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Assistive technology with device for self-inflating bag in neonatology

Research on Biomedical engineering 2025年第2期41卷

作者： Marcelino, Ana Carolina Rodovanski, Giovana Pascoali Bonetti, Karoline Panes, Caio Rabinovich de Almeida Martins, Fernando Moran, Cristiane Aparecida Araranguá Brazil Graduate Program in Neurosciences and Behavior Department of Experimental Psychology of the Institute of Psychology-University of São Paulo Sao Paulo Brazil Araranguá Brazil Computer Engineering Instituto Mauá de Tecnologia São Caetano do Sul Brazil Electronic Engineering and Computing with Emphasis on Electronic Devices and Systems at Instituto Tecnológico de Aeronáutica–ITA São Caetano do Sul Brazil Department of Physiotheraphy and at the Postgraduate Program in Rehabilitation Science of the Federal University of Santa Catarina-UFCS Ararangua Brazil

Purpose: The objectives of this study were to create a device with technological development of the self-inflating bag (SIB) equipment to measure the variables tidal volume, peak inspiratory pressure, and inspiratory flow and to evaluate the knowledge of undergraduate students in handling the SIB. To reduce the risks of mortality, length of hospital stay, and infections, SIB is a resource used to ventilate the patient through the inflation of the device, but it is not capable of measuring the ventilatory parameters. Excess ventilation and incorrect handling of the bag can cause lung injury in newborns. Therefore, measuring these parameters can prevent lung injury resulting from inadequate ventilation. Method: This is a cross-sectional and experimental study, with the development of a device SIB that allows the evaluation of variables of neonatal respiratory mechanics that were tested with an artificial lung. It was approved by the Research Ethics Committee and the research was developed in three stages: the first represents the search for scientific articles for the consensus of neonatal ventilatory variables for the construction of the SIB parameters;the second stage depicts the technological development of a device capable of monitoring such variables through the SIB. In the third stage, the content validation of the device with the handling of the SIB was carried out by students of medicine and physiotherapy courses of Brazil. Results: In this work, a device that analyzes the values of the main ventilatory parameters in neonatology was developed and to generate a safety range for the use of the device, curves with a tolerance of 10% up and down were created. All electronic components were coupled to the equipment, with a display that transmits the parameter values. The web page can be used on a cell phone, tablet, computer, or SmartTv, as long as it is connected to the "RespiratorIoT_AP" network. Among the 29 participants in the study, 8 said they were familiar w

关键词： Students

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Variable-speed teaching–playback as real-world data augmentation for imitation learning

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Advanced Robotics 2025年

作者： Masuya, Nozomu Sato, Hiroshi Yamane, Koki Kusume, Takuya Sakaino, Sho Tsuji, Toshiaki Doctoral Program in Intelligent and Mechanical Interaction Systems Degree Programs in Systems and Information and Engineering Graduate School of Science and Technology University of Tsukuba Tsukuba Japan Master’s Program in Intelligent and Mechanical Interaction Systems Degree Programs in Systems and Information and Engineering Graduate School of Science and Technology University of Tsukuba Tsukuba Japan Department of Intelligent Interaction Technologies Institute of Systems and Information Engineering University of Tsukuba Tsukuba Japan Graduate School of Science and Engineering Saitama University Saitama Japan

Imitation learning’s inevitable reliance on human demonstrations in hard-to-simulate settings has resulted in a shortage of training data, even with a simple change in speed. Although the field of data augmentation has addressed the lack of data, conventional methods of data augmentation for robot manipulation are limited to simulation-based methods or downsampling for position control. This paper proposes a novel method of data augmentation that is applicable to force control and preserves the advantages of real-world datasets. We applied teaching–playback at variable speeds as real-world data augmentation to increase both the quantity and quality of environmental reactions at variable speeds. An experiment was conducted on bilateral control-based imitation learning using a method of imitation learning equipped with position–force control. We evaluated the effect of real-world data augmentation on two tasks, pick-and-place and wiping, at variable speeds, each from two human demonstrations at fixed speed. The results showed that generation of variable-speed movement from human demonstrations with less than 10% variety of durations is feasible, and improved success rate and accuracy along the duration/frequency command by gathering environmental reactions at variable speeds, rather than simply altering speeds of gathered data. © 2025 Informa UK Limited, trading as Taylor & Francis Group and The Robotics Society of Japan.

关键词： Demonstrations

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A Zero Harmonic Distortion Grid-Connected Grid-Forming Converter for Battery Energy Storage System Applications

A Zero Harmonic Distortion Grid-Connected Grid-Forming Conve...

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Annual IEEE Conference on Applied Power Electronics Conference and Exposition (APEC)

作者： Gabriel V. Ramos Thiago M. Parreiras Fangzhou Zhao Xiongfei Wang Braz de J. C. Filho Graduate Program in Electrical Engineering - Universidade Federal de Minas Gerais Belo Horizonte MG Brazil Department of Electrical Engineering Centro Federal de Educação Tecnológica de Minas Gerais Belo Horizonte Brazil Department of Energy Aalborg University Aalborg Denmark Division of Electric Power and Energy Systems KTH Royal Institute of Technology Stockholm Sweden Department of Electrical Engineering Universidade Federal de Minas Gerais Belo Horizonte Brazil

ISBN: (数字)9798331516116

ISBN: (纸本)9798331516123

The work proposes the Zero Harmonic Distortion Converter (ZHD) as a grid-connected grid-forming (GFM) converter due to its unique sinusoidal characteristic without capacitive filters, low parts count, and off-the-shelf power circuitry with a simple open-loop control structure that does not contribute to possible control interaction and resonances in grid-connected mode. These characteristic are reached by a harmonic cancellation in a three-winding transformer along with harmonic elimination using the Selective Harmonic Elimination Pulse Width Modulation (SHE PWM). The ZHD GFM converter is a compelling alternative for GFM battery energy storage systems (BESS) in medium-voltage applications.

关键词： Filters Battery energy storage system Medium voltage Pulse width modulation Harmonic analysis Harmonic distortion Voltage control Power harmonic filters Grid forming Voltage-source converters

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Feedback-responsive cell factories for dynamic modulation of the unfolded protein response

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Nature Communications 2025年第1期16卷 1-17页

作者： Barrios, Daniela Bachhav, Bhagyashree Carlos-Alcalde, Wendolyn Llanos, Carlos D. Zhou, Wenchang Segatori, Laura Department of Bioengineering Rice University Houston TX United States Department of Chemical and Biomolecular Engineering Rice University Houston TX United States Department of BioSciences Rice University Houston TX United States Systems Synthetic and Physical Biology Graduate Program Rice University Houston TX United States

engineering cell factories that support the production of large quantities of protein therapeutics remains a significant biomanufacturing challenge. The overexpression of secretory proteins causes proteotoxic stress, affecting cell viability and protein productivity. Proteotoxic stress leads to the activation of the Unfolded Protein Response (UPR), a series of signal transduction pathways regulating protein quality control mechanisms aimed at restoring homeostasis. Sustained UPR activation culminates with the induction of apoptosis. Current strategies for enhancing the production of therapeutic proteins have focused on the deregulated modulation of key components of the UPR. These strategies have resulted in limited and often protein-specific improvements as they may lead to adaptation and cell toxicity and do not account for natural population heterogeneities. We report here feedback-responsive cell factories that sense proteotoxic stress and, in response, modulate the UPR to enhance stress attenuation and delay cell death, addressing the limitations of current strategies. We demonstrate that our cell engineering approach enables dynamic UPR modulation upon proteotoxic stress. The sense-and-respond systems that mediate dynamic UPR modulation enhance the production of the therapeutic enzyme tissue plasminogen activator and the bispecific antibody blinatumomab. Our feedback-responsive cell factories provide an innovative strategy for dynamically adjusting the innate cellular stress response and enhancing therapeutic protein manufacturing. © The Author(s) 2025.

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Framework of decision in data modeling for quality improvement

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TQM Journal 2015年第1期27卷 135-149页

作者： Sant'Anna, Ângelo Márcio Oliveira Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana Curitiba Brazil

Purpose - The purpose of this paper is to propose a framework of decision making to aid practitioners in modeling and optimization experimental data for improvement quality of industrial processes, reinforcing idea that planning and conducting data modeling are as important as formal ***/methodology/approach - The paper presents an application was carried out about the modeling of experimental data at mining company, with support at Catholic University from partnership projects. The literature seems to be more focussed on the data analysis than on providing a sequence of operational steps or decision support which would lead to the best regression model given for the problem that researcher is confronted with. The authors use the concept of statistical regression technique called generalized linear ***/value - An essential point is that the study is based on the feedback from practitioners and industrial managers, which makes the analyses and conclusions from practical points of view, without relevant theoretical knowledge of relationship among the process variables. Regression model has its own characteristics related to response variable and factors, and misspecification of the regression model or their components can yield inappropriate inferences and erroneous experimental *** - The authors analyze the relevant case study in mining company, based on best statistical regression models. Starting from this analysis, the results of the industrial case study illustrates the strong relationship of the improvement process with the presented framework approach into practice. Moreover, the case study consolidating a fundamental advantage of regression models: modeling guided provides more knowledge about products, processes and technologies, even in unsuccessful case *** limitations/implications - The study advances in regression model for data modeling are applicable in several types of industrial processes and phenom

关键词： Regression analysis

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Drivetrain simulation using variational autoencoders

arXiv

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arXiv 2025年

作者： Sharma, Pallavi Urrea-Quintero, Jorge-Humberto Bogdan, Bogdan Ciotec, Adrian-Dumitru Vasilie, Laura Wessels, Henning Skull, Matteo Porsche Engineering Etzelstraße 1 Bietigheim-Bissingen74321 Germany Graduate Program Computational Sciences in Engineering Technische Universität Braunschweig Braunschweig Germany Fraunhofer Institute for Energy Economics and Energy System Technology Joseph-Beuys-Straße 8 Kassel34117 Germany Institute of Applied Mechanics Division Data-Driven Modeling of Mechanical Systems Technische Universität Braunschweig Pockelsstraße 3 Braunschweig38106 Germany

This work proposes variational autoencoders (VAEs) to predict a vehicle’s jerk from a given torque demand, addressing the limitations of sparse real-world datasets. Specifically, we implement unconditional and conditional VAEs to generate jerk signals that integrate features from different drivetrain scenarios. The VAEs are trained on experimental data collected from two variants of a fully electric SUV, which differ in maximum torque delivery and drivetrain configuration. New meaningful jerk signals are generated within an engineering context through the interpretation of the VAE’s latent space. A performance comparison with baseline physics-based and hybrid models confirms the effectiveness of the VAEs. We show that VAEs bypass the need for exhaustive manual system parametrization while maintaining physical plausibility by conditioning data generation on specific inputs. © 2025, CC BY.

关键词： Signal encoding

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Wind speed forecasting approach using conformal prediction and feature importance selection

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International Journal of Electrical Power and Energy systems 2025年 168卷

作者： Zuege, Cesar Vinicius Stefenon, Stefano Frizzo Yamaguchi, Cristina Keiko Mariani, Viviana Cocco Gonzalez, Gabriel Villarrubia Coelho, Leandro dos Santos Graduate Program in Electrical Engineering Federal University of Parana PR Curitiba Brazil Postgraduate Program in Productive Systems in Association with UNIPLAC UNC UNESC and UNIVILLE SC Brazil Department of Electrical Engineering Federal University of Parana PR Curitiba Brazil Graduate Program in Mechanical Engineering Federal University of Parana PR Curitiba Brazil Expert Systems and Applications Lab Faculty of Science University of Salamanca Salamanca37008 Spain

Wind energy is a rising renewable energy source that plays an important role in the transition to a more sustainable energy system. Variation in wind power generation is one of the main challenges facing this energy source. Wind forecasting approaches are essential for planning and operating wind farms, but are complex due to the dynamic nature of the wind and the influence of local factors. This paper evaluates short-term forecasting of time series with a measure of uncertainty associated with wind speeds. The proposed method considers the conformal prediction approach and, based on Shapley values, uses optimal selection of features given their importance. Furthermore, a Bayesian Optimization with Tree-structured Parzen Estimators (BO-TPE) will be used to tune the hyperparameters of the models. The results showed that using Variational Mode Decomposition (VMD) allied with Singular Spectrum Analysis (SSA) to feed into a conformal prediction model improved the performance of the model. Taking into account a Beutenberg data set, Germany, the best model was Light Gradient Boosting Machine (LGBM)-VMD-SSA without partial fit, resulting in a root mean squared error (RMSE) criterion of 0.25031, coverage measure of 94.4%, and width measure of 1.008. When considering a dataset from Limoeiro, Brazil, the best model was also LGBM-VMD-SSA without partial fit, resulting in an RMSE of 0.21597, a coverage of 90.3%, and a width of 0.678. SHapley Additive exPlanations (SHAP) bring explainability to the model results. The models proposed in this study, hypertuned by BO-TPE with interpretable results based on SHAP, can be useful in predicting wind speed and power generation. © 2025 The Authors

关键词： Windmill

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Adaptive Contextual Caching for Mobile Edge Large Language Model Service

arXiv

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arXiv 2025年

作者： Liu, Guangyuan Liu, Yinqiu Wang, Jiacheng Du, Hongyang Niyato, Dusit Kang, Jiawen Xiong, Zehui College of Computing and Data Science The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore College of Computing and Data Science Nanyang Technological University Singapore Department of Electrical and Electronic Engineering University of Hong Kong Hong Kong School of Automation Guangdong University of Technology China Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore

Mobile edge Large Language Model (LLM) deployments face inherent constraints, such as limited computational resources and network bandwidth. Although Retrieval-Augmented Generation (RAG) mitigates some challenges by integrating external knowledge bases, inefficient cache management can still result in high retrieval latency and frequent cache updates. To address these issues, we propose an Adaptive Contextual Caching (ACC) framework that anticipates user needs by proactively caching semantically relevant data for mobile-edge LLMs. ACC utilizes a deep reinforcement learning (DRL) module to refine cache replacement policies, balancing user context, document similarity, and the overhead associated with cache misses. Experimental results demonstrate that ACC increases cache hit rates to over 80% after only 11 training episodes, outperforming FIFO, LRU, and semantic-only caching while reducing retrieval latency by up to 40%. In particular, ACC also reduces local caching overhead (i.e., the cost of updating the cache when a miss occurs) by as much as 55%, enabling scalable, low-latency LLM services in resource-constrained edge environments. © 2025, CC BY.

关键词： Deep reinforcement learning

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Combining of chaotic differential evolution and quadratic programming for economic dispatch optimization with valve-point effect (vol 21, pg 989, 2006)

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IEEE TRANSACTIONS ON POWER systems 2006年第3期21卷 1465-1465页

作者： dos Santos Coelho, Leandro Cocco Mariani, Viviana Production and Systems Engineering Graduate Program Automation and Systems Laboratory PUCPRJCCET/PPGEPSILAS Pontifical Catholic University of Paraná 802 15-901 Curitiba Paraná Brazil Mechanical Engineering Graduate Program PUCPRJCCETIPPGEM Pontifical Catholic University of Paraná 802 15-901 Curitiba Paraná Brazil

Evolutionary algorithms are heuristic methods that have yielded promising results for solving nonlinear, nondifferentiable, and multi-modal optimization problems in the power systems area. The differential evolution (DE) algorithm is an evolutionary algorithm that uses a rather greedy and less stochastic approach to problem solving than do classical evolutionary algorithms, such as genetic algorithms, evolutionary programming, and evolution strategies. DE also incorporates an efficient way of self-adapting mutation using small populations. The potentialities of DE are its simple structure, easy use, convergence property, quality of solution, and robustness. This paper proposes a new approach for solving economic load dispatch problems with valve-point effect. The proposed method combines the DE algorithm with the generator of chaos sequences and sequential quadratic programming (SQP) technique to optimize the performance of economic dispatch problems. The DE with chaos sequences is the global optimizer, and the SQP is used to fine-tune the DE run in a sequential manner. The combined methodology and its variants are validated for two test systems consisting of 13 and 40 thermal units whose incremental fuel cost function takes into account the valve-point loading effects. The proposed combined method outperforms other state-of-the-art algorithms in solving load dispatch problems with the valve-point effect. [ABSTRACT FROM AUTHOR]

关键词： Chaotic sequences differential evolution (DE) economic dispatch evolutionary algorithms optimization power generation valve-point effect

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Resolution of one-dimensional bin packing problems using augmented neural networks and minimum bin slack

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International Journal of Innovative Computing and Applications 2016年第4期7卷 214-224页

作者： de Almeida, Ricardo Steiner, Maria Teresinha Arns Industrial and Systems Engineering Post-Graduate Program Pontifical Catholic University of Paraná - PUCPR Curitiba Brazil

The objective of this work is to compare the augmented neural network (AugNN) metaheuristic to minimum bin slack (MBS) heuristic to solve combinatorial optimisation problems, specifically, in this case, the one-dimensional bin packing problem (1D-BPP), a class of cutting and packing problems (CPP). CPP are easily found among various industry sectors and its proper treatment can improve the use of stocks in cutting problems or optimise physical space in packing problems. In order to optimise AugNN parameters, a design of experiment (DOE) was applied in order to guide a statistical analysis of different configurations of AugNN. The tests, developed in many benchmark problems found in the literature, showed that MBS heuristic was, in general superior, both in terms of the solution quality, which is about 70% better, and computational time, which is about 90% less. Copyright © 2016 Inderscience Enterprises Ltd.

关键词： Design of experiments

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