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In case practice at forensic drug departments, multiple items from one seizure are sometimes sent in with the question: what is the total amount of drugs in the seizure? This may be complicated especially if impregnated material is involved such as clothes or rubber. Measurement uncertainty is typically stable on drug percentages, not weights, and subsampling may take place. It is recognized more and more that determination and reporting of uncertainty on estimators are an essential part of obtaining scientifically sound results in the forensic field. Methodology is described to quantify uncertainty on estimations of the total drug weight in groups of complex matrices, given simple statistical models, along a subdivision of five types of cases. Given each of these types, case examples are given where uncertainty is quantified in estimations of drug weights, by means of confidence intervals. The described models are statistically sound and relatively easy to implement.
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http://dx.doi.org/10.1111/1556-4029.12533 | DOI Listing |
Magn Reson Med
September 2025
Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand.
Purpose: Tracer kinetic models are used in arterial spin labeling (ASL); however, deciding which model parameters to fix or fit is not always trivial. The identifiability of the resultant system of equations is useful to consider, since it will likely impact parameter uncertainty. Here, we analyze the identifiability of two-compartment models used in multi-echo (ME) blood-brain-barrier (BBB)-ASL and evaluate the reliability of the fitted water-transfer rate ).
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September 2025
Department of Obstetrics and Gynaecology, Faculty of Medicine and Health, Örebro University, Örebro, Sweden.
Objective: To estimate the effect on healthcare resource use after introducing the World Health Organization diagnostic criteria (WHO-2013) for gestational diabetes mellitus (GDM) compared to former criteria in Sweden (SWE-GDM).
Design: A cost-analysis alongside the Changing Diagnostic Criteria for Gestational Diabetes (CDC4G) randomised controlled trial.
Setting: Sweden, with risk-factor based screening for GDM.
Neotrop Entomol
September 2025
Museu de Entomologia, Depto de Entomologia, Univ Federal de Viçosa (UFV), Viçosa, MG, Brazil.
This study addresses historical uncertainties regarding morphological variation in the paraprocts of Tupiperla illiesi, a stonefly with a complex taxonomic history. We tested whether these variations represent phenotypic plasticity or distinct species using integrative taxonomy. Adult gripopterygids were collected from Estação Biológica de Boracéia utilizing Malaise and light traps.
View Article and Find Full Text PDFEur J Obstet Gynecol Reprod Biol
September 2025
Department of Obstetrics and Gynecology, Zhongda Hospital, Southeast University, Nanjing, Jiangsu, China. Electronic address:
Background: Ectopic pregnancy (EP) represents a leading cause of maternal mortality in early gestation and a significant contributor to future reproductive impairment. Comprehensive understanding of global EP epidemiological patterns and their temporal evolution is crucial for developing holistic strategies to promote health equity and optimize allocation of medical resources worldwide.
Methods: Leveraging Global Burden of Disease (GBD) 2021 data, this investigation systematically examined age-standardized rates (ASRs) of EP incidence, prevalence, mortality, and disability-adjusted life years (DALYs) across 204 countries and 21 regions from 1990 to 2021.
Sci Total Environ
September 2025
Environmental Science and Engineering Department, Indian Institute of Technology Bombay, Mumbai, 400076, India; Centre for Climate Studies, Indian Institute of Technology Bombay, Mumbai, 400076, India.. Electronic address:
With growing populations and an increasing frequency of flood events, large-scale flood hazard assessment (LSFHA) and exposure analyses have become critically important. Global Flood Models (GFMs) significantly contribute to these efforts by simulating flood dynamics based on runoff inputs from Land Surface Models (LSMs), Global Hydrological Models (GHMs), or Reanalysis datasets. However, GFM outputs remain highly sensitive to runoff input choice, leading to substantial uncertainty in LSFHA.
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