A Novel Approach to Pod Count Estimation Using a Depth Camera in Support of Soybean Breeding Applications.

Improving soybean (Glycine max L. (Merr.)) yield is crucial for strengthening national food security. Predicting soybean yield is essential to maximize the potential of crop varieties. Non-destructive methods are needed to estimate yield before crop maturity. Various approaches, including the pod-count method, have been used to predict soybean yield, but they often face issues with the crop background color. To address this challenge, we explored the application of a depth camera to real-time filtering of RGB images, aiming to enhance the performance of the pod-counting classification model. Additionally, this study aimed to compare object detection models (YOLOV7 and YOLOv7-E6E) and select the most suitable deep learning (DL) model for counting soybean pods. After identifying the best architecture, we conducted a comparative analysis of the model's performance by training the DL model with and without background removal from images. Results demonstrated that removing the background using a depth camera improved YOLOv7's pod detection performance by 10.2% precision, 16.4% recall, 13.8% mAP@50, and 17.7% mAP@0.5:0.95 score compared to when the background was present. Using a depth camera and the YOLOv7 algorithm for pod detection and counting yielded a mAP@0.5 of 93.4% and mAP@0.5:0.95 of 83.9%. These results indicated a significant improvement in the DL model's performance when the background was segmented, and a reasonably larger dataset was used to train YOLOv7.

Predictors of COVID-19 severity and outcomes in Indian patients with rheumatic diseases: a prospective cohort study.

Objective: There is dearth of data regarding the outcomes of coronavirus disease 2019 (COVID-19) among rheumatic and musculoskeletal disease (RMD) patients from Southeast Asia. We report the clinicodemographic profile and identify predictors of COVID-19 outcomes in a large cohort of Indian RMD patients. Methods: This prospective cohort study, carried out at the Postgraduate Institute of Medical Education and Research, Chandigarh (a tertiary care centre in India), included RMD patients affected with COVID-19 between April 2020 and October 2021. Demographic and clinical and laboratory details of COVID-19 and underlying RMD were noted. Predictors of mortality, hospitalization and severe COVID-19 were identified using stepwise multivariable logistic regression. Results: A total of 64 severe acute respiratory syndrome coronavirus-2-infected RMD patients [age 41.5 (19-85) years; 46 (72%) females] were included. Eighteen (28%) patients had severe COVID-19. Twenty-three (36%) required respiratory support [11 (17%) required mechanical ventilation]. Thirty-six (56%) patients required hospitalization [median duration of stay 10 (1-42) days]; 17 (27%) required intensive care unit admission. Presence of co-morbidities [odds ratio (OR) = 4.5 (95% CI: 1.4, 14.7)] was found to be an independent predictor of COVID-19 severity. Co-morbidities [OR = 10.7 (95% CI: 2.5, 45.4)] and underlying lupus [OR = 7.0 (95% CI: 1.2, 40.8)] were independently associated with COVID-19 hospitalization. Ongoing rheumatic disease activity [OR = 6.8 (95% CI: 1.3, 35.4)] and underlying diagnosis of lupus [OR = 7.1 (95% CI: 1.2, 42.4)] and SSc [OR = 9.5 (95% CI: 1.5, 61.8)] were found to be strong independent predictors of mortality. Age, sex, underlying RMD-associated interstitial lung disease and choice of immunosuppressive therapy were not associated with COVID-19 severity or adverse outcomes. Conclusion: The presence of co-morbidities was independently associated with COVID-19 severity and hospitalization. Ongoing rheumatic disease activity and the presence of lupus or SSc independently predicted mortality. Age, sex, type of immunosuppressive therapy and presence of RMD-associated interstitial lung disease did not affect COVID-19 severity or outcomes in Indian RMD patients.

Plasmapheresis in lethal yellow phosphorus poisoning: a scope for recovery.

A 16-year-old girl presented with grade 3 hepatic encephalopathy (HE) following suicide attempt after consuming a lethal dose of yellow phosphorus containing rodenticide. Although she was a candidate for liver transplantation, it could not be done. In the absence of a specific antidote for yellow phosphorus poisoning, the patient was managed conservatively. In addition, low volume-therapeutic plasma exchange (LV-TPE) was initiated, which resulted in a dramatic improvement in HE. Although liver transplantation is the definitive treatment, this case has shown that TPE has a promising role as a 'bridge to recovery' in situations where transplantation is not feasible. We describe our experience with the above-mentioned case, along with the sequence of clinical recovery and the trend in biochemical parameters during follow-up. The patient made a full recovery and is doing well.