Miracle-dz/UniFAR-FTUs huggingface dataset:
Bridging Juvenile Justice and Positive Youth Development

P lacing juvenile justice and positive youth development in the same sentence is somewhat like mixing oil and water. The reader may recognize each of these concepts individually but have great difficulty imagining how they could be merged into an integrated whole. On one hand, the juvenile justice system embodies the tension between criminal justice and child welfare, seeking to address youthful misbehavior with a combination of punishment and rehabilitation. On the other hand, positive youth development advocates seek nothing less than a transformation of public consciousness and resource commitments, from a concern with preventing and treating youth problems to a comprehensive approach providing supports and opportunities enabling all children to develop optimally. This author has attended numerous public meetings highlighted by angry and mistrustful exchanges between positive youth development advocates and traditional service providers, including juvenile justice professionals. The former argue that resources are excessively earmarked for expensive and ineffective interventions with “problem youth” while ignoring basic supports for families and children. In response, the other side expresses fears that redirecting resources toward universal supports and opportunities compounds the privileges already realized by the “best and brightest” while relegating those most “at risk” to what would remain of the juvenile justice (or mental health or child welfare) system. The two sides, both genuinely
Designing Smart Objects with Autistic Children: Four Design Exposès

This paper describes the design work being conducted as part of the OutsideTheBox project. Within the time-frame of eight months, we engaged four children with autism in a participatory design process to develop their own smart object. We re-interpreted Future Workshops and Co-operative Inquiry to demonstrate that a) autistic children can lead processes with a deliberately open design brief and b) this leads us to explore design spaces that are un-imaginable for neuro-typical, adult designers. To capture these four design cases, we have developed Design Exposes, a concept that is inspired by annotated portfolios and Actor-Network Theory. We apply this concept to our cases and present four exposes that subsequently allow us to draw out intermediate-level design knowledge about co-creating technology with autistic children. We close by critically reflecting on the design processes as well as our concept of capturing them.
Learning Generalized Reactive Policies using Deep Neural Networks

We present a new approach to learning for planning, where knowledge acquired while solving a given set of planning problems is used to plan faster in related, but new problem instances. We show that a deep neural network can be used to learn and represent a generalized reactive policy (GRP) that maps a problem instance and a state to an action, and that the learned GRPs efficiently solve large classes of challenging problem instances. In contrast to prior efforts in this direction, our approach significantly reduces the dependence of learning on handcrafted domain knowledge or feature selection. Instead, the GRP is trained from scratch using a set of successful execution traces. We show that our approach can also be used to automatically learn a heuristic function that can be used in directed search algorithms. We evaluate our approach using an extensive suite of experiments on two challenging planning problem domains and show that our approach facilitates learning complex decision making policies and powerful heuristic functions with minimal human input.
, Supersymmetry , and Janus

We consider theories consisting of a planar interface with N = 4 super-YangMills on either side and varying gauge coupling across the interface. The interface does not carry any independent degrees of freedom, but is allowed to support local gauge invariant operators, included with independent interface couplings. In general, both conformal symmetry and supersymmetry will be broken, but for special arrangements of the interface couplings, these symmetries may be restored. We provide a systematic classification of all allowed interface supersymmetries. We find new theories preserving eight and four Poincaré supersymmetries, which get extended to sixteen and eight supersymmetries in the conformal limit, respectively with SU(2) × SU(2), SO(2) × SU(2) internal symmetry. The Lagrangians for these theories are explicitly constructed. We also recover the theory with two Poincaré supersymmetries and SU(3) internal symmetry proposed earlier as a candidate CFT dual to super Janus. Since our new interface theories have only operators from the supergravity multiplet turned on, dual supergravity solutions are expected to exist. We speculate on the possible relation between the interface theory with maximal supersymmetry and the near-horizon limit of the D3-D5 system.
Signature Verification using Integrated Classifiers

This paper presents a new approach for off-line signature verification. The proposed system is based on global, grid, ink distribution and texture features. The Boosting algorithm is applied to train and integrate multiple classifiers, and the distance-based classifier used as the base classifier corresponding to each feature set. Adaptive threshold is associated with individuality. Experimental results show the system is insensitive to the order of base-classifiers and gets a high verification ratio.
Determinants of Online Social Business Network Usage Behavior—Applying the Technology Acceptance Model and Its Extensions

Usage of online social business networks like LinkedIn and XING have become commonplace in today’s workplace. This research addresses the question of what factors drive the intention to use online social business networks. Theoretical frame of the study is the Technology Acceptance Model (TAM) and its extensions, most importantly the TAM2 model. Data has been collected via a Web Survey among users of LinkedIn and XING from January to April 2010. Of 541 initial responders 321 finished the questionnaire. Operationalization was tested using confirmatory factor analyses and causal hypotheses were evaluated by means of structural equation modeling. Core result is that the TAM2 model generally holds in the case of online social business network usage behavior, explaining 73% of the observed usage intention. This intention is most importantly driven by perceived usefulness, attitude towards usage and social norm, with the latter effecting both directly and indirectly over perceived usefulness. However, perceived ease of use has—contrary to hypothesis—no direct effect on the attitude towards usage of online social business networks. Social norm has a strong indirect influence via perceived usefulness on attitude and intention, creating a network effect for peer users. The results of this research provide implications for online social business network design and marketing. Customers seem to evaluate ease of use as an integral part of the usefulness of such a service which leads to a situation where it cannot be dealt with separately by a service provider. Furthermore, the strong direct impact of social norm implies application of viral and peer-to-peer marketing techniques while it’s also strong indirect effect implies the presence of a network effect which stabilizes the ecosystem of online social business service vendors.
Predictors for E-government Adoption in Jordan: Deployment of an Empirical Evaluation Based on a Citizen-centric Approach

Purpose – This paper aims to engage with the growing debate on the factors that affect e‐government adoption in the developing country of Jordan. The change from traditional interactions between government and citizens in Jordan to interaction via the web needs further exploration in order to understand the factors that might affect e‐government adoption by citizens. This paper therefore aims to report on a study to identify the main factors that influence citizens' intention to adopt e‐government websites in Jordan, using a theoretical framework consisting of diffusion of innovation theory (DOI) and the technology acceptance model (TAM). Design/methodology/approach – A survey study of 400 Jordanian citizens who were internet users investigated the influence of the aforementioned factors on the adoption and use of e‐government websites. Multiple regression analysis was used to test the hypotheses.Findings – Contrary to previous research, trust in the internet, relative advantage, compatibility and perceive.
Hemispheric Differences in Frontal and Parietal Influences on Human Occipital Cortex: Direct Confirmation with Concurrent TMS–fMRI

We used concurrent TMS–fMRI to test directly for hemispheric differences in causal influences of the right or left fronto-parietal cortex on activity (BOLD signal) in the human occipital cortex. Clinical data and some behavioral TMS studies have been taken to suggest right-hemisphere specialization for top–down modulation of vision in humans, based on deficits such as spatial neglect or extinction in lesioned patients, or findings that TMS to right (vs. left) fronto-parietal structures can elicit stronger effects on visual performance. But prior to the recent advent of concurrent TMS and neuroimaging, it was not possible to directly examine the causal impact of one (stimulated) brain region upon others in humans. Here we stimulated the frontal or intraparietal cortex in the left or right hemisphere with TMS, inside an MR scanner, while measuring with fMRI any resulting BOLD signal changes in visual areas V1–V4 and V5/MT+. For both frontal and parietal stimulation, we found clear differences between effects of right- versus left-hemisphere TMS on activity in the visual cortex, with all differences significant in direct statistical comparisons. Frontal TMS over either hemisphere elicited similar BOLD decreases for central visual field representations in V1–V4, but only right frontal TMS led to BOLD increases for peripheral field representations in these regions. Hemispheric differences for effects of parietal TMS were even more marked: Right parietal TMS led to strong BOLD changes in V1–V4 and V5/MT+, but left parietal TMS did not. These data directly confirm that the human frontal and parietal cortex show right-hemisphere specialization for causal influences on the visual cortex.
The Curse of Zipf and Limits to Parallelization: An Look at the Stragglers Problem in MapReduce

This paper explores the problem of \stragglers" in MapReduce: a common phenomenon where a small number of mappers or reducers takes signicantly longer than the others to complete. The eects of these stragglers include unnecessarily long wall-clock running times and sub-optimal cluster utilization. In many cases, this problem cannot simply be attributed to hardware idiosyncrasies, but is rather caused by the Zipan distribution of input or intermediate data. I present a simple theoretical model that shows how such distributions impose a fundamental limit on the amount of parallelism that can be extracted from a large class of algorithms where all occurrences of the same element must be processed together. A case study in parallel ad hoc query evaluation highlights the severity of the stragglers problem. Fortunately, a simple modication of the input data cuts end-to-end running time in half. This example illustrates some of the issues associated with designing ecient MapReduce algorithms for real-world datasets.
Conformational state of the MscS mechanosensitive channel in solution revealed by pulsed electron–electron double resonance (PELDOR) spectroscopy

The heptameric mechanosensitive channel of small conductance (MscS) provides a critical function in Escherichia coli where it opens in response to increased bilayer tension. Three approaches have defined different closed and open structures of the channel, resulting in mutually incompatible models of gating. We have attached spin labels to cysteine mutants on key secondary structural elements specifically chosen to discriminate between the competing models. The resulting pulsed electron–electron double resonance (PELDOR) spectra matched predicted distance distributions for the open crystal structure of MscS. The fit for the predictions by structural models of MscS derived by other techniques was not convincing. The assignment of MscS as open in detergent by PELDOR was unexpected but is supported by two crystal structures of spin-labeled MscS. PELDOR is therefore shown to be a powerful experimental tool to interrogate the conformation of transmembrane regions of integral membrane proteins.
Collective agility, paradox and organizational improvisation: the development of a particle physics grid

This paper examines systems development in a global collaborative community of high‐energy physics and offers insights and implications for agile systems development in other large scale and distributed settings. The paper studies the ongoing construction of the UK's computing grid for particle physics (GridPP), a grid that is itself part of the world's largest grid, the Large Hadron Collider Computing Grid. We observe in this project a collective, agile and distributed performance through which the Grid is constructed. We express this through the concept of ‘collective agility’ which captures a large distributed performance rather than the more conventional sense of agility as small‐group and deliberate systems development practices. The collective agility of GridPP is analysed as a process of ‘enacted emergence’ expressed through the dynamics of six improvisation paradoxes.
Sex-biased genetic effects on gene regulation in humans

Human regulatory variation, reported as expression quantitative trait loci (eQTLs), contributes to differences between populations and tissues. The contribution of eQTLs to differences between sexes, however, has not been investigated to date. Here we explore regulatory variation in females and males and demonstrate that 12%–15% of autosomal eQTLs function in a sex-biased manner. We show that genes possessing sex-biased eQTLs are expressed at similar levels across the sexes and highlight cases of genes controlling sexually dimorphic and shared traits that are under the control of distinct regulatory elements in females and males. This study illustrates that sex provides important context that can modify the effects of functional genetic variants.
Disgust as Embodied Moral Judgment

How, and for whom, does disgust influence moral judgment? In four experiments participants made moral judgments while experiencing extraneous feelings of disgust. Disgust was induced in Experiment 1 by exposure to a bad smell, in Experiment 2 by working in a disgusting room, in Experiment 3 by recalling a physically disgusting experience, and in Experiment 4 through a video induction. In each case, the results showed that disgust can increase the severity of moral judgments relative to controls. Experiment 4 found that disgust had a different effect on moral judgment than did sadness. In addition, Experiments 2-4 showed that the role of disgust in severity of moral judgments depends on participants' sensitivity to their own bodily sensations. Taken together, these data indicate the importance—and specificity—of gut feelings in moral judgments.
Examination of Parent Insurance Ratings, Child Expenditures, and Financial Burden Among Children With Autism: A Mismatch Suggests New Hypotheses to Test

OBJECTIVE: Families raising children with autism contribute significant amounts to the cost of care. In this era of health care reform, families have more insurance choices, but people are unfamiliar with health insurance terms. This study uses 2 national data sets to examine health insurance ratings from parents raising children with autism and child expenditures to explore how these measures align. METHODS: Children with autism who met criteria for special health care needs and were continuously insured were examined. Data from the National Survey of Children With Special Health Care Needs 2009–2010 were used to examine parent report of adequate insurance (n = 3702). Pooled data from the Medical Expenditure Panel Survey 2002–2011 were used to examine expenditures (n = 346). Types of health insurance included private alone, Medicaid alone, and combined private and wrap-around Medicaid. RESULTS: Having Medicaid doubled the odds of reporting adequate insurance compared with private insurance alone (P < .0001), and children on Medicaid had the lowest out-of-pocket costs ($150, P < .0001). Children covered by combined private and wrap-around Medicaid had the highest total expenditures ($11 596, P < .05) and the highest expenditures paid by their insurance ($10 638, P < .05). CONCLUSIONS: These findings highlight a mismatch between parent ratings of insurance adequacy, child expenditures, and relative financial burden. Findings generate a number of questions to address within single sources of data. By elaborating the frameworks families use to judge the adequacy of their insurance, future research can develop policy strategies to improve both their satisfaction with their insurance coverage and the service use of children with autism.
Modularity Based Community Detection with Deep Learning

Identification of module or community structures is important for characterizing and understanding complex systems. While designed with different objectives, i.e., stochastic models for regeneration and modularity maximization models for discrimination, both these two types of model look for low-rank embedding to best represent and reconstruct network topology. However, the mapping through such embedding is linear, whereas real networks have various nonlinear features, making these models less effective in practice. Inspired by the strong representation power of deep neural networks, we propose a novel nonlinear reconstruction method by adopting deep neural networks for representation. We then extend the method to a semi-supervised community detection algorithm by incorporating pairwise constraints among graph nodes. Extensive experimental results on synthetic and real networks show that the new methods are effective, outperforming most state-of-the-art methods for community detection.
Neural Network Models of Simple Mechanical Systems Illustrating the Feasibility of Accelerated Life Testing

A complete evaluation of the tribological characteristics of a given material/mechanical system is a time-consuming operation since the friction and wear process is extremely systems sensitive. As a result, experimental designs (i.e., Latin Square, Taguchi) have been implemented in an attempt to not only reduce the total number of experimental combinations needed to fully characterize a material/mechanical system, but also to acquire life data for a system without having to perform an actual life test. Unfortunately, these experimental designs still require a great deal of experimental testing and the output does not always produce meaningful information. In order to further reduce the amount of experimental testing required, this study employs a computer neural network model to investigate different material/mechanical systems. The work focuses on the modeling of the wear behavior, while showing the feasibility of using neural networks to predict life data. The model is capable of defining which input variables will influence the tribological behavior of the particular material/mechanical system being studied based on the specifications of the overall system.
Can Neuroimaging Help Us to Understand and Classify Somatoform Disorders? A Systematic and Critical Review

Objective: Debate about the nature of somatoform disorders and their current diagnostic classification has been stimulated by the anticipation of new editions of Diagnostic and Statistical Manual of Mental Disorders and International Statistical Classification of Diseases and Related Health Problems diagnostic classifications. In the current paper, we review systematically the literature on the neuroimaging of somatoform disorders and related conditions with the aim of addressing two specific questions: Is there evidence of altered neural function or structure that is specifically associated with somatoform disorders? What conclusions can we draw from these findings about the etiology of somatoform disorders? Methods: Studies reporting neuroimaging findings in patients with a somatoform disorder or a functional somatic syndrome (such as fibromyalgia) were found using Pubmed, PsycINFO, and EMBASE database searches. Reported structural and functional neuroimaging findings were then extracted to form a narrative review. Results: A relatively mature literature on symptoms of pain and less developed literatures on conversion and fatigue symptoms were identified. The available evidence indicates that, when compared with nonclinical groups, somatoform diagnoses are associated with increased activity of limbic regions in response to painful stimuli and a generalized decrease in gray matter density; however, methodological considerations restrict the interpretation of these findings. Conclusions: Whereas the neuroimaging literature has provided evidence about the possible mechanisms underlying somatoform disorders, this is not yet sufficient to provide a basis for classification. By adopting a wider variety of experimental designs and a more dynamic approach to diagnosis, there is every reason to be hopeful that neuroimaging data will play a significant role in future taxonomies. 5-HT = 5 hydroxytryptamine (serotonin); ACC = anterior cingulate cortex; CBT = cognitive behavioral therapy; CFS = chronic fatigue syndrome; dlPFC = dorsolateral prefrontal cortex; DSM = Diagnostic and Statistical Manual of Mental Disorders; EEG = electroencephalography; FM = fibromyalgia; fMRI = functional magnetic resonance imaging; IBS = irritable bowel syndrome; ICD = International Classification of Diseases and Related Health Problems; PET = positron emission tomography; VBM = voxel-based morphometry.