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Deep mastering centered recognition and examination of COVID-19 in chest X-ray photos.
Accurate and precise estimates of ambient air temperatures that can capture fine-scale within-day variability are necessary for studies of air temperature and health.

We developed statistical models to predict temperature at each hour in each cell of a 927-m square grid across the Northeast and Mid-Atlantic United States from 2003 to 2019, across ~4000 meteorological stations from the Integrated Mesonet, using inputs such as elevation, an inverse-distance-weighted interpolation of temperature, and satellite-based vegetation and land surface temperature. We used a rigorous spatial cross-validation scheme and spatially weighted the errors to estimate how well model predictions would generalize to new cell-days. We assess the within-county association of temperature and social vulnerability in a heat wave as an example application.

We found that a model based on the XGBoost machine-learning algorithm was fast and accurate, obtaining weighted root mean square errors (RMSEs) around 1.6K, compared to standard deviations around 11.0K. We found similar accuracy when validating our model on an external dataset from Weather Underground. Assessing predictions from the North American Land Data Assimilation System-2 (NLDAS-2), another hourly model, in the same way, we found it was much less accurate, with RMSEs around 2.5K. This is likely due to the NLDAS-2 model's coarser spatial resolution, and the dynamic variability of temperature within its grid cells. Finally, we demonstrated the health relevance of our model by showing that our temperature estimates were associated with social vulnerability across the region during a heat wave, whereas the NLDAS-2 showed a much weaker association.

Our high spatiotemporal resolution air temperature model provides a strong contribution for future health studies in this region.
Our high spatiotemporal resolution air temperature model provides a strong contribution for future health studies in this region.Wetlands such as rice paddies are important ecosystems that provide habitat for a numerous range of species but are considered as a major source of mercury in the most toxic form of methylmercury. An in situ mesocosm experiment was conducted during the rice cultivation season of 2018 in rice paddies from the Ebro Delta (NE Spain) to investigate the bioaccumulation of mercury in fish. Common goldfish (Carassius auratus) were exposed to three types of rice-fields subject to different agricultural management (conventional or ecological agriculture) and different hydric practices (wet, dry) and were sampled monthly. Total mercury concentration in fish increased over time for almost all the fields under study, but the mercury increase was particularly higher for fish exposed to ecological fields. We conducted δ15N and δ13C measurements to follow up fish diet changes within or among fields. The results have shown there were no variations in the diet of the fish over time within fields, although differences among management practices were observed, which could explain to some extent the THg variation in fish exposed to each of the agricultural practices. Results indicate that wetting and drying rice fields might be a greater source of mercury for fish and a potential hotspot for MeHg production enhanced by physicochemical parameters. Thus, mercury bioaccumulation in fish inhabiting rice paddies depend on several factors what, in turn, could lead to biomagnification across the food webs.The presence of pharmaceutically active compounds in aquatic bodies is a global concern, and suitable treatment technologies are required. In this study, the efficacy of photocatalytic, sonocatalytic, and sonophotocatalytic oxidation processes for the degradation of amoxicillin (AMX) was investigated using visible light with N doped TiO2 (N-TiO2) nanoparticles as the catalyst and low-frequency ultrasound in a novel multifrequency reactor. The influence of different operational parameters on the extent of AMX degradation was studied. Sonophotocatalytic oxidation was found more efficient for AMX degradation when compared to photocatalysis or sonocatalysis alone, and may be due to the reduced bandgap of the catalyst, enhanced cavitation effect due to the presence of the solid catalyst, and improved mass transfer of pollutants. AMX degradation during sono, photo, and sonophotocatalytic oxidation processes was in good agreement with pseudo-first-order kinetics. VH298 datasheet Empirical kinetic models were also developed using multiple linear regression for predicting the degradation efficiency accounting for the operational parameters. Scavenger experiments suggested that •OH radicals largely contributed to AMX degradation, and a plausible mechanism for degradation was proposed. Further, possible degradation pathways for all three treatment processes are also proposed after identifying the degradation products.This paper aims to develop a Box-Behnken experimental design system to optimize the removal process of doxorubicin anticancer drugs. For this goal, Fe3O4/graphene nanoribbons was selected as adsorbent and removal of doxorubicin anticancer drug optimized using Box-Behnken experimental design with a selection of four effective factors. A three-level, four-factor Box-Behnken experimental design was used to assess the relationship between removal percentage as a dependent variable with adsorption weight (0.0015-0.01 mg), pH (3-9), temperature (15-45 °C) and time (1-15 min) as independent variables. Optimized condition by Behnken experimental design (pH = 7.36; time = 15 min; adsorbent weight = 0.01 mg and temperature = 29.26 °C) improved removal of doxorubicin anticancer drug about 99.2% in aqueous solution. The dynamic behavior, adsorption properties and mechanism of doxorubicin molecule on Fe3O4/graphene nanoribbon were investigated based on ab initio molecular dynamics (AIMD) simulations and density functional theory calculations with dispersion corrections. A closer inspection of the adsorption configurations and binding energies revealed that π-π interactions were the driving force when the doxorubicin molecule adsorbed on Fe3O4/graphene nanoribbon. The observed negative adsorption energy signifies a favourable and exothermic adsorption process of the various adsorbate-substrate systems. Besides, AIMD and phonon dispersion calculations confirm the dynamic stability of Fe3O4/graphene nanoribbon.
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