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Abstract Background In the near future, the incidence of mosquito-borne diseases may expand to new sites due to changes in temperature and rainfall patterns caused by climate change. Therefore, there is a need to use recent technological advances to improve vector surveillance methodologies. Unoccupied Aerial Vehicles (UAVs), often called drones, have been used to collect high-resolution imagery to map detailed information on mosquito habitats and direct control measures to specific areas. Supervised classification approaches have been largely used to automatically detect vector habitats. However, manual data labelling for model training limits their use for rapid responses. Open-source foundation models such as the Meta AI Segment Anything Model (SAM) can facilitate the manual digitalization of high-resolution images. This pre-trained model can assist in extracting features of interest in a diverse range of images. Here, we evaluated the performance of SAM through the Samgeo package, a Python-based wrapper for geospatial data, as it has not been applied to analyse remote sensing images for epidemiological studies. Results We tested the identification of two land cover classes of interest: water bodies and human settlements, using different UAV acquired imagery across five malaria-endemic areas in Africa, South America, and Southeast Asia. We employed manually placed point prompts and text prompts associated with specific classes of interest to guide the image segmentation and assessed the performance in the different geographic contexts. An average Dice coefficient value of 0.67 was obtained for buildings segmentation and 0.73 for water bodies using point prompts. Regarding the use of text prompts, the highest Dice coefficient value reached 0.72 for buildings and 0.70 for water bodies. Nevertheless, the performance was closely dependent on each object, landscape characteristics and selected words, resulting in varying performance. Conclusions Recent models such as SAM can potentially assist manual digitalization of imagery by vector control programs, quickly identifying key features when surveying an area of interest. However, accurate segmentation still requires user-provided manual prompts and corrections to obtain precise segmentation. Further evaluations are necessary, especially for applications in rural areas.

A soil column experiment was conducted to study the winter wheat growth and yield under effects of different soil wetting (overall wetting, upper part wetting, and lower part wetting) and fertilization (overall fertilization, upper part fertilization, and lower part fertilization). The plant height and leaf area at tillering stage decreased significantly under lower part fertilization, compared with those under upper part and overall soil fertilization, but had no significant differences under different soil wetting. At jointing stage, the plant height was higher when the soil wetting and fertilization were at same location than at different location, manifesting a synergistic coupling effect of water and fertilizer. Lower part soil wetting and lower part fertilization decreased the root-, shoot-, and total dry biomass significantly, upper part fertilization benefited the biomass accumulation of winter wheat, and upper part soil wetting combined with upper part fertilization had an obvious coupling effect on the shoot- and total dry biomass. Soil wetting and fertilization at same location induced a higher ratio of root to shoot, compared with soil wetting and fertilization at different location, and lower part soil wetting resulted in the maximum water use efficiency (WUE), compared with upper part and overall soil wetting. A higher WUE was observed in the soil wetting and fertilization at same location than at different location, but a lower WUE was induced by lower part fertilization. The grain number per spike under upper part and overall soil wetting was increased by 41.7% and 61.9%, respectively, compared with that under lower part soil wetting, and this yield component under upper part and overall soil fertilization was also higher, compared with that under lower part fertilization. Upper part soil wetting and fertilization had an obvious coupling effect of water-fertilizer on the yield and yield components (except for 1000-grain mass). Different soil wetting and fertilization affected the yield mainly through affecting the grain number per spike.

Crop production is an important variable in social, economic and environmental analyses. There is an abundance of crop data available for the United States, but we lack a typology of county-level crop production that accounts for production similarities in counties across the country. We fill this gap with a county-level classification of crop production with ten mutually exclusive categories across the contiguous United States.To create the typology we ran a cluster analysis on acreage data for 21 key crops from the United States Department of Agriculture's 2012 Agricultural Census. Prior to clustering, we estimated undisclosed county acreage values, controlled for acreage in other crop types, and removed counties with low agricultural production to produce proportional scores for each crop type in each county. We used proportional scores to control for the influence of county size in the cluster analysis and used internal and stability measures to validate the analysis. The final dataset features 2922 counties. Future research can leverage this typology as an input for county- or regional-level analysis.

This paper reports a study conducted by students as an independent research project under the mentorship of a research scientist at the National Institute of Education, Singapore. The aim of the study was to explore the relationships between local environmental stressors and physiological responses from the perspective of citizen science. Starting from July 2021, data from EEG headsets were complemented by those obtained from smartwatches (namely heart rate and its variability and body temperature and stress score). Identical units of a wearable device containing environmental sensors (such as ambient temperature, air pressure, infrared radiation, and relative humidity) were designed and worn, respectively, by five adolescents for the same period. More than 100,000 data points of different types—neurological, physiological, and environmental—were eventually collected and were processed through a random forest regression model and deep learning models. The results showed that the most influential microclimatic factors on the biometric indicators were noise and the concentrations of carbon dioxide and dust. Subsequently, more complex inferences were made from the Shapley value interpretation of the regression models. Such findings suggest implications for the design of living conditions with respect to the interaction of the microclimate and human health and comfort.

Pneumonia, a leading cause of childhood mortality, is associated with household air pollution (HAP) exposure. Mechanisms between HAP and pneumonia are poorly understood, but studies suggest that HAP may increase the likelihood of bacterial, instead of viral, pneumonia. We assessed the relationship between HAP and infant microbial nasal carriage among 260 infants participating in the Ghana Randomized Air Pollution and Health Study (GRAPHS).Data are from GRAPHS, a cluster-randomized controlled trial of cookstove interventions (improved biomass or LPG) versus the 3-stone (baseline) cookstove. Infants were surveyed for pneumonia during the first year of life and had routine personal exposure assessments. Nasopharyngeal swabs collected from pneumonia cases (n = 130) and healthy controls (n = 130) were analyzed for presence of 22 common respiratory microbes by MassTag polymerase chain reaction. Data analyses included intention-to-treat (ITT) comparisons of microbial species presence by study arm, and exposure-response relationships.In ITT analyses, 3-stone arm participants had a higher mean number of microbial species than the LPG (LPG: 2.71, 3-stone: 3.34, p < 0.0001, n = 260). This difference was driven by increased bacterial (p < 0.0001) rather than viral species presence (non-significant). Results were pronounced in pneumonia cases and attenuated in healthy controls. Higher prevalence bacterial species were Haemophilus influenzae, Streptococcus pneumoniae, and Moraxella catarrhalis. Exposure-response relationships did not yield significant associations between measured CO and nasal microbial carriage.Our intention-to-treat findings are consistent with a link between HAP and bacterial nasal carriage. No relationships were found for viral carriage. Given the null results in exposure-response analysis, it is likely that a pollutant besides CO is driving these differences.

The perennial shrub guayule (Parthenium argentatum A. Gray) has gained interest as a potential source of natural and hypoallergenic rubber in Southern Europe. Although, native to northern Mexico, it is suited to semi-arid and Mediterranean environments. A research study was conducted in Sardinia (Italy) to evaluate adaptation and biometric traits of introduced guayule lines and to determine the contents and yields of rubber and resin obtainable from its aboveground biomass. Seedlings of the accessions AZ-1, AZ-2, P803, and 11591 were field transplanted in 2015 at two locations of southern, and northern Sardinia, respectively, differing for annual precipitation. Plant survival rate, height and width, trunk diameter, leaf chlorophyll concentration and photosystem photochemical efficiency were monitored. Shoots were harvested at 30 months after transplanting and were partitioned into twigs and remaining stems and its rubber and resin contents were determined. Location markedly affected plant survival rates and biometric traits. Dry matter yield of aboveground components as well as contents of rubber and resin and plant rubber and resin yields differed significantly among accessions under comparison. We found that AZ1 and 11591 were the most successful accessions at southern Sardinia site, whereas 11591 was the only accession exhibiting a satisfactory plant survival rate in the northern location.

Often carrion decomposition studies are conducted using a single carcass or a few carcasses sampled repeatedly through time to reveal trends in succession community composition. Measurements of biomass and other abiotic parameters (e.g., temperature) are often collected on the same carcasses but are rarely a focal point of the studies. This study investigated the effects that repeated sampling during experiments have on the decomposition of carrion, measured as both gross biomass (carcass plus fauna) and net biomass (carcass only), on carcasses disturbed on every visit (with weighing only or also with the collection of fauna) and on carcasses disturbed only once. Each trial lasted at least 21 days, with samples taken in triplicate. Rat carcasses used in this study were placed in the field on the same day and either weighed on every visit or ignored until a given day. Internal and ambient air temperatures were recorded on each carcass at the time of sampling and on undisturbed carcasses using temperature loggers. The presence of succession fauna did not result in significant biomass loss on most days; however, there were individual days early in decomposition (days 3 through 6) when the succession fauna comprised a large portion of the gross biomass. With the exception of biomass loss by the emigration of maggots on days 4 and 5, neither repeated weighing of the carcasses nor repeated weighing and faunal sampling of the carcasses statistically affected the rate of biomass loss. Internal temperatures of carcasses sampled repeatedly were frequently 2-5°C lower than those that had not been disturbed, and ambient temperatures differed significantly depending on the location of measurement device. Results indicate that methods used historically for biomass loss determination in experimental forensic entomology studies are adequate, but further refinements to experimental methodology are desirable.

Food provides energy and nutrients, but its acquisition requires energy expenditure. In post-hunter-gatherer societies, extra-somatic energy has greatly expanded and intensified the catching, gathering, and production of food. Modern relations between energy, food, and health are very complex, raising serious, high-level policy challenges. Together with persistent widespread under-nutrition, over-nutrition (and sedentarism) is causing obesity and associated serious health consequences. Worldwide, agricultural activity, especially livestock production, accounts for about a fifth of total greenhouse-gas emissions, thus contributing to climate change and its adverse health consequences, including the threat to food yields in many regions. Particular policy attention should be paid to the health risks posed by the rapid worldwide growth in meat consumption, both by exacerbating climate change and by directly contributing to certain diseases. To prevent increased greenhouse-gas emissions from this production sector, both the average worldwide consumption level of animal products and the intensity of emissions from livestock production must be reduced. An international contraction and convergence strategy offers a feasible route to such a goal. The current global average meat consumption is 100 g per person per day, with about a ten-fold variation between high-consuming and low-consuming populations. 90 g per day is proposed as a working global target, shared more evenly, with not more than 50 g per day coming from red meat from ruminants (ie, cattle, sheep, goats, and other digastric grazers).