Miracle-dz/UniFAR-FTUs huggingface dataset:
Barriers to increasing the physical activity of people with intellectual disabilities

© 2016 John Wiley & Sons Ltd Accessible summary: We talked to people with intellectual disabilities and their carers about being healthy. Sometimes it was difficult for people with intellectual disabilities to take part in activities that would help keep them healthy. Being active is not just about doing special sports and activities. It can be part of everyday life. People with intellectual disabilities could become more active and be healthier with help from their carers. Abstract: Background: The prevalence of obesity, inactivity and related morbidity and mortality is higher amongst people with intellectual disabilities than in the population in general, an issue of global concern. This research examined the perspectives of people with intellectual disabilities and their carers, on exercise and activity. Materials and Methods: Qualitative data were collected via interviews and a focus group with people with intellectual disabilities and their paid and family carers, recruited via state-funded community-based day centres in Scotland. Results: Three barriers hindered service users with intellectual disabilities from regular involvement in physical activity: (i) acceptance of an inactive lifestyle by carers; (ii) restrictions on activity due to paid carer preferences and resource limitations; (iii) communication issues between family carers and paid carers. Barriers were based on assumptions made by paid and family carers, so there is potential to increase activity by changing attitudes, improving communication and reconceptualising activity as integral to everyday living, rather than as additional exercise requiring special resources. Conclusions: Carers should be supported to promote physical activity in a variety of ways to enhance the motivation of service users, to encourage them to engage with physical activity as an integral part of a healthy lifestyle and to transfer this to their lives beyond day care.
Automatic Generation Control of Two-area Interconnected Hydro-Hydro Restructured Power System with TCPS and SMES

Non-minimum phase characteristic of hydro turbine shows an opposite initial power surge in the event of frequency disturbance, thus possesses widely different characteristic than thermal generating unit. This paper presents Automatic Generation Control (AGC) of an interconnected two-area multiple-units hydro-hydro power system in restructured electricity market. The step load perturbation to such a system results in heavy frequency oscillations and the system is unable to regain its stable state as the positive real parts of some eigenvalue pairs confirm the inherent dynamically unstable characteristic of the system. To stabilize the frequency oscillations, impacts of Superconducting Magnetic Energy Storage (SMES) placed at terminal of area and Thyristor Controlled Phase Shifter (TCPS) located in series with tie-line have been investigated. Two cases such as (a) SMES-SMES coordination and (b) TCPS-SMES coordination are evaluated to compare their effectiveness to suppress the frequency oscillations. The parameters of TCPS, SMES and integral gains of AGC loop are optimized through craziness- based particle swarm optimization algorithm in order to have the optimal transient response of the system under different PoolCo and bilateral transaction in restructured electricity market.
Formal Ontology Learning on Factual IS-A Corpus in English using Description Logics

Ontology Learning (OL) is the computational task of generating a knowledge base in the form of an ontology given an unstructured corpus whose content is in natural language (NL). Several works can be found in this area most of which are limited to statistical and lexico-syntact ic pattern matching based techniques (Light-Weight OL). These techniques do not lead to very accurate learning mostly because of several linguistic nuances in NL. Formal OL is an alternative (less explored) methodology were deep linguistics analysis is made using theory and tools found in computational linguistics to generate formal axioms and definitions instead simply inducing a taxonomy. In this paper we propose “Description Logic (DL)” based formal OL framework for learning factual IS-A type sentences in English. We claim that semantic construction of IS-A sentences is non trivial. Hence, we also claim that such sentences requires special studies in the context of OL before any truly formal OL can be proposed. We introduce a learner tool, called DLOLIS−A, that generated such ontologies in the owl format. We have adopted “Gold Standard” based OL evaluation on IS-A rich WCL v.1. 1 dataset and our own Community representative IS-A dataset. We observed significant improvement of DLOLIS−A when compared to the light-weight OL tool Text2Onto and formal OL tool FRED.
Evidence-based African-centered HIV/AIDS prevention interventions: Best practices and opportunities

ABSTRACT African Americans have been disproportionately impacted by HIV/AIDS since the beginning of the epidemic and today bear the significant brunt of the health crisis as reflected in their disproportionate representation among the number of persons living with HIV/AIDS, the cumulative numbers of persons who have succumbed to AIDS-related conditions, and those who are newly diagnosed with HIV. According to the Centers for Disease Control and Prevention, at some point in their lives, an estimated one in 16 African American men and one in 32 African American women will be diagnosed with HIV infection. Despite accounting for a little more than 13% of the U.S. population, African Americans accounted for 43% of all new HIV cases in 2014. This article provides a critical review of evidenced-based, African-centered HIV primary prevention interventions designed to address the cultural realities of African Americans. Following a brief contextualization of the impact of HIV/AIDS among African Americans as a reflection of multisystemic complexities and a discussion of the authors’ procedures regarding inclusion of selected interventions, exemplars of highly efficacious African-centered HIV prevention interventions are reviewed, and central components of these interventions are discussed. Finally, the authors discuss implications and opportunities regarding the design and implementation of African-centered HIV prevention interventions targeting African Americans.
Beyond Mutations: Additional Mechanisms and Implications of SWI/SNF Complex Inactivation

SWI/SNF is a major regulator of gene expression. Its role is to facilitate the shifting and exposure of DNA segments within the promoter and other key domains to transcription factors and other essential cellular proteins. This complex interacts with a wide range of proteins and does not function within a single, specific pathway; thus, it is involved in a multitude of cellular processes, including DNA repair, differentiation, development, cell adhesion, and growth control. Given SWI/SNF’s prominent role in these processes, many of which are important for blocking cancer development, it is not surprising that the SWI/SNF complex is targeted during cancer initiation and progression both by mutations and by non-mutational mechanisms. Currently, the understanding of the types of alterations, their frequency, and their impact on the SWI/SNF subunits is an area of intense research that has been bolstered by a recent cadre of NextGen sequencing studies. These studies have revealed mutations in SWI/SNF subunits, indicating that this complex is thus important for cancer development. The purpose of this review is to put into perspective the role of mutations versus other mechanisms in the silencing of SWI/SNF subunits, in particular, BRG1 and BRM. In addition, this review explores the recent development of synthetic lethality and how it applies to this complex, as well as how BRM polymorphisms are becoming recognized as potential clinical biomarkers for cancer risk. Significance: Recent reviews have detailed the occurrence of mutations in nearly all SWI/SNF subunits, which indicates that this complex is an important target for cancer. However, when the frequency of mutations in a given tumor type is compared to the frequency of subunit loss, it becomes clear that other non-mutational mechanisms must play a role in the inactivation of SWI/SNF subunits. Such data indicate that epigenetic mechanisms that are known to regulate BRM may also be involved in the loss of expression of other SWI/SNF subunits. This is important since epigenetically silenced genes are inducible, and thus, the reversal of the silencing of these non-mutationally suppressed subunits may be a viable mode of targeted therapy.
MEETING DYNAMIC IS MARKET DEMANDS: LEVERAGING CONSULTING PRACTICES TO GUIDE CURRICULUM REFORM

The dot com bust and fears of outsourcing have lead to declining IS enrollments nationwide. IS faculty have not been successful at adapting their curricula to changing market pressures. We maintain that it requires a different skill set to adapt to market forces. When businesses are not able to adapt, they often bring in consultants. Consultants typically employ a methodology to change the business while ensuring buy in and success. We were fortunate to have consultants on our staff that leveraged a change methodology to guide us through the curriculum reform process. This paper presents an account of that process and lessons learned from it.
General Analysis Tool Box for Controlled Perturbation

The implementation of reliable and efficient geometric algorithms is a challenging task. The reason is the following conflict: On the one hand, computing with rounded arithmetic may question the reliability of programs while, on the other hand, computing with exact arithmetic may be too expensive and hence inefficient. One solution is the implementation of controlled perturbation algorithms which combine the speed of floating-point arithmetic with a protection mechanism that guarantees reliability, nonetheless. This paper is concerned with the performance analysis of controlled perturbation algorithms in theory. We answer this question with the presentation of a general analysis tool box. This tool box is separated into independent components which are presented individually with their interfaces. This way, the tool box supports alternative approaches for the derivation of the most crucial bounds. We present three approaches for this task. Furthermore, we have thoroughly reworked the concept of controlled perturbation in order to include rational function based predicates into the theory; polynomial based predicates are included anyway. Even more we introduce object-preserving perturbations. Moreover, the tool box is designed such that it reflects the actual behavior of the controlled perturbation algorithm at hand without any simplifying assumptions.
Scaffolding on-line segmentation of full body human motion patterns

This paper develops an approach for on-line segmentation of whole body human motion patterns during human motion observation and learning. A Hidden Markov Model is used to represent the incoming data sequence, where each model state represents the probability density estimate over a window of the data. Based on the assumption that data belonging to the same motion primitive will have the same underlying distribution, the segmentation is implemented by finding the optimum state sequence over the developed model. The basic algorithm is modified to add the capability for modifying the model based on known motion primitives. The inclusion of such scaffolding motion primitives can improve the performance of the basic segmentation algorithm. The modified algorithm is tested on a corpus of continuous human motion data to show the efficacy of the proposed approach.
Helios, and not FoxP3, is the marker of activated Tregs expressing GARP/LAP

Regulatory T cells (Tregs) are key players of immune regulation/dysregulation both in physiological and pathophysiological settings. Despite significant advances in understanding Treg function, there is still a pressing need to define reliable and specific markers that can distinguish different Treg subpopulations. Herein we show for the first time that markers of activated Tregs [latency associated peptide (LAP) and glycoprotein A repetitions predominant (GARP, or LRRC32)] are expressed on CD4+FoxP3− T cells expressing Helios (FoxP3−Helios+) in the steady state. Following TCR activation, GARP/LAP are up-regulated on CD4+Helios+ T cells regardless of FoxP3 expression (FoxP3+/−Helios+). We show that CD4+GARP+/−LAP+ Tregs make IL-10 immunosuppressive cytokine but not IFN-γ effector cytokine. Further characterization of FoxP3/Helios subpopulations showed that FoxP3+Helios+ Tregs proliferate in vitro significantly less than FoxP3+Helios− Tregs upon TCR stimulation. Unlike FoxP3+Helios− Tregs, FoxP3+Helios+ Tregs secrete IL-10 but not IFN-γ or IL-2, confirming they are bona fide Tregs with immunosuppressive characteristics. Taken together, Helios, and not FoxP3, is the marker of activated Tregs expressing GARP/LAP, and FoxP3+Helios+ Tregs have more suppressive characteristics, compared with FoxP3+Helios− Tregs. Our work implies that therapeutic modalities for treating autoimmune and inflammatory diseases, allergies and graft rejection should be designed to induce and/or expand FoxP3+Helios+ Tregs, while therapies against cancers or infectious diseases should avoid such expansion/induction.
Hedge Fund Contagion and Liquidity Shocks

Defining contagion as correlation over and above that expected from economic fundamentals, we find strong evidence of worst return contagion across hedge fund styles for 1990 to 2008. Large adverse shocks to asset and hedge fund liquidity strongly increase the probability of contagion. Specifically, large adverse shocks to credit spreads, the TED spread, prime broker and bank stock prices, stock market liquidity, and hedge fund flows are associated with a significant increase in the probability of hedge fund contagion. While shocks to liquidity are important determinants of performance, these shocks are not captured by commonly used models of hedge fund returns. Copyright (c) 2010 the American Finance Association.
A data definition and mapping language

Abstract : A data definition language is a declarative computer language for specifying data structures. Most data definition languages concentrate on the declaration of logical data structures with little concern for how these structures are physically realized on a computer system. However, the need for data definition languages which describe both the logical and physical aspects of data is increasingly apparent. Such languages will be a key element in the translation of data among computer systems, as well as in advanced data management systems and distributed data bases. The paper reviews past work in the data definition language for describing both logical and physical aspects of data. Applications of these generalized data definition languages are also discussed. (Author)
Facial design for humanoid robot

In this research, the authors succeeded in creating facial expressions made with the minimum necessary elements for recognizing a face. The elements are two eyes and a mouth made using precise circles, which are transformed to make facial expressions geometrically, through rotation and vertically scaling transformation. The facial expression patterns made by the geometric elements and transformations were composed employing three dimensions of visual information that had been suggested by many previous researches, slantedness of the mouth, openness of the face, and slantedness of the eyes. In addition, the relationships between the affective meanings of the visual information also corresponded to the results of the previous researches. The authors found that facial expressions can be classified into 10 emotions: happy, angry, sad, disgust, fear, surprised, angry*, fear*, neutral (pleasant) indicating positive emotion, and neutral (unpleasant) indicating negative emotion. These emotions were portrayed by different geometric transformations. Furthermore, the authors discovered the "Tetrahedral model," which can express most clearly the geometric relationships between facial expressions. In this model, each side connecting the face is an axis that controlled the rotational and vertically scaling transformations of the eyes and mouth.
A quantitative comparison of the most sophisticated EOG-based eye movement recognition techniques

Although ElectroOculoGraphic (EOG) signals have been intensively used for human-machine interfaces, none of the available eye movement recognition techniques have been objectively compared to each other. In this paper, we propose to compare two widely known techniques (the standard R. Barea (RB) and A. Bulling (AB)'s works) and a Spiking Neural Network based approach. We also suggest several potential improvements that were all assessed according to the Fl-score. Additionally, we investigate 3 different target configurations on the screen: 3×3, 3×5 and 5×5. This aims at detecting which configuration can reach the best bitrate. Finally, double blink and wink detectors are Fl-score evaluated to estimate their relevancy as a mouse click. In this 6-healthy-subject experiment, we observed that both RB and AB methods provide fairly similar results. According to the bitrate analysis while considering complexity, the 3×3 is the most suitable interface. Among the different potential enhancements, the clustering approach instead of a fixed grid leads to a much quicker learning procedure. Regarding the eye mouse click detectors, their performance should be high enough to be used in a reliable interface.
A clockless sequential PUF with autonomous majority voting

Physical unclonable functions (PUFs) leverage minute silicon process variations to produce device-tied secret keys. The energy and area costs of creating keys from PUFs can far exceed the costs of the basic PUF circuits alone. Minimizing the end-to-end cost of reliable key generation is critical to enable broader adoption of PUFs. In this work, we introduce a new style of PUF that employs autonomous majority voting to improve reliability. The novelty of this design, and the source of its efficiency, is that the inherently sequential majority voting procedure is carried out by a self-timed circuit without orchestration by a global clock. We use circuit simulation to evaluate the energy versus reliability tradeoffs achieved by different parameterizations of the design, to show that the design performs well across a range of supply voltages, and to quantify the robustness of the design across a broad range of operating temperatures.
Transparently Gathering Provenance with Provenance Aware Condor

We observed that the Condor batch execution system exposes a lot of information about the jobs that run in the system. This observation led us to explore whether this system information could be used for provenance. The result of our explorations is Provenance Aware Condor (PAC), a system that transparently gathers provenance while jobs run in Condor. Transparent provenance gathering requires that the application not be altered in order to run in the provenance system. This requirement allows any application that can run in Condor to also run in PAC. Through SQL queries, PAC is able to answer a wide range of questions about the files used by a job and the machines that execute jobs.
Transcriptional Targeting of Primary and Metastatic Tumor Neovasculature by an Adenoviral Type 5 Roundabout4 Vector in Mice

New approaches targeting metastatic neovasculature are needed. Payload capacity, cellular transduction efficiency, and first-pass cellular uptake following systemic vector administration, motivates persistent interest in tumor vascular endothelial cell (EC) adenoviral (Ad) vector targeting. While EC transductional and transcriptional targeting has been accomplished, vector administration approaches of limited clinical utility, lack of tumor-wide EC expression quantification, and failure to address avid liver sequestration, challenged prior work. Here, we intravenously injected an Ad vector containing 3 kb of the human roundabout4 (ROBO4) enhancer/promoter transcriptionally regulating an enhanced green fluorescent protein (EGFP) reporter into immunodeficient mice bearing 786-O renal cell carcinoma subcutaneous (SC) xenografts and kidney orthotopic (KO) tumors. Initial experiments performed in human coxsackie virus and adenovirus receptor (hCAR) transgenic:Rag2 knockout mice revealed multiple ECs with high-level Ad5ROBO4-EGFP expression throughout KO and SC tumors. In contrast, Ad5CMV-EGFP was sporadically expressed in a few tumor vascular ECs and stromal cells. As the hCAR transgene also facilitated Ad5ROBO4 and control Ad5CMV vector EC expression in multiple host organs, follow-on experiments engaged warfarin-mediated liver vector detargeting in hCAR non-transgenic mice. Ad5ROBO4-mediated EC expression was undetectable in most host organs, while the frequencies of vector expressing intratumoral vessels and whole tumor EGFP protein levels remained elevated. In contrast, AdCMV vector expression was only detectable in one or two stromal cells throughout the whole tumor. The Ad5ROBO4 vector, in conjunction with liver detargeting, provides tractable genetic access for in-vivo EC genetic engineering in malignancies.
Vision based approach for active selection of robot’s localization action

The paper presents a mobile robot localization system that integrates Monte-Carlo localization (MCL) with an active action-selection approach based on an aliasing map. The main novelties of the approach are: the off-line evaluation of the perceptual aliasing of the environment; the use of this knowledge to actively perform the localization processes; the use of an improved SIFT feature extractor to aliasing map evaluation and to measure image similarity. Results, obtained in a real scenario using a real robot, show improved performances in the number of steps needed to correctly localize the robot and in the localization error, compared with the classic MCL approach. Also better performances in computational time due to improvements in the vision system are shown.
Pathophysiological Concepts in Mild Traumatic Brain Injury: Diffusion Tensor Imaging Related to Acute Perfusion CT Imaging

Background A subgroup of patients with mild traumatic brain injury (TBI) experiences residual symptoms interfering with their return to work. The pathophysiological substrate of the suboptimal outcome in these patients is a source of debate. Objective To provide greater insight into the pathophysiological mechanisms of mild TBI. Methods Diffusion tensor imaging (DTI) was performed during follow-up of 18 patients with mild TBI and compared with healthy control subjects. DTI data of the patient group were also compared with perfusion CT imaging in the acute phase of injury. Results In patients with mild TBI, a trend was observed for a decreased fractional anisotropy (FA) in widespread bilateral frontal white matter areas with increased mean diffusivity (MD) in the parieto-temporal regions, compared to healthy control subjects. Cerebral blood volume (CBV) correlated significantly with FA in several white matter tracts including the corpus callosum, the internal capsule, the inferior fronto-occipital fascicle, the corticospinal tract, the superior and the inferior longitudinal fascicle. Conclusion In mild TBI with normal conventional imaging significant associations between cerebral perfusion in the acute phase of injury and DTI analyses in the chronic phase of injury were discerned. The pathophysiological concept of these findings is being outlined.