Ecological Risk and Security Research

Abstract Klebsiella pneumoniae  is one of the leading causes of urinary tract infections (UTIs) and is increasingly associated with multidrug resistance, posing significant therapeutic challenges. Continuous surveillance of its antimicrobial susceptibility profile is essential for effective clinical management. This cross-sectional study was conducted from July 2023 to December 2023 in a tertiary care hospital. A total of 12 urine samples were collected from patients with suspected UTIs. Samples were cultured using standard microbiological techniques, and isolates were identified by colony morphology, Gram staining, and biochemical tests. Antibiotic susceptibility testing was performed by the Kirby–Bauer disc diffusion method following CLSI guidelines. Out of 12 urine samples, 10 (83%) showed bacterial growth and were identified as Klebsiella pneumoniae . Among the isolates, 8 (80%) were from female patients and 2 (20%) from male patients. The majority of patients (40%) belonged to the 41–60 years age group, followed by ≥61 years (30%). Most isolates were obtained from OPD patients (70%), while 30% were from IPD patients. The highest sensitivity was observed to Meropenem (90%) and Tigecycline (90%), followed by Gentamicin (70%). Moderate sensitivity (50%) was noted for Cefotaxime, Amoxicillin, Ceftazidime, Cefoxitin, Ampicillin, and Ciprofloxacin. The lowest sensitivity was seen with Doxycycline (10%) and Colistin (40%). Multidrug resistance (MDR) was detected in 7 (70%) isolates, while no extensively drug-resistant (XDR) or pan drug-resistant (PDR) strains were identified. Klebsiella pneumoniae  remains a significant uropathogen with a high prevalence of multidrug resistance. Carbapenems and Tigecycline showed the highest effectiveness, whereas resistance to commonly used antibiotics was considerable. Regular antimicrobial surveillance and rational antibiotic use are essential to control the spread of resistant strains.

Abstract This study applies the Small Baseline Subset InSAR (SBAS-InSAR) technique, together with an Analytic Hierarchy Process (AHP)-GIS weighted-overlay framework, to assess surface deformation and landslide susceptibility along the Ghazi-i-Millat Road (GMR), Azad Jammu and Kashmir, Pakistan. Time-series analysis of 91 Sentinel-1 acquisitions (January 2021-December 2023) indicates a mean Line-of-Sight (LOS) velocity ranging from -14.50 to +15.00 mm/year, with a maximum cumulative LOS displacement of approximately +130 mm and -96 mm over the three-year observation period; a localized maximum LOS velocity of 17.07 mm/year was also recorded. Because LOS displacement records motion toward or away from the sensor rather than true vertical or slope-parallel movement, these values are interpreted as indicators of possible ground instability rather than direct proof of active landsliding. Landslide susceptibility mapping incorporates eight causative parameters, slope gradient, slope aspect, geology, drainage network, fault proximity, road proximity, NDVI, and NDWI, combined through AHP-derived weights in a GIS weighted-overlay model. Dense vegetation cover is associated with qualitatively reduced SBAS-InSAR coherence and data reliability, consistent with well-documented vegetation-induced radar decorrelation. The weighted-overlay analysis assigns the greatest relative importance to slope gradient, followed by drainage network and road proximity, and the resulting susceptibility map places the majority of the mapped landslide inventory within the considerable-to-very-high susceptibility classes. The findings support the value of combining SBAS-InSAR deformation monitoring with AHP-GIS susceptibility mapping as a regional decision-support tool for infrastructure planning, slope stabilization, and drainage management along this economically important corridor, while underscoring the need for independent field validation, ascending/descending geometric decomposition, and quantitative uncertainty assessment in future work.