bluuebunny/crossref_metadata_2025_split huggingface dataset:
May Coronary Artery Bypass Grafting Affect Native Coronary Atherosclerosis progression?
Authors: Labib Dokhan Ahmed , Fekry Soliman Rafik , Meselhy Abd Elsabour Meselhy Mohammed , Mohammed Khalil Ibrahim , Kamal El Melegy Ehab , Ahmed El-Hag-Aly Mohammed 
Published: January 2023

Background: Coronary artery bypass grafting (CABG) continues to be the best standard in the management of severe coronary artery disease (CAD), providing good symptom management and life extension. Although CABG was first performed by reversed saphenous veins (SVGs), surgeons have increasingly adopted arterial conduits because of their longer-term patency and resistance to atherosclerosis. CABG's efficacy may potentially be affected by the extension of atherosclerosis in the native coronary arteries. Few researches have investigated the long-term angiographic disease progression of native coronary arteries after surgical revascularization, or the variables that may impact this progression. Proximal native disease progression was presented to be two to six times more common than distal disease progression, with greater rates of progression in coronaries bypassed by SVGs than arterial grafts. The goal of this research was to determine influence of CABG on the extension of native coronaries atherosclerosis.
Methods: This prospective study was established on 25 patients who were diagnosed to have ischemic heart disease in cardiothoracic surgery department in Faculty of Medicine Menoufia University.
Results: The study showed that according to the risk factors among the studied cases, smoking was (60%), Dyslipidemia was (32%), HTN was (32%) and Diabetes was (32). According to grafts in proximal lesions, there was progression of atherosclerosis up to total occlusion, but in Distal lesions, there was significant regression of atherosclerosis. As result, there was statistically significant difference between proximal with distal lesions. Also, study showed that there was a significant difference between left system (LAD, D, OM) in comparison with right system (PDA) regarding distal lesion. Our results showed that univariate logistic regression analysis for progression in distal lesion regarding Dyslipidemia and Diabetes.
Conclusion: Progression of disease is more evident in coronary segment proximal to anastomosis, while regression of disease is more evident in coronary segment distal to anastomosis with statistically significant difference between them, also the risk of disease progression post CABG was found to be multifactorial, as certain risk factors can affect progression of the disease as Diabetes mellitus and dyslipidemia that were of statistically significance.
The Sonographic Measurement of the Inferior Vena Cava Diameter versus the Central Venous Pressure in Assessing Fluid Responsiveness in Patients after Coronary Artery Bypass Graft Surgery
Authors: El-Gazzar Mohamed , Soubih Ahmed , Sanad Osama , Rashid Hesham , Elnahhas Ashraf 
Published: January 2023

Background: Fluid status assessment and management post coronary artery bypass grafting (CABG) is a clinical challenge. The study aimed to establish whether central venous pressure (CVP) and ultrasound measures of respiratory variability of inferior vena cava (IVC) diameter might predict fluid responsiveness in mechanically ventilated patients after CABG.
Methods: This comparative study included 200 consecutive adult patients who underwent elective CABG. We recorded the following parameters: heart rate (HR), systolic blood pressure (SBP), diastolic blood pressure (DBP), central venous pressure (CVP), inferior vena cava maximum (IVCmax), and minimum (IVCmin) diameters, left ventricular ejection fraction (LVEF), and velocity-time integral in the left ventricular outflow tract (VTI-LVOT).
Results: The age of the patients ranged from 45 to 71 years, and 147 were males (73.5%). Patients were grouped into fluid responders (n= 135), defined as stroke volume variation (SVV) of 15% or greater following fluid bolus administration, and fluid non-responders (n= 65), defined SVV of less than 15% following fluid bolus administration. There was no statistically significant difference between the groups regarding their CVP, maximum and minimum IVC diameters, inferior vena cava distensibility index (IVC-DI), and other markers of fluid responsiveness (p-value 0.47, 0.34, 0.59, and 0.64, respectively). There was a significant difference in SVV between fluid responders (18.33±2.767) and non-responders (10.95±1.940) (p-value <0.001).
Conclusion: Neither CVP nor sonographic measures of IVC diameter respiratory variability provided an accurate method to distinguish between fluid responders and non-responders in the early postoperative period after CABG.
Hephaestus: Modelling, Analysis, and Performance Evaluation of Cross-Chain Transactions
Authors: Belchior Rafael , Somogyvari Peter , Pfannschmid Jonas , Vasconcelos André , Correia Miguel 
Published: January 2023

<p>Ecosystems of multiple blockchains are now a reality. Multi-chain applications and protocols are perceived as necessary to enable scalability, privacy, and composability. Despite being a promising emerging research area, we recently have witnessed many attacks that have caused billions of dollars in losses. Attacks against bridges that connect chains are at the top of such attacks in terms of monetary cost, and no apparent solution seems to emerge from the ongoing chaos. </p>
<p>In this paper, we present our contribution to minimizing bridge attacks. In particular, we explore the concepts of <em>cross-chain transaction, cross-chain logic, </em>and the<em> cross-chain state</em> as the enablers of the cross-chain model. We propose <strong>Hephaestus</strong>, the first cross-chain model generator that captures the operational complexity of cross-chain applications. <strong>Hephaestus</strong> can generate cross-chain models from local transactions on different ledgers realizing arbitrary use cases and allowing operators to monitor their cross-chain applications. Monitoring helps identify outliers and malicious behavior, which can help programmatically to stop bridge hacks and other attacks. We conduct a detailed evaluation of our system, where we implement a cross-chain bridge use case. Our experimental results show that <strong>Hephaestus </strong>can process 600 cross-chain transactions in less than 5.5 seconds in an environment with two blockchains and requires sublinear storage.</p>
Augmentation assisted robust fringe detection on unseen experimental signals applied to optical feedback interferometry using a deep network
Authors: Khurshid Sumair Saeed , Hussain Wajahat , Zabit Usman , Bernal Olivier 
Published: January 2023

<p>In this work, we propose using deep neural 2D networks, which have renowned generalization performance on unseen data. It specifically explains the use of Novel Augmentation technique for SMI Fringe detection and classification. Overall, it highlights the importance of data augmentation in computer vision algorithms. The results prove that computer vision can be used to cater the problems in signal processing and photoelectronics domain.</p>
Impact of Channel Models on Performance Characterization of RIS-Assisted Wireless Systems
Authors: Jamali Vahid , Ghanem Walid. R. , Schober Robert , Poor H. Vincent 
Published: January 2023

<p>The performance characterization of communication systems assisted by large reconfigurable intelligent surfaces (RISs) significantly depends on the adopted models for the underlying channels. Under unrealistic channel models, the system performance may be over- or under-estimated which yields inaccurate conclusions for the system design. In this paper, we review five channel models that are chosen to progressively improve the modeling accuracy for large RISs. For each channel model, we highlight the underlying assumptions, its advantages, and its limitations. We compare the system performance under the aforementioned channel models using RIS configuration algorithms from the literature and a new scalable algorithm proposed in this paper specifically for the configuration of extremely large RISs.</p>
Failure Management in 5G RAN: Challenges and Open Research Lines
Authors: Tarrías Antonio , Fortes Sergio , Barco Raquel 
Published: January 2023

<p>Failure management is one of the key aspects in cellular networks. 5G technology is introducing several novel features that will cause the occurrence of new problems in the network. The objective of the present work is to identify which features may lead to potential network failures. In this way, a subset of problems has been identified and categorized. They were analyzed in order to know how they are in line with 3GPP specifications. Based on this, the present work proposes a novel failure management approach, applying it for failure simulation and impact analysis over the network performance. </p>
Reduction of nonlinear impairments in optical transmission systems for high-order quadrature-amplitude-modulation signals by using phase-conjugated twin waves
Authors: Kikuchi Kazuro 
Published: January 2023

<p>Using computer simulations, we analyze the bit-error rate (BER) characteristics of the optical transmission system repeated by erbium-doped fiber amplifiers (EDFAs) and two-mode phase-sensitive optical parametric amplifiers (PSAs), where phase-conjugated (PC) twin waves are co-propagating through the link. We focus on the 256 quadrature-amplitude-modulation (QAM) format, whose transmission characteristics are seriously affected by fiber nonlinearity because the required power is significantly high.</p>
<p>Changing the repeater spacing and group-velocity dispersion (GVD) of fibers for transmission in the two-mode PSA-based system, we calculate the BERs as a function of the launched power. When the repeater spacing and GVD value of fibers are properly designed, the two-mode PSA-based system can mitigate nonlinear impairments more effectively than the EDFA-based PC twin system.</p>
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Automated muscle localization and model-based estimation of ankle torques post-stroke via a wearable sensorised leg garment
Authors: Simoneti Donatella , Hendriks Maartje , Herijgers Joost , Rio Carmen Cuerdo del , Koopman Bart , Keijsers Noel , Sartori Massimo 
Published: January 2023

<p>This study presents a technology that can provide computer-based, signal-driven, musculoskeletal model-based analysis for musculoskeletal assessment post-stroke during gait. It comprises a modular 64 textile-embedded electromyography (EMG) leg garment integrated with a generalized and automated algorithm for the fast localization of leg muscles and an EMG-driven neuromusculoskeletal (NMS) modeling framework for the estimation of ankle torques and muscle forces. </p>
<p>Our results showed that the automated clustering could extract muscle-specific clusters from 64 electrode activations of post-stroke individuals during a few gait cycles of a single walking task. Moreover, resulting muscle-specific EMG envelopes were electrophysiologically consistent for different walking speeds. Furthermore, the automated clustering provided EMG envelopes with the accuracy needed to drive an NMS modeling framework and estimate dynamically consistent ankle torques using unseen data. The technology proposed in this study opens new avenues for fast and quantitative musculoskeletal function assessment in neurologically impaired individuals.</p>
Proportional and Simultaneous Real-Time Control of the Full Human Hand From High-Density Electromyography
Authors: Sîmpetru Raul , März Michael , Vecchio Alessandro Del 
Published: January 2023

<p>Surface electromyography (sEMG) is a non-invasive technique that measures the electrical activity generated by the muscles using sensors placed on the skin. It has been widely used in the field of prosthetics and other assistive systems because of the physiological connection between muscle electrical activity and movement dynamics. However, most existing sEMG-based decoding algorithms show a limited number of detectable degrees of freedom that can be proportionally and simultaneously controlled in real-time, which limits the use of EMG in a wide range of applications, including prosthetics and other consumer-level applications (e.g., human/machine interfacing). In this work, we surpass the current state of the art by developing a new deep learning method that can decode and map the electrophysiological activity of the forearm muscles into proportional and simultaneous control of > 20 degrees of freedom of the human hand with real-time resolution and with latency within the neuromuscular delays (< 50 ms). We recorded the kinematics of the human hand during grasping, pinching, individual digit movements and three gestures at slow (0.5 Hz) and fast (0.75 Hz) movement speeds in healthy participants.</p>
<p>We demonstrate that our neural network can predict the kinematics of the hand in real-time at a constant 32 predictions per second. To achieve this, we employed transfer learning and created a prediction smoothing algorithm for the output of the neural network that reconstructed the full geometry of the hand in three-dimensional Cartesian space in real-time. Our results demonstrate that high-density EMG signals from the forearm muscles contain almost all the information that is needed to predict the kinematics of the human hand. The proposed method has the capability of predicting the full kinematics of the human hand in an unprecedented way and with real-time resolution with immediate translational impact in subjects with motor impairments. </p>
Optimization of Gang-operated On-load Tap Changers in Multi-conductor Radial Networks: Formulation and Convex Relaxation
Authors: Geth Frederik , Deconinck Geert , Claeys Sander 
Published: January 2023

<p>Unbalanced optimal power flow refers to mathematical optimization problems subject to the physics of grids with phase unbalance. They can serve as a core technology, or benchmark, for centralized or distributed optimal control solutions. In recent years, convex relaxations of this problem have attracted significant interest in the community. For many common test feeders, it turned out they return exact solutions. However, more research is needed to study how well this holds up in more complicated modelling contexts. This paper therefore studies gang-operated on-load tap changers in detail. Analogous to balanced optimal power flow, it is possible to reformulate the problem exactly without an explicit tap variable. This is a non-trivial result that is discussed in detail. Furthermore, this paper describes in detail how a solution in the lifted variable space can be projected back to the original variable space. Best case, it then becomes possible to solve the problem as a convex optimization problem instead. Worst case, it provides a lower bound on the objective value. Two numerical case studies, a simple test case and IEEE13, are included. The case studies are made publicly available. </p>
Critical Materials for Climate Technologies in the EU
Authors: Schmidt Patrick , Barkhausen Robin , Hofmann Alexander , Gervais Estelle , Heumann Johannes 
Published: January 2023

<p>Against the backdrop of the climate crisis, countries worldwide agreed in the Paris agreement to keep global warming below 2°C compared to the pre-industrial era, ideally below 1.5°C. The EU set out the goal to reach carbon neutrality by 2050 - a goal for which the energy sector will play a central role, as the production and use of energy is responsible for more than 75% of greenhouse gas emissions. To transition to low carbon energy production, photovoltaic and wind turbines, coupled with energy conversion technologies such as electrolysers, fuel cells, and batteries, are believed to be key solutions. But these technologies require substantial amounts of scarce raw materials with EU import dependency and environmental and social problems connected to extraction and refining. The vulnerability of the EU energy sector became apparent in 2022 at the example of its dependency on Russian oil and gas. The supply chain for clean energy technologies could be equally vulnerable and jeopardise the achievement of EU climate targets. </p>
<p>A plethora of studies dealing with resource scarcity has been performed. These studies, however, differ in their results regarding the most critical materials and often only provide vague recommendations on how to increase the resilience of the production and supply chains. Hence, it is of interest to synthesize the findings of major studies from renowned institutions, identify commonalities as well as differences, filter out areas with need for immediate action and create an overview of critical materials in climate technologies. </p>
MRI retrospective respiratory gating and cardiac sensing by CW Doppler radar: A feasibility study
Authors: Lee Wonje , Ryu Kanghyun , Li Zhitao , Wu Yuxin , Robb Fraser , Vasanawala Shreyas , pauly john , Scott Greig 
Published: January 2023

<p>This study investigates the feasibility of non-contact retrospective respiratory gating and cardiac sensing using continuous wave Doppler radar deployed in an MRI system. </p>
Compressing the Activation Maps in Deep Convolutional Neural Networks and the Regularization Effect of Compression
Authors: Vu Minh , Garpebring Anders , Nyholm Tufve , Löfstedt Tommy 
Published: January 2023

<p>Deep learning has dramatically improved performance in various image analysis applications in the last few years. However, recent deep learning architectures can be very large, with up to hundreds of layers and millions or even billions of model parameters that are impossible to fit into commodity graphics processing units. We propose a novel approach for compressing high-dimensional activation maps, the most memory-consuming part when training modern deep learning architectures. To this end, we also evaluated three different methods to compress the activation maps: Wavelet Transform, Discrete Cosine Transform, and Simple Thresholding. We performed experiments in two classification tasks for natural images and two semantic segmentation tasks for medical images. Using the proposed method, we could reduce the memory usage for activation maps by up to 95%. Additionally, we show that the proposed method induces a regularization effect that acts on the layer weight gradients. </p>
Analytic Theory of Current-Voltage Characteristics of OLEDs
Authors: Ahmed Khaled 
Published: January 2023

<p>The development of OLED displays is a non-ergodic process in which there is continuous novel change; and comprehending emitters that are evolving requires new theory, or at least modification of that which is already possessed. For the first time, a new data-validated closed-form physics-based expression is derived for the I-V characteristics of OLEDs in this paper. Two parameters emerge from the new model: liminal current and liminal voltage. Both parameters are expressed in terms of device and material parameters, allowing a device engineer to intuitively design experiments to target low voltage operation OLEDs. Robust parameter extraction methods are proposed and validated with experimental data</p>
Characterising the Blood Pressure Response to Physical Counterpressure Manoeuvres Using Surface Electromyography in Adults with Long Covid
Authors: Duggan Eoin , Jennings Glenn , Monaghan Ann , Byrne Lisa , Xue Feng , Romero-Ortuno roman 
Published: January 2023

<p>Objective: Orthostatic intolerance (OI) is common in Long Covid. Physical counterpressure manoeuvres (PCM) may improve OI in other disorders. We characterised the blood pressure-rising effect of PCM using surface electromyography (sEMG) and investigated its association with fatigue in adults with Long Covid. Methods: Participants performed an active stand with beat-to-beat hemodynamic monitoring and sEMG of both thighs, including PCM at 3-minutes post-stand. Multivariable linear regression investigated the association between change in systolic blood pressure (SBP) and change in normalised root mean square (RMS) of sEMG amplitude, controlling for confounders including the Chalder Fatigue Scale (CFQ). Results: In 90 participants (mean age 46), mean SBP rise with PCM was 13.7 (SD 9.0) mmHg. In regression, SBP change was significantly, directly associated with change in RMS sEMG (β=0.25, 95% CI 0.07–0.43, P=0.007); however, CFQ was not significant. Discussion/Conclusion: PCM measured by sEMG augmented SBP without the influence of fatigue. </p>
Over-the-Air Computing with Imperfect CSI: Design and Performance Optimization
Authors: Evgenidis Nikos , Papanikolaou Vasilis , Diamantoulakis Panagiotis D. , Karagiannidis George K. 
Published: January 2023

<p>Over-the-air computing (AirComp) has recently attracted considerable attention as an efficient method of data fusion by integrating uncoded communication transmissions with computation thanks to the signal superposition offered by the multiple access channels. However, appropriate processing is required to neutralize the wireless channel effect. As, internet-of-things (IoT) applications through low-cost devices is the main target of AirComp, perfect availability of channel state information (CSI) is not always practical, there is the need to investigate the effect of imperfect CSI on AirComp. Specifically, we present novel closed-form expressions for tight approximations that can be used to design and evaluate AirComp systems. Furthermore, we design a general optimization framework that takes into account both magnitude and phase errors in the CSI. Finally, a pilot retransmission policy is designed, that offers trade-off between resources cost and the gain in the accuracy of the computations. In order to validate its application, a utility function of the cost of retransmission is introduced, namely, <em>Retransmission Policy Cost (RPC)</em>, which can incorporate the power or throughput cost opposing to the expected gain of the selected policy. Simulations show the deterioration caused by the imperfect CSI and highlight the added value of the proposed policy under various system conditions. </p>
A Deterministic Approach to Approximate Computing on Stochastic Computing Hardware, with Reduced Sequence Lengths for Convolutional Neural Networks
Authors: Hekmatshoar Bahman 
Published: January 2023

<p>In this work, a deterministic sequence suitable for approximate computing on stochastic computing hardware is proposed and its effectiveness in achieving high accuracies with relatively short sequence lengths is studied for convolutional neural networks. It is shown that in the range of interest for neural network computations, multiplication errors can be lower than quantization errors with this approach. The sequence lengths required for achieving accuracies within ~0.5% of the floating-point baseline are of the order of 16 and 32 for CIFAR10 classification with VGG16 and ResNet20 networks, respectively, when all convolutions and matrix multiplications are performed using the proposed sequence. For ImageNet classification, the sequence lengths required for accuracies within ~1% of the floating-point baseline are of the order of 32 for MobileNetV1 and ResNet50 networks. This work suggests that stochastic computing hardware and approaches may be feasible for approximate neural network computations with higher accuracies, lower latencies and/or larger networks than previously reported. </p>