On Nucleation Pathways and Particle Size Distribution Evolutions in Stratospheric Aircraft Exhaust Plumes with H2SO4 Enhancement.

Stratospheric aerosol injection (SAI) is proposed as a means of reducing global warming and climate change impacts. Similar to aerosol enhancements produced by volcanic eruptions, introducing particles into the stratosphere would reflect sunlight and reduce the level of warming. However, uncertainties remain about the roles of nucleation mechanisms, ionized molecules, impurities (unevaporated residuals of injected precursors), and ambient conditions in the generation of SAI particles optimally sized to reflect sunlight. Here, we use a kinetic ion-mediated and homogeneous nucleation model to study the formation of H2SO4 particles in aircraft exhaust plumes with direct injection of H2SO4 vapor. We find that under the conditions that produce particles of desired sizes (diameter ∼200-300 nm), nucleation occurs in the nascent (t < 0.01 s), hot (T = 360-445 K), and dry (RH = 0.01-0.1%) plume and is predominantly unary. Nucleation on chemiions occurs first, followed by neutral new particle formation, which converts most of the injected H2SO4 vapor to particles. Coagulation in the aging and diluting plumes governs the subsequent evolution to a narrow (σg = 1.3) particle size distribution. Scavenging by exhaust soot is negligible, but scavenging by acid impurities or incomplete H2SO4 evaporation in the hot exhaust plume and enhanced background aerosols can matter. This research highlights the need to obtain laboratory and/or real-world experiment data to verify the model prediction.

Development of natural dye photosensitizers for dye-sensitized solar cells: a review.

Dye-sensitized solar cell (DSSC) is a photovoltaic device that can be produced from natural source pigments or natural dyes. The selection of natural dyes for DSSC application is currently under research. The utilization of natural dye materials that are easy to obtain, cost-effective, and non-toxic can reduce waste during DSSC fabrication. Natural dyes can be extracted from plants through extraction and chromatography methods. The suitability and viability of utilizing natural dyes as photosensitizers in DSSCs can be predicted using appropriate software simulation by varying related parameters to produce high power conversion efficiency. In this context, the purpose of the review is to highlight the evolution of performance improvement in the development of DSSCs with consideration of natural dye extraction and software simulation. This review also focuses on the results of extracting natural dyes from herbal ingredients, which are still very limited in information, and several parts of herbal plants that can be used as natural dye sources in the future of solid-state DSSCs have been identified. Based on the results of this review, the highest efficiency was obtained for the DSSC that used chlorophyll pigments as natural dyes using Peltophorum pterocarpum leaves with 6.07%, followed by anthocyanin pigments as natural dyes using raspberries (black) fruits with 1.5%, flavonoid pigments as natural dyes using Curcuma longa herbs with 0.64%, and flavonoid pigments as natural dyes using Indigofera tinctoria flowers with 0.46%.

Validation of a 3D Local-Scale Adaptive Solar Radiation Model by Using Pyranometer Measurements and a High-Resolution Digital Elevation Model.

The result of the multidisciplinary collaboration of researchers from different areas of knowledge to validate a solar radiation model is presented. The MAPsol is a 3D local-scale adaptive solar radiation model that allows us to estimate direct, diffuse, and reflected irradiance for clear sky conditions. The model includes the adaptation of the mesh to complex orography and albedo, and considers the shadows cast by the terrain and buildings. The surface mesh generation is based on surface refinement, smoothing and parameterization techniques and allows the generation of high-quality adapted meshes with a reasonable number of elements. Another key aspect of the paper is the generation of a high-resolution digital elevation model (DEM). This high-resolution DEM is constructed from LiDAR data, and its resolution is two times more accurate than the publicly available DEMs. The validation process uses direct and global solar irradiance data obtained from pyranometers at the University of Salamanca located in an urban area affected by systematic shading from nearby buildings. This work provides an efficient protocol for studying solar resources, with particular emphasis on areas of complex orography and dense buildings where shadows can potentially make solar energy production facilities less efficient.

The impact of meteorological factors on tuberculosis incidence in Spain: a spatiotemporal analysis.

Tuberculosis (TB) remains a global leading cause of death, necessitating an investigation into its unequal distribution. Sun exposure, linked to vitamin D (VD) synthesis, has been proposed as a protective factor. This study aimed to analyse TB rates in Spain over time and space and explore their relationship with sunlight exposure. An ecological study examined the associations between rainfall, sunshine hours, and TB incidence in Spain. Data from the National Epidemiological Surveillance Network (RENAVE in Spanish) and the Spanish Meteorological Agency (AEMET in Spanish) from 2012 to 2020 were utilized. Correlation and spatial regression analyses were conducted. Between 2012 and 2020, 43,419 non-imported TB cases were reported. A geographic pattern (north-south) and distinct seasonality (spring peaks and autumn troughs) were observed. Sunshine hours and rainfall displayed a strong negative correlation. Spatial regression and seasonal models identified a negative correlation between TB incidence and sunshine hours, with a four-month lag. A clear spatiotemporal association between TB incidence and sunshine hours emerged in Spain from 2012 to 2020. VD levels likely mediate this relationship, being influenced by sunlight exposure and TB development. Further research is warranted to elucidate the causal pathway and inform public health strategies for improved TB control.

Innovative enhancement of electron tunneling synergy in carbon-doped Ta2O5CuO photocatalyst with nematic liquid crystal for safe drinking water.

This study focuses on enhancing the photocatalytic properties of carbon-doped Ta2O5CuO (C-Ta2O5CuO) nanocomposites for drinking water purification. The nanocomposites were fabricated by depositing C-Ta2O5CuO onto Nematic Liquid Crystal Polaroid (NLCP) obtained from a discarded laptop monitor, employing the sputter deposition method. The X-ray diffraction (XRD) and High-resolution transmission electron microscopy (HRTEM) determined the nanocomposite thin films' crystallinity and structural properties. The EDX and XPS analyses confirmed the elemental composition and reality of the Cu-incorporated Ta2O5 nanocomposites, respectively. The combination of electron tunneling enhancement provided by the NLCP and graphitic carbon led to exceptional photocatalytic performance. This was particularly evident in the efficient degradation of P-Rosaniline Hydrochloride (PRH) dye in an aqueous medium. C-Ta2O5CuO catalytic activities were estimated at various dye concentrations, repeatability, reusability with time, and kinetics. Coating's stability and long-term activity in photocatalysis reactions were also tested. Additionally, Cu present in the C-Ta2O5CuO and ˙OH radicals exhibited remarkable bactericidal activity. They displayed significant antibacterial efficacy against both gram-positive Escherichia coli (E. coli) and gram-negative Staphylococcus aureus (S. aureus) bacteria. These findings have significant implications for the development of advanced materials with potent photocatalytic and antibacterial properties, holding promise for improving drinking water quality and addressing environmental and health challenges.

Actors, legitimacy, and governance challenges facing negative emissions and solar geoengineering technologies.

Institutional theory, behavioral science, sociology and even political science all emphasize the importance of actors in achieving social change. Despite this salience, the actors involved in researching, promoting, or deploying negative emissions and solar geoengineering technologies remain underexplored within the literature. In this study, based on a rigorous sample of semi-structured expert interviews (N = 125), we empirically explore the types of actors and groups associated with both negative emissions and solar geoengineering research and deployment. We investigate emergent knowledge networks and patterns of involvement across space and scale. We examine actors in terms of their support of, opposition to, or ambiguity regarding both types of climate interventions. We reveal incipient and perhaps unforeseen collections of actors; determine which sorts of actors are associated with different technology pathways to comprehend the locations of actor groups and potential patterns of elitism; and assess relative degrees of social acceptance, legitimacy, and governance.

Optimal placement and operation of soft open points, capacitors, and renewable distributed generators in distribution power networks to reduce total one-year energy loss.

The paper optimizes the placement of soft open points (SOPs) devices, shunt capacitor banks (SCBs), and distributed generators (DGs) in the IEEE 69-node distribution power grid for reducing the power loss of a single hour and total energy losses of one year. EO is proven to be more effective than previous methods and three other applied algorithms, including the Coot optimization algorithm (COOT), Modified weight inertia factor and modified acceleration coefficients-based particle swarm optimization (CFPSO), and Tunicate swarm algorithm (TSA). So, EO is applied for the last case considering one SOPs, one wind turbine (WT), two solar photovoltaic systems (PVs), and two SCBs over one year with twelve months and 24 h each month. The study reaches the smallest power loss compared to previous studies in the first case with one SOPs device. The results from the second to the fourth cases indicate that the power grid needs the placement of SCBs and DGs first and SOPs devices to reach the lowest power loss. Case 5 indicates that the hybrid system with one WT and two PVs suffers higher power losses than the base system at hours with high generation from renewable sources; however, integrating the SOPs and SCBs into the hybrid system can reach smaller losses than the base system at these hours. Thus, using SOPs and SCBs in integrated distribution power grids with renewable energies can greatly benefit energy loss reduction.

Performance optimization of energy-efficient solar absorbers for thermal energy harvesting in modern industrial environments using a solar deep learning model.

Thermal energy harvesting has seen a rise in popularity in recent years due to its potential to generate renewable energy from the sun. One of the key components of this process is the solar absorber, which is responsible for converting solar radiation into thermal energy. In this paper, a smart performance optimization of energy efficient solar absorber for thermal energy harvesting is proposed for modern industrial environments using solar deep learning model. In this model, data is collected from multiple sensors over time that measure various environmental factors such as temperature, humidity, wind speed, atmospheric pressure, and solar radiation. This data is then used to train a machine learning algorithm to make predictions on how much thermal energy can be harvested from a particular panel or system. In a computational range, the proposed solar deep learning model (SDLM) reached 83.22 % of testing and 91.72 % of training results of false positive absorption rate, 69.88 % of testing and 81.48 % of training results of false absorption discovery rate, 81.40 % of testing and 72.08 % of training results of false absorption omission rate, 75.04 % of testing and 73.19 % of training results of absorbance prevalence threshold, and 90.81 % of testing and 78.09 % of training results of critical success index. The model also incorporates components such as insulation and orientation to further improve its accuracy in predicting the amount of thermal energy that can be harvested. Solar absorbers are used in industrial environments to absorb the sun's radiation and turn it into thermal energy. This thermal energy can then be used to power things such as heating and cooling systems, air compressors, and even some types of manufacturing operations. By using a solar deep learning model, businesses can accurately predict how much thermal energy can be harvested from a particular solar absorber before making an investment in a system.

Effects of meteorological factors and groundwater depths on sap flow density of Populus euphratica in a desert oasis, Taklamakan Desert, China.

Accurate estimation of desert vegetation transpiration is key to regulating desert water resources of desert ecosystems. Sap flow density (SFD) can indirectly reflect a tree's transpiration consumption, and it has been affected by climate warming and groundwater depths in desert ecosystems. Sap flow responses to meteorological conditions and groundwater depths are further affected by tree of different sizes. However, how meteorological factors and groundwater depths affects tree sap flow among tree sizes remains poorly understand. In this study, a 50 × 50 m P. euphratica stand was selected as a sample plot in the hinterland of the Taklamakan Desert, and the SFD of P. euphratica of different sizes was measured continuously using the thermal diffusion technique from May to October of 2021 and 2022. The results showed that SFD of large P. euphratica was consistently higher than that of small P. euphratica in 2021 and 2022. and the SFD of P. euphratica was significantly and positively correlated with solar radiation (Rad) and vapor pressure deficit (VPD), and the correlation was higher than that of the air temperature (Ta) and relative humidity (RH), and also showed a strong non-linear relationship. Analysis of the hour-by-hour relationship between P. euphratica SFD and VPD and Rad showed a strong hysteresis. Throughout the growing season, there was no significant relationship between SFD of P. euphratica and groundwater depth, VPD and Rad were still the main controlling factors of SFD in different groundwater depths. However, during the period of relative groundwater deficit, the effect of groundwater depth on the SFD of P. euphratica increased, and the small P. euphratica was more sensitive, indicating that the small P. euphratica was more susceptible to groundwater changes. This study emphasized that Rad and VPD were the main drivers of SFD during the growing season, as well as differences in the response of different sizes of P. euphratica to groundwater changes. The results of the study provide a scientific basis for future modeling of transpiration consumption in P. euphratica forests in desert oases, as well as the regulation and allocation of water resources.

Even cooler insights: On the power of forests to (water the Earth and) cool the planet.

Scientific innovation is overturning conventional paradigms of forest, water, and energy cycle interactions. This has implications for our understanding of the principal causal pathways by which tree, forest, and vegetation cover (TFVC) influence local and global warming/cooling. Many identify surface albedo and carbon sequestration as the principal causal pathways by which TFVC affects global warming/cooling. Moving toward the outer latitudes, in particular, where snow cover is more important, surface albedo effects are perceived to overpower carbon sequestration. By raising surface albedo, deforestation is thus predicted to lead to surface cooling, while increasing forest cover is assumed to result in warming. Observational data, however, generally support the opposite conclusion, suggesting surface albedo is poorly understood. Most accept that surface temperatures are influenced by the interplay of surface albedo, incoming shortwave (SW) radiation, and the partitioning of the remaining, post-albedo, SW radiation into latent and sensible heat. However, the extent to which the avoidance of sensible heat formation is first and foremost mediated by the presence (absence) of water and TFVC is not well understood. TFVC both mediates the availability of water on the land surface and drives the potential for latent heat production (evapotranspiration, ET). While latent heat is more directly linked to local than global cooling/warming, it is driven by photosynthesis and carbon sequestration and powers additional cloud formation and top-of-cloud reflectivity, both of which drive global cooling. TFVC loss reduces water storage, precipitation recycling, and downwind rainfall potential, thus driving the reduction of both ET (latent heat) and cloud formation. By reducing latent heat, cloud formation, and precipitation, deforestation thus powers warming (sensible heat formation), which further diminishes TFVC growth (carbon sequestration). Large-scale tree and forest restoration could, therefore, contribute significantly to both global and surface temperature cooling through the principal causal pathways of carbon sequestration and cloud formation.

Functional interactions between coat structure and colour in the determination of solar heat load on arid living kangaroos in summer: balancing crypsis and thermoregulation.

Interactions of solar radiation with mammal fur are complex. Reflection of radiation in the visible spectrum provides colour that has various roles, including sexual display and crypsis, i.e., camouflage. Radiation that is absorbed by a fur coat is converted to heat, a proportion of which impacts on the skin. Not all absorption occurs at the coat surface, and some radiation penetrates the coat before being absorbed, particularly in lighter coats. In studies on this phenomenon in kangaroos, we found that two arid zone species with the thinnest coats had similar effective heat load, despite markedly different solar reflectances. These kangaroos were Red Kangaroos (Osphranter rufus) and Western Grey Kangaroos (Macropus fuliginosus).Here we examine the connections between heat flow patterns associated with solar radiation, and the physical structure of these coats. Also noted are the impacts of changing wind speed. The modulation of solar radiation and resultant heat flows in these coats were measured at wind speeds from 1 to 10 m s-1 by mounting them on a heat flux transducer/temperature-controlled plate apparatus in a wind tunnel. A lamp with a spectrum like solar radiation was used as a proxy for the sun. The integrated reflectance across the solar spectrum was higher in the red kangaroos (40 ± 2%) than in the grey kangaroos (28 ± 1%). Fur depth and insulation were not different between the two species, but differences occurred in fibre structure, notably in fibre length, fibre density and fibre shape. Patterns of heat flux within the species' coats occurred despite no overall difference in effective solar heat load. We consider that an overarching need for crypsis, particularly for the more open desert-adapted red kangaroo, has led to the complex adaptations that retard the penetrance of solar radiation into its more reflective fur.

A multilayer perceptron neural network approach for optimizing solar irradiance forecasting in Central Africa with meteorological insights.

Promoting renewable energy sources, particularly in the solar industry, has the potential to address the energy shortfall in Central Africa. Nevertheless, a difficulty occurs due to the erratic characteristics of solar irradiance data, which is influenced by climatic fluctuations and challenging to regulate. The current investigation focuses on predicting solar irradiance on an inclined surface, taking into consideration the impact of climatic variables such as temperature, wind speed, humidity, and air pressure. The used methodology for this objective is Artificial Neural Network (ANN), and the inquiry is carried out in the metropolitan region of Douala. The data collection device used in this research is the meteorological station located at the IUT of Douala. This station was built as a component of the Douala sustainable city effort, in partnership with the CUD and the IRD. Data was collected at 30-min intervals for a duration of around 2 years, namely from January 17, 2019, to October 30, 2020. The aforementioned data has been saved in a database that underwent pre-processing in Excel and later employed MATLAB for the creation of the artificial neural network model. 80% of the available data was utilized for training the network, 15% was allotted for validation, and the remaining 5% was used for testing. Different combinations of input data were evaluated to ascertain their individual degrees of accuracy. The logistic Sigmoid function, with 50 hidden layer neurons, yielded a correlation coefficient of 98.883% between the observed and estimated sun irradiation. This function is suggested for evaluating the intensities of solar radiation at the place being researched and at other sites that have similar climatic conditions.

Thermotolerance capabilities, blood metabolomics and mammary gland hemodynamics and transcriptomic profiles of slick-haired Holstein cattle during mid-lactation in Puerto Rico.

Holstein cattle carrying a prolactin receptor gene mutation (SLICK) exhibit short and sleek hair coats enhancing thermotolerance and productivity compared with wild type-haired Holstein (WT) under tropical conditions. The objectives were to unravel the physiological and molecular mechanisms that confer an advantage to this SLICK genotype in Puerto Rico and determine potential correlations between metabolites and physiological variables. At 160 ± 3 d in milk (DIM) we compared vaginal temperatures (VT) and voluntary solar radiation exposure (VSRE) during 48 h between 9 SLICK and 9 WT Holsteins, whereas a subsample of 7 SLICK and 7 WT were used to assess udder skin temperature, mammary gland hemodynamics and transcriptomics, and blood plasma untargeted metabolomics at a single time point. The SLICK cattle showed lower vaginal temperatures throughout the day and greater VSRE at 1000 h and 1100 h compared with their WT counterparts. Total mammary blood flow was greater in SLICK Holsteins compared with WT. The metabolite 9-nitrooctadecenoic acid was identified as a potential biomarker for MBF; moreover, SLICK cattle had greater amounts of this metabolite in their plasma. Prostaglandin D2 synthase (PTGS) was upregulated in the SLICK mammary gland, while plasma prostaglandin D2 was positively correlated with milk yield and increased in SLICK Holsteins compared with WT. Interestingly, the arachidonic acid metabolism pathway was enriched in the mammary gland transcriptome and perturbed in the blood metabolome in the SLICK Holsteins. In conclusion, SLICK Holsteins exhibited lower body temperatures, greater voluntary solar radiation exposure, enhanced blood supply to the mammary gland, and alterations in genes and metabolites involved in arachidonic acid metabolism at the mammary gland and blood plasma. The usage of the slick-haired Holstein cattle genetics in dairy operations could be a feasible alternative to mitigate the adverse consequences of heat stress.

Impact of real-time weather conditions on crash injury severity in Kentucky using the correlated random parameters logit model with heterogeneity in means.

The present study investigated the impact of real-time weather (air temperature, relative humidity, precipitation, wind speed, and solar radiation) on crash injury severity. Recent crash data (January 2016 to April 2021) on Interstate-75 in the state of Kentucky were merged with real-time weather information (retrieved from Kentucky Mesonet stations) at the 1-hour level. The severity index "SI" (i.e., the ratio of percent severe crashes to percent exposure of a specific weather state during the crash period) was introduced to evaluate the impact of different real-time weather states on fatal and severe injury crashes. Furthermore, the standard mixed logit (MXL), correlated mixed logit (CMXL), and correlated mixed logit with heterogeneity in means (CMXLHM) models were fitted and compared to identify the risk factors contributing to crash injury severity while accounting for unobserved heterogeneity. The results showed that the CMXLHM model was statistically superior to the CMXL and MXL models based on various goodness-of-fit measures (e.g., Akaike information criterion "AIC" and McFadden pseudo R-squared). Results from the SI analysis and CMXLHM model showed that real-time weather-related factors (e.g., air temperature ≥ 70 0F and relative humidity ≥ 90 %) were significantly associated with higher severe injury likelihood. Further, driving under the influence (DUI), young drivers, and vehicle travel speed were associated with greater injury severities. On the other hand, presence of horizontal curve, passenger cars, and hourly traffic volume were associated with lower injury severity likelihood. The study outcomes can help in incident management by suggesting specific real-time weather-related states to feed to dynamic message signs (DMS) to enhance travelers' safety along the interstates.

Cardiovascular Effects of Cosmic Radiation and Microgravity.

Recent spaceflights involving nonprofessional people have opened the doors to the suborbital space tourism business. However, they have also drawn public attention to the safety and hazards associated with space travel. Unfortunately, space travel involves a myriad of health risks for people, ranging from DNA damage caused by radiation exposure to the hemodynamic changes that occur when living in microgravity. In fact, the primary pathogenetic role is attributed to cosmic radiation, since deep space lacks the protective benefit of Earth's magnetic shielding. The second risk factor for space-induced pathologies is microgravity, which may affect organ function and cause a different distribution of fluid inside the human body. Both cosmic radiation and microgravity may lead to the alteration of cellular homeostasis and molecular changes in cell function. These, in turn, might have a direct impact on heart function and structure. The aim of this review is to draw attention to the fact that spaceflights constitute a novel frontier in biomedical research. We summarize the most important clinical and experimental evidence regarding the cardiovascular effects of cosmic radiation and microgravity. Finally, we highlight that unraveling the mechanisms underlying how space radiation and microgravity affect the cardiovascular system is crucial for identifying potential countermeasures and developing effective therapeutic strategies.

Definition of a maximum threshold of direct solar radiation exposure for pedestrians of diverse walking abilities.

Since pedestrians are impacted by solar radiation differently, urban designers must evaluate solar radiation exposure of pedestrian paths adopting an inclusive approach. This paper proposes a maximum threshold of direct solar radiation exposure for pedestrians based on activity, user profile and environmental conditions, defined as the difference between the energy consumption before feeling exhausted and the energy cost of walking. Two users of diverse walking abilities, a young adult and an elderly person with mobility impairment, were characterised by metabolic activity, walking speed and maximum energy capacity. Based on the theoretical framework, the energy budget of young adults to cope with thermal stress was set as three times higher than for the elderly. This framework was used to quantify the contribution of direct solar radiation to energy balance and then classify walkability during clear-sky summer hours; the term 'walkable' referred to environmental conditions allowing users to walk without feeling exhausted. The methodology was tested on an open area and an urban canyon in Milan; applicability by urban designers was key in developing a simplified way to evaluate shading needs. This approach could be applied to evaluate solar radiation exposure of pedestrian paths adopting diverse user experiences as an evaluation criterion.

Short-term solar radiation forecasting using machine learning models under different sky conditions: evaluations and comparisons.

Forecasting short-term solar radiation is crucial for many solar energy applications. Additionally, solar energy has a lower environmental impact than conventional sources like fossil fuels and can be used for investment purposes through the construction of large solar farm facilities. To test, evaluate, and compare various solar radiation models, short-term observations of meteorological, astronomical, computational, and geographical data were collected at two distinct locations from 2012 to 2015. In this study, seven machine learning models were employed: multi-layer perceptron (MLP), feedforward backpropagation algorithm (FFBP), autoregressive integrated moving average (ARIMA), linear regression (LR), radial basis function neural network (RBFNN), random forest (RF), and Gaussian process regression (GPR) models. These models were used to forecast hourly global solar radiation (GSR) using the aforementioned data as model input. The performance of the selected models' forecast accuracy was thoroughly examined by assessing it for a typical day, for four seasons, and under three sky conditions. The RF model can forecast GSR with satisfactory accuracy, and MLP and GPR models provide better accuracy than LR, FFBP, RBF, and ARIMA models. For example, the R2 value range of RF are 0.9621 for Tetuan site and 0.9534 for Tangier site, respectively. Meanwhile, RF, MLP, and GPR models under-forecast few high radiation values on clear days, which may due to the differences in training and testing data ranges and distributions of the sky conditions. Finally, the obtained result of this study indicate that the proposed RF model is a reliable alternative for short-term global solar radiation forecasting due to its high forecast accuracy.

Assessment of maternal knowledge of solar exposure and vitamin D in the neonatal period / Avaliação do conhecimento materno sobre exposição solar e vitamina D no período neonatal

ABSTRACT Objective: To assess mothers' knowledge on sun exposure related to serum vitamin D levels in the neonatal period. Methods: Observational, analytical and cross-sectional study, carried out from August 2020 to May 2021 through a questionnaire directed to mothers of newborns, in a maternity hospital in Southern Brazil. Results: From 141 interviewees, 132 (93.6%) believe it is important to expose the neonate to sun, 101 (71.6%) think this exposure can increase vitamin D levels, 86 (61%) received such information from a doctor, 108 (76.6%) believe there are no risks of sun exposure, 88 (62.4%) claim it isn´t necessary to use any kind of protection, 96 (68.1%) said that only exposure to the sun was necessary to maintain adequate levels of vitamin D during the neonatal period. Only two mothers (1.4%) claim that you should not exposure the neonate to the sun, and only one (0.7%) stated that sun expose can cause skin problems. Conclusions: Most mothers lack satisfactory knowledge about sun exposure related to serum vitamin D levels in the neonatal period. The need to inform and clarify the population about sun exposure during this period is remarkable, in addition to disseminating the proper way to maintain serum levels of vitamin D.

RESUMO Objetivo: Avaliar o conhecimento das mães acerca da exposição solar relacionada com níveis séricos de vitamina D no período neonatal. Métodos: Estudo observacional, analítico e transversal, realizado de agosto de 2020 a maio de 2021 por meio de questionário dirigido às mães de recém-nascidos, em uma maternidade no sul do Brasil. Resultados: De 141 entrevistadas, 132 (93,6%) acreditam ser importante expor o lactente ao sol no primeiro mês de vida, 101 (71,6%) acham que essa exposição aumenta os níveis de vitamina D, 86 (61,0%) receberam tal informação de um médico, 108 (76,6%) acreditam que expor o neonato ao sol não causa riscos para a saúde, 88 (62,4%) acham que não é necessário usar proteção contra radiação solar ao expor o neonato ao sol, e 96 (68,1%) afirmaram que apenas a exposição ao sol basta para manter os níveis adequados de vitamina D durante o período neonatal. Apenas duas mães (1,4%) afirmaram que não se deve expor o neonato ao sol e uma (0,7%) que a exposição solar pode causar problemas de pele. Conclusões: A maioria das mães não possui conhecimento satisfatório acerca da exposição solar relacionada aos níveis séricos de vitamina D no período neonatal. É notável a necessidade de informar e esclarecer a população sobre a exposição solar nesse período, além de disseminar a maneira adequada de manter os níveis séricos de vitamina D.

Solar-assisted oxidation of organochlorine pesticides in groundwater using persulfate and ferrioxalate.

The oxidation of hexachlorocyclohexane isomers in the aqueous phase (Milli-Q and groundwater) was studied using persulfate activated by ferrioxalate and solar light at circumneutral pH. The experiments were conducted in a solar simulator reactor with local radiation fluxes qw= 1.12·10-7 E cm-2s-1 and in compound parabolic collectors with solar light (qw≈10-7 E cm-2s-1) for 390 min. The effect of activator dosage (18-125 µM ferrioxalate) and persulfate concentration (520-2600 µM) on hexachlorocyclohexane conversion and oxalate and oxidant consumption was analyzed. Conversion of about 95% of ß isomer was achieved at 390 min using 1300 µM of initial persulfate and 63 µM of Fe3+ concentration despite this ß isomer being the most recalcitrant to oxidation (XHexachlorocyclohexanes=0.98). Dechlorination above 80% was achieved under these conditions, analyzing the chlorides released into the water. The influence of chloride and bicarbonate on hexachlorocyclohexanes degradation was analyzed in milli-Q water and in groundwater. Hexachlorocyclohexane conversion at 390 min decreases from 98% to 83, 75 and 65% in the presence of chloride, bicarbonate or groundwater, respectively. Results obtained with compound parabolic collectors and solar light using 2600 µM Na2S2O8 and 63 µM Fe for removing hexachlorocyclohexanes agreed with those from the solar simulator reactor, supporting using solar light to activate persulfate for sustainable abatement of persistent organic pollutants in aqueous matrixes.

[Mathematical simulation of the corpse's temperature change during exposure of a direct solar radiation to diagnose a postmortem interval]. / Matematicheskoe modelirovanie protsessa izmeneniya temperatury trupa pri vozdeistvii na nego pryamoi solnechnoi radiatsii v tselyakh diagnostiki davnosti smerti.

OBJECTIVE: To choose an optimal mathematical model and to practice the method of its use during finding the corpse under exposure of a direct solar radiation. MATERIAL AND METHODS: The studies were carried out on 9 corpses with body weight from 50 to 83 kg. The influence of black (6 corpses) and white (3 corpses) colored cotton fabrics was investigated to standardize a photoreceptive surface of clothes. In addition, the objects (bags made of substantial polyethylene, densely filled with moderately humid black soil) replacing corpses with mass of 5.5, 11.0, 16.5 and 22.0 kg, wrapped in cotton fabric of specified colors, that imitates clothes, were used. The objects' temperature was measured within the accuracy of 0.001 °C, air temperature - within accuracy of 0.1 °C. A simplified one-dimensional variant of the finite mathematical differences method, representing the process of corpse's cooling as a discrete transfer of heat from one layer (node) to another, was used in developing the mathematical modeling algorithm. The model consisted of ten nodes was used in calculations. RESULTS: A mathematical model in the form of equations' system was developed, in which the variable reflecting the intensity of corpse's surface heating by sun rays was introduced. The example of calculation made with data of real measurements of corpse's temperature, that was in open place for the sun rays, is shown.