Search Results (2,386)

We study the Moore–Penrose inverse of idempotent operators on Hilbert $C^{*}$-modules. First, we extend the computation of the Moore–Penrose inverse of an idempotent operator and its difference from the range projection to this setting. This leads to an explicit formula for the Moore–Penrose inverse of the sum of an idempotent and its adjoint. Furthermore, we establish a decomposition of an idempotent operator into a product of two commuting idempotents and clarify the relationship between their Moore–Penrose inverses and that of the original operator. We also analyze spectral properties and operator norms, obtaining sharp norm bounds. Full article

In automated driving, drivers may sleep during rides, making it important to study napping preferences and wake-up scenarios for human-centered system design. We conducted an online study with 280 participants, balanced by age and gender, examining how often, when, and how long individuals would nap if given the opportunity. The study also explored preferred wake-up methods when the vehicle nears the end of its operational design domain. Using a mixed 2 × 2 design, participants were assigned to one of two travel purposes (“commuting” vs. “holiday trip”) and two minimal risk conditions (rest area vs. hard shoulder). The results showed that 40% intended to sleep during automated driving, highlighting a strong interest in in-car sleeping. Wake-up preferences varied by travel purpose and minimal risk condition, with many favoring awakening before the drive ended. Participants also anticipated sleep inertia and desired post-wake-up support. The findings allow suggestions for designing wake-up concepts that mitigate sleep inertia. Full article

Colour algebras are noncommutative Jordan algebras and closely related to octonion algebras. They initially emerged in physics since the multiplication of a colour algebra over the real or complex numbers describes the colour symmetry of the Gell–Mann quark model. Over fields of characteristic not equal to two, their structure is now well-known. We initiate the study of colour algebras over a unital commutative base ring R where two is an invertible element, and show when colour algebras can be constructed canonically by employing nondegenerate ternary hermitian forms with trivial determinant. We investigate their structure, their automorphism group and their derivations. We show that there is again a close connection between the colour algebras obtained from hermitian forms and certain types of octonion algebras. Full article

Transport affordability defined as the share of household income devoted to transport expenditure is a key dimension of urban equity and social inclusion, particularly in contexts characterised by spatial inequality and income disparities. This study examines provincial variation in public transport affordability across South Africa using a hierarchical Bayesian regression framework applied to province–year data from 2015 to 2022 (n = 72). Affordability is operationalised as a transport cost burden, with higher values indicating a greater proportion of household income spent on transport, and is modelled as a function of household income, trip frequency, household population, and total provincial employment, with province-level random intercepts capturing unobserved regional heterogeneity. The results indicate that household income is negatively associated with transport cost burden, suggesting that provinces with higher average income devote a smaller share of income to transport and therefore experience better affordability. In contrast, household population and aggregate provincial employment are positively associated with transport cost burden, reflecting higher overall mobility and commuting demands in larger and more economically active provinces rather than improved affordability. Trip frequency shows no statistically meaningful association with affordability once household composition and income capacity are accounted for. After accounting for observed characteristics, between-province variation is limited, indicating that affordability dynamics are broadly similar across provinces over the study period. Methodologically, the hierarchical Bayesian framework enables partial pooling across provinces and supports probabilistic inference through credible intervals, thereby improving the stability of estimates in a small-sample multilevel context. While the analysis is associational rather than causal, the findings provide policy-relevant evidence for monitoring transport affordability, including benchmarking the prevalence of affordability burdens relative to the commonly used 10% threshold. Full article

The high rate of bike commuting around the globe has greatly transformed the mode of transportation in cities, but the high speeds of motorized cycling have contributed to a high rate of serious road trauma. Although conventional helmets offer necessary passive structural protection, they do not consider the most important aspect of the emergency response, which is the Golden Hour the time frame during which medical intervention can have the most significant impact. This paper is a development and validation of an autonomous, low-cost smart helmet architecture that is programmed to operate in real-time to detect accidents and autonomously inform the operator of accidents. The system is built up of an ESP32 microcontroller with a multi-modal sensor package, which comprises an inertial measurement unit (IMU), force-impact sensors, and MQ-3 alcohol sensors to conduct proactive safety screening. To overcome the single threshold limitation of unreliable systems, a time-windowed sensor-fusion algorithm was applied in order to distinguish between normal riding dynamics and bona fide collisions. This reasoning involves concurrent cues of high-G inertial rotations and physical impacting features over a time window of 500 ms to reduce spurious activations. The architecture of the system is completely self-sufficient and employs an in-built GPS-GSM module to send the geographical location through SMS without the need to have a smartphone connection. The prototype was also put through 150 experimental tests, with some conducted in laboratories, and real-world running tests in diverse terrains. The findings reveal an accuracy in detection of 93.7, a false positive rate (FPR) of 2.6 and a mean emergency alert latency of 2.8 s. In addition, it was found that structural integrity was confirmed at ECE 22.05 impact conditions using Finite Element Analysis (FEA), with a safety factor of 1.38. These quantitative results mean that the proposed system is an effective way to address a cultural shift between passive structural protection and active rescue intervention as a statistical and computationally efficient safety measure of modern micro-mobility. Full article

Let ${\mathcal{M}}_{\alpha }$ be the bilinear fractional maximal operator. In this paper, we prove that the commutators ${\mathcal{M}}_{\alpha ,b}^i$ in the i-th entry $(i=1,2)$ and the bilinear iterated commutators ${\mathcal{M}}_{\alpha ,\overrightarrow{b}}$ of ${\mathcal{M}}_{\alpha }$ are bounded operators from product weighted Morrey spaces $L^{p_1,\frac{\kappa p_1}{q_1}}\left(w_1^{p_1},w_1^{q_1}\right)\times L^{p_2,\frac{\kappa p_2}{q_2}}\left(w_2^{p_2},w_2^{q_2}\right)$ to weighted Morrey spaces $L^{q,\kappa }\left(v_{\overrightarrow{w}}^q\right)$, provided that $b\in \mathrm{BMO}\left({\mathbb{R}}^{\mathrm{n}}\right)$ and $\overrightarrow{b}=(b_1,b_2)\in \mathrm{BMO}\left({\mathbb{R}}^{\mathrm{n}}\right)\times \mathrm{BMO}\left({\mathbb{R}}^{\mathrm{n}}\right)$. Furthermore, by using the techniques of function decompositions and the Fréchet–Kolmogorov theorem on weighted Morrey spaces, the compactness of ${\mathcal{M}}_{\alpha ,b}^i(i=1,2)$ and ${\mathcal{M}}_{\alpha ,\overrightarrow{b}}$ are also established whenever $b\in \mathrm{CMO}\left({\mathbb{R}}^{\mathrm{n}}\right)$ and $\overrightarrow{b}=(b_1,b_2)\in \mathrm{CMO}\left({\mathbb{R}}^{\mathrm{n}}\right)\times \mathrm{CMO}\left({\mathbb{R}}^{\mathrm{n}}\right)$, where $\mathrm{CMO}\left({\mathbb{R}}^{\mathrm{n}}\right)$ denotes the closure of $C_c^{\infty }\left({\mathbb{R}}^n\right)$ in the $\mathrm{BMO}\left({\mathbb{R}}^{\mathrm{n}}\right)$ topology. Full article

Background: Dialysis adequacy (Kt/V) remains an essential marker of hemodialysis quality; however, it does not fully capture patients’ overall well-being. Growing evidence underscores the need for a more holistic, patient-centered approach that integrates clinical efficiency with factors affecting daily functioning and quality of life (QoL). Objectives: This study aimed to identify the key determinants of health-related quality of life (HRQoL) among Polish patients undergoing hemodialysis. Methods: Seventy hemodialysis patients from a single center completed the KDQOL-36 questionnaire and provided demographic and clinical data. Statistical analyses included Pearson’s and Spearman’s correlations, as well as multiple linear regression, to determine predictors of HRQoL. Results: The mean (SD) KDQOL summary score was 60.9 (17.3). Pain (B = −15.9, p < 0.001) and the need for additional dialysis sessions (B = −10.2, p = 0.008) were the strongest independent predictors of poorer HRQoL, collectively accounting for 28.6% of variance. Longer dialysis-related transportation time (r = −0.238, p = 0.03) and longer hemodialysis vintage (r = −0.254, p = 0.03) were also significantly associated with lower HRQoL, while dialysis adequacy showed no significant effect. Conclusions: Pain, additional dialysis sessions, and longer dialysis-related transportation time are key, modifiable contributors to reduced HRQoL in Polish hemodialysis patients. These findings underscore the importance of a patient-centered approach that supplements clinical measures with interventions targeting comfort, education, and accessibility. Incorporating structured pain management and improved transport into routine nephrology practice can meaningfully improve patient QoL. Full article

To enhance the resilience of urban road networks under frequent recurrent disturbances such as morning peak commuting congestion, this study develops a dynamic resilience assessment framework from the perspective of land-use mix. The model evaluates network resilience by quantifying performance evolution and recovery capacity during the morning peak from both road segment and node dimensions, using land-use mix entropy to characterize functional complexity. The compounded effects of tidal commuting directions and land-use mix are further investigated. Results indicate clear heterogeneity in degradation and recovery trajectories across different land-use mix levels: segments and nodes in high land-use mix areas exhibit more pronounced performance deterioration and delayed recovery. When high land-use mix areas spatially overlap with predominant commuting directions, performance degradation is further amplified and recovery at the end of the morning peak remains lower, revealing critical resilience weaknesses. Accordingly, a land-use mix-oriented targeted optimization strategy is proposed, which enhances system-level resilience by prioritizing capacity improvements on high land-use mix segments. Simulation results show that the proposed strategy increases the network resilience value by 9.46% compared with the baseline scenario, achieving an improvement 2.3 times that of a random capacity expansion strategy. This study provides quantitative evidence for the linkage between land-use mix and dynamic road-network resilience and offers a spatially informed framework for resilience enhancement under recurrent disturbances. Full article

In the Seoul Metropolitan Area of Korea, ongoing urban expansion continuously increases commuting demand toward Seoul, resulting in severe congestion in the urban core due to the large inflow of interregional buses. In response, the government proposed the introduction of a transfer-type interregional bus system as an alternative to alleviate downtown congestion. Transfer-type buses terminate at the Seoul boundary and rely on passenger transfers to other modes for access to the urban core. By shortening route lengths, this system enables reduced headways and increased service frequency. This approach can mitigate urban congestion. However, required transfers may generate user resistance, highlighting the need to analyze users’ willingness to shift. This study applies a latent class mixed logit model to stated preference survey data collected from 502 interregional bus users in order to capture heterogeneous preferences. As a result, users are grouped into three classes: transfer-avoidant, cost-sensitive, and time-sensitive. In all segments, more than half of respondents express a willingness to shift, with the highest level observed in the cost-sensitive group (64.3%). The class-specific choice models reveal that heterogeneity exists not only across segments but also within each segment. These findings indicate that a transfer-type interregional bus policy cannot operate uniformly across all users. Instead, a targeted strategy that simultaneously improves travel time and travel cost for subgroups with conversion potential is required. By systematically identifying users’ willingness to shift and heterogeneous response structures prior to implementation, this study provides empirical evidence to support the design of effective policies and operational strategies for transfer-type interregional buses. Full article

Norway reached a Battery Electric Vehicle market share of 96% in 2025. The fleet share reached 33%. Other countries are 5–10 years behind Norway. The extraordinary Norwegian development is the result of a 35-year-long complex process involving BEV testing from 1990 and Norwegian BEV industrialization from 1998, supported by a large package of incentives. The incentive package remained in place after the Norwegian actors went bankrupt in 2010 and the global OEMs took over the BEV supply. Norway has a had head start over other countries with high visibility, awareness, and a BEV fleet that accounted for 35% of all BEVs in Europe to build a market from. The incentives made the new OEM BEVs immediately competitive, contrasting with other countries’ insufficient incentives and slow development. A second market expansion followed from 2017 with access to lower-cost and long-range BEVs in more market segments. The EU’s new vehicle CO₂-regulation forced OEMs to sell BEVs on a large scale. BEV technology improved rapidly with longer range and faster charging at a reduced cost, making the incentive even more efficient. The model availability increased rapidly from 2020, while ICEV model availability declined rapidly from 2022, enabling Norway to reach the national target of only selling BEVs from 2025. Norway solved the demand-side challenges of BEV adoption through large market pull incentives. The early supply-side challenges were attempted to be solved with Norwegian BEV production targeting a small-city BEV niche. When that failed, a window of opportunity opened to solve the supply-side challenges with the availability of OEM BEVs. The market scope broadened to commuters and multi-vehicle households and eventually to all new vehicle buyers. By 2020, all demand-side and supply-side challenges were solved, and the transition was accelerated by societal processes. Full article

Community detection in graphs can be viewed as the estimation of a partition map that remains stable under admissible perturbations of graph topology and node attributes. While modern graph neural networks (GNNs) achieve strong empirical accuracy, they often exhibit severe assignment drift under minor perturbations, leading to illusory community structures. In this work, we propose DISPEL-GNN, a stability-aware graph learning framework that integrates spectral operator regularization, Bayesian uncertainty modeling, and risk-aware dynamic attention for perturbation-bounded community detection. The model explicitly constrains graph operators through uniform spectral norm bounds, high-frequency energy suppression, and commutator alignment while dynamically modulating message passing based on node-level spectral risk and epistemic uncertainty. We further formalize instability via assignment of drift functional and establish perturbation bounds linking drift to operator norms and spectral gaps, complemented by a PAC-Bayesian generalization guarantee. Extensive experiments on real-world benchmarks including Cora, Citeseer, Pubmed, Cora-Full, and DBLP demonstrate that DISPEL-GNN consistently reduces assignment drift by 18–35% under feature noise and edge perturbations while improving clustering quality with up to +3.0 NMI and +0.04 ARI compared to strong baselines such as GAT and Bayesian GNNs. The normalized mutual information (NMI), adjusted Rand index (ARI), and PAC-Bayesian (PAC) constraints serve as evaluative and theoretical instruments in this study. Additional studies on synthetic graphs with controlled spectral gaps confirm that the proposed method maintains stable community assignments in low-gap regimes where classical spectral and GNN-based methods degrade sharply. These results establish DISPEL-GNN as a mathematically grounded and practically effective framework for robust and interpretable community detection. A metric-wise dominance analysis shows that DISPEL-GNN achieves metric-wise dominance across most accuracy and robustness criteria, with minor tradeoffs in modularity on selected datasets. These results indicate that explicitly modeling stability and uncertainty provides a principled pathway toward reliable and interpretable community detection in noisy graph environments. Full article

Quasi-resonant (QR) DC–DC converters with PWM control achieve soft switching by shaping the commutation transient through a local resonant process. This paper proposes a symmetry-based unified perspective on classical QR converters by interpreting zero-voltage switching (ZVS) and zero-current switching (ZCS) as dual commutation symmetries: ZVS restores voltage symmetry at turn-on, whereas ZCS restores current symmetry at turn-off. Building on this viewpoint, we organize QR Buck, Boost, and Buck–Boost converters through two complementary forms of symmetry: (i) commutation symmetry (ZVS vs. ZCS) and (ii) topological duality (Buck ↔ Boost and the self-dual nature of Buck–Boost). The framework is anchored in normalized parameter spaces commonly used in QR analyses and is illustrated using representative ZVS and ZCS Buck cases, including waveform-stage symmetry and loss/stress implications. Furthermore, we discuss the “cost of symmetry” via stress and conduction-loss metrics, highlighting how soft-switching conditions trade voltage and current stresses in dual fashions. The proposed organization offers a compact conceptual map that links operating regimes, design degrees of freedom, and expected stress/loss trends across the main classical QR-PWM converter families. Full article

Distinct from the traditional Modular Multilevel Converter (MMC) which focuses on fundamental frequency operation, the Static Var and Filter (SVF) within the Multi-Source Line-Commutated Converter (SLCC) system is tasked with the core function of high-frequency harmonic filtering. This paper reveals a unique engineering reliability issue stemming from this functional difference: to satisfy the Nyquist sampling theorem for precise tracking and elimination of high-frequency harmonics, the update frequency of the capacitor voltage balancing algorithm in the SLCC-SVF system is forced to increase significantly. Mathematical modeling and quantitative analysis demonstrate that this strong coupling between harmonic tracking demands and the voltage sorting strategy directly drives an abnormal surge in the average switching frequency (reaching over five times that of the fundamental condition), severely threatening device safety. To address this, an optimized adaptive hybrid modulation strategy is proposed. The system operates under Nearest Level Modulation (NLM) in normal conditions and automatically transitions to Carrier Phase-Shifted PWM (CPS-PWM)—leveraging its closed-loop balancing capability—when switching frequency or junction temperature exceeds safety thresholds. Furthermore, a non-integer frequency ratio optimization theory for low-modulation indices is constructed specifically for SVF conditions to prevent low-frequency oscillations. PLECS simulation results validate the theoretical analysis, showing that the proposed strategy effectively reduces the average switching frequency by approximately 20% under complex harmonic conditions, significantly enhancing thermal stability and operational reliability while guaranteeing filtering performance. Full article

Background: Since World War II, the number of motorized vehicles has increased dramatically. Yet, few studies have evaluated how perceptions of single and multiple motorized traffic variables, in different combinations, influence pedestrians’ appraisals of the route environment in relation to whether it facilitates or deters walking. We have previously illuminated this in an inner urban area of a metropolitan region. This study aims to scrutinize these matters in the suburban–rural parts of the same metropolitan area. For comparative reasons, we use the same methods as used for the inner urban area. Our hypothesis is that these kinds of perceptions, to some extent, may be context-specific. Methods: Relations between pedestrians’ perceptions of motorized traffic variables (flow and speeds of motor vehicles, noise, and exhaust fumes) and combinations of them, as well as if appraisals of route environments hinder–stimulate walking and are unsafe–safe for reasons of traffic, have been evaluated. This was studied in the suburban and rural areas of Greater Stockholm, Sweden. The pedestrians (n = 233) rated their route environment with the Active Commuting Route Environment Scale (ACRES). Correlation, multiple regression, and mediation analyses were used to study the relationships. Results: The regression analyses showed that noise was the primary negative predictor variable in relation to hindering–stimulating walking. With respect to the other outcome, unsafe–safe traffic, none of the variables had a significant relation. The mediation analyses showed that (1) vehicle speed had an indirect effect on unsafe–safe traffic via noise, (2) both vehicle speed and vehicle flow had, via noise, indirect effects on hinders–stimulates walking, and (3) vehicle speed had, via vehicle flow, an indirect effect on noise and exhaust fumes. Conclusions: In suburban–rural route environments, noise protrudes as a hindering variable for walking. The mediation analyses showed that vehicle speed intensified noise and had negative effects on both outcomes. Therefore, by reducing vehicle speed, noise levels will be lowered, and the walking experience is likely to be enhanced, which can influence the amount of walking. The results are further illuminated through the exploration of existing and potential future research strategies. Full article

In this study, we present a unified symmetry-conservation solution analysis of a well-posed resonant nonlinear Schrödinger (NLS)-type equation incorporating spatio-temporal dispersion and inter-modal dispersion. Working within the truncated M-fractional derivative framework, we first construct exact traveling-wave solution families via the Kudryashov expansion method, together with the corresponding parameter constraints and limiting cases. We then determine the admitted Lie point symmetries and establish the associated Lie algebra, including the commutator structure, adjoint representation, and an optimal system of one-dimensional subalgebras for classification. Using the conservation theorem, we derive conserved vectors associated with the fundamental invariances of the model; in the NLS setting and under suitable conditions, these quantities can be interpreted as generalized power (mass), momentum, and energy-type invariants. Overall, the results provide explicit wave profiles and structural invariants that enhance the interpretability of the model and offer benchmark expressions useful for further qualitative, numerical, and stability investigations in nonlinear dispersive wave dynamics. Full article