Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparative efficacy of Chinese herbal injections for septic shock

Abstract Background: Septic shock is a life-threatening syndrome. Despite Western medicine guidelines being continually updated on septic shock, the disease still has a high mortality rate. Chinese herbal injections (CHIs) are injections made from effective components of traditional Chinese medicine, which have a potential therapeutic effect on septic shock and are recommended as the adjunctive treatment for septic shock in China. Although pairwise meta-analysis has been published for category-single CHIs about treatment effects of septic shock, there is no meta-analysis comparing more than 3 various types of CHIs used for septic shock. Methods: Chinese and English databases will be retrieved for randomized controlled trials from the establishment of the databases to September 30, 2021. Two reviewers will perform literature searches and data extractions while another 2 reviewers for risk assessments. RevMan V.5. 4 software, Stata V.14. 0 software, and R V. 4.1. 1 software will be applied to perform pairwise meta-analysis and network meta-analysis. We will apply the Cochrane risk of bias tool to assess the risk of bias while the Grades of Recommendation, Assessment, Development, and Evaluation approach will be used to summarize the results of the study. The PRISMA-P guideline was followed for this protocol. Results: The current study will explore the therapeutic effect of CHIs in the treatment of septic shock through pairwise meta-analysis and network meta-analysis. Conclusion: This study will seek out the best-performed CHIs under various indicators for septic shock, providing supporting evidence for clinical selection of CHIs for septic shock.
Medial Plantar Fasciocutaneous Flap Reconstruction for Load-Bearing Foot Defects in Patients With Acral Melanoma

Background Acral lentiginous melanoma (ALM) is a rare subtype of malignant melanoma that usually involves the weight-bearing plantar area. Plantar defect reconstruction has traditionally been performed with skin grafts or free flaps. This study examined the efficacy and safety of a medial plantar artery perforator flap (MPAPF) for plantar defect reconstruction after wide excision of an ALM. Method Twenty-five patients who underwent reconstruction with a MPAPF between 2011 and 2021 were enrolled in this study. The defects were classified into 6 plantar zones. Demographic and clinical data were retrospectively analyzed. Results Reconstruction with medial plantar fasciocutaneous island flaps was performed in all cases, except for 4 patients who had lesions in forefoot, which required free medial plantar flaps. Defects in lateral and posterior heel were more likely to present with venous congestion and require longer healing times and revision surgery (P < 0.05). The average follow-up period was 49 months. Four and 5 patients developed local recurrence and distant metastasis, respectively. Four cases of hyperkeratosis and paresthesia were documented, but there were no cases of ulceration or wound dehiscence. None of the cases required secondary debulking procedures. Conclusions The MPAPF is safe and effective for plantar defect reconstruction among patients with ALM. Meticulous dissection and adequate tunneling are needed, particularly for defects in the lateral and posterior heel, to minimize flap congestion and revision operations.
Stable and Functionally Diverse Versatile Peroxidases Designed Directly from Sequences

White-rot fungi secrete a repertoire of high-redox potential oxidoreductases to efficiently decompose lignin. Of these enzymes, versatile peroxidases (VPs) are the most promiscuous biocatalysts. VPs are attractive enzymes for research and industrial use but their recombinant production is extremely challenging. To date, only a single VP has been structurally characterized and optimized for recombinant functional expression, stability, and activity. Computational enzyme optimization methods can be applied to many enzymes in parallel but they require accurate structures. Here, we demonstrate that model structures computed by deep-learning-based ab initio structure prediction methods are reliable starting points for one-shot PROSS stability-design calculations. Four designed VPs encoding as many as 43 mutations relative to the wildtype enzymes are functionally expressed in yeast, whereas their wildtype parents are not. Three of these designs exhibit substantial and useful diversity in their reactivity profiles and tolerance to environmental conditions. The reliability of the new generation of structure predictors and design methods increases the scale and scope of computational enzyme optimization, enabling efficient discovery and exploitation of the functional diversity in natural enzyme families directly from genomic databases.
Optimal Current Phase Curve Fitting of IPM Motors in Flux-Weakening Region Based on Neural Network

To take the nonlinear effect of interior permanent magnet(IPM) motors into account,a method of fitting the optimal phase curve in flux-weakening region by BP neural network is presented.The theory of maximum torque per ampere(MTPA) control is analyzed.Considering the voltage and current limits of power inverter,the condition for IPM motors to output maximum torque in flux-weakening region is derived.A BP neural network is constructed to map the motor speed and current amplitude to optimal phase angel in flux-weakening region.Computation and simulation results show that the maximum error between the fitting result of the constructed BP neural network and the result of finite element method(FEM) is less than 1°.
Endoscopic management of subepithelial lesions including neuroendocrine neoplasms: European Society of Gastrointestinal Endoscopy (ESGE) Guideline.

1: ESGE recommends endoscopic ultrasonography (EUS) as the best tool to characterize subepithelial lesion (SEL) features (size, location, originating layer, echogenicity, shape), but EUS alone is not able to distinguish among all types of SEL.Strong recommendation, moderate quality evidence. 2: ESGE suggests providing tissue diagnosis for all SELs with features suggestive of gastrointestinal stromal tumor (GIST) if they are of size > 20 mm, or have high risk stigmata, or require surgical resection or oncological treatment.Weak recommendation, very low quality evidence. 3: ESGE recommends EUS-guided fine-needle biopsy (EUS-FNB) or mucosal incision-assisted biopsy (MIAB) equally for tissue diagnosis of SELs ≥ 20 mm in size.Strong recommendation, moderate quality evidence. 4: ESGE recommends against surveillance of asymptomatic gastrointestinal (GI) tract leiomyomas, lipomas, heterotopic pancreas, granular cell tumors, schwannomas, and glomus tumors, if the diagnosis is clear.Strong recommendation, moderate quality evidence. 5: ESGE suggests surveillance of asymptomatic esophageal and gastric SELs without definite diagnosis, with esophagogastroduodenoscopy (EGD) at 3-6 months, and then at 2-3-year intervals for lesions < 10 mm in size, and at 1-2-year intervals for lesions 10-20 mm in size. For asymptomatic SELs > 20 mm in size that are not resected, ESGE suggests surveillance with EGD plus EUS at 6 months and then at 6-12-month intervals.Weak recommendation, very low quality evidence. 6: ESGE recommends endoscopic resection for type 1 gastric neuroendocrine neoplasms (g-NENs) if they grow larger than 10 mm. The choice of resection technique should depend on size, depth of invasion, and location in the stomach.Strong recommendation, low quality evidence. 7: ESGE suggests considering removal of histologically proven gastric GISTs smaller than 20 mm as an alternative to surveillance. The decision to resect should be discussed in a multidisciplinary meeting. The choice of technique should depend on size, location, and local expertise.Weak recommendation, very low quality evidence. 8: ESGE suggests that, to avoid unnecessary follow-up, endoscopic resection is an option for gastric SELs smaller than 20 mm and of unknown histology after failure of attempts to obtain diagnosis.Weak recommendation, very low quality evidence. 9: ESGE recommends basing the surveillance strategy on the type and completeness of resection. After curative resection of benign SELs no follow-up is advised, except for type 1 gastric NEN for which surveillance at 1-2 years is advised.Strong recommendation, low quality evidence. 10: For lower or upper GI NEN with a positive or indeterminate margin at resection, ESGE recommends repeating endoscopy at 3-6 months and another attempt at endoscopic resection in the case of residual disease.Strong recommendation, low quality evidence.
Data-Driven Adaptive Iterative Learning Bipartite Consensus for Heterogeneous Nonlinear Cooperation–Antagonism Networks

Heterogeneous dynamics, strongly nonlinear and nonaffine structures, and cooperation–antagonism networks are considered together in this work, which have been considered as challenging problems in the output consensus of multiagent systems. A heterogeneous linear data model (LDM) is presented to accommodate the nonlinear nonaffine structure of the heterogeneous agent. It also builds an I/O dynamic relationship of the agents along the iteration-dimensional direction to make it possible to learn control experience from previous iterations to improve the transient consensus performance. Then, an adaptive update algorithm is developed for the estimation of the uncertain parameters of the LDM to compensate for the unknown heterogeneous dynamics and model structures. To address the problem of cooperation and antagonism, an adaptive learning consensus protocol is proposed considering two signed graphs, which are structurally balanced and unbalanced, respectively. The learning gain can be regulated using the proposed adaptive updating law to enhance the adaptability to the uncertainties. With rigorous analysis, the bipartite consensus is proven in the case that the graph is structurally balanced, and the convergence of the agent output to zero is also proven in the case that the graph is unbalanced in its structure. The presented bipartite consensus method is data-based without the use of any explicit model information. The theoretical results are demonstrated through simulations.
Attention Enhanced Reinforcement Learning for Multi agent Cooperation

In this article, a novel method, called attention enhanced reinforcement learning (AERL), is proposed to address issues including complex interaction, limited communication range, and time-varying communication topology for multi agent cooperation. AERL includes a communication enhanced network (CEN), a graph spatiotemporal long short-term memory network (GST-LSTM), and parameters sharing multi-pseudo critic proximal policy optimization (PS-MPC-PPO). Specifically, CEN based on graph attention mechanism is designed to enlarge the agents’ communication range and to deal with complex interaction among the agents. GST-LSTM, which replaces the standard fully connected (FC) operator in LSTM with graph attention operator, is designed to capture the temporal dependence while maintaining the spatial structure learned by CEN. PS-MPC-PPO, which extends proximal policy optimization (PPO) in multi agent systems with parameters’ sharing to scale to environments with a large number of agents in training, is designed with multi-pseudo critics to mitigate the bias problem in training and accelerate the convergence process. Simulation results for three groups of representative scenarios including formation control, group containment, and predator–prey games demonstrate the effectiveness and robustness of AERL.
Disentangling Light Fields for Super-Resolution and Disparity Estimation

Light field (LF) cameras record both intensity and directions of light rays, and encode 3D cues into 4D LF images. Recently, many convolutional neural networks (CNNs) have been proposed for various LF image processing tasks. However, it is challenging for CNNs to effectively process LF images since the spatial and angular information are highly inter-twined with varying disparities. In this paper, we propose a generic mechanism to disentangle these coupled information for LF image processing. Specifically, we first design a class of domain-specific convolutions to disentangle LFs from different dimensions, and then leverage these disentangled features by designing task-specific modules. Our disentangling mechanism can well incorporate the LF structure prior and effectively handle 4D LF data. Based on the proposed mechanism, we develop three networks (i.e., DistgSSR, DistgASR and DistgDisp) for spatial super-resolution, angular super-resolution and disparity estimation. Experimental results show that our networks achieve state-of-the-art performance on all these three tasks, which demonstrates the effectiveness, efficiency, and generality of our disentangling mechanism. Project page: https://yingqianwang.github. io/DistgLF/.
Conceptions of healthcare professionals about rehabilitees’ participation in goal setting in an acute hospital: A phenomenographic study

ABSTRACT Purpose In acute care, effective goal-setting is an essential phase of a successful rehabilitation process. However, professionals’ knowledge and skills in rehabilitee-centered practice may not always match the ways of implementing goal-setting. This study aimed to describe the variation in how acute hospital professionals perceive and comprehend rehabilitee participation in rehabilitation goal-setting. Methods Data were collected by interviewing 27 multidisciplinary rehabilitation team members in small groups shortly after rehabilitation goal-setting sessions. A qualitative research design based on phenomenography was implemented. Results We identified four conceptions of rehabilitee participation, based on four hierarchically constructed categories: 1) Professional-driven rehabilitee participation; 2) Awakening rehabilitee participation; 3) Coaching participation; and 4) Shared participation. These categories varied according to four themes: 1) Use of power; 2) Ability to involve; 3) Interaction process; and 4) Atmosphere. Three critical aspects between the categories were also identified: 1) Appreciative listening; 2) Trustful relationship; and 3) Collaborative partnership. Conclusion The study generated new insights into the meaning of rehabilitee participation, as conceptualized in relation to rehabilitation goal-setting and an acute hospital context. The identified critical aspects can be useful for planning and developing continuing professional education (CPE) in rehabilitation goal-setting for professionals.
Human papillomavirus dose reminder preferences among parents from a diverse clinical sample: a qualitative study

ABSTRACT Reminders are an important method for encouraging patients to return for follow-up visits, such as for successive doses of the human papillomavirus (HPV) vaccine. However, patients may have preferences for different types of reminders. This study examined which reminder methods parents of pediatric patients found most useful and their thoughts on how the reminders helped them to complete their children’s HPV vaccine series. This qualitative study was conducted on a purposively sampled group of parents who participated in a multi-level intervention intended to improve uptake and completion of the HPV vaccine series. Parents who agreed to participate were interviewed by phone using semi-structured interviews about their satisfaction with different program components, including reminders they received. Interviews were conducted between May 26, 2016 and October 18, 2017. Thematic analyses of data were conducted using NVivo software. Among 269 program participants invited to participate in the interviews, 157 agreed (58.4%) and 89 were successfully interviewed (33.1%). Participants thought that reminders were effective at helping them return for follow-up visits to ensure their children received all recommended HPV vaccine doses. Although most parents preferred texts, many also favored other reminder methods by themselves or in combination with texts. Parents suggested that the reminders indicate the purpose of the appointment and for which child. Reminders are an important part of a multi-component intervention that aims to increase completion of the HPV vaccine series. Program enrollees prefer different types of reminders, so offering several options may improve returns for follow-up doses.
Microglial cathepsin E plays a role in neuroinflammation and amyloid β production in Alzheimer’s disease

Regulation of neuroinflammation and β‐amyloid (Aβ) production are critical factors in the pathogenesis of Alzheimer's disease (AD). Cathepsin E (CatE), an aspartic protease, is widely studied as an inducer of growth arrest and apoptosis in several types of cancer cells. However, the function of CatE in AD is unknown. In this study, we demonstrated that the ablation of CatE in human amyloid precursor protein knock‐in mice, called APPNL−G−F mice, significantly reduced Aβ accumulation, neuroinflammation, and cognitive impairments. Mechanistically, microglial CatE is involved in the secretion of soluble TNF‐related apoptosis‐inducing ligand, which plays an important role in microglia‐mediated NF‐κB‐dependent neuroinflammation and neuronal Aβ production by beta‐site APP cleaving enzyme 1. Furthermore, cannula‐delivered CatE inhibitors improved memory function and reduced Aβ accumulation and neuroinflammation in AD mice. Our findings reveal that CatE as a modulator of microglial activation and neurodegeneration in AD and suggest CatE as a therapeutic target for AD by targeting neuroinflammation and Aβ pathology.
A Credit Risk Recognition Model for Commercial Bank Based on SOC Neural Network

This paper constructs a credit risk recognition model for commercial banks by combining Self-Organized Competition(SOC) neural network's superiority in pattern classification with principal component analysis.First, a set of index system is established for credit risk assesment,then extracting character index from principal componet analysis,finally finishing non-supervisory pattern classification by SOC neural network.At the same time,26 listed companies of Shanxi are selected as samples in 2007.The results show that the model has strong risk recognition capability and preferable risk predicting fanction for commercial banks.
Test Bench for the Unsteady Characterization of a Pulsed Green Monopropellant Thruster

PulCheR is a R&D project funded by the European Union Seventh Framework Programme with the main aim of demonstrating the feasibility of a new propulsion concept in which the propellants are fed in the combustion chamber at low pressure and the thrust is generated by means of high frequency pulses. The characterization of this type of thruster has required to carefully design the test bench in order to allow the right assessment of the thruster performance. The unsteady behavior of the thruster has been the main difficulty during the design and the choice of transducers. The most difficult measurement concerns the assessment of the mass injected at each pulse inside the thruster. Because of this, two distinct test benches have been designed and two approaches at measuring the mass injected have been considered. The present article focuses on the challenges concerning the design of the test bench for the characterization of the PulCheR monopropellant thruster.
Novel Methods for Slosh Parameter Estimation Using Pendulum Analogy

Liquid slosh is modeled as simple pendulum. Parameter estimation strategies for this model are developed using translational and pitching excitations. Translational excitation and quick stop gives the parameters like natural frequency, slosh mass and hinge point location. Moment of inertia of rigid mass of liquid is estimated by giving pitching excitation to the tank. It is observed that moment of inertia of rigid liquid mass has a strong dependency on frequency of excitation.
Population genetic structure of the malaria vector Anopheles fluviatilis species T (Diptera: Culicidae) in India

Anopheles fluviatilis James (Diptera: Culicidae) represents a complex that comprises four sibling species (S, T, U, and V). Among these, species T is widely distributed in India. Chromosomal inversion polymorphism exists among different geographic populations of An. fluviatilis species T; however, population genetic structure is not understood. This study inferred a genetic structure among six geographically diverse populations of species T using a panel of microsatellite markers. Analyses indicated a significant but low genetic differentiation among the majority of the studied populations. A significant correlation was observed between genetic and geographic distances, exhibiting stepwise migration patterns among populations.
Risk of SARS-CoV-2 Reinfection 18 Months After Primary Infection: Population-Level Observational Study

Current data suggest that SARS-CoV-2 reinfections are rare. Uncertainties remain, however, on the duration of the natural immunity, its protection against Omicron variant, and on the impact of vaccination to reduce reinfection rates. In this retrospective cohort analysis of the entire population of an Italian region, we followed 1,293,941 subjects from the beginning of the pandemic to the current scenario of Omicron predominance (up to mid-February 2022). After an average of 277 days, we recorded 729 reinfections among 119,266 previously infected subjects (overall rate: 6.1‰), eight COVID-19-related hospitalizations (7/100,000), and two deaths. Importantly, the incidence of reinfection did not vary substantially over time: after 18–22 months from the primary infection, the reinfection rate was still 6.7‰, suggesting that protection conferred by natural immunity may last beyond 12 months. The risk of reinfection was significantly higher among females, unvaccinated subjects, and during the Omicron wave.
Selection of Random Processes in Application of Monte Carlo Method to Calculation of the Lightning Flash-over Rate of Transmission Lines

It is well known that lightening trip out caused by lightening flashover of electrical power transmission lines greatly influences the safety and steady operating of power system.Research has been widely carried out with calculation of lightening flash-over rate of transmission lines.In calculation of lightning flash-over rate of transmission lines,the selection of random processes is very important for the speed and the precision of the calculation.In this paper,the lightening flashover rate of transmission lines is studied by using a modified Monte Carlo method.Typical tower parameters of 110 kV,220 kV and 500 kV transmission lines are selected and the electric geometry method is introduced.The probability of hitting the tower under different kinds of landscape and the shield failure flashover rate under different obliquities are calculated.The back flash-over rate as well as the shield failure flash-over rate of typical towers before and after considering the power frequency voltage is also calculated.The influence of stroke current,front time,the hitting point,transient power frequency voltage and windage yaw on the lightning flash-over rate of transmission line is analyzed.On the basis of analyses above and considering the speed and the precision of the calculation,it is found that the random processes including stroke current,the hitting part and power frequency voltage of back flashover are crucial in the Monte Carlo method.After calculating actual 110 kV,220 kV and 500 kV transmission lines,it is proved on site that this new Monte Carlo method has good correspondence with the real calculating results.