpora are annotated on a constituency oriented basis (e.g. Penn TreeBank for English), the evaluation of parsing systems based on different paradigms requires a mapping between the different grammatical representations. Furthermore, the parse description (usually as a set of trees and/or forests) is unsuited for some grammatical information (i.e. dependencies or clause boundaries) that is usually extracted and recognized in robust parsers (e.g. chunker or link grammar parsers). In this paper the experience in the evaluation of a robust parser for the Italian language is described. The evaluation framework (i.e. development of specific test data, performance indexes and results) will be defined and discussed. Aspects and outcomes related to systematic criteria of creation and annotations of large test data sets will be presented.
Cancer Patient Navigator Tasks across the Cancer Care Continuum

Cancer patient navigation (PN) programs have been shown to increase access to and utilization of cancer care for poor and underserved individuals. Despite mounting evidence of its value, cancer patient navigation is not universally understood or provided. We describe five PN programs and the range of tasks their navigators provide across the cancer care continuum (education and outreach, screening, diagnosis and staging, treatment, survivorship, and end-of-life). Tasks are organized by their potential to make cancer services understandable, available, accessible, affordable, appropriate, and accountable. Although navigators perform similar tasks across the five programs, their specific approaches reflect differences in community culture, context, program setting, and funding. Task lists can inform the development of programs, job descriptions, training, and evaluation. They also may be useful in the move to certify navigators and establish mechanisms for reimbursement for navigation services.
Synchronized neural oscillations and the pathophysiology of Parkinson's disease.

PURPOSE OF THE REVIEW Developments in functional neurosurgery for movement disorders and recent advances in electrophysiological techniques have allowed important insights into the role of oscillations in corticobasal ganglia circuits, both in health and in neurological disease states. Here we review recent developments in our understanding of how abnormally synchronized oscillatory activity within the corticobasal ganglia loop may play a key role in the pathophysiology of cognitive and motor phenotypes in Parkinson's disease. RECENT FINDINGS Recent developments highlight the motor and non-motor roles of α, β and γ oscillations in the context of Parkinson's disease. They also emphasize the importance of oscillatory coupling between basal ganglia and cortex and draw attention to the importance of interactions between different frequency bands. SUMMARY Oscillatory activities across multiple frequency bands and their cross-frequency interactions within spatially segregated loops of the basal ganglia-thalamo-cortical system may relate to distinct components of clinical impairment, both motor and non-motor. It is hoped that this characterization will lead to improved interventions like deep brain stimulation, tailored to specific components of clinical impairment and their associated spatial and spectral signatures.
Real-time classification of auditory sentences using evoked cortical activity in humans

Objective. Recent research has characterized the anatomical and functional basis of speech perception in the human auditory cortex. These advances have made it possible to decode speech information from activity in brain regions like the superior temporal gyrus, but no published work has demonstrated this ability in real-time, which is necessary for neuroprosthetic brain–computer interfaces. Approach. Here, we introduce a real-time neural speech recognition (rtNSR) software package, which was used to classify spoken input from high-resolution electrocorticography signals in real-time. We tested the system with two human subjects implanted with electrode arrays over the lateral brain surface. Subjects listened to multiple repetitions of ten sentences, and rtNSR classified what was heard in real-time from neural activity patterns using direct sentence-level and HMM-based phoneme-level classification schemes. Main results. We observed single-trial sentence classification accuracies of 90% or higher for each subject with less than 7 minutes of training data, demonstrating the ability of rtNSR to use cortical recordings to perform accurate real-time speech decoding in a limited vocabulary setting. Significance. Further development and testing of the package with different speech paradigms could influence the design of future speech neuroprosthetic applications.
Adaptation of guinea pig diaphragm muscle to aging and endurance training.

LIEBERMAN,DAVID A. , LEO C.MAXWELL,ANDJOHN A. FAULKtype was calculated. The effects of age were determined by NER. Adaptation of guinea pig diaphragm muscle to aging and endurance comparison of 6-week, 14-week, and mature animals (older training. Am. J. Physiol. 222(3) : 556-560. 1972. -The percentage , than 40 weeks). The effects of endurance training were determined by comparison of guinea pigs exercised on a motordriven treadmill for 8 weeks with age-matched controls. of red and white fibers in diaphragm muscle of guinea pigs 6, 14, and 40 weeks of age was determined by succinic dehydrogenase activity. The percentage of red fibers decreased with increase in age. The percentages were : 86 y0 at 6 weeks, 70 y0 at 14 weeks, and 6597, at maturity. Mean fiber area increased with age in proportion to increases in body and diaphragm weights. Following 8 weeks of exercise, the percentage of red fibers in young animals was maintained while it increased by 20y0 in mature animals. These effects may be associated with the role of the guinea pig diaphragm in temperature regulation and ventilation. METHODS
Getting by with a Little Help from the Crowd : Optimal Human Computation Approaches to Social Image Labeling

Validating user tags helps to refine them, making them more useful for finding images. In the case of interpretation-sensitive tags, however, automatic (i.e., pixel-based) approaches cannot be expected to deliver optimal results. Instead, human input is key. This paper studies how crowdsourcing-based approaches to image tag validation can achieve parsimony in their use of human input from the crowd, in the form of votes collected from workers on a crowdsourcing platform. Experiments in the domain of social fashion images are carried out using the dataset published by the Crowdsourcing Task of the Mediaeval 2013 Multimedia Benchmark. Experimental results reveal that when a larger number of crowd-contributed votes are available, it is difficult to beat a majority vote. However, additional information sources, i.e., crowdworker history and visual image features, allow us to maintain similar validation performance while making use of less crowd-contributed input. Further, investing in “expensive" experts who collaborate to create definitions of interpretation-sensitive concepts does not necessarily pay off. Instead, experts can cause interpretations of concepts to drift away from conventional wisdom. In short, validation of interpretation-sensitive user tags for social images is possible, with “just a little help from the crowd. "
Measuring protein reduction potentials using 15N HSQC NMR spectroscopy†

NMR spectroscopy was used to measure reduction potentials of four redox proteins by following multiple 15N HSQC protein resonances across a titration series using mixtures of oxidised and reduced glutathione. Results for PDI a, PDI ab and DsbA agree with the literature and our result for ERp18 confirms this protein as an oxidoreductase of comparable or greater reducing strength than PDI a.
A Mind Model for an Affective Computer

， †† † Summary A pragmatic emotional model is one of obligatory subjects for building a humanoid computer. This paper presents a conception of a Mental State Transition Network Model using psychological research for reference [1]. The ongoing work proposes a novel approach to detect human emotions. According to Pluchik’s basic emotional classification, we defined nine basic emotional states and carried out a series of psychological investigations [2]. By the results of experiments we provide a new way to predict coming human’s emotions depending on the various currents emotional states under various reinforcements. By means of statistic data derived from 227 questionnaires, the transitions in distribution among the emotions and relationships between internal mental situations and external stimuli are concluded. The high precision achieved in our evaluating experiments shows the model is helping in recognition and synthesis of human emotion.
Statistical Learning for Shape Applications

Statistical methods are well suited to the large amounts of data typically involved in digital shape applications. In this paper, we look at two statistical learning methods related to digital shape processing. The first, neural meshes, learns the shape of a given point cloud – the surface reconstruction problem – in O(n) time. We present an alternate implementation of the algorithm that takes O(n log n) time. Secondly, we present a simple method to automatically learn the correct orientation of a shape in an image from a database of images with correctly oriented shapes.
Reduction of a conductance-based model for individual neurons

We investigated schemes to systematically reduce the number of of different of differential equations required for biophysically realistic neuron model. The original scheme is invented by Thomas Kepler in 1992, and it is used in many neuronal models, such as Hodgkin-Huxley, A-current model and a stomatogastric neuron model. The general idea of this scheme is to inverse all the gating variable equations to get corresponding equivalent potential. We base the reduction on the fact that some of those potentials have similar wave forms with the membrane potential or the other equivalent potentials. We use singular perturbation theory and principal component analysis to analyze the reduction. We successfully reduce the phasedimensionality of a realistic HVC neuron model from 12 to 3. The membrane potential and equivalent potentials have identical behavior in both the reference and reduced model and it holds for arbitrary injected current under certain parameters.
SASSY: A Design for a Scalable Agent-Based Simulation System using a Distributed Discrete Event Infrastructure

The PDES literature offers a rich set of techniques for distributed and efficient simulation. However, there is a growing need for simulators that support agent-based applications, and PDES systems are not always well suited for these applications. Example agent-based applications include simulation of biological systems such as ants and bees, multi-robot systems and battlefield simulations. The robotics research community has developed agent-based simulators that provide useful APIs for agent applications. However, such simulators have performance limitations, and they do not scale well. Our approach is to provide middleware between an agent-based API and a PDES simulation kernel. The result is a simulation system that offers an agent-based API for the programmer to a high performance PDES system. Here we describe our design and initial implementation of SASSY, the scalable agents simulation system. We describe our initial implementation and compare the design with related approaches