Search Results (26)

Disaster frequency is rising, and response-phase planners face a binding constraint: relief capacity is always smaller than need, so directing affected people to relief centres is a triage decision under time pressure. Published optimisation models speak operations-research vocabulary (cost, distance, equity); civil-protection planners speak supply-chain-resilience vocabulary (the 4R framework of Bruneau et al.). We close the gap with a four-objective humanitarian last-mile allocation model whose objectives map one-to-one onto the 4R components—Resourcefulness, Robustness, Rapidity, Redundancy—evaluated by Mamdani fuzzy inference systems and solved by NSGA-II, NRGA, and NSGA-III. Across 540 runs over three problem sizes, the four-objective formulation surfaces independent Robustness and Rapidity axes that the baseline three-objective formulation fuses into one, a visibility gain established by rank-correlation analysis; NSGA-III is faster than NSGA-II at every size (27–37%, mean 32%), with the hypervolume ranking depending on the reference-point scheme. Weight- and rule-perturbation sweeps confirm the recommendations are robust to expert-elicitation noise, flagging the three-rule Rapidity classifier as a sensitivity hot-spot. The framework is released as a production-grade, openly licensed decision-support tool—continuously tested, dependency-audited, and reproducible bit-for-bit on stock hardware—treating reproducibility as a first-class resilience criterion and positioning audit-ready operational tooling as the digital-technology innovation supply-chain-resilience practice needs. Full article

Morphological differences between sea-caught and farmed fish reflect environmental conditions and long-term domestication. However, standardized and objective quantification of these differences remains limited for many commercially important species. The large yellow croaker (Larimichthys crocea) represents a typical marine fish with clear contrasts between natural and aquaculture production systems. In this study, an image-based phenotyping workflow was developed to quantify external morphological traits of sea-caught and farmed L. crocea. Visible-light images were acquired under standardized conditions. A YOLOv11-based instance segmentation model was applied to automatically delineate major anatomical regions, including the body, head, eyes, pectoral fins, and tail. Surface areas and proportional indices were calculated following geometric calibration to ensure measurement consistency. The segmentation model achieved high accuracy on the test dataset (mAP@50 > 98%). Morphometric analyses revealed clear differences between the two groups. Farmed individuals exhibited larger body-related surface areas, whereas the relative proportions of pectoral fins and tail regions were reduced. Sea-caught fish showed higher proportional investment in locomotor structures, consistent with the physical demands of natural marine environments. These results indicate a shift in morphological allocation associated with aquaculture, characterized by enhanced trunk growth and reduced relative development of propulsion-related structures. The proposed workflow provides a rapid, non-invasive, and reproducible approach for fish morphometric analysis. It offers practical potential for phenotypic monitoring and stock assessment, while contributing quantitative evidence for domestication-driven morphological divergence in marine fishes. Full article

Background: In the context of increasing supply chain complexity, efficient inventory management has become important in enhancing the performance of logistics systems and sustaining the competitiveness of companies. Real-time visibility, tracking, and control over stock levels ensure responsiveness, reduce waste, and support strategic decision-making. Decision support systems that integrate demand analysis with inventory policies play a pivotal role in improving operational efficiency. This paper addresses the need for more efficient stock management to optimize purchasing and inventory costs within a manufacturing environment. Methods: Production planning processes were analyzed to determine material requirements, and a representative product was selected. The study involved ABC classification based on the average annual stock value of purchased parts, complemented by an XYZ analysis to evaluate demand variability. Afterwards, stock management policies were tested, namely, continuous and periodic review models. Each item was assessed to determine the most suitable inventory management method based on its consumption profile. Results: A comparison with the company’s existing approach revealed that for 9 out of the 13 materials studied, the application of stock management models led to improvements. Conclusions: The results show a potential cost reduction of 33% for the nine materials to which stock policies were successfully applied. Full article

Background/Objectives: Vaccine usage rates (VURs) for COVID-19 vaccines (C19V) in KwaZulu-Natal (KZN), South Africa, remain insufficiently documented. This study assessed VUR for Pfizer–BioNTech (Pfizer) and Janssen Biotech Inc. (J&J) and reviewed monitoring systems in public (PUBS) and private (PRIVS) sectors. Methods: A dual-phase, multicentre study was conducted in PUBS and PRIVS facilities. Phase 1 comprised a retrospective, cross-sectional analysis of VUR for Pfizer and J&J (May 2021–July 2022). Phase 2 involved qualitative interviews with public (PUBSR) and private (PRIVSR) sector respondents (January–March 2024). Results: Pfizer VURs were 78.7% (PUBS) and 104.4% (PRIVS), while J&J recorded 64.7% (PUBS) and 40.2% (PRIVS). Stock reconciliations were complete across PUBSR and PRIVSR, but challenges persisted in stock on hand, reporting systems, and operational indicators. Conclusions: Pfizer achieved higher VURs than J&J, with PRIVS exceeding 100% due to under-reporting of issued doses. Integrated, real-time monitoring of VURs is urgently required to strengthen evidence-based policymaking, optimise supply chain management, reduce wastage, and improve vaccine uptake. Standardised monitoring frameworks across PUBS and PRIVS are essential to align with national objectives. Full article

The current climate emergency makes it imperative to take action to halt the irreversible destruction of the planet, with the renovation of existing buildings playing a crucial role. In Europe, particularly in Spain, energy efficiency improvements in existing buildings are undertaken in only a small fraction of cases. This gap presents a valuable opportunity to implement measures that encourage such interventions. To enhance energy production and tackle this issue from a distributed energy perspective, building-integrated photovoltaic (BIPV) systems emerge as a key solution. In this context, the primary objective of this research is to enhance the visibility and promote the adoption of BIPV systems in building energy retrofitting through the development of a standardised action framework for their installation across distinct typological clusters. To achieve this objective, a comprehensive and systematic analysis was undertaken to construct a classification that most accurately and exhaustively represents the Spanish building stock. The analysis resulted in the identification of 15 typological clusters, which, based on shared formal attributes, were consolidated into 3 principal clusters. For each of these three primary groups, a tailored action guide for BIPV system implementation was developed, addressing their specific characteristics and highlighting the critical factors to be considered in each case. To illustrate the practical application of the proposed framework, a representative case study was selected and subjected to an in-depth analysis, resulting in a detailed proposal for BIPV system installations on both the façade and the roof. In this regard, this research develops an initial procedural framework that comprehensively represents diverse building typologies, providing a structured protocol for the integration of BIPV systems within the context of energy retrofit interventions. Full article

Geodata, geographical information science (GISc), and GeoAI (geo-intelligence workflows) play an increasingly important role in predictive disaster risk reduction and management (DRRM), aiding decision-makers in determining where and when to allocate resources. There have been discussions on the ethical pitfalls of these predictive systems in the context of DRRM because of the documented cases of biases in AI systems in other socio-technical systems. However, none of the discussions expound on how to audit geo-intelligence workflows for biases from data collection, processing, and model development. This paper considers a case study that uses AI to characterize housing stock vulnerability to flooding in Karonga district, Malawi. We use Friedman and Nissenbaum’s definition and categorization of biases that emphasize biases as a negative and undesirable outcome. We limit the scope of the audit to biases that affect the visibility of different housing typologies in the workflow. The results show how AI introduces and amplifies these biases against houses of certain materials. Hence, a group within the population in the area living in these houses would potentially miss out on DRRM interventions. Based on this example, we urge the community of researchers and practitioners to normalize the auditing of geo-intelligence workflows to prevent information disasters from biases. Full article

Background: Ensuring the consistent availability of essential medicines is crucial for effective healthcare systems. However, Ethiopian public health facilities have faced frequent stockouts of crucial medications, highlighting systemic challenges such as inadequate forecasting, prolonged procurement processes, a disjointed distribution system, suboptimal data quality, and a shortage of trained professionals. This study focuses on the Ethiopian Pharmaceutical Supply Services (EPSS), known for its highly unstable and volatile supply chain, aiming to identify risks and mitigation strategies. Methods: Using a mixed-method approach involving surveys and interviews, the research investigates successful and less successful strategies, key success factors, and barriers related to pharmaceutical shortages. Results: Proactive measures such as communication, stock assessment, supervision, and streamlined procurement are emphasized as vital in mitigating disruptions, while reactive strategies like safety stock may lack long-term efficacy. The study highlights the importance of aligning supply chain strategies with product uncertainties, fostering collaboration, and employing flexible designs for resilience. Managerial implications stress the need for responsive structures that integrate data quality, technology, and visibility. Conclusions: This study contributes by exploring proactive and reactive strategies, elucidating key success factors for overcoming shortages in countries with unstable supply chains, and offering actionable steps for enhancing supply chain resilience. Embracing uncertainty and implementing proactive measures can help navigate volatile environments, thereby enhancing competitiveness and sustainability. Full article

The operational effectiveness of a railroad track robot that is designed for railcar undercarriage inspection is provided. Beyond describing the robot’s design details and onboard imaging system, the paper analyzes the recorded video images and offers design improvements to increase their clarity. The robot is designed to be deployed trackside, traverse over the rails, and then maneuver in between the rails beneath a stopped train in a siding or a railyard. The under-carriage conditions are documented by onboard video cameras for automated or manual postprocessing. The intent is to inspect the components that are not visible to the conductor or train inspector during a walk-along inspection of a stationary train. An assessment of the existing design, followed by modification and validation, is presented. The results from a prototype unit developed by the Railway Technologies Laboratory at Virginia Tech (RTL) indicate that with proper positioning of off-the-shelf imaging systems such as cameras manufactured by GoPro® in San Mateo, CA, USA and appropriate lighting, it is possible to capture videos that are sufficiently clear for manual (by a railroad engineer), semi-automated, or fully automated (using Artificial Intelligence or Machine Learning methods) inspections of rolling stock undercarriages. Additionally, improvements to the control, mobility, and reliability of the system are documented, although reliability throughout operation and the ability to consistently climb out of the track bed remain points of future investigation. Full article

Identification of contamination sources and delineation of plumes in the geological environment stand as pivotal elements in reconstructing the conceptual site model (CSM) and devising remediation strategies tailored to specific physicochemical traits. This study endeavors to showcase the capabilities of a 3D digital interface, seamlessly integrating multi-source data, to elucidate site-specific contamination dynamics and steer the implementation of remediation strategies harmoniously aligned with the ethos of remediation geology. In a site historically marred by chlorinated solvent contamination, the digitization of stratigraphic, piezometric, chemical, and membrane interface probe (MIP) data underpins geomodeling endeavors and yields a meticulously crafted, data-driven CSM. The hydrogeochemical and hydrogeophysical data were interpolated to build a volumetric, digital 3D model illustrating data-driven elements. The comprehensive 3D clone adeptly delineates secondary contamination sources and renders visible the contamination plume within a georeferenced framework, mirroring the nuanced interplay of stratigraphic nuances and groundwater path. A data-centric approach to modeling facilitates the design of the first hydraulic virtual barrier leveraging groundwater circulation well (GCW) technology, its geometry finely attuned to intercept the contamination plume originating from source dissolution and aligning with preferential groundwater flow trajectories. Conventional hydrochemical monitoring and multilevel sampling substantiate the discernible reduction in chlorinated solvent concentrations across various depths within the aquifer horizon, affirming the efficacy of GCWs in their virtual barrier configuration. The findings highlight the effectiveness and limited groundwater consumption of the virtual barrier compared to the on-site pump-and-stock system. This research underscores the potency of a multi-faceted evidence-driven puzzle in conceptualizing contamination mechanisms within the geological milieu, thereby fostering the application of cutting-edge, effective, and sustainable remediation strategies. Full article

The quality of supply chains in public health interventions in low- and middle-income countries can determine how effectively a program is able to treat its intended population group and subsequently achieve its health targets. We aimed to disentangle where challenges exist hierarchically and administratively through the application of process mapping to the supply chain of an integrated community case management (iCCM) intervention in the Democratic Republic of the Congo (DRC). We conducted a document review, semi-structured key informant interviews, and focus group discussions with program agents involved in supply chain processes of the child health intervention. Enterprise architecture was used to map the intervention’s supply chain and its participatory actors, and detailed bottlenecks of the chain through the application of a health systems framework. The results of this study will be used to inform a system dynamics model of the supply chain of iCCM in DRC. The greatest bottlenecks leading to stockouts at the community level occurred upstream (from national to province and from zone to health facility). While the use of local procurement processes was partially attempted to strengthen systems, parallel supply chain activities compromised sustainable system integration and development. Initial delays in stock dispensation were due to international procurement at the supplier, inducing a trickle-down effect. Inadequate quantification of supply needs and subsequent insufficient product procuration were the single most important steps that led to stockouts. This study demonstrated that the community health supply chain would be most impacted by improvements made in processes at the highest administrative strata, while exposing its delicate dependence on activities at the lowest levels. Visibility of inventory at all levels and improved data quality and use through a transparent tracking system have the potential to significantly reduce stockouts. Future interventions should take care to not develop parallel processes or exclude local health system agents to avoid disruption and ensure sustainable health outcome gains. Causal loop studies and system dynamics can further identify the systems interactions and relationships and their underlying causal mechanisms in need of intervention. Full article

The introduction of the National Surveillance Centre (NSC) has improved the efficiency and effectiveness of managing medicines availability within the public healthcare system in South Africa. However, at present, there is limited data regarding the perceptions among users of the NSC and challenges that need addressing. A descriptive quantitative study was performed among all registered active NSC users between August and November 2022. Overall, 114/169 users responded to a custom-developed, self-administered questionnaire (67.5% response rate). Most respondents used the Stock Visibility System (SVS) National Department of Health (NDoH) (66.7% for medicines and 51.8% for personal protective equipment (PPE) or SVS COVID-19 (64.9% for COVID-19 vaccines) or RxSolution (57.0% manual report or 42.1% application programming interface (API)) for reporting medicines, PPE, and COVID-19 vaccines to the NSC and were confident in the accuracy of the reported data. Most respondents focused on both medicines availability and reporting compliance when accessing the NSC, with the integrated medicines availability dashboard and the COVID-19 vaccine dashboard being the most popular. The respondents believed the NSC allowed ease of access to data and improved data quality to better monitor medicines availability and use. Identified areas for improvement included improving internet connectivity, retraining some users, standardising the dashboards, adding more data points and reports, and expanding user adoption by increasing licence limits. Overall, this study found that the NSC in South Africa provides an effective solution for monitoring and improving medicines availability. Full article

Synergies of optical, thermal and laser scanning remotely sensed data provide valuable information to study the structure and functioning of terrestrial ecosystems. One of the few fully operational airborne multi-sensor platforms for ecosystem research in Europe is the Flying Laboratory of Imaging Systems (FLIS), operated by the Global Change Research Institute of the Czech Academy of Sciences. The system consists of three commercial imaging spectroradiometers. One spectroradiometer covers the visible and near-infrared, and the other covers the shortwave infrared part of the electromagnetic spectrum. These two provide full spectral data between 380–2450 nm, mainly for the assessment of biochemical properties of vegetation, soil and water. The third spectroradiometer covers the thermal long-wave infrared part of the electromagnetic spectrum and allows for mapping of surface emissivity and temperature properties. The fourth instrument onboard is the full waveform laser scanning system, which provides data on landscape orography and 3D structure. Here, we describe the FLIS design, data acquisition plan and primary data pre-processing. The synchronous acquisition of multiple data sources provides a complex analytical and data framework for the assessment of vegetation ecosystems (such as plant species composition, plant functional traits, biomass and carbon stocks), as well as for studying the role of greenery or blue-green infrastructure on the thermal behaviour of urban systems. In addition, the FLIS airborne infrastructure supports calibration and validation activities for existing and upcoming satellite missions (e.g., FLEX, PRISMA). Full article

(1) Introduction: Near-infrared fluorescence (NIRF) combined with tumour-targeted tracers, such as bevacizumab-800CW, could aid surgical decision-making. This study explored the use of IRDye800CW, conjugated to bevacizumab, with four commercially available NIRF laparoscopes optimised for indocyanine green (ICG). (2) Methods: A (lymph node) phantom was made from a calibration device for NIRF and tissue-mimicking material. Serial dilutions of bevacizumab-800CW were made and ICG functioned as a reference. System settings, working distance, and thickness of tissue-mimicking material were varied to assess visibility of the fluorescence signal and tissue penetration. Tests were performed with four laparoscopes: VISERA ELITE II, Olympus; IMAGE1 S™ 4U Rubina, KARL STORZ; ENDOCAM Logic 4K platform, Richard Wolf; da Vinci Xi, Intuitive Surgical. (3) Results: The lowest visible bevacizumab-800CW concentration ranged between 13–850 nM (8–512 times diluted stock solution) for all laparoscopes, but the tracer was not visible through 0.8 cm of tissue in all systems. In contrast, ICG was still visible at a concentration of 0.4 nM (16,384 times diluted) and through 1.6–2.4 cm of tissue. Visibility and tissue penetration generally improved with a reduced working distance and manually adjusted system settings. (4) Conclusion: Depending on the application, bevacizumab-800CW might be sufficiently visible with current laparoscopes, but optimisation would widen applicability of tumour-targeted IRDye800CW tracers. Full article

Wheelsets form an indispensable part of the railway rolling stock and need to be periodically inspected to ensure stable, safe, reliable, and sustainable rail operation. Wheel profiles are usually inspected and measured in a workshop environment using handheld equipment or by utilizing wayside measuring equipment. A common practice for both methods is to measure the wheel profile at one position along the circumference of the wheel, resulting in a one-slice measurement strategy, based on the assumption that the wheel profile has the same shape independent of the measurement position along the wheel. In this article, the representability of a one-slice measurement strategy with respect to the wheel profile parameters is investigated using handheld measurement equipment. The calculated range of standard deviation of the parameters estimated such as flange height, flange width, flange slope, and hollow wear from the measurements shows a spread in the parameter value along the circumference of the wheel. As an initial validation of the results, measurements from the wayside monitoring systems were also investigated to see if a similar spread was visible. The spread was significantly higher for flange height, flange width, and flange slope estimated from wayside measurement equipment than for the same parameters estimated using the handheld measurement equipment. Full article

While much attention has been given, to date, to subsidies and taxes, the literature on the topic is yet to address less visible aspects of electro-mobility. These include the interactions among players, including money exchanges, and balance sheet issues. Analysing these is needed, as it helps identify additional mechanisms that may affect electro-mobility. This paper reports a modelling exercise that applies the system dynamics method, with its focus on stock and flow variables. The resulting simulation model captures the financial statements of several macro agents. The results show that the objective of the study is met: the model remains ‘stock-flow consistent’, meaning that assets and equity and liabilities balance out. By attaining this, the model serves as a coherent framework that makes the “hidden” side of electro-mobility visible, for the first time, based on current state-of-the-art, with the implication that it facilitates the analysis of potential financial factors that may either jeopardise or be conducive to faster road electrification. We conclude that the incorporation of the financial statements of key electro-mobility agents and their interlinkages in a simulation model is both a feasible and desired property for policy-relevant models. Full article