Determining the effective elastic thickness through cross-correlation between isostatic disturbances

The elastic thickness parameter was estimated using the mobile correlation technique between the observed isostatic disturbance and the gravity disturbance calculated through direct gravimetric modeling. We computed the vertical flexure value of the crust for a specific elastic thickness using a given topographic dataset. The gravity disturbance due to the topography was determined after the calculation. A grid of values for the elastic thickness parameter was generated. Then, a moving correlation was performed between the observed gravity data(representing actual surface data) and the calculated data from the forward modeling. The optimum elastic thickness of the particular point corresponded to the highest correlation coefficient. The methodology was tested on synthetic data and showed that the synthetic depth closely matched the original depth, including the elastic thickness value. To validate the results, the described procedure was applied to a real dataset from the Barreirinhas Basin, situated in the northeastern region of Brazil. The results show that the obtained crustal depth is highly correlated with the depth from known models. Additionally, we noted that the elastic thickness behaves as expected, decreasing from the continent towards the ocean. Based on the results, this method has the potential to be employed as a direct estimate of crustal depth and elastic thickness for any region.

Tuning the electronic conductance of REH_(x)(RE=Nd,Ce,Pr)by structural deformation

Hydride ion(H-)conductors have drawn much attention due to their potential applications in hydrideion-based devices.Rare earth metal hydrides(REH_(x))have fast H-conduction which,unfortunately,is accompanied by detrimental electron conduction preventing their application as ion conductors.Here,REH_(x)(RE=Nd,Ce,and Pr)with varied grain sizes,rich grain boundaries,and defects have been prepared by ball milling and subsequent sintering.The electronic conductivity of the ball-milled REH_(x)samples can be reduced by 2-4 orders of magnitude compared with the non-ball-milled samples.The relationship of electron conduction and miscrostructures in REH_(x)is studied and discussed based on experimental data and previously-proposed classical and quantum theories.The H-conductivity of all REH_(x)is about 10^(-4)to 10^(-3)S cm^(-1)at room temperature,showing promise for the development of H-conductors and their applications in clean energy storage and conversion.

Peak structure in the interlayer conductance of Moirésuperlattices

We investigate the peak structure in the interlayer conductance of Moirésuperlattices using a tunneling theory wedeveloped previously.The theoretical results predict that,due to the resonance of two different partial waves,the doublepeakstructure can appear in the curve of the interlayer conductance versus twist angle.Furthermore,we study the influencesof the model parameters,i.e.,the chemical potential of electrodes,the thickness of Moirésuperlattice,and the strength ofinterface potential,on the peak structure of the interlayer conductance.In particular,the parameter dependence of the peakstructure is concluded via a phase diagram,and the physical meanings of the phase diagram is formulized.Finally,thepotential applications of the present work is discussed.

People Recognition by RGB and NIR Analysis from Digital Image Database Using Cross-Correlation and Wavelets

This document presents a framework for recognizing people by palm vein distribution analysis using cross-correlation based signatures to obtain descriptors. Haar wavelets are useful in reducing the number of features while maintaining high recognition rates. This experiment achieved 97.5% of individuals classified correctly with two levels of Haar wavelets. This study used twelve-version of RGB and NIR (near infrared) wavelength images per individual. One hundred people were studied;therefore 4,800 instances compose the complete database. A Multilayer Perceptron (MLP) was trained to improve the recognition rate in a k-fold cross-validation test with k = 10. Classification results using MLP neural network were obtained using Weka (open source machine learning software).

Inter‑Skeleton Conductive Routes Tuning Multifunctional Conductive Foam for Electromagnetic Interference Shielding,Sensing and Thermal Management

Conductive polymer foam(CPF)with excellent compressibility and variable resistance has promising applications in electromagnetic interference(EMI)shielding and other integrated functions for wearable electronics.However,its insufficient change amplitude of resistance with compressive strain generally leads to a degradation of shielding performance during deformation.Here,an innovative loading strategy of conductive materials on polymer foam is proposed to significantly increase the contact probability and contact area of conductive components under compression.Unique inter-skeleton conductive films are constructed by loading alginate-decorated magnetic liquid metal on the polymethacrylate films hanged between the foam skeleton(denoted as AMLM-PM foam).Traditional point contact between conductive skeletons under compression is upgraded to planar contact between conductive films.Therefore,the resistance change of AMLM-PM reaches four orders of magnitude under compression.Moreover,the inter-skeleton conductive films can improve the mechanical strength of foam,prevent the leakage of liquid metal and increase the scattering area of EM wave.AMLM-PM foam has strain-adaptive EMI shielding performance and shows compression-enhanced shielding effectiveness,solving the problem of traditional CPFs upon compression.The upgrade of resistance response also enables foam to achieve sensitive pressure sensing over a wide pressure range and compression-regulated Joule heating function.

Low Level of Cystic Fibrosis Transmembrane Conductance Regulator Is Associated with Human Sperm Autophagy and Vitality

Low sperm motility is one of the main causes of male infertility. Cystic fibrosis transmembrane conductance regulator (CFTR, an anion channel protein) is related to the progressive motility of sperm. CFTR disruptor CFTRinh-172 or forskolin (FSK) in this study were used to treat human sperm separately, and the rates of sperm autophagy and progressive motility, mitochondrial membrane potential (MMP) and ATP concentration, and the expression levels of related factors were detected to explore their relationship. It was showed that sperms treated with CFTRinh-172 or FSK reduced the levels of cAMP, CFTR and PKA, but increased sperm autophagy rate, expression levels of AMPK and LC3B. However, reactive oxygen species content had no significant difference. It was indicated that low level of CFTR performed with cAMP and its downstream effectors such as PKA and AMPK to regulate mitochondrial structure and function, leading to increased autophagy rate and reduced vitality of sperm.

Cross-Correlation between Global Temperature and Atmospheric CO2 with a Temperature-Leading Time Lag

The temperature change and rate of CO2 change are correlated with a time lag, as reported in a previous paper. The correlation was investigated by calculating a correlation coefficient r of these changes for selected ENSO events in this study. Annual periodical increases and decreases in the CO2 concentration were considered, with a regular pattern of minimum values in August and maximum values in May each year. An increased deviation in CO2 and temperature was found in response to the occurrence of El Niño, but the increase in CO2 lagged behind the change in temperature by 5 months. This pattern was not observed for La Niña events. An increase in global CO2 emissions and a subsequent increase in global temperature proposed by IPCC were not observed, but an increase in global temperature, an increase in soil respiration, and a subsequent increase in global CO2 emissions were noticed. This natural process can be clearly detected during periods of increasing temperature specifically during El Niño events. The results cast strong doubts that anthropogenic CO2 is the cause of global warming.

Effect of a Carbon Fibre-steel Fibre-graphite Conductive Filler on the Electrothermal Properties of Cementitious Materials

Carbon fibre,steel fibre and graphite were used as conductive fillers to prepare cementitious materials with excellent electrothermal properties.The electrically conductive cementitious materials with different volume dosages were analysed through compressive and flexural strength,electrochemical impedance spectroscopy and temperature rise tests.An equivalent circuit model was established to study the electrically conductive heat generation mechanism in the electrically conductive cementitious composites.The results indicate that the mechanical properties of cementitious composite materials with a ternary conductive phase are better than those of pristine cementitious materials because the fibrous filler improves their mechanical properties.However,the incorporation of graphite in the material reduces its strength.Introducing fibrous and point-like conductive phase materials into the cementitious material enhances the overall conductive pathway and considerably reduces the electrical resistance of the cementitious material,enhancing its conductive properties.The volume ratios of carbon fibre,steel fibre and graphite that achieve an optimal complex doping in the cementitious material were 0.35%,0.6%and 6%,respectively.This was determined using the mutation point of each circuit element parameter as the percolation threshold.In addition,at a certain safety voltage,there is a uniform change between the internal and surface temperatures of the conductive cementitious material,and the heating effect in this materialis is considerably better than that in the pristine cementitious material.

Laser‑Induced Highly Stable Conductive Hydrogels for Robust Bioelectronics

Despite the promising progress in conductive hydrogels made with pure conducting polymer,great challenges remain in the interface adhesion and robustness in longterm monitoring.To address these challenges,Prof.Seung Hwan Ko and Taek-Soo Kim’s team introduced a laserinduced phase separation and adhesion method for fabricating conductive hydrogels consisting of pure poly(3,4-ethylenedioxythiophene):polystyrene sulfonate on polymer substrates.The laser-induced phase separation and adhesion treated conducting polymers can be selectively transformed into conductive hydrogels that exhibit wet conductivities of 101.4 S cm^(−1) with a spatial resolution down to 5μm.Moreover,they maintain impedance and charge-storage capacity even after 1 h of sonication.The micropatterned electrode arrays demonstrate their potential in long-term in vivo signal recordings,highlighting their promising role in the field of bioelectronics.

Aligned Ion Conduction Pathway of Polyrotaxane‑Based Electrolyte with Dispersed Hydrophobic Chains for Solid‑State Lithium–Oxygen Batteries

A critical challenge hindering the practical application of lithium–oxygen batteries(LOBs)is the inevitable problems associated with liquid electrolytes,such as evaporation and safety problems.Our study addresses these problems by proposing a modified polyrotaxane(mPR)-based solid polymer electrolyte(SPE)design that simultaneously mitigates solvent-related problems and improves conductivity.mPR-SPE exhibits high ion conductivity(2.8×10^(−3)S cm^(−1)at 25℃)through aligned ion conduction pathways and provides electrode protection ability through hydrophobic chain dispersion.Integrating this mPR-SPE into solid-state LOBs resulted in stable potentials over 300 cycles.In situ Raman spectroscopy reveals the presence of an LiO_(2)intermediate alongside Li_(2)O_(2)during oxygen reactions.Ex situ X-ray diffraction confirm the ability of the SPE to hinder the permeation of oxygen and moisture,as demonstrated by the air permeability tests.The present study suggests that maintaining a low residual solvent while achieving high ionic conductivity is crucial for restricting the sub-reactions of solid-state LOBs.

Large-deformation finite-element modeling of seismic landslide runout: 3D probabilistic analysis with cross-correlated random field

Landslides significantly threaten lives and infrastructure, especially in seismically active regions. This study conducts a probabilistic analysis of seismic landslide runout behavior, leveraging a large-deformation finite-element (LDFE) model that accounts for the three-dimensional (3D) spatial variability and cross-correlation in soil strength — a reflection of natural soils' inherent properties. LDFE model results are validated by comparing them against previous studies, followed by an examination of the effects of univariable, uncorrelated bivariable, and cross-correlated bivariable random fields on landslide runout behavior. The study's findings reveal that integrating variability in both friction angle and cohesion within uncorrelated bivariable random fields markedly influences runout distances when compared with univariable random fields. Moreover, the cross-correlation of soil cohesion and friction angle dramatically affects runout behavior, with positive correlations enlarging and negative correlations reducing runout distances. Transitioning from two-dimensional (2D) to 3D analyses, a more realistic representation of sliding surface, landslide velocity, runout distance and final deposit morphology is achieved. The study highlights that 2D random analyses substantially underestimate the mean value and overestimate the variability of runout distance, underscoring the importance of 3D modeling in accurately predicting landslide behavior. Overall, this work emphasizes the essential role of understanding 3D cross-correlation in soil strength for landslide hazard assessment and mitigation strategies.

Hydraulic conductivity over a wide suction range of loess with different dry densities

Experimental research into the hydraulic conductivity curve (HCC) of unsaturated soil is limited due to the inherent challenge associated with labor, cost, and time. Typically, the HCC is estimated using the soil water characteristic curve (SWCC) based models and saturated hydraulic conductivity (SHC). However, the efficiency of the SWCC-based model is rarely assessed, and the influence of soil density and pore structure on HCC remains incomplete due to limited experimental data. To address this gap, this study employs an innovative filter-paper-based column method, which can measure the HCC over a wide suction range (e.g. 0−105 kPa), to capture the HCCs of both intact and compacted specimens with varying dry densities. The efficiency of two typical SWCC-based models is assessed using the measured data. Meanwhile, the mercury intrusion porosity (MIP) technique is employed to obtain the pore characteristic (i.e. pore size distribution (PSD)) and a method of predicting the HCC using the PSD data is proposed, emphasizing the dominant role of the pore structure in shaping the HCC. The results reveal that the dry density's influence on the HCC is primarily observed within the low suction range, corresponding to variations in the dominant and large pores. In the high suction range, the HCCs align along a linear trajectory when plotted in a log-log format. A notable finding is the overestimation of the HCC obtained from the SWCC-based models using the measured SHC. When the SHC is regarded as a fitting parameter, good agreement is achieved. The adjusted SHC value is typically 0-1 order of magnitude lower than the measured value, and this discrepancy diminishes as dry density increases. On the other hand, the proposed PSD-based model performs well with the measured SHC data. Caution is exercised when using the SHC to estimate the HCC for modeling water movement in partially saturated soil.

SIMULATION OF THE PHYSIOLOGICAL RESPONSES OF C 3 PLANT LEAVES TO ENVIRONMENTAL FACTORS BY A MODEL WHICH COMBINES STOMATAL CONDUCTANCE, PHOTOSYNTHESIS AND TRANSPIRATION

Transpiration element is included in the integrated stomatal conductance photosynthesis model by considering gaseous transfer processes, so the present model is capable to simulate the influence of boundary layer conductance. Leuning in his revised Ball's model replaced relative humidity with VPD s (the vapor pressure deficit from stomatal pore to leaf surface) and thereby made the relation with transpiration more straightforward, and made it possible for the regulation of transpiration and the influence of boundary layer conductance to be integrated into the combined model. If the differences in water vapor and CO 2 concentration between leaf and ambient air are considered, VPD s , the evaporative demand, is influenced by stomatal and boundary layer conductance. The physiological responses of photosynthesis, transpiration, and stomatal function, and the changes of intercellular CO 2 and water use efficiency to environmental factors, such as wind speed, photon flux density, leaf temperature and ambient CO 2, are analyzed. It is shown that if the boundary layer conductance drops to a level comparable with stomatal conductance, the results of simulation by the model presented here differ significantly from those by the previous model, and, in some cases, are more realistic than the latter.

Predicted interfacial thermal conductance and thermal conductivity of diamond/Al composites with various interfacial coatings

The interfacial thermal conductance （ITC） and thermal conductivity （TC） of diamond/Al composites with various coatings were theoretically studied and discussed. A series of predictions and numerical analyses were performed to investigate the effect of thickness, sound velocity, and other parameters of coating layers on the ITC and TC. It is found that both the ITC and TC decline with increasing coating thickness, especially for the coatings with relatively low thermal conductivity. Nevertheless, if the coating thickness is close to zero, or quite a small value, the ITC and TC are mainly determined by the constants of the coating material. Under this condition, coatings such as Ni, TiC, Mo 2 C, SiC, and Si can significantly improve the ITC and TC of diamond/Al composites. By contrast, coatings like Ag will exert the negative effect. Taking the optimization of interfacial bonding into account, conductive carbides such as TiC or Mo 2 C with low thickness can be the most suitable coatings for diamond/Al composites.

Fractal Prediction Model of Thermal Contact Conductance of Rough Surfaces

The thermal contact conductance problem is an important issue in studying the heat transfer of engineering surfaces, which has been widely studied since last few decades, and for predicting which many theoretical models have been established. However, the models which have been existed are lack of objectivity due to that they are mostly studied based on the statistical methodology characterization for rough surfaces and simple partition for the deformation formats of contact asperity. In this paper, a fractal prediction model is developed for the thermal contact conductance between two rough surfaces based on the rough surface being described by three-dimensional Weierstrass and Mandelbrot fractal function and assuming that there are three kinds of asperity deformation modes： elastic, elastoplastic and fully plastic. Influences of contact load and contact area as well as fractal parameters and material properties on the thermal contact conductance are investigated by using the presented model. The investigation results show that the thermal contact conductance increases with the increasing of the contact load and contact area. The larger the fractal dimension, or the smaller the fractal roughness, the larger the thermal contact conductance is. The thermal contact conductance increases with decreasing the ratio of Young＇s elastic modulus to the microhardness. The results obtained indicate that the proposed model can effectively predict the thermal contact conductance at the interface, which provide certain reference to the further study on the issue of heat transfer between contact surfaces.

Temporal-spatial cross-correlation analysis of non-stationary near-surface wind speed time series

Temporal-spatial cross-correlation analysis of non-stationary wind speed time series plays a crucial role in wind field reconstruction as well as in wind pattern recognition.Firstly,the near-surface wind speed time series recorded at different locations are studied using the detrended fluctuation analysis(DFA),and the corresponding scaling exponents are larger than 1.This indicates that all these wind speed time series have non-stationary characteristics.Secondly,concerning this special feature( i.e.,non-stationarity)of wind signals,a cross-correlation analysis method,namely detrended cross-correlation analysis(DCCA) coefficient,is employed to evaluate the temporal-spatial cross-correlations between non-stationary time series of different anemometer pairs.Finally,experiments on ten wind speed data synchronously collected by the ten anemometers with equidistant arrangement illustrate that the method of DCCA cross-correlation coefficient can accurately analyze full-scale temporal-spatial cross-correlation between non-stationary time series and also can easily identify the seasonal component,while three traditional cross-correlation techniques(i.e.,Pearson coefficient,cross-correlation function,and DCCA method) cannot give us these information directly.

Reconstruction of sub cross-correlation cancellation technique for unambiguous acquisition of BOC(kn, n) signals

In order to solve the problem of ambiguous acquisition of BOC signals caused by its property of multiple peaks,an unambiguous acquisition algorithm named reconstruction of sub cross-correlation cancellation technique(RSCCT)for BOC(kn,n)signals is proposed.In this paper,the principle of signal decomposition is combined with the traditional acquisition algorithm structure,and then based on the method of reconstructing the correlation function.The method firstly gets the sub-pseudorandom noise(PRN)code by decomposing the local PRN code,then uses BOC(kn,n)and the sub-PRN code cross-correlation to get the sub cross-correlation function.Finally,the correlation peak with a single peak is obtained by reconstructing the sub cross-correlation function so that the ambiguities of BOC acquisition are removed.The simulation shows that RSCCT can completely eliminate the side peaks of BOC(kn,n)group signals while maintaining the narrow correlation of BOC,and its computational complexity is equivalent to sub carrier phase cancellation(SCPC)and autocorrelation side-peak cancellation technique(ASPeCT),and it reduces the computational complexity relative to BPSK-like.For BOC(n,n),the acquisition sensitivity of RSCCT is 3.25 dB,0.81 dB and 0.25 dB higher than binary phase shift keying(BPSK)-like,SCPC and ASPeCT at the acquisition probability of 90%,respectively.The peak to average power ratio is 1.91,3.0 and 3.7 times higher than ASPeCT,SCPC and BPSK-like at SNR=–20 dB,respectively.For BOC(2n,n),the acquisition sensitivity of RSCCT is 5.5 dB,1.25 dB and 2.69 dB higher than BPSK-like,SCPC and ASPeCT at the acquisition probability of 90%,respectively.The peak to average power ratio is 1.02,1.68 and 2.12 times higher than ASPeCT,SCPC and BPSK-like at SNR=–20 dB,respectively.

Estimation of Cloud Motion Using Cross-Correlation

This paper describes the estimation of cloud motion using lag cross-correlation. In order to compute the lag cross correlation, the Bayes Decision method is used first to identify cloud and surface of earth. Then cloud motion vectors are retrieved at a subset of points through multiple applications of a cross-correlation analysis. An objective analysis is used to define displacement at every satellite pixel throughout the domain and smooth the local inconsistencies. Cloud motions are then produced with a backward trajectory technique by using these displacement vectors.

Study of the Conductance Characteristic of Doped Polymer by Monte Carlo Method

The conduct mechanism of the doped polymer is considered. In an asymmetrysystem composed of high polymer and doping conductive matte, chain or congeries framework will beformed between the conductive particles to improve the conductance characteristic. In thisprocession, the conductive particles interact to each other. In this paper, we describe theconductance of the doped polymer by Monte Carlo method. The results accord with the experimentsquite well. It can be concluded that there is an evident change of doped polymer from nonconductorto metal.

Detrended cross-correlation analysis of electroencephalogram

In the paper we use detrended cross-correlation analysis （DCCA） to study the electroencephalograms of healthy young subjects and healthy old subjects. It is found that the cross-correlation between different leads of a healthy young subject is larger than that of a healthy old subject. It was shown that the cross-correlation relationship decreases with the aging process and the phenomenon can help to diagnose whether the subject＇s brain function is healthy or not.