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This work proposes a methodology for noise removal, separation, and classification of partial discharges in electrical system assets. Partial discharge analysis is an essential method for fault detection and evaluation of the operational conditions of high-voltage equipment. However, it faces several limitations in field measurements due to interference from radio signals, television transmissions, WiFi, corona signals, and multiple sources of partial discharges. To address these challenges, we propose the development of a clustering model to identify partial discharge sources and a classification model to identify the types of discharges. New features extracted from pulses are introduced to model the clustering and classification of discharge sources. The methodology is tested in the laboratory with controlled partial discharge sources, and field tests are conducted in substations to assess its practical applicability. The results of laboratory tests achieved an accuracy of 85% in classifying discharge sources. Field tests were performed in a substation of the Eletrobras group, allowing the identification of at least three potentially defective current transformers. [ABSTRACT FROM AUTHOR]

In the detection process of the internal defects of large oil-immersed transformers, due to the huge size of large transformers and metal-enclosed structures, the positional localization of miniature inspection robots inside the transformer faces great difficulties. To address this problem, this paper proposes a three-dimensional positional localization method based on adaptive denoising and the SCOT weighting function with the addition of the exponent β (SCOT-β) generalized cross-correlation for L-type ultrasonic arrays of transformer internal inspection robots. Aiming at the strong noise interference in the field, the original signal is decomposed by an improved Empirical Mode Decomposition (EMD) method, and the optimal center frequency and bandwidth of each mode are adaptively searched. By extracting the modes in the frequency band of the positional localization signal, suppressing the modes in the noise frequency band, and reconstructing the Intrinsic Mode Function (IMF) of the independently selected superior modal components, a signal with a high signal-to-noise ratio is obtained. In addition, for the traditional mutual correlation algorithm with a large delay estimation error at a low signal-to-noise ratio, this paper adopts an improved generalized joint weighting function, SCOT-β, which improves the anti-jamming ability of the generalized mutual correlation method at a low signal-to-noise ratio by adding an exponential function to the denominator term of the SCOT weighting function's generalized cross-correlation. Finally, the accurate positional localization of the transformer internal inspection robot is realized based on the quadratic L-array and search-based maximum likelihood estimation method. Simulation and experimental results show the following: the improved EMD denoising method better improves the signal-to-noise ratio of the positional localization signal with a lower distortion rate; in the transformer test tank, which is 120 cm in length, 100 cm in width, and 100 cm in height, based on the positional localization method in this paper, the average relative positional localization error of the transformer internal inspection robot in three-dimensional space is 2.27%, and the maximum positional localization error is less than 2 cm, which meets the requirements of engineering positional localization. [ABSTRACT FROM AUTHOR]

Electronic cigarette (e-cig) use, otherwise known as "vaping", is widespread among adolescent never-smokers and adult smokers seeking a less-harmful alternative to combustible tobacco products. To date, however, the long-term health consequences of vaping are largely unknown. Many toxicants and carcinogens present in e-cig vapor and tobacco smoke exert their biological effects through epigenetic changes that can cause dysregulation of disease-related genes. Long non-coding RNAs (lncRNAs) have emerged as prime regulators of gene expression in health and disease states. A large body of research has shown that lncRNAs regulate genes involved in the pathogenesis of smoking-associated diseases; however, the utility of lncRNAs for assessing the disease-causing potential of vaping remains to be fully determined. A limited but growing number of studies has shown that lncRNAs mediate dysregulation of disease-related genes in cells and tissues of vapers as well as cells treated in vitro with e-cig aerosol extract. This review article provides an overview of the evolution of e-cig technology, trends in use, and controversies on the safety, efficacy, and health risks or potential benefits of vaping relative to smoking. While highlighting the importance of lncRNAs in cell biology and disease, it summarizes the current and ongoing research on the modulatory effects of lncRNAs on gene regulation and disease pathogenesis in e-cig users and in vitro experimental settings. The gaps in knowledge are identified, priorities for future research are highlighted, and the importance of empirical data for tobacco products regulation and public health is underscored. [ABSTRACT FROM AUTHOR]

Chronic pain is a prevalent condition with a multifaceted pathogenesis, where epigenetic modifications, particularly DNA methylation, might play an important role. This review delves into the intricate mechanisms by which DNA methylation and demethylation regulate genes associated with nociception and pain perception in nociceptive pathways. We explore the dynamic nature of these epigenetic processes, mediated by DNA methyltransferases (DNMTs) and ten-eleven translocation (TET) enzymes, which modulate the expression of pro- and anti-nociceptive genes. Aberrant DNA methylation profiles have been observed in patients with various chronic pain syndromes, correlating with hypersensitivity to painful stimuli, neuronal hyperexcitability, and inflammatory responses. Genome-wide analyses shed light on differentially methylated regions and genes that could serve as potential biomarkers for chronic pain in the epigenetic landscape. The transition from acute to chronic pain is marked by rapid DNA methylation reprogramming, suggesting its potential role in pain chronicity. This review highlights the importance of understanding the temporal dynamics of DNA methylation during this transition to develop targeted therapeutic interventions. Reversing pathological DNA methylation patterns through epigenetic therapies emerges as a promising strategy for pain management. [ABSTRACT FROM AUTHOR]

As an advanced energy storage technology, the compressed CO2 energy storage system (CCES) has been widely studied for its advantages of high efficiency and low investment cost. However, the current literature has been mainly focused on the TC-CCES and SC-CCES, which operate in high-pressure conditions, increasing investment costs and bringing operation risks. Meanwhile, some studies based on the phase-change CO2 energy storage system also have had the disadvantages of low efficiency and the extra necessity of heat or cooling sources. To overcome the above problems, this paper proposes an innovative compressed CO2 phase-change energy storage system. During the energy charge process, molten salt and water are used to store heat with a smaller temperature difference in heat exchangers, and high-pressure CO2 is reserved in liquid form. During the energy discharge process, throttle expansion is applied to realize the evaporation at room temperature, and CO2 absorbs the reserved heat to improve the power capacity in the turbine and the system energy storage efficiency. The thermodynamic and exergoeconomic studies are performed firstly by using MATLAB. Then, the parametric study based on energy storage efficiency, system unit product cost, and exergy destruction is analyzed. The results show that energy storage efficiency can be improved by lifting liquid CO2 pressure as well as compressor and turbine isentropic efficiencies, and CO2 evaporation pressure has the optimal pressure point. The system unit product cost can be reduced by decreasing liquid CO2 pressure and compressor isentropic efficiency, while CO2 evaporation pressure and turbine isentropic efficiency both have optimal points. Finally, the optimization of two performances is performed by NSGA-II, and they can reach 75.30% and 41.17 $/GJ, respectively. Moreover, the optimal energy storage efficiency is obviously higher than that of other energy storage technologies, indicating the great advantage of the proposed system. This study provides an innovative research method for a new type of large-scale energy storage system. [ABSTRACT FROM AUTHOR]

In the environment of oil and gas wells, the shielding effect of metal casing increases the difficulty of applying wireless electromagnetic wave transmission technology in such wells. This paper constructs a theoretical model of downhole electromagnetic helical loop transmission based on the finite element method. The magnetic loop is equated with the helical loop antenna in the model. By means of simulation calculations, this study deeply investigates the impact of various factors, such as working frequency within the cased well, drilling fluid resistivity, formation resistivity, drill string dimensions, and electrical conductivity, on the attenuation pattern of the helical loop antenna. The results show that low-frequency signals experience relatively less attenuation underground, while high-frequency signals demonstrate better transmission effects over shorter distances. Moreover, drilling fluids with low resistivity are more suitable for short-distance transmission, whereas high resistivity can effectively reduce signal attenuation and improve transmission distance. The variation in formation resistivity has a relatively small impact on signal transmission and can be considered negligible. In terms of drill string characteristics, as the electrical conductivity of the drill collars increases, signal attenuation gradually decreases, and the amplitude of the received signal is enhanced. With the inner and outer diameters of the drill collars remaining the same, a finer inner diameter of the casing aids electromagnetic wave short-distance transmission, whereas a thicker casing can reduce electromagnetic wave attenuation. Theoretical and practical results are in good agreement through field trial comparative analysis. [ABSTRACT FROM AUTHOR]

Partial discharge (PD) is one of the major causes of insulation accidents in oil-immersed transformers, generating a large number of signals that represent the health status of the transformer. In particular, acoustic signals can be detected by sensors to locate the source of the partial discharge. However, the array, type, and quantity of sensors play a crucial role in the research on the localization of partial discharge sources within transformers. Hence, this paper proposes a novel sensor array for the specific localization of PD sources using COMSOL Multiphysics software 6.1 to establish a three-dimensional model of the oil-immersed transformer and the different defect types of two-dimensional models. "Electric-force-acoustic" multiphysics field simulations were conducted to model ultrasonic signals of different types of PD by setting up detection points to collect acoustic signals at different types and temperatures instead of physical sensors. Subsequently, simulated waveforms and acoustic spatial distribution maps were acquired in the software. These simulation results were then combined with the time difference of arrival (TDOA) algorithm to solve a system of equations, ultimately yielding the position of the discharge source. Calculated positions were compared with the actual positions using an error iterative algorithm method, with an average spatial error about 1.3 cm, which falls within an acceptable range for fault diagnosis in transformers, validating the accuracy of the proposed method. Therefore, the presented sensor array and computational localization method offer a reliable theoretical basis for fault diagnosis techniques in transformers. [ABSTRACT FROM AUTHOR]

The muscarinic acetylcholine receptor M3 (M3-mAChR) is involved in various physiological and pathological processes. Owing to specific cardioprotective effects, M3-mAChR is an ideal diagnostic and therapeutic biomarker for cardiovascular diseases (CVDs). Growing evidence has linked M3-mAChR to the development of multiple CVDs, in which it plays a role in cardiac protection such as anti-arrhythmia, anti-hypertrophy, and anti-fibrosis. This review summarizes M3-mAChR's expression patterns, functions, and underlying mechanisms of action in CVDs, especially in ischemia/reperfusion injury, cardiac hypertrophy, and heart failure, opening up a new research direction for the treatment of CVDs. [ABSTRACT FROM AUTHOR]

Diabetes is a widespread chronic disease that occurs mainly in the elderly population. Due to the difference in pathophysiology between elderly and young patients, the current clinical practice to treat elderly patients with anti-diabetes medications still faces some challenges and dilemmas, such as the urgent need for early diagnosis and prevention, and an imbalance between restricted dietary intake and the risk of undernutrition. Traditional Chinese medicine (TCM) offers various treatment regimens that are actively utilized in the field of diabetes management. Through multiple targets and multiple pathways, TCM formulas, medicinal herbs, and active natural products enhance the efficacy of diabetes prevention and diabetes control measures, simplify complex medication management, and improve common symptoms and common diabetic complications in elderly people. Historically, natural products have played a key role in material composition analysis of TCM and mechanism interpretation to enable drug discovery. However, there have been few conclusions on this topic. This review summarizes the development of TCM for the prevention and management of diabetes in elderly people, existing evidence-based clinical practices, and prospects for future development. [ABSTRACT FROM AUTHOR]

The epidermal cells of insects are polarized epithelial cells that play a pivotal role in the insect's molting process. Sinuous, a pivotal structural protein involved in the formation of septate junctions among epithelial cells, is essential for its physiological function. In this study, to determine whether sinuous participates in the regulation of insect molting, we identified the sinuous gene, Lmsinu, in Locusta migratoria, which encodes a protein belonging to the claudin family and shares 62.6% identity with Drosophila's sinuous protein. Lmsinu is expressed in multiple tissues, and its expression level in the integument significantly increases prior to molting. Knockdown of Lmsinu in L. migratoria results in larval mortality during molting. Furthermore, hematoxylin and eosin and chitin staining demonstrate that the downregulation of Lmsinu led to a prolonged degradation process of the old cuticle during the molting process. Electron microscopy analysis further revealed that knockdown of Lmsinu disrupts the formation of septate junctions among epidermal cells, which are a monolayer of polarized epithelial cells, which may hinder the functionality of epidermal cells during the process of molting. In summary, these findings suggest that Lmsinu plays a role in nymph molting by regulating the formation of septate junctions among epidermal cells. [ABSTRACT FROM AUTHOR]

A class of semi-linear elliptic equations with the critical Hardy–Sobolev exponent has been considered. This model is widely used in hydrodynamics and glaciology, gas combustion in thermodynamics, quantum field theory, and statistical mechanics, as well as in gravity balance problems in galaxies. The P S c sequence of energy functional was investigated, and then the mountain pass lemma was used to prove the existence of at least one nontrivial solution. Also a multiplicity result was obtained. Some known results were generalized. [ABSTRACT FROM AUTHOR]

Granule size distribution of wheat starch is an important characteristic that could affect the functionality of wheat (Triticum aestivum L.) products. Lodging is a major limiting factor for wheat production. Few studies have been conducted to clarify how lodging influences the granule size distribution and viscosity parameters of starch in wheat grains. Two growing seasons, two high-yield winter wheat cultivars, and five artificial lodging treatments were imposed. The results indicated that lodging significantly reduced the content of starch and increased that of protein. Additionally, lodging caused a marked drop in both starch and protein yields. The relative loss of grain yield, starch yield, harvest index, and protein yield all differed remarkably among lodging treatments with a ranking of L2 > L1 > L4 > L3. Lodging also led to a reduction in the proportion (both by volume and by surface area) of B-type granules and a corresponding increase in that of A-type granules, and the more serious the lodging degree, the greater effect on the changes in these proportions. The smaller starch granules predominated in number, even though their collective contribution to the overall volume is was relatively minor. Meanwhile, it was found that the peak viscosity, hold viscosity, final viscosity, breakdown viscosity, and rebound value of wheat starch were significantly decreased by lodging. Correlation analysis showed that the peak and final viscosities were negatively correlated with volume percentages of A-type starch granules, but were positively correlated with B-type granules. This indicates that B-type granules have higher peak and final viscosities compared with A-type granules in wheat kernels. Lodging can reduce the proportion of B-type starch granules, and thus reduce the peak and the final viscosity in wheat grain. [ABSTRACT FROM AUTHOR]

In the context of the increasingly serious issues of resource waste, soil degradation, and environmental pollution caused by excessive nitrogen fertilizer application worldwide, this study conducted a two-year field experiment in Qinghai Province to explore suitable nitrogen fertilizer management strategies for the region. Ten fertilization levels were set, incorporating varying ratios of conventional nitrogen fertilizer and organic fertilizer, as well as the proportion of base fertilizer and topdressing. The focus was on monitoring the forage yield, quality, and related physiological indicators of oats during the flowering and milk stages. The use of correlation analysis and the multi-criteria decision-making model TOPSIS was applied for comprehensive data evaluation to determine the optimal fertilization strategy. After systematic data collection and analysis, the results showed that when 75% conventional nitrogen fertilizer was combined with 4500 kg·hm−2 of organic fertilizer (F4), the oat yield during the milking stage reached its peak at 14,722.48 kg·hm−2. Additionally, the yield effect was optimal (13,677.34 kg·hm−2) when using 30% base fertilizer and 70% jointing fertilizer (D2). Regarding nutritional quality, the fertilization strategy combining 75% conventional nitrogen fertilizer with 4500 kg·hm−2 of organic fertilizer, along with 30% base fertilizer and 70% jointing fertilizer (F4D2), significantly reduced the content of acid detergent fiber (ADF), neutral detergent fiber (NDF), and coarse fiber (CF) in oats, while increasing the content of EE (crude fat) and CP (crude protein). This significantly improved the nutritional value of oats. Correlation analysis further revealed the positive effect of fertilization amount and fertilization period on oat yield, as well as a negative correlation with fiber content. Finally, through comprehensive evaluation using the multi-criteria decision-making model TOPSIS, we verified the superiority of the fertilization strategy. [ABSTRACT FROM AUTHOR]

Non-albicans Candida (NAC) species are increasingly recognized as significant contributors to candidemia infections; however, relatively less is known about the immune responses induced by these species. In this study, we compared the cytokine production ability of human peripheral blood mononuclear cells (PBMCs) upon stimulation with different Candida species (Candida spp.). We measured secreted cytokines using ELISA and checked the functional profiles of T-cell responses using multicolor flow cytometry. Although there was a differential expression of cytokines against Candida spp., significant difference were observed in the levels of IFN-γ, TNF-α, IL-10, IL-12p40, and IL-23 (p < 0.05) between Candida spp. A significant difference was observed between C. albicans and C. glabrata (p = 0.026) in the levels of TNF-α. C. glabrata showed significant differences compared to C. albicans, C. parapsilosis, and C. krusei in the levels of IL-10 (p values of 0.02, 0.04, and 0.01, respectively). Despite the percentages of CD4+ and CD8+ expressing Th1, Th2, and Th17 cytokines being higher in stimulated PBMCs, none of the Candida spp. showed significant differences. The levels of secreted IL-17A and IL-23 were consistently lower in Candida spp. regardless of the stimulus used. Here, we showed the differential regulation of Th1, Th2, and Th17 during Candida spp. stimulation of the immune system ex vivo. Additionally, our findings suggest that C. albicans elicits an IFN-γ response, whereas C. glabrata promotes IL-10 cellular responses, but this warrants additional studies to conclude this association. This investigation holds the potential to advance our comprehension of the distinct immune responses induced by Candida spp., with probable implications in designing antifungal immunotherapeutics. [ABSTRACT FROM AUTHOR]

Jasminum sambac is an excellent ornamental species that is renowned worldwide for its pure white flowers and strong fragrance. However, its intolerance to low temperatures limits its cultivation range. Methyl jasmonate (MeJA), an essential plant growth regulator, plays a significant role in assisting plants to resist various stresses. Hence, this study was carried out to decipher the capabilities of diverse concentrations of MeJA in helping J. sambac to resist cold stress by measuring different physiological indexes. A normal temperature (15 °C/10 °C) and low temperature (7 °C/2 °C) were applied to J. sambac seedlings, and a one-way analysis of variance followed by a Duncan's multiple range test was adopted to compare the differences between the indicators under 5 μmol·L−1, 10 μmol·L−1 and 20 μmol·L−1 of MeJA treatments. The results showed that cold stress significantly decreased the contents of soluble sugar and soluble protein, while the application of MeJA at 10 μmol·L−1 and 20 μmol·L−1 resulted in a partial recovery. In addition, cold stress dramatically hindered the accumulation of total chlorophyll in leaves. Exogenous MeJA elevated the total chlorophyll content during the whole sampling period. The hydrogen peroxide and malondialdehyde levels generally increased in response to low temperatures, and they caused adverse effects on J. sambac, whereas this was effectively alleviated through the application of MeJA. MeJA was also able to improve the resistance of J. sambac by boosting the activity of antioxidant enzymes to remove the excess of reactive oxygen species. In conclusion, we highlighted that exogenous MeJA could attenuate the negative consequences of cold stress for J. sambac, and 10 μmol·L−1 of MeJA treatment could be a feasible strategy for enhancing the resistance of J. sambac to low temperatures and promoting its growth. [ABSTRACT FROM AUTHOR]

Purpose: The study aims to examine the role of green learning orientation, green knowledge acquisition and green knowledge management in fostering corporate environmental performance of small and medium-sized enterprises (SMEs) in China. In addition, this research assesses the moderating role of chief executive officer (CEO) gender between green knowledge management and corporate environmental performance. Finally, this study examines the sequential mediating role of green knowledge acquisition and green knowledge management. Design/methodology/approach: The study collected the data of 300 SMEs' CEOs taken from five different provinces in China. The study used a partial least squares regression-based structural equation modelling technique. Findings: The findings revealed that green learning orientation plays an important role in increasing SMEs' corporate environmental performance. The results showed that green knowledge acquisition and green knowledge management serially and completely mediate the relationship between green learning orientation and corporate environmental performance. Originality/value: To the best of the authors' knowledge, this is the first study addressing the sequence of knowledge orientation, acquisition, management and results in terms of corporate environmental performance. Meanwhile, this study is the first to examine the indirect role of CEO gender on the relationship between green knowledge management and corporate environmental performance. As decisions are taken by the top management and CEO, especially in the case of SMEs, the role of top management and how well top management uses the knowledge acquired by the organization matters significantly. [ABSTRACT FROM AUTHOR]