Research on line loss analysis and intelligent diagnosis of abnormal causes in distribution networks: artificial intelligence based method.

The primary source of energy losses in distribution networks (DNs) is rooted in line losses, which is crucial to conduct a thorough and reasonable examination of any unusual sources of line losses to guarantee the power supply in a timely and safe manner. In recent studies, identifying and analyzing abnormal line losses in DNs has been a widely and challenging research subject. This article investigates a key technology for the line loss analyses of DNs and intelligent diagnosis of abnormal causes by implementing artificial intelligence (AI), resulting in several prominent results. The proposed algorithm optimizes the parameters of the support vector machine (SVM) and suggests an intelligent diagnosis algorithm called the Improved Sparrow Search Algorithm and Support Vector Machine (ISSA-SVM). The ISSA-SVM algorithm is trained to calculate the data anomalies of line losses when changing loads and exhibiting exceptional performance to identify abnormal line losses. The accuracy of abnormality identification employing the ISSA-SVM algorithm reaches an impressive 98%, surpassing the performances of other available algorithms. Moreover, the practical performance of the proposed approach for analyzing large volumes of abnormal line loss data daily in DNs is also noteworthy. The ISSA-SVM accurately identifies the root causes of abnormal line losses and lowers the error in calculating abnormal line loss data. By combining different types of power operation data and creating a multidimensional feature traceability model, the study successfully determines the factors contributing to abnormal line losses. The relationship between transformers and voltage among various lines is determined by using the Pearson correlation, which provides valuable insights into the relationship between these variables and line losses. The algorithm's reliability and its potential to be applied to real-world scenarios bring an opportunity to improve the efficiency and safety of power supply systems. The ISSA that incorporates advanced techniques such as the Sobol sequence, golden sine algorithm, and Gaussian difference mutation appears to be a promising tool.

The Efficacy and Safety of Trifluridine/Tipiracil Treatment for Elderly Patients With Metastatic Colorectal Cancer in a Real-world Setting.

BACKGROUND/AIM: Recently, trifluridine/tipiracil (FTD/TPI) treatment was established as a later-line treatment for metastatic colorectal cancer (mCRC). However, FTD/TPI treatment is frequently associated with hematological toxicity. The aim of this study was to evaluate the efficacy and safety of FTD/TPI in elderly patients with mCRC in a real-world setting. PATIENTS AND METHODS: We retrospectively reviewed the medical records of 74 patients with mCRC who were treated with FTD/TPI. RESULTS: The treatment effect of the elderly patient group was not inferior to that of the younger patient group. Although the incidence of hematological toxicity in the elderly patient group was higher than that in the younger patient group, there were no significant differences in the rate of treatment discontinuation due to adverse events between the two groups. CONCLUSION: In elderly patients with mCRC, FTD/TPI treatment was effective for prolonging survival. However, it should be noted that elderly patients showed a higher rate of hematological toxicity than younger patients.

Impact of Intraoperative Blood Loss and Blood Transfusion on the Prognosis of Colorectal Liver Metastasis Following Curative Resection.

BACKGROUND/AIM: The identification of risk factors for recurrence after resection of colorectal liver metastasis is necessary in order to establish a more effective treatment strategy. In addition to well-known prognostic factors, such as the tumor diameter and number of metastatic tumors, a large amount of intraoperative blood loss (IBL) and blood transfusion have recently been reported to be associated with shorter long-term survival. The aim of this study was to assess the impact of IBL and blood transfusion on the prognosis of colorectal liver metastasis after curative resection. PATIENTS AND METHODS: A total of 104 patients who underwent R0 resection for colorectal liver metastasis were enrolled in this study. RESULTS: The high-IBL (>300 ml) group had significantly shorter relapse-free survival after hepatic resection in comparison to the low-IBL (≤300 ml) group (p=0.0025). Patients with blood transfusion had significantly shorter relapse-free survival after hepatic resection in comparison to patients without blood transfusion (p=0.0026). CONCLUSION: A large amount of IBL and blood transfusion may have a negative impact on long-term survival in patients who undergo hepatic resection for colorectal liver metastasis.

A High Postoperative Serum C-reactive Protein Level Has a Negative Impact on Long-term Survival, Regardless of Postoperative Infectious Complications, in Patients Who Undergo Laparoscopic Surgery for Colorectal Cancer.

BACKGROUND/AIM: We previously showed that an elevated postoperative serum C-reactive protein (CRP) level has a negative impact on long-term survival outcomes, regardless of the occurrence of infectious complications in colorectal cancer. However, the cause of postoperative inflammation could not be properly evaluated, because patient background factors, such as the surgical approach (open/laparoscopic), were not unified. PATIENTS AND METHODS: A total of 277 patients who underwent laparoscopic surgery for stage II/III colorectal cancer were enrolled. RESULTS: The high-CRP group had lower relapse-free and overall survival rates in comparison to the low-CRP group. A high postoperative serum CRP level was significantly associated with a larger tumor diameter and longer operation time, and tended to be associated with a higher T stage and larger amount of bleeding. CONCLUSION: Larger tumor volume, longer operation time and larger amount of bleeding were associated with the promotion of postoperative inflammation, which worsened long-term survival outcomes in colorectal cancer.

Patience moderates the class cleavage in demand for redistribution.

Previous studies on class voting have yielded mixed results linking income and demand for redistribution. Why do some poor people oppose redistribution, while some rich people support it? This article argues that an individual's level of patience, an important personal characteristic that influences how people calculate immediate and distinct outcomes, may moderate the effect of class on redistributive preference. In a one-shot game, redistribution between the rich and the poor is zero sum. When people extend their time horizons, however, the poor see the possibility of upward mobility, while the rich emphasize future losses, such as unemployment and economic instability. Consistent with the hypotheses, analyses of the 2014 Cooperative Congressional Election Study and a representative Taiwanese dataset from 2016 reveal a clear class cleavage in demand for redistribution among impatient poor and rich respondents, but the cleavage between their patient counterparts diminished. This pattern of convergence extends previous studies on upward mobility and risk perception theory.