Traffic-informed Pavement Performance Prediction and Maintenance Prioritization Using the Pavement Condition Index: A Case Study from Afghanistan
Published on: 27th August, 2026
Road infrastructure serves as the primary medium of economic and agricultural transportation in developing countries. Afghanistan’s district roads play a critical role in connecting rural production centers to markets; however, systematic maintenance is often hindered by inadequate funding, lack of structural monitoring, and climatic deterioration. This research develops pavement condition assessment and deterioration prediction models using Pavement Condition Index (PCI), pavement age, characteristic rebound deflection (Dc), and Average Annual Daily Traffic (AADT). Multiple regression models were generated based on recorded field data across six district road sections in Herat Province. Regression coefficients demonstrated high goodness of fit (R² = 0.964 – 0.992), indicating reliable predictive capability. Based on PCI-based prioritization, maintenance strategies were ranked and scheduled under budget constraints. Results indicate that Sections D01 and D02 urgently require rehabilitation due to structural fatigue and distress propagation, while other sections can be preserved through preventive maintenance. This study provides a scientifically supported PMS framework for Afghan district roads, enabling optimized resource allocation, deterioration forecasting, and long-term serviceability planning.
Risk Factors and Their Impact on Diabetes Mellitus in Elderly People
Published on: 20th August, 2026
Diabetes mellitus is a metabolic disorder characterized by chronic hyperglycemia and disrupted carbohydrate, fat, and protein metabolism, representing a growing health issue in Bosnia and Herzegovina, particularly among the elderly. This study evaluated the accumulation and distribution of identified risk factors among 108 elderly patients with type 2 diabetes (54 females and 54 males) treated at the Clinical Center University of Sarajevo. Evaluated risk factors included age, sex, hyperlipidemia, adiposity, family history, smoking, hypertension, and elevated fibrinogen levels. The overall mean number of identified risk factors was 4.11 per patient (SD = 1.32, range: 1–8). Female patients exhibited a slightly higher mean (4.26, SD = 1.36) than male patients (3.96, SD = 1.27), but this difference was not statistically significant (t = 1.18, df = 106, p = 0.240). Overall, 80.56% of patients presented with 3–5 risk factors, 12.04% with 6 or more, and only 7.41% with 2 or fewer, showing no significant association between sex and risk burden category (p = 0.670). In conclusion, elderly patients with type 2 diabetes exhibit a high cumulative risk-factor burden that is comparable between sexes, underscoring the need for comprehensive, multi-targeted intervention strategies in clinical practice.
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