Wei Li, Jingzhe Wang, Hao Bai, Yongqian Yan, Min Xu, Yipeng Liu, Hao Wang, Wei Huang, Chunyan Li
With the rapid development of distribution networks and increasing demand for electricity, the pressure of power supply for medium- and low-voltage distribution networks (M&LVDNs) is increasingly significant, especially considering the large scale of customers at the low-voltage (LV) level. In this paper, an outage sequence optimization method for low-voltage distribution networks (LVDNs) that considers the importance of users is proposed. The method aims to develop an optimal outage sequence strategy for LV customers in case of medium-voltage (MV) failure events. First, a multi-dimensional importance indicator system for LV users is constructed, and the customers are ranked using a modified Analytic Hierarchy Process–Entropy Weight (AHP-EW) method to determine their priorities during outages. Then, an elastic net regression-based method is used to identify the topology of the LV network. Finally, an outage sequence optimization model based on the user importance is proposed to reduce the load-shedding level. Extensive case studies are conducted in the modified LV distribution network. The results show that the proposed method results in fewer outage losses throughout the restoration periods than traditional methods and effectively improves the reliability of the power supply to LV users.
{"title":"Optimization Strategy for an Outage Sequence in Medium- and Low-Voltage Distribution Networks Considering the Importance of Users","authors":"Wei Li, Jingzhe Wang, Hao Bai, Yongqian Yan, Min Xu, Yipeng Liu, Hao Wang, Wei Huang, Chunyan Li","doi":"10.3390/app14188386","DOIUrl":"https://doi.org/10.3390/app14188386","url":null,"abstract":"With the rapid development of distribution networks and increasing demand for electricity, the pressure of power supply for medium- and low-voltage distribution networks (M&LVDNs) is increasingly significant, especially considering the large scale of customers at the low-voltage (LV) level. In this paper, an outage sequence optimization method for low-voltage distribution networks (LVDNs) that considers the importance of users is proposed. The method aims to develop an optimal outage sequence strategy for LV customers in case of medium-voltage (MV) failure events. First, a multi-dimensional importance indicator system for LV users is constructed, and the customers are ranked using a modified Analytic Hierarchy Process–Entropy Weight (AHP-EW) method to determine their priorities during outages. Then, an elastic net regression-based method is used to identify the topology of the LV network. Finally, an outage sequence optimization model based on the user importance is proposed to reduce the load-shedding level. Extensive case studies are conducted in the modified LV distribution network. The results show that the proposed method results in fewer outage losses throughout the restoration periods than traditional methods and effectively improves the reliability of the power supply to LV users.","PeriodicalId":8224,"journal":{"name":"Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142249222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Luca Muscarà, Marco Cisternino, Andrea Ferrero, Andrea Iob, Francesco Larocca
The prediction of separated flows at low Reynolds numbers is crucial for several applications in aerospace and energy fields. Reynolds-averaged Navier–Stokes (RANS) equations are widely used but their accuracy is limited in the presence of transition or separation. In this work, two different strategies for improving RANS simulations by means of field inversion are discussed. Both strategies require solving an optimization problem to identify a correction field by minimizing the error on some measurable data. The obtained correction field is exploited with two alternative strategies. The first strategy aims to the identification of a relation that allows to express the local correction field as a function of some local flow features. However, this regression can be difficult or even impossible because the relation between the assumed input variables and the local correction could not be a function. For this reason, an alternative is proposed: a U-Net model is trained on the original and corrected RANS results. In this way, it is possible to perform a prediction with the original RANS model and then correct it by means of the U-Net. The methodologies are evaluated and compared on the flow around the NACA0021 and the SD7003 airfoils.
{"title":"A Comparison of Local and Global Strategies for Exploiting Field Inversion on Separated Flows at Low Reynolds Number","authors":"Luca Muscarà, Marco Cisternino, Andrea Ferrero, Andrea Iob, Francesco Larocca","doi":"10.3390/app14188382","DOIUrl":"https://doi.org/10.3390/app14188382","url":null,"abstract":"The prediction of separated flows at low Reynolds numbers is crucial for several applications in aerospace and energy fields. Reynolds-averaged Navier–Stokes (RANS) equations are widely used but their accuracy is limited in the presence of transition or separation. In this work, two different strategies for improving RANS simulations by means of field inversion are discussed. Both strategies require solving an optimization problem to identify a correction field by minimizing the error on some measurable data. The obtained correction field is exploited with two alternative strategies. The first strategy aims to the identification of a relation that allows to express the local correction field as a function of some local flow features. However, this regression can be difficult or even impossible because the relation between the assumed input variables and the local correction could not be a function. For this reason, an alternative is proposed: a U-Net model is trained on the original and corrected RANS results. In this way, it is possible to perform a prediction with the original RANS model and then correct it by means of the U-Net. The methodologies are evaluated and compared on the flow around the NACA0021 and the SD7003 airfoils.","PeriodicalId":8224,"journal":{"name":"Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142249217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper proposes a new robust model for text classification on the Stanford Sentiment Treebank v2 (SST-2) dataset in terms of model accuracy. We developed a Recurrent Neural Network Bert based (RNN_Bert_based) model designed to improve classification accuracy on the SST-2 dataset. This dataset consists of movie review sentences, each labeled with either positive or negative sentiment, making it a binary classification task. Recurrent Neural Networks (RNNs) are effective for text classification because they capture the sequential nature of language, which is crucial for understanding context and meaning. Bert excels in text classification by providing bidirectional context, generating contextual embeddings, and leveraging pre-training on large corpora. This allows Bert to capture nuanced meanings and relationships within the text effectively. Combining Bert with RNNs can be highly effective for text classification. Bert’s bidirectional context and rich embeddings provide a deep understanding of the text, while RNNs capture sequential patterns and long-range dependencies. Together, they leverage the strengths of both architectures, leading to improved performance on complex classification tasks. Next, we also developed an integration of the Bert model and a K-Nearest Neighbor based (KNN_Bert_based) method as a comparative scheme for our proposed work. Based on the results of experimentation, our proposed model outperforms traditional text classification models as well as existing models in terms of accuracy.
{"title":"Improving the Accuracy and Effectiveness of Text Classification Based on the Integration of the Bert Model and a Recurrent Neural Network (RNN_Bert_Based)","authors":"Chanthol Eang, Seungjae Lee","doi":"10.3390/app14188388","DOIUrl":"https://doi.org/10.3390/app14188388","url":null,"abstract":"This paper proposes a new robust model for text classification on the Stanford Sentiment Treebank v2 (SST-2) dataset in terms of model accuracy. We developed a Recurrent Neural Network Bert based (RNN_Bert_based) model designed to improve classification accuracy on the SST-2 dataset. This dataset consists of movie review sentences, each labeled with either positive or negative sentiment, making it a binary classification task. Recurrent Neural Networks (RNNs) are effective for text classification because they capture the sequential nature of language, which is crucial for understanding context and meaning. Bert excels in text classification by providing bidirectional context, generating contextual embeddings, and leveraging pre-training on large corpora. This allows Bert to capture nuanced meanings and relationships within the text effectively. Combining Bert with RNNs can be highly effective for text classification. Bert’s bidirectional context and rich embeddings provide a deep understanding of the text, while RNNs capture sequential patterns and long-range dependencies. Together, they leverage the strengths of both architectures, leading to improved performance on complex classification tasks. Next, we also developed an integration of the Bert model and a K-Nearest Neighbor based (KNN_Bert_based) method as a comparative scheme for our proposed work. Based on the results of experimentation, our proposed model outperforms traditional text classification models as well as existing models in terms of accuracy.","PeriodicalId":8224,"journal":{"name":"Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142249223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Malaria is a leading cause of morbidity and mortality in tropical and sub-tropical regions. This research proposed a malaria diagnosis system based on the you only look once algorithm for malaria parasite detection and the convolutional neural network algorithm for malaria parasite life stage classification. Two public datasets are utilized: MBB and MP-IDB. The MBB dataset includes human blood smears infected with Plasmodium vivax (P. vivax). While the MP-IDB dataset comprises 4 species of malaria parasites: P. vivax, P. ovale, P. malariae, and P. falciparum. Four distinct stages of life exist in every species, including ring, trophozoite, schizont, and gametocyte. For the MBB dataset, detection and classification accuracies of 0.92 and 0.93, respectively, were achieved. For the MP-IDB dataset, the proposed algorithms yielded the accuracies for detection and classification as follows: 0.84 and 0.94 for P. vivax; 0.82 and 0.93 for P. ovale; 0.79 and 0.93 for P. malariae; and 0.92 and 0.96 for P. falciparum. The detection results showed the models trained by P. vivax alone provide good detection capabilities also for other species of malaria parasites. The classification performance showed the proposed algorithms yielded good malaria parasite life stage classification performance. The future directions include collecting more data and exploring more sophisticated algorithms.
{"title":"Staining-Independent Malaria Parasite Detection and Life Stage Classification in Blood Smear Images","authors":"Tong Xu, Nipon Theera-Umpon, Sansanee Auephanwiriyakul","doi":"10.3390/app14188402","DOIUrl":"https://doi.org/10.3390/app14188402","url":null,"abstract":"Malaria is a leading cause of morbidity and mortality in tropical and sub-tropical regions. This research proposed a malaria diagnosis system based on the you only look once algorithm for malaria parasite detection and the convolutional neural network algorithm for malaria parasite life stage classification. Two public datasets are utilized: MBB and MP-IDB. The MBB dataset includes human blood smears infected with Plasmodium vivax (P. vivax). While the MP-IDB dataset comprises 4 species of malaria parasites: P. vivax, P. ovale, P. malariae, and P. falciparum. Four distinct stages of life exist in every species, including ring, trophozoite, schizont, and gametocyte. For the MBB dataset, detection and classification accuracies of 0.92 and 0.93, respectively, were achieved. For the MP-IDB dataset, the proposed algorithms yielded the accuracies for detection and classification as follows: 0.84 and 0.94 for P. vivax; 0.82 and 0.93 for P. ovale; 0.79 and 0.93 for P. malariae; and 0.92 and 0.96 for P. falciparum. The detection results showed the models trained by P. vivax alone provide good detection capabilities also for other species of malaria parasites. The classification performance showed the proposed algorithms yielded good malaria parasite life stage classification performance. The future directions include collecting more data and exploring more sophisticated algorithms.","PeriodicalId":8224,"journal":{"name":"Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142249271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mohamed Badawy, Nada H. Sherief, Ayman A. Abdel-Hamid
As security breaches are increasingly widely reported in today’s culture, cybersecurity is gaining attention on a global scale. Threat modeling methods (TMM) are a proactive security practice that is essential for pinpointing risks and limiting their impact. This paper proposes a hybrid threat modeling framework based on system-centric, attacker-centric, and risk-centric approaches to identify threats in Operational Technology (OT) applications. OT is made up of software and hardware used to manage, secure, and control industrial control systems (ICS), and its environments include factories, power plants, oil and gas refineries, and pipelines. To visualize the “big picture” of its infrastructure risk profile and improve understanding of the full attack surface, the proposed framework builds on several threat modeling methodologies: PASTA modeling, STRIDE, and attack tree components. Nevertheless, the continuity and stability of vital infrastructure will continue to depend heavily on legacy equipment. Thus, protecting the availability, security, and safety of industrial environments and vital infrastructure from cyberattacks requires operational technology (OT) cybersecurity. The feasibility of the proposed approach is illustrated with a case study from a real oil and gas production plant control system where numerous significant cyberattacks in recent years have targeted OT networks more frequently as hackers realized the possibility of disruption due to insufficient OT security, particularly for outdated systems. The proposed framework achieved better results in detecting threats and severity in the design of the case study system, helping to increase security and support cybersecurity assessment of legacy control systems.
在当今文化中，安全漏洞的报道越来越多，网络安全在全球范围内日益受到关注。威胁建模方法（TMM）是一种积极主动的安全实践，对于准确定位风险并限制其影响至关重要。本文提出了一种基于以系统为中心、以攻击者为中心和以风险为中心的混合威胁建模框架，用于识别操作技术（OT）应用中的威胁。OT 由用于管理、保护和控制工业控制系统 (ICS) 的软件和硬件组成，其环境包括工厂、发电厂、油气精炼厂和管道。为了使基础设施风险概况的 "全貌 "可视化，并提高对整个攻击面的理解，拟议框架建立在几种威胁建模方法的基础上：PASTA 建模、STRIDE 和攻击树组件。然而，重要基础设施的连续性和稳定性仍将在很大程度上依赖于传统设备。因此，要保护工业环境和重要基础设施的可用性、安全性和安全免受网络攻击，就需要操作技术（OT）网络安全。近年来，由于黑客意识到 OT 安全性不足（尤其是过时的系统）有可能造成破坏，因此针对 OT 网络的重大网络攻击日益频繁。在案例研究系统的设计中，建议的框架在检测威胁和严重性方面取得了更好的效果，有助于提高安全性并支持对传统控制系统进行网络安全评估。
{"title":"Legacy ICS Cybersecurity Assessment Using Hybrid Threat Modeling—An Oil and Gas Sector Case Study","authors":"Mohamed Badawy, Nada H. Sherief, Ayman A. Abdel-Hamid","doi":"10.3390/app14188398","DOIUrl":"https://doi.org/10.3390/app14188398","url":null,"abstract":"As security breaches are increasingly widely reported in today’s culture, cybersecurity is gaining attention on a global scale. Threat modeling methods (TMM) are a proactive security practice that is essential for pinpointing risks and limiting their impact. This paper proposes a hybrid threat modeling framework based on system-centric, attacker-centric, and risk-centric approaches to identify threats in Operational Technology (OT) applications. OT is made up of software and hardware used to manage, secure, and control industrial control systems (ICS), and its environments include factories, power plants, oil and gas refineries, and pipelines. To visualize the “big picture” of its infrastructure risk profile and improve understanding of the full attack surface, the proposed framework builds on several threat modeling methodologies: PASTA modeling, STRIDE, and attack tree components. Nevertheless, the continuity and stability of vital infrastructure will continue to depend heavily on legacy equipment. Thus, protecting the availability, security, and safety of industrial environments and vital infrastructure from cyberattacks requires operational technology (OT) cybersecurity. The feasibility of the proposed approach is illustrated with a case study from a real oil and gas production plant control system where numerous significant cyberattacks in recent years have targeted OT networks more frequently as hackers realized the possibility of disruption due to insufficient OT security, particularly for outdated systems. The proposed framework achieved better results in detecting threats and severity in the design of the case study system, helping to increase security and support cybersecurity assessment of legacy control systems.","PeriodicalId":8224,"journal":{"name":"Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142249266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A bi-Gamma distribution model is proposed to determine the probability density function (PDF) of broadband non-Gaussian random stress rainflow ranges during vibration fatigue. A series of stress Power Spectral Densities (PSD) are provided, and the corresponding Gaussian random stress time histories are generated using the inverse Fourier transform and time-domain randomization methods. These Gaussian random stress time histories are then transformed into non-Gaussian random stress time histories. The probability density values of the stress ranges are obtained using the rainflow counting method, and then the bi-Gamma distribution PDF model is fitted to these values to determine the model’s parameters. The PSD parameters and the kurtosis, along with their corresponding model parameters, constitute the neural network input–output dataset. The neural network model established after training can directly provide the parameter values of the bi-Gamma model based on the input PSD parameters and kurtosis, thereby obtaining the PDF of the stress rainflow ranges. The predictive capability of the neural network model is verified and the effects of non-Gaussian random stress with different kurtosis on the structural fatigue life are compared for the same stress PSD. And all life predicted results were within the second scatter band.
{"title":"A bi-Gamma Distribution Model for a Broadband Non-Gaussian Random Stress Rainflow Range Based on a Neural Network","authors":"Jie Wang, Huaihai Chen","doi":"10.3390/app14188376","DOIUrl":"https://doi.org/10.3390/app14188376","url":null,"abstract":"A bi-Gamma distribution model is proposed to determine the probability density function (PDF) of broadband non-Gaussian random stress rainflow ranges during vibration fatigue. A series of stress Power Spectral Densities (PSD) are provided, and the corresponding Gaussian random stress time histories are generated using the inverse Fourier transform and time-domain randomization methods. These Gaussian random stress time histories are then transformed into non-Gaussian random stress time histories. The probability density values of the stress ranges are obtained using the rainflow counting method, and then the bi-Gamma distribution PDF model is fitted to these values to determine the model’s parameters. The PSD parameters and the kurtosis, along with their corresponding model parameters, constitute the neural network input–output dataset. The neural network model established after training can directly provide the parameter values of the bi-Gamma model based on the input PSD parameters and kurtosis, thereby obtaining the PDF of the stress rainflow ranges. The predictive capability of the neural network model is verified and the effects of non-Gaussian random stress with different kurtosis on the structural fatigue life are compared for the same stress PSD. And all life predicted results were within the second scatter band.","PeriodicalId":8224,"journal":{"name":"Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142249177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Gilberto Calvillo, Marco A. Panduro, Elizvan Juarez, Alberto Reyna, Carlos del Rio
New configurations of 2-D phased arrays are proposed in this paper for reducing the number of phase shifters. This design methodology is based on the use of a novel coherently radiating periodic structures (CORPSs) block for 2-D phased arrays. Two new antenna systems for 2-D phased arrays are studied and analyzed utilizing the CORPSs blocks of four inputs and nine outputs. These CORPSs feeding blocks are applied in a smart way to feed the planar antenna arrays by generating the required phase plane and reducing the number of control ports. Interesting results are provided based on the experimental measurements and full-wave simulations. These results illustrate a great reduction of the active devices (phase shifters), providing a good design compromise in terms of the scanning range and side lobe level performance. Furthermore, the provided results illustrate a maximum reduction capability in the number of phase shifters of 81%, considering a scanning range of ±30° in azimuth and ±30° in elevation. A raised cosine distribution is applied to reach side lobe levels of −19 dB for ±18° and −17 dB for ±30° in elevation. These benefits could be of interest to designers of phased antenna systems.
{"title":"A Design Proposal Using Coherently Radiating Periodic Structures (CORPSs) for 2-D Phased Arrays of Limited Scanning","authors":"Gilberto Calvillo, Marco A. Panduro, Elizvan Juarez, Alberto Reyna, Carlos del Rio","doi":"10.3390/app14188409","DOIUrl":"https://doi.org/10.3390/app14188409","url":null,"abstract":"New configurations of 2-D phased arrays are proposed in this paper for reducing the number of phase shifters. This design methodology is based on the use of a novel coherently radiating periodic structures (CORPSs) block for 2-D phased arrays. Two new antenna systems for 2-D phased arrays are studied and analyzed utilizing the CORPSs blocks of four inputs and nine outputs. These CORPSs feeding blocks are applied in a smart way to feed the planar antenna arrays by generating the required phase plane and reducing the number of control ports. Interesting results are provided based on the experimental measurements and full-wave simulations. These results illustrate a great reduction of the active devices (phase shifters), providing a good design compromise in terms of the scanning range and side lobe level performance. Furthermore, the provided results illustrate a maximum reduction capability in the number of phase shifters of 81%, considering a scanning range of ±30° in azimuth and ±30° in elevation. A raised cosine distribution is applied to reach side lobe levels of −19 dB for ±18° and −17 dB for ±30° in elevation. These benefits could be of interest to designers of phased antenna systems.","PeriodicalId":8224,"journal":{"name":"Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142249278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Itziar Salas-Reguera, José I. Rodríguez-Barbosa, Peter A. Federolf, Luis Santos
This study’s goals were to determine the health status of a group of heart transplant recipients (HTRs) and their level of physical activity and to compare the health status among them and with a group of healthy sedentary individuals. Fifty-four HTRs and eighteen sedentary individuals (S) were assigned to four groups, according to their level of physical activity (determined with the International Physical Activity Questionnaire); patients with a low, moderate, and high level of physical activity (HTRL, HTRM, and HTRH, respectively) and S participants underwent a basic blood analysis and several tests to assess their cardiovascular, neuromuscular, and functional mobility condition and their quality of life. The S and HTRH were very similar in terms of BP, HR, and blood analysis while HTRM and HTRL differed from both S and HTRH in these parameters. Regarding the cardiovascular, neuromuscular, functional mobility, and quality of life variables assessed in this study, HTRH showed the best results across all of them, followed by S, HTRM, and HTRL. It is suggested that the weekly level of physical activity of HTRs should be high, which might help them to enhance their health and quality of life.
{"title":"Comparative Analysis of the Health Status of Heart Transplant Patients with Different Levels of Physical Activity","authors":"Itziar Salas-Reguera, José I. Rodríguez-Barbosa, Peter A. Federolf, Luis Santos","doi":"10.3390/app14188379","DOIUrl":"https://doi.org/10.3390/app14188379","url":null,"abstract":"This study’s goals were to determine the health status of a group of heart transplant recipients (HTRs) and their level of physical activity and to compare the health status among them and with a group of healthy sedentary individuals. Fifty-four HTRs and eighteen sedentary individuals (S) were assigned to four groups, according to their level of physical activity (determined with the International Physical Activity Questionnaire); patients with a low, moderate, and high level of physical activity (HTRL, HTRM, and HTRH, respectively) and S participants underwent a basic blood analysis and several tests to assess their cardiovascular, neuromuscular, and functional mobility condition and their quality of life. The S and HTRH were very similar in terms of BP, HR, and blood analysis while HTRM and HTRL differed from both S and HTRH in these parameters. Regarding the cardiovascular, neuromuscular, functional mobility, and quality of life variables assessed in this study, HTRH showed the best results across all of them, followed by S, HTRM, and HTRL. It is suggested that the weekly level of physical activity of HTRs should be high, which might help them to enhance their health and quality of life.","PeriodicalId":8224,"journal":{"name":"Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142249218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Dane A. L. Miller, Hirotaka Uchitomi, Yoshihiro Miyake
Aging often leads to elderly gait characterized by slower speeds, shorter strides, and increased cycle; improving gait can significantly enhance the quality of life. Early gait training can help reduce gait impairment later on. Augmented reality (AR) technologies have shown promise in gait training, providing real-time feedback and guided exercises to improve walking patterns and gait parameters. The aim of this study was to observe the effects of gradual spatial and temporal cues provided by a synchronized walking avatar on the gait of elderly participants. This experiment involved 19 participants aged over 70 years, who walked while interacting with a synchronized walking avatar that provided audiovisual spatial and temporal cues. Spatial cueing and temporal cueing were provided through distance changes and phase difference changes, respectively. The WalkMate AR system was used to synchronize the avatar’s walking cycle with the participants’, delivering auditory cues matched to foot contacts. This study assessed the immediate and carry-over effects of changes in distance and phase difference on stride length, cycle time, and gait speed. The results indicate that gradual spatial and temporal cueing significantly influences elderly gait parameters, with potential applications in gait rehabilitation and training.
衰老通常会导致老年人步态特征为速度变慢、步幅变短和周期增加；改善步态可以显著提高生活质量。早期的步态训练有助于减少日后的步态障碍。增强现实（AR）技术在步态训练中大有可为，它能提供实时反馈和指导练习，以改善行走模式和步态参数。本研究的目的是观察同步行走化身提供的渐进空间和时间线索对老年参与者步态的影响。这项实验有 19 名 70 岁以上的参与者参加，他们一边行走一边与提供视听空间和时间提示的同步行走化身互动。空间提示和时间提示分别通过距离变化和相位差变化提供。WalkMate AR 系统用于使虚拟人的行走周期与参与者的行走周期同步，并提供与脚部接触相匹配的听觉提示。这项研究评估了距离和相位差变化对步幅、周期时间和步速的直接影响和延续影响。结果表明，渐进的空间和时间提示会显著影响老年人的步态参数，在步态康复和训练中具有潜在的应用价值。
{"title":"Effects of Gradual Spatial and Temporal Cues Provided by Synchronized Walking Avatar on Elderly Gait","authors":"Dane A. L. Miller, Hirotaka Uchitomi, Yoshihiro Miyake","doi":"10.3390/app14188374","DOIUrl":"https://doi.org/10.3390/app14188374","url":null,"abstract":"Aging often leads to elderly gait characterized by slower speeds, shorter strides, and increased cycle; improving gait can significantly enhance the quality of life. Early gait training can help reduce gait impairment later on. Augmented reality (AR) technologies have shown promise in gait training, providing real-time feedback and guided exercises to improve walking patterns and gait parameters. The aim of this study was to observe the effects of gradual spatial and temporal cues provided by a synchronized walking avatar on the gait of elderly participants. This experiment involved 19 participants aged over 70 years, who walked while interacting with a synchronized walking avatar that provided audiovisual spatial and temporal cues. Spatial cueing and temporal cueing were provided through distance changes and phase difference changes, respectively. The WalkMate AR system was used to synchronize the avatar’s walking cycle with the participants’, delivering auditory cues matched to foot contacts. This study assessed the immediate and carry-over effects of changes in distance and phase difference on stride length, cycle time, and gait speed. The results indicate that gradual spatial and temporal cueing significantly influences elderly gait parameters, with potential applications in gait rehabilitation and training.","PeriodicalId":8224,"journal":{"name":"Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142249175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Citric acid is widely used in the Food and Pharmaceutical Industry. Various issues regarding its thermal behavior and infrared spectrum require clarification. Here, we studied citric acid monohydrate (raw, heated, freeze-dried and recrystallized from D2O) via Differential Scanning Calorimetry, Thermogravimetric Analysis, Infrared Spectroscopy, and antioxidant capacity assay. Also, we used ab initio Density Functional Theory calculations for further supporting the interpretations of the experimental results. Citric acid monohydrate exhibits desolvation inability and upon heating does not dehydrate but esterifies. Nor by freeze drying can it be dehydrated. The heated sample is not anhydrous, it exhibits melting inability, and any fluidization occurs simultaneously with decomposition. In other words, the interpretations regarding the two endothermic peaks in the DSC curve of citric acid that have been attributed to water evaporation and melting are not correct. The increase in the molecular weight due to esterification is most likely responsible for the increased antioxidant/chelation capacity of the heated sample. We concluded that what we call citric acid monohydrate and anhydrous do not exist in a pure form (in the solid state) and actually are mixtures of different compositions of citric acid, water and a citric acid oligomer that is produced through esterification. The esterification reaction seems to be able to proceed easily under mild heating or even at room temperature. The presence of the ester oligomer and water affect the infrared spectrum of citric acid monohydrate and anhydrous and is responsible for the existence of multiple peaks in the C=O stretching region, which partially overlaps with the water H-O-H bending vibration. The insights presented in this work could be useful for optimizing the design, performance and quality of food and drug products in which citric acid is used.
{"title":"Thermal Behavior and Infrared Absorbance Bands of Citric Acid","authors":"Costas Tsioptsias, Afroditi Panagiotou, Paraskevi Mitlianga","doi":"10.3390/app14188406","DOIUrl":"https://doi.org/10.3390/app14188406","url":null,"abstract":"Citric acid is widely used in the Food and Pharmaceutical Industry. Various issues regarding its thermal behavior and infrared spectrum require clarification. Here, we studied citric acid monohydrate (raw, heated, freeze-dried and recrystallized from D2O) via Differential Scanning Calorimetry, Thermogravimetric Analysis, Infrared Spectroscopy, and antioxidant capacity assay. Also, we used ab initio Density Functional Theory calculations for further supporting the interpretations of the experimental results. Citric acid monohydrate exhibits desolvation inability and upon heating does not dehydrate but esterifies. Nor by freeze drying can it be dehydrated. The heated sample is not anhydrous, it exhibits melting inability, and any fluidization occurs simultaneously with decomposition. In other words, the interpretations regarding the two endothermic peaks in the DSC curve of citric acid that have been attributed to water evaporation and melting are not correct. The increase in the molecular weight due to esterification is most likely responsible for the increased antioxidant/chelation capacity of the heated sample. We concluded that what we call citric acid monohydrate and anhydrous do not exist in a pure form (in the solid state) and actually are mixtures of different compositions of citric acid, water and a citric acid oligomer that is produced through esterification. The esterification reaction seems to be able to proceed easily under mild heating or even at room temperature. The presence of the ester oligomer and water affect the infrared spectrum of citric acid monohydrate and anhydrous and is responsible for the existence of multiple peaks in the C=O stretching region, which partially overlaps with the water H-O-H bending vibration. The insights presented in this work could be useful for optimizing the design, performance and quality of food and drug products in which citric acid is used.","PeriodicalId":8224,"journal":{"name":"Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142249274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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