Miracle-dz/UniFAR-FTUs huggingface dataset:
Randomised controlled trial of physiotherapy compared with advice for low back pain

Abstract Objective To measure the effectiveness of routine physiotherapy compared with an assessment session and advice from a physiotherapist for patients with low back pain. Design Pragmatic, multicentre, randomised controlled trial. Setting Seven British NHS physiotherapy departments. Participants 286 patients with low back pain of more than six weeks' duration. Intervention Routine physiotherapy or advice on remaining active from a physiotherapist. Both groups received an advice book. Main outcome measures Primary outcome was scores on the Oswestry disability index at 12 months. Secondary outcomes were scores on the Oswestry disability index (two and six months), scores on the Roland and Morris disability questionnaire and SF-36 (2, 6 and 12 months), and patient perceived benefit from treatment (2, 6, and 12 months). Results 200 of 286 patients (70%) provided follow up information at 12 months. Patients in the therapy group reported enhanced perceptions of benefit, but there was no evidence of a long term effect of physiotherapy in either disease specific or generic outcome measures (mean difference in change in Oswestry disability index scores at 12 months −1.0%, 95% confidence interval −3.7% to 1.6%). The most common treatments were low velocity spinal joint mobilisation techniques (72%, 104 of 144 patients) and lumbar spine mobility and abdominal strengthening exercises (94%, 136 patients). Conclusions Routine physiotherapy seemed to be no more effective than one session of assessment and advice from a physiotherapist.
Ligand Composition and Coating Density Co-Modulate the Chondrocyte Function on Poly(glycerol-dodecanedioate)

Inducing chondrocyte redifferentiation and promoting cartilaginous matrix accumulation are key challenges in the application of biomaterials in articular cartilage repair. Poly(glycerol-dodecanedioate) (PGD) is a viable candidate for scaffold design in cartilage tissue engineering (CTE). However, the surface properties of PGD are not ideal for cell attachment and growth due to its relative hydrophobicity compared with natural extracellular matrix (ECM). In this study, PGD was coated with various masses of collagen type I or hyaluronic acid, individually or in combination, to generate a cell–material interface with biological cues. The effects of ligand composition and density on the PGD surface properties and shape, metabolic activity, cell phenotype, and ECM production of human articular chondrocytes (hACs) were evaluated. Introducing ECM ligands on PGD significantly improved its hydrophilicity and promoted the chondrocyte’s anabolic activity. The morphology and anabolic activity of hACs on PGD were co-modulated by ligand composition and density, suggesting a combinatorial effect of both coating parameters on chondrocyte function during monolayer culture. Hyaluronic acid and its combination with collagen maintained a round cell shape and redifferentiated phenotype. This study demonstrated the complex mechanism of ligand-guided interactions between cell and biomaterial substrate and the potential of PGD as a scaffold material in the field of CTE.
A Unified Optimal Modulation Strategy for DAB Converters to Tradeoff the Backflow Power Reduction and All ZVS in the Full Operating Range

The backflow power in dual-active bridge (DAB) converters can cause power circulation in the H-bridge instead of flowing to the load, which increases the power loss of switching devices and magnetic components and lowers the system’s efficiency. Hence, a unified optimal modulation strategy (UOMS) is proposed in this article to reduce the backflow power and consequently improve the system efficiency. However, there is a conflict between minimizing the backflow power and achieving the zero-voltage-switching (ZVS) conditions of all the switching devices. Hence, a regulatory factor “<inline-formula> <tex-math notation="LaTeX">$\gamma $ </tex-math></inline-formula>” is introduced into the control variables to minimize the backflow power on the premise of all ZVS conditions, and hence, comprehensively improve the system efficiency. Moreover, the regulatory factor “<inline-formula> <tex-math notation="LaTeX">$\gamma $ </tex-math></inline-formula>” simplifies the calculation form of the control variables, which is easier to perform in the controller and can effectively shorten the computational time. According to the value ranges of the control variables (<inline-formula> <tex-math notation="LaTeX">$D_{\mathbf {0}}$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$D_{\mathbf {1}}$ </tex-math></inline-formula>, and <inline-formula> <tex-math notation="LaTeX">$D_{\mathbf {2}}$ </tex-math></inline-formula>) in the proposed UOMS, 12 operating modes are classified and four effective modes are detailed. For the four effective modes, the optimal triple-phase shift (TPS), optimal primary-dual-phase shift (PDPS), and optimal secondary-dual-phase shift (SDPS) modulation strategies are derived and their switching relationships are revealed. With various transferred powers, the proposed UOMS combines the optimal TPS, PDPS, SDPS, and SPS modulation strategies and can realize smooth and seamless transition switching processes among them in the full operating range. Therefore, the DAB converter can always operate in the optimal states for the full operating range of both the “Buck Mode” (<inline-formula> <tex-math notation="LaTeX">$k > $ </tex-math></inline-formula> 1) and “Boost Mode” (<inline-formula> <tex-math notation="LaTeX">$k < 1$ </tex-math></inline-formula>). Finally, experimental results verify the correctness of the theoretical analysis and the effectiveness of the proposed UOMS.
A Prospective Cohort Study Assessing the Relationship between Plasma Levels of Osimertinib and Treatment Efficacy and Safety

Osimertinib is a standard treatment for patients with EGFR-mutated non-small cell lung carcinoma (NSCLC). We evaluated the relationship between plasma osimertinib concentrations and treatment outcome in patients with NSCLC for this cohort study. The plasma levels of osimertinib and its metabolite AZ5104 were measured a week after the start of treatment (P1). The primary endpoint was to evaluate the correlation between plasma concentration and adverse events (AEs). The correlation with treatment efficacy was one of the secondary endpoints. In patients with CNS metastases, the concentration in the cerebrospinal fluid was also measured. Forty-one patients were enrolled. The frequency of AEs was highest for rash, followed by anorexia and thrombocytopenia. Thirty-eight cases provided measurements for P1. The median plasma concentration of osimertinib was 227 ng/mL, and that of AZ5104 was 16.5 ng/mL. The mean CNS penetration rate of two cases was 3.8%. The P1 in the group with anorexia was significantly higher than that in the group without anorexia (385.0 ng/mL vs. 231.5 ng/mL, p = 0.009). Divided into quartiles by P1 trough level, Q2 + Q3 (164–338 ng/mL) had longer PFS, while Q1 and Q4 had shorter PFS. An appropriate plasma level of osimertinib may avoid some adverse events and induce long PFS. Further large-scale trials are warranted.
Trade Openness and Economic Growth: A Panel Data Analysis of Baltic Countries

The theoretical propositions suggest that trade openness leads to a greater economic activity, due to the spread of knowhow and technological transferability. In that framework, it is generally expected that as trade openness increases, economic growth will follow the same trend because of innovation and productivity. Henceforth, establishing the contribution of trade openness to economic growth is of high priority, especially in the case of developing countries such as the Baltic ones. The current paper examines the causal relationship between trade openness and economic growth in the case of three Baltic countries for the period 1990-2020, using the recently developed by Dumitrescu and Hurlin (2012) non-causal Granger test for heterogenous panel data. The findings of the current study suggested that there is a cross-sectional dependence on the model time series between the counties under investigation, which proved that Baltic countries have common factors and common economic links. The theoretical and empirical studies previously conducted, are useful starting points for the discussion on policies which could increase the development of Baltic countries. For the development to be increased, the developmental procedures in the Baltic countries should upload their ? development chains? Such transformation of the ? development chains? will be achieved through investments in capital equipment, human capital and innovations by securing a favorable and stable economic climate.
Predict first–assemble later versus assemble first–predict later: Revisiting the dilemma for functional biogeography

Predicting community‐level trait indices, such as community‐weighted mean or functional dispersion, in space or time, is crucial, as they are markers of ecosystem functions, proxies for ecosystem services, and are now integral part of conservation planning. On one hand, since members of a species share similar traits, a natural way is to model species distributions as a function of the environment first (i.e. with species distribution models), and then to reconstruct trait indices for any locality of interest (predict‐first). On the other hand, community‐level trait indices can be seen as the direct result of environmental filtering, and thus their distributions may directly be modelled in response to the environment (assemble‐first). Although relatively different, these two approaches have been used interchangeably in trait‐based ecology with unknown consequences on their usability. Here, using plant community (4463 plots) and trait data (LNC, leaf nitrogen content; PLH, plant height; SLA, specific leaf area, for >800 species) covering the French Alps, we compared the two approaches to predict community mean and functional dispersion indices, accounting or not for abundance (CM, community mean; CWM, community weighted mean; FDis, functional dispersion; uFDis, unweighted functional dispersion). We tested both interpolation versus extrapolation capabilities of the two approaches. To support the empirical findings, we also run the same comparative analysis on simulated community data. While both approaches produced similar and skillful CM/CWM predictions (R2 > 0.63 for CWM PLH) for interpolation, the assemble‐first outperformed the predict‐first approach for extrapolation to unobserved environmental conditions (R2 = 0.60 against 0.54 for CWM PLH). Functional dispersion was generally less well predicted, although the assemble‐first approach again provided better predictions for both interpolation (R2 = 0.31 against 0.27 for FDis PLH) and extrapolation (R2 = 0.28 against 0.18 for FDis PLH). The predict‐first approach systematically overestimated FDis. Results were confirmed by the simulation experiments. We conclude that the direct modelling of community‐level indices provides more robust spatial predictions over space and time and should thus be preferred. This approach also does not suffer from having generally too many species predicted by the predict‐first approach.
Short- and long-term effects of the patient education strategy-learning and coping-in cardiac rehabilitation: a randomized controlled trial (LC-REHAB).

The objectives were to assess the short- and long-term effect of the patient education strategy 'Learning and Coping' (LC) in cardiac rehabilitation (CR) on health-related quality of life, patient education impact, cardiac risk factors and lifestyle. In total, 825 patients hospitalized with ischaemic heart disease or heart failure were randomized to either LC-CR or standard CR at three Danish hospitals. Teaching approach in LC-CR was situational, inductive and reflective, with experienced patients as co-educators and supplemental interviews. Teaching approach in standard CR was structured and deductive. Outcomes were assessed immediately after CR, and after 3 months (short term), and after 3 years (long term). Between-arm differences in favour of LC-CR were SF-12 'role emotional' (3.7, 95% CI: 0.6-6.8) and MDI depression score (0.9, 0.1-1.8) immediately after CR, exercise capacity (4 W, 1-9) at 3 months and SF-12 'role physical' (4.6, 0.1-9.0) (long term). Between-arm differences in favour of controls were waist circumference (-1.7 cm, -2.3 to -1.0) immediately after CR and HeiQ domain 'Constructive attitudes and approaches' (0.11, 0.04-0.18), triglycerides (-0.12 mmol/l, -0.21 to -0.02), systolic blood pressure (-3.12 mmHg, -5.66 to -0.58) at 3 months. Adding LC strategies to CR provides inconsistent short-term results but improves 'role physical' long term.
Diagnosis of Early Bacterial Pneumonia and Sepsis After Cardiovascular Surgery: A Diagnostic Prediction Model Based on LASSO Logistic Regression

Background Early postoperative bacterial pneumonia and sepsis (ePOPS), which occurs within the first 48 hours after cardiovascular surgery, is a serious life-threatening complication. Diagnosis of ePOPS is extremely challenging, and the existing diagnostic tools are insufficient. The purpose of this study was to construct a novel diagnostic prediction model for ePOPS. Methods Least Absolute Shrinkage and Selection Operator (LASSO) with logistic regression was used to construct a model to diagnose ePOPS based on patients’ comorbidities, medical history, and laboratory findings. The area under the receiver operating characteristic curve (AUC) was used to evaluate the model discrimination. Results A total of 1203 patients were recruited and randomly split into a training and validation set in a 7:3 ratio. By early morning on the 3rd postoperative day (POD3), 103 patients had experienced 133 episodes of bacterial pneumonia or sepsis (15 patients had both). LASSO logistic regression model showed that duration of mechanical ventilation (P=0.015), NYHA class ≥ III (P=0.001), diabetes (P<0.001), exudation on chest radiograph (P=0.011) and IL-6 on POD3 (P<0.001) were independent risk factors. Based on these factors, we created a nomogram named DICS-I with an AUC of 0.787 in the training set and 0.739 in the validation set. Conclusion The DICS-I model may be used to predict the risk of ePOPS after cardiovascular surgery, and is also especially suitable for predicting the risk of IRAO. The DICS-I model could help clinicians to adjust antibiotics on the POD3.
Polymorphic transitions mediated by surfactants in liquid crystal nanodroplet

ABSTRACT Recently, various techniques have been developed using photonic crystals. Liquid crystals (LC) confined in a nanodroplet mimicked photonic crystals, such as those of opal. Therefore, investigating the phase behaviour of LC molecules in nanodroplets is very important in the next-generation optical field. In this study, the chemical interaction between surfactants and LCs in nanodroplets is reproduced using a dissipative particle dynamics method. We identify the phase behaviour of LCs and investigate how the chemical interaction affect on the orientation of LCs. In particular, by adding surfactant molecules, various morphological behaviours were observed in the LC nanodroplet. The phase transition temperature varied depending on RND (amount of surfactant molecules). Furthermore, difference of the self-assembly structure also appeared inside the droplet depending on RND. Our simulation offers a theoretical guide to control morphologies of self-assembled LCs inside a nanodroplet, a novel system that may find applications in nanofluidic devices or in photonic crystal technology. Graphical Abstract
Scaling-Up eConsult: Promising Strategies to Address Enabling Factors in Four Jurisdictions in Canada

Background: Effective healthcare innovations are often not scaled up beyond their initial local context. Lack of practical knowledge on how to move from local innovations to large-system improvement hinders innovation and learning capacity in health systems. Studying scale-up processes can lead to a better understanding of how to facilitate the scale-up of interventions. eConsult is a digital health innovation that aims to connect primary care professionals with specialists through an asynchronous electronic consultation. The recent implementation of eConsult in the public health systems of four Canadian jurisdictions provides a unique opportunity to identify different enabling strategies and related factors that promote the scaling up of eConsult across jurisdictions. Methods: We conducted a narrative case study in four Canadian provinces, Quebec, Ontario, Manitoba, and Newfoundland & Labrador, over a 3-year period (2018–2021). We observed provincial eConsult committee meetings (n=65) and national eConsult forums (n=3), and we reviewed internal documents (n=93). We conducted semi-structured interviews with key actors in each jurisdiction (eg, researchers, primary care professionals, specialists, policy-makers, and patient partners) (n=40). We conducted thematic analysis guided by the literature on factors and strategies used to scale up innovations. Results: We identified a total of 31 strategies related to six key enabling factors to scaling up eConsult, including: (1) multi-actor engagement; (2) relative advantage; (3) knowledge transfer; (4) strong evidence base; (5) physician leadership; and (6) resource acquisition (eg, human, material, and financial resources). More commonly used strategies, such as leveraging research infrastructure and bringing together various actors, were used to address multiple enabling factors. Conclusion: Actors used various strategies to scale up eConsult within their respective contexts, and these helped address six key factors that seemed to be essential to the scale-up of eConsult.
The influence of chosen ore properties on efficiency of HPGR-based grinding circuits

Comminution processes are fundamental operations in raw material processing, they are also the most energy-intensive mining processes. The efficiency improvement of crushing processes is a key problem from technological, economic and ecological points of view. Physico-mechanical feed properties play a key role in the process course optimization, at given technological process conditions. A suitable selection of processing technology for determined ore characteristics increases the process efficiency and the raw materials economy through their better utilization. High-pressure ore comminution processes are practically the most efficient methods of material size reduction. It is a result of the lower process energy-consumption in HPGR and lower energy-consumption of the downstream grinding processes, as compared to conventional crushing devices. The reduction ratio value in downstream upgrading operations is also favourable due to the micro-cracks generation. It appears that the feed particle size distribution during high-pressure comminution is crucial to the obtained technological results. The experimental programme covered investigations of the influence of different particle size composition of ore on technological and economic results as well as the influence of feed moisture content on the process capacity and comminution effects. Economic results were assessed through the HPGR energy-consumption and throughput indices. The results of investigations presented in the paper confirm the thesis that, apart from the dmax value, proportions of individual particle fraction contents are also significant, especially the contents of finer fractions. The crushing results of the material with diverse particle compositions are reflected in the obtained different technological and economic effects. Considering the overall effect it is possible to design the most suitable circuit for a given feed. The results of investigations can be then helpful during the process of industrial application of HPGR, either in modernization of an existing circuit, or during the designing of a new flowsheet. The optimal circuit designed on the basis of crushing results should provide maximization of both technological and economic effects. 44
Unrolled iPPG: Video Heart Rate Estimation via Unrolling Proximal Gradient Descent

Imaging photoplethysmography (iPPG) is the process of estimating a person’s heart rate from video. In this work, we propose Unrolled iPPG, in which we integrate iterative optimization updates with deep learning-based signal priors to estimate the pulse waveform and heart rate from facial videos. We model the signal extracted from video as the sum of an underlying pulse signal and noise, but instead of explicitly imposing a handcrafted prior (e.g., sparsity in the frequency domain) on the signal, we learn priors on the signal and noise using neural networks. We solve for the underlying pulse signal by unrolling proximal gradient descent; the algorithm alternates between gradient descent steps and application of learned denoisers, which replace handcrafted priors and their proximal operators. Using this method, we achieve state-of-the-art heart rate estimation on the challenging MMSE-HR dataset.
A comparison of advanced time series models for environmental dependent stock recruitment of the western rock lobster

Time series models have been applied in many areas including economics, stock recruitment and the environment. Most environmental time series involve highly correlated dependent variables, which makes it difficult to apply conventional regression analysis. Traditionally, regression analysis has been applied to the environmental dependent stock and recruitment relationships for crustacean species in Western Australian fisheries. Alternative models, such as transfer function models and state space models have the potential to provide unproved forecasts for these types of data sets. This dissertation will explore the application of regression models, transfer function models, and state space models to modelling the puerulus stage of the western rock lobster (Panulirus Cygnus) in the fisheries of Western Australia. The transfer function models are consulted to examining the influences of the environment on crustacean species and can be used where correlated variables are involved. These models aim at producing short-term forecasts that may help in the management of the fisheries. In comparison with regression models, TFM models gave better forecast values with state space models given the forecast values in the first two years. Overall, it was shown that environmental effects, westerly winds and the Leeuwin Current, have a significant effect on the puerulus settlement for Dongara and Alkimos. It was also shown that westerly winds and spawning stock have a significant effect on the puerulus settlement at the Abrolhos Islands.
Paper-Based Aptasensors: Working Principles, Detection Modes, and Applications

Aptamers are short oligonucleotides designed to possess high binding affinity towards specific target compounds (ions, molecules, or cells). Due to their function and unique advantages, aptamers are considered viable alternatives to antibodies as biorecognition elements in bioassays and biosensors. On the other hand, paper-based devices (PADs) have emerged as a promising and powerful technology for the fabrication of low-cost analytical tools, mainly intended for on-site and point-of-care applications. The present work aims to provide a comprehensive overview of paper-based aptasensors. The review describes the fabrication methods and working principles of paper-based devices, the properties of aptamers as bioreceptors, the different modes of detection used in conjunction with aptasensing PADs, and representative applications for the detection of ions, small molecules, proteins, and cells. The future challenges and prospects of these devices are also discussed.