In-hospital outcomes of ad hoc versus planned PCI for unprotected left-main disease: An analysis of 8574 cases from British Cardiovascular Intervention Society database 2006-2018.

BACKGROUND: Although data suggests ad hoc percutaneous coronary intervention (PCI) results in similar patient outcomes compared to planned PCI in nonselected patients, data for ad hoc unprotected left main stem PCI (uLMS-PCI) are lacking. AIM: To determine if in-hospital outcomes of uLMS-PCI vary by ad hoc versus planned basis. METHODS: Data were analyzed from all patients undergoing uLMS-PCI in the United Kingdom 2006-2018, and patients grouped into uLMS-PCI undertaken on an ad hoc or a planned basis. Patients who presented with ST-segment elevation, cardiogenic shock, or with an emergency PCI indication were excluded. RESULTS: In total, 8574 uLMS-PCI procedures were undertaken with 2837 (33.1%) of procedures performed on an ad hoc basis. There was a lower likelihood of intervention for stable angina (28.8% vs. 53.8%, p < 0.001) and a higher rate of potent P2Y12 inhibitor use (16.4% vs. 12.1%, p < 0.001) in the ad hoc PCI group compared to the planned PCI group. Patients undergoing uLMS-PCI on an ad hoc basis tended to undergo less complex procedures. Acute procedural complications including slow flow (odds ratio [OR]: 1.70, 95% confidence interval [CI]: 1.01-2.86), coronary dissection (OR: 1.41, 95% CI: 1.12-1.77) and shock induction (OR: 2.80, 95% CI: 1.64-4.78) were more likely in the ad hoc PCI group. In-hospital death (OR: 1.65, 95% CI: 1.19-2.27) and in-hospital major adverse cardiac or cerebrovascular events (OR: 1.50, 95% CI: 1.13-1.98) occurred more frequently in the ad hoc group. In sensitivity analyses, these observations did not differ when several subgroups were separately examined. CONCLUSIONS: Ad hoc PCI for uLMS disease is associated with adverse outcomes compared to planned PCI. These data should inform uLMS-PCI procedural planning.

New Approach Methodologies (NAMs) for ad hoc human health risk assessment of food and non-food products - Proceedings of a workshop.

RIVM convened a workshop on the use of New Approach Methodologies (NAMs) for the ad hoc human health risk assessment of food and non-food products. Central to the workshop were two case studies of marketed products with a potential health concern: the botanical Tabernanthe iboga which is used to facilitate mental or spiritual insight or to (illegally) treat drug addiction and is associated with cardiotoxicity, and dermal creams containing female sex hormones, intended for use by perimenopausal women to reduce menopause symptoms without medical supervision. The workshop participants recognized that data from NAM approaches added valuable information for the ad hoc risk assessment of these products, although the available approaches were inadequate to derive health-based guidance values. Recommendations were provided on how to further enhance and implement NAM approaches in regulatory risk assessment, specifying both scientific and technical aspects as well as stakeholder engagement aspects.

ReLoki: A Light-Weight Relative Localization System Based on UWB Antenna Arrays.

Ultra Wide-Band (UWB) sensing has gained popularity in relative localization applications. Many localization solutions rely on using Time of Flight (ToF) sensing based on a beacon-tag system, which requires four or more beacons in the environment for 3D localization. A lesser researched option is using Angle of Arrival (AoA) readings obtained from UWB antenna pairs to perform relative localization. In this paper, we present a UWB platform called ReLoki that can be used for ranging and AoA-based relative localization in 3D. To enable AoA, ReLoki utilizes the geometry of antenna arrays. In this paper, we present a system design for localization estimates using a Regular Tetrahedral Array (RTA), Regular Orthogonal Array (ROA), and Uniform Square Array (USA). The use of a multi-antenna array enables fully onboard infrastructure-free relative localization between participating ReLoki modules. We also present studies demonstrating sub-50cm localization errors in indoor experiments, achieving performance close to current ToF-based systems, while offering the advantage of not relying on static infrastructure.

Internet of Vehicles (IoV)-Based Task Scheduling Approach Using Fuzzy Logic Technique in Fog Computing Enables Vehicular Ad Hoc Network (VANET).

The intelligent transportation system (ITS) relies heavily on the vehicular ad hoc network (VANET) and the internet of vehicles (IoVs), which combine cloud and fog to improve task processing capabilities. As a cloud extension, the fog processes' infrastructure is close to VANET, fostering an environment favorable to smart cars with IT equipment and effective task management oversight. Vehicle processing power, bandwidth, time, and high-speed mobility are all limited in VANET. It is critical to satisfy the vehicles' requirements for minimal latency and fast reaction times while offloading duties to the fog layer. We proposed a fuzzy logic-based task scheduling system in VANET to minimize latency and improve the enhanced response time when offloading tasks in the IoV. The proposed method effectively transfers workloads to the fog computing layer while considering the constrained resources of car nodes. After choosing a suitable processing unit, the algorithm sends the job and its associated resources to the fog layer. The dataset is related to crisp values for fog computing for system utilization, latency, and task deadline time for over 5000 values. The task execution, latency, deadline of task, storage, CPU, and bandwidth utilizations are used for fuzzy set values. We proved the effectiveness of our proposed task scheduling framework via simulation tests, outperforming current algorithms in terms of task ratio by 13%, decreasing average turnaround time by 9%, minimizing makespan time by 15%, and effectively overcoming average latency time within the network parameters. The proposed technique shows better results and responses than previous techniques by scheduling the tasks toward fog layers with less response time and minimizing the overall time from task submission to completion.

Integrated Sensing and Secure Communication with XL-MIMO.

This paper studies extremely large-scale multiple-input multiple-output (XL-MIMO)-empowered integrated sensing and secure communication systems, where both the radar targets and the communication user are located within the near-field region of the transmitter. The radar targets, being untrusted entities, have the potential to intercept the confidential messages intended for the communication user. In this context, we investigate the near-field beam-focusing design, aiming to maximize the achievable secrecy rate for the communication user while satisfying the transmit beampattern gain requirements for the radar targets. We address the corresponding globally optimal non-convex optimization problem by employing a semidefinite relaxation-based two-stage procedure. Additionally, we provide a sub-optimal solution to reduce complexity. Numerical results demonstrate that beam focusing enables the attainment of a positive secrecy rate, even when the radar targets and communication user align along the same angle direction.

Routing Selection Algorithm for Mobile Ad Hoc Networks Based on Neighbor Node Density.

In the process of data transmission in mobile ad hoc networks, it is essential to establish optimal routes from source nodes to destination nodes. However, as network density increases, this process is often accompanied by a significant rise in network overhead. To address this issue, the ND-AODV (neighborhood density AODV) protocol has been introduced, which reduces the probability of transmitting control information in high-density node environments to mitigate network overhead. Nevertheless, this may come at the cost of reduced routing accuracy, potentially leading to unnecessary resource wastage in certain scenarios. Furthermore, ND-AODV does not comprehensively consider the location of the receiving nodes, which limits its ability to reduce network overhead effectively. To overcome these limitations, this paper introduces a novel routing approach, known as CND-AODV (common neighborhood density AODV). In comparison to ND-AODV, CND-AODV offers a more comprehensive solution to the challenges posed by high-density network environments. It intelligently processes control information based on the special positioning of the receiving nodes, thereby significantly reducing unnecessary network overhead. Through simulation experiments comparing performance metrics such as throughput, packet delivery rate, and latency, the results clearly indicate that CND-AODV substantially decreases network overhead, enhancing network performance. Compared to ND-AODV, this innovative routing approach exhibits significant advantages. It provides a more efficient and reliable solution for ad hoc networks in high-density environments.

Ad Hoc Mesh Network Localization Using Ultra-Wideband for Mobile Robotics.

This article explores the implementation of high-accuracy GPS-denied ad hoc localization. Little research exists on ad hoc ultra-wideband-enabled localization systems with mobile and stationary nodes. This work aims to demonstrate the localization of bicycle-modeled robots in a non-static environment through a mesh network of mobile, stationary robots, and ultra-wideband sensors. The non-static environment adds a layer of complexity when actors can enter and exit the node's field of view. The method starts with an initial localization step where each unmanned ground vehicle (UGV) uses the surrounding, available anchors to derive an initial local or, if possible, global position estimate. The initial localization uses a simplified implementation of the iterative multi-iteration ad hoc localization system (AHLos). This estimate was refined using an unscented Kalman filter (UKF) following a constant turn rate and velocity magnitude model (CTRV). The UKF then fuses the robot's odometry and the range measurements from the Decawave ultra-wideband receivers stationed on the network nodes. Through this position estimation stage, the robot broadcasts its estimated position to its neighbors to help the others further improve their localization estimates and localize themselves. This wave-like cycle of nodes helping to localize each other allows the network to act as a mobile ad hoc localization network.

Delay-Oriented Roadside Unit Deployment for Highway Intersections in Vehicular Ad Hoc Networks.

Optimizing the deployment of roadside units (RSUs) holds great potential for enhancing the delay performance of vehicular ad hoc networks. However, there has been limited focus on devising RSU deployment strategies tailored specifically for highway intersections. In this study, we introduce a novel probabilistic model to characterize events occurring around highway intersections. By leveraging this model, we analytically determine the expected event reporting delays for both highway segments and intersections. Subsequently, we propose an RSU deployment scheme specifically designed for highway intersections, aimed at minimizing the expected event reporting delay. To implement this scheme, we introduce an innovative algorithm named cooperative walking. Through illustrative examples, we demonstrate that our proposed RSU deployment strategy for highway intersections outperforms the commonly employed uniform RSU deployment scheme and the previously proposed balloon method in terms of delay performance.

A Novel Framed Slotted Aloha Medium Access Control Protocol Based on Capture Effect in Vehicular Ad Hoc Networks.

The capture effect is a frequently observed phenomenon in vehicular ad hoc networks (VANETs) communication. When conflicts arise during time slot access, failure to access does not necessarily occur; instead, successful access may still be achieved. The capture effect can enhance the likelihood of multiple access and improve communication efficiency. The security of VANETs communication is undoubtedly the primary concern. One crucial approach to enhance security involves the design of an efficient and reliable medium access control (MAC) protocol. Taking into account both aspects, we propose a novel framed slotted Aloha (FSA) MAC protocol model. Firstly, we derive the closed-form expression for the capture probability in the Rician fading channel in this paper. Subsequently, we analyze how the number of vehicles and time slots influence the success probability of vehicle access channels as well as examine the impact of the capture effect on this success probability. Then, under constraints regarding vehicle access channel success probability, we derive optimal values for slot numbers, access times, and transmission power while proposing a comprehensive implementation method to ensure high access channel success probabilities. We verify both theoretical derivations and proposed methods through simulation experiments.

An Adaptive 3D Neighbor Discovery and Tracking Algorithm in Battlefield Flying Ad Hoc Networks with Directional Antennas.

Neighbor discovery and tracking with directional antennas in flying ad hoc networks (FANETs) is a challenging issue because of dispersed node distribution and irregular maneuvers in three-dimensional (3D) space. In this paper, we propose an adaptive 3D neighbor discovery and tracking algorithm in battlefield FANETs with directional antennas. With time synchronization, a flying node transmits/receives the neighbor discovery packets sequentially in each beam around it to execute a two-way handshake for neighbor discovery. The transmitting or receiving status of each discovery slot depends on the binary code corresponding to the identification of the node. Discovered neighbor nodes exchange their 3D positions in tracking slots periodically for node tracking, and the maximum tracking period is determined by node velocity, beamwidth, and the minimum distance between nodes. By configuring the relevant parameters, the proposed algorithm can also apply to two-dimensional planar ad hoc networks. The simulation results suggest that the proposed algorithm can achieve shorter neighbor discovery time and longer link survival time in comparison with the random scanning algorithm in scenarios with narrow beamwidth and wide moving area. When the frame length increases, the protocol overhead decreases but the average neighbor discovery time increases. The suitable frame length should be determined based on the network range, node count, beamwidth, and node mobility characteristics.

Dual-Slope Path Loss Model for Integrating Vehicular Sensing Applications in Urban and Suburban Environments.

The development of intelligent transportation systems (ITS), vehicular ad hoc networks (VANETs), and autonomous driving (AD) has progressed rapidly in recent years, driven by artificial intelligence (AI), the internet of things (IoT), and their integration with dedicated short-range communications (DSRC) systems and fifth-generation (5G) networks. This has led to improved mobility conditions in different road propagation environments: urban, suburban, rural, and highway. The use of these communication technologies has enabled drivers and pedestrians to be more aware of the need to improve their behavior and decision making in adverse traffic conditions by sharing information from cameras, radars, and sensors widely deployed in vehicles and road infrastructure. However, wireless data transmission in VANETs is affected by the specific conditions of the propagation environment, weather, terrain, traffic density, and frequency bands used. In this paper, we characterize the path loss based on the extensive measurement campaign carrier out in vehicular environments at 700 MHz and 5.9 GHz under realistic road traffic conditions. From a linear dual-slope path loss propagation model, the results of the path loss exponents and the standard deviations of the shadowing are reported. This study focused on three different environments, i.e., urban with high traffic density (U-HD), urban with moderate/low traffic density (U-LD), and suburban (SU). The results presented here can be easily incorporated into VANET simulators to develop, evaluate, and validate new protocols and system architecture configurations under more realistic propagation conditions.

Predictivism and avoidance of ad hoc-ness: An empirical study.

Predictivism is the thesis that evidence successfully predicted by a scientific theory counts more (or ought to count more) in the confirmation of that theory than already known evidence would. One rationale that has been proposed for predictivism is that predictive success guards against ad hoc hypotheses. Despite the intuitive attraction of predictivism, there is historical evidence that speaks against it. As valuable as the historical evidence may be, however, it is largely indirect evidence for the epistemic attitudes of individual - albeit prominent - scientists. This paper presents the results of an empirical study of scientists' attitudes toward predictivism and ad hoc-ness (n = 492), which will put the debate on a more robust empirical footing. The paper also draws attention to a tension between the ad hoc-ness avoidance rationale of predictivism and the ways philosophers have spelled out the notion of ad hoc-ness.

A clustering approach for attack detection and data transmission in vehicular ad-hoc networks.

Vehicular ad-hoc networks (VANETs) are increasingly pivotal for empowering applications in smart cities and intelligent traffic systems. However, the reliability and stability of VANET communications face formidable obstacles. Natura 2000 (N2k), the largest globally coordinated network of protected areas, has drawn significant criticism for its conservation-centric management structure lacking a strategic vision. This study proposes a three-phase strategy to address these concerns, aiming for effective and sustainable N2K site management. The novel approach employs DNN-Assisted Canonical Correlation Analysis (DNN-CCAS), encompassing cluster formation, cluster head selection, and outbreak recognition for enhanced VANET security. Vehicle clustering begins with an amended K-consonance method, emphasizing both position and speed through AKCEM clustering. A cluster head is chosen via a linear measure promenade approach, followed by secure data transmission to the cloud using DNN-CCAS if the cluster head is deemed normal. The proposed method outperforms prevailing techniques, achieving an impressive 91% accuracy. This comprehensive strategy not only addresses VANET communication challenges but also aims to revolutionize the management of N2K sites by integrating a strategic vision into conservation practices.

Faculty Decision Making in Ad Hoc Entrustment of Pediatric Critical Care Fellows: A National Case-Based Survey.

Phenomenon: Ad hoc entrustment decisions reflect a clinical supervisor's estimation of the amount of supervision a trainee needs to successfully complete a task in the moment. These decisions have important consequences for patient safety, trainee learning, and preparation for independent practice. Determinants of these decisions have previously been described but have not been well described for acute care contexts such as critical care and emergency medicine. The ad hoc entrustment of trainees caring for vulnerable patient populations is a high-stakes decision that may differ from other contexts. Critically ill patients and children are vulnerable patient populations, making the ad hoc entrustment of a pediatric critical care medicine (PCCM) fellow a particularly high-stakes decision. This study sought to characterize how ad hoc entrustment decisions are made for PCCM fellows through faculty ratings of vignettes. The authors investigated how acuity, relationship, training level, and task interact to influence ad hoc entrustment decisions. Approach: A survey containing 16 vignettes that varied by four traits (acuity, relationship, training level, and task) was distributed to U.S. faculty of pediatric critical care fellowships in 2020. Respondents determined an entrustment level for each case and provided demographic data. Entrustment ratings were dichotomized by "high entrustment" versus "low entrustment" (direct supervision or observation only). The authors used logistic regression to evaluate the individual and interactive effects of the four traits on dichotomized entrustment ratings. Findings: One hundred seventy-eight respondents from 30 institutions completed the survey (44% institutional response rate). Acuity, relationship, and task all significantly influenced the entrustment level selected but did not interact. Faculty most frequently selected "direct supervision" as the entrustment level for vignettes, including for 24% of vignettes describing fellows in their final year of training. Faculty rated the majority of vignettes (61%) as "low entrustment." There was no relationship between faculty or institutional demographics and the entrustment level selected. Insights: As has been found in summative entrustment for pediatrics, internal medicine, and surgery trainees, PCCM fellows often rated at or below the "direct supervision" level of ad hoc entrustment. This may relate to declining opportunities to practice procedures, a culture of low trust propensity among the specialty, and/or variation in interpretation of entrustment scales.

BBSF: Blockchain-Based Secure Weather Forecasting Information through Routing Protocol in Vanet.

A vehicular ad hoc network (VANET) is a technique that uses vehicles with the ability to sense data from the environment and use it for their safety measures. Flooding is a commonly used term used for sending network packets. VANET may cause redundancy, delay, collision, and the incorrect receipt of the messages to their destination. Weather information is one of the most important types of information used for network control and provides an enhanced version of the network simulation environments. The network traffic delay and packet losses are the main problems identified inside the network. In this research, we propose a routing protocol which can transmit the weather forecasting information on demand based on source vehicle to destination vehicles, with the minimum number of hop counts, and provide significant control over network performance parameters. We propose a BBSF-based routing approach. The proposed technique effectively enhances the routing information and provides the secure and reliable service delivery of the network performance. The results taken from the network are based on hop count, network latency, network overhead, and packet delivery ratio. The results effectively show that the proposed technique is reliable in reducing the network latency, and that the hop count is minimized when transferring the weather information.

Research on Routing Algorithm of Construction Robot Cluster Enhanced Ad Hoc Network.

An enhanced self-assembling network routing algorithm is proposed for the problem of weak connectivity of communication networks caused by factors such as movement or environmental interference in the construction and operation, and the maintenance of construction robot clusters. Firstly, the dynamic forwarding probability is calculated based on the contribution of nodes joining routing paths to network connectivity, and the robust connectivity of the network is achieved by introducing the connectivity feedback mechanism; secondly, the influence of link quality evaluation index Q balanced hop count, residual energy, and load on link stability is used to select appropriate neighbors for nodes as the subsequent hop nodes; finally, the dynamic characteristics of nodes are combined with the topology control technology to eliminate low-quality links and optimize the topology by link maintenance time prediction and to set robot node priority. The simulation results show that the proposed algorithm can guarantee a network connectivity rate above 97% under heavy load, reduce the end-to-end delay, and improve the network survival time, providing a theoretical basis for achieving stable and reliable interconnection between building robot nodes.

Multiple Precaching Vehicle Selection Scheme Based on Set Ranking in Intermittently Connected Vehicular Networks.

In vehicular networks, vehicles download vehicular information for various applications, including safety, convenience, entertainment, and social interaction, from the corresponding content servers via stationary roadside units. Since sufficient RSUs might be difficult to deploy due to rough geographical conditions or high deployment costs, vehicular networks can feature uncovered outage zones between two neighboring RSUs. In these outage zones, vehicles cannot download content, and thus the vehicle networks are defined as intermittently connected vehicular networks. In intermittently connected vehicular networks, the download delay and traffic overhead on the backhaul links are increased due to the large size of the content requested by vehicle users and the long distances between RSUs. Using the mobility information of vehicles, several schemes have been proposed to solve this issue by precaching and relaying content via multiple relaying vehicles in the outage zone. However, because they involved the individual ranking of vehicles for precaching and allocated all of the available precaching amounts to the top-ranking vehicles, they decreased the success rate of content requests and the fairness of vehicle precaching. To overcome the problem of these previous schemes, this paper proposes a multiple precaching vehicle selection (MPVS) scheme that efficiently selects a content-precaching vehicle group with multiple precaching vehicles to precache relayed content in outage zones. To achieve this, we first designed numerical models to decide the necessity and the amount of precaching and to calculate the available precaching amounts of vehicles. Next, MPVS calculates all available vehicle sets and ranks each set based on the available precaching amount. Then, the content-precaching vehicle group is identified from the sets by considering both set rankings and vehicle communication overheads. MPVS also provides a content downloading process through the content-precaching vehicle group in the outage zone. Simulation results conducted in various environments with a content request model and a highway mobility model verified that MPVS was superior to a representative previous scheme.

A Deep-Learning-Based Secure Routing Protocol to Avoid Blackhole Attacks in VANETs.

Vehicle ad hoc networks (VANETs) are a vital part of intelligent transportation systems (ITS), offering a variety of advantages from reduced traffic to increased road safety. Despite their benefits, VANETs remain vulnerable to various security threats, including severe blackhole attacks. In this paper, we propose a deep-learning-based secure routing (DLSR) protocol using a deep-learning-based clustering (DLC) protocol to establish a secure route against blackhole attacks. The main features and contributions of this paper are as follows. First, the DLSR protocol utilizes deep learning (DL) at each node to choose secure routing or normal routing while establishing secure routes. Additionally, we can identify the behavior of malicious nodes to determine the best possible next hop based on its fitness function value. Second, the DLC protocol is considered an underlying structure to enhance connectivity between nodes and reduce control overhead. Third, we design a deep neural network (DNN) model to optimize the fitness function in both DLSR and DLC protocols. The DLSR protocol considers parameters such as remaining energy, distance, and hop count, while the DLC protocol considers cosine similarity, cosine distance, and the node's remaining energy. Finally, from the performance results, we evaluate the performance of the proposed routing and clustering protocol in the viewpoints of packet delivery ratio, routing delay, control overhead, packet loss ratio, and number of packet losses. Additionally, we also exploit the impact of the mobility model such as reference point group mobility (RPGM) and random waypoint (RWP) on the network metrics.

Data Dissemination in VANETs Using Particle Swarm Optimization.

A vehicular Ad-Hoc Network (VANET) is a type of Mobile Ad-Hoc Networks (MANETs) that uses wireless routers inside each vehicle to act as a node. The need for effective solutions to urban traffic congestion issues has increased recently due to the growing number of automobile connections in the car communications system. To ensure a high level of service and avoid unsafe situations brought on by congestion or a broadcast storm, data dissemination in a VANET network requires an effective approach. Effective multi-objective optimization methods are required to tackle this because of the implied competing nature of multi-metric approaches. A meta-heuristic technique with a high level of solution interactions can handle efficient optimization. To accomplish this, a meta-heuristic search algorithm particle optimization was chosen. In this paper, we have created a network consisting of vehicles as nodes. The aim is to send emergency messages immediately to the stationary nodes. The normal messages will be sent to the FIFO queue. To send these messages to a destination node, multiple routes were found using Time delay-based Multipath Routing (TMR) method, and to find the optimal and secure path Particle Swarm Optimization (PSO) is used. Our method is compared with different optimization methods such as Ant Colony Optimization (ACO), Firefly Optimization (FFO), and Enhanced Flying Ant Colony Optimization (EFACO). Significant improvements in terms of throughput and packet loss ratio, reduced end-to-end delay, rounding overhead ratio, and the energy consumption are revealed by the experimental results.

Provably Secure Receiver-Unrestricted Group Key Management Scheme for Mobile Ad Hoc Networks.

Mobile ad hoc networks (MANETs) are self-configuring networks of wireless nodes, i.e., mobile devices. Since communications in MANETs occur via wireless channels, it is of significance to secure communications among wireless and mobile nodes. Group key management, as a widely used method for securing group communications, has potentially been used in MANETs for years. Most recently, a secure receiver-unrestricted group key management scheme for MANETs has been proposed, which is used to establish a secure channel among a group of wireless nodes without a trusted dealer, which has some advantages such as eliminating the certificate management problem and receiver restriction. However, a formal security analysis of this scheme is still lacking. Therefore, in this paper, we propose the complete security proof to demonstrate that the scheme satisfies the essential security properties including authentication, message confidentiality, known-key security and dynamic secrecy. We also give a brief discussion about the efficiency of the scheme.