Miracle-dz/UniFAR-FTUs huggingface dataset:
Pragmatic cluster randomised double-blind pilot and feasibility trial of an active behavioural physiotherapy intervention for acute non-specific neck pain: a mixed-methods protocol

Introduction Non-specific neck pain causes pain and disability and contributes substantial socioeconomic burden internationally. Up to 50% of adults experience neck pain annually, leading to reduced the quality of life. An active behavioural physiotherapy intervention (ABPI) may be feasible to manage patients with acute non-specific neck pain to prevent transition to chronicity. A recent pilot and feasibility trial investigating an acute whiplash-associated disorder population found potential value of the ABPI with 95% of participants fully recovered (Neck Disability Index: NDI ≤4, compared with 17% in the standard physiotherapy arm); supporting a definitive trial. Qualitative findings from the physiotherapists supported the potential of the ABPI in a non-specific neck pain population. Methods and analysis Two phases: (1) Pragmatic cluster randomised double-blind, parallel 2-arm (ABPI vs standard physiotherapy intervention) pilot and feasibility trial to evaluate the procedures and feasibility of the ABPI for the management of acute non-specific neck pain. Six physiotherapy departments from six public hospitals in Thailand will be recruited and cluster randomised by a computer-generated randomisation sequence with block sampling. Sixty participants (30 each arm, 10 per hospital) will be assessed at baseline and 3 months following baseline for NDI, Numerical Rating Scale for pain intensity, cervical range of motion, fear-avoidance beliefs questionnaire and EuroQol-5 dimensions 5 levels outcomes, and (2) Embedded qualitative study using semistructured interviews to explore acceptability of the ABPI to participants (n=12) and physiotherapists (n=3). Descriptive analysis of the quantitative data and interpretative phenomenological analysis to code and analyse qualitative data (deductive and inductive) will inform feasibility for a future definitive trial. Ethics and dissemination This trial is approved by the Naresuan University Institutional Review Board (NUIRB_0380/61). Trial registration number and status TCTR20180607001; Recruiting commenced 1 February 2019.
Combining Soft Polysilazanes with Melt-Shear Organization of Core–Shell Particles: On the Road to Polymer-Templated Porous Ceramics

The preparation of ordered macroporous SiCN ceramics has attracted significant interest and is an attractive area for various applications, e.g., in the fields of catalysis, gas adsorption, or membranes. Non-oxidic ceramics, such as SiCN, own a great stability based on the covalent bonds between the containing elements, which leads to interesting properties concerning resistance and stability at high temperature. Their peculiar properties have become more and more important for a manifold of applications, like catalysis or separation processes, at high temperatures. Within this work, a feasible approach for the preparation of ordered porous materials by taking advantage of polymer-derived ceramics is presented. To gain access to free-standing films consisting of porous ceramic materials, the combination of monodisperse organic polymer-based colloids with diameters of 130 nm and 180 nm featuring a processable preceramic polymer is essential. For this purpose, the tailored design of hybrid organic/inorganic particles featuring anchoring sites for a preceramic polymer in the soft shell material is developed. Moreover, polymer-based core particles are used as sacrificial template for the generation of pores, while the preceramic shell polymer can be converted to the ceramic matrix after thermal treatment. Two different routes for the polymer particles, which can be obtained by emulsion polymerization, are followed for covalently linking the preceramic polysilazane Durazane1800 (Merck, Germany): (i) Free radical polymerization and (ii) atom transfer radical polymerization (ATRP) conditions. These hybrid hard core/soft shell particles can be processed via the so-called melt-shear organization for the one-step preparation of free-standing particle films. A major advantage of this technique is the absence of any solvent or dispersion medium, enabling the core particles to merge into ordered particle stacks based on the soft preceramic shell. Subsequent ceramization of the colloidal crystal films leads to core particle degradation and transformation into porous ceramics with ceramic yields of 18–54%.
Cs2NaVCl6 : a Pb-Free Halide Double Perovskite with Strong Visible and Near-Infrared Light Absorption.

Developing the environmentally-friendly, stable as well as narrow and direct bandgap halide perovskite materials has attracted substantial interests due to their potential wide applications. Here, an all-inorganic Pb-free halide double perovskite, Cs2NaVCl6, was prepared by solid state reaction method and hydrothermal method. It crystallizes in cubic Fm-3m space group with unit parameter of a=10.3497(14) Å. The combined density functional theory and experimental study demonstrates that the compound is a direct band gap semiconductor with bandgap of ~2.64 eV. More importantly, it exhibits strong visible and near-infrared light absorptions and markedly ambient and thermal stability.
Exploring How People Affected by Methamphetamine Exchange Social Support Through Online Interactions on Facebook: Content Analysis

Background Methamphetamine is an illicit and addictive psychostimulant that remains to be a significant cause of economic burden in Australia. Social media is increasingly being used by nongovernment organizations and health services to encourage the growth of social support networks among people with health-related issues. Several studies have investigated the utility of social media in providing social support to groups of people with health-related issues. However, limited research exists that explores how people who have been directly or indirectly affected by methamphetamine use social media for social support. Objective This study aimed to determine the types of social support being sought and provided by people affected by methamphetamine when interacting with others on a Facebook page. Methods A total of 14,777 posts were collected from a Facebook page and transferred into an Excel document for content analysis. The posts were manually coded into categories of social support using an adapted version of Cutrona and Suhr’s Social Support Behavior Code. Posts could be coded into more than one category. Saturation was reached at 2000 posts, which were used to draw inferences. Results Emotional support was the most offered support type, with 42.05% (841/2000) of posts providing this form of support. This is followed by esteem support, which was provided in 40.40% (808/2000) of posts. Overall, 24.20% (484/2000) of posts offered informational support. Network support and tangible support were the least offered support types, with 2.25% (45/2000) and 1.70% (34/2000) of posts offering these types of support, respectively. Conclusions This study suggests that online social support groups can be effective in challenging stigma by encouraging people affected by methamphetamine to connect with each other and talk about their struggles. This in turn represents an important step toward successful rehabilitation.
The YAP1–NMU Axis Is Associated with Pancreatic Cancer Progression and Poor Outcome: Identification of a Novel Diagnostic Biomarker and Therapeutic Target

Yes-associated protein (YAP)-1 is highly upregulated in pancreatic cancer and associated with tumor progression. However, little is known about the role of YAP1 and related genes in pancreatic cancer. Here, we identified target genes regulated by YAP1 and explored their role in pancreatic cancer progression and the related clinical implications. Analysis of different pancreatic cancer databases showed that Neuromedin U (NMU) expression was positively correlated with YAP1 expression in the tumor group. The Cancer Genome Atlas data indicated that high YAP1 and NMU expression levels were associated with poor mean and overall survival. YAP1 overexpression induced NMU expression and transcription and promoted cell motility in vitro and tumor metastasis in vivo via upregulation of epithelial–mesenchymal transition (EMT), whereas specific inhibition of NMU in cells stably expressing YAP1 had the opposite effect in vitro and in vivo. To define this functional association, we identified a transcriptional enhanced associate domain (TEAD) binding site in the NMU promoter and demonstrated that YAP1–TEAD binding upstream of the NMU gene regulated its transcription. These results indicate that the identified positive correlation between YAP1 and NMU is a potential novel drug target and biomarker in metastatic pancreatic cancer.
Effect of Methyl Jasmonate on Phenolic Accumulation in Wounded Broccoli

In order to find an efficient way for broccoli to increase the phenolic content, this study intended primarily to elucidate the effect of methyl jasmonate (MeJA) treatment on the phenolic accumulation in broccoli. The optimum concentration of MeJA was studied first, and 10 μM MeJA was chosen as the most effective concentration to improve the phenolic content in wounded broccoli. Furthermore, in order to elucidate the effect of methyl jasmonate (MeJA) treatment on phenolic biosynthesis in broccoli, the key enzyme activities of phenylpropanoid metabolism, the total phenolic content (TPC), individual phenolic compounds (PC), antioxidant activity (AOX) and antioxidant metabolism-associated enzyme activities were investigated. Results show that MeJA treatment stimulated phenylalanine ammonia-lyase (PAL), cinnamate 4-hydroxylase (C4H), and 4-coumarin coenzyme A ligase (4CL) enzymes activities in phenylpropanoid metabolism, and inhibited the activity of polyphenol oxidase (PPO), and further accelerated the accumulation of the wound-induced rutin, caffeic acid, and cinnamic acid accumulation, which contributed to the result of the total phenolic content increasing by 34.8% and ferric reducing antioxidant power increasing by 154.9% in broccoli. These results demonstrate that MeJA in combination with wounding stress can induce phenylpropanoid metabolism for the wound-induced phenolic accumulation in broccoli.
Comparison of the efficacy of continuous epidural block with epidural electrical stimulation and conventional continuous epidural block for management of zoster-associated pain beyond the acute phase

Abstract Continuous epidural block (CEB) is a popular clinical method for controlling postherpetic neuralgia (PHN). However, the long-term effects of CEB on PHN have not yet been established. This study aimed to confirm the clinical efficacy of epidural electrical stimulation catheters in CEB to manage PHN. Patients were classified into 2 groups: those with subacute PHN, between 30 and 180 days after the onset of the rash; and those with chronic PHN, over 180 days after the onset of the rash. On the basis of the type of catheter used, the patients were further divided into the following 2 groups: the esopocan group, in which the site of herpes zoster infection was confirmed using a contrast medium alone; and the epistim group, in which an additional method of electrical stimulation through a guide-wire in the catheter was used for detecting the site affected by herpes. Clinical efficacy was assessed with a numerical rating scale immediately 1, 3, and 6 months after the procedure. We also investigated whether additional interventional treatment was necessitated because of insufficient pain control during the 6-month follow-up. We examined 88 patients. In the subacute PHN period, the numerical rating scale score was significantly lower in the epistim group than in the esopocan group until 6 months. In the chronic PHN period, no significant differences in the numerical rating scale scores were observed between the 2 groups until 6 months. In the subacute PHN period, the adjusted odds ratio for other interventional procedures within 6 months in the esopocan group versus the epistim group was 2.59 (95% confidence interval [CI] 0.83–8.09, P = .10), and in the chronic PHN period, it was 1.31 (95% CI 0.11–5.46, P = .79). Epidural drug administration to specific segments using electrical stimulation catheters may be more useful in mitigating zoster-associated pain in subacute PHN.
Maternal Thyroid Hormone Replacement Therapy Exposure and Language and Communication Skills of Offspring at 8 Years of Age

Key Points Question Is prenatal exposure to thyroid hormone replacement therapy associated with children’s language, speech, and communication skills at 8 years of age? Findings In this nationwide population-based cohort linkage study of 53 862 mother-child pairs in Norway, prenatal thyroid hormone replacement therapy exposure was not associated with diagnoses and symptoms of child language and speech impairment, compared with the group not exposed to thyroid hormone replacement therapy or the group that received thyroid hormone replacement therapy after delivery. Meaning These findings indicate that the children of mothers treated with thyroid hormone replacement therapy for hypothyroidism were not associated with symptoms of or increased risk of language impairment.
Endobronchial ultrasound-guided transbronchial needle aspiration versus mediastinoscopy for mediastinal staging of lung cancer

Abstract Background: Lung cancer is a major health problem, with estimates of 1.6 million tumor-related deaths annually worldwide. The emergence of endobronchial ultrasound (EBUS), a minimally invasive procedure capable of providing valuable information for primary tumor diagnosis and mediastinal staging, significantly changed the approach of pulmonary cancer, becoming part of the routine mediastinal evaluation of lung cancer in developed countries. Some economic evaluation studies published in the last 10 years have already analyzed the incorporation of the EBUS technique in different health systems. The aim of this systematic review is to synthesize the relevant information brought by these studies to better understand the economic effect of the implementation of this staging tool. Methods: The systematic review will be reported using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement guidelines. Eletronic databases (Medline, Lilacs, Embase, Cochrane Library of Trials, Web of Science, Scopus, National Health System Economic Evaluation Database) will be searched for full economic analyses regarding the use of EBUS-guided transbronchial needle aspiration (EBUS-TBNA) compared to the surgical technique of mediastinoscopy for the mediastinal staging of lung cancer. Two authors will perform the selection of studies, data extraction, and the assessment of risk of bias. Occasionally, a senior reviewer will participate, if necessary, on study selection or data extraction. Results: Results will be published in a peer-reviewed journal. Conclusion: This review may influence a more cost-effective mediastinal staging approach for patients with lung cancer around the world and help health decision makers decide whether the EBUS-TBNA technique should be incorporated into their health systems and how to do it efficiently. Protocol Registry: PROSPERO 42019107901.
Analysis of CEISA Services User Satisfaction Using the EUCS Method in The Directorate General of Customs and Excise

The purpose of this study is to analyze the factors that influence the satisfaction of users of CEISA services (Customs & Excise Information System and Automation) at the Directorate General of Customs and Excise (DGCE). CEISA uses Single Sign-On (SSO) technology, meaning that users only do one login to be able to access all applications in accordance with their authority. Therefore, the CEISA database and server are centrally managed so that they can be accessed throughout the DGCE office. But in practice there are still DGCE offices that develop independent applications. User satisfaction is one of the important factors that influence the success of implementing an information system. This study uses the End-User Computing Satisfaction (EUCS) method as an indicator of research. The variables tested in this study were 100 respondents as samples taken from employees at the Tanjung Priok Type A Customs and Excise Service Office (CESO). Data analysis using Multiple Linear Regression Test with IBM SPSS Statistics 25 as a tool to process data. There are five hypotheses proposed in this study. The results showed that all proposed hypotheses were accepted. That is, all variables in the EUCS method have a positive and significant effect on CEISA service user satisfaction in the DGCE environment.
Apprentissage de plongements lexicaux par une approche réseaux complexes (Complex networks based word embeddings)

La littérature des réseaux complexes a montré la pertinence de l’étude de la langue sous forme de réseau pour différentes applications : désambiguïsation, résumé automatique, classification des langues, etc. Cette même littérature a démontré que les réseaux de co-occurrences de mots possèdent une structure de communautés latente. Nous formulons l’hypothèse que cette structuration du réseau sous forme de communautés est utile pour travailler sur la sémantique d’une langue et introduisons donc dans cet article une méthode d’apprentissage de plongements originale basée sur cette hypothèse. Cette hypothèse est cohérente avec la proximité qui existe entre la détection de communautés sur un réseau de co-occurrences et la factorisation d’une matrice de co-occurrences, méthode couramment utilisée pour l’apprentissage de plongements lexicaux. Nous décrivons notre méthode structurée en trois étapes : construction et pré-traitement du réseau, détection de la structure de communautés, construction des plongements de mots à partir de cette structure. Après avoir décrit cette nouvelle méthodologie, nous montrons la pertinence de notre approche avec des premiers résultats d’évaluation sur les tâches de catégorisation et de similarité. Enfin, nous discutons des perspectives importantes d’un tel modèle issu des réseaux complexes : les dimensions du modèle (les communautés) semblent interprétables, l’apprentissage est rapide, la construction d’un nouveau plongement est presque instantanée, et il est envisageable d’en expérimenter une version incrémentale pour travailler sur des corpus textuels temporels.
Efficient Community Detection in Boolean Composed Multiplex Networks

Networks (or graphs) are used to model the dyadic relations between entities in a complex system. In cases where there exists multiple relations between the entities, the complex system can be represented as a multilayer network, where the network in each layer represents one particular relation (or feature). The analysis of multilayer networks involves combining edges from specific layers and then computing a network property. Different subsets of the layers can be combined. For any Boolean combination operation (e.g. AND, OR), the number of possible subsets is exponential to the number of layers. Thus recomputing for each subset from scratch is an expensive process. In this paper, we propose to efficiently analyze multilayer networks using a method that we term network decomposition. Network decomposition is based on analyzing each network layer individually and then aggregating the analysis results. We demonstrate the effectiveness of using network decomposition for detecting communities on different combinations of network layers. Our results on multilayer networks obtained from real-world and synthetic datasets show that our proposed network decomposition method requires significantly lower computation time while producing results of high accuracy.
A deep surrogate approach to efficient Bayesian inversion in PDE and integral equation models

We propose a novel deep learning approach to efficiently perform Bayesian inference in partial differential equation (PDE) and integral equation models over potentially high-dimensional parameter spaces. The contributions of this paper are two-fold; the first is the introduction of a neural network approach to approximating the solutions of Fredholm and Volterra integral equations of the first and second kind. The second is the description of a deep surrogate model which allows for efficient sampling from a Bayesian posterior distribution in which the likelihood depends on the solutions of PDEs or integral equations. For the latter, our method relies on the approximate representation of parametric solutions by neural networks. This deep learning approach allows the accurate and efficient approximation of parametric solutions in significantly higher dimensions than is possible using classical techniques. Since the approximated solutions are very cheap to evaluate, the solutions of Bayesian inverse problems over large parameter spaces are tractable using Markov chain Monte Carlo. We demonstrate the efficiency of our method using two real-world examples; these include Bayesian inference in the PDE and integral equation case for an example from electrochemistry, and Bayesian inference of a function-valued heat-transfer parameter with applications in aviation.
Recognizing UMLS Semantic Types with Deep Learning

Entity recognition is a critical first step to a number of clinical NLP applications, such as entity linking and relation extraction. We present the first attempt to apply state-of-the-art entity recognition approaches on a newly released dataset, MedMentions. This dataset contains over 4000 biomedical abstracts, annotated for UMLS semantic types. In comparison to existing datasets, MedMentions contains a far greater number of entity types, and thus represents a more challenging but realistic scenario in a real-world setting. We explore a number of relevant dimensions, including the use of contextual versus non-contextual word embeddings, general versus domain-specific unsupervised pre-training, and different deep learning architectures. We contrast our results against the well-known i2b2 2010 entity recognition dataset, and propose a new method to combine general and domain-specific information. While producing a state-of-the-art result for the i2b2 2010 task (F1 = 0.90), our results on MedMentions are significantly lower (F1 = 0.63), suggesting there is still plenty of opportunity for improvement on this new data.
New results on large induced forests in graphs

For a graph $G$, let $a(G)$ denote the maximum size of a subset of vertices that induces a forest. We prove the following. 1. Let $G$ be a graph of order $n$, maximum degree $\Delta>0$ and maximum clique size $\omega$. Then \[ a(G) \geq \frac{6n}{2\Delta + \omega +2}. \] This bound is sharp for cliques. 2. Let $G=(V,E)$ be a triangle-free graph and let $d(v)$ denote the degree of $v \in V$. Then \[ a(G) \geq \sum_{v \in V} \min\left(1, \frac{3}{d(v)+2} \right). \] As a corollary we have that a triangle-free graph $G$ of order $n$, with $m$ edges and average degree $d \geq 2$ satisfies \[ a(G) \geq \frac{3n}{d+2}. \] This improves the lower bound $n - \frac{m}{4}$ of Alon-Mubayi-Thomas for graphs of average degree greater than $4$. Furthermore it improves the lower bound $\frac{20n - 5m - 5}{19}$ of Shi-Xu for (connected) graphs of average degree at least $\frac{9}{2}$.