Search

As one of the most complex systems known to science, modeling brain behavior and function is both fascinating and extremely difficult. Empirical data is increasingly available from ex vivo human brain organoids and surgical samples, as well as in vivo animal models, so the problem of modeling the behavior of large-scale neuronal systems is more relevant than ever. The statistical physics concept of a mean-field model offers a tractable way to bridge the gap between single-neuron and population-level descriptions of neuronal activity, by modeling the behavior of a single representative neuron and extending this to the population. However, existing neural mean-field methods typically either take the limit of small interaction sizes, or are applicable only to the specific neuron models for which they were derived. This paper derives a mean-field model by fitting a transfer function called Refractory SoftPlus, which is simple yet applicable to a broad variety of neuron types. The transfer function is fitted numerically to simulated spike time data, and is entirely agnostic to the underlying neuronal dynamics. The resulting mean-field model predicts the response of a network of randomly connected neurons to a time-varying external stimulus with a high degree of accuracy. Furthermore, it enables an accurate approximate bifurcation analysis as a function of the level of recurrent input. This model does not assume large presynaptic rates or small postsynaptic potential size, allowing mean-field models to be developed even for populations with large interaction terms.

Defining the required trackability level of the target condition for the testing facility reconditioning unit represents an unresolved challenge in improving the reproducibility of load-based tests and corresponding performance rating standards development. To enhance the reproducibility of such testing methodology, this paper presents and discusses a new feed-forward compensation technique based on the development of a transfer function model for the delay and offset characteristics of the psychrometric room's air temperature and humidity modulations with reference to the target signal from the room emulator. It is demonstrated that the proposed methodology enables offset and delay reduction in the trackability of the return air condition within 60 s at different testing conditions, enhances the reproducibility of the test results to limit performance deviations to within 2 %, and achieves closely matched controlled parameter modulations during load-based tests. [ABSTRACT FROM AUTHOR]

Mathematical modeling and numerical simulation have a considerable presence in the vast universe of engineering disciplines, given their usefulness in explaining, comprehending, and simulating phenomena and processes with which engineers are in contact in their daily creative and problem‐solving work. For this reason, engineering study programs have at least one course dedicated to dealing with the mathematical modeling of dynamic systems as an essential complement to subsequent courses such as automatic control, structural dynamics, and mechanical vibrations. Nowadays, many technological tools illustrate the applications of mathematical modeling interactively through experiments that offer an incomparable motivation to the students to corroborate with real‐world examples, the utility and veracity of the theory presented to them in the classroom and that in many occasions seems lacking utility and direct relation with the world in which they develop. Based on those mentioned above, this paper presents an example of applying the Laplace transform in modeling physical systems, using a second‐order circuit attached to an Arduino Due board in conjunction with the Jupyter Notebook environment. The numerical and experimental results can be obtained through three optional kernels: Python, Octave, or MATLAB®. For educational purposes, the resulting computer application was presented to undergraduate students of Mechatronics Engineering as an illustrative complement to two courses entitled Signals and Systems Analysis, part of the second semester, and Mathematical Modeling, part of the fifth semester. [ABSTRACT FROM AUTHOR]

Deepwater subsea wellhead system is subjected to the various cyclic loads transmitted from the drilling riser due to ocean waves, currents and platform motion during drilling operation; therefore, the fatigue damage is accumulated. A fatigue damage assessment methodology and its detailed analysis procedure for subsea wellheads utilising transfer function theory based on monitoring acceleration data at the drilling riser are developed. Studies on an actual monitoring case for a subsea wellhead under drilling operation with 336 h of monitoring events are conducted and a verification method by comparison of the measured fatigue results and predicted fatigue results based on wave and current data are introduced. The results for wave and vortex-induced vibration (VIV) fatigue life based on measured acceleration data are calculated, and the fatigue bias with predicted results are summarised. The developed fatigue damage assessment method and monitoring case studies can be valuable references for deepwater drilling engineering. [ABSTRACT FROM AUTHOR]

In response to improve the quality and level of hydrostatic transmission (HST) products for modern mobile machineries, the closed-loop transfer functions of a HST are established by mathematical modeling, a comprehensive testing equipment is developed employing a proportional relief valve for automatic program loading and fuzzy-PID oil temperature control, the testing equipment is capable of conducting various performance tests for various models of HST integrated pump-motor products, including factory and type tests, especially continuous impact and endurance performance tests under high temperature and high-speed conditions. Comprehensive performance test of the above test sample is carried out using the developed equipment, that the test results agree well with the previous simulation results verifies the correctness of the established theoretical analysis model. The obtained theory and equipment from this work provide theoretical and experimental technical support for improving design and development of high-end fluid components for modern mobile machinery HST. [ABSTRACT FROM AUTHOR]

During the fault period, a phase angle jump may occur at the stator or the point of common coupling, which will deteriorate the low-voltage ride-through (LVRT) characteristics of a doubly fed induction generator (DFIG). The existing LVRT studies focus on the impact of a voltage drop on DFIGs but often ignore that of a phase angle jump. The time-domain simulation is accurate in describing the response of a DFIG during the LVRT process, but it is time-consuming for a DFIG with the full-order model. In this paper, by using the voltage magnitude and phase angle of the stator or the point of common coupling as the inputs, and the state variables as the outputs, the transfer function of a DFIG is derived to analyze its response and find the LVRT measures against the voltage drop and, especially, the phase angle jump. Firstly, the differential-algebraic equations of the DFIG are linearized to propose their transfer function model. Secondly, considering its high-order characteristic, a model reduction method for the transfer function of the DFIG using the Schur decomposition is proposed, and the analytical expression of the output variables of the DFIG with the phase angle jump is derived by the inverse Laplace transformation to judge the necessity of the LVRT measures. Finally, the simulation results of the DFIG are provided to verify the accuracy of the transfer function model and its reduced-order form and validate the feasibility of the LVRT against the phase angle jump with the proposed models. [ABSTRACT FROM AUTHOR]

This work presents an unprecedented resolution for the lack of harmony between wired network TCP, which transacts with stationary routers, and the Ad-hoc, which appoints mobile hosts as routers, causing failure. This is done by modifying the TCP's queue via fuzzy logic as a controller (FLC). The novelty is that when the mobile router changes location, leading to failure, the controller keeps tracking error signals, which become a behavior prediction base for the next error before occurring. The transfer function is designed with respect to the I/O parameters to optimize the system, leading to the steady with free of fluctuation and overshoot. Other than previous techniques, which depend on fixed criteria or proactive strategies such as AQM, the proposed system is distinguished by dynamic adaptation with continuous changes like mobility and signal power. Using FLC, the system response is improved by reducing time delay, packet loss, and enhancing stability and spectral efficiency. A simulation is designed to continuously monitor these parameters' results, represented by the metrics rise time, undershoot, overshoot, and steady time. For comparison purposes, the PID controller is applied, and the results show surpassing this system where the metrics rise time, undershoot, overshoot, and steady time values are for FLC 0.55, 0.017, 0, and 2.5, respectively, with fluctuation-free, while for PID 0.6, 0.526, 9.341, and 3.6533, respectively, with fluctuation. Furthermore, by dealing the FLC with the challenges of high mobility and the signal power changes, it exceeds the traditional PID controller, as the simulation results show that in terms of reducing the delay time by 28.6%, packet loss by 50%. Besides, there is a remarkable increase in the throughput by 20% and spectral efficiency by 16.7%. [ABSTRACT FROM AUTHOR]

The continuous enhancement of optimization algorithms and their parameters has spurred the expansion of AI into novel application domains such as image recognition and smart home technology. This paper employs the system response curve (SRC) to the adaptive learning rate optimizer, addressing challenges associated with the establishment of the optimizer control model and parameter adjustments affecting the dynamic performance of the system. These insights offer theoretical support for the optimizer's application in deep learning models. To begin, the adaptive learning rate optimizer is a time‐varying system. Based on the intrinsic relationship between the network optimization and the control system, the time domain expression and approximate transfer function of the adaptive learning rate optimizer are derived, and the system dynamic model is established. Furthermore, based on the system control model of the optimizer, it is proposed to explain the performance impacts of different optimizers and their hyperparameters on the deep learning model through the SRC. Finally, experiments are performed on the MNIST, CIFAR‐10, UTKinect‐Action3D, and Florence3D‐Action datasets to validate the control theory of explaining optimizers through system response curves. The experimental results show that the recognition performance of the Adaptive Moment Estimate (Adam) is better than that of the Adaptive Gradient (AdaGrad) and Root Mean Square Propagation (RMSprop). Additionally, the learning rate affects the model training speed, and the practical application aligns with the theoretical analysis. [ABSTRACT FROM AUTHOR]

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) 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.)

This proposed work investigates the performance of dc voltage of a three-phase Active Front-End (AFE) Sinusoidal Pulse Width Modulated (SPWM) rectifier during load switching. To obtain desired performances, a transfer function is derived in synchronous reference frame (dq), from which the gain of the PI controllers are estimated and observed the performance accordingly. In this research, the load current is feed-forwarded with d-axis current by a suitable choice of gain factor, which results a fractional feedback d-axis current control and improves the transient behaviour simultaneously. This will unalter the other performance parameters of the system such as, UPF operation, less Total Harmonic Distortion (THD) of input current, dc voltage boost etc. All the simulation results exhibits satisfactory performance and validated with a prototype developed using STM32F303RE microcontroller accordingly. [ABSTRACT FROM AUTHOR]

Unwanted signals in electrical systems frequently overpower the desired signal. In an attempt to increase the ratio, the desired signals are amplified proportionately to the undesired ones. Frequency selective circuits, often known as filters, can be used to separate desired signals from undesirable ones as signals can be identified by their frequency characteristics. Analog filters are available in both active and passive varieties, each having unique properties. A first order band pass active filter is developed and characterized in this study. The Operational Amplifier (OP AMP 741) is the active element in this case. With the Band Width (BW), Cut-off Frequencies (FL and FH), Center Frequency (FC), and Quality factor (Q) provided, the Transfer Function (TF) equation is generated and defined. [ABSTRACT FROM AUTHOR]

The current planting of economically important timber species, such as Douglas-fir, mainly relies on genetically improved seeds from seed orchards. However, published research on the effects of climate change has largely focused on natural populations. To bridge this gap, data from 80 cooperative second-cycle coastal Douglas-fir progeny tests across eight breeding zones in western Washington and Oregon were analyzed. Climate transfer functions for age-12 growth were derived, showing significant results for the US Pacific Northwest. Region-specific transfer functions (Coast, Inland, and Cascade) displayed stronger correlations. Mean annual temperature and mean coldest month temperature were the most important climatic variables explaining growth. The study found that populations from slightly warmer areas tended to grow better but moving populations from colder to warmer areas by 2 °C (analogous to projected global warming) would result in an 8% genetic loss in age-12 height and a 25% genetic loss in age-12 volume. However, substantial diversity in climatic response was found among full-sib families within large breeding zones, suggesting that breeding and selecting suitable families for future climatic conditions within breeding zones is feasible. The study discusses potential strategies to adapt current breeding programs to address the impacts of future climate change while maintaining high population growth rates in Douglas-fir breeding programs. [ABSTRACT FROM AUTHOR]

Introduction: Central aortic pressure waveform analyses can provide clinically relevant information beyond conventional brachial blood pressure (BP) assessment. This waveform can be reproduced noninvasively through application of a generalized transfer function (GTF) on a peripheral waveform, as conventionally performed by applanation tonometry. Photoplethysmography (PPG) is an alternate approach; however, differences in measurement site and modality demand the use of a transfer function (TF) specific for those differences. This study aimed to compare central aortic waveform features generated from radial tonometry (reference) using a proprietary GTF with a central aortic waveform and its features generated from a simultaneous fingertip PPG measurement using a selective method where one of three different TFs is chosen based on the input signal harmonic profile. Methods: Brachial BP was measured in triplicate under resting conditions and was used for subsequent calibration. Multiple simultaneous radial tonometry (SphygmoCor CVMS) and fingertip PPG measurements were then performed in individual participants (n = 21, 10 females, age: 39 ± 16 years). Measurements were converted into central aortic waveforms with their respective TFs. Twenty central aortic pressure waveform parameters were compared through correlation analysis, Bland-Altman plots, and a repeated measure mixed-effects ANOVA model. Central aortic waveform shape was compared using the root-mean-squared error (RMSE). Results: Correlation (r) of PPG-derived parameters with radially tonometry-derived central aortic parameters was high ranging from 0.79 to 0.99. Mean differences of pressure-related parameters were within 1.3 mm Hg, and differences of time-related parameters ranged from −2.2 to 3.4%. While some parameters were statistically different, these differences are not physiologically meaningful. Central aortic waveform shape had an average RMSE of 1.8 ± 0.9%. Conclusion: Fingertip PPG-derived central aortic waveform parameters using a novel selective TF were comparable to central aortic waveform features derived from radial tonometry using a previously validated GTF.

Abstract The article introduces an innovative approach to global optimization and feature selection (FS) using the RIME algorithm, inspired by RIME-ice formation. The RIME algorithm employs a soft-RIME search strategy and a hard-RIME puncture mechanism, along with an improved positive greedy selection mechanism, to resist getting trapped in local optima and enhance its overall search capabilities. The article also introduces Binary modified RIME (mRIME), a binary adaptation of the RIME algorithm to address the unique challenges posed by FS problems, which typically involve binary search spaces. Four different types of transfer functions (TFs) were selected for FS issues, and their efficacy was investigated for global optimization using CEC2011 and CEC2017 and FS tasks related to disease diagnosis. The results of the proposed mRIME were tested on ten reliable optimization algorithms. The advanced RIME architecture demonstrated superior performance in global optimization and FS tasks, providing an effective solution to complex optimization problems in various domains.

The work is devoted to the helicopter turboshaft engines' gas generator rotor R.P.M. neuro-fuzzy controller development, which improves control accuracy and increases the system's stability to external disturbances and adaptability to changing operating conditions. Methods have been developed, including improvements to the automatic control system structural diagram which made it possible to obtain the system transfer function in the bandpass filter transfer function form. The work also improved the fuzzy rules base and the neuron activation function mathematical model, which significantly accelerated the neuro-fuzzy controller training process. The transfer function frequency and time characteristics analysis showed that the system effectively controlled the engine and reduced vibration. Methods for ensuring a guaranteed stability margin and the synthesis of an adaptive filter were studied, which made it possible to achieve the system's high stability and reliability. The results showed that the developed controller provided high stability with amplitude and phase margins, effectively compensating for changes in external conditions. Experimental studies have demonstrated that the control quality improved by 2.31–2.42 times compared to previous neuro-fuzzy controllers and by 5.13–5.65 times compared to classic PID controllers. Control errors were reduced by 1.84–2.0 times and 5.28–5.97 times, respectively, confirming the developed neuro-fuzzy controller's high efficiency and adaptability. [ABSTRACT FROM AUTHOR]

Summary: Large‐scale linear time‐invariant (LTI) dynamical systems are widely used to characterize complicated physical phenomena. Glover developed the Hankel norm approximation (HNA) algorithm for optimally reducing the system in the Hankel norm, and we study its numerical issues. We provide a remedy for the numerical instabilities of Glover's HNA algorithm caused by clustered singular values. We analyze the effect of our modification on the degree and the Hankel error of the reduced system. Moreover, we propose a two‐stage framework to reduce the order of a large‐scale LTI system given samples of its transfer function for a target degree k$$ k $$ of the reduced system. It combines the adaptive Antoulas–Anderson (AAA) algorithm, modified to produce an intermediate LTI system in a numerically stable way, and the modified HNA algorithm. A carefully computed rational approximation of an adaptively chosen degree d$$ d $$ gives us an algorithm for reducing an LTI system, which achieves a balance between speed and accuracy. [ABSTRACT FROM AUTHOR]

Owing to the significant differences in environmental characteristics and explanatory factors among estuarine and coastal regions, research on diatom transfer functions and database establishment remains incomplete. This study analysed diatoms in surface sediment samples and a sediment core from the Lianjiang coast of the East China Sea, together with environmental variables. Principal component analysis of the environmental variables showed that sea surface salinity (SSS) and sea surface temperature were the most important factors controlling hydrological conditions in the Lianjiang coastal area, whereas canonical correspondence analysis indicated that SSS and pH were the main environmental factors affecting diatom distribution. Based on the modern diatom species-environmental variable database, we developed a diatom-based SSS transfer function to quantitatively reconstruct the variability in SSS between 1984 and 2021 for sediment core HK3 from the Lianjiang coastal area. The agreement between the reconstructed SSS and instrument SSS data from 1984 to 2021 suggests that diatom-based SSS reconstruction is reliable for studying past SSS variability in the Lianjiang coastal area. Three low SSS events in AD 2019, 2013, and 1999, together with an increased relative concentration of freshwater diatom species and coarser sediment grain sizes, corresponded to two super-typhoon events and a catastrophic flooding event in Lianjiang County. Thus, a diatom-based SSS transfer function for reconstructing past SSS variability in the estuarine and coastal areas of the East China Sea can be further used to reflect the paleoenvironmental events in this region. [ABSTRACT FROM AUTHOR]

Feature Selection (FS) is a key pre-processing step in pattern recognition and data mining tasks, which can effectively avoid the impact of irrelevant and redundant features on the performance of classification models. In recent years, meta-heuristic algorithms have been widely used in FS problems, so a Hybrid Binary Chaotic Salp Swarm Dung Beetle Optimization (HBCSSDBO) algorithm is proposed in this paper to improve the effect of FS. In this hybrid algorithm, the original continuous optimization algorithm is converted into binary form by the S-type transfer function and applied to the FS problem. By combining the K nearest neighbor (KNN) classifier, the comparative experiments for FS are carried out between the proposed method and four advanced meta-heuristic algorithms on 16 UCI (University of California, Irvine) datasets. Seven evaluation metrics such as average adaptation, average prediction accuracy, and average running time are chosen to judge and compare the algorithms. The selected dataset is also discussed by categorizing it into three dimensions: high, medium, and low dimensions. Experimental results show that the HBCSSDBO feature selection method has the ability to obtain a good subset of features while maintaining high classification accuracy, shows better optimization performance. In addition, the results of statistical tests confirm the significant validity of the method. [ABSTRACT FROM AUTHOR]

This study presents the electrical modeling and characteristic analyses of energy storage systems (ESSs) based on the internal impedance characteristics of batteries to improve ESS stability. Frequencies ranging from 1 kHz to 0.1 Hz were injected into lithium-ion batteries, and the variation of the internal impedance of the batteries was obtained based on the reflected wave to determine the ESS state of charge (SoC) and temperature. The changes in the basic electrochemical impedance spectroscopy characteristics of the ESSs were observed. Specifically, the voltage, temperature, and SoC of an ESS that could be employed as a renewable ESS were analyzed. The impedance characteristics of the ESS were investigated via experimentation and simulation. The ESS comprised an electrically equivalent circuit of a series inductor ( L S ), series resistor ( R S ), parallel resistor ( R P ), and parallel capacitor ( C P ), as well as a MATLAB program based on its transfer function to generate energy. Furthermore, a method was developed for analyzing the frequency response of ESSs. The feasibility of the proposed electrical modeling was examined for a 58.4 V, 75 Ah, 4.4 kWh ESS. [ABSTRACT FROM AUTHOR]

Vibration is an indispensable part of the tactile perception, which is encoded to oscillatory synaptic currents by receptors and transferred to neurons in the brain. The A2 and B1 neurons in the drosophila brain postsynaptic to the vibration receptors exhibit selective preferences for oscillatory synaptic currents with different frequencies, which is caused by the specific voltage-gated Na+ and K+ currents that both oppose the variations in membrane potential. To understand the peculiar role of the Na+ and K+ currents in shaping the filtering property of A2 and B1 neurons, we develop a linearized modeling framework that allows to systematically change the activation properties of these ionic channels. A data-driven conductance-based biophysical model is used to reproduce the frequency filtering of oscillatory synaptic inputs. Then, this data-driven model is linearized at the resting potential and its frequency response is calculated based on the transfer function, which is described by the magnitude–frequency curve. When we regulate the activation properties of the Na+ and K+ channels by changing the biophysical parameters, the dominant pole of the transfer function is found to be highly correlated with the fluctuation of the active current, which represents the strength of suppression of slow voltage variation. Meanwhile, the dominant pole also shapes the magnitude–frequency curve and further qualitatively determines the filtering property of the model. The transfer function provides a parsimonious description of how the biophysical parameters in Na+ and K+ channels change the inhibition of slow variations in membrane potential by Na+ and K+ currents, and further illustrates the relationship between the filtering properties and the activation properties of Na+ and K+ channels. This computational framework with the data-driven conductance-based biophysical model and its linearized model contributes to understanding the transmission and filtering of vibration stimulus in the tactile system. [ABSTRACT FROM AUTHOR]

The analytical method for the synthesis of a generator of a random process with a given spectrum in the form of a linear system of Itô's equations is proposed. The stationarity of a random process is assumed, the spectral and corresponding transfer functions of which are defined in the form of rational fractions. The coefficients of the system of Itô's equations of the generator are found from recurrent algebraic relations. The method is focused on working with mathematical models of nature random processes, such as the Dryden's wind model. The transformation of the spectra of the wind gust model in three directions is presented in detail and the corresponding stochastic equations are given. [ABSTRACT FROM AUTHOR]

We study L-system realizations generated by the original Weyl–Titchmarsh functions m α (z) . In the case when the minimal symmetric Schrödinger operator is non-negative, we describe Schrödinger L-systems that realize inverse Stieltjes functions (- m α (z)) . This approach allows to derive a necessary and sufficient conditions for the functions (- m α (z)) to be inverse Stieltjes. In particular, the criteria when (- m ∞ (z)) is an inverse Stieltjes function is provided. Moreover, it is shown that the knowledge of the value m ∞ (- 0) and parameter α allows us to describe the geometric structure of the L-system realizing (- m α (z)) . Additionally, we present the conditions in terms of the parameter α when the main and associated operators of a realizing (- m α (z)) L-system have the same or different angle of sectoriality which sets connections with the Kato problem on sectorial extensions of sectorial forms. An example that illustrates the obtained results is presented in the end of the paper. [ABSTRACT FROM AUTHOR]

Ground observation of precipitation is fundamental in preparing and evaluating various precipitation datasets, which are essential for running hydrologic and climatologic models. The undercatch of traditional precipitation gauges leads to significant uncertainty in ground observation, which is particularly severe in the central Qinghai–Tibet Plateau (QTP). To evaluate the undercatch biases, intercomparison experiments between Geonor T‐200B, the Chinese standard precipitation gauge (CSPG), and OTT Parsivel2 disdrometer were conducted at Tanggula (TGL) and Wudaoliang (WDL) sites. The adjustment schemes for 30‐min and daily precipitation were proposed and applied to 30‐min precipitation at TGL over 10 years and the monthly precipitation of the national meteorological stations on the QTP over 37 years. The results indicated that after adjustment the annual precipitation increased by 49.09% at TGL and 16.41% over the QTP. Snow took up 9.91% of the annual precipitation over the QTP, while it took up over 60% at TGL. Because of the high snow proportion, the central QTP had lower catch ratio and higher adjustment ratio than the QTP average. From 1981 to 2017, the central QTP presented a wetter trend, and the annual precipitation increased by 3.15 mm/yr, higher than the QTP average. Moreover, in the central QTP, precipitation increased more in wet than dry seasons, which were 2.45 and 0.83 mm/yr, respectively. While on the entire QTP, the dry season precipitation increased slightly more than the wet season, which were 0.67 and 0.50 mm/yr, respectively. On the QTP, adjustment amount presented an increasing trend from the northwest to the southeast, whereas annual adjustment ratio was the opposite. This study could enhance the knowledge of precipitation characteristics over the QTP, especially in the central region. More effort will be given to the calibration and uncertainty evaluation of the proposed schemes in future work. [ABSTRACT FROM AUTHOR]

Optimized viscous dampers mitigate the dynamic response of building with plan asymmetry. Previous research efforts limit the optimization method to time domain requiring time history analyses to optimize damper placement for plan eccentricity-induced torsional response combined with translational response. This can consume high computational effort and lead to the variability in the ground motion selection. To expedite the optimization process while taking ground motion variability into account, this study will offer a novel criterion based on stochastic performance. This technique will skip the traditional approach of employing time history analyses and will take frequency domain variability into account. Through given distance between the center of mass (CM) and the target frame, the study establishes the stochastic criterion for the response at the perimeter of the building where the maximum torsional-translational response occurs. This allows the optimization methods to generate high quality solution with less computational efforts compared to traditional approach (i.e. time domain-based optimization). It is noteworthy that the proposed criterion is applicable to extensive kinds of responses (e.g. peak floor acceleration, story shear and etc.) once the geometric relationship is given. The proposed criterion as the objective function is compared against their counterpart in time domain through a case study. The case study is based on a reinforced concrete (RC) moment-resisting-frame (MRF) building with two-way asymmetric plan and adopts Element Exchange Method (EEM) to optimize the damper placement. The effectiveness of optimized design based in frequency domain and time domain is evaluated for their total running time and maximum peak interstory drift against a suite of ground motions. The result showed that the proposed criterion can offer the improvement against the traditional approach in terms of solution quality (i.e. performance in time domain and frequency domain) and computational efforts (i.e. total running time for optimization). [ABSTRACT FROM AUTHOR]

The article introduces an innovative approach to global optimization and feature selection (FS) using the RIME algorithm, inspired by RIME-ice formation. The RIME algorithm employs a soft-RIME search strategy and a hard-RIME puncture mechanism, along with an improved positive greedy selection mechanism, to resist getting trapped in local optima and enhance its overall search capabilities. The article also introduces Binary modified RIME (mRIME), a binary adaptation of the RIME algorithm to address the unique challenges posed by FS problems, which typically involve binary search spaces. Four different types of transfer functions (TFs) were selected for FS issues, and their efficacy was investigated for global optimization using CEC2011 and CEC2017 and FS tasks related to disease diagnosis. The results of the proposed mRIME were tested on ten reliable optimization algorithms. The advanced RIME architecture demonstrated superior performance in global optimization and FS tasks, providing an effective solution to complex optimization problems in various domains. [ABSTRACT FROM AUTHOR]

High-dimensional datasets often harbor redundant, irrelevant, and noisy features that detrimentally impact classification algorithm performance. Feature selection (FS) aims to mitigate this issue by identifying and retaining only the most pertinent features, thus reducing dataset dimensions. In this study, we propose an FS approach based on black hole algorithms (BHOs) augmented with a mutation technique termed MBHO. BHO typically comprises two primary phases. During the exploration phase, a set of stars is iteratively modified based on existing solutions, with the best star selected as the "black hole". In the exploration phase, stars nearing the event horizon are replaced, preventing the algorithm from being trapped in local optima. To address the potential randomness-induced challenges, we introduce inversion mutation. Moreover, we enhance a widely used objective function for wrapper feature selection by integrating two new terms based on the correlation among selected features and between features and classification labels. Additionally, we employ a transfer function, the V2 transfer function, to convert continuous values into discrete ones, thereby enhancing the search process. Our approach undergoes rigorous evaluation experiments using fourteen benchmark datasets, and it is compared favorably against Binary Cuckoo Search (BCS), Mutual Information Maximization (MIM), Joint Mutual Information (JMI), and minimum Redundancy Maximum Eelevance (mRMR), approaches. The results demonstrate the efficacy of our proposed model in selecting superior features that enhance classifier performance metrics. Thus, MBHO is presented as a viable alternative to the existing state-of-the-art approaches. We make our implementation source code available for community use and further development. [ABSTRACT FROM AUTHOR]

According to standards, the harmonic content should be less than 5% at the time of calibration, while the calibration index proposed in this paper stipulates that the primary current amplitude of 1%~120% of the full range of the accuracy level reaches 0.05 S level. In view of the above problems and indexes, this paper adopts the active regulation technology of primary current; firstly, the harmonics of primary current are extracted, and then the opposite harmonic currents are injected by the penetrating wire to offset the harmonics, and finally, charged calibration is carried out. The inductive current transformer charged calibration device was first designed, and the particle swarm algorithm was used to optimize the offset performance of the key link of the background current offset suppression. The transfer function of the offset loop was derived, and it was theoretically analyzed that it can meet the offset requirements up to the 200th harmonic. The results show that the optimized calibration method can realize the full-range calibration of low-voltage inductive current transformers under charged conditions by making a prototype of the device and constructing a test circuit for experiments, and measuring the data and analyzing them. [ABSTRACT FROM AUTHOR]

In this article, we formulate and solve the representation problem for diffusion equations: giving a discretization of the Laplace transform of a diffusion equation under a space discretization over a space scale determined by an increment h > 0 , can we construct a continuous in h family of Cauer ladder networks whose constitutive equations match for all h > 0 the discretization. It is proved that for a finite differences discretization over a uniform geometric space scale, the representation problem over fractal Cauer networks is possible if and only if the coefficients of the diffusion are exponential functions in the space variable. Such diffusion equations admit a (Laplace) transfer function with a fractional behavior whose exponent is explicit. This allows us to justify previous works made by Sabatier and co-workers in [15-16] and Oustaloup and co-workers [14]. [ABSTRACT FROM AUTHOR]

In this paper, we study large classes of nonlinear systems that admit a transfer function completely described by their input-output behavior. Our objective is to identify and analyze the aforementioned classes, which exhibit unique characteristics related to separable systems. We aim to fit certain examples of automata/dynamical systems with new concepts. We observe that for a Discrete System or Automaton, the state set forms a group. Furthermore, there exists a natural near-ring for Separable Systems. Some substructures of this near-ring are generated by id. and a map from state set Q to itself if the state set Q is an abelian structure. It is interesting to note that Separable Systems themselves form a nearring with respect to parallel and series connections. We discuss certain results and provide examples to validate separable systems and the outcomes. This paper offers a theoretical and practical overview of dynamical systems in our daily lives. [ABSTRACT FROM AUTHOR]

Extended projects usually undergo different motions at their supports located at varying soil property conditions when an earthquake occurs. A theoretical framework including the key transfer function is proposed for simulating multi-support seismic underground motions in media-transition sites. First, a multi-layer media-transition site is illustrated. Then, the transfer function is theoretically derived and given explicitly using seismic wave propagation theory and fulfilling rigorously continuous boundary conditions. The obtained transfer function is the critical factor to calculate the underground Auto-Power Spectral Density (A-PSD). Meanwhile, the derivation and illustration of the other key factor (i.e. underground coherency function) is also given and the essential effect caused by media transition is further disclosed. The underground Cross-Power Spectral Density (C-PSD) is obtained by combining the underground coherency function with the transfer function. The underground Power Spectral Density Matrix (PSDM) is finally assembled by combining the A-PSD with C-PSD. Subsequently, multi-support seismic motions at varying depths of the media-transition site are generated, and its accuracy is further validated. Additionally, a numerical study is conducted to demonstrate the effect of water and soil phase on transfer functions and the underground seismic motions among dual-phase and media-transition sites. Results show the difference of seismic underground motions in two sites is obvious. This paper can provide a specific and feasible methodology for generating the multi-support seismic underground motions. [ABSTRACT FROM AUTHOR]

Transcranial alternating current stimulation (tACS) is widely used in studying brain functions and the treatment of neuropsychiatric diseases in a frequency-specific manner. However, how tACS works on neuronal activity has been poorly understood. In this paper, we use linear system analysis to investigate how weak alternating electric fields (EFs) affect the membrane polarization of neurons in the frequency domain. Two biophysically realistic conductance-based two-compartment models of cortical pyramidal neurons are developed to simulate subthreshold membrane polarization with weak alternating EFs. We linearize the original nonlinear models at the stable equilibrium points and further simplify them to the two- or three-dimensional linear systems. Thus, we calculate the transfer functions of the low-dimensional linear models to model neuronal polarization patterns. Based on the transfer functions, we compute the amplitude- and phase-frequency characteristics to describe the relationship between weak EFs and membrane polarization. We also computed the parameters (gain, zeros, and poles) and structures (the number of zeros and poles) of transfer functions to reveal how neuronal intrinsic properties affect the parameters and structure of transfer functions and thus the frequency-dependent membrane polarization with alternating EFs. We find that the amplitude and phase of membrane polarization both strongly depended on EF frequency, and these frequency responses are modulated by the intrinsic properties of neurons. The compartment geometry, internal coupling conductance, and ionic currents (except Ih) affect the frequency-dependent polarization by mainly changing the gain and pole of transfer functions. Larger gain contributes to larger amplitude-frequency characteristics. The closer the pole is to the imaginary axis, the lower phase-frequency characteristics. However, Ih changes the structure of transfer function in the dendrite by introducing a new pair of zero-pole points, which decrease the amplitude at low frequencies and thus lead to a visible resonance. These results highlight the effects of passive properties and active ion currents on subthreshold membrane polarization with alternating EFs in the frequency domain, which provide an explainable connection of how intrinsic properties of neurons modulate the neuronal input–output functions with weak EF stimulation. [ABSTRACT FROM AUTHOR]

The Three Parallel Rivers of Yunnan Protected Area (TPRYPA) is in the core area of the Hengduan Mountains, characterized by paralleling alternately high mountains and canyons that led to significant vertical temperature variation. Developing a climate transfer function for this region is crucial for both biodiversity protection and enhancing our understanding of feedback mechanisms between low-latitude and high-altitude areas in the context of global climate change. We investigated the chrysophycean stomatocyst assemblages from surface sediments of 46 high mountain lakes (altitude: 3244 to 5043 m) in the TPRYPA to assess the suitability of cysts in prediction of climate variability in high mountains. A total of 194 morphotypes were identified. Gradient forest (GF) model identified that altitude is the key environmental gradient with relation to cyst assemblages and cyst assemblages changed the composition substantially at altitude of 3200 and 4400 m, respectively. Cyst-based inference model for altitude using weighted-averaging method resulted in cross-validated jack-knifed-R2 of 0.60. The cyst-altitude transfer functions suggest that chrysophycean stomatocysts have a great potential as a powerful tool for climate reconstructions in alpine regions of the Hengduan Mountains.

Control of large structures often involves the use of hydraulic equipment due to the large power requirements. In this study, a large telescope is taken as an example of a large structure. A large telescope is equipped with hydraulic support systems to adjust the deformation of the structure, as changes in its pointing direction and ambient temperature deform the structure and reduce the telescope's observational performance. In previous studies, hydraulic support system elements and piping paths have been discussed, but quantitative evaluations and design considerations for the overall system performance of multiple hydraulic support systems and telescope structures have not been discussed. In this paper, simple transfer function models are derived for a coupled system of multiple hydraulic support systems and telescope structures, which allow the static and dynamic transient response characteristics to be evaluated. A design example using these transfer function models is also proposed and it is shown that the selected design parameters enable the large telescope to meet the specifications.

The fluctuations in groundwater levels (GWLs) in the Beijing Plain area are profoundly affected by precipitation (Pre) and groundwater (GW) overexploitation, altering regional water cycle processes and constraining regional economic and ecological development. The South-to-North Water Diversion Project (SWDP) has altered water supply structure in Beijing, leading to a new pattern in GWL fluctuations. This study quantitatively analyzes the evolution patterns of shallow GWLs and quantifies the response relationship between Pre-driven GWL-response on spatial and temporal scales before and after the SWDP. Using GWL and Pre data from 2000 to 2021, employs the coefficient of variation to analyze interannual variability, identifies variation points using the Pettitt and sliding T-test combined with correlation coefficient-based method for the classification of jump degree (R_Jump degree), subsequently divides the sub-sequences. The hydrological trend variation classification method based on correlation coefficient (R_Trend) is used to quantify the spatiotemporal evolution patterns of GWLs in each sub-sequence, and cross-correlation analysis is utilized to examine the time-lag characteristics of GWL responses to Pre in each sub-sequence. The results indicate: (1) GWLs exhibited jump variations in 2015 and 2017, with variation degrees mainly of moderate and strong, and correlation coefficients ranging from 0.18 to 0.67; (2) The overall trend of GWLs shifted from a significant decline to a substantial rebound before and after the SWDP. However, GWLs in the toe of the alluvial fan continued to show a decreasing trend until 2017; (3) The time lag between Pre and GWLs shortened by 6–10 months before and after the SWDP, with the toe of the alluvial fan showing a longer lag time due to over-exploitation. The Pre-GWL lag pattern mainly depends on GW extraction. Compared to existing methods, this paper proposes a research framework for systematically and comprehensively quantifying the evolution of GWLs and their response patterns to Pre, clearly revealing the natural-artificial water cycle processes in the Beijing Plain, providing scientific basis for ecological conservation and water resource management.