Statistical assessment of natural radioactivity, radon activity, and associated radiological exposure due to artisanal mining in Atiwa West district of the Eastern region, Ghana.

The activity concentration of natural radionuclides, radon activity concentration, mass and area exhalation rates have been studied in soils from gold mining communities in Atiwa West district. The natural radionuclides were determined by gamma ray spectrometry method while radon concentrations were measured using CR-39 detectors. The mean activity concentrations were found to be 26.9 ± 1.7 Bq/kg, 57.5 ± 3.6 Bq/kg, 237.5 ± 17.6 Bq/kg and 560.0 ± 54 Bq/m3 for Ra-226, Th-232, K-40 and Rn-222 respectively. The evaluated mass exhalation rates ranged from 2.8 ± 0.3 to 6.5 ± 0.7 × 10-5 Bq/kg/h while the area exhalation rates were from 0.8 ± 0.09 to 2.0 ± 0.21 × 10-3 Bq/m2/h. Some mining and farming areas recorded high exhalation rates indicating that the use of soils as building materials from such areas could pose a level of radiation hazard to the population. The evaluated radiological risks were below reference levels. A good linear correlation was observed between Ra-226 and Rn-222 activity concentrations and in the investigated soils. The Pearson correlation coefficient, cluster analysis and principal component analysis were used to study the relationship between the determined parameters of the study.

Ecological and human health risk assessment of potentially toxic elements in water and soils within a crude oil waste management facility, Southwestern Ghana.

Crude oil waste management is challenging due to the diverse constituents of the waste and its consequent impact on valued environmental receptors (water and soil). Characterization of the potentially toxic elements (PTEs) in soils and water within the surroundings of crude oil waste management facility is imperative, to aid evaluation of potential risks. The study assessed the potential environmental and human health risks posed by PTEs in soil and water from surroundings and adjoining settlement communities. A total of forty-four (44) samples were analyzed for PTEs (Cr, Pb, Zn, Co, Mn, Ni, Hg, Fe, As, Cu, Hg, and Cd) and physicochemical properties in both matrices. The total carcinogenic risk (TCR) for adults and children in the neighbouring community was 4.73 × 10-6 and 1.2 × 10-4, respectively, which was due to the high carcinogenic slope factor of arsenic. A strong correlation was observed between the PTEs and physicochemical properties, and their health risk was attributed to both geogenic and anthropogenic factors. The study indicated that the human health and ecological risk values obtained were within acceptable limits, with the waste management facility posing a higher risk in comparison to the nearby community. These risks may be attributed to the specific nature and intensity of the activities conducted at the facility. Hence, there is the need for continuous promotion of occupational and public awareness on the health and environmental impact of crude oil waste management.

Environmental radiation and health risk assessment in the neighborhood of a radioactive waste management facility.

The Radioactive Waste Management Center (RWMC) of the Ghana Atomic Energy Commission (GAEC) operates a licensed radioactive waste management facility known as the Centralized Radioactive Waste Management Facility (CRWMF). The Center undertakes environmental radiation monitoring in which indoor dose rates at various microenvironments, and nearby ambient environments of the facility are measured. A 2-year radiation dose data (i.e., 2017 and 2018) obtained from the monitoring exercise was used to determine whole-body exposure and cancer risk analysis for adult and child age groups. With the exception of the high dose area of the facility, observed doses in all microenvironments of the facility as well as the ambient environment were below the regulatory dose limits of 1 mSv/y and 20 mSv/y, set for radiation workers and the general public, respectively. Dose rate variation for the 2017 and 2018 datasets were not significant (p > 0.05) at 95% confidence interval (CI). Cancer risks due to exposure to alpha, neutron, and gamma radiation sources for both adult and child age groups were above the global average value of 2.90 × 10-4 reported by the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR). Gamma sources recorded the highest cancer risk followed by neutron and alpha sources with risk values of 3.95 × 10-1 and 3.92 × 10-2; 4.06 × 10-2 and 4.03 × 10-3; and 7.96 × 10-4 and 7.91 × 10-5 for the adult and child age groups, respectively. Radium (226Ra) recorded the highest activity concentration (9.62 × 1010 Bq) with 4 quantities in the inventory while plutonium-beryllium (as alloyed source) recorded the lowest activity concentration (9.82 × 1001) with 12 quantities in the inventory.

Influence of photolysis on source characterization and health risk of polycyclic aromatic hydrocarbons (PAHs), and carbonyl-, nitro-, hydroxy- PAHs in urban road dust.

In this study, PAHs and their transformed PAH products (TPPs) in road dust were subjected to UV driven photolysis, and then extracted using simultaneous pressurized fluid extraction, and analysed using Shimadzu Triple Quadrupole GC/MS. The results of the analysis were used to investigate the robustness and reliability of 14 existing diagnostic ratios (DRs) and two newly proposed molecular DRs that are relevant for characterizing the sources of PAHs and TPPs. The influence of photolysis on the carcinogenic health risk posed to humans by these hazardous pollutants was then assessed. The findings indicated that the DRs segregated into stable, moderately stable and non-stable classes of source characteristics under the influence of photolysis. Only two of the existing DRs, namely, benzo(a)pyrene/benzo(ghi)perylene (BaP/BghiP) and total index exhibited consistent stability to photolysis, whilst fluoranthene/(fluoranthene + pyrene) (FRT/(FRT+PYR)) showed moderate stability. The two newly proposed DRs, naphthalene/1-nitronaphthalene (NAP/NNAP) and pyrene/(1-nitropyrene + 1-hydroxypyrene) (PYR/(1NPY+HPY)) were found to be highly reliable in post-emission source characterization. The cross-plots of the most stable DRs showed that traffic emissions is the primary source of PAHs, whilst post-emission photolysis is the secondary source of nitro-PAH (NPAH) TPPs. The percent resonance energy thermodynamic stability of the PAH pollutants does not exert any direct influence on the source characteristics of the DRs. Adults are more vulnerable to potential carcinogenic risks as a result of PAH and TPPs photolysis whereas negligible risk exist for children. This study contributes to a more reliable diagnosis of PAH and TPP sources and thus, to the regulatory mitigation of these hazardous pollutants thereby, promoting enhanced protection of human health and the environment.

Multi-modular AI Approach to Streamline Autism Diagnosis in Young Children.

Autism has become a pressing healthcare challenge. The instruments used to aid diagnosis are time and labor expensive and require trained clinicians to administer, leading to long wait times for at-risk children. We present a multi-modular, machine learning-based assessment of autism comprising three complementary modules for a unified outcome of diagnostic-grade reliability: A 4-minute, parent-report questionnaire delivered via a mobile app, a list of key behaviors identified from 2-minute, semi-structured home videos of children, and a 2-minute questionnaire presented to the clinician at the time of clinical assessment. We demonstrate the assessment reliability in a blinded, multi-site clinical study on children 18-72 months of age (n = 375) in the United States. It outperforms baseline screeners administered to children by 0.35 (90% CI: 0.26 to 0.43) in AUC and 0.69 (90% CI: 0.58 to 0.81) in specificity when operating at 90% sensitivity. Compared to the baseline screeners evaluated on children less than 48 months of age, our assessment outperforms the most accurate by 0.18 (90% CI: 0.08 to 0.29 at 90%) in AUC and 0.30 (90% CI: 0.11 to 0.50) in specificity when operating at 90% sensitivity.

Machine learning approach for early detection of autism by combining questionnaire and home video screening.

Background: Existing screening tools for early detection of autism are expensive, cumbersome, time- intensive, and sometimes fall short in predictive value. In this work, we sought to apply Machine Learning (ML) to gold standard clinical data obtained across thousands of children at-risk for autism spectrum disorder to create a low-cost, quick, and easy to apply autism screening tool. Methods: Two algorithms are trained to identify autism, one based on short, structured parent-reported questionnaires and the other on tagging key behaviors from short, semi-structured home videos of children. A combination algorithm is then used to combine the results into a single assessment of higher accuracy. To overcome the scarcity, sparsity, and imbalance of training data, we apply novel feature selection, feature engineering, and feature encoding techniques. We allow for inconclusive determination where appropriate in order to boost screening accuracy when conclusive. The performance is then validated in a controlled clinical study. Results: A multi-center clinical study of n = 162 children is performed to ascertain the performance of these algorithms and their combination. We demonstrate a significant accuracy improvement over standard screening tools in measurements of AUC, sensitivity, and specificity. Conclusion: These findings suggest that a mobile, machine learning process is a reliable method for detection of autism outside of clinical settings. A variety of confounding factors in the clinical analysis are discussed along with the solutions engineered into the algorithms. Final results are statistically limited and will benefit from future clinical studies to extend the sample size.

Rainfall erosivity index for the Ghana Atomic Energy Commission site.

Rainfall erosivity is the potential ability for rainfall to cause soil loss. The purpose of this study was to estimate the rainfall erosivity index for the Ghana Atomic Energy Commission site in order to compute the surface erosion rate. Monthly rainfall data, for the period 2003-2012 were used to compute annual rainfall erosivity indices for the site, using the Modified Fournier index. Values of the annual rainfall erosivity indices ranged from 73.5 mm for 2004 to 200.4 mm for the year 2003 with a mean annual erosivity index of 129.8 mm for the period. The Pearson's Coefficient of Correlation was used to establish the relationship between annual rainfall and annual rainfall erosivity. This showed a high degree of positive relationship (r = 0.7) for the study area. The computed mean annual erosivity index revealed that the site is in the high erosion risk zone. Therefore, it is necessary to develop soil protection and management strategies to protect the soil from erosion.

Technologically Enhanced Naturally Occurring Radioactive Materials (TENORM) in the Oil and Gas Industry: A Review.

Radiation is part of the natural environment: it is estimated that approximately 80 % of all human exposure comes from naturally occurring or background radiation. Certain extractive industries such as mining and oil logging have the potential to increase the risk of radiation exposure to the environment and humans by concentrating the quantities of naturally occurring radiation beyond normal background levels (Azeri-Chirag-Gunashli 2004).

The hydrochemistry of groundwater in the Densu River Basin, Ghana.

Hydrochemical analyses of groundwater samples were used to establish the hydrochemistry of groundwater in the Densu River Basin. The groundwater was weakly acidic, moderately mineralized, fresh to brackish with conductivity ranging from of 96.6 microS cm(-1) in the North to 10,070 microS cm( - 1) in the South. Densu River basin have special economic significance, representing the countries greatest hydrostructure with freshwater. Chemical constituents are generally low in the North and high in the South. The order of relative abundance of major cations in the groundwater is Na+>Ca2+>Mg2+>K+ while that of anions is Cl->HCO3->SO4(2-)>NO3-. Four main chemical water types were delineated in the Basin. These include Ca-Mg-HCO3, Mg-Ca-Cl, Na-Cl, and mixed waters in which neither a particular cation nor anion dominates. Silicate weathering and ion exchange are probably the main processes through which major ions enter the groundwater system. Anthropogenic activities were found to have greatly impacted negatively on the quality of the groundwater.

Winners don't take all: Characterizing the competition for links on the web.

As a whole, the World Wide Web displays a striking "rich get richer" behavior, with a relatively small number of sites receiving a disproportionately large share of hyperlink references and traffic. However, hidden in this skewed global distribution, we discover a qualitatively different and considerably less biased link distribution among subcategories of pages-for example, among all university homepages or all newspaper homepages. Although the connectivity distribution over the entire web is close to a pure power law, we find that the distribution within specific categories is typically unimodal on a log scale, with the location of the mode, and thus the extent of the rich get richer phenomenon, varying across different categories. Similar distributions occur in many other naturally occurring networks, including research paper citations, movie actor collaborations, and United States power grid connections. A simple generative model, incorporating a mixture of preferential and uniform attachment, quantifies the degree to which the rich nodes grow richer, and how new (and poorly connected) nodes can compete. The model accurately accounts for the true connectivity distributions of category-specific web pages, the web as a whole, and other social networks.