Miracle-dz/UniFAR-FTUs huggingface dataset:
Shore-MT: a scalable storage manager for the multicore era

Database storage managers have long been able to efficiently handle multiple concurrent requests. Until recently, however, a computer contained only a few single-core CPUs, and therefore only a few transactions could simultaneously access the storage manager's internal structures. This allowed storage managers to use non-scalable approaches without any penalty. With the arrival of multicore chips, however, this situation is rapidly changing. More and more threads can run in parallel, stressing the internal scalability of the storage manager. Systems optimized for high performance at a limited number of cores are not assured similarly high performance at a higher core count, because unanticipated scalability obstacles arise. We benchmark four popular open-source storage managers (Shore, BerkeleyDB, MySQL, and PostgreSQL) on a modern multicore machine, and find that they all suffer in terms of scalability. We briefly examine the bottlenecks in the various storage engines. We then present Shore-MT, a multithreaded and highly scalable version of Shore which we developed by identifying and successively removing internal bottlenecks. When compared to other DBMS, Shore-MT exhibits superior scalability and 2--4 times higher absolute throughput than its peers. We also show that designers should favor scalability to single-thread performance, and highlight important principles for writing scalable storage engines, illustrated with real examples from the development of Shore-MT.
The context toolkit: aiding the development of context-enabled applications

Context-enabled applications are just emerging and promisericher interaction by taking environmental context into account.However, they are difficult to build due to their distributednature and the use of unconventional sensors. The concepts oftoolkits and widget libraries in graphical user interfaces has beentremendously successtil, allowing programmers to leverage offexisting building blocks to build interactive systems more easily.We introduce the concept of context widgets that mediate betweenthe environment and the application in the same way graphicalwidgets mediate between the user and the application. We illustratethe concept of context widgets with the beginnings of a widgetlibrary we have developed for sensing presence, identity andactivity of people and things. We assess the success of ourapproach with two example context-enabled applications we havebuilt and an existing application to which we have addedcontext-sensing capabilities.
EMG and visual based HMI for hands-free control of an intelligent wheelchair

This paper presents a new human-machine interaction (HMI) method designed for hands-free control of electric wheelchairs. Both forehead electromyography (EMG) signals and color face image information is jointly used to identify winking and jaw clenching movements. Five winking and jaw clenching movement patterns are selected and classified, mapping into five control commands to drive a simulated wheelchair in an office environment. Six subjects participated in the experiments and the result shows that this new control method can work well and reliably.
TNF Inhibits Notch-1 in Skeletal Muscle Cells by Ezh2 and DNA Methylation Mediated Repression: Implications in Duchenne Muscular Dystrophy

Background Classical NF-κB signaling functions as a negative regulator of skeletal myogenesis through potentially multiple mechanisms. The inhibitory actions of TNFα on skeletal muscle differentiation are mediated in part through sustained NF-κB activity. In dystrophic muscles, NF-κB activity is compartmentalized to myofibers to inhibit regeneration by limiting the number of myogenic progenitor cells. This regulation coincides with elevated levels of muscle derived TNFα that is also under IKKβ and NF-κB control. Methodology/Principal Findings Based on these findings we speculated that in DMD, TNFα secreted from myotubes inhibits regeneration by directly acting on satellite cells. Analysis of several satellite cell regulators revealed that TNFα is capable of inhibiting Notch-1 in satellite cells and C2C12 myoblasts, which was also found to be dependent on NF-κB. Notch-1 inhibition occurred at the mRNA level suggesting a transcriptional repression mechanism. Unlike its classical mode of action, TNFα stimulated the recruitment of Ezh2 and Dnmt-3b to coordinate histone and DNA methylation, respectively. Dnmt-3b recruitment was dependent on Ezh2. Conclusions/Significance We propose that in dystrophic muscles, elevated levels of TNFα and NF-κB inhibit the regenerative potential of satellite cells via epigenetic silencing of the Notch-1 gene.
New method to study bacterial adhesion to meat

A new method was developed for the study of bacterial adhesion to meat surfaces. Thin slices of meat (40 microns thick) were inserted into a specially designed observation chamber. The meat slices were then exposed to a bacterial suspension (ca. 10(6) CFU.ml-1) to initiate adhesion (20 min of contact time) and subsequently rinsed to eliminate nonadherent bacteria. Because of the special chamber design, the disruptive force exerted on the bacteria during rinsing (shear stress) was uniform over the whole surface of the meat slices, was constant, and could be varied from 0 to 0.08 N.m-2. After being rinsed, the meat slices were stained with basic fuschin and observed under light microscopy to determine the number and distribution of adherent bacteria. This new method was used to study the adhesion of Acinetobacter strain LD2, a Lactobacillus sp. , and Pseudomonas fluorescens to slices of beef fat and tendon. At 25 degrees C, most (greater than or equal to 99.9%) of the cells of the Lactobacillus sp. deposited on the meat were washed off the surface during rinsing (0.05 N.m-2), whereas a large number (ca. 10(5) CFU.cm-2) of Acinetobacter strain LD2 and P. fluorescens cells remained adherent. The extent of adhesion was similar on fat and tendon, and adherent bacteria were distributed evenly over the whole surface of the slices. This preliminary study indicates that the combined use of thin slices of meat and of the observation chamber provides us with the means to more accurately study bacterial adhesion to meat surfaces.
Mirror-like brain responses to observed touch and personality dimensions

The last years have shown a growing interest in research on the neural mechanisms for perceiving and understanding social interactions. Only very recently, a role for somatosensation in social perception has been suggested. Numerous studies reported vicarious responses in the primary somatosensory cortex (SI) and other areas merely when seeing others being touched. Moreover, it has been demonstrated that these vicarious somatosensory responses can be linked with inter-individual differences in empathy. However, beyond empathy other personality traits have been shown to interact with social perception and behavior. Here we tested if personality traits according to the Five-Factor-Model interact with vicarious activation in somatosensory brain regions. We conducted a functional magnetic resonance imaging (fMRI) study in which subjects viewed video clips showing simple non-painful touch to a hand and a control condition including the same visual and motion parts. Results revealed vicarious somatosensory activation when viewing the touched hand, as expected. Vicarious activation in SI showed a trend for a positive correlation with the personality trait openness to experience. Moreover, mirror-like responses in the insula were strongly correlated with the personality trait conscientiousness, suggesting links to processes of self-control. We conclude that vicarious brain responses to seen touch seem to interact with personality traits.
DiRT - Dust in Real-time: The Specification Process

Dust in Real-time (DiRT) is a 3D dust visualization program and interactive computer benchmarking tool designed to model real world dust dynamics in a virtual environment, in real-time. The interactive benchmarking tool allows users to track and gauge the performance of their system’s ability to render the dust by issuing real-time system and environment related reports. The system reports update, in accordance with the user’s quality and realism settings. Similar to a video game, users will be able to “play” during the simulation by way of a simple vehicle simulator. This paper presents details of DiRT’s UML requirements specification, software architecture specifics, high and low-level design details, user interface principles and snapshots.
Sparse Signal Reconstruction from Compressed Measurements using Hybrid Differential Evolution

One of the main challenges in Compressed Sensing (CS) is the sparse signal reconstruction from less number ofnon-adaptive linear measurements. The recovery process, based on l0 minimization, involves exhaustive search for non-zero entries in the estimated signal thus making it practically intractable. This workpresents a n ovel technique of recovering a K -sparse signal from compressive measurements using hybrid Differential Evolution (DE). In the proposed algorithm, the slow convergence of conventional DE is accelerated with the help of Separable Surrogate Functionals (SSF) algorithm. Thecombination of DE with SSF makes the l0 minimization faster and accurate. The effectiveness of the hybrid DEis substantiated by comparing its results with those of SSF and Parallel Coordinate Descent (PCD) algorithms. The performance ofthe combined DE-SSF methodis further validatedby reconstructing a synthetic one- dimensional sparse signalaccurately from only a small number of compressive measurements.
Ursa minor: versatile cluster-based storage

No single encoding scheme or fault model is optimal for all data. A versatile storage system allows them to be matched to access patterns, reliability requirements, and cost goals on a per-data item basis. Ursa Minor is a cluster-based storage system that allows data-specific selection of, and on-line changes to, encoding schemes and fault models. Thus, different data types can share a scalable storage infrastructure and still enjoy specialized choices, rather than suffering from "one size fits all. " Experiments with Ursa Minor show performance benefits of 2-3× when using specialized choices as opposed to a single, more general, configuration. Experiments also show that a single cluster supporting multiple workloads simultaneously is much more efficient when the choices are specialized for each distribution rather than forced to use a "one size fits all" configuration. When using the specialized distributions, aggregate cluster throughput nearly doubled.
Object Oriented Design through game development in XNA

The difficulties in teaching introductory programming, Object Oriented Design (OOD) and Object Oriented Programming (OOP) are well known, whereas game attraction in young teens as well as the strong appeal that mobile technologies has on students is being debated as a means to engage students and overcome such difficulties. This work presents a one term teaching experience on a K-11 class focusing on learning OOD and OOP by using a versatile framework such as XNA to build games. The pedagogical approach, the context and the contents of the course are presented, with a focus on the challenges in presenting advanced curriculum topics in a classroom with highly differentiated students and on the strategies used to overcome such difficulties. The main elements of the approach are: a project and inquiry based pedagogical method; an “object first” approach leading to designing an UML class and a sequence diagram from the beginning, formation of a shared memory of student's solutions to assignments and a blog used for supporting class activities and fostering self-reflection and critical thinking. A content analysis of the blog as well as of the data collected during face to face conversation both in the laboratory and in class reveals common errors and suggests approaches for avoiding them.
A Personalized Online News Recommendation System

Traditional news recommendation systems strive to adapt their services to individual users by virtue of both user and news context information. This paper describes personalized news recommendation approach based on dynamic updating policy and collaborative filtering. Adaptive user profiling is a principled framework for news selection based on the intrinsic property of user interest presented, with a good balance between the novelty and diversity of the recommendation result. Also it considers the exclusive characteristics like news context, access patterns, popularity of the news and recency. Collaborative filtering approach can efficiently capture user’s behavior in case where the overlap in historical assumptions across users in relatively high and the context universe is almost static. The major issue with the personalized news recommendation system is scalability. This paper addresses the above mentioned issue with the help of hadoop framework. Experiments on a collection of sports related news obtained from various news websites demonstrate the efficiency of the proposed approach.
Gaze Estimation Based on 3D Face Structure and Pupil Centers

It is a challenging problem to realize a robust and low cost gaze estimation system. Most existing feature-based gaze estimation methods strongly rely on cornea reflections, which are unstable to glasses, head movements and natural light. In this paper, we propose a novel gaze estimation method without use of cornea reflections based on a stereo camera system. Firstly, 3D Active Shape Models (ASM) is reconstructed using stereo vision to represent 3D face structure. Then, without use of cornea reflections, a 3D Pupil-Eye-Contours based feature is proposed to represent human gaze information. What's more, precise estimation of head poses based on 3D face structure is employed to rectify the 3D pupil centers and eye contours for improving the ability of tolerance to head movements. Experiments on fifteen subjects show that the system is accurate and allows natural head movements.
Factor structure of the Parent Emotional Reaction Questionnaire: analysis and validation

Background Although many children experience violence and abuse each year, there is a lack of instruments measuring parents’ emotional reactions to these events. One instrument, the Parent Emotional Reaction Questionnaire (PERQ), allows researchers and clinicians to survey a broad spectrum of parents’ feelings directly related to their children's traumatic experiences. The objectives of this study were: (1) to examine the factor structure and the internal consistency of the PERQ; (2) to evaluate the discriminant validity of the instrument; and (3) to measure whether potential subscales are sensitive to change. Method A Norwegian sample of 120 primary caregivers of a clinical sample of 120 traumatized children and youths (M age=14.7, SD=2.2; 79.8% girls) were asked to report their emotional reactions to their child's self-reported worst trauma. Exploratory factor analysis was used to explore the underlying factor structure of the data. Results The analysis of the PERQ showed a three-factor structure, conceptualized as PERQdistress, PERQshame, and PERQguilt. The internal consistencies of all three subscales were satisfactory. The correlations between the PERQ subscales and two other parental measurements revealed small to moderate effect sizes, supporting the discriminant validity of the PERQ subscales. The differences in sum scores of the PERQ subscales before and after a therapeutic intervention suggest that all of the subscales were sensitive to change. Conclusions Study findings support the validity of conceptualizing the PERQ as three separate subscales that capture clinically meaningful features of parents’ feelings after their children have experienced trauma. However, the subscales need to be further evaluated using a larger sample size and a confirmatory factor analytic approach.
Estimating Standardized Effect Sizes for Two- and Three-Level Partially Nested Data

ABSTRACT Although previous research has discussed an effect size estimator for partially nested cluster randomized designs, the existing estimator (a) is not efficient when used with primary data, (b) can be biased when the homogeneity of variance assumption is violated, and (c) has not yet been empirically evaluated for its finite sample properties. The present paper addresses these limitations by proposing an alternative maximum likelihood estimator for obtaining standardized mean difference effect size and the corresponding sampling variance for partially nested data, as well as the variants that do not make an assumption of homogeneity of variance. The typical estimator, denoted as d (dW with pooled SD and dC with control arm SD), requires input of summary statistics such as observed means, variances, and the intraclass correlation, and is useful for meta-analyses and secondary data analyses; the newly proposed estimator ( and ) takes parameter estimates from a correctly specified multilevel model as input and is mainly of interest to researchers doing primary research. The simulation results showed that the two methods (d and ) produced unbiased point and variance estimates for effect size. As expected, in general, was more efficient than d with unequal cluster sizes, especially with large average cluster size and large intraclass correlation. Furthermore, under heterogeneous variances, demonstrated a greater relative efficiency with small sample size for the unclustered control arm. Real data examples, one from a youth preventive program and one from an eating disorder intervention, were used to demonstrate the methods presented. In addition, we extend the discussion to a scenario with a three-level treatment arm and an unclustered control arm, and illustrate the procedures for effect size estimation using a hypothetical example of multiple therapy groups of clients clustered within therapists.
Query Processing, Approximation, and Resource Management in a Data Stream Management System

This paper describes our ongoing work developing the Stanford Stream Data Manager (STREAM), a system for executing continuous queries over multiple continuous data streams. The STREAM system supports a declarative query language, and it copes with high data rates and query workloads by providing approximate answers when resources are limited. This paper describes specific contributions made so far and enumerates our next steps in developing a general-purpose Data Stream Management System.
Photometric and Chromatic Calibration for Multi-Projector Tiled Displays

We address the problem of calibrating the colors of a multiple projector tiled display. Differences in the characteristics of the projectors lead to varying color and intensity among the tiles of the display. These differences do generally not only arise between two different projectors, but also between different spatial locations on the projected surface of one single projector. In this paper, we present two algorithms for calibrating the colors of a tiled display. The first method is an automatic procedure to make the luminance uniform over the projected surface of one single beamer, using a common digital camera as a luminance measuring device. The second method aims at uniformizing the colors of multiple projectors by computing the set of color commonly displayable by all the beamers (the common gamut). We show how to find an optimal color gamut displayable by all the projectors in linear time, and derive the color conversion from one color gamut to the common gamut. We successfully tested the method on a tiled display made of 48 projectors with large chrominance shifts.
Comparison of trends and frequencies of drought in central North China and sub-Saharan Africa from 1901 to 2010

Abstract This study compares the trends and frequencies of drought between central North China (CNC) and (SSA) for the periods 1901–2010 and 1951–2010. The Standardized Precipitation Evapotranspiration Index (SPEI) and Self-Calibrating Palmer Drought Severity Index (sc-PDSI) are used to assess the drought trends and frequencies. In general, the results exhibit downward trends of drought index values and upward trends of drought frequencies over CNC and SSA. A high rate of the trends’ slopes for the drought index and a low rate of the frequencies’ slopes is found over CNC with respect to SPEI and sc-PDSI. Furthermore, some abrupt changes are revealed after applying the sequential Mann–Kendall test to detect change points. These findings offer insight into the trends and frequencies of drought over the regions studied. Further analysis needs to be undertaken to understand the mechanisms underlying the occurrence of drought in these areas.
How to build up the actionable knowledge base: the role of ‘best fit’ framework synthesis for studies of improvement in healthcare

Increasing recognition of the role and value of theory in improvement work in healthcare offers the prospect of capitalising upon, and consolidating, actionable lessons from synthesis of improvement projects and initiatives. We propose that informed use of theory can (i) provide a mechanism by which to collect and organise data from a body of improvement work, (ii) offer a framework for analysis and identification of lessons learnt and (iii) facilitate an evaluation of the feasibility, effectiveness and acceptability of improvement programmes. Improvement practitioners can benefit from using an underpinning external structure as a lens by which to examine the specific achievements of their own projects alongside comparable initiatives led by others. We demonstrate the utility of a method known as ‘best fit framework synthesis’ (BFFS) in offering a ubiquitous and versatile means by which to collect, analyse and evaluate improvement work in healthcare. First reported in 2011, BFFS represents a pragmatic, flexible approach to integrating theory with findings from practice. A deductive phase, where a review team seeks to accommodate a substantial part of the data, is followed by an inductive phase, in which the team explores data not accommodated by the framework. We explore the potential for BFFS within improvement work by drawing upon the evidence synthesis methodology literature and practical examples of improvement work reported in BMJ Quality and Safety (2011–2015). We suggest four variants of BFFS that may have particular value in synthesising a body of improvement work. We conclude that BFFS, alongside other approaches that seek to optimise the contribution of theory to improvement work, represents one important enabling mechanism by which to establish the rigour and scientific credentials of the emerging discipline of ‘improvement science’.
Influence of adult attachment insecurities on parenting self-esteem: the mediating role of dyadic adjustment

Background: Parenting self-esteem includes two global components, parents’ self-efficacy and satisfaction with their parental role, and has a crucial role in parent–child interactions. The purpose of this study was to develop an integrative model linking adult attachment insecurities, dyadic adjustment, and parenting self-esteem. Methods: The study involved 118 pairs (236 subjects) of heterosexual parents of a firstborn child aged 0–6 years. They were administered the Experiences in Close Relationships-Revised (ECR-R) questionnaire, the Dyadic Adjustment Scale, and the Parenting Sense of Competence Scale. Results: Path analysis was used to design and test a theoretical integrative model, achieving a good fit with the data. Findings showed that dyadic adjustment mediates the negative influence on parenting self-efficacy of both attachment anxiety and attachment avoidance. Parenting satisfaction is positively influenced by parenting self-efficacy and negatively affected by child’s age. Attachment anxiety negatively influences parenting satisfaction. Conclusion: Our findings are in line with the theoretical expectations and have promising implications for future research and intervention programs designed to improve parenting self-esteem.