Robust shift scheduling with discretionary rest breaks

Planning on-street parking for cars and trucks in urban areas with limited curbside space poses significant challenges for decision-makers. This paper proposes a flexible, multi-criteria planning tool for allocating on-street parking that accounts for heterogeneous user needs. The problem is formulated as a Mixed-Integer Programming (MIP) model, suitable for applications where real-time information is unavailable, during initial planning stages, or when curbside space must be reallocated. The allocation criteria aim to maximize the level of service within the planning area, defined in terms of the number of users served, infrastructure utilization, and parking search impacts. Results show that explicitly modeling cars and trucks separately substantially alters optimal allocation outcomes, increasing truck service by up to 50%, reducing truck parking search time by 75%, and increasing the parking search component of the objective function by 8%. Sensitivity analyses further indicate that prioritizing user types yields moderate changes in performance (−3% to +9%), whereas shifting the planning emphasis between service and utilization versus minimizing parking search externalities leads to the largest improvements, increasing the overall level of service by up to 153%. These findings highlight the importance of accounting for user heterogeneity in curbside planning and demonstrate the usefulness of the proposed tool in supporting objective-driven parking allocation decisions.

Building data capacity for maternal health equity: Introduction of a novel dataset.

• Offers a new vision on automated data harmonization in Dataspace (DS) systems. • Introduces LLM-based methods for scalable DS ingestion of heterogeneous datasources. • Presents a system with Harmonizer, Transformer, Evaluator components for ingestion. • Demonstrated an automated data ingestion prototype using LLM agents. • Validates the system with healthcare use case harmonizing heterogeneous data sources. Dataspaces (DS) enable stakeholders to collaborate on innovative, data-driven services by integrating data across domains. However, the realization and adoption of DS remain challenging due to domain-specific heterogeneity at the system, service, and data levels. While system and service-level heterogeneity can often be addressed through standards, data-level heterogeneity, namely data structures and semantics variations, remains challenging. To effectively ingest data into the DS, two communication endpoints must correctly interpret each other’s data models, therefore, DS ecosystems rely on “harmonization”, the process of generating a unified target data model from heterogeneous sources and transforming incoming data accordingly. Currently, harmonization and transformation are performed manually whenever new data sources are integrated. This is time-consuming, costly, and difficult to scale, posing a critical barrier to the realization and adoption of DS in practice. This study proposes a novel methodology for automated data harmonization during ingestion into DS ecosystems. The approach integrates harmonization, transformation, and human-in-the-loop evaluation within an automated system powered by modern LLM-based AI agents. These agents address data-level heterogeneity and generate harmonized target data models, representing a substantial departure from current manually-handled data harmonization. The system is validated through a healthcare use case, demonstrating its practical feasibility for harmonization during data ingestion into the DS. Overall, this work provides a foundational step toward seamless, efficient, and scalable data integration in DS. By automating data harmonization, it delivers substantial value to industry digital solutions as well as domains where data heterogeneity persists, including IoT or Big Data platforms.

A demand response to line planning

The stochastic production routing problem with adaptive routing and service level constraints

Autonomous utility service vehicles (AUSVs) represent a distinct class of automated platforms designed to operate at very low speeds (often around 5–10 km/h) for urban road maintenance tasks, yet their integration in mixed traffic remains poorly understood. This study evaluates the effect of AUSVs through a microscopic simulation using a real-world network modeled on the Pangyo autonomous driving testbed in South Korea. Twelve scenarios (six AUSV speeds, 5–30 km/h, and two traffic volumes, level of service [LOS] C and LOS D) were simulated; LOS C and D were deliberately selected—beyond the typical off-peak LOS A/B context—to empirically identify the demand threshold above which AUSV effects become operationally significant. Performance was assessed across vehicle, lane, link, and network levels using speed, shockwave propagation, time-to-collision (TTC) ratios, and lane-change rates. Results revealed consistent patterns. At the lane level, AUSVs at 5 km/h induced backward-moving queues up to 120 m in length and critical TTC ratios of up to 0.50 under LOS D, while no significant disturbances occurred under LOS C—revealing a critical operational threshold between the two demand regimes. At the link level, speed reductions of ≥20 km/h concentrated on two-lane bottlenecks, where overtaking opportunities were constrained. Network-wide, average speeds increased monotonically with AUSV speed, while lane-change rates peaked at 5 km/h (32.5 events/km under LOS C; 59.1 events/km under LOS D) and declined thereafter. These findings support demand-aware scheduling (off-peak for ≤10 km/h operation), minimum speed thresholds (≈15 km/h), and bottleneck-avoiding routes as practical strategies for sustainable AUSV deployment.

The rural cultural landscapes in the Yellow River Basin, as an important part of the blue-green infrastructure, not only provide ecological services and public spaces, but also carry the function of regional cultural inheritance. The spatial layout of rural cultural landscapes deeply aligns with the multi-level living circles of residents, and has a significant impact on the organization of landscape spaces and social ecological resilience in rural areas. This study took 14,502 administrative villages in 25 counties (cities and districts) along the Yellow River in Shandong Province as the research objects. Based on mobile phone signaling data, the boundaries of rural living circles at the three scales of towns, counties and cities were identified, and the accessibility evaluation indicators of six types of cultural landscape facilities were constructed in combination with POI data. The aim is to reveal the service level of rural cultural landscapes and their potential role in promoting health equity and resilience. The research shows: (1) The travel radius of rural living circles in the Yellow River region as a whole shows an increasing trend from upstream to downstream, with a concentric expansion feature centered on county towns. The average radius of township, county and municipal living circles is approximately 8 km, 13 km and 18 km respectively; (2) The overall accessibility of cultural landscape facilities shows a multi-center and ring-shaped distribution pattern. There are significant spatial differences in the spatial distribution of different types of facilities. Among them, landscape green spaces form a high accessibility zone with a relatively high degree of continuity relying on prefecture-level cities and county parks. Sports, leisure, science and education, and cultural facilities are concentratedly distributed in county towns and key towns. Cultural relics, ancient sites and scenic spots are scattered in a point-like manner due to historical evolution and natural conditions. The cultural facilities along the main stream of the Yellow River are arranged in a string-like pattern; (3) The results of geographically weighted regression (GWR) show that the effects of different facility types on the characteristics of living circles have significant spatial non-stationarity. The response degree in the middle section of the Yellow River region is relatively higher. The research results can provide quantitative support for the layout optimization of rural cultural landscape facilities and the construction of living circle systems in the Yellow River region.

IntroductionOnly 6% of UK memory services meet Alzheimer’s disease (AD) biomarker access guidelines, limiting psychiatrists’ experience. Emerging AD blood biomarker (BBM) tests will potentially expand access. Exploring implementation barriers and enablers a priori can inform rollout strategies. This study examined current clinical practises, barriers and enablers to implementation and potential interventions to support implementation.MethodsIn November 2024, Royal College of Psychiatrists Old Age Psychiatry Faculty members (n = 172) participated in an online survey and four focus groups (n = 16 participants), informed by the Theoretical Domains Framework (TDF) and Behaviour Change Wheel. Demographic data were summarised descriptively. Mean (SD) belief statement scores for TDF domains and percentage agreement were calculated. Multiple linear regression examined associations between TDF domains and intention to use BBMs.ResultsRespondents were mainly consultants in England; <33% had used biomarkers. Key barriers to use were: ‘Knowledge,’ ‘Environmental Context and Resources’ and ‘Goals.’ Enablers included: ‘Behavioural Regulation,’ ‘Social Influences’ and ‘Intention.’ Mixed enablers/barriers included: ‘Beliefs about Consequences’, ‘Optimism’ and ‘Social/Professional Role & Identity’. In regression analyses, ‘Memory, Attention and Decision Processes’ (B = 0.44, 95%CI 0.20–0.68), ‘Beliefs about Consequences’(B = 0.45, 95%CI 0.11–0.78), and ‘Social Influences’ (B = 0.24, 95%CI 0.04–0.44) were positively associated with intention, while ‘Optimism’ (B = -0.31,95% CI-0.58 to-0.04) and ‘Emotion’ (B = -0.33, 95%CI -0.60 to-0.06) were negatively associated. Key interventions were ‘Guidelines’ (e.g. appropriate use criteria) and ‘Environmental Restructuring’ to expand resources and re-organise pathways.DiscussionA complex interplay of barriers and enablers influences AD BBM implementation. Interventions targeting clinician, service and policy levels are required to support their introduction.

Cervical cancer (CC) is the most common cancer among women in Uganda, with many being diagnosed when the disease is in an advanced stage. Visual Inspection with Acetic acid (VIA) remains the most readily available CC screening method in most health facilities in Uganda, but with low screening coverage. This study aimed to understand the barriers and facilitators to CC screening in Uganda. A qualitative study was conducted between March 2022 and March 2023 in Mukono, and Wakiso. Through Focus Group Discussions (FGDs) data was collected on perceived barriers and facilitators to CC screening among women aged 25-65 years, primary health care workers (PHC), and community representatives (local authorities and members of civil society organisations). Sixteen FGDs were conducted with 8-12 participants per group. Four FGDs with women (57 participants), four with community representatives (35participants) and four FGDs with PHC workers (32participants). Thematic analysis was performed using deductive and inductive coding guided by the social ecological model. Perceived barriers and facilitators to CC screening emerged at multiple levels. At the individual level, women identified limited knowledge about CC screening as a major barrier, alongside several forms of fears, including fear of exposing private parts, fear of positive screening results, and concerns regarding the potential costs of treatment. At the interpersonal level, inadequate support from partners, peers, and family hindered CC screening uptake. Institutional barriers included negative attitude of health worker, prolonged waiting times, and long distances to health facilities. At the community level, stigma such as being labeled adulterous for seeking CC screening services discouraged participation. Conversely, facilitators of CC screening included awareness of the benefits of screening and experience sharing at the individual level, community sensitization and decentralization of services at the community level; and availability of accessible treatment services at the institutional level. Despite free, publicly available CC screening services in Uganda, women continue to encounter numerous barriers that influence both access to and utilization of these services. Enhanced community sensitization is essential to improve awareness of the importance of early CC screening. Additionally, there is a critical need to ensure that subsequent care and treatment services are more financially accessible to all women. Not applicable.

Efficiency in the health system can be referred to as the attained level compared to the maximum level of outcome that could be achieved using the given amount of resources. In a resource-constrained country like India, analysing the efficiency of the health system is of utmost importance, as limited resources must serve a vast population. In India, Tamil Nadu is a frontrunner in the provision of health services. The state of Tamil Nadu strives to provide quality health services to its people, for which improving the efficiency of health services is imperative. Therefore, this study analyses the efficiency of public health services among the districts of Tamil Nadu using a two-stage approach. In the first stage, Data Envelopment Analysis (DEA) is solved, and efficiency scores are calculated using the selected inputs and outputs. In the second stage, the obtained efficiency scores are regressed on the selected explanatory variables that are expected to influence the efficiency scores. The DEA results reveal wide differences in the efficiency levels of public health services among Tamil Nadu’s districts. Among the explanatory variables, economic development, measured in terms of Net District Domestic Product, was found to be an influencing factor in the efficiency scores. This calls for the state to focus on regional development to achieve efficiency and provide improved health services to the people.

Internet of Things (IoT) is rapidly expanding in smart city usage in applications such as smart traffic systems, power management, ecological monitoring, security in cities, and some more vital services. Quality of connectivity and response time have significant effects on how well these systems function. It is thus the crucial factor with respect to their functioning performance. The emerging requirement is then for IoT technologies with enhanced connectivity efficiency and data-loss minimization capabilities. To reduce Packet Error Rate (PER) higher Quality of Service (QoS) levels are used but at the expanse of imposing more load on the broker which should serve multiple publishers and subscribers. In this paper, it is proposed to improve the PER at a target subscriber by the assistance of a peer neighbor subscriber. The conducted tests show the capability of the proposed Peer-Assistance (PA) scheme to enhance PER up to 65% with respect to conventional QoS schemes tested under the same conditions. Although, this enhancement is at the expense of an increase in system latency, it provides a useful trade-off enabling design customization to suit the requirements of the specific application. Moreover, the proposed PA scheme introduces a mechanism that redistributes the retransmission load from the broker to neighboring subscribers, thereby enhancing the broker's availability to serve its clients

Urban Air Mobility (UAM) systems offer a three-dimensional transportation alternative by using low-altitude airspace, with the potential to reduce travel times and improve access to mobility in regions underserved by current transportation systems. To support efficient design and operation of UAM systems, we develop an integrated optimization framework in response to three interrelated challenges: (i) land use, aeronautical feasibility, community acceptance and other factors that restrict the number of potential locations for vertiports, (ii) bidirectional demand–supply interaction that needs to be considered, as the level of service influences demand for UAM and operators adjust the level of service in response to demand, and (iii) strong interactions between strategic decisions on the distribution of ground infrastructure, tactical decisions on eVTOL fleet size and operational decisions on dispatching and repositioning. Analyzing the decisions in isolation can lead to poor estimates of the overall system performance. The framework consists of (1) a knock-off criteria analysis model for the identification of a realistic set of candidate locations for vertiports, (2) integer programming models in which strategic, tactical and operational decision levels are modeled, and (3) pre-processing techniques to generate near-optimal solutions for real-world instances. By applying the framework in a large-scale real-world setting in the Île-de-France region, we demonstrate complex interactions between strategic, tactical, and operational decision levels and customer demand, revealing various trade-offs between operator profit and traveler generalized travel costs. • Provide realistic candidate vertiports in the Île-de-France region using knock-off criteria screening. • Integrate vertiport location selection with eVTOL fleet sizing and operations and demand interaction. • Identify non-linear trade-offs between operator profit and user generalized travel costs. • Conclusions on the economic viability of UAM operations. • Identification of UAM network structures with distinct vertiport roles.

Previous studies have shown poison centers (PCs) reduce healthcare costs, often by preventing unnecessary emergency care visits. An updated cost-savings estimate has not been recently conducted. This was a retrospective study analyzing caller survey data for a three-state American PC, gathered from 2021 to 2024. The PC's annual budget is $3.3 million (M). Eligible cases included public callers whose poisoning question was managed on-site and later completed a post-call telephone survey, including the question, "What would you have done if the poison center was not available to you?" Emergency care costs were estimated using three variables to reflect costs rather than charges. Ambulance transport costs and physician professional fee reimbursements for emergency department (ED) evaluation and management (E&M) codes were calculated from the U.S. Centers for Medicare and Medicaid Services published data. Facility fees from the associated E&M codes were calculated based on a general reimbursement rate of 33% of charges from our PC's affiliated safety-net hospital. E&M codes 99284 and 99285 (levels of service [LOS] 4 and 5, respectively) were used to calculate a cost-savings range. Among 1670 respondents to the survey (overall completion rate, 24%), 1346 (81%) would have immediately sought care; n=916 [55%] of which would immediately call a healthcare professional while n=430 [26%] would call 911 or go to the ED. Extrapolating survey results to our entire caller population, the estimated annual cost-savings from avoided emergency care visits for each state were as follows: Minnesota, $29.4 to 48.0M; North Dakota, $5.0 to 5.7M; South Dakota, $5.1M to 7.5M, for a benefit-to-cost ratio of $12.07 to $18.55:1. When factoring in our annual budget, this results in an annual net savings of $36.5 to 58.0M for our three-state region. Sensitivity analysis, assuming all ED visits reimbursed at LOS 4 and that ambulance transports occurred less frequently and were less costly per transport, still demonstrated robust cost-savings, with a benefit-to-cost ratio of $6.22-6.88:1. Using standard reimbursement data, we demonstrated our poison center likely saves our three-state region more than six times its annual budget solely from preventing unnecessary emergency care visits.

Location-based accessibility is widely assessed using zonal frameworks that aggregate high-resolution results into summary statistics. This aggregation-induced error is often assumed to be negligible, yet this assumption is rarely verified and may obscure critical disparities. This study introduces “Accessibility Misrepresentation” as the deviation between high-resolution accessibility and zonal proxies. Using building-level public transport accessibility in Metropolitan Melbourne, the research evaluates the magnitude, spatial patterns, and equity implications of misrepresentation. Results show systematic variation across travel time thresholds, built environment characteristics, aggregation methods, and service levels. Missed detection of populations without accessibility peaks at 15–20 min thresholds commonly used in neighbourhood accessibility policies, predominantly affecting densely populated middle suburbs where public transport catchments misalign with administrative boundaries. Continuous errors in accessibility values show no systematic directional bias; however, minorities can experience substantial misstatements sufficient to alter normative assessments. Equity analysis reveals disproportionate impacts on middle-status populations often overlooked by conventional frameworks. Population-weighted medians substantially outperform means in reducing misrepresentation. However, no single statistic adequately captures internal variation, particularly with multimodal distributions. A dual-scale approach is recommended: high-resolution computation to characterise within-zone distributions, combined with zonal summaries accompanied by distributional diagnostics, including share of residents without accessibility and upper-tail error indicators. This approach enhances transparency, supports equity-focused and defensible planning decisions without costing additional resources. • Zonal summaries cause “Accessibility Misrepresentation”. • Well-served zones may mask large accessibility gaps. • Middle socioeconomic group has large underserved subpopulations. • Medians outperform means as summaries of zonal accessibility. • Dual-scale analyses expose disparities and preserve interpretability.

Purpose With the intensification of market competition and the widespread adoption of the dual-channel model, the interaction among pricing, services, and digital investment in the supply chain has become crucial. The influence of corporate social responsibility (CSR) and digital transformation is also becoming increasingly significant. The purpose of this paper is to explore the collaborative decision-making mechanism for digital investment, CSR undertakings, and retail service levels in a manufacturer-led dual-channel supply chain. Design/methodology/approach The study uses game theory to develop a supply chain model for manufacturers to fulfill CSR, compare and analyze the equilibria under centralized and decentralized decision-making, and extend the model for retailers to fulfill CSR. Findings The consumer's CSR sensitivity significantly affects the benefits of CSR behavior, and centralized decision-making is always superior; under conditions related to CSR sensitivity, digital investment is positively correlated with manufacturer profits. The study further indicates that in low-sensitivity markets, it is more beneficial for retailers to undertake CSR, and the level of digital investment is higher. The relationship between digital investment and CSR, however, is the opposite of how manufacturers implement CSR. In contrast, in high-sensitivity markets, it is more effective for manufacturers to undertake it. In addition, this paper designs a coordination contract based on wholesale prices and clarifies the pricing range that can achieve a win-win situation. Originality/value The innovation of this study lies in integrating digital investment and CSR into a dual-channel decision-making process and systematically comparing the impact of different CSR undertaking entities on supply chain performance. This provides enterprises with collaborative management insights to promote responsible governance and digital transformation.

Assessing household water and sanitation service levels in an informal settlement using the WHO/UNICEF JMP framework: Evidence from Stoneridge, Harare (Zimbabwe).

Servitization for environmental and social management practices in manufacturing: The role of digitalization as an enabler.

Stochastic dynamic lot-sizing with supplier-driven substitution and service level constraints

Introduction: The Lansia Sehat application was developed as a recording and reporting system for elderly health services. However, its utilization at the service level has not been optimal. This study aimed to evaluate the implementation of the Lansia Sehat application in Tanggamus Regency from a health management perspective. Methods: This study used a qualitative design with a case study approach. Informants included elderly program managers, primary healthcare staff, and related application users. Data were collected through in-depth interviews, observations, and document reviews. Data analysis was conducted using the Input–Process–Output (IPO) framework. Results: The application implementation was not optimal, indicated by double recording practices and limited data use for reporting purposes only. In the input aspect, issues included limited interface design, absence of integrated user guidance, lack of offline features, and weak operational policy support. In the process aspect, data entry was inefficient, the system was not integrated, and synchronization problems frequently occurred. In the output aspect, the application improved report standardization, but the speed, accuracy, and use of data for decision-making remained low. Conclusion: The application is still in a transitional phase and has not produced significant managerial impact. Required improvements include simplification of data entry workflows, provision of integrated user guidance, addition of offline features with automatic synchronization, and integration with other reporting systems to reduce duplicate recording. Strengthening governance, improving system design, clarifying roles, and optimizing data utilization are required to transform the application into a decision-support system for elderly health programs.