Materials Classification Using Multichannel Radiographs

This work aims to validate previous exploratory work done to characterize materials by matching their attenuation profiles using a multichannel radiograph given an initial energy spectrum. The experiment was performed in order to evaluate the effects of noise on the resulting attenuation profiles, which was ignored in simulation. Spectrum measurements have also been collected from various materials of interest. Additionally, a MATLAB optimization algorithm has been applied to these candidate spectrum measurements in order to extract an estimate of the attenuation profile. Being able to characterize materials through this nondestructive method has an extensive range of applications for national security

White-tailed deer hunting and habitat use in Robert Allerton Park

Using Robert Allerton Park (RAP) and the immediately surrounding properties in east-central Illinois as a study site, my objectives were to investigate changes in deer habitat use and spatial clustering following 10 years of deer removal in RAP. I evaluated changes in annual deer counts within RAP’s three main habitat types, dry mesic upland forest, wet mesic floodplain forest and developed land using a generalized linear mixed model. Annual counts were categorized into two periods: no deer removal (1988-2004) and deer removal (2005-2015). Second, I used Moran’s I spatial autocorrelation measures to evaluate annual changes in deer clustering. To evaluate changes in spatial clustering as a result of deer removal, I used Getis-Ord General Gi* hot spot analysis to compare spatial clustering between periods of no removal and removal. As expected, my results indicate that the number of deer removed annually decreased deer count in RAP. When analyzed by period, deer removal affected deer count, however, this impact varied between habitat types. Wet mesic floodplain forest and developed areas experienced insignificant reductions in deer count between periods whereas dry mesic upland forested habitats experienced significant reductions. Moreover, I detected an increasing trend in annual deer clustering across the study area prior to deer removal. Once the removal program was implemented, I observed a decrease in deer clustering across years. Changes were evident in both cluster location and size across the study site between periods. In conclusion, more deer were observed in wet mesic floodplain forest and developed land following removal which could be explained by the deer removal program, preferential habitat selection, temporal changes in understory quality or a combination of these factors

Air quality resolution for health impact assessment: influence of regional characteristics

We evaluate how regional characteristics of population and background pollution might impact the selection of optimal air quality model resolution when calculating the human health impacts of changes to air quality. Using an approach consistent with air quality policy evaluation, we use a regional chemical transport model (CAMx) and a health benefit mapping program (BenMAP) to calculate the human health impacts associated with changes in ozone and fine particulate matter resulting from an emission reduction scenario. We evaluate this same scenario at 36, 12 and 4 km resolution for nine regions in the eastern US representing varied characteristics. We find that the human health benefits associated with changes in ozone concentrations are sensitive to resolution. This finding is especially strong in urban areas where we estimate that benefits calculated using coarse resolution results are on average two times greater than benefits calculated using finer scale results. In three urban areas we analyzed, results calculated using 36 km resolution modeling fell outside the uncertainty range of results calculated using finer scale modeling. In rural areas the influence of resolution is less pronounced with only an 8% increase in the estimated health impacts when using 36 km resolution over finer scales. In contrast, health benefits associated with changes in PM[subscript 2.5] concentrations were not sensitive to resolution and did not follow a pattern based on any regional characteristics evaluated. The largest difference between the health impacts estimated using 36 km modeling results and either 12 or 4 km results was at most ±10% in any region. Several regions showed increases in estimated benefits as resolution increased (opposite the impact seen with ozone modeling), while some regions showed decreases in estimated benefits as resolution increased. In both cases, the dominant contribution was from secondary PM. Additionally, we found that the health impacts calculated using several individual concentration–response functions varied by a larger amount than the impacts calculated using results modeled at different resolutions. Given that changes in PM[subscript 2.5] dominate the human health impacts, and given the uncertainty associated with human health response to changes in air pollution, we conclude that, when estimating the human health benefits associated with decreases in ozone and PM[subscript 2.5] together, the benefits calculated at 36 km resolution agree, within errors, with the benefits calculated using fine (12 km or finer) resolution modeling when using the current methodology for assessing policy decisions.United States. Environmental Protection Agency. Science to Achieve Results Program (Grant R834279)MIT Energy Initiative (Total Energy Fellowship)United States. Dept. of Energy. Office of Science (Grant DE-FG02-94ER61937)Massachusetts Institute of Technology. Joint Program on the Science & Policy of Global Chang

Fisheries Surveys Are Essential Ocean Observing Programs in a Time of Global Change: A Synthesis of Oceanographic and Ecological Data From U.S. West Coast Fisheries Surveys

As climate change and other anthropogenic impacts on marine ecosystems accelerate in the 21st century, there is an increasing need for sustained ocean time series. A robust and collaborative network of regional monitoring programs can detect early signs of unanticipated changes, provide a more holistic understanding of ecosystem responses, and prompt faster management actions. Fisheries-related surveys that collect fisheries-independent data (hereafter referred to as “fisheries surveys”) are a key pillar of sustainable fisheries management and are ubiquitous in the United States and other countries. From the perspective of ocean observing, fisheries surveys offer three key strengths: (1) they are sustained due to largely consistent funding support from federal and state public sector fisheries agencies, (2) they collect paired physical, chemical, and biological data, and (3) they have large and frequently overlapping spatial footprints that extend into the offshore region. Despite this, information about fisheries survey data collection can remain poorly known to the broader academic and ocean observing communities. During the 2019 CalCOFI Symposium, marking the 70th anniversary of the California Cooperative Oceanic Fisheries Investigations (CalCOFI), representatives from 21 ocean monitoring programs on the North American West Coast came together to share the status of their monitoring programs and examine opportunities to leverage efforts to support regional ecosystem management needs. To increase awareness about collected ocean observing data, we catalog these ongoing ocean time series programs and detail the activities of the nine major federal or state fisheries surveys on the U.S. West Coast. We then present three case studies showing how fisheries survey data contribute to the understanding of emergent ecosystem management challenges: marine heatwaves, ocean acidification, and contaminant spills. Moving forward, increased cross-survey analyses and cooperation can improve regional capacity to address emerging challenges. Fisheries surveys represent a foundational blueprint for ecosystem monitoring. As the international community moves toward a global strategy for ocean observing needs, fisheries survey programs should be included as data contributors.publishedVersio

Evaluation of HIV treatment outcomes with reduced frequency of clinical encounters and antiretroviral treatment refills: A systematic review and meta-analysis

BACKGROUND: Global HIV treatment programs have sought to lengthen the interval between clinical encounters for people living with HIV (PLWH) who are established on antiretroviral treatment (ART) to reduce the burden of seeking care and to decongest health facilities. The overall effect of reduced visit frequency on HIV treatment outcomes is however unknown. We conducted a systematic review and meta-analysis to evaluate the effect of implementation strategies that reduce the frequency of clinical appointments and ART refills for PLWH established on ART. METHODS AND FINDINGS: We searched databases​ between 1 January 2010 and 9 November 2021 to identify randomized controlled trials (RCTs) and observational studies that compared reduced (6- to 12-monthly) clinical consultation or ART refill appointment frequency to 3- to 6-monthly appointments for patients established on ART. We assessed methodological quality and real-world relevance, and used Mantel-Haenszel methods to generate pooled risk ratios (RRs) with 95% confidence intervals for retention, viral suppression, and mortality. We evaluated heterogeneity quantitatively and qualitatively, and overall evidence certainty using GRADE. Searches yielded 3,955 records, resulting in 10 studies (6 RCTs, 3 observational studies, and 1 study contributing observational and RCT data) representing 15 intervention arms with 33,599 adults (≥16 years) in 8 sub-Saharan African countries. Reduced frequency clinical consultations occurred at health facilities, while reduced frequency ART refills were delivered through facility or community pharmacies and adherence groups. Studies were highly pragmatic, except for some study settings and resources used in RCTs. Among studies comparing reduced clinical consultation frequency (6- or 12-monthly) to 3-monthly consultations, there appeared to be no difference in retention (RR 1.01, 95% CI 0.97-1.04, p = 0.682, 8 studies, low certainty), and this finding was consistent across 6- and 12-monthly consultation intervals and delivery strategies. Viral suppression effect estimates were markedly influenced by under-ascertainment of viral load outcomes in intervention arms, resulting in inconclusive evidence. There was similarly insufficient evidence to draw conclusions on mortality (RR 1.12, 95% CI 0.75-1.66, p = 0.592, 6 studies, very low certainty). For ART refill frequency, there appeared to be little to no difference in retention (RR 1.01, 95% CI 0.98-1.06, p = 0.473, 4 RCTs, moderate certainty) or mortality (RR 1.45, 95% CI 0.63-3.35, p = 0.382, 4 RCTs, low certainty) between 6-monthly and 3-monthly visits. Similar to the analysis for clinical consultations, although viral suppression appeared to be better in 3-monthly arms, effect estimates were markedly influence by under-ascertainment of viral load outcomes in intervention arms, resulting in overall inclusive evidence. This systematic review was limited by the small number of studies available to compare 12- versus 6-monthly clinical consultations, insufficient data to compare implementation strategies, and lack of evidence for children, key populations, and low- and middle-income countries outside of sub-Saharan Africa. CONCLUSIONS: Based on this synthesis, extending clinical consultation intervals to 6 or 12 months and ART dispensing intervals to 6 months appears to result in similar retention to 3-month intervals, with less robust conclusions for viral suppression and mortality. Future research should ensure complete viral load outcome ascertainment, as well as explore mechanisms of effect, outcomes in other populations, and optimum delivery and monitoring strategies to ensure widespread applicability of reduced frequency visits across settings

Health Benefits, Risks, and Cost-Effectiveness of Influenza Vaccination of Children

Vaccinating children aged 6–23 months, plus all other children at high-risk, will likely be more effective than vaccinating all children against influenza

The scale dependency of trait-based tree neighborhood models

Questions: We asked: (a) whether the strength of conspecific and heterospecific neighborhood crowding effects on focal tree survival and growth vary with neighborhood radii; and (b) if the relative strength of the effect of neighborhood interactions on tree growth and survival varies with neighborhood scale. Location: Luquillo Forest Dynamics Plot, Puerto Rico. Methods: We used tree survival and growth data and included information on species‐mean trait values related to several leaf traits, maximum height, seed mass and wood density. We incorporated a tree neighborhood modeling approach that uses an area around a focal tree with a specified radius, to describe the interactions between a focal tree and its neighbors. We constructed survival and growth models for each functional trait using a Bayesian approach, and varied the size of the radius from 5 m to 30 m, at 5‐m intervals. Results: The results suggested that the estimated effects of conspecific and heterospecific neighbors on tree performance do not vary based on the size of the neighborhood (5–30 m), suggesting that the effects of conspecific and heterospecific neighbors on the performance of a focal tree likely do not vary substantially beyond a neighborhood radius of 5 m in the Luquillo forest. In contrast, the estimated strength of the functional neighborhood (effect of neighbors based on their functional trait values) on tree performance was dependent on the neighborhood range. Our results also suggested that the effects of trait distances and trait hierarchies on tree survival and growth are acting simultaneously and at the same spatial scales. Conclusion: Findings from this study highlight the importance of spatial scale in community assembly processes, and specifically, call for increased attention when selecting the radius that defines the neighborhood around a focal tree as the selected neighborhood radius influences the community patterns discovered, and affects the conclusions about the drivers that control community assembly