Miracle-dz/UniFAR-FTUs huggingface dataset:
Polar Constrained Image Stitching Algorithm for Unmanned Aerial Vehicle Based on Crossing Area

Stitching the aerial images from an Unmanned Aerial Vehicle (UAV) is usually needed to obtain a more comprehensive image information, but the image stitching technology is limited by the requirements of stitching quality and stitching speed. This study proposed a method to achieve good quality, fast stitching speed, and good robustness in image stitching. A large number of feature points in the intersection region were extracted and incorrect feature matching point pairs were accurately filtered out. The area with large cross area of multiple images was extracted as the target area of feature points to be extracted. The Scale-Invariant Feature Transform (SIFT) algorithm was employed to extract the feature points in the image which was not invariant with illumination, environment, and scale. Given that Brute Force (BF) matching soundly produces large number of wrong feature point pairs, the polar constraint was added to improve the matching accuracy, and the feature point pairs were further filtered through the Progressive Sample Consensus (PROSAC) algorithm. Finally, the homograph transformation matrix was used for image registration, and the fusion algorithm was applied to naturally fuse the two images together. Results demonstrate that this algorithm largely reduces the computational complexity, improves the speed by 0.124% compared with other algorithms, and improves the performance of Root Mean Square Error (RMSE) and Mean Square Error (MAE) by 0.224% and 0.173%, respectively. The stitched image quality is obviously better than the general algorithm process. The proposed method provides a certain reference for UAV aerial image Mosaic methods.
A branch and bound method solving the max–min linear discriminant analysis problem

Fisher linear discriminant analysis (FLDA or LDA) is a well-known technique for dimension reduction and classification. The method was first formulated in 1936 by Fisher in the one-dimensional setting. In this paper, we will examine the LDA problem using a different objective function. Instead of maximizing the sum of all distances between all classes, we will define an objective function that will maximize the minimum separation among all distances between all classes. This leads to a difficult nonconvex optimization problem. We present a branch and bound method for the problem in the case where the reduction is to the one-dimensional space.
Social Networks and Political Group Participation: The Chain Mediation Effect of Social Participation and Intrinsic Political Efficacy

Political groups serve as an important forum for grassroots participation in social governance and political dominance, and are a powerful guarantee for political democratisation and social modernisation. Using data from the China CGSS 2017 national survey, this study explores the relationship between social networks and political group participation, and the role of social participation and intrinsic political efficacy in this relationship.The result indicated the following: (1) social networks positively predict political group participation, even after controlling for age, gender, education, and economic status. (2)Social participation and intrinsic political efficacy mediate between social networks and political groups via three pathways: parallel mediation of social participation and intrinsic political efficacy, sequential mediation of social participation, and sequential mediation of intrinsic political efficacy. This study suggests that different incentives can be used to promote political group participation for people with different social network statuses, and that a focus on the composition and operation of social networks can provide insight into the future direction of democratic politics in China.
An Ultra-Broadband Energy Selective Surface Design Method: From Filter Circuits to Metamaterials

A novel design method for ultra-broadband energy selective surface (ESS) is presented in this article based on the equivalent theory from filter circuits to metamaterial units. This method provides a new way of designing ESS in ultra-broadband with low insertion loss (IL) and high shielding efficiency from the perspective of filter circuit topology. It is illustrated and verified with a three layer ultra-broadband ESS. Firstly, a third-order filter with a switching bandpass to bandstop in C to Ku-band is designed and optimized. Then, the filter is mapped to a physical model of a three-layer ESS which has a nonlinear transmission response for low-intensity radiation field (LIRF) and high-intensity radiation field (HIRF) in C/X/Ku-band. The three ESS prototypes are fabricated and measured in three different band waveguides to prove the design method of the ESS proposed in ultra-broadband. Simulated and measured results demonstrate that low IL and high shielding efficiency at the same time can be obtained under low and high incident power levels, respectively, where the 1 dB loss and 23 dB shielding bandwidth cover from 5.4 to 14.45 GHz. Furthermore, the IL is less than 0.5 dB in the frequency band of 5.45–13.8 GHz and maximum shielding effectiveness (SE) reaches 25 dB at 10 GHz.
Tuning the Luminescence Response of an Air-Hole Photonic Crystal Slab Using Etching Depth Variation

Detailed studies of the luminescent properties of the Si-based 2D photonic crystal (PhC) slabs with air holes of various depths are reported. Ge self-assembled quantum dots served as an internal light source. It was obtained that changing the air hole depth is a powerful tool which allows tuning of the optical properties of the PhC. It was shown that increasing the depth of the holes in the PhC has complex influences on its overall photoluminescence (PL) response due to the simultaneous influences of counteracting factors. As a result, the maximal increase in the PL signal of more than two orders of magnitude was obtained for some intermediate, but not full, depth of the PhC’s air holes. It was demonstrated that it is possible to engineer the PhC band structure in such a way as to construct specific states, namely bound states in continuum (BIC), with specially designed dispersion curves being relatively flat. In this case, such states manifest themselves as sharp peaks in the PL spectra, and have high Q-factors which are larger than those of radiative modes and other BIC modes without such a flat dispersion characteristic.
Analysis of data association methods of SLAM

The result of data association is affected by the state of features in the environment.In order to analyze the influence,two kinds of simulation scenes are set up,where feature pairs are arranged at different intervals.Four kinds of data association methods,individual compatibility nearest neighbor(ICNN),sequential compatibility nearest neighbor(SCNN),joint compatibility(JC) and joint maximum likelihood(JML) are tested in different situations for the comparison of feature association.The results show that the feature locations and the interval between features have important effects on the association method.The worse results can be gotten for the most association method when the interval is not large,but good results can be gotten when the interval is large,and each method has its advantages and disadvantages in different situations.The results are of significance in applications to the analysis and selection of the method of data association in simultaneous localization and mapping(SLAM).
The Role of Identity in Human Behavior Research: A Systematic Scoping Review

ABSTRACT Many theories of motivation recognize a person’s identity adds value to the prediction of behavior; albeit indirectly, through constructs such as social norms, self-efficacy, perceived behavioral control, and values. Recently, behavioral research has more directly assessed the influence of identity on behavior; however, it is unclear whether such research aligns with the theoretical establishments of identity. This review investigated the identity theory alignment of existing behavior research by systematically searching, screening, and reviewing identity-behavior relevant papers, across three behavioral psychology databases. Twenty-three papers meet the inclusion criteria for review (original research with a primary focus on identity and behavior, within healthy adult population), and data relating to identity-behavior theoretical viewpoints, research methods, and study findings were extracted and synthesized to provide a scoping overview of current research. Most reviewed papers presented identity as a loosely defined construct; commonly operationalized as social identity, omitting the theorized multiplicity of social and self-identities. Overall outcomes suggested that identity influences behavior indirectly through intention strength, rather than directly as a post-intention mechanism. While existing research has been crucial in illuminating potential influences of identity on behavior, there is a need to strengthen current understandings and theoretical alignments within future research relating to identity and behavior.
Balancing a wheeled inverted pendulum with a single accelerometer in the presence of time delay

The output of an accelerometer often has coupled components of displacement and acceleration, and is rarely used individually for balancing tasks. In order to balance a wheeled inverted pendulum like the Segway, the conventional control usually requires gyroscopes or a combination of accelerometers and gyroscopes. In this paper, we prove that even in the presence of time delay, a wheeled inverted pendulum can be well stabilized with only one accelerometer as the sensor when the mechanical structure is slightly modified. The key idea is the introduction of an additional damper that does not have a physical connection with the wheels. Moreover, we show that balancing can be achieved with an appropriately selected accelerometer position over a range of time delays.
A Procedure for Identifying Planes and Axes of Symmetry Candidates in B-rep CAD Models

Computer-Aided Symmetry Detection (CASD) supports mechanical engineers in detecting the planes and axes of symmetry in 3D CAD models. A common approach of many CASD techniques is first to create a set of planes of symmetry candidates (POSCs) and axes of symmetry candidates (AOSCs), which are then evaluated to identify the actual planes and axes of symmetry among them. The candidates are often identified from the input model’s geometry by pairing entities (e.g., point clouds, surfaces, mesh triangles, etc.). Consequently, a considerable number of candidates may be generated without their practical need to detect symmetries, thus making the CASD computationally demanding. Hence, this study proposes a procedure for identifying a reduced number of POSCs and AOSCs to detect exact global and partial axis-and reflectional symmetry in 3D CAD models with Boundary Representation.
Coupling Coordination between Fintech and Digital Villages: Mechanism, Spatiotemporal Evolution and Driving Factors—An Empirical Study Based on China

Based on Chinese provincial data from 2013 to 2020, this research constructed a fintech index and a digital index and analyzed the temporal and spatial coupling coordination status and driving factors of the two using a coupled coordination model. The results of the study were as follows. (1) In general, the comprehensive index of fintech and digital villages increased year by year in the time sequence and fell into fintech-dominated coupling. The divergence in space was significant, showing an overall decreasing trend from the eastern coastal areas to the central areas and western areas. (2) In terms of sequential characteristics, the coupling coordination between fintech and digital villages shifted into the stage of primary coordination, which was phased and rising and continued to grow during the examination period. (3) In terms of spatial characteristics, the degree of coupling coordination between fintech and digital villages was different and agglomerative, with a trend of “strong in the east, mediocre in the middle and poor in the west”; seven provinces and cities entered the intermediate coordination stage. (4) In terms of drivers, the levels of economic development, regional industrial structure, regional population density, and digital infrastructure had a positive influence on coupling coordination. (5) Conditional convergence existed in eastern, central and western China from the convergence test; also, the speed was faster than absolute convergence.
Single Machine Scheduling Problems with Learning Effect

This paper considers a single machine scheduling problem in which the job processing times will decrease as a result of learning effect.The learning effect can be described by a piecewise linear function of normal processing times.Based on the analysis of the problem,we proved that the due date assignment problem to minimize total penalty can be formulated as assignment problem and get polynomial algorithm.The dual target problem of mininmizing total completion time and variation of completion times can also be formulated as assignment problem.Moreover,for some special cases,the simple algorithms are presented for the makespan and total completion time minimization problems.
Sur une suite de fonctions liées à un procédé itératif. II

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A Parallel Processing CNN Accelerator on Embedded Devices Based on Optimized MobileNet

In the field of machine vision and pattern recognition, the convolutional neural network (CNN) is one of the hottest research topics. However, the application of CNN, which requires complicated operations, appears to be exceptionally difficult in resource-constrained embedded devices. In this article, a parallel processing CNN accelerator based on optimized MobileNet is presented. By modifying the fully connected layer of the MobileNet network topology with the convolution process, and postponing the global pooling layer, the model topology is unified, which is conducive to the design of the hardware accelerator. After using the 8-bit quantization strategy of network model parameters, the process of depthwise separable convolution is accelerated by parallel processing between channels and pipelined processing between layers. Thus, the processing speed and throughput of the accelerator can be improved. The designed accelerator classification performance on ImageNet achieved 580.6 frames per second (fps) on a ZYNQ AXZU5EV platform and a system power consumption of only 6.51 W. This result represents a $22.3\times $ speedup compared to CPU and a $1.7\times $ speedup compared to graphics processing unit (GPU), while the design has a lower power consumption than CPU and GPU, providing a reference for the application of CNN in embedded devices.
Optimal stopping and dynamic allocation

A class of optimal stopping problems for the Wiener process is studied herein, and asymptotic expansions for the optimal stopping boundaries are derived. These results lead to a simple index-type class of asymptotically optimal solutions to the classical discounted multi-armed bandit problem: given a discount factor 0<β <1 and k populations with densities from an exponential family, how should x 1, x 2,… be sampled sequentially from these populations to maximize the expected value of Ʃ∞ 1 β i−1 x i , in ignorance of the parameters of the densities?
Applications of artificial neural networks and multiple linear regression algorithms in modelling of pig’s body weight

Background: Experiments were conducted to analyze environmental parameters and growth-related factors to identify the most influential factors in estimating pig’s body weight (PBW) using artificial neural networks (ANNs) and multiple linear regression (MLR)-based models. Methods: Four different ANNs, including Cascade Forward Back-propagation (CFBP), Layer Recurrent (LR), Feed Forward Back-propagation (FFBP) and Elman (EL), and MLR models were developed to estimate the body weight of pigs. The current research was conducted for 92 days during the two experimental periods (2021–2022) in a pig barn. Result: The Levenberg-Marquardt training function, gradient descent weight and bias learning function, tan-sigmoid transfer function, and two hidden layers with 16 neurons in each layer were shown to be the most effective architecture of the FFBP model in predicting PBW. According to the sensitivity analysis, length of pig (LP) was the most influential factor in estimating the PBW for MLR/ANN models. However, the environmental parameters along with growth-related factors could not always be the same association with PBW. Therefore, further research on viable alternative breeds with different management conditions may be considered to evaluate MLR and ANN model’s performance.
Comparison of potential field solutions for Carrington Rotation 2144

We examined differences among the coronal magnetic field structures derived with the potential field source surface (PFSS) model for Carrington Rotation 2144, from 21 November to 19 December 2013. We used the synoptic maps of solar photospheric magnetic field from four observatories, the Huairou Solar Observing Station (HSOS), Global Oscillation Network Group (GONG), Helioseismic Magnetic Imager (HMI), and Wilcox Solar Observatory (WSO). We tested two smoothing methods, Gaussian and boxcar averaging, and correction of unbalanced net magnetic flux. The solutions of three‐dimensional coronal magnetic field are significantly different each other. An open‐field region derived with HSOS data agrees best with the corresponding coronal hole observed by Solar Dynamics Observatories/Atmospheric Imaging Assembly, while HMI data yielded best agreements with the near‐Earth OMNI database. The GONG data overall gave agreements as good as the HMI. The PFSS calculations using WSO data were least sensitive to the choices we examined in this work. Differences in PFSS solutions using different choices and parameters in smoothing imply that the photospheric magnetic field distributions with size of several degrees at midlatitude and low‐latitude regions can be decisive, at least, in the examined period. To better determine the global solar corona, therefore, further evaluation of influences from compact bipolar magnetic field is needed.
A Capacitor-Less Digital Low-Dropout Regulator With Self-Clocked Operation

A capacitorless digital low-dropout (D-LDO) voltage regulator with built in adaptive sampling clock is proposed for wireless sensor’s power management applications. The D-LDO regulator adopts a coarse-fine control scheme to accelerate the load transient response. In steady state, the regulator operates at fine-tuning mode with a small switch strength and a low clock frequency. Once the output voltage exceeds the boundaries, a coarse-tuning mode is triggered to quickly find out the desired control bits with a large switch strength and a high clock frequency. The sampling clock is generated with the inherent delay of the internal circuit, thus eliminating the dependence on the external clock. In addition, an active analog-assisted loop is introduced to improve the voltage droop. Fabricated in 180 nm CMOS process, the D-LDO regulator regulates the output voltage range from 0.65 V to 1.15 V. At a VOUT of 0.75 V and VIN of 0.85 V, the proposed D-LDO regulator shows a transient response time of 195 ns with an undershoot of 133 mV at a step load alternating between 5 and 30 mA. It attains a peak current efficiency 99.97% and figure of merit 0.016 ps.
Probabilistic Risk Evaluation of Microgrids Considering Stability and Reliability

Microgrids are being developed with higher penetration of renewable energy sources and utilization of power electronics. The functionality of microgrids is normally measured by two indices, stability and reliability, which are highly influenced by system configuration and generation/load mission profiles. Although system-level modeling approaches have been proposed to evaluate both the said indices for microgrids, they are still considered independently due to the mismatch in their timescales. To this end, it limits the derivation of a comprehensive risk framework to exploit the interdependencies between stability and reliability. Hence, this article addresses this gap for the first time in the realm of microgrids by proposing a probabilistic risk framework by considering stability and reliability simultaneously. Long-timescale reliability are basically decomposed into shorter timescale events, whereas stability is treated as probabilistic events to be integrated into the risk evaluation. This framework can quantify the operation risk of microgrids, thereby providing a more intuitive approach to the design of microgrids. To validate the ruggedness of the proposed framework, system stability and reliability are assessed and interpreted under experimental conditions.
Developing In Vitro Models to Define the Role of Direct Mitochondrial Toxicity in Frequently Reported Drug-Induced Rhabdomyolysis

The United States Food and Drug Administration Adverse Event Reporting System (FAERS) logged 27,140 rhabdomyolysis cases from 2004 to 31 March 2020. We used FAERS to identify 14 drugs frequently reported in 6583 rhabdomyolysis cases and to investigate whether mitochondrial toxicity is a common pathway of drug-induced rhabdomyolysis by these drugs. Preliminary screening for mitochondrial toxicity was performed using the acute metabolic switch assay, which is adapted here for use in murine L6 cells. Fenofibrate, risperidone, pregabalin, propofol, and simvastatin lactone drugs were identified as mitotoxic and underwent further investigation, using real-time respirometry (Seahorse Technology) to provide more detail on the mechanism of mitochondrial-induced toxicity. To confirm the human relevance of the findings, fenofibrate and risperidone were evaluated in primary human skeletal muscle-derived cells (HSKMDC), using the acute metabolic switch assay and real-time respirometry, which confirmed this designation, although the toxic effects on the mitochondria were more pronounced in HSKMDC. Overall, these studies demonstrate that the L6 model of acute modification may find utility as an initial, cost-effective screen for identifying potential myotoxicants with relevance to humans and, importantly, that drug-induced mitochondrial dysfunction may be a common mechanism shared by some drugs that induce myotoxicity.