Search Results (4,497)

We study control synthesis under Signal Temporal Logic (STL) specifications for driving scenarios where strict rule satisfaction is not always feasible and human experts exhibit context-dependent flexibility. We represent such behavior using robustness slackness—learned rule-wise lower bounds on STL robustness—and introduce sub-goals that encode intermediate intent in the state/output space (e.g., lane-level waypoints). Prior learning-based MPC–STL methods typically infer slackness with VAE priors and plug it into MPC, but these priors can underrepresent multimodal and rare yet valid expert behaviors and do not explicitly model intermediate intent. We propose a diffusion-guided MPC–STL framework that jointly learns slackness and sub-goals from demonstrations and integrates both into STL-constrained MPC. A conditional diffusion model generates pairs of (rule-wise slackness, sub-goal) conditioned on features from the ego vehicle, surrounding traffic, and road context. At run time, a few denoising steps produce samples for the current situation; slackness values define soft STL margins, while sub-goals shape the MPC objective via a terminal (optionally stage) cost, enabling context-dependent trade-offs between rule relaxation and task completion. In closed-loop simulations on held-out highD track-driving scenarios, our method improves task success and yields more realistic lane-changing behavior compared to imitation-learning baselines and MPC–STL variants using CVAE slackness or strict rule enforcement, while remaining computationally tractable for receding-horizon MPC in our experimental setting. Full article

Extensive research in laboratory rodents has shown that novelty exposure enhances the consolidation of memories for preceding or following low-arousal events by elevating dopamine release in the dorsal hippocampus (dHipp). Additionally, numerous studies have demonstrated that post-encoding noradrenergic activation of the basolateral amygdala (BLA) can also enhance memory consolidation in dHipp. Since the BLA is most active during emotionally arousing or stress-related situations, it was suggested that this nuclear complex mediates the effects of emotional salience on memory consolidation. However, it is presently unknown whether the reinforcement of memory storage in dHipp induced by novel and arousing environmental conditions results from the interaction between these two modulatory systems. To test the hypothesis of a functional interaction between dopaminergic and noradrenergic systems, this study assessed their combined effects on a low-arousal object-location (OL) task. Rats received post-training intra-BLA infusions of vehicle or clenbuterol (Clen), a selective β-adrenoceptor agonist. Novelty-induced dopamine release in the dHipp was enhanced by omitting habituation prior to training, and the contribution of dopamine signaling was further evaluated using pre-infusion administration of the D1/D5 receptor antagonist SCH 23390. The distribution of two important proteins for memory processing, namely the activity-regulated cytoskeleton-associated protein (Arc) and the phosphorylated form of the transcription factor, cAMP-response element-binding protein (pCREB) in the dHipp, was explored in a subset of rats perfused 60 min after the training phase. Stimulation of the BLA significantly increased the number of Arc- and pCREB-positive cells in several dHipp areas. The preceding application of SCH 23390, however, substantially decreased these effects in the same areas, i.e., the dentate gyrus (DG), CA2, and CA1 subregions for pCREB, and the CA3b, CA3c, CA2, and CA1 subregions for Arc. This interaction is considered essential for the initial stages of memory consolidation. The obtained results indicate the presence of a region-specific interaction between BLA modulatory inputs and intrahippocampal dopaminergic transmission, the mechanisms of which remain to be elucidated. Full article

With the expanding electric vehicle market, there is increasing demand for improved battery safety and fast-charging performance. Ceramic-based solid electrolytes have attracted attention due to their high thermal and electrochemical stabilities. Li-glass solid electrolytes (e.g., Li₂O–LiCl–B₂O₃–Al₂O₃, LCBA) are promising materials because they enable low-temperature sintering (<550 °C), suppress lithium volatilization, mitigate ionic conductivity degradation, and enable cost-effective manufacturing. LCBA can be co-sintered with graphite anodes to form composite anode materials for LCBA-based all-solid-state batteries. However, insufficient densification and shrinkage mismatch often lead to limited ionic conductivity and interfacial delamination. In this study, the sintering behavior of LCBA was investigated using a hot-press-assisted process, and LCBA/graphite composite anodes were co-sintered to evaluate their electrochemical and interfacial properties. The LCBA electrolyte sintered at 550 °C exhibited high densification and an ionic conductivity of 3.86 × 10⁻⁵ S cm⁻¹. Additionally, the composite containing 50 wt% LCBA achieved a maximum tensile stress of ~0.23 MPa and a high interfacial fracture energy of ~180–200 J m⁻², indicating enhanced deformation tolerance and fracture resistance. This approach improves the densification, ionic conductivity, and interfacial mechanical stability of LCBA solid electrolytes and their composite anodes, highlighting their potential for next-generation all-solid-state secondary battery applications. Full article

Maritime surveillance is critical for ensuring the safety and continuity of sea logistics, port operations, and coastal activities in the presence of anomalies such as unlawful maritime activities, security-related incidents, and anomalous events (e.g., tsunamis or aggressive marine wildlife). Recent advances in unmanned aerial vehicles (UAVs)/drones and computer vision enable automated, wide-area monitoring that can reduce dependence on continuous human observation and mitigate the limitations of traditional methods in complex maritime environments (e.g., waves, ship clutter, and marine animal movement). This study proposes a hybrid anomaly detection and tracking pipeline that integrates YOLOv12, as the primary object detector, with two auxiliary modules: (i) motion assistance for tracking moving anomalies and (ii) stillness (appearance) assistance for tracking slow-moving or stationary anomalies. The system is trained and evaluated on a custom maritime dataset captured using a DJI Mini 2 drone operating around a port area near Bayshore MRT Station (TE29), Singapore. Windsurfers are used as proxy (dummy) anomalies because real anomaly footage is restricted for security reasons. On the held-out test set, the trained model achieves over 90% on Precision, Recall, and mAP50 across all classes. When deployed on real maritime video sequences, the pipeline attains a mean Precision of 92.89% (SD 13.31), a mean Recall of 90.44% (SD 15.24), and a mean Accuracy of 98.50% (SD 2.00%), indicating strong potential for real-world maritime anomaly detection. This proof of concept provides a basis for future deployment and retraining on genuine anomaly footage obtained from relevant authorities to further enhance operational readiness for maritime and coastal security. Full article

The rapid proliferation of connected vehicles equipped with both Vehicle-to-Vehicle (V2V) sidelink and cellular interfaces creates new opportunities for real-time vehicular applications, yet achieving ultra-reliable communication without prohibitive cellular costs remains challenging. This paper addresses reliable inter-vehicle video streaming for safety-critical applications such as See-Through for Passing and Obstructed View Assist, which require stringent Service Level Objectives (SLOs) of 50 ms latency with 99% reliability. Through measurements in Seoul urban environments, we characterize the complementary nature of V2V and Vehicle-to-Network-to-Vehicle (V2N2V) paths: V2V provides ultra-low latency (mean 2.99 ms) but imperfect reliability (95.77%), while V2N2V achieves perfect reliability but exhibits high latency variability ($P_{99}$: 120.33 ms in centralized routing) that violates target SLOs. We propose a hybrid framework that exploits V2V as the primary path while selectively retransmitting only lost packets via V2N2V. The key innovation is a dual loss detection mechanism combining gap-based and timeout-based triggers leveraging Real-Time Protocol (RTP) headers for both immediate response and comprehensive coverage. Trace-driven simulation demonstrates that the proposed framework achieves a 99.96% packet reception rate and 99.71% frame playback ratio, approaching lossless transmission while maintaining cellular utilization at only 5.54%, which is merely 0.84 percentage points above the V2V loss rate. This represents a $7\times$ cost reduction versus PLR Switching (4.2 GB vs. 28 GB monthly) while reducing video stalls by $10\times$. These results demonstrate that packet-level selective redundancy enables cost-effective ultra-reliable V2X communication at scale. Full article

Infectious endometritis is a primary cause of subfertility in mares. Many manuals and guidelines are available for administering intrauterine infusions of antibiotics and biofilm-disrupting solutions, detailing concentrations, vehicle solutions, and buffers. However, the stability of these combinations has not been documented. Therefore, our study investigated how factors such as storage temperature, concentration, buffer types, combinations of biofilm disruptors, and vehicle solutions affected pH stability over 24 h in uterine infusion preparations commonly used by veterinary theriogenologists to treat endometritis in mares. In experiment 1, amikacin, ampicillin, ceftiofur, ciprofloxacin, gentamicin, penicillin G potassium, penicillin G procaine, and ticarcillin clavulanate were diluted in saline and lactated Ringer’ s solution and stored at 5 ° C, 21 ° C, and 37 ° C for 24 h. Solutions were evaluated for pH and physical characteristics at 0, 1, 3, 6, and 24 h after storage. In experiment 2, 1- and 2-g doses of amikacin, ampicillin, and gentamicin were compared, evaluating the same volume at different concentrations and their stability over 24 h. Experiment 3 combined biofilm chelators (i.e., Tris-EDTA, hydrogen peroxide, and dimethyl sulfoxide) with antibiotic solutions and evaluated interactions among products. Experiment 4 compared the stability of each antibiotic diluted in saline and lactated Ringer’ s solution. Statistical analysis was performed using GraphPad Prism 9.3.0. Significance was set at p < 0.05. The results indicated that the stability of antibiotic solutions for uterine infusions in mares is significantly influenced by storage conditions and pH fluctuations. Solutions containing aminoglycosides showed an increase in pH over time, suggesting that buffering agents like sodium bicarbonate can enhance stability. In contrast, other antibiotics exhibited a decrease in pH, particularly at elevated temperatures, which may reduce their effectiveness. In conclusion, the pH stability of uterine infusions is affected by various storage conditions and vehicles, underscoring the importance of evaluating antibiotic treatments for quality control. While pH changes were observed, the potential impact on the overall stability or antimicrobial activity of the solutions requires further investigation. Full article

Traffic-related air pollution (TRAP) is known to contribute to oxidative stress in the central nervous system (CNS) and has been linked to increased risk of Alzheimer’s disease (AD). Alterations in the renin–angiotensin system (RAS), specifically increased angiotensin II (Ang II) signaling via the angiotensin II type 1 (AT₁) receptor, are implicated in increased oxidative stress in the CNS via activation of NADPH oxidase (NOX). As exposure to TRAP may further elevate AD risk, we investigated whether exposure to inhaled mixed gasoline and diesel vehicle emissions (MVE) promotes RAS-dependent expression of factors that contribute to AD pathophysiology in an apolipoprotein E-deficient (ApoE^−/−) mouse model. Male ApoE^−/− mice (6–8 weeks old) on a high-fat diet were treated with either an ACE inhibitor (captopril, 4 mg/kg/day) or water and exposed to filtered air (FA) or MVE (200 µg PM/m³) for 30 days. MVE exposure elevated plasma Ang II, inflammation, and oxidative stress in the hippocampus, associated with increased levels of Aph-1 homolog B (APH1B), a gamma-secretase subunit, and beta-secretase 1 (BACE1), involved in Aβ production. Each of these endpoints was normalized with ACEi treatment. These findings indicate that TRAP exposure in ApoE^−/− mice drives a RAS- and NOX-dependent oxidative and inflammatory response and shifts Aβ processing towards an amyloidogenic profile before overt Aβ deposition, suggesting a potential therapeutic approach for air pollution-induced AD risk. Full article

Hypoxia–ischemia (HI)-related brain injury impacts millions of neonates worldwide. Male neonates are two times more susceptible to developing HI. We have previously reported that the administration of the neurotrophin receptor tyrosine kinase B (TrkB) agonist 7,8-dihydroxyflavone (DHF) following neonatal HI increases hippocampal TrkB phosphorylation and improves hippocampal-dependent learning and memory in early adult life only in females. We hypothesize that sex differences in HI outcomes are due to alterations in neonatal hippocampal steroid content, mainly the neural testosterone. At postnatal day 9, C57BL/6J mice underwent sham and Vannucci’s HI surgeries and were treated either with DHF or vehicle control. Hippocampi and plasma were collected on days 1 and 3 post-HI and liquid chromatography tandem mass spectrometry was used to determine the testosterone (T), estradiol (E₂), progesterone (P₄), and corticosterone (CORT) contents in these samples. All hippocampal steroid contents were at least 10-fold higher than in plasma, suggesting neural synthesis. Males had higher hippocampal T content than females at 3 days post-HI. Treatment with DHF reduced T in the female hippocampi at 3 days post-HI, but not in males. These findings suggest that the neuroprotective effect of DHF in females may be mediated, at least in part, through the reduction in hippocampal T following HI. Full article

Collision avoidance between unmanned aerial vehicles (UAVs) and non-cooperative targets (e.g., off-nominal operations or birds) presents significant challenges in urban air mobility (UAM). This difficulty arises due to the highly dynamic and unpredictable flight intentions of these targets. Traditional collision-avoidance methods primarily focus on cooperative targets or non-cooperative ones with fixed behavior, rendering them ineffective when dealing with highly unpredictable flight patterns. To address this, we introduce a deep reinforcement learning-based collision-avoidance approach leveraging global and local intent prediction. Specifically, we propose a Global and Local Perception Prediction Module (GLPPM) that combines a state-space-based global intent association mechanism with a local feature extraction module, enabling accurate prediction of short- and long-term flight intents. Additionally, we propose a Fusion Sector Flight Control Module (FSFCM) that is trained with a Dueling Double Deep Q-Network (D3QN). The module integrates both predicted future and current intents into the state space and employs a specifically designed reward function, thereby ensuring safe UAV operations. Experimental results demonstrate that the proposed method significantly improves mission success rates in high-density environments, with up to 80 non-cooperative targets per square kilometer. In 1000 flight tests, the mission success rate is 15.2 percentage points higher than that of the baseline D3QN. Furthermore, the approach retains an 88.1% success rate even under extreme target densities of 120 targets per square kilometer. Finally, interpretability analysis via Deep SHAP further verifies the decision-making rationality of the algorithm. Full article

Background: The integration of unmanned aerial vehicles (UAVs) into warehouse management is shaped by a broad spectrum of influencing factors, yet practical adoption lagged behind its potential due to scarce quantitative models of factor interdependencies. Methods: This study systematically reviewed academic literature to identify key factors affecting UAV adoption and explored their interrelationships using complex network and social network analysis. Results: Sixty-six distinct factors were identified and mapped into a weighted network with 527 connections, highlighting the multifaceted nature of UAV integration. Notably, two factors, i.e., Disturbance Prediction and System Resilience, were found to be isolated, suggesting they have received little research attention. The overall network is characterized by low density but includes a set of 25 core factors that strongly influence the system. Significant interconnections were uncovered among factors such as drone design, societal factors, rack characteristics, environmental influences, and simulation software. Conclusions: These findings provide a comprehensive understanding of the dynamics shaping UAV adoption in warehouse management. Furthermore, the open-access dataset and network model developed in this research offer valuable resources to support future studies and practical decision-making in the field. Full article

Over-the-Air updates have emerged as a critical competitive frontier in the Software-Defined Vehicle era. While offering value creation opportunities, automakers face strategic uncertainty regarding pricing models (e.g., subscription vs. one-time purchase). To clarify these dynamics, this study develops an evolutionary game model of duopolistic pricing competition. Unlike traditional studies with exogenous payoff assumptions, we innovatively employ the Hotelling model to endogenously derive firm profit functions based on consumer utility maximization. The highlights of this study include: (1) We establish an integrated “static–dynamic” framework connecting micro-level consumer choice with macro-level strategy evolution; (2) We identify that product differentiation is the decisive variable governing market stability; (3) We demonstrate that under moderate differentiation, the market exhibits a robust self-correcting tendency towards “Tacit Collusion” (mutual high pricing). However, simulation results also warn that an asymmetric disruptive strategy by a market leader can override this robustness, forcing the market into a low-profit equilibrium. These findings provide theoretical guidance for automakers to optimize pricing strategies and avoid value-destroying price wars. Full article

As a core support for the integration of new energy and smart grids, Vehicle-to-Grid (V2G) networks face a core contradiction between user privacy protection and transaction security traceability—a dilemma that is further exacerbated by issues such as the quantum computing vulnerability of traditional cryptography, cumbersome key management in stateful ring signatures, and conflicts between revocation mechanisms and privacy protection. To address these problems, this paper proposes a post-quantum revocable linkable ring signature scheme based on SPHINCS+, with the following core innovations: First, the scheme seamlessly integrates the pure hash-based architecture of SPHINCS+ with a stateless design, incorporating WOTS+, FORS, and XMSS technologies, which inherently resists quantum attacks and eliminates the need to track signature states, thus completely resolving the state management dilemma of traditional stateful schemes; second, the scheme introduces an innovative “real signature + pseudo-signature polynomially indistinguishable” mechanism, and by calibrating the authentication path structure and hash distribution of pseudo-signatures (satisfying the Kolmogorov–Smirnov test with $D\le 0.05$), it ensures signer anonymity and mitigates the potential risk of distinguishable pseudo-signatures; third, the scheme designs a KEK (Key Encryption Key)-sharded collaborative revocation mechanism, encrypting and storing the $(I,pk,RID)$ mapping table in fragmented form, with KEK split into $KE{K}_1$ (held by the Trusted Authority, TA) and $KE{K}_2$ (held by the regulatory node), with collaborative decryption by both parties required to locate malicious users, thereby resolving the core conflict of privacy leakage in traditional revocation mechanisms; fourth, the scheme generates forward-secure linkable tags based on one-way private key updates and one-time random factors, ensuring that past transactions cannot be traced even if the current private key is compromised; and fifth, the scheme adopts hash commitments instead of complex cryptographic commitments, simplifying computations while efficiently binding transaction amounts to signers—an approach consistent with the pure hash-based design philosophy of SPHINCS+. Security analysis demonstrates that the scheme satisfies the following six core properties: post-quantum security, unforgeability, anonymity, linkability, unframeability, and forward secrecy, thereby providing technical support for secure and anonymous payments in V2G networks in the quantum era. Full article

This paper reports part of the research results carried out within the National Centre for Sustainable Mobility (MOST—CN4)—Spoke 5 “Light Vehicle and Active Mobility”—funded by the Italian National Recovery and Resilience Plan (PNRR). Specifically, it presents the design of a bicycle frame based on the pursuit of maximum modularity and adaptability. The research investigates multi-level modularity as a strategic design lever to improve flexibility, usability, and production efficiency in light vehicles. A design-driven and interdisciplinary methodology combined a systematic analysis of 76 patents with a qualitative cross-comparison of 15 case-study products and collaborative co-design activities involving domain experts. The resulting insights informed the development of a modular bike frame prototype, enabling evaluation of user-centered adaptability, production-oriented modularity, and functional transformations such as e-bike integration and cargo configurations. Findings provide evidence-based, qualitative insights and practical design exploration for modular light vehicle development, offering an operational framework and laying the groundwork for a structured, generalized framework to guide future research and industrial applications. Full article

Considering the variability of driving conditions in mining areas, existing control strategies are difficult to meet the comprehensive performance requirements of mining dump trucks in the longitudinal, lateral, and vertical directions. Longitudinal, lateral, and vertical (LLV) coordinated control of active hydro-pneumatic suspension system based on model predictive control (MPC) is constructed in this paper. The vehicle dynamic response under random road surface input based on wheelbase characteristics is established, and the rationality of the active hydro-pneumatic suspension LLV coordinated control strategy based on MPC is analyzed. Handling stability is taken as the overall control objective for active hydro-pneumatic suspension on C-class road surfaces. The dynamic tire loads of the six wheels of the mining dump truck are reduced by 25.8%, 29.1%, 30.6%, 27.6%, 29.9%, and 28.1%, respectively, in the unloaded state, while the longitudinal, lateral, and vertical body accelerations have not deteriorated. Under the E-class road surface, the overall control objective of the mining dump truck is comfort, and the longitudinal, lateral, and vertical accelerations in the unloaded state have been optimized by 34.6%, 31.4%, and 34.1%, respectively. Full article

Amidst the increasing aerial traffic and road traffic congestion, Urban Air Mobility (UAM) has emerged as a new mode of aerial transport offering less travel time and ease of portability. A critical factor in reducing travel time is the emerging electric Vertical Take-Off and Landing (eVTOL) vehicles, which require infrastructure such as vertiports to operate smoothly. However, the dynamics of vertiport operations, particularly the integration of battery charging facilities, remain relatively unexplored. This work aims to bridge this gap by delving into vertiport management by utilizing separate taxing and parking levels. The study also focuses on the time eVTOLs spend at the vertiport to anticipate potential delays. This factor helps optimise arrival and departure times via a scheduling strategy that accounts for hourly demand fluctuations. The simulation results, conducted with hourly demand, underscore the significant impact of battery charging on operational time while also highlighting the role of parking spots in augmenting capacity and facilitating more efficient scheduling. Full article