Negligible Error Research Articles

Novel machine learning investigation for Buongiorno fluidic model with Sutterby nanomaterial

The nanomaterials are frequently employed in a variety of heat transfer applications arising in energy generation, engine cooling, extrusion procedures, heat exchanger, thermos-chemical systems, manufacturing structures, powered plants etc. Experts and researchers in these fields often encounter such materials, leading to discernible impacts on velocity, temperature and concentration profiles. The objective of this study is to represent the mathematical structures for Sutterby nanomaterial fluidic model involving porous medium BFM-SNM using nonlinear autoregressive exogeneous networks backpropagated with Levenberg-Marquardt technique (NARX-LMT). The mathematical design of the model is originally presented by PDEs, which are converted into ODEs system through suitable modifications with alternative transformation incorporating numbers, i.e., Deborah, Prandtl and Reynold, as well as parameters, i.e., magnetic thermophoresis, radiation and temperature. The synthetic data is produced numerically by simulating Adams numerical method for BFM-SNM and the supervised computing paradigm of NARX-LMT is applied to the obtained datasets, and the results of NARX-LMT consistently align with numerical observations for each variant of the presented model, exhibiting negligible errors. The NARX-LMT performance on exhaustive experimentation is effectively illustrated through iterative convergence curves on mean squared error, control metrics of the optimization, distribution of error on histograms and regression outputs for Sutterby nanomaterial fluidic model.

Electrochemical chiral sensor developed using nanofibrous polyaniline chiral Structures: Detection and differentiation of D- and L-tryptophan

In this work, a simple strategy for electrochemical detection and differentiation of D- and L- forms of tryptophan is demonstrated using nanofibrous structures of chiral polyaniline (CP). Basically, CP with desired chirality is prepared using a chiral acid namely, ± camphor sulfonic acid (±CSA) in presence of either a cationic (or) anionic surfactant (CTAB / SDS) through a simple oxidative polymerization process. Structure, morphology and phase purity of the resultant CP materials are characterized by field emission scanning electron microscopy, Fourier transform infrared spectroscopy, Raman spectroscopy and X-ray diffraction studies. Moreover, the chiral properties of these conducting polymers are evaluated using circular dichroism (CD) spectroscopic studies. From these analyses it is found that CP exhibited twisted nanofibrous morphology and possesses the chirality whereas the non-chiral polyaniline (PANI), prepared in the absence of chiral acid, displayed the formation of a simple fibrous structures without any twists or chirality. Interestingly, such CP materials are found to be electrochemically selective for the detection and differentiation of D- and L- forms of tryptophan (Trp). Among the different chiral materials, CP-CT(−) prepared using CTAB displayed a much better sensing characteristics with higher IL/ID ratio, wider concentration range of detection and lower detection limit of 0.98 µM for l-Trp and 1.2 µM for d-Trp respectively. On the other hand, non-chiral PANI does not display any sensing behavior towards the differentiation of amino acid, Trp. Further, chronoamperometric studies reveal the selectivity of this chiral sensor for the detection of Trp among the other potentially interfering analytes. Although the difference in the measured peak current value is smaller, a significant difference of 70 mV peak potential is observed for the differentiation of L- and d-Trp. Moreover, the proposed CP-based sensing platform exhibits excellent stability and reproducibility with statistically negligible error values suggesting the potential use of the developed material towards electrochemical chiral detection and differentiation of amino acid, Trp.

Multiphysics modeling of 3D traction force microscopy with application to cancer cell-induced degradation of the extracellular matrix

Abstract3D Traction Force Microscopy (3DTFM) constitutes a powerful methodology that enables the computation of realistic forces exerted by cells on the surrounding extracellular matrix (ECM). The ECM is characterized by its highly dynamic structure, which is constantly remodeled in order to regulate most basic cellular functions and processes. Certain pathological processes, such as cancer and metastasis, alter the way the ECM is remodeled. In particular, cancer cells are able to invade its surrounding tissue by the secretion of metalloproteinases that degrade the extracellular matrix to move and migrate towards different tissues, inducing ECM heterogeneity. Typically, 3DTFM studies neglect such heterogeneity and assume homogeneous ECM properties, which can lead to inaccuracies in traction reconstruction. Some studies have implemented ECM degradation models into 3DTFM, but the associated degradation maps are defined in an ad hoc manner. In this paper, we present a novel multiphysics approach to 3DTFM with evolving mechanical properties of the ECM. Our modeling considers a system of partial differential equations based on the mechanisms of activation of diffusive metalloproteinase MMP2 by membrane-bound metalloproteinase MT1-MMP. The obtained ECM density maps in an ECM-mimicking hydrogel are then used to compute the heterogeneous mechanical properties of the hydrogel through a multiscale approach. We perform forward and inverse TFM simulations both accounting for and omitting degradation, and results are compared to ground truth reference solutions in which degradation is considered. The main conclusions resulting from the study are: (i) the inverse methodology yields results that are significantly more accurate than those provided by the forward methodology; (ii) ignoring ECM degradation results in a considerable overestimation of tractions and non negligible errors in all analyzed cases.

A Segmentation-based Automated Calculation of Patient Size and Size-specific Dose Estimates in Pediatric Computed Tomography Scans.

Size-specific dose estimates (SSDE) have been introduced into computed tomography (CT) dosimetry to tailor patients' unique sizes to facilitate accurate CT radiation dose quantification and optimization. The purpose of this study was to develop and validate an automated algorithm for the determination of patient size (effective diameter) and SSDE. A MATLAB platform was used to develop software of algorithms based on image segmentation techniques to automate the calculation of patient size and SSDE. The algorithm was used to automatically estimate the individual size and SSDE of four CT dose index phantoms and 80 CT images of pediatric patients comprising head, thorax, and abdomen scans. For validation, the American Association of Physicists in Medicine (AAPM) manual methods were used to determine the patient's size and SSDE for the same subjects. The accuracy of the proposed algorithm in size and SSDE calculation was evaluated for agreement with the AAPM's estimations (manual) using Bland-Altman's agreement and Pearson's correlation coefficient. The normalized error, system bias, and limits of agreement (LOA) between methods were derived. The results demonstrated good agreement and accuracy between the automated and AAPM's patient size estimations with an error rate of 1.9% and 0.27% on the patient and phantoms study, respectively. A 1% percentage difference was found between the automated and manual (AAPM) SSDE estimates. A strong degree of correlation was seen with a narrow LOA between methods for clinical study (r > 0.9771) and phantom study (r > 0.9999). The proposed automated algorithm provides an accurate estimation of patient size and SSDE with negligible error after validation.

Estimation of the lateral mis-registrations of the GRAVITY+ adaptive optics system

Context. The GRAVITY+ upgrade implies a complete renewal of its adaptive optics (AO) systems. Its complex design, featuring moving components between the deformable mirrors and the wavefront sensors, requires the monitoring and auto-calibrating of the lateral mis-registrations of the system while in operation. Aims. For preset and target acquisition, large lateral registration errors must be assessed in open loop to bring the system to a state where the AO loop closes. In closed loop, these errors must be monitored and corrected, without impacting the science. Methods. With respect to the first requirement, our method is perturbative, with two-dimensional modes intentionally applied to the system and correlated to a reference interaction matrix. For the second requirement, we applied a non-perturbative approach that searches for specific patterns in temporal correlations in the closed loop telemetry. This signal is produced by the noise propagation through the AO loop. Results. Our methods were validated through simulations and on the GRAVITY+ development bench. The first method robustly estimates the lateral mis-registrations, in a single fit and with a sub-subaperture resolution while in an open loop. The second method is not absolute, but it does successfully bring the system towards a negligible mis-registration error, with a limited turbulence bias. Both methods proved to robustly work on a system still under development and not fully characterised. Conclusions. Tested with Shack-Hartmann wavefront sensors, the proposed methods are versatile and easily adaptable to other AO instruments, such as the pyramid, which stands as a baseline for all future AO systems. The non-perturbative method, not relying on an interaction matrix model and being sparse in the Fourier domain, is particularly suitable to the next generation of AO systems for extremely large telescopes that will present an unprecedented level of complexity and numbers of actuators.

의료사고에 있어 과실범의 양형판단과 특수성

Many people receive treatment at the hospital to cure the disease. However, medical accidents that have been damaged by doctors' negligence or hospital errors often occur. It is not an exaggeration to say that the victim is suffering damage in various directions as the burden of proof is left to the victim (patient) for the damage caused by such a medical accident. In addition, our criminal law is so-called 'justifiable act (Article 20), so even if the result is not good, it is considered to be a reason for illegal sculpture. However, if it does not fall under the grounds for illegal sculpture, punishment is made according to the law of the negligent offender. Negligence offenders are weaker in illegality than intentional offenders, and the Korean Criminal Law also requires that negligence offenders be punished only when there are separate provisions (Article 14). If a constituent requirement result occurs due to medical negligence, the legal principles of negligence offenders may be applied, and as mentioned, negligence offenders are subject to punishment only when there are separate constituent requirements, so the criteria for punishment are not clear. Accordingly, it seems necessary to set the criteria for determining sentencing. In Japan, many discussions began to take place on the sentencing of medical accidents at medical institutions and academic societies in the wake of the Fukushima Prefectural Ono Hospital case regarding criminal responsibility for medical accidents. In this situation, many precedents related to medical accidents have been accumulated in Japan. Regarding the liability of negligent offenders, it is necessary to review the aspect of negligence, the duty of care, and the contents of negligence, and in relation to sentencing, it is necessary to review what factors are necessary for determining sentencing. However, in the case of medical accidents, they are considered negligent offenders, and the criteria for determining sentencing have not been clearly established, so it seems necessary to review them. Therefore, this paper examined similar accident cases among medical accident cases in both countries so that they can be compared. As a result, common factors to be taken into account were found along with the situation of medical accidents, and this confirmed that there was a tendency to be different from sentencing judgments in other negligence crimes, especially general occupational negligence and injury crimes. Most medical accidents were sentenced to probation except for fines, and imprisonment or higher was extremely rare. In addition, with regard to the imposition of punishment, Korea and Japan seem to have strong preventive and educational aspects as a function of punishment rather than the imposition of retributive sentences. In this paper, we reviewed the criteria for sentencing judgment based on medical accident cases in Korea and Japan, and based on this, we hope that it will be of great help in discussing sentencing in future medical accident related cases.

A novel approach to the FPIBSC strategy for an electric power steering system

The electric power steering system is used to improve comfort and steering feel for the user. In this article, we propose to use an integrated nonlinear control strategy for the electric steering system, which is described based on a complicated dynamic model. This work provides two new contributions. First, this control algorithm combines backstepping and proportional–integral (PI) techniques with parameters adjusted by a fuzzy algorithm, so it is called Fuzzy proportional–integral backstepping control (FPIBSC). The output of the PI algorithm is the input of the backstepping technique, while system stability is evaluated based on the Lyapunov function with virtual control variables. Second, road reaction torque is calculated based on a spatial dynamic model, which considers the influence of many other factors. Numerical simulation methods are used to evaluate the performance of the system. According to research findings, the value of the steering motor angle (controlled object) continuously tracks the desired value with negligible error. Under some specific conditions, the error between signals can be reduced to zero. In addition, other outputs that are obtained from the FPIBSC algorithm also tend to follow the reference signal with high accuracy. The phase difference phenomenon only occurs when using the conventional backstepping algorithm instead of FPIBSC. The assisted torque increases as speed decreases or the driver torque increases. In general, the system’s stability is always guaranteed under many different simulation conditions.

Merits and Demerits of Machine Learning of Ferroelectric, Flexoelectric, and Electrolytic Properties of Ceramic Materials.

In the present review, the merits and demerits of machine learning (ML) in materials science are discussed, compared with first principles calculations (PDE (partial differential equations) model) and physical or phenomenological ODE (ordinary differential equations) model calculations. ML is basically a fitting procedure of pre-existing (experimental) data as a function of various factors called descriptors. If excellent descriptors can be selected and the training data contain negligible error, the predictive power of a ML model is relatively high. However, it is currently very difficult for a ML model to predict experimental results beyond the parameter space of the training experimental data. For example, it is pointed out that all-dislocation-ceramics, which could be a new type of solid electrolyte filled with appropriate dislocations for high ionic conductivity without dendrite formation, could not be predicted by ML. The merits and demerits of first principles calculations and physical or phenomenological ODE model calculations are also discussed with some examples of the flexoelectric effect, dielectric constant, and ionic conductivity in solid electrolytes.

Quasi-degenerate extension of local N-electron valence state perturbation theory with pair-natural orbital method based on localized virtual molecular orbitals.

Chemical phenomena involving near-degenerate electronic states, such as conical intersections or avoided crossing, can be properly described using quasi-degenerate perturbation theory. This study proposed a highly scalable quasi-degenerate second-order N-electron valence state perturbation theory (QD-NEVPT2) using the local pair-natural orbital (PNO) method. Our recent study showed an efficient implementation of the PNO-based state-specific NEVPT2 method using orthonormal localized virtual molecular orbitals (LVMOs) as an intermediate local basis. This study derived the state-coupling (or off-diagonal) terms to implement QD-NEVPT2 in an alternative manner to enhance efficiency based on the internally contracted basis and PNO overlap matrices between different references. To facilitate further acceleration, a local resolution-of-the-identity (RI) three-index integral generation algorithm was developed using LMOs and LVMOs. Although the NEVPT2 theory is considered to be less susceptible to the intruder-state problem (ISP), this study revealed that it can easily suffer from ISP when calculating high-lying excited states. We ameliorated this instability using the imaginary level shift technique. The PNO-QD-NEVPT2 calculations were performed on small organic molecules for the 30 lowest-lying states, as well as photoisomerization involving the conical intersection of 1,1-dimethyldibenzo[b,f] silepin with a cis-stilbene skeleton. These calculations revealed that the PNO-QD-NEVPT2 method yielded negligible errors compared to the canonical QD-NEVPT2 results. Furthermore, we tested its applicability to a large photoisomerization system using the green fluorescent protein model and the ten-state calculation of the large transition metal complex, showcasing that off-diagonal elements can be evaluated at a relatively low cost.

Comparative study of a high‐speed permanent magnet motor when powered by different methods

AbstractThe authors present the multi‐physical field performances comparative research for a 30 kW, 30,000 r/min high‐speed permanent magnet motor (HSPMM) when the motor is powered by the sinusoidal pulse width modulation (SPWM) voltage inverter and sinusoidal voltage source, respectively. Firstly, electromagnetic performances including torque, voltage and current of the HSPMM with different driving methods are compared and analysed by the finite element method (FEM). Considering the effects of high operation frequency, power losses of the HSPMM with different driving methods under full‐load conditions are calculated and compared with the skin effect and the proximity effect considered for HSPMM winding copper loss estimation. Based on the above analysis, a prototype driven by the SPWM voltage inverter is manufactured, with its electromagnetic and thermal performances tested and verified. In addition, several influencing factors of the HSPMM rotor eddy current loss are studied, with their effects on the HSPMM under different driving methods further analysed and compared as well. A novel equivalent power supply method is proposed to effectively save the calculation time with a negligible error. Finally, in order to further improve the heat dissipation capacity of the HSPMM, a novel cooling method is intensively studied with its influencing factors further analysed. The cooling effect of the novel cooling method and the temperature of the motor components are verified and calculated by the computational fluid dynamics (CFD) method.

Predicting scale deposition in oil reservoirs using machine learning optimization algorithms

Scale deposition, a form of formation damage, not only affects the reservoir but also damages the well and equipment. This phenomenon occurs due to changes in temperature, pressure, and the injection of incompatible salt water, leading to ionic reactions. This study investigated permeability reduction due to scale deposition and examined how parameters such as temperature, pressure drop, and ion concentration affect the prediction accuracy. The scale deposits investigated in this study include CaSO4, BaSO4, and SrSO4. This paper uses Python to employ different machine-learning algorithms to predict the results. Each machine learning model has certain hyper-parameters that need adjustment. Failure to do so will result in reduced accuracy and incomplete interpretation of input data. The accuracy of the support vector regression (SVR) algorithm was significantly affected by the variation of the epsilon parameter in the dataset used. Therefore, before hyperparameter optimization, SVR had the lowest accuracy at 0.575. After adjusting the hyper-parameters, our findings show that SVR had the highest increase in R-squared value, which was 0.900, and the most minor growth in KNN, which went from 0.995 to 0.996. Additionally, the highest accuracy value for K-Nearest Neighbor is 0.996. Furthermore, most errors were related to SVR and XGBoost algorithms, while the most negligible errors were for the Decision Tree and KNN algorithms.

Ironic processes of concentration and suppression under pressure: A study on rifle shooting in Norwegian elite biathletes.

This study examined how priming attentional and negative cues affected participants' shooting performances toward ironic error targets under cognitive load conditions in Stroop task across two experiments. Semi-elite biathletes (Experiment 1, n = 10; Experiment 2, n = 9) participated in the study. The study used a within-subject quasi-experimental design, particularly a one-way repeated measures multivariate analysis of variance and a 2 × 2 fully repeated measures analysis of variance, to determine the participants' hit rates and shooting response times (RTs). In both experiments, the participants completed the reverse-Stroop-based target shooting performance under low- and high-cognitive load conditions while receiving frequent priming attentional and negative cues. The findings from Experiment 1 suggest that regulating repetitive priming attentional thoughts is efficacious in mitigating the likelihood of ironic performance errors and interference effects. The results of Experiment 2 show that repetitive priming negative cues resulted in negligible ironic error hit rates and slower RTs in target hits under high-cognitive load conditions. The Bayesian analyses provided evidence supporting the null hypotheses. Trying to control repetitive priming attentional and negative thoughts reduces ironic performance errors to a similar degree under cognitive load conditions among biathletes, regardless of interference effects. Further research is needed to determine the effectiveness of suppressing task-relevant negative instructions in reducing the likelihood of ironic performance errors under pressure.

The structure of cross-ventilation flow in an isolated cylindrical building: Numerical study

Cross-ventilation serves as an efficient means to expel pollutants and heat from buildings, requiring no energy consumption due to variations in wind pressure. The structure of the cross-ventilation flow significantly influences ventilation effectiveness. However, limited attention has been given to understanding the impact of a building's cross-section on the structure of cross-ventilation flow. This study aims to fill this gap by numerically investigating the cross-ventilation flow structure in an isolated cylindrical building. The numerical simulation results are validated against reported experimental data, indicating a negligible simulation error of 0.8 % in the volume ventilation rate. This attests to the accuracy of the numerical method in predicting cross-ventilation flow in isolated buildings. As airflow traverses the cylindrical building along the curved side walls, pressure loss diminishes, facilitating increased air inflow. This results in a more horizontal entry of the incoming jet compared to that in a square building. Analysis of Root-Mean-Square streamwise-velocity and turbulence kinetic energy reveals greater airflow fluctuation outdoors for the square building and increased turbulence indoors for the cylindrical building. Notably, the volume ventilation rate of the cylindrical building demonstrates an 8.3 % improvement. Furthermore, the air exchange rate in the cylindrical building surpasses that of the square building by 1.38 times.

A stochastic scale conjugate neural network procedure for the SIRC epidemic delay differential system

In this study, a stochastic computing structure is provided for the numerical solutions of the SIRC epidemic delay differential model, i.e. SIRC-EDDM using the dynamics of the COVID-19. The design of the scale conjugate gradient (CG) neural networks (SCGNNs) is presented for the numerical treatment of SIRC-EDDM. The mathematical model is divided into susceptible S ( ρ ) , recovered R ( ρ ) , infected I ( ρ ) , and cross-immune C ( ρ ) , while the numerical performances have been provided into three different cases. The exactitude of the SCGNNs is perceived through the comparison of the accomplished and reference outcomes (Runge-Kutta scheme) and the negligible absolute error (AE) that are performed around 10−06 to 10−08 for each case of the SIRC-EDDM. The obtained results have been presented to reduce the mean square error (MSE) using the performances of train, validation, and test data. The neuron analysis is also performed that shows the AE by taking 14 neurons provide more accurateness as compared to 4 numbers of neurons. To check the proficiency of SCGNNs, the comprehensive studies are accessible using the error histograms (EHs) investigations, state transitions (STs) values, MSE performances, regression measures, and correlation.

Mode I fracture propagation and post-peak behavior of sandstone: Insight from AE and DIC observation

Microcracks generated at the crack tip, particularly in quasi-brittle materials such as sandstone, give rise to a non-linear region known as the fracture process zone (FPZ), which cannot be analyzed using linear elastic fracture mechanics (LEFM). To gain insights into the nonlinear fracturing behavior of rock, this study conducted three-point bending experiments on sandstone beams with prefabricated notch. Stable mode-Ⅰ fracture propagation during the post-peak stage was achieved by the monotonic increment of crack mouth opening displacement (CMOD) measured by a clip gauge. The acoustic emission (AE) and digital image correlation (DIC) techniques were utilized to visually track the detailed crack propagation process from both micro and macro perspectives. Nonlinear fracture parameters, including FPZ length, were identified by AE and DIC measurements and compared with the theoretical calculation. A nonlinear fracture criterion relating applied load, equivalent crack length, and stress intensity factor were established, from which the theoretical CMOD-P curve at the post-peak stage were obtained and validated with experimental measurement from MTS machine. The results reveal that microcracks formulating the FPZ materialize in the pre-peak stage, with the majority emerging post-peak to facilitate the propagation of the traction-free crack and FPZ in the loading direction, as evidenced by AE locations and DIC displacement gradient. Throughout the crack propagation process, over 65 % of microcracks are estimated to be tensile mode based on both AF/RA and polarity analysis, aligning with anticipated outcomes from macroscopic three-point bending fracture tests. Energy dissipation primarily occurs within the FPZ to facilitate separation of crack faces, with the dissipated energy region advancing towards the beam boundary. By integrating AE source locations and DIC displacement gradient, the FPZ length of the 3-point-bending sandstone specimens is determined to be lp = 8.1 mm, slightly exceeding the theoretical FPZ lengths calculated by the Irwin model (lp = 7.0 mm) and the Dugdale-Barenblatt model (lp = 7.6 mm). Using a non-linear fracture criterion that incorporates the FPZ and employing the in-time equivalent crack length measured by AE and DIC as an intermediate variable, the theoretical applied load-crack length curve during the post-peak stage is calculated, showing close agreement with load cell measurements with a negligible error of approximately 2 %. Furthermore, the theoretical post-peak CMOD vs. load curve aligns with experimentally obtained results, demonstrating a non-linear crack propagation speed at a constant CMOD rate, wherein crack propagation speed decreases as crack length increases.

A COMPARATIVE STUDY OF CATBOOST AND ARTIFICIAL NEURAL NETWORKS IN ENHANCING TRIP GENERATION MODELLING FOR ILORIN CITY

Trip generation plays a crucial role in transportation planning, and the choice of an appropriate model is essential for predicting future travel patterns. This study focuses on comparing the suitability and performance of CatBoost and ANN for trip generation (production and attraction) modelling of Ilorin City. By incorporating Ilorin household and trip characteristics, population data, and maps, this study evaluates the performance of the models. The two models demonstrated high accuracy and performance. In terms of trip production, the CatBoost model displayed exceptional accuracy, attaining an R-squared value of 0.99999992016446, accompanied by an impressively low mean squared error (MSE) of 3.93870930136429e-05. In contrast, the neural network exhibited a slightly lower accuracy of 0.999873850524181, with an error value of 0.0581313408911228. Similarly, for trip attraction, the CatBoost model showcased remarkable accuracy and precision, achieving an accuracy score of 0.9999999999999994 and an extremely low error value of 2.26762031965784e-13. The neural network model demonstrated an accuracy of 0.99999999990335 and a negligible error value of 0.000000041994. These findings underscore the strong predictive capabilities of both models for trip production and attraction, with the CatBoost model notably excelling in achieving nearly flawless accuracy and minimal error values across both aspects in Ilorin. Further research can explore the application of other advanced machine-learning techniques and combine their strengths to enhance the accuracy and robustness of trip-generation models.

Spatiotemporal Analysis of Carbon Emissions Based on Night-time Light Data in Western Provinces of China

This study focuses on the fusion and calibration of DMSP–OLS and NPP–VIIRS night-time light data, sourced from the National Geophysical Data Centre in the United States. A long-time series night-time light dataset, spanning from 1999 to 2019, for the western provinces of China is created. In conjunction with carbon emission statistics from these 11 western provinces, an estimation model is constructed to analyse the changes in the spatiotemporal pattern of carbon emissions within the region, revealing the characteristics of carbon emissions caused by human night-time economic activities in western China, and provides theoretical reference for the formulation of energy conservation and emission reduction policies. Results show that: – A strong correlation coefficient of 0.9067 exists between carbon emissions and the total digital number (DN) value of night-time light in the western provinces, with a negligible average relative error, and this result indicates the effectiveness of the estimation model; – The study reveals an increasing trend in carbon emissions across all 11 provinces from 1999 to 2019, and this growth forms a radial expansion pattern centred around the provincial capitals of Sichuan, Shaanxi, and Inner Mongolia; – By integrating night-time light images and calculated carbon emissions through the estimation model, a significantly positive spatial correlation of carbon emissions is discernible. This outcome presents as a high carbon agglomeration area in the Inner Mongolia Autonomous Region and a low carbon agglomeration area in Qinghai Province. On the basis of these findings, the study proposes transformation measures to promote low carbon emissions in China’s western provinces. These practical suggestions provide a point of reference for China as it aims to meet its “carbon neutrality” and “peak carbon emissions” targets.

Exploration of Four-Channel Coherent Optical Chaotic Secure Communication with the Rate of 400 Gb/s Using Photonic Reservoir Computing Based on Quantum Dot Spin-VCSELs

In this work, we present a novel four-channel coherent optical chaotic secure communication (COCSC) system, incorporating four simultaneous photonic reservoir computers in tandem with four coherent demodulation units. We employ a quartet of photonic reservoirs that capture the chaotic dynamics of four polarization components (PCs) emitted by a driving QD spin-VCSEL. These reservoirs are realized utilizing four PCs of a corresponding reservoir QD spin-VCSEL. Through these four concurrent photonic reservoir structures, we facilitate high-quality wideband-chaos synchronization across four pairs of PCs. Leveraging wideband chaos synchronization, our COCSC system boasts a substantial 4 × 100 GHz capacity. High-quality synchronization is pivotal for the precise demasking or decoding of four distinct signal types, QPSK, 4QAM, 8QAM and 16QAM, which are concealed within disparate chaotic PCs. After initial demodulation via correlation techniques and subsequent refinement through a variety of digital signal processing methods, we successfully reconstruct four unique baseband signals that conform to the QPSK, 4QAM, 8QAM and 16QAM specifications. Careful examination of the eye diagrams, bit error rates, and temporal trajectories of the coherently demodulated baseband signals indicates that each set of baseband signals is flawlessly retrieved. This is underscored by the pronounced eye openings in the eye diagrams and a negligible bit error rate for each channel of baseband signals. Our results suggest that delay-based optical reservoir computing employing a QD spin-VCSEL is a potent approach for achieving multi-channel coherent optical secure communication with optimal performance and enhanced security.

A temperature control method of hot-bar soldering based on extended Kalman filter

PurposeThis study aims to introduce a novel technique for nonlinear sensor time constant estimation and sensor dynamic compensation in hot-bar soldering using an extended Kalman filter (EKF) to estimate the temperature of the thermocouple.Design/methodology/approachTemperature optimal control is combined with a closed-loop proportional integral differential (PID) control method based on an EKF. Different control methods for measuring the temperature of the thermode in terms of temperature control, error and antidisturbance are studied. A soldering process in a semi-industrial environment is performed. The proposed control method was applied to the soldering of flexible printed circuits and circuit boards. An infrared camera was used to measure the top-surface temperature.FindingsThe proposed method can not only estimate the soldering temperature but also eliminate the noise of the system. The performance of this methodology was exemplary, characterized by rapid convergence and negligible error margins. Compared with the conventional control, the temperature variability of the proposed control is significantly attenuated.Originality/valueAn EKF was designed to estimate the temperature of the thermocouple during hot-bar soldering. Using the EKF and PID controller, the nonlinear properties of the system could be effectively overcome and the effects of disturbances and system noise could be decreased. The proposed method significantly enhanced the temperature control performance of hot-bar soldering, effectively suppressing overshoot and shortening the adjustment time, thereby achieving precise temperature control of the controlled object.

Behaviorist Theory in Philippine English L2 Acquisition: Transition Point from L1 Contact

Skinner’s behaviorist theory delineates how a child acquires L1; notwithstanding, what sets the present study apart from Skinner’s findings can be culled-out from the research context itself. This paper validates the principles behind behaviorist theory as proposed by Skinner (1985) taking into account applied linguistics context. Careful scrutiny of data reveals that the explored theory also plays a vital role in the gradual L2 acquisition through meaningful linguistic attempts (e.g., There are persons cutting trees without replanting; His friends Marilyn and Alicia clean the classroom) and reading activities by fostering affirmative learning atmosphere to induce positive language attitude towards L2 acquisition and functionality. Negligible errors in the process of L2 acquisition are attributed to linguistic variability, interlanguage, and inflectional morphology component. This study is advantageous to EFL learners and teachers globally for it highlights some linguistic implications indispensable to interpret the learning rate, lexical range, comprehensible input (CI), and language cognition of L2 students specifically in early language education. EFL educators may be able to provide meaningful linguistic activities by considering the essential tenets of this academic piece as well as the multiculturalism factor to L2 acquisition.