Background The COMET-CTO trial was a randomized prospective study that assessed long-term follow-up in patients with chronic total occlusion (CTO) in coronary arteries treated with percutaneous coronary intervention (PCI) or with optimal medical therapy (OMT). During the 9-month follow-up, the incidence of major adverse cardiac events (MACE) did not differ between the two groups; no death or myocardial infarction (MI) was observed. There was a significant difference in quality of life (QoL), assessed by the Seattle Angina Questionnaire (SAQ), in favor of the PCI group. Here we report long-term follow-up results (56 ± 12 months). Methods Between October 2015 and May 2017, a total of 100 patients with CTO were randomized into two groups of 50 patients: PCI CTO or OMT group. The primary endpoint of the current study was the incidence of MACE defined as cardiac death, MI, and revascularization [PCI or coronary artery bypass graft (CABG)]. As the secondary exploratory outcome, we analyzed all the cause-mortality rate. Results Out of 100 randomized patients, 92 were available for long-term follow-up (44 in the PCI group and 48 in the OMT group). The incidence of MACE did not differ significantly between the two groups (p = 0.363). Individual components of MACE were distributed, respectively: cardiac death (OMT vs. PCI group, 6 vs. 3, p = 0.489), MI (OMT vs. PCI group, 1 vs. 0, p = 1), and revascularization (PCI: OMT vs. PCI group, 2 vs. 2, p = 1; CABG: OMT vs. PCI group, 1 vs. 1, p = 1). There was no significant difference between the two groups regarding the individual component of MACE. Six patients died from non-cardiac causes [five deaths were reported in the OMT group and one death in the PCI group (p = 0.206)]. Kaplan-Meier survival curves for MACE did not differ significantly between the study groups (log-rank 0.804, p = 0.370). Regarding the secondary exploratory outcome, a total of 15 patients died at 56 ± 12 months (11 in the OMT and 4 in the PCI group) (p = 0.093). The Kaplan-Meier survival curves for all-cause mortality rates did not differ significantly between the two groups (log rank 3.404, p = 0.065). There were no statistically significant differences between OMT and PCI groups in all five SAQ domains. There was a significant improvement in three SAQ domains in the PCI group: PL (p < 0.001), AF (p = 0.007), and QoL (p = 0.001). Conclusion After 56 ± 12 months of follow-up, the incidence of MACE, as well as QoL measured by SAQ, did not differ significantly between the PCI and OMT groups.

A search for nonresonant Higgs boson pair production in the $b\bar{b}b\bar{b}$ final state is presented. The analysis uses 126 fb$^{-1}$ of $pp$ collision data at $\sqrt{s}={13}$ TeV collected with the ATLAS detector at the Large Hadron Collider, and targets both the gluon-gluon fusion and vector-boson fusion production modes. No evidence of the signal is found and the observed (expected) upper limit on the cross-section for nonresonant Higgs boson pair production is determined to be 5.4 (8.1) times the Standard Model predicted cross-section at 95% confidence level. Constraints are placed on modifiers to the $HHH$ and $HHVV$ couplings. The observed (expected) $2\sigma$ constraints on the $HHH$ coupling modifier, $\kappa_\lambda$, are determined to be $[-3.5, 11.3]$ ($[-5.4, 11.4]$), while the corresponding constraints for the $HHVV$ coupling modifier, $\kappa_{2V}$, are $[-0.0, 2.1]$ ($[-0.1, 2.1]$). In addition, constraints on relevant coefficients are derived in the context of the Standard Model effective field theory and Higgs effective field theory, and upper limits on the $HH$ production cross-section are placed in seven Higgs effective field theory benchmark scenarios.

For an integer $r\ge 2$, the space of $r$-immersions of $M$ in $\mathbb R^n$ is defined to be the space of immersions of $M$ in $\mathbb R^n$ such that at most $r-1$ points of $M$ are mapped to the same point in $\mathbb R^n$. The space of $r$-immersions lies"between"the embeddings and the immersions. We calculate the connectivity of the layers in the homological Taylor tower for the space of $r$-immersions in $\mathbb R^n$ (modulo immersions), and give conditions that guarantee that the connectivity of the maps in the tower approaches infinity as one goes up the tower. We also compare the homological tower with the homotopical tower, and show that up to degree $2r-1$ there is a"Hurewicz isomorphism"between the first non-trivial homotopy groups of the layers of the two towers.

Despite the success of neural-based combinatorial optimization methods for end-to-end heuristic learning, out-of-distribution generalization remains a challenge. In this paper, we present a novel formulation of Combinatorial Optimization Problems (COPs) as Markov Decision Processes (MDPs) that effectively leverages common symmetries of COPs to improve out-of-distribution robustness. Starting from a direct MDP formulation of a constructive method, we introduce a generic way to reduce the state space, based on Bisimulation Quotienting (BQ) in MDPs. Then, for COPs with a recursive nature, we specialize the bisimulation and show how the reduced state exploits the symmetries of these problems and facilitates MDP solving. Our approach is principled and we prove that an optimal policy for the proposed BQ-MDP actually solves the associated COPs. We illustrate our approach on five classical problems: the Euclidean and Asymmetric Traveling Salesman, Capacitated Vehicle Routing, Orienteering and Knapsack Problems. Furthermore, for each problem, we introduce a simple attention-based policy network for the BQ-MDPs, which we train by imitation of (near) optimal solutions of small instances from a single distribution. We obtain new state-of-the-art results for the five COPs on both synthetic and realistic benchmarks. Notably, in contrast to most existing neural approaches, our learned policies show excellent generalization performance to much larger instances than seen during training, without any additional search procedure.

The shipping sector has become one of the corner-stone aspects of modern production systems, which has been impacting economic growth over the past decades. Its digitalization is expected to make significant improvements in ship control safety and reliability by enabling autonomous operations. Nonetheless, there are still many challenges that need to be thoroughly studied, and in this paper, we focus on one of them, i.e., the communication between barges, ports, and services, as the increased network latency and the limitations on the bandwidth imposed by satellite communications could result in significant risks for accident occurrence. Thus, we present one of the first attempts to leverage the potential of 5G systems for automating barge operations, starting from teleoperation as an enabler of automation, toward creating and validating a cellular-based automated barge control system in a real-life environment.

Vehicular Edge Computing (VEC) brings cloud infrastructure to the vehicular edge, resulting in better performances and avoiding network congestions. In this work-in-progress paper, the benefits of edge computing over cloud computing are discussed in a vehicular environment context, and they are leveraged by creating a Cooperative, Connected and Automated Mobility (CCAM) performance measurement framework. This measurement tool can follow vehicles by moving across different devices, enabling measurements on Key Performance Indicators (KPIs) using edge computing. We already used this tool to evaluate latencies of both a stationary and driving vehicle, moving over the Smart Highway testbed in Antwerp, Belgium. When driving, smart-edge-following algorithms can be deployed to choose the nearest Road Side Unit (RSU) using broadcasted Cooperative Awareness Messages (CAMs) of the vehicle. While driving on the Smart Highway, the application monitors important performance metrics such as throughput, latency, packet loss, packet delivery rate and more. We compare short-range vehicular communications technologies on the Smart Highway (ITS-G5 and LTE-V2X PC5) against the cellular. Our preliminary results demonstrate the benefits in terms of latency by using short-range communications technologies in VEC applications. These results validate that moving applications to the edge is truly beneficial, since our results confirmed up to 90% lower latency using ITS-G5, up to 50% using LTE-V2X PC5. Future deployments of 5G in the Smart Highway are planned, which would further improve the performance edge computing technologies.

To properly orchestrate challenging services such as those deployed for Vehicle-to-Everything (V2X) use cases, MANO systems need to be intelligent and automated. Network Function Virtualization (NFV) and Machine Learning (ML) provide opportunities for automating MANO operations, and this paper presents our MI-enhAnced Edge Service orchesTRatiOn (MAESTRO) algorithm that makes proactive ML-driven decisions for edge service relocation to ensure Quality of Service (QoS) guarantees for V2X services. Moreover, to validate the effectiveness of our proposed solution, we have performed the experimentation using real-life testbeds for high computing and smart mobility i.e., Smart Highway and Virtual Wall, located in Antwerp and Gent, Belgium. The contribution of our paper is two-fold: i) we study the interrelation between the Key Performance Indicators (KPIs) measured at the vehicle client side, and the infrastructure metrics at the edge computing nodes and ii) we propose and evaluate an ML-based quality-aware algorithm that automates edge service orchestration to decrease average latency while guaranteeing high service availability and reliability.

Vehicular communication is a core technology of Intelligent Transportation Systems (ITS). Vehicle-to-vehicle (V2V) communication still needs to develop resilience, such that communication is safe and efficient, in time-critical applications. The radio-based systems, such as cellular V2X (C-V2X) and Dedicated Short Range Communication (DSRC), which are used classically for vehicular communication suffer from performance degradation in traffic scenarios where traffic is dense. In recent years, Line of Sight (LoS) technologies such as Visible Light Communication (VLC) are considered complementary technology to Radio Frequency (RF). VLC utilizes the light-emitting diodes (LEDs) headlamps and tail lights that are standard on modern vehicles to exchange information with the predecessor and subsequent vehicle. This work-in-progress paper highlights the need to combine RF and LoS technologies to improve the stability and reliability of $V2 V$ communication. Therefore, we discuss the different LoS and RF technologies, and we present the combinations that can be used for communication. Finally, we propose a hybrid strategy that combines the best properties of individual technologies.

Premature ventricular complex (PVC) is a frequent finding in the general population. The atrial conduction time (ACT) is the period between the electrocardiographic P wave and the atrial mechanical contraction, and its prolongation indicates an atrial electromechanical delay (EMD). In our study, we compared atrial conduction parameters by echocardiographic methods between patients with frequent PVC and healthy control subjects.

Self-powered sensors are gaining a lot of attention in recent years due to their possible application in the Internet of Things, medical implants and wireless and wearable devices. Human breath detection has applications in diagnostics, medical therapy and metabolism monitoring. One possible approach for breath monitoring is detecting the humidity in exhaled air. Here, we present an extremely sensitive, self-powered sensor for breath humidity monitoring. As a power source, the sensor uses electromagnetic energy harvested from the environment. Even electromagnetic energy harvested from the human body is enough for the operation of this sensor. The signal obtained using the human body as a source was up to 100 mV with an estimated power of 1 nW. The relatively low amount of energy that could be harvested in this way was producing a signal that was modulated by an interdigitated capacitor made out of electrochemically activated aluminum. The signal obtained in this way was rectified by a set of Schottky diodes and measured by a voltmeter. The sensor was capable of following a variety of different respiration patterns during normal breathing, exercise and rest, at the same time powered only by electromagnetic energy harvested from the human body. Everything happened in the normal environment used for everyday work and life, without any additional sources, and at a safe level of electromagnetic radiation.

Background Cigarette use is one of the major risk factors for non-communicable diseases in Bosnia and Herzegovina, with 41.1% of adults being current smokers in 2019 and almost half of current smokers using more than 20 cigarettes per day. Methods This study applies the prevalence-based, cost-of-illness approach to estimate the annual economic cost of smoking in Bosnia and Herzegovina in 2019. Results The study estimates that cigarette use by adults in Bosnia and Herzegovina caused between 24.4% and 42.8% of all deaths in 2019 and a total economic cost of between €367.5 and €635.1 million (2.0%–3.5% of gross domestic product). The direct costs represent the largest share of the total cost (between 1.0% and 1.7% of gross domestic product). Conclusion Cigarette use imposes a significant health and economic burden in the society of Bosnia and Herzegovina. Various tobacco control measures can be implemented to prevent and reduce tobacco consumption and the negative health consequences of tobacco use. Numerous studies have shown taxes on tobacco products are very effective in reducing tobacco use, especially among certain demographic groups, such as youth and low-income individuals. Smoke-free laws have also shown benefits. Other policy measures that can be implemented include restrictions to advertising, limitations on who can purchase tobacco products, how and where they can be purchased, etc. In addition, governments could also implement various education programmes on the negative health consequences of smoking. The results of this study provide information that calls for prompt and strengthened implementation of tobacco control measures to reduce cigarette consumption in the country and improve the health outcomes and productivity of its inhabitants.

Minarets are slender and tall structures that are built from different types of materials. Modern materials are also starting to be used in such structures with the recent developments in material technology. The seismic vulnerability and dynamic behavior of minarets can vary, depending on the material characteristics. Within this study’s scope, thirteen different material types used in minarets in Türkiye were chosen as variables. A sample minaret model was chosen as an example with nine different heights to reveal how material characteristic change affects seismic and dynamic behavior. Information and mechanical characteristics were given for all the material types. Natural fundamental periods, displacements, and base shear forces were attained from structural analyses for each selected material. The empirical period formula for each material is proposed using the obtained periods, depending on the different minaret heights taken into consideration. At the same time, fundamental natural periods for the first ten modes and 13 different types of materials used in the study were estimated with the established Artificial Neural Network (ANN) model. The real periods from the experimental analyses were compared with the values estimated by the ANN using fewer parameters, and 99% of the results were successful. In addition, time history analyses were used to evaluate the seismic performance of the minaret (three different materials were considered). In this specific case, the acceleration record from the 2011 Van (Eastern Turkiye) earthquake (Mw = 7.2) was taken into consideration. Performance levels were determined for the minaret according to the results obtained for each material. It has been concluded that material characteristics significantly affect the dynamic and seismic behavior of the minarets.

BACKGROUND: Heat-not-burn (HNB) technology by the U.S. Food and Drug Administration has been classified as a modified risk tobacco product, which can be a better option for those populations who cannot give up the habit of smoking. The outlook on the effects of these products is quite controversial in the scientific world. OBJECTIVE: To present the effect of HNB tobacco products on the cardiovascular system, with reference to the existence of possible benefits of the technology. METHODS: The literature search was conducted in PubMed/Medline, the Cochrane Central Register of Controlled Trials (CENTRAL), and ClinicalTrials.gov databases, with reliance on a well-defined guiding research statement. Quality appraisal was performed using the CASP checklist for randomized controlled trials. RESULTS: The search of three databases identified 167 records, and after selection process, 25 randomized controlled trials were eligible for our study’s criteria. Twenty studies investigated the effects of HNB products on biomarkers of clinical relevance. Five studies evaluated other functional heart parameters rather than biomarkers. CONCLUSION: With HNB tobacco products, significant reductions were found in biomarkers of exposure and biological effect related to pathways involved in cardiovascular disease, including inflammation, oxidative stress, lipid metabolism, platelet function, and endothelial dysfunction.