Entropy (Basel, Switzerland)最新文献

{"title":"Lack of Habituation in Migraine Patients Based on High-Density EEG Analysis Using the Steady State of Visual Evoked Potential.","authors":"Msallam Abbas Abdulhussein,&nbsp;Zaid Abdi Alkareem Alyasseri,&nbsp;Husam Jasim Mohammed,&nbsp;Xingwei An","doi":"10.3390/e24111688","DOIUrl":"https://doi.org/10.3390/e24111688","url":null,"abstract":"<p><p>Migraine is a periodic disorder in which a patient experiences changes in the morphological and functional brain, leading to the abnormal processing of repeated external stimuli in the inter-ictal phase, known as the habituation deficit. This is a significant feature clinically of migraine in both two types with aura or without aura and plays an essential role in studying pathophysiological differences between these two groups. Several studies indicated that the reason for migraine aura is cortical spreading depression (CSD) but did not clarify its impact on migraine without aura and lack of habituation. In this study, 22 migraine patients (MWA, N = 13), (MWoA, N = 9), and healthy controls (HC, N = 19) were the participants. Participants were exposed to the steady state of visual evoked potentials also known as (SSVEP), which are the signals for a natural response to the visual motivation at four Hz or six Hz for 2 s followed by the inter-stimulus interval that varies between 1 and 1.5 s. The order of the temporal frequencies was randomized, and each temporal frequency was shown 100 times. We recorded from 128 customized electrode locations using high-density electroencephalography (HD-EEG) and measured amplitude and habituation for the N1-P1 and P1-N2 from the first to the sixth blocks of 100 sweep features in patients and healthy controls. Using the entropy, a decrease in amplitude and SSVEP N1-P1 habituation between the first and the sixth block appeared in both MWA and MWoA (<i>p</i> = 0.0001, Slope = -0.4643), (<i>p</i> = 0.065, Slope = 0.1483), respectively, compared to HC. For SSVEP P1-N2 between the first and sixth block, it is varied in both MWA (<i>p</i> = 0.0029, Slope = -0.3597) and MWoA (<i>p</i> = 0.027, Slope = 0.2010) compared to HC. Therefore, migraine patients appear amplitude decrease and habituation deficit but with different rates between MWA, and MWoA compared to HCs. Our findings suggest this disparity between MWoA and MWA in the lack of habituation and amplitude decrease in the inter-ictal phase has a close relationship with CSD. In light of the fact that CSD manifests during the inter-ictal phase of migraine with aura, which is when migraine seizures are most likely to occur, multiple researchers have lately reached this conclusion. This investigation led us to the conclusion that CSD during the inter-ictal phase and migraine without aura are associated. In other words, even if previous research has not demonstrated it, CSD is the main contributor to both types of migraine (those with and without aura).</p>","PeriodicalId":520609,"journal":{"name":"Entropy (Basel, Switzerland)","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2022-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689466/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40482814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"BHGAttN: A Feature-Enhanced Hierarchical Graph Attention Network for Sentiment Analysis.","authors":"Junjun Zhang,&nbsp;Zhengyan Cui,&nbsp;Hyun Jun Park,&nbsp;Giseop Noh","doi":"10.3390/e24111691","DOIUrl":"https://doi.org/10.3390/e24111691","url":null,"abstract":"<p><p>Recently, with the rise of deep learning, text classification techniques have developed rapidly. However, the existing work usually takes the entire text as the modeling object and pays less attention to the hierarchical structure within the text, ignoring the internal connection between the upper and lower sentences. To address these issues, this paper proposes a Bert-based hierarchical graph attention network model (BHGAttN) based on a large-scale pretrained model and graph attention network to model the hierarchical relationship of texts. During modeling, the semantic features are enhanced by the output of the intermediate layer of BERT, and the multilevel hierarchical graph network corresponding to each layer of BERT is constructed by using the dependencies between the whole sentence and the subsentence. This model pays attention to the layer-by-layer semantic information and the hierarchical relationship within the text. The experimental results show that the BHGAttN model exhibits significant competitive advantages compared with the current state-of-the-art baseline models.</p>","PeriodicalId":520609,"journal":{"name":"Entropy (Basel, Switzerland)","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2022-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689255/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40482816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diffusion and Velocity Correlations of the Phase Transitions in a System of Macroscopic Rolling Spheres.","authors":"Francisco Vega Reyes,&nbsp;Álvaro Rodríguez-Rivas,&nbsp;Juan F González-Saavedra,&nbsp;Miguel A López-Castaño","doi":"10.3390/e24111684","DOIUrl":"https://doi.org/10.3390/e24111684","url":null,"abstract":"<p><p>We study an air-fluidized granular monolayer composed of plastic spheres which roll on a metallic grid. The air current is adjusted so that the spheres never lose contact with the grid and so that the dynamics may be regarded as pseudo two dimensional (or two dimensional, if the effects of the sphere rolling are not taken into account). We find two surprising continuous transitions, both of them displaying two coexisting phases. Moreover, in all the cases, we found the coexisting phases display a strong energy non-equipartition. In the first transition, at a weak fluidization, a glass phase coexists with a disordered fluid-like phase. In the second transition, a hexagonal crystal coexists with the fluid phase. We analyze, for these two-phase systems, the specific diffusive properties of each phase, as well as the velocity correlations. Surprisingly, we find a glass phase at a very low packing fraction and for a wide range of granular temperatures. Both phases are also characterized by strong anticorrelated velocities upon a collision. Thus, the dynamics observed for this quasi two-dimensional system unveil phase transitions with peculiar properties, very different from the predicted behavior in well-know theories for their equilibrium counterparts.</p>","PeriodicalId":520609,"journal":{"name":"Entropy (Basel, Switzerland)","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2022-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689610/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40492963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Complexity Science in Human Change: Research, Models, Clinical Applications.","authors":"Franco Orsucci,&nbsp;Wolfgang Tschacher","doi":"10.3390/e24111670","DOIUrl":"https://doi.org/10.3390/e24111670","url":null,"abstract":"<p><p>Complexity and entropy prevail in human behavior and social interaction because the systems underlying behavior and interaction are, without a doubt, highly complex [...].</p>","PeriodicalId":520609,"journal":{"name":"Entropy (Basel, Switzerland)","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2022-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689421/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40722017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fractional-Order Active Disturbance Rejection Control with Fuzzy Self-Tuning for Precision Stabilized Platform.","authors":"Jianjian Zhao,&nbsp;Tao Zhao,&nbsp;Nian Liu","doi":"10.3390/e24111681","DOIUrl":"https://doi.org/10.3390/e24111681","url":null,"abstract":"<p><p>In this paper, a novel fractional-order active disturbance rejection control with fuzzy self-tuning method (FSFOADRC) is proposed for photoelectric tracking system (PTS). Firstly, aiming at the internal uncertainty of PTS and external disturbance, a fraction-order extended state observer (FOESO) is designed, and the FOESO can transform the plant into a simple form, which greatly simplifies the mathematical model. Secondly, a fuzzy regulator is applied to the proportion-differentiation controller (PD), increasing the flexibility and adaptivity of the controller. In addition, the stability of the whole control system can be guaranteed. Eventually, numerical comparative simulations are implemented to verify the feasibility and superiority of the proposed method. Compared with the integral-order active disturbance rejection control (IOADRC), fractional-order active disturbance rejection control (FOADRC) without the fuzzy regulator and proportion-integration-differentiation (PID) controller, the proposed method performs better with faster response, smaller overshoot, and stronger disturbance suppression capability.</p>","PeriodicalId":520609,"journal":{"name":"Entropy (Basel, Switzerland)","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2022-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689549/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40492960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Point Cloud Geometry Compression Based on Multi-Layer Residual Structure.","authors":"Jiawen Yu,&nbsp;Jin Wang,&nbsp;Longhua Sun,&nbsp;Mu-En Wu,&nbsp;Qing Zhu","doi":"10.3390/e24111677","DOIUrl":"https://doi.org/10.3390/e24111677","url":null,"abstract":"<p><p>Point cloud data are extensively used in various applications, such as autonomous driving and augmented reality since it can provide both detailed and realistic depictions of 3D scenes or objects. Meanwhile, 3D point clouds generally occupy a large amount of storage space that is a big burden for efficient communication. However, it is difficult to efficiently compress such sparse, disordered, non-uniform and high dimensional data. Therefore, this work proposes a novel deep-learning framework for point cloud geometric compression based on an autoencoder architecture. Specifically, a multi-layer residual module is designed on a sparse convolution-based autoencoders that progressively down-samples the input point clouds and reconstructs the point clouds in a hierarchically way. It effectively constrains the accuracy of the sampling process at the encoder side, which significantly preserves the feature information with a decrease in the data volume. Compared with the state-of-the-art geometry-based point cloud compression (G-PCC) schemes, our approach obtains more than 70-90% BD-Rate gain on an object point cloud dataset and achieves a better point cloud reconstruction quality. Additionally, compared to the state-of-the-art PCGCv2, we achieve an average gain of about 10% in BD-Rate.</p>","PeriodicalId":520609,"journal":{"name":"Entropy (Basel, Switzerland)","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2022-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689459/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40722022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genetic Algorithm Based on a New Similarity for Probabilistic Transformation of Belief Functions.","authors":"Yilin Dong,&nbsp;Lei Cao,&nbsp;Kezhu Zuo","doi":"10.3390/e24111680","DOIUrl":"https://doi.org/10.3390/e24111680","url":null,"abstract":"<p><p>Recent studies of alternative probabilistic transformation (PT) in Dempster-Shafer (DS) theory have mainly focused on investigating various schemes for assigning the mass of compound focal elements to each singleton in order to obtain a Bayesian belief function for decision-making problems. In the process of such a transformation, how to precisely evaluate the closeness between the original basic belief assignments (BBAs) and transformed BBAs is important. In this paper, a new aggregation measure is proposed by comprehensively considering the interval distance between BBAs and also the sequence inside the BBAs. Relying on this new measure, we propose a novel multi-objective evolutionary-based probabilistic transformation (MOEPT) thanks to global optimizing capabilities inspired by a genetic algorithm (GA). From the perspective of mathematical theory, convergence analysis of EPT is employed to prove the rationality of the GA used here. Finally, various scenarios in evidence reasoning are presented to evaluate the robustness of EPT.</p>","PeriodicalId":520609,"journal":{"name":"Entropy (Basel, Switzerland)","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2022-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689147/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40492959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Thermodynamically Consistent Models for Coupled Bulk and Surface Dynamics.","authors":"Xiaobo Jing,&nbsp;Qi Wang","doi":"10.3390/e24111683","DOIUrl":"https://doi.org/10.3390/e24111683","url":null,"abstract":"<p><p>We present a constructive paradigm to derive thermodynamically consistent models coupling the bulk and surface dynamics hierarchically following the generalized Onsager principle. In the model, the bulk and surface thermodynamical variables are allowed to be different and the free energy of the model comprises the bulk, surface, and coupling energy, which can be weakly or strongly non-local. We illustrate the paradigm using a phase field model for binary materials and show that the model includes the existing thermodynamically consistent ones for the binary material system in the literature as special cases. In addition, we present a set of such phase field models for a few selected mobility operators and free energies to show how boundary dynamics impart changes to bulk dynamics and vice verse. As an example, we show numerically how reactive transport on the boundary impacts the dynamics in the bulk using a reactive transport model for binary reactive fluids by adopting a structure-preserving algorithm to solve the model equations in a rectangular domain.</p>","PeriodicalId":520609,"journal":{"name":"Entropy (Basel, Switzerland)","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2022-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689322/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40492962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A New Exergy Disaggregation Approach for Complexity Reduction and Dissipative Equipment Isolation in Thermoeconomics.","authors":"Rodrigo Guedes Dos Santos,&nbsp;Atilio Barbosa Lourenço,&nbsp;Pedro Rosseto de Faria,&nbsp;Marcelo Aiolfi Barone,&nbsp;José Joaquim Conceição Soares Santos","doi":"10.3390/e24111672","DOIUrl":"https://doi.org/10.3390/e24111672","url":null,"abstract":"<p><p>Thermoeconomics connects thermodynamic and economic concepts in order to provide information not available in conventional energy and economic analysis. Most thermoeconomicists agree that exergy is the most appropriate thermodynamic magnitude to associate with cost. In some applications, exergy disaggregation is required. Despite the improvement in result accuracy, the modeling complexity increases. In recent years, different exergy disaggregation approaches have been proposed, mostly to deal with dissipative components and residues, despite all of them also increasing the complexity of thermoeconomics. This study aims to present a new thermoeconomic approach based on exergy disaggregation, which is able to isolate dissipative components with less modeling complexity. This approach, called the A&F Model, splits the physical exergy into two terms, namely, Helmholtz energy and flow work. These terms were evaluated from a thermoeconomic point of view, through a cost allocation in an ideal Carnot cycle, and they were also applied and compared with the UFS Model, through a cost allocation analysis, in a case study with an organic Rankine cycle-powered vapor compression refrigeration system. The complexity and computational effort reduction in the A&F are significantly less than in the UFS Model. This alternative approach yields consistent results.</p>","PeriodicalId":520609,"journal":{"name":"Entropy (Basel, Switzerland)","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2022-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689488/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40722016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating the Applications of Dendritic Neuron Model with Metaheuristic Optimization Algorithms for Crude-Oil-Production Forecasting.","authors":"Mohammed A A Al-Qaness,&nbsp;Ahmed A Ewees,&nbsp;Laith Abualigah,&nbsp;Ayman Mutahar AlRassas,&nbsp;Hung Vo Thanh,&nbsp;Mohamed Abd Elaziz","doi":"10.3390/e24111674","DOIUrl":"https://doi.org/10.3390/e24111674","url":null,"abstract":"<p><p>The forecasting and prediction of crude oil are necessary in enabling governments to compile their economic plans. Artificial neural networks (ANN) have been widely used in different forecasting and prediction applications, including in the oil industry. The dendritic neural regression (DNR) model is an ANNs that has showed promising performance in time-series prediction. The DNR has the capability to deal with the nonlinear characteristics of historical data for time-series forecasting applications. However, it faces certain limitations in training and configuring its parameters. To this end, we utilized the power of metaheuristic optimization algorithms to boost the training process and optimize its parameters. A comprehensive evaluation is presented in this study with six MH optimization algorithms used for this purpose: whale optimization algorithm (WOA), particle swarm optimization algorithm (PSO), genetic algorithm (GA), sine-cosine algorithm (SCA), differential evolution (DE), and harmony search algorithm (HS). We used oil-production datasets for historical records of crude oil production from seven real-world oilfields (from Tahe oilfields, in China), provided by a local partner. Extensive evaluation experiments were carried out using several performance measures to study the validity of the DNR with MH optimization methods in time-series applications. The findings of this study have confirmed the applicability of MH with DNR. The applications of MH methods improved the performance of the original DNR. We also concluded that the PSO and WOA achieved the best performance compared with other methods.</p>","PeriodicalId":520609,"journal":{"name":"Entropy (Basel, Switzerland)","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2022-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689334/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40722020","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}