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Simulations are an essential tool in all areas of population genetic research, used in tasks such as the validation of theoretical analysis and the study of complex evolutionary models. Forward-in-time simulations are especially flexible, allowing for various types of natural selection, complex genetic architectures, and non-Wright–Fisher dynamics. However, their intense computational requirements can be prohibitive to simulating large populations and genomes. A popular method to alleviate this burden is to scale down the population size by some scaling factor while scaling up the mutation rate, selection coefficients, and recombination rate by the same factor. However, this rescaling approach may in some cases bias simulation results. To investigate the manner and degree to which rescaling impacts simulation outcomes, we carried out simulations with different demographic histories and distributions of fitness effects using several values of the rescaling factor, Q , and compared the deviation of key outcomes (fixation times, allele frequencies, linkage disequilibrium, and the fraction of mutations that fix during the simulation) between the scaled and unscaled simulations. Our results indicate that scaling introduces substantial biases to each of these measured outcomes, even at small values of Q. Moreover, the nature of these effects depends on the evolutionary model and scaling factor being examined. While increasing the scaling factor tends to increase the observed biases, this relationship is not always straightforward; thus, it may be difficult to know the impact of scaling on simulation outcomes a priori. However, it appears that for most models, only a small number of replicates was needed to accurately quantify the bias produced by rescaling for a given Q. In summary, while rescaling forward-in-time simulations may be necessary in many cases, researchers should be aware of the rescaling procedure's impact on simulation outcomes and consider investigating its magnitude in smaller scale simulations of the desired model(s) before selecting an appropriate value of Q. [ABSTRACT FROM AUTHOR]

Abstract China's operational highway subgrades exhibit a trend of diversifying types and an increasing number of defects, leading to more frequent urban road safety incidents. This paper starts from the non-destructive testing of urban road subgrade defects using geological radar, aiming to achieve intelligent identification of subgrade pathologies with geological radar. The GprMax forward simulation software is used to establish multi-layer composite structural models of the subgrade, studying the characteristics of geological radar images for different types of subgrade diseases. Based on the forward simulation images of geological radar for subgrade defects and field measurement data, a geological radar subgrade defect image database is established. The Faster R-CNN deep learning algorithm is applied to achieve target detection, recognition, and classification of subgrade defect images. By comparing the loss value, total number of identified regions, and recognition accuracy as metrics, the study compares four improved versions of the Faster R-CNN algorithm. The results indicate that the faster_rcnn_inception_v2 version is more suitable for the intelligent identification of non-destructive testing of urban road subgrade defects.

Copyright of World Nuclear Geoscience is the property of World Nuclear Geoscience Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

China's operational highway subgrades exhibit a trend of diversifying types and an increasing number of defects, leading to more frequent urban road safety incidents. This paper starts from the non-destructive testing of urban road subgrade defects using geological radar, aiming to achieve intelligent identification of subgrade pathologies with geological radar. The GprMax forward simulation software is used to establish multi-layer composite structural models of the subgrade, studying the characteristics of geological radar images for different types of subgrade diseases. Based on the forward simulation images of geological radar for subgrade defects and field measurement data, a geological radar subgrade defect image database is established. The Faster R-CNN deep learning algorithm is applied to achieve target detection, recognition, and classification of subgrade defect images. By comparing the loss value, total number of identified regions, and recognition accuracy as metrics, the study compares four improved versions of the Faster R-CNN algorithm. The results indicate that the faster_rcnn_inception_v2 version is more suitable for the intelligent identification of non-destructive testing of urban road subgrade defects. [ABSTRACT FROM AUTHOR]

Cracks are the most typical faults of concrete structures, and their extension can lead to structural fracture. However, when cracks develop inside a structure, the most important depth information is invisible and difficult to measure. The tracer electromagnetic method is an effective technique for detecting the depth of concrete cracks, but since concrete is a multiphase stochastic composite material, its complex internal structure often interferes with the radar detection results, making the conventional radar interpretation technique difficult. In this study, the detection results for concrete crack depth detection based on the tracer electromagnetic method were comprehensively analyzed by combining the complex signal analysis technique, using transient information such as amplitude, phase, and frequency in order to improve the precision and accuracy of radar signal interpretation. In this study, a numerical model was established to determine whether typical cracks such as vertical cracks and diagonal cracks contain indicators or not, and the ground-penetrating radar forward simulation software was used to perform forward simulation of the numerical model and analyze the forward results. The complex signal analysis technique was used to obtain the response characteristics of typical cracks when they did and did not contain the indicator, and the complex signal was finally analyzed by combining it with the actual crack depth detection data. The results show that the tracer electromagnetic method can significantly improve the crack bottom's reflection ability for radar signals, and when the crack bottom contains an indicator, the amplitude of the reflected signal at the bottom of the crack is enhanced, the phase is reversed, and the frequency is reduced. The distribution of the crack morphology and the location of the crack bottom can be analyzed more conveniently by using the complex signal analysis technique. [ABSTRACT FROM AUTHOR]

In the absence of records of near-fault ground strains and rotations from strong earthquakes, deterministic physics-based simulations have become an important tool for characterizing these motions in the low-frequency range (e.g., < 1.0 Hz). Building on a previous study of near-fault ground strains and rotations from actual strike-slip ruptures conducted by the authors, this article investigates the spatial and temporal characteristics of such motions generated by actual earthquakes with predominantly dip-slip mechanisms. This is achieved by performing forward ground-motion simulations of the 1994 Mw 6.7 Northridge, the 1989 Mw 6.9 Loma Prieta, and the 1985 Mw 8.1 Michoacan earthquakes using previously published finite-fault rupture models. For each considered seismic event, time histories of ground strains and rotations are generated at near-fault recording stations and at a dense grid of observation points. This is accomplished by finite differencing translational motions simulated at very closely spaced stations using a kinematic modeling approach. The simulation results show large-amplitude axial strain, shear strain, and rocking in the near-fault region. For the considered earthquakes, the maximum peak ground strain over all grid points is of the order of ~ 100–250 μstrain, whereas the maximum peak ground rocking ranges from ~ 100 to ~ 200 μrad. The attenuation characteristics of peak ground strains and rotations differ for the considered seismic events and depend on the component of interest and the rupture distance. Finally, peak ground rocking can be reasonably estimated from peak vertical ground velocity using a properly selected scaling factor despite the significant variability of the latter in the near-fault region. Filtering out the very low frequencies of ground motion (< 0.1 Hz), including the static offset, significantly affects the scaling factor. [ABSTRACT FROM AUTHOR]

Emerging technologies such as genomic selection have been applied to modern plant and animal breeding to increase the speed and efficiency of variety release. However, breeding requires decisions regarding parent selection and mating pairs, which significantly impact the ultimate genetic gain of a breeding scheme. The selection of appropriate parents and mating pairs to increase genetic gain while maintaining genetic diversity is still an urgent need that breeders are facing. This study aimed to determine the best progeny allocation strategies by combining future-oriented simulations and numerical black-box optimization for an improved selection of parents and mating pairs. In this study, we focused on optimizing the allocation of progenies, and the breeding process was regarded as a black-box function whose input is a set of parameters related to the progeny allocation strategies and whose output is the ultimate genetic gain of breeding schemes. The allocation of progenies to each mating pair was parameterized according to a softmax function, whose input is a weighted sum of multiple features for the allocation, including expected genetic variance of progenies and selection criteria such as different types of breeding values, to balance genetic gains and genetic diversity optimally. The weighting parameters were then optimized by the black-box optimization algorithm called StoSOO via future-oriented breeding simulations. Simulation studies to evaluate the potential of our novel method revealed that the breeding strategy based on optimized weights attained almost 10% higher genetic gain than that with an equal allocation of progenies to all mating pairs within just four generations. Among the optimized strategies, those considering the expected genetic variance of progenies could maintain the genetic diversity throughout the breeding process, leading to a higher ultimate genetic gain than those without considering it. These results suggest that our novel method can significantly improve the speed and efficiency of variety development through optimized decisions regarding the selection of parents and mating pairs. In addition, by changing simulation settings, our future-oriented optimization framework for progeny allocation strategies can be easily implemented into general breeding schemes, contributing to accelerated plant and animal breeding with high efficiency. [ABSTRACT FROM AUTHOR]

During the coal mining process, the change in the floor stress state of coal seam will produce deformation and failure. The seam floor failure in different coal mining processes has a certain law. At present, the water disaster monitoring of coal seam floors based on the DC resistivity method mainly focuses on the resistivity response characteristics of floor deformation and damage. To investigate the temporal changes in the electrical properties of the coal seam floor during mining, this study employs the inter-hole DC perspective observation system and the time-lapse resistivity reflection coefficient method. Through numerical simulation and field tests, the study uncovers the temporal variation law of the resistivity of coal seam floor induced by mining activities. First, this paper compares the results of individual inversion and time-lapse resistivity change rates for a typical geoelectric model to validate the reliability of the inter-hole DC perspective time-lapse method. Next, considering the mining-induced damage to the coal seam floor, this paper analyzes the electrical response patterns and charac-teristics of the rise of confined water and the damage zone in the floor during the mining process. It also discusses the feasibility of using a time-lapse resistivity reflection coefficient to assess the depth of coal seam floor damage, offering a theoretical basis for field construction. Finally, , the on-site monitoring tests reveal the electrical change characteristics of coal seam floor during the coal mining process. The time-lapse resistivity reflection coefficient R is utilized to determine the damage depth of the rock layer of the working face floor, which is found to be 15 m. The study results demonstrate that the time-lapse characteristics of the resistivity of coal seam floor mining damage obtained by the inter-hole DC perspective method can mitigate the influence of formation factors and random noise in the monitoring data to a certain extent. Additionally, the time-lapse resistivity reflection coefficient can be utilized to determine the depth of coal seam floor failure. This method transforms the detection target from the single study of geological anomalies to the full life cycle dynamic monitoring of the floor damage of the working face in the process of coal mining and then realizes the detailed depiction of structural damage to the working surface floor.

Ground-penetrating radar (GPR) is a rapid and non-destructive geophysical technique widely employed to detect and quantify subsurface structures and characteristics. Its capability for time lapse (TL) detection provides essential insights into subsurface hydrological dynamics, including lateral flow and soil water distribution. However, during TL-GPR surveys, field conditions often create discrepancies in surface geometry, which introduces mismatches across sequential TL-GPR images. These discrepancies may generate spurious signal variations that impede the accurate interpretation of TL-GPR data when assessing subsurface hydrological processes. In responding to this issue, this study introduces a TL-GPR image alignment method by employing the dynamic time warping (DTW) algorithm. The purpose of the proposed method, namely TLIAM–DTW, is to correct for geometric mismatch in TL-GPR images collected from the identical survey line in the field. We validated the efficacy of the TLIAM–DTW method using both synthetic data from gprMax V3.0 simulations and actual field data collected from a hilly, forested area post-infiltration experiment. Analyses of the aligned TL-GPR images revealed that the TLIAM–DTW method effectively eliminates the influence of geometric mismatch while preserving the integrity of signal variations due to actual subsurface hydrological processes. Quantitative assessments of the proposed methods, measured by mean absolute error (MAE) and root mean square error (RMSE), showed significant improvements. After performing the TLIAM–DTW method, the MAE and RMSE between processed TL-GPR images and background images were reduced by 96% and 78%, respectively, in simple simulation scenarios; in more complex simulations, MAE declined by 27–31% and RMSE by 17–43%. Field data yielded reductions in MAE and RMSE of >82% and 69%, respectively. With these substantial improvements, the processed TL-GPR images successfully depict the spatial and temporal transitions associated with subsurface lateral flows, thereby enhancing the accuracy of monitoring subsurface hydrological processes under field conditions. [ABSTRACT FROM AUTHOR]

A dynamic game framework is developed to study market dynamics between two manufacturers/service providers competing on pricing and switching costs. In this game, a portion of consumers may choose to upgrade their products by repurchasing from one of the providers in each period. The switching cost is the one-time costs when consumers "switch" from one provider to another. Switching costs provide consumers an incentive to continue buying from the same firm even if its competitors offer functionally identical but incompatible products. In practice, the switching costs can be increased or decreased by firms through designing products. A mixed logit demand model, which can arbitrarily closely approximate any discrete choice behavior of consumers, is adopted to characterize the dynamic market evolution under stochastically varying consumer preferences. We find that switching costs are usually beneficial to the firm with a dominant market share. Moreover, large switching costs can be detrimental to the firm with a disadvantaged market share, so it wants to decrease switching costs. On the contrary, small switching costs have a negative effect on the demand of the firm with a weak market share but benefit its profit by leading a high price. We implement a simulation study to validate our theoretical results on market dynamics. [ABSTRACT FROM AUTHOR]

Copyright of Computer Measurement & Control is the property of Magazine Agency of Computer Measurement & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In mountainous landscapes, the diverse geotechnical conditions amplify landslide susceptibility. Factors such as precipitation and seismic activity can trigger landslides, while inherent hazards such as voids, fissures, and compaction deficits jeopardize long-term slope stability. Detecting and forecasting these susceptibilities accurately is crucial. In this paper, the time-domain finite- difference approach and the gprMax software are used to conduct forward modeling of landslide susceptibility. An electrical model of subsurface aqueous structures is created, including water-filled and air-filled cavities, fracture zones, and fault lines. The distinctive radar signal responses within these environments are examined, and a dataset of B-scan images associated with their electrical models is constructed. By employing deep learning algorithms and the robust nonlinear mapping ability of convolutional neural networks in the Pix2Pix generative adversarial network, we accelerate the intelligent inversion of the geological radar data on landslide susceptibility. This innovative approach effectively reconstructs hazard models, offering a reliable basis for interpretation of radar signals. [ABSTRACT FROM AUTHOR]

Cracks are the most typical faults of concrete structures, and their extension can lead to structural fracture. However, when cracks develop inside a structure, the most important depth information is invisible and difficult to measure. The tracer electromagnetic method is an effective technique for detecting the depth of concrete cracks, but since concrete is a multiphase stochastic composite material, its complex internal structure often interferes with the radar detection results, making the conventional radar interpretation technique difficult. In this study, the detection results for concrete crack depth detection based on the tracer electromagnetic method were comprehensively analyzed by combining the complex signal analysis technique, using transient information such as amplitude, phase, and frequency in order to improve the precision and accuracy of radar signal interpretation. In this study, a numerical model was established to determine whether typical cracks such as vertical cracks and diagonal cracks contain indicators or not, and the ground-penetrating radar forward simulation software was used to perform forward simulation of the numerical model and analyze the forward results. The complex signal analysis technique was used to obtain the response characteristics of typical cracks when they did and did not contain the indicator, and the complex signal was finally analyzed by combining it with the actual crack depth detection data. The results show that the tracer electromagnetic method can significantly improve the crack bottom’s reflection ability for radar signals, and when the crack bottom contains an indicator, the amplitude of the reflected signal at the bottom of the crack is enhanced, the phase is reversed, and the frequency is reduced. The distribution of the crack morphology and the location of the crack bottom can be analyzed more conveniently by using the complex signal analysis technique.

The zeroing neural network (ZNN) is an important kind of continuous-time recurrent neural network (RNN). Meanwhile, the existence of forward and backward simulations and bisimulations for weighted finite automata (WFA) over the field of real numbers has been widely investigated. Two types of quantitative simulations and two types of bisimulations between WFA are determined as solutions to particular systems of matrix and vector inequations over the field of real numbers R. The approach used in this research is unique and based on the application of a ZNN dynamical evolution in solving underlying matrix and vector inequations. This research is aimed at the development and analysis of four novel ZNN dynamical systems for addressing the systems of matrix and/or vector inequalities involved in simulations and bisimulations between WFA. The problem considered in this paper requires solving a system of two vector inequations and a couple of matrix inequations. Using positive slack matrices, required matrix and vector inequations are transformed into corresponding equations and then the derived system of matrix and vector equations is transformed into a system of linear equations utilizing vectorization and the Kronecker product. The solution to the ZNN dynamics is defined using the pseudoinverse solution of the generated linear system. A detailed convergence analysis of the proposed ZNN dynamics is presented. Numerical examples are performed under different initial state matrices. A comparison between the ZNN and linear programming (LP) approach is presented.

In mountainous landscapes, the diverse geotechnical conditions amplify landslide susceptibility. Factors such as precipitation and seismic activity can trigger landslides, while inherent hazards such as voids, fissures, and compaction deficits jeopardize long-term slope stability. Detecting and forecasting these susceptibilities accurately is crucial. In this paper, the time-domain finite-difference approach and the gprMax software are used to conduct forward modeling of landslide susceptibility. An electrical model of subsurface aqueous structures is created, including water-filled and air-filled cavities, fracture zones, and fault lines. The distinctive radar signal responses within these environments are examined, and a dataset of B-scan images associated with their electrical models is constructed. By employing deep learning algorithms and the robust nonlinear mapping ability of convolutional neural networks in the Pix2Pix generative adversarial network, we accelerate the intelligent inversion of the geological radar data on landslide susceptibility. This innovative approach effectively reconstructs hazard models, offering a reliable basis for interpretation of radar signals.

Accurate judgement of devoid damage information by 3D-Radar is an effective way of repairing damage in nondestructive pavements. In order to systematically analyse the characteristics of devoid damage under nondestructive pavements in 3D-Radar response. In this study, the 3D-Radar response to devoid damage of different sizes, locations and moisture contents was quantified by FDTD orthorectified simulations. Data acquisition of the pre-buried devoid damage on site was carried out using 3D-Radar, compared with the orthorectified simulation results and numerical analysis. The detection effect was also verified by relying on the project. The results show that the radar wave characteristics of the devoid damage are obvious. Different colour and waveform image characteristics in B-Scan in the presence and absence of water at the location; the size of the devoid also has an impact on the image characteristics. It depends on the footprints and size of the devoid. It creates "upward-convex", "down-concave" and straight features; the presence of the devoid characteristics in the 3D-Radar mapping will enhance the confidence of the devoid identification through field tests and engineering verification. [ABSTRACT FROM AUTHOR]

The seismic while driving technology is one of the most urgently needed geological guarantee technologies for the intelligent rapid driving development of roadways. Due to the large difference between the seismic while driving source and active sources such as explosives, conventional cognitive and data processing technologies have failed to achieve results. In view of the lack of cognitive of the source of seismic while driving and the lack of effective forward simulation methods for seismic while driving data, the research on the generation mechanism analysis and source time function construction of seismic while driving source were carried out. It is found that: the seismic while driving signal is a complex, variable frequency, continuous signal with a certain duration. Its relative low-frequency signal is mainly related to the mechanical rotation of the cutting head, the action of the gangue raking machine, the random coal falling, and the operation of the loader and belt conveyor, its high frequency and strong energy signals are determined by cutting coal, generally characterized by a pseudo random signal superimposed by multiple sources. Secondly, under the linear array data acquisition mode, the seismic while driving source can be approximated to a comprehensive virtual point source formed by the superposition of multiple sources that are continuously fired at different time delays. The seismic source is formed by the combined action of the vibration when the fully mechanized driving machine is cutting the coal seam and the coal body fracture, random coal falling, refuse raking, drilling, belt transportation, etc., in which the coal seam cutting plays a major role. Then, based on the analysis of source generation mechanism, the time function of the seismic while driving source is constructed, and the numerical model experiment of the seismic while driving is carried out with the time function as the source loading item. The simulated seismic while driving data obtained has the same time domain, frequency domain and time-frequency domain characteristics as the measured seismic while driving data, which show that the source time function constructed can effectively carry out forward modeling of seismic data while driving, and improve the cognition of the source while driving. In addition, in order to verify the effectiveness of the impulse algorithm based on spike deconvolution and cross-correlation in seismic while driving data processing, taking two common seismic interference technologies as comparison methods, effective signal extraction experiments were conducted using the simulation seismic while driving data. The experimental results show that: the impulse processing results based on spike deconvolution and cross-correlation are more similar to the wave field characteristics of seismic records obtained by using conventional Ricker wavelet simulation under the same simulation conditions, which verifies the effectiveness of the impulse algorithm. The research in this paper provides a basis for the further research and application of seismic while driving technology.

Seed banking (or dormancy) is a widespread bet‐hedging strategy, generating a form of population overlap, which decreases the magnitude of genetic drift. The methodological complexity of integrating this trait implies it is ignored when developing tools to detect selective sweeps. But, as dormancy lengthens the ancestral recombination graph (ARG), increasing times to fixation, it can change the genomic signatures of selection. To detect genes under positive selection in seed banking species it is important to (1) determine whether the efficacy of selection is affected, and (2) predict the patterns of nucleotide diversity at and around positively selected alleles. We present the first tree sequence‐based simulation program integrating a weak seed bank to examine the dynamics and genomic footprints of beneficial alleles in a finite population. We find that seed banking does not affect the probability of fixation and confirm expectations of increased times to fixation. We also confirm earlier findings that, for strong selection, the times to fixation are not scaled by the inbreeding effective population size in the presence of seed banks, but are shorter than would be expected. As seed banking increases the effective recombination rate, footprints of sweeps appear narrower around the selected sites and due to the scaling of the ARG are detectable for longer periods of time. The developed simulation tool can be used to predict the footprints of selection and draw statistical inference of past evolutionary events in plants, invertebrates, or fungi with seed banks. [ABSTRACT FROM AUTHOR]

Electromagnetic (EM) surveys play a significant role in mineral exploration. However, the EM method often faces limitations when investigating minerals in areas covered by rivers, lakes, or other water bodies. This paper introduces audio magnetotelluric (AMT) observation technology that utilizes separated electric and magnetic channels to deal with this challenge over water-covered areas. The study analyzes and discusses the characteristics of the relative error of the magnetic field through forward simulation. The observation and profile experiments were conducted at the estuary of a river in Liaoning Province, China, and high-quality data in the river and the pseudo-geoelectric section of the underwater space were successfully obtained. The results demonstrate the feasibility and effectiveness of the AMT observation technology over water-covered areas, emphasizing the importance of locating the magnetic channel in a quiet zone at a certain distance from the shore. This configuration helps reduce the influence of resistivity differences between water and shore, ultimately improving data quality and accuracy. The research suggests that the AMT observation technology, utilizing separated electric and magnetic channels, has the potential for further improvement and can serve as a valuable guide for mineral exploration over water-covered areas. [ABSTRACT FROM AUTHOR]

Predictions about the effect of natural selection on patterns of linked neutral variation are largely based on models involving the rapid fixation of unconditionally beneficial mutations. However, when phenotypes adapt to a new optimum trait value, the strength of selection on individual mutations decreases as the population adapts. Here, I use explicit forward simulations of a single trait with additive-effect mutations adapting to an "optimum shift." Detectable "hitchhiking" patterns are only apparent if (i) the optimum shifts are large with respect to equilibrium variation for the trait, (ii) mutation rates to large-effect mutations are low, and (iii) large-effect mutations rapidly increase in frequency and eventually reach fixation, which typically occurs after the population reaches the new optimum. For the parameters simulated here, partial sweeps do not appreciably affect patterns of linked variation, even when the mutations are strongly selected. The contribution of new mutations vs. standing variation to fixation depends on the mutation rate affecting trait values. Given the fixation of a strongly selected variant, patterns of hitchhiking are similar on average for the two classes of sweeps because sweeps from standing variation involving large-effect mutations are rare when the optimum shifts. The distribution of effect sizes of new mutations has little effect on the time to reach the new optimum, but reducing the mutational variance increases the magnitude of hitchhiking patterns. In general, populations reach the new optimum prior to the completion of any sweeps, and the times to fixation are longer for this model than for standard models of directional selection. The long fixation times are due to a combination of declining selection pressures during adaptation and the possibility of interference among weakly selected sites for traits with high mutation rates.

Controlled-source audio magnetotellurics, which is a common technology in geophysical surveys, typically uses the multichannel mode of data acquisition. Often, a capacitive coupling effect occurs among the multiple receiving wires and receiving electrodes and the earth. This effect causes the distortion of the observed apparent resistivity and phase curves. The capacitive coupling of the observation mode is simulated using an equivalent circuit model, and the characteristics of the influence of the length of the receiving wire and grounding resistance of the electrode on capacitive coupling are investigated via the forward simulation of several typical models. The capacitive decoupling of a device for controlled-source audio geomagnetic observation is studied and applied to process the measured data from the Hongtoushan mining area in Liaoning Province, China. This approach effectively weakens the capacitance coupling effect and improves observation quality, and the inversion results match well with known geological information. This study examines the capacitive decoupling technique and offers a scientific foundation for the standardization of the controlled-source audio geomagnetic data gathering technology. [ABSTRACT FROM AUTHOR]

Tight and unconventional reservoirs have become the focus with the progress of petroleum exploration and development. Micro-fractures in these reservoirs can effectively improve reservoir permeability, and well-developed micro-fractures can serve to directly improve productivity. Compared with the centered electrical well logging method, the Micro Spherical Focused Logging (MSFL) is more suitable for microfracture identification due to its high resolution and near borehole wall measuring method. In this study, an anisotropic model is used to depict micro-fractured formation. First, a forward model with microfractured formation, borehole, logging instrument and surrounding rock is established. Subsequently, MSFL responses under different micro-fracture porosity, resistivity, dip angle and borehole radius, are calculated based on the finite element method (FEM). Finally, the MSFL responses under different microfracture parameters are analyzed with the response laws clarified. [ABSTRACT FROM AUTHOR]

Copyright of Water Conservancy Science & Techonlogy & Economy is the property of Water Conservancy Science & Technology & Economy Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Groundwater environment is closely related to the protection and restoration of surface ecological environment, and the detection of groundwater resources is an important content to master the characteristics of groundwater environment. In the setting of the ecological restoration of Hongshaquan Open-pit Mining Area, four different geoelectric models are constructed on the basis of geological column and its resistivity logging curves obtained by a borehole. Based on one-dimensional forward theory, the transient electromagnetic induced voltage and its apparent resistivity response curves with a small coil device are obtained. Comparative analysis for these curves shows that induced voltage and its apparent resistivity under different aquifer geoelectric model conditions are sensitive to aquifer water-bearing response, and there are obvious differences between them in 0.01-50 ms, which reflects the feasibility of using small coil transient electromagnetic method to detect groundwater resources in the study area in theory. Combined with the field detection test data and drilling exposure, the effectiveness and reliability of small coil transient electromagnetic technology in the detection of groundwater resources are verified.

Taking the SaErTU and Putaohua oil layers in the L29 well area of LHP oilfield in the northern Songliao Basin as the research object, In response to the difficulty of interference between thin interbedded sand and mudstone and strong reflection between strata, which have a significant impact on fine prediction of sand bodies, a stratigraphic model is established based on the geological characteristics of the target layer to eliminate the impact of stratigraphic reflection; Then add a thin layer of sand body to its interior, establish a thin interlayer model, and obtain a geological model that is more in line with the actual situation of the target layer. Using forward simulation, analyze the seismic response characteristics of sand bodies, extract 30 seismic attributes from 4 categories: amplitude statistics, composite seismic trace statistics, sequence and frequency spectrum statistics, and calculate the correlation between cumulative sandstone thickness and seismic attributes, and select a sensitive seismic attribute set;By combining sedimentary and drilling data, the seismic attribute with the highest sensitivity to the target layer is selected. The multi-level dimensionality reduction and gradual improvement of seismic attribute selection methods using “model forward modeling, attribute analysis, relevant optimization, and drilling implementation” can effectively improve the prediction accuracy of thin interbedded sand bodies and greatly reduce the risk of oilfield exploration and development.

Copyright of Coal Science & Technology (0253-2336) is the property of Coal Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Experimental Technology & Management is the property of Experimental Technology & Management Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

While studies suggest that peer influence can in some cases encourage adolescent substance use, recent work demonstrates that peer influence may be on average protective for cigarette smoking, raising questions about whether this effect occurs for other substance use behaviors. Herein, we focus on adolescent drinking, which may follow different social dynamics than smoking. We use a data-calibrated Stochastic Actor-Based (SAB) Model of adolescent friendship tie choice and drinking behavior to explore the impact of manipulating the size of peer influence and selection effects on drinking in two school-based networks. We first fit a SAB Model to data on friendship tie choice and adolescent drinking behavior within two large schools (n = 2178 and n = 976) over three time points using data from the National Longitudinal Study of Adolescent to Adult Health. We then alter the size of the peer influence and selection parameters with all other effects fixed at their estimated values and simulate the social systems forward 1000 times under varying conditions. Whereas peer selection appears to contribute to drinking behavior similarity among adolescents, there is no evidence that it leads to higher levels of drinking at the school level. A stronger peer influence effect lowers the overall level of drinking in both schools. There are many similarities in the patterning of findings between this study of drinking and previous work on smoking, suggesting that peer influence and selection may function similarly with respect to these substances.

Based on the geological characteristics and the seismic wave propagation characteristics of the collapse column, a collapse column model is constructed. Considering the change of single factor variation and the acoustic equation used to simulate the effect of different receptor interval and shot interval on the collapse column. Interpretation of the collapsed column fracture boundary is carried out by using the reflected wave amplitude changes of the offset profile and combined with seismic attribute analysis and manual interpretation. The detection accuracy is judged by the average deviation of the horizontal resolution of the collapsed column as an index. And the interpretation error of the diameter of the collapsed column is analyzed by ray tracing method. The results show, that the small receptor spacing is beneficial to the exploration of the collapse column, and when the receptor interval is 5 meters and the shot interval is 40 meters, it is favorable to the exploration of the collapse column model.

The newly reported forward simulation method is used to extract concentration-dependent interdiffusion coefficient (D=F(C)) from experimental concentration profiles obtained under constant and time-varying surface concentration conditions, which is impossible by the standard analytical methods. Also, theoretical D=F(C) under constant and time-varying surface concentration conditions are computed in systems with diffusion-induced stress generation and relaxation. The experimental and theoretical results show that the long-held general assumption that D=F(C) is the same for constant surface concentration and time-varying surface concentration is not valid, and such assumption can cause model prediction errors in cases where a surface concentration changes with time. These include the use of D=F(C) computed by the standard analytical techniques, such as the Boltzmann-Matano, Sauer-Freise, Hall, and Wagner methods, for predicting diffusion during homogenization processes. [ABSTRACT FROM AUTHOR]

Non-aqueous reactive polymer grouting technology has been widely used in the repair engineering of dikes and dams with shallow diseases. By using the finite difference time-domain method and perfectly matched layer boundary conditions, the calculation model of dikes and dams with shallow diseases such as water-filled cave, air-filled cave and incompact area is established. The propagation process of electromagnetic waves of ground-penetrating radar in dikes and dams with shallow diseases using polymer grouting repair is simulated, and the forward simulation profiles and single-channel waveforms are obtained. The propagation characteristics such as waveform amplitude, waveform shape, transmission time, and reflection time are compared and analyzed. The results show that the forward simulation profiles of dikes and dams with water-filled caves before and after polymer grouting repair present two clusters of hyperbolas, but three clusters of hyperbolas with different amplitudes were observed at 50% repair. The amplitude of the hyperbola and the single-channel reflected waves before repair and 50% repair of the cave and incompact area are greater than those of 100% repair. The propagation characteristics of ground-penetrating radar can effectively explain the degree of polymer grouting repair for dikes and dams with shallow diseases, and provide a theoretical basis for using the ground-penetrating radar to evaluate the effect of polymer grouting technology to repair dikes and dams with shallow diseases. [ABSTRACT FROM AUTHOR]

The presence of coal in complex structures featuring sandstone reservoirs seriously hinders reservoir characterization and the identification of fluids in subsurface formations. Coal can strongly obscure the reflections from sandstone, easily leading to false bright spots during exploration; thus, reservoirs and their boundaries cannot be accurately described. Furthermore, sandstone layers intercalated with thin coal seams form complex composite reflections. Therefore, considering the complexity of coal-bearing reservoirs together with the geological evolution of coal and actual logging data, this study systematically analyses the seismic reflections of coal-bearing reservoirs. First, the seismic responses of various coal-bearing reservoir models are established by evaluating multiple well logs of the target layer. Then, by forward-simulating theoretical seismic data, seismic response models comprising different lithological combinations are established. Finally, seismic attributes (such as the amplitude, frequency and phase) of coal-bearing and non-coal-bearing strata are compared, and the seismic responses of typical lithological combinations of coal-bearing reservoirs are summarized. A single-well model test and a comparison between synthetic and seismic data confirm that numerical simulations can be used to forward model the seismic response characteristics of different sand–coal models, thereby eliminating the influences of coal and accurately characterizing sandstone reservoirs. [ABSTRACT FROM AUTHOR]

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Evolve and resequence (E&R) experiments, in which artificial selection is imposed on organisms in a controlled environment, are becoming an increasingly accessible tool for studying the genetic basis of adaptation. Previous work has assessed how different experimental design parameters affect the power to detect the quantitative trait loci (QTL) that underlie adaptive responses in such experiments, but so far there has been little exploration of how this power varies with the genetic architecture of the evolving traits. In this study, we use forward simulation to build a more realistic model of an E&R experiment in which a quantitative polygenic trait experiences a short, but strong, episode of truncation selection. We study the expected power for QTL detection in such an experiment and how this power is influenced by different aspects of trait architecture, including the number of QTL affecting the trait, their starting frequencies, effect sizes, clustering along a chromosome, dominance, and epistasis patterns. We show that all of these parameters can affect allele frequency dynamics at the QTL and linked loci in complex and often unintuitive ways, and thus influence our power to detect them. One consequence of this is that existing detection methods based on models of independent selective sweeps at individual QTL often have lower detection power than a simple measurement of allele frequency differences before and after selection. Our findings highlight the importance of taking trait architecture into account when designing and interpreting studies of molecular adaptation with temporal data. We provide a customizable modeling framework that will enable researchers to easily simulate E&R experiments with different trait architectures and parameters tuned to their specific study system, allowing for assessment of expected detection power and optimization of experimental design.

Genetic bottlenecks can reduce effective population sizes (Ne), increase the rate at which genetic variation is lost via drift, increase the frequency of deleterious mutations and thereby accentuate inbreeding risk and lower evolutionary potential. Here, we tested for the presence of a genetic bottleneck in the endangered Australian sea lion (Neophoca cinerea), estimated Ne and predicted future losses of genetic variation under a range of scenarios. We used 2238 genome‐wide neutral single‐nucleotide polymorphisms (SNPs) from 72 individuals sampled from colonies off the southern (SA) and western (WA) coastline of Australia. Coalescent analyses using approximate Bayesian computation (ABC) methods indicated that both the SA and WA populations have experienced a historical genetic bottleneck. Using LD‐based methods, we estimated contemporary Ne to be 160 (CI = 146–178) and 424 (CI = 397–458) for the WA and SA populations respectively. Modelled future population declines suggested that disease epidemics prompted the highest increases in inbreeding relative to fishery‐related mortalities and other modelled threats. Small effective sizes and relatively low genetic variation leave this species vulnerable, and these risks may be compounded if current population declines are not reversed. [ABSTRACT FROM AUTHOR]

Tractor-trailer vehicles, which are composed of a car-like tractor towing a passive trailer, have been widely deployed in the transportation industry, and trajectory planning is a critical step in enabling such a system to drive autonomously. Owing to the properties of being highly nonlinear and nonholonomic with complex dynamics, the tractor-trailer system poses great challenges to the development of motion-planning algorithms. In this study, an indirect trajectory planning framework for a tractor-trailer vehicle under on-road driving is presented to deal with the problem that the traditional planning framework cannot consider the feasibility and quality simultaneously in real-time trajectory generation of the tractor-trailer vehicle. The indirect planning framework can easily handle complicated tractor-trailer dynamics and generate high-quality, obstacle-free trajectory using quintic polynomial spline, speed profile optimization, forward simulation, and properly designed cost functions. Simulations under different driving scenarios and trajectories with different driving requirements are conducted to validate the performance of the proposed framework. [ABSTRACT FROM AUTHOR]

Abstract In this study, we investigate the source rupture process of the 2018 Hokkaido Eastern Iburi earthquake in Japan (M JMA 6.7) and how the ground motion can be reproduced using available source and velocity models. First, we conduct a multiple-time-window kinematic waveform inversion using strong motion waveforms, which indicates that a large slip area located at a depth of 25–30 km in the up-dip direction from the hypocenter was caused by a rupture propagating upward 6–12 s after its initiation. Moreover, the high-seismicity area of aftershocks did not overlap with the large-slip area. Subsequently, using the obtained source model and a three-dimensional velocity structure model, we conduct a forward long-period (

Abstract In this study, we investigate the source rupture process of the 2018 Hokkaido Eastern Iburi earthquake in Japan (M JMA 6.7) and how the ground motion can be reproduced using available source and velocity models. First, we conduct a multiple-time-window kinematic waveform inversion using strong-motion waveforms, which indicates that a large-slip area located at a depth of 25–30 km in the up-dip direction from the hypocenter was caused by a rupture propagating upward 6–12 s after its initiation. Moreover, the high-seismicity area of aftershocks did not overlap with the large-slip area. Subsequently, using the obtained source model and a three-dimensional velocity structure model, we conduct a forward long-period (

Purpose: Blood flow is known to add variability to hepatic radiofrequency ablation (RFA) treatment outcomes. However, few studies exist on its impact on temperature‐controlled RFA. Hence, we investigate large‐scale blood flow effects on temperature‐controlled RFA in flow channel experiments and numerical simulations. Methods: Ablation zones were induced in tissue‐mimicking, thermochromic phantoms with a single flow channel, using an RF generator with temperature‐controlled power delivery and a monopolar needle electrode. Channels were generated by molding the phantom around a removable rod. Channel radius and saline flow rate were varied to study the impact of flow on (i) the ablated cross‐sectional area, (ii) the delivered generator power, and (iii) the occurrence of directional effects on the thermal lesion. Finite volume simulations reproducing the experimental geometry, flow conditions, and generator power input were conducted and compared to the experimental ablation outcomes. Results: Vessels of different channel radii r affected the ablation outcome in different ways. For r=0.275 mm, the ablated area decreased with increasing flow rate while the energy input was hardly affected. For r=0.9 mm and r=2.3 mm, the energy input increased toward larger flow rates; for these radii, the ablated area decreased and increased toward larger flow rates, respectively, while still being reduced overall as compared to the reference experiment without flow. Directional effects, that is, local shrinking of the lesion upstream of the needle and an extension thereof downstream, were observed only for the smallest radius. The simulations qualitatively confirmed these observations. As compared to performing the simulations without flow, including flow effects in the simulations reduced the mean absolute error between experimental and simulated ablated areas from 0.23 to 0.12. Conclusion: While the temperature control mechanism did not detect the heat sink effect in the case of the smallest channel radius, it counteracted the heat sink effect in the case of the larger channel radii with an increased energy input; this explains the increase in ablated area toward high flow rates (for r=2.3 mm). The experiments in a simple phantom setup, thus, contribute to a good understanding of the phenomenon and are suitable for model validation. [ABSTRACT FROM AUTHOR]

Specific to the full-range detection demand for the magnetic anomaly targets such as metal in shallow strata, transportation pipelines, and mined-out regions during the geophysical survey, based on the transient electromagnetic method, using the Gauss inverse Laplace transform, a magnetic excitation model for metal targets in medium-shallow strata is proposed. By using the adjustment of the electrical parameters such as frequency, amplitude, and phase of the excitation current, a spatial multimode magnetic excitation field is formed, an array magnetic excitation detection device is developed, and a distribution model for the array magnetic excitation field is established. The hardware-in-the-loop simulation results show that the frequency and amplitude of the excitation signal are directly proportional to the spectral amplitude and the induced amplitude of the secondary field of the signal, where the signal has the most spectral components when selecting a frequency of 25 Hz. The duty cycle of the excitation signal is of nonlinear correlation to the magnitude of the signal frequency spectrum. When the duty cycle is 50%, the signal spectral components are the least and concentrated in the part with lower frequency, and when the duty cycle is lower or higher than 50%, the spectral components increase and spread to the middle and high frequencies. The indoor test results indicate that changing the excitation signal parameters can also increase the detection range and depth to a certain extent without changing the sensor parameters. It can also reduce the detection blind area to a certain extent. Therefore, the conclusion of this article can solve the problem of large detection blind areas in transient electromagnetic detection, and the application field can also be extended from deep mineral detection to new areas, such as medium and shallow unexploded bombs, metal pipelines, and goafs. [ABSTRACT FROM AUTHOR]

Genetic differentiation plays an essential role in the assessment of metapopulation systems of conservation concern. Migration rates affect the degree of genetic differentiation between subpopulations, with increasing genetic differentiation leading to increasing extinction risk. Analyses of genetic differentiation repeated over time together with projections into the future are therefore important to inform conservation. We investigated genetic differentiation in a closed metapopulation system of an obligate forest grouse, the Western capercaillie Tetrao urogallus, by comparing microsatellite population structure between a historic and a recent time period. We found an increase in genetic differentiation over a period of approximately 15 years. Making use of forward simulations accounting for population dynamics and genetics from both time periods, we explored future genetic differentiation by implementing scenarios of differing migration rates. Using migration rates derived from the recent dataset, simulations predicted further increase of genetic differentiation by 2050. We then examined effects of two realistic yet hypothetical migration scenarios on genetic differentiation. While isolation of a subpopulation led to overall increased genetic differentiation, the re-establishment of connectivity between two subpopulations maintained genetic differentiation at recent levels. Our results emphasize the importance of maintaining connectivity between subpopulations in order to prevent further genetic differentiation and loss of genetic variation. The simulation set-up we developed is highly adaptable and will aid researchers and conservationists alike in anticipating consequences of conservation strategies for metapopulation systems. [ABSTRACT FROM AUTHOR]

Simulations are an essential tool in all areas of population genetic research, used in tasks such as the validation of theoretical analysis and the study of complex evolutionary models. Forward-in-time simulations are especially flexible, allowing for various types of natural selection, complex genetic architectures, and non-Wright-Fisher dynamics. However, their intense computational requirements can be prohibitive to simulating large populations and genomes. A popular method to alleviate this burden is to scale down the population size by some scaling factor while scaling up the mutation rate, selection coefficients, and recombination rate by the same factor. However, this rescaling approach may in some cases bias simulation results. To investigate the manner and degree to which rescaling impacts simulation outcomes, we carried out simulations with different demographic histories and distributions of fitness effects using several values of the rescaling factor, Q , and compared the deviation of key outcomes (fixation times, allele frequencies, linkage disequilibrium, and the fraction of mutations that fix during the simulation) between the scaled and unscaled simulations. Our results indicate that scaling introduces substantial biases to each of these measured outcomes, even at small values of Q . Moreover, the nature of these effects depends on the evolutionary model and scaling factor being examined. While increasing the scaling factor tends to increase the observed biases, this relationship is not always straightforward, thus it may be difficult to know the impact of scaling on simulation outcomes a priori . However, it appears that for most models, only a small number of replicates was needed to accurately quantify the bias produced by rescaling for a given Q . In summary, while rescaling forward-in-time simulations may be necessary in many cases, researchers should be aware of the rescaling procedure's impact on simulation outcomes and consider investigating its magnitude in smaller scale simulations of the desired model(s) before selecting an appropriate value of Q .