Miracle-dz/UniFAR-FTUs huggingface dataset:
Associations Among End-of-Life Discussions, Health-Care Utilization, and Costs in Persons With Advanced Cancer: A Systematic Review

Background: Aggressive end-of-life (EOL) care is associated with lower quality of life and greater regret about treatment decisions. Higher EOL costs are also associated with lower quality EOL care. Advance care planning and goals-of-care conversations (“EOL discussions”) may influence EOL health-care utilization and costs among persons with cancer. Objective: To describe associations among EOL discussions, health-care utilization and place of death, and costs in persons with advanced cancer and explore variation in study measures. Methods: A systematic review was conducted using PubMed, Embase, and CINAHL. Twenty quantitative studies published between January 2012 and January 2019 were included. Results: End-of-life discussions are associated with lower health-care costs in the last 30 days of life (median US$1048 vs US$23482; P < .001); lower likelihood of acute care at EOL (odds ratio [(OR] ranging 0.43-0.69); lower likelihood of intensive care at EOL (ORs ranging 0.26-0.68); lower odds of chemotherapy near death (ORs 0.41, 0.57); lower odds of emergency department use and shorter length of hospital stay; greater use of hospice (ORs ranging 1.79 to 6.88); and greater likelihood of death outside the hospital. Earlier EOL discussions (30+ days before death) are more strongly associated with less aggressive care outcomes than conversations occurring near death. Conclusions: End-of-life discussions are associated with less aggressive, less costly EOL care. Clinicians should initiate these discussions with patients having cancer earlier to better align care with preferences.
Enhancing color texture quality of 3D models for digital preservation of indigenous ceramic artworks

We present a contribution to the digital preservation of artworks made by the Wauja and Karaja indians; both communities acknowledged for their expertise in ceramic artworks and the symbolism embedded in their art. Our goal is to enhance the texture color quality of 3D models obtained from color and depth images of a laser scanner. Although laser scanners offer high-performance regarding depth information, the color information is still poor and limits the generation of realistic texture. We propose a method through which we add color information obtained from a high resolution digital camera to solve this limitation. Thus, our approach generates texture maps for 3D models by using color data obtained from triplets of: (1) high resolution photographs captured by a digital camera; and (2) color and (3) range images captured by a laser scanner. For each triplet, we calculate a partial texture map for the 3D model. Then, we merge all partial maps based on weights we have defined to reflect the reliability of each partial texture map pixel. We present several results of preserved artworks with realistic and enhanced quality texture maps. The 3D models can be visualized through a tool we developed to support the virtual exhibition of the artworks.
Application of high hydrostatic pressure for the inactivation of norovirus and quality stability in fresh sea squirt (Halocynthia roretzi)

Sea squirt (Halocynthia roretzi) is considered a potential cause of human norovirus in Korea. This study investigated the effect of high hydrostatic pressure at 100–500 MPa for 5 min at room temperature (23 ± 2 ℃) on the inactivation of murine norovirus-1 (initial inoculum of 6–7 log10 plaque forming units/ml) as a human norovirus surrogate in fresh sea squirt. The effects of high hydrostatic pressure on the Hunter colors and pH were also examined as the main indices of quality. No reductions in murine norovirus-1 titers were observed in sea squirt treated at 100–400 MPa. However, murine norovirus-1 in sea squirt was completely inactivated by 500 MPa of high hydrostatic pressure. Furthermore, the Hunter colors (“L,” “a,” and “b”) and pH values (6.10–6.19) were not significantly (P > 0.05) different between non-high hydrostatic pressure-treated sea squirts and all high hydrostatic pressure-treated sea squirts. Therefore, 500 MPa of high hydrostatic pressure at room temperature may be an optimal treatment for Tunicata meat without altering the food quality (color and pH).
Inferring dependencies from relations: a conceptual clustering approach

In this paper we consider two related types of data dependencies that can hold in a relation: conjunctive implication rules between attribute‐value pairs, and functional dependencies. We present a conceptual clustering approach that can be used, with some small modifications, for inferring a cover for both types of dependencies. The approach consists of two steps. First, a particular clustered representation of the relation, called concept (or Galois) lattice, is built. Then, a cover is extracted from the lattice built in the earlier step. Our main emphasis is on the second step. We study the computational complexity of the proposed approach and present an experimental comparison with other methods that confirms its validity. The results of the experiments show that our algorithm for extracting implication rules from concept lattices clearly outperforms an earlier algorithm, and suggest that the overall lattice‐based approach to inferring functional dependencies from relations can be seen as an alternative to traditional methods.
Achieving Portability and Performance through OpenACC

OpenACC is a directive-based programming model designed to allow easy access to emerging advanced architecture systems for existing production codes based on Fortran, C and C++. It also provides an approach to coding contemporary technologies without the need to learn complex vendor-specific languages, or understand the hardware at the deepest level. Portability and performance are the key features of this programming model, which are essential to productivity in real scientific applications. OpenACC support is provided by a number of vendors and is defined by an open standard. However the standard is relatively new, and the implementations are relatively immature. This paper experimentally evaluates the currently available compilers by assessing two approaches to the OpenACC programming model: the "parallel" and "kernels" constructs. The implementation of both of these construct is compared, for each vendor, showing performance differences of up to 84%. Additionally, we observe performance differences of up to 13% between the best vendor implementations. OpenACC features which appear to cause performance issues in certain compilers are identified and linked to differing default vector length clauses between vendors. These studies are carried out over a range of hardware including GPU, APU, Xeon and Xeon Phi based architectures. Finally, OpenACC performance, and productivity, are compared against the alternative native programming approaches on each targeted platform, including CUDA, OpenCL, OpenMP 4.0 and Intel Offload, in addition to MPI and OpenMP.
Fast Online Incremental Attribute-based Object Classification using Stochastic Gradient Descent and Self-Organizing Incremental Neural Network

In computer image processing, traditional object classification methods focus on visual objects such as cars, dogs, and airplanes. However, these objects are not easy to scale, require extensive training for all classes, and are susceptible to unseen object classification failure. Recently, a new object classification approach called attribute-based object classification has been introduced by considering visual adjectives that are easily discernible, such as “red, furry, has legs”, instead of visual objects. Based on this concept, knowledge of an unseen object’s categories can be conveyed by a description of its attributes. In this study, we proposed the first online incremental learning system for attribute-based object classification. Our proposed method can overcome online incremental learning tasks, and the learning and classification process is very fast. The presented experimental results are the first reported results of online incremental attribute-based object classification and hence can serve as a reference with which other results are compared. Moreover, our computation time is also more than 90% faster than other offline approaches.
The role of appraisal in emotion

The idea that appraisal plays a role in emotion can be traced back to Aristotle, Descartes, Spinoza, and Hume, who considered it self-evident that the states variously called passions, affects, or emotions are differentiated by the type of evaluation or judgment a person makes of the eliciting event. This shared conviction was shattered by James' (1884/1968) claim that "that the bodily changes follow directly the perception of the exciting fact, and that our feeling of the same changes as they occur is the emotion". While James meant " feeling " when he wrote "emotion" and he later acknowledged that the nature of the bodily changes was determined by the overwhelming "idea" of the significance of a situation for well-being (e.g., the probability that the bear will kill us or that we will kill it; James, 1894, p. 518), a century of debate and misunderstanding was launched (Ellsworth, 1994). Appraisal did not play much of a role in this debate nor did it in the (biological versions of) basic emotion theories, pioneered by Tomkins (1962) and his disciples Ekman (1972) and Izard (1977), which dominated the emotion domain from the 60s to the 80s. The term appraisal was first used in a technical sense by Arnold (1960) and Lazarus (1966). Detailed development of this notion only occurred in the early 80s (Scherer, 1999; Schorr, 2001) leading to what is now referred to as appraisal theories. Theorists in this tradition propose that most, but not all, emotions are elicited and differentiated by people's evaluation of the significance of events for their well-being (Ellsworth & Scherer, 2003). Currently, many contemporary emotion theories mention appraisal. For instance, Ekman (2004, p. 121-126) postulated "automatic appraisal mechanisms" as triggers of emotion. Barrett (2006) suggested that appraisal can play a role in the generation of core affect and Russell (2003) suggested that appraisal may be one of several independent components of an emotion episode. Yet, not all theories that mention appraisal qualify as appraisal theories. In the present chapter, we propose two related criteria for a theory to count as an appraisal ROLE OF APPRAISAL IN EMOTION 3 theory: (a) appraisal theories consider appraisal as a typical cause of emotion (or of emotional components), and because of this, (b) appraisal is the core determinant of the content of feelings. Before addressing the relation between appraisal and emotion, we consider definitions of the terms emotion and appraisal. This …
Sound Mode Hydrodynamics from Bulk Scalar Fields

We study the hydrodynamic sound mode using gauge/gravity correspondence by examining a generic black brane background's response to perturbations. We assume that the background is generated by a single scalar field, and then generalize to the case of multiple scalar fields. The relevant differential equations obeyed by the gauge invariant variables are presented in both cases. Finally, we present an analytical solution to these equations in a special case; this solution allows us to determine the speed of sound and bulk viscosity for certain special metrics. These results may be useful in determining sound mode transport coefficients in phenomenologically motivated holographic models of strongly coupled systems.
Mispriced or Properly Risk-Adjusted ?

Research has established that R&D-intensive firms are characterized by substantial future risk-adjusted stock returns. The reasons for this phenomenon and its policy implications, however, are widely debated. Some attribute the excess returns to investors‘ systematic undervaluation of R&D firms and argue for improved disclosure to mitigate the mispricing, while others claim that the excess returns are just compensating for an R&D-specific risk factor and, therefore, no accounting changes are called for. We aim at providing insights into this controversy by examining R&D firms with substantial R&D outlays, i.e., firms with R&D as an important ingredient in their strategy. Among such firms we compare firms with high and low industry-adjusted R&D intensity. The high industry-adjusted R&D intensity firms are more likely to be engaged in basic research activities, while the low industry-adjusted R&D intensity firms are likely to mimic and extend existing technologies. As such, compared to the low industry-adjusted R&D intensity firms, the high industry-adjusted R&D intensity firms are likely to suffer from higher information asymmetry. We find that high industry-adjusted R&D intensity firms exhibit substantially positive risk-adjusted returns during the first four-five future years, after which these excess returns converge to those of low industry-adjusted R&D intensity firms. This evidence is consistent with a significant undervaluation of high industry-adjusted R&D intensity firms. The long-term excess returns are positive for both the high and the low industry-adjusted R&D intensity firms and these excess returns are partly attributable to information risk. We also show that the future excess returns of high industry-adjusted R&D intensity firms are substantially lower for those firms who provide voluntary disclosure (earnings guidance) suggesting that the short-term undervaluation is likely due to mispricing.
Enhancement of Voltage Stability Margin Using FACTS Controllers

This paper presents a methodology for selection of location of static VAR compensator based on static voltage stability analysis of a power system. The analysis presented here uses the L-index of load buses. This includes voltage stability information of a normal power flow in the range of 0 to 1(no load to voltage collapse). An approach has been developed to select a suitable size and location of static VAR compensator as required in an IEEE-14 bus system. The STATCOM and SVC are used in the continuation power flow process for static voltage stability analysis to enhance stability margin.
High incidence of venous thromboembolism recurrence in patients with sickle cell disease

Previous reports show increased incidence of venous thromboembolism [VTE, deep‐vein thrombosis (DVT) and pulmonary embolus (PE)] in sickle cell disease (SCD) patients. The incidence, time course, and risk factors for VTE recurrence have been less well described. We determined the cumulative incidence of first VTE recurrence and bleeding in a cohort of SCD patients with incident VTE. Risk factors for recurrence and bleeding were also determined using multivariable Cox regression models, adjusting for gender, race/ethnicity, era of incident VTE, location and hospitalization‐associated status of incident VTE, and SCD‐related complications. Results are presented as adjusted hazard ratios (HR) and 95% confidence intervals (CI). Among 877 SCD patients with an incident VTE, the 1‐year and 5‐year cumulative incidence of recurrence was 13.2% (95% CI 11.0%‐15.5%) and 24.1% (95% CI 21.2%‐27.1%). Risk factors for VTE recurrence included more severe SCD (HR = 2.41; CI: 1.67‐3.47), lower extremity DVT as the incident event (HR = 1.64; CI: 1.17‐2.30), and pneumonia/acute chest syndrome (HR = 1.68; CI: 1.15‐2.45). The cumulative incidence of bleeding was 4.9% (CI 3.5%‐6.4%) at 6 months and 7.9% (CI: 6.2%‐9.8%) at 1 year. More severe SCD (HR = 1.61; CI: 1.11‐2.35) was associated with bleeding. The high incidence of VTE recurrence in patients with SCD suggests that extended anticoagulation may be indicated; however, this must be weighed against a relatively high risk of bleeding. Prospective, randomized studies of anticoagulation in SCD patients with VTE are needed.
A Convolutional Neural Network for the Detection of Asynchronous Steady State Motion Visual Evoked Potential

A key issue in brain-computer interface (BCI) is the detection of intentional control (IC) states and non-intentional control (NC) states in an asynchronous manner. Furthermore, for steady-state visual evoked potential (SSVEP) BCI systems, multiple states (sub-states) exist within the IC state. Existing recognition methods rely on a threshold technique, which is difficult to realize high accuracy, i.e., simultaneously high true positive rate and low false positive rate. To address this issue, we proposed a novel convolutional neural network (CNN) to detect IC and NC states in a SSVEP-BCI system for the first time. Specifically, the steady-state motion visual evoked potentials (SSMVEP) paradigm, which has been shown to induce less visual discomfort, was chosen as the experimental paradigm. Two processing pipelines were proposed for the detection of IC and NC states. The first one was using CNN as a multi-class classifier to discriminate between all the states in IC and NC state (FFT-CNN). The second one was using CNN to discriminate between IC and NC states, and using canonical correlation analysis (CCA) to perform classification tasks within the IC (FFT-CNN-CCA). We demonstrated that both pipelines achieved a significant increase in accuracy for low-performance healthy participants when traditional algorithms such as CCA threshold were used. Furthermore, the FFT-CNN-CCA pipeline achieved better performance than the FFT-CNN pipeline based on the stroke patients’ data. In summary, we showed that CNN can be used for robust detection in an asynchronous SSMVEP-BCI with great potential for out-of-lab BCI applications.
Prediction of nuclear export signals using weighted regular expressions (Wregex)

MOTIVATION Leucine-rich nuclear export signals (NESs) are short amino acid motifs that mediate binding of cargo proteins to the nuclear export receptor CRM1, and thus contribute to regulate the localization and function of many cellular proteins. Computational prediction of NES motifs is of great interest, but remains a significant challenge. RESULTS We have developed a novel approach for amino acid motif searching that can be used for NES prediction. This approach, termed Wregex (weighted regular expression), combines regular expressions with a position-specific scoring matrix (PSSM), and has been implemented in a web-based, freely available, software tool. By making use of a PSSM, Wregex provides a score to prioritize candidates for experimental testing. Key features of Wregex include its flexibility, which makes it useful for searching other types of protein motifs, and its fast execution time, which makes it suitable for large-scale analysis. In comparative tests with previously available prediction tools, Wregex is shown to offer a good rate of true-positive motifs, while keeping a smaller number of potential candidates.
Fluctuations in shear-jammed states: A statistical ensemble approach

Granular matter exists out of thermal equilibrium, i.e. it is athermal. While conventional equilibrium statistical mechanics is not useful for characterizing granular materials, the idea of constructing a statistical ensemble analogous to its equilibrium counterpart to describe static granular matter was proposed by Edwards and Oakshott more than two decades ago. Recent years have seen several implementations of this idea. One of these is the stress ensemble, which is based on properties of the force moment tensor, and applies to frictional and frictionless grains. We demonstrate the full utility of this statistical framework in shear-jammed (SJ) experimental states, a special class of granular solids created by pure shear, which is a strictly non-equilibrium protocol for creating solids. We demonstrate that the stress ensemble provides an excellent quantitative description of fluctuations in experimental SJ states. We show that the stress fluctuations are controlled by a single tensorial quantity: the angoricity of the system, which is a direct analog of the thermodynamic temperature. SJ states exhibit significant correlations in local stresses and are thus inherently different from density-driven, isotropically jammed (IJ) states.
An Energy Perspective of Multimedia Streaming Systems

The demand for multimedia streaming is growing at a phenomenal rate, and data-centre-empowered streaming services are becoming more common nowadays. To better accommodate the demand, the computing power and networking components in data centres are being upgraded regularly, leading to higher energy bills. Many studies have been conducted around reducing the power consumed by data centres, but very little attention has been paid to the data transmissions and the power consumed by the entire system, from the streaming source to the end-user devices. In this paper, we are interested in the power efficiency of multimedia streaming system as a whole. We take on the analysis in three directions: traffic imposed by different streaming protocols, underlay physical network structure, and the network infrastructure (data centre vs. Peer-to-Peer). Three main conclusions drawn from the study are: (1) very insignificant power savings can be achieved by tuning the streaming protocol, router connectivity, or the network infrastructure, (2) significant power savings can be achieved through reducing the idle power of routers and end-user devices, and (3) the energy efficiency of the end-user devices determines whether the Peer-to-Peer (P2P) infrastructure can be a green alternative for data-centre-empowered streaming.
The use of new Technology in Higher Education : From Unlearning to wiki use Appropriation in a French Business School : a Case Study

It is widely agreed that the development of new technology in higher education is of particular importance. Yet, with a few exceptions, little is known about the conditions of appropriation by learners in this specific context. This paper attempts to address the relationship between the appropriation of new technology and the process of unlearning. We investigate why and how the actions modifying old knowledge can favour the use of collaborative and virtual technology. The framework of the paper is built on a review of Giddens's theory of structuration and learning theories, with particular focus on the concept of unlearning (Nystrom and Starbuck 1984). Unlearning is defined as the questioning and destruction process of knowledge, logic and patterns established, in order to propose new responses and behaviours. The empirical study proposes the analysis of the process appropriation of wiki technology by 300 students in a French business school [“Euromed Marseille”] in their workgroup sessions. We use a case study methodology (Eisenhardt 1989, Yin 1990) based on a qualitative investigation (Miles and Huberman 1984) and a combination of different collection. The results show that unlearning of traditional workgroup methods clearly facilitates appropriation of wiki technology. In other words, the unlearninglearning process appears to be essential to create virtual collective knowledge. Furthermore, this research provides some evidence about the factors that influence the speed of unlearning – deviant behaviours and tensions within groups, weak ties among group members, various expertise and visions, flexible collaboration. Finally, we discuss the implications of these findings for research and practice, and also make recommendations to encourage unlearning opportunities in the process of new technology appropriation.