Miracle-dz/UniFAR-FTUs huggingface dataset:
The Elderly Perceived Meanings and Values of Virtual Reality Leisure Activities: A Means-End Chain Approach

This study uses means-end chain (MEC) techniques to examine the awareness, decision-making procedure, and personal values of the elderly with regard to virtual reality leisure activities. The results of the study show that elderly respondents value virtual reality leisure activities that are fun, safe, and easy. In terms of outcome benefits, elderly respondents value feeling physically and mentally healthy, firsthand experience, and satisfied curiosity. In value terms, elderly respondents hope that their chosen virtual reality leisure activities improve not only their relationships with others, but also their enjoyment, quality of life, and sense of belonging. The results show that, while consumers with different awarenesses of virtual reality leisure activities have different decision-making processes, they share creating “good memories” as the terminal value with the most significant effect. This presents a potential opportunity to promote virtual reality leisure activities. Relevant bodies or enterprises can seek to create good memories in consumers by developing activities that are safe and fun, promote good health, and provide good service, thereby attracting the interest of elderly consumers.
The 5C Concept and 5S Principles in Inflammatory Bowel Disease Management

Abstract Background and Aims The international Inflammatory Bowel Disease [IBD] Expert Alliance initiative [2012–2015] served as a platform to define and support areas of best practice in IBD management to help improve outcomes for all patients with IBD. Methods During the programme, IBD specialists from around the world established by consensus two best practice charters: the 5S Principles and the 5C Concept. Results The 5S Principles were conceived to provide health care providers with key guidance for improving clinical practice based on best management approaches. They comprise the following categories: Stage the disease; Stratify patients; Set treatment goals; Select appropriate treatment; and Supervise therapy. Optimised management of patients with IBD based on the 5S Principles can be achieved most effectively within an optimised clinical care environment. Guidance on optimising the clinical care setting in IBD management is provided through the 5C Concept, which encompasses: Comprehensive IBD care; Collaboration; Communication; Clinical nurse specialists; and Care pathways. Together, the 5C Concept and 5S Principles provide structured recommendations on organising the clinical care setting and developing best-practice approaches in IBD management. Conclusions Consideration and application of these two dimensions could help health care providers optimise their IBD centres and collaborate more effectively with their multidisciplinary team colleagues and patients, to provide improved IBD care in daily clinical practice. Ultimately, this could lead to improved outcomes for patients with IBD.
Dense Error Correction via L1-Minimization

This paper studies the problem of recovering a non-negative sparse signal $\x \in \Re^n$ from highly corrupted linear measurements $\y = A\x + \e \in \Re^m$, where $\e$ is an unknown error vector whose nonzero entries may be unbounded. Motivated by an observation from face recognition in computer vision, this paper proves that for highly correlated (and possibly overcomplete) dictionaries $A$, any non-negative, sufficiently sparse signal $\x$ can be recovered by solving an $\ell^1$-minimization problem: $\min \|\x\|_1 + \|\e\|_1 \quad {subject to} \quad \y = A\x + \e. $ More precisely, if the fraction $\rho$ of errors is bounded away from one and the support of $\x$ grows sublinearly in the dimension $m$ of the observation, then as $m$ goes to infinity, the above $\ell^1$-minimization succeeds for all signals $\x$ and almost all sign-and-support patterns of $\e$. This result suggests that accurate recovery of sparse signals is possible and computationally feasible even with nearly 100% of the observations corrupted. The proof relies on a careful characterization of the faces of a convex polytope spanned together by the standard crosspolytope and a set of iid Gaussian vectors with nonzero mean and small variance, which we call the ``cross-and-bouquet'' model. Simulations and experimental results corroborate the findings, and suggest extensions to the result.
Do Peers Affect Student Achievement? Evidence from Canada Using Group Size Variation

We provide the first empirical application of a new approach proposed by Lee (Journal of Econometrics 2007; 140(2), 333–374) to estimate peer effects in a linear-in-means model when individuals interact in groups. Assumingsufficient group size variation, this approach allows to control for correlated effects at the group level and to solve the simultaneity (reflection) problem. We clarify the intuition behind identification of peer effects in the model. We investigate peer effects in student achievement in French, Science, Mathematics and History in secondary schools in the Province of Quebec (Canada). We estimate the model using conditional maximum likelihood and instrumental variables methods. We find some evidence of peer effects. The endogenous peer effect is large and significant in Mathematics but imprecisely estimated in the other subjects. Some contextual peer effects are also significant. In particular, for most subjects, the average age of peers has a negative effect on own test score. Using calibrated Monte Carlo simulations, we find that high dispersion in group sizes helps with potential issues of weak identification. Copyright © 2012 John Wiley & Sons, Ltd.
Fecal Incontinence in Inflammatory Bowel Disease: A Systematic Review and Meta-Analysis.

Background Understanding of the prevalence, pathophysiology, and management of fecal incontinence (FI) in inflammatory bowel disease (IBD) patients without an ileal pouch anal anastomosis (IPAA) is suboptimal. We conducted a systematic review and meta-analysis on the prevalence, pathophysiology, and management of primary FI in IBD patients without IPAA. Methods We searched MEDLINE, EMBASE, and Cochrane Database of Systematic Reviews (1966 through March 2017) for studies on the prevalence, physiology, or management of FI in IBD patients without IPAA. A random effects model was used to calculate pooled prevalence rates and odds ratio (OR) with 95% confidence interval (CI). Heterogeneity was assessed with I2 statistics, Cochran Q statistic, and sensitivity analyses. Results Seventeen studies were included. Six studies evaluated the prevalence of FI in 4671 IBD patients. There was significant heterogeneity among the studies, but the pooled prevalence of FI among case-control studies was homogeneous at 24% (95% CI 18%-30%, I2 = 50.6%, P = 0.16). FI was more common among IBD patients than non-IBD controls (OR = 7.73; 95% CI 6.26 to 9.84). Therapeutic options were poorly evaluated in uncontrolled studies. Surgery was effective in 70% of patients (7/10), sacral nerve stimulation was effective in 100% of patients (5/5), and 41.6% of patients (5/12) reported subjective improvement in FI with percutaneous tibial nerve stimulation. Conclusions FI is prevalent in IBD patients without IPAA, and more common than non-IBD controls. Additional controlled studies are warranted to further identify effective therapeutic interventions for FI in IBD. 10.1093/ibd/izx109_video1izx109_Video_15760611117001.
Implementing successful residential alternatives to acute in-patient psychiatric services: lessons from a multi-centre study of alternatives in England

Background. Standard acute psychiatric care in the UK is costly but problematic. Alternatives to standard in-patient wards exist, but little is known about their effectiveness, implementation and sustainability. This paper explores successful features and limitations of five residential alternative services in England and factors that facilitate or impede their initial and sustained implementation and success. Methods. Semi-structured interviews about the functioning of six alternative services were conducted with 36 mental health professionals with good working knowledge of, and various connections with these services. A group interview with study researchers was also conducted. Data were analysed using thematic analysis. Results. One service did not show evidence of operating as an alternative and was excluded from further analysis. The remaining five alternatives are valued for providing a more holistic style of care than standard services that confers many perceived benefits. However, they are seen as less appropriate for compulsorily detained or highly disturbed patients, and as providing less comprehensive treatment packages than hospital settings. Factors identified as important to successful implementation and sustainability are: responding to known shortcomings in local acute care systems; balancing role clarity and adaptability; integration with other services; and awareness of the alternative among relevant local health-care providers. Conclusions. Residential alternatives can play an important role in managing mental health crises. Their successful implementation and endurance depend on establishing and maintaining a valued position within local service systems. Findings contribute to bridging the gap between research evidence on the problems of standard acute care and delivering improved crisis management services.
Valproate reduces spontaneous generalized spikes and waves but not photoparoxysmal reactions in patients with idiopathic generalized epilepsies

Purpose: Patients with idiopathic generalized epilepsies (IGEs) often present with interictal spike‐wave discharges (SWDs) at rest (spontaneous SWDs), during hyperventilation, and in response to photic stimulation (photoparoxysmal response or PPR). Valproic acid (VPA) is a first‐line antiepileptic drug for therapy of patients with IGE. Herein we investigated the effect of VPA on all three types of SWDs in children and adolescents with IGE.
Decoding Speech With Integrated Hybrid Signals Recorded From the Human Ventral Motor Cortex

Restoration of speech communication for locked-in patients by means of brain computer interfaces (BCIs) is currently an important area of active research. Among the neural signals obtained from intracranial recordings, single/multi-unit activity (SUA/MUA), local field potential (LFP), and electrocorticography (ECoG) are good candidates for an input signal for BCIs. However, the question of which signal or which combination of the three signal modalities is best suited for decoding speech production remains unverified. In order to record SUA, LFP, and ECoG simultaneously from a highly localized area of human ventral sensorimotor cortex (vSMC), we fabricated an electrode the size of which was 7 by 13 mm containing sparsely arranged microneedle and conventional macro contacts. We determined which signal modality is the most capable of decoding speech production, and tested if the combination of these signals could improve the decoding accuracy of spoken phonemes. Feature vectors were constructed from spike frequency obtained from SUAs and event-related spectral perturbation derived from ECoG and LFP signals, then input to the decoder. The results showed that the decoding accuracy for five spoken vowels was highest when features from multiple signals were combined and optimized for each subject, and reached 59% when averaged across all six subjects. This result suggests that multi-scale signals convey complementary information for speech articulation. The current study demonstrated that simultaneous recording of multi-scale neuronal activities could raise decoding accuracy even though the recording area is limited to a small portion of cortex, which is advantageous for future implementation of speech-assisting BCIs.
Atoms and molecules in cavities, from weak to strong coupling in quantum-electrodynamics (QED) chemistry

Significance Traditionally, quantum chemistry investigates molecular systems assuming that the photon field, which leads to the interaction of charged particles, is well approximated by the Coulomb interaction. On the other hand, quantum optics describe the photon field in detail while approximating the matter systems via few levels. Recent experiments at the interface between these two areas of research have uncovered situations where both the molecular system and the photon field have to be treated in detail. In this work, we show how theoretical approaches have to be adapted to treat such coupled matter–photon problems and which effects can be anticipated. Our quantum electrodynamics density-functional formalism provides the theoretical framework to open a field of research able to deal with emergent properties of matter. In this work, we provide an overview of how well-established concepts in the fields of quantum chemistry and material sciences have to be adapted when the quantum nature of light becomes important in correlated matter–photon problems. We analyze model systems in optical cavities, where the matter–photon interaction is considered from the weak- to the strong-coupling limit and for individual photon modes as well as for the multimode case. We identify fundamental changes in Born–Oppenheimer surfaces, spectroscopic quantities, conical intersections, and efficiency for quantum control. We conclude by applying our recently developed quantum-electrodynamical density-functional theory to spontaneous emission and show how a straightforward approximation accurately describes the correlated electron–photon dynamics. This work paves the way to describe matter–photon interactions from first principles and addresses the emergence of new states of matter in chemistry and material science.
Automated Grouping of Action Potentials of Human Embryonic Stem Cell-Derived Cardiomyocytes

Methods for obtaining cardiomyocytes from human embryonic stem cells (hESCs) are improving at a significant rate. However, the characterization of these cardiomyocytes (CMs) is evolving at a relatively slower rate. In particular, there is still uncertainty in classifying the phenotype (ventricular-like, atrial-like, nodal-like, etc.) of an hESC-derived cardiomyocyte (hESC-CM). While previous studies identified the phenotype of a CM based on electrophysiological features of its action potential, the criteria for classification were typically subjective and differed across studies. In this paper, we use techniques from signal processing and machine learning to develop an automated approach to discriminate the electrophysiological differences between hESC-CMs. Specifically, we propose a spectral grouping-based algorithm to separate a population of CMs into distinct groups based on the similarity of their action potential shapes. We applied this method to a dataset of optical maps of cardiac cell clusters dissected from human embryoid bodies. While some of the nine cell clusters in the dataset are presented with just one phenotype, the majority of the cell clusters are presented with multiple phenotypes. The proposed algorithm is generally applicable to other action potential datasets and could prove useful in investigating the purification of specific types of CMs from an electrophysiological perspective.
Compact Dielectric Constant Characterization of Low-Loss Thin Dielectric Slabs With Microwave Reflection Measurement

A microwave reflection measurement method is proposed to determine the dielectric constant of dielectric slabs without knowing their exact thickness. The expression of dielectric constant is derived according to the transmission line theory, in which the loss of material is neglected. Error analysis for lossy dielectric slabs has also been conducted. In-house measurement results on commercial polymethyl methacrylate, polytetrafluoroethylene, and FR4 samples have been presented to validate the proposed method. Excellent agreement has been achieved between the proposed method and the conventional free-space method. The proposed method is suitable for the dielectric constant characterization of thin-slab materials with low loss and low dielectric constant.
Information Science in the web era: A term-based approach to domain mapping

We propose a methodology for mapping the research in Information Science (IS) field based on a combined use of symbolic (linguistic) and numeric information. Using the same list of 12 IS journals as in earlier studies on this same topic (White & McCain 1998 ; Zhao & Strotmann 2008a&b), we mapped the structure of research in IS for two consecutive periods: 1996-2005 and 2006-2008. We focused on mapping the content of scientific publications from the title and abstract fields of underlying publications. The labels of clusters were automatically derived from titles and abstracts of scientific publications based on linguistic criteria. The results showed that while Information Retrieval (IR) and Citation studies continued to be the two structuring poles of research in IS, other prominent poles have emerged: webometrics in the first period (1996-2005) evolved into general web studies in the second period, integrating more aspects of IR research. Hence web studies and IR are more interwoven. There is still persistence of user studies in IS but now dispersed among the web studies and the IR poles. The presence of some recent trends in IR research such as automatic summarization and the use of language models were also highlighted by our method. Theoretic research on "information science" continue to occupy a smaller but persistence place. Citation studies on the other hand remains a monolithic block, isolated from the two other poles (IR and web studies) save for a tenuous link through user studies. Citation studies have also recently evolved internally to accommodate newcomers like "h-index, Google scholar and the open access model". All these results were automatically generated by our method without resorting to manual labeling of specialties nor reading the publication titles. Our results show that mapping domain knowledge structures at the term level offers a more detailed and intuitive picture of the field as well as capturing emerging trends.
Stability analysis of networked control systems with uncertain packet-loss probability

This paper is concerned with the robust stability in the mean square sense of networked control systems subject to packet dropout with uncertain probability. Both cases of time-invariant and time-varying uncertain probability with an upper bound are considered by introducing different classes of parameter-dependent Lyapunov functions. For time-invariant uncertain packet-loss probability, a new necessary and sufficient condition which can be solved by LMIs is proposed for the mean-square stability, and the largest upper bound of the packet-loss probability can be therefore obtained. For time-varying uncertain packet-loss probability, a sufficient condition in the form of LMIs is derived. Moreover, the proposed methodologies are further developed for the case where there are multiple packet-loss channels with respective uncertain probability under the parallel transmission strategy.
Unifying Bilateral Filtering and Adversarial Training for Robust Neural Networks

Recent analysis of deep neural networks has revealed their vulnerability to carefully structured adversarial examples. Many effective algorithms exist to craft these adversarial examples, but performant defenses seem to be far away. In this work, we attempt to combine denoising and robust optimization methods into a unified defense which we found to not only work extremely well, but also makes our model robust against future adversarial attacks. We explore the use of bilateral filtering as a projection back to the space of natural images. We first show that with carefully chosen parameters, bilateral filtering can remove more than 90% of adversarial examples from a variety of different attacks. We then adapt our recovery method as a trainable layer in a neural network. When trained under the adversarial training framework, we show that the resulting model is hard to fool with even the best attack methods.
Anti-inflammatory therapy with canakinumab for atherosclerotic disease: lessons from the CANTOS trial.

Inflammation plays a pivotal role in the development of atherosclerosis and in plaque instability (1). This has led to the hope that agents inhibiting inflammatory pathways in atherosclerosis can be employed to improve the clinical outcome of patients with coronary disease over and above treatments that target cholesterol accumulation and platelet initiated thrombosis (2).
Large‐scale network organization of EEG functional connectivity in newborn infants

The organization of functional brain networks changes across human lifespan. The present study analyzed functional brain networks in healthy full‐term infants (N = 139) within 1–6 days from birth by measuring neural synchrony in EEG recordings during quiet sleep. Large‐scale phase synchronization was measured in six frequency bands with the Phase Lag Index. Macroscopic network organization characteristics were quantified by constructing unweighted minimum spanning tree graphs. The cortical networks in early infancy were found to be significantly more hierarchical and had a more cost‐efficient organization compared with MST of random control networks, more so in the theta and alpha than in other frequency bands. Frontal and parietal sites acted as the main hubs of these networks, the topological characteristics of which were associated with gestation age (GA). This suggests that individual differences in network topology are related to cortical maturation during the prenatal period, when functional networks shift from strictly centralized toward segregated configurations. Hum Brain Mapp 38:4019–4033, 2017. © 2017 Wiley Periodicals, Inc.
Exercise and heart failure: an update

The present update is dedicated to the evolution of the interaction between heart failure (HF) and exercise and how the scientific community has handled it. Indeed, on the one hand, HF is a leading cause of morbidity and mortality with a stable prevalence from 1998 onward varying between 6.3% and 13.3%. On the other hand, exercise is seen as a diagnostic and prognostic tool as well as a therapeutic intervention in chronic HF. More precisely, the knowledge, the clinical application, and the research interest on the mutual interactions between exercise and HF have different phases in disease progression: Before HF onset (past): exercise provides protective benefit in preventing HF (primary prevention). With HF present: exercise improvement with training provides benefits in HF (secondary prevention). The prediction of future in HF patients: exercise impairment, as a leading characteristic of HF, is used as a prognostic factor.