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Collagenous gastritis has been reported as a rare cause of nausea, diarrhea, weight changes, and early satiety in female patients. Here, we describe two women aged 43 and 71 years who presented with similar symptoms. Gastric biopsies from both individuals showed thickened, irregular subepithelial collagen bands (>10 μm). The pathogenesis of collagenous gastritis is poorly understood, but it may be the presenting symptom for many underlying autoimmune conditions. In particular, there is a well-established connection between collagenous disorders of the gastrointestinal tract and celiac sprue, Sjögren syndrome, and lymphocytic colitis; however, none of these conditions had been diagnosed in our patients. The older woman had incidentally discovered hypogammaglobinemia and IgA deficiency, whereas the younger woman suffered from fibromyalgia. Although a gluten-free diet and budesonide have been effective in some cases, there is no standardized therapy for collagenous gastritis. Our patients trialed diet modification and have required no additional medical interventions.

Background and aimsDifferentiating pancreatic cystic lesions remains a challenge when the current technique of EUS-guided FNA is used. Recently, a miniaturized biopsy forceps with an outer diameter of 0.8 mm has been developed, thus allowing it to be passed through the bore of a standard 19-gauge FNA needle to acquire tissue.MethodsThis study consisted of a retrospective review of all cases of EUS-guided through-the-needle forceps biopsy technique (TTNFB) performed for pancreatic cystic lesions at a single academic tertiary care center over a 12-month period. Technical success was defined as acquisition of adequate tissue for formal histologic analysis. Safety was assessed through the monitoring and recording of periprocedural and postprocedural adverse events.ResultsThe technical success of EUS-guided TTNFB was 87% (13/15). EUS-guided TTNFB with histologic analysis yielded pancreatic cyst diagnoses in 11 of 15 (73%) patients, compared with 0 of 15 (0%) patients with the use of EUS-FNA and cytologic analysis (P < .001). Of the 15 cystic lesions, 8 were diagnosed as intrapapillary mucinous neoplasm based on EUS-TTNFB.ConclusionThis TTNFB technique has the potential to improve the diagnostic yield of EUS-FNA for pancreatic cystic neoplasms.

[Introduction] During the earth return and metallic return mode conversion of China's HVDC transmission projects in operation, several MRTB (metallic return transfer breaker) or ERTB (earth return transfer breaker) oscillation platform arrester damage have occurred, leading to conversion failure. Therefore, it is necessary to study several modification plans of DC transfer breaker arrester. [Method] Regarding the characteristics of high energy absorption, long current flow time and high ratio of residual voltage to reference voltage of the DC transfer switch arrester, the calculation results of the arrester's absorbed energy, flow time and overvoltage were proposed to judge whether the two modification plans of increasing the number of arrester columns and increasing the number of valves in series per column could improve the operation environment of the arrester, and the impact on the insulation level of other equipment and the arrangement of equipment were also analyzed in this paper. [Result] Increasing the number of arrester columns has no obvious effect on improving the operation characteristics of the arrester. Increasing the number of valves in series per column can reduce the current flow time of the arrester but will increase the insulation level of the circuit breaker and the capacitor of the oscillation circuit. [Conclusion] It is not recommended to increase the number of columns or the number of valves in series per column of the HVDC transfer switch arrester in the existing converter station. It can be transferred at a lower power level to reduce the stress of the arrester. If the energy margin of the arrester is sufficient, measures can be taken to remove the faulty unit and continue operation in the event that the arrester fails due to valve defects.

This research introduces a novel damped alternating current (DAC) testing methodology, which integrates an enhanced DAC generator with a pulse‐based distributed partial discharge (PD) detection technique. The advanced DAC generator is designed without the need for high voltage (HV) solid‐state switches, thereby offering a cost‐effective solution for field‐testing voltage generation through a direct current–alternating current conversion approach. To meet the demand for high instantaneous power, a capacitor bank is employed as the power supply. Furthermore, the implementation of a distributed PD detection technique enhances sensitivity and eliminates limitations associated with cable length. To minimize the construction costs of the distributed PD‐detection system, a pulse synchronization technique has been employed. Efforts to reduce the system's weight were informed by simulations, resulting in the design and development of a prototype weighing 850 kg for a 64/110 kV power cable. The reduction in the number of HV solid‐state switches contributes to significant cost savings, amounting to tens of thousands of dollars, when compared to conventional DAC generators. Laboratory and field tests validated the effectiveness of the cost‐efficient DAC testing methodology. [ABSTRACT FROM AUTHOR]

In practical working environments, rolling bearings are one of the components that are prone to failure. Their vibration signal samples are faced with challenges, mainly including the imbalance between normal and fault samples as well as an insufficient number of labeled samples. This study proposes a sample-expansion method based on generative adversarial networks (GANs) and a fault diagnosis method based on a transformer to solve the above issues. First, selective kernel networks (SKNets) and a genetic algorithm (GA) were introduced to construct a conditional variational autoencoder–evolutionary generative adversarial network with a selective kernel (CVAE-SKEGAN) to achieve a balance between the proportion of normal and faulty samples. Then, a semi-supervised learning–variational convolutional Swin transformer (SSL-VCST) network was built for the fault classification, specifically introducing variational attention and semi-supervised mechanisms to reduce the overfitting risk of the model and solve the problem of a shortage of labeled samples. Three typical operating conditions were designed for the multi-case applicability verification. The results show that the method proposed in this study had good application effects when solving both sample imbalances and labeled-sample deficiencies and improved the accuracy of fault diagnosis in the above scenarios. [ABSTRACT FROM AUTHOR]

The integration of photovoltaic, energy storage, direct current, and flexible load (PEDF) technologies in building power systems is an important means to address the energy crisis and promote the development of green buildings. The friendly interaction between the PEDF systems and the power grid can promote the utilization of renewable energy and enhance the stability of the power grid. For this purpose, this work introduces a framework of multiple incentive mechanisms for a PEDF park, a building energy system that implements PEDF technologies. The incentive mechanisms proposed in this paper include both economic and noneconomic aspects, which is the most significant innovation of this paper. By modeling the relationship between a PEDF park and the power grid into a Stackelberg game, we demonstrate the effectiveness of these incentive measures in promoting the friendly interaction between the two entities. In this game model, the power grid determines on the prices of electricity trading and incentive subsidy, aiming to maximize its revenue while reducing the peak load of the PEDF park. On the other hand, the PEDF park make its dispatch plan according to the prices established by the grid, in order to reduce electricity consumption expense, improve electricity utility, and enhance the penetration rate of renewable energy. The results show that the proposed incentive mechanisms for the PEDF park can help to optimize energy consumption and promote sustainable energy practices. [ABSTRACT FROM AUTHOR]

In order to achieve batch production, we propose a simple and fast method to prepare leather-finished plywood. In this study, ethylene–vinyl acetate was selected as the intermediate layer to prepare EVA/polyurethane (PU) leather composites. ESEM, tensile property test and compressive property test were used to characterize the microstructure and physical-mechanical properties of the composites. The response surface method (RSM) was also used to explore the relationship between hot pressing temperature, hot pressing pressure and hot pressing time. The significance of the factors and the interactions between the two factors were determined by ANOVA, with the most significant effect being that of the temperature. The theoretical optimal hot pressing process conditions were calculated by the regression equation as a temperature of 124.4 °C, a time of 200 s and a pressure of 1.3 MPa. The surface bond strength of the test specimen measured under this condition was 1.89 MPa, it has good finishing properties and the impregnation peel strength and surface bond strength met the requirements of GB/T 15104-2021. [ABSTRACT FROM AUTHOR]

Introduction: Accurate prediction of line losses in distribution networks is crucial for optimizing power system planning and network restructuring, as these losses significantly impact grid operation quality. This paper proposes a novel approach that combines advanced feature selection techniques with Stacking ensemble learning to enhance the effectiveness of distribution network loss analysis and assessment. Methods: Utilizing data from 44 substations over an 18-month period, we integrated a Stacking ensemble learning model with multiple feature selection methods, including correlation coefficient, maximum information coefficient, and tree-based techniques. These methods were employed to identify the key predictors of power loss in the distribution network. Results: The proposed model achieved a Mean Absolute Percentage Error (MAPE) of 3.78% and a Root Mean Square Error (RMSE) of 1.53, demonstrating a substantial improvement over traditional linear regression-based prediction methods. The analysis revealed that historical line loss and line active power were the most influential predictive variables, while the inclusion of time-related features further refined the model's performance. Discussion: This study highlights the efficacy of combining multiple feature selection methods with Stacking ensemble learning for predicting power loss in 10 kV distribution networks. The enhanced accuracy and reliability of the proposed model offer valuable insights for electrical engineering applications, potentially contributing to more efficient and sustainable energy distribution systems. Future research could explore the applicability of this approach to other distribution network voltage levels and investigate the incorporation of additional environmental and network-specific factors to further improve power loss prediction. [ABSTRACT FROM AUTHOR]

In response to climate change, the proportion of renewable energy penetration is increasing daily. However, there is a lack of flexible energy transfer mechanisms. The optimization effect of low-carbon economic dispatch in a single park is limited. In the context of the sharing economy, this study proposes a research method for multi-park electricity sharing and benefit allocation based on carbon credit trading. Firstly, a framework for multi-park system operation is constructed, and an energy hub model is established for the electrical, cooling, and heating interconnections with various energy conversions. Secondly, a park carbon emission reduction trading model is established based on the carbon credit mechanism, further forming an optimal economic and environmental dispatch strategy for multi-park electricity sharing. Matlab+Gurobi is used for solving. Then, based on asymmetric Nash bargaining, the comprehensive contribution rate of each park is calculated by considering their energy contribution and carbon emission reduction contribution, thereby achieving a fair distribution of cooperation benefits among multiple parks. The results show that the proposed method can effectively reduce the overall operational cost of multiple parks and decrease carbon emissions, and the benefit allocation strategy used is fair and reasonable, effectively motivating the construction of new energy in parks and encouraging active participation in cooperative operations by all parks. [ABSTRACT FROM AUTHOR]

Day length modulates hypocotyl elongation in seedlings to optimize their overall fitness. Variations in cell growth‐associated genes are regulated by several transcription factors. However, the specific transcription factors through which the plant clock increases plant fitness are still being elucidated. In this study, we identified the no apical meristem, Arabidopsis thaliana‐activating factor (ATAF‐1/2), and cup‐shaped cotyledon (NAC) family transcription factor ATAF1 as a novel repressor of hypocotyl elongation under a short‐day (SD) photoperiod. Variations in day length profoundly affected the transcriptional and protein levels of ATAF1. ATAF1‐deficient mutant exhibited increased hypocotyl length and cell growth‐promoting gene expression under SD conditions. Moreover, ATAF1 directly targeted and repressed the expression of the cycling Dof factor 1/5 (CDF1/5), two key transcription factors involved in hypocotyl elongation under SD conditions. Additionally, ATAF1 interacted with and negatively modulated the effects of phytochrome‐interacting factor (PIF), thus inhibiting PIF‐promoted gene expression and hypocotyl elongation. Taken together, our results revealed ATAF1–PIF as a crucial pair modulating the expression of key transcription factors to facilitate plant growth during day/night cycles under fluctuating light conditions. Summary statement: This study identified Arabidopsis NAC transcription factor Arabidopsis thaliana‐activating factor (ATAF1) as a novel repressor of hypocotyl elongation under short‐day conditions. ATAF1 controls the transcription levels of key regulator CDF1/5 by repressing the central regulators phytochrome‐interacting factor via protein–protein interaction. [ABSTRACT FROM AUTHOR]