Explore the vast range of titles available.

Capacitors are critical components of power converter systems as they influence the cost, size, performance, and scale of such systems. However, capacitors exhibit the highest degeneration and breakdown rates among all power converter components due to their wear-out failures and short lifespans. Therefore, condition monitoring is a vital process to estimate the health status of capacitors and to provide predictive maintenance for ensuring stability in the operation of power converter systems. The equivalent series resistance (ESR) and the capacitance of the capacitor are two widely used parameters for evaluating the health status of capacitors. Unlike the ESR, the capacitance of a capacitor is suitable for the health monitoring of various types of capacitors; therefore, it is more preferable for large-scale systems. This paper presents an overview of previous research addressing this aspect of capacitors and provides a better understanding of the capacitance monitoring of capacitors utilized in power converter systems.

Allioideae includes economically important bulb crops such as garlic, onion, leeks, and some ornamental plants in Amaryllidaceae. Here, we reported the complete chloroplast genome (cpDNA) sequences of 17 species of Allioideae, five of Amaryllidoideae, and one of Agapanthoideae. These cpDNA sequences represent 80 protein-coding, 30 tRNA, and four rRNA genes, and range from 151,808 to 159,998 bp in length. Loss and pseudogenization of multiple genes (i.e., rps2, infA , and rpl22 ) appear to have occurred multiple times during the evolution of Alloideae. Additionally, eight mutation hotspots, including rps15-ycf1 , rps16-trnQ-UUG , petG-trnW-CCA , psbA upstream, rpl32-trnL-UAG , ycf1 , rpl22 , matK , and ndhF , were identified in the studied Allium species. Additionally, we present the first phylogenomic analysis among the four tribes of Allioideae based on 74 cpDNA coding regions of 21 species of Allioideae, five species of Amaryllidoideae, one species of Agapanthoideae, and five species representing selected members of Asparagales. Our molecular phylogenomic results strongly support the monophyly of Allioideae, which is sister to Amaryllioideae. Within Allioideae, Tulbaghieae was sister to Gilliesieae-Leucocoryneae whereas Allieae was sister to the clade of Tulbaghieae- Gilliesieae-Leucocoryneae. Molecular dating analyses revealed the crown age of Allioideae in the Eocene (40.1 mya) followed by differentiation of Allieae in the early Miocene (21.3 mya). The split of Gilliesieae from Leucocoryneae was estimated at 16.5 mya. Biogeographic reconstruction suggests an African origin for Allioideae and subsequent spread to Eurasia during the middle Eocene. Cool and arid conditions during the late Eocene led to isolation between African and Eurasian species. African Allioideae may have diverged to South American taxa in the late Oligocene. Rather than vicariance, long-distance dispersal is the most likely explanation for intercontinental distribution of African and South American Allioideae species.

The slider-crank mechanism (SCM) is fundamental to various mechanical systems. However, optimizing its dynamic performance remains a pressing challenge due to excessive torque, joint reactions, and energy consumption. This study introduces two key innovations to address these challenges: (1) the integration of springs into SCM to optimize dynamic performance and (2) a novel hybrid optimization approach combining the Conjugate Direction with Orthogonal Shift (CDOS) method and Parameter Space Investigation (PSI). The mathematical model evaluates the effects of spring placement and stiffness on critical performance parameters such as energy efficiency, torque demands, and joint forces. The hybrid CDOS-PSI approach systematically identifies optimal design configurations to balance these performance objectives. The methodology’s efficacy is validated through a case study on a wood splitter, a commonly used agricultural and industrial machine. Experimental tests were carried out to measure splitting forces for different wood types, enabling accurate model calibration. Results demonstrate that the spring-integrated SCM reduces dynamic loads significantly compared to conventional designs. Comparative numerical analysis confirms the proposed model’s accuracy, with less than 5% deviations. This research offers innovative contributions to SCM design by combining spring-based dynamic enhancement with a novel hybrid optimization framework for improved efficiency and durability in practical applications.

G-protein signaling modulators (GPSMs) are a class of proteins involved in the regulation of G protein-coupled receptors, the most abundant family of cell-surface receptors that are crucial in the development of various tumors, including breast cancer. This study aims to identify the potential therapeutic and prognostic roles of GPSMs in breast cancer. Oncomine and UALCAN databases were queried to determine GPSM expression levels in breast cancer tissues compared to normal samples. Survival analysis was conducted to reveal the prognostic significance of GPSMs in individuals with breast cancer. Functional enrichment analysis was performed using cBioPortal and MetaCore platforms. Finally, the association between GPSMs and immune infiltration cells in breast cancer was identified using the TIMER server. The experimental results then showed that all GPSM family members were significantly differentially expressed in breast cancer according to Oncomine and UALCAN data. Their expression levels were also associated with advanced tumor stages, and GPSM2 was found to be related to worse distant metastasis-free survival in patients with breast cancer. Functional enrichment analysis indicated that GPSMs were largely involved in cell division and cell cycle pathways. Finally, GPSM3 expression was correlated with the infiltration of several immune cells. Members of the GPSM class were differentially expressed in breast cancer. In conclusion, expression of GPSM2 was linked with worse distant metastasis-free outcomes, and hence could potentially serve as a prognostic biomarker. Furthermore, GPSM3 has potential to be a possible target for immunotherapy for breast cancer.

DC series arc faults pose a significant threat to the reliability of DC systems, particularly in DC generation units where aging components and high voltage levels contribute to their occurrence. Recognizing the severity of this issue, this study aimed to enhance DC arc fault detection by proposing an advanced recognition procedure. The methodology involves a sophisticated combination of current filtering using the Three-Sigma Rule in the time domain and the removal of switching noise in the frequency domain. To further enhance the diagnostic capabilities, the proposed method utilizes time and frequency signals generated from power supply-side signals as a reference input. The time–frequency features extracted from the filtered signals are then combined with artificial learning models. This fusion of advanced signal processing and machine learning techniques aims to capitalize on the strengths of both domains, providing a more comprehensive and effective means of detecting arc faults. The results of this detection process validate the effectiveness and consistency of the proposed DC arc failure identification schematic. This research contributes to the advancement of fault detection methodologies in DC systems, particularly by addressing the challenges associated with distinguishing arc-related distortions, ultimately enhancing the safety and dependability of DC electrical systems.

Mental health literacy (MHL) is key for mental health development, particularly in low-and-middle-income countries (LMIC) where mental health resources are limited. MHL development can be thought of as occurring at two levels: the individual person level (via direct contact, with specifically-targeted individuals), and the public health level (via indirect contact through public media, targeting the general public). Each approach has advantages and disadvantages. The present mixed methods study assessed the status of and best approaches for development of mental health literacy in the Southeast Asian LMIC Vietnam. Because there has been relatively little discussion of MHL development at the public health level, this assessment focused on the public health level, although not exclusively. Because mental health professionals generally have the most in-depth understanding of their mental health system, study participants were 82 Vietnamese mental health professionals who completed a quantitative survey, with 48 participating in focus groups. Most of the professionals viewed MHL in Vietnam as low or very low, and that it was difficult or very difficult for the general public to find effective mental health services. Main barriers underlying these problems and more generally for developing MHL in Vietnam identified in the focus groups were: (a) misinformation in the media regarding mental health and mental illness; (b) lack of licensure for non-medical mental health professionals (e.g., psychologists; social workers); (c) lack of interest in mental health from upper-level leadership. To the best of our knowledge, this is the first study assessing professionals' perceptions regarding mental health literacy at both the public health and individual-person levels. Although sampling was restricted to Vietnamese professionals, results may provide initial preliminary guidance for other LMIC considering mental health literacy development at multiple levels.

Labor law is traditionally viewed as a crucial mechanism for advancing gender equality in the workplace by providing a framework to eliminate sex-based discrimination and enhance women’s participation in the workforce. As nations strive to achieve the UN’s Sustainable Development Goals (SDGs), the significance of such laws is amplified, with gender equality not only a key indicator but also an enabler for other SDGs. This study demonstrates that, despite recent reforms in Vietnam's labour law reducing barriers to female employment, pervasive gender inequality persists, fuelled by enduring employment stereotypes that often depict women as victims. To develop a sustainable workforce, Vietnam's labor laws and policies should implement strategies to dismantle these stereotypes. This research suggests transitioning from the traditional approach of female protection to involving men in domestic roles. A strategy targeting men is expected to promote gender equality in the Vietnamese workforce by altering employer perceptions of female employees' maternal roles. From the perspective of masculinity theory, the potential of paternity bonuses is significant; they can enhance women’s career opportunities by alleviating domestic burdens and broadening acceptable roles for men.

The Asia-Pacific region is known as a favorite destination for global medical travelers due to its medical expertise, innovative technology, safety, attractive tourism destination and cost advantage in the recent decade. This study contributes to propose an approach which effectively assesses performance of medical tourism industry based on considering the economic impact factors as well as provides a conceptual framework for the industry analysis. Grey system theory is utilized as a major analyzing approach. According to that, factors impact on the sustainable development of medical tourism in Asia-Pacific region could be identified. The performance of each destination in this region was simultaneously revealed. The results presented an overall perspective of the medical tourism industry in the scope of the Asia-Pacific region, and in Taiwan particularly. Data was collected on six major destinations including Singapore, Thailand, India, South Korea, Malaysia and Taiwan. The results proved that tourism sources and healthcare medical infrastructures play a crucial role in promoting the healthcare travel industry, while cost advantage and marketing effectiveness were less considered. In addition, performance analyse indicated that Thailand has a good performance and stands in the top ranking, followed by Malaysia, India, Singapore, South Korea and Taiwan, respectively. The revenue of Taiwan has increased slowly in the last six years, with a market worth approximately NT$20.5 billion, and the number of medical travelers is expected to increase to 777,523 by 2025. The findings of this study are expected to provide useful information for the medical tourism industry and related key players in strategic planning.

Glioblastoma (GBM) is one of the most progressive and prevalent cancers of the central nervous system. Identifying genetic markers is therefore crucial to predict prognosis and enhance treatment effectiveness in GBM. To this end, we obtained gene expression data of GBM from TCGA and GEO datasets and identified differentially expressed genes (DEGs), which were overlapped and used for survival analysis with univariate Cox regression. Next, the genes’ biological significance and potential as immunotherapy candidates were examined using functional enrichment and immune infiltration analysis. Eight prognostic-related DEGs in GBM were identified, namely CRNDE, NRXN3, POPDC3, PTPRN, PTPRN2, SLC46A2, TIMP1, and TNFSF9. The derived risk model showed robustness in identifying patient subgroups with significantly poorer overall survival, as well as those with distinct GBM molecular subtypes and MGMT status. Furthermore, several correlations between the expression of the prognostic genes and immune infiltration cells were discovered. Overall, we propose a survival-derived risk score that can provide prognostic significance and guide therapeutic strategies for patients with GBM.

Rising infrastructure density and transportation networks along the riverbank landslide alter critical stress and horizontal displacement in riverbank soils, contributing to erosion. Early warning systems can detect structural changes in soil to help mitigate damage. However, there is still a lack of studies evaluating horizontal pressure in landslide masses under the influence of load and horizontal displacement causing erosion or externally induced stress. This study presents a monitoring system based on wireless transmission technology combined with sensors embedded in the soil to track the displacement of the soil mass along the riverbank. The system uses tilt, soil moisture, and earth pressure sensors to collect real-time data on the mechanical properties of the soil. Experimental results show that a load of 17.5 kPa can destabilize the slope, with tilt angles increasing significantly as soil mass shifts toward the canal. The maximum recorded horizontal soil pressure is 2.77 kPa. The analysis reveals significant discrepancies between analytical methods and finite element method (FEM) in predicting soil behavior under loads, highlighting the superior accuracy of FEM, especially at higher loads. This research contributes to developing a reliable information system for managing landslide risks as well as externally induced stress, protecting people and infrastructure.