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Run-off modelling of pervious and impervious areas using couple SWAT and a novel machine learning model in cross-rivers state Nigeria

Salele B, Dodo YA, Sani DA, Abuhussain MA, Sayfutdinovna Abdullaeva B, Brysiewicz A

Water Sci Technol, 2023 Oct;88(7):1893-1909.
PMID: 37831003 DOI: 10.2166/wst.2023.304

Using the soil and water assessment tool (SWAT), runoff in pervious and impervious urban areas was simulated in this study. In the meantime, as a novel application of machine learning, the emotional artificial neural network (EANN) model was employed to enhance the SWAT obtained for this study. As a result of the EANN model's capabilities in rainfall-runoff phenomena, the SWAT-EANN couple model has been used to assess urban flooding. The pervious, impervious, and water body areas of the study area were classified and mapped to estimate the cover change over three epochs. Land use map, precipitation data, temperature (minimum and maximum) data, wind speed, relative humidity, soil map, solar radiation, and digital elevation model were used as inputs for modelling rainfall-runoff of the study area in the ArcGIS environment. The accuracy assessment of this study was excellent (root-mean-square error 1 mm of precipitation). It also revealed that (a) a land use map illustrating changes in impervious, pervious surface, and water body for 1998, 2008, and 2018; (b) runoff modelling using a historical pattern of rainfall-runoff changes (1998-2018); and (c) descriptive statistical analysis of the runoff results of the research. This research will aid in urban planning, administration, and development. Specifically, it will prevent flooding and environmental problems.
Gender differences in the prevalence and psychopathological mechanisms of internet addiction among Iranians aged 18 to 24: A nationwide study

Hammood YM, Abdullaeva B, Abdullaev D, Sunitha BK, Yajid MSA, Singh A, et al.

Child Abuse Negl, 2025 Mar 25;163:107428.
PMID: 40138740 DOI: 10.1016/j.chiabu.2025.107428

BACKGROUND: The rapid advancement of technology has revolutionized interaction, learning, and entertainment but also led to Internet addiction, characterized by excessive internet use causing impairment or distress.
OBJECTIVE: The study explores gender differences in prevalence, risk factors, and clinical aspects of Internet addiction among Iranian youth, highlighting cultural and societal influences.
METHODS: A nationwide sample of 3149 individuals aged 18 to 24 was categorized into two groups: those with Internet addiction (n = 1040) and those without (n = 2109). Participants completed the Childhood Trauma Questionnaire-28, Dissociative Experiences Scale (DES), Difficulties in Emotion Regulation Scale (DERS), and Internet Addiction Test (IAT). Data analyses were conducted using SPSS software version 26, with a significance level set at <0.05.
RESULTS: Overall prevalence of Internet addiction was found to be 33 %, with a higher incidence in males (63.3 %) compared to females (36.7 %) (χ2 = 13.28, p = 0.001). In men, the severity of Internet addiction was significantly linked to emotional abuse (β = 0.20, p˂0.001), DES (β = 0.39, p˂0.001), and DERS (β = 0.16, p˂0.001) (F(3, 654) = 89.85, p˂0.001, R2 = 0.29); while in women, it was associated with emotional abuse (β = 0.18, p˂0.001) and dissociative experiences (β = 0.16, p˂0.001) (F(2, 379) = 13.70, p˂0.001, R2 = 0.06). The DES partially mediated the relationship between emotional abuse and IAT scores in both genders, whereas DERS only did so in males.
CONCLUSIONS: The study suggests Internet addiction as a maladaptive coping mechanism for early emotional abuse, highlighting the need for prevention programs and emotion regulation interventions. Future research should consider longitudinal effects and cultural influences.

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