Search Results (1,167)

This study assessed the feasibility of a technology-supported high-intensity interval training (HIIT) program for occupational drivers. A multiphase feasibility study incorporating participant feedback was conducted in Flanders, Belgium, including consultation, pilot, and intervention phases. Occupational drivers were randomized to a HIIT group, an active control group (mindfulness program), or a passive control group (no intervention). The 16-week, equipment-free HIIT program consisted of two 15-min sessions per week, delivered via a technology-supported mobile application, preceded by a 2-week baseline. Primary feasibility outcomes included program completion, session adherence, intervention fidelity, adverse events, and participant experiences, while changes in health-related outcomes were assessed as secondary exploratory outcomes using validated questionnaires. During the consultation (n = 11) and pilot (n = 2) phases, participants reported positive attitudes toward the intervention. Key barriers, including scheduling constraints (n = 5) and bicycle transportation (n = 4), informed refinements such as an equipment-free, technology-supported protocol and flexible scheduling. Of the 23 randomized participants across all groups, 16 participants initiated their assigned study protocol, and 10 completed all assessment points and were included in the final analysis. Of the nine participants allocated to the HIIT group, four initiated the intervention (44.4%), and three completed the program (33.3% of those allocated; 75% of those who initiated). Among the three completers, mean session attendance was 80.2%. Session fidelity was well maintained, but exercise-intensity fidelity could not be objectively confirmed. No exercise-related adverse events were reported. Participant feedback indicated generally positive usability but mixed acceptability of the technology-supported HIIT program among the three participants who completed the intervention. Exploratory individual-level changes in health-related outcomes were heterogeneous, with lower mean scores for depression, anxiety, stress, and fatigue. A technology-supported HIIT program was feasible among the small subgroup of occupational drivers who initiated it, with high session attendance. However, considerable pre-initiation attrition and low retention limit its feasibility for the broader target population. Observed health-related outcomes were heterogeneous and should be interpreted descriptively, warranting evaluation in a fully powered randomized controlled trial. Full article

Lithium-ion battery-powered (LIB-powered) electric bicycles (E-bicycles) are widely used in China, with many accidental fires occurring in parking facilities in high-rise buildings. E-bicycle parking areas in high-rise buildings have become fire-prone zones. There is an urgent need to establish fire codes for the parking facilities in high-rise buildings. However, only limited research has been conducted on protecting against such fires. Uncertainties also remain about appropriate methods for fire barriers and fire suppression in parking facilities. To better understand parking facility fires in high-rise buildings, four fire scenarios and a total of six experiments on LIB-powered E-bicycle fires were studied in this paper, aiming to seek principles on how to prevent serious fire accidents by isolating E-bicycles parked in parking facilities. Fire spread between the LIB-powered E-bicycles and the propagation patterns of smoke generated by E-bicycle fires within parking facilities were studied. The effectiveness of different fire extinguishing methods in suppressing LIB-powered E-bicycles fires was discussed. The reasonable fire separation distance for E-bicycles was determined. It was found that LIBs with ternary lithium-ion batteries (such as nickel-cobalt-manganese) are more prone to initiate thermal runaway. Setting appropriate separation distances could effectively minimize the spreading of E-bicycle fires in high-rise buildings. A sprinkler system with a lower hazard class is proposed to operate under lower water pressure and flow rates. Fire control methods were proposed, including fire-resistive eave and fire barrier. The results can be used in setting up fire code. Full article

Decalin, accessible through the hydrogenation of coal-tar-derived naphthalene, is a saturated bicyclic hydrocarbon consisting of two fused cyclohexane rings, and provides a promising platform for high-energy-density fuel (HEDF) design. A systematic library of alkyl- and cycloalkyl-substituted trans-decalin derivatives was constructed to investigate structure–property relationships involving density, net heat of combustion (NHOC), specific impulse, viscosity, flash point, and thermal/oxidative stability. Minimum C–C and C–H bond dissociation enthalpies were used to comparatively assess thermal and oxidative stability by reflecting initial C–C homolysis and H abstraction tendencies, respectively. Density and volumetric NHOC were governed mainly by molecular compactness and packing efficiency, whereas gravimetric NHOC and specific impulse depended primarily on the H/C ratio and ring strain. The flash point was mainly associated with molecular mass, while viscosity was influenced by molecular mass and molecular architecture. Under the engineering-oriented constraints of viscosity ≤ 16 mPa·s and flash points ≥ 360 K, multi-objective screening identified the spiro four-membered-ring motif, particularly α-S-Cycle4, as providing the best overall property balance. In contrast, the fused three-membered-ring motif showed higher specific impulse but greater susceptibility to initial bond activation, suggesting its potential use as a blending component. This work provides quantitative structure-based guidelines for the rational design of HEDFs. Full article

Cycling is increasingly promoted as part of sustainable transport strategies, but safety concerns remain an important barrier. Crash-based safety assessment is limited because crashes are reactive indicators and cycling crashes are often underreported. This study evaluates whether smartphone inertial sensor data can be used to detect selected potentially critical cycling manoeuvres that may support proactive safety screening. A two-stage workflow intended for possible future smartphone implementation was evaluated offline. In Stage 1, kinematic thresholds were applied to identify short candidate sensor windows when a high-dynamic manoeuvre was detected. In Stage 2, a machine learning classifier was applied to these candidate windows to classify the manoeuvre type and reduce false positives. The workflow was evaluated using three datasets collected in Germany from 10 riders, including controlled test-track manoeuvres and urban rides in Aachen and Bonn. The dataset included 148 hard-braking and 132 abrupt-swerving manoeuvres. In addition, 45 bicycle-only crash-like reference sequences were collected to compare low-speed impact-like signal patterns. In leave-one-dataset-out evaluation, the Support Vector Machine achieved mean precision–recall areas under the curve of 0.954 for hard braking and 0.884 for abrupt swerving. The corresponding mean F1-scores were 0.924 and 0.876. The offline evaluation showed that smartphone sensor data can support the detection of selected high-dynamic cycling manoeuvres with good classification performance under controlled and semi-controlled conditions. However, most target manoeuvres were controlled or rider-initiated proxy manoeuvres rather than confirmed traffic conflicts. The results should therefore be interpreted as manoeuvre detection, not as direct crash-risk validation. In future naturalistic studies, the workflow could help identify candidate locations where cyclists frequently brake hard or swerve abruptly. These locations can then be prioritised for site inspections, video-based conflict analysis, or comparison with crash records. Full article

Mountain biking over rough terrain exposes riders to vibrations that may affect comfort, health, bicycle control, and performance. This study analyzed the effect of wheel diameter on vibration transmission and performance during a short uphill and downhill test over rocky terrain. Forty-nine highly trained male mountain bikers completed repeated trials using two equivalent hardtail mountain bikes with 26- and 29-inch wheels. Vibrations were recorded with eight triaxial accelerometers placed on the bicycle and rider, and performance was assessed using an electronic photocell timing system. Both wheel sizes showed a similar vibration pattern, with lower root mean square (RMS) acceleration values at the helmet and coccyx and higher values at the wrists and ankles. However, wheel diameter significantly influenced vibration transmission. During the uphill test, the 26-inch bicycle produced higher accelerations at the coccyx and rear hub, whereas during the downhill test, the 29-inch bicycle transmitted greater vibrations to the rider’s wrists and ankles. No significant differences were observed between wheel sizes in the time required to complete either the uphill or downhill tests. These findings suggest that, in short and highly irregular uphill and downhill sections, 29-inch wheels do not necessarily improve performance over 26-inch wheels, although they modify the distribution of vibrations transmitted to the rider. Full article

Lewis acid-catalyzed epoxide openings efficiently promote intramolecular cyclizations forming complex oxygenated frameworks. Herein, we investigated the reactivity of epoxyolefins under catalytic conditions using various metal triflates. The study focuses on the competition between epoxide isomerization and intramolecular cyclization involving a pendant olefin. Screening of several metal triflates revealed that Lewis superacids, particularly Bi(OTf)₃, promote efficient transformations at room temperature with low catalyst loadings (1 mol%). Structural variation in the substrates significantly influenced product distribution likely through coordination effects, impacting cyclization efficiency with higher yields observed for non-chelating epoxyolefins. Substrates derived from geraniol underwent selective cyclization to cis-cyclic alcohols and bicyclic ethers in good yields, with stereochemical outcomes consistent with the Eschenmoser model. Reaction conditions such as temperature and catalyst loading further modulated selectivity, allowing control over product distribution. These results highlight the potential of metal triflates as versatile and efficient catalysts for the stereoselective intramolecular cyclization of epoxyolefins, offering access to cyclic frameworks under mild conditions. Full article

A compact 24 GHz FMCW radar board was evaluated for low-speed bicycle and small-vehicle sensing under strict memory and latency constraints. The hardware uses only 30 MHz modulation bandwidth, giving a nominal range resolution of about 5.0 m and a Doppler-bin spacing of about 2.57 m/s. Its small, incompletely calibrated antenna path also prevents any claim of high-angular-resolution imaging-radar performance. Within this constrained platform, the measured sequences reveal four coupled failure modes: static reflectors remain prominent in the range–Doppler map, useful low-Doppler responses are easily lost near the processed spectral boundary, weak plots do not always initiate a track, and short echo gaps can break otherwise continuous trajectories. To address these limitations, we combine frame-differential range–Doppler enhancement, quadrant-aware boundary-adaptive CA-CFAR, physically gated seed-growing initiation, and finite-frame retained Kalman tracking with SNR-weighted updates. In addition to natural bicycle and small-vehicle measurements, a labeled synthetic 64 by 32 range–Doppler benchmark is used to report Precision, Recall, F1-score, ROC/AUC, detection probability, and false alarms per frame for multiple CFAR variants. Public-radar tracking metrics are also reported on RadarScenes, a public RADIATE foggy sample, and nuScenes mini radar-only sequences with a bounded-approximation JPDA baseline. These public-radar results evaluate tracker-lifecycle and data-association behavior under public target-center observations; they are not presented as full validation of the board-specific RD-to-track pipeline. The evidence supports a bounded embedded-processing claim for this low-resolution board, not general applicability to high-resolution imaging radar systems. Full article

Topological indices provide numerical descriptions of graph structure and support graph analysis in cheminformatics, network design, and graph mining. This study presents a reproducible computational framework that combines controlled cyclic-graph generation, structure-preserving transformations, exact computation of six classical topological indices, and multi-output graph neural network regression. The framework evaluates the Wiener, Merrifield–Simmons, Hosoya, first Zagreb, second Zagreb, and Randi’c indices for unicyclic and bicyclic graphs. It represents each graph using sparse connectivity and node-level features that encode degree, cycle membership, pendant connectivity, leaf status, and normalized eccentricity. A graph isomorphism network (GIN) jointly predicts the six indices and is compared with graph convolutional networks (GCNs), graph attention networks (GATs), and descriptor-based regression baselines. The controlled benchmark shows that nonlinear descriptor-based models achieve the lowest aggregate errors because the supplied graph-level descriptors contain strong prior information about graph size, degree structure, branching, and cycle complexity. Although GIN does not achieve the highest overall accuracy, it provides the strongest graph-native performance by learning directly from sparse connectivity and node-level features without requiring a fixed handcrafted graph-level descriptor vector. The proposed surrogate does not replace exact evaluation for isolated small graphs, where exact computation remains more appropriate. Instead, its practical value emerges through repeated evaluations of larger, more complex graph instances. To examine this setting, a computational stress experiment evaluates sparse multicyclic graphs under increasing cyclomatic complexity and measures exact computation time, timeout frequency, prediction accuracy, and the amortized break-even point. The results indicate that surrogate prediction becomes beneficial when combinatorial index computation becomes sufficiently expensive, and the trained model is reused across many structurally related graph queries. An external experiment on circulant graphs also demonstrates that the framework can extend beyond the original graph generators by modifying only the graph-construction stage. Full article

This paper addresses the problem that autonomous bicycles struggle to achieve precise obstacle avoidance and robust dynamic balance at the same time in rugged terrain and narrow constrained spaces. A hybrid hierarchical control architecture that integrates Rapidly-exploring Random Trees (RRT*) with a dual-layer Proximal Policy Optimization (PPO) scheme is proposed, referred to hereafter as the RRT*-2LPPO architecture. In the global planning layer, RRT* combined with cubic B-spline smoothing generates $C^2$-continuous reference trajectories. In the local control layer, decision-making and execution are hierarchically coupled through a dual-layer cooperation scheme. The upper-layer PPO network incorporates LiDAR data and uses the vehicle body pitch angle to enhance rugged terrain perception for heading planning, while the lower-layer PPO network coordinates the momentum wheel and the steering mechanism to maintain vehicle stability. Validation across various challenging scenarios demonstrates that the proposed framework achieves excellent robustness and consistently attains the highest navigation success rates, significantly outperforming traditional control methods and non-hierarchical architectures. Full article

The bicycle industry, despite its sustainable image, remains underrepresented in research on non-financial reporting. This study benchmarks the sustainability reporting practices of 19 global bicycle manufacturers and component manufacturers that publish dedicated reports in English. It draws on content analysis of each company’s most recent, or most complete, sustainability report to examine patterns consistent with institutional isomorphism. The results show strong convergence around the Greenhouse Gas Protocol, adopted by 68% of firms, and the Global Reporting Initiative Standards, adopted by 53%. This pattern is consistent with normative isomorphism. Similarities in multi-framework reporting may also indicate mimetic behaviour, although direct evidence of imitation is limited. European firms are overrepresented in the sample, and some company reports refer directly to EU reporting requirements. These findings suggest possible coercive influence from the Corporate Sustainability Reporting Directive, although geographic concentration alone does not establish causation. Reporting practices vary across firms. Larger companies often use more comprehensive reporting systems, while some SMEs provide more limited disclosure. However, company size alone does not fully explain reporting maturity. Sustainability disclosure among the reporting firms is shaped by shared standards, institutional pressures, and differences in organisational capacity. Overall, the analysis provides insights into reporting practices among selected firms and highlights the need for practical support for smaller manufacturers. Full article

For a simple connected graph G, let $d_G\left(u\right)$ denote the degree of a vertex u. The second Zagreb index $Z_2\left(G\right)={\sum }_{uv\in E\left(G\right)}{d}_G\left(u\right)d_G\left(v\right)$ and its reciprocal index ^m$Z_2\left(G\right)={\sum }_{uv\in E\left(G\right)}1/\left(d_G\left(u\right)d_G\left(v\right)\right)$ are widely studied topological indices in graph theory. Their sum $Z_2\left(G\right)+{}^m{Z}_2\left(G\right)$ has been studied for trees, unicyclic graphs, and bicyclic graphs, but relevant results for tricyclic graphs remain unexplored. Using the path-lifting transformation, we prove that the maximum value of $Z_2\left(G\right)+{}^m{Z}_2\left(G\right)$ among all tricyclic graphs is ${\mathrm{Y}}_4={\displaystyle \frac{3n^3+9n^2+58n-76}{3(n-1)}}$, which is attained by the extremal graph $G_4\cong S_5(n-4,0,0,0)$. Our work completes the research framework of this index sum from acyclic to tricyclic graphs and provides theoretical support for chemical topological modeling. Full article

Objectives: To analyze the effect of whole-body cryotherapy on exercise tolerance in healthy, training men related to their profession based on the 6 min walk test (6MWT). Methods: The study group consisted of 30 individuals aged 24 to 59 years (mean age 39.2; median 38, SD 8.72). The subjects were soldiers from the Special Forces Unit (Military Unit GROM) and officers from the State Protection Service (SOP). All participants underwent a physical fitness assessment using the 6 min walk test: before the study, after two weeks of kinesiotherapy, and after 10 cryotherapy sessions combined with exercise on a stationary bicycle. Kinesiotherapy consisted of 20 min of cycling on a stationary bicycle (cycloergometer) under the supervision of trained personnel (with a load of 50–100 W) from Monday to Friday, from 11 a.m. to 12 noon. Whole-body cryostimulation treatments took place from Monday to Friday from 11 a.m. to 12 noon, entering the cryogenic chamber with a temperature of −130 °C for 2 min, then they went to the gym and rode a stationary bicycle (cycloergometer) for 20 min under the supervision of trained personnel (with a load of 50–100 W). Results: Both analyzed factors, i.e., 20 min of stationary cycle ergometer riding and whole-body cryostimulation treatments combined with kinesiotherapy, had a statistically significant effect on improving 6 min walk test results. The obtained results indicate that the impact of the exercise program was slightly greater than the impact of a series of 10 whole-body cryotherapy treatments followed by cycle ergometer riding. Conclusions: Both physical activity and cryostimulation had an impact on the physical performance of the subjects, but the obtained results indicate that the impact of exercise alone was slightly greater. Full article

Electric scooters (e-scooters) and electric bicycles (e-bikes) are established urban micromobility modes, and children and adolescents form a growing share of riders. This narrative review synthesises peer-reviewed evidence on e-scooter and e-bike injuries in patients aged 18 years or younger, covering epidemiology, mechanisms, injury patterns, clinical outcomes, comparisons with conventional devices, and prevention. Each source was classified as dedicated paediatric evidence, mixed-age evidence with extractable paediatric results, adult or mixed-age evidence used only for context, or an adult-dominated systematic review, so that the basis of every claim is explicit. The reported burden has risen across national surveillance data and single-centre series, and one population-adjusted analysis found injury rates increasing by 293% for e-bikes and by 88% for powered scooters between 2019 and 2022. Most studies lack exposure denominators, so exposure-adjusted paediatric risk remains poorly quantified and rising counts cannot be equated with rising risk. Injuries affect adolescent boys disproportionately and peak at ages 11 to 14 years. Extremity and soft-tissue injuries predominate, while a clinically important minority sustain traumatic brain injury, craniofacial and dental trauma, or severe multisystem injury. Low helmet use and higher device speeds are consistently associated with more severe outcomes, although observational designs cannot establish causal effects and device type is confounded with rider age and road exposure in every available paediatric comparison. Powered devices are associated with greater severity than non-powered counterparts. Speed limitation and helmet promotion appear promising, but paediatric-specific effectiveness evidence remains limited. Prospective paediatric research incorporating exposure denominators is the priority. Full article

The increasing demand for urban last-mile delivery services has intensified the need for routing approaches that simultaneously address operational efficiency and environmental sustainability. This study introduces the Green Multi-Courier Delivery Routing Problem (GMCDRP), a heterogeneous routing and assignment problem involving pedestrian couriers, electric bicycles, and motorized vehicles under capacity, distance, and service-time constraints. To solve the problem, a state-aware constructive heuristic named Emission-Minimizing Green Routing (EMGRO) is proposed. Unlike conventional metaheuristics that evaluate emissions after route generation, EMGRO integrates emission awareness directly into the assignment process by considering the real-time operational state of each courier and prioritizing the lowest-emission feasible alternative. The proposed method is evaluated using 20 large-scale scenarios derived from the real road network of Adana, Türkiye, each containing up to 1000 delivery requests. Its performance is compared with Genetic Algorithm (GA), Ant Colony Optimization (ACO), and Particle Swarm Optimization (PSO) approaches. Experimental results demonstrate that EMGRO achieves the lowest average emission per delivered package (0.512 g CO₂/package), outperforming ACO, PSO, and GA by 47.9%, 44.1%, and 41.9%, respectively, while maintaining identical delivery coverage. Furthermore, EMGRO generates solutions within seconds, providing substantial computational advantages over population-based metaheuristics. The findings indicate that embedding environmental considerations directly into the decision-making process can significantly improve both sustainability and computational efficiency in heterogeneous urban delivery systems. Full article

The development of suspension systems for urban micro-mobility vehicles, such as bicycles and e-bikes, requires balancing effective road filtering with structural simplicity. Traditional solutions, such as telescopic forks and rear shock absorbers, face significant challenges related to weight, bulk, and mechanical complexity, which increase production and maintenance costs. The integration of in-wheel motors into wheel hubs further complicates the design by increasing unsprung mass and vertical vibrations, negatively affecting ride comfort. The In-Wheel Suspension (IWS) system offers an innovative solution by incorporating elastic and damping elements directly into the wheel rim, eliminating the need for frame modifications and reducing overall weight. This study proposes an integrated approach to optimising the internal geometries of IWS elastic elements, using structural analyses with LS-Dyna and dynamic simulations in the Simulink environment for comfort assessment. Results demonstrate that optimising the geometry of spokes and rims significantly reduces stiffness variations and self-induced vibrations, with enhancements in ride comfort and resistance to fatigue. The optimized IWS design minimises discomfort peaks at critical speeds and improves vibration attenuation. However, the high average stiffness limits filtering performance at speeds above 10 km/h. While IWS systems represent a promising alternative to traditional suspensions due to their advantages in weight reduction, compactness, and construction simplicity, further improvements—such as the use of composite materials and alternative geometries—are necessary to further increase comfort and to ensure structural resistance to variable loads. Full article