Since the 1980s, quality management mechanisms gradually emerged in forensic science as a response to the challenges faced by the discipline across the globe. However, in recent years, there has been debates about whether current quality assurance and accreditation frameworks are fit-for-purpose, in particular regarding crime scene examination. Therefore, this proof-of-concept study aims to provide some preliminary empirical insights into this question and explore some of the challenges associated with the assessment of the impact of accreditation of crime scene units under both ISO/IEC 17025 and the AS 5388 quality standards. To do so, open-sourced data drawn from the Report on Government Services (RoGS) were analysed using an exploratory difference-in-difference framework and multiple linear regression models to compare pre- and post-accreditation finalisation rates for various offences, in unaccredited and accredited Australian law enforcement agencies. The findings suggest that, based on the data available and within the methodological limitations of this study, accreditation under the ISO/IEC 17025 quality standard had mostly no significant improvement or decline in finalisation rates. In contrast, accreditation under the AS 5388 quality standard was consistently associated with significantly higher finalisation rates among accredited agencies compared to their non-accredited counterparts. While these results echo ongoing debates and uncertainties regarding the positive and/or negative impacts of accreditation and quality assurance in forensic science (if any), above all, they underscore the challenges of defining clear objectives, developing appropriate metrics, and designing robust methodological approaches for a more comprehensive empirical assessment of their effects. Although finalisation rates alone provide a limited indicator, this study represents a valuable first step toward a systematic evaluation of the impact of quality assurance and accreditation in forensic science.

Status of Biochar and briquette technologies in Ethiopia: A review of production systems, efficiency and utilization

Deformable Dose Mapping and Accumulation Techniques for Stereotactic Body Radiation Therapy (SBRT) of Lung Cancers.

Routine Histology After Hemorrhoidectomy: Uncovering the Hidden Risk of Malignancy?

The Microtransition Adverse Event Sign-In/Sign-Out (MASS) Form: A Potential Solution to Communication Barriers for Outpatient Medical Appointments and Nonmedical Outings in Post-Acute and Long-Term Care.

Global population aging exacerbates the challenges of multimorbidity and polypharmacy in older adults. Clinical practice guidelines are essential for addressing these issues. This systematic review aims to evaluate the quality of existing guidelines and synthesize their recommendations based on the Ariadne principles, to inform future guideline development and clinical practice. We searched nine databases and five guideline repositories (e.g., PubMed, Web of Science, Cochrane Library, CNKI, WHO) up to August 2025. Guidelines and consensus documents focusing on multimorbidity or polypharmacy in older adults, published in English or Chinese, were included. Each guideline was evaluated using four validated tools: AGREE II (methodological quality), RIGHT (reporting completeness), AGREE-REX (recommendation credibility and applicability), and GLIA (implementation feasibility). Recommendations were categorized and synthesized according to the Ariadne principles, with independent screening and data extraction and consensus resolution of discrepancies. The multidimensional appraisal of the 21 included guidelines revealed consistent weaknesses. According to AGREE II, the domains of Scope and Purpose (81.9 %) and Clarity of Presentation (61.1 %) demonstrated the highest median scores, whereas Rigor of Development (16.7 %) and Applicability (8.3 %) scored the lowest. Based on the RIGHT checklist, overall reporting completeness was 43.2 %, with the Evidence (0.0 %) and Quality Assurance (0.0 %) domains being particularly underreported. AGREE-REX evaluation indicated limited implementability at the individual recommendation level (12.5 %), and GLIA, while suggesting moderate implementability at the guideline level (65.4 %), identified frequent barriers in the domains of Measurable Outcomes (100.0 %) and Innovation Requirements (66.7 %). Thematically, most guidelines addressed interaction assessment (n = 15, 71.4 %), but far fewer incorporated patient preferences (n = 9, 42.9 %) or monitoring strategies (n = 9, 42.9 %). Only three guidelines (14.3 %) fully adhered to all five steps of Ariadne principles. Current guidelines for older adults with multimorbidity or polypharmacy exhibit substantial weaknesses in methodological rigor, reporting completeness, and implementation feasibility. Synthesis based on the Ariadne principles revealed an imbalanced pattern of recommendations, with a predominant focus on medication safety rather than patient-centered and longitudinal care management. Future guideline development should strengthen methodological processes, systematically integrate patient perspectives, and co-design practical implementation strategies to better support personalized care for an aging population.

Stereotactic Body Radiation Therapy (SBRT) schedules for prostate cancer are emerging as a standard treatment approach. However, although high efficacy is achieved in clinical trials, additional efforts at accurate treatment delivery are necessary to maximize the therapeutic ratio in the community setting. Kilovoltage Intrafraction Monitoring (KIM) is a technology developed to address the unmet clinical need of accurate intrafraction motion management without a requirement for additional hardware on standard linear accelerators. This paper describes the journey from bench to bedside of KIM. The concept of KIM emerged in 2008 in a series of simulations, progressing to phantom experiments commencing in 2010, culminating in the first clinical trial starting in 2014. A series of technical innovations integrating rotational prostate movements, quality assurance, and dynamic multileaf collimator tracking were included within the multi-institutional Trans-Tasman Radiation Oncology Group 15.01 Stereotactic Prostate Adaptive Radiation therapy using KIM clinical trial for prostate SBRT. Submillimeter accuracy of KIM was observed in simulations, phantom experiments, and clinical trials. The Stereotactic Prostate Adaptive Radiation therapy using KIM trial demonstrated multicenter feasibility of use, a high rate of intrafraction motion triggering a gating event, and a significant dosimetric impact of KIM deployment for target volume coverage. KIM is being made available through commercialization with an industry partner, and through a 300-patient, 10-center clinical trial. The collaboration between researchers, clinicians, and industry has led to KIM being developed from a concept to clinical trials, enabling the safe delivery of prostate cancer SBRT in the presence of intrafraction motion. This journey provides a template for similar bench-to-bedside translational research.

Process-induced pores in metal additive manufacturing (AM) components critically compromise mechanical performance, necessitating reliable characterisation methods for quality assurance. While ultrasound offers promising advantages for rapid, non-destructive evaluation with deep penetration, existing studies struggle to isolate pore effects from confounding grain scattering. This work overcomes these limitations by investigating selective laser melted TiB 2 /Al composites, whose ceramic-reinforced microstructure exhibits refined equiaxed grains and minimal texture, effectively suppressing grain scattering to reveal fundamental pore-ultrasound interactions. We systematically examined how porosity (0.22%–2.21%), morphology, and size distribution influence ultrasonic attenuation and velocity. This was achieved through integrated experimental measurements and three-dimensional pore-scale finite element simulations incorporating realistic pores derived from stereological transformation of microscopy data. Our findings reveal hierarchical pore effects: porosity exhibits strong linear correlations with both attenuation coefficient and phase velocity under the same pore morphology conditions; irregular morphologies amplify these effects, generating fivefold higher attenuation sensitivity and twofold higher velocity sensitivity compared to spherical pores; size variations primarily affect attenuation with minimal velocity impact. Additional, we demonstrated ultrasound’s spatial mapping capability for detecting subtle microstructural heterogeneities, with attenuation exhibiting superior porosity sensitivity. These quantitative pore-ultrasound relationships establish a robust framework for non-destructive evaluation in metal AM, enabling morphology-sensitive quality control and process optimisation for safety-critical applications.

Food spoilage poses a global challenge, contributing to economic losses, food insecurity, and health risks from microbial contamination. Conventional detection methods are often destructive, time-consuming and ineffective at identifying early biochemical changes or stereospecific microbial by-products. We developed SkiNET-FoodSpec, a novel, non-invasive biosensor platform integrating biomolecular spectroscopy with an advanced self-organising map-based neural network (SkiNET) for rapid, real-time spoilage detection. The system achieves >93% classification accuracy across a range of food matrices, including meat, milk and leafy greens. It detects key spoilage markers, such as cadaverine in meat (LoD: 0.06875 mg/kg), D-/L-lactic acid enantiomers in milk (LoD:3 mmol/mL) and carotenoid and cellulose degradation in greens (LoD: 0.071 mg/kg). By generating matrix-specific spectral barcodes, SkiNET-FoodSpec identifies early spoilage prior to visible or olfactory cues. This advance in biotechnology enables intelligent, point-of-need diagnostics for food quality assurance, offering a powerful tool to enhance food safety, reduce waste and support resilient, sustainable food systems.

Learning to ask and answer in specialized documents: Exemplifying through modular integrated construction regulatory documents

REBCO coated conductor has great potential to be used in ultra-high field magnets. Commercial REBCO tapes are strong in the longitudinal direction but prone to delamination by tensile stress in the thickness direction. For high field magnet applications, it is crucial to characterize delamination strength of REBCO conductor and better manage the electromagnetic stress. In this work, the electromagnetic stress in high magnetic fields by screening current is used to study the delamination behavior of commercial REBCO tapes. Screening currents are induced in REBCO by either ramping field or rotating sample in magnetic fields up to 35 T. The results of delamination strength are presented. The prospect of using this method for quality assurance in large magnet projects is discussed.

A comparison of sensitivity and specificity of dosimetry audits for intensity modulated radiation therapy used internationally for clinical trial credentialing.

OT2Eye: Detection of labware conditions to monitor and extend affordable liquid-handling robots.

To evaluate the impact of deep learning reconstruction (DLR) on MRI productivity at a tertiary care academic hospital, and to validate a previously published Monte Carlo-based forecast of the productivity enhancement potential of DLR. Scanner log data were analyzed for two periods: pre-DLR adoption (January-October 2023, six scanners) and post-DLR (January-October 2025, five scanners). Examination and sequence durations were obtained from the Siemens Healthcare Teamplay platform. Observed changes were compared with capacity increases predicted by earlier Monte Carlo simulations. The impact of shortened scan durations across different scanner utilization levels was further evaluated using a simulation. Finally, four radiologists assessed image quality to identify potential clinical limitations of DLR. Optimized scanners demonstrated a total reduction between 4.8 and 11.1min (11.5-27.2%) in sequence duration and 5.0-10.7min (9.5-21.2%) in total examination time. Despite operating with one fewer scanner in 2025 (six scanners before DLR adoption, 5 scanners after), the mean hourly throughput of the entire fleet decreased by only 6.4%, indicating improved productivity per scanner. Notably, this throughput was achieved while DLR deployment and protocol optimization were still in progress, underscoring the substantial productivity benefit even at a partial implementation stage. DLR deployment was associated with improved MRI suite productivity, enabling nearly pre-DLR throughput despite operating with one fewer scanner. The results demonstrate the utility of DLR in improving MRI productivity and support the predictive accuracy of simulation-based health technology assessment. Nevertheless, unpredictable performance, particularly in neuroimaging, where artifacts in T2-weighted sequences and reduced quality in contrast-enhanced studies were observed, limits the applicability of DLR and underscores the need for rigorous quality assurance.

Impact of ionizable lipid source on quality and stability of siRNA-loaded lipid nanoparticles.

RF105. American Association for Thoracic Surgery Quality Gateway Procedure Outcomes Models for General Thoracic Surgery Quality Assurance

Methodological validation of microbial limit tests for high-viscosity and common pharmaceutical excipients.

A Pipeline for MRI-Guided dose painting by number radiation Therapy: GLIORAD - a phase I-II clinical trial in recurrent glioblastoma.

Radiotheranostics in an evolving landscape: Emerging themes and considerations from a radiation therapy perspective.

Artificial intelligence (AI) has been increasingly applied to address challenges in food packaging, including food waste, sustainability, and real-time quality assurance. However, existing studies are often confined to specific applications, with limited integration across different stages of the packaging life cycle and insufficient linkage between material performance, functionality, and system-level outcomes. This review systematically analyzes peer-reviewed studies retrieved from the Web of Science Core Collection (2021-2025), selected based on their relevance to AI applications in food packaging, including material performance, safety, and life cycle management. A life cycle-oriented framework is proposed, linking major AI paradigms (supervised, unsupervised, reinforcement, deep learning, and hybrid models) to six key domains: material design, production optimization, food quality prediction, safety assurance, smart labeling and traceability, and recycling. Within this framework, AI supports data-driven prediction, monitoring, and decision-making, whereas hybrid models improve robustness in complex, multifactor systems. Despite challenges related to data quality, model generalization, and regulatory acceptance, AI-driven packaging systems may support a transition from passive containment toward more adaptive and data-informed solutions that improve efficiency, sustainability, and consumer trust.