Condition Rating Prediction Using an Interactive Deterioration Model Development Package

This paper presents an advanced method to determine explanatory variables required for developing deterioration models without the interference of human bias. Although a stationary set of explanatory variables is ideal for long-term monitoring and asset management, the penalty regression results vary annually due to the innate bias in the inspection data. In this study, weighting factors were introduced to consider the inspection data collected for several years, and the most stationary set was identified. To manage the substantial amount of inspection data effectively, we proposed a software package referred to as the Deterioration Model Development Package (DMDP). The objective of the DMDP is to provide a convenient platform for users to process and investigate bridge inspection data. Using the standardized data interpretation, the user can update an initial dataset for the deterioration model development when new inspection data are archived. The deterministic method and several stochastic approaches were included for the development of the deterioration models. The performances of the investigated methods were evaluated by estimating the error between the predicted and inspected condition ratings; further, this error was used for estimating the most effective number of explanatory variables for a given number of bridges

Improving Accuracy of Unmanned Aerial System Thermal Infrared Remote Sensing for Use in Energy Balance Models in Agriculture Applications

Unmanned aerial system (UAS) remote sensing has rapidly expanded in recent years, leading to the development of several multispectral and thermal infrared sensors suitable for UAS integration. Remotely sensed thermal infrared imagery has been used to detect crop water stress and manage irrigation by leveraging the increased thermal signatures of water stressed plants. Thermal infrared cameras suitable for UAS remote sensing are often uncooled microbolometers. This type of thermal camera is subject to inaccuracies not typically present in cooled thermal cameras. In addition, atmospheric interference also may present inaccuracies in measuring surface temperature. In this study, a UAS with integrated FLIR Duo Pro R (FDPR) thermal camera was used to collect thermal imagery over a maize and soybean field that contained twelve infrared thermometers (IRT) that measured surface temperature. Surface temperature measurements from the UAS FDPR thermal imagery and field IRTs corrected for emissivity and atmospheric interference were compared to determine accuracy of the FDPR thermal imagery. The comparison of the atmospheric interference corrected UAS FDPR and IRT surface temperature measurements yielded a RMSE of 2.24 degree Celsius and a R2 of 0.85. Additional approaches for correcting UAS FDPR thermal imagery explored linear, second order polynomial and artificial neural network models. These models simplified the process of correcting UAS FDPR thermal imagery. All three models performed well, with the linear model yielding a RMSE of 1.27 degree Celsius and a R2 of 0.93. Laboratory experiments also were completed to test the measurement stability of the FDPR thermal camera over time. These experiments found that the thermal camera required a warm-up period to achieve stability in thermal measurements, with increased warm-up duration likely improving accuracy of thermal measurements

Calibration of a common shortwave multispectral camera system for quantitative agricultural applications

Unmanned aerial systems (UAS) for collecting multispectral imagery of agricultural fields are becoming more affordable and accessible. However, there is need to validate calibration of sensors on these systems when using them for quantitative analyses such as evapotranspiration, and other modeling for agricultural applications. The results of laboratory testing of a MicaSense (Seattle, WA, USA) RedEdge™ 3 multispectral camera and MicaSense Downwelling Light Sensor (irradiance sensor) system using a calibrated integrating sphere were presented. Responses of the camera and irradiance sensor were linear over many light levels and became non-linear at light levels below expected real-world, field conditions. Simple linear corrections should suffice for most light conditions encountered during the growing season. Using an irradiance sensor or similar system may not properly account for light variability in cloudy or partly cloudy conditions as also identified by others. A simple stand for aiding in reference panel imagining was also described, which may facilitate repetitive, consistent reference panel imaging

Unmanned Aerial System-Based Data Ferrying over a Sensor Node Station Network in Maize

© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/)

Comparison of stationary and mobile canopy sensing systems for irrigation management of maize and soybean in Nebraska

Accurate knowledge of plant and field characteristics is crucial for irrigation management. Irrigation can potentially be better managed by utilizing data collected from various sensors installed on different platforms. The accuracy and repeatability of each data source are important considerations when selecting a sensing system suitable for irrigation management. The objective of this study was to compare data from multispectral (red and near-infrared bands) and thermal (long wave thermal infrared band) sensors mounted on different platforms to investigate their comparative usability and accuracy. The different sensor platforms included stationary posts fixed on the ground, the lateral of a center pivot irrigation system, unmanned aircraft systems (UAS), and Planet (PlanetScope multispectral imager, Planet Labs, Inc., San Francisco, Calif.) satellites. The surface reflectance data from multispectral (MS) sensors were used to compute the Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI). The experimental plots were managed with rainfed and irrigated treatments. Irrigation was applied according to a spatial evapotranspiration model informed with Planet satellite imagery. The NDVI and SAVI curves computed from the different sensing systems exhibited similar patterns and were able to capture differences between the rainfed and irrigated treatments when the crops were approaching senescence. Strong correlations were observed for canopy temperature measurements between the stationary and pivot-mounted infrared thermometer (IRT) sensors (p-value of less than 0.01 for the correlations) when canopy were scanned with no irrigation application (dry scans). The best correlation was obtained for the irrigated maize, which yielded r2 of 0.99, RMSE of 0.4°C, and MAE of 0.3°C. The correlation for the canopy temperature data collected during dry scan between UAS and pivot-mounted thermal sensors was weak with r2 = 0.26 to 0.28, larger RMSE values of 3.7°C and MAE values of 3.4°C. Secondary analysis between thermal data from stationary and pivot-mounted IRTs collected during wet scans (during an irrigation event) demonstrated reduced canopy temperature from pivot-mounted IRTs by approximately 2°C for irrigated soybean due to wetting of the canopy by the irrigation. Understanding the performance of these sensor systems is valuable in configuring practical design and operational considerations when using sensor feedback for irrigation management

Examining a staging model for anorexia nervosa: empirical exploration of a four stage model of severity.

Background: An illness staging model for anorexia nervosa (AN) has received increasing attention, but assessing the merits of this concept is dependent on empirically examining a model in clinical samples. Building on preliminary findings regarding the reliability and validity of the Clinician Administered Staging Instrument for Anorexia Nervosa (CASIAN), the current study explores operationalising CASIAN severity scores into stages and assesses their relationship with other clinical features. Method: In women with DSM-IV-R AN and sub-threshold AN (all met AN criteria using DSM 5), receiver operating curve (ROC) analysis (n = 67) assessed the relationship between the sensitivity and specificity of each stage of the CASIAN. Thereafter chi-square and post-hoc adjusted residual analysis provided a preliminary assessment of the validity of the stages comparing the relationship between stage and treatment intensity and AN sub-types, and explored movement between stages after six months (Time 3) in a larger cohort (n = 171). Results: The CASIAN significantly distinguished between milder stages of illness (Stage 1 and 2) versus more severe stages of illness (Stages 3 and 4), and approached statistical significance in distinguishing each of the four stages from one other. CASIAN Stages were significantly associated with treatment modality and primary diagnosis, and CASIAN Stage at Time 1 was significantly associated with Stage at 6 month follow-up. Conclusions: Provisional support is provided for a staging model in AN. Larger studies with longer follow-up of cases are now needed to replicate and extend these findings and evaluate the overall utility of staging as well as optimal staging models

Improving Delivery of Secondary Prophylaxis for Rheumatic Heart Disease in a High-Burden Setting: Outcome of a Stepped-Wedge, Community, Randomized Trial

BACKGROUND Health system strengthening is needed to improve delivery of secondary prophylaxis against rheumatic heart disease. METHODS AND RESULTS We undertook a stepped-wedge, randomized trial in northern Australia. Five pairs of Indigenous community clinics entered the study at 3-month steps. Study phases comprised a 12 month baseline phase, 3 month transition phase, 12 month intensive phase and a 3- to 12-month maintenance phase. Clinics received a multicomponent intervention supporting activities to improve penicillin delivery, aligned with the chronic care model, with continuous quality-improvement feedback on adherence. The primary outcome was the proportion receiving ≥80% of scheduled penicillin injections. Secondary outcomes included "days at risk" of acute rheumatic fever recurrence related to late penicillin and acute rheumatic fever recurrence rates. Overall, 304 patients requiring prophylaxis were eligible. The proportion receiving ≥80% of scheduled injections during baseline was 141 of 304 (46%)-higher than anticipated. No effect attributable to the study was evident: in the intensive phase, 126 of 304 (41%) received ≥80% of scheduled injections (odds ratio compared with baseline: 0.78; 95% confidence interval, 0.54-1.11). There was modest improvement in the maintenance phase among high-adhering patients (43% received ≥90% of injections versus 30% [baseline] and 28% [intensive], P<0.001). Also, the proportion of days at risk in the whole cohort decreased in the maintenance phase (0.28 versus 0.32 [baseline] and 0.34 [intensive], P=0.001). Acute rheumatic fever recurrence rates did not differ between study sites during the intensive phase and the whole jurisdiction (3.0 versus 3.5 recurrences per 100 patient-years, P=0.65). CONCLUSIONS This strategy did not improve adherence to rheumatic heart disease secondary prophylaxis within the study time frame. Longer term primary care strengthening strategies are needed. CLINICAL TRIAL REGISTRATION URL: www.anzctr.org.au. Unique identifier: ACTRN12613000223730

Qualitative Evaluation of a Complex Intervention to Improve Rheumatic Heart Disease Secondary Prophylaxis

BACKGROUND Rheumatic heart disease is a high-burden condition in Australian Aboriginal communities. We evaluated a stepped-wedge, community, randomized trial at 10 Aboriginal communities from 2013 to 2015. A multifaceted intervention was implemented using quality improvement and chronic care model approaches to improve delivery of penicillin prophylaxis for rheumatic heart disease. The trial did not improve penicillin adherence. This mixed-methods evaluation, designed a priori, aimed to determine the association between methodological approaches and outcomes. METHODS AND RESULTS An evaluation framework was developed to measure the success of project implementation and of the underlying program theory. The program theory posited that penicillin delivery would be improved through activities implemented at clinics that addressed elements of the chronic care model. Qualitative data were derived from interviews with health-center staff, informants, and clients; participant observation; and project officer reports. Quantitative data comprised numbers and types of "action items," which were developed by participating clinic staff with project officers to improve delivery of penicillin injections. Interview data from 121 health-center staff, 22 informants, and 72 clients revealed barriers to achieving the trial's aims, including project-level factors (short trial duration), implementation factors (types of activities implemented), and contextual factors (high staff turnover and the complex sociocultural environment). Insufficient actions were implemented addressing "self-management support" and "community linkage" streams of the chronic care model. Increased momentum was evident in later stages of the study. CONCLUSIONS The program theory underpinning the study was sound. The limited impact made by the study on adherence was attributable to complex implementation challenges.This study was funded by the Australian National Health and Medical Research Council (NHMRC) project grant 1027040 and Center of Research Excellence 1080401 and by the Wesfarmers Center for Vaccines and Infectious Diseases at Telethon Kids Institute. Ralph and Maguire are supported by NHMRC fellowships (1142011 and 1046563, respectively)

Event Reconstruction in the PHENIX Central Arm Spectrometers

The central arm spectrometers for the PHENIX experiment at the Relativistic Heavy Ion Collider have been designed for the optimization of particle identification in relativistic heavy ion collisions. The spectrometers present a challenging environment for event reconstruction due to a very high track multiplicity in a complicated, focusing, magnetic field. In order to meet this challenge, nine distinct detector types are integrated for charged particle tracking, momentum reconstruction, and particle identification. The techniques which have been developed for the task of event reconstruction are described.Comment: Accepted for publication in Nucl. Instrum. A. 34 pages, 23 figure

Mental Health of Parents and Life Satisfaction of Children: A Within-Family Analysis of Intergenerational Transmission of Well-Being

This paper addresses the extent to which there is an intergenerational transmission of mental health and subjective well-being within families. Specifically it asks whether parents’ own mental distress influences their child’s life satisfaction, and vice versa. Whilst the evidence on daily contagion of stress and strain between members of the same family is substantial, the evidence on the transmission between parental distress and children’s well-being over a longer period of time is sparse. We tested this idea by examining the within-family transmission of mental distress from parent to child’s life satisfaction, and vice versa, using rich longitudinal data on 1,175 British youths. Results show that parental distress at year t-1 is an important determinant of child’s life satisfaction in the current year. This is true for boys and girls, although boys do not appear to be affected by maternal distress levels. The results also indicated that the child’s own life satisfaction is related with their father’s distress levels in the following year, regardless of the gender of the child. Finally, we examined whether the underlying transmission correlation is due to shared social environment, empathic reactions, or transmission via parent-child interaction