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This paper focuses on identifying voltage sag-sensitive loads within unknown load type or when the load is already in operation. To achieve this, a new method of sensitive load identification based on power quality monitoring data is proposed. Firstly, the active power RMS monitoring data is used as the base data. The Hodrick-Prescott filtering and sliding mean segmentation are used to divide the period of the voltage sag event. Next, based on the division result, the differences of steady-state power quality monitoring data before and after each event are calculated as the dataset. The dynamic K-means is used to divide various load action areas. Finally, the voltage tolerance curves of each action area are fitted and compared with the preset curves, then according to the constituted rules in this paper, the type of sensitive load contained by user is recognized. The feasibility and accuracy of the proposed method are verified by analyzing the simulation examples and actual power quality monitoring data.© 2017 Elsevier Inc. All rights reserved.

The development and application scope of the Internet of Things is also becoming more and more extensive. Especially in the application of power testing improved systems, great progress has been made. This article aims to study how to analyze the system detection equipment based on the Internet of Things. This article describes the basic theoretical knowledge of the Internet of Things and power detection improved systems. A clustering analysis algorithm and a support vector machine algorithm based on the Internet of Things are proposed. In the experiment of this article, the scoring items of the expert’s traditional detection system include complex technology, inconvenient use, and incomplete intelligence. Among them, the highest score for complex technology is 8.6 points, the lowest score is 7 points; the highest score for inconvenience is 8.6 points, and the lowest is 8.3 points. It can be seen that related experts believe that the traditional power detection improved system is not only very complicated in technology, very inconvenient to use but also incompletely intelligent. Therefore, it is very necessary to study the system detection equipment based on the Internet of Things.

Urban last-mile express delivery in China encounters several challenges. This paper presents the establishment of a sharing logistics center aimed at enhancing the overall efficiency of urban last-mile express delivery while optimizing the utilization of essential resources. The successful implementation of shared delivery within sharing logistics center necessitates the creation of a robust collaborative mechanism. Recognizing that cooperative benefit allocation is dynamically influenced by factors such as resource input, operational efficiency, risk management, and other cost-related considerations, this study introduces a multi-weight H-Shapley value method for benefit allocation. By conducting empirical analyses of urban last-mile express delivery in Beijing within a sharing logistics service framework, our findings reveal that the revised benefit allocation model better aligns with the interests of participating entities and positively correlates with their contributions. Analyzing the impact of delivery volume and express operational costs changes, it is found that when the delivery volume and express operational costs of the sharing logistics center change, the benefits of participating enterprises move in the same direction. The benefit allocation model established in this study enriches the existing body of research in the field of shared delivery and offers valuable insights for benefit allocation issues that necessitate consideration of the dynamic effects of multiple parameter variations. [ABSTRACT FROM AUTHOR]

Building operations account for a large amount of energy use and CO2 emissions, and the morphology of buildings in residential clusters strongly impacts energy efficiency performance. However, little research has focused on the morphology and energy electricity usage of high-rise residential clusters in hot summer and cold winter (HSCW) regions. We investigated 96 residential clusters in Hangzhou, China, and established a corresponding morphology database. Additionally, we obtained annual electricity consumption for 16 of these residential clusters. With this database, we performed optimization of morphological parameters upon energy use intensity (EUI) using a genetic algorithm (GA). Specifically, the cooling, heating, and lighting EUIs of high-rise residential clusters were studied. After implementing the optimized morphological parameters, there was a reduction of up to 7.73% in EUI. According to regression analysis, the average aspect ratio was the most significant factor influencing EUI (r = −0.907), followed by floor area ratio (r = −0.755), average orientation (r = 0.502), and average number of floors (r = −0.453). These results indicate that a higher intensity of land development with a greater floor area ratio, average aspect ratio, and average number of floors can reduce total energy consumption. Additionally, we found that an average building orientation of southwest 15° (with respect to south) is optimal. The findings of this study can assist urban planners and designers in developing more sustainable residential clusters, leading to decreased energy costs and CO2 emissions. [ABSTRACT FROM AUTHOR]

Background and Aims. The aim of this study was to investigate the association between serum phosphate levels and diabetic retinopathy (DR) in patients with type 2 diabetes mellitus (T2DM). Methods and Results. The study sample consisted of 1657 T2DM patients hospitalized between 2017 and 2019. Patients were categorized into quartiles based on their serum phosphate levels (Q1–Q4). An increasing trend in the prevalence of DR was observed across these quartiles. Subsequently, logistic regression analysis was employed to adjust for potential confounders, such as gender, age, BMI, and duration of diabetes, and to evaluate the odds ratios (ORs) associated with these quartiles. The prevalence of DR showed an increasing trend with elevated serum phosphate levels. Logistic regression further confirmed that serum phosphate levels remain an independent risk factor for DR. Conclusion. Elevated serum phosphate levels are closely associated with the prevalence of DR in hospitalized T2DM patients. Further studies are needed to establish causality. This trial is registered with chiCTR2000032374. [ABSTRACT FROM AUTHOR]

To address the situation that the degraded system cannot be repaired as new and the degradation is accelerated after repair in engineering practice, an imperfect condition-based maintenance model is proposed based on the Gamma process by introducing the maintenance improvement factor and the accelerated degradation factor. The maintenance improvement factor describes the recovery degree of the degradation amount after imperfect maintenance, then gives a quantitative representation method of the system maintenance improvement effect and the determination method of the maximum number of imperfect maintenance. The accelerated degradation factor is combined with the geometric process to describe the accelerated degradation process of the system after imperfect maintenance. The Monte Carlo method is used to determine the optimal number of imperfect preventive maintenance decisions. Through the demonstration of calculation examples, the influence of accelerated degradation factor and maintenance improvement factor on the long-term operation maintenance rate and the optimal number of imperfect maintenance is analyzed. The results show that the model can more comprehensively describe the degradation and maintenance process of degraded systems, and it can effectively reduce maintenance cost ratio under long-term operation. It provides a certain theoretical support for formulating an economical and reasonable maintenance strategy that is more in line with the actual degradation and maintenance process in engineering practice. [ABSTRACT FROM AUTHOR]

To address the challenges faced in the prediction of rolling bearing life, where temporal signals are affected by noise, making fault feature extraction difficult and resulting in low prediction accuracy, a method based on optimal time–frequency spectra and the DenseNet-ALSTM network is proposed. Firstly, a signal reconstruction method is introduced to enhance vibration signals. This involves using the CEEMDAN deconvolution method combined with the Teager energy operator for signal reconstruction, aiming to denoise the signals and highlight fault impacts. Subsequently, a method based on the snake optimizer (SO) is proposed to optimize the generalized S-transform (GST) time–frequency spectra of the enhanced signals, obtaining the optimal time–frequency spectra. Finally, all sample data are transformed into the optimal time–frequency spectrum set and input into the DenseNet-ALSTM network for life prediction. The comparison experiment and ablation experiment show that the proposed method has high prediction accuracy and ideal prediction performance. The optimization terms used in different contexts in this paper are due to different optimization methods, specifically the CEEMDAN method. [ABSTRACT FROM AUTHOR]

Sarcopenia and chronic pain are prevalent among older adults, and despite numerous studies, the potential epidemiological link between the two conditions remains a topic of controversy. Therefore, we performed a comprehensive systematic review and meta-analysis to assess the relationship between chronic pain and sarcopenia in the elderly.Methods: EMBASE, Web of Science, PubMed, and the Cochrane Library were searched through 22 March 2023 with additional manual searches of reference lists of included studies and relevant reviews. We used a random effects model to conduct the meta-analysis and evaluated heterogeneity across studies with Cochran's Q statistic and I2. Subgroup analyses were conducted based on income level, diagnostic criteria for sarcopenia, and pain site.Results: 17 observational studies (33,600 participants, 49% female) were included, of which 6 articles were retrieved for narrative review. The pooled prevalence of sarcopenia and the pooled odds ratios (OR) between chronic pain and sarcopenia were extracted from the remaining 11 studies. The pooled prevalence of sarcopenia among older adults suffering from chronic pain was 0.11 (95% CI, 0.08– 0.18). Our analysis revealed a statistically significant positive association between chronic pain and an increased risk of sarcopenia, yielding a pooled OR of 1.52 (95% CI, 1.31– 1.76). Furthermore, our subgroup analysis demonstrated that the low-income countries group showed a stronger association (OR, 1.73; 95% CI, 1.54– 1.95) between chronic pain and sarcopenia than the high-income countries group (OR, 1.38; 95% CI, 1.20– 1.60).Conclusion: Older adults with chronic pain have a significantly higher prevalence of sarcopenia and risk of developing sarcopenia compared to those without pain. These findings highlight the importance of prioritizing the assessment and early detection of chronic pain in older people, as well as implementing proactive intervention measures in clinical practice. In addition, our results suggest that older people with chronic pain should be actively screened for sarcopenia.Prospero Registration Number: CRD42021239807. [ABSTRACT FROM AUTHOR]

The paper analysed the impact of accessibility of urban parks within the third ring on housing prices of Fuzhou through network analysis and SPSS correlation analysis based on data of sources like remote-sensing image, web crawling and urban road network, discovering that: (1)The density of residence within the third ring of Fuzhou decreases from the centre to the edges; (2) The housing price, ranging between 18000 and 28000 RMB/ m2, peaks in the city centre; (3) For houses within the third ring of Fuzhou, Gulou District enjoys the greatest access to urban parks while Cangshan District is the poorest in this regard. (4) The residence within the third ring of Fuzhou could be rated as A or A- in terms of access to urban parks, with an overall excellence performance; (5) The walking distance to the parks is significantly correlated with the housing price. The shorter the distance, the higher the price. Regarding this, the paper proposed the following suggestions: (1) Revise the routes to Gaogai Mountain Park by increasing entrances and exists to improve its accessibility; (2) Improve the transportation network and increase footpaths to the park, thus shortening the distance between the park and the surrounding residences.