Global Entropy Research Articles

The effect of fatigue on climbing fluidity and hand movements

ABSTRACT In rock climbing, climbers use their arms to regulate their posture on the wall, which can lead to localised muscle fatigue. Evidence shows fatigue is the primary cause of falls, but little is known about how fatigue specifically affects climbing rhythm and hand movements. The present study examined climbing fluidity and hand movements on an indoor climbing wall before and after a specific fatiguing protocol. Seventeen climbers completed three repetitions of a challenging climbing route (21 on Ewbank scale) with different levels of localised arm fatigue. Climbers’ movements were tracked using 3D motion capture, and their hand actions assessed using notational analysis. Seventy markers were used to create 15 rigid body segments and the participants' centre of mass. The global entropy index was calculated on the path of the participants' centre of mass. Climbers fell more often when fatigued, but there were no significant differences in hip jerk or global entropy index when fatigued. No significant differences were found between the number of exploratory or performatory hand movements with different amounts of fatigue. The results suggest that localised arm fatigue affects a climber’s ability to prevent themselves from falling, but it does not specifically affect their fluidity.

CardioLabelNet: An uncertainty estimation using fuzzy for abnormalities detection in ECG

AbstractElectrocardiography (ECG) abnormalities are evaluated through several automatic detection methods. Primarily, real‐world ECG data are digital signals those are stored in the form of images in hospitals. Also, the existing automated detection technique eliminates the cardiac pattern that is abnormal and it is difficult to multiple abnormalities at some instances. To address those issues in this paper conventional ECG image automated techniques CardioLabelNet model is proposed. The proposed model incorporates two stages for image abnormality detection. At first fuzzy membership is performed in the image for computation of uncertainty. In second stage, classification is performed for computation of abnormal activity. The proposed CardioLabelNet collect ECG image data set for the uncertainty estimation while taking the account of various image classes which includes the global and local entropy of image pixels. For each waveform, uncertainties are calculated on the basis of global entropy. The computation of uncertainty in the images is performed with the fuzzy membership function. The spatial likelihood estimation of a fuzzy weighted membership function is used to calculate local entropy. Upon completion of fuzzification, classification is performed for the detection of normal and abnormal patterns in the ECG signal images. Through integration of stacked architecture model classification is performed for ECG images. The proffered algorithm performance is calculated in terms of accuracy for segmentation, Dice similarity coefficient, and partition entropy. Additionally, classification parameters accuracy sensitivity, specificity, and AUC are evaluated. The proposed approach outperforms the existing methodology, according to the results of a comparative analysis.

A family of second-order dissipative finite volume schemes for hyperbolic systems of conservation laws

We propose and study a family of formally second-order accurate schemes to approximate weak solutions of hyperbolic systems of conservation laws. Theses schemes are based on a dissipative property satisfied by the second-order discretization in space. They are proven to satisfy a global entropy inequality for a generic strictly convex entropy. These schemes do not involve limitation techniques. Numerical results are provided to illustrate their accuracy and stability.

A Novel Lower-Limb Coordination Assessment Scheme Using Multi-Scale Nonlinear Coupling Characteristics With sEMG

Motor dysfunction (e.g., incoordination of upper or lower limb) significantly limits the individuals’ ability of daily living, and thus the provisioning of a motion coordination assessment method becomes of vital importance. As a quantitative indicator, inter-muscular coupling strength could assess limb coordination. Since surface electromyography (sEMG) signals cover nonlinear coupling characteristics, in this paper, a lower-limb motion coordination assessment scheme with intermuscular coherence (IMC) analysis and optimization variational mode decomposition (VMD) is proposed. First, sEMG signals are decomposed into several intrinsic mode functions (IMFs) using optimized VMD. Then, the nonlinear coupling feature vector in the beta-band frequency domian (15-35Hz) is extracted by the G-P algorithm from optimal IMF, thereby estimating intermuscular coupling strength by IMC. In particular, differential evolution (DE) algorithm’s global optimization capability and envelope entropy (EE)’s sparsity are adopted to provide the basis for optimization VMD and screening optimal IMF, respectively. Finally, signals are collected from four muscle pairs of the 12 male and 12 female subjects to assess lower-limb motions coordination. Simultaneously, the independent sample T test is leveraged to compare the effects of gender on groups’ characteristics (e.g., age, height, and body mass). Results demonstrate not only the effectiveness of the proposed approach (i.e., p < 0.01 with both “S-walking” and “Running” motions, p < 0.05 with “Q-walking”), but also the difference of motion coordination relationship between male and female adults as well as the significance of muscle selection.

Some recent advances on the method of moments in kinetic theory

This review presents some recent works on the construction of closure relations for moment systems extracted from a kinetic equation. A rough construction of those closures and the main properties of the resulting systems are described. Especially, based on the underlying kinetic equation, the main properties desired for such moment systems are the realizability, i.e. the positivity of an underlying kinetic solution, global strong hyperbolicity and entropy dissipation.

Global Weak Entropy Solution of Nonlinear Ideal Reaction Chromatography System and Applications

Global Weak Entropy Solution of Nonlinear Ideal Reaction Chromatography System and Applications

CAT: Learning to collaborate channel and spatial attention from multi‐information fusion

AbstractChannel and spatial attention mechanisms have proven to provide an evident performance boost of deep convolution neural networks. Most existing methods focus on one or run them parallel (series), neglecting the collaboration between the two attentions. In order to better establish the feature interaction between the two types of attentions, a plug‐and‐play attention module is proposed, which is termed as ‘CAT’—activating the Collaboration between spatial and channel Attentions based on learned Traits. Specifically, traits are represented as trainable coefficients (i.e. colla‐factors) to adaptively combine contributions of different attention modules to fit different image hierarchies and tasks better. Moreover, the global entropy pooling is proposed apart from global average pooling and global maximum pooling (GMP) operators, which is an effective component in suppressing noise signals by measuring the information disorder of feature maps. A three‐way pooling operation is introduced into attention modules and the adaptive mechanism is applied to fuse their outcomes. Extensive experiments on MS COCO, Pascal‐VOC, Cifar‐100, and ImageNet show that our CAT outperforms the existing state‐of‐the‐art attention mechanisms in object detection, instance segmentation, and image classification. The model and code will be released soon.

Entropy generation study due to MHD double-diffusive convection in the rectangular cavity with built-in rectangular blockage

In the present work, the influence of the aspect ratio of the rectangular cavity (length > width) and the built-in rectangular blockage (length > width) on the local and global entropy generation (EG) characteristics due to double-diffusive convection and external magnetic field have been explored. Particularly, the effect of the pertinent parameters, such as the aspect ratio of the cavity and blockage Lewis number Rayleigh number Hartmann number and buoyancy ratios on the EG characteristics have been explored. The working fluid is considered to be a liquid metal-sodium–potassium alloy (Pr = 0.054). Lattice Boltzmann method numerical scheme is employed to solve the double-diffusive natural convection phenomenon. The increase in Ra induces an enhancement in the localized EG terms, whereas the augmentation in Ha diminishes the local total EG (S Total) for a given Ra. The dominance of thermal and species transport irreversibility in the cavity was noticed for Conversely, for AR = 4, the significance of flow friction irreversibility within the cavity was observed (). The results of the work are also summarized in terms of simpler empirical correlations of and ST , which might be useful for possible engineering design purposes.

Network‐level permutation entropy of resting‐state MEG recordings: a novel biomarker for early‐stage Alzheimer’s disease?

AbstractBackgroundIncreasing evidence suggests that measures of signal variability and complexity could present promising biomarkers for Alzheimer’s disease (AD). Earlier studies have however been limited to the characterization of local activity. Here, we investigate whether a network version of permutation entropy could serve as a novel biomarker for early‐stage AD.MethodResting‐state source‐space magnetoencephalography was recorded in 18 subjects with subjective cognitive decline (‘SCD’) and 18 subjects with mild cognitive impairment (‘MCI’). Local activity was characterized by permutation entropy (PE). Network level interactions were studied using the inverted Joint Permutation Entropy (JPEinv), corrected for volume conduction. Entropy of the overall network across different temporal scales was quantified using a global permutation entropy measure.ResultThe JPEinv showed a reduction of nonlinear connectivity in MCI subjects in the theta and alpha band. Local PE showed increased theta‐band entropy. Between‐group differences were widespread across brain regions. ROC analysis of classification of MCI versus SCD subjects revealed that a linear regression model trained on JPEinv features (78.4% [62.5‐93.3%]) slightly outperformed PE (76.9% [60.3‐93.4%]) and relative theta power based models (76.9% [60.4‐93.3%]). The global entropy measure is currently being optimized. Results will be available at a later stage.ConclusionClassification performance of theta JPEinv was at least as good as the relative theta power benchmark. The JPEinv is therefore a potential biomarker for early‐stage AD and should be explored in larger studies.

The Future of the Energy Sector and the Global Economy: Prosumer Capitalism and What Comes Next

This paper describes the present and the future of the energy sector in relation to the dominant and constantly evolving form of the global economic system. These considerations have their starting point in transformations of the energy sector in prosumer capitalism, which has dramatically changed the picture of the global economy in recent years. Subsequently, a futuristic approach is applied to determine the role and importance of energy from renewable sources for further human development. The main objective of the paper is to explain the current situation of the energy sector in prosumer capitalism and to extrapolate these relationships for the future, considering the need to enter the path of sustainable development to eliminate the global warming processes and climate changes. A review of the existing scientific literature was applied as the research method. The historical wave concept, proposed by Toffler, was found to be highly useful because of its high potential in futurology, where it enables one to study megatrends. The Fourth Wave was linked to prosumer capitalism, and it provided the base for defining the next ones: the Fifth Wave of Computing (ecosocialism) and the Sixth Wave in the form of technological and energy communism (solar communism). It also turned out that the key to solving mankind’s energy problems lies in the global mean entropy budget. The literature review shows that founding the global energy system on solar radiation is the only known method for eliminating the anthropogenic greenhouse effect, which is the source of global warming and, consequently, of climate change. Therefore, the second law of thermodynamics provides a physical, economic, and logical justification for introducing a new and ultimate management form—solar communism—by 2050.

Shannon entropy as a reliable score to diagnose human fibroelastic degenerative mitral chords: A micro-ct ex-vivo study.

This paper is aimed at identifying by means of micro-CT the microstructural differences between normal and degenerative mitral marginal chordae tendineae. The control group is composed of 21 normal chords excised from 14 normal mitral valves from heart transplant recipients. The experimental group comprises 22 degenerative fibroelastic chords obtained at surgery from 11 pathological valves after mitral repair or replacement. In the control group the superficial endothelial cells and spongiosa layer remained intact, covering the wavy core collagen. In contrast, in the experimental group the collagen fibers were arranged as straightened thick bundles in a parallel configuration. 100 cross-sections were examined by micro-CT from each chord. Each image was randomized through the K-means machine learning algorithm and then, the global and local Shannon entropies were obtained. The optimum number of clusters, K, was estimated to maximize the differences between normal and degenerative chords in global and local Shannon entropy; the p-value after a nested ANOVA test was chosen as the parameter to be minimized. Optimum results were obtained with global Shannon entropy and 2≤K≤7, providing p<0.01; for K=3, p=2.86·10-3. These findings open the door to novel perioperative diagnostic methods in order to avoid or reduce postoperative mitral valve regurgitation recurrences.

Spatiotemporal Differentiation of the Coupling and Coordination of Production-Living-Ecology Functions in Hubei Province Based on the Global Entropy Value Method

Rapid urbanization and industrialization have brought about regional prosperity and pressure on the ecological environment, and the disorder of development has led to competition among the production-living-ecology functions. How to build livable cities, optimize the spatial layout of land, and promote the coordinated development of the production-living-ecology functions in various regions has become an important issue in the sustainable development and utilization of land space. In order to study the spatiotemporal conflict and coordination of the production-living-ecology functions with respect to the dramatic developments associated with the 21st century, this study took Hubei Province, which is the top-ranking economic region in China in recent years, as the study area and adopted the global entropy value method, triangle model, and coupled evaluation model to delineate an index system to measure the degree of conflict and coordination of the production-living-ecology functions in Hubei Province from 2000 to 2020, and also delineate zoning management based on statistical yearbook data. The results showed the following: (1) With respect to the time scale, the indices of the production-living-ecology functions in Hubei Province increased year by year, and the degree of coordination also increased yearly, from the stage of disorder with certain conflict to the stage of coordination with a high level of coupling. (2) On the spatial scale, the development of production-living-ecology functions in Hubei Province was unbalanced, which may be related to the overall development strategy of "two circles and one belt" in Hubei Province, with the eastern part of the province having a higher degree of coordination of the production-living-ecology functions and the western part having a lower degree of coordination. (3) Among the production-living-ecology functions, the ecological function of Hubei Province as a whole exhibited minimal change and maintained stable development, while the living and production functions underwent considerable development, indicating that Hubei Province has protected the orderly development of the ecological environment in the process of urbanization and new industrialization. (4) According to the development and coordination of the production-living-ecology functions in each region of Hubei Province, four development management zones were created: high-quality development zone, secondary development zone, balanced development zone, and development potential zone. Finally, policy suggestions are given for each zone.

Reservoir Dynamic Interpretability for Time Series Prediction: A Permutation Entropy View.

An echo state network (ESN) is an efficient recurrent neural network (RNN) that is widely used in time series prediction tasks due to its simplicity and low training cost. However, the "black-box" nature of reservoirs hinders the development of ESN. Although a large number of studies have concentrated on reservoir interpretability, the perspective of reservoir modeling is relatively single, and the relationship between reservoir richness and reservoir projection capacity has not been effectively established. To tackle this problem, a novel reservoir interpretability framework based on permutation entropy (PE) theory is proposed in this paper. In structure, this framework consists of reservoir state extraction, PE modeling, and PE analysis. Based on these, the instantaneous reservoir states and neuronal time-varying states are extracted, which are followed by phase space reconstruction, sorting, and entropy calculation. Firstly, the obtained instantaneous state entropy (ISE) and global state entropy (GSE) can measure reservoir richness for interpreting good reservoir projection capacity. On the other hand, the multiscale complexity-entropy analysis of global and neuron-level reservoir states is performed to reveal more detailed dynamics. Finally, the relationships between ESN performance and reservoir dynamic are investigated via Pearson correlation, considering different prediction steps and time scales. Experimental evaluations on several benchmarks and real-world datasets demonstrate the effectiveness and superiority of the proposed reservoir interpretability framework.

Entropy-Based Feature Extraction Model for Fundus Images with Deep Learning Model

Diabetic retinopathy (DR) is stated as a disease in the eyes that affects the retina blood vessels and causes blindness. The early diagnosis and detection of the DR in patients preserve the patient’s vision. In general, for the diagnosis of eye diseases, retinal fundus images are employed. The advancement in the automatic diagnosis of diseases attained higher significance for rapid advancement in computing technology in the medical field. Besides, for the diagnosis of the diseases, fundus image automatic detection is involved in the recognition of blood vessels evaluated based on the length, branching pattern, and width. However, fundus images have low contrast and it is difficult to evaluate the identification of the disease in blood vessels. As a result, it is necessary to adopt a consistent automated method to extract blood vessels in the fundus images for DR. The conventional automated localization of the macula and optic disk in the retinal fundus images needs to be improved for DR disease diagnosis. But existing methods are not sufficient for the early identification and detection of DR. This paper proposed an entropy distributed matching global and local clustering (EDMGL) for fundus images. The developed EDMGL comprises the different uncertainties for the evaluation of the classes based on local and global entropy. The fundus image local entropy is evaluated based on the spatial likelihood fuzzifier membership function estimation for segmentation. The final proposed algorithm membership function is estimated using the addition of weighted parameters through membership estimation based on the global and local entropy. The classification performance of the proposed EDMGL is evaluated based on the dice coefficient, segmentation accuracy, and partition entropy. The performance of the proposed EDMGL is comparatively examined with the conventional technique. The comparative analysis expressed that the performance of the proposed EDMGL exhibits ∼5% improved performance in terms of accuracy, precision, recall, and F1-score.

The research on spatial-temporal evolution and influence factors of urban resilience: A case study in the Guangzhou metropolitan area

Resilience city, a new concept of city sustainable development, becomes one of the important subjects of high-quality development research. Compared to the traditional urban disaster mitigation approach, resilient cities focus more on the organizational capacity and coordination within the urban systems. Taking Guangzhou metropolitan area as an instance, which is featured a highly developed economy and society and frequently happened hazards and disturbances, the paper constructs an evaluation index system from four city subsystems, including economy, society, ecology, and engineering. Meanwhile, by applying the methods of global entropy weight, variation coefficient, geographic information system, and obstacle degree model, the paper explores the time changes, space evolution, and obstacle degree factors of city resilience in the Guangzhou metropolitan area from 2010 to 2020. The research results show that: (1) There is a significant change in the time difference of city comprehensive resilience of the Guangzhou metropolitan area. The resilience of each city’s resilience subsystem has grown steadily, of which the development level of economic resilience, social resilience, and engineering resilience has been steadily improved, and ecology resilience level shows a slight decline among a steadily increasing. (2) The overall city resilience of the Guangzhou metropolitan area shows a radial pattern taking Guangzhou as the core, of which the city economy, society, and engineering resilience grades mainly show a medium and low resilience level, the ecology resilience mainly shows a medium and high resilience level, and the general performance of resilience space distribution level is high in the southeast and low in the northwest. (3) Social resilience and ecological resilience are the main driving subsystems in the early and late stages of city resilience development in Guangzhou metropolitan area during the research period, and engineering resilience is the main constraint subsystem. (4) Water and soil loss control area and population density are the main obstacle factors in the early and late stages of city resilience in the Guangzhou metropolitan area. The density of the city drainage pipeline and the total import and export volume are the basic resilience barrier factors. The paper analyzes the spatial-temporal pattern and influencing factors of city resilience in the metropolitan area from a multi-dimensional perspective, provides a new thinking and analysis framework for the management and sustainability of city resilience in the metropolitan area, and provides a reference for the coordinated development of the metropolitan area.

Quaternion with quantum walks for designing a novel color image cryptosystem

Data confidentiality plays a paramount part in our everyday lives. While most modern cryptosystems perform skillfully on digital resources, the rapid development of quantum resources may provide sufficient capability in the near future to hack most current cryptosystems because their construction is mathematical model-based. Although quantum algorithms will not be effective until quantum computers are physically realized and have sufficient capability to outperform digital computation, new cryptosystems are required to be designed using quantum technologies and have the capability to be implemented in both digital and quantum resources besides resisting the probable attacks from those resources. Quantum walk is a computational paradigm that can be implemented as a quantum-inspired paradigm and serves as a chaotic dynamical model employed for developing modern cryptosystems. This work presented a new color image cryptosystem using quaternion, quantum walks, and logistic-sine map. The aim of utilizing quaternion is to increase the key space of the presented cryptosystem, in addition to integrating the sequence originating from the logistic-sine map with the probability distribution originating from quantum walks for generating inseparable chaotic sequences utilized in the permutation and substitution phases of the presented image cryptosystem. Experimental outcomes were performed on 21 color images and the average values of UACI is 33.45969%, NPCR is 99.61070%, correlation is -0.00003, Chi-square is 255.904, global entropy is 7.999837, local entropy is 7.902542, and the encryption speed is 0.725868 Megabytes/second, in which the outcomes demonstrated that the offered encryption technique is both efficient and secure.

Cell-centered Lagrangian scheme for multi-material flows with pressure equilibration

A cell-centered Lagrangian scheme is presented for a multi-material hydrodynamics model with equilibrated material pressures. The scheme is conservative in mass, momentum, and total energy while being entropic per material. This last point is critical for various engineering applications but is seldom addressed. The entropy production in each material is taken as an arbitrary part of the global entropy production hence mimicking different viscosity operators and the underlying vanishing viscosity solution. The scheme is applied to various 1 or 2-dimensional test cases where materials have highly contrasted equations of state. These challenging test cases confirm the robustness of the scheme and show that pressures are kept equal up to the scheme order or even strictly if an additional equilibration procedure is added.

Adaptive segmentation method in radiographic testing for turbine blades based on spatial entropy

During the radiographic testing with multiple voltage exposures, the problem of image redundancy has serious influences on the speed of analysis. In this paper, by the calculation of spatial entropy and the extraction of microtopography features, a new segmentation method for an unpredictable free-form surface in turbine blades is presented to reduce the testing redundancy. First, the entropy calculation is applied to a set of radiography images of the target object. The optimized image for surface segmentation is determined according to global entropy values and exposure parameters. Then, the obtained image is set as the reference image for the segmentation process. Through the spatial entropy calculation, the reference radiographic image is divided into several regions by geometric features of the tested object. The different thickness range of free-form surfaces is indicated by those regions through the analysis of spatial entropy distribution in the reference image. By the statistical advantage of entropy calculation, the selected region is self-adaptive to the unpredictable free-form surface in the blade. A nickel-based alloy turbine blade is used to validate the segmentation method in the radiographic testing. The processed image quality is assessed by using the American Society for Testing and Materials image quality indicator to address its capability for the detection of defects, where the resolution of the image is not affected by the down-sampled effect of entropy calculation. The experimental results show that the image redundancy in the multiple exposure testing is reduced to less than 30% during the inline testing, while the dynamic range in each extracted region with an optimal image is significantly improved.

Evaluation of provincial carbon-neutral capacities in the Yellow River basin using DPSIR

The Yellow River basin spans nine provinces and autonomous regions and plays an important role in China's economic and social development and ecological security. However few studies have integrated the concept of carbon neutrality into research to evaluate the carbon-neutral development level. This paper calculates the comprehensive evaluation value of the provincial carbon-neutral capacities comprehensive evaluation index in the Yellow River basin through the driving-force-pressure-state-impact-response (DFPSIR) index system and the global entropy method based on provinces data between 2008 to 2019. The final results indicated that from 2008 to 2019, the carbon-neutral capacities of the provinces in the Yellow River basin were in a state of rapid development and had achieved a grade leap. However, seven provinces had carbon-neutral capacity levels at the Grade III standard in 2019, thereby leaving scope for substantial improvement. Through the above research, we identified the changes in the trend and driving mechanisms of the carbon-neutral capacity of the Yellow River basin and provide a theoretical reference value for a comprehensive realization of carbon neutrality in China in 2060.

Numerical Study of Heat Transfer Enhancement by Arc-Shaped Fins in a Shell-Tube Thermal Energy Storage Unit

Latent heat thermal energy storage (LHTES) technology can alleviate the mismatch between the supply and demand of solar energy and industrial waste heat, but the low thermal conductivity of phase change materials (PCMs) is an issue that needs to be solved. In this work, the effects of the bifurcated fins on melting and solidification are studied, and local and global entropy generation are discussed. The radial lag time and the circumferential lag time were defined to evaluate thermal penetration and thermal uniformity. Subsequently, a novel arc-shaped fin configuration was proposed to further enhance the heat transfer. The results showed that attaching the bifurcated fins could effectively reduce the global entropy generation. Increasing the trunk fin length was beneficial to enhance the thermal uniformity and promote the melting process, while increasing the branch fin was more effective in the solidification process. Overall, thermal uniformity determined the phase change process. More importantly, the concentric arc-shaped fins significantly reduced the heat transfer hysteresis region, showed better thermal performance than straights fins, and the energy storage and release time were reduced by 52.7% and 51.6%, respectively.