Miracle-dz/UniFAR-FTUs huggingface dataset:
Poststroke Apathy

In addition to acute motor, sensory, and language impairments, subacute and chronic neuropsychiatric disturbances after stroke can have major impact on activities of daily living. Cognitive impairment and depression are the most commonly reported neuropsychiatric symptoms, both occurring in approximately one third of patients after stroke. Apathy, most commonly defined as a syndrome of diminished goaldirected behavior, emotion, and cognition, is far less studied but has also been reported as a frequent consequence of stroke. Apathy can have negative impact on functional recovery, activities of daily living, general health, and quality of life. It can also lead to significant burden for caregivers. Apathy can occur as an independent syndrome, although it may also occur as a symptom of depression or dementia. Patients present with loss of motivation, concern, interest, and emotional response, resulting in a loss of initiative, decreased interaction with their environment, and a reduced interest in social life. Despite its potentially pervasive and negative consequences, the importance of poststroke apathy is difficult to interpret. Differences in study design, results, and interpretation have lead to a wide variety in reported characteristics, prevalence, and clinical impact. In this systematic review and meta-analysis, we aim to establish the impact of poststroke apathy by assessing the prevalence and the association with disability, depression, and cognitive impairment. In addition, the influence of lesion location on the occurrence of apathy and the possibilities for pharmacological treatment are systematically reviewed.
BAYESIAN APPROACH TO MULTI-AGENT SYSTEMS

Multi-agent systems are increasingly popular approach to control of complex industrial processes. The idea of distribution of a complex task into many semi-autonomous cooperating units has been formalized using many frameworks. In this paper, we review the close relation of distributed Bayesian decision making and multi-agent systems. The Bayesian methodology was primarily designed for systems with uncertainty. Therefore, a distinctive feature of a Bayesian agent is that all information is represented by probability density functions. Many algorithms derived for a single Bayesian decision maker are suitable for use in multiagent scenarios, however, more work is required to resolve issues related to Bayesian approach to communication and cooperation. The challenges for future research will be outlined. It is concluded that the Bayesian paradigm provides a solid, consistent framework for formalization of the task.
Feedback linearization for stabilization of a class of mobile, multibody systems

In this note we propose the input structure for a system of multi-articulated bodies and undertake the evaluation of some system input scenarios and the corresponding methods for which the proposed multibody system stabilization is possible. The system input structure analysis plays a major role in this regard. We concentrate attention on cases that allow for stabilization through feedback linearization.
SHM via topological derivative

This paper deals with the use of the topological derivative as an analysis tool for structural health monitoring, to locate the presence of flaws in a homogeneous material plate that is subject to guided elastic waves excitation. Using a numerical solver to compute the response of the system and defining a scalar objective function that measures the least squares difference between the measured and calculated signals, the topological derivative somehow describes the sensitivity of the objective function to localized perturbations of the material properties due to the presence of defects. Thus, defects are guessed to be located near the topological derivative peaks. This is somehow related to the minimization of the objective function and uses the whole physics of the problem (to compute the objective function), instead of a smaller amount of physical information, as conventional methods do. Here, we reconstruct small defects via the topological derivative by using multi-frequency synthetic data, for several representative configurations of the actuators and sensors, and several defect locations. Among these, some fairly demanding configurations are considered that are not accessible to conventional methods, such as actuators and sensors located very close to the plate boundary, and defects located beyond both elongated through-slits and elongated inclusions of a different material.
Reconfiguralbe multimedia accelerator for mobile systems

In this paper, we present a reconfigurable multimedia accelerator (RMA) weakly coupled to an application processor. RMA relies on explicit multithreading and streaming intrinsics to mitigate the effects of memory latency and efficient bandwidth requirements dictated by modern multimedia applications. RMA is designed in 65 nm and operates at a working frequency of 200 MHz.
Quantitative analysis of the effect of lesions of the subthalamic nucleus on intertemporal choice: further evidence for enhancement of the incentive value of food reinforcers

Recent evidence suggests that the subthalamic nucleus (STN) is involved in regulating the incentive value of food reinforcers. The objective of this study was to examine the effect of lesions of the STN on intertemporal choice (choice between reinforcers differing in size and delay). Rats with bilateral quinolinic acid-induced lesions of the STN (n = 15) or sham lesions (n = 14) were trained in a discrete-trials progressive delay schedule to press levers A and B for a sucrose solution. Responses on A delivered 50 μl of the solution after a delay dA; responses on B delivered 100 μl after a delay dB. dB increased across blocks of trials; dA was manipulated across phases of the experiment. Indifference delay, dB(50) (value of dB corresponding to 50% choice of B), was estimated for each rat in each phase, and linear indifference functions (dB(50) vs. dA) were derived. The STN-lesioned group showed a flatter slope of the indifference function (implying higher instantaneous reinforcer values) than the sham-lesioned group; the intercepts did not differ between the groups. The results agree with recent evidence for a role of the STN in incentive value. Unlike some earlier studies, these results do not indicate a role of the STN in delay discounting.
Discrimination of Dental Caries Using Colorimetric Characteristics of Fluorescence Spectrum

The feasibility of colorimetric parameters for the discrimination of the stages of dental caries based on a light-induced autofluorescence spectrum at a 405-nm excitation wavelength was investigated. The fluorescence spectra of 4 groups of tooth samples (10 sound, 10 early-stage decay, 14 established decay, and 10 severe decay), which were classified by the International Caries Detection and Assessment System, were experimentally measured in vitro. The carious lesion samples had an additional fluorescence peak at around 627 nm. The mathematical relation of the fluorescence spectrum and human color perception was established and computed. With increasing severity, the fluorescence color changed from green to yellow according to the colorimetric parameters of the CIE 1931 (x, y) chromaticity coordinates and dominant wavelengths. The results from a one-way ANOVA of the dominant wavelength showed a statistically significant difference among the 4 classified groups. The colorimetric parameters of the light-induced fluorescence spectrum can potentially be applied to evaluate the various carious levels.
Directed Evolution of Lectins with Sugar-binding Specificity for 6-Sulfo-galactose*

Background: 6-sulfo-galactose is a potential marker of various diseases, but no useful probes to detect this glycoepitope have been available. Results: Mutants with novel affinity for 6-sulfo-galactose were engineered from an R-type galactose-binding lectin. Conclusion: We succeeded in providing a method to create probes for 6-sulfo-galactose by a molecular evolutionary strategy. Significance: The tools developed in our study will be especially useful in the context of sulfoglycomics. 6-sulfo-galactose (6S-Gal) is a prevalent motif observed in highly sulfated keratan sulfate, which is closely associated with the glioblastoma malignancy while acting as a critical determinant for endogenous lectins. However, facile detection of this unique glycoepitope is greatly hampered because of a lack of appropriate probes. We have previously reported tailoring an α2-6-linked sialic acid-binding lectin from a ricin-B chain-like galactose-binding protein, EW29Ch, by a reinforced ribosome display system following an error-prone PCR. In this study, we challenged the creation of novel lectins to recognize 6S-Gal-terminated glycans by incorporating a high-throughput screening system with a glycoconjugate microarray. After two rounds of selection procedures, 20 mutants were obtained and 12 were then successfully expressed in Escherichia coli, 8 of which showed a significant affinity for 6′-Sulfo-LN (6-O-sulfo-Galβ1–4GlcNAc), which the parental EW29Ch lacked. Analysis of two representative mutants by frontal affinity chromatography revealed a substantial affinity (Kd ∼3 μm) for a 6S-Gal-terminated glycan. On the basis of the observation that all eight mutants have a common mutation at Glu-20 to Lys, site-directed mutagenesis experiments were performed focusing on this aspect. The results clearly indicated that the E20K mutation is necessary and sufficient to acquire the specificity for 6S-Gal. We also confirmed a difference in binding between E20K and EW29Ch to CHO cells, in which enzymes to catalyze the synthesis of 6S-Gal were overexpressed. The results clearly demonstrate that these mutants have potential to distinguish between cells containing different amounts of 6S-Gal-terminated glycans. This new technology will be used to provide novel tools essential for sulfoglycomics.
High permeability cores to optimize the stimulation of deeply located brain regions using transcranial magnetic stimulation

Efficient stimulation of deeply located brain regions with transcranial magnetic stimulation (TMS) poses many challenges, arising from the fact that the induced field decays rapidly and becomes less focal with depth. We propose a new method to improve the efficiency of TMS of deep brain regions that combines high permeability cores, to increase focality and field intensity, with a coil specifically designed to induce a field that decays slowly with increasing depth. The performance of the proposed design was investigated using the finite element method to determine the total electric field induced by this coil/core arrangement on a realistically shaped homogeneous head model. The calculations show that the inclusion of the cores increases the field's magnitude by as much as 25% while also decreasing the field's decay with depth along specific directions. The focality, as measured by the area where the field's norm is greater than of its maximum value, is also improved by as much as 15% with some core arrangements. The coil's inductance is not significantly increased by the cores. These results show that the presence of the cores might make this specially designed coil even more suited for the effective stimulation of deep brain regions.
Clinical Investigation : Genitourinary Cancer Cardiovascular Comorbidity and Mortality in Men With Prostate Cancer Treated With Brachytherapy-Based Radiation With or Without Hormonal Therapy

Cardiovascular Comorbidity and Mortality in Men With Prostate Cancer Treated With Brachytherapy-Based Radiation With or Without Hormonal Therapy Akash Nanda, MD, PhD,* Ming-Hui Chen, PhD,y Brian J. Moran, MD,z Michelle H. Braccioforte, MPH,z and Anthony V. D’Amico, MD, PhDx *Department of Radiation Oncology, MD Anderson Cancer Center Orlando, Orlando, Florida; yDepartment of Statistics, University of Connecticut, Storrs, Connecticut; zProstate Cancer Foundation of Chicago, Westmont, Illinois; and xDepartment of Radiation Oncology, Brigham and Women’s Hospital/Dana-Farber Cancer Institute, Boston, Massachusetts
2016 Ieee International Conference on Big Data (big Data) High-performance Design of Apache Spark with Rdma and Its Benefits on Various Workloads

—The in-memory data processing framework, Apache Spark, has been stealing the limelight for low-latency interactive applications, iterative and batch computations. Our early experience study [17] has shown that Apache Spark can be enhanced to leverage advanced features (e.g., RDMA) on high-performance networks (e.g., InfiniBand and RoCE) to improve the performance of shuffle phase. With the fast evolving of the Apache Spark ecosystem, the Spark architecture has been changing a lot. This motivates us to investigate whether the earlier RDMA design can be adapted and further enhanced for the new Apache Spark architecture. We also aim to improve the performance for various Spark workloads (e.g., Batch, Graph, SQL). In this paper, we present a detailed design for high-performance RDMA-based Apache Spark on high-performance networks. We conduct systematic performance evaluations on three modern clusters (Chameleon, SDSC Comet, and an in-house cluster) with cutting-edge InfiniBand technologies, such as latest IB EDR (100 Gbps) network, recently introduced Single Root I/O Virtualization (SR-IOV) technology for IB, etc. The evaluation results show that compared to the default Spark running with IP over InfiniBand (IPoIB), our proposed design can achieve up to 79% performance improvement for Spark RDD operation benchmarks (e.g., GroupBy, SortBy), up to 38% performance improvement for batch workloads (e.g., Sort and TeraSort in Intel HiBench), up to 46% performance improvement for graph processing workloads (e.g., PageRank), up to 32% performance improvement for SQL queries (e.g., Aggregation, Join) on varied scales (up to 1,536 cores) of bare-metal IB clusters. Performance evaluations on SR-IOV enabled IB clusters also show 37% improvement achieved by our RDMA-based design. Our RDMA-based Spark design is implemented as a pluggable module and it does not change any Spark APIs, which means that it can be combined with other existing enhanced designs for Apache Spark and Hadoop proposed in the community. To show this, we further evaluate the performance of a combined version of 'RDMA-Spark+RDMA-HDFS' and the numbers show that the combination can achieve the best performance with up to 82% improvement for Intel HiBench Sort and TeraSort on SDSC Comet cluster.
Topography of cerebral atrophy in early Huntington’s disease: a voxel based morphometric MRI study

Objectives: To analyse grey matter changes in early stages of Huntington’s disease using magnetic resonance imaging (MRI) and the technique of voxel based morphometry (VBM). Methods: Forty four patients with a molecularly confirmed clinical diagnosis of Huntington’s disease based on the presence of motor signs were included in the study. Patients were clinically rated using the Unified Huntington’s Disease Rating Scale; all were in early clinical stages of the disease (that is, Shoulson stages I and II). High resolution volume rendering MRI scans (MP-RAGE) were acquired. MRI data were volumetrically analysed in comparison to an age matched normal database by VBM, using statistical parametric mapping (SPM99). Results: In Huntington’s disease, robust regional decreases in grey matter density (p<0.001, corrected for multiple comparisons)—that is, atrophy—were found bilaterally in striatal areas as well as in the hypothalamus and the opercular cortex, and unilaterally in the right paracentral lobule. The topography of striatal changes corresponded to the dorso-ventral gradient of neuronal loss described in neuropathological studies. Stratification according to clinical severity showed a more widespread involvement extending into the ventral aspects of the striatum in the group of more severely affected patients. Conclusions: The topography of cerebral volume changes associated with Huntington’s disease can be mapped using VBM. It can be shown that cerebral grey matter changes co-vary with clinical severity and CAG repeat length.
Evaluating a Trainable Sentence Planner for a Spoken Dialogue Travel System

This paper reports on the evaluation of a trainable sentence planner. We compare a trainable sentence planner with a currently operational hand-crafted template-based generator, two rule-based generators and two baseline generators. We show that the trainable sentence planner performs as well as the hand-crafted generator and better than the rule-based and baseline generators. Evaluating a Trainable Sentence Planner for a Spoken Dialogue Travel System Paper-ID: ACL-2001-0315
An approach of hypertension prevalence in a sample of 5381 Portuguese children and adolescents. The AVELEIRA registry. “Hypertension in Children”

Abstract Introduction. The distribution of blood pressure (BP) in children and adolescents remains relatively unknown. Thus, it is imperative to ascertain BP distribution at a young age, which constitutes the main objective of this registry. Methods. Cross-sectional assessment of BP in 5381 Portuguese children and adolescents, mean age 12.50±3.23 years (4–18 years), body mass index (BMI) 19.65±4.00 kg/m2 (9.37–60.30 kg/m2), mostly male (4519), mean age 12.70±3.16 years, and with 862 females, mean age 11.44±3.34 years. BP and heart rate were measured three times after a 10-min resting period, with a validated automatic blood pressure monitor (OMRON 705IT) and an appropriately sized cuff over the brachial artery. About 30% of the youngsters were amateur registered athletes and 70% were beginning their sportive activity at the time of evaluation. Results. BP distribution was 12.8% stage 1 hypertension, 21.6% high-normal, and 65.6% normal (similar between genders). Registered athletes and subjects beginning their sports activity revealed different hypertension prevalence (9.8% vs 14.3%, respectively; p < 0.0001). Overweight was found in 7.8%. Hypertension and high-normal BP increased with increasing BMI. Body weight classification was independently associated with hypertension and high-normal BP. Registered sportive practice was independently associated with a reduction in hypertension prevalence. Conclusions. The proportion of children with BP above the 90th percentile was high, with an overall prevalence of hypertension of 12.8%, independent of gender and related to overweight. The implications of these observations are even more important when we consider the epidemiology of hypertension in Portugal and its link with stroke as the leading cause of death and disability.
A path planning approach to (dis)assembly sequencing

The paper describes a new method for simultaneously (dis)assembly sequencing and path planning. Indeed, both are parts of a same problem that can be formulated in a general path planning framework. Based on this formulation, the algorithm proposed in this paper extends a popular sampling-based path planner, RRT, to solve general (dis)assembly planning problems involving objects with arbitrary shapes, and possibly requiring non-monotonic (dis)assembly sequences. The method does not require complex geometric computations, and is easy to implement. Experimental results show the efficiency of the method for solving a large class of problems.
Sensory Competition in the Face Processing Areas of the Human Brain

The concurrent presentation of multiple stimuli in the visual field may trigger mutually suppressive interactions throughout the ventral visual stream. While several studies have been performed on sensory competition effects among non-face stimuli relatively little is known about the interactions in the human brain for multiple face stimuli. In the present study we analyzed the neuronal basis of sensory competition in an event-related functional magnetic resonance imaging (fMRI) study using multiple face stimuli. We varied the ratio of faces and phase-noise images within a composite display with a constant number of peripheral stimuli, thereby manipulating the competitive interactions between faces. For contralaterally presented stimuli we observed strong competition effects in the fusiform face area (FFA) bilaterally and in the right lateral occipital area (LOC), but not in the occipital face area (OFA), suggesting their different roles in sensory competition. When we increased the spatial distance among pairs of faces the magnitude of suppressive interactions was reduced in the FFA. Surprisingly, the magnitude of competition depended on the visual hemifield of the stimuli: ipsilateral stimulation reduced the competition effects somewhat in the right LOC while it increased them in the left LOC. This suggests a left hemifield dominance of sensory competition. Our results support the sensory competition theory in the processing of multiple faces and suggests that sensory competition occurs in several cortical areas in both cerebral hemispheres.
Child Impairment and Parenting Self-Efficacy in Relation to Mothers’ Views of ADHD Treatments

Objective: This study assessed the relations of child impairment and parenting self-efficacy with parental views of the acceptability and effectiveness of behavioral, medication, and combined treatments for child ADHD. Child impairment and parenting self-efficacy were also assessed in relation to the effectiveness views of specific behavioral treatment strategies. Method: Ninety-five mothers of children with ADHD completed questionnaires assessing child impairment, parenting self-efficacy, perceptions of the overall acceptability and effectiveness of ADHD treatments, and views of the effectiveness of specific behavioral treatment strategies. Results: Hierarchical linear modeling using child impairment and parenting self-efficacy as predictors of treatment views suggests that mothers viewed combined treatments as most acceptable and effective when their child was more impaired, and mothers with higher parenting self-efficacy rated behavioral treatment strategies as more effective. Conclusion: Child impairment and parenting self-efficacy are related to perceptions of the acceptability and/or effectiveness of ADHD treatments.
Averaging Model Forecasts and Expert Forecasts: Why Does It Work?

This paper addresses a situation in which a manager has forecasts of country-specific stock-keeping unit (SKU)-level sales data from both a statistical model and from a range of experts. Empirical evidence suggests that averaging model forecasts and expert forecasts could give more accuracy than the individual forecasts do. At the same time, empirical evidence demonstrates that expert forecasts tend to be biased. So, why is it that this average could work? This paper assumes that expert forecasts can be decomposed into a judgmental bootstrapping equation, to be created by the manager, and a part based on unobserved intuition. When the bootstrapping equation dominates the intuition, it is this underlying model for the expert that can make the combined average forecast more accurate. An illustration for no less than 1,221 cases supports this conjecture.
Image-based stereoscopic stylization

We present a method to generate stylized stereo imagery that effectively communicates shape and distance of the depicted scene objects. We use computer vision techniques to analyze real stereo image pairs. In particular, a region based stereo matching algorithm with symmetrical treatment of occlusions is used to extract a disparity map and successively the depth information of the scene. The reference image is color segmented for the purpose of color stylization and an algorithm combining intensity image edges and depth discontinuities is applied to depict dominant object contours in the image. We use disparity information to propagate stylized color segments to the second view together with the object outlining contours. The stylized image pairs are consistent across the two views and can be easily fused for stereoscopic viewing. The stereoscopic image fusion provides an extra dimension of depth that is absent on the individual images.