Publications by authors named "K Surya Mohan Rao"
Despite the significant benefits of aquatic passive sampling (low detection limits and time-weighted average concentrations), the use of passive samplers is impeded by uncertainties, particularly concerning the accuracy of sampling rates. This study employed a systematic evaluation approach based on the combination of meta-analysis and quantitative structure-property relationships (QSPR) models to address these issues. A comprehensive meta-analysis based on extensive data from 298 studies on the Polar Organic Chemical Integrative Sampler (POCIS) identified essential configuration parameters, including the receiving phase (type, mass) and the diffusion-limiting membrane (type, thickness, pore size), as key factors influencing uptake kinetic parameters.
View Article and Find Full Text PDFFP-YOLOv8: Surface Defect Detection Algorithm for Brake Pipe Ends Based on Improved YOLOv8n.
Sensors (Basel)
December 2024
To address the limitations of existing deep learning-based algorithms in detecting surface defects on brake pipe ends, a novel lightweight detection algorithm, FP-YOLOv8, is proposed. This algorithm is developed based on the YOLOv8n framework with the aim of improving accuracy and model lightweight design. First, the C2f_GhostV2 module has been designed to replace the original C2f module.
View Article and Find Full Text PDFArticle Synopsis
- The study examined seasonal and daily changes in soil CO2 flux (Fc) at Kaziranga National Park between November 2019 and March 2020, identifying pre-monsoon as the peak season for carbon release.
- Fc showed strong positive correlations with air and soil temperatures, solar radiation, vapor pressure deficit, and photosynthetically active radiation, indicating these elements significantly influence soil respiration rates.
- Diurnal patterns highlighted higher Fc during daytime hours and lower levels at night, emphasizing how environmental factors affect carbon dynamics in subtropical forests.
Background: Surgery is the best approach to treat endometrial cancer (EC); however, there is currently a deficiency in effective scoring systems for predicting EC recurrence post-surgical resection. This study aims to develop a clinicopathological-inflammatory parameters-based nomogram to accurately predict the postoperative recurrence-free survival (RFS) rate of EC patients.
Methods: A training set containing 1068 patients and an independent validation set consisting of 537 patients were employed in this retrospective study.