Miracle-dz/UniFAR-FTUs huggingface dataset:
Imaging-Based Endovascular Therapy for Acute Ischemic Stroke due to Proximal Intracranial Anterior Circulation Occlusion Treated Beyond 8 Hours From Time Last Seen Well: Retrospective Multicenter Analysis of 237 Consecutive Patients

Background and Purpose— Current selection criteria for intra-arterial therapies in the anterior circulation use time windows of 8 hours. Modern neuroimaging techniques have identified individuals with salvageable penumbra who present beyond this timeframe. We sought to assess safety, procedural, and clinical outcomes of MRI or CT perfusion imaging-based endovascular therapy in patients with anterior circulation stroke treated beyond 8 hours from time last seen well. Methods— We conducted a multicenter retrospective review of consecutive patients meeting the following criteria: (1) acute proximal intracranial anterior circulation occlusion; (2) endovascular treatment initiated >8 hours from time last seen well; and (3) treatment selection based on MRI or CT perfusion imaging. Results— Two hundred thirty-seven patients were identified (mean age, 63.8±16 years; mean baseline National Institutes of Health Stroke Scale, 15±5.5; mean time last seen well to treatment, 15±11.2 hours; male gender, 46%). Successful revascularization was achieved in 175 of 237 (73.84%) patients. Parenchymal hematoma occurred in 21 of 237 (8.86%) patients. The 90-day mortality rate was 21.5% (51 of 237). The rate of good outcomes was 45% (100 of 223) in the 223 patients with available modified Rankin Scale data at 90 days or time of hospital discharge. In multivariate analyses, age (OR, 0.96; 95% CI, 0.94 to 0.98; P=0.002), admission National Institutes of Health Stroke Scale (OR, 0.93; 0.87 to 0.98; P=0.016), and successful revascularization (OR, 4.32; 1.99 to 9.39; P<0.0001) were identified as independent predictors of good outcomes. Conclusions— Endovascular therapy can be instituted with acceptable safety beyond 8 hours from time last seen well when selection is based on advanced neuroimaging. Successful revascularization is significantly associated with higher rates of good outcomes. The benefit of this approach compared with standard medical therapy should be assessed in a prospective randomized trial.
Robust blind PIC with adaptive despreader and improved interference estimator

An effective design of multistage parallel interference cancellation (PIC) receiver using blind adaptive (BA) despreader and pre‐respreader interference estimator for uplink CDMA is proposed and analysed. A novel algorithm is designed, which exploits constant modulus (CM) property of the users' transmitted signals and inherent channel condition to perform adaptive despreading based on minimum error variance criteria. This is carried out by BA weighting of each chip signal for accurate tracking of the desired user's signal power and hence for more improved data detection at the output of each stage of PIC. Furthermore, the despreader weights are used within the adaptive pre‐respreader interference estimation and cancellation to obtain online scaling factors during every symbol period, without any knowledge of users' channels or the use of training sequences. It is found that this way of estimation is optimal in minimum mean squared error sense, and hence, significant reduction in interference and noise variance is observed in detection and estimation of the desired users' signals compared with conventional PIC. Bit error probability of the proposed PIC is obtained using Gaussian Approximation method. Extensive simulation results are shown, which demonstrate impressive performance advantage in fading environments, high system loading, and severe near far conditions. Copyright © 2008 John Wiley & Sons, Ltd.
Pilot Study: Brief Posttrauma Nightmare Treatment for Persons With Bipolar Disorder

Previous research on an efficacious cognitive-behavioral treatment for posttrauma nightmares and sleep disturbances (exposure, relaxation, and rescripting therapy; ERRT) has not tested the treatment in individuals with bipolar disorder. However, research suggests that individuals diagnosed with bipolar disorder are at increased risk for trauma exposure and development of posttrauma symptoms. The present pilot study sought to examine the acceptability and preliminary efficacy of a modified version of ERRT (ERRT-B) on reducing the frequency and severity of nightmares and improving sleep quality for 7 trauma-exposed individuals diagnosed with bipolar disorder who also reported frequent posttrauma nightmares (experienced on average for 16 years). Participants attended 5 weeks of ERRT-B and completed baseline, posttreatment, and 3-month follow-up assessments to measure changes in nightmare frequency, nightmare severity, and associated symptoms. Large effect sizes were observed for nightmare frequency, nightmare severity, and posttraumatic stress disorder symptoms, with 6 participants reporting zero nightmares at the 3-month follow-up assessment. Improvements in depression, global sleep quality, and insomnia severity were mixed. Results obtained from this study offer preliminary evidence in support of ERRT-B in reducing nightmare frequency and severity, and posttraumatic stress disorder symptoms. These results suggest clinical utility for the treatment of trauma-related nightmares in individuals with bipolar disorder and encourage more research.
The Impact of Diabetes Mellitus on Vascular Biomarkers in Patients with End-Stage Renal Disease

Purpose Diabetes mellitus (DM) is the most common cause of end-stage renal disease (ESRD) and an important risk factor for cardiovascular (CV) disease. We investigated the impact of DM on subclinical CV damage by comprehensive screening protocol in ESRD patients. Materials and Methods Echocardiography, coronary computed tomography angiogram, 24-h ambulatory blood pressure monitoring, and central blood pressure with pulse wave velocity (PWV) were performed in 91 ESRD patients from the Cardiovascular and Metabolic disease Etiology Research Center-HIgh risk cohort. Results The DM group (n=38) had higher systolic blood pressure than the non-DM group (n=53), however, other clinical CV risk factors were not different between two groups. Central aortic systolic pressure (148.7±29.8 mm Hg vs. 133.7±27.0 mm Hg, p= 0.014), PWV (12.1±2.7 m/s vs. 9.4±2.1 m/s, p<0.001), and early mitral inflow to early mitral annulus velocity (16.7±6.4 vs. 13.7±5.9, p=0.026) were higher in the DM group. Although the prevalence of coronary artery disease (CAD) was not different between the DM and the non-DM group (95% vs. 84.4%, p=0.471), the severity of CAD was higher in the DM group (p=0.01). In multivariate regression analysis, DM was an independent determinant for central systolic pressure (p=0.011), PWV (p<0.001) and the prevalence of CAD (p=0.046). Conclusion Diabetic ESRD patients have higher central systolic pressure and more advanced arteriosclerosis than the non-DM control group. These findings suggest that screening for subclinical CV damage may be helpful for diabetic ESRD patients.
Response to the Special Issue: The Utility of the Pattern of the Strengths and Weaknesses Approach

Unlike abilityachievement discrepancy and response-to-intervention approaches, the processing strengths and weaknesses (PSW) approach is the only empirically based approach that attempts to identify the pattern of deficit in the basic psychological processes that interferes with academic achievement for children with specific learning disabilities (SLD). If used in combination with RTI, any child who meets PSW criteria would be more likely to be correctly identified as having SLD because both IDEA (2004) statutory (i.e., SLD definition) and regulatory (i.e., SLD method) requirements would be met. In addition, understanding a childs PSW could lead directly to differentiated instruction and targeted interventions for affected children. Although PSW research has been emerging in recent years, this is the first special issue devoted to empirical examination of the PSW method. The articles presented here attest to the value and potential of a PSW approach to identifying SLD, but the critique presented here suggests a rigid psychometric PSW approach is insufficient for identifying SLD and other disorders. Implications for clinical practice and future research will be elucidated.
Demonstration of the TrajStore System

The proliferation of GPS devices has led to a substantial interest in location based services. In particular, modern vehicles can generate an incredible amount of drive data. However, current storage systems are not optimized for storing and querying such large spatial-temporal data sets. In this demonstration, we show the performance of the TrajStore system, a dynamic storage system optimized for quickly accessing data in a particular spatial-temporal region. In particular, TrajStore uses a novel adaptive indexing technique that dynamically adjusts itself to co-locate spatially close trajectories on disk, as well as a number of compression techniques in the storage layer that significantly reduce access time for a given index cell. In this demonstration, we will store a set of real world taxi cab drive traces in TrajStore, and users will be able to query the data through a map based interface.
Caching and operator cooperation policies for layered video content delivery

Distributed caching architectures have been proposed for bringing content close to requesters and the key problem is to design caching algorithms for reducing content delivery delay. The problem obtains an interesting new twist with the advent of advanced layered-video encoding techniques such as Scalable Video Coding (SVC). We show that the problem of finding the caching configuration of video encoding layers that minimizes average delay for a network operator is NP-Hard, and we establish a pseudopolynomial-time optimal solution using a connection with the multiple-choice knapsack problem. We also design caching algorithms for multiple operators that cooperate by pooling together their co-located caches, in an effort to aid each other, so as to avoid large delays due to downloading content from distant servers. We derive an approximate solution to this cooperative caching problem using a technique that partitions the cache capacity into amounts dedicated to own and others' caching needs. Numerical results based on real traces of SVC-encoded videos demonstrate up to 25% reduction in delay over existing (layer-agnostic) caching schemes, with increasing gains as the video popularity distribution gets steeper, and cache capacity increases.
Feature level fusion in multimodal biometrie identification

In this paper, we propose the fusion of two uni-modal biométric verification systems, based on face and offline signature. The extraction of Gabor filter parameters is studied in two ways. A new paradigm is proposed in machine learning as the spiking neuron network) called Liquid State Machine, strategy at fusion feature vector is used and tested. The experiment is performed on a multimodal database consisting of 400 images of 80 subjects (i.e. five images per subject,), three images are used for training and two are used for testing. Good performance is obtained by merging: the contribution of multi-modality is confirmed. This preliminary study confirms the feasibility of a robust and reliable multimodal biométrie system.
Uncovering learning patterns in a MOOC through conformance alignments

Web-based learning is now offered in multiple forms. One of these is the phenomenon of Massive Open Online Courses (MOOCs). Several approaches in Learning Analytics (LA) attempt to analyze and explain students learning patterns in MOOCs. In addition to traditional data mining techniques, online surveys constitute another way used in LA for analyzing students’ learning habits in MOOCs. However, such an approach can be error-prone with data collection. Therefore, we adopt the use of process mining techniques. Process mining techniques provide more robust ways of extracting, analyzing and visualizing students’ activities trail. In this paper, we make use of alignment-based conformance checking to extract and analyse students’ learning patterns in MOOCs. The aim is to provide a guideline and demonstrate how process mining can provide critical insights in tems of students’ learning and quiz submissions behavior, their resulting performance and the correlation therein. Keywords: Learning Analytics, Mooc, Coursera, Educational Data Mining, Process Mining,Online Learning, Conformance Checking
International Conference on Computational Science , ICCS 2013 Optimization techniques for 3 D-FWT on systems with manycore GPUs and multicore CPUs

Programming manycore GPUs or multicore CPUs for high performance requires a careful balance of several hardware specific related factors, which is typically achieved by expert users through trial and error. To reduce the amount of hand-made optimization time required to achieve optimal performance, general guidelines can be followed or different metrics can be considered to predict performance, but ultimately a trial and error process is still prevalent. In this paper, we present an optimization method to run the 3D-Fast Wavelet Transform (3D-FWT) on hybrid systems. The optimization engine detects the different platforms found on a system, executing the appropriate kernel, implemented in both CUDA or OpenCL for GPUs, and programmed with pthreads for a CPU. Moreover, the proposed method selects automatically parameters such as the block size, the work-group size or the number of threads for reducing the execution time, obtaining the optimal performance in many cases. Finally, the optimization engine sends proportionally different parts of a video sequence to run concurrently in all platforms of the system. Speedups with respect to a normal user, who sends all frames to a GPU with a version of the 3D-FWT implemented in CUDA or OpenCL, presents an averaged gains of up to 7.93.
Quantitative comparison of group-based music therapy experiences in an acute care adult mental health setting: A four-group cluster-randomized study

ABSTRACT Introduction: Acute care mental health inpatients have the expertise to evaluate different group-based music therapy interventions. Moreover, from an objectivist worldview, there is a need for data concerning non-symptom measures that are specific to group-based music therapy experiences using randomized designs. The purpose of this posttest-only study is to compare how adult acute care mental health inpatients rated group experiences of three different types of educational music therapy for illness management and recovery (EMT-IMR) interventions and a recreational music therapy (RMT) intervention. Methods: Participants (N = 91) were cluster-randomized to one of four single-session group-based conditions: EMT-IMR-songwriting, EMT-IMR-lyric analysis, EMT-IMR-social story, or RMT-music therapy game. Results: There were significant between-group differences concerning RMT and EMT-IMR (both lyric analysis and songwriting conditions) in the sharing of emotions and experiences subscale. Participants in the EMT-IMR conditions rated this subscale higher than participants in the RMT condition. Although no other difference was significant, descriptive statistics tended to favor the three EMT-IMR conditions. Group experiences descriptive data from people in community mental health services from a previous study were also compared with data collected in the current study. Results indicated tendencies for the three EMT-IMR conditions to have slightly higher mean group experiences scores across all subscales than participants in the non-music therapy community mental health services condition. Discussion: Specifically targeting illness management and recovery via EMT-IMR may be practical, effective, and constitute an ideal model within acute care mental health facilities. Limitations, suggestions for future inquiry, and implications for clinical practice are provided.
Parallel Midbrain Microcircuits Perform Independent Temporal Transformations

The capacity to select the most important information and suppress distracting information is crucial for survival. The midbrain contains a network critical for the selection of the strongest stimulus for gaze and attention. In avians, the optic tectum (OT; called the superior colliculus in mammals) and the GABAergic nucleus isthmi pars magnocellularis (Imc) cooperate in the selection process. In the chicken, OT layer 10, located in intermediate layers, responds to afferent input with gamma periodicity (25–75 Hz), measured at the level of individual neurons and the local field potential. In contrast, Imc neurons, which receive excitatory input from layer 10 neurons, respond with tonic, unusually high discharge rates (>150 spikes/s). In this study, we reveal the source of this high-rate inhibitory activity: layer 10 neurons that project to the Imc possess specialized biophysical properties that enable them to transform afferent drive into high firing rates (∼130 spikes/s), whereas neighboring layer 10 neurons, which project elsewhere, transform afferent drive into lower-frequency, periodic discharge patterns. Thus, the intermediate layers of the OT contain parallel, intercalated microcircuits that generate different temporal patterns of activity linked to the functions of their respective downstream targets.
Correlation Analysis of SOX9, -5, and -6 as well as COL2A1 and Aggrecan Gene Expression of Collagen I Implant–Derived and Osteoarthritic Chondrocytes

Objective Matrix-assisted autologous chondrocyte implantation is frequently applied to replace damaged cartilage in order to support tissue regeneration or repair and to prevent progressive cartilage degradation and osteoarthritis. Its application, however, is limited to primary defects and contraindicated in the case of osteoarthritis that is partially ascribed to dedifferentiation and phenotype alterations of chondrocytes obtainable from patients’ biopsies. The differentiation state of chondrocytes is reflected at the level of structural gene (COL2A1, ACAN, COL1A1) and transcription factor (SOX9, 5, 6) expression. Methods/Design We determined the mRNA abundances of COL2A1, ACAN, and COL1A1as well as SOX9, -5, and -6 of freshly isolated and passaged collagen I implant–derived and osteoarthritic chondrocytes via reverse transcription–polymerase chain reaction. Moreover, we analyzed the correlation of structural and transcription factor gene expression. Thus, we were able to evaluate the impact of the mRNA levels of transcription factors on the expression of cartilage-specific structural genes. Results Significant differences were obtained (1) for freshly isolated osteoarthritic versus collagen I implant–derived chondrocytes, (2) due to passaging of the respective cell sources, (3) for osteoarthritic versus nonosteoarthritic chondrocytes, and (4) for COL2A1 versus ACAN expression with respect to the coherence with SOX9, -5, and -6 transcript levels. Conclusion Our results might contribute to a better understanding of the transcriptional regulation of structural gene expression of chondrocytes with implications for their use in matrix-assisted autologous chondrocyte implantation.
Model Based Tracking on 3D Objects

In this paper, a new tracking algorithm, based on local minimum energy, is proposed for matching between a projected model and corresponding image features in real-time. The algorithm is simple and accurate comparing with known literature. It has added advantage of robustness to changes in lighting or background and requires only a workstation with a frame grabber card installed. By using the proposed algorithm, a real-time motion tracking is performed. In practice, rigid objects with known geometric features are to be tracked in 6 degrees of freedom arbitrary motion.
More than pink shirts and posters: beyond the limits of anti-homophobia education

Most schools in Canada are unsafe spaces for queer youth or those perceived by their peers as queer. Gay/Straight Alliances (GSAs) and other LGBTQ+ inclusive groups exist in schools with the goal of mitigating and working against homophobia and transphobia. Homophobia, heterosexism, heteronormativity, and transphobia are consistent forms of oppression in K-12 schooling in Ontario. Typically, it is straight teachers who lead GSA-type groups and are committed to LGBTQ+ equity work in their schools despite often being under-supported by their colleagues, supervisors, and school board policy. In addition to the other demands of their profession, teachers who take on allyship in their already busy professional lives should be recognized for their efforts and hard work. However, most allies fall short of acknowledging or mitigating against their own straight privilege. Given the role straight teachers play in GSAs, this research analyzes the role and experiences of straight teacher ally activists working with LGBTQ+ students. Guided by the research question: How can straight teacher ally activists move beyond the limits of anti-homophobia education by challenging heteronormativity and heterosexism in schools? , I suggest that the overall effectiveness resisting normalized heterosexuality through anti-homophobia efforts is limited. Teacher allies should work toward queering school spaces by examining their own straight privilege as a starting point. This research stands as a call to action for policy makers, school board administrators, and leadership to provide mandatory training for all staff that zeros-in on straight privilege and heteronormativity as a way to resist its dominance. Following a manuscript-style, the research findings are reported in three manuscripts written and formatted for submission to scholarly journals. More than pink shirts and posters Potvin 3
Prediction of Binding Poses and Binding Affinities for Glycans and their Binding Proteins using a Robust Scoring Function for General Protein-Ligand Interactions

The binding of glycans to proteins represents the major way in which the information contained in glycan structures is recognised, deciphered and put into biological action. The physiological and pathological significance of glycan–protein interactions are drawing increasing attention in the field of structure-based drug design. We have implemented a quantum chemical charge model, the Austin-model 1-bond charge correction (AM1-BCC) method, into a robust scoring function for general protein ligand interactions, called, AutoDock. Here we report its capability to predict the binding poses and binding affinities of glycans to glycan-binding proteins. Our benchmark indicates that this generally applicable scoring function can be adopted in virtual screening of drug candidates and in prediction of ligand binding modes, given the structures of the well-defined recognition domains of glycan-binding proteins. 11 This article is part of the Proceedings of the Beilstein Glyco-Bioinformatics Symposium 2013. www.proceedings. beilstein-symposia.org Discovering the Subtleties of Sugars June 10 – 14, 2013, Potsdam, Germany
Triarchic Model of Psychopathy: A Brief Measure Among Detained Female Youths

ABSTRACT The present study examined the psychometric properties of a brief measure of the Triarchic model of psychopathy based on the Youth Psychopathic Traits Inventory (YPI-Tri-S) among a forensic sample of detained female youth offenders (M = 16.41 years; SD = 1.19 years) from Portugal. Results supported the expected three-factor structure and cross-gender measurement invariance. The YPI-Tri-S showed good psychometric properties in terms of factor structure, internal consistency, convergent validity, discriminant validity, and criterion-related validity. Findings suggest that the YPI-Tri-S is a valid and reliable measure of the Triarchic model of psychopathy, which can be used to assess female juvenile offenders.