Miracle-dz/UniFAR-FTUs huggingface dataset:
Cross-case Methodology: Bringing Rigour to Community and Systems Change Research and Evaluation

Cross-case study methodology is a more appropriate and still rigorous methodology for community and systems change research and evaluation. It supports learning about effective implementation, community capacity building, and resident engagementall core elements of community and systems change efforts. It also communicates more effectively to non-researchers and evaluators if, how, and why community and systems change occurred through the use of a narrative that combines qualitative and quantitative data to tell a story. The application of the cross-case study methodology, adapted from Yin's cross-case synthesis approach, requires five essential steps: developing a theory of change, establishing a measurement framework that reflects methodological and data source triangulation, developing a cross-case study protocol and building a database, analysing and interpreting the findings, and communicating the results. This methodology was applied to the evaluation of the Safe Start Demonstration Project, a national community and systems change effort funded by the US Department of Justice, Office of Juvenile Justice and Delinquency Prevention. This methodology has all the attributes of scientific rigour. In this paper, we argue for a reconsideration of case study research by funders, policymakers, researchers, and evaluators and advance the cross-case methodology as the emerging standard for community and systems change research and evaluation. Copyright (c) 2011 John Wiley & Sons, Ltd. KW: Juvenile justice; Juvenile delinquency; Language: en
Influencing Factors Analysis of People's Answering Behaviours on Social Network Based Questions

Recently the social question/answering systems have become a natural way for people to get information from their social connections. Despite its popularity in knowledge sharing, its development still faces several challenges, among which a notable one is that a majority of questions get no response. How to improve the response ratio and reduce the number of unanswered social questions has become a challenging problem. Though some research in this context has been well studied, intrinsic factors that reveal profiles of social answerers are still less understood. In this paper, we try to discover: what kind of person is likely to be an answerer? To answer this question, we study multiple hypothetical factors from the perspectives of social and personal analysis. A set of experiments are conducted to identify the relationship between these factors and the action of answering. We present a comprehensive description alongside our analysis of behavioural patterns of answerers in the scenario of social information seeking.
Object Class Recognition at a Glance

This video shows our real-time object class recognition system at work. Object class recognition is a very challenging problem. The difficulty lies in capturing the variability of appearance and shape of different objects belonging to the same class, while avoiding confusing objects from different classes. However, state of the art algorithms such as [2] are capable of delivering high classification accuracy at interactive speed when dealing with a limited number of classes (around ten). Following the texton-based modeling approach in [2] we have developed an application for real-time segmentation and recognition of objects placed on a table top (figure 1). The system comprises two steps: object segmentation and classification. First, each object region is separated from the table top. This happens by running a patch-based classifier which discriminates between the class “table” and everything else. This technique is very different from more conventional background subtraction and is robust with respect to shadows, light changes and camera shake or motion. Second, once all the non-table connected regions have been extracted, they are classified as belonging to one of fifteen object classes using the same discriminative technique. Each classifier is a random forests discriminative model [1], [3] using pixel difference features. The classifier is learned similarly to [2] to achieve maximum generalisation with high efficiency and is designed to be invariant both to rotation and to small changes in scale. Our features are computed on both the RGB image (thus providing information about appearance) and on the binary segmentation mask (thus capturing information about object shape). In the learnt random decision trees each node is hence associated to either appearance or shape. Figure 2 Fig. 2
Public and Private Families: An Introduction

Part I: Introduction Chapter 1:Public and Private Families Chapter 2:The History of the Family Part II: Gender, Class, and Race-Ethnicity Chapter 3: Gender and Families Chapter 4:Social Class and Families Chapter 5: Race, Ethnicity, and Families Part III: Sexuality, Partnership, and Marriage Chapter 6:Sexualities Chapter 7:Cohabitation and Marriage Chapter 8:Work and Families Part IV: Links Across the Generations Chapter 9:Children and Parents Chapter 10: The Elderly and Their Families Part V: Conflict, Disruption, and Reconstitution Chapter 11: Domestic Violence Chapter 12: Divorce Chapter 13: Remarriage and Stepfamilies
Ideas on improving Linux infrastructure for performance on multi-core platforms

With maturing compiler technologies, compiletime analysis can be a very powerful tool for optimizing and monitoring code on any architecture. In combination with modern runtime analysis tools and existing program interfaces to monitor hardware counters, we will survey modern techniques for analyzing performance issues. We propose using performance counter data and sequences of performance events to trigger event handlers in either the application or the operating system. In this way, sequence of performance events can be your debugging breakpoint or a callback. This paper will try to bridge the capabilities of advanced performance monitoring with common software development infrastructure (debuggers, gcc, loader, process scheduler). One proposed approach is to extend the run-time environment with an interface layer that will filter performance profiles, capture sequences of performance hazards, and provide summary data to the OS, debuggers, or application. With the introduction of hyper-threading technology several years ago, there were obvious challenges to look beyond a single running process to monitor and schedule compute intensive processes on multi-threaded cores. Multi-level memory hierarchy and scaling on SMP systems complicated the situation even further, causing essential changes in kernel scheduler and performance tools. In the era of parallel and platform computing, we rely less on single execution process performance—with each component optimized by the compiler—and it becomes important to evaluate performance of the platform as a whole. The new concept of performance adaptive schedulers is one example of intelligently maximizing the performance on platform level of CMP systems. Performance data at higher granularity and a concept of processor efficiency per functionality can be applied to making intelligent decisions on process scheduling in the operating system. Towards the end, we will suggest particular improvements in performance and run-time tools as a reflection of proposed approaches and transition to platform-level optimization goals.
Where are your eyes going to look during reading? A critical evaluation of saccade targeting hypothesis

The word-based account of saccades drawn by a central gravity of the PVL is supported by two pillars of evidences. The first is the finding of the initial fixation location on a word resembled a normal distribution (Rayner, 1979). The other is the finding of a moderate slope coefficient between the launch site and the landing site (b=0.49, see McConkie, Kerr, Reddix, & Zola, 1988). Four simulations on different saccade targeting strategies and one eye-movement experiment of Chinese reading have been conducted to evaluate the two findings. We demonstrated that the current understanding of the word-based account is not conclusive by showing an alternative strategy of the word-based account and identifying the problem with the calculation of the slope coefficient. Although almost all the computational models of eye-movement control during reading have built on the two findings, future efforts should be directed to understand the precise contribution of different saccade targeting strategies, and to know how their weighting might vary across desperate writing systems.
A new generalized LVQ algorithm via harmonic to minimum distance measure transition

We present a novel generalized learning vector quantization (LVQ) framework called the harmonic to minimum generalized LVQ algorithm (H2M-GLVQ). Through incorporating the distance measure transition procedure from harmonic average distance to minimum distance, the H2M-GLVQ cost function is gradually changing from the soft model to the hard model. Our proposed method, at the early training stage, can effectively tackle the initialization sensitivity problem associated with the original generalized LVQ algorithm while the convergence of the algorithm can be ensured by the hard model in the later training stage. Experimental results have shown the superior performance of the H2M-GLVQ algorithm over the generalized LVQ and one of its variants on some artificial multi-modal datasets
Myocardial Blood Flow during General Anesthesia with Xenon in Humans: A Positron Emission Tomography Study

Background:Xenon has only minimal hemodynamic side effects and induces pharmacologic preconditioning. Thus, the use of xenon could be an interesting option in patients at risk for perioperative myocardial ischemia. However, little is known about the effects of xenon anesthesia on myocardial blood flow (MBF) and coronary vascular resistance in humans. Methods:Myocardial blood flow was noninvasively quantified by H215O positron emission tomography in six healthy volunteers (age: 38 ± 8 yr). MBF was measured at baseline and during general anesthesia induced with propofol and maintained with xenon, 59 ± 0%. Absolute quantification of MBF was started after the calculated plasma concentration of propofol had decreased to less than 1.5 &mgr;g · ml−1. Results:Compared with baseline (MBFbaseline, 1.03 ± 0.09 ml · min−1 · g −1; mean ± SD), MBF was decreased insignificantly by xenon (MBFxenon, 0.80 ± 0.22 ml · min−1 · g−1; −21%, P = 0.11). Xenon decreased the rate–pressure product (RPP; heart rate × systolic arterial pressure), an indicator of cardiac work and myocardial oxygen consumption (−15%, P < 0.04). When correcting for the RPP, the decrease in MBF observed during xenon anesthesia was reduced to −9% (MBFcorr-xenon, 1.42 ± 0.28 ml · g−1 · mmHg−1vs. MBFcorr-baseline, 1.60 ± 0.28 ml · g−1 · mmHg−1, P = 0.32). Xenon did not affect the dependency of MBF on the RPP. Coronary vascular resistance did not significantly change (+15 ± 23%, P = 0.18) during xenon anesthesia. Conclusions:In healthy subjects, xenon has only minimal effects on coronary flow dynamics. These effects are probably of indirect nature, reflecting the decrease in myocardial oxygen consumption induced by the effects of xenon anesthesia on cardiac work.
Combining Learning and Word Sense Disambiguation for Intelligent User Profiling

Understanding user interests from text documents can provide support to personalized information recommendation services. Typically, these services automatically infer the user profile, a structured model of the user interests, from documents that were already deemed relevant by the user. Traditional keyword-based approaches are unable to capture the semantics of the user interests. This work proposes the integration of linguistic knowledge in the process of learning semantic user profiles that capture concepts concerning user interests. The proposed strategy consists of two steps. The first one is based on a word sense disambiguation technique that exploits the lexical database WordNet to select, among all the possible meanings (senses) of a polysemous word, the correct one. In the second step, a naive Bayes approach learns semantic sense-based user profiles as binary text classifiers (user-likes and user-dislikes) from disambiguated documents. Experiments have been conducted to compare the performance obtained by keyword-based profiles to that obtained by sense-based profiles. Both the classification accuracy and the effectiveness of the ranking imposed by the two different kinds of profile on the documents to be recommended have been considered. The main outcome is that the classification accuracy is increased with no improvement on the ranking. The conclusion is that the integration of linguistic knowledge in the learning process improves the classification of those documents whose classification score is close to the likes/dislikes threshold (the items for which the classification is highly uncertain).
Validation of a Brachial Cuff-Based Method for Estimating Central Systolic Blood Pressure

The prognostic value of central systolic blood pressure has been established recently. At present, its noninvasive assessment is limited by the need of dedicated equipment and trained operators. Moreover, ambulatory and home blood pressure monitoring of central pressures are not feasible. An algorithm enabling conventional automated oscillometric blood pressure monitors to assess central systolic pressure could be of value. We compared central systolic pressure, calculated with a transfer-function like method (ARCSolver algorithm), using waveforms recorded with a regular oscillometric cuff suitable for ambulatory measurements, with simultaneous high-fidelity invasive recordings, and with noninvasive estimations using a validated device, operating with radial tonometry and a generalized transfer function. Both studies revealed a good agreement between the oscillometric cuff-based central systolic pressure and the comparator. In the invasive study, composed of 30 patients, mean difference between oscillometric cuff/ARCSolver-based and invasive central systolic pressures was 3.0 mm Hg (SD: 6.0 mm Hg) with invasive calibration of brachial waveforms and −3.0 mm Hg (SD: 9.5 mm Hg) with noninvasive calibration of brachial waveforms. Results were similar when the reference method (radial tonometry/transfer function) was compared with invasive measurements. In the noninvasive study, composed of 111 patients, mean difference between oscillometric cuff/ARCSolver–derived and radial tonometry/transfer function–derived central systolic pressures was −0.5 mm Hg (SD: 4.7 mm Hg). In conclusion, a novel transfer function-like algorithm, using brachial cuff-based waveform recordings, is suited to provide a realistic estimation of central systolic pressure.
The Role of Activity Level in Orthopaedics: An Important Prognostic and Outcome Variable

A patient’s activity level is increasingly recognized as an important factor that can influence orthopaedic outcomes. Validated, reliable activity measurement tools now exist for the shoulder, hip, knee, and ankle. These tools can be directly applied as outcome measures that determine whether interventions restored function. It is now evident that activity level is a powerful prognostic factor for outcomes in orthopaedic procedures such as anterior cruciate ligament reconstruction, articular cartilage repair, and total joint arthroplasty. Yet despite the recent increase in studies that have made use of quantitative, joint-specific activity scales, much room remains for further understanding of the exact role of activity level in the progression, treatment, and patient perception of musculoskeletal disorders, particularly in the shoulder and ankle, as well as in pediatric patients.
Loss of Synaptic Connectivity, Particularly in Second Order Neurons Is a Key Feature of Diabetic Retinal Neuropathy in the Ins2Akita Mouse

Retinal neurodegeneration is a key component of diabetic retinopathy (DR), although the detailed neuronal damage remains ill-defined. Recent evidence suggests that in addition to amacrine and ganglion cell, diabetes may also impact on other retinal neurons. In this study, we examined retinal degenerative changes in Ins2Akita diabetic mice. In scotopic electroretinograms (ERG), b-wave and oscillatory potentials were severely impaired in 9-month old Ins2Akita mice. Despite no obvious pathology in fundoscopic examination, optical coherence tomography (OCT) revealed a progressive thinning of the retina from 3 months onwards. Cone but not rod photoreceptor loss was observed in 3-month-old diabetic mice. Severe impairment of synaptic connectivity at the outer plexiform layer (OPL) was detected in 9-month old Ins2Akita mice. Specifically, photoreceptor presynaptic ribbons were reduced by 25% and postsynaptic boutons by 70%, although the density of horizontal, rod- and cone-bipolar cells remained similar to non-diabetic controls. Significant reductions in GABAergic and glycinergic amacrine cells and Brn3a+ retinal ganglion cells were also observed in 9-month old Ins2Akita mice. In conclusion, the Ins2Akita mouse develops cone photoreceptor degeneration and the impairment of synaptic connectivity at the OPL, predominately resulting from the loss of postsynaptic terminal boutons. Our findings suggest that the Ins2Akita mouse is a good model to study diabetic retinal neuropathy.
The creation of an unethical work environment: organisational outcome‐based control systems

While research on outcome‐based control systems (and rewards) have been shown to lead to unethical behaviour, the same cannot be said when the research focuses on specific outcome‐based control systems. Both the positive and negative research focused on the effects of moderators on the outcome‐based control system and unethical behaviour link. The relationship was dependent on ethical climate, personality traits, and internal communications. While research yielded a slightly positive result, it was shown that ethical climate was likely a stronger contributor to ethical behaviour. The influence of client fee expectations, the influence of an audit program and unethical auditor behaviour was examined. Further research was necessary to see how people of different ages responded in terms of ethics. While the empirical research did not provide a complete positive link between outcome‐based control systems and unethical behaviour, it did show that the relationship could exist and was dependent often upon other factors, such as the ethical environment of the organisation. The purpose of this article was not to show that outcome‐based control systems are always going to drive employees to behave unethically, but that these systems can lead to unethical behaviour.
Integration of Molecular Profiling into the Lung Cancer Clinic

Individuals from five thoracic oncology centers in the United States recently met to discuss how to integrate molecular profiling into the care of all patients with carcinoma of the lung. Lung cancer is an area of medical oncology in which clinicians are beginning to use specific tumor-associated molecular aberrations to assign and/or prioritize targeted therapies for patients. At this early stage, multiple hurdles remain before molecular profiling becomes a routine part of thoracic oncology practice. Concrete collaborative next steps were discussed that could help lead to standardized methods across institutions. In particular, to develop specific targeted therapies for patients whose tumors harbor rare mutations, it will be important for multiple institutions to work together to identify appropriate candidates, design the appropriate trials, and execute the trials with adequate numbers to achieve the necessary end points. Implementation will facilitate realization of the promise of molecularly tailored therapy, which could lead to more effective treatments with fewer side effects. (Clin Cancer Res 2009;15(17):5317–22)
Assessing the accuracy of self-reported smoking status and impact of passive smoke exposure among pregnant Aboriginal and Torres Strait Islander women using cotinine biochemical validation.

INTRODUCTION AND AIMS A significant level of misreport or error occurs during questionnaire-based assessment of smoking behaviour. Failure to measure environmental tobacco smoke, and participant's inclination to under-report their smoking raise questions as to the accuracy of assessment. In order to establish an estimation of the possible error associated with such assessment, the accuracy of self-reported smoking status among a group of pregnant Aboriginal and Torres Strait Islander women was examined. DESIGN AND METHODS Women attending two Aboriginal Medical services in Far North Queensland for antenatal care were invited to participate. Women completed an interviewer assisted questionnaire relating to their smoking status and a 24 h diary of their exposure to nicotine and consumption of alcohol. Urine samples were analysed for cotinine using an Enzyme Linked Immunosorbent Assay. RESULTS Cotinine analysis indicated that 17% of women who reported that they were non-smokers were likely to have misreported this status, or be exposed to high levels of passive smoke. The only significant predictors of cotinine level were self-reported nicotine exposure (including passive smoke) and number of cigarettes smoked in the previous 24 h. Other individual and environmental variables had no significant influence on cotinine level using this analysis technique. DISCUSSION AND CONCLUSIONS The level of potential error in smoking assessment among this group was substantial. Exposure to environmental tobacco smoke might explain part of this error, but the reasons for misreport can only be speculated. This rate of misclassification should be taken into consideration in routine screening of antenatal women in primary health care.
Cultural Differences in Innovation Championing Strategies

This study examines the relationship between national culture and national preferences for innovation championing strategies for a sample of 1228 individuals in 30 countries. The study finds that the more uncertainty avoiding a society is the more people prefer champions to work through organizational norms, rules and procedures to promote innovation. The more power distant a society is the more people prefer champions to focus on gaining the support of those in authority before other actions are taken on an innovation rather than on building a broad base of support among organization members for new ideas. The more collectivist a society is the more people prefer champions to seek cross-functional support for the innovation effort.
EMC ’ 09 / Kyoto Practical Evaluation of ESD Protection Devices for High-speed Interface

In this paper, three types of ESD protection devices with low capacitance used for high-speed interfaces are evaluated by transmission line pulse measurement. Different suppression characteristics were observed for rise time and pulse width. The results suggest there could be some differences in practical system-level ESD tests among ESD protection devices. An ESD gun test confirms this, and polymer ESD devices are found suitable to protect high-speed signaling.
Eigen-points: control-point location using principal component analyses

Eigen-points estimates the image-plane locations of fiduciary points on an object. By estimating multiple locations simultaneously, eigen-points exploits the interdependence between these locations. This is done by associating neighboring, inter-dependent control-points with a model of the local appearance. The model of local appearance is used to find the feature in new unlabeled images. Control-point locations are then estimated from the appearance of this feature in the unlabeled image. The estimation is done using an affine manifold model of the coupling between the local appearance and the local shape. Eigen-points uses models aimed specifically at recovering shape from image appearance. The estimation equations are solved non-iteratively, in a way that accounts for noise in the training data and the unlabeled images and that accounts for uncertainty in the distribution and dependencies within these noise sources.