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The article presents an obituary for literature scholar Thomas A. Lathrop.

Cognitive cloud computing in space (3CS) describes a new frontier of space innovation powered by Artificial Intelligence, enabling an explosion of new applications in observing our planet and enabling deep space exploration. In this framework, machine learning (ML) payloads—isolated software capable of extracting high level information from onboard sensors—are key to accomplish this vision. In this work we demonstrate, in a satellite deployed in orbit, a ML payload called 'WorldFloods' that is able to send compressed flood maps from sensed images. In particular, we perform a set of experiments to: (1) compare different segmentation models on different processing variables critical for onboard deployment, (2) show that we can produce, onboard, vectorised polygons delineating the detected flood water from a full Sentinel-2 tile, (3) retrain the model with few images of the onboard sensor downlinked to Earth and (4) demonstrate that this new model can be uplinked to the satellite and run on new images acquired by its camera. Overall our work demonstrates that ML-based models deployed in orbit can be updated if new information is available, paving the way for agile integration of onboard and onground processing and "on the fly" continuous learning. [ABSTRACT FROM AUTHOR]

A preface for the December 2000 issue of the "Journal of Crop Production" is presented.

Abstract Beginning in 2012, NASA used a strategic process to identify broad societal questions, or grand challenges, that are well suited to the aerospace sector and align with national priorities. This effort generated NASA's first grand challenge, the Asteroid Grand Challenge (AGC), a large-scale effort using multidisciplinary collaborations and innovative engagement mechanisms, that focused on finding and addressing asteroid threats to human populations. In April 2010, President Barack Obama announced a mission to send humans to an asteroid by 2025. This resulted in the agency's Asteroid Redirect Mission (ARM) to leverage and maximize existing robotic and human efforts to capture and reroute an asteroid, with the goal of eventual human exploration. The AGC, initiated in 2013, complemented ARM by expanding public participation, partnerships, and other approaches to find, understand, and overcome these potentially harmful asteroids. This article describes a selection of AGC activities implemented from 2013 to 2017 and their results, excluding those conducted by NASA's Near-Earth Object Observations Program and other organizations. The strategic development of the initiative is outlined as well as initial successes, strengths, and weaknesses resulting from the first 4 years of AGC activities and approaches. Finally, we describe lesson learned and areas for continued work and study. The AGC lessons learned and strategies could inform the work of other agencies and organizations seeking to conduct a global scientific investigation with matrixed organizational support, multiple strategic partners, and numerous internal and external open innovation approaches and audiences. [ABSTRACT FROM AUTHOR]

Presents a study which examines the use of the thermodynamics of membranes and the titration calorimetry in the measuring of the enthalpy, partition coefficients, and heat capacity. Efforts to determine the role of the hydrophobic effect; Comparison of the incremental thermodynamic quantities with the model compound data for partitioning into bulk hydrocarbon solvents.

The development and deployment of machine learning systems can be executed easily with modern tools, but the process is typically rushed and means-to-an-end. Lack of diligence can lead to technical debt, scope creep and misaligned objectives, model misuse and failures, and expensive consequences. Engineering systems, on the other hand, follow well-defined processes and testing standards to streamline development for high-quality, reliable results. The extreme is spacecraft systems, with mission critical measures and robustness throughout the process. Drawing on experience in both spacecraft engineering and machine learning (research through product across domain areas), we've developed a proven systems engineering approach for machine learning and artificial intelligence: the Machine Learning Technology Readiness Levels framework defines a principled process to ensure robust, reliable, and responsible systems while being streamlined for machine learning workflows, including key distinctions from traditional software engineering, and a lingua franca for people across teams and organizations to work collaboratively on machine learning and artificial intelligence technologies. Here we describe the framework and elucidate with use-cases from physics research to computer vision apps to medical diagnostics., (© 2022. The Author(s).)

Background: Both maturity and relative age selection biases are entrenched within professional academy soccer programmes. Lay opinion, and that of some scholars, holds that relative age effects exist as a product of advanced biological maturity, that is relatively older players succeed as a consequence of the physical and athletic advantages afforded by earlier maturation. There is, however, a growing body of evidence to suggest that this is not the case, and that relative age and maturation should be considered and treated as independent constructs., Purpose: To avoid a disconnect between contemporary academic evidence and practitioner practice, the aim of this commentary is to provide a discussion of pre-existing and new evidence relating to maturity and relative age selection biases in soccer. It is hoped that this commentary will provide an overview of new insight regarding the differences between the two selection phenomena and enable practitioners who are responsible for the (de)selection of academy soccer players for talent development programmes to make more informed decisions regarding their retention/selection strategies.

Purpose: To investigate the influence of maturation on match running performance in elite male youth soccer players., Methods: A total of 37 elite male youth soccer participants from an English professional soccer academy from the U14s, U15s, and U16s age groups were assessed over the course of 1 competitive playing season (2018-2019). Relative biological maturity was assessed using percentage of predicted adult height. A global positioning system device was used between 2 and 30 (mean = 8 [5]) times on each outfield player. The position of each player in each game was defined as defender, midfielder, or attacker and spine or lateral. A total of 5 match-running metrics were collected total distance covered, high-speed running distance, very high-speed running distance, maximum speed attained, and number of accelerations., Results: Relative biological maturity was positively associated with all global positioning system running metrics for U14s. The U15/16s showed variation in the associations among the global positioning system running metrics against maturity status. A multilevel model which allowed slopes to vary was the best model for all parameters for both age groups. In the U14 age group, advanced maturation was associated with greater high-speed running distance. However, maturation did not contribute toward variance in any of the indices of running performance in the U15/16s. In the U15/16 age group, significance was observed in the spine/lateral playing positions when undertaking actions that required covering distance at high speeds., Conclusions: Maturation appeared to have an impact on match-running metrics within the U14s cohort. However, within the U15/16s, the influence of maturation on match-running metrics appeared to have less of an impact.

Background: Three commonly used non-invasive protocols are implemented to estimate the timing at which PHV most likely occurs. Accurate estimation of circumpubertal years can aid in managing training load of adolescent athletes., Aim: Three protocols were compared against observed age at PHV: an estimate of 13.8 ± 1.0 years - generic age at PHV (from longitudinal measures); an estimate based on the maturity offset equation, predicted age at PHV ±1.0 year; a window of PHV based on 85-96% of predicted adult height at time of observation., Subjects and Methods: A final sample of 23 (from 28) adolescent male participants were selected from the academy of an English Premier League club. Anthropometric measures were collected across five playing seasons; age at PHV was estimated with Super-Imposition by Translation and Rotation (SITAR). The three protocols were compared based on measures at 13.0 years. Results and Conclusions: An age window based on predicted maturity offset did not improve estimation of PHV compared to generic age method; however, the percentage of predicted adult height window showed improvement in performance shown by the following results. Predicted age at PHV correctly assigned 15 participants (65%) as experiencing PHV, while the percentage height correctly assigned 17 participants (74%). Generic age and predicted age at PHV correctly predicted observed age at PHV for 14 participants (61%), percentage of adult height window correctly predicted 22 participants (96%).

Objectives: To determine the effect of reference-based pricing (RBP) on the percentage of lab services utilized by members that were at or below the reference price., Study Design: Retrospective, quasi-experimental, matched, case-control pilot evaluation of an RBP benefit for lab services., Methods: The study group included employees of a multinational grocery chain covered by a national health insurance carrier and subject to RBP for lab services; it had access to an online lab shopping tool and was informed about the RBP benefit through employer communications. The reference group was covered by the same insurance carrier but not subject to RBP. The primary end point was lab compliance, defined as the percentage of lab claims with total charges at or below the reference price. Difference-in-difference regression estimation evaluated changes in lab compliance between the 2 groups., Results: Higher compliance per lab claim was evident for the study group compared with the reference group (69% vs 57%; P<.05). The online shopping tool was used by 7% of the matched-adjusted study group prior to obtaining lab services. Lab compliance was 76% for study group members using the online tool compared with 68% among nonusers who were subject to RBP (P<.01)., Conclusions: RBP can promote cost-conscious selection of lab services. Access to facilities that offer services below the reference price and education about RBP improve compliance. Evaluation of the effect of RBP on higher-cost medical services, including radiology, outpatient specialty, and elective inpatient procedures, is needed.

Refractive index (RI) matching is a unique way of making clear emulsions to meet market trends. However, RI matching has not been sufficiently investigated in terms of physical principles and methodologies. Snell's law (n2 sin r2= n1 sin r1) is applicable to cosmetic emulsions. When oil phase and water phase have equal RI (n2 = n1) values, light will not bend as it strikes obliquely at the emulsion interface. Instead, light is transmitted through the emulsion without refraction, which produces clarity. Theoretical RI values in solution can be calculated with summation of the product of the weight percentage and refractive index of each ingredient (RI(mix) = [W1 x n1 + W2 x n2 + W3 x n3 + + Wn x nn]Wtau). Oil-phase RI values are normally at 1.4 or higher. Glycols are used to adjust the water phase RI, since they typically have larger RI values than water. Noticeable deviations from calculated RI values are seen in experimentally prepared solutions. Three basic deviation types are observed: negative, positive, and slightly negative or positive, which can occur in glycol aqueous solutions at different concentrations. The deviations are attributed to changes in molecular interaction between molecules in solution, which can lead to changes in specific gravity. Negative RI deviation corresponds to a decrease in specific gravity, and positive RI deviation corresponds to an increase in specific gravity. RI values will deviate from calculated values since an increase or decrease in specific gravity leads to a change in optical density.

Sodium cocoyl isethionate (SCI) has been a predominant ingredient in syndet bar formulation for more than thirty years. Although cost effective and well recognized for good skin compatibility, SCI is not regularly found in liquid detergent systems due to its limited solubility in water. This study focuses on the understanding of enthalpy of solubilization, equilibrium of solubilization, and the structures and properties of sodium cocoyl isethionate and various surfactants. The purpose of this exercise is to help the formulator to find appropriate surfactant systems to keep sodium cocoyl isethionate in aqueous solution. The solubility of SCI in water is unfavorable in terms of enthalpy of solvation. When setting up equilibrium of solubilization, there are three possible phases, and three methods have been developed to prevent SCI from recrystallizing in aqueous solutions. The first focuses on tying CI ions within micelles made of secondary surfactants. The second focuses on the exchange of sodium ions with ammonium ions (and/or triethanolammonium). The third centers on emulsification of SCI and the subsequent change of micelles into emulsified oil drops. A combination of two or three of these methods will enable the formulator to use SCI as the primary surfactant in liquid detersive systems.