Search Results (218)

Lateral passing distance (LPD) when motor vehicles overtake cyclists is a key safety metric, yet infrastructure-aware evidence remains limited. This study analyses 11,399 overtaking measurements from Austria’s OpenBikeSensor (OBS) project, spatially linked to the national road graph (GIP), with urban and rural networks examined separately. LPD was treated as a continuous dependent variable, and bivariate relationships were tested using nonparametric methods: Spearman’s rho/Kendall’s tau for metric predictors (speed limit, lane width, number of lanes) and Kruskal–Wallis tests with Dunn–Holm post hoc adjustments for categorical factors (Functional Road Class, Road Configuration, Infrastructure Type). Effect sizes and confidence intervals supported substantive interpretation. LPD was higher in rural than urban contexts, with compliance to Austria’s 2023 legal thresholds averaging 40% in cities (≥1.5 m) and 19% in rural areas (≥2.0 m). Positive correlations were found between LPD and lane width, speed limit, and functional class. The findings highlight infrastructure-sensitive patterns in sensor-generated LPD and emphasise the importance of clear cyclist allocation or physical separation, especially where high speeds or spatial constraints increase close-passing risk. Full article

Background/Objectives: In recent years, electric scooters have gained widespread popularity as an easy and affordable mode of transport in urban areas worldwide. Simultaneously, trauma centers have observed an increasing number of associated injuries to users. While injury patterns associated with other vehicles are now well-researched, electric-scooter-related injuries are a new topic in the literature. Our study aims to investigate the differences in injury patterns and other critical crash characteristics among riders of bicycles, electric scooters, and scooters. Methods: This one-year retrospective observational study examined patients who sustained injuries while riding bicycles, electric scooters, or scooters between April 2021 and March 2022 at Hungary’s largest trauma center in Budapest. During this one-year period, we identified 1938 patients, 1378 cyclists, 370 electric scooter users, and 190 scooter users. Basic demographic information, recorded injury type and severity, time of day the injury occurred, and alcohol usage were recorded as outcome measures. Results: While 4.6% of cyclists and 5.8% of scooter riders had consumed alcohol, 26.8% of electric scooter riders were under the influence of alcohol at the time of their crash. Of electric-scooter-related injuries, 45.8% occurred at night, compared to only 9.2% and 14.1% of bike and scooter-related injuries, respectively. E-scooter crashes constituted 19.1% of total cases but surged to 52.3% at night. Patients under the influence of alcohol were much more likely to experience mild head injuries (p < 0.0001) and severe head injuries (p < 0.0001), but less likely to suffer mild limb injuries (p < 0.0001) and severe limb injuries (p < 0.0001) compared with sober patients. Cyclists had significantly 3 times fewer cases of severe head trauma than those injured while using electric scooters (p = 0.0166). Conclusions: The study highlights a significant risk of severe craniofacial injuries in e-scooter users after consuming alcohol, exceeding that in sober riders and cyclists. Predominantly occurring at night, these injuries are closely linked with alcohol use. The findings advocate for mandatory helmet laws and stricter regulations on e-scooter use to enhance safety, especially at night. Full article

Isosorbide-based aliphatic polyesters are a promising class of biodegradable polymers for biomedical applications, representing an attractive alternative to poly(α-hydroxy acids). Derived from the bio-based bicyclic diol, they combine structural rigidity, tunable hydrophilicity, and enhanced biocompatibility, making them suitable for drug delivery and sustainable medical devices. In this study, we developed novel in situ forming implant (ISFI) formulations composed of poly(isosorbide sebacate) (PISEB) and dimethyl isosorbide (DMI), and evaluated their applicability for local delivery of doxycycline hyclate (DOXY), minocycline hydrochloride (MIN), and/or eugenol (EUG). Basic characteristics of new ISFI formulations were investigated. Rheological analysis demonstrated that the liquid formulations exhibited shear-thinning behavior, which is advantageous for ISFI systems. However, the MIN-loaded formulation exhibited excessively rapid drug release, with a pronounced initial burst (86.4 ± 5.9%) within 24 h, whereas the DOXY-loaded system showed a lower burst of 41.1 ± 5.9% over the same period. The effect of EUG addition on depot morphology and antibiotic release profiles was also assessed. In vitro drug release studies demonstrated that EUG reduced the release rate of both antibiotics, increasing and prolonging their antibacterial activity. Eugenol co-released with antibiotics also reduced the pro-inflammatory effect of the released antibiotic doses by more than tenfold. Full article

Bridges serve as vital connectors in the transportation network and infrastructure. Given their significance, it is crucial to continuously monitor bridge conditions to ensure the efficient operation of transportation systems. With advancements in sensing technologies, transportation infrastructure assessment has evolved through the integration of structural health monitoring (SHM) methodologies. Traditionally, bridge monitoring has relied on direct sensor instrumentation; however, this method encounters practical obstacles, including traffic disruptions and limited sensor availability. In contrast, indirect bridge health monitoring (iBHM) utilizes data from moving traffic on the bridge itself. This innovative approach eliminates the need for embedded instrumentation, as sensors on vehicles traverse the bridge, capturing the dynamic characteristics of the bridge. In this paper, system identification methods are explored to analyze the acceleration data gathered using a bicycle-mounted sensor traversing the bridge. To explore the feasibility of this micromobility-based approach, bridge responses are measured under varying traversing conditions combined with dynamic rider–bicycle–bridge interaction for comprehensive evaluation. The proposed method involves a hybrid approach combining Wavelet Packet Transform (WPT) with Synchro-extracting Transform (SET), which are employed to analyze the time–frequency characteristics of the acceleration signals of bike-based iBHM. The results indicate that the combination of WPT-SET demonstrates superior robustness and accuracy in isolating dominant nonstationary frequencies. The performance of the proposed method is compared with another prominent signal processing algorithm known as Time-Varying Filtering Empirical Mode Decomposition (TVF-EMD). Ultimately, this study underscores the potential of bicycles as low-cost, mobile sensing platforms for iBHM that are otherwise inaccessible to motorized vehicles. Full article

Promoting cycling as a sustainable mode of transport is a pressing priority in contemporary urban mobility planning. This study examines the infrastructure characteristics that most strongly influence bicycle use in dense metropolitan contexts. A mixed-methods approach was adopted, combining a systematic review of current design guidelines with a large-scale empirical analysis of Barcelona’s Bicing bike-sharing system. The dataset comprised more than 54 million recorded trips, enabling the identification of the most and least frequented routes and the subsequent assessment of their infrastructural attributes. The results indicate that network configuration, continuity, and adaptation to topographic conditions have the greatest influence on cycling uptake. By contrast, factors frequently emphasized in design recommendations, such as lane width, were not decisive, as several of the city’s most intensively used corridors did not conform to these standards. These findings suggest that the expansion of network coverage and the improvement of route connectivity are more effective strategies for increasing cycling adoption than isolated design optimizations. This study contributes evidence-based guidance for urban planners and policy-makers seeking to advance cycling as a principal component of sustainable urban mobility in Barcelona and other comparable urban environments. Full article

Objectives: The aim of this study was to determine the epidemiological characteristics of bicycling-related maxillofacial fractures in a defined population and to identify factors contributing to these injuries. Methods: An 8-year cohort study was carried out, including all patients presenting with bicycling-related maxillofacial fractures at a tertiary care center from 2017 through 2024. Data recorded for each patient included age, gender, date and cause of injury, contributing factors, type of facial fractures, other injuries, hospital stay, and helmet use. Statistical analysis was performed. Continuous variables were assessed for normality (Shapiro–Wilk test) and compared using the Mann–Whitney test. Categorical variables were analyzed with chi-square tests. A p-value ≤ 0.05 was considered statistically significant. Results: Out of 899 cycling accident patients seeking medical treatment, 122 (13%) sustained facial fractures, accounting for 4% of all facial fracture cases in our department during the study period. In our cohort, the male–female ratio was 2.6:1, and the mean age was 29.5 years (SD 12.8, range 13–77). Collision with another object/vehicle was the most common cause (64%), followed by isolated falls (36%). A total of 135 facial fractures were recorded (some patients had multiple fractures). Mandibular fractures were most frequent (49% of patients), followed by zygomatic (32%), orbital (13%), nasal (7%), maxillary (2%) and frontal (2%) fractures. Among mandibular injuries, condylar fractures were the most common subtype (63%). Dental injuries were found in 27% of patients. The most common dental trauma was tooth fracture (43% of those with dental injuries), followed by tooth luxation (32%) and tooth avulsion (25%). In 80% of cases involving dental injuries, the upper anterior teeth were involved. Concomitant injuries were present in 20% of patients, most often orthopedic limb injuries. Only 27% of patients reported always wearing a helmet, whereas 43% reported never having worn one. Conclusions: Bicycling-related facial injuries are a noteworthy subset of facial trauma. Missed or delayed diagnosis can lead to lasting deformities and functional issues. Preventive strategies—especially promoting helmet use and improving helmet design—along with broader safety measures are important to reduce the incidence and severity of these injuries. Full article

This study presents the development and implementation of an electronically actuated steering system in a Formula Student Driverless race car, aiming to support autonomous driving capability. A DC motor with a belt-drive mechanism was integrated into the original steering rack assembly without altering its core mechanical characteristics. The research also includes a validation of the steering geometry using both physical measurements and CAD simulations. The objective of this measurement is to determine the steering angle as a function of the steering wheel input angle, ensuring that the resulting data accurately informs vehicle dynamics models such as the kinematic bicycle model. These steps form the basis for closed-loop control integration in the autonomous driving platform. Full article

In recent years, the evolution of competitive road cycling has included the use of larger tires inflated at lower pressure compared to the thin, high-pressure tires used previously. This trend is also emerging in non-competitive cycling, where comfort is more important. An issue often reported by cyclist concerns discomfort in the hands and upper limbs due to handlebar vibrations. To evaluate the effect of certain tire characteristics on vibrations in the handlebar and the bicycle seat-post, a small, portable, wireless connected, measurement system has been developed and tested on the road. Experimental conditions included tire-related factors, such as pressure, width, and the presence of an internal air chamber, as well as two speed conditions, while keeping all the other factors constant and under strict control. Results confirm that lower pressure reduces vibration levels, and tire width is also an important factor. Full article

Objectives: The increasing popularity of electric scooters (E-scooters) has led to a rise in trauma-related injuries, particularly in the craniofacial region. This study aims to compare dentoalveolar trauma (DT) patterns between E-scooter and bicycle accidents in a German urban area to identify differences in injury characteristics, risk factors, and treatment approaches. Materials and Methods: This retrospective study analyzed 178 patients treated for DT following E-scooter (n = 56) or bicycle (n = 122) accidents between January 2022 and December 2022 at a single oral and maxillofacial surgery department in a German urban area. Demographic, clinical, temporal, and therapeutic data were collected and statistically compared. Results: E-scooter patients were significantly younger (mean age: 33.6 vs. 47.0 years, p < 0.001) and predominantly female (85.7% vs. 26.2%, p < 0.001) compared to bicycle patients. E-scooter accidents more frequently occurred at night (69.6%) and on weekends (62.5%) and were significantly associated with alcohol consumption (55.4%) and low helmet use (8.9%). Clinically, E-scooter accidents resulted in more complex dental injuries, including a higher incidence of root fractures (14.3% vs. 0%, p < 0.001), complicated crown fractures (25.0% vs. 9.0%, p = 0.004), and crown-root fractures (32.1% vs. 9.8%, p < 0.001). Mandibular injuries were more prevalent in the E-scooter group, and concomitant facial fractures (excluding alveolar) were also more common (28.6% vs. 19.7%, p = 0.018). Conclusion: E-scooter accidents are associated with a distinct DT pattern involving younger, often alcohol-intoxicated, and helmetless patients, typically presenting with more severe and complex DT-injuries. These findings highlight the urgent need for targeted prevention strategies, legislative measures on helmet use, and clinician awareness of specific trauma profiles linked to E-scooter use. Full article

Background: Bicycles constitute a primary means of transportation, particularly within the scope of urban micromobility. However, the use of this mode of transport is associated with the risk of traffic accidents and subsequent maxillofacial trauma. Cyclists are classified as vulnerable road users, among whom the assessment of injury patterns is a significant issue. This study aimed to identify the most common maxillofacial fractures resulting from bicycle-related traffic accidents. Methods: A retrospective analysis was conducted on the medical records of patients treated at the Clinic of Maxillofacial Surgery at the University Clinical Hospital in Poznan, who sustained maxillofacial injuries as a result of bicycle-related accidents between 2019 and 2023. Results: A total of 99 patients met the inclusion criteria. Most of the study population was males (70.7%), with a median age of 38. Accidents most frequently occurred during the summer months and on Fridays and weekends. The most common fracture site was the mandible (40.4%), with double fractures being the predominant type. Additionally, zygomatic-orbital fractures were frequently observed (30.3%). In terms of treatment, surgical intervention was predominant, and the mean duration of hospitalisation was 6 days. Only 5.1% of patients were under the influence of alcohol at the time of the incident. Furthermore, it was found that isolated mandibular fractures occurred more frequently in younger patients, whereas midface fractures of the Le Fort II and III types were more commonly observed in individuals under the influence of alcohol at the time of the event. Moreover, accidents involving alcohol consumption were associated with a higher incidence of concomitant cranio-cerebral injuries. Conclusions: Defining the profile of maxillofacial fractures resulting from bicycle accidents constitutes a clinically relevant issue. Additionally, identifying the main risk factors and developing preventive measures is of critical importance. Full article

This study focuses on exploring the differences in driving abilities in emergency traffic situations between older drivers (aged 60–70) and young drivers (aged 20–35) in a simple traffic environment. Two typical emergency scenarios were designed in the experiment: Scenario A (intrusion of electric bicycles) and Scenario B (pedestrians crossing the road). The experiment employed a driving simulation system to synchronously collect data on eye movement characteristics, driving behavior, and physiological metrics from 30 drivers. Two-factor covariance analysis, correlation analysis, and regression analysis were conducted on the experimental data. The comprehensive study results indicated that the older group exhibited better driving performance in emergency scenarios compared to the younger group. Specifically, in Scenario A, the older group had a faster first fixation time on the AOI compared to the younger group, a faster braking reaction time, a higher maximum brake pedal depth, and a higher skin conductance level. In Scenario B, the older group’s driving performance was similar to that in Scenario A, with better performance than the younger group. The study reveals that in some simple driving tasks, young-old drivers (60–70 years) can compensate for their physiological decline through self-regulation and self-restraint, thereby exhibiting safer driving behaviors. Full article

This research explores how artificial intelligence (AI) can be leveraged to optimize packaging design, reduce operational costs, and enhance sustainability in e-commerce. As packaging waste and shipping inefficiencies grow alongside global online retail demand, traditional methods for determining box size, material use, and logistics planning have become economically and environmentally inadequate. Using a three-phase framework, this study integrates data-driven diagnostics, AI modeling, and real-world validation. In the first phase, a systematic analysis of current packaging inefficiencies was conducted through secondary data, benchmarking, and cost modeling. Findings revealed significant waste caused by over-packaging, suboptimal box-sizing, and poor alignment between product characteristics and logistics strategy. In the second phase, a random forest (RF) machine learning model was developed to predict optimal packaging configurations using key product features: weight, volume, and fragility. This model was supported by AI simulation tools that enabled virtual testing of material performance, space efficiency, and damage risk. Results demonstrated measurable improvements in packaging optimization, cost reduction, and emission mitigation. The third phase validated the AI framework using practical case studies—ranging from a college textbook to a fragile kitchen dish set and a high-volume children’s bicycle. The model successfully recommended right-sized packaging for each product, resulting in reduced material usage, improved shipping density, and enhanced protection. Simulated cost-saving scenarios further confirmed that smart packaging and AI-generated configurations can drive efficiency. The research concludes that AI-based packaging systems offer substantial strategic value, including cost savings, environmental benefits, and alignment with regulatory and consumer expectations—providing scalable, data-driven solutions for e-commerce enterprises such as Amazon and others. Full article

Several empirical studies have attempted to clarify whether differences in regulations affect people’s behavior. However, due to a lack of data, few have attempted to clarify whether these differences affect the purchase of insurance. Therefore, in this study, I conducted a survey of consumers in Japan and analyzed the characteristics of those who bought bicycle insurance. My findings are as follows: First, users tend to purchase bicycle insurance in prefectures where it is compulsory. Second, bicycle users with a high level of insurance knowledge tend to purchase insurance. Third, consumers who use bicycles more frequently tend to purchase insurance. Full article

Nowadays, antimicrobial resistance (AMR) is a growing global health threat, with carbapenem-resistant Enterobacteriaceae (CRE) posing particular concern due to limited treatment options. In fact, CRE have been classified as a critical priority by the World Health Organization (WHO). Carbapenem resistance results from complex mechanisms, often combining the production of hydrolytic enzymes such as β-lactamases with reduced membrane permeability and efflux system induction. The Ambler classification is an effective tool for differentiating the characteristics of serine-β-lactamases (SβLs) and metallo-β-lactamases (MβLs), including ESβLs (different from carbapenemases), KPC, NDM, VIM, IMP, AmpC (different from carbapenemases), and OXA-48. Recently approved inhibitor drugs, such as diazabicyclooctanones and boronic acid derivatives, only partially address this problem, not least because of their ineffectiveness against MβLs. However, compared with taniborbactam, xeruborbactam is the first bicyclic boronate in clinical development with a pan-β-lactamase inhibition spectrum, including the IMP subfamily. Recent studies explore strategies such as chemical optimization of β-lactamase inhibitor scaffolds, novel β-lactam/β-lactamase inhibitor combinations, and siderophore–antibiotic conjugates to enhance bacterial uptake. A deeper understanding of the mechanistic properties of the active sites enables rational drug design principles to be established for inhibitors targeting both SβLs and MβLs. This review aims to provide a comprehensive overview of current therapeutic strategies and future perspectives for the development of carbapenemase inhibitor drug candidates. Full article

Background: This sport involves the integration of various capabilities and mechanisms, including cognitive, physiological, and biomechanical components, that allow the athlete to perform in competition. However, to date, no systematic review has analyzed the indicators that are decisive for sports performance in Bicycle Motocross (BMX). The objective of this work was to carry out a systematic review of the performance variables in BMX and establish recommendations for researchers and trainers. Materials and Methods: The following databases were consulted: PubMed, Scopus, and Web of Science. This systematic review uses the guidelines of the PRISMA statement and the guidelines for performing systematic reviews in sports sciences. The search approach, along with the selection criteria and additional details, were previously noted in the prospective registry (INPLASY202480036). The quality of the evidence was evaluated via the PEDro scale. Results: The 21 studies that make up the sample of this systematic review have a total sample of 287 athletes. However, in the studies analyzed, there are five main categories for the study of performance in BMX: (i) physiological profile and BMX and bicarbonate; (ii) BMX and physical characteristics (power, speed, and sprint); (iii) translation and rotational acceleration and systems and implements; (iv) psychological variables; and (v) skills and techniques. Conclusions: This systematic review provides convincing evidence regarding the influence of several factors that can determine performance in BMX, including P_max, cadence, neuromuscular capacity, feedback and cognitive training, accelerometry and video analysis, anaerobic–aerobic relationships, physical conditioning, strength, and speed. Full article