Miracle-dz/UniFAR-FTUs huggingface dataset:
Applied Photoelasticity for Residual Stress Measurement inside Crystal Silicon Wafers for Solar Applications

A full automated NIR polariscope has been specially built for residual stress measurement in crystal silicon wafers for solar applications. The multiple configurations of the instrument allow measuring both the isoclinic and the isochromatic parameters on a full field. A new algorithm has also been developed to extract the maximal shear stress inside the silicon wafers without linking the isoclinic parameter to the isochromatic parameter. Hence, it is straightforward to use and the extraction errors are reduced. Coupling this improved data analysis with the comprehensive capabilities of the test rig, allowed to show that the effect of the cutting process on the residual stress inside the silicon wafers is predominant compared with the effect of the cast process, related to the thermal gradient and impurities.
A general framework for parametric survival analysis

Parametric survival models are being increasingly used as an alternative to the Cox model in biomedical research. Through direct modelling of the baseline hazard function, we can gain greater understanding of the risk profile of patients over time, obtaining absolute measures of risk. Commonly used parametric survival models, such as the Weibull, make restrictive assumptions of the baseline hazard function, such as monotonicity, which is often violated in clinical datasets. In this article, we extend the general framework of parametric survival models proposed by Crowther and Lambert (Journal of Statistical Software 53:12, 2013), to incorporate relative survival, and robust and cluster robust standard errors. We describe the general framework through three applications to clinical datasets, in particular, illustrating the use of restricted cubic splines, modelled on the log hazard scale, to provide a highly flexible survival modelling framework. Through the use of restricted cubic splines, we can derive the cumulative hazard function analytically beyond the boundary knots, resulting in a combined analytic/numerical approach, which substantially improves the estimation process compared with only using numerical integration. User‐friendly Stata software is provided, which significantly extends parametric survival models available in standard software. Copyright © 2014 John Wiley & Sons, Ltd.
Atypical Hepatocellular Neoplasms: Review of Clinical, Morphologic, Immunohistochemical, Molecular, and Cytogenetic Features

The distinction of hepatocellular adenoma from well-differentiated hepatocellular carcinoma (HCC) can be difficult in some cases, especially on biopsy specimens. These borderline cases often occur in men or older patients and may have &bgr;-catenin activation or focal atypical morphologic features (such as small cell change, prominent pseudoacinar formation, cytologic atypia, focally thick plates, and/or focal reticulin loss) that are insufficient for an unequivocal diagnosis of HCC. The term “atypical hepatocellular neoplasm” has been advocated for these tumors, but a number of other terms, including “atypical adenoma,” “hepatocellular neoplasm of uncertain malignant potential,” and “well-differentiated hepatocellular neoplasm with atypical or borderline features” have also been proposed. This review proposes guidelines for designating tumors as atypical hepatocellular neoplasm and describes clinical, morphologic, immunohistochemical, molecular, and cytogenetic features that distinguish these tumors from typical hepatocellular adenoma and HCC.
Women exposed to intimate partner violence: expectations and experiences when they encounter health care professionals: a meta-analysis of qualitative studies.

BACKGROUND The appropriate response of health care professionals to intimate partner violence is still a matter of debate. This article reports a meta-analysis of qualitative studies that answers 2 questions: (1) How do women with histories of intimate partner violence perceive the responses of health care professionals? and (2) How do women with histories of intimate partner violence want their health care providers to respond to disclosures of abuse? METHODS Multiple databases were searched from their start to July 1, 2004. Searches were complemented with citation tracking and contact with researchers. Inclusion criteria included a qualitative design, women 15 years or older with experience of intimate partner violence, and English language. Two reviewers independently applied criteria and extracted data. Findings from the primary studies were combined using a qualitative meta-analysis. RESULTS Twenty-nine articles reporting 25 studies (847 participants) were included. The emerging constructs were largely consistent across studies and did not vary by study quality. We ordered constructs by the temporal structure of consultations with health care professionals: before the abuse is discussed, at disclosure, and the immediate and further responses of the health care professional. Key constructs included a wish from women for responses from health care professionals that were nonjudgmental, nondirective, and individually tailored, with an appreciation of the complexity of partner violence. Repeated inquiry about partner violence was seen as appropriate by women who were at later stages of an abusive relationship. CONCLUSION Women's perceptions of appropriate and inappropriate responses partly depended on the context of the consultation, their own readiness to address the issue, and the nature of the relationship between the woman and the health care professional.
Energy management of a virtual power plant with a battery-ultracapacitor based Hybrid Energy Storage System

In this work, a battery-ultracapacitor based Hybrid Energy Storage System (HESS) is proposed to attain a constant output power on a 10kVA Virtual Power Plant (VPP) with three days autonomy. Firstly, the importance of a HESS is remarked and different topologies of battery-ultracapacitor based HESS are analyzed. Thus, the VPP scheme based on a photovoltaic farm, a wind energy conversion system and the proposed HESS is described. Furthermore, in order to achieve a suitable energy conversion, Sliding-Mode Control (SMC) on a cascade scheme is designed by using the space state representation of the DC-DC power converters. Finally, the system performance is presented remarking proper dynamic and steady-state responses under different solar irradiation, wind speed and load profiles.
Labour as a Buffer: Do Temporary Workers Suffer?

In this paper we investigate whether or not there is an equal opportunities dimension to regulating equal pay and conditions for temporary work. We develop a 'buffer stock' model of temporary work that suggests a number of reasons why ethnic minorities and women may be more likely to be on fixed-term contracts than comparable white males. Using three different British datasets (a random representative survey of households and two data sets of specific labour market groups), we then estimate the degree to which women and/or ethnic minorities are more likely to be on temporary contracts and estimate any associated wage differentials.
Novice Shooters With Lower Pre-shooting Alpha Power Have Better Performance During Competition in a Virtual Reality Scenario

Competition changes the environment for athletes. The difficulty of training for such stressful events can lead to the well-known effect of “choking” under pressure, which prevents athletes from performing at their best level. To study the effect of competition on the human brain, we recorded pilot electroencephalography (EEG) data while novice shooters were immersed in a realistic virtual environment representing a shooting range. We found a differential between-subject effect of competition on mu (8–12 Hz) oscillatory activity during aiming; compared to training, the more the subject was able to desynchronize his mu rhythm during competition, the better was his shooting performance. Because this differential effect could not be explained by differences in simple measures of the kinematics and muscular activity, nor by the effect of competition or shooting performance per se, we interpret our results as evidence that mu desynchronization has a positive effect on performance during competition.
Growing Health and Quality of Life: Benefits of Urban Organic Community Gardens

Objectives: To characterize the horticulturists of an urban garden in terms of their current state of health and health behaviors (at gardening beginning) and to evaluate the effect of horticulture practice on health behaviors and quality of life (after a six month gardening stretch). Introduction: The way in which cities have grown, with heavy air and noise pollution, reduced green spaces, a long distance and out of season food based system and limited sunshine access has led to multiple public health challenges. This in turn has prompted the emergence of various local and state policies aimed at improving the health and quality of life of urbanites. Method: Interviews using structured questionnaires were conducted twice with 115 city dwellers: when they got started in a vegetable garden and about 6 months later. Results: Participants were mainly female (57.8%), professionally active (48.0%) and with a mean age of 53 years. This research showed significant behavioral changes among its users, including positive outcomes in anthropometric parameters, physical activity, smoking habits, eating habits, health status and overall quality of life. Conclusion: Despite a short follow-up period, it could be shown that gardening did influence health and quality of life behaviors.
Coupling index and stocks

In this paper, we are interested in continuous-time models in which the index level induces feedback on the dynamics of its composing stocks. More precisely, we propose a model in which the log-returns of each stock may be decomposed into a systemic part proportional to the log-returns of the index plus an idiosyncratic part. We show that, when the number of stocks in the index is large, this model may be approximated by a local volatility model for the index and a stochastic volatility model for each stock with volatility driven by the index. This result is useful from a calibration perspective: it suggests that one should first calibrate the local volatility of the index and then calibrate the dynamics of each stock. We explain how to do so in the limiting simplified model and in the original model.
Studio2Shop: From Studio Photo Shoots to Fashion Articles

Fashion is an increasingly important topic in computer vision, in particular the so-called street-to-shop task of matching street images with shop images containing similar fashion items. Solving this problem promises new means of making fashion searchable and helping shoppers find the articles they are looking for. This paper focuses on finding pieces of clothing worn by a person in full-body or half-body images with neutral backgrounds. Such images are ubiquitous on the web and in fashion blogs, and are typically studio photos, we refer to this setting as studio-to-shop. Recent advances in computational fashion include the development of domain-specific numerical representations. Our model Studio2Shop builds on top of such representations and uses a deep convolutional network trained to match a query image to the numerical feature vectors of all the articles annotated in this image. Top-$k$ retrieval evaluation on test query images shows that the correct items are most often found within a range that is sufficiently small for building realistic visual search engines for the studio-to-shop setting.
Automatically Correcting Networks with NEAt

Configuring and maintaining an enterprise network is a challenging and error-prone process. Administrators often need to consider security policies from a variety of sources such as regulatory requirements, industry standards, and mitigating attack vectors. Erroneous configuration or network application could violet crucial policies, and result in costly data breaches and intrusions. Relying on humans to discover and troubleshoot violations is slow and prone to error, considering the speed at which new attack vectors propagate and the increasing network dynamics, partly an effect of SDN. To address this problem, we present NEAt, a system analogous to a smartphone’s autocorrect feature that enables on-the-fly repair to policy-violating updates. It does so by modifying the forwarding behavior of updates to automatically repair violations of policies such as reachability, service chaining, and segmentation. NEAt takes as input a set of administrator-defined high-level policies, and formulates these policies as directed graphs. Sitting between an SDN controller and the forwarding devices, NEAt intercepts updates proposed by SDN applications. If an update violates a policy, NEAt transforms the update into one that complies with the policy. Unlike domain-specific languages or synthesis platforms, NEAt allows enterprise networks to leverage the advanced functionality of SDN applications while simultaneously achieving strong, automated enforcement of general policies. Based on a prototype implementation and experimentation using Mininet and operation trace of a large enterprise network we demonstrate that NEAt achieves promising performance in real-time bug-fixing.
Perceived Simultaneity and Temporal Order of Audiovisual Events Following Concussion

The central nervous system allows for a limited time span referred to as the temporal binding window (TBW) in order to rapidly determine whether multisensory events correspond with the same event. Failure to correctly identify whether multisensory events occur simultaneously and their sequential order can lead to inaccurate representations of the physical world, poor decision-making and dangerous behavior. Damage to the neural systems that coordinate the relative timing of sensory events may explain some of the long-term consequences associated with concussion. The aim of this study was to investigate whether the perception of simultaneity and the discrimination of temporal order of audiovisual stimuli are impaired in those with a history of concussion. Fifty participants (17 with concussion history) were recruited to complete audiovisual simultaneity judgment (SJ) and temporal order judgment (TOJ) tasks. From these tasks, the TBW and point of subjective simultaneity (PSS) were extracted to assess whether the precision and or the accuracy of temporal perception changes with concussion, respectively. Results demonstrated that those with concussion history have a significantly wider TBW (less precise), with no significant change in the PSS (no change in accuracy), particularly for the TOJ task but no significant differences were found between the SJ and TOJ tasks. Importantly, a negative correlation between the time elapsed since last concussion and TBW width in the TOJ task suggests that precision in temporal perception does improve over time. These findings suggest that those with concussion history display an impairment in the perceived timing of sensory events and that monitoring performance in the SJ and TOJ tasks may be a useful additional assessment tool when making decisions about returning to regular work and play following concussion.
Measuring Economic Globalization: Spatial Hierarchies and Market Topologies

Measuring the degree and extent of economic globalization is subject to a variety of issues ranging from theoretical conceptualization to the selection of appropriate data. This examination of economic globalization underscores the importance of a geographic perspective that is necessarily situated within a temporal context. International trade data and exploratory spatial data analyses are used to assess patterns of economic globalization between 1970 and 1997. Results indicate that preserving topological relationships between states in the global economy can guide, inform, and extend future studies of the processes and patterns of economic globalization.
Measurement Data Classification Optimization Based on a Novel Evolutionary Kernel Clustering Algorithm for Multi-Target Tracking

In the field of range-based multi-target localization and tracking, measurement data of each time cannot associate with its corresponding target, and clustering analysis can be used to solve this problem. In this paper, a novel evolutionary kernel clustering algorithm was developed for range-based multi-target tracking in wireless sensor networks. First, the locations of multi-targets are predicted according to the previous trajectories. Second, we apply the clustering number recognition algorithm to filter out the outliers and calculate the initial cluster center by analyzing the density of each measurement data. For each cluster, its relationship with corresponding target is established according to the predictive position and the initial cluster center. Third, the density factors of each measurement data are fused into the Gaussian kernel function to improve the accuracy of the cluster center. Finally, the accurate position of each target at current moment is calculated based on the predictive position and the measurement data set of corresponding cluster. Two different experiments are done in this paper: in the first experiment, the clustering performance of our proposed algorithm is evaluated based on the training data set. In the second one, the accuracy improvement of range-based target tracking is shown when proposed algorithm is used to analyze the measurement data. The tracking results show that the proposed algorithm is more robust to large localization errors.
Learning to Filter Unsolicited Commercial E-Mail

We discuss the model and search biases of the learning algorithms, along withworst-case computational complexity figures, and observe how the latter relate to experimental measurements.We study how classification accuracy is affected when using attributes that represent sequences of tokens, as opposed to single tokens, and explore the effect of the size of the attribute and training set, all within a cost-sensitive framework. Furthermore, we describe the architecture of a fully implemented learning-based anti-spam filter, and present an analysis of its behavior in real use over a period of seven months. Information is also provided on other available learning-based anti-spam filters, and alternative filtering approaches.
The system for appraisal of vehicle accident based on radial basis function neural networks

In Taiwan, there are hundreds of accidents every day recorded by government due to the human factor and environmental factor. The accident usually involved the money dispute; therefore the accident appraisal must indicate the bilateral parties' blame clearly: all blame; major blame; minor blame and none blame. Although the local police can give a preliminary analysis report at first, the report cannot be official evidence. If the people need a credible appraisal report, they have to apply for the Taiwan Provincial Government Traffic Accident Investigation Committee's accident appraisal report. However, applying for Committee's accident appraisal report will take long time. Therefore, this study employed radial basis function neural network to build an expert system for appraisal of bilateral vehicle accident. The database was built from 307 accident cases in Taiwan from the year of 2004 to 2008. According to Committee's analysis, there are 30 appraisal basses including 6 environmental basses and 24 vehicle basses chosen to be the input of the expert system. The training data includes three types: 70 cases training; 140 cases training; 207 cases training. Validation stage was carried out by using 100 fixed cases and the correctness was recorded. In the first stage, correctness rate is 76% for training with 70 cases. In the second stage, correctness rate is increased to 81% for training with 140 cases. In the third stage, correctness rate is increased to 89% for training with 207 cases. The training and validation processes were completed in one second. Therefore, the expert system proposed in this work is demonstrated to be an efficient system for the accident appraisal.
The VIMOS VLT Deep Survey final data release: a spectroscopic sample of 35 016 galaxies and AGN out to z ~ 6.7 selected with 17.5 ≤ iAB ≤ 24.75

We describe the completed VIMOS VLT Deep Survey, and the final data release of 35016 galaxies and type-I AGN with measured spectroscopic redshifts up to redshift z~6.7, in areas 0.142 to 8.7 square degrees, and volumes from 0.5x10^6 to 2x10^7h^-3Mpc^3. We have selected samples of galaxies based solely on their i-band magnitude reaching i_{AB}=24.75. Spectra have been obtained with VIMOS on the ESO-VLT, integrating 0.75h, 4.5h and 18h for the Wide, Deep, and Ultra-Deep nested surveys. A total of 1263 galaxies have been re-observed independently within the VVDS, and from the VIPERS and MASSIV surveys. They are used to establish the redshift measurements reliability, to assess completeness, and to provide a weighting scheme taking into account the survey selection function. We describe the main properties of the VVDS samples, and the VVDS is compared to other spectroscopic surveys. In total we have obtained spectroscopic redshifts for 34594 galaxies, 422 type-I AGN, and 12430 Galactic stars. The survey has enabled to identify galaxies up to very high redshifts with 4669 redshifts in 1 3, and specific populations like LAE have been identified out to z=6.62. We show that the VVDS occupies a unique place in the parameter space defined by area, depth, redshift coverage, and number of spectra. The VVDS provides a comprehensive survey of the distant universe, covering all epochs since z, or more than 12 Gyr of cosmic time, with a uniform selection, the largest such sample to date. A wealth of science results derived from the VVDS have shed new light on the evolution of galaxies and AGN, and their distribution in space, over this large cosmic time. A final public release of the complete VVDS spectroscopic redshift sample is available at http://cesam.lam. fr/vvds.
Darwinian Foundations for Evolutionary Economics

Abstract This paper engages with the methodological debate on the contribution of Darwinism to Veblen’s (1898) evolutionary research program for economics. I argue that ontological continuity, generalized Darwinism, and multi-level selection are necessary building blocks for an explanatory framework that can fulfill the promise of Veblen’s program. I clarify the causal logic of generalized Darwinism and suggest an ontology for the study of economic development on the basis of multi-level selection theory. Conceptualizing economic development along these lines has interesting implications for the evolutionary analysis of institutions: institutions only become units of selection in the competition between groups of individuals.