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Forest ecosystems play a decisive role in the global climatic condition, as well as, provides a wide range of societal benefits, including fuel-wood, tourism, and ecosystem services are considered as one of the major sources of livelihood for the local people in the upper Blue Nile Basin. Therefore, rapid and accurate estimation of forest biomass is crucial for greatly reducing the uncertainty in carbon stock assessments, and for designing strategic forest management plans. Because, above-ground biomass (AGB) estimation is important in determining the management, environmental, and economic roles of forests in the Blue Nile basin. The study was aimed at estimating above-ground biomass in the Upper Blue Nile Basin forests by integrating field-measured data with predictors from Sentinel-2 image. The relationship between measured AGB and sentinel-2 derived vegetation indices and biophysical parameters showed a good correlation result (r value ranging from 0.67 to 0.74). A stepwise regression analysis was carried out in order to develop AGB estimation model by identifying the most important variable. The result demonstrated that, green normalized difference vegetation index, leaf area index, fraction of absorbed photosynthetic active radiation and fractional vegetation cover achieved good performance in predicting AGB with R2 value > 0.5. AGB was estimated with a coefficient of determination (R2) of 0.59 adjusted R2 of 0.618 and root mean square error of (RMSE) 38.36 t/ha in comparison to field observations. The maximum AGB value of 268.32 t/ha was estimated in the Alemsaga natural forest, which is a highly protected dense forest stand from any entrance and disturbance. Generally, integrating field data with optical remote sensing data provides more reliable result for AGB estimation. Moreover, it is also recommended to employ RADAR and LiDAR remote sensing data products together in order to attain more precise estimate results of AGB with great potential for forest resource monitoring and management. [ABSTRACT FROM AUTHOR]

Background: Skin type has a strong influence on how sensitive skin develops, with oily skin accounting for a larger proportion of sensitive skin. However, there has not been a scientifically sound questionnaire for determining oily sensitive (OS)‐type skin in prior studies. Objectives: In order to identify OS‐type skin in the general population, we therefore intend to create an OS‐type skin evaluation questionnaire, develop various thresholds through data analysis and classify skin based on two dimensions of sensitivity and oiliness. Methods: A questionnaire with questions regarding subjects' basic information, skin oiliness and skin sensitivity was given to each individual who participated in the study (n = 1297). To define the thresholds for OS‐type skin, receiver‐operating characteristic (ROC) curves were generated. The results of the lactic acid stinging test (LAST) and noninvasive instrument information obtained were compared with the thresholds mentioned above to verify the effectiveness of this tool. Results: According to the ROC curves, questionnaire cut‐off values of 11.5, 20.5 and 29.5 can be used to detect mildly, moderately and severely sensitive skin, respectively. In addition, the questionnaire cut‐off values of 22.5 and 31.5 can be used to detect moderately and severely oily skin, respectively. According to our study, the four sensitive‐skin groups' LAST scores differed significantly from one another, while the skin sebum levels differed significantly between the three oily groups. Additionally, the EI and LAST scores were significantly correlated with skin sensitivity levels, whereas sebum, moisture and EI were positively correlated with skin oiliness levels. Conclusions: We developed an OS‐type skin evaluation questionnaire that has been tested and shown scientifically to be a promising method for evaluating OS‐type skin and to completely examine the traits of sensitive and oily skin. [ABSTRACT FROM AUTHOR]

Abstract Forest ecosystems play a decisive role in the global climatic condition, as well as, provides a wide range of societal benefits, including fuel-wood, tourism, and ecosystem services are considered as one of the major sources of livelihood for the local people in the upper Blue Nile Basin. Therefore, rapid and accurate estimation of forest biomass is crucial for greatly reducing the uncertainty in carbon stock assessments, and for designing strategic forest management plans. Because, above-ground biomass (AGB) estimation is important in determining the management, environmental, and economic roles of forests in the Blue Nile basin. The study was aimed at estimating above-ground biomass in the Upper Blue Nile Basin forests by integrating field-measured data with predictors from Sentinel-2 image. The relationship between measured AGB and sentinel-2 derived vegetation indices and biophysical parameters showed a good correlation result (r value ranging from 0.67 to 0.74). A stepwise regression analysis was carried out in order to develop AGB estimation model by identifying the most important variable. The result demonstrated that, green normalized difference vegetation index, leaf area index, fraction of absorbed photosynthetic active radiation and fractional vegetation cover achieved good performance in predicting AGB with R2 value > 0.5. AGB was estimated with a coefficient of determination (R2) of 0.59 adjusted R2 of 0.618 and root mean square error of (RMSE) 38.36 t/ha in comparison to field observations. The maximum AGB value of 268.32 t/ha was estimated in the Alemsaga natural forest, which is a highly protected dense forest stand from any entrance and disturbance. Generally, integrating field data with optical remote sensing data provides more reliable result for AGB estimation. Moreover, it is also recommended to employ RADAR and LiDAR remote sensing data products together in order to attain more precise estimate results of AGB with great potential for forest resource monitoring and management.

The temporal behaviors of land surface temperature (LST) coupled with its associated parameters play a crucial role in determining the microclimate at the city scale. The increasing pattern of LST and consequent changes in biophysical parameters (parameters specify the amalgamation of living system with their physical characteristics including vegetation, water, built-up, bareness and drought parameters) at monthly, seasonal and annual time spans and from regional to global scale need to be comprehensively evaluated. The present study deals with LST estimation along with other spectral indices including Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI), Normalized Difference Built-up Index (NDBI), Normalized Difference Bareness Index (NDBaI), and Normalized Multi-band Drought Index (NMDI) using Landsat series datasets from 1991 to 2022 of Aligarh city, Uttar Pradesh, India. The spatial pattern of LST indicates that the areas having water bodies and dense vegetation are colder such as the Aligarh Muslim University Campus and the catchment of Ganga canal areas, whereas the areas of high urbanization and bare grounds reflect high LST trends. Study finds a positive correlation of LST with NDBI (R2-0.56), NDBaI (R2-0.22) and NDWI (R2-0.22), whereas a negative correlation with NDVI (R2-0.35), MNDWI (R2-0.36) and NMDI (R2-0.41). Land use land cover (LULC)-based change detection in land cover classes was found consistent with the obtained results for spectral indices and LST patterns in the study area. Finally, the cross-validation using Modern-Era Retrospective analysis for Research and Applications (MERRA) reanalysis-based products of earth skin temperature and rainfall showed a good fit between observed and reanalysis products. [ABSTRACT FROM AUTHOR]

Forest fire is a major disturbance in mountainous ecosystems across the world. It impacts the composition, functioning, and structure of the forest ecosystem. Demographic pressure and the related climatic factors are thought to exacerbate the danger of forest fires, although there is a lack of statistical data to support this, particularly in South Asian countries with limited historical records. The study looks at how forest fires interact with their causative variables, such as population, topography, vegetation, and climate regimes, in the forests of Northern India. In order to do so, the paper presents a 15-year trend analysis of forest burn scars. This investigation confirmed the utility of principal component analysis using multisource spatial data and correlation matrices. The findings reveal that the occurrence and intensity of forest fires in mountainous locations are influenced by anthropogenic activities, forests near roads and settlements are extremely vulnerable. Based on the analysis, we emphasize the need for restructuring the existing policies like National Action Plan for forest fires and forest fire prevention and management scheme into more practical science-based policies. These findings may be utilized in planning effective fire control processes in time, and the technique provided in this study may be used to discover potential fire-risk zones in other areas. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of the study is to identify differences between axisymmetric diffusion kurtosis imaging (DKI) and standard DKI, their consequences for biophysical parameter estimates, and the protocol choice influence on parameter estimation. Methods: Noise‐free and noisy, synthetic diffusion MRI human brain data is simulated using standard DKI for a standard and the fast "199" acquisition protocol. First the noise‐free "baseline" difference between both DKI models is estimated and the influence of fiber complexity is investigated. Noisy data is used to establish the signal‐to‐noise ratio at which the baseline difference exceeds noise variability. The influence of protocol choices and denoising is investigated. The five axisymmetric DKI tensor metrics (AxTM), the parallel and perpendicular diffusivity and kurtosis and mean of the kurtosis tensor are used to compare both DKI models. Additionally, the baseline difference is also estimated for the five parameters of the WMTI‐Watson model. Results: The parallel and perpendicular kurtosis and all of the WMTI–Watson parameters had large baseline differences. Using a Westin or FA mask reduced the number of voxels with large baseline difference, that is, by selecting voxels with less complex fibers. For the noisy data, precision was worsened by the fast "199" protocol but adaptive denoising can help counteract these effects. Conclusion: For the diffusivities and mean of the kurtosis tensor, axisymmetric DKI with a standard protocol delivers similar results as standard DKI. Fiber complexity is one main driver of the baseline differences. Using the "199" protocol worsens precision in noisy data but adaptive denoising mitigates these effects. [ABSTRACT FROM AUTHOR]

A study was carried out during kharif season of 2022 and 2023 at the Punjab Agricultural University (PAU)-Regional Research Station (RRS), Ballowal Saunkhri (SBS Nagar) with the objective to find out the impact of foliar spray of agrochemicals on biophysical parameters, PAR interception and heat use efficiency of rainfed mung bean (Vigna radiata (L.) Wilczek) under variable sowing dates. Timely sown crop (second fortnight of July) resulted in higher leaf area index, chlorophyll index, PAR interception and heat use efficiency (HUE) as compared to late sowing (first fortnight of August). Significantly higher seed yield, stover yield and biological yields were obtained in timely sowing during both the years of study. Foliar spray of KNO3 @ 1.5% recorded significantly higher leaf area index, chlorophyll index, PAR interception, heat use efficiency (HUE) and helio-thermal use efficiency (HTUE) but it was statistically similar with foliar spray of N:P:K (20:20:20) @ 1.5%. Foliar spray of KNO3 @ 1.5% and N:P:K (20:20:20) @ 1.5% gave statistically similar seed, stover and biological yields and significantly better than other treatments. There was an increase of 33.3% in seed yield with foliar spray of KNO3 @ 1.5% and increase of 29.1% with foliar spraying of N:P:K (20:20:20) @ 1.5%, when compared with control. [ABSTRACT FROM AUTHOR]

The effect of evolutionary history on wood density variation may play an important role in shaping variation in wood density, but this has largely not been tested. Using a comprehensive global dataset including 27,297 measurements of wood density from 2621 tree species worldwide, we test the hypothesis that the legacy of evolutionary history plays an important role in driving the variation of wood density among tree species. We assessed phylogenetic signal in different taxonomic (e.g., angiosperms and gymnosperms) and ecological (e.g., tropical, temperate, and boreal) groups of tree species, explored the biogeographical and phylogenetic patterns of wood density, and quantified the relative importance of current environmental factors (e.g., climatic and soil variables) and evolutionary history (i.e., phylogenetic relatedness among species and lineages) in driving global wood density variation. We found that wood density displayed a significant phylogenetic signal. Wood density differed among different biomes and climatic zones, with higher mean values of wood density in relatively drier regions (highest in subtropical desert). Our study revealed that at a global scale, for angiosperms and gymnosperms combined, phylogeny and species (representing the variance explained by taxonomy and not direct explained by long-term evolution process) explained 84.3% and 7.7% of total wood density variation, respectively, whereas current environment explained 2.7% of total wood density variation when phylogeny and species were taken into account. When angiosperms and gymnosperms were considered separately, the three proportions of explained variation are, respectively, 84.2%, 7.5% and 6.7% for angiosperms, and 45.7%, 21.3% and 18.6% for gymnosperms. Our study shows that evolutionary history outpaced current environmental factors in shaping global variation in wood density.

Objective: This study was designed to comprehensively evaluate the changes in facial skin biophysical parameters with age, as well the influence of gender differences in populations of Shaanxi Province, China. Methods: Fourteen skin parameters, including stratum corneum hydration (SCH), transdermal water loss (TEWL), erythema, melanin, R0, R2, R5, R7, F4, gloss, skin surface pH, skin erythema index (a*), wrinkle length, and sebum, were measured by noninvasive instruments in 481 volunteers from Shaanxi Province. Spearman correlation analysis was performed to analyze the relationship between skin parameters and age. Additionally, skin parameters were analyzed for different age groups and different genders. Results: The results of the study showed a linear decrease in skin surface pH and sebum content with age, and the skin elasticity parameters R0, R2, R5, and R7 decreased significantly at the age of 54–65 years. Wrinkle length showed a linear and increase with age. R5 showed a weak negative correlation with age, R2, R7, and sebum content showed a moderate negative correlation, while wrinkle length showed a strong positive correlation. Considering the effect of gender on skin parameters, the results showed that SCH and gloss were lower in men than in women, while TEWL, erythema, melanin, wrinkle length, and sebum were higher than in women. However, there was no difference in skin elasticity between them. Conclusion: The facial skin parameters, especially for the wrinkle length, exhibited the strong correlation relationship with ages in Shaanxi Province. Meanwhile, most skin parameters show significant differences with gender, which can provide a reference for future research and development in the field of cosmetics. [ABSTRACT FROM AUTHOR]

Northeast Brazil (NEB), particularly its semiarid region, represents an area highly susceptible to the impacts of climate change, including severe droughts, and intense anthropogenic activities. These stresses may be accelerating environmental degradation and desertification of soil in NEB. The main aim of this study was to gain geospatial insights into the biophysical parameters of surface energy balance and actual evapotranspiration on a multi-temporal scale, aiming to detect and analyze the spectral behavioral patterns of areas vulnerable to degradation processes, based on thematic maps at the surface, for NEB and mainly the semiarid region of NEB from 2000 to 2019. Geospatial data from 8-day MODIS sensor products were used, such as surface reflectance (Terra/MOD09A1 and Aqua/MYD09A1), surface temperature (Terra/MOD11A2 and Aqua/MYD11A2), and actual evapotranspiration (Terra/MOD16A2 and Aqua/MYD16A2), version 6. Therefore, in this study, pixel-to-pixel values were processed by calculating the average pixel statistics for each year. From the reflectance product, digital processing of the surface albedo and spectral vegetation indices was also carried out, using computational programming scripts and machine learning algorithms developed via the Google Earth Engine (GEE) platform. The study also presents a seasonal analysis of these components and their relationships over 20 years. Through vegetation indices and statistical correlations, a new predictive model of actual evapotranspiration was developed. The quantitative and spatiotemporal spectral patterns of the parameters were assessed through descriptive statistics, measures of central tendency and dispersion, and statistical error analyses and correlation indices. Thematic maps highlighted the pixel-to-pixel results, with patterns of high temperature distribution mainly in the central and northeastern part of NEB and the semiarid region of NEB, highlighting the formation of persistent heat islands over time. Meanwhile, in these areas, the maps of actual evapotranspiration showed a drastic reduction due to the lesser availability of energy. Over time, the semiarid region of NEB presented areas with little and/or no vegetation cover, which were highly well-defined between the years 2012 and 2019, confirming that these areas are extremely vulnerable to degradation and desertification processes due to significant loss of vegetative and water resilience. The components of energy balance were highly interconnected to climatological and environmental conditions, showing the severe results of drought and accentuation of the water deficit in NEB, presenting a greater condition of aridity in the semiarid region of NEB over time. [ABSTRACT FROM AUTHOR]

A study was carried out during kharif season of 2022 and 2023 at the Punjab Agricultural University (PAU)-Regional Research Station (RRS), Ballowal Saunkhri (SBS Nagar) with the objective to find out the impact of foliar spray of agrochemicals on biophysical parameters, PAR interception and heat use efficiency of rainfed mung bean (Vigna radiata (L.) Wilczek) under variable sowing dates. Timely sown crop (second fortnight of July) resulted in higher leaf area index, chlorophyll index, PAR interception and heat use efficiency (HUE) as compared to late sowing (first fortnight of August). Significantly higher seed yield, stover yield and biological yields were obtained in timely sowing during both the years of study. Foliar spray of KNO3 @ 1.5% recorded significantly higher leaf area index, chlorophyll index, PAR interception, heat use efficiency (HUE) and helio-thermal use efficiency (HTUE) but it was statistically similar with foliar spray of N:P:K (20:20:20) @ 1.5%. Foliar spray of KNO3 @ 1.5% and N:P:K (20:20:20) @ 1.5% gave statistically similar seed, stover and biological yields and significantly better than other treatments. There was an increase of 33.3% in seed yield with foliar spray of KNO3 @ 1.5% and increase of 29.1% with foliar spraying of N:P:K (20:20:20) @ 1.5%, when compared with control.

This paper makes an assessment of the coastal erosion hazard of the Odisha state with the use of 'Coastal Hazard Wheel' methodology which is a multi-hazard assessment as well as a management tool in a changing global climate. This study analyses the coastal environment to assess the vulnerability profile of coastal erosion by using bio-geophysical parameters such as geological layout, tidal range, exposure to waves, balance or deficit of sediments, characteristics of flora and fauna and exposure to storm climate. These are also used in analysing climate change hazards of the coast which are inherent to an area like saline flooding, gradual inundation, ecosystem disruption and salt water intrusion. CHW framework has generated information about the degree to which coastal erosion is inherent in a particular coastal location along the coast. This application has used remote sensing data from the public domain and a GIS approach to screen the problem with an appropriate scale as suitable for regional and national planning purposes with a management perspective because of limited data availability. The study has generated coastal erosion data and maps for the 480 km of the coastline dividing the coast in to 14 different morphological segments. Assessment of this hazard shows that 50 percent of Odisha's coastline is vulnerable to a high or very high inherent hazard of erosion, 45 percent exhibits a lower level of erosion presence and 5 percent is moderately vulnerable to erosion. This study has revealed increasing magnitude of coastal erosion than previous assessments by different researchers which were mostly based on coastal vulnerability indices. The study also identifies a number of possible erosion hazard management and mitigation options which can be used depending on their location specific field data and coastal characteristics. The finding of the study is significant in view of its contribution towards a first step in understanding coastal erosion at the regional level for their management. However, input of local data and manmade structures along the coast in the model would enhance the results for the site-specific mitigation measures. [ABSTRACT FROM AUTHOR]

The objective of this research is to characterize the hydrological network of the "Hondo" estuary micro-basin through the use of morphometric and biophysical parameters, in order to analyze and predict its hydrodynamic behavior, in order to contribute to environmental management plans and be a contribution to the conservation and protection of optimal conditions for their development. Three shape parameters, two of relief, its drainage network and physiography were analyzed. While in the biophysical variables they were calculated by means of ArcGIS geospatial information processing, identifying their temperature, precipitation, soil texture, land use and cover, slope and taxonomy. According to the results obtained, its morphometry the micro-basin presented an oblong or rectangular shape, a moderate drainage network, where it is concluded that its water system is not prone to present flood peaks, due to the stability of its runoff regimes. superficial. However, as it is a young basin and presents a concave hypsometric shape, it is likely that it will experience high erosive processes in the future. Finally, in the biophysical component it was identified that the texture of the soil was mostly sandy loam, with strong and steep slopes and a predominance of alfisols whose water filtration is low, where it is concluded that the micro-basin could present loss of the layer vegetative by dragging sediment. [ABSTRACT FROM AUTHOR]

This study endeavors to produce a comprehensive land cover map for Morocco, addressing the absence of such a detailed map in the country. Our research encompasses ecological and climatic aspects specific to Morocco, while the methods used can be adapted to various regions and countries, considering their unique climatic conditions and land cover types. A combination of MODIS and Landsat datasets was employed to create a 5 km resolution Land Use and Land Cover (LULC) map for the entire nation. The process involved the aggregation and advanced processing of these datasets using surface processes algorithms. The resulting LULC map is the first of its kind for Morocco, shedding light on land cover distribution nationwide. It shows that approximately 13.5% of the country is covered by forests, predominantly in the Atlas and Rif mountains, Rabat–Sale, and the southern regions. Grasslands occupy over 16% of the study area, mainly in the north-east and west. Urban areas, including major cities like Casablanca, Rabat, and Marrakech, span nearly 3400 km². Moreover, large areas of shrublands and bare lands are evident across the country, while agricultural lands account for almost 20% of the national territory, mainly in the interior plains and north-western Atlantic coast. This study forms a crucial basis for ecological and climatic research in Morocco and serves as a valuable reference for various disciplines such as agriculture, natural resource management, and climate modeling. The mapping of biophysical parameters for each land cover class is a key feature of our research, and these parameters will be instrumental in a subsequent study examining the impact of urban development on surface climate in Morocco. Overall, our study underscores the importance of understanding biophysical parameters in addressing environmental and societal challenges. [ABSTRACT FROM AUTHOR]

In acute care facilities, the detection of pressure ulcers (PUs) relies on visual and manual examination of the patient's skin, which has been reported to be inconsistent and may lead to misdiagnosis. In skin and wound research, various biophysical parameters have been extensively employed to monitor changes in skin health. Nonetheless, the transition of these measures into care settings as part of a routine clinical assessment has been limited. This study was designed to examine the spatial and temporal changes in skin biophysical parameters over the site of a category I PU, in a cohort of hospitalised patients. Thirty patients, each presenting with a category I PU, were enrolled in the study. Skin integrity was assessed at the PU‐compromised site and two adjacent areas (5 and 10 cm away). Data was collected over three sessions to examine both temporal differences and longitudinal changes. Skin integrity was assessed using two biophysical parameters, namely, transepidermal water loss (TEWL) and stratum corneum (SC) hydration. In addition, the influence of intrinsic factors, namely, incontinence and mobility status, on the parameters was evaluated. TEWL values at the sites compromised by PU were statistically significantly greater (P <.001) than corresponding values at the adjacent control sites at 5 and 10 cm, which were consistent with a normative range (<20 g/h/m2). By contrast, SC hydration values did not reveal clear distinctions between the three sites, with high inter‐patient variation detected at the sites. Nevertheless, individual profiles were consistent across the three sessions, and the PU site was observed to be either abnormally dry or overhydrated in different individuals. No consistent temporal trend in either parameter was evident. However, intrinsic factors were shown to influence the parameters, with females, bedridden and incontinent patients presenting significantly higher TEWL and SC hydration values (P <.05). TEWL was able to identify differences in skin responses at skin sites compromised with a category I PU when compared to healthy adjacent skin sites. Accordingly, this parameter could be included in the clinical assessment for the identification of PU risk. Further studies are required to elucidate the role of hydration and skin barrier function in the development of PUs and their ability to monitor temporal changes in skin integrity. [ABSTRACT FROM AUTHOR]

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The retrieval of the biophysical parameters and subsequent estimation of the above-ground biomass (AGB) of vegetation stands are made possible by the simulation of the extinction and scattering components from the canopy layer using vector radiative transfer (VRT) theory-based scattering models. With the use of such a model, this study aims to evaluate and compare the potential of dual-pol, multi-frequency SAR data for estimating above-ground biomass. The data selected for this work are L-band dual polarized (HH/HV) ALOS-2 data, S-band dual polarized (HH/HV) NovaSAR data, and C-band dual polarized (VV/VH) Sentinel-1 data. The two key biophysical parameters, tree height, and trunk radius are retrieved using the proposed methodology, applying the frequencies independently. A general allometric equation with vegetation-specific coefficients is used to estimate the AGB from the retrieved biophysical parameters. The retrieval results are validated using ground truth measurements collected from the study area. The L-band, with the coefficient of determination ( R 2 ) of 0.73 and the root mean square error (RMSE) of 35.90 t/ha, has the best correlation between the modeled and field AGBs, followed by the S-band with an R 2 of 0.37 and an RMSE of 63.37 t/ha, and the C-band with an R 2 of 0.25 and an RMSE of 72.32 t/ha. The L-band has yielded improved estimates of AGB in regression analysis as well, with an R 2 of 0.48 and an RMSE of 50.02 t/ha, compared to the S- and C-bands, which have the R 2 of 0.12 and 0.03 and the RMSE of 70.98 t/ha and 80.84 t/ha, respectively. [ABSTRACT FROM AUTHOR]

Irrigated crops have experienced a significant global expansion. The biophysical response of climate change to irrigated crop expansion in different regions, particularly in terms of monitoring the influence mechanism of nighttime land surface temperature (LST) change, however, remains insufficiently explored. Taking the three northeastern provinces of China as our study area, we apply window analysis, partial correlation analysis, and geographical detector to quantitatively characterize the spatial and temporal distribution pattern of daytime and nighttime LST (diurnal LST) and biophysical parameters, and the main driving mechanism of diurnal LST change. The results showed that irrigated crop expansion led to asymmetric changes in daytime (−2.11 ± 0.2°C, 97.4%) and nighttime (0.64 ± 0.2°C, 79.9%) LST. ΔLSTDT had a negative correlation with ΔLE (63%), but a positive correlation with ΔSSR and ΔH (91% and 77%). This revealed that the cooling effect caused by the superposition of the output latent heat flux and the absorbed solar shortwave radiation was greater than its heating effect. ΔLSTNT and ΔLE had a positive connection across 69% of the region. ΔLSTNT demonstrated a negative correlation with ΔSSR and ΔH in 82% and 75% of the regions, respectively. At this time, the superposition of latent heat flux and heating potential term produces a greater heating effect. The explanatory power of the single factor (the mean of q0.50, p

Hyperspectral technology offers significant potential for non-invasive monitoring and prediction of morphological parameters in plants. In this study, UV−VIS−NIR−SWIR reflectance hyperspectral data were collected from Nicotiana tabacum L. plants using a spectroradiometer. These plants were grown under different light and gibberellic acid (GA3) concentrations. Through spectroscopy and multivariate analyses, key growth parameters, such as height, leaf area, energy yield, and biomass, were effectively evaluated based on the interaction of light with leaf structures. The shortwave infrared (SWIR) bands, specifically SWIR1 and SWIR2, showed the strongest correlations with these growth parameters. When classifying tobacco plants grown under different GA3 concentrations in greenhouses, artificial intelligence (AI) and machine learning (ML) algorithms were employed, achieving an average accuracy of over 99.1% using neural network (NN) and gradient boosting (GB) algorithms. Among the 34 tested vegetation indices, the photochemical reflectance index (PRI) demonstrated the strongest correlations with all evaluated plant phenotypes. Partial least squares regression (PLSR) models effectively predicted morphological attributes, with R2CV values ranging from 0.81 to 0.87 and RPDP values exceeding 2.09 for all parameters. Based on Pearson's coefficient XYZ interpolations and HVI algorithms, the NIR−SWIR band combination proved the most effective for predicting height and leaf area, while VIS−NIR was optimal for optimal energy yield, and VIS−VIS was best for predicting biomass. To further corroborate these findings, the SWIR bands for certain morphological characteristic wavelengths selected with s−PLS were most significant for SWIR1 and SWIR2, while i−PLS showed a more uniform distribution in VIS−NIR−SWIR bands. Therefore, SWIR hyperspectral bands provide valuable insights into developing alternative bands for remote sensing measurements to estimate plant morphological parameters. These findings underscore the potential of remote sensing technology for rapid, accurate, and non-invasive monitoring within stationary high-throughput phenotyping systems in greenhouses. These insights align with advancements in digital and precision technology, indicating a promising future for research and innovation in this field. [ABSTRACT FROM AUTHOR]

The concept of skin microbiota is not really clear and more accurate approaches are necessary to explain how microbial flora can influence skin biophysical parameters in healthy individuals and in pathology patients with non-infectious skin disease. The aim of this work is to provide a suitable, fast and reproducible protocol to correlate skin parameters with the composition of skin microbiota. For this purpose, the work was split into two main phases. The first phase was focused on the selection of volunteers by the administration of a specific questionnaire. The skin microbiota was then collected from the forehead of selected volunteers as a test area and from the shoulder as control area. On the same skin area, the biophysical parameters, such as trans-epidermal water loss (TEWL), sebum level (SL), porphyrin intensity, keratin content and stratum corneum water content were taken. All parameters were taken at t0 and after 15 days without changes in the volunteers' lifestyle. A strong correlation was found between forehead and shoulder area for porphyrin intensity, pH and TEWL parameters, and between Cutibacterium acnes and some biophysical parameters both in the forehead and the shoulder area. The procedural setup in this work represents the starting point for evaluating problematic skins and the efficacy of cosmetic products or treatment against skin dysbiosis. [ABSTRACT FROM AUTHOR]

Northeast Brazil (NEB), particularly its semiarid region, represents an area highly susceptible to the impacts of climate change, including severe droughts, and intense anthropogenic activities. These stresses may be accelerating environmental degradation and desertification of soil in NEB. The main aim of this study was to gain geospatial insights into the biophysical parameters of surface energy balance and actual evapotranspiration on a multi-temporal scale, aiming to detect and analyze the spectral behavioral patterns of areas vulnerable to degradation processes, based on thematic maps at the surface, for NEB and mainly the semiarid region of NEB from 2000 to 2019. Geospatial data from 8-day MODIS sensor products were used, such as surface reflectance (Terra/MOD09A1 and Aqua/MYD09A1), surface temperature (Terra/MOD11A2 and Aqua/MYD11A2), and actual evapotranspiration (Terra/MOD16A2 and Aqua/MYD16A2), version 6. Therefore, in this study, pixel-to-pixel values were processed by calculating the average pixel statistics for each year. From the reflectance product, digital processing of the surface albedo and spectral vegetation indices was also carried out, using computational programming scripts and machine learning algorithms developed via the Google Earth Engine (GEE) platform. The study also presents a seasonal analysis of these components and their relationships over 20 years. Through vegetation indices and statistical correlations, a new predictive model of actual evapotranspiration was developed. The quantitative and spatiotemporal spectral patterns of the parameters were assessed through descriptive statistics, measures of central tendency and dispersion, and statistical error analyses and correlation indices. Thematic maps highlighted the pixel-to-pixel results, with patterns of high temperature distribution mainly in the central and northeastern part of NEB and the semiarid region of NEB, highlighting the formation of persistent heat islands over time. Meanwhile, in these areas, the maps of actual evapotranspiration showed a drastic reduction due to the lesser availability of energy. Over time, the semiarid region of NEB presented areas with little and/or no vegetation cover, which were highly well-defined between the years 2012 and 2019, confirming that these areas are extremely vulnerable to degradation and desertification processes due to significant loss of vegetative and water resilience. The components of energy balance were highly interconnected to climatological and environmental conditions, showing the severe results of drought and accentuation of the water deficit in NEB, presenting a greater condition of aridity in the semiarid region of NEB over time.

Background: Skin is the largest organ in the body, representing an important interface to monitor health and disease. However, there is significant variation in skin properties for different ages, genders and body regions due to the differences in the structure and morphology of the skin tissues. This study aimed to evaluate the use of non‐invasive tools to discriminate a range of mechanical and functional skin parameters from different skin sites. Materials and methods: A cohort of 15 healthy volunteers was recruited following appropriate informed consent. Four well‐established CE‐marked non‐invasive techniques were used to measure four anatomical regions: palm, forearm, sole and lower lumbar L3, using a repeated measures design. Skin parameters included trans‐epidermal water loss (TEWL), pH (acidity), erythema, stratum corneum hydration and stiffness and elasticity using Myoton Pro (skin and muscle probe). Differences between body locations for each parameter and the intra‐rater reliability between days were evaluated by the same operator. Results: The results indicate that parameters differed significantly between skin sites. For the Myoton skin probe, the sole recorded the highest stiffness value of 1006 N/m (SD ± 179), while the lower lumbar recorded the least value of 484 N/m (SD ± 160). The muscle indenter Myoton probe revealed the palm's highest value of 754 N/m (± 108), and the lower lumbar recorded the least value of 208 N/m (SD ± 44). TEWL values were lowest on the forearm, averaging 11 g/m2/h, and highest on the palm, averaging 41 g/m2/h. Similar skin hydration levels were recorded in three of the four sites, with the main difference being observed in the sole averaging 13 arbitrary units. Erythema values were characterised by a high degree of inter‐subject variation, and no significant differences between sites or sides were observed. The Myoton Pro Skin showed excellent reliability (intra‐class correlation coefficients > 0.70) for all sites with exception of one site right lower back; the Myoton pro muscle probes showed good to poor reliability (0.90–017), the corneometer showed excellent reliability (>0.75) among all the sites tested, and the TEWL showed Good to poor reliability (0.74–0.4) among sites. Conclusion: The study revealed that using non‐invasive methods, the biophysical properties of skin can be mapped, and significant differences in the mechanical and functional properties of skin were observed. These parameters were reliably recorded between days, providing a basis for their use in assessing and monitoring changes in the skin during health and disease. [ABSTRACT FROM AUTHOR]

• SUHII of 21 Brazilian metropolitan regions were characterised from 2003 to 2022. • SUHI intensities are increasing with contrasting patterns. • Latitude affects the occurrence of SUHI seasonality and its intensity. • Urban night-time LST reflects an increase in net surface radiation (Rn). • Evapotranspiration is decreasing due to the urbanisation process. • Enhanced surface albedo and vegetation cover is an alternative to mitigate SUHIs. This study analysed the influence of urbanisation on the expansion of surface urban heat island intensities (SUHIIs) and the variability of biophysical parameters in twenty one major Brazilian Metropolitan Regions (MRs), from 2003 to 2022. We use land surface temperature (LST) data from MODIS sensors to continuously quantify the daytime and night-time SUHIIs. Spectral reflectance and re-analysis data were used to access the variability of Enhanced Vegetation Index-2 (EVI2), surface albedo (α), urban area (UA) growth, net surface radiation (Rn), and actual evapotranspiration (ET). The Mann-Kendall trend test was applied to all variables and their relationships with LST were investigated using statistical metrics. The results show that the SUHIIs were 60 % (1.64 °C) higher during the daytime than during the night, with significant growth trends throughout the studied period and more pronounced monthly seasonal variations in higher latitude MRs. The UAs are shown to be more influential on LST during the daytime, with the association of LST with EVI2 and α playing a fundamental role in regulating the urban climate. The results also demonstrate that increasing ET potentially mitigates LST, especially during the daytime. For the night-time, Rn is a stronger factor influencing LST, leading to the higher availability of sensible heat. [ABSTRACT FROM AUTHOR]

This study endeavors to produce a comprehensive land cover map for Morocco, addressing the absence of such a detailed map in the country. Our research encompasses ecological and climatic aspects specific to Morocco, while the methods used can be adapted to various regions and countries, considering their unique climatic conditions and land cover types. A combination of MODIS and Landsat datasets was employed to create a 5 km resolution Land Use and Land Cover (LULC) map for the entire nation. The process involved the aggregation and advanced processing of these datasets using surface processes algorithms. The resulting LULC map is the first of its kind for Morocco, shedding light on land cover distribution nationwide. It shows that approximately 13.5% of the country is covered by forests, predominantly in the Atlas and Rif mountains, Rabat–Sale, and the southern regions. Grasslands occupy over 16% of the study area, mainly in the north-east and west. Urban areas, including major cities like Casablanca, Rabat, and Marrakech, span nearly 3400 km². Moreover, large areas of shrublands and bare lands are evident across the country, while agricultural lands account for almost 20% of the national territory, mainly in the interior plains and north-western Atlantic coast. This study forms a crucial basis for ecological and climatic research in Morocco and serves as a valuable reference for various disciplines such as agriculture, natural resource management, and climate modeling. The mapping of biophysical parameters for each land cover class is a key feature of our research, and these parameters will be instrumental in a subsequent study examining the impact of urban development on surface climate in Morocco. Overall, our study underscores the importance of understanding biophysical parameters in addressing environmental and societal challenges.

Yao Pan,1– 3 Xue Ma,1,2 Yanqing Song,1,2 Jinfeng Zhao,1,2 Shiyu Yan1,2 1Department of Cosmetics, College of Chemistry and Materials Engineering, Beijing Technology and Business University, Beijing, 100048, People’s Republic of China; 2Beijing Key Laboratory of Plant Research and Development, Beijing, 100048, People’s Republic of China; 3Institute of Cosmetic Regulatory Science, Beijing Technology and Business University, Beijing, 100048, People’s Republic of ChinaCorrespondence: Yao PanDepartment of Cosmetics, College of Chemistry and Materials Engineering, Beijing Technology and Business University, Beijing, People’s Republic of ChinaTel +86-10-68984937Email panyao@btbu.edu.cnBackground: Questionnaires and lactic acid sting test (LAST) are two widely used methods to identify sensitive skin. However, the self-perceived sensitive skin by questionnaires was not consistent with the determination of LAST.Objective: The aim of the study was to measure the biophysical properties noninvasively of sensitive skin evaluated by questionnaire and LAST and to investigate their correlations with the scores of questionnaire and LAST.Methods: A total of 209 healthy Chinese females completed the study. Self-assessment questionnaire and LAST were both performed to identify sensitive skin. Epidermal biophysical properties, including skin hydration, transepidermal water loss (TEWL), sebum content, erythema index (EI), a&ast; value, L&ast; value, skin elasticity, and skin pH, were measured with noninvasive instruments.Results: The frequency of sensitive skin was 50.2% and 66.0% by questionnaire and LAST, respectively. Subjects with self-assessed sensitive skin had a slightly higher LAST positive rate. Skin hydration, sebum content, a&ast; and EI values were significantly higher in the self-assessed sensitive skin group, while TEWL, a&ast; and EI values increased but L&ast; value decreased with significance in the LAST positive group. The LAST stingers among sensitive skin subjects had higher EI but not in the healthy skin subjects. In addition, questionnaire scores positively correlated with skin hydration, sebum content, a&ast; and EI values, while a positive relationship of LAST scores with TEWL, a&ast; and EI values was observed. The scores of questionnaire and LAST both negatively related to L&ast; value.Conclusion: Self-assessed questionnaire is associated with sensitive skin featured by oily and red face without impaired barrier function, whereas LAST is suitable to identify fragile skin barrier and enhanced blood flow on the face. Combination of both methods to diagnose sensitive skin might be more reliable.Keywords: sensitive skin, questionnaire, lactic acid sting test, biophysical parameters

Background and objective: The hemodynamic model is a fundamental approach for successfully monitoring and possibly forecasting brain activities in the biomedical engineering field. The hemodynamic model describes the inner scenario of a blood flowing voxel in a human brain and it is most popular hypothesis on the brain related research activities. The hemodynamic model has nonlinearities in nature. The solution of such type hemodynamic model is researchable work. Method: There are many model solving algorithms by using fMRI images; recently, Haifeng Wu presented Confounds Square-root Cubature Kalman Filtering and Confounds Square-root Cubature Smoothing (CSCKF-CSCKS) is the latest approach for solving hemodynamic models. The relative accuracy of this model was shown 84%. In this article, in order to achieve better accuracy, the data analysis and model algorithms are presented differently and find new result that was not mentioned earlier. Result: The data analysis of this experiment shows that if the maximum number of iterations increases three times, the overall accuracy for solving the hemodynamic model raises by 5.76% under the exact type of fMRI measurements used in both cases. We also represent a formula for calculating a relative error to evaluate the performance of these estimations. Conclusion: A recommendation is made for solving the hemodynamic model algorithm by using fMRI images to get better performance for estimating the model's biophysical parameters and hidden states. As a result, we will find out more accurate scenario of a specific region of human brain by using fMRI images of that region.

Hyperspectral technology offers significant potential for non-invasive monitoring and prediction of morphological parameters in plants. In this study, UV−VIS−NIR−SWIR reflectance hyperspectral data were collected from Nicotiana tabacum L. plants using a spectroradiometer. These plants were grown under different light and gibberellic acid (GA3) concentrations. Through spectroscopy and multivariate analyses, key growth parameters, such as height, leaf area, energy yield, and biomass, were effectively evaluated based on the interaction of light with leaf structures. The shortwave infrared (SWIR) bands, specifically SWIR1 and SWIR2, showed the strongest correlations with these growth parameters. When classifying tobacco plants grown under different GA3 concentrations in greenhouses, artificial intelligence (AI) and machine learning (ML) algorithms were employed, achieving an average accuracy of over 99.1% using neural network (NN) and gradient boosting (GB) algorithms. Among the 34 tested vegetation indices, the photochemical reflectance index (PRI) demonstrated the strongest correlations with all evaluated plant phenotypes. Partial least squares regression (PLSR) models effectively predicted morphological attributes, with R2CV values ranging from 0.81 to 0.87 and RPDP values exceeding 2.09 for all parameters. Based on Pearson’s coefficient XYZ interpolations and HVI algorithms, the NIR−SWIR band combination proved the most effective for predicting height and leaf area, while VIS−NIR was optimal for optimal energy yield, and VIS−VIS was best for predicting biomass. To further corroborate these findings, the SWIR bands for certain morphological characteristic wavelengths selected with s−PLS were most significant for SWIR1 and SWIR2, while i−PLS showed a more uniform distribution in VIS−NIR−SWIR bands. Therefore, SWIR hyperspectral bands provide valuable insights into developing alternative bands for remote sensing measurements to estimate plant morphological parameters. These findings underscore the potential of remote sensing technology for rapid, accurate, and non-invasive monitoring within stationary high-throughput phenotyping systems in greenhouses. These insights align with advancements in digital and precision technology, indicating a promising future for research and innovation in this field.

Burns are common practices in Brazil and cause major fires, especially in the Legal Amazon. This study evaluated the dynamics of the fire foci in the Legal Amazon in Brazil and their consequences on environmental degradation, particularly in the transformation of the forest into pasture, in livestock and agriculture areas, mining activities and urbanization. The fire foci data were obtained from the reference satellites of the BDQueimadas of the CPTEC/INPE for the period June 1998–May 2022. The data obtained were subjected to descriptive and exploratory statistical analysis, followed by a comparison with the PRODES data during 2004–2021, the DETER data (2016–2019) and the ENSO phases during the ONI index for the study area. Biophysical parameters were used in the assessment of environmental degradation. The results showed that El Niño's years of activity and the years of extreme droughts (2005, 2010 and 2015) stand out with respect to significant increase in fire foci. Moreover, the significant numbers of fire foci indices during August, September, October and November were recorded as 23.28%, 30.91%, 15.64% and 10.34%, respectively, and these were even more intensified by the El Niño episodes. Biophysical parameters maps showed the variability of the fire foci, mainly in the south and west part of the Amazon basin referring to the Arc of Deforestation. Similarly, the states of Mato Grosso, Pará and Amazonas had the highest alerts from PRODES and DETER, and in the case of DETER, primarily mining and deforestation (94.3%) increased the environmental degradation. The use of burns for agriculture and livestock, followed by mining and wood extraction, caused the degradation of the Amazon biome. [ABSTRACT FROM AUTHOR]

The concept of skin microbiota is not really clear and more accurate approaches are necessary to explain how microbial flora can influence skin biophysical parameters in healthy individuals and in pathology patients with non-infectious skin disease. The aim of this work is to provide a suitable, fast and reproducible protocol to correlate skin parameters with the composition of skin microbiota. For this purpose, the work was split into two main phases. The first phase was focused on the selection of volunteers by the administration of a specific questionnaire. The skin microbiota was then collected from the forehead of selected volunteers as a test area and from the shoulder as control area. On the same skin area, the biophysical parameters, such as trans-epidermal water loss (TEWL), sebum level (SL), porphyrin intensity, keratin content and stratum corneum water content were taken. All parameters were taken at t0 and after 15 days without changes in the volunteers’ lifestyle. A strong correlation was found between forehead and shoulder area for porphyrin intensity, pH and TEWL parameters, and between Cutibacterium acnes and some biophysical parameters both in the forehead and the shoulder area. The procedural setup in this work represents the starting point for evaluating problematic skins and the efficacy of cosmetic products or treatment against skin dysbiosis.

Abstract The remote sensing techniques must be used to obtain long-term information in remote areas, like the Antarctic continent, to monitor the environmental productivity and its changes. The aim of this work was to analyze the surface reflectance profile patterns for the Antarctic biological soil crusts (algae, lichens, and mosses) in an area of Nelson Island (South Shetland Islands, maritime Antarctic), calculated from Landsat and Sentinel-2 images to identify its similarities and differences due to targets, sensors and acquired date. The surface reflectance values for Antarctic biological soil crusts are similar for those observed for biological soil crusts in other Earth extreme environments, like deserts. In Landsat images, the differences among biological soil crusts surface reflectance were identified at visible and near-infrared wavelengths and for Sentinel-2 images, the differences occur at visible, red-edge and shortwave infrared wavelengths, showing the feasibility of using surface reflectance products to identify these different crusts, despite its inherent pixel spectral mixture. Long-term biophysical parameters from such crusts as retrieved from orbital data is not possible due to very low cloud-free images over the Antarctic, which prevents building a consistent surface reflectance time-series which covers all biological soil crusts growth season.

The carbon emissions linked to land use and cover, has been drawing attention in the scientific community. The objective of this work was to estimate carbon sequestration in different uses and land cover in areas of the Cerrado Biome, in the North of Minas Gerais, specifically in the Environmental Protection Area of Rio Pandeiros (APA-RP). Orbital remote sensing techniques were used, especially the combination of the estimation models of Photosynthetically Active Absorbed Radiation, Light Use Efficiency and Evaporative Fraction. For the Cerradão, Eucalyptus, FED, Pastures and Veredas areas in the summer, values of 15.61, 21.03, 18.37, 15.28 and 19.99 g C / m-2 / dm-1 were estimated, and in winter, 10.52, 15.97, 3.23, 2.05 and 7.50 g C / m-2 / dm-1. [ABSTRACT FROM AUTHOR]

Introduction: At present, there is a lack of baseline data on the facial skin biophysical profile of women in Malaysia. The implications related to the daily habits and facial skincare product use on the skin biophysical condition are, thus, unknown. In this study, we aim to evaluate facial skin biophysical parameters of Malaysian women and examine the influence of demographic characteristics, daily habits, and facial skincare product use on these parameters. Methods: Four skin biophysical parameters – transepidermal water loss (TEWL), melanin content, elasticity, and collagen intensity – were assessed on the cheek of the subjects (20–60 years). Demographic background, daily habits, and skincare product use were gauged through a survey. Only 197 from the 213 subjects recruited initially were used for analysis after the data were screened for normality. Results: The biophysical parameters were similar in different races, except a higher melanin content in Indian female individuals. Elasticity and collagen intensity reduced with age, while melanin content increased in the older age-groups. But no difference was observed in TEWL at different ages. Evaluating the influence of daily habits, we observed that exercise significantly lowered TEWL and increased melanin content, which may be associated with UV radiation exposure. Facial skincare products are popular among the female subjects (>85% users). Products with moisturizing, sunscreening, and other skincare functions (astringent, antiaging, and anti-wrinkle) were preferred by subjects of all ages. These product functions significantly improve skin elasticity and reduce melanin content in the young adults. While aged women recognized the importance of having an additional skin-lightening function in their skincare routine. Although the influence of individual skincare function on skin biophysical parameters was mostly positive, the alteration of these parameters varied at different ages. Conclusion: This is the first report of facial skin biophysical profile of Malaysian women. There is no difference among 3 major races saved for melanin content. This work demonstrated age-dependent influences on the biophysical parameters, except TEWL. The significance of skincare product use is well reflected in the improvement of these parameters at different age-groups based on individual skincare functions. [ABSTRACT FROM AUTHOR]

Quantifying the variation of biophysical parameters and their driving mechanisms is essential for monitoring land surface environmental changes and for understanding the land–atmosphere interaction in the arid region. Due to the complexity of human activities, most researches are limited to climate change, whereas the response analysis of human activities to changes in biophysical parameters are still lacking or not comprehensively considered. Therefore, large biases and uncertainties still exist in the estimates of regional responses to global change. Firstly, we specifically quantified the main human activities related to land use/land cover change (LULCC) in the northern Tianshan Mountains (NTM), and identified the spatiotemporal changes of primary biophysical parameters, including Albedo, leaf area index (LAI), land surface temperature (LST), and Normalized Difference Vegetation Index (NDVI). Then, we tested the performance of the five models used, including multiple linear regression (MLR), random forest (RF), support vector regression (SVR), multi-layer perceptron (MLP), and K-nearest neighbor (KNN). RF outperformed others and was used to quantify and disaggregate the contribution of climate change and human activities to land surface parameters in the NTM. We found a strong spatial heterogeneity in the spatial variation of all biophysical parameters. Except for LST, the annual maximum Albedo, LAI, and NDVI showed a significant increasing trend in the NTM from 2000 to 2019 (p

Background: Skin is constantly exposed to mechanical and chemical insults, in the form of prolonged loading, overhydration or exposure to irritants. An array of non‐invasive biophysical tools has been adopted to monitor the changes in skin response. The present study aims to identify a set of robust parameters sensitive to mechanical and chemical challenges to skin integrity. Materials and methods: Eleven healthy participants were recruited to evaluate the skin response following mechanical loading, tape stripping, overhydration and chemical irritation. Forearm skin responses were recorded at baseline and at three time points following the insult. Measurements included transepidermal water loss, sub‐epidermal moisture, erythema and laser Doppler imaging. Thresholds were informed by basal values, and the sensitivity of parameters to detect skin changes was evaluated. Results: High degree of variability in skin response was observed with selected biophysical parameters, such as sub‐epidermal moisture, laser Doppler imaging and erythema, even in the absence of an applied insult. Temporal skin response revealed distinct response profiles during each evoked insult. Indeed, the sensitivity of the biophysical parameters was influenced by the threshold values and time point of measurement. Some statistically significant correlations were determined between the biophysical parameters. Conclusion: The study revealed that thresholds derived from single biophysical parameters were limited in detecting skin changes following insults. A complementary evaluation using combined parameters has the potential to provide a more sensitive assessment. Further research is required to identify robust biophysical parameters, to aid the early detection of skin damage in clinical settings. [ABSTRACT FROM AUTHOR]

Evapotranspiration (ET) is an important parameter in hydrologic processes and modelling. In agricultural watersheds with competing uses of fresh water including irrigated agriculture, estimating crop evapotranspiration (ETc) accurately is critical for improving irrigation system and basin water management. The use of remote sensing‐based basal crop coefficients is becoming a common method for estimating crop evapotranspiration for multiple crops over large areas. The Normalized Difference Vegetation Index (NDVI) and the Soil Adjusted Vegetation Index (SAVI), based on reflectance in the red and near‐infrared bands, are commonly used for this purpose. In this paper, we examine the effects of row crop orientation and soil background darkening due to shading and soil surface wetness on these two vegetation indices through modelling, coupled with a field experiment where canopy reflectance of a cotton crop at different solar zenith angles, was measured with a portable radiometer. The results show that the NDVI is significantly more affected than the SAVI by background shading and soil surface wetness, especially in north–south oriented rows at higher latitudes and could lead to a potential overestimation of crop evapotranspiration and irrigation water demand if used for basal crop coefficient estimation. Relationships between the analysed vegetation indices and canopy biophysical parameters such as crop height, fraction of cover and leaf area index also were developed for both indices. [ABSTRACT FROM AUTHOR]

Aim. To determine the electrophysiological and biophysical predictors of sustained isolation of pulmonary vein (PV) ostia, affecting the immediate and longterm results of interventional treatment of atrial fibrillation (AF) using cryoballoon ablation (CBA) with the second-generation cryoballoon Arctic Front Advance.Material and methods. The analysis included 143 PV in 37 patients with a paro-xysmal/persistent form of AF, which, after the primary CBA with the use of the second-generation cryoballoon, carried out additional interventions due to recurrence of AF and/or combined arrhythmia. During the primary CBA, the registration of biophysical and electrophysiological parameters of the procedure was performed. During the ablation in the right PV from the diagnostic electrode installed in the superior vena cava, the ipsilateral phrenic nerve was stimulated (2000 ms, 25 mA). When the phrenic nerve response to stimulation was decreased/disappeared, ablation ceased instantly. At the end of the procedure, isolation control of the PV was performed. A repeat/additional procedure was performed for the recurrence of AF and/or documented combined arrhythmia no earlier than 3 months after the initial ablation. The stability of the LV isolation was assessed using a circular mapping technique. According to the results of mapping, drugs were divided into 2 groups: isolated and with recurrent activity.Results. The frequency of sustained isolation of PV was 67,8%. Recurrent spike activity was recorded in 46 PV (32,2%). Higher frequency of registration of electrical isolation of PV in real time (68% vs 50%, p=0,001), stability of occlusion with a cryoballoon (85,5% vs 69,5%, p=0,024), low values of the minimum cryoballoon temperatures reached (49,2±6,3 vs 44,0±4,9, p

Abstract Background To investigate the possibility of using maternal biophysical parameters only in screening for the different types of gestational hypertensive diseases. Methods A total of 969 pregnant women were randomly screened in first and second trimester, of which 8 developed Early-onset Preeclampsia, 29 Late-onset Preeclampsia, 35 Gestational Hypertension and 897 women had a normal outcome. An observational maternal hemodynamics assessment was done via standardized electrocardiogram-Doppler ultrasonography, Impedance Cardiography and bio-impedance, acquiring functional information on heart, arteries, veins and body fluid. Preliminary prediction models were developed to test the screening potential for early preeclampsia, late preeclampsia and gestational hypertension using a Partial Least Square Discriminant Analysis. Results A combined model using maternal characteristics with cardiovascular parameters in first and second trimester offers high screening performance with Area Under the Curve of 99,9% for Early-onset Preeclampsia, 95,3% for Late-onset Preeclampsia and 94% for Gestational Hypertension. Conclusions Using biophysical parameters as fundament for a new prediction model, without the need of biochemical parameters, seems feasible. However, validation in a large prospective study will reveal its true potential.

Forest canopies have an important influence on the global climate balance. Through the analysis of the temperature of the canopy, it is possible to infer about the physiological aspects of the plants, helping to understand the behavior of the vegetation and, consequently, in the environmental monitoring and management of green areas. This study aims to validate the MOD11A2 V006 product from canopy surface temperature data obtained by an infrared radiation sensor. For the validation of the MOD11A2 product, a comparative analysis was performed between the land surface temperature (LST) data, obtained by the MODIS sensor, and the canopy temperature data, obtained by the SI-111 infrared radiation sensor coupled to the Itatiaia National Park (PNI) micrometeorological tower. Meteorological variables and land surface temperature collected from January to December 2018 in the PNI were also analyzed. The results reveal that the MOD11A2 product overestimates the canopy temperature in the daytime (MB ranging from 1.56 to 3.57 °C) and underestimates in the night time (MB ranging from − 0.18 to − 4.22 °C). During daytime, the months corresponding to the dry season presented a very high correlation (r = 0.74 and 0.86) and the highest values for the Willmott index (d = 0.70 and 0.64). At nighttime, the MOD11A2 product did not present a good performance for the LST estimation, especially in the rainy season. Therefore, we observed that the MOD11A2 product has limitations to estimate the land surface temperature and that possible changes in the algorithm of this product can be performed for high atmospheric humidity conditions. [ABSTRACT FROM AUTHOR]

The effect of evolutionary history on wood density variation may play an important role in shaping variation in wood density, but this has largely not been tested. Using a comprehensive global dataset including 27,297 measurements of wood density from 2621 tree species worldwide, we test the hypothesis that the legacy of evolutionary history plays an important role in driving the variation of wood density among tree species. We assessed phylogenetic signal in different taxonomic (e.g., angiosperms and gymnosperms) and ecological (e.g., tropical, temperate, and boreal) groups of tree species, explored the biogeographical and phylogenetic patterns of wood density, and quantified the relative importance of current environmental factors (e.g., climatic and soil variables) and evolutionary history (i.e., phylogenetic relatedness among species and lineages) in driving global wood density variation. We found that wood density displayed a significant phylogenetic signal. Wood density differed among different biomes and climatic zones, with higher mean values of wood density in relatively drier regions (highest in subtropical desert). Our study revealed that at a global scale, for angiosperms and gymnosperms combined, phylogeny and species (representing the variance explained by taxonomy and not direct explained by long-term evolution process) explained 84.3% and 7.7% of total wood density variation, respectively, whereas current environment explained 2.7% of total wood density variation when phylogeny and species were taken into account. When angiosperms and gymnosperms were considered separately, the three proportions of explained variation are, respectively, 84.2%, 7.5% and 6.7% for angiosperms, and 45.7%, 21.3% and 18.6% for gymnosperms. Our study shows that evolutionary history outpaced current environmental factors in shaping global variation in wood density., Competing Interests: The authors have no competing interest to declare., (© 2024 Kunming Institute of Botany, Chinese Academy of Sciences. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co., Ltd.)

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Vittorio Mazzarello, Marco Ferrari, Pasquale Ena Skinlab, Department of Biomedical Sciences, University of Sassari, Sassari, Italy Background: Werner syndrome (WS) is a rare autosomal recessive disorder characterized by premature aging in adults. Although not sufficient to diagnose WS, persistent short stature and alteration of the dentition are among the few early signs that appear at puberty and can lead to a suspected diagnosis. Objective: The study aimed at quantifying the signs of WS skin aging through biophysical parameters to find new parameters to be applied together with clinical observations in order to diagnose the disease early. Patients and methods: The skin disorders induced by the disease were studied using noninvasive techniques: Tewameter TM300, Corneometer CM825, Skin-pH-Meter PH900, Mexameter MX16, Visioscan VC98, and Cutometer MPA580. Twenty-four patients divided into young group, WS group, and elderly group were recruited for the study. Results: The WS skin is quite similar to aged skin, with some differences concerning the barrier function and skin elasticity; for instance, a WS patient of 30 years of age has the same skin roughness of a 50/60 years old subject with a more severe skin condition leading to higher dryness, high transepidermal water loss, and less distensibility correlating with skin indurations. Conclusion: In patients with WS, the biophysical parameters can quantify the damage induced on the skin by the disease. In order to stage the degree of the disease, biophysical parameters could be used in the future as a diagnostic procedure in the initial stages of the disease as they may reveal lesions not yet clinically perceptible or in advanced stages. Keywords: Werner syndrome, biophysical parameters, skin aging, noninvasive analysis

Reseña de tesis doctoral defendida el 17 de Julio de 2017. Lugar: Facultat de Física, Universitat de València.

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COVID-19 has resulted in millions of deaths and severe impact on economies worldwide. Moreover, the emergence of SARS-CoV-2 variants presented significant challenges in controlling the pandemic, particularly their potential to avoid the immune system and evade vaccine immunity. This has led to a growing need for research to predict how mutations in SARS-CoV-2 reduces the ability of antibodies to neutralize the virus. In this study, we assembled a set of 1813 mutations from the interface of SARS-CoV-2 spike protein's receptor binding domain (RBD) and neutralizing antibody complexes and developed a machine learning model to classify high or low escape mutations using interaction energy, inter-residue contacts and predicted binding free energy change. Our approach achieved an Area under the Receiver Operating Characteristics (ROC) Curve (AUC) of 0.91 using the Random Forest classifier on the test dataset with 217 mutations. The model was further utilized to predict the escape mutations on a dataset of 29,165 mutations located at the interface of 83 RBD-neutralizing antibody complexes. A small subset of this dataset was also validated based on available experimental data. We found that top 10 % high escape mutations were dominated by charged to nonpolar mutations whereas low escape mutations were dominated by polar to nonpolar mutations. We believe that the present method will allow prioritization of high/low escape mutations in the context of neutralizing antibodies targeting SARS-CoV-2 RBD region and assist antibody design for current and emerging variants. • Change in binding affinity alone is not capable of accurately predicting the immune escape of the SARS-CoV-2 RBD mutation • Combining interaction energy, binding affinity change and residue contacts predicts antibody escape with 82% accuracy • Charged to nonpolar mutations are frequent in high immune escape and polar to nonpolar are least prone to immune escape • Predictions on the blind test dataset were found consistent with available experimental observation for high escape mutations [ABSTRACT FROM AUTHOR]