Call for papers: Special Issue on “Novel technologies for sustainable monitoring of polar environment upscaling from in situ observations to aerial and space-borne remote sensing”

Polar regions have received increasing scientific research attentions,in great part,due to its dramatic changes of temperature in recent decades.Satellite remote sensing data provides consistent,regional and large scales patterns of polar oceans and sea ice that are essential for polar climate modelling and operational service.One the other hand,acquiring in situ observations data is hampered by harsh environmental conditions.These ground truths are critical for remote sensing algorithms and numerical models’validation,and therefore,play important roles to improve the quality of polar weather and climate forecast and enhance better understanding of advances in polar science.

Exploring the mechanisms of calcium carbonate deposition on various substrates with implications for effective anti-scaling material selection

The unexpected scaling phenomena have resulted in significant damages to the oil and gas industries,leading to issues such as heat exchanger failures and pipeline clogging.It is of practical and fundamental importance to understand the scaling mechanisms and develop efficient anti-scaling strategies.However,the underlying surface interaction mechanisms of scalants(e.g.,calcite)with various substrates are still not fully understood.In this work,the colloidal probe atomic force microscopy(AFM)technique has been applied to directly quantify the surface forces between calcite particles and different metallic substrates,including carbon steel(CR1018),low alloy steel(4140),stainless steel(SS304)and tungsten carbide,under different water chemistries(i.e.,salinity and pH).Measured force profiles revealed that the attractive van der Waals(VDW)interaction contributed to the attachment of the calcium carbonate particles on substrate surfaces,while the repulsive electric double layer(EDL)interactions could inhibit the attachment behaviors.High salinity and acidic p H conditions of aqueous solutions could weaken the EDL repulsion and promote the attachment behavior.The adhesion of calcite particles with CR1018 and4140 substrates was much stronger than that with SS304 and tungsten carbide substrates.The bulk scaling tests in aqueous solutions from an industrial oil production process showed that much more severe scaling behaviors of calcite was detected on CR1018 and 4140 than those on SS304 and tungsten carbide,which agreed with surface force measurement results.Besides,high salinity and acidic p H can significantly enhance the scaling phenomena.This work provides fundamental insights into the scaling mechanisms of calcite at the nanoscale with practical implications for the selection of suitable antiscaling materials in petroleum industries.

Generating highly active oxide-phosphide heterostructure through interfacial engineering to break the energy scaling relation toward urea-assisted natural seawater electrolysis

Urea-assisted natural seawater electrolysis is an emerging technology that is effective for grid-scale carbon-neutral hydrogen mass production yet challenging.Circumventing scaling relations is an effective strategy to break through the bottleneck of natural seawater splitting.Herein,by DFT calculation,we demonstrated that the interface boundaries between Ni_(2)P and MoO_(2) play an essential role in the selfrelaxation of the Ni-O interfacial bond,effectively modulating a coordination number of intermediates to control independently their adsorption-free energy,thus circumventing the adsorption-energy scaling relation.Following this conceptual model,a well-defined 3D F-doped Ni_(2)P-MoO_(2) heterostructure microrod array was rationally designed via an interfacial engineering strategy toward urea-assisted natural seawater electrolysis.As a result,the F-Ni_(2)P-MoO_(2) exhibits eminently active and durable bifunctional catalysts for both HER and OER in acid,alkaline,and alkaline sea water-based electrolytes.By in-situ analysis,we found that a thin amorphous layer of NiOOH,which is evolved from the Ni_(2)P during anodic reaction,is real catalytic active sites for the OER and UOR processes.Remarkable,such electrode-assembled urea-assisted natural seawater electrolyzer requires low voltages of 1.29 and 1.75 V to drive 10 and600 mA cm^(-2)and demonstrates superior durability by operating continuously for 100 h at 100 mA cm^(-2),beyond commercial Pt/C||RuO_(2) and most previous reports.

Scaling Laws Behind Penetrative Turbulence:History and Perspectives

An unstably stratified flow entering into a stably stratified flow is referred to as penetrative convection,which is crucial to many physical processes and has been thought of as a key factor for extreme weather conditions.Past theoretical,numerical,and experimental studies on penetrative convection are reviewed,along with field studies providing insights into turbulence modeling.The physical factors that initiate penetrative convection,including internal heat sources,nonlinear constitutive relationships,centrifugal forces and other complicated factors are summarized.Cutting-edge methods for understanding transport mechanisms and statistical properties of penetrative turbulence are also documented,e.g.,the variational approach and quasilinear approach,which derive scaling laws embedded in penetrative turbulence.Exploring these scaling laws in penetrative convection can improve our understanding of large-scale geophysical and astrophysical motions.To better the model of penetrative turbulence towards a practical situation,new directions,e.g.,penetrative convection in spheres,and radiation-forced convection,are proposed.

Integer multiple quantum image scaling based on NEQR and bicubic interpolation

As a branch of quantum image processing,quantum image scaling has been widely studied.However,most of the existing quantum image scaling algorithms are based on nearest-neighbor interpolation and bilinear interpolation,the quantum version of bicubic interpolation has not yet been studied.In this work,we present the first quantum image scaling scheme for bicubic interpolation based on the novel enhanced quantum representation(NEQR).Our scheme can realize synchronous enlargement and reduction of the image with the size of 2^(n)×2^(n) by integral multiple.Firstly,the image is represented by NEQR and the original image coordinates are obtained through multiple CNOT modules.Then,16 neighborhood pixels are obtained by quantum operation circuits,and the corresponding weights of these pixels are calculated by quantum arithmetic modules.Finally,a quantum matrix operation,instead of a classical convolution operation,is used to realize the sum of convolution of these pixels.Through simulation experiments and complexity analysis,we demonstrate that our scheme achieves exponential speedup over the classical bicubic interpolation algorithm,and has better effect than the quantum version of bilinear interpolation.

Direct scaling of residual displacements for bilinear and pinching oscillators

The estimation of residual displacements in a structure due to an anticipated earthquake event has increasingly become an important component of performance-based earthquake engineering because controlling these displacements plays an important role in ensuring cost-feasible or cost-effective repairs in a damaged structure after the event.An attempt is made in this study to obtain statistical estimates of constant-ductility residual displacement spectra for bilinear and pinching oscillators with 5%initial damping,directly in terms of easily available seismological,site,and model parameters.None of the available models for the bilinear and pinching oscillators are useful when design spectra for a seismic hazard at a site are not available.The statistical estimates of a residual displacement spectrum are proposed in terms of earthquake magnitude,epicentral distance,site geology parameter,and three model parameters for a given set of ductility demand and a hysteretic energy capacity coefficient in the case of bilinear and pinching models,as well as for a given set of pinching parameters for displacement and strength at the breakpoint in the case of pinching model alone.The proposed scaling model is applicable to horizontal ground motions in the western U.S.for earthquake magnitudes less than 7 or epicentral distances greater than 20 km.

Accelerated Primal-Dual Projection Neurodynamic Approach With Time Scaling for Linear and Set Constrained Convex Optimization Problems

The Nesterov accelerated dynamical approach serves as an essential tool for addressing convex optimization problems with accelerated convergence rates.Most previous studies in this field have primarily concentrated on unconstrained smooth con-vex optimization problems.In this paper,on the basis of primal-dual dynamical approach,Nesterov accelerated dynamical approach,projection operator and directional gradient,we present two accelerated primal-dual projection neurodynamic approaches with time scaling to address convex optimization problems with smooth and nonsmooth objective functions subject to linear and set constraints,which consist of a second-order ODE(ordinary differential equation)or differential conclusion system for the primal variables and a first-order ODE for the dual vari-ables.By satisfying specific conditions for time scaling,we demonstrate that the proposed approaches have a faster conver-gence rate.This only requires assuming convexity of the objective function.We validate the effectiveness of our proposed two accel-erated primal-dual projection neurodynamic approaches through numerical experiments.

Nonparametric Statistical Feature Scaling Based Quadratic Regressive Convolution Deep Neural Network for Software Fault Prediction

The development of defect prediction plays a significant role in improving software quality. Such predictions are used to identify defective modules before the testing and to minimize the time and cost. The software with defects negatively impacts operational costs and finally affects customer satisfaction. Numerous approaches exist to predict software defects. However, the timely and accurate software bugs are the major challenging issues. To improve the timely and accurate software defect prediction, a novel technique called Nonparametric Statistical feature scaled QuAdratic regressive convolution Deep nEural Network (SQADEN) is introduced. The proposed SQADEN technique mainly includes two major processes namely metric or feature selection and classification. First, the SQADEN uses the nonparametric statistical Torgerson–Gower scaling technique for identifying the relevant software metrics by measuring the similarity using the dice coefficient. The feature selection process is used to minimize the time complexity of software fault prediction. With the selected metrics, software fault perdition with the help of the Quadratic Censored regressive convolution deep neural network-based classification. The deep learning classifier analyzes the training and testing samples using the contingency correlation coefficient. The softstep activation function is used to provide the final fault prediction results. To minimize the error, the Nelder–Mead method is applied to solve non-linear least-squares problems. Finally, accurate classification results with a minimum error are obtained at the output layer. Experimental evaluation is carried out with different quantitative metrics such as accuracy, precision, recall, F-measure, and time complexity. The analyzed results demonstrate the superior performance of our proposed SQADEN technique with maximum accuracy, sensitivity and specificity by 3%, 3%, 2% and 3% and minimum time and space by 13% and 15% when compared with the two state-of-the-art methods.

基于分数阶傅里叶变换和图像加权熵的chirp scaling算法

针对传统的基于傅里叶变换和匹配滤波实现的chirp scaling(CS)成像算法中多普勒参数随斜距变化以及成像分辨率低的问题,提出利用分数阶傅里叶变换(FRFT)对CS成像算法进行优化。首先建立斜视合成孔径雷达(SAR)回波信号模型,理论推导利用FRFT代替匹配滤波进行信号压缩。针对方位向最优旋转角的搜索问题,对得到的图像基于加权最小熵建立代价函数,利用动量法的梯度下降优化算法进行迭代计算,最终得到分辨率更高的SAR图像。为验证算法的有效性,分别在点目标仿真数据和实测SAR数据集上进行实验。结果表明,与传统CS成像算法相比,该算法的成像结果成像主瓣宽度更窄、旁瓣更低、成像更加清晰。

The Impact of Model Based Offset Scaling Technique on the Amplitude Variation with Offset Responses from 3D Seismic Data Acquired from the Tano Basin, Offshore Ghana

Amplitudes have been found to be a function of incident angle and offset. Hence data required to test for amplitude variation with angle or offset needs to have its amplitudes for all offsets preserved and not stacked. Amplitude Variation with Offset (AVO)/Amplitude Variation with Angle (AVA) is necessary to account for information in the offset/angle parameter (mode converted S-wave and P-wave velocities). Since amplitudes are a function of the converted S- and P-waves, it is important to investigate the dependence of amplitudes on the elastic (P- and S-waves) parameters from the seismic data. By modelling these effects for different reservoir fluids via fluid substitution, various AVO geobody classes present along the well and in the entire seismic cube can be observed. AVO analysis was performed on one test well (Well_1) and 3D pre-stack angle gathers from the Tano Basin. The analysis involves creating a synthetic model to infer the effect of offset scaling techniques on amplitude responses in the Tano basin as compared to the effect of unscaled seismic data. The spectral balance process was performed to match the amplitude spectra of all angle stacks to that of the mid (26°) stack on the test lines. The process had an effect primarily on the far (34° - 40°) stacks. The frequency content of these stacks slightly increased to match that of the near and mid stacks. In offset scaling process, the root mean square (RMS) amplitude comparison between the synthetic and seismic suggests that the amplitude of the far traces should be reduced relative to the nears by up to 16%. However, the exact scaler values depend on the time window considered. This suggests that the amplitude scaling with offset delivered from seismic processing is only approximately correct and needs to be checked with well synthetics and adjusted accordingly prior to use for AVO studies. The AVO attribute volumes generated were better at resolving anomalies on spectrally balanced and offset scaled data than data delivered from conventional processing. A typical class II AVO anomaly is seen along the test well from the cross-plot analysis and AVO attribute cube which indicates an oil filled reservoir.

Gravitation, Density Upper Limit and Quantization of Space

The singularity at distance r → 0 at the center of a spherically symmetric non-rotating, uncharged mass of radius R, is considered here. Under inverse square law force, the Schwarzschild metric, needs to be modified, to include Newton’s Shell Theorem (NST). By including NST for r, both Schwarzschild singularity at r = 2GM/c2 and at r → 0 singularities are removed from the metric. Near R → 0, the question of maximal density is considered based on Schwarzschild’s modified metric, and compared to the quantum limit of maximal mass density put by Planck’s quantum-based universal units. It is asserted, that General relativity, when combined with Planck’s universal units, inevitably leads to quantization of gravity.

Classical Cosmology III. Modified Tired Light and Distance Modulus for Supernovae

We analyze a simple model for tired light in a cosmological environment, a generalized model, and a spectroscopic model. The three models are tested on different compilations for the distance modulus of supernovae. The tests are negative for the simple tired light and the spectroscopic models, but positive for the generalized tired light model. The percentage error of the distance modulus for the generalized tired light model compared with the distance modulus of standard cosmology is less than one percent over the considered ranges in redshift.

High Dimension Multivariate Data Analysis for Small Group Samples of Chemical Volatile Profiles of African Nightshade Species

Quantitative headspace analysis of volatiles emitted by plants or any other living organisms in chemical ecology studies generates large multidimensional data that require extensive mining and refining to extract useful information. More often the number of variables and the quantified volatile compounds exceed the number of observations or samples and hence many traditional statistical analysis methods become inefficient. Here, we employed machine learning algorithm, random forest (RF) in combination with distance-based procedure, similarity percentage (SIMPER) as preprocessing steps to reduce the data dimensionality in the chemical profiles of volatiles from three African nightshade plant species before subjecting the data to non-metric multidimensional scaling (NMDS). In addition, non-parametric methods namely permutational multivariate analysis of variance (PERMANOVA) and analysis of similarities (ANOSIM) were applied to test hypothesis of differences among the African nightshade species based on the volatiles profiles and ascertain the patterns revealed by NMDS plots. Our results revealed that there were significant differences among the African nightshade species when the data’s dimension was reduced using RF variable importance and SIMPER, as also supported by NMDS plots that showed S. scabrum being separated from S. villosum and S. sarrachoides based on the reduced data variables. The novelty of our work is on the merits of using data reduction techniques to successfully reveal differences in groups which could have otherwise not been the case if the analysis were performed on the entire original data matrix characterized by small samples. The R code used in the analysis has been shared herein for interested researchers to customise it for their own data of similar nature.

Assessment of Groundwater Stability Using Corrosion and Scaling Tendency Indices on Selected Springs in the Manga Region in Nyamira County, Kenya

We present the result of groundwater stability assessment on three major springs in the Manga region in Nyamira County found in Kenya in 2018. These springs are Kiangoso (SP1), Kerongo (SP2) and Tetema (SP3). The corrosion and scaling tendency indices were obtained using the Langelier saturation index (LSI), Ryznar stability index (RSI), and Puckorius scaling index (PSI). The LSI values obtained for SP1, SP2, and SP3 are −3.93, −4.71, and −4.17, respectively, while using RSI, the values obtained for SP1, SP2, and SP3 are 14.15, 14.53, and 13.74, respectively. Using PSI, the values of SP1, SP2, and SP3 are 5.58, 5.45, and 5.58, respectively. From the interpretation of the indices, the groundwater from the three springs in the Manga region using LSI and RSI showed intolerable corrosion;hence, it is unlikely to scale as obtained from PSI.

Evaluation of Digits-in-Noise Test and Hearing Handicap Inventory for Adults Screening in Patients with Occupational Noise-Induced Hearing Loss

Objective:To explore the clinical evaluation role of the Digits-in-Noise(DIN)test and Hearing Handicap Inventory for Adults Screening(HHIA-S)for patients with occupational noise-induced hearing loss and to observe and analyze their application values.Methods:Fifty patients with suspected occupational noise-induced hearing loss were randomly selected from the Department of Otolaryngology at the hospital as the research target.The collection period for the research cases spanned from January 2022 to November 2023,and all patients had a history of noise exposure.The DIN test and HHIA-S were used for hearing examinations,with clinical,comprehensive diagnosis serving as the gold standard to study their diagnostic performance.Results:The compliance rate of the DIN test was 88.00%,the HHIA-S’s compliance rate was 80.00%,and the combined compliance rate was 94.00%.The compliance rate of the DIN test and the combined compliance rates of the patients were statistically significant compared to the clinical gold standard data(P<0.05),while there was no difference between the compliance rate of the HHIA-S and the gold standard(P>0.05).The data shows that the sensitivity of the combined diagnosis is significantly higher than the sensitivity data of the DIN test and HHIA-S examination alone(P<0.05).Its specificity is 100.00%,and the accuracy data of the joint diagnosis in the degree were higher than those of the DIN test alone(P>0.05)and the HHIA-S alone(P<0.05).Conclusion:For patients with occupational noise-induced hearing loss,the joint evaluation of the DIN test and HHIA-S can significantly improve their diagnostic value with high sensitivity and accuracy.

Upsilon Constants and Their Usefulness in Planck Scale Quantum Cosmology

This paper introduces the two Upsilon constants to the reader. Their usefulness is described with respect to acting as coupling constants between the CMB temperature and the Hubble constant. In addition, this paper summarizes the current state of quantum cosmology with respect to the Flat Space Cosmology (FSC) model. Although the FSC quantum cosmology formulae were published in 2018, they are only rearrangements and substitutions of the other assumptions into the original FSC Hubble temperature formula. In a real sense, this temperature formula was the first quantum cosmology formula developed since Hawking’s black hole temperature formula. A recent development in the last month proves that the FSC Hubble temperature formula can be derived from the Stephan-Boltzmann law. Thus, this Hubble temperature formula effectively unites some quantum developments with the general relativity model inherent in FSC. More progress towards unification in the near-future is expected.

Coupling Research on the Process of Transfer of Surplus Labor Forces and Scaling-up of Farmland

On the basis of giving an overview of efficiency research on transformation of land from fragmentation to scale economy, by using the concept of coupling in physics, this paper expounds the behavior basis of transfer of surplus rural labor forces in China and transformation of land from fragmentation to scaling up, and analyzes behaviors of all parties and equilibrium outcomes in the three stages concerning the transformation of agricultural land from fragmentation to scaling up as follows. At the first stage of coupling, after multitudinous rural surplus labor forces emerge, the farmers begin to go to city seeking jobs. In this period, the amalgamation of land management has not occurred and the single farmer's land has not yet concentrated. The total land area of single farmer has not yet increased and the total amount of farmers has not yet decreased. At the second stage of coupling, driven by living standards and income, multitudinous rural surplus labor forces begin to live in the city permanently in fact, and the scale management of rural land begins to arise. Foreign funded enterprises begin to enter agriculture, and the industrialization management of agriculture is equipped with the most fundamental conditions due to the occurrence of scaling up of land. At the third stage of coupling, the transfer of rural surplus labor forces basically ends. The property rights of agricultural land or the management forms also, in a large measure, concentrate. The obstacles to agricultural scaling-up management are solved fundamentally, and the income gap between urban areas and rural areas is narrowed. Urban-rural population migration is no longer the main form of China's population migration. This stage has not yet been realized in China and it is the future state of villages. Finally, through the two cases researched by the predecessors, we verify the research results of the preceding two stages, which provides reliable reference for transformation of China's agricultural land management, and policy formulation of transfer of surplus labor forces.

Surface lurking and interfacial ion release strategy for fabricating a superhydrophobic coating with scaling inhibition

The design and manufacture of anti-scaling surface is a prospective way to prevent scaling in oil field.In this work,a novel superhydrophobic Cu^(2+)-loaded and DTPMPA-modified anodized copper oxide(S-Cu^(2+)/D-ACO)coating was fabricated by modification of 1H,1H,2H,2H-perfluorodecyltriethoxysilane.The valid storing of scale inhibitors at the coating surface and the interfacial release of Cu^(2+)ions contribute to enhancing the anti-scaling of the S-Cu^(2+)/D-ACO coating.The water contact angle of the S-Cu^(2+)/D-ACO coating is 163.03°and exhibits superhydrophobicity,which makes it difficult for CaCO_(3)to deposit at the surface of the coating.DTPMPA will steadily lurk into the inner space,and Cu^(2+)will be loaded at the interface in the form of the DTPMPA:Cu^(2+)chelate.During the deposition of CaCO_(3),the dynamic release of DTPMPA can be realized by transferring DTPMPA:Cu^(2+)to DTPMPA:Ca^(2+).Interestingly,the released Cu^(2+)hinders the active growth of CaCO_(3).After 48 h of scaling,the mass of CaCO_(3)scale at the S-Cu^(2+)/D-ACO coating surface is only 44.1%that of the anodized copper oxide coating.The excellent anti-scaling performance of the S-Cu^(2+)/D-ACO coating is determined by the synergistic effect of the DTPMPA lurking and dynamic release,as well as the Cu^(2+)inhibition at the interface of superhydrophobic coating and against CaCO_(3)deposition.This research provides a new exploration for designing and fabricating anti-scaling superhydrophobic surface for oil field development.

基于逆chirp scaling的合成孔径雷达卷积欺骗干扰方法

针对现有合成孔径雷达(synthetic aperture radar,SAR)欺骗干扰方法生成虚假场景时难以兼顾逼真度和低计算量的问题,提出了一种基于逆chirp scaling(CS)成像方法的SAR卷积欺骗干扰方法.该方法利用相位相乘补偿虚假场景内各虚假点的距离徙动,避免了插值运算,在降低求解干扰机频率响应函数计算量的同时,提高了虚假场景的生成精度.并且通过对欺骗模板进行线性调频Z变换(chirp-Z transform,CZT),直接从模板图像变换到实际SAR信号对应的空间频域,再次避免了插值运算,进一步降低了求解干扰机频率响应函数的计算量,提高了干扰机实时性.理论分析和仿真实验验证了相比逆omega-K(ωk)近似方法和经典的两步生成方法,本文方法能够兼顾虚假场景的生成精度和计算效率.

可视化编程语言中small-screen与scaling-up问题解决方法探讨

由于目前可视化编程语言的设计工具主要集中于将其语素和数据应用二维图形对象来表示的范例来实现,针对其随之产生的sm all-screen与scaling-up问题,提出了一种在二维可视化编程环境下进行解决的方案。可以证明在解决实际问题中效果明显。