Background/Objectives: Non-muscle invasive bladder cancer (NMIBC) management is increasingly complex due to conflicting guideline-based risk classifications, ongoing Bacillus Calmette-Guérin (BCG) shortages, and emerging alternative therapies. Computational Histology Artificial Intelligence (CHAI) tests are clinically available, providing insights from tumor specimens including predicting BCG responsiveness and individualized recurrence and progression risks, which may support precision medicine. This technology features biomarkers purpose-built for clinically unmet needs and has practical advantages including a fast turnaround time and no need for consumption of tissue or other specimens. We assessed the impact of such tests on physicians' decision-making in routine, real-world NMIBC management. Methods: Physicians at six centers ordered CHAI tests (Vesta Bladder) at their discretion during routine NMIBC care. Tumor specimens were processed by a CLIA/CAP-accredited laboratory (Valar Labs, Houston, TX, USA) where H&E-stained slides were analyzed with the CHAI assay to extract histomorphic features of the tumor and microenvironment, which were algorithmically assessed to generate biomarker test results. For each case from 24 June 2024 to 18 July 2025, ordering physicians were surveyed to assess pre- and post-test management plans and post-test result usefulness. Results: Among 105 high-grade NMIBC cases with complete survey results available, primary management changed in 67% (70/105). Changes included modality shifts (n = 7; three to radical cystectomy with high prognostic risk scores; four avoiding cystectomy with low scores) and intravesical agent change (n = 63). Surveillance was intensified in 7%, predominantly among those with ≥90th percentile risk scores. The therapeutic agent changed in 80% (40/50) of predictive biomarker-present (indicative of poor response to BCG) tumors vs. 48% (23/48) of biomarker-absent tumors. Conclusions: In two thirds of cases, CHAI biomarker results influenced clinical decision-making during routine care. BCG predictive biomarker results frequently guided intravesical agent selection. These results have implications for optimizing clinical outcomes, especially in the setting of ongoing BCG shortages. Prognostic risk stratification results guided treatment escalation vs. de-escalation, including surveillance intensification and surgical vs. bladder-sparing decisions. CHAI biomarkers are currently utilized in routine clinical care and informing precision NMIBC management.

Vibration-Based Structural Health Monitoring (SHM) systems offer significant potential for damage detection due to their non-destructive nature and real-time capabilities, while reducing maintenance costs for aerospace and automotive applications. This study investigates the effect of damage on the modal parameters of a Carbon Fiber Reinforced Polymer (CFRP) fixed-free beam, with the goal of identifying damage location and severity. The lamina material properties of the CFRP were evaluated using composite lamination theory (CLT). By altering the location and depth of the damage, numerical analyses were conducted on the CFRP beam, and discrepancies between the intact and damaged models were examined. Modal frequency shifts were quantified using Relative Natural Frequency Change (RNFC), and RNFC-based mapping surfaces dependent on damage location and severity were generated for first four transverse vibrational modes of the beam. The model was validated through experiments on the intact and damaged CFRP specimens. The beam was excited with an impact hammer near the fixed-end, and responses were collected by piezoelectric sensors placed along the beam and laser vibrometer focused on the free end of the beam. The modal parameters were extracted using Ho-Kalman’s subspace method and experimental RNFC results of damaged samples were calculated. Then Nearest Neighbor search algorithm was successfully employed to estimate the damage location and severity by comparing experimental results to generated RNFC-based mapping surfaces.

The teaching and learning process has been challenged due to the sudden shift in modality brought by the COVID-19 pandemic. Currently, in the Philippines, schools have shifted from purely online classes to hybrid setup, while some conduct classes purely onsite. With the continuous implementation of online classes, schools utilise learning management systems (LMS) to allow the teaching and learning process to proceed. This research aimed to explore the different features of the learning management system and how these impact the oral communication skills of first-year college students. The study was conducted in a private tertiary educational institution based in Manila where first-year college students were purposively tapped as respondents. Said students were taking the general education course Purposive Communication during the second term of the school year. Mixed-method design was employed, where two instruments were used to gather data from the respondents: a survey and an interview. Out of the respondents who consented to participate in the survey, ten (10) were randomly selected to take part in the online interview. Descriptive analysis and thematic analysis were used to provide answers to the research questions, which are about the features of the learning management system that aid students in honing their oral communication skills and how these LMS features impact the students’ enhancement of the said skill. The study aimed to significantly aid the educational institution where the study was implemented, professors handling Purposive Communication, and the student-respondents as they work on improving their oral communication skills.

When less travel means more carbon: How rainfall-induced shifts from public transit to cars increase urban transport emissions.

Forecasting electric air taxi demand and modal shift for airport travel: a case study of northern Utah

Assessing modal shift potential to ease port-city tensions: A case study for the port of Antwerp based on truck GPS data

User satisfaction and transport modal shift in secondary Indonesian cities: Evidence from Palu

The willingness to adopt Autonomous Vehicles (AVs) represents a crucial advancement from the sustainable mobility perspective. This is progressively continuing in the developed countries. A comparable shift is expected in developing nations; however, empirical studies remain limited, especially in areas where AVs have not yet been deployed. This study investigates the willingness to adopt AVs in a developing city where AVs have not been deployed yet. A comprehensive travel behavior questionnaire was conducted among local commuters in Alexandria, Egypt, to identify the influential variables affecting AV choice. The well-known machine learning classifier, Extreme Gradient Boosting (XGB), was employed to develop a forecasting model, which indicated a notable accuracy. The results indicated that trip cost was the most influential feature. On the other hand, there is a considerable level of mode captivity, since most travelers prefer to remain with their current mode, regardless of the effects of other variables. A significant share of travelers expressed concerns about shifting to AVs due to safety worries associated with the travel behavior of other transportation modes’ commuters. The analysis provides nuanced perspectives on the variables promoting modal shift toward the AVs, supporting future policies for smart urban mobility.

This paper reviews the role of high-speed rail (HSR) and other fast rail technologies in decarbonising inter-urban transport. It first outlines the global deployment of HSR, with particular emphasis on Europe and China, and situates these networks within the wider geography of fast rail systems. The paper then compares HSR with competing modes such as air transport and passenger cars along key dimensions including door-to-door travel time, energy use and emissions. Building on a qualitative synthesis of the international literature, it discusses the environmental, economic and social impacts of HSR, highlighting conditions under which HSR can deliver substantial modal shift and life-cycle greenhouse gas savings, as well as situations where benefits are more limited or unevenly distributed. Finally, the review briefly considers emerging fast rail concepts such as Maglev and Hyperloop and argues that they should currently be treated as complementary, long-term options rather than immediate substitutes for conventional HSR.

ABSTRACT Demand responsive transport (DRT) systems have emerged as innovative solutions to address transportation inequality in areas underserved by conventional public transit. However, some recent DRT services have struggled because of a limited understanding of local contexts and user needs. A growing number of studies have investigated successful modal shift cases, the advantages of DRT, and user satisfaction. Nevertheless, studies conducting in-depth analyses of the factors influencing satisfaction and deriving the factors contributing to modal shifts are rare, with most evaluations limited to simple score-based assessments. This study aims to fill this gap by identifying factors affecting the three core characteristics of DRT services: mobility, accessibility, and user convenience. Using survey data from passengers, we analyzed both satisfaction and dissatisfaction using Binary Logistic Regression with a structured dataset. The analysis revealed several pivotal factors that influence user satisfaction. Key findings include the following: satisfaction levels are positively influenced by a ‘stronger intention to continue using DRT’, ‘reduced first-mile walking time’, and ‘lower detour rates’. Satisfaction with mobility and user convenience is particularly enhanced by the ‘experience of travelling to previously inaccessible locations’. Accessibility satisfaction was significantly affected by a ‘stronger intention to continue using DRT’. Furthermore, user convenience satisfaction is notably influenced by ‘female passengers’, ‘booking via phone’, and ‘no experience with call cancellations’. These findings have significant implications for the DRT service design and operational strategies.

The transport sector accounts for almost a fourth of the emissions in Europe, which makes it one of the priority sectors to decarbonize. As such, it should be modeled appropriately in all national energy and climate planning exercises. Unfortunately, most of these deal with transport demand in an aggregated way, unable to capture the differences existing in urban or rural environments in terms of potential for modal shift or penetration of transition technologies, and also erring in the estimation of the cost of these changes. This in turn may result in the wrong strategies being pursued to decarbonize transport. To overcome these problems, this paper proposes a methodology in which urban and non-urban areas are separated into different categories to represent their different configurations. The methodology allows representing a more realistic modal shift among demands, indicating where and how different paths and policies could be applied, which also makes it possible to understand the impact of deploying Low Emission Zones (LEZ). When applied to the case of Spain, results show that the decarbonization strategies assuming disaggregated demands differ significantly from the aggregated demand version, in particular for large metropolitan or suburban areas. Overall costs are also overestimated by the aggregated demand model, showing significant differences among urban areas. The disaggregation of transport demand presented in the paper allows therefore for a significantly better planning and budgeting of decarbonization strategies at a national or regional level.

The paper presents a detailed optimization model that considers supply chain network design (SCND) alternatives and carbon emission costs. To meet capacity and demand constraints, the model is designed to minimize overall logistical costs and carbon impact while also accommodating capacity and demand constraints through mixed-integer linear programming. How does this work? When applied to three-housing and seven-retail distribution systems, the model yields substantial advantages, including reduced carbon emissions of 3.6% and cost savings. The strategic internalization of carbon costs is a key finding, as it results in more sustainable network topologies while still being economically viable. According to the study, modal shift opportunities, warehouse utilization strategies, and route optimization are among the key contributors to emissions reduction. The results also demonstrate the feasibility of carbon-based SCND, provide a business case for emission reduction, and 'flexible planning frameworks' that can optimize efficiency across multiple regulatory areas; and supply chain managers gain valuable insights to help drive transitions towards low-carbon activities.

Impact of COVID-19 pandemic on treatment patterns for stage I Non-Small Cell Lung Cancer in the Netherlands.

How does bike-sharing prompt the modal shift from cars to public transit?

Human-powered vehicles as a way to abate transport-related greenhouse gas emissions, Part 1: Assessing modal shift impact through comparative Life Cycle Assessment — An Italian case study

The persistent challenge of Over Dimension Over Load (ODOL) violations in Indonesia's freight transport system poses critical threats to road infrastructure integrity, traffic safety, and economic efficiency. Despite regulatory frameworks established through Ministry of Transportation directives, enforcement remains fragmented, and compliance rates remain alarmingly low. This study develops an integrated multimodal transportation policy model employing Soft Systems Methodology (SSM) to address systemic ODOL violations through coordinated stakeholder engagement, technology-enabled enforcement, and strategic modal integration. Drawing on comprehensive analysis of 100+ peer-reviewed publications (2020-2025), international regulatory standards, and empirical enforcement data, this research constructs a holistic framework that transcends traditional command-and-control approaches. The proposed model integrates Weigh-In-Motion (WIM) technology deployment, port-gate digital integration systems, progressive sanction mechanisms calibrated to infrastructure damage externalities, and multimodal freight corridor development. Through SSM's seven-stage methodology, the study maps complex stakeholder interactions among government agencies, transport operators, infrastructure managers, and enforcement authorities, revealing systemic bottlenecks and leverage points for policy intervention. Empirical evidence from Abu Dhabi demonstrates 61% overload prevalence in unregulated environments, while Indonesian enforcement unit performance evaluations expose critical gaps in inter-agency coordination and enforcement capacity. The research proposes a phased nationwide implementation strategy encompassing governance architecture establishment, targeted enforcement pilots in high-risk corridors, sanction calibration linked to quantified road damage costs, and complementary modal shift incentives. This SSM-informed policy model offers actionable pathways for Indonesia to achieve Zero ODOL objectives while maintaining freight system efficiency and stakeholder viability, contributing theoretical advancement in systems-based transportation governance and practical frameworks for developing-country freight policy reform.

Speed pedelecs—electric bicycles with pedal support up to 45 km/h—have been identified as promising alternatives to car travel, particularly for commuting. However, their uptake in Germany is limited, potentially hindered by legal restrictions to their use of existing cycling infrastructure. This paper reports on qualitative interviews with 11 participants who tested speed pedelecs for several weeks in Tübingen, the first German city to create a designated speed pedelec network by opening up cycle infrastructure and agricultural roads. The aim of the study was to explore the experiences of the speed pedelec testers and their perceptions of the speed pedelec as a potential replacement for more carbon-intense modes of transport. Thematic analysis produced four key themes: (1) Suitability for everyday life, including speed, independence, and commuting utility; (2) Cycling for body and mind, with benefits to physical and mental health; (3) Mixed interactions, reflecting tensions and co-existence with drivers, cyclists and pedestrians, and (4) Questioning the status quo, with critiques of regulatory limitations and infrastructure. While participants successfully used the speed pedelecs to replace car or public transport trips and largely enjoyed using the bikes, barriers such as limited infrastructure, interactions with drivers, limited luggage transport and high costs hindered long-term adoption intentions. From the perspective of the speed pedelec testers, interactions with cyclists and pedestrians were generally positive, challenging the blanket ban of speed pedelecs on cycling paths and instead highlighting the need for attractive and safe infrastructure design for all types of active transport.

Abstract After the collapse of the command-and-control system, Central and Eastern European countries witnessed a significant modal shift. Previously, mobility there was largely dominated by public transport, but the political and economic reforms transformed these areas into places where individual mobility plays a main role. Poland was no exception. Currently, the majority of Polish people, especially from small- and medium-sized towns and rural areas, use passenger cars on a daily basis, which leads to negative societal and environmental consequences such as congestion, maintenance costs of road infrastructure, and air and soil pollution. In response to these problems, public authorities have initiated policies and investments designed to stimulate a modal shift towards public transport. This article aims to verify the possibility of a modal shift as a result of upcoming railway infrastructural investment. The above-mentioned objective is achieved by means of a survey conducted among commuters performing daily travel to and from the case city of Polkowice. The collected data were analysed using a decision tree method, which is relatively novel in geographic and transport studies. The results showed that the majority of the surveyed respondents expressed an inclination to use the restored railway line, whereas only a small proportion were willing to abandon car transport in favour of train travel. The applied method also allowed the profile of those persons most inclined the to make a modal shift to be identified.

Given the huge contribution of the transportation sector to CO2 emissions in metropolitan areas, urgent countermeasures are needed to achieve carbon neutrality. In this study of 66 administrative units (cities, counties, and districts) in the Seoul metropolitan area, we applied cluster analysis and a hierarchical regression model to analyze the impact of the 7D factors of Transit-Oriented Development (TOD) on CO2 emissions from road transportation. The effects of TOD factors were found to vary in diverse contexts. A higher concentration of employment intensified regional travel demand, thereby increasing emissions—a phenomenon referred to as the Paradox of Concentration. In contrast, the expansion of urban rail and bicycle infrastructure facilitated modal shift toward sustainable transport but simultaneously stimulated commercial and logistics activities, leading to elevated overall emissions. Thus, a ‘two-faced infrastructure’ pattern is evident in the Seoul metropolitan area. Conversely, strengthened local self-containment by destination accessibility promoted short-distance travel, curbing emissions. These outcomes empirically exhibit that the low-carbon effect of TOD is contingent, implying that urban structure and policy context are key factors in determining emission pathways. The impacts of the TOD 7D factors are discussed in terms of emission effects, and differentiated policy directions reflecting inter-city heterogeneity are suggested. In particular, the results of our analysis emphasize the need for comprehensive TOD strategies that combine transportation infrastructure, demand management, local self-containment, and zero-emission logistics systems, beyond simple compact development strategies. The policy implications described here are applicable in other countries experiencing rapid urbanization.

Background: This study analyzes modal distribution patterns across Europe and 28 European countries, employing clustering analysis to identify trends in transport mode utilization. The research quantifies logistics diversification, examining extreme cases and addressing gaps in understanding modal transitions affecting environmental and economic performance. Methods: Statistical testing using compositional data transformations revealed significant differences between modal distributions (p < 0.001), justifying country-specific and European-level assessments. K-means clustering was applied to identify groups of countries with similar modal distribution patterns. Results: Maritime and road transport constitute the predominant modes across all analyzed countries in the study period. Among terrestrial modes, road transport dominates universally, exhibiting systematic growth, while rail transport experienced a corresponding decline. This trend directly contradicts European sustainability objectives promoting modal shift toward environmentally superior alternatives. Romania demonstrates the highest logistics diversification with the most balanced modal distribution, while Portugal exhibits the lowest diversification due to maritime transport dominance. K-means clustering positioned Portugal within a maritime-dominated group alongside Greece, Cyprus, and Ireland, reflecting similar geographical constraints and distribution patterns. Conclusions: The findings reveal critical aspects requiring further investigation concerning European modal distribution trends that challenge current policy effectiveness, highlighting the divergence between observed transport patterns and stated sustainability goals. These results provide essential insights for addressing persistent modal shift challenges in European transport systems.