Miracle-dz/UniFAR-FTUs huggingface dataset:
Decentralized adaptive output feedback design for large-scale nonlinear systems

In this paper, we present a global, decentralized adaptive design procedure for a class of large-scale nonlinear systems, which utilizes only local output feedback. The advocated scheme guarantees robustness to parametric and dynamic uncertainties in the interconnections and also rejects any bounded disturbances entering the system. The systems belonging to this class are those which can be transformed using a global diffeomorphism to the output feedback canonical form, where the interconnections are a function of subsystem outputs only. The uncertainties are assumed to be bounded by an unknown pth-order polynomial in the outputs. The resulting controller maintains global robustness and disturbance rejection properties. The output tracking error is shown to be bounded within a compact set, the size of which can be made arbitrarily small by appropriate choice of the control gains. For the case where the objective is regulation, global asymptotic regulation of all the states of the closed-loop system is achieved.
Efficient Methods for Numerical Modeling of Laminar Friction in Fluid Lines

An improved method for simulating frequency-dependent friction in laminar pipe flow using the method of characteristics is proposed. It has a higher computational efficiency than previous methods while retaining a high accuracy. By lumping the frequency-dependent friction at the ends of the pipeline, the computational efficiency can be improved further, at the expense of a slight reduction in accuracy. The technique is also applied to the transmission line method and found to give a significant improvement in accuracy over previous methods, while retaining a very high computational efficiency.
Gastrointestinal parasites in phyllostomid bats from the Colombian Amazon

ABSTRACT Bats are natural reservoirs of protozoal, viral, fungal and bacterial pathogens. However, little has been described about their endoparasites, especially in the Neotropics, despite the fact that this region represents a high taxonomic and functional bat diversity. In this study, we describe gastrointestinal parasites found in faecal samples of Neotropical bats from the Amazon rainforest of Colombia. We characterise the prevalence of parasites by employing flotation and McMaster techniques. We obtained 222 samples, but only 15 bats (6.8%) of the species Carollia brevicauda (n = 9), C. perspicillata (n = 3), Artibeus planirostris (n = 1), A. lituratus (n = 1) and Gardnerycteris crenulatum (n = 1) were positive for gastrointestinal parasites. This is the first survey of bat gastrointestinal parasites conducted in the Colombian Amazon. We report for the first time coccidian parasites in phyllostomid bats from Colombia. We also found nematodes in gestating females, which may suggest a transfer of parasites to the foetus during pregnancy in fruit bats. Besides insectivorous bats, frugivores can also represent a source for gastrointestinal parasites in the Neotropics, but the factors that determine their hosting capacity are still not fully understood. Further research should explore the interactions of wild and domestic hosts with parasites, which could be useful for analysing potential risks to the human population.
Implementing adaptive power control as a 30/20-GHz fade countermeasure

Satellite systems in the 30/20-GHz band are very susceptible to outages due to rain-induced fades. In order to reduce the impact of these fades, it has been proposed that the power of a transmitting ground station be adjusted during the fade to compensate for the additional attenuation. Real-time frequency scaling of attenuation from the downlink to the uplink shows promise for estimating the uplink attenuation for uplink power control (ULPC). A scaling-type ULPC algorithm using 20-GHz attenuation scaled to 30 GHz is presented. The limitations of such an algorithm and the effects of scintillation on ULPC are explored. The algorithm is tested using OLYMPUS fade data measured on the 14/spl deg/ elevation OLYMPUS to Blacksburg, VA path. An ULPC scheme employing a beacon at the uplink is also presented. It offers better performance than scaled downlink attenuation ULPC.
What can modern deep-learning models tell us about asphalt road distress classification: an empirical study

Several years have passed, DL methods have made a series of progress. However, within the field of road distress recognition, there are few works using recent methods, especially the transformer. Studying how modern models can help us in this field is important for us to figure out the direction we should move forward to. In this paper, we mainly research the performance of the modern DL model in asphalt road distress classification. GAPs is the dataset we used. We apply the recent SOTA of CNN model and transformer model to find out how far we have come. Totally, the improvement in these years is limited, 7.4% increment of f1 score for the validation set. Some problems like overfitting still need a better solution. And in terms of the dataset, characters like local similarity need to be considered when making a dataset and designing a model.
FIT-Net: Feature Interaction Transformer Network for Pathologic Myopia Diagnosis

Automatic and accurate classification of retinal optical coherence tomography (OCT) images is essential to assist physicians in diagnosing and grading pathological changes in pathologic myopia (PM). Clinically, due to the obvious differences in the position, shape, and size of the lesion structure in different scanning directions, ophthalmologists usually need to combine the lesion structure in the OCT images in the horizontal and vertical scanning directions to diagnose the type of pathological changes in PM. To address these challenges, we propose a novel feature interaction Transformer network (FIT-Net) to diagnose PM using OCT images, which consists of two dual-scale Transformer (DST) blocks and an interactive attention (IA) unit. Specifically, FIT-Net divides image features of different scales into a series of feature block sequences. In order to enrich the feature representation, we propose an IA unit to realize the interactive learning of class token in feature sequences of different scales. The interaction between feature sequences of different scales can effectively integrate different scale image features, and hence FIT-Net can focus on meaningful lesion regions to improve the PM classification performance. Finally, by fusing the dual-view image features in the horizontal and vertical scanning directions, we propose six dual-view feature fusion methods for PM diagnosis. The extensive experimental results based on the clinically obtained datasets and three publicly available datasets demonstrate the effectiveness and superiority of the proposed method. Our code is avaiable at: https://github.com/chenshaobin/FITNet.
Seagull optimization-based near-duplicate image detection in large image databases

ABSTRACT Many of the near-duplicate (ND) image detection methods involve a greater number of interest points (IPs) and large dimensions of the feature descriptors requiring huge computations and are unsuitable for large image databases. They may fail to detect NDs if the query and images in the database contain sparse IPs due to low entropy. Besides, the k-means algorithm used for the quantization of visual words may land at a sub-optimal minimum for descriptors because of their distance distribution in feature space. This article presents a new ND image detection method, which uniformly distributes the IPs over low and high entropy regions, reduces the dimension of feature descriptors using discrete wavelet transform (DWT) and employs Seagull Optimization algorithm (SOA) for optimally forming the visual words. It examines proposed method performs on image databases of various sizes and shows that the developed method is more reliable and computationally efficient than the alternatives.
Visual Object Tracking Using Fast Three-Dimensional Discrete Cosine Transform

A novel visual object tracking method for color video stream based on traditional particle filter is proposed in this paper. Feature vectors are extracted from coefficient matrices of fast three-dimensional Discrete Cosine Transform (fast 3-D DCT). The feature, as experiment showed, is very robust to occlusion and rotation and it is not sensitive to scale changes. The proposed method is efficient enough to be used in a real-time application. The experiment was carried out on some common used datasets in literature. The results are satisfied and showed the estimated trace follows the target object very closely.
Detection of Babesia conradae in Coyotes (Canis latrans) and Coyote-Hunting Greyhound Dogs (Canis familiaris)

Babesia conradae is a small piroplasm previously detected in coyote-hunting Greyhound dogs in California and Oklahoma. In dogs, B. conradae causes clinical signs similar to other tick-borne illnesses, and if not treated it can lead to acute kidney injury and other life-threating complications. To date, the life cycle of this apicomplexan parasite has not been fully described, but suggestions of direct contact or tick transmission have been proposed. The purpose of this study was to test coyote tissue samples from coyotes hunted by Greyhound dogs with a history of B. conradae infection to determine if this parasite is present in the coyote population in Northwestern Oklahoma. The analyzed tissue samples included liver, lung and tongue samples collected by hunters. DNA was isolated from these tissues and assessed by RT-PCR of the 18S rRNA and PCR of the COX1 genes for B. conradae. A total of 66 dogs and 38 coyotes were tested, and the results demonstrated the presence of B. conradae DNA in 21 dogs (31.8%) and 4 coyotes (10.5%). These results indicate that B. conradae is present in the dog and coyote population from the same area and that direct contact with coyotes may increase the risk of infection in dogs. Further studies are required to test possible modes of transmission, including direct bite, tick or vertical transmission.
Effect of Single-Residue Mutations on CTCF Binding to DNA: Insights from Molecular Dynamics Simulations

In humans and other eukaryotes, DNA is condensed into chromatin fibers that are further wound into chromosomes. This organization allows regulatory elements in the genome, often distant from each other in the linear DNA, to interact and facilitate gene expression through regions known as topologically associating domains (TADs). CCCTC–binding factor (CTCF) is one of the major components of TAD formation and is responsible for recruiting a partner protein, cohesin, to perform loop extrusion and facilitate proper gene expression within TADs. Because single-residue CTCF mutations have been linked to the development of a variety of cancers in humans, we aim to better understand how these mutations affect the CTCF structure and its interaction with DNA. To this end, we compare all-atom molecular dynamics simulations of a wildtype CTCF–DNA complex to those of eight different cancer-linked CTCF mutant sequences. We find that most mutants have lower binding energies compared to the wildtype protein, leading to the formation of less stable complexes. Depending on the type and position of the mutation, this loss of stability can be attributed to major changes in the electrostatic potential, loss of hydrogen bonds between the CTCF and DNA, and/or destabilization of specific zinc fingers. Interestingly, certain mutations in specific fingers can affect the interaction with the DNA of other fingers, explaining why mere single mutations can impair CTCF function. Overall, these results shed mechanistic insights into experimental observations and further underscore CTCF’s importance in the regulation of chromatin architecture and gene expression.
Citizen Science and Natural Resource Management: A Social Network Analysis of Two Community-Based Water Monitoring Programs

Abstract In natural resource management contexts, citizen science programs often involve a diversity of actors collaborating in broad social networks. However, the characteristics and functioning of these networks has received limited attention. In this article, we demonstrate the benefits of applying social network research to citizen science practice. Through a mixed methods approach, we compare data sharing and collaboration networks of two community-based water monitoring programs in Australia. The quantitative component revealed that despite similarities in actor diversity and activities, both programs have created divergent network structures (centralized vs decentralized) corresponding to their scale of influence in environmental decision-making (regional vs local impacts). The qualitative component showed how individuals navigated their relationships and managed key tensions inherent to network functioning. This study provides new insights on the role of social networks in citizen science and concludes by recommending program leaders adopt a “networking mindset” to maximize their sphere of influence.
NUMERICAL SOLUTION OF FRACTIONAL VOLTERRA INTEGRO-DIFFERENTIAL EQUATIONS VIA THE RATIONALIZED HAAR FUNCTIONS

In this paper rationalized Haar (RH) functions method is applied to approximate the numerical solution of the fractional Volterra integro-differential equations (FVIDEs). The fractional derivatives are described in Caputo sense. The properties of RH functions are presented, and the operational matrix of the fractional integration together with the product operational matrix is used to reduce the computation of FVIDEs into a system of algebraic equations. By using this technique for solving FVIDEs computation time is low. Numerical examples are given to demonstrate application of the presented method with RH functions base.
Sequential test and parameter estimation for array processing of seismic data

We present a sequential test and parameter estimation technique for measured seismic data from the GERESS array situated in Germany. A new approximation of the test statistic distribution and the test threshold is proposed. The sequentially rejecting Bonferroni-Holm test guarantees a global test level. This allows one to avoid the computationally expensive bootstrap method and leads to a simpler algorithm. Approximate conditional maximum likelihood estimates in the frequency domain are used to overcome the resolution limits of conventional methods for wideband signal processing and to construct the sequential test. The combination of global optimization via genetic algorithm and a local one using the scoring seems to be a good compromise to handle the problem of cumbersome maximization of the log-likelihood function over the parameters of interest. The algorithm for testing the number of signal phases is applied simultaneously with the estimation of the model parameters.
Shifting the struggle inward: Mainstream debate on digital grassroots feminism in China

ABSTRACT This research suggests that the legitimacy of Chinese feminist public opinion is reflected in mainstream digital grassroots feminism. The authors investigate the use of feminist discourse in the Chinese Internet with the aim of highlighting and focusing current discussions among grassroots feminists in China. This research reveals that mainstream debates revolve around radical and conservative feminism. We propose that there is an emerging radical force in the mainstream debate, which is conceptualized as “new feminist activism. ” It tries to separate itself from national and sexual politics, and has evolved from western radical feminism, separatist feminism, and socialist feminism in China. In addition, new feminist activism is labeled as extreme feminism and pseudo-feminism and is not only criticized by conservatives such as liberal feminists and socialist feminists but is also ruled by the state for ideological control. Appropriation of feminist discourses by grassroots feminists have led to positions of different groups splitting, and there is an intense internal fight for power over discourse. In general, digital feminism in China is characterized by a focus on the private sphere, de-political, and indirect confrontation.
Numerical analysis of a dielectric rod antenna - demonstration of the discontinuity-radiation concept

A technique combining the finite-difference time-domain method and the imaginary-distance beam-propagation method is used to demonstrate the discontinuity-radiation concept for a dielectric rod antenna. The field near the rod is decomposed into a guided and an unguided wave. Using the two waves, the feed and terminal patterns are evaluated. It is numerically revealed that superposing the two patterns forms the radiation field of the antenna. The decomposition technique enables us to efficiently evaluate the directivity of a long rod antenna.
An infrared study of hot dust in quasars using prism spectrophotometry

Low-resolution near-infrared spectra were obtained for 14 quasars with redshift z<0.3. The observed continua from 0.95 to 2.5 μm were reproduced remarkably well with a combination of two radiation components, i.e., the power law and the blackbody radiation which are, respectively, dominated at shorter than ∼1.2 μm and longer than ∼1.5 μm. The longer part of the spectra fit a single-temperature blackbody of 1470±90 K which is attributable to the thermal emission from hot dust grains heated by the central power source. The flux ratio of the blackbody of the power-law component ranges by a factor of 6. It was found that an IRAS color selected sample tended to have a larger flux ratio as compared to non-IRAS quasars
Fermi-liquid versus non-Fermi-liquid behaviour

Abstract The current understanding of the theory of quantum liquids is presented. The properties of the three- and one-dimensional conductors are compared. A comprehensive description of the bosonization technique is presented for the one-dimensional systems. The two-dimensional systems are also analysed, and the theoretical and experimental results for this case are briefly presented.
Compile runtime system technology for airborne high-performance heterogeneous computing

Most tasks in airborne scenarios are composed of neural networks (NN) and non-NN tasks. On the one hand, Deep neural networks (DNNs) have become the mainstream method of AI task processing. DNNs are accompanied by a large number of complex tensor calculations, as well as network delays and data privacy risks caused by using the cloud to process data. The combination of dedicated AI hardware accelerators and edge computing has become a new solution. On the other hand, dedicated AI hardware accelerators cannot efficiently handle non-NN class tasks (such as signal processing, control flow, etc.), so onboard systems need to design new hardware, complete compiler stacks, and runtime systems to handle non-NN class tasks. In order to effectively deal with multiple tasks in the airborne environment, the airborne computing system needs to establish a set of unified compilation and runtime systems, which can optimize multiple tasks and be deployed on the heterogeneous computing platform to achieve "one compilation, multiple deployment. " This paper analyzes the development of compiler and runtime systems at home and abroad, and compares the advantages and disadvantages of different technologies. Finally, this paper discusses the application scenarios of the compilation system and runtime in the airborne environment and the technical directions that need to be breakthroughs in the future, so as to provide guidance for the development of the airborne intelligent compilation and runtime system.
Convergence to ends for random walks on the automorphism group of a tree

Let μ be a probability on a free group Γ of rank r ≥2. Assume that Supp(μ) is not contained in a cyclic subgroup of Γ. We show that if (X n )n≥0 is the right random walk on Γ determined by μ, then with probability 1, X n converges (in the natural sense) to an infinite reduced word. The space Ω of infinite reduced words carries a unique probability ν such that (Ω, ν) is a frontier of (Γ, μ) in the sense of Furstenberg. This result extends to the right random walk (X n ) determined by a probability μ on the group G of automorphisms of an arbitrary infinite locally finite tree T
Planar Hall effect bridge magnetic field sensors

Until now, the planar Hall effect has been studied in samples with cross-shaped Hall geometry. We demonstrate theoretically and experimentally that the planar Hall effect can be observed for an exchange-biased ferromagnetic material in a Wheatstone bridge topology and that the sensor signal can be significantly enhanced by a geometric factor. For the samples in the present study, we demonstrate an enhancement of the sensor output by a factor of about 100 compared to cross-shaped sensors. The presented construction opens a new design and application area of the planar Hall effect, which we term planar Hall effect bridge sensors.
High power GaAs∕AlGaAs lasers (λ∼850nm) with ultranarrow vertical beam divergence

The authors study 850nm GaAs∕AlGaAs longitudinal photonic band crystal lasers with a vertical far field divergence of 9° (full width at half maximum). Differential quantum efficiency of 95% is achieved at a cavity length of 500μm. A total optical output power from broad area multimode devices was up to 6.3W and a maximum continuous wave single mode power from narrow stripe devices was 270mW.
A High Gain Single Switch DC-DC Converter with Double Voltage Booster Switched Inductors

The research for novel power conversion topologies and the development of cutting-edge power component technologies are driven by the demand for renewable and much more efficient electricity generation, delivery, and con - version. Simulation and analysis high voltage gain DC-DC converter with double voltage booster switched inductor are analyzed in this paper. Multilevel boost converter topologies recently reintroduced, are gaining popularity as a solution for industrial and transportation power systems because they enable the use of innovative, efficient, but relatively low voltage low-voltage devices at greater voltage and power levels. there is only one power switch on the converter that is planned here, three diodes, two capacitors, and two inductors to achieve ultra-high gain with better efficiency. High voltage gain, minimal switch stress, and the ability to lessen input-current ripple and capacitor voltage ripple are all benefits of the topology. When it switches complementary, the capacitors’ ripple is reduced, which lowers the size requirement for the capacitors. A 12V, 500 watts prototype was analyzed, simulated and designed. at a duty cycle of 0.75 it is achieved high DC-DC gain i.e 19 and efficiency 93%. The practicality of the converter will be demonstrated by the close agreement between the analysis and simulation findings.