UNASSIGNED: Salt-affected soils have significant enough salt concentrations to impact other land and soil resource uses, plant health, soil characteristics, and water quality. Consequently, a study was carried out in the South Ethiopian Rift Valley area around the lakes of Abaya and Chamo to determine the intensity and the types of salt-affected soil and map their spatial distributions.
UNASSIGNED: At 0-20 cm depths, a grid soil sampling scheme was employed to gather data from agricultural soils affected by salt. An adequately spaced grid cell of 200 m*200 m or seven transects, with seven samples collected every 200 m on each sampling site, was generated by the QGIS software\'s Fishnet tool, and an auger collected 226 soil samples from the proposed 245 soil sampling points. The analysis and interpretation of the data were done using both statistical and geostatistical methods. The un-sampled surface was predicted and mapped from laboratory point data using the standard Kriging algorithm in QGIS.
UNASSIGNED: According to the results, the soil in the study area was rated as strongly alkaline and moderately alkaline in the reaction. The coefficient of variation (CV) was the lowest for soil pH. Except for the Ganta Kanchama site, low CV (<10 %) confirmed the similarity of pH values throughout all research areas. The EC values depicted that the study area is slightly saline except for the Ganta Kanchame site, which rated moderately saline to strongly saline. The variability of soil EC rated moderate to strong variation for the studied area. The exchangeable sodium percentage (ESP) values distribution between the study sites demonstrates considerable variability and difference. The area is dominated by low to high-risk rate soil sodicity, as evidenced by the soil ESP CV of the studied area, which was >100 % and showed significant variability among the samples. Out of 2274.65ha of the studied area, the type of salt 62.28 %, 26.09 %, 10.99 %, and 0.63 % were categorized as non-saline non-sodic, saline-sodic, sodic, and saline, respectively. Following saline-sodic, sodic, and saline soils, respectively, non-saline and non-sodic soils comprise most of the investigated areas.
UNASSIGNED: The result indicates almost all the salt-affected areas were situated in relatively lower slope areas exhibiting a flat to almost flat slope (0-2%). The study\'s findings are that the studied area needs specific soil management strategies to boost the salinity and sodicity problems around the study area and recommended reclamation techniques as the extent of the problems.

BACKGROUND: The United Nations established the Sustainable Development Goals (SDGs) in 2015 to enhance global development. In this study, we examine an SDG indicator: the percentage of women aged 15-49 whose family planning needs are met by modern contraception (mDFPS). We evaluate both the factors influencing its coverage and its progress since 2015.
METHODS: We used nationally representative surveys data (Demographic and Health Surveys (DHS) and Performance Monitoring for Action (PMA)) from Ethiopia, Kenya, and Nigeria. We assessed predictors of mDFPS. We also computed mDFPS coverage across countries and subnational areas, assessing coverage changes from the SDGs onset to the most recent period, using a Bayesian model-based geostatistical approach. We assessed whether the subnational areas exceeded the minimum recommended WHO mDFPS coverage of 75%.
RESULTS: Varied individual and community-level determinants emerged, highlighting the countries\' uniqueness. Factors such as being part of a female-headed household, and low household wealth, lowered the odds of mDFPS, while rural-residence had low odds only in Ethiopia and Nigeria. The results indicate mDFPS stagnation in most administrative areas across the three countries. Geographic disparities persisted over time, favouring affluent regions. The predicted posterior proportion of mDFPS and exceedance probability (EP) for WHO target for Ethiopia was 39.85% (95% CI: [4.51, 83.01], EP = 0.08) in 2016 and 46.28% (95% CI: [7.15, 85.99], EP = 0.13) in 2019. In Kenya, the adjusted predicted proportion for 2014 was 30.19% (95% CI: [2.59, 80.24], EP = 0.06) and 44.16% (95%CI: [9.35, 80.24], EP = 0.13) in 2022. In Nigeria, the predicted posterior proportion of mDFPS was 17.91% (95% CI: [1.24, 61.29], EP = 0.00) in 2013, and it was 23.08% (95% CI: [1.80, 56.24], EP = 0.00) in 2018. None of the sub-national areas in Ethiopia and Nigeria exceeded the WHO target. While 9 out of 47 counties in Kenya in 2022 exceeded the WHO mDFPS target.
CONCLUSIONS: The study unveils demographic, geographic, and socioeconomic mDFPS disparities, signalling progress and stagnation across administrative areas. The findings offer policymakers and governments insights into targeting interventions for enhanced mDFPS coverage. Context-specific strategies can address local needs, aiding SDG attainment.

For all the benefits of a compost barn system to be achieved, the management, especially with the bedding, must be done correctly. One should consider the requirements regarding the revolving of the material, use of good quality organic matter, suitable ventilation, and an ideal animal stocking rate, so that the composting occurs efficiently. Given this, this work aimed to evaluate the spatial variability of thermal characteristics of rice straw bedding, using values of temperature (surface and internal) and humidity. The temperature and moisture values of the litter were recorded at intervals during the morning shift, from 6:00 am to 7:00 am and from 8:00 am to 9:00 am, and during the afternoon shift, from 3:00 pm to 4:00 pm and from 5:00 pm to 6:00 pm, considering the management of the turn-over, that is, before and after the movement of the litter. Litter variables were collected at points distributed on a 39-point grid. There were no differences between litter surface temperatures before and after turning over in the morning shift, but in the afternoon shift, the surface temperature was lower (P < 0.05) before, when compared to after turning. The internal temperature and litter moisture were higher (P < 0.05) before revolving in both shifts. Spatial dependence was verified (IDE) for the variables studied. Based on the geostatistical analysis, it is concluded that the IDE was rated as strong for surface and internal temperatures, which demonstrates heterogeneity among the points evaluated and a large spatial variability regarding bed temperatures. In the case of litter moisture, the greatest variability occurred in the morning period. The litter surface temperature values did not exceed the ambient air temperature values.

The quality of water used for irrigation is one of the major threats to maintaining the long-term sustainability of agricultural practices. Although some studies have addressed the suitability of irrigation water in different parts of Bangladesh, the irrigation water quality in the drought-prone region has yet to be thoroughly studied using integrated novel approaches. This study aims to assess the suitability of irrigation water in the drought-prone agricultural region of Bangladesh using traditional irrigation metrics such as sodium percentage (NA%), magnesium adsorption ratio (MAR), Kelley\'s ratio (KR), sodium adsorption ratio (SAR), total hardness (TH), permeability index (PI), and soluble sodium percentage (SSP), along with novel irrigation indices such as irrigation water quality index (IWQI) and fuzzy irrigation water quality index (FIWQI). Thirty-eight water samples were taken from tube wells, river systems, streamlets, and canals in agricultural areas, then analyzed for cations and anions. The multiple linear regression model predicted that SAR (0.66), KR (0.74), and PI (0.84) were the primary important elements influencing electrical conductivity (EC). Based on the IWQI, all water samples fall into the \"suitable\" category for irrigation. The FIWQI suggests that 75% of the groundwater and 100% of the surface water samples are excellent for irrigation. The semivariogram model indicates that most irrigation metrics have moderate to low spatial dependence, suggesting strong agricultural and rural influence. Redundancy analysis shows that Na+, Ca2+, Cl-, K+, and HCO3- in water increase with decreasing temperature. Surface water and some groundwater in the southwestern and southeastern parts are suitable for irrigation. The northern and central parts are less suitable for agriculture because of elevated K+ and Mg2+ levels. This study determines irrigation metrics for regional water management and pinpoints suitable areas in the drought-prone region, which provides a comprehensive understanding of sustainable water management and actionable steps for stakeholders and decision-makers.

Aedes mosquitoes are some of the most important and globally expansive vectors of disease. Public health efforts are largely focused on prevention of human-vector contact. A range of entomological indices are used to measure risk of disease, though with conflicting results (i.e. larval or adult abundance does not always predict risk of disease). There is a growing interest in the development and use of biomarkers for exposure to mosquito saliva, including for Aedes spp, as a proxy for disease risk. In this study, we conduct a comprehensive geostatistical analysis of exposure to Aedes mosquito bites among a pediatric cohort in a peri‑urban setting endemic to dengue, Zika, and chikungunya viruses. We use demographic, household, and environmental variables (the flooding index (NFI), land type, and proximity to a river) in a Bayesian geostatistical model to predict areas of exposure to Aedes aegypti bites. We found that hotspots of exposure to Ae. aegypti salivary gland extract (SGE) were relatively small (< 500 m and sometimes < 250 m) and stable across the two-year study period. Age was negatively associated with antibody responses to Ae. aegypti SGE. Those living in agricultural settings had lower antibody responses than those living in urban settings, whereas those living near recent surface water accumulation were more likely to have higher antibody responses. Finally, we incorporated measures of larval and adult density in our geostatistical models and found that they did not show associations with antibody responses to Ae. aegypti SGE after controlling for other covariates in the model. Our results indicate that targeted house- or neighborhood-focused interventions may be appropriate for vector control in this setting. Further, demographic and environmental factors more capably predicted exposure to Ae. aegypti mosquitoes than commonly used entomological indices.

Several statistical techniques have been adopted in the analysis and interpretation of radiometric survey data set with little attention to the geostatistical approach. In this study, the geostatistical technique was used to analyse an airborne uranium data set in the North-western part of Ogun state to deduce the autocorrelation level of uranium with the corresponding geological composition through the geostatistical model fitting. Twelve uranium lithological (UL) units were identified and analysed using variogram and kriging. Three variogram models namely; spherical, exponential and gaussian, were utilised. The variogram results showed that the three models fit in the interpretation of uranium data in the order of Spherical < Gaussian < Exponential models for all the UL units except at UL6 which had range (R) values of 4227.3 m, 5318.2 m and 5636.4 m for Gaussian, Spherical and Exponential models, respectively. The Nugget-Sill ratios (NSR) were in the range of 3.57-18.97% for the three models across the 12 UL units. These results indicate strong spatial autocorrelation/dependency of uranium concentration on geological composition. The ordinary kriging estimator revealed that the weathered basement formation has the highest uranium concentration compared to basement and sedimentary formations across the study area. The coefficient of variation results also revealed homogeneity in the uranium source across the UL units. The geostatistics technique is a useful mathematical tool in the analysis and interpretation of uranium concentration in the North-western part of Ogun State.

BACKGROUND: Injury-causing events are not randomly distributed across a landscape, but how they are associated with the features and characteristics of the places where they occur in Arizona (AZ) remains understudied. Clustering of trauma events and associations with areal sociodemographic characteristics in the greater Phoenix (PHX), AZ region can promote understanding and inform efforts to ameliorate a leading cause of death and disability for Arizonans. The outcomes of interest are trauma events unrelated to motor vehicle crashes (MVC) and the subgroup of trauma events due to interpersonal assaults.
METHODS: A retrospective, ecological study was performed incorporating data from state and national sources for the years 2013-2017. Geographically weighted regression models explored associations between the rates of non-MVC trauma events (n/10,000 population) and the subgroup of assaultive trauma events per 1000 and areal characteristics of socioeconomic deprivation (areal deprivation index [ADI]), the density of retail alcohol outlets for offsite consumption, while controlling for race/ethnicity, population density, and the percentage urban population.
RESULTS: The 63,451 non-MVC traumas within a 3761 mile2 study area encompassing PHX and 22 surrounding communities, an area with nearly 60% of the state\'s population and 54% of the trauma events in the AZ State Trauma Registry for the years 2013-2017. Adjusting for confounders, ADI was associated with the rates of non-MVC and assaultive traumas in all census block groups studied (mean coefficients 0.05 sd. 0.001 and 0.07 sd. 0.002 for non-MVC and assaultive trauma, respectively). Alcohol retail outlet density was also associated with non-MVC and assaultive traumas in fewer block groups compared to ADI.
CONCLUSIONS: Socioeconomic deprivation and alcohol outlet density were associated with injury producing events in the greater PHX area. These features persist in the environment before and after the traumas occur. Ongoing research is warranted to identify the most influential areal predictors of traumatic injury-causing events in the greater PHX area to inform and geographically target prevention initiatives.

Metal(loid) pollution in vegetable field soils has become increasingly severe and affects the safety of vegetable crops. Research in China has mainly focused on greenhouse vegetables (GV), while open field vegetables (OV) and the spatial distribution patterns of metal(loid)s in the surrounding soils have rarely been assessed. In the present study, spatial analysis methods combining Geographic Information Systems (GIS) and Moran\'s I were applied to analyze the effects of vegetable fields on metal(loid) accumulation in soils. Overall, vegetable fields affected the spatial distribution of metal(loid)s in soils. In long-term vegetable production, the use of large amounts of organic fertilizer led to the bioconcentration of cadmium (Cd) and mercury (Hg), and long-term fertilization resulted in a significant pH decrease and consequent transformation and migration of chromium (Cr), lead (Pb), and arsenic (As). Thus, OV fields with a long history of planting had lower average pH and Cd, and higher average As, Cr, Hg, and Pb than GV fields, reached 0.93%, 10.1%, 5.8%, 3.0%, 80.8%, and 0.43% respectively. Due to the migration and transformation of metal(loid)s in OV soils, these should be further investigated regarding their abilities to reduce the accumulation of metal(loid)s in soils and protect the quality of the cultivated land.

Soil iron has an important impact on the ecological environment and on crop growth. This study selected a typical small watershed basin in the middle reaches of the Han River (Yujiehe) at Ankang City and used geostatistical methods and kriging interpolation to analyze the spatial distribution and structure of soil iron content for different land uses and at different depths, using the single-factor pollution evaluation to evaluate the pollution degree of soil iron. The results showed that soil iron in the Yujie River basin decreased with increasing soil depth, with contents of 8.80 mg/kg, 5.52 mg/kg, and 4.92 mg/kg at depths A1 (0-20 cm), A2 (20-40 cm), and A3 (40-60 cm). According to the classification index of effective trace elements in soil, the average contents of soil iron at these three depths were between 4.5 and 10 mg/kg, which are all considered moderate values. The coefficients of variation of soil iron at the three soil depths were 59%, 75%, and 83%, all of which showed moderate spatial variability, and the coefficient of variation increased gradually with soil depth. With semi-variance calculated at the three soil depths, soil iron optimal theoretical models were all exponential models with nugget coefficients of 9.52%, 47.76%, and 33.93%, indicating that spatial correlation was very strong in the A1 layer and moderate in the A2 and A3 layers. The spatial distribution of soil iron showed some variation in the study area, and the soil content was higher in the midwestern part in the A1 and A2 layers; however, in the A3 layer, the higher content was in the center and lower content was in the southern region. Correlations were significant between soil iron content on the one hand and land-use type and topographic factors on the other. The pollution indices of soil iron at the three soil depths under different land uses were all greater than 1.0, with the A1 layer in farmland being the worst, at 3.34. In the study area, using the background value of soil iron as an evaluation standard, the soil iron content of more than 65% of the Yujiehe region exceeded this standard.

The conditions of the sources of heavy metals are essential to assess its potential threats to human health. The identification of the origin of heavy metals is essential for planning effective measures to control long-term accumulation of heavy metals. In this study, analysis of pollution sources was performed on 100 soil samples with geostatistics and absolute principal component score-multiple linear regression (APCS-MLR) receptor model. The descriptive statistics revealed that concentrations of heavy metals (Pb, Zn, Cu, Ni) have exceeded the background value of Zhejiang Province. The coefficient of variation is Pb > Cd > Cu > Zn > Ni > Cr. The APCS-MLR and geo statistical analysis showed that sources of pollution: PC1 was Ni, Cr, Cu, Zn because of soil parent material. The contribution rates were 89.42%, 87.19%, 29.64%, and 33.58%, respectively. The PC2 was Pb, Zn and Cu which were mainly caused by anthropogenic mining activities. The contribution rates were 95.92%, 24.81%, and 40.62%, respectively. The PC3 was Cd、Zn and Cu which was mainly caused by agricultural inputs, and their contribution rates were 91.96%, 41.61%, and 30.14% respectively. According to Nemero Synthesis Index evaluation method, the Shaoxing City Zhejiang, China is heavily polluted with heavy metals.