Miracle-dz/UniFAR-FTUs huggingface dataset:
Perceptions of the benefits of the basic medical insurance system among the insured: a mixed methods research of a northern city in China

Background The perceptions of the benefits of the basic medical insurance system among the insured not only reflect the system's performance but also the public's basic medical insurance policy literacy, valuable information for countries that have entered the stage of deepening reform. This study aims to examine the factors that affect the perceptions of the benefits of the basic medical insurance system in China, diagnose the key problems, and propose corresponding measures for improvement. Methods A mixed method design was used. Data for the quantitative study were obtained from a cross-sectional questionnaire survey (n = 1,045) of residents of Harbin who had enrolled for basic medical insurance system. A quota sampling method was further adopted. A multivariate logistic regression model was then employed to identify the factors influencing the perceptions of the benefits of the basic medical insurance system, followed by semi-structured interviews with 30 conveniently selected key informants. Interpretative phenomenological analysis was used to analyze the interview data. Results Approximately 44% of insured persons reported low perceptions of benefits. The logistic regression model showed that low perceptions of the benefits of the basic medical insurance system was positively correlated with the experience of daily drug purchases (OR = 1.967), perceptions of recognition with basic medical insurance system (OR = 1.948), perceptions of the financial burden of participation costs (OR = 1.887), perceptions of the convenience of using basic medical insurance for medical treatment (OR = 1.770), perceptions of the financial burden of daily drug purchases costs (OR = 1.721), perceptions of the financial burden of hospitalization costs (OR = 1.570), and type of basic medical insurance system (OR = 1.456). The results of the qualitative analysis showed that the key problem areas of perceptions of the benefits of the basic medical insurance system were: (I) system design of basic medical insurance; (II) intuitive cognition of the insured; (III) rational cognition of the insured; and (IV) the system environment. Conclusions Improving the perceptions of the benefits of the basic medical insurance system of the insured requires joint efforts in improving system design and implementation, exploring effective publicity methods of basic medical insurance system information, supporting public policy literacy, and promoting the health system environment.
Auditory temporal resolution and backward masking in musicians with absolute pitch

Among the many questions regarding the ability to effortlessly name musical notes without a reference, also known as absolute pitch, the neural processes by which this phenomenon operates are still a matter of debate. Although a perceptual subprocess is currently accepted by the literature, the participation of some aspects of auditory processing still needs to be determined. We conducted two experiments to investigate the relationship between absolute pitch and two aspects of auditory temporal processing, namely temporal resolution and backward masking. In the first experiment, musicians were organized into two groups according to the presence of absolute pitch, as determined by a pitch identification test, and compared regarding their performance in the Gaps-in-Noise test, a gap detection task for assessing temporal resolution. Despite the lack of statistically significant difference between the groups, the Gaps-in-Noise test measures were significant predictors of the measures for pitch naming precision, even after controlling for possible confounding variables. In the second experiment, another two groups of musicians with and without absolute pitch were submitted to the backward masking test, with no difference between the groups and no correlation between backward masking and absolute pitch measures. The results from both experiments suggest that only part of temporal processing is involved in absolute pitch, indicating that not all aspects of auditory perception are related to the perceptual subprocess. Possible explanations for these findings include the notable overlap of brain areas involved in both temporal resolution and absolute pitch, which is not present in the case of backward masking, and the relevance of temporal resolution to analyze the temporal fine structure of sound in pitch perception.
Permian trilobites and the applicability of the “living fossil” concept to extinct clades

Some taxa occupy our imaginations as “living fossils” because they were known from the fossil record before being discovered alive today. Other taxa are considered “living fossils” because modern relatives bear a strong morphological resemblance to fossil relatives, or because they occupy a contracted geographic range or have less diversity now than in the past, or because they represent phylogenetic diversity that requires conservation. A characterizing feature of living fossils–and thus an implicit assumption of all criteria–is that the “living fossil” of interest is extant. However, the general research questions that “living fossils” inspire–Why do rates of evolution vary across organisms, across traits, and across time? Why do some clades decline in diversity over extended periods? –may be applied to any clade, including completely extinct clades. We propose that there is nothing special about “now” when it comes to pursuing these questions and that it is unnecessarily limiting to restrict research programs to clades for which an extant member meets some conception of the “living fossil” moniker. To this end, we investigate the extent to which Permian trilobites might resemble “living fossils,” albeit from the perspective of 253 million years ago, when the last trilobites were still alive. We do so by comparing the taxonomic diversity, geographic range, and morphological disparity of trilobites living in the Permian to earlier time periods. We find that Permian trilobites meet most definitions of living fossils, although our assessment of morphological change and character retention depend on taxonomic scale.
Vortex force map for incompressible multi-body ﬂows with application to wing–ﬂap conﬁgurations

The vortex force map method for incompressible viscous ﬂows with multiple bodies is derived in this work. The method breaks the ﬂuid force into inertial, vortex-pressure, viscous-pressure and skin-friction components, and it could be used to analyse the ﬂuid dynamic forces on individual bodies in a multi-body assembly. For the ﬁrst time, we provide a graphical representation of the vortex-pressure force – the vortex force map – for individual bodies in a multi-body assembly. We have shown that the vortex force map in a multi-body set-up differs from single-bodied counterparts from modiﬁcations to their hypothetical potential through a nonlinear cross-coupling, and that the inertial and viscous-pressure contributions contain inﬂuences from other bodies explicitly. We then demonstrate the multi-body vortex force decomposition method with a wing–ﬂap starting ﬂow problem using computational ﬂuid dynamics data, identifying the positive and negative force-generating critical regions or directions. It is found that the dominant force is the vortex-pressure force, and the force variation against time is closely related to the evolution of the vortex structures. Furthermore, we showed that the existence of another body signiﬁcantly alters the force contribution roles of vortices in the ﬂow.
Viscoplastic constructions optimisation with the account of the history of loading

Two possible ways of problem setting of viscoplastic constructions optimisation with the account of the history of loading are considered. For the illustrations of both approaches optimum configurations of fixed area opening in the loaded along a outline square plate were calculated. It is shown that the optimum project for the case of the fixed opening and the changing external loading differs from the project where it is taken into consideration that the loading is fixed and the opening is made in an originally solid plate.
Optimal design on parameters of Z-pinch wire-array load

Based on the load current of S-300 machine, in Russia, optimal combinations of radius and mass per unit length of tungsten wire-arrays were obtained by a lot of optimal calculation by means of 0-D model, under different drive current with peak value of 2.5MA, 4MA, 5MA, 6MA, 8MA, and 20MA, respectively. The calculation shows that the optimal linear mass increases with the rising time of current, and that the maximal kinetic energy of implosion is in direct proportion to square of current peak value.
Gradient-based multiobjective optimization using a distance constraint technique and point replacement

This paper proposes techniques to improve the diversity of the searching points during the optimization process in an Aggregative Gradient-based Multiobjective Optimization (AGMO) method, so that well-distributed Pareto solutions are obtained. First to be discussed is a distance constraint technique, applied among searching points in the objective space when updating design variables, that maintains a minimum distance between the points. Next, a scheme is introduced that deals with updated points that violate the distance constraint, by deleting the offending points and introducing new points in areas of the objective space where searching points are sparsely distributed. Finally, the proposed method is applied to example problems to illustrate its effectiveness.
The character characteristic extraction based on projection characterist and wavelet analysis

This paper presents a new method which combines the traditional projection characteristic and wavelet multiresolution analysis.The simple and crude character projection characteristic was transformed with wavelet multiresolution analysis,extracting the valid characteristic in the coefficients of approximation and particular.The result of control experiment illustrates the effect of wavelet multi-scale transform and wavelet coefficients on character characteristic extraction.
Subsonic potential flow past a circle and the transonic controversy

Abstract The Mach-number series expansion of the potential function for the two-dimensional flow of an inviscid, compressible, perfect, diatomic gas past a circular cylinder is obtained to 29 terms. Analysis of this expansion allows the critical Mach number, at which flow first becomes locally sonic, to be estimated as M* = 0.39823780 ± 0.00000001. Analysis also permits the following estimate of the radius of convergence of the series for the maximum velocity to be made: Mc = 0.402667605 ± 0.00000005, though we have been unable to determine the nature of the singularity of M = Mc. Since Mc exceeds M* by some 1.1%, it follows that this particular “airfoil” can possess a continuous range of shock-free potential flows above the critical Mach number. This result hopefully resolves a 70-year old controversy.
Approximation using rational splines with adjustable tension

An interpolation procedure using the rational spline approximation is presented . The rational spline contains an adjustable tension parameter for each pair of uccessive knots such that in the limit of zero tension, the spline reduces to a conventional cubic spline and in the limit of infinite tension the spline reduces to a straight line . The procedure for adjusting the tension parameters is completely automated such that by adjusting the tension it is possible to achieve the quot;bestquot; fit (in a least-squares sense) of the data . A detailed derivation of the algorithm is presented along with its procedural implementation.the method is successfully implemented on a computer and tested for two cases . Recommendations are made for further extension and application of this method.
Further results on finite‐time consensus of second‐order multi‐agent systems without velocity measurements

This paper investigates the problem of finite‐time consensus (FTC) for second‐order nonlinear multi‐agent systems when the velocity information is unavailable. Based on the global finite‐time stability theory and homogeneity with dilation, a class of novel finite‐time consensus protocols are proposed for the multi‐agent systems. The protocol design is divided into two parts. First, when all the state information of the agents are measurable, a new continuous state feedback is designed to achieve FTC. Then, when the velocity information is unmeasurable, two finite‐time convergent discontinuous observers are presented to estimate the velocities of the followers and the leader, respectively, which further ensure the final FTC for the multi‐agent systems. Finally, one example is given to demonstrate the efficiency of the proposed method. Copyright © 2015 John Wiley & Sons, Ltd.
THE EFFECT OF AUXILIARY FIELDS ON STRESS INTENSITY FACTORS IN FUNCTIONALLY GRADED MATERIALS

Original Research Paper Received 08 May 2015 Accepted 01 July 2015 Available Online 25 July 2015 This paper concerns the effect of auxiliary fields and also the contour distance from the crack tips on accuracy of stress intensity factors of Functionally Graded Materials (FGMs), using the interaction integral method. In the first step, defining auxiliary fields of displacement, strain, and, stress appropriately, the interaction integral is derived which is independent from derivatives of properties of the materials. Actual and auxiliary fields of displacement, strain and stress are used to compute the interaction integral. Actual fields are obtained by isoparametric finite element method, while auxiliary fields are constructed by use of the crack tip properties on the basis of Williams’ solution. These auxiliary fields are not appropriate, except near the crack tips. Therefore, di erent non-equilibrium and incompatibility formulations are used to consider the changes in non-homogeneous material. Considering the changes in FGMs as an exponential function, the results will then be obtained from these formulations and are compared with others recorded in the literature. Furthermore, considering different contours, the effect of contour distance from the crack tips on the stress intensity factors of FGMs is examined. The results confirm that the solutions using the incompatibility and constant constitutive tensor are more accurate. In contrast, the non-equilibrium method is not proper for contours which are placed far away from the crack tips and presents less accuracy.
Noise, coherent activity and network structure in neuronal cultures

In this thesis we apply a multidisciplinary approach, based on statistical physics and complex systems, to the study of neuronal dynamics. We focus on understanding, using theoretical and computational tools, how collective neuronal activity emerges in a controlled system, a neuronal culture. We show how the interplay between noise and network structure defines the emergent collective behavior of the system. We build, using theory and simulation, a framework that takes carefully describes spontaneous activity in neuronal cultures by taking into account the underlying network structure of neuronal cultures and use an accurate, yet simple, model for the individual neuronal dynamics. We show that the collective behavior of young cultures is dominated by the nucleation and propagations of activity fronts (bursts) throughout the system. These bursts nucleate at specific sites of the culture, called nucleation points, which result in a highly heterogeneous probability distribution of nucleation. We are able to explain the nucleation mechanism theoretically as a mechanism of noise propagation and amplification called noise focusing. We also explore the internal structure of activity avalanches by using well--defined regular networks, in which all the neurons have the same connectivity rules (motifs). Within these networks, we are able to associate to the avalanches an effective velocity and topological size and relate it to specific motifs. We also devise a continuum description of a neuronal culture at the mesoscale, i.e., we move away from the single neuron dynamics into a coarse--grained description that is able to capture most of the characteristic observables presented in previous chapters. This thesis also studies the spontaneous activity of neuronal cultures within the framework of quorum percolation. We study the effect of network structure within quorum percolation and propose a new model, called stochastic quorum percolation, that includes dynamics and the effect of internal noise. Finally, we use tools from information theory, namely transfer entropy, to show how to reliably infer the connectivity of a neuronal network from its activity, and how to distinguish between different excitatory and inhibitory connections purely from the activity, with no prior knowledge of the different neuronal types. The technique works directly on the fluorescence traces obtained in calcium imaging experiments, without the need to infer the underlying spike trains.
Error of Measurement and Statistical Inference: Some Anomalies.

This paper was designed to examine some relations between the reliability of a dependent variable and the magnitude of the associated test statistic, and to point out some anomalies that arise when the usual reliability formulas are applied. These anomalies suggest that error of measurement, as investigated in classical test theory, cannot be routinely incorporated into the “error term” in statistical tests, and that the reliability of test scores, as traditionally defined, does not have the simple relationship to statistical inference that one might expect.
Obstacle detect based on improved neural network for fusion of radar and visual information

Image target detection technology using deep learning has been fully developed in recent years, but in harsh and complex environments such as rain, snow, and darkness, the information collected by the image sensor will have a lot of noise, and it is easy to lose information about small distant targets and fuzzy targets, resulting in false detection and missed detection. Millimeter-wave(mmWave) radar uses electromagnetic waves for obstacle detection, and the detection performance in harsh environments basically does not degrade, in order to solve the situation that the detection accuracy is significantly reduced when single sensor environmental sensing technology is applied to complex scenes. In this paper, an enhanced neural network model for feature fusion is proposed by fusing radar and camera sensor features and combining them with an improved YOLO-S neural network. Firstly, the model is designed to convert the radar point cloud into image form while applying the BiFPN structure with integrated CA attention mechanism to the YOLOX-S neural network. By connecting radar features with image features and combining radar features with spatial attention weights, the useless information in the extracted features is suppressed while the key information is enhanced, and the sensor features are complementary. The experimental results show that the fusion-enhanced network designed in this paper fully integrates the features of both sensors and provides better detection results and stronger robustness in detecting small distant objects and objects in dark and low-light environments.
Linear Closed-Loop Control of Fluid Instabilities and Noise-Induced Perturbations: A Review of Approaches and Tools

This review article is concerned with the design of linear reduced-order models and control laws for closed-loop control of instabilities in transitional flows. For oscillator flows, such as open-cavity flows, we suggest the use of optimal control techniques with Galerkin models based on unstable global modes and balanced modes. Particular attention has to be paid to stability–robustness properties of the control law. Specifically, we show that large delays and strong amplification between the control input and the estimation sensor may be detrimental both to performance and robustness. For amplifier flows, such as backward-facing step flow, the requirement to account for the upstream disturbance environment rules out Galerkin models. In this case, an upstream sensor is introduced to detect incoming perturbations, and identification methods are used to fit a model structure to available input–output data. Control laws, obtained by direct inversion of the input–output relations, are found to be robust when applied to the large-scale numerical simulation. All the concepts are presented in a step-by-step manner, and numerical codes are provided for the interested reader. [DOI: 10.1115/1.4033345]
Multidecadal evaluation of changes in coffee-growing areas using Landsat data in Central Highlands, Vietnam

Abstract Vietnam is the world’s second-largest coffee exporter. Information on coffee-growing areas is thus important for production estimation. This research developed an approach for coffee mapping and change detection using Landsat and DEM data in Central Highlands, Vietnam. The data were processed for 1995, 2005, and 2020 using random forests (RF). The mapping results, verified with reference data, showed overall accuracy and Kappa coefficient higher than 86.9% and 0.74, respectively. These findings were reaffirmed by a close relationship between the satellite-based coffee area and official statistics, with the root mean squared percentage error (RMSPE) and mean absolute percentage error (MAPE) greater than 9.9% and 7.6%, respectively. From 1995 to 2020, the newly planted coffee area increased by 135,520 ha, due to the conversion of forests to coffee plantations. Such distributions of coffee areas and decadal changes in farming activities are critically useful for policymakers to formulate successful crop planning strategies.
Learning Non-linear SVM in Input Space for Image Classification

The kernel trick enables learning of nonlinear decision functions without having to explicitly map the original data to a high dimensional space.However, at test time, it requires evaluating the kernel with each one of the support vectors, which is time consuming. We propose a novel approach for learning nonlinear support vector machine (SVM) corresponding to commonly used kernels in computer vision, namely (i) Histogram Intersection, (ii) χ 2 , (ii) Radial Basis Function (RBF) and (iv) RBF with χ 2 distance, without using the kernel trick. The proposed classifier incorporates non-linearity while maintaining O(D) testing complexity (for D-dimensional space), compared to O(D×Nsv ) (for Nsv number of support vectors) when using the kernel trick. We also promote the idea that such efficient non-linear classifier, combined with simple image encodings, is a promising direction for image classification. We validate the proposed method with experiments on four challenging image classification datasets. It achieves similar performance w.r. t. kernel SVM and recent explicit feature mapping method while being significantly faster and memory efficient. It obtains competitive performance while being an order of magnitudefaster than the state-of-the-art Fisher Vector method and, when combined with it, consistently improves performance with a very small additional computation cost.