Miracle-dz/UniFAR-FTUs huggingface dataset:
Interactive and Authentic e-Learning Tools for Criminal Justice Education

ABSTRACT This mixed-method study tested the effectiveness of two experiential e-learning tools for criminal justice courses. The first tool was a comprehensive video series, including a criminal trial and interviews with the judge, defense counsel, prosecution, investigators and court director (virtual trial), in order to enhance course and learning outcomes. The tool was a comprehensive and Interactive Criminal Justice Computer Model flowchart that allowed the students to work within the multifaceted and complex systems and explore descriptions, concepts, theories, relationships, and sequences in order to enhance learning outcomes regarding the system(s) of justice. Survey data were collected from an array of learning and criminal justice professionals. Student self-assessments and course satisfaction indicators were administered. These tools presented authentic and holistic criminal justice learning opportunities to students that would not have been possible otherwise. Both professionals and students found the e-learning tools expanded students’ understanding and allowed them to apply new information for problem solving within the complex criminal justice system.
Offset-based response time analysis of distributed systems scheduled under EDF

Offset-based response time analysis of tasks scheduled with fixed priorities has demonstrated to be a powerful tool to analyze many task models with different kinds of timing constraints, like regular periodic tasks, suspending tasks, distributed systems, tasks with varying priorities, multi frame models, etc. Offset-based analysis techniques are capable of performing a global schedulability analysis in distributed systems, as opposed to the less efficient techniques that consider each processing or communication resource as independent. In this paper we extend the offset-based schedulability analysis techniques to system with EDF (earliest deadline first) scheduling, using analytical techniques that are similar to those developed for fixed priority scheduling. With this new analysis, we now have a complete set of techniques to perform the analysis of different task models in distributed heterogeneous systems, i.e., processors and communication networks having either fixed priority or EDF schedulers.
On the relation between p-adic and ordinary strings

The amplitudes for the tree-level scattering of the open string tachyons, generalised to the field of p-adic numbers, define the p-adic string theory. There is empirical evidence of its relation to the ordinary string theory in the p → 1 limit. We revisit this limit from a worldsheet perspective and argue that it is naturally thought of as a continuum limit in the sense of the renormalisation group.
Peer Intervention To Increase Physical Activity Among Working Women

Peer Intervention to Increase Physical Activity Among Working Women Sheri A Rowland, PhD University of Nebraska Medical Center, 2017 Advisor: Bernice C. Yates PhD, RN Most Americans do not engage in enough healthy physical activity (PA), with working women particularly at-risk for inactivity. Workplace PA interventions have been effective, however studies using peers as the central theoretical strategy, have not been found. Social cognitive theory and social comparison theory were used to develop a peer-modeling workplace PA intervention. The aims of this experimental, two-group, preliminary study were: 1) assess intervention feasibility, 2) determine the intervention effect on cardiorespiratory fitness (primary outcome), and PA behavior, cardiovascular risk, self-efficacy, motivation, and social comparison, and 3) describe participant perceptions of the intervention using qualitative focus-group data. Female employees from a health system were randomized to either an attention control group (ACG) or an intervention group (IG). The ACG (n = 26) received general health information. The IG (n = 26) participated in six group sessions with a peer-model, received an exercise prescription, and PA information. Measures at baseline and 12-weeks were: PA (ActiGraph), VO2max (cycle ergometer), resting heart rate, glucose, lipids, and cardiovascular risk score. Using hierarchical linear modeling, no significant group by time effects were found. Although PA increased in both groups (F [df = 1] = 11.4, p = .002), the IG had greater improvements in measures of fitness and cardiovascular risk compared to the ACG. Both groups decreased in selfefficacy while motivation remained stable. The IG group increased in all measures of social comparison while the ACG dropped in comparisons of ability, opinions, modeling, and futureself. Focus-group data indicated peer-models were perceived to be credible, informative, and motivating. The intervention could be expanded to include more peer-model interaction and nutritional content. These findings support testing the intervention with a fully-powered study.
Atlas: Look-ahead scheduling using workload metrics

From video and music to user interface animations, a lot of real-time workloads run on today's desktops and mobile devices, yet commodity operating systems offer scheduling interfaces like nice-levels, priorities or shares that do not adequately convey timing requirements. Real-time research offers many solutions with strong timeliness guarantees, but they often require a periodic task model and ask the developer for information that is hard to obtain like execution times or reservation budgets. Within this design space of easy programming, but weak guarantees on one hand and strong guarantees, but harder development on the other, we propose Atlas, the Auto-Training Look-Ahead Scheduler. With a simple yet powerful interface it relies exclusively on data from the application domain: It uses deadlines to express timing requirements and workload metrics to express resource requirements. It replaces implicit knowledge of future job releases as provided by periodic tasks with explicit job submission to enable look-ahead scheduling. Using video playback as a dynamic high-throughput load, we show that the proposed workload metrics are sufficient for Atlas to know an application's execution time behavior ahead of time. Atlas' predictions have a typical relative error below 10%.
Mediterranean Diet and Health-Related Quality of Life in Two Cohorts of Community-Dwelling Older Adults

Introduction In older adults, the Mediterranean diet is associated with lower risk of chronic diseases, but its association with health-related quality of life (HRQL) is still uncertain. This study assessed the association between the Mediterranean diet and HRQL in 2 prospective cohorts of individuals aged ≥60 years in Spain. Methods The UAM-cohort (n = 2376) was selected in 2000/2001 and followed-up through 2003. At baseline, diet was collected with a food frequency questionnaire, which was used to develop an 8-item index of Mediterranean diet (UAM-MDP). The Seniors-ENRICA cohort (n = 1911) was recruited in 2008/2010 and followed-up through 2012. At baseline, a diet history was used to obtain food consumption. Mediterranean diet adherence was measured with the PREDIMED score and the Trichopoulou’s Mediterranean Diet Score (MSD). HRQL was assessed, at baseline and at the end of follow-up, with the physical and mental component summaries (PCS and MCS) of the SF-36 questionnaire in the UAM-cohort, and the SF-12v.2 questionnaire in the Seniors-ENRICA cohort. Analyses were conducted with linear regression, and adjusted for the main confounders including baseline HRQL. Results In the UAM-cohort, no significant associations between the UAM-MDP and the PCS or the MCS were found. In the Seniors-ENRICA cohort, a higher PREDIMED score was associated with a slightly better PCS; when compared with the lowest tertile of PREDIMED score, the beta coefficient (95% confidence interval) for PCS was 0.55 (-0.48 to 1.59) in the second tertile, and 1.34 (0.21 to 2.47) in the highest tertile. However, the PREDIMED score was non-significantly associated with a better MCS score. The MSD did not show an association with either the PCS or the MCS. Conclusions No clinically relevant association was found between the Mediterranean diet and HRQL in older adults in Spain.
Proteomics and disease: opportunities and challenges

Since the human genome was sequenced, there has been intense activity to understand the function of the 30 000 identified genes; attention has now turned to the products of genes — proteins. Proteomics is the large‐scale study of the structure and function of proteins; it includes the rapidly evolving field of disease proteomics, which aims to identify proteins involved in human disease and to understand how their expression, structure and function cause illness. Proteomics has identified proteins that offer promise as diagnostic or prognostic markers, or as therapeutic targets in a range of illnesses, including cancer, immune rejection after transplantation, and infectious diseases such as tuberculosis and malaria; it has the potential to allow patient‐tailored therapy. Some major challenges remain, both technical (eg, detecting “low‐abundance” proteins, and maintaining sample stability) and in data management (eg, correlating changes in proteins with disease processes).
Smooth Morphing of Handwritten Text

There are several approaches for pen-based systems to improve legibility of handwritten text, e.g. smoothing the strokes composing the characters and words. A very challenging solution is the smooth morphing approach: handwritten strokes are transformed gradually into perfectly legible characters provided by a previously executed handwriting recognition process. In this paper we present our approach to a smooth real-time metamorphosis of handwritten characters into clean typography. Our main contributions are a new hybrid algorithm for character mapping, heuristics for splitting and joining strokes, and finding a stroke mapping with the use of radial distances. We implemented our methods in a whiteboard application that provides intuitive to use editing operations due to floating menus and stroke gestures. The implementation is based on the Microsoft Tablet PC SDK and the handwriting recognizer provided with the Tablet PC operating system.
Control system for lower limb function training device by using internal model control

This paper presents a new control system for a lower limb function training device by the internal model control scheme. The proposed control method is able to estimate exercise capacity of patients without additional sensors, e.g. force sensor, pressure sensor, and EMG. The training device provides appropriate power when patients need support of pedaling in rehabilitation. A prototype of the training device is proposed, and effectiveness of disturbance estimation property of the internal model control scheme is shown in this paper.
Effectiveness of Cppi Strategies Under Discrete-Time Trading

The paper analyzes the effectiveness of the constant proportion portfolio insurance (CPPI) method under trading restrictions. If the CPPI method is applied in continuous time, the CPPI strategies provide a value above a floor level unless the price dynamics of the risky asset permit jumps. The risk of violating the floor protection is called gap risk. In practice, it is caused by liquidity constraints and price jumps. Both can be modelled in a setup where the price dynamics of the risky asset are described by a continuous-time stochastic process but trading is restricted to discrete time. We propose a discrete-time version of the continuous-time CPPI strategies which satisfies three conditions. The resulting strategies are self-financing, the asset exposure is non-negative and the value process converges. We determine risk measures such as the shortfall probability and the expected shortfall and discuss criteria which ensure that the gap risk does not increase to a level which contradicts the original intention of portfolio insurance. In addition, we introduce proportional transaction costs and analyze their effects on the risk profile.
Mining the history of synchronous changes to refine code ownership

When software repositories are mined, two distinct sources of information are usually explored: the history log and snapshots of the system. Results of analyses derived from these two sources are biased by the frequency with which developers commit their changes. We argue that the usage of mainstream SCM systems influences the way that developers work. For example, since it is tedious to resolve conflicts due to parallel commits, developers tend to minimize conflicts by not contemporarily modifying the same file. This however defeats one of the purposes of such systems. We mine repositories created by our Syde tool, which records every change by every developer in multi-developer projects. This new source of information can augment the accuracy of analyses and breaks new ground in terms of how such information can assist developers. In this paper we illustrate how the information we mine can help to provide a refined notion of code ownership. As a case study, we analyze the developers' activities of the development of a commercial system.
Gender and Racial Discrimination in Pay and Promotion for NHS Nurses

For many years the NHS has been subject to allegations that gender and racial discrimination are a feature of the internal labour market for qualified nurses. This paper examines this issue with regard to the promotion process using 1994 survey data. We start by rejecting the assumption of covariate exogeneity inherent in the ordered probit model. A full simultaneous model is then developed which has important consequences for estimates of the influence of gender, ethnicity, training and career interruptions. We find evidence of significant differences in speed of promotion between gender and ethnic groups, which imply large differences in career earnings.
JEnsembl: a version-aware Java API to Ensembl data systems

Motivation: The Ensembl Project provides release-specific Perl APIs for efficient high-level programmatic access to data stored in various Ensembl database schema. Although Perl scripts are perfectly suited for processing large volumes of text-based data, Perl is not ideal for developing large-scale software applications nor embedding in graphical interfaces. The provision of a novel Java API would facilitate type-safe, modular, object-orientated development of new Bioinformatics tools with which to access, analyse and visualize Ensembl data. Results: The JEnsembl API implementation provides basic data retrieval and manipulation functionality from the Core, Compara and Variation databases for all species in Ensembl and EnsemblGenomes and is a platform for the development of a richer API to Ensembl datasources. The JEnsembl architecture uses a text-based configuration module to provide evolving, versioned mappings from database schema to code objects. A single installation of the JEnsembl API can therefore simultaneously and transparently connect to current and previous database instances (such as those in the public archive) thus facilitating better analysis repeatability and allowing ‘through time’ comparative analyses to be performed. Availability: Project development, released code libraries, Maven repository and documentation are hosted at SourceForge (http://jensembl.sourceforge.net). Contact: jensembl-develop@lists.sf. net, andy.law@roslin.ed.ac.uk, trevor.paterson@roslin.ed.ac.uk
Electromagnetic Wave Propagation Modeling Using the Ant Colony Optimization Algorithm

The Ant Colony Optimization algorithm a multiagent approach to combinatorial optimization problems is introduced for a simple ray tracing performed on only an ordinary bitmap describing a two-dimensional scenario. This bitmap can be obtained as a simple scan where different colors represent different mediums or obstacles. It is shown that using presented algorithm a path minimizing the wave traveling time can be found according to the Fermat’s principle. An example of practical application is a simple ray tracing performed on only an ordinary scanned bitmap of the city map. Together with the Berg’s recursive model a non-line-of-sight path loss could be calculated without any need of building database. In this way the coverage predictions for urban microcells could become extremely easy and fast to apply.
VQM : A 3 D Video Quality Measure

Three dimensional television (3DTV) and free viewpoint television (FTV) are believed to be the future of television broadcasting that would bring a more life-like and visually immersive home entertainment experience. These technologies will provide the users with the freedom to navigate through the scene and choosing a desired viewpoint. A desired viewpoint video can be synthesized at the receiver side using depth image-based rendering (DIBR). In this paper, we present a new method for objectively evaluating the quality of stereoscopic 3D videos generated by DIBR. The quality of the synthesized 3D videos is affected by errors or noise in the depth maps. To evaluate the distortions in DIBR-based 3D videos a reference depth is needed for evaluation. In this paper, we show how to derive an ideal depth estimate at each pixel value that would constitute a distortion-free rendered video. The ideal depth estimate will then be used to derive three distortion measures to objectify the visual discomfort in the stereoscopic videos. The three measures are defined as temporal outliers (TO), temporal inconsistencies (TI), and spatial outliers (SO). The combination of the three measures will constitute a visual quality measure for 3D DIBR-based videos, 3VQM. 3VQM can be both derived in a full-reference (FR-3VQM) and noreference (NR-3VQM) scenarios. Finally, the proposed measure will be verified and validated against a fully conducted subjective evaluation and compared to 2D-based quality measures used in literature to evaluate 3D video quality. The results show that our proposed measure is significantly accurate, coherent and consistent with the subjective scores and outperforms the few 2D-based metrics proposed in literature.
Up-Regulated Expression of LAMP2 and Autophagy Activity during Neuroendocrine Differentiation of Prostate Cancer LNCaP Cells

Neuroendocrine (NE) prostate cancer (PCa) is a highly aggressive subtype of prostate cancer associated with resistance to androgen ablation therapy. In this study, we used LNCaP prostate cancer cells cultured in a serum-free medium for 6 days as a NE model of prostate cancer. Serum deprivation increased the expression of NE markers such as neuron-specific enolase (NSE) and βIII tubulin (βIII tub) and decreased the expression of the androgen receptor protein in LNCaP cells. Using cDNA microarrays, we compared gene expression profiles of NE cells and non-differentiated LNCaP cells. We identified up-regulation of 155 genes, among them LAMP2, a lysosomal membrane protein involved in lysosomal stability and autophagy. We then confirmed up-regulation of LAMP2 in NE cells by qRT-PCR, Western blot and confocal microscopy assays, showing that mRNA up-regulation correlated with increased levels of LAMP2 protein. Subsequently, we determined autophagy activity in NE cells by assessing the protein levels of SQSTM/p62 and LC3 by Western blot and LC3 and Atg5 mRNAs content by qRT-PCR. The decreased levels of SQSTM/p62 was accompanied by an enhanced expression of LC3 and ATG5, suggesting activation of autophagy in NE cells. Blockage of autophagy with 1μM AKT inhibitor IV, or by silencing Beclin 1 and Atg5, prevented NE cell differentiation, as revealed by decreased levels of the NE markers. In addition, AKT inhibitor IV as well as Beclin1 and Atg5 kwockdown attenuated LAMP2 expression in NE cells. On the other hand, LAMP2 knockdown by siRNA led to a marked blockage of autophagy, prevention of NE differentiation and decrease of cell survival. Taken together, these results suggest that LAMP2 overexpression assists NE differentiation of LNCaP cells induced by serum deprivation and facilitates autophagy activity in order to attain the NE phenotype and cell survival. LAMP2 could thus be a potential biomarker and potential target for NE prostate cancer.
Neural network based adaptive non linear PID controller for non-holonomic mobile robot

This paper presents an approach for velocity and orientation tracking control of a nonholonomic mobile robot based on an adaptive controller. The developed PID controller is based on analog neural networks. The feed forward neural networks controller is trained on-line to find the inverse kinematical model, which controls the outputs of the mobile robot system. The proposed controller has a better performance because of its capability of continuous online learning due to neural network. The simulation results for a differentially driven nonholonomic mobile robot are presented to establish the better performance of the proposed adaptive controller.
Autonomic body sensor networks

Recent advances in Body Sensor Networks (BSNs) and ambient assistive technologies have facilitated the realisation of technology enabled assisted living. Integrating ambient sensors with wearable sensors will not only enable comprehensive health monitoring of the user, but by utilising network resources from ambient sensors, it could also greatly prolong the battery lifetime of wearable sensors, extend the coverage of BSNs and enable context aware sensing. The challenge lies in the complex management of these two platforms. Autonomic sensing provides a solution by allowing the sensor network to manage itself. This paper proposes a self-organising approach for an integrated ambient and wearable sensor network. A multi-cluster network design is adopted in the proposed approach, and the network structure is limited to having a maximum of two hops for real-time requirements. In addition, to maximise the lifetime and reduce signal losses of the network, a cluster-head selection mechanism using a Maximum A Posteriori (MAP) estimation technique is designed based on sensors' remaining battery, connectivity and distance to the base station. This approach enables full connections of a two-hop sensor network in a data collecting scenario, and it has been shown to outperform the conventional sensor network approach, the Low-Energy Adaptive Clustering Hierarchy (LEACH).
French version of the profiles of occupational engagement in people with severe mental illness: Translation, adaptation, and validation

ABSTRACT Occupational engagement is affected in many persons with severe mental illness (SMI) because of personal, occupational, and environmental issues. However, no French assessment tool measuring occupational engagement in these persons is currently available. The objectives of the study were to translate the “Profiles of Occupational Engagement in People with Severe Mental Illness” (POES), including a time use diary and an interview, and to measure the interrater reliability of the French version. First, a transcultural validation process of the English version of the POES into French was completed. Second, to determine interrater reliability, ten evaluators assessed 23 participants with an SMI. Specific concepts were clarified with the author of the original tool. No items were added or removed following the translation process. An interview guide was developed to assist the interview on occupational engagement. Analyses indicated high interrater reliability (ICC = 0.94). French-speaking clinicians will be able to use a validated French version of the POES to better capture occupational engagement in people with SMI, facilitating the individualisation of interventions.