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The role of load modeling in power systems is crucial for both operational and regulatory considerations. It is essential to develop an effective and reliable method for optimizing load modeling parameter identification. In this paper, the dung beetle algorithm is improved by using the good point set, and a load model parameter identification strategy based on the good point set dung beetle optimization algorithm (GDBO) within the framework of the measurement-based load modeling method. The proposed parameter identification strategy involves utilizing PMU voltage data as input, selecting a comprehensive load model, and refining the initialization process based on the good point set to mitigate the influence of local maxima. Through iterative optimization of the objective function using the Dung Beetle Optimizer (DBO) algorithm, the optimal parameters for the comprehensive load model are determined, enhancing the model’s ability to accurately capture the power curve. Analysis of examples pertaining to PMU-measured modeling parameter identification reveals that the proposed GDBO algorithm, which incorporates a good point set, outperforms alternative methods such as the improved differential evolution algorithm (IDE), particle swarm optimization algorithm (PSO), grey wolf optimization algorithm (GWO), and conventional DBO algorithm. This demonstrates the superior performance of the introduced approach in the context of load model parameter identification.

Intravesical instillation of Bacillus Calmette-Guérin has been used as an immunotherapy to treat superficial bladder cancer for almost half a century. In recent years, the approval of several monoclonal antibody treatments has transformed the treatment landscape for patients with muscle-invasive or metastatic uroepithelial carcinoma. The purpose of this study was to conduct a thorough review of immunotherapy in bladder cancer through a bibliometric approach. Publications related to bladder cancer immunotherapy were obtained from the Web of Science Core Collection on July 1st, 2022. We conducted a bibliometric analysis of literature information using CiteSpace IV, VOSviewer, and Scimago Graphica, including co-authorship or co-citation of authors, countries/regions, journals, references, and keyword co-occurrence. There was a total of 2,352 papers included, with the most contributions coming from the United States, China, and Italy. The United States had the highest H-index value and was the leading country in this field. Meanwhile, the number of publications in China was steadily growing. The top three productive researchers were Kamat AM, Necchi A, and Shariat SF, with Powles T as the top co-cited author. Most papers were published by the University of Texas System. The majority of papers in this field were published in Urologic Oncology Seminars and Original Investigations and European Urology was the most influential journal with the highest H-index. The tumor microenvironment and complete molecular characterization may still be the frontier in this research area, allowing us to obtain a better understanding of the pathogenesis and clinical prognosis of bladder cancer. More research are conducted to identify clinically meaningful biomarkers that may provide opportunities for the personalization of bladder cancer therapy. This study provides clinicians and researchers with an overview and helpful guidance on how to choose the research direction and management of bladder cancer immunotherapy.

The repetition of a stimulus often produces a shorter subjective duration than does the presentation of a novel item. To test whether familiarity mediates the repetition compression effect, the present study compared the influence of repeated words and pseudowords on apparent duration, using a duration discrimination task. We found a similar magnitude of temporal compression for the repeated-word and repeated-pseudoword conditions. When introducing a further experiment with two new conditions in which the standard–comparison pair shared a character at the first or second constituent position, we observed a shorter subjective duration for whole word (or whole pseudoword) repetition compared with the remaining conditions (i.e., first-character repetition, second-character repetition, and novel baseline). However, temporal compression for the first- and second-character repetitions was observed only for pseudowords but not for words. Our findings indicate that familiarity modulates the perception of duration in constituent character repetition. The results are discussed on the basis of the predictive coding theory.