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Non-ST elevation acute coronary syndrome in the elderly

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Journal of Geriatric Cardiology 2020年第1期17卷 9-15页

作者： Pablo Díez-Villanueva César Jiménez Méndez fernando alfonso Cardiology Department Hospital Universitario La Princesa Universidad Autónoma de Madrid

1 Introduction Societies are ageing at an accelerated *** scenario is a well-known challenge for health care systems,as chronic diseases,multiple comorbidities and dependency are all entities that often converge in the ***,there is an issue regarding a reduction in the general incidence of acute coronary syndrome(ACS)together with a delayed in the age of presentation,which,in sum,lead to an increase in both incidence and prevalence of ACS with age,especially non-ST elevation myocardial infarction(NSTEMI).

关键词： Acute coronary syndrome Myocardial infarction The elderly

Heart failure in the elderly

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Journal of Geriatric Cardiology 2021年第3期18卷 219-232页

作者： Pablo Díez-Villanueva César Jiménez-Méndez fernando alfonso Cardiology Department Hospital Universitario La PrincesaUniversidad Autónoma de MadridCIBER-CVMadridSpain

Heart failure(HF)is a clinical syndrome caused by structural and/or functional cardiac abnormalities,resulting in a reduced cardiac output and/or elevated intracardiac filling pressures at rest or during *** is a major public health problem with high prevalence and incidence,involving both high morbidity and mortality,but also high economic *** incidence of HF progressively increases with age,reaching around 20%among people over 75 years ***,HF represents the leading cause of hospitalization in patients older than 65 years in Western ***,some authors even consider HF a geriatric syndrome,entailing worse prognosis and high residual disability,and often associating some complex comorbidities,common in older population,that may further complicate the course of the *** the other hand,however,clinical course and prognosis may be often difficult to *** this article,main pathophysiological issues related to the aging heart are addressed,together with key aspects related to both diagnosis and prognosis in elderly patients with ***,main geriatric conditions,common in the elderly population,are reviewed,highlighting the importance of a comprehensive and multidisciplinary approach.

关键词： diagnosis elevated mortality

Gold nanoshells： Contrast agents for cell imaging by cardiovascular optical coherence tomography

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Nano Research 2018年第2期11卷 676-685页

作者： Jie Hu Francisco Sanz-Rodríguez fernando Rivero Emma Martín Rodríguez Río Aguilar Torres Dirk H. Ortgies José García Solé fernando alfonso Daniel Jaque Fluorescence Imaging Group Departamento de Física de Materiales Instituto Nicolás Cabrera Facultad de Ciencias Universidad Autónoma de Madrid Madrid Spain Instituto Ramón y Cajal de Investigación Sanitaria Hospital Ramón y Cajal Madrid Spain Departamento de Biología Universidad Autónoma de Madrid Madrid Spain Cardiology Department Hospital Universitario de la Princesa IIS-IP Universidad Autónoma de Madrid Madrid Spain

Optical coherence tomography （OCT） has gained considerable attention in interventional cardiovascular medicine and is currently used in clinical settings to assess atherosclerotic lesions and to optimize stent placement. Artery imaging at the cellular level constitutes the first step towards cardiovascular molecular imaging, which represents a major advance in the development of personalized noninvasive therapies. In this work we demonstrate that cardiovascular OCT can be used to detect individual cells suspended in biocompatible fluids. Importantly, the combination of this catheter-based clinical technique with gold nanoshells （GNSs） as intracellular contrast agents led to a substantial enhancement in the backscattered signal produced by individual cells. This cellular contrast enhancement was attributed to the large backscattering cross-section of GNSs at the OCT laser wavelength （1,300 nm）. A simple intensity analysis of OCT cross-sectional images of suspended cells makes it possible to identify the sub-population of living cells that successfully incorporated GNSs. The generalizability of this method was demonstrated using two different cell lines （HeLa and Jurkat cells）. This work provides novel insights into cardiovascular molecular imaging using specifically modified GNSs.

关键词： optical coherencetomography (OCT)intravascular imaging gold nanoparticles three-dimensional (3D)imaging

From the epicardial adipose tissue to vulnerable coronary plaques

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World Journal of Cardiology 2013年第4期5卷 68-74页

作者： Mauro Echavarría-Pinto Lorenzo Hernando fernando alfonso Interventional Cardiology Cardiovascular InstituteHospital Clinico San Carlos28040 MadridSpain Cardiology Department Fundación Alcorcón28922 MadridSpain

Thin cap fibroatheromas(TCFAs) are thought to be the most common underlying substrate in patients suffering acute coronary thrombotic ***,an interesting association between TCFAs and a particular depot of visceral fat called epicardial adipose tissue(EAT) has been *** this article,we discuss some basic and clinical aspects of this association and then briefly review some of the pathophysiological characteristics attributed to EAT that explain why this particular depot of fat has been attracting the attention of the cardiological scientific community in recent *** we discuss the value of optical coherence tomography in the diagnosis of TCFAs and the role of multislice computed tomography to assess EAT.

关键词： Epicardial adipose tissue Thin-cap fibroatheromas Coronary thrombotic events Optical coherence tomography Multislice computed tomography

Using fused filament fabrication to improve the tribocorrosion behaviour of 17-4 PH SS in comparison to other metal forming techniques

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Friction 2024年第10期12卷 2325-2343页

作者： Cristina GARCÍA-CABEZÓN Juan alfonso NARANJO Celia GARCÍA-HERNÁNDEZ Cristina BERGES Gemma HERRANZ fernando MARTÍN-PEDROSA Materials Engineering E.I.I.Universidad de ValladolidValladolid 47011Spain INEI-Escuela Técnica Superior de Ingeniería Industrial(ETSII) Universidad de Castilla La ManchaCastilla-La Mancha 13071Spain

Fused filament fabrication(FFF)is one of the additive manufacturing processes which has gained more interest because of its simplicity and *** technology is similar to the conventional metal injection moulding(MIM)process,consisting of the feedstock preparation of metal powder and polymer binders,followed by layer-by-layer 3D printing(FFF)or injection(MIM)to create green parts and,finally,debinding and ***,both technologies provide near-dense *** work presents an in-depth study of the processing method’s *** porosity,microstructure,hardness,corrosion,and tribocorrosion behaviour are compared for 17-4 PH SS samples processed from powder by additive manufacturing using FFF and MIM,as well as conventional powder metallurgy(PM)*** samples exhibited the highest macro and microhardness,while corrosion behaviour was similar for both MIM and FFF samples,but superior in comparison to conventional PM ***,the FFF-as fabricated samples displayed a significant improvement in tribocorrosion resistance that could be explained by the higher proportion of delta ferrite and retained austenite in their microstructure.

关键词： 17-4 PH SS fused filament fabrication(FFF) metal injection moulding(MIM) corrosion behaviour powder metallurgy(PM) tribocorrosion behaviour

An innovative heterogeneous transfer learning framework to enhance the scalability of deep reinforcement learning controllers in buildings with integrated energy systems

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Building Simulation 2024年第5期17卷 739-770页

作者： Davide Coraci Silvio Brandi Tianzhen Hong alfonso Capozzoli Politecnico di Torino Department of EnergyTEBE research groupBAEDA Lab.Corso Duca degli Abruzzi 24Torino10129Italy Building Technology and Urban Systems Division Lawrence Berkeley National LaboratoryOne Cyclotron RoadBerkeleyCA 94720USA

Deep Reinforcement Learning(DRL)-based control shows enhanced performance in the management of integrated energy systems when compared with Rule-Based Controllers(RBCs),but it still lacks scalability and generalisation due to the necessity of using tailored models for the training *** Learning(TL)is a potential solution to address this ***,existing TL applications in building control have been mostly tested among buildings with similar features,not addressing the need to scale up advanced control in real-world scenarios with diverse energy *** paper assesses the performance of an online heterogeneous TL strategy,comparing it with RBC and offline and online DRL controllers in a simulation setup using EnergyPlus and *** study tests the transfer in both transductive and inductive settings of a DRL policy designed to manage a chiller coupled with a Thermal Energy Storage(TES).The control policy is pre-trained on a source building and transferred to various target buildings characterised by an integrated energy system including photovoltaic and battery energy storage systems,different building envelope features,occupancy schedule and boundary conditions(e.g.,weather and price signal).The TL approach incorporates model slicing,imitation learning and fine-tuning to handle diverse state spaces and reward functions between source and target *** show that the proposed methodology leads to a reduction of 10% in electricity cost and between 10% and 40% in the mean value of the daily average temperature violation rate compared to RBC and online DRL ***,online TL maximises self-sufficiency and self-consumption by 9% and 11% with respect to ***,online TL achieves worse performance compared to offline DRL in either transductive or inductive ***,offline Deep Reinforcement Learning(DRL)agents should be trained at least for 15 episodes to reach the same level of performance as the online

关键词： transfer learning reinforcement learning building control building energy management

E-Commerce Fraud Detection Based on Machine Learning Techniques:Systematic Literature Review

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Big Data Mining and Analytics 2024年第2期7卷 419-444页

作者： Abed Mutemi fernando Bacao NOVA Information Management School(NOVA IMS) Universidade Nova de LisboaCampus de CampolideLisboa 1070-312Portugal

The e-commerce industry’s rapid growth,accelerated by the COVID-19 pandemic,has led to an alarming increase in digital fraud and associated *** establish a healthy e-commerce ecosystem,robust cyber security and anti-fraud measures are ***,research on fraud detection systems has struggled to keep pace due to limited real-world *** in artificial intelligence,Machine Learning(ML),and cloud computing have revitalized research and applications in this *** ML and data mining techniques are popular in fraud detection,specific reviews focusing on their application in e-commerce platforms like eBay and Facebook are lacking *** reviews provide broad overviews but fail to grasp the intricacies of ML algorithms in the e-commerce *** bridge this gap,our study conducts a systematic literature review using the Preferred Reporting Items for Systematic reviews and Meta-Analysis(PRISMA)*** aim to explore the effectiveness of these techniques in fraud detection within digital marketplaces and the broader e-commerce *** the current state of the literature and emerging trends is crucial given the rising fraud incidents and associated *** our investigation,we identify research opportunities and provide insights to industry stakeholders on key ML and data mining techniques for combating e-commerce *** paper examines the research on these techniques as published in the past *** the PRISMA approach,we conducted a content analysis of 101 publications,identifying research gaps,recent techniques,and highlighting the increasing utilization of artificial neural networks in fraud detection within the industry.

关键词： E-commerce Machine Learning(ML) systematic review fraud detection organized retail fraud

Exploring multifaceted factors in chronic kidney disease risk: A comprehensive analysis of biochemistry, lifestyle, and inflammation in elderly Chinese individuals

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World Journal of Clinical Cases 2024年第5期12卷 1033-1035页

作者： fernando Cardona Unitat de Genètica Molecular Instituto de Biomedicina de Valencia–CSICValencia 46010Spain Centro de investigación Biomédica en Red Enfermedades Neurodegenerativas(CIBERNED) Instituto de Salud Carlos IIIMadrid 28029Spain Departamento de Biotecnología Escuela Técnica Superior de Ingeniería Agronómica y del Medio Natural(ETSIAMN)Univeristat Politècnica de ValenciaValencia 46022Spain

This letter praises a recent article in the World Journal of Clinical Cases(Roles of biochemistry data,lifestyle,and inflammation in identifying abnormal renal function in old Chinese),examining factors affecting abnormal renal function in elderly Chinese using advanced machine *** highlights the importance of uric acid,age,hemoglobin,body mass index,sport hours,and systolic blood *** study's holistic approach,integrating lifestyle and inflammation,offers a nuanced understanding of chronic kidney disease risk *** letter suggests exploring mechanistic pathways of hyperuricemia,the link between anemia and renal function,and the connection between body mass index and estimated glomerular filtration *** advocates investigating physical activity's impact on renal health and the independent effects of blood *** study significantly contributes to chronic kidney disease understanding,proposing avenues for further exploration and *** are extended to the authors and the journal.

关键词： Biochemistry data Lifestyle Machine learning Renal function

Autonomous Vehicle Platoons In Urban Road Networks:A Joint Distributed Reinforcement Learning and Model Predictive Control Approach

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 141-156页

作者： Luigi D’alfonso Francesco Giannini Giuseppe Franzè Giuseppe Fedele Francesco Pupo Giancarlo Fortino IEEE the Department of Computer Engineering ModelingElectronics and SystemsUniversitàdella CalabriaVia Pietro BucciCubo 42-CRende(CS)87036Italy the Department of Mechanical Engineering Energy Engineering and ManagementUniversitàdella CalabriaVia Pietro BucciCubo 42-CRende(CS)87036Italy

In this paper, platoons of autonomous vehicles operating in urban road networks are considered. From a methodological point of view, the problem of interest consists of formally characterizing vehicle state trajectory tubes by means of routing decisions complying with traffic congestion criteria. To this end, a novel distributed control architecture is conceived by taking advantage of two methodologies: deep reinforcement learning and model predictive control. On one hand, the routing decisions are obtained by using a distributed reinforcement learning algorithm that exploits available traffic data at each road junction. On the other hand, a bank of model predictive controllers is in charge of computing the more adequate control action for each involved vehicle. Such tasks are here combined into a single framework:the deep reinforcement learning output(action) is translated into a set-point to be tracked by the model predictive controller;conversely, the current vehicle position, resulting from the application of the control move, is exploited by the deep reinforcement learning unit for improving its reliability. The main novelty of the proposed solution lies in its hybrid nature: on one hand it fully exploits deep reinforcement learning capabilities for decisionmaking purposes;on the other hand, time-varying hard constraints are always satisfied during the dynamical platoon evolution imposed by the computed routing decisions. To efficiently evaluate the performance of the proposed control architecture, a co-design procedure, involving the SUMO and MATLAB platforms, is implemented so that complex operating environments can be used, and the information coming from road maps(links,junctions, obstacles, semaphores, etc.) and vehicle state trajectories can be shared and exchanged. Finally by considering as operating scenario a real entire city block and a platoon of eleven vehicles described by double-integrator models, several simulations have been performed with the a

关键词： Distributed model predictive control distributed reinforcement learning routing decisions urban road networks