Search

With the increasing complexity of power systems due to the integration of new energy sources， there is a heightened demand for advanced protection and control technologies. In response to this challenge， a protection and control architecture designed for new-type power systems is presented. To prevent isolated incidents from cascading into system-wide failures， a new relay protection configuration model is proposed to establish a more robust guard. In view of the evolution of incidents across the system， an information integration and coordination mechanism is established between protection and control systems. Through a combination of station-level autonomy with regional collaboration， the autonomous protection and control is fulfilled. The functional layout of the three guards is optimized to effectively suppress and disrupt the occurrence and development of incidents in the systems and thereby enhances the safety defense capabilities of the new-type power systems.

With the development of new energy， the integration of large-scale doubly-fed wind turbin units into the power systems have a great impact on the transient stability of the power grid. Therefore， a transient stability analysis method for power systems with wind turbines integrated based on fault information is proposed. This method incorporates fault information provided by protective relays into the transient stability judgment. Firstly， the external characteristics of the doubly-fed wind farm after faults and the negative-sequence and zero-sequence impedance models are analyzed. Subsequently， a system admittance matrix containing fault information is derived. Moreover， the EEAC （extended equal area criterion） is utilized to introduce a transient stability margin index， which serves as the basis for determining whether the system undergoes transient instability. Finally， the correctness and effectiveness of the proposed method are verified through simulation on a 3-machine 9-bus system containing doubly-fed wind farms.

Environmental context: Atmospheric particulate NH4+, primarily produced from the reaction of NH3 and acids, is an important component of PM2.5. In this study, nitrogen stable isotope analyses and an atmospheric chemistry model were used to estimate the contribution of major NH3 sources to particulate NH4+ in Tianjin, a megacity in North China Plain (NCP). Our research has implications for investigations of NH3 emission sources and relevant pollution control in Tianjin and NCP. Rationale: The North China Plain (NCP) has been identified as an NH3 emission hotspot. Source apportionment of NH3 is a prerequisite for controlling NH3 or NH4+ pollution. Nitrogen stable isotope (δ 15N) analysis is a promising method for NH3 source apportionment but its accuracy is still in question. Methodology: In this study, daytime and nighttime PM2.5 samples were collected from two sites in Tianjin, NCP, in autumn. Concentrations and δ 15N of particulate NH4+ were then measured. Nitrogen stable isotope analyses and isotope mixing model (MixSIAR), and an atmospheric chemistry model (WRF-CMAQ-ISAM) were used to estimate the sources of NH3 in Tianjin. Results: Results from the MixSIAR and WRF-CMAQ-ISAM models suggested that all the sources including livestock breeding, N-fertiliser application, fossil fuels, NH3 slip (especially from traffic), human waste and biomass burning (mostly from bioapplication) were non-negligible to NH3 and NH4+ in Tianjin. This high complexity is due to significant agricultural and industrial production and residential life in Tianjin and the surrounding regions. Our results indicate all NH3 sources need to be considered if we want to reduce NH4+ pollution in Tianjin in autumn. Environmental context. Atmospheric particulate NH4+, primarily produced from the reaction of NH3 and acids, is an important component of PM2.5. In this study, nitrogen stable isotope analyses and an atmospheric chemistry model were used to estimate the contribution of major NH3 sources to particulate NH4+ in Tianjin, a megacity in North China Plain (NCP). Our research has implications for investigations of NH3 emission sources and relevant pollution control in Tianjin and NCP. Photograph by Libin Wu. This article belongs to the collection Dedication to Roy Harrison. [ABSTRACT FROM AUTHOR]

Background: Benign prostatic hyperplasia (BPH) is a common health disorder of the male genitourinary system with a high prevalence, especially among middle-aged and older adults, which seriously affects men's quality of life. Inflammatory markers derived from complete blood cell count (CBC) have previously been considered a prognostic indicator for various diseases, but little is known about their relationship with BPH. This study evaluated the relationship between complete blood cell count (CBC)-derived inflammatory biomarkers and BPH. Methods: Data for this cross-sectional study were gathered from the National Health and Nutrition Examination Survey (NHANES) between 2001 and 2008. Using multiple logistic regressions, the study examined the association between benign prostatic hyperplasia(BPH) and Inflammatory biomarkers derived from blood cell counts such as neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), Systemic Inflammatory Response Index (SIRI) and Systemic Immunoinflammatory Index (SII). Results: 3,919 participants were included, with a median age of 61.00 (52.00–71.00) years old. Among them, 609 participants had benign prostatic hyperplasia, with a prevalence of 15.54%. Upon accounting for confounding factors, the study revealed a positive correlation between the plurality of BPH PLR and SII. However, MLR, NLR, and SIRI did not significantly correlate with the prevalence of BPH (p>0.05). In contrast to the lowest quartile, higher quartiles of PLR (OR = 1.93[1.38–2.69]) and SII (OR = 1.71[1.22–2.40]) were linked to an elevated risk of BPH. Interaction tests showed that age, body mass index, hypertension, diabetes, smoking, and drinking had no significant effect on this positive correlation (p for interaction>0.05). In addition, we found a roughly linear association between SII, PLR, and BPH using smoothed curve fitting. Conclusions: According to our research, high levels of PLR and SII are positively linked with an increased risk of BPH in middle-aged and elderly individuals in the United States. The results compensate for previous studies that still need to be validated with larger prospective cohorts. [ABSTRACT FROM AUTHOR]

Ozone is widely used to inactivate bacteria, fungi, and viruses. In recent years, the treatment of itchy skin diseases (eczema and atopic dermatitis) using trace ozone has also received attention. However, the feasibility of using trace ozone to replace personal care products (PCPs) has rarely been analyzed. In this study, the applicability of trace ozone was evaluated in terms of its efficiency for microbial inactivation in three types of skin microbiomes, cleaning performance on simulated human hair and epidermis, safety for simulated human hair, and contribution to emission reduction. The results revealed that at a 10:1 ratio of ozonated water to bacterial suspension, the inactivation ratios of Malassezia, C. albicans, and S. epidermidis reached 99.63%, 83.47%, and 100%, respectively. In addition, the cleaning performance of an ozone solution (0.4 mg/L) for simulated human skin contaminated with carbon black and sebum could reach 95.89% and 95.63%, respectively, with 5 min of washing. The average scores were 0.40 and 0.37 after 5 min and 10 min of ozone treatments, respectively, indicating that trace ozone does not significantly damage simulated human hair. Results also revealed that the total emissions of COD, TP, and TN would be reduced by 1.29×106, 3.55×103, and 3.63×103 mg/ (household · year), respectively, if PCPs are replaced by trace ozone. In short, our findings indicate that trace ozone is a potential alternative to PCPs. By replacing PCPs with trace ozone, the use of synthetic chemical products can be reduced and carbon emissions from oil extraction can be countered. [ABSTRACT FROM AUTHOR]

Although self-supervised depth estimation models based on transformers have achieved success, lightweight depth prediction networks exhibit a particularly pronounced issue with depth prediction blurriness at object boundaries compared to standard depth prediction networks. We found that this problem arises from the token dimension constraints, which limit the precise representation of semantic and spatial information. To address this challenge, we introduce a lightweight monocular self-supervised depth estimation network, RENA-Depth, which leverages convolutional neural network neighborhood attention-guided recursive Transformers to enhance depth estimation precision. Specifically, the design begins with the introduction of neighborhood adaptive attention (NA), which focuses on local and regional scales. This component adaptively mines latent semantic and spatial information from the neighborhoods of the input features of self-attention. Subsequently, a global feature recursive interaction module was developed to recursively refine the interaction between local and global information, enhancing the representation of semantic and spatial information without a significant increase in parameters. Finally, an attention equilibrium loss is proposed, which motivates richer semantic information representation and clarifies boundary depth by penalizing the orthogonality similarity of attention mechanisms. Extensive evaluations on the Karlsruhe Institute of Technology and Toyota Technological Institute and Make3D datasets have demonstrated that the proposed lightweight self-supervised depth estimation model, RENA-Depth, outperforms the most advanced lightweight depth detection algorithms, confirming its efficacy and innovation in improving depth prediction accuracy. [ABSTRACT FROM AUTHOR]