Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficacy of Repetitive Transcranial Magnetic Stimulation in Patients With Methamphetamine Use Disorder: A Systematic Review and Meta-Analysis of Double-Blind Randomized Controlled Trials

Background Repetitive transcranial magnetic stimulation (rTMS) has demonstrated therapeutic potential for treating patients with methamphetamine use disorder (MUD). However, the most effective target and stimulation frequency of rTMS for treating MUD remains unclear. This meta-analysis explored the effect of rTMS on MUD. Methods In this study, PubMed, Cochrane Systematic Reviews, and the Cochrane Collaboration Central Register of Controlled Clinical Trials were searched electronically for double-blind randomized controlled trials that used rTMS for treating MUD. We used published trials to investigate the efficacy of rTMS in MUD up to March 5, 2022, and pooled studies using a random-effect model to compare rTMS treatment effects. Patients who were diagnosed with MUD according to the criteria of the Diagnostic and Statistical Manual of Mental Disorders were recruited. Clinical craving scores between baseline and after rTMS were compared using the standardized mean difference (SMD) with 95% confidence intervals (CIs). The heterogeneity of the included trials was evaluated through a visual inspection of funnel plots and the I2 statistic. Results We identified seven trials with 462 participants with MUD that met the inclusion criteria. All the studies evaluated craving scores, with rTMS demonstrating a more significant effect than the sham treatment on reducing craving scores (SMD = 0.983, CI = 0.620–1.345, p ≤ 0.001). A subgroup meta-analysis revealed that intermittent theta-burst stimulation (iTBS) had a greater positive effect than 10-Hz rTMS. A metaregression revealed that the SMDs increased with the increase in baseline craving scores, whereas they decreased with the increase in the proportion of men and duration of abstinence. Conclusion The meta-analysis suggests that rTMS may be associated with treatment effect on craving symptoms in patients with MUD. iTBS may have a greater positive effect on craving reduction than 10-z rTMS.
Artificial Intelligence Network Embedding, Entrepreneurial Intention, and Behavior Analysis for College Students’ Rural Tourism Entrepreneurship

To promote the development of the rural economy and improve entrepreneurship education in colleges and universities, college students’ willingness and behavior toward rural tourism entrepreneurship were investigated in this study. First of all, based on the previous research results, the influencing factor model was determined for college students’ entrepreneurial intention. Second, a questionnaire survey was made to collect data from a university in Xi’an City. Finally, the artificial neural network (ANN), improved by a genetic algorithm (GA) based on an artificial intelligence network, was used to study the relationship between college students’ entrepreneurial intention and behavior, and the simulation was carried out on MATLAB2013b software. The results show that the average evaluation accuracy is 81.13% for 60 groups of data using the unmodified back propagation neural network (BPNN) algorithm, while the average evaluation accuracy is 92.17% for the BPNN algorithm improved and optimized by GA, with an ascent of 11.04%. Therefore, the BPNN algorithm improved and optimized by GA is better than the unmodified BPNN algorithm; It is also feasible and effective in the analysis of influencing factors of college students’ entrepreneurial intention and behavior. The research provides a basis for colleges and universities to carry out entrepreneurship education on a large scale and to cultivate their innovative talents.
Identification of the Key Enzymes in WL Gum Biosynthesis and Critical Composition in Viscosity Control

As an important microbial exopolysaccharide, the sphingan WL gum could be widely used in petroleum, food, and many other fields. However, its lower production is still limiting its wider application. Therefore, to gain insights into the bottlenecks of WL gum production by identifying the key enzymes in the WL gum biosynthesis pathway, more than 20 genes were over-expressed in Sphingomonas sp. WG and their effects on WL gum production and structure were investigated. Compared to the control strain, the WL gum production of welB over-expression strain was increased by 19.0 and 21.0% at 36 and 84 h, respectively. The WL gum production of both atrB and atrD over-expression strains reached 47 g/L, which was approximately 34.5% higher than that of the control strain at 36 h. Therefore, WelB, AtrB, and AtrD may be the key enzymes in WL production. Interestingly, the broth viscosity of most over-expression strains decreased, especially the welJ over-expression strain whose viscosity decreased by 99.3% at 84 h. Polysaccharides’ structural features were investigated to find the critical components in viscosity control. The uronic acid content and total sugar content was affected by only a few genes, therefore, uronic acid and total sugar content may be not the key composition. In comparison, the acetyl degrees were enhanced by over-expression of most genes, which meant that acetyl content may be the critical factor and negatively correlated with the apparent viscosity of WL gum. This work provides useful information on the understanding of the bottlenecks of WL gum biosynthesis and will be helpful for the construction of high WL gum-yielding strains and rheological property controlling in different industries.
Design Driven Testing: Test Smarter, Not Harder

The groundbreaking book Design Driven Testing brings sanity back to the software development process by flipping around the concept of Test Driven Development (TDD)restoring the concept of using testing to verify a design instead of pretending that unit tests are a replacement for design. Anyone who feels that TDD is Too Damn Difficult will appreciate this book. Design Driven Testing shows that, by combining a forward-thinking development process with cutting-edge automation, testing can be a finely targeted, business-driven, rewarding effort. In other words, youll learn how to test smarter, not harder. Applies a feedback-driven approach to each stage of the project lifecycle. Illustrates a lightweight and effective approach using a core subset of UML. Follows a real-life example project using Java and Flex/ActionScript. Presents bonus chapters for advanced DDTers covering unit-test antipatterns (and their opposite, test-conscious design patterns), and showing how to create your own test transformation templates in Enterprise Architect. What youll learn Create unit and behavioral tests using JUnit, NUnit, FlexUnit. Generate acceptance tests for all usage paths through use case thread expansion. Generate requirement tests for functional requirements. Run complex acceptance tests across the enterprise. Isolate individual control points for self-contained unit/behavioral tests. Apply Behavior Driven Development frameworks like JBehave and NBehave Design Driven Testing should appeal to developers, project managers, testers, business analysts, architectsin fact anyone who builds software that needs to be tested. While equally applicable on both large and small projects, Design Driven Testing is especially helpful to those developers who need to verify their software against formal requirements. Such developers will benefit greatly from the rational and disciplined approach espoused by the authors.
FC-ZSM: Spatiotemporal Downscaling of Rain Radar Data Using a Feature Constrained Zooming Slow-Mo Network

This work studies the application of deep learning methods in the spatiotemporal downscaling of meteorological elements. Aiming at solving the problems of the single network structure, single input data feature type, and single fusion mode in the existing downscaling problem’s deep learning methods, a Feature Constrained Zooming Slow-Mo network is proposed. In this method, a feature fuser based on the deformable convolution is added to fully fuse dynamic and static data. Tested on the public rain radar dataset, we found that the benchmark network without feature fusion is better than the mainstream U-Net series networks and traditional interpolation methods in various performance indexes. After fully integrating various data features, the performance can be further improved.
The Association of Postoperative Complications and Hospital Costs Following Distal Pancreatectomy

Background Understanding the financial implications associated with the complications post-distal pancreatectomy (DP) may be beneficial for the future optimisation of postoperative care pathways and improved cost-efficiency. The primary outcome of this retrospective study was the characterisation of the additional cost associated with postoperative complications following DP. The secondary outcome was the estimation of the prevalence, type and severity of complications post-DP and the determination of which complications were associated with higher costs. Methods Postoperative complications were retrospectively examined for 62 adult patients undergoing distal pancreatectomy at an Australian university hospital between January 2012 and July 2021. Complications were defined and graded using the Clavien–Dindo (CVD) classification system. In-hospital cost of index admission was calculated using an activity-based costing methodology and was reported in US dollars at 2021 rates. Regression modelling was used to investigate the relationships among selected perioperative variables, complications and costs. Results 45 patients (72.6%) experienced one or more postoperative complications. The median (IQR) hospital cost in US dollars was 31.6% greater in patients who experienced complications compared to those who experienced no complications ($40,717.8 [27,358.0–59,834.3] vs. $30,946.9 [23,910.8–46,828.1]). Costs for patients with four or more complications were 43.5% higher than for those with three or fewer complications (p = 0.015). Compared to patients with no complications, the median hospital costs increased by 17.1% in patients with minor complications (CVD grade I/II) and by 252% in patients who developed major complication (i.e., CVD grade III/IV) complications. Conclusion Postoperative complications are a key target for cost-containment strategies. Our findings demonstrate a high prevalence of postoperative complications following distal pancreatectomy with number and severity of postoperative complications being associated with increased hospital costs. (Registered in the Australian New Zealand Clinical Trials Registry [No. ACTRN12622000202763]).
NNMT: Mean-Field Based Analysis Tools for Neuronal Network Models

Mean-field theory of neuronal networks has led to numerous advances in our analytical and intuitive understanding of their dynamics during the past decades. In order to make mean-field based analysis tools more accessible, we implemented an extensible, easy-to-use open-source Python toolbox that collects a variety of mean-field methods for the leaky integrate-and-fire neuron model. The Neuronal Network Mean-field Toolbox (NNMT) in its current state allows for estimating properties of large neuronal networks, such as firing rates, power spectra, and dynamical stability in mean-field and linear response approximation, without running simulations. In this article, we describe how the toolbox is implemented, show how it is used to reproduce results of previous studies, and discuss different use-cases, such as parameter space explorations, or mapping different network models. Although the initial version of the toolbox focuses on methods for leaky integrate-and-fire neurons, its structure is designed to be open and extensible. It aims to provide a platform for collecting analytical methods for neuronal network model analysis, such that the neuroscientific community can take maximal advantage of them.
A Prediction Model for Tacrolimus Daily Dose in Kidney Transplant Recipients With Machine Learning and Deep Learning Techniques

Tacrolimus is a major immunosuppressor against post-transplant rejection in kidney transplant recipients. However, the narrow therapeutic index of tacrolimus and considerable variability among individuals are challenges for therapeutic outcomes. The aim of this study was to compare different machine learning and deep learning algorithms and establish individualized dose prediction models by using the best performing algorithm. Therefore, among the 10 commonly used algorithms we compared, the TabNet algorithm outperformed other algorithms with the highest R2 (0.824), the lowest prediction error [mean absolute error (MAE) 0.468, mean square error (MSE) 0.558, and root mean square error (RMSE) 0.745], and good performance of overestimated (5.29%) or underestimated dose percentage (8.52%). In the final prediction model, the last tacrolimus daily dose, the last tacrolimus therapeutic drug monitoring value, time after transplantation, hematocrit, serum creatinine, aspartate aminotransferase, weight, CYP3A5, body mass index, and uric acid were the most influential variables on tacrolimus daily dose. Our study provides a reference for the application of deep learning technique in tacrolimus dose estimation, and the TabNet model with desirable predictive performance is expected to be expanded and applied in future clinical practice.
Mitral Valve-in-Valve Implant of a Balloon-Expandable Valve Guided by 3-Dimensional Printing

Background Our goal was to explore the role of 3-dimensional (3D) printing in facilitating the outcome of a mitral valve-in-valve (V-in-V) implant of a balloon-expandable valve. Methods From November 2020 to April 2021, 6 patients with degenerated mitral valves were treated by a transcatheter mitral V-in-V implant of a balloon-expandable valve. 3D printed mitral valve pre- and post-procedure models were prepared to facilitate the process by making individualized plans and evaluating the outcomes. Results Each of the 6 patients was successfully implanted with a balloon-expandable valve. From post-procedural images and the 3D printed models, we could clearly observe the valve at the ideal position, with the proper shape and no regurgitation. 3D printed mitral valve models contributed to precise decisions, the avoidance of complications, and the valuation of outcomes. Conclusions 3D printing plays an important role in guiding the transcatheter mitral V-in-V implant of a balloon-expandable valve. Clinical Trial Registration ClinicalTrials.gov Protocol Registration System (NCT02917980).
An Integrated Approach to Characterize Temporal–Spatial Variations in PM2.5 Concentrations at the Ground Level and Its Implication on Health Impact Assessments

Although PM2.5 concentrations measured by the governmental air quality monitoring station (AQMS) have been widely used for conducting exposure assessments, it might be not able to reflect the residents’ exposures, especially for those associated with ground emissions. The present study was conducted in a city area for 1 year. A mobile monitoring station (MMS) was established to measure the PM2.5 concentrations at the ground level. A significant linear relationship (R 2 = 0.53) was found between the MMS-measured concentrations and the corresponding concentrations obtained from the AQMS (15 m above the ground level), and the former was ∼ 1.11 times (95% CI: 1.08-1.15) in magnitude higher than that of the latter. To characterize the spatial variation of the area, the MMS-measured values were further classified into three different regions. A consistent trend was found in the present study for all collected data as industry region≒urban region > harbor region. The aforementioned results clearly indicate that the residents’ ambient PM2.5 exposures do have spatial differences. Seven-year AQMS-measured concentrations (i.e., AQMS7-yr) were used to establish the long-term PM2.5 concentrations at the ground level (i.e., MMS7-yr) of the three different regions using the linear regression equations obtained from the MMS and AQMS. Health impact functions and local health data were used to quantify the PM2.5-attributable health burden for both AQMS7-yr and MMS7-yr, respectively. Results show that the former is ∼ 10.4% lower in magnitude than the latter in the estimated lung cancer death attributed fraction (AF). In particular, the decrease of unit PM2.5 (μg/m3) would lead to a 0.75 and 0.71% decrease in the estimated AF of lung cancer death for AQMS7-yr and MMS7-yr, respectively. As a result, directly using AQMS7-yr would lead to an underestimation of ∼ 1,000 lung cancer deaths annually in Taiwan in comparison with those using MMS7-yr. The aforementioned results clearly indicate the importance of characterizing ground-level exposures for assessing the health impact of residents, and the methodology developed by the present study would be helpful for solving the aforementioned problem.
Enhancing Biomethane Production From Lignite by an Anaerobic Polycyclic Aromatic Hydrocarbon Degrading Fungal Flora Enriched From Produced Water

The coal-degrading ability of microorganisms is essential for the formation of biogenic coalbed methane. The ability to degrade the aromatic compound of coal is more important because it is perceived as the main refractory component for bioconversion. In this paper, a polycyclic aromatic hydrocarbon (PAH) degrading fungal community (PF) was enriched from produced water using phenanthrene as sole carbon source. The goal was to improve both the microbial structure of the methanogenic microflora and its coal-degrading ability. Two strategies were pursued. The first used coal pretreatment with PF (PP), followed by methane production by methanogenic microflora; the second used methane production directly from coal by mixed culture of PF and methanogenic microflora (PM). The results showed that methane productions of PP and PM increased by 29.40 and 39.52%, respectively. After 7 days of cultivation, the fungal community has been altered in PP and PM, especially for Penicillium the proportions of which were 67.37 and 89.81% higher than that in methanogenic microflora, respectively. Furthermore, volatile fatty acid accumulations increased by 64.21 and 58.15%, respectively. The 13C-NMR results showed that PF addition promoted the transformation of aromatic carbons in coal to carboxyl and carbonyl carbons, which contributed greatly to the production of methane together with oxygen-containing functional groups. These results suggest that methane production can be increased by indigenous PAH-degrading fungi by improving the fermentation of aromatics in coal and the generation of volatile fatty acids. This provided a feasible method for enhancing biomethane generation in the coal seam.
Two, Six, and Twelve-Month Dropout Rate and Predictor Factors After a Multidisciplinary Residential Program for Obesity Treatment. A Prospective Cohort Study

Introduction The aim of the present study was to assess the dropout rate at 2, 6, and 12 months after an inpatient multidisciplinary residential program (MRP) for the treatment of obesity. Furthermore, this study assessed anthropometric and biochemical predictors associated with the dropout. Methods Adult and elderly patients (age 59 ± 14 years) with obesity had undergone an MRP, were followed up from 2 to 12 months. Biochemical and anthropometric markers have been assessed at the beginning of the follow-up period after the MRP. Results The study enrolled 178 subjects, 117 women and 61 men. The overall dropout rate at 2 months was 21.3%, after 6 months was 44.4%, and after 1 year was 68.5%. There was no difference by gender recorded. Furthermore, patients under medical treatment with psychiatric disorders did not show an association with the dropout rate. Patients with a higher level of body mass index (BMI) at the discharge of MRP showed +48% of dropout at 6 months. After the MRP, the baseline values of uricemia and white blood cells (WBCs) resulted as predictors of dropout at 2 months (p > 0.05). Furthermore, the excess percentage of fat mass lost during the MRP was associated with the risk of dropout at 2, 6, and 12 months (p > 0.05). Conclusion The MRP for obesity is an opportunity for losing weight for patients with established criteria. The future challenge will be addressing the best strategic plans in order to reduce the dropout rate after this intervention. Investigating deeply the main predictors could be an opportunity to improve the long-term efficacy of MRP.
Investigations on Spray Characteristics and Self-Pulsation of a Gas-Centered Shear Coaxial Injector

The spray characteristics of a gas-centered shear coaxial injector under different conditions and recess ratios (RR) were studied through experiments and numerical simulations. The numerical study was carried out based on the coupled level set and volume-of-fluid (CLSVOF) method and the adaptive mesh refinement (AMR) method. The results indicated that without recess, the spray angle first stayed almost constant and then dropped linearly with an increase in the gas mass flow rate ( m ˙ g ) when holding the liquid mass flow rate ( m ˙ l ) constant. In contrast, with recess, the spray angle was found to increase with m ˙ g , which could be attributed to the secondary expansion of the central gas flow. Under specific conditions, self-pulsation occurred and was accompanied by a loud scream. The frequency of the self-pulsation increased with both m ˙ g and m ˙ l . Moreover, the self-pulsation frequency decreased with RR. Meanwhile, the mechanism of self-pulsation was initially explored through numerical simulation. It was concluded that self-pulsation was caused by the surface tension and the pressure difference between the inside and outside of the liquid sheet, together with the central airflow impact extrusion.
Long-Term Safety of Rituximab in DLBCL Patients With Hepatitis B-Related Cirrhosis: A Retrospective Case Series

Objective Chemotherapy regimens containing rituximab (RTX) have been extensively used to treat diffuse large B cell lymphoma (DLBCL). However, data looking at long-term safety of DLBCL patients with hepatitis B-related cirrhosis are still lacking. This study aims to report the safety and outcomes of RTX administration in DLBCL patients with hepatitis B-related cirrhosis. Methods A retrospective case series was designed and implemented, using data from January 1, 2011 to December 31, 2020. Consecutive patients who were diagnosed with DLBCL and hepatitis B-related cirrhosis receiving RTX treatment were included. The primary outcomes included HBV reactivation, hepatitis flares or abnormal liver function. Survival status, the secondary outcome measure, was observed until death, loss to follow-up, or the end of follow-up, whichever occurred first. Results A total of 8 DLBCL patients combined with hepatitis B-related cirrhosis were included in this study [4 men; median age 62.5 years (range, 44–77 years); median RTX-containing regimen course 5 (range, 2–11)]. Of them, 6 patients had current HBV infection with HBsAg-positive and anti-HBc-positive, whereas 2 patients had previously resolved HBV infection with HBsAg-negative and anti-HBc-positive. The HBV reactivation was observed in only one patient, who received 11 courses of RTX-containing immunochemotherapies within 15 months. No hepatitis flares or abnormal liver function occurred in any patients included. All patients received standardized antiviral therapy for a lifelong time. Of 8 patients included, 3 patients died, and 1 patient was lost to follow-up, and the median overall survival among patients was 39 months (range, 7–82 months). Conclusion The findings provide support for the concept that, on the premise of standardized and valid management strategy, RTX containing regimens may be a safe option for use as the treatment of DLBCL patients combined with hepatitis B-related cirrhosis.