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Optimal spare management via statistical model checking:a case study in research reactors
Get PDFSystematic spare management is important to optimize the twin goals of high reliability and low costs. However, existing approaches to spare management do not incorporate a detailed analysis of the effect on the absence of spares on the system’s reliability. In this work, we combine fault tree analysis with statistical model checking to model spare part management as a stochastic priced timed game automaton (SPTGA). We use Uppaal Stratego to find the number of spares that minimizes the total costs due to downtime and spare purchasing. The resulting SPTGA model can then additionally be analyzed according to a wide range of other metrics, including expected availability. We apply these techniques to the emergency shutdown system of a research nuclear reactor. In this case study, the failure probability is low, so we change the settings of Uppaal Stratego setting to obtain reliable results about rare events. We consider both a single subsystem and the combination of two subsystems. In both situations, our methods find the optimal number of spares, minimizing cost while ensuring an expected availability of 99.96% and 99.93%, respectively.</p
Preparing for Future Supply Disruptions:A Roadmap from the Healthcare Procurement Perspective
No full textPurpose: The COVID-19 pandemic exposed critical vulnerabilities in healthcare systems, particularly in hospital procurement and preparedness for supply chain disruptions. This study investigates how healthcare procurement professionals can develop sustainable preparedness plans for future supply disruptions. Methodology: A case study approach was adopted in this research. Data was collected through 15 semi-structured interviews with purchasing experts in 11 German hospitals.Findings: The findings of this research led to the development of a roadmap to support preparedness planning, based on the best practices identified by hospital purchasing professionals during the COVID-19 pandemic. The study also identified six types of barriers affecting physical preparedness, intangible preparedness activities, and both simultaneously. The best practices were categorised under six domains: storage, human resources, knowledge management, operations and process management, financial resources, and community collaboration. The findings suggest that combining different types of preparedness activities is essential for developing preparedness plans.Practical implications: This research provides practical guidelines for hospital purchasing professionals to better prepare for future disruptions, such as a roadmap to improve preparedness.Originality/value: A healthcare procurement lens is applied in our study, exploring preparedness at the organisational level, a perspective that has been underexplored in literature. This study raises awareness of the lack of preparedness plans in hospitals from a procurement perspective. This research provides a roadmap based on best practices to strengthen hospitals’ preparedness plans for possible future disruptions
Toward an ontology-based modeling for risk management
Get PDFAccording to ISO 31000, the risk management process comprises communication, risk assessment, risk treatment , monitoring, and reporting. Numerous techniques address these aspects, particularly risk assessment and treatment, such as attack trees, fault trees, risk matrix, etc. These approaches implicitly or explicitly require a conceptualization of the risk management domain, that is, a reference domain ontology as a background theory. However, because these techniques are not grounded in ontological analyses and well-founded reference ontologies, they suffer from several limitations and semantic confusion, such as ambiguity, little to no modeling guidance, and lack of semantic integration. Existing well-founded reference ontologies of value, risk, security, and related topics, can support a full-fledge ontologically sound risk management framework capable of solving those semantic issues. Nevertheless, such a comprehensive approach to risk management is yet to be seen. To cover this gap, we present a research proposal integrating these ontologies and associated services into a domain-specific modeling language for risk management. First, we establish a risk management ontology network, including value, risk, incident, security, monitoring, trust, and resilience concepts. We will employ them to ground ontological analyses of those important risk management techniques to identify their shortcomings. This analysis will support redesigns of these techniques to overcome the limitations. We will design a domain-specific modeling language interpreted by the ontology network and served by the redesigned versions of those techniques. By doing so, we expect to address semantic interoperability problems among risk management approaches and data sources
Anatomical characteristics are associated with aneurysm sac regression after endovascular repair
Get PDFObjective: Recent findings show that patients with abdominal aortic aneurysm (AAA) sac regression after endovascular repair (EVAR) have significantly better long-term outcomes than patients with a stable or expanding sac. Previous studies have not yet identified strong predictors of sac regression, but suggest that anatomical AAA parameters might play a role in the remodeling. This study aimed to conduct a comprehensive analysis of preoperative AAA anatomy to identify predictors of sac regression 1 year after EVAR.Methods: This retrospective two-center cohort study included patients with regressing or stable sacs one-year after elective infrarenal EVAR between January 2011 and December 2019. The lumen and intraluminal thrombus (ILT) of the AAA were automatically segmented. From this, the center lumen line and a range of anatomical characteristics were automatically derived, including volume, diameter and length measurements, (hostile) neck parameters, ILT distribution, radiodensities, calcification, and aortic curvature. Logistic regression was performed to identify the added predictive value of the anatomical characteristics.Results: Enrolled were 289 patients (84% male, 72.0 ± 7.4 years old) of whom 46% experienced sac regression and 54% had a stable sac 1 year after EVAR. Significant differences between the regression and stable group were found for the relative neck ILT volume (1.2 ± 1.6 vs 1.7 ± 2.2; P = .029), location of maximum thrombus thickness (187° ± 109° vs 156° ± 105°; P = .018), variation in ILT circumference (25 ± 10% vs 23 ± 10%; P = .029), the roundness of the lumen (1.46 ± 0.24 vs 1.52 ± 0.25; P = .029), and variation in lumen radiodensity (77 ± 25 Hounsfield units vs 85 ± 24 Hounsfield units; P = .005). No significant differences were observed for the other volumes, lengths, and (hostile) neck parameters. Compared with a baseline model that included only clinical variables, the addition of the anatomical variables increased the model sensitivity from 42.1% to 58.3% and the overall accuracy from 59.9% to 66.3%. For the receiver operating characteristic curve, the area under the curve also significantly improved by 0.08 to 0.71 when the anatomical variables were added.Conclusions: Anatomical AAA characteristics relating to ILT play an important role in sac regression after EVAR. Furthermore, this study supports the existing evidence confirming that various mostly geometric neck parameters are not associated with sac regression, such as diameter, calcification, length, angulation, shape, and presence of a hostile neck. Although the anatomical analysis is of added value for predicting sac regression, further improvement is needed before clinical implementation.</p
Cities near volcanoes:which cities are most exposed to volcanic hazards?
Get PDFCities near volcanoes expose dense concentrations of people, buildings, and infrastructure to volcanic hazards. Identifying cities globally that are exposed to volcanic hazards helps guide local risk assessment for better land-use planning and hazard mitigation. Previous city exposure approaches have used the city centroid to represent an entire city and assess population exposure and proximity to volcanoes. However, cities can cover large areas and populations may not be equally distributed within their bounds, meaning that a centroid may not accurately capture the true exposure. In this study, we suggest a new framework to rank global city exposure to volcanic hazards. We assessed global city exposure to volcanoes in the Global Volcanism Program database that are active in the Holocene by analysing populations located within 10, 30, and 100 km of volcanoes. These distances are commonly used in volcanic hazard exposure assessment. City margins and populations were obtained from the Global Human Settlement (GHS) model datasets. We ranked 1133 cities based on the number of people exposed at different distances from volcanoes, the distance of the city margin from the nearest volcano, and the number of nearby volcanoes. Notably, 50 % of people living within 100 km of a volcano are in cities. We highlight Jakarta, Bandung, and San Salvador as scoring highly across these rankings. Bandung in Indonesia ranks highest overall, with over 8 million people exposed within 30 km of up to 12 volcanoes. South-East Asia has the highest number of exposed city populations (∼ 161 million). Jakarta (∼ 38 million), Tokyo (∼ 30 million), and Manila (∼ 24 million) have the largest number of people within 100 km. Central America has the highest proportion of its city population exposed, with Quezaltepeque and San Salvador exposed to the most volcanoes (n = 23). Additionally, we ranked the 1264 Holocene volcanoes by city populations exposed within 10, 30, and 100 km, the number of nearby cities, and the distance to the nearest city. Tangkuban Parahu, Tampomas, and San Pablo Volcanic Field score highly across these rankings. Notably, the Gede-Pangrango (∼ 48 million), Tangkuban Parahu (∼ 8 million), and Nejapa-Miraflores (∼ 0.8 million) volcanoes have the largest city populations within 100, 30, and 10 km, respectively. We developed a web app to visualize all cities with over 100 000 people exposed. This study provides a global perspective on city exposure to volcanic hazards, identifying critical areas for future research and mitigation efforts
Multisensory approaches to urban pollution:A controlled study of sound-odour interactions and their impact on physiology and perception
Get PDFTraffic-related pollution not only directly harms health but also shapes how people perceive and interact with their surroundings. These effects are rarely driven by individual sensory input, like noise or air pollution, but emerge from interactions between sensory cues. For example, the perception of diesel as an unfamiliar odour may shift when experienced alongside traffic noise. Yet, research often treats urban stressors in isolation, overlooking their combined effects, potentially creating a double health burden. While crossmodal interactions – where one sense influences another – have been mostly studied in audio-visual contexts, little attention has been given to how pollution-related odours and sounds interact. To address this gap, we recreated the basic visual characteristics of a Dagenham (East London) streetscape in the laboratory, adding controlled sound- and smellscapes to examine the impact of unimodal versus multisensory pollution on physiology and perception. Participants experienced visual streetscapes with diesel odour, traffic sounds, or both. Heart rate and skin conductance levels were measured, and participants rated odour intensity, sound loudness, and their liking of the sound, odour, and overall streetscape. Traffic noise tended to increase physiological arousal, was unanimously disliked, perceived as loud, and reduced streetscape liking. It also made traffic odours feel significantly more intense and less liked, while odours had little effect on sound. This highlights the need to examine multisensory urban pollution, not just unimodal stressors, to better understand their impacts on physiology and perception. Crossmodal interactions offer richer design opportunities for creating urban spaces that support well-being amidst unavoidable stressors
Hyperglycaemia does not modify the efficacy of endovascular therapy in the late time window (6–24 hours)
Get PDFIntroduction: Hyperglycemia is common in ischemic stroke. Admission glucose modifies the effect of endovascular therapy (EVT) in patients with ischemic stroke of the anterior circulation, who are treated 0 to 6 hours since onset. Whether this also applies for late-window EVT (6–24 hours since symptom onset or last known well) is unknown. In this study, we assessed whether admission glucose level and/or hyperglycemia modifies the EVT effect in patients with ischemic stroke of the anterior circulation in the late time window. Methods: We used data from the MR CLEAN LATE trial. The primary outcome measure was the modified Rankin Scale (mRS) score at 90 days. Secondary outcome measures were symptomatic intracranial hemorrhage and mortality at 90 days. Treatment effect modification of EVT by either glucose or hyperglycemia on admission was assessed by multiplicative interaction factors with logistic regression analysis and adjusted for potential confounders. Hyperglycemia was defined as glucose level >7.8 mmol/L on admission. Results: On admission, median glucose was 7.0 mmol/L (IQR 6.0–8.3 mmol/L), and 147 patients (32%) were hyperglycemic. We found no interaction of either hyperglycemia or serum glucose on admission with treatment effect on functional outcome (p = 0.76 and p = 0.79, respectively), symptomatic intracranial hemorrhage (p = 0.29 for hyperglycemia; p = 0.57 for glucose on admission), and for mortality (p = 0.52 for hyperglycemia; p = 0.69 for glucose on admission). Conclusion: We found no evidence for effect modification of EVT by admission glucose level or hyperglycemia in patients with acute ischemic stroke and large-vessel occlusion of the anterior circulation in the late treatment window.</p
The contribution of facial components to face recognition
Get PDFFacial components, such as the eyes, nose, and eyebrows, play a critical role in biometric and forensic identification. While previous studies have explored the effects of partial occlusion and masking on face recognition, the systematic analysis of individual facial components’ contributions to deep face recognition remains limited. This thesis introduces a method to analyze the importance of different face components to face recognition and a tool that enables the selective replacement of facial components to study their impact on recognition performance. Through a series of experiments, we demonstrate that certain components, particularly the eyebrows and nose, carry more discriminative information than others, with texture generally being more influential than shape, except for the eyebrows. The method also extends to historical facial analysis, such as identifying Roman emperors from sculptures by isolating features like hairstyles and facial hair. Moreover, we present an open-source tool developed in Python, capable of seamlessly replacing facial components, including their textures and shapes, suitable for both research and application contexts. This work bridges a gap in facial analysis by providing a systematic approach and practical tool for studying the role of facial components in face recognition
A Cox Rate-and-State Model for Monitoring Seismic Hazard in the Groningen Gas Field
Get PDFTo monitor the seismic hazard in the Groningen gas field, this paper modifies the rate-and-state model that relates changes in pore pressure to induced seismic hazard by allowing for noise in pore pressure measurements and by explicitly taking into account gas production volumes. The first and second-moment structures of the resulting Cox process are analysed, an unbiased estimating equation approach for the unknown model parameters is proposed and the conditional distribution of the driving random measure is derived. A parallel Metropolis-adjusted Langevin algorithm is used for sampling from the conditional distribution and to monitor the hazard
Analyzing Gait With Minimal Body-Worn Sensing: Combining UWB and IMU
Get PDFGait disorders are seeing an increase in incidence due to the aging world population. To improve mobility in daily life, it is necessary to accurately monitor gait parameters using body-worn devices. However, current device setups are either too complex or inaccurate. To that end, we propose to combine ultrawideband (UWB) and inertial measurement units (IMUs) technology as a portable setup on the feet of the user. An extended Kalman filter (EKF) was implemented to fuse the distance information (from UWB) with the integration of acceleration and angular velocity measurements to obtain relative foot positions that do not suffer from integration drift. Our results show that spatiotemporal parameters are estimated with higher accuracy (mean step length relative (to the body height of the subject) root mean squared error (rRMSE) = 0.037, step width rRMSE = 0.049, FIA RMSE = 4.0°, and FPA RMSE = 3.4°) using the combination of UWB and IMU sensors compared to using IMUs only: mean step length rRMSE = 0.198, step width rRMSE = 0.456, FIA RMSE = 4.0°, and FPA RMSE = 3.3°