Keiththrane0417

The atmospheric products of the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm include column water vapor (CWV) at a 1 km resolution, derived from daily overpasses of NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard the Aqua and Terra satellites. We have recently shown that machine learning using extreme gradient boosting (XGBoost) can improve the estimation of MAIAC aerosol optical depth (AOD). Although MAIAC CWV is generally well validated (Pearson's R >0.97 versus CWV from AERONET sun photometers), it has not yet been assessed whether machine-learning approaches can further improve CWV. Using a novel spatiotemporal cross-validation approach to avoid overfitting, our XGBoost model, with nine features derived from land use terms, date, and ancillary variables from the MAIAC retrieval, quantifies and can correct a substantial portion of measurement error relative to collocated measurements at AERONET sites (26.9% and 16.5% decrease in root mean square error (RMSE) for Terra and Aqua datasets, respectively) in the Northeastern USA, 2000-2015. We use machine-learning interpretation tools to illustrate complex patterns of measurement error and describe a positive bias in MAIAC Terra CWV worsening in recent summertime conditions. We validate our predictive model on MAIAC CWV estimates at independent stations from the SuomiNet GPS network where our corrections decrease the RMSE by 19.7% and 9.5% for Terra and Aqua MAIAC CWV. Empirically correcting for measurement error with machine-learning algorithms is a postprocessing opportunity to improve satellite-derived CWV data for Earth science and remote sensing applications.Mantle cell lymphoma (MCL) is a clinically heterogeneous B cell malignancy for which a variety of prognostic factors have been proposed. Previously, a digital gene expression profiling "proliferation signature" capable of risk stratifying MCL was identified and subsequently developed into a multi-analyte prognostic assay, known as the "MCL35" assay. In this study, we sought to explore the performance characteristics of the MCL35 assay in a clinical laboratory and compare results with the Ki67 proliferation marker. The results describe the clinical validation of the MCL35 assay for molecular risk stratification of MCL including accuracy, sensitivity, specificity, use in acid-decalcified bone marrow core biopsies, fixatives, lower limit of RNA input, quality metrics, and other laboratory parameters. The resulting data indicate that this is a robust technique with outstanding reproducibility. Overall, the data support the concept of molecular signatures, as assessed with digital gene expression profiling, for improved standardization and reproducibility for proliferation assessment in MCL.The crisis caused by COVID-19 has affected research in a variety of ways. As far as research on sustainable development is concerned, the lockdown has significantly disrupted the usual communication channels and, among other things, has led to the cancellation of meetings and long-planned events. It has also led to delay in the delivery of research projects. There is a gap in the literature in regards to how a global crisis influences sustainability research. Therefore, this ground-breaking paper undertakes an analysis of the extent to which COVID-19 as a whole, and the lockdown in particular, has influenced sustainability research, and it outlines the solutions pursued by researchers around the world to overcome the many challenges they have experienced. This paper also outlines some measures that may be implemented in the future to take more advantage of existing technologies that support research on sustainable development.Climate change and coronavirus pandemic are the twin crises in the Anthropocene, the era in which unsustainable growth of human activities has led to a significant change in the global environment. The two crises have also exposed a chronic social illness of our time-a deep, widespread inequality in society. Whilst the circumstances are unfortunate, the pandemic can provide an opportunity for sustainability scientists to focus more on human society and its inequalities, rather than a sole focus on the natural environment. It opens the way for a new normative commitment of science in a time of crises. We suggest three agendas for future climate and sustainability research after the pandemic (1) focus on health and well-being, (2) moral engagement through empathy, and (3) science of loss for managing grief.Background To evaluate the patterns of recurrence and survival related to deep stromal invasion (DSI) in cervical cancer patients who underwent the radical surgery. Methods Patients with International Federation of Gynaecology and Obstetrics (FIGO) 2009 stage IB and IIA and definite pathology-confirmed deep stromal invasion between 03/2006 and 06/2014 were collected. A subcategorization of deep stromal invasion (inner full-thickness, full-thickness and outer full-thickness) were performed. Disease-free survival (DFS) and overall survival (OS) were compared by Kaplan-Meier analysis and independent predictors were identified using Cox regression analysis. Results A total of 3,298 cervical cancer patients were included. The proportion of patients with outer 1/3 to full-thickness invasion, full-thickness invasion and outer-full-thickness invasion were 60.6%, 33.5% and 5.9%, respectively. click here Deep stromal invasion strongly correlated with patients' age, stage, menopause status, tumor diameter, lymphovascular space invasion (LVSI), nodal metastasis, parametrial and vaginal involvement, as well as the site of recurrence. However, no connection was found between the DSI and tumor histologic type. Upon further analysis, patients with full- and outer-full-thickness invasion exhibited significantly higher recurrence rates compared to inner full-thickness group. Both DFS and OS was independently associated with the depth of deep stromal invasion. By subgroup analysis, multivariate analysis revealed that only adjuvant radiotherapy was independent risk factors for both DFS and OS in isolated full-thickness invasion patients. Conclusions This study indicated that the depth of deep stromal invasion is an important prognostic factor in patients with cervical cancer. Patients with full-thickness invasion should receive customized adjuvant treatment.