A Combination of Residual Distribution and the Active Flux Formulations or a New Class of Schemes That Can Combine Several Writings of the Same Hyperbolic Problem:Application to the 1D Euler Equations

We show how to combine in a natural way(i.e.,without any test nor switch)the conservative and non-conservative formulations of an hyperbolic system that has a conservative form.This is inspired from two different classes of schemes:the residual distribution one(Abgrall in Commun Appl Math Comput 2(3):341–368,2020),and the active flux formulations(Eyman and Roe in 49th AIAA Aerospace Science Meeting,2011;Eyman in active flux.PhD thesis,University of Michigan,2013;Helzel et al.in J Sci Comput 80(3):35–61,2019;Barsukow in J Sci Comput 86(1):paper No.3,34,2021;Roe in J Sci Comput 73:1094–1114,2017).The solution is globally continuous,and as in the active flux method,described by a combination of point values and average values.Unlike the“classical”active flux methods,the meaning of the point-wise and cell average degrees of freedom is different,and hence follow different forms of PDEs;it is a conservative version of the cell average,and a possibly non-conservative one for the points.This new class of scheme is proved to satisfy a Lax-Wendroff-like theorem.We also develop a method to perform nonlinear stability.We illustrate the behaviour on several benchmarks,some quite challenging.

Optimal Location and Sizing of Distributed Generator via Improved Multi-Objective Particle Swarm Optimization in Active Distribution Network Considering Multi-Resource

In the framework of vigorous promotion of low-carbon power system growth as well as economic globalization,multi-resource penetration in active distribution networks has been advancing fiercely.In particular,distributed generation(DG)based on renewable energy is critical for active distribution network operation enhancement.To comprehensively analyze the accessing impact of DG in distribution networks from various parts,this paper establishes an optimal DG location and sizing planning model based on active power losses,voltage profile,pollution emissions,and the economics of DG costs as well as meteorological conditions.Subsequently,multiobjective particle swarm optimization(MOPSO)is applied to obtain the optimal Pareto front.Besides,for the sake of avoiding the influence of the subjective setting of the weight coefficient,the decisionmethod based on amodified ideal point is applied to execute a Pareto front decision.Finally,simulation tests based on IEEE33 and IEEE69 nodes are designed.The experimental results show thatMOPSO can achieve wider and more uniformPareto front distribution.In the IEEE33 node test system,power loss,and voltage deviation decreased by 52.23%,and 38.89%,respectively,while taking the economy into account.In the IEEE69 test system,the three indexes decreased by 19.67%,and 58.96%,respectively.

Blockchain-Based Power Transaction Method for Active Distribution Network

A blockchain-based power transaction method is proposed for Active Distribution Network(ADN),considering the poor security and high cost of a centralized power trading system.Firstly,the decentralized blockchain structure of the ADN power transaction is built and the transaction information is kept in blocks.Secondly,considering the transaction needs between users and power suppliers in ADN,an energy request mechanism is proposed,and the optimization objective function is designed by integrating cost aware requests and storage aware requests.Finally,the particle swarm optimization algorithm is used for multi-objective optimal search to find the power trading scheme with the minimum power purchase cost of users and the maximum power sold by power suppliers.The experimental demonstration of the proposed method based on the experimental platform shows that when the number of participants is no more than 10,the transaction delay time is 0.2 s,and the transaction cost fluctuates at 200,000 yuan,which is better than other comparison methods.

Combined CNN-LSTM Deep Learning Algorithms for Recognizing Human Physical Activities in Large and Distributed Manners:A Recommendation System

Recognizing human activity(HAR)from data in a smartphone sensor plays an important role in the field of health to prevent chronic diseases.Daily and weekly physical activities are recorded on the smartphone and tell the user whether he is moving well or not.Typically,smartphones and their associated sensing devices operate in distributed and unstable environments.Therefore,collecting their data and extracting useful information is a significant challenge.In this context,the aimof this paper is twofold:The first is to analyze human behavior based on the recognition of physical activities.Using the results of physical activity detection and classification,the second part aims to develop a health recommendation system to notify smartphone users about their healthy physical behavior related to their physical activities.This system is based on the calculation of calories burned by each user during physical activities.In this way,conclusions can be drawn about a person’s physical behavior by estimating the number of calories burned after evaluating data collected daily or even weekly following a series of physical workouts.To identify and classify human behavior our methodology is based on artificial intelligence models specifically deep learning techniques like Long Short-Term Memory(LSTM),stacked LSTM,and bidirectional LSTM.Since human activity data contains both spatial and temporal information,we proposed,in this paper,to use of an architecture allowing the extraction of the two types of information simultaneously.While Convolutional Neural Networks(CNN)has an architecture designed for spatial information,our idea is to combine CNN with LSTM to increase classification accuracy by taking into consideration the extraction of both spatial and temporal data.The results obtained achieved an accuracy of 96%.On the other side,the data learned by these algorithms is prone to error and uncertainty.To overcome this constraint and improve performance(96%),we proposed to use the fusion mechanisms.The last combines deep learning classifiers tomodel non-accurate and ambiguous data to obtain synthetic information to aid in decision-making.The Voting and Dempster-Shafer(DS)approaches are employed.The results showed that fused classifiers based on DS theory outperformed individual classifiers(96%)with the highest accuracy level of 98%.Also,the findings disclosed that participants engaging in physical activities are healthy,showcasing a disparity in the distribution of physical activities between men and women.

Identification and distribution of 13003 landslides in the northwest margin of Qinghai-Tibet Plateau based on human-computer interaction remote sensing interpretation

The periphery of the Qinghai-Tibet Plateau is renowned for its susceptibility to landslides.However,the northwestern margin of this region,characterised by limited human activities and challenging transportation,remains insufficiently explored concerning landslide occurrence and dispersion.With the planning and construction of the Xinjiang-Tibet Railway,a comprehensive investigation into disastrous landslides in this area is essential for effective disaster preparedness and mitigation strategies.By using the human-computer interaction interpretation approach,the authors established a landslide database encompassing 13003 landslides,collectively spanning an area of 3351.24 km^(2)(36°N-40°N,73°E-78°E).The database incorporates diverse topographical and environmental parameters,including regional elevation,slope angle,slope aspect,distance to faults,distance to roads,distance to rivers,annual precipitation,and stratum.The statistical characteristics of number and area of landslides,landslide number density(LND),and landslide area percentage(LAP)are analyzed.The authors found that a predominant concentration of landslide origins within high slope angle regions,with the highest incidence observed in intervals characterised by average slopes of 20°to 30°,maximum slope angle above 80°,along with orientations towards the north(N),northeast(NE),and southwest(SW).Additionally,elevations above 4.5 km,distance to rivers below 1 km,rainfall between 20-30 mm and 30-40 mm emerge as particularly susceptible to landslide development.The study area’s geological composition primarily comprises Mesozoic and Upper Paleozoic outcrops.Both fault and human engineering activities have different degrees of influence on landslide development.Furthermore,the significance of the landslide database,the relationship between landslide distribution and environmental factors,and the geometric and morphological characteristics of landslides are discussed.The landslide H/L ratios in the study area are mainly concentrated between 0.4 and 0.64.It means the landslides mobility in the region is relatively low,and the authors speculate that landslides in this region more possibly triggered by earthquakes or located in meizoseismal area.

Application of DSAPSO Algorithm in Distribution Network Reconfiguration with Distributed Generation

With the current integration of distributed energy resources into the grid,the structure of distribution networks is becoming more complex.This complexity significantly expands the solution space in the optimization process for network reconstruction using intelligent algorithms.Consequently,traditional intelligent algorithms frequently encounter insufficient search accuracy and become trapped in local optima.To tackle this issue,a more advanced particle swarm optimization algorithm is proposed.To address the varying emphases at different stages of the optimization process,a dynamic strategy is implemented to regulate the social and self-learning factors.The Metropolis criterion is introduced into the simulated annealing algorithm to occasionally accept suboptimal solutions,thereby mitigating premature convergence in the population optimization process.The inertia weight is adjusted using the logistic mapping technique to maintain a balance between the algorithm’s global and local search abilities.The incorporation of the Pareto principle involves the consideration of network losses and voltage deviations as objective functions.A fuzzy membership function is employed for selecting the results.Simulation analysis is carried out on the restructuring of the distribution network,using the IEEE-33 node system and the IEEE-69 node system as examples,in conjunction with the integration of distributed energy resources.The findings demonstrate that,in comparison to other intelligent optimization algorithms,the proposed enhanced algorithm demonstrates a shorter convergence time and effectively reduces active power losses within the network.Furthermore,it enhances the amplitude of node voltages,thereby improving the stability of distribution network operations and power supply quality.Additionally,the algorithm exhibits a high level of generality and applicability.

Method for Determination of Optimal Installed Capacity of Renewable Sources of Energy by the Criterion of Minimum Losses of Active Power in Distribution System

New method for determination of optimal placement and value of installed capacity of renewable source of energy (RES) by the criterion of minimum losses of active power, that allows taking into consideration the dependence of RES on natural conditions of region, schedule of energy supply, parameters and configuration of distribution network is suggested in the paper. Results of computations of test scheme confirm the efficiency of the proposed method and its simplicity as compared with the methods considered in literature sources.

Evaluating the Impacts of Human Activities on Diversity, Abundance, and Distribution of Large Mammals in Nimule National Park, South Sudan

Globally, human activities have a significant impact on the diversity, abundance, and distribution of large mammals in Protected Areas (PAs). These disturbances increase human pressure on biodiversity and species habitats, highlighting the need for conservation. This study aimed to assess the abundance and distribution of large mammals in different habitat types within Nimule National Park (NNP) and understand the impacts of human activities on them. Data on the abundance and distribution of large mammals and their respective habitat types were collected through line transect surveys. Human activity signs were observed and recorded along the transect lines. To estimate the impacts of human activities on the diversity, abundance, and distribution of large mammal species, as well as to identify any significant differences between them and their habitat types, the study utilized the Kruskal Wallis test, Polynomial multiple regressions, and diversity indices. The findings from the Shannon-Weiner and Simpson indices indicated that large mammal species were more diverse inside the park (H’ = 1.136;D = 0.570) compared to the buffer zone (H’ = 0.413;D = 0.171), with 85% (443 out of 510 samples) recorded within Nimule National Park. The species abundance showed a semi-balanced status (0.58). The diversity results among different habitat types revealed that large mammals were more diverse and highly distributed in both open woodlands (244) and dense woodlands (192), while riverine vegetation had the lowest diversity (8). Statistical tests demonstrated a highly significant difference at a 99% confidence interval (p-value = 0.01) between habitat types and identified species of large mammals. Additionally, the results highlighted the high abundance of Uganda kob (274), baboons (141), and warthog (57) across most habitat types, accounting for at least 75% of their distribution. The most prevalent human activities observed were cattle footprints (27%) and cattle dung (14%). Human footprints and tree cutting combined accounted for 9%, indicating the practice of livestock grazing, poaching, encroachment, and fuelwood collection by local communities. However, these activities did not appear to significantly impact the diversity, abundance, and distribution of large mammals in Nimule National Park. Therefore, it is crucial to foster shared responsibilities and engage relevant stakeholders in the management and conservation of large wildlife species. Regular community awareness programs should be implemented to cultivate a sense of ownership. Moreover, it is recommended that a comprehensive survey be conducted on the population status of all mammal species in Nimule National Park, including its surrounding Buffer Zone. Monitoring the impact of human activities on their behavior and habitats using satellite images should also be carried out at least every five to ten years.

Particle swarm optimization algorithm for simultaneous optimal placement and sizing of shunt active power conditioner(APC)and shunt capacitor in harmonic distorted distribution system

Due to development of distribution systems and increase in electricity demand,the use of capacitor banks increases.From the other point of view,nonlinear loads generate and inject considerable harmonic currents into power system.Under this condition if capacitor banks are not properly selected and placed in the power system,they could amplify and propagate these harmonics and deteriorate power quality to unacceptable levels.With attention of disadvantages of passive filters,such as occurring resonance,nowadays the usage of this type of harmonic compensator is restricted.On the other side,one of parallel multi-function compensating devices which are recently used in distribution system to mitigate voltage sag and harmonic distortion,performs power factor correction,and improves the overall power quality as active power conditioner(APC).Therefore,the utilization of APC in harmonic distorted system can affect and change the optimal location and size of shunt capacitor bank under harmonic distortion condition.This paper presents an optimization algorithm for improvement of power quality using simultaneous optimal placement and sizing of APC and shunt capacitor banks in radial distribution networks in the presence of voltage and current harmonics.The algorithm is based on particle swarm optimization(PSO).The objective function includes the cost of power losses,energy losses and those of the capacitor banks and APCs.

Leader-follower Optimal Selection Method for Distributed Control System in Active Distribution Networks

Aiming at the shortcomings of a traditional centralized control in an active distribution network(AND),this paper proposes a leader-follower distributed group cooperative control strategy to realize multiple operation and control tasks for an ADN.The distributed information exchange protocols of the distributed generation(DG)group devoted to node voltage regulation or exchange power control are developed using a DG power utilization ratio as the consensus variable.On these bases,this study further investigates the leader optimal selection method for a DG group to improve the response speed of the distributed control system.Furthermore,a single or multiple leader selection model is established to minimize the constraints of the one-step convergence factor and the number of leaders to improve the response speed of the distributed control system.The simulation results of the IEEE 33 bus standard test system show the effectiveness of the proposed distributed control strategy.In addition,the response speed of a DG control group can be improved effectively when the single or multiple leaders are selected optimally.

A Privacy-preserving Energy Management System Based on Homomorphic Cryptosystem for IoT-enabled Active Distribution Network

Active distribution network(ADN),as a typically cyber-physical system,develops with the evolution of Internet of Things(IoTs),which makes the network vulnerable to cybersecurity threats.In this paper,the eavesdropping attacks that lead to privacy breaches are addressed for the IoT-enabled ADN.A privacy-preserving energy management system(EMS)is proposed and empowered by secure data exchange protocols based on the homomorphic cryptosystem.During the information transmission among distributed generators and load customers in the EMS,private information including power usage and electricity bidding price can be effectively protected against eavesdropping attacks.The correctness of the final solutions,e.g.,optimal market clearing price and unified power utilization ratio,can be deterministically guaranteed.The simulation results demonstrate the effectiveness and the computational efficiency of the proposed homomorphically encrypted EMS.

DISTRIBUTION OF ACTIVE EARTH PRESSURE OF RETAINING WALL WITH WALL MOVEMENT OF ROTATION ABOUT TOP

Based on the Coulomb's theory that the earth pressure against the back of a retaining wall is due to the thrust exerted by the sliding wedge of soil from the back of the wall to a plane which passes through the bottom edge of the wall and has an inclination equal to the angle of θ, the theoretical answers to the unit earth pressure, the resultant earth pressure and the point of application of the resultant earth pressure on a retaining wall were obtained for the wall movement mode of rotation about top. The comparisons were made among the formula presented here, the formula for the wall movement mode of translation, the Coulomb's formula and some experimental observations. It is demonstrated that the magnitudes of the resultant earth pressures for the wall movement mode of rotation about top is equal to that determined by the formula for the wall movement mode of translation and the Coulomb's theory. But the distribution of the earth pressure and the points of application of the resultant earth pressures have significant difference.

EFFECTS OF EXTERNAL DONOR ON ACTIVE CENTER DISTRIBUTION OF SUPPORTED ZIEGLER-NATTA CATALYST

The composition distribution (CD) and microisotacticity distribution (ID) of propene/1-hexene copolymer synthesized by MgCl2/DIBP/TiCl4 (DIBP: diisobutyl phthalate) were determined by fractionating the copolymers according to crystallinity and characterizing the fractions by (CNMR)-C-13. The effects of two alkoxysilane donors, triethoxyphenylsilane (PTES) and dimethoxydi-tert-butylsilane (TBMS), on CD and ID of the copolymers were compared. Three main parts in the CD diagram of each copolymer were distinguished, which were correlated to active center distribution (ACD) based on three groups of different active centers. By studying the changes in l-hexene content, microisotacticity and reactivity ratio product of three typical fractions, the effects of external donor on ACD were better elucidated. It was found that TBMS shows much stronger effects on ACD than PTES. In the former system, most fractions were produced on active centers with relatively lower r(1)r(2), higher reactivity to I-hexene, and higher stereospecificity as compared to the system without external donor. It is concluded that the observed very extensive changes in ACD are mainly resulted by the formation of new types of active centers, possibly by coordination of external donor to certain positions on the catalyst.

Estimation of Pore Size Distribution by CO_2 Adsorption and Its Application in Physical Activation of Precursors

The CO2 adsorption data may show more than one section in the Dubinin-Radushkevich-Kaganer(DRK) plot if samples had been over-activated. Each section in the plot represents a range of pore size. The whole DRK plot provided information on the pore size distribution(PSD) of a sample, which may be used to monitor the effect of activation conditions in activation processes.

Cell-type continuous electromagnetic radiation system generating millimeter waves for active denial system applications

The cell-type continuous electromagnetic radiation system is a demonstration device capable of generating high-power millimeter electromagnetic waves of a specific wavelength and observing their effects on living organisms.It irradiates a biological sample placed in a 30×30×50 cm^(3)cell with electromagnetic waves in the 3.15-mm-wavelength region(with an output of≥1 W)and analyzes the temperature change of the sample.A vacuum electronic device-based coupled-cavity backward-wave oscillator converts the electron energy of the electron beam into radiofrequency(RF)energy and radiates it to the target through an antenna,increasing the temperature through the absorption of RF energy in the skin.The system causes pain and ultimately reduces combat power.A cell-type continuous electromagnetic radiation system consisting of four parts—an electromagnetic-wave generator,a highvoltage power supply,a test cell,and a system controller—generates an RF signal of≥1 W in a continuous waveform at a 95-GHz center frequency,as well as a chemical solution with a dielectric constant similar to that of the skin of a living organism.An increase of 5°C lasting approximately 10 s was confirmed through an experiment.

Distribution of phosphorylated Elk-1 in rat brain after Y-maze active avoidance training in a temporal manner

BACKGROUND： Elk-1 mRNA distributes extensively in the neurons of mice, rat and human brains, and the Elk-1 expression may be correlated with the synaptic plasticity, learning and memory. OBJECTIVE： To observe the distribution of phosphorylated Elk-1 （pEIk-1） in whole brain of rats received Y-maze active avoidance training and the changes of pEIk-1 expression at different time points after training. DESIGN ： A randomized controlled study SETTING ： Research Room of Neurobiology, the Second Affiliated Hospital of Southern Medical University MATERIALS ： Fifty-five male clean-degree SD rats of 3-4 months old, weighing 200-250 g, were provided by the Experimental Animal Center of Southem Medical University. The rabbit anti-monoclonal pEIk-1 antibody was purchased from Cell Signal Transduction Company, and ABC kit from Vector Company. METHODS ： The experiments were carried out in the Research Room of Neurobiology, Second Affiliated Hospital of Southern Medical University from September 2004 to February 2005. ① Grouping： The rats were randomly divided into training group （n = 25）, sham-training group （n = 25） and normal control group （n = 5）, and the training and sham-training groups were observed at 0, 1, 3, 6 and 24 hours after training, which represented the five phases in the process of leaming and memory. ② Y-maze training： The rats were preconditioned in the electrical Y-maze apparatus, 20 minutes a day for 3 days continuously, and training began from the 4^th day. In the training group, the rats were trained with the combination of light and electddty. Each rat repeated for 60 times in each training, and the correct times were recorded, those correct for less than 25 times were taken as unqualified, and excluded from the training group, and supplemented by other rats in time. In the sham-training group, there was no fixed correlation between the application of light and electricity. The rats in the normal contrel group were given not any training. ③Detection of pEIk-1 expression： The rats were anesthetized after Y-maze training, brain tissue was removed to prepare coronal freezing sections, and the pEIk-1 expression was detected with routine ABC method. MATN OUTCOME MEASURES： ① Distribution of pEIk-1 immuno-positive neurons in whole brain of rats in the normal control group. ②Comparison of the expression of pEIk-1 immuno-positive neurons in whole brain at different time points after training between the training group and sham-training group. RESULTS ： All the 55 rats were involved in result analysis. ③ Distribution of pEIk-1 immuno-positive neurons in the whole brain of rats in the normal control group： Strong expressions of pEIk-1 immuno-positive neurons were observed in prefrontal lobe, granular layer of olfactory bulbs, Purkinje cell layer and granular layer of cerebellum, whole stdate cortex, temporal cortex, pre-pyriform cortex, hypothalamic supraoptic nucleus, hypothalamic paraventricular nucleus and periventricular nucleus, thalamic paraventricular nucleus, pronucleus and postnucleus of amygdala cortex, central nucleus of amygdala, medial amygdaloid nucleus, entorhinal cortex, hippocampal dentate gyros, CA1-4 regions, caudate-putamen, material division, brain stem spinal nucleus of trigeminal nerve, and superior olivary nucleus, and those in hippocampal dentate gyrus and CA1 region were the strongest.② Distribution of pEIk-1 immuno-positive neurons in the whole brain of rats at different time points after training in the training group and sham-training group： In the training group, the expressions were obviously enhanced in caudate-putamen of striatum, material division, most cortexes, hippocampal dentate gyrus, hippocampal CA regions, nucleus amygdalae, thalamic paraventricular nucleus, Purkinje cell layer of cerebellum, entorhinal cortex, hypothalamic supraoptic nucleus, hypothalamic paraventricular nucleus, and periventricular nucleus at 0 hour after training, and the enhancement lasted for 6 hours at least, and those at 24 hours were decreased to normal. In the sham-training group, obvious enhanced expressions of pEIk-1 immuno-positive neurons could be observed in most cortexes, nucleus amygdalae, entorhinal cortex, hypothalamic supraoptic nucleus, hypothalamic paraventdoular nucleus and periventricular nucleus, brain stem spinal nucleus of trigeminal nerve, Purkinje cell layer and granular layer of cerebellum at O, 1, 3 and 6 hours, and decreased to normal after 24 hours. The expressions in material division, caudate-putamen of striatum, hippocampus were not obviously enhanced as compared with those in the normal control group, but significantly different from those in the training group （0, 1, 3, 6 hours after training, material division： F= 0.576, 0.023, 0.116, 8.873, P〈 0.01; caudate-putamen： F= 0.157, 0.427, 0.030, 0.001, P〈 0.01; hippocampus： F= 6.716, 2.405, 14.137, 1.416, P 〈 0.05-0.01 ）. CONCLUSION： The expression of activated pEIk-1 can be detected in the learning related brain areas under normal status, and the perk-1 expression in the brain areas dynamically changed in a time-dependent manner after Y-maze training, and it is indicated that pEIk-1 is involved in the learning and memory process in Y-maze related brain areas.

Distribution of Random Session Key Based on Key-Insulated Public-Key Cryptosystems

Based on the characteristic of key-insulated public-key cryptosystem, wepropose a distributed landora session keys distribution protocol without a key distribution center.The session key is generated by different user and only used one time. So thekey is one-time key. Inaddition, the user who generates the next one-time key, is random selected by the current sessionkey. In the protocol of this paper, the characteristic of time in the key-insulated public-key, adistributed protocol, translates into the characteristic of spaee which every point has differentsecret key in the different period. At the same time, the system is fit for key management in AdHoe, and is a new scheme of key management in Ad Hoc.

DEPENDENCE OF THE DISTRIBUTION OF ACTIVE CENTERS ON MONOMER IN SUPPORTED ZIEGLER-NATTA CATALYSTS

Distribution of active centers(ACD)of ethylene or 1-hexene homopolymerization and ethylene-1-hexene copolymerization with a MgCl_2/TiCl_4 type Z-N catalyst were studied by deconvolution of the polymer molecular weight distribution into multiple Flory components.Each Flory component is thought to be formed by a certain type of active center. ACD of ethylene-1-hexene copolymer with very low 1-hexene incorporation was compared with that of ethylene homopolymer to see the effect of introducingα-olefin on ethyle...

A Dynamic Active Multicast Group Access Control Framework Based on Trust Management System

The current multicast model provides no access control mechanism. Any host can send data directly to a multicast address or join a multicast group to become a member, which brings safety problems to multicast. In this paper, we present a new active multicast group access control mechanism that is founded on trust management. This structure can solve the problem that exists in multicast members＇ access control and distributing authorization of traditional IP multicast.

Ion dynamics into different pore size distributions in supercapacitors under compression

Compressing supercapacitor(SCs)electrode is essential for improving the energy storage characteristics and minimizing ions’distance travel,faradaic reactions,and overall ohmic resistance.Studies comprising the ion dynamics in SC electrodes under compression are still rare.So,the ionic dynamics of five aqueous electrolytes in electrodes under compression were studied in this work for tracking electrochemical and structural changes under mechanical stress.A superionic state is formed when the electrode is compressed until the micropores match the dimensions with the electrolyte’s hydrated ion sizes,which increases the capacitance.If excessive compression is applied,the accessible pore regions decrease,and the capacitance drops.Hence,as the studied hydrated ions have different dimensions,the match between ion/pore sizes differs.To the LiOH and NaClO4electrolytes,increasing the pressure from 60 to 120 and 100 PSI raised the capacitance from 13.5 to 35.2 F g^(-1)and 30.9 to 39.0 F g^(-1),respectively.So,the KOH electrolyte with the lowest and LiCl with the biggest combination of hydrated ion size have their point of maximum capacitance(39.5 and 36.7F g^(-1))achieved at 140 and 80 PSI,respectively.To LiCl and KCl electrolytes,overcompression causes a drop in capacitance higher than 23%.