Search

Bile acids (BAs) affect the growth of potentially pathogenic commensals, including those from the Enterobacteriaceae family, which are frequently overrepresented in inflammatory bowel disease (IBD). BAs are normally reabsorbed in the ileum for recycling and are often increased in the colonic lumina of patients with IBD, including those with Crohn's disease (CD). Here, we investigated the influence of BAs on gut colonization by Enterobacteriaceae. We found increased abundance of Enterobacteriaceae in the colonic mucosae of patients with CD with a concomitant decrease in the transporters that resorb BAs in the ileum. The increase in Enterobacteriaceae colonization was greater in the colons of patients who had undergone terminal ileum resection compared with those with intact ileum, leading us to hypothesize that BAs promote intestinal colonization by Enterobacteriaceae. Exposure of human colonic epithelial cell lines to BAs reduced mitochondrial respiration, increased oxygen availability, and enhanced the epithelial adherence of several Enterobacteriaceae members. In a publicly available human dataset, mucosal Enterobacteriaceae was negatively associated with the expression of genes related to mitochondrial function. In a murine model, increased intestinal BA availability enhanced colonization by Escherichia coli in a manner that depended on bacterial respiration. Together, our findings demonstrate that BAs reduce mitochondrial respiration in the colon, leading to an increase in oxygen availability that facilitates Enterobacteriaceae colonization. This identification of BAs as facilitators of host-commensal interactions may be relevant to multiple intestinal diseases. Editor's summary: Crohn's disease is associated with imbalances in the microbiota and increases in bile acids in the colon. Holani et al. investigated whether bile acids were linked to intestinal colonization by Enterobacteriaceae, a family of potentially pathogenic bacteria that are frequently increased in patients with Crohn's disease. Bile acids reduced mitochondrial respiration in human colonic epithelial cells and promoted oxygen-dependent colonization of the mouse intestine by Enterobacteriaceae. Analysis of samples from patients with Crohn's disease showed that Enterobacteriaceae abundance was associated with increases in bile acids and reductions in transcripts related to mitochondrial function. Thus, bile acids promote Enterobacteriaceae colonization of the intestine by increasing oxygen availability. —Annalisa M. VanHook [ABSTRACT FROM AUTHOR]

We report on a fetus presenting with an increased nuchal translucency, in which chorionic villus sampling led to the diagnosis of mosaic trisomy 8. Ultrasound scan performed at 15(+6) weeks revealed bilateral cleft lip and palate, flat facial profile, and arrhinia. Pregnancy was terminated at 16(+6); postmortem examination showed additional findings including hypospadias, bilateral renal dysplasia, and focal portal fibrosis of the liver. In order to confirm the presence of trisomy 8, FISH analysis was performed in abnormal renal and hepatic tissue, which, unexpectedly, showed a higher fraction of cells with only one fluorescent probe signal (43% and 23%, respectively), if compared with normal fetal liver and kidney (3-10%). This finding is consistent with the survival in this fetus of a monosomic cell line after mitotic non-disjunction, which is in contrast with what is generally thought about mosaic trisomy genesis. We hypothesize that the possible persistence of the monosomic cell line, in addition to the variable distribution of aneuploid cells in the body tissues, could explain the high heterogeneity of mosaic trisomy 8 phenotype., (Copyright © 2011 Wiley Periodicals, Inc.)

Objective: To evaluate the usefulness of uterine artery Doppler in the prediction of outcome in patients with late-onset preeclampsia., Study Design: Patients with late-onset preeclampsia underwent Doppler interrogation of the uterine arteries. Patients with abnormal uterine artery Doppler were compared with those who had a normal uterine artery Doppler., Results: Ninety-nine patients were included in the study group. Abnormal uterine artery Doppler group presented significantly lower gestational age at admission (36.1 +/- 2.1 weeks vs 37.2 +/- 1.9 weeks; P < .005), lower gestational age at delivery (36.5 +/- 1.9 weeks vs 37.7 +/- 1.7 weeks; P < .005), lower birthweight (2429 +/- 590 g vs 3013 +/- 597 g; P < .0001), and a higher admission rate to neonatal intensive care unit (17/51 vs 6/48; odds ratio, 3.5; 95% confidence interval, 1.2-9.5). No significant difference in the occurrence of maternal complications (10/51 vs 6/48; odds ratio, 1.7; 95% confidence interval, 0.5-4.9) was registered., Conclusion: Women with late-onset preeclampsia show a higher risk of perinatal complications if uterine resistance is increased although maternal outcome does not seem to be related to Doppler findings.

Objective: The study focused on the safety of electrosurgical devices in endoscopic fetal surgery. The thermic effects of monopolar electric waves were studied in vitro in order to obtain safety indications in terms of mode of intramniotic application of electrical devices (time and number of shots; volts; and distance from tissues to be preserved)., Study Design: A glass model filled with saline solution, and an electrical device with resistor and voltage supply, were constructed to reproduce the physical effects of thermic conductivity in vitro; a Swan-Ganz thermic sensor was used to measure the temperature inside the beuta. Different series of tests were carried out., Results: The maximal increase (8.60 +/- 0.04 degrees C) takes place at the external surface of the resistor (distance: 0 cm), while at 2 cm, the temperature of the saline solution does not change., Conclusions: Our tests demonstrate that in order to avoid any kind of risk during electrosurgical procedures on fetuses, the electrode must be placed at least 0.5 cm from delicate tissues., ((c) 2006 John Wiley & Sons, Ltd.)

Objective: The aim of this study was to determine the platelet count in fetuses undergoing cordocentesis for hydrops caused by parvovirus infection., Study Design: Fetal platelets were measured at cordocentesis in 11 pregnant women who underwent the procedure because of fetal ascites and/or hydrops caused by parvovirus infection. Thrombocytopenia was defined as mild (platelet count < 150 x 10(9)/L), moderate (platelet count < or = 100 x 10(9)/L), or severe (platelet count to < or = 50 x 10(9)/L). Paired Student t test was performed to compare the platelet count before and after the transfusion., Results: The fetuses underwent 20 cordocenteses. They were thrombocytopenic in 17 and anemic in 15 occasions. The platelet count was reduced after the transfusion (P < .05). Demises occurred after the first transfusion in 2 fetuses. The first occurred within 5 minutes from the procedure and the second within 24 hours. Both were attributed to exsanguination from the umbilical cord puncture site (platelet count 2 and 24 x 10(9)/L, respectively)., Conclusion: Thrombocytopenia is common in fetuses with hydrops caused by parvovirus infection, and can cause exsanguination from the umbilical cord puncture site. We recommend platelet transfusion during cordocentesis when there is severe thrombocytopenia.

Platooning is one of the promising technologies that maximizes the power efficiency of electric vehicles by decreasing the distances between the vehicles. Along with the development of autonomous driving technology, platooning is expected to be commercialized. Recent studies on the operation of platooning focused on power-efficient maintenance of platooning. However, power-efficient operation strategy is also needed for practical applications. Therefore, this study deals with platooning operations that can maximize the power efficiency of electric vehicles in various operational situations. In order to derive the operation method, a mathematical model structured with an objective function that minimizes power consumption is developed. To derive the solution of the mathematical model, a hybrid genetic algorithm is applied. The numerical experiments on four different operational situations are performed to verify the validity of the model and the solution procedure. The four situations consider overall situation that can happen during the platooning stage. The stages are formation, disassembly, join and breakaway of vehicles of platoon. Those four situations are decided upon since they can represent the general situation that can happen during platooning. As a result, the power-efficient driving patterns of electric vehicles are identified. After the development of electric and systematic technology, operational technology for platooning will collaborate for the further improvement. Therefore, throughout consideration of the formation of platooning, technology will expand the sustainability of technological development. [ABSTRACT FROM AUTHOR]

In this paper, a leader motion mechanism is studied for the finite time achievement of any desired formation of a multi-agent system. The approach adopted in this paper exploits a recent technique based on leader motion to the formation control problem of second-order systems, with a special effort to networks of mobile devices and teams of vehicles. After a thorough description of the problem framework, the leader motion mechanism is designed to accomplish the prescribed formation attainment in finite time. Both asymptotic and transient behavior are thoroughly analyzed, to derive the appropriate analytical conditions for the controller design. The overall algorithm is then finalized by two procedures that allow the exploitation of local data only, and the leader motion mechanism is performed based on data collected by the leader during a preliminary experimental stage. A final section of simulation results closes the paper, confirming the effectiveness of the proposed strategy for formation control of a multi-agent system. [ABSTRACT FROM AUTHOR]

Background: Tomato (Solanum lycopersicum L.) production is severely threatened by bacterial wilt, caused by the phytopathogenic bacterium Ralstonia solanacearum. Recently, nano-enabled strategies have shown tremendous potential in crop disease management. Objectives: This study investigates the efficacy of biogenic nanoformulations (BNFs), comprising biogenic silica nanoparticles (SiNPs) and melatonin (MT), in controlling bacterial wilt in tomato. Methods: SiNPs were synthesized using Zizania latifolia leaves extract. Further, MT containing BNFs were synthesized through the one-pot approach. Nanomaterials were characterized using standard characterization techniques. Greenhouse disease assays were conducted to assess the impact of SiNPs and BNFs on tomato plant immunity and resistance to bacterial wilt. Results: The SiNPs and BNFs exhibited a spherical morphology, with particle sizes ranging from 13.02 nm to 22.33 nm for the SiNPs and 17.63 nm to 21.79 nm for the BNFs, indicating a relatively uniform size distribution and consistent shape across both materials. Greenhouse experiments revealed that soil application of BNFs outperformed SiNPs, significantly enhancing plant immunity and reducing bacterial wilt incidence by 78.29% in tomato plants by maintaining oxidative stress homeostasis via increasing the activities of antioxidant enzymes such as superoxide dismutase (31.81%), peroxidase (32.9%), catalase (32.65%), and ascorbate peroxidase (47.37%) compared to untreated infected plants. Additionally, BNFs induced disease resistance by enhancing the production of salicylic acid and activating defense-related genes (e.g., SlPAL1, SlICS1, SlNPR1, SlEDS, SlPD4, and SlSARD1) involved in phytohormones signaling in infected tomato plants. High-throughput 16 S rRNA sequencing revealed that BNFs promoted growth of beneficial rhizosphere bacteria (Gemmatimonadaceae, Ramlibacter, Microscillaceae, Anaerolineaceae, Chloroplast and Phormidium) in both healthy and diseased plants, while suppressing R. solanacearum abundance in infected plants. Conclusion: Overall, these findings suggest that BNFs offer a more promising and sustainable approach for managing bacterial wilt disease in tomato plants. [ABSTRACT FROM AUTHOR]

Congenital anomalies of the neck are rare or uncommon conditions, and for this reason their real incidence is practically unknown. Due to the particular anatomical topography, these abnormalities may comprise certain pathophysiological interferences with the base of the fetal skull, mouth, thorax, mediastinum, or musculoskeletal structures. Thus, even with the contribution of new obstetric imaging perspectives, such as fetal magnetic resonance imaging (MRI), the precise prenatal diagnosis of such anomalies represents a real challenge. The most important anomalies of the fetal neck, which we present in this systematic review, are represented by cystic hygroma (CH), neck teratoma, fetal goiter and fetal thyroid masses, branchial anomalies, vascular neck abnormalities, thyroglossal duct cyst, cervical thymic cyst, other rare anomalies of the fetal neck, and congenital high airway obstruction syndrome. [ABSTRACT FROM AUTHOR]

Vehicle-to-everything (V2X) communication is pivotal in enhancing cooperative awareness in vehicular networks. Typically, awareness is viewed as a vehicle's ability to perceive and share real-time kinematic information. We present a novel definition of awareness in V2X communications, conceptualizing it as a multi-faceted concept involving vehicle detection, tracking, and maintaining their safety distances. To enhance this awareness, we propose a deep reinforcement learning framework for the joint control of beacon rate and transmit power (DRL-JCBRTP). Our DRL−JCBRTP framework integrates LSTM-based actor networks and MLP-based critic networks within the Soft Actor-Critic (SAC) algorithm to effectively learn optimal policies. Leveraging local state information, the DRL-JCBRTP scheme uses an innovative reward function to increase the minimum awareness failure distance. Our SLMLab-Gym-VEINS simulations show that the DRL-JCBRTP scheme outperforms existing beaconing schemes in minimizing awareness failure probability and maximizing awareness distance, ultimately improving driving safety. [ABSTRACT FROM AUTHOR]

Autonomous vehicles (AVs) have the potential to revolutionize transportation by offering safer, more efficient, and convenient mobility solutions. As AV technology advances, there is a growing need to understand and model traffic dynamics in environments where AVs interact with human-driven vehicles. This review provides a comprehensive overview of the modeling techniques used to simulate and analyze autonomous vehicle traffic. It covers the fundamental principles of AVs, key factors influencing traffic dynamics, various modeling approaches, their applications, challenges, and future directions in AV traffic modeling. [ABSTRACT FROM AUTHOR]

The production of municipal solid waste incineration fly ash (MSWI-FA) and municipal sludge (MS) has been increasing annually, raising concerns about proper disposal. In this study, a thermal treatment method with attributes of energy efficiency and complete detoxification was applied to synergistically convert MSWI-FA and MS into precursors for the synthesis of high-strength alkali-activated materials (AAMs). The impact of mass ratios of MSWI-FA and MS on the mineralogy, microstructure, and reactivity of obtained precursors were investigated. The mechanism of alkali activation was deeply studied by characterizing the evolution of reaction products. The strength development of synthesized AAMs was characterized in a one-year time scale, as well as the environmental compatibility. The results revealed that strength, with values ranging from 12.8–33.0 MPa at 3 d, 29.5–44.1 MPa at 28 d and 39.3–54.8 MPa at 365 d. Furthermore, after one year of curing, the release of Ni, Cr, Cu, Pb, Zn, Mn, and Ba from synthesized AAMs into both deionized water and acetic acid were far below the regulatory limits in China. All these contribute to promoting the safe disposal and effective valorization of MSWI-FA and MS. [ABSTRACT FROM AUTHOR]

The authentication of wireless devices through physical layer attributes has attracted a fair amount of attention recently. Recent work in this area has examined various features extracted from the wireless signal to either identify a uniqueness in the channel between the transmitter–receiver pair or more robustly identify certain transmitter behaviors unique to certain devices originating from imperfect hardware manufacturing processes. In particular, the carrier frequency offset (CFO), induced due to the local oscillator mismatch between the transmitter and receiver pair, has exhibited good detection capabilities in stationary and low-mobility transmission scenarios. It is still unclear, however, how the CFO detection capability would hold up in more dynamic time-varying channels where there is a higher mobility. This paper experimentally demonstrates the identification accuracy of CFO for wireless devices in time-varying channels. To this end, a software-defined radio (SDR) testbed is deployed to collect CFO values in real environments, where real transmission and reception are conducted in a vehicular setup. The collected CFO values are used to train machine-learning (ML) classifiers to be used for device identification. While CFO exhibits good detection performance (97% accuracy) for low-mobility scenarios, it is found that higher mobility (35 miles/h) degrades (72% accuracy) the effectiveness of CFO in distinguishing between legitimate and non-legitimate transmitters. This is due to the impact of the time-varying channel on the quality of the exchanged pilot signals used for CFO detection at the receivers. [ABSTRACT FROM AUTHOR]

The platooning of cars and trucks is a pertinent approach for autonomous driving due to the effective utilization of roadways. The decreased gas consumption levels are an added merit owing to sustainability. Conventional platooning depended on Dedicated Short-Range Communication (DSRC)-based vehicle-to-vehicle communications. The computations were executed by the platoon members with their constrained capabilities. The advent of 5G has favored Intelligent Transportation Systems (ITS) to adopt Multi-access Edge Computing (MEC) in platooning paradigms by offloading the computational tasks to the edge server. In this research, vital parameters in vehicular platooning systems, viz. latency-sensitive radio resource management schemes, and Age of Information (AoI) are investigated. In addition, the delivery rates of Cooperative Awareness Messages (CAM) that ensure expeditious reception of safety-critical messages at the roadside units (RSU) are also examined. However, for latency-sensitive applications like vehicular networks, it is essential to address multiple and correlated objectives. To solve such objectives effectively and simultaneously, the Multi-Agent Deep Deterministic Policy Gradient (MADDPG) framework necessitates a better and more sophisticated model to enhance its ability. In this paper, a novel Cascaded MADDPG framework, CMADDPG, is proposed to train cascaded target critics, which aims at achieving expected rewards through the collaborative conduct of agents. The estimation bias phenomenon, which hinders a system's overall performance, is vividly circumvented in this cascaded algorithm. Eventually, experimental analysis also demonstrates the potential of the proposed algorithm by evaluating the convergence factor, which stabilizes quickly with minimum distortions, and reliable CAM message dissemination with 99 % probability. The average AoI quantity is maintained within the 5–10 ms range, guaranteeing better QoS. This technique has proven its robustness in decentralized resource allocation against channel uncertainties caused by higher mobility in the environment. Most importantly, the performance of the proposed algorithm remains unaffected by increasing platoon size and leading channel uncertainties. [ABSTRACT FROM AUTHOR]

Mycelium-based composites (MBCs) exhibit varied properties as alternative biodegradable materials that can be used in various industries such as construction, furniture, household goods, and packaging. However, these properties are primarily influenced by the type of substrate used. This study aims to investigate the properties of MBCs produced from Lentinus sajor-caju strain CMU-NK0427 using different ratios of sawdust to corn husk in the development of mycelium composite boards (MCBs) with thicknesses of 8, 16, and 24 mm. The results indicate that variations in the ratios of corn husk to sawdust and thickness affected the mechanical and physical properties of the obtained MCBs. Reducing the corn husk content in the substrate increased the modulus of elasticity, density, and thermal conductivity, while increasing the corn husk content increased the bending strength, shrinkage, water absorption, and volumetric swelling. Additionally, an increase in thickness with the same substrate ratio only indicated an increase in density and shrinkage. MCBs have sound absorption properties ranging from 61 to 94% at a frequency of 1000 Hz. According to the correlation results, a reduction in corn husk content in the substrate has a significant positive effect on the reduction in bending strength, shrinkage, and water absorption in MCBs. However, a decrease in corn husk content shows a strong negative correlation with the increase in the modulus of elasticity, density, and thermal conductivity. The thickness of MCBs with the same substrate ratio only shows a significant negative correlation with the modulus of elasticity and bending strength. Compared to commercial boards, the mechanical (bending strength) and physical (density, thermal conductivity, and sound absorption) properties of MCBs made from a 100% corn husk ratio are most similar to those of softboards and acoustic boards. The results of this study can provide valuable information for the production of MCBs and will serve as a guide to enhance strategies for further improving their properties for commercial manufacturing, as well as fulfilling the long-term goal of eco-friendly recycling of lignocellulosic substrates. [ABSTRACT FROM AUTHOR]

Objective: Assessment of the middle cerebral artery (MCA) peak systolic velocity (PSV) can accurately diagnose fetal anemia and has decreased the number of invasive procedures, such as amniocentesis and cordocentesis. The objective of this investigation was to evaluate the intraobserver and interobserver variability as a measure of reproducibility of MCA PSV. The technique of correctly sampling this vessel is described., Methods: The study population included 30 appropriate-for-gestational-age fetuses. In each fetus, MCA PSV was determined proximal to the transducer at 3 different locations: 2 mm after its origin from the internal carotid artery, at the midlength between its origin and division, and at its division. The peak systolic velocity was also determined at the contralateral MCA 2 mm after its origin. With each measurement (obtained at 2 different institutions), care was taken to ensure that the ultrasound beam was parallel to the artery for its entire length. The reliability of an angle corrector was also assessed. The intraobserver and interobserver reliabilities were determined from the appropriate version of the intraclass correlation., Results: Gestational age at study entry ranged from 14 to 37.5 weeks (median, 23.6 weeks). The proximal MCA, 2 mm after its origin from the internal carotid artery, had the best intraobserver and interobserver variability in both institutions. (Intraclass correlation ranged from 0.98 to 0.99.), Conclusions: Our data indicate that fetal MCA PSV is optimally measured soon after the MCA's origin from the internal carotid artery. Given the importance of clinical decision making based on this measurement, sonographers and sonologists interested in measuring MCA PSV should test their variability after a suitable period of training.

Purpose of Review: The purpose of this review is to summarize recently published studies on noninvasive diagnosis of fetal anemia in order to give recommendations for the use of these new tools., Recent Findings: Red cell alloimmunization remains one of the most common causes of fetal anemia. Amniocentesis and cordocentesis have been used for many years to diagnose fetal anemia due to red cell aloimmunization. These techniques, however, are invasive and many complications are associated with their use. Noninvasive diagnosis of fetal anemia has been performed with Doppler ultrasonography. Based on robust data, several authors recommend the use of middle cerebral artery peak systolic velocity in the management of fetuses at risk for anemia because of red cell alloimmunization. This Doppler parameter can also diagnose fetal anemia due to other conditions., Summary: Middle cerebral artery peak systolic velocity appears to be the best test for the noninvasive diagnosis of fetal anemia. It is important to emphasize that training of sonographers and sonologists is the 'conditio sine qua non' for the correct sampling of the middle cerebral artery.

Background: Orofacial clefts are one of the most common congenital malformations of the fetal face and ultrasound is mainly responsible for its diagnosis. It is difficult to view the fetal palate, so there is currently no unified standard for fetal palate screening, and the diagnosis of cleft palate is not included in the relevant prenatal ultrasound screening guidelines. Many prenatal diagnoses for cleft palate are missed due to the lack of effective screening methods. Therefore, it is imperative to increase the display rate of the fetal palate, which would improve the detection rate and diagnostic accuracy for cleft palate. We aim to introduce a fetal palate screening software based on the "sequential sector scan though the oral fissure", an effective method for fetal palate screening which was verified by our follow up results and three-dimensional ultrasound and to evaluate its feasibility and clinical practicability. Methods: A software was designed and programmed based on "sequential sector scan through the oral fissure" and three-dimensional ultrasound. The three-dimensional ultrasound volume data of the fetal face were imported into the software. Then, the median sagittal plane was taken as the reference interface, the anterior upper margin of the mandibular alveolar bone was selected as the fulcrum, the interval angles, and the number of layers of the sector scan were set, after which the automatic scan was performed. Thus, the sector scan sequential planes of the mandibular alveolar bone, pharynx, soft palate, hard palate, and maxillary alveolar bone were obtained in sequence to display and evaluate the palate. In addition, the feasibility and accuracy of the software in fetal palate displaying and screening was evaluated by actual clinical cases. Results: Full views of the normal fetal palates and the defective parts of the cleft palates were displayed, and relatively clear sequential tomographic images and continuous dynamic videos were formed after the three-dimensional volume data of 10 normal fetal palates and 10 cleft palates were imported into the software. Conclusions: The software can display fetal palates more directly which might allow for a new method of fetal palate screening and cleft palate diagnosis. [ABSTRACT FROM AUTHOR]

In the pursuit of string stability within CACC (cooperative adaptive cruise control) platoons, prevalent research has favored constant time gap (CTG) spacing policies; namely, vehicle interspacing increases linearly with the speed. Although constant distance gap (CDG) spacing policies have greater potential to enhance traffic capacity, they suffer from notable limitations regarding string stability and diminished safety margins at high velocities. In our previous work, we proposed applying CDG in specific scenarios, such as starting platoons at signalized intersections, where traffic throughput is critical and safety requirements can be met due to relatively low speeds. We demonstrated the substantial potential of CDG to increase the capacity of signalized intersections under oversaturated conditions. However, our study also revealed potential performance drops of CDG in dense traffic networks. To address these issues, we propose close-range coordination between vehicles to (1) limit platoon length, (2) create gaps for merging, and (3) avoid entering intersections when there is a high likelihood of stopping within the intersection area. In this paper, we extend our previous work by implementing these three measures. We successfully evaluate their positive impact on CDG's performance in entire traffic systems through large-scale traffic simulations involving several thousand vehicles, thereby affirming our earlier hypothesis [ABSTRACT FROM AUTHOR]

Fifth-generation (5G) mobile networks offer flexibility to address various emerging use cases. Radio virtualization enhances flexibility by enabling multiple heterogeneous virtual radios to coexist on the same hardware. One method for virtualizing radio devices involves using virtual machines and containers to multiplex software radio implementations over generic multipurpose radio hardware. This paper reviews security issues in this context, evaluates the experimental bounds of communication for software-defined radio (SDR) devices, and assesses virtualization's impact on radio virtualization's performance. This study aims to determine the suitability of virtual environments for SDR applications. The results indicate that container-based radio virtualization performance is comparable to SDR applications running on native Linux. [ABSTRACT FROM AUTHOR]

Alite(C3S)-Ye'elimite(C4A3$) cement is a high cementitious material that incorporates a precise proportion of ye'elimite into the ordinary Portland cement. The synthesis and hydration behavior of Alite-Ye'elimite clinker with different lime saturation factors were investigated. The clinkers were synthesized using a secondary thermal treatment process, and their compositions were characterized. The hydrated pastes were analyzed for their hydration products, pore structure, mechanical strength, and microstructure. The clinkers and hydration products were characterized using XRD, TG-DSC, SEM, and MIP analysis. The results showed that the Alite-Ye'elimite cement clinker with a lime saturation factor (KH) of 0.93, prepared through secondary heat treatment, contained 64.88% C3S and 2.06% C4A3$. At this composition, the Alite-Ye'elimite cement clinker demonstrated the highest 28-day strength. The addition of SO3 to the clinkers decreased the content of tricalcium aluminate (C3A) and the ratio of Alite/Belite (C3S/C2S), resulting in a preference for belite formation. The pore structure of the hydrated pastes was also investigated, revealing a distribution of pore sizes ranging from 0.01 to 10 μm, with two peaks on each differential distribution curve corresponding to micron and sub-micron pores. The pore volume decreased from 0.22 ± 0.03 to 0.15 ± 0.18 cm3 g−1, and the main peak of pore distribution shifted towards smaller sizes with increasing hydration time. [ABSTRACT FROM AUTHOR]

The recent advancements in autonomous driving come with the associated cybersecurity issue of compromising networks of autonomous vehicles (AVs), motivating the use of AI models for detecting anomalies on these networks. In this context, the usage of explainable AI (XAI) for explaining the behavior of these anomaly detection AI models is crucial. This work introduces a comprehensive framework to assess black-box XAI techniques for anomaly detection within AVs, facilitating the examination of both global and local XAI methods to elucidate the decisions made by XAI techniques that explain the behavior of AI models classifying anomalous AV behavior. By considering six evaluation metrics (descriptive accuracy, sparsity, stability, efficiency, robustness, and completeness), the framework evaluates two well-known black-box XAI techniques, SHAP and LIME, involving applying XAI techniques to identify primary features crucial for anomaly classification, followed by extensive experiments assessing SHAP and LIME across the six metrics using two prevalent autonomous driving datasets, VeReMi and Sensor. This study advances the deployment of black-box XAI methods for real-world anomaly detection in autonomous driving systems, contributing valuable insights into the strengths and limitations of current black-box XAI methods within this critical domain. [ABSTRACT FROM AUTHOR]

This paper provides a detailed literature review of the environmental implications of vehicle platooning, a topic gaining significant attention in transportation. While previous reviews have focused on the safety, planning, fuel economy, and microsimulation aspects of platooning, this paper delves into environmental aspects. It identifies a lack of research adopting a holistic approach to transport and environmental benefits and emphasizes the need for further research to enhance vehicle efficiency and improve air quality and health conditions. This study traces the historical evolution of platooning, highlighting the shift in research focus over the decades. It advocates for more research on platooning's environmental aspects, particularly pollutant emissions and air quality. The primary contributions of this work are threefold and include the following: firstly, it delineates simulation methodologies for platooning and the associated pollutant emissions; secondly, it offers a critical assessment of the existing literature on vehicle emissions, fuel consumption, and energy savings; and thirdly, it illuminates the prospective research challenges within the specialized domain of vehicle platooning. [ABSTRACT FROM AUTHOR]

Public transportation systems, including trams and buses, play a crucial role in urban traffic. However, these traditional modes of transport have some well-known drawbacks, such as long distances between stops, lengthy waiting times, and a lack of privacy. In response to these challenges, an innovative mobility concept called "FLAIT-train" offers potential solutions. The FLAIT-train operates on regular roads and aims to provide DOOR-2-DOOR transport, addressing the issues associated with fixed stops and offering increased accessibility and convenience. In its initial phase, the FLAIT-train operates on exclusive lanes, but it is designed to integrate with other traffic eventually. The vehicle technology of FLAIT-trains closely resembles that of battery electric autonomous vehicles. To assess whether FLAIT-trains can be used as a suitable alternative to conventional public transportation systems, this paper employs traffic simulations that consider key performance indicators, including the average waiting time per passenger, maximum waiting time of a single passenger, average in-vehicle time per passenger, and average occupancy rate of the vehicles. Using SUMO software ("Simulation of Urban Mobility", version 1.12.0), a night bus service scenario is meticulously designed and generated. Within this scenario, both FLAIT-trains and conventional buses are simulated under identical conditions and based on statistical data. [ABSTRACT FROM AUTHOR]

Vehicular Ad hoc Networks (VANETs) have become prominent in the past few years for the transportation sector. Vehicular mobility poses a significant challenge for establishing private communications in VANETs. The classical Ad hoc On-Demand Distance Vector (AODV) routing protocol used in VANET assumes that all nodes are non-malicious. To address this matter, this paper proposes making AODV routing protocols more secure by using a privacy scheme in AODV for vehicle-to-vehicle communication. The AODV privacy scheme tries to keep the automobile network connected reliably and stably during communication with the secured transmission of messages and minimize the risk of unauthorized access to sensitive information from eavesdropper attacks. The proposed privacy secure AODV routing named PSAODV used pseudonym changes in vehicle communication to hide the target vehicle's location. A VANET simulator based on OMNET++ and SUMO are used for evaluating the PSAODV routing protocol. A simulation study was conducted that compared the PSAODV with SE-AOMDV, ECC-AODV, and AODV in fundamentals of efficiency and confidentiality. The analysis results showed that PSAODV routing demonstrates routing efficiency with privacy by diminishing the effect of eavesdropping of vehicles information based on various scenarios in urban cities. [ABSTRACT FROM AUTHOR]

Microbial transmission from mother to infant is important for offspring microbiome formation and health. However, it is unclear whether maternal gut inflammation (MGI) during lactation influences mother-to-infant microbial transmission and offspring microbiota and disease susceptibility. In this study, it is found that MGI during lactation altered the gut microbiota of suckling pups by shaping the maternal microbiota in the gut and mammary glands. MGI-induced changes in the gut microbiota of suckling pups lasted into adulthood, resulting in the exacerbation of acute liver failure (ALF) caused by acetaminophen (APAP) in offspring. Specifically, MGI reduced the abundance of Lactobacillus reuteri (L. reuteri) and its metabolite indole-3-acetic acid (IAA) level in adult offspring. L. reuteri and IAA alleviated ALF in mice by promoting intestinal IL-22 production. Mechanistically, IL-22 limits APAP-induced excessive oxidative stress and ferroptosis by activating STAT3. The intestinal abundances of L. reuteri and IAA are inversely associated with the progression of patients with ALF. Overall, the study reveals the role of MGI in mother-to-infant microbial transmission and disease development in offspring, highlighting potential strategies for intervention in ALF based on the IAA-IL-22-STAT3 axis., (© 2025 The Author(s). Advanced Science published by Wiley‐VCH GmbH.)

Ensuring pedestrian safety is one of the most significant challenges for autonomous driving systems in urban scenarios due to the non-cooperative and unpredictable nature of pedestrian movements. To tackle this problem, firstly, we propose a collision avoidance strategy based on entropy-increasing risk perception in a vehicle–pedestrian reaction space. Our approach combines a limited range of reaction space regions with entropy to quantify the risk of pedestrian–vehicle collision. Then, multi-vehicle candidate trajectories are generated using the path and speed sequence method, and the uncertain states of pedestrians are predicted based on the social force model and Markov model accordingly. Finally, to determine the optimal collision avoidance trajectory, we use quantitative reaction-space entropy as a new "cost function" to measure potential risk and perform multi-objective trajectory optimization based on the elitist non-dominated-sorting genetic algorithm region-focused (NSGA-RF) approach. Simulation results show that our proposed strategy can enhance the safety of the planned trajectory interaction between vehicles and pedestrians for autonomous driving under normal and emergency conditions. [ABSTRACT FROM AUTHOR]

Despite modern antiseptic techniques, surgical site infection (SSI) remains a leading complication of surgery. However, the origins of SSI and the high rates of antimicrobial resistance observed in these infections are poorly understood. Using instrumented spine surgery as a model of clean (class I) skin incision, we prospectively sampled preoperative microbiomes and postoperative SSI isolates in a cohort of 204 patients. Combining multiple forms of genomic analysis, we correlated the identity, anatomic distribution, and antimicrobial resistance profiles of SSI pathogens with those of preoperative strains obtained from the patient skin microbiome. We found that 86% of SSIs, comprising a broad range of bacterial species, originated endogenously from preoperative strains, with no evidence of common source infection among a superset of 1610 patients. Most SSI isolates (59%) were resistant to the prophylactic antibiotic administered during surgery, and their resistance phenotypes correlated with the patient's preoperative resistome (P = 0.0002). These findings indicate the need for SSI prevention strategies tailored to the preoperative microbiome and resistome present in individual patients. Editor's summary: Despite enhanced sterility procedures, surgical site infections can still occur after surgery. To examine why, Long et al. compared the microbes found in surgical site infections with the endogenous microbiome at the to-be surgical location of those same patients before spine surgery. Genomic analysis of these pre- and postoperative strains showed no evidence of between-patient pathogen transfer. Rather, for most individuals, the bacteria responsible for the surgical site infection, along with any antibiotic resistance genes circumventing the chosen prophylactic antibiotic, were likely already present on the patient's own skin before the first incision. These findings suggest a need for alternative antiseptic strategies. —Catherine Charneski [ABSTRACT FROM AUTHOR]

In the present paper, we propose a method for controlling the interval of safety message transmissions in a fully distributed manner that maximizes the number of successful transmissions to vehicles located a set target distance away. In the proposed method, each vehicle estimates the density of vehicles in its vicinity, and, based on the estimated vehicle density, each vehicle calculates an optimal message transmission interval in order to maximize the number of successful message transmissions to vehicles located a set target distance away. The optimal message transmission interval can be analytically obtained as a simple expression when it is assumed that the vehicles are positioned according to a two-dimensional Poisson point process, which is appropriate for downtown scenarios. In addition, we propose two different methods for a vehicle by which to estimate the density of other vehicles in its vicinity. The first method is based on the measured channel busy ratio, and the second method relies on counting the number of distinct IDs of vehicles in the vicinity. We validate the effectiveness of the proposed methods using several simulations. [ABSTRACT FROM AUTHOR]

The reliability of V2X (vehicle-to-everything) communication is important for safe automated driving. With the advances in wireless communication and multipath transport protocols, a vehicle can employ multiple wireless interfaces and carry out multipath communication. Although there has been extensive research into increasing the Quality of Service (QoS) performance, such as throughput and delay in V2X communication, few studies have addressed explicit ways of improving the reliability of vehicle-to-cloud (V2C) communication through multipath-based redundancy. This paper addresses the issue of improving V2C reliably via multipath-based packet duplication, with particular consideration given to redundancy mitigation. We propose a method that employs dynamic adjustment of multipath redundancy to maintain packet-delivery reliability in V2C communication while enabling redundancy mitigation. The evaluation results show that the proposed method allows the vehicle to maintain the desired reliability in terms of successful packet transmission while reducing redundancy caused by packet duplication in a multipath connection. [ABSTRACT FROM AUTHOR]

Introduction: Chemotherapy during pregnancy can increase the risk of fetal anemia. Severe fetal anemia can lead to the development of hydrops fetalis and potentially fetal demise. Hence, it is imperative to implement consistent monitoring methods in the context of chemotherapy treatment. This study aimed to diagnose and monitor fetal anemia using middle cerebral artery peak systolic velocity (MCA‐PSV) as a diagnostic tool during chemotherapy in pregnant women. Material and methods: The study employed a prospective analysis involving a case series of 15 patients diagnosed with cancer during pregnancy and subsequently underwent chemotherapy. MCA‐PSV was used to identify fetal anemia. The patients were scheduled for ultrasound examinations of the MCA‐PSV. The first examination was performed on the same day as the administration of chemotherapy, while the second occurred on the 10th day after chemotherapy. The measurement technique used in the study was based on the methodology proposed by Mari and Barr. The multiples of the median were calculated using the calculators provided by Medicina Fetal Barcelona. Based on these values anemia severity was determined. When moderate or severe anemia was identified, chemotherapy was individually modified. Additionally, a blood count analysis was conducted immediately after the delivery of the newborn. Results: Five patients were diagnosed with fetal or newborn anemia. With MCA‐PSV, we identified moderate fetal anemia in two patients and severe fetal anemia in one. The complete blood count testing of newborns revealed mild anemia in three patients. One case was unrelated to chemotherapy‐induced anemia. During treatment, fetal anemia did not corelate with maternal anemia. Conclusions: In four cases of anemia the combination of cisplatin and iphosphamide was used as a chemotherapy agent. No anemia was observed in other drug combinations. Our findings suggest that MCA‐PSV is a reliable method for identifying anemia and should be included in the treatment protocol for chemotherapy‐induced fetal anemia. [ABSTRACT FROM AUTHOR]

Cement, as a construction material, has low thermal resistance, inherent fire resistance, and is incombustible up to a certain degree. However, the loss of its mechanical performance and spalling are its primary issues, and it thus cannot retain its performance in refractory applications. The present study explores the performance of geopolymer formulations that have excellent fire resistance properties for potential refractory applications. This study is unique, as it investigates advanced solid geopolymer formulations that need only water to activate and bind. Various solid geopolymer formulations with fly ash as a precursor; potassium hydroxide and potassium silicate as activators; and mullite and alumina as refractory aggregates were studied for their compressive strength at up to 1100 °C and compared with their two-part conventional liquid alkaline geopolymer counterparts. Advanced solid geopolymer formulations with mullite and alumina as refractory aggregates had mechanical strength values of 84 MPa and 64 MPa post-1100 °C exposure and were further exposed to ten thermal cycles of 1100 °C to study their fatigue resistance and post-exposure compressive strengths. The geopolymer sample with mullite as a refractory aggregate yielded 115.2 MPa compressive strength after the fourth cycle of exposure. This sample was also studied for its temperature distribution upon direct flame exposure. All the geopolymer formulations displayed a drop in compressive strength at 600 °C due to viscous sintering and then a rise in strength at 1100 °C due to phase transformation. X-ray diffraction studies revealed that the formation of crystalline phases such as leucite, sanidine, and annite were responsible for the superior strengths at 1100 °C for the alumina- and mullite-based geopolymer formulations. [ABSTRACT FROM AUTHOR]

In vehicle ad hoc networks (VANETs), a beacon is a periodic message sent to nearby vehicles containing essential details like the sender's vehicle ID, location, speed, and direction. Maintaining the freshness of this information without causing network congestion requires adaptive beaconing to adjust to changes in mobility and network density. Our research, based on extensive simulation experiments, identifies specific parameter sets optimal for adapting beaconing rates to different scenarios. From this analysis, we introduce a novel scheme called high-awareness and channel-efficient adaptive beaconing (HACEAB), employing fuzzy logic to adapt to various environments and conditions. Initially, the protocol gauges network density using an adaptive threshold function, followed by estimating the node spatial distribution through the quadrat statistic method to discern uniform distribution or clustering. Utilizing these data, the protocol adjusts beaconing rates via appropriate input parameters for the fuzzy logic system. Remarkably, HACEAB represents the first beaconing scheme capable of simultaneously adjusting to changes in network density and spatial distribution. Furthermore, the protocol enhances performance by adapting transmission power to fluctuations in node density and distribution. NS-3 simulations validate the efficacy of these improvements. [ABSTRACT FROM AUTHOR]

Copyright of Automobile Technology is the property of Automobile Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Chlorobenzene (CB) and Chloronaphthalene (CN) emissions from cement plant operations pose significant environmental risks. This study investigates the mass transfer effects of chlorinated aromatic Volatile Organic Compounds (VOCs), specifically CB and CN, in the gas phase of a continuous-tangential-flow annular photocatalytic reactor. The experiments involved introducing CB and CN into the reactor, and the degradation kinetics were analyzed using the Langmuir–Hinshelwood (L-H) model. The L-H model was applied to assess the impact of the flow rate, concentration, and relative humidity (% RH) on the degradation rate (DR). The results indicate that both the experimental and simulated degradation rates improved with increased flow rates (1 to 9 m3·h−1) and inlet concentrations (30 to 216 mg·m−3). This enhancement of the DR correlates with the availability of active OH* species on the TiO2 surface. The L-H model emphasizes the role of H2O molecules in VOC removal kinetics. The degradation rates increased with a rising water content (5 to 55%), but adverse effects on VOC conversion were observed beyond a 55% RH. This study reveals a mass transfer effect, with internal diffusional limitations in the TiO2 pores under operational conditions. The kinetics were predominantly controlled by chemical kinetics and catalyst pore availability. Furthermore, this study demonstrates a higher CB degradation than CN in the reactor and experimental conditions. For a concentration of 1.328 mM·m−3, the CB DR ranged from 0.70 to 2.84 µM·m2·s−1, as the flow rate varied from 1 to 9 m3·h−1. The CN DR varied from 0.60 to 2.20 µM·m2·s−1 within the same flow rate range. [ABSTRACT FROM AUTHOR]

The Intelligent transport systems (ITS) have evolved with the Internet of Vehicles (IoV) and the growth of advanced wireless technology associated with billions of smart devices connected to Internet. The rapidly evolving use of the Internet of Things (IoT) has led to significant growth in VANETs have transformed the traditional VANET topology into an Internet of vehicles (IoV),an improving road safety and automatic traffic monitoring to reduce issues related to traffic congestion. However, the security risk is expanding due to VANET communications' dependence on resources such as computing as well as a lack of standards due to rapidly evolving technologies. Existing methods have proposed very limited protections in using a single pseudonym or invalidating the trust scheme that anonymous attackers can easily compromise. During vehicular communication, messages in VANET might be associated with reliability since the transaction of messages in vehicular communication needs to be comprehensive enough and secure enough to withstand the security threats by achieving trustworthiness transmission of the dynamic pseudonyms trust model (DPTM). Conversely, the severe challenge is to protect information exchange between vehicles because some malicious nodes might perform as Man-in-the-Middle (MiTM) network attackers due to dishonest vehicles in VANET. The increasing trustworthiness between nodes can thus lead to an increase in VANET's trustworthy sharing of knowledge, privacy, security, accuracy, and authenticity. In this paper, we proposed a dynamic trust-based model in the term of dynamic pseudonyms changing scheme that first identify the honest vehicles as nodes to broadcast messages to normal vehicles on the road and secondly change their pseudonyms in only some specific zone to identify the dishonest nodes for protection assurance in the State of MiTM and Sybil attacks. Furthermore, it has addressed the use of pseudonym schemes for privacy and security requirements. All VANET nodes have built the trust given initially by the various RSUs and servers, trusted communication in the network. The experiment was performed based on various network scenarios to assess the accuracy and efficacy of the dynamic trust-based model. We have extensively evaluated performance measures of the F-Score, Recall, and Precision indices to demonstrate that the proposed model has outperformed the MARINE and PPARTM models already reported. The experimental results have verified the proposed lightweight model for certifying the recognized trust level of 40% of MiTM attackers with an F-Score of 95% compared to the MARINE model's highest recognized detection of 90%. [ABSTRACT FROM AUTHOR]

Connected vehicles (CVs) are an emerging technology in intelligent transportation systems. Currently, many data-driven intelligent transportation systems (D2ITS) use CV data. Unfortunately, these D2ITS still need serious improvement before they meet higher-level visualization needs. Thus, we aim to develop a new, intelligent data-driven transportation system framework. We focus on visualizing real-time CV data using a big data analytic system in urban areas. In response, we first propose an effective real-time data distribution approach within the Vehicular Ad-hoc NETwork. Second, we develop novel strategies for aggregating, extracting and ingesting data. We provide scalable and fault-tolerant delivery methods without interruption or delay. Finally, we proposed a novel visualization REpresentational State Transfer (REST) web service. We used Simulation of Urban MObility, OMNET++ and Veins to simulate a traffic incident dataset. Then, we tested the Basic Safety Messages in an experimental big data cluster. We used NIFI, Kafka and Cassandra for ingestion, distribution, delivery and storage. The results show accurate performance for packet loss, packet delivery and communication delay. Also, it indicates high throughput and low latency for distributed data delivery systems. Additionally, we obtained the smallest response time for the RESTFUL visualization web service. [ABSTRACT FROM AUTHOR]

As an environmentally responsible alternative to conventional concrete, geopolymer concrete recycles previously used resources to prepare the cementitious component of the product. The challenging issue with employing geopolymer concrete in the building business is the absence of a standard mix design. According to the chemical composition of its components, this work proposes a thorough system or framework for estimating the compressive strength of fly ash-based geopolymer concrete (FAGC). It could be possible to construct a system for predicting the compressive strength of FAGC using soft computing methods, thereby avoiding the requirement for time-consuming and expensive experimental tests. A complete database of 162 compressive strength datasets was gathered from the research papers that were published between the years 2000 and 2020 and prepared to develop proposed models. To address the relationships between inputs and output variables, long short-term memory networks were deployed. Notably, the proposed model was examined using several soft computing methods. The modeling process incorporated 17 variables that affect the CSFAG, such as percentage of SiO2 (SiO2), percentage of Na2O (Na2O), percentage of CaO (CaO), percentage of Al2O3 (Al2O3), percentage of Fe2O3 (Fe2O3), fly ash (FA), coarse aggregate (CAgg), fine aggregate (FAgg), Sodium Hydroxide solution (SH), Sodium Silicate solution (SS), extra water (EW), superplasticizer (SP), SH concentration, percentage of SiO2 in SS, percentage of Na2O in SS, curing time, curing temperature that the proposed model was examined to several soft computing methods such as multi-layer perception neural network (MLPNN), Bayesian regularized neural network (BRNN), generalized feed-forward neural networks (GFNN), support vector regression (SVR), decision tree (DT), random forest (RF), and LSTM. Three main innovations of this study are using the LSTM model for predicting FAGC, optimizing the LSTM model by a new evolutionary algorithm called the marine predators algorithm (MPA), and considering the six new inputs in the modeling process, such as aggregate to total mass ratio, fine aggregate to total aggregate mass ratio, FASiO2:Al2O3 molar ratio, FA SiO2:Fe2O3 molar ratio, AA Na2O:SiO2 molar ratio, and the sum of SiO2, Al2O3, and Fe2O3 percent in FA. The performance capacity of LSTM-MPA was evaluated with other artificial intelligence models. The results indicate that the R2 and RMSE values for the proposed LSTM-MPA model were as follows: MLPNN (R2 = 0.896, RMSE = 3.745), BRNN (R2 = 0.931, RMSE = 2.785), GFFNN (R2 = 0.926, RMSE = 2.926), SVR-L (R2 = 0.921, RMSE = 3.017), SVR-P (R2 = 0.920, RMSE = 3.291), SVR-S (R2 = 0.934, RMSE = 2.823), SVR-RBF (R2 = 0.916, RMSE = 3.114), DT (R2 = 0.934, RMSE = 2.711), RF (R2 = 0.938, RMSE = 2.892), LSTM (R2 = 0.9725, RMSE = 1.7816), LSTM-MPA (R2 = 0.9940, RMSE = 0.8332), and LSTM-PSO (R2 = 0.9804, RMSE = 1.5221). Therefore, the proposed LSTM-MPA model can be employed as a reliable and accurate model for predicting CSFAG. Noteworthy, the results demonstrated the significance and influence of fly ash and sodium silicate solution chemical compositions on the compressive strength of FAGC. These variables could adequately present variations in the best mix designs discovered in earlier investigations. The suggested approach may also save time and money by accurately estimating the compressive strength of FAGC with low calcium content. [ABSTRACT FROM AUTHOR]

The Internet of Vehicles (IoV) is a technology that is connected to the public internet and is a subnetwork of the Internet of Things (IoT) in which vehicles with sensors are connected to a mobile and wireless network. Numerous vehicles, users, things, and networks allow nodes to communicate information with their surroundings via various communication channels. IoV aims to enhance the comfort of driving, improve energy management, secure data transmission, and prevent road accidents. Despite IoV's advantages, it comes with its own set of challenges, particularly in the highly important aspects of security and trust. Trust management is one of the potential security mechanisms aimed at increasing reliability in IoV environments. Protecting IoV environments from diverse attacks poses significant challenges, prompting researchers to explore various technologies for security solutions and trust evaluation methods. Traditional approaches have been employed, but innovative solutions are imperative. Amid these challenges, machine learning (ML) has emerged as a potent solution, leveraging its remarkable advancements to effectively address IoV's security and trust concerns. ML can potentially be utilized as a powerful technology to address security and trust issues in IoV environments. In this survey, we delve into an overview of IoV and trust management, discussing security requirements, challenges, and attacks. Additionally, we introduce a classification scheme for ML techniques and survey ML-based security and trust management schemes. This research provides an overview for understanding IoV and the potential of ML in improving its security framework. Additionally, it provides insights into the future of trust and security enhancement. [ABSTRACT FROM AUTHOR]