Miracle-dz/UniFAR-FTUs huggingface dataset:
Gender differences in experiences of social support among men and women releasing from prison

Objectives: Positive social support is critically important to postprison well-being outcomes. However, researchers and program developers are still trying to understand how to best promote stable and sustainable social support for formerly incarcerated individuals during reentry to the community. We sought to add to the body of knowledge on social support and prisoner reentry by comparing men and women releasing from prison on the quality (e.g., positive or negative) and amount of informal social support. Methods: A random sample of 395 male (n = 165) and female (n = 230) releasing prisoners participated in the study. After unadjusted bivariate comparisons, multivariate regression was conducted to identify gender differences in preincarceration social support quality of influence and anticipated number of postrelease support persons while controlling for important covariates such as substance abuse and mental illnesses. Results: Males reported higher rates of negative social support overall, and females reported higher rates of both mixed and positive social support compared to their male counterparts. Older participants reported higher levels of positive support compared to younger participants. Men of color reported significantly higher levels of positive support than their White male counterparts. Overall, women had higher prevalence of behavioral health factors that complicate quality of support. However, there were no differences in gender found for the amount of perceived social support available postrelease in the unadjusted models. Implications: Study findings suggest the need for gender-specific and culturally tailored targets for prisoner reentry programs addressing social support. Possible adaptations for interventions are explored.
Whole Grain Rye Intake, Reflected by a Biomarker, Is Associated with Favorable Blood Lipid Outcomes in Subjects with the Metabolic Syndrome – A Randomized Study

Background and Aim Few studies have explored the possible plasma cholesterol lowering effects of rye consumption. The aim of this secondary analysis in the SYSDIET study was to investigate the association between plasma alkylresorcinols (AR), a biomarker for whole grain wheat and rye intake, and blood lipid concentrations in a population with metabolic syndrome. Furthermore, we analyzed the associations between the AR C17∶0/C21∶0 ratio, a suggested marker of the relative intake of whole grain/bran rye, and blood lipid concentrations. Methods Participants were 30–65 years of age, with body mass index (BMI) 27–40 kg/m2 and had metabolic syndrome. Individuals were recruited through six centers in the Nordic countries and randomized either to a healthy Nordic diet (ND, n = 93), rich in whole grain rye and wheat, as well as berries, fruits and vegetables, rapeseed oil, three fish meals per week and low-fat dairy products, or a control diet (n = 65) for 18/24 weeks. Associations between total plasma AR concentration and C17∶0/C21∶0 homologue ratio and blood lipids were investigated in pooled (ND + control group) regression analyses at 18/24 weeks adjusted for baseline value for the dependent variable, age, BMI and statin use. Results When adjusted for confounders, total plasma AR at 18/24 weeks was not significantly associated with blood lipids but the AR ratio C17∶0/C21∶0 was inversely associated with LDL cholesterol concentrations (B (95% CI): −0.41 (−0.80 to −0.02)), log LDL/HDL cholesterol ratio (−0.20 (−0.37 to −0.03)), log non-HDL cholesterol (−0.20 (−0.37 to −0.03)), log apolipoprotein B (−0.12 (−0.24 to 0.00)) and log triglyceride concentrations (−0.35 (−0.59 to −0.12)). Discussion Increased proportion of whole grain rye, reflected by a biomarker, in the diet is associated with favorable blood lipid outcomes, a relationship that should be further investigated. Trial Registration ClinicalTrials.gov NCT00992641
Urdu noun phrase chunking: HMM based approach

Extraction of noun phrase (NP) from text is useful for many natural language processing applications, such as name entity recognition, indexing, searching, parsing etc. We present a noun phrase chunker for Urdu which is based on a statistical approach. A 100,000 words Urdu corpus is manually tagged with NP chunk tags. The corpus is used to develop a statistical approach. Initially, a statistical approach based on standard HMM model is developed for automatics NP chunking. In Urdu phrases, the case marker (CM) indicates the end of a noun phrase and is appended at its end. Thus, if one scans the sentence in reverse order, one may be able to better predict phrase endings. So, the technique is enhanced by changing scanning direction. The technique is further enhanced by merging chunk and POS tags to achieve maximum accuracy. The results of all experiments are reported with maximum overall accuracy of 97.61% achieved using HMM based approach with extended tagset and right to left (RTL) scanning.
Testing for the Church-Rosser Property

The central notion in a replacement system is one of a transformation on a set of objects. Starting with a given object, in one “move” it is possible to reach one of a set of objects. An object from which no move is possible is called irreducible. A replacement system is Church-Rosser if starting with any object a unique irreducible object is reached. A generalization of the above notion is a replacement system (<italic>S</italic>, ⇒, ≡), where <italic>S</italic> is a set of objects, ⇒ is a transformation, and ≡ is an equivalence relation on <italic>S</italic>. A replacement system is Church-Rosser if starting with objects equivalent under ≡, equivalent irreducible objects are reached. Necessary and sufficient conditions are determined that simplify the task of testing if a replacement system is Church-Rosser. Attention will be paid to showing that a replacement system (<italic>S</italic>, ⇒, ≡) is Church-Rosser using information about parts of the system, i.e. considering cases where ⇒ is ⇒<subscrpt>1</subscrpt> ∪ ⇒<subscrpt>2</subscrpt>, or ≡ is (≡<subscrpt>1</subscrpt> ∪ ≡<subscrpt>2</subscrpt>)<supscrpt>*</supscrpt>.
Density-based Projected Clustering over High Dimensional Data Streams

Clustering of high dimensional data streams is an important problem in many application domains, a prominent example being network monitoring. Several approaches have been lately proposed for solving independently the different aspects of the problem. There exist methods for clustering over full dimensional streams and methods for finding clusters in subspaces of high dimensional static data. Yet only a few approaches have been proposed so far which tackle both the stream and the high dimensionality aspects of the problem simultaneously. In this work, we propose a new density-based projected clustering algorithm, HDDStream, for high dimensional data streams. Our algorithm summarizes both the data points and the dimensions where these points are grouped together and maintains these summaries online, as new points arrive over time and old points expire due to ageing. Our experimental results illustrate the effectiveness and the efficiency of HDDStream and also demonstrate that it could serve as a trigger for detecting drastic changes in the underlying stream population, like bursts of network attacks.
Using Latent Semantic Analysis for automated grading programming assignments

Traditionally, computer programming assignments are graded manually by educators. As this task is tedious, time-consuming and prone to bias, the need for automated grading tool is necessary to reduce the educators' burden and avoid inconsistency and favoritism. Recent researches have claimed that Latent Semantic Analysis (LSA) has the ability to represent human cognitive knowledge to assess essays, retrieving information, classification of documents and indexing. In this paper, we adapt LSA technique to grade computer programming assignments and observe how far it can be applied as an alternative approach to traditional grading methods by human. The grades of the assignments are generated from the cosine similarity that shows how close students' assignments to the model answers in the latent semantic vector space. The results show that LSA is not able to detect orders of computer programming and symbols; however, LSA is able to grade assignments faster and consistently, which avoid bias and reduces the time spent by human.
Conservation in hedgehog signaling: induction of a chicken patched homolog by Sonic hedgehog in the developing limb.

Hedgehog genes have been implicated in inductive signaling during development in a variety of organisms. A key element of the hedgehog signaling system is encoded by the gene patched. In Drosophila hedgehog regulates gene expression by antagonizing the action of patched. In addition, patched is itself a transcriptional target of hedgehog signaling. We have isolated a chicken patched homolog and find it to be strongly expressed adjacent to all tissues where members of the hedgehog family are expressed. As in Drosophila, ectopic expression of Sonic hedgehog leads to ectopic induction of chicken Patched. Based on this regulatory conservation, vertebrate Patched is likely to be directly downstream of Sonic hedgehog signaling. An important role of Sonic hedgehog is the regulation of anterior/posterior pattern in the developing limb bud. Since Patched is directly downstream of the hedgehog signal, the extent of high level Patched expression provides a measure of the distance that Sonic hedgehog diffuses and directly acts. On this basis, we find that Sonic hedgehog directly acts as a signal over only the posterior third of the limb bud. During limb patterning, secondary signals are secreted in both the mesoderm (e.g. Bone Morphogenetic Protein-2) and apical ectodermal ridge (e.g. Fibroblast Growth Factor-4) in response to Sonic hedgehog. Thus knowing which is the direct target tissue is essential for unraveling the molecular patterning of the limb. The expression of Patched provides a strong indication that the mesoderm and not the ectoderm is the direct target of Sonic hedgehog signaling in the limb bud. Finally we demonstrate that induction of Patched requires Sonic hedgehog but, unlike Bone Morphogenetic Protein-2 and Hox genes, does not require Fibroblast Growth Factor as a co-inducer. It is therefore a more direct target of Sonic hedgehog than previously reported patterning genes.
The Using virtual reality technology in Incubator organizational behavior research

Summary Conventional research methodologies that use written vignettes to present stimuli have been criticized as lacking in realism. We propose the use of highly immersive virtual reality (VR) technology to overcome limitations of written vignettes and other traditional methodologies. We also illustrate how VR technology can be effectively used to investigate various topics in organizational behavior and industrial/organizational psychology. 1997 John Wiley & Sons, Ltd.
A Method for Detecting Windows from Mobile Lidar Data

This article describes how mobile lidar (light detection and ranging) data collection is a rapidly emerging technology where multiple georeferenced sensors (e.g., laser scanners, cameras) are mounted on a moving vehicle to collect real world data. The photorealistic modeling of large-scale real world scenes such as urban environments has become increasingly interesting to the vision, graphics, and photogrammetry communities. The article presents an automatic approach to window and facade detection from mobile lidar data. The proposed method combines bottom-up with top-down strategies to extract facade planes from noise lidar point clouds. The window detection is achieved through a two-step approach: potential window point detection and window localization. The facade pattern is automatically inferred to enhance the robustness of the window detection. The application potential presented in this article includes the generation of building facade models with street-level details and texture synthesis for producing realistic occlusion-free facade texture.
Semantic transfer in Verbmobil

This paper is a detailed discussion of semantic transfer in the context of the Verbmobil Machine Translation project The use of semantic transfer as a translation mechanism is introduced and justi ed by comparison with alternative approaches Some criteria for evaluation of transfer frame works are discussed and a comparison is made of three di erent approaches to the representation of translation rules or equivalences This is followed by a discussion of control of application of transfer rules and interaction with a domain description and inference component
Extended Kalman Filter for spacecraft pose estimation using dual quaternions

Based on the highly successful Quaternion Multiplicative Extended Kalman Filter (Q-MEKF) for spacecraft attitude estimation using unit quaternions, this paper proposes a Dual Quaternion Multiplicative Extended Kalman Filter (DQ-MEKF) for spacecraft pose (i.e., attitude and position) and linear and angular velocity estimation using unit dual quaternions. By using the concept of error unit dual quaternion, defined analogously to the concept of error unit quaternion in the Q-MEKF, this paper proposes, as far as the authors know, the first multiplicative EKF for pose estimation. Compared to existing literature, the state of the DQ-MEKF only includes six elements of a unit dual quaternion, instead of eight, resulting in obvious computational savings. A version of the DQ-MEKF is presented that takes only discrete-time pose measurements with noise and, hence, is suitable for uncooperative satellite proximity operation scenarios where the chaser satellite has only access to measurements of the relative pose, but requires the relative velocities for control. Finally, the DQ-MEKF is experimentally validated and compared with two alternative EKF formulations on a 5-DOF air-bearing platform.
Euler characteristics of universal cotangent line bundles on $\mbar_{1,n}$

We give an effective algorithm to compute the Euler characteristics $\chi(\mbar_{1,n}, \otimes_{i=1}^n L_i^{d_i})$. In addition, we give a simple proof of Pandharipande's vanishing theorem $H^j (\mbar_{0,n}, \otimes_{i=1}^n L_i^{d_i})=0$ for $j \ge 1, d_i \ge0$.
Complexity-based Fitness Evaluation for Variable Length Representation

We have chosen MDL-based approach to GA and GP, mainly for the purpose of improving the robustness of learning. Its applicability has been studied in various problem domains, e.g., generating a decision tree, solving a system identi(cid:12)cation problem, and evolving a hardware. This paper summarizes our recent research results on the complexity-based (cid:12)tness evaluation for the variable length representation. We also discuss plausible extensions and future works.
American Counseling Association Competencies for Counseling with Transgender Clients

This document contains suggested competencies for use in counseling with transgender clients. These competencies are geared toward professionally trained counselors who work with transgender individuals, families, groups, or communities. These competencies are based on a wellness (e.g., Myers & Sweeney, 2005), resilience (Singh, Hays, & Watson, in press; Singh & McKleroy, in press), and strength-based approach (e.g., Bockting, Knudson, & Goldberg, 2007; Carroll, 2010; Lev, 2004; Vanderburgh, 2009) for working with transgender clients. The authors of these competencies come from diverse theoretical and professional backgrounds in working with transgender
The magnetotail reconnection region in a global MHD simulation

This work investigates the nature and the role of magnetic reconnection in a global magnetohydrodynamic simulation of the magnetosphere. We use the Gumics-4 simulation to study reconnection that occurs in the near-Earth region of the current sheet in the magnetotail. We locate the current sheet surface and the magnetic x-line that appears when reconnection starts. We illustrate the difference between quiet and active states of the reconnection region: variations in such quantities as the current sheet thickness, plasma flow velocities, and Poynting vector divergence are strong. A characteristic feature is strong asymmetry caused by non-perpendicular inflows. We determine the reconnection efficiency by the net rate of Poynting flux into the reconnection region. The reconnection efficiency in the simulation is directly proportional to the energy flux into the magnetosphere through the magnetopause: about half of all energy flowing through the magnetosphere is converted from an electromagnetic into a mechanical form in the reconnection region. Thus, the tail reconnection that is central to the magnetospheric circulation is directly driven; the tail does not exhibit a cycle of storage and rapid release of magnetic energy. We find similar behaviour of the tail in both synthetic and real event runs.
Neuromuscular Electrical Stimulation in the Early Intervention Population: A Series of Five Case Studies

The use of Neuromuscular Electrical Stimulation (NMES) to improve swallowing function in the Early Intervention home-based population with pharyngeal phase dysphagia is described using a case series design. Five children had Modified Barium Swallow studies (MBSS) completed followed by a course of swallowing therapy. The children had NMES administered home-based for 60-minute sessions. The number of treatment sessions ranged from 11 to 63, and the MBSS was repeated at the end of therapy. All five children improved functional swallowing as documented by the attending radiologist This case series design provides data that may support the use of NMES in the Early Intervention population as a treatment modality for pharyngeal phase dysphagia.
Robust Face Recognition in Rotated Eigenspaces

Face recognition is a very complex classification problem due to nuisance variations in different conditions. Most face recognition approaches either assume constant lighting condition or standard facial expressions, thus cannot deal with both kinds of variations simultaneously. Principal Component Analysis (PCA) cannot handle complex pattern variations such as illumination and expression. Adaptive PCA rotates eigenspace to extract more representative features thus improving the performance. In this paper, we present a way to extract various sets of features by different eigenspace rotations and propose a method to fuse these features to generate nonorthogonal mappings for face recognition. The proposed method is tested on the Asian Face Database with 856 images from 107 subjects with 5 lighting conditions and 4 expressions. We register only one normally lit neutral face image and test on the remaining face images with variations. Experiments show a 95% classification accuracy and a 20% reduction in error rate. This illustrates that the fused features can provide significantly improved pattern classification.
ClaimFinder: A Framework for Identifying Claims in Microblogs

Twitter is a microblogging platform that allows users to post public short messages. Posts shared by users pertaining to real-world events or themes can provide a rich “on-the-ground”live update of the events for the beneﬁt of everyone. Unfortunately, the posted information may not be all cred-ible and rumours can spread over this platform. Existing credibility assessment work have focused on identifying features for discriminating the credibility of messages at the tweet level. However, they do not handle tweets that contain multiple pieces of information, each of which may have diﬀerent level of credibility. In this work, we introduce the notion of a claim based on subject and predicate terms, and propose a framework to identify claims from a corpus of tweets related to some major event or theme. Speciﬁcally, we draw upon work done in open information extraction to extract from tweets, tuples that comprises of subjects and their predicate. Then we cluster these tuples to identify claims such that each claim refers to only one aspect of the event. Tweets corresponding to the tuples in each cluster serve as evidence supporting subsequent credibility assessment task. Extensive experiments on two real world datasets shows the eﬀectiveness of the proposed approach in identifying claims.
AHP Construct Mining Component strategy applied for data mining process

AHP Construct Mining Component (ACMC), which is a new term, is an enhancement of applicable structure for multidimensional and multi-level complex dataflow. ACMC is applied into data mining framework and different processing components with the purpose are improvement on numerous aspects in multiply level. ACMC provides not only an integrated platform to support different processing components with comprehensive and systemic methodology but also provides controllable strategy for whole processing. The instances of KPI (key performance indicator) and CSF (critical success factor) are the key points and foundation of the whole data mining structure. Mode-Refresh and Model-Evaluation are recognized as engines of the data mining machine. Influencing factor that come from these engines will influence decision constrictions. ACMC supports combination of different mining component from strategy level, tactical level to abstractive level, and then provide the successful model component for the whole data mining processing. ACMC is a new direction of the decision of KDD (Knowledge Discovery in Database).
Foreground motion and spatial saliency-based efficient HEVC Video Coding

High Efficiency Video Coding (HEVC) could not provide real time facilities to the limited processing and battery powered electronic devices as its encoding time complexity increases multiple times compared to its predecessor. Numerous researchers contribute to address this limitation by reducing a number of motion estimation (ME) modes where they analyze homogeneity, residual and statistical correlation among different modes. Although their approaches save some encoding time, however, could not reach the similar rate-distortion (RD) performance with HEVC encoder as they merely depend on existing Lagrangian cost function (LCF) within HEVC framework. To overcome this limitation, in this paper, we capture visual attentive Foreground motion and salient region (FMSR) which are sensitive to human visual system for quality assessment. The FMSR features captured by visual attentive and dynamic background modeling are adaptively synthesized to determine a subset of candidate modes. This preprocessing phase is independent from LCF. Since the proposed technique can avoid exhaustive exploration of all modes with simple criteria, it can reduce 27% encoding time on average. With efficient selection of FMSR-based appropriate block partitioning modes, it can also improve up to 1.0dB peak signal-to-noise ratio (PSNR).