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• In grid-connected PV systems, the synthetic current signal is seriously affected by extra multicomponent noises. • Due to the noise signal synthesis influence, the existing Db9-based features would become invalid. • The established Rbio3.1-based features directly focus on the arc fault instead of synthetic signal. • The proposed protection strategy could adapt to different PV systems even without adjusting parameters. • The proposed protection strategy could achieve the effective arc fault detection. The arc fault protection strategy should be applied in grid-connected photovoltaic (PV) systems to guarantee the human and equipment safety. In this paper, PV series arc faults are conducted in different grid-connected PV systems through the designed experimental platform firstly. Having analyzed these synthetic arc fault current signals through the existing Db9-based features used in the resistive system, the amplitude is found no longer increasing during the arc fault period in some frequency bands. Inverters would inject extra multicomponent noises to influence electrical characterization of arc faults in grid-connected PV systems, causing that Db9-based features show undesirable constant even decreasing amplitude patterns. Next, the Rbio3.1-based features have the better symmetric property to achieve the singularity detection of arc faults. The biorthogonality property of Rbio3.1 could further improve the reconstruction accuracy cooperating with the symmetric property. Besides, its higher vanishing moment is able to display the arc salient disturbances more clearly. Then the Rbio3.1 is able to give more arc fault occurrence time discovery pulses and better arc fault separation degree for different switching frequencies, inverter types, and inverter stages. Ideally, its feature improvement ability may not appear under fault-like conditions. Finally, the random forest (RF) outputs the final state recognition result through combining multiple classifications without adjusting parameters. For the desired Rbio3.1-based features, different feature combinations are able to significantly improve the detection accuracy at the acceptable speed for complicated interference scenes in multiple grid-connected PV systems based on the MATLAB platform. [ABSTRACT FROM AUTHOR]

Background: In recent years, numerous guidelines and expert consensus have recommended the inclusion of digital technologies and products in cardiac rehabilitation. Digital therapeutics (DTx) is an evidence-based medicine that uses digital means for data collection and monitoring of indicators to control and optimize the treatment, management, and prevention of disease. Objective: This study collected and reviewed real-world data and built a model using health economics assessment methods to analyze the potential cost-effectiveness of DTx applied to home-based cardiac rehabilitation for patients with chronic heart failure. From the perspective of medical and health decision-makers, the economic value of DTx is evaluated prospectively to provide the basis and reference for the application decision and promotion of DTx. Methods: Markov models were constructed to simulate the outcomes of DTx for home-based cardiac rehabilitation (DT group) compared to conventional home-based cardiac rehabilitation (CH group) in patients with chronic heart failure. The model input parameters were clinical indicators and cost data. Outcome indicators were quality-adjusted life years (QALYs) and incremental cost-effectiveness ratios (ICERs). The robustness of the evaluation methods and results was tested using sensitivity analyses. Clinical indicators, cost data, and health utility values were obtained from real-world data, including clinical study data, published literature, and public website information. Results: The Markov model simulated a time span of 10 years, with a cycle set at one month, for 120 cycles. The results showed that the per capita cost of the CH group was 38,442.11 CNY/year, with a QALY of 0.7196 per person per year. The per capita cost of the DT group was 42,300.26 CNY/year, with a QALY of 0.81687 per person per year. The ICER per person was 39,663.5 CNY/QALY each year, which was below the willingness-to-pay threshold of 85,698 CNY (China's GDP per capita in 2022). Conclusions: DTx for home-based cardiac rehabilitation is an extremely cost-effective rehabilitation option compared with conventional home-based cardiac rehabilitation. DTx for home-based cardiac rehabilitation is potentially valuable from the perspective of healthcare decision-makers. [ABSTRACT FROM AUTHOR]

Pulmonary hypertension (PH) is characterized by vascular remodeling predominantly driven by a phenotypic switching in pulmonary artery smooth muscle cells (PASMCs). However, the underlying mechanisms for this phenotypic alteration remain incompletely understood. Here, we identified that RNA methyltransferase METTL3 is significantly elevated in the lungs of hypoxic PH (HPH) mice and rats, as well as in the pulmonary arteries (PAs) of HPH rats. Targeted deletion of Mettl3 in smooth muscle cells exacerbated hemodynamic consequences of hypoxia-induced PH and accelerated pulmonary vascular remodeling in vivo. Additionally, the absence of METTL3 markedly induced phenotypic switching in PASMCs in vitro. Mechanistically, METTL3 depletion attenuated m6A modification and hindered the processing of pri-miR-143/145, leading to a downregulation of miR-143-3p and miR-145-5p. Inhibition of hnRNPA2B1, an m6A mediator involved in miRNA maturation, similarly resulted in a significant reduction of miR-143-3p and miR-145-5p. We demonstrated that miR-145-5p targets Krüppel-like factor 4 (KLF4) and miR-143-3p targets fascin actin-bundling protein 1 (FSCN1) in PASMCs. The decrease of miR-145-5p subsequently induced an upregulation of KLF4, which in turn suppressed miR-143/145 transcription, establishing a positive feedback circuit between KLF4 and miR-143/145. This regulatory circuit facilitates the persistent suppression of contractile marker genes, thereby sustaining PASMC phenotypic switch. Collectively, hypoxia-induced upregulation of METTL3, along with m6A mediated regulation of miR-143/145, might serve as a protective mechanism against phenotypic switch of PASMCs. Our results highlight a potential therapeutic strategy targeting m6A modified miR-143/145-KLF4 loop in the treatment of PH. [ABSTRACT FROM AUTHOR]

Objective: Tumors are highly heterogeneous, and within their parenchyma, a small population of tumor-stem cells possessing differentiation potential, high oncogenicity, and self-renewal capabilities exists. These cells are pivotal in mediating tumor development, chemotherapy resistance, and recurrence. Ovarian cancer shares characteristics with tumor stem cells, making it imperative to investigate molecular markers associated with these cells. Methods: Stem cell-related genes were collected, and molecular subtypes were established based on gene expression profiles from The Cancer Genome Atlas using the R package tool "ConsensusClusterPlus." Multi-gene prognostic markers were identified using LASSO regression analysis. Gene set enrichment analysis was employed to gain insights into the potential molecular mechanisms of these identified markers. The robustness of these prognostic markers was analyzed across different cohorts, and their clinical independence was determined through multivariate Cox analysis. A nomogram was constructed to assess the model's clinical applicability. Immunohistochemistry was performed to validate the expression of hub genes. Results: Utilizing 49 tumor stem cell-related genes associated with prognosis, 362 ovarian cancer samples were divided into two distinct clusters, revealing significant prognostic disparities. A seven-gene signature (GALP, CACNA1C, COL16A1, PENK, C4BPA, PSMA2, and CXCL9), identified through LASSO regression, exhibited stability and robustness across various platforms. Multivariate Cox regression analysis confirmed the signature's independence in predicting survival in patients with ovarian cancer. Furthermore, a nomogram combining the gene signature demonstrated strong predictive abilities. Immunohistochemistry results indicated significantly elevated GALP, CACNA1C, COL16A1, PENK, C4BPA, PSMA2, and CXCL9 expression in cancer tissues. Conclusion: The seven-gene signature holds promise as a valuable tool for decision-making and prognosis prediction in patients with ovarian cancer. [ABSTRACT FROM AUTHOR]

Aprotic lithium‐oxygen (Li–O2) batteries hardly cycle at the condition of high area capacity for realizing their high energy density, because the unconducive lithium peroxide (Li2O2) discharge product limits the electron transfer between electrode and O2/Li2O2. Here, it is demonstrated that one of redox mediator (RM), triethylene glycol bis‐2,2,6,6‐tetramethylpiperidin‐1‐oxyl radical (D‐TEMPO), can be effectively used to promote the electron transfer between electrode and Li2O2, which the shuttle effect of RM can be cooperatively inhibited by regulating the size of RM and the thickness of ion‐selective membrane. As a result, the Li–O2 battery coupled with double cathodes, D‐TEMPO, and ion‐selective membrane can be stably operated for 46 days at a capacity of 5 mAh cm−2. The concept in this work provides the cooperative design of a stable solution‐mediated pathway for high‐capacity Li–O2 battery with long cycle stability. [ABSTRACT FROM AUTHOR]

In this paper, laser-induced breakdown spectroscopy (LIBS) combined with a probabilistic neural network (PNN) was applied to classify engineering structural metal samples (valve stem, welding material, and base metal). Additionally, utilizing data from the plasma emission spectrum generated by laser ablation of samples with different aging times, an aging time prediction model based on a firefly optimized probabilistic neural network (FA-PNN) was established, which can effectively evaluate the service performance of structural materials. The problem of insufficient features obtained by principal component analysis (PCA) for predicting the aging time of materials is addressed by the proposal of a time-frequency feature extraction method based on short-time Fourier transform (STFT). The classification accuracy (ACC) of time-frequency features and principal component features was compared under PNN. The results indicate that, in comparison to the PCA feature extraction approach, the time-frequency feature extraction method based on STFT demonstrates higher accuracy in predicting the time of aging materials. Then, the relationship between classification accuracy (ACC) and settings of PNN was discussed. The ACC of the PNN model for both the material classification test set and the aging time test set achieved 100% with Firefly (FA) optimization algorithms. This result was also compared with the ACC of ANN, KNN, PLS-DA, and SIMCA for the aging time test set (95%, 87.5%, 85%, and 62.5%, respectively). The experimental results demonstrated that the classification model using LIBS combined with FA-PNN could realize better classification accuracy. [ABSTRACT FROM AUTHOR]

• The operation characteristics of household appliances masks the arc fault characteristics. • Arc fault location affects the performance of arc fault detection features. • The adaptive algorithm can effectively extract arc fault detection features and help accurately detect multi-branch arc faults. • Leaf-wise strategy can simplify the algorithm structure and improve efficiency. The operation characteristics of household appliances would interfere with the arc fault detection. Especially in the case of the multi-branch circuit, the arc fault information is mixed with the operation characteristics of various loads, which makes the traditional arc fault detection algorithm invalid. In this paper, arc fault signals are acquired from the designed multi-branch experimental platform composed of masking loads according to IEC 62606. By adding the adaptive noise, ICEEMDAN algorithm is found to be suitable to extract more sufficient arc fault information. By selecting the IMF and constructing its variance, the detection variables are constructed to distinguish the arc fault from the normal state. Compared with wavelet transform, the ability to extract arc fault information is improved by 8.47 times on average. In order to simplify the algorithm structure, the Boruta and LightGBM algorithm are used to reduce the feature dimension and improve the algorithm efficiency. Based on the well-trained LightGBM model, the arc fault detection algorithm is finally proposed, which could detect multi-branch arc faults accurately and fast. It is proved to have the higher detection accuracy of 97.06% and the lower detection time of no more than 300 ms on the Raspberry pi platform. [Display omitted] [ABSTRACT FROM AUTHOR]

Endometriosis, a common benign gynecological disease, has the growth characteristics of malignant tumors, however, the pathogenesis of this disease remains unclear. It is well known that micro ribonucleic acids (miRNAs) are involved in epithelial-mesenchymal transition (EMT), associated with the development of endometriosis. This study investigated the role of a specific miRNA, miR-34c-5p, in endometriosis. High-throughput sequencing (HTS) showed that miR-34c-5p expression was reduced in ectopic endometrium (ecEM) in patients from Northeast Asia with ovarian endometriosis. A wound healing assay and a transwell invasion assay showed that miR-34c-5p inhibits the invasion and migration of Ishikawa and End1/E6E7 endocervical cells. Dual luciferase gene reporter assays revealed that miR-34c-5p specifically targets Notch1 3 'UTR, and Western blot analyses showed that miR-34c-5p promotes E-cadherin expression but inhibits Notch1, N-cadherin and vimentin expression in Ishikawa and End1/E6E7 cell lines. These results were reversed following knockdown of miR-34c-5p. Using quantitative real time reverse transcriptase polymerase chain reaction (qRT-PCR) and western blot analyses, there was a significant reduction in the expression of Notch1 in ecEM compared with eutopic endometrium (euEM). The results of this study indicate that miR-34c-5p inhibits the progression of EMT and cell invasion and migration by targeting the Notch signaling pathway, specifically, Notch1. The findings of this study provide unique insights into the development of EMT in endometriosis and novel, potential therapeutic targets • HTS results showed decreased expression of miR-34c-5p in ecEM of patients with ovarian endometriosis compared with euEM. • miR-34c-5p inhibits invasion and migration of endometrial epithelial cells • miR-34c-5p/Notch regulates epithelial-mesenchymal transition in endometrial epithelium [ABSTRACT FROM AUTHOR]