The state of the Martian climate

60°N was +2.0°C, relative to the 1981–2010 average value (Fig. 5.1). This marks a new high for the record. The average annual surface air temperature (SAT) anomaly for 2016 for land stations north of starting in 1900, and is a significant increase over the previous highest value of +1.2°C, which was observed in 2007, 2011, and 2015. Average global annual temperatures also showed record values in 2015 and 2016. Currently, the Arctic is warming at more than twice the rate of lower latitudes

Coevolution of machine learning and process-based modelling to revolutionize Earth and environmental sciences: A perspective

Machine learning (ML) applications in Earth and environmental sciences (EES) have gained incredible momentum in recent years. However, these ML applications have largely evolved in ‘isolation’ from the mechanistic, process-based modelling (PBM) paradigms, which have historically been the cornerstone of scientific discovery and policy support. In this perspective, we assert that the cultural barriers between the ML and PBM communities limit the potential of ML, and even its ‘hybridization’ with PBM, for EES applications. Fundamental, but often ignored, differences between ML and PBM are discussed as well as their strengths and weaknesses in light of three overarching modelling objectives in EES, (1) nowcasting and prediction, (2) scenario analysis, and (3) diagnostic learning. The paper ponders over a ‘coevolutionary’ approach to model building, shifting away from a borrowing to a co-creation culture, to develop a generation of models that leverage the unique strengths of ML such as scalability to big data and high-dimensional mapping, while remaining faithful to process-based knowledge base and principles of model explainability and interpretability, and therefore, falsifiability

Coevolution of machine learning and process-based modelling to revolutionize Earth and environmental sciences: A perspective

Machine learning (ML) applications in Earth and environmental sciences (EES) have gained incredible momentum in recent years. However, these ML applications have largely evolved in ‘isolation’ from the mechanistic, process-based modelling (PBM) paradigms, which have historically been the cornerstone of scientific discovery and policy support. In this perspective, we assert that the cultural barriers between the ML and PBM communities limit the potential of ML, and even its ‘hybridization’ with PBM, for EES applications. Fundamental, but often ignored, differences between ML and PBM are discussed as well as their strengths and weaknesses in light of three overarching modelling objectives in EES, (1) nowcasting and prediction, (2) scenario analysis, and (3) diagnostic learning. The paper ponders over a ‘coevolutionary’ approach to model building, shifting away from a borrowing to a co-creation culture, to develop a generation of models that leverage the unique strengths of ML such as scalability to big data and high-dimensional mapping, while remaining faithful to process-based knowledge base and principles of model explainability and interpretability, and therefore, falsifiability.Water Resource

Longitudinal Assessment of Resident Performance Using Entrustable Professional Activities

Question What is the progression of performance for entrustable professional activities (EPAs) throughout pediatric residency training and at graduation? Findings This multisite cohort study of 1987 pediatric residents found that developmental growth curves can be established for EPAs. When generated to reflect the results in this study, at least 90% of trainees achieved the level of unsupervised practice at the end of residency for only 8 of the 17 EPAs studied. Meaning This study suggests that gaps exist between observed practice readiness and standards needed to produce physicians able to meet the health needs of the patient populations they serve based on the general pediatrics EPAs. Importance Entrustable professional activities (EPAs) are an emerging workplace-based, patient-oriented assessment approach with limited empirical evidence. Objective To measure the development of pediatric trainees' clinical skills over time using EPA-based assessment data. Design, Setting, and Participants Prospective cohort study of categorical pediatric residents over 3 academic years (2015-2016, 2016-2017, and 2017-2018) assessed on 17 American Board of Pediatrics EPAs. Residents in training at 23 pediatric residency programs in the Association of Pediatric Program Directors Longitudinal Educational Assessment Research Network were included. Assessment was conducted by clinical competency committee members, who made summative assessment decisions regarding levels of supervision required for each resident and each EPA. Data were collected from May 2016 to November 2018 and analyzed from November to December 2018. Interventions Longitudinal, prospective assessment using EPAs. Main Outcomes and Measures Trajectories of supervision levels by EPA during residency training and how often graduating residents were deemed ready for unsupervised practice in each EPA. Results Across the 5 data collection cycles, 1987 residents from all 3 postgraduate years in 23 residency programs were assigned 25503 supervision level reports for the 17 general pediatrics EPAs. The 4 EPAs that required the most supervision across training were EPA 14 (quality improvement) on the 5-level scale (estimated mean level at graduation, 3.7; 95% CI, 3.6-3.7) and EPAs 8 (transition to adult care; mean, 7.0; 95% CI, 7.0-7.1), 9 (behavioral and mental health; mean, 6.6; 95% CI, 6.5-6.6), and 10 (resuscitate and stabilize; mean, 6.9; 95% CI, 6.8-7.0) on the expanded 5-level scale. At the time of graduation (36 months), the percentage of trainees who were rated at a supervision level corresponding to "unsupervised practice" varied by EPA from 53% to 98%. If performance standards were set to align with 90% of trainees achieving the level of unsupervised practice, this standard would be met for only 8 of the 17 EPAs (although 89% met this standard for EPA 17, performing the common procedures of the general pediatrician). Conclusions and Relevance This study presents initial evidence for empirically derived practice readiness and sets the stage for identifying curricular gaps that contribute to discrepancy between observed practice readiness and standards needed to produce physicians able to meet the health needs of the patient populations they serve. Future work should compare these findings with postgraduation outcomes data as a means of seeking validity evidence. This cohort study measures the development of pediatric resident clinical skills using assessments based on entrustable professional activities

The immunological and virological consequences of planned treatment interruptions in children with HIV infection

Contains fulltext : 126098.pdf (publisher's version ) (Open Access)OBJECTIVES: To evaluate the immunological and viral consequences of planned treatment interruptions (PTI) in children with HIV. DESIGN: This was an immunological and virological sub-study of the Paediatric European Network for Treatment of AIDS (PENTA) 11 trial, which compared CD4-guided PTI of antiretroviral therapy (ART) with continuous therapy (CT) in children. METHODS: HIV-1 RNA and lymphocyte subsets, including CD4 and CD8 cells, were quantified on fresh samples collected during the study; CD45RA, CD45RO and CD31 subpopulations were evaluated in some centres. For 36 (18 PTI, 18 CT) children, immunophenotyping was performed and cell-associated HIV-1 DNA analysed on stored samples to 48 weeks. RESULTS: In the PTI group, CD4 cell count fell rapidly in the first 12 weeks off ART, with decreases in both naive and memory cells. However, the proportion of CD4 cells expressing CD45RA and CD45RO remained constant in both groups. The increase in CD8 cells in the first 12 weeks off ART in the PTI group was predominantly due to increases in RO-expressing cells. PTI was associated with a rapid and sustained increase in CD4 cells expressing Ki67 and HLA-DR, and increased levels of HIV-1 DNA. CONCLUSIONS: PTI in children is associated with rapid changes in CD4 and CD8 cells, likely due to increased cell turnover and immune activation. However, children off treatment may be able to maintain stable levels of naive CD4 cells, at least in proportion to the memory cell pool, which may in part explain the observed excellent CD4 cell recovery with re-introduction of ART