Global average cooling and Northern Hemisphere winter warming are well‐known climatic responses to the June 15, 1991 eruption of the Mount Pinatubo volcano in the Philippines. Here we investigate the Southern Hemisphere response. Using National Centers for Environmental Prediction/National Center for Atmospheric Research Reanalysis, European Centre for Medium‐Range Weather Forecasting Reanalysis, and simulations with the National Aeronautics and Space Administration Goddard Institute for Space Studies ModelE climate model, we find that, in contrast to the Northern Hemisphere, there were no strong significant anomalies in atmospheric circulation in the Southern Hemisphere. We examined 50 mb and 500 mb circulation patterns, as well as the Southern Hemisphere Annular Mode index, and found no consistent significant anomalies associated with the volcanic eruption, or the previous large volcanic eruptions of the past 50 years, the 1963 Agung and 1982 El Chichón eruptions. The few anomalies that occurred after Pinatubo are consistent with patterns found during an El Niño event, which took place that same year.

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This study explores the efficacy of utilizing a novel ground penetrating radar (GPR) acquisition platform and data analysis methods to quantify peanut yield for breeding selection, agronomic research, and producer management and harvest applications. Sixty plots comprising different peanut market types were scanned with a multichannel, air-launched GPR antenna. Image thresholding analysis was performed on 3D GPR data from four of the channels to extract features that were correlated to peanut yield with the objective of developing a noninvasive high-throughput peanut phenotyping and yield-monitoring methodology. Plot-level GPR data were summarized using mean, standard deviation, sum, and the number of nonzero values (counts) below or above different percentile threshold values. Best results were obtained for data below the percentile threshold for mean, standard deviation and sum. Data both below and above the percentile threshold generated good correlations for count. Correlating individual GPR features to yield generated correlations of up to 39% explained variability, while combining GPR features in multiple linear regression models generated up to 51% explained variability. The correlations increased when regression models were developed separately for each peanut type. This research demonstrates that a systematic search of thresholding range, analysis window size, and data summary statistics is necessary for successful application of this type of analysis. The results also establish that thresholding analysis of GPR data is an appropriate methodology for noninvasive assessment of peanut yield, which could be further developed for high-throughput phenotyping and yield-monitoring, adding a new sensor and new capabilities to the growing set of digital agriculture technologies.

Background We surveyed patients in an adult reconstruction practice as to their use of the Web-based portal provided by our electronic health record, seeking to reveal patterns of use and helpfulness. Methods A total of 150 completed surveys were received. The survey queried demographics, the number of clinic visits, Internet access, portal activation, portal use frequency, and portal information questions and how patients answered them. Helpfulness was rated from 1 (not helpful) to 5 (very helpful). Statistical analysis included bivariate analysis and logistic regression, with odds ratio (OR) and 95% confidence interval (CI) reported. Results The mean age was 67.6 years. Most were females (n = 97, 65.1%). Most (68.7%) patients used the portal. Younger age (OR, 0.94; CI, 0.90-0.99) and access to Internet (OR, 31.8; CI, 8.5-119.4) predicted portal use ( P < .005), whereas gender and number of clinic visits did not ( P > .373). Of all, 47.5% of patients were unclear about online chart information. Older age indicated being unclear of portal information (68.5 vs 66, P = .0002). Of those who clarified doubts regarding information (n = 67), 23 used the Internet (34.3%), 32 (47.7%) called the physician, and 12 (17.9%) asked a friend and/or family member. Most (90.3%) patients felt the portal was helpful in gathering health information. Conclusions Age and Internet access affected portal usage; ability to understand chart information decreased with age. Most patients used the Internet or a family member to clarify doubts regarding portal information. The use of portal data resulted in 32 extra communications to the physician.

Challenges in rapid prototyping are a major bottleneck for plant breeders trying to develop the needed cultivars to feed a growing world population. Remote sensing techniques, particularly LiDAR, have proven useful in the quick phenotyping of many characteristics across a number of popular crops. However, these techniques have not been demonstrated with cassava, a crop of global importance as both a source of starch as well as animal fodder. In this study, we demonstrate the applicability of using terrestrial LiDAR for the determination of cassava biomass through binned height estimations, total aboveground biomass and total leaf biomass. We also tested using single LiDAR scans versus multiple registered scans for estimation, all within a field setting. Our results show that while the binned height does not appear to be an effective method of aboveground phenotyping, terrestrial laser scanners can be a reliable tool in acquiring surface biomass data in cassava. Additionally, we found that using single scans versus multiple scans provides similarly accurate correlations in most cases, which will allow for the 3D phenotyping method to be conducted even more rapidly than expected.

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Background: Obesity rates continue to rise among children and adolescents across the globe. A multicenter research consortium composed of institutions in the Southern US, located in states endemic for childhood obesity, was formed to evaluate the effect of obesity on pediatric musculoskeletal disorders. This study evaluates the effect of body mass index (BMI) percentile and socioeconomic status (SES) on surgical site infections (SSIs) and perioperative complications in patients with adolescent idiopathic scoliosis (AIS) treated with posterior spinal fusion (PSF). Methods: Eleven centers in the Southern US retrospectively reviewed postoperative AIS patients after PSF between 2011 and 2017. Each center contributed data to a centralized database from patients in the following BMI-for-age groups: normal weight (NW, 5th to < 85th percentile), overweight (OW, 85th to < 95th percentile), and obese (OB, ≥ 95th percentile). The primary outcome variable was the occurrence of an SSI. SES was measured by the Area Deprivation Index (ADI), with higher scores indicating a lower SES. Results: Seven hundred fifty-one patients were included in this study (256 NW, 235 OW, and 260 OB). OB and OW patients presented with significantly higher ADIs indicating a lower SES (P < 0.001). In addition, SSI rates were significantly different between BMI groups (0.8% NW, 4.3% OW, and 5.4% OB, P = 0.012). Further analysis showed that superficial and not deep SSIs were significantly different between BMI groups. These differences in SSI rates persisted even while controlling for ADI. Wound dehiscence and readmission rates were significantly different between groups (P = 0.004 and 0.03, respectively), with OB patients demonstrating the highest rates. EBL and cell saver return were significantly higher in overweight patients (P = 0.007 and 0.002, respectively). Conclusion: OB and OW AIS patients have significantly greater superficial SSI rates than NW patients, even after controlling for SES. Level of Evidence: Level III.

Cassava as a world food security crop still suffers from an inadequate means to measure early storage root bulking (ESRB), a trait that describes early maturity and a key characteristic of improved cassava varieties. The objective of this study is to evaluate the capability of ground penetrating radar (GPR) for non-destructive assessment of cassava root biomass. GPR was evaluated for this purpose in a field trial conducted in Ibadan, Nigeria. Different methods of processing the GPR radargram were tested, which included time slicing the radargram below the antenna surface in order to reduce ground clutter; to remove coherent sub-horizontal reflected energy; and having the diffracted energy tail collapsed into representative point of origin. GPR features were then extracted using Discrete Fourier Transformation (DFT), and Bayesian Ridge Regression (BRR) models were developed considering one, two and three-way interactions. Prediction accuracies based on Pearson correlation coefficient (r) and coefficient of determination (R2) were estimated by the linear regression of the predicted and observed root biomass. A simple model without interaction produced the best prediction accuracy of r = 0.64 and R2 = 0.41. Our results demonstrate that root biomass can be predicted using GPR and it is expected that the technology will be adopted by cassava breeding programs for selecting early stage root bulking during the crop growth season as a novel method to dramatically increase crop yield.