Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparing the efficacy and safety of medications in adults with hypertrophic cardiomyopathy: a systematic review and network meta-analysis

Background Hypertrophic cardiomyopathy (HCM) is the most common genetic heart disease. The purpose of this study was to evaluate the efficacy and safety of several medications and recommend better drug treatments for adults with HCM. Methods A review of PubMed, Embase, the Cochrane Controlled Register of Trials (CENTRAL), ClinicalTrials.gov and CNKI databases was conducted for studies on the efficacy and safety of drugs for adults with HCM. A frequentist random effects model was used in this network analysis. Results This network meta-analysis included 7 studies assessing seven medications, 6 studies evaluating monotherapy and 1 study evaluating combination therapy. Based on the network meta-analysis results, xiaoxinbi formula plus metoprolol (MD −56.50% [−72.43%, −40.57%]), metoprolol (MD −47.00% [−59.07%, −34.93%]) and mavacamten (MD −34.50% [−44.75%, −24.25%]) significantly reduced the resting left ventricular outflow tract gradient (LVOTG) in comparison with placebo. Resting LVOTG could also be reduced with N-acetylcysteine (NAC). The incidence of adverse drug reactions was not significantly different between the placebo group and the treatment group. Conclusion For adults with HCM, the top 4 treatments included xiaoxinbi formula plus metoprolol, metoprolol, mavacamten and NAC. Systematic Review Registration: [https://www.crd. york.ac. uk/prospero/display_record. php? RecordID=374222], identifier [CRD42022374222].
Strain-Induced Structural Phase Transitions in Epitaxial (001) BiCoO3 Films: A First-Principles Study

We have simulated BiCoO3 films epitaxially grown along (001) direction with density functional theory computations. Leading candidates for the lowest-energy phases have been identified. The tensile strains induce magnetic phase transition in the ground state (P4mm symmetry) from a C-type antiferromagnetic order to a G-type order for the in-plane lattice parameter above 3.922 Å. The G-type antiferromagnetic order will be maintained with larger tensile strains; however, a continuous structural phase transition will occur, combining the ferroelectric and antiferrodistortive modes. In particular, the larger tensile strain allows an isostructural transition, the so-called Cowley’s ‘‘Type Zero’’ phase transitions, from Cc-(I) to Cc-(II), with a slight volume collapse. The orientation of ferroelectric polarization changes from the out-of-plane direction in the P4mm to the in-plane direction in the Pmc21 state under epitaxial tensile strain; meanwhile, the magnetic ordering temperature TN can be strikingly affected by the variation of misfit strain.
Landfill Waste Segregation Using Transfer and Ensemble Machine Learning: A Convolutional Neural Network Approach

Waste disposal remains a challenge due to land availability, and environmental and health issues related to the main disposal method, landfilling. Combining computer vision (machine learning) and robotics to sort waste is a cost-effective solution for landfilling activities limitation. The objective of this study was to combine transfer and ensemble learning to process collected waste images and classify landfill waste into nine classes. Pretrained CNN models (Inception–ResNet-v2, EfficientNetb3, and DenseNet201) were used as base models to develop the ensemble network, and three other single CNN models (Models 1, 2, and 3). The single network performances were compared to the ensemble model. The waste dataset, initially grouped in two classes, was obtained from Kaggle, and reorganized into nine classes. Classes with a low number of data were improved by downloading additional images from Google search. The Ensemble Model showed the highest prediction precision (90%) compared to the precision of Models 1, 2, and 3, 86%, 87%, and 88%, respectively. All models had difficulties predicting overlapping classes, such as glass and plastics, and wood and paper/cardboard. The environmental costs for the Ensemble network, and Models 2 and 3, approximately 15 g CO2 equivalent per training, were lower than the 19.23 g CO2 equivalent per training for Model 1.
A Semi-Supervised Failure Knowledge Graph Construction Method for Decision Support in Operations and Maintenance

Maintenance logs of industrial equipment record descriptive and unstructured operation and maintenance (O&M) information, which is the basis of reliability, availability, and maintainability investigations. However, the construction of failure knowledge graphs as a basis for understanding the failure and maintenance properties of systems is challenging due to the requirement of annotation efforts and domain knowledge. This article proposes a novel semi-supervised method for failure knowledge graph construction. Initially, a semantic module is proposed to extract hidden contextual information from maintenance records and identify corresponding failure modes. The semantic module is trained by unlabeled maintenance records with the assistance of the hard pseudo-label acquisition and the proposed self-training algorithm. Subsequently, a taxonomy induction module is presented to extract failure items and their relationships to construct failure knowledge graphs that provide decision support. The feasibility and superiority of the proposed method are validated by maintenance logs from real wind farms. Overall, the proposed method provides an effective tool for semantic information digitalization of well-cumulated industrial O&M data.
C-Band Right-Circular Polarization Ocean Wind Retrieval

We report an investigation of ocean-surface wind speed retrieval from C-band RADARSAT Constellation Mission (RCM) Synthetic Aperture Radar (SAR) images using a new channel of coright-circular polarization (RR-pol) in compact polarimetry (CP) option. The analysis of simulated RCM quad-polarized CP SAR data and collocated in situ buoy measurements suggests that the RR-pol is much less sensitive to wind directions than the other three polarizations in the CP option. A method is proposed for the RR-pol radar signal as a function of wind speed and incidence angle. We demonstrate that C-band RR-pol has the potential for ocean high wind retrieval, especially for cyclone studies.
Enhancing speech corrupted by nonstationary noise using nonnegative matrix factorization with multiple constraints

: The enhancement of speech corrupted by nonstationary noises under low signal-to-noise ratio (SNR) conditions is remaining open and still a very challenging task. To improve the traditional nonnegative matrix factorization (NMF) based speech enhancement, jointly taking the speech sparsity property in time-frequency domain and the low-rank property of nonstationary noise into account, a termed multi-constraint NMF speech enhancement method (MC–NMFSE) is developed. Essentially, in training stage, the speech and noise dictionaries have been constructed by using speech and noise training sets, respectively. In the speech enhancement stage, multi-constraint NMF method is adopted where the data matrix is factorized into two nonnegative sub-matrices with the sparsity and low rank constraints to guarantee the good representation of the speech components from their corrupted version by nonstationary noise. Compared with the traditional NMF speech enhancement method (NMF–SpEnM) and MC–NMFSE, intensive experiments under different nonstationary noise conditions and different signal-to-noise ratios have been carried out to evaluate their performance. Experimental results demonstrate that MC–NMFSE has lower speech distortion and better capability to suppress nonstationary noises.
Pharmacological Treatment of Alcohol Cravings

(1) Background: The treatment of substance addiction is challenging and has persisted for decades, with only a few therapeutic options. Although there are some recommendations for specific treatments for Alcohol Use Disorder (AUD), there is no specific medication used to treat alcohol cravings, which could benefit millions of patients that are suffering from alcoholism. Cravings, or the urge to use drugs, refer to the desire to experience the effects of a previously experienced psychoactive substance. (2) Methods: We included original studies of alcohol abuse or dependence extracted from a controlled, blind, pharmacological treatment study which presented measures and outcomes related to alcohol cravings. (3) Results: Specific drugs used for the treatment of alcoholism, such as Naltrexone and Acamprosate, have had the best results in relieving craving symptoms, as well as promoting abstinence. Baclofen and anticonvulsants such as Gabapentin and Topiramate have shown good results in promoting abstinence and the cessation of cravings. (4) Conclusions: Specific drugs used for the treatment of alcoholism to obtain the best results can be considered the gold standard for promoting abstinence and relieving cravings. Anticonvulsants and Baclofen also had good results, with these medications being considered as second-line ones. Varenicline is an option for alcohol dependents who also concomitantly ingest tobacco.
On-Chip Batteries as Distributed Energy Sources in Heterogeneous 2.5D/3D Integrated Circuits

Energy efficiency in digital systems faces challenges due to the constraints imposed by small-scale transistors. Moreover, the growing demand for portable consumer electronics necessitates the use of compact energy sources. To address these challenges, heterogeneous 3D IC technology has emerged as a promising solution for the former. Regarding the latter, we propose the concept of distributed batteries within a heterogeneous 3D IC. This approach involves utilizing multiple smaller batteries with different specifications among different modules of 3D ICs. This approach optimizes performance and overcomes limitations associated with both 3D ICs and conventional power delivery methods. Distributed batteries play a vital role in effectively managing the heat generated by energy sources and modules within a 3D IC. Furthermore, they contribute to achieving a uniform distribution of heat throughout the entire structure, which ultimately ensures the optimal performance of the batteries and modules. The simulation results indicate a 40 percent enhancement in achieving a more even distribution of generated heat. Additionally, the proposed distributed battery techniques improve power delivery, enhance reliability, and enable optimized voltage regulation while improving efficiency. In addition to the primary benefits, alternative configurations of the proposed approach can offer extra energy storage capacity and act as efficient electromagnetic shields, resulting in an impressive reduction of external electromagnetic noises by 60 dB.
A Web-Based COVID-19 Tool for Testing Residents in Retirement Homes: Development Study

Background Long-term care facilities have been widely affected by the COVID-19 pandemic. Empirical evidence demonstrated that older people are the most impacted and are at higher risk of mortality after being infected. Regularly testing care facility residents is a practical approach to detecting infections proactively. In many cases, the care staff must perform the tests on the residents while also providing essential care, which in turn causes imbalances in their working time. Once an outbreak occurs, suppressing the spread of the virus in retirement homes (RHs) is challenging because the residents are in contact with each other, and isolation measures cannot be widely enforced. Regular testing strategies, on the other hand, have been shown to effectively prevent outbreaks in RHs. However, high-frequency testing may consume substantial staff working time, which results in a trade-off between the time invested in testing and the time spent providing essential care to residents. Objective We developed a web application (Retirement Home Testing Optimizer) to assist RH managers in identifying effective testing schedules for residents. The outcome of the app, called the “testing strategy,” is based on dividing facility residents into groups and then testing no more than 1 group per day. Methods We created the web application by incorporating influential factors such as the number of residents and staff, the average rate of contacts, the amount of time spent to test, and constraints on the test interval and size of groups. We developed mixed integer nonlinear programming models for balancing staff workload in long-term care facilities while minimizing the expected detection time of a probable infection inside the facility. Additionally, by leveraging symmetries in the problem, we proposed a fast and efficient local search method to find the optimal solution. Results Considering the number of residents and staff and other practical constraints of the facilities, the proposed application computes the optimal trade-off testing strategy and suggests the corresponding grouping and testing schedule for residents. The current version of the application is deployed on the server of the Where2Test project and is accessible on their website. The application is open source, and all contents are offered in English and German. We provide comprehensive instructions and guidelines for easy use and understanding of the application’s functionalities. The application was launched in July 2022, and it is currently being tested in RHs in Saxony, Germany. Conclusions Recommended testing strategies by our application are tailored to each RH and the goals set by the managers. We advise the users of the application that the proposed model and approach focus on the expected scenarios, that is, the expected risk of infection, and they do not guarantee the avoidance of worst-case scenarios.
Relationships between Serum Interleukin-6, Radiographic Severity a WOMAC Index in Patients with Primary Knee Osteoarthritis

Background: Osteoarthritis (OA) is the highest prevalent degenerative joint condition, leading to joint discomfort and impaired function. Objective: This study aimed to examin the relationship among serum interleukin-6 (IL-6) and knee osteoarthritis (KOA) signs as well as the relationship among serum IL-6 and radiographic severity in cases with primary KOA. Methods: This case-control research involved 50 primary KOA cases and 50 controls. Signs were measured through the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). Results: Serum IL-6 was significantly elevated in OA cases than controls. WOMAC in OA cases ranged from 0 to 95 and Kellegren-Lawrence (KL) score mean was 2.7 ± 0.76. Serum IL-6 was significantly correlated with pain, physical function score, and radiographic score. Regression analysis revealed that IL-6 had a higher influence on WOMAC and KL score. Conclusion: Serum IL-6 is elevated in KOA cases. In addition, serum IL-6 is associated with OA signs and radiographic severity.
Multigenerational Effects of Graphene Oxide Nanoparticles on Acheta domesticus DNA Stability

The use of nanoparticles like graphene oxide (GO) in nanocomposite industries is growing very fast. There is a strong concern that GO can enter the environment and become nanopollutatnt. Environmental pollutants’ exposure usually relates to low concentrations but may last for a long time and impact following generations. Attention should be paid to the effects of nanoparticles, especially on the DNA stability passed on to the offspring. We investigated the multigenerational effects on two strains (wild and long-lived) of house cricket intoxicated with low GO concentrations over five generations, followed by one recovery generation. Our investigation focused on oxidative stress parameters, specifically AP sites (apurinic/apyrimidinic sites) and 8-OHdG (8-hydroxy-2′-deoxyguanosine), and examined the global DNA methylation pattern. Five intoxicated generations were able to overcome the oxidative stress, showing that relatively low doses of GO have a moderate effect on the house cricket (8-OHdG and AP sites). The last recovery generation that experienced a transition from contaminated to uncontaminated food presented greater DNA damage. The pattern of DNA methylation was comparable in every generation, suggesting that other epigenetic mechanisms might be involved.
Long-Term Survival Analysis and Prognostic Factors of Arabic Patients with Differentiated Thyroid Carcinoma: A 20-Year Observational Study at the King Hussein Cancer Center (KHCC) Involving 528 Patients

Simple Summary The impact of ethnic and geographic variation on observed differentiated thyroid cancer (DTC) outcomes has been well-documented, demonstrating distinct and disparate observations across different countries. However, there remains a paucity of evidence regarding the analysis of factors influencing DTC outcomes, specifically within the Arabic population. This study examines the long-term outcome of DTC in the Arab population, looking at various influential factors. The analysis of 528 cases revealed favorable survival outcomes. Disease progression was observed in a subset of cases, but the majority of patients achieved positive outcomes. Age at diagnosis, gender, risk categorization, and tumor stage impact both disease progression and mortality. The survival rates were favorable for patients who received RAI treatment. Moreover, adherence to institutional clinical practice guidelines (CPG) resulted in better disease control. Our study features the largest Middle Eastern and Arab cohort to date, highlighting the long-term favorable outcomes of DTC patients. Abstract DTC accounts for the majority of endocrine tumors. While the incidence of thyroid cancer has been increasing globally over the past few decades, papillary thyroid carcinoma (PTC) generally shows an excellent prognosis, except in cases with aggressive clinicopathological features. This study aimed to assess the 5- and 10-year overall survival (OS) and progression-free survival (PFS) of 528 Arabic patients diagnosed with primary DTC from 1998 to 2021. Additionally, the study aimed to analyze the impact of various factors on both OS and PFS. An univariable survival analysis was conducted using Kaplan–Meier curves. The 5- and 10-year OS for patients with DTC have exceeded 95%. Additionally, PFS showed very good rates (ranging between 96.5 and 85% at 5 and 10 years, respectively). Age, male gender, risk of recurrence, and distant metastasis were identified as the main negative prognostic factors for both OS and PFS, while RAI treatment was found to be a significant factor in improving OS. Moreover, adherence to the King Hussein Cancer Center’s (KHCC) CPG demonstrated significant improvement in PFS. These findings highlight common prognostic factors and favorable outcomes in Arabic patients with DTC treated at a tertiary cancer center using standard of care approaches.
An Adaptive Sample Assignment Network for Tiny Object Detection

Tiny objects often have a small proportion of pixels in the image, leading to significant differences in the number of positive and negative samples and the lack of feature information. Accurately determining the position and category of tiny objects remains a huge challenge for object detection research. Therefore, we design an Adaptive Sample Assignment Strategy(ASAS) and tiny object focusing enhancement module to solve the above two problems. Specifically, starting from the study of positive and negative sample selection and balance strategies for tiny objects, we construct a lightweight Object Existence Probability Determination Network (OEPD/Net) to focus on the areas where tiny objects exist, and achieve adaptive assignment and balance of samples. A top/down, layer by layer focusing enhancement module is designed to effectively enhance the propagation ability of high/level semantic information for tiny objects. The above two solutions have excellent generalization and migration capabilities and can be applied to any stage and two-stage object detection network, effectively enhancing TOD performance. Finally, this article provides a performance analysis of detection performance the detection network based on the OEPD/Net output results, and demonstrates the effectiveness of the proposed OEPD-Net and focusing enhancement module through extensive experiments on a public dataset.
GLP-1RA Liraglutide and Semaglutide Improves Obesity-Induced Muscle Atrophy via SIRT1 Pathway

Background Obesity is related to the loss of skeletal muscle mass and function (sarcopenia). The co-existence of obesity and sarcopenia is called sarcopenic obesity (SO). Glucagon like peptide-1 receptor agonists (GLP-1RA) are widely used in the treatment of diabetes and obesity. However, the protective effects of GLP-1RA on skeletal muscle in obesity and SO are not clear. This study investigated the effects of GLP-1RA liraglutide and semaglutide on obesity-induced muscle atrophy and explored the underlying mechanisms. Methods Thirty-six male C57BL/6J mice were randomly divided into two groups and fed a regular diet and a high-fat diet for 18 weeks, respectively. After establishing an obesity model, mice were further divided into six groups: control group, liraglutide (LIRA) group, semaglutide (SEMA) group, high-fat diet (HFD) group, HFD + LIRA group, HFD + SEMA group, and subcutaneous injection for 4 weeks. The body weight, muscle mass, muscle strength, glycolipid metabolism, muscle atrophy markers, myogenic differentiation markers, GLUT4 and SIRT1 were analyzed. C2C12 myotube cells treated with palmitic acid (PA) were divided into four groups: control group, PA group, PA + LIRA group, PA + SEMA group. The changes in glucose uptake, myotube diameter, lipid droplet infiltration, markers of muscle atrophy, myogenic differentiation markers, GLUT4 and SIRT1 were analyzed, and the changes in related indicators were observed after the addition of SIRT1 inhibitor EX527. Results Liraglutide and semaglutide reduced HFD-induced body weight gain, excessive lipid accumulation and improved muscle atrophy. Liraglutide and semaglutide eliminated the increase of muscle atrophy markers in skeletal muscle and C2C12 myotubes. Liraglutide and semaglutide restored impaired glucose tolerance and insulin resistance. However, these beneficial effects were attenuated by inhibiting SIRT1 expression. Conclusion Liraglutide and semaglutide protects skeletal muscle against obesity-induced muscle atrophy via the SIRT1 pathway.
Adaptive Multistrategy Particle Swarm Optimization for Hyperspectral Remote Sensing Image Band Selection

Hyperspectral remote sensing band selection picks out characteristic feature combinations to weaken the strong correlation caused by spectral continuity. However, it is difficult for traditional methods with fixed strategies to search the entire space and make adjustments for the optimization process. Thus, the solutions obtained can be mostly local optima. In this article, a novel adaptive multistrategy particle swarm optimization (PSO) for hyperspectral image remote sensing band selection (AMSPSO_BS) is introduced to obtain a subset solution suitable for classification. The problem is modeled as an effective fitness function, and the quotient of the linear discriminant value and the mean mutual information (LD/MMI) is used to remove the redundancy between bands. The randomly generated solutions are then encoded to form a population, which rely on various particle update strategies (PUS) with different reference positions for updating. During the particle motion, the effect of each strategy on population evolution is considered comprehensively and reflected in the change of selection probability. And the motion parameters are dynamically adjusted to balance the global and local capabilities. Four hyperspectral remote sensing image datasets were utilized to conduct band selection experiments, to confirm the effectiveness of AMSPSO_BS.