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Introduction: Vaccination is mentioned as a most successful way of intervention in public health. Vaccination against other diseases is usually recommended for people with Human Immunodeficiency Virus (HIV/AIDS) infection. Purpose: To identify the correlation of vaccines and vaccination in patients suffering from HIV/AIDS infection. Methodology:This narrative review was based on the bibliographic search of reviews and research studies drawn from the international databases. The exclusion criterion of the articles was the language other than English and Greek. Results:HIV infection is characterized by severe immunodeficiency, which is the result of a decrease in the number of CD4+ T – lymphocytes. The right time to vaccinate a HIV patient is not precisely determined, but it is recommended for those with low CD4 values. All HIV patients are recommended to be vaccinated the annual vaccination of Influenza virus vaccination. It also is recommended to be vaccinated with the vaccination against human papillomavirus (HPV), the vaccination against hepatitis A virus (HAV) and hepatitis B virus (HBV), the vaccination against herpes zoster or shingles and the vaccination against COVID-19 infection. Conclusion:People with HIV/AIDS are more vulnerable to infections from various diseases. Therefore, it is necessary patients with HIV infection be vaccinated against life-threatening diseases.

Large-scale storage systems employ erasure-coding redundancy schemes to protect against device failures. The adverse effect of latent sector errors on the Mean Time to Data Loss (MTTDL) and the Expected Annual Fraction of Data Loss (EAFDL) reliability metrics is evaluated. A theoretical model capturing the effect of latent errors and device failures is developed, and closed-form expressions for the metrics of interest are derived. The MTTDL and EAFDL of erasure-coded systems are obtained analytically for (i) the entire range of bit error rates; (ii) the symmetric, clustered, and declustered data placement schemes; and (iii) arbitrary device failure and rebuild time distributions under network rebuild bandwidth constraints. The range of error rates that deteriorate system reliability is derived analytically. For realistic values of sector error rates, the results obtained demonstrate that MTTDL degrades, whereas, for moderate erasure codes, EAFDL remains practically unaffected. It is demonstrated that, in the range of typical sector error rates and for very powerful erasure codes, EAFDL degrades as well. It is also shown that the declustered data placement scheme offers superior reliability.

ZusammenfassungDie sekundäre Mitralinsuffizienz ist bei Patienten mit Herzinsuffizienz häufig und mit einem schlechten Verlauf assoziiert. Aufgrund des hohen OP-Risikos war die Therapie traditionell auf eine Behandlung der Herzinsuffizienz beschränkt. Die Entwicklung von kathetergestützten Techniken ermöglicht nun die Behandlung mit geringem Risiko. Wenngleich die Studienevidenz immer noch begrenzt ist, erfolgte in den aktuellen Leitlinien der europäischen Fachgesellschaften eine Aufwertung der kathetergestützten Therapie für ausgewählte Patienten mit hohem OP-Risiko und hoher Wahrscheinlichkeit für ein Therapieansprechen. Dennoch bleiben viele Fragen offen, was die Rolle der chirurgischen Behandlung und auch die Patientenselektion für kathetergestützte Therapieverfahren angeht. Hier beschreiben wir den aktuellen Stand der Behandlung der sekundären Mitralinsuffizienz und zeigen Strategien von transuniversitären Verbundprojekten mit dem Ziel, Evidenz für die Behandlung dieser Patienten zu entwickeln.

Part 1: Adaptive Modeling/Neuroscience; International audience; In this paper counterfactual thinking is addressed based on literature mainly from Neuroscience and Psychology. A detailed literature review was conducted in identifying processes, neural correlates and theories related to counterfactual thinking from different disciplines. A familiar scenario with respect to counterfactual thinking was identified. Based on the literature, an adaptive self-modeling network model was designed. This model captures the complex process of counterfactual thinking and the learning and control involved.

Right ventricular dysfunction (RVD), as expressed by right ventricular to pulmonary artery coupling, has recently been identified as a strong outcome predictor in patients undergoing mitral valve edge-to-edge repair (M-TEER) for secondary mitral regurgitation (MR). The aim of this study was to define RVD in patients undergoing M-TEER for primary MR (PMR) and to evaluate its impact on procedural MR reduction, symptomatic development and 2-year all-cause mortality.This multicentre study included patients undergoing M-TEER for symptomatic PMR at nine international centres. The study cohort was divided into a derivation (DC) and validation cohort (VC) for calculation and validation of the best discriminatory value for RVD. A total of 648 PMR patients were included in the study. DC and VC were comparable regarding procedural success and outcomes at follow-up. Sensitivity analysis identified RVD as an independent predictor for 2-year mortality in the DC (hazard ratio [HR] 2.37, 95% confidence interval [CI] 1.47-3.81, p 0.001), which was confirmed in the VC (HR 2.06, 95% CI 1.36-3.13, p 0.001). Procedural success (MR ≤2+) and symptomatic improvement at follow-up (New York Heart Association [NYHA] class ≤II) were lower in PMR patients with RVD (MR ≤2+: 82% vs. 93%, p = 0.002; NYHA class ≤II: 57.3% vs. 66.5%, p = 0.09 for with vs. without RVD). In all PMR patients, the presence of RVD significantly impaired 2-year survival after M-TEER (HR 2.23, 95% CI 1.63-3.05, p 0.001).Mitral valve edge-to-edge repair is an effective treatment option for PMR patients. The presence of RVD is associated with less MR reduction, less symptomatic improvement and increased 2-year mortality. Accordingly, RVD might be included into pre-procedural prognostic considerations.

Circular frame fixation remains a key tool in the armamentarium of the limb reconstruction surgeon. One of the key drawbacks is the onset of pin-site infection (PSI). As a result of limited evidence and consensus of PSI prevention, a wide variation in practice remains.The principal aim of this review is to synthesise primary research concerning all aspects of treatment regarded as relevant to PSI in frame constructs.Comparative studies until week 26, 2021, were included in the trial. Studies were included that concerned patients undergoing management of a musculoskeletal condition in which pin-site care is necessary for over 4 weeks.Eighteen studies over a 13-year period were captured using the search strategy. Sulphadiazine and hydrogen peroxide cleansing was found to reduce PSI, with the use of low-energy fine wires and hydroxyapatite (HA)-coated pins also associated with lower infection rate. The remainder of studies found no significant improvement across interventions.There is no superiority between weekly and daily care. Low-energy pin-insertion technique had lower rates of infection. Sulphadiazine has positive results as a pin-care solution, but more research is necessary to determine the most effective care regime. Current literature is limited by absence of established definitions and by a lack of studies addressing all aspects of care relevant to PSI.Shields DW, Iliadis AD, Kelly E

BACKGROUND: In patients with severe mitral regurgitation (MR) who are scheduled for transcatheter mitral valve repair (TMVR), risk stratification is predominantly based on surgical risk scores. AIMS: We sought to characterise and define stages of right heart remodelling in patients undergoing TMVR and evaluate the impact of this staging classification on survival. METHODS: According to echocardiographic parameters, 929 patients undergoing MitraClip treatment were classified into three stages: severe MR without right heart damage (stage 0), with moderate-to-severe tricuspid regurgitation (TR) (stage 1), with right ventricular dysfunction defined as a reduced fractional area change 25 cm(2) and/or indexed right ventricular volume >30 ml/m(2) (stage 2). We compared clinical outcomes and performed a multivariate analysis to evaluate the predictive value of the extent of cardiac damage. RESULTS: Rates of one-year all-cause mortality increased with more advanced stages of right heart remodelling (stage 0: 8% vs stage 1: 9.7% vs stage 2: 18.1%; p

Pursuing "intelligent justice" necessitates an impartial, productive, and technologically driven methodology for judicial determinations. This scholarly composition proposes a framework that harnesses Artificial Intelligence (AI) innovations such as Natural Language Processing (NLP), ChatGPT, ontological alignment, and the semantic web, in conjunction with blockchain and privacy techniques, to examine, deduce, and proffer recommendations for the administration of justice. Specifically, through the integration of blockchain technology, the system affords a secure and transparent infrastructure for the management of legal documentation and transactions while preserving data confidentiality. Privacy approaches, including differential privacy and homomorphic encryption techniques, are further employed to safeguard sensitive data and uphold discretion. The advantages of the suggested framework encompass heightened efficiency and expediency, diminished error propensity, a more uniform approach to judicial determinations, and augmented security and privacy. Additionally, by utilizing explainable AI methodologies, the ethical and legal ramifications of deploying intelligent algorithms and blockchain technologies within the legal domain are scrupulously contemplated, ensuring a secure, efficient, and transparent justice system that concurrently protects sensitive information upholds privacy.

This study investigates the interpretability of machine learning (ML) models applied to cumulative damage prediction during a sequence of earthquakes, emphasizing the use of techniques such as SHapley Additive exPlanations (SHAP), Partial Dependence Plots (PDPs), Local Interpretable Model-agnostic Explanations (LIME), Accumulated Local Effects (ALE), Permutation and Impurity-based technique. The research explores the cumulative damage during seismic sequences, aiming to identify critical predictors and assess their influence on the cumulative damage. Moreover, the predictors contribution in respect with the range of final damage is evaluated. Nonlinear time history analyses are applied to extract the seismic response of an eight-story Reinforced Concrete (RC) frame. The regression problem’s input variables are divided into two distinct physical classes: pre-existing damage from the initial seismic event and seismic parameters representing the intensity of the subsequent earthquake, expressed by Park and Ang damage index (DIPA) and Intensity Measures (IMs), respectively. The study offers a comprehensive review of cutting-edge ML methods, hyperparameter tuning, and ML method comparisons. A LightGBM model emerges as the most efficient, among 15 different ML methods examined, with critical predictors for final damage being the initial damage caused by the first shock and the IMs of the subsequent shock: IFVF and SIH. The importance of these predictors is supported by feature importance analysis and local/global explanation methods, enhancing the interpretability and practical utility of the developed model.

Conservative management of endometrial cancer (CMEC) is viable for women with early-stage disease wishing to preserve fertility, but there is poor knowledge regarding clinicians’ attitudes towards treatment or guidelines adherence. This 55-item survey study investigated CMEC-related experience, practice and attitudes among clinically active Swedish gynecologists and gynecological oncologists, focusing on reproductive eligibility criteria. The survey consisted of a general and two specific subsets, selectively delivered to clinicians active in infertility (subset A) and endometrial cancer (subset B) care. Answers from 218 clinicians were included. More than half agreed on CMEC whereas only 5% explicitly disagreed. The majority supported a fertility work-up to substantiate reasonable chances to pregnancy and live birth. Most disagreed about CMEC in case of previous unsuccessful fertility treatments, while more than 1/3 disagreed about CMEC in known fertility problems, recurrent miscarriages or previous children. Over 50% of respondents in subset A (n = 107) found it applicable with fertility investigations such as ovarian reserve testing or, in case of male partner, semen analysis. Respondents in subset B (n = 165) agreed on items based on existing recommendations regarding the oncological management of CMEC, including the use of continuous progestins, hysteroscopic resection of macroscopic lesions, control biopsy with curettage or hysteroscopy after 6 months of treatment, pursuing pregnancy as soon as possible after complete response, and performing a hysterectomy once live birth is achieved. While many clinicians were familiar with CMEC, the overall experience is limited. Fertility specialists seem less involved than oncologists in patient care but there is broad support for fertility-related eligibility criteria.

Both nonresonant and resonance reaction data are subject to laboratory electron screening effects. For nonresonant reactions, such effects are well documented and the measured cross sections can be corrected to find the unscreened ones. Frequently, the procedure and expression to calculate laboratory electron screening factors for nonresonant reactions are also applied to isolated narrow resonances, without much theoretical support or experimental evidence. A simple model is applied to estimate electron screening factors, lengths, and potentials for narrow resonances. The corrections to the measured data result in an enhancement of the unscreened resonance strengths by less than 0.2%, contrary to published narrow-resonance screening correction factors, which predict a reduction of the unscreened strengths by up to 25%. Unless it can be proven otherwise, it is recommended that measured strengths of isolated narrow resonances not be corrected for laboratory electron screening. The prospects of investigating laboratory electron screening effects by measuring almost negligible differences in resonance strengths are not promising. Instead, the difference of the resonance energy for the unscreened and screened situation may be measurable. As an example, the case of the E_cm = 956-keV resonance in the 27Al(p,gamma)28Si reaction is discussed. It is also demonstrated that the claim of a previously reported detection of a resonance near 800 keV in the 176Lu(p,n)176}Hf reaction is incorrect., 2 figures

An integrated method, which combines Electronic Speckle Pattern Interferometry, impulse response measurements, finite element method simulations, and psychoacoustic tests, is proposed to evaluate the vibroacoustic behavior of a carbon fiber bouzouki. Three of the carbon fiber instruments are manufactured, and one is qualified via interferometric experimental measurements with reference to a traditional wooden bouzouki, which was evaluated for its sound and playability by the proposed method. Psychoacoustic tests were used to evaluate the sound and playability of the newly qualified carbon fiber bouzouki, which was further modeled by the finite element method and simulated. The simulation results agreed well with the experimental measurements. Furthermore, finite element simulation results of the qualified carbon fiber bouzouki were demonstrated with reference to the traditional wooden bouzouki experimental results, providing new findings crucial for the optimization of the manufacturing and the vibroacoustic behavior of the carbon fiber instrument. The proposed integrated method can be applied to a variety of carbon fiber stringed musical instruments.

Aims: This international study aimed to assess: 1) the prevalence of preoperative and postoperative COVID-19 among patients with hip fracture, 2) the effect on 30-day mortality, and 3) clinical factors associated with the infection and with mortality in COVID-19-positive patients. Methods: A multicentre collaboration among 112 centres in 14 countries collected data on all patients presenting with a hip fracture between 1st March-31st May 2020. Demographics, residence, place of injury, presentation blood tests, Nottingham Hip Fracture Score, time to surgery, management, ASA grade, length of stay, COVID-19 and 30-day mortality status were recorded. Results: A total of 7090 patients were included, with a mean age of 82.2 (range 50–104) years and 4959 (69.9%) being female. Of 651 (9.2%) patients diagnosed with COVID-19, 225 (34.6%) were positive at presentation and 426 (65.4%) were positive postoperatively. Positive COVID-19 status was independently associated with male sex (odds ratio (OR) 1.38, p = 0.001), residential care (OR 2.15, p < 0.001), inpatient fall (OR 2.23, p = 0.003), cancer (OR 0.63, p = 0.009), ASA grades 4 (OR 1.59, p = 0.008) or 5 (OR 8.28, p < 0.001), and longer admission (OR 1.06 for each increasing day, p < 0.001). Patients with COVID-19 at any time had a significantly lower chance of 30-day survival versus those without COVID-19 (72.7% versus 92.6%, p < 0.001). COVID-19 was independently associated with an increased 30-day mortality risk (hazard ratio (HR) 2.83, p < 0.001). Increasing age (HR 1.03, p = 0.028), male sex (HR 2.35, p < 0.001), renal disease (HR 1.53, p = 0.017), and pulmonary disease (HR 1.45, p = 0.039) were independently associated with a higher 30-day mortality risk in patients with COVID-19 when adjusting for confounders. Conclusion: The prevalence of COVID-19 in hip fracture patients during the first wave of the pandemic was 9%, and was independently associated with a three-fold increased 30-day mortality risk. Among COVID-19-positive patients, those who were older, male, with renal or pulmonary disease had a significantly higher 30-day mortality risk.

Introduction:Nuclear medicine involves the handling and storing of radioactive materials known to pose a risk to human health. The size of the exposure depends on the radionuclide, the person’s activity and the type of one’s work in a nuclear medicine laboratory. Purpose:The purpose of this literature review is to investigate the contribution of radiation protection and safety measures regarding the protection of professionals’ health working in the nuclear medicine laboratory, as well as patients who undergo relevant tests. Methodology:The study material consists of recent articles on the subject mainly found in Greek and international databases as the Medline, Google Scholar and the Hellenic Academic Libraries Association (HEAL-Link). Results:In Greece, the principles of radiation protection are defined by Law 4310/2014. Radiation protection regulations are provided for the procedures as regards the implementation of a radiation protection system in general and regulation of all issues related to the protection of the professionals’ health exposed to radiation as well as for the issues arising from ionizing radiation during the activities referred to the protection of the general public by legislation. Conclusion:The control of radiation exposure in nuclear medicine not only for health care professionals, but also for patients and the public, can be achieved effectively through many actions being crucial to this direction.

This file provides some details on the mathematical models and their properties.

Large media platforms are now in the habit of providing facts in their products and representing knowledge to various publics. For example, Google’s Knowledge Graph is a database of facts that Google uses to provide quick answers to publics who use their products, while Wikipedia has a product called Wikidata that similarly stores facts about the world in data formats through which various apps can retrieve the data. Microsoft, Amazon, and IBM use similar fact storing and retrieval techniques in their products. This panel introduces papers that take a political economy perspective on such platformaized versions of fact production and examines the underlying infrastructures, histories, and modeling techniques used in such knowledge representation systems. Knowledge representation, long a central topic in archiving work in library and information sciences, is a key feature of platforms and practiced by internet companies more broadly. Much of this work has historically centered on metadata models that seek to organize and describe information in standardized ways. In the context of expanding this data organizing and labeling work into the wider web, one of the main facilitators was the “Semantic Web” project proposed by Tim-Berners Lee and the World Wide Web Consortium (W3C). Today, many of the same principles, technologies, and standards that were proposed by those early projects in metadata modeling from groups like W3C are found at companies like Google and Facebook, organizations like Wikipedia, government portals, and beyond. These platform metadata models are typically produced by industry professionals (e.g., taxonomists, ontologists, knowledge engineers, etc.) who help structure information for algorithmic processing on platforms and their recommender systems. Such structured information is supposed to add a layer of contextual expressivity to web data that would otherwise be more difficult to parse, though the issue of context control is not unproblematic in relation to statements of facts. In many of these automated systems, metadata models contribute to articulating ready-made facts that then travel through these systems and eventually reach the products that are engaged by everyday web users. This panel connects scholars working in information, media studies, and science and technology studies to discuss these semantic technologies. The first paper presents data gathered from interviews with semantic web practitioners who build or have built metadata models at large internet and platform companies. It presents results from a qualitative study of these platform data management professionals (collectively referred to as “metadata modelers”) and draws from unstructured interviews (n=10) and archival research. The paper describes the image of a metadata ecology along with selected work-related contestations expressed by interview subjects regarding some of the difficulties and intractable problems in metadata modeling work. The paper includes a discussion of the political economy of platform semantics through an examination of critical semantic web literature and ends with some policy concerns. The second paper translates the method of tracing “traveling facts” from science studies to the context of online knowledge about evolving, historic events. The goal is to understand the socio-political impact of the semantic web as it has been implemented by monopolistic digital platforms and how such practices intersect in the context of Wikipedia, where the majority of knowledge graph entities are sourced from. The paper describes how the adoption (and domination) by platform companies of linked data has catalyzed a re-shaping of web content to accord with the question and answer linked data formats, weakening the power of open content licenses to support local knowledge and consolidating the power of algorithmic knowledge systems that favor knowledge monopolies. The third paper discusses building a semantic foundation for machine learning and examines how information infrastructures that convey meaning are intimately tied to colonial labor relations. It traces the practice of building a digital infrastructure that enables machines to learn from human language. The paper describes examples from an ethnographic study of semantic computing and its infrastructuring practices to show how such techniques are materially and discursively performative in their co-emergence with techno-epistemic discourses and politico-economic structures. It examines sociomaterial process in which classifications, standards, metadata, and methods co-emerge with processes of signification that reconstitute and/or shift hegemonic ecologies of knowledge. The fourth paper evaluates and examines the ethics of “free” data (CC-0) in Wikidata by evaluating the sources and usage of data from and within Wikidata. From knowledge graphs to AI training, Wikidata is the semantic web platform that is being used across the Internet to power new platforms. Through a consideration of the ways in which Wikidata scrapes Wikipedia’s “share alike” knowledge through scraping metadata and the significant donations and partnerships from large technology firms (Google in particular), this paper addresses ethical concerns within the largest semantic web platform, how these transformations of knowledge alienate donated volunteer labor, and offers some ways in which these issues might be mitigated.

Solar power (SP) passive optical network (PON)-based fiber-wireless (FiWi) access systems are becoming increasingly popular as they provide coverage to rural and urban areas where no power grid exists. Secure operation of such networks which includes solar- and/or battery-powered devices, is crucial for anticipating potential network issues and prolong the life of the network operation. Since optical network units (ONUs) may be powered by SP-charged batteries, energy awareness becomes an important issue, particularly when it comes to reducing ONUs’ energy consumption and allowing them to operate in off-grid remote areas. With the PON as the fixed part of these networks, the optical line terminal (OLT) informs the ONUs through a message exchange mechanism when no traffic is present, allowing them to transition to a low-power-consumption sleep mode. However, man-in-the-middle (MITM) attacks pose a serious threat to the message exchange mechanisms, which can eventually drain the energy of battery-powered ONUs resulting in their shutdown. Consequently, this paper introduces two novel mechanisms for reducing ONU energy consumption, namely the wake-up and time-out mechanisms, which can be used to mitigate the effectiveness of MITM attacks that may seek to affect the unit’s operation due to battery drain. The formal verification results show that these goals were effectively achieved.

This article portrays the authors’ experience with a complex lower limb bone and soft tissue defect, following chronic osteomyelitis and pathological fracture, which was managed by the multidisciplinary orthoplastic team. The decision for functional amputation versus limb salvage was deemed necessary, enhanced by the principles of “spare parts” in reconstructive microsurgery. This case describes the successful use of the osteocutaneous distal tibia turn-up fillet flap that allowed ‘lowering the level of the amputation’ from a through knee to a below-knee amputation to preserve the knee joint function. We comprehensibly review reports of turn-up flaps which effectively lower the level of amputation, also applying ‘spare-parts’ surgery principles and explore how these concepts refine complex orthoplastic approaches when limb salvage is not possible to enhance function. The osteocutaneous distal tibia turn-up fillet flap is a robust technique for modified BKA reconstructions that provides sufficient bone length to achieve a tough, sensate stump and functional knee joint.

The present research investigated whether accidental contact through stinging with honeybees, wasps, and hornets could represent a microbial hazard for humans. It has been previously suggested that such contact may transmit pathogens causing infections that could even be fatal for some susceptible individuals. Stinging simulation experiments were performed in the lab with live insects collected from the environment in Lemnos Island (north-eastern Greece), while different selective agar media targeting some clinically important bacteria (i.e., Staphylococcus aureus, Streptococcus pyogenes, Enterococcus faecalis/faecium, and Pseudomonas aeruginosa) were used as substrates for microbial recovery and identification. Results revealed none of the target pathogenic bacterial species in the honeybee samples, with bacilli, staphylococci, and micrococci dominating their surveyed microbiota. However, most of the suspect colonies isolated from wasps and hornets belonged to important hygienic indicators (i.e., enterococci, Proteus mirabilis, and coliforms), implying possible contact of these insects with fecal origin materials. To sum up, the microbiota that may be transmitted to humans through stinging appears to differ between honeybees and wasps/hornets, while the isolation from the latter samples of some other important opportunistic pathogens, such as Enterobacter spp. and Klebsiella spp., also known for multidrug resistance, could be an additional reason of concern.

Hyperparameter optimization (HPO) is concerned with the automated search for the most appropriate hyperparameter configuration (HPC) of a parameterized machine learning algorithm. A state-of-the-art HPO method is Hyperband, which, however, has its own parameters that influence its performance. One of these parameters, the maximal budget, is especially problematic: If chosen too small, the budget needs to be increased in hindsight and, as Hyperband is not incremental by design, the entire algorithm must be re-run. This is not only costly but also comes with a loss of valuable knowledge already accumulated. In this paper, we propose incremental variants of Hyperband that eliminate these drawbacks, and show that these variants satisfy theoretical guarantees qualitatively similar to those for the original Hyperband with the "right" budget. Moreover, we demonstrate their practical utility in experiments with benchmark data sets.

Introduction: Investigations of biofeedback (BF) and neurofeedback (NF) training for nicotine addiction have been long documented to lead to positive gains in smoking status, behavior and to changes in brain activity. We aimed to: (a) evaluate a multi-visit combined BF/NF intervention as an alternative smoking cessation approach, (b) validate training-induced feedback learning, and (c) document effects on resting-state functional connectivity networks (rsFCN); considering gender and degree of nicotine dependence in a longitudinal design.Methods: We analyzed clinical, behavioral, and electrophysiological data from 17 smokers who completed five BF and 20 NF sessions and three evaluation stages. Possible neuroplastic effects were explored comparing whole-brain rsFCN by phase-lag index (PLI) for different brain rhythms. PLI connections with significant change across time were investigated according to different resting-state networks (RSNs).Results: Improvements in smoking status were observed as exhaled carbon monoxide levels, Total Oxidative Stress, and Fageström scores decreased while Vitamin E levels increased across time. BF/NF promoted gains in anxiety, self-esteem, and several aspects of cognitive performance. BF learning in temperature enhancement was observed within sessions. NF learning in theta/alpha ratio increase was achieved across baselines and within sessions. PLI network connections significantly changed across time mainly between or within visual, default mode and frontoparietal networks in theta and alpha rhythms, while beta band RSNs mostly changed significantly after BF sessions.Discussion: Combined BF/NF training positively affects the clinical and behavioral status of smokers, displays benefit in smoking harm reduction, plays a neuroprotective role, leads to learning effects and to positive reorganization of RSNs across time.Clinical Trial Registration:https://clinicaltrials.gov/ct2/show/NCT02991781.

Artificial intelligence is the branch of computer science that attempts to model cognitive processes such as learning, adaptability and perception to generate intelligent behavior capable of solving complex problems with environmental adaptation and deductive reasoning. Applied research of cutting-edge technologies, primarily computational intelligence, including machine/deep learning and fuzzy computing, can add value to modern science and, more generally, to entrepreneurship and the economy. Regarding the science of civil engineering and, more generally, the construction industry, which is one of the most important in economic entrepreneurship both in terms of the size of the workforce employed and the amount of capital invested, the use of artificial intelligence can change industry business models, eliminate costly mistakes, reduce jobsite injuries and make large engineering projects more efficient. The purpose of this paper is to discuss recent research on artificial intelligence methods (machine and deep learning, computer vision, natural language processing, fuzzy systems, etc.) and their related technologies (extensive data analysis, blockchain, cloud computing, internet of things and augmented reality) in the fields of application of civil engineering science, such as structural engineering, geotechnical engineering, hydraulics and water resources. This review examines the benefits and limitations of using computational intelligence in civil engineering and the challenges researchers and practitioners face in implementing these techniques. The manuscript is targeted at a technical audience, such as researchers or practitioners in civil engineering or computational intelligence, and also intended for a broader audience such as policymakers or the general public who are interested in the civil engineering domain.

Microservices-based architectures become a very popular method to design cloud-based containerized applications. Kubernetes is a container orchestration system for automating software deployment, scaling, and management. The Kubernetes cluster consists of nodes (VMs) and the microservices are placed in pods into the nodes.The default Kubernetes scheduler selects an optimal node to run newly created or unscheduled pods but it does not adapt to workload changes so the default placement is static.Microservices (Pods) should be placed in nodes so that they are minimizing the infrastructure cost by minimizing the egress traffic (traffic between nodes), the number of nodes and also the response time. In modern applications due to high workloads, services need to run in multiple instances to keep up with high traffic. In Kubernetes a Horizontal Pod Autoscaler (HPA) automatically updates a workload (Service), with the aim of automatically scaling the workload to match demand, but if starting from sub-optimal placement (using the default Kubernetes Scheduler) this solution can be sub-optimal overall. In this work we aim to improve the initial placement of application services in Pods. The problem is is handled as a graph clustering one, to minimize the applications cost and the latency.Graph clustering needs to be fuzzy so it will allow pods to belong in more than one node.In this thesis two microservice-based applications were deployed in the Kubernetes of the GCP (Google Cloud Platform) to test the service placement solution, iXen an IoT application and Google’s OnlineBoutique an e-shop application. The experimental results reveal that the fuzzy placement solution can reduce the total response time of the application and the total monetary cost compared to default kubernetes scheduler and with or without the use of Kubernetes horizontal pod autoscaler., Οι αρχιτεκτονικές που βασίζονται σε μικροϋπηρεσίες γίνονται μια πολύ δημοφιλής μέθοδος σχεδιασμού που βασίζεται σε containerized εφαρμογές στο υπολογιστικό νέφος. Το Kubernetes είναι ένα σύστημα ενορχήστρωσης κοντέινερ για αυτοματοποίηση ανάπτυξη, κλιμάκωση και διαχείριση λογισμικού. Το Kubernetes cluster αποτελείται από Nodes (εικονικές Μηχανές) και οι μικροϋπηρεσίες τοποθετούνται σε Pods στα Nodes. O default kubernetes scheduler επιλέγει έναν βέλτιστο κόμβο για να τρέξει πρόσφατα δημιουργημένα pods, αλλά δεν προσαρμόζεται στις αλλαγές του φόρτου εργασίας, ώστε η προεπιλεγμένη τοποθέτηση να είναι στατική. Οι μικροϋπηρεσίες (Pods) θα πρέπει να τοποθετούνται σε κόμβους έτσι ώστε να ελαχιστοποιούν το κόστος της υποδομής ελαχιστοποιώντας egress traffic (traffic μεταξύ κόμβων), τον αριθμό των κόμβων και επίσης τον χρόνο απόκρισης. Στις σύγχρονες εφαρμογές λόγω υψηλού workload, οι υπηρεσίες πρέπει να εκτελούνται σε πολλά αντίγραφα για να μπορούν να διαχειριστούν το μεγάλο traffic. Στο Kubernetes, ο Horizontal Pod Autoscaler (HPA) ενημερώνει αυτόματα το workload (Service) με στόχο την αυτόματη κλιμάκωση του workload ώστε να συμβαδίζει με τη ζήτηση, αλλά αν ξεκινάμε από μια μη βέλτιστη τοποθέτηση (χρησιμοποιώντας τον default Kubernetes scheduler ) αυτή η λύση μπορεί να είναι συνολικά υποβέλτιστη. Σε αυτή την εργασία στοχεύουμε να βελτιώσουμε την αρχική τοποθέτηση των υπηρεσιών εφαρμογών στα Pods. Το πρόβλημα αντιμετωπίζεται ως graph clustering, με σκοπό την ελαχιστοποίηση του κόστους των εφαρμογών και του latency. Το graph clustering πρέπει να είναι fuzzy ούτος ώστε να επιτρέψει στα pods να ανήκουν σε περισσότερους από έναν κόμβους. Σε αυτή την εργασία δύο εφαρμογές μικροϋπηρεσιών αναπτύχθηκαν στο Kubernetes του GCP (Google Cloud Platform) για να ελέγξουμε τη λύση τοποθέτησης υπηρεσιών, το iXen μια εφαρμογή IoT, και το OnlineBoutique της Google μία εφαρμογή ηλεκτρονικού καταστήματος. Τα πειραματικά αποτελέσματα αποκαλύπτουν ότι η λύση της ασαφούς τοποθέτησης μπορεί να μείωση το συνολικό χρόνο απόκρισης της εφαρμογής και το συνολικό της κόστος σε σύγκριση με το default kubernetes scheduler με ή χωρίς τη χρήση του Kubernetes Horizontal pod Autoscaler.

BACKGROUND Guideline-directed medical therapy (GDMT) optimization is mandatory before transcatheter edge-to-edge mitral valve repair (M-TEER) in patients with secondary mitral regurgitation (SMR) and heart failure (HF) with reduced ejection fraction (HFrEF). However, the effect of M-TEER on GDMT is unknown. OBJECTIVES The authors sought to evaluate frequency, prognostic implications and predictors of GDMT uptitration after M-TEER in patients with SMR and HFrEF. METHODS This is a retrospective analysis of prospectively collected data from the EuroSMR Registry. The primary events were all-cause death and the composite of all-cause death or HF hospitalization. RESULTS Among the 1,641 EuroSMR patients, 810 had full datasets regarding GDMT and were included in this study. GDMT uptitration occurred in 307 patients (38%) after M-TEER. Proportion of patients receiving angiotensin-converting enzyme inhibitors/angiotensin receptor blockers/angiotensin receptor-neprilysin inhibitors, beta-blockers, and mineralocorticoid receptor antagonists was 78%, 89%, and 62% before M-TEER and 84%, 91%, and 66% 6 months after M-TEER (all P < 0.001). Patients with GDMT uptitration had a lower risk of all-cause death (adjusted HR: 0.62; 95% CI: 0.41-0.93; P = 0.020) and of all-cause death or HF hospitalization (adjusted HR: 0.54; 95% CI: 0.38-0.76; P < 0.001) compared with those without. Degree of MR reduction between baseline and 6-month follow-up was an independent predictor of GDMT uptitration after M-TEER (adjusted OR: 1.71; 95% CI: 1.08-2.71; P = 0.022). CONCLUSIONS GDMT uptitration after M-TEER occurred in a considerable proportion of patients with SMR and HFrEF and is independently associated with lower rates for mortality and HF hospitalizations. A greater decrease in MR was associated with increased likelihood for GDMT uptitration.

Education for diabetes mellitus is not only acceptable, but it is now recognized as an urgent need for modern citizens, and especially for the elderly, as the dimensions of the disease are enormous. Education is a comprehensive process of reassessing the attitude and culture of society towards the acceptance of diversity and the better treatment of sick people.

Human activity recognition (HAR) is vital in a wide range of real-life applications such as health monitoring of olderly people, abnormal behaviour detection and smart home management. HAR systems can employ smart human-computer interfaces and be parts of active, intelligent surveillance systems. The increasing use of high-tech mobile and wearable devices, such as smart phones, smart watches and smart bands, can be the key elements in building high accuracy models, as they can provide a tremendous number of signals. This research aims to develop and test a machine learning (ML) model, which can successfully recognize a performed activity using raw signals obtained by wearable devices. Photoplethysmography – Daily Life Activities (PPG-DaLiA) dataset contains data related to 15 individuals wearing physiological and motion sensors. PPG-DaLiA was used as an input to a custom data segmentation model to obtain the respective training and testing dataset. Overall, 23 ML well-established models were employed. The weighted and the fine k-nearest neighbours, the fine Gaussian support vector machines and the bagged trees were the algorithms that achieved the best performance with a very high accuracy level.

BACKGROUND Mitral valve repair may lead to alterations of tricuspid regurgitation (TR). AIMS We aimed to investigate alterations, predictors and prognostic relevance of TR evolution in a large-scale multicentre population of patients undergoing transcatheter mitral valve repair (TMVR) via the MitraClip. METHODS In total, we included 531 TMVR patients with at least one available follow-up echocardiography. TR improvement was defined as a TR ≥II at baseline, which showed a decline of at least one TR categorisation. RESULTS Distribution of preprocedural TR severity was TR 0/I 41% (220/531), TR II 39% (209/531) and TR ≥III 19% (102/531), respectively. Follow-up echocardiography was at 308±187 days. TR severity improved to TR 0/I 49% (259/531), TR II 35% (183/531) and TR III 17% (89/531), p=0.003. Out of 311 patients with TR ≥II at baseline, 41% (127/311) showed TR improvement. Atrial fibrillation (AF), residual mitral regurgitation ≥II (rMR) and tricuspid annular diameter (TAD) remained variables which prevented TR improvement (odds ratio 0.49 [0.29-0.84], 0.47 [0.27-0.81] and 0.97 [0.93-0.997], respectively). TR improvement was associated with better event-free survival regarding post-procedural heart failure hospitalisation (HHF) (hazard ratio 0.6 [0.38-0.94]). The main changes of TR severity occurred within 3 months post TMVR (p=0.006), while there were only minor TR changes between 3 and 12 months of follow-up (p=0.813). CONCLUSIONS TR improvement was frequent after TMVR. Predictors preventing TR improvement were AF, post-procedural rMR, and TAD. Furthermore, TR improvement was an early phenomenon occurring primarily within the first three months post TMVR and served as a suitable marker of reduced HHF.

Background The change in right-ventricular function (RVF) after transcatheter mitral valve repair is still poorly understood. We assessed the early response of RVF to the MitraClip procedure and its clinical relevance. Methods We analyzed consecutive patients who underwent a MitraClip procedure to treat MR between August 2010 and March 2019 in the Heart Failure Network Rhineland registry. RVF was assessed before and after the procedure. Impaired RVF was defined as an RV fractional area change (RVFAC) Results 816 eligible patients (77 ± 9 years, 58.5% male) were included in the analysis. Baseline values of RVF were: RVFAC 38.6 (IQR 29.7–46.7) % and TAPSE 17.0 (IQR 14.0–21.0) mm. At a median time of 3 (IQR 2–5) days after the procedure, the RVF remained normal in 34% (n = 274), normalized in 17% (n = 140), deteriorated in 15% (n = 125), and was persistently impaired in 34% (n = 277) of patients. The RVF response was significantly associated with a composite outcome of all-cause mortality and hospitalization due to heart failure within a 2-year follow-up. Compared to stable/normal RVF, the adjusted hazard ratios for the outcome were 1.78 (95% CI 1.10–2.86) for normalized RVF, 1.89 (95% CI 1.34–3.15) for deteriorated RVF, and 2.25 (95% CI 1.47–3.44) for persistently impaired RVF. Changes in TAPSE and RVFAC as continuous variables were significantly correlated with the outcome. Conclusion An early change in RVF following transcatheter mitral valve repair is predictive of mortality and hospitalization due to heart failure during follow-up. Graphic abstract Early response of RVF after MitraClip and its clinical significance. An acute, early change in RVF can be observed following the MitraClip procedure, which is associated with the risk of mortality and hospitalization for HF.

Introduction Gender affirming surgery of primary and/or secondary sex characteristics has been shown to alleviate gender dysphoria. A descriptive snapshot of current treatment preferences is useful to understand the needs of the transgender population seeking health care. This study aimed to describe preferences for gender affirming treatment, and their correlates, among individuals seeking health care for gender dysphoria in Sweden after major national legislative reforms. Methods Cross-sectional study where transgender patients (n = 232) recruited from all six Gender Dysphoria centers in Sweden 2016–2019, answered a survey on treatment preferences and sociodemographic, health, and gender identity-related information during the same time-period. Factors associated with preferring top surgery (breast augmentation or mastectomy), genital surgery, and other surgery (e.g., facial surgery) were examined in univariable and multivariable regression analyses in the 197 people without prior such treatment. Main study outcomes were preferences for feminizing or masculinizing hormonal and surgical gender affirming treatment. Results The proportion among birth assigned male and assigned female patients preferring top surgery was 55.6% and 88.7%, genital surgery 88.9% and 65.7%, and other surgery (e.g., facial surgery) 85.6% and 22.5%, respectively. Almost all participants (99.1%) wanted or had already received hormonal treatment and most (96.7%) wished for some kind of surgical treatment; 55.0% wanted both top and genital surgery. Preferring a binary pronoun (he/she) and factors indicating more severe gender incongruence were associated with a greater wish for surgical treatment. Participants with somatic comorbidities were less likely to want genital surgery, while aF with lacking social support were less likely to want internal genital surgery, in the multivariable analyses. Conclusions In this sample of Swedish young adults seeking health care for gender dysphoria, preferences for treatment options varied according to perceived gender identity. Policy Implications The study findings underline the need for individualized care and flexible gender affirming treatment options. The role of somatic comorbidities should be further explored, and support should be offered to transgender people in need. There is an unmet need for facial surgery among aM.

As water is a valuable and indispensable ingredient of life, drinking water’s safety is extremely important both for ensuring consumers’ health and for the proper functioning of the ecosystem. The implementation of new technologies aiming to ensure that water quality and monitoring in water utilities lies in compliance with current EU and national standards, prove very promising for enhancing risk assessment processes and management of water supply systems. The overall objective of the PathoCERT project is to strengthen the coordination capability of the first responders in handling waterborne pathogen contamination events, allowing the rapid and accurate detection of pathogens, improving their situational awareness and their ability to control and mitigate emergency situations involving waterborne pathogens. The developed methodologies involve the processing of a vast amount of data of different sources; PathoSAT collects data and images from satellites, analyse them to identify water contaminations and their extent and relays them to PathoCERT’s platform. PathoTWEET analyses data and photos from social media to assess the occurrence, severity and extent of water contamination events. To align PathoCERT’s various components with the needs of the first responders, three Community of Practice (CoP) meetings were organized, where the scenarios are formed based on the usability of the presented technologies.