Search Results (131)

The Internet of Drones (IoD) is rapidly expanding into sensitive applications, necessitating robust and efficient authentication. Traditional methods struggle against prevalent attacks, especially considering the unique vulnerabilities of the IoD, such as drone physical capture. This paper proposes Bio-2FA-IoD, a novel biometric-enhanced two-factor authentication protocol designed for secure IoD operations. Drawing on established 2FA principles and fuzzy extractor technology, Bio-2FA-IoD achieves strong mutual authentication between an operator (via an operator device), a drone (as a relay), and a ground control station (GCS), supported by a trusted authority. We detail the protocol’s registration and authentication phases, emphasizing reliable biometric key generation. A formal security analysis using BAN logic demonstrates secure belief establishment and key agreement, while a proof sketch under the Bellare–Pointcheval–Rogaway (BPR) model confirms its security against active adversaries in Authenticated Key Exchange (AKE) contexts. Furthermore, a comprehensive performance evaluation conducted using the Contiki OS and Cooja simulator illustrates Bio-2FA-IoD’s superior efficiency in computational and communication costs, alongside very low latency, high packet delivery rate, and minimal energy consumption. This positions it as a highly viable and lightweight solution for resource-constrained IoD environments. Additionally, this paper conceptually explores potential extensions to Bio-2FA-IoD, including the integration of Diffie–Hellman for enhanced perfect forward secrecy and a Sybil-free pseudonym management scheme for improved user anonymity and unlinkability. Full article

The accelerated uptake of unmanned aerial vehicles (UAVs) has significantly altered communication and data exchange landscapes but has also introduced substantial security challenges, especially in open-access UAV communication environments. To address these, Elliptic curve cryptography (ECC) offers robust security with computational efficiency, ideal for resource-constrained Internet of Drones (IoD) systems. This study proposes a Secure and Efficient Three-Way Key Exchange (SETKE) protocol using ECC, specifically tailored for IoD. The SETKE protocol’s security was rigorously analyzed within an extended Bellare–Pointcheval–Rogaway (BPR) model under the random oracle assumption, demonstrating its resilience. Formal verification using the AVISPA tool confirmed the protocol’s safety against man-in-the-middle (MITM) attacks, and formal proofs establish its Authenticated Key Exchange (AKE) security. In terms of performance, SETKE is highly efficient, requiring only 3 ECC scalar multiplications for the Service Requester drone, 4 for the Service Provider drone, and 3 for the Control Server, which is demonstrably lower than several existing schemes. My approach achieves this robust protection with minimal communication overhead (e.g., a maximum payload of 844 bits per session), ensuring its practicality for resource-limited IoD environments. The significance of this work for the IoD field lies in providing a provably secure, lightweight, and computationally efficient key exchange mechanism vital for addressing critical security challenges in IoD systems. Full article

Background/Objectives: Cancer stem cells (CSCs) represent a minor yet critical subpopulation within tumors, endowed with self-renewal and differentiation capacities, and are implicated in tumor initiation, progression, metastasis, therapeutic resistance, and recurrence. Reliable in vitro functional assays to characterize CSCs are pivotal for the development of personalized oncology strategies. This study sought to establish and validate a microfluidic device (MD) platform for the enrichment, functional assessment, and therapeutic evaluation of CSC populations derived from experimental models and primary tumor samples. Methods: Murine (LM38LP) and human (BPR6) breast cancer cell lines were cultured within MDs to promote sphere formation. CSC enrichment was confirmed through the expression analysis of pluripotency-associated genes (Oct4, Sox2, Nanog, and CD44) by quantitative PCR (qPCR) and immunofluorescence. Sphere number, size, and gene expression profiles were quantitatively assessed before (control) and after chemotherapeutic exposure. To validate the MD platform against conventional scale, parallel experiments were performed in 12 well plates. To extend translational relevance, three primary canine tumor samples (solid thyroid carcinoma, simple tubular carcinoma, and reactive lymph node) were mechanically disaggregated and processed within MDs for CSC characterization. Results: The MD platform enabled the consistent enrichment of CSC populations, showing significant modulation of sphere growth parameters and stemness marker expression following chemotherapeutic treatment. Beyond its comparability with conventional culture, the MD also supported immunofluorescence staining and allowed real-time monitoring of individual cell growth. Sphere formation efficiency (SFE) and CSC marker expression were similarly demonstrated in primary veterinary tumor cultures, highlighting the device’s cross-species applicability. Conclusions: Microfluidic-based sphere assays represent a robust, reproducible, and scalable platform for the functional interrogation of CSC dynamics and therapeutic responses. This methodology holds great promise for advancing CSC-targeted therapies and supporting personalized oncology in both human and veterinary settings. Full article

Empirical studies have suggested that travelers’ risk attitudes affect their choice behavior when travel conditions are stochastic. By considering the travelers’ risk attitudes, we extend the classical two-route model, in which road capacities vary due to such shocks as bad weather, accidents, and special events. Two information regimes have been investigated. In the zero-information regime, we postulate that travelers acquire the variability in route travel time based on past experiences and choose the route to minimize the travel time budget. In the full-information regime, travelers have pre-trip information of the road capacities and thus choose the route to minimize the travel time. User equilibrium states of the two regimes have been analyzed, based on the canonical BPR travel time function with power coefficient $p$. In the special case $p=1$, the closed form solutions have been derived. Three cases and eleven subcases have been classified concerning the dependence of expected total travel times on the risk attitude in the zero-information regime. In the general condition $p>0$, although we are not able to derive the closed form solutions, we proved that the results are qualitatively unchanged. We have studied the benefit gains/losses by shifting from the zero-information to the full-information regime. The circumstance under which pre-trip information is beneficial has been identified. A numerical analysis is conducted to further illustrate the theoretical findings. Full article

Substance Use Disorders (SUDs) are frequently associated with impairments in emotional regulation and behavioural control. Among the most prevalent substances of abuse, alcohol and cocaine are known to exert distinct effects on neuropsychological functioning. This study aimed to compare individuals with Alcohol Use Disorder (AUD) and Cocaine Use Disorder (CUD) in terms of impulsivity and alexithymia, and to examine the clinical implications of poly-substance use involving both alcohol and cocaine. Participants completed standardized psychometric assessments, including the Barratt Impulsiveness Scale (BIS-11), the Brief Psychiatric Rating Scale (BPRS), and the Toronto Alexithymia Scale (TAS-20). Group comparisons were conducted using non-parametric tests, and logistic regression models were applied to control for demographic covariates. The findings showed that impulsivity levels were comparable across groups, whereas alexithymia scores were significantly higher in individuals with AUD and in those with poly-substance use, relative to CUD-only participants. These findings underscore the relevance of targeting emotional regulation difficulties, particularly alexithymia, in the assessment and treatment of SUDs. Integrating emotion-focused interventions may enhance treatment outcomes, especially for individuals with co-occurring substance use patterns. Future research is needed to clarify the underlying neuropsychological mechanisms contributing to these differences and to inform more personalized approaches to addiction care. Full article

LiFePO₄ (LFP) batteries are among the earliest commercialized and most discarded lithium-ion batteries. Although existing recovery technologies focus on the conversion of LiFePO₄ to Li₂CO₃, challenges associated with achieving near-full recovery and high-value products remain. This study proposes a strategy for the conversion of spent LiFePO₄ to LiF by mechanical chlorination coupled with a fluorination reaction. The optimum conditions were determined to be a ball-to-powder ratio (BPR) = 15, NH₄Cl:LFP = 3, H₂O₂ = 2.0 mL, rotation speed = 600 rpm, and grinding time = 12 h. Results showed that 97.14% Li was converted into LiCl by H₂O₂–NH₄Cl mechanical chlorination. When chlorinated intermediates were immersed in water, FePO₄ could be harvested, and 96.79% Li could be recovered as LiF with a purity of 99.50% after adding NH₄F. When Cl-functionalized renewable resin was used to exchange 99.89% F⁻, 0.63 g NH₄Cl per litre of LiF conversion residual liquid was derived. The favourable results were attributed to the ¹O₂ generated by H₂O₂, which had a strong electron affinity to break Li–O bonds and provided superior conditions for the combination of Li and Cl. During fluorination, the formation of LiF reduced the ion concentration, and the entropy decreased, contributing to the spontaneous reaction. Therefore, the proposed method paves the way for near-full recovery and high-value products of spent LiFePO₄. Full article

The rapid growth in the global apparel market and the rise of online consumption underscore the necessity for intelligent clothing recommendation systems that balance visual compatibility with personalized preferences, particularly price sensitivity. Existing recommendation systems often neglect nuanced consumer price behaviors, limiting their ability to deliver truly personalized suggestions. To address this gap, we propose DeepFMP, a multimodal deep learning framework that integrates visual, textual, and price features through an enhanced DeepFM architecture. Leveraging the IQON3000 dataset, our model employs ResNet-50 and BERT for image and text feature extraction, alongside a comprehensive price feature module capturing individual, statistical, and category-specific price patterns. An attention mechanism optimizes multimodal fusion, enabling robust modeling of user preferences. Comparative experiments demonstrate that DeepFMP outperforms state-of-the-art baselines (LR, FM, Wide & Deep, GP-BPR, and DeepFM), achieving AUC improvements of 1.6–12.2% and NDCG@10 gains of up to 3.2%. Case analyses further reveal that DeepFMP effectively improves the recommendation accuracy, offering actionable insights for personalized marketing. This work advances multimodal recommendation systems by emphasizing price sensitivity as a pivotal factor, providing a scalable solution for enhancing user satisfaction and commercial efficacy in fashion e-commerce. Full article

Background/Objectives: Schizophrenia is a severe psychiatric disorder, with onset typically occurring in late adolescence or early adulthood. Early identification of psychotic symptoms, especially those occurring before age 12, has been linked to better long-term outcomes. This study aims to assess the presence of psychotic spectrum symptoms before the age of 12 in adult schizophrenia patients and explore their clinical implications for early detection and intervention. Methods: This retrospective, observational study included 170 adult patients diagnosed with schizophrenia, confirmed by the SCID-5. Patients were recruited from the University of Siena Medical Center and completed the modified lifetime version of the Psychotic Spectrum Self-Report (PSY-SR) questionnaire, which assessed the onset of specific psychotic symptoms before and after age 12. Symptom severity was evaluated using the Brief Psychiatric Rating Scale (BPRS) and the Clinical Global Impression Scale (CGI). This study also examined the impact of the duration of untreated psychosis (DUP) on symptom severity. Results: In our cohort, 21% of patients exhibited prodromal symptoms before age 12 (95% CI: 15–27%). Prodromal symptoms were linked to a 9.53-point increase in the BPRS scores (p = 0.0478) and a 0.50-point increase in the CGI scores (p = 0.0347). The age of symptom onset negatively correlated with the BPRS scores (p < 0.0001), with each year of delay resulting in a 1.33-point decrease. The DUP correlated significantly with both the BPRS (ρ = 0.97) and CGI scores (ρ = 0.94). The multivariate analysis revealed that a longer DUP was associated with significant increases in both scores: a 27.16-point increase in the BPRS (p < 0.0001) for a moderate DUP and a 67.51-point increase (p < 0.0001) for a severe DUP. The CGI scores increased by 1.11 points with a moderate DUP and 3.17 points with a severe DUP (p < 0.0001). However, the interaction between the DUP and prodromal symptoms at age 12 was not significant, indicating similar impacts of the DUP regardless of early symptom onset. Conclusions: The results support the critical importance of early detection and intervention in schizophrenia. Early psychotic spectrum symptoms, particularly those occurring before age 12, are significant predictors of later severity and functional impairment. This study underscores the value of screening tools like the PSY-SR for identifying prodromal symptoms and facilitating timely intervention. Our findings highlight the need for the early identification of psychotic symptoms, particularly in at-risk populations, to improve long-term outcomes. Intervening before the onset of full-blown psychosis may reduce the severity of schizophrenia and promote better clinical outcomes. Full article

This study presents a practical implementation of Business Process Reengineering (BPR) to streamline teaching assignment workflows at the University of Basilicata, a higher education institution (HEI) facing administrative inefficiencies exacerbated by rigid regulatory frameworks. By integrating process modeling, simulation, and digital tools, the research addresses systemic bottlenecks in resource allocation, transparency, and procedural delays inherent in traditional academic workflows. The methodology employs a dual-phase approach: (1) a detailed “AS-IS” analysis using BPMN 2.0 to map existing processes and (2) a data-driven “TO-BE” redesign validated through discrete event simulation (Simul8^®, Version 31). Key innovations include the automation of approval workflows, dynamic resource prioritization, and stakeholder communication protocols. Simulation results demonstrate a 35% reduction in end-to-end processing time and a 22% improvement in administrative staff utilization while maintaining compliance with national accreditation standards (the AVA framework) and legislative mandates (Law 240/2010). The case study underscores BPR’s role in balancing bureaucratic constraints with operational agility, offering actionable insights for HEIs navigating digital transformation. By prioritizing transparency and stakeholder alignment, the redesigned process not only enhances efficiency but also strengthens accountability in resource management—a critical factor for public institutions under increasing scrutiny for fiscal and educational quality outcomes. This work contributes to the growing discourse on BPR in academia, advocating for simulation-driven methodologies as catalysts for sustainable, stakeholder-centric process innovation in bureaucratic environments. Full article

Business Process Redesign (BPR) is a fundamental approach to enhancing efficiency, compliance, and digital transformation in public sector operations. Despite extensive theoretical advancements, its application in real-world settings remains limited. This study addresses this gap by applying the BPR Assessment Framework to business processes within the Greek Public Financial Management (PFM) domain, specifically analyzing workflows from the Greek Customs Service and the Financial and Economic Crime Unit (S.D.O.E.). This research employs a structured methodology that integrates internal process metrics with clustering techniques to systematically classify processes based on their redesign potential. The findings reveal that a significant proportion of public sector workflows demonstrate high redesign capacity, highlighting opportunities for efficiency gains and improved regulatory compliance. Furthermore, this study identifies key challenges, such as organizational resistance and technological constraints, that impact BPR implementation. By demonstrating the framework’s applicability in a complex, operational environment, this study provides actionable insights for policymakers and practitioners. Specifically, the results show how structured process evaluation enables targeted redesign initiatives that streamline administrative workflows, enhance compliance with financial regulations, and support digital transformation in public administration. These insights contribute to advancing BPR practices by bridging the gap between theoretical development and real-world application, offering a replicable methodology for improving public sector efficiency. Full article

Aripiprazole as a long-acting injectable (LAI) is initiated in oral aripiprazole-stabilised patients and needs, after first injection, 14 days supplementation of oral aripiprazole (one-injection start, OIS). Recently, an alternative two-injection start (TIS) was advanced, involving two 400 mg injections with a single 20 mg oral supplementation of aripiprazole. We tested the two regimens in patients with schizophrenia (SCZ, n = 152, 90 men and 62 women) with (SUD⁺; n = 93) or without (SUD^–; n = 59) substance use disorders (SUDs), comparing OIS (n = 66) with TIS (n = 86) and SUD⁺ vs. SUD^–. For 26 patients, we measured weekly for one month, aripiprazole + dehydroaripiprazole (active moiety) levels. Patients were followed for three months after LAI with psychopathology and quality-of-life scales (BPRS, CGI-S, ACES, BIS-11, and WHOQOL). All groups improved in psychopathology with no differences between OSI and TIS and between SCZ–SUD⁺ and SCZ–SUD^–. The TIS group was associated with serum blood levels of the active moiety within the therapeutic window, while the OIS group showed peaks above the window, possibly exposing patients to toxicity. Treatments were well-tolerated. Here we showed no disadvantages for TIS vs. OIS and possibly increased safety. Shifting the initiation of aripiprazole LAIs to the TIS modality may be safe and pharmacokinetically advantageous. Full article

Objective: Electroconvulsive therapy (ECT) is utilized for treating psychiatric disorders, such as schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BD). We aimed to compare pre- and post-ECT treatment outcomes between patients with SCZ and a combined group of patients with MDD and BD (MDD+BD) to assess the distinction between the antipsychotic and antidepressant effects of ECT. Methods: ECT was administered to patients with SCZ (n = 17) and those with MDD+BD (n = 7). Symptoms were evaluated using the brief psychiatric rating scale (BPRS), clinical global impression scale (CGI), and global assessment of functioning (GAF). Plasma brain-derived neurotrophic factor (BDNF) levels were also measured. Results: The BPRS, CGI, and GAF scores significantly differed after ECT compared with those before ECT in each patient group. However, no significant differences were observed between the groups for each disorder. No significant differences were observed in plasma BDNF levels between the groups at baseline and during ECT. At baseline, only depression scores were more favorable in the SCZ group, whereas positive symptoms and disorganization scores were higher in the MDD+BD group. During treatment, positive symptoms, activation, and disorganization items were significantly more favorable in the MDD+BD group compared with the SCZ group. Total BPRS scores were not associated with plasma BDNF levels; however, rating scores of the several items related to activation, resistance, and disorganization were positively correlated with BDNF levels. Conclusion: ECT effects on several clinical outcomes in the MDD+BD group were associated with plasma BDNF levels. These findings suggest that ECT may be more effective for treating MDD than SCZ. Full article

Given the rapid development of technologies such as new energy vehicles, autonomous driving, and vehicle-to-everything (V2X) communication, a mixed traffic flow comprising connected and autonomous vehicles (CAVs) and human-driven vehicles (HDVs) is anticipated to emerge. This necessitates the development of a daily dynamic evolution model for mixed traffic flow to address the dynamic traffic management needs of urban environments characterized by mixed traffic. The daily dynamic evolution model can capture the temporal evolution of traffic flow in road networks, with a focus on the daily path choice behavior of travelers and the evolving traffic flow in the network. First, based on the travel characteristics of CAVs and HDVs, the user group in a connected autonomous driving environment is classified into three categories, each adhering to the system optimal (SO) criterion, the user equilibrium (UE) criterion, or the stochastic user equilibrium (SUE) criterion. Next, the pure HDV traffic capacity BPR (Bureau of Public Roads) function is adapted into a heterogeneous traffic flow travel time function to compute the travel time cost for mixed traffic flow. Based on the energy consumption calculation formula for HDVs, the impact of CAVs is fully considered to establish the travel energy consumption cost for both CAVs and HDVs. The total individual travel cost for CAVs and HDVs encompasses both travel time cost and energy consumption cost. Furthermore, a daily dynamic evolution model for mixed traffic flow in a connected autonomous driving environment is developed using the proportional-switch adjustment process (PAP) model. The fundamental properties of the model are validated. Finally, numerical simulations on an N-dimensional (N-D) network confirm the validity and effectiveness of the daily evolution model for mixed traffic flow. A sensitivity analysis of traveler responses in the daily evolution model reveals that, as the sensitivity of CAVs to impedance changes increases, the fluctuations in mixed traffic flow during the early stages of evolution become more pronounced, and the time required to reach a mixed-equilibrium state decreases. Therefore, the PAP-based daily dynamic evolution model for mixed traffic flow effectively captures the evolution process of CAV and HDV mixed traffic flow and supports urban traffic management in a connected autonomous driving environment. Full article

Public transport is an integral part of sustainable urban development when its use is promoted by setting bus priority routes (BPRs). BPRs provide clear mobility benefits, but they raise pedestrian safety concerns. In this study, observations were conducted at signalized intersections with two types of BPRs, center-lane and curbside, aiming to characterize pedestrian crossing behaviors, with a particular focus on red-light crossings. We found that at intersections with center-lane BPRs, 30% of pedestrians crossed at least one crosswalk on red, while at another type, 11% crossed on red. Multivariate analyses showed that the risk of crossing on red was substantially higher at intersections with center-lane vs. curbside BPRs; it was also higher among pedestrians crossing to/from the bus stop, males, and young people but lower under the presence of other waiting pedestrians. Furthermore, among pedestrians crossing on red at center-lane BPRs, over 10% did not check the traffic before crossing and another 10% checked the traffic in the wrong direction, thus further increasing the risk. At center-lane BPRs, infrastructure solutions are needed to reduce pedestrian intention to cross on red. Additionally, education and awareness programs for pedestrians should be promoted to emphasize the heightened risk of red-light crossing at intersections with BPRs. Full article

Seaweed presents a sustainable alternative source of valuable fatty acids (FAs) involving omega-3 (n-3) and omega-6 (n-6). As such, there is great potential to reduce pressure on wild fish populations, helping to combat overfishing and its associated global impacts. This study explored the effect of various environmental factors on the FA content and profile of Ulva lactuca using indoor photobioreactors. The taxonomic identity of U. lactuca was confirmed through DNA sequencing using 3 markers (rbcL, ITS, and tufa). The effects of temperature (8, 20, and 30 °C), seawater salinity (3.5, 3.0, 2.5, and 2.0% w/v), nutrient type and concentration (0 or 6.4 ppm, consisting of 50% w/w N-NO₃, 50% w/w N-NH₄, and 0–1 ppm P-PO₄), and irradiance (50, 100, and 150 μmol photons m⁻² s⁻¹) were evaluated. This study assessed their influence on U. lactuca’s biomass production rate (BPR), dry weight (DW), ash content (AC), and FA composition after 7 and 21 days. The results revealed that after 21 days, the polyunsaturated FA (PUFA) content decreased with the increasing seawater salinity (i.e., 38.9% ± 0.7, 33.8% ± 0.4, and 27.0% ± 0.4, and 6.6% ± 0.1 for a salinity of 2.0, 2.5, 3.0, and 3.5% w/v, respectively). The content of n-3 after 21 days increased significantly under the following conditions: 8 °C, a salinity of 2.5% w/v, 6.4 ppm of nitrogen without the addition of phosphorous, and an irradiation of 50 and 150 μmol photons m⁻² s⁻¹, affording a low n-6/n-3 proportion that fits a desirable level of an n6/n3 ratio (1–10) for a balanced nutritional diet. Full article