Harnessing urban analytics and machine learning for sustainable urban development: A multidimensional framework for modeling environmental impacts of urbanization in Saudi Arabia

Sustainable urban development is crucial for managing natural resources and mitigating environmental impacts induced by rapid urbanization. This study demonstrates an integrated framework using machine learning-based urban analytics techniques to evaluate spatiotemporal urban expansion in Saudi Arabia (1987-2022) and quantify impacts on leading land, water, and air-related environmental parameters (EPs). Remote sensing and statistical techniques were applied to estimate vegetation health, built-up area, impervious surface, water bodies, soil characteristics, thermal comfort, air pollutants (PM2.5, CH4, CO, NO2, SO2), and nighttime light EPs. Regression assessment and Principal Component Analysis (PCA) were applied to assess the relationships between urban expansion and EPs. The findings highlight the substantial growth of urban areas (0.067%-0.14%), a decline in soil moisture (16%-14%), water bodies (60%-22%), a nationwide increase of PM2.5 (44 μg/m3 to 73 μg/m3) and night light intensity (0.166-9.670) concentrations resulting in significant impacts on land, water, and air quality parameters. PCA showed vegetation cover, soil moisture, thermal comfort, PM2.5, and NO2 are highly impacted by urban expansion compared to other EPs. The results highlight the need for effective and sustainable interventions to mitigate environmental impacts using green innovations and urban development by applying mixed-use development, green space preservation, green building technologies, and implementing renewable energy approaches. The framework recommended for environmental management in this study provides a robust foundation for evidence-based policies and adaptive management practices that balance economic progress and environmental sustainability. It will also help policymakers and urban planners in making informed decisions and promoting resilient urban growth.

Decoding seasonal variability of air pollutants with climate factors: A geostatistical approach using multimodal regression models for informed climate change mitigation

In response to changes in climatic patterns, a profound comprehension of air pollutants (AP) variability is vital for enhancing climate models and facilitating informed decision-making in nations susceptible to climate change. Earlier research primarily depended on limited models, potentially neglecting intricate relationships and not fully encapsulating associations. This study, in contrast, probed the spatiotemporal variability of airborne particles (CO, CH4, SO2, and NO2) under varying climatic conditions within a climate-sensitive nation, utilizing multiple regression models. Spatial and seasonal AP data were acquired via the Google Earth Engine platform, which indicated elevated AP concentrations in primarily urban areas. Remarkably, the average airborne particle levels were lower in 2020 than in 2019, though they escalated during winter. The study employed linear regression, Pearson's correlation (PC), Spearman rank correlation models, and Geographically Weighted Regression (GWR) models to probe the relationship between pollutant variability and climatic elements such as rainfall, temperature, and humidity. Across all seasons, APs showed a negative correlation with rainfall while displaying positive correlations with temperature and humidity. The GWR and PC models produced the most reliable results from all the models employed, with the GWR model superseding the rest. Moreover, heightened aerosol levels were detected within a rainfall range of 600 mm/season, a temperature range of 25-30 °C, and humidity levels of 75 %-85 %. Overall, this study emphasizes the growing levels of APs in correlation with meteorological changes. By adopting a comprehensive approach and considering multiple factors, this research provides a more sophisticated understanding of the relationship between AP variability and climatic shifts.

Spatiotemporal characterization of relative humidity trends and influence of climatic factors in Bangladesh

The frequency and intensity of climate change and resulting impacts are more prevalent in South Asian countries, particularly in Bangladesh. Relative humidity (RH) is a crucial aspect of climate, and higher RH variability has far-reaching impacts on human health, agriculture, environment, and infrastructure. While temperature and rainfall have gained much research attention, RH studies have received scant attention in the research literature. This study investigated the trends and variability of RH levels in Bangladesh and the influence of other meteorological factors over the past 40 years. Variabilities in the meteorological factors were identified by calculating descriptive statistics. Innovative trend analysis (ITA) and Mann-Kendall test (MK-test) methods were utilized to assess monthly, seasonal, and annual trends. The magnitude of temperature, rainfall, and windspeed influences on RH variability were identified using Pearson's correlation, Spearman rank correlation, and Kendall correlation model. Variability analysis showed higher spatial variations in RH levels across the country, and RH skewed negatively in all stations. Results reveal that daily, monthly, seasonal, and annual trends of RH exhibited positive trends in all stations, with an increasing rate of 0.083-0.53% per year in summer, 0.43-0.68% per year in winter, and 0.58-0.31% per year in the rainy season. Both ITA and MK-test provided consistent results, indicating no discrepancies in trend results. All three models indicate that temperature, rainfall, and windspeed have weak to moderate positive influences on changing RH levels in Bangladesh. The study will contribute to decision-making to improve crop yields, health outcomes, and infrastructure efficiency.

A GIS and remote sensing approach for measuring summer-winter variation of land use and land cover indices and surface temperature in Dhaka district, Bangladesh

Rapid urbanization has induced land use and land cover change (LULC) that increases land surface temperature (LST). Analyzing seasonal variations of LULC and LST is a precondition for mitigating heat island effects and promoting a sustainable living environment. The objective of this study is to explore the association between the seasonal LST dynamics and LULC indices for the Dhaka district of Bangladesh. The LULC indices are comprised of the Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI), Normalized Difference Bareness Index (NDBAI), and Modified Normalized Difference Water Index (MNDWI). The results show that the LULC effect on LST in Dhaka is significant, with an increase in summer season LST from 34.58 °C to 37.66 °C and in winter season LST from 24.710C to 26.24 °C. Predictably, the highest and lowest LST values were observed in the built-up and vegetation-covered areas, respectively. Secondly, the correlation values indicate a significant inverse correlation (R² > 0.50) between NDVI and LST, as well as MNDWI and LST. On the contrary, positive correlations were observed between NDBI and LST, and between NDBAI and LST for both the summer and winter seasons. Finally, subsequent vegetation decline (-69.34%) and increasing built-up area (+11.30%) between 2000 and 2020 in Dhaka district were found to be the most significant factors for the increasing trend and spatial heterogeneity of LST in Dhaka. The methodological approach of this study offers a low-cost efficient technique for monitoring LST hotspots, which can guide land use planners and urban managers for spatial intervention to ensure a livable environment.

Utility of cytokine, adhesion molecule and acute phase proteins in early diagnosis of neonatal sepsis

Background and Aim:

Neonatal infection, including bacterial sepsis, is a major health care issue with an annual global mortality in excess of one million lives. Therefore, this study aimed to evaluate the potential diagnostic value of C-reactive protein (CRP), E-selectin, procalcitonin (PCT), interleukins-6 (IL-6), and tumor necrosis factor-α (TNF-α) both independently and in combination for the diagnosis of neonatal sepsis in its earliest stages.

Materials and Methods:

A total of 320 subjects were included in this study. A prospective cross-sectional study was conducted among neonates admitted to Neonatal Intensive Care Unit at King Abdulaziz Medical City, Riyadh, KSA during January 2013 to August 2015, the study based on three study groups categorized according to clinical symptoms and blood culture result. Study groups include healthy control neonates (n = 80), clinical sepsis (CS) group (n = 80) with clinical signs of sepsis but their blood culture was negative, and sepsis group with clinical signs of sepsis and their blood culture was positive.

Results:

The study observed significant difference in plasma levels of CRP, IL-6, TNF-α, E-selectin, and PCT in patients group when compared with control group (P < 0.001). Furthermore, the levels are significantly different between patient groups including CS and neonatal sepsis group. Moreover, result observed significant difference in CRP and IL-6 in early onset sepsis (EOS) when compared with late onset sepsis (LOS) neonates (P < 0.001 and 0.01), respectively, while there were no significant difference in TNF-α, E-selectin, and PCT between EOS and LOS (P = 0.44, 0.27 and 0.24), respectively. Regarding biomarkers accuracy, the result showed that CRP has the best diagnostic accuracy with cutoff value of 3.6 ng/ml (sensitivity 78% and specificity of 70%). The best combination is shown with CRP and IL-6 in which sensitivity increased to 89% and specificity to 79%.

Conclusion:

It was concluded that infected new-born babies have a higher E-selectin, PCT, IL-6, TNF-α, and CRP compared with the neonates with CS and control. IL-6, TNF-α, and CRP should be measured in combination for mare diagnostic accuracy in neonatal sepsis. Likewise, PCT should be investigated as a part of sepsis screening for all suspected neonates.

Effects of vitamin E, age and sex on performance of Japanese quail. 1. Haematological indices and liver function

1. A trial was conducted to examine the effects of dietary vitamin E content, age and sex on haematological indices and liver enzymes of Japanese quails. A total of 800 1-d-old quail chicks were assigned at random into 4 equal groups and fed on starter and layer diets containing 0, 1, 5 or 10 times the NRC recommended supplements of vitamin E. No selenium was added to the basal deficient diets; the other diets were supplied with 0.2 mg selenium/kg diet. 2. The investigation covered the age span of 3 to 12 weeks in female and male birds. Blood samples were collected at 3-week intervals and tested for haematological indices (erythrocyte count; leucocyte count; susceptibility of erythrocytes to haemolysis; haemoglobin concentration (Hb); packed cell volume (PCV); and mean corpuscular volume (MCV)) and liver enzymes (aspartate transaminase, AST, and glutathione peroxidase, GSH-Px). 3. The significant differences between the 4 dietary treatments indicated that as the levels of selenium and/or vitamin E increased, the percentage of erythrocytes haemolysed and AST activity decreased, whereas Hb and GSH-Px concentrations increased. 4. Differences between age groups showed that older quails had higher erythrocyte susceptibility to haemolysis, higher AST levels and but lower erythrocyte count and PCV. 5. Females had lower erythrocyte haemolysis and higher Hb concentrations than males. 6. The interaction between dietary groups and age groups revealed that the differences between age groups were reduced as the level of selenium and/or vitamin E increased, leading to similar group means over the age period of study. 7. In conclusion, NRC recommended supplements of vitamin E (12 and 25 mg/kg diet) were not adequate. Doses equal to, at least, 5 times that recommended were advised to improve GSH-Px (index of antioxidant status) and Hb concentrations.

Defective growth hormone (GH) secretion and short-term treatment in Noonan syndrome

Auxological and endocrine data from 12 prepubertal children (3 males, 9 females) with Noonan syndrome (NS) were compared with those of 15 children with constitutional short stature (CSS), 20 children with partial GH deficiency (GHD), and 6 children with Turner syndrome (TS). Four children with NS were treated with human growth hormone (hGH) (n = 4) (25 units/m2 week, divided on daily s.c. doses). In children with NS, the peak serum GH response to clonidine (5.4 +/- 2.7 ug/L) and glucagon (7.4 +/- 3.4 ug/L) were significantly lower than those for children with CSS (14.8 +/- 3.4 and 12.8 +/- 2.8 ug/L respectively). Nine out of the 12 (75%) children with NS did not mount normal GH peak (10 ug/L or more) after provocation. The 12-h integrated GH secretion in the 3 children with NS who had normal GH response to provocation (2.7 +/- 0.7 ug/L) was markedly lower compared to that for children with CSS (6.7 +/- 1.2 ug/L). The serum insulin-like growth factor-1 (IGF-I) concentrations were lower in children with NS (67 +/- 32 ng/ml) vs CSS (165 +/- 35 ng/ml), but not different from those for GHD children (59 +/- 33 ng/ml). In 4 children with NS, hGH therapy for a year increased height growth velocity from 4.1 +/- 0.3 cm/yr to 7.4 +/- 0.6 cm/yr and height standard deviation score (Ht SDS) from -2.2 +/- 0.6 to -1.45 +/- 0.3. This growth acceleration was accompanied by an increase in IGF-I concentration (from 52 +/- 21 ng/ml to 89 +/- 25 ng/ml). In summary, these results prove a defect of the GH secretion in children with NS and suggest that GH therapy has an important role in the management of their short stature.

Prevalence of chorea, dystonia and athetosis in Assiut, Egypt: a clinical and epidemiological study

Involuntary movements originate from different parts of the nervous system. The character of movements depends upon the site of the lesion and the type of pathological change. The presence of more than one type of involuntary movement in a patient can cause confusion and difficulty in the proper classification of movement disorders, which then leads to problems in the differential diagnosis and appropriate treatment. This work was planned to estimate the prevalence and to study the aetiological factors of chorea, dystonia, athetosis and hemiballismus in Assiut, a representative community of Upper Egypt. This study was carried out on 7,000 families (42,000 subjects) representing different types of communities (2,000 families from urban, 2,000 families from suburban and 3,000 families from rural communities). All members of these samples were personally interviewed at home. Full clinical assessment and special investigations required for the diagnosis of different types of chorea, dystonia and athetosis were carried out in Assiut University Hospital. The prevalence rate for rheumatic chorea was 62/100,000 population and it was significantly higher (p < 0.01) among rural than urban and suburban populations, whereas Huntington's chorea had a prevalence rate of 21/100,000 with no significant difference between different areas studied (urban, suburban and rural). The other two common types of chorea were reported with prevalence rates of 12/100,000 for the encephalitic type and 17/100,000 for the atherosclerotic type. No single case of generalized dystonia was recorded and all cases were of the focal type of dystonia with a prevalence rate of 26/100,000 population. No significant differences were recorded between the different areas studied (urban, suburban and rural).(ABSTRACT TRUNCATED AT 250 WORDS)