Greedy Ensemble Hyperspectral Anomaly Detection.

Hyperspectral images include information from a wide range of spectral bands deemed valuable for computer vision applications in various domains such as agriculture, surveillance, and reconnaissance. Anomaly detection in hyperspectral images has proven to be a crucial component of change and abnormality identification, enabling improved decision-making across various applications. These abnormalities/anomalies can be detected using background estimation techniques that do not require the prior knowledge of outliers. However, each hyperspectral anomaly detection (HS-AD) algorithm models the background differently. These different assumptions may fail to consider all the background constraints in various scenarios. We have developed a new approach called Greedy Ensemble Anomaly Detection (GE-AD) to address this shortcoming. It includes a greedy search algorithm to systematically determine the suitable base models from HS-AD algorithms and hyperspectral unmixing for the first stage of a stacking ensemble and employs a supervised classifier in the second stage of a stacking ensemble. It helps researchers with limited knowledge of the suitability of the HS-AD algorithms for the application scenarios to select the best methods automatically. Our evaluation shows that the proposed method achieves a higher average F1-macro score with statistical significance compared to the other individual methods used in the ensemble. This is validated on multiple datasets, including the Airport-Beach-Urban (ABU) dataset, the San Diego dataset, the Salinas dataset, the Hydice Urban dataset, and the Arizona dataset. The evaluation using the airport scenes from the ABU dataset shows that GE-AD achieves a 14.97% higher average F1-macro score than our previous method (HUE-AD), at least 17.19% higher than the individual methods used in the ensemble, and at least 28.53% higher than the other state-of-the-art ensemble anomaly detection algorithms. As using the combination of greedy algorithm and stacking ensemble to automatically select suitable base models and associated weights have not been widely explored in hyperspectral anomaly detection, we believe that our work will expand the knowledge in this research area and contribute to the wider application of this approach.

Extracorporeal Membrane Oxygenation (ECMO) Use as Supportive Therapy in a Patient With Acute Respiratory Distress Syndrome Due to Rupture of a Pulmonary Hydatid Cyst.

Pulmonary echinococcosis is a parasitic infection that accounts for 20% of the infected cases with echinococcosis. Patients may present after a cyst rupture associated with a variety of complications, including acute respiratory distress syndrome (ARDS). Extracorporeal membrane oxygenation (ECMO) is known as supportive therapy for patients with respiratory and cardiac failure, including ARDS associated with multiple causes. Parasitic infection associated with ARDS due to cyst rupture managed with ECMO as bridging to definitive surgical intervention is documented in two previous case reports only. Here, we are presenting a 21-year-old female with a pulmonary hydatid cyst complicated by ARDS and managed with ECMO.

A combination of generated hydrogen sulfide and nitric oxide activity has a potentiated protectant effect against cisplatin induced nephrotoxicity.

Aim: Hydrogen sulfide and nitricoxide possess cytoprotective activity and in vivo, they are generated from exogenous sodium hydrosulfide and L-arginine respectively. Cisplatin is a major chemotherapeutic agent used to treat cancer and has a high incidence of nephrotoxicity as a side effect. The study aim was to explore the effects of NaHS and L-arginine or their combination on cisplatin induced nephrotoxicity in rats. Methods: Wistar Kyoto rats were given a single intraperitoneal dose of cisplatin (5 mg/kg) followed either by NaHS (56 µmol/kg, i. p.), L-arginine (1.25 g/L in drinking water) or their combination daily for 28-days. Post-mortem plasma, urine and kidney samples were collected for biochemical assays and histopathological analysis. Results: Cisplatin decreased body weights and increased urinary output, while plasma creatinine and urea levels were elevated, but sodium and potassium concentrations were diminished. The renal function parameters, blood urea nitrogen and creatinine clearance, were raised and decreased respectively. Regarding markers of reactive oxygen species, plasma total superoxide dismutase was reduced, whereas malondiadehyde was augmented.Cisplatin also diminished plasma and urinary H2S as well as plasma NO, while NaHS and L-arginine counteracted this activity on both redox-active molecules. Cisplatin cotreatment with NaHS, and/or L-arginine exhibited a reversal of all other measured parameters. Conclusion: In current study, NaHS and L-arginine as monotherapy protected the rats from cisplatin-induced nephrotoxicity but the combination of both worked more effectively suggesting the augmented anti-inflammatory and antioxidative potential of test treatments when administered together.