Miracle-dz/UniFAR-FTUs huggingface dataset:
Retrieval of phenological stages of onion fields during the first year of growth by means of C-band polarimetric SAR measurements

The phenological stages of onion fields in the first year of growth are estimated using polarimetric observables and single-polarization intensity channels. Experiments are undertaken on a time series of RADARSAT-2 C-band full-polarimetric synthetic aperture radar (SAR) images collected in 2009 over the Barrax region, Spain, where ground truth information about onion growth stages is provided by the European Space Agency (ESA)-funded agricultural bio/geophysical retrieval from frequent repeat pass SAR and optical imaging (AgriSAR) field campaign conducted in that area. The experimental results demonstrate that polarimetric entropy or copolar coherence when used jointly with the cross-polarized intensity allows unambiguously distinguishing three phenological intervals.
Stochastic Resonance in a Time-Delayed Bistable System Subjected to Dichotomous Noise and White Noise

Stochastic resonance in a time-delayed bistable system subjected to asymmetric dichotomous noise and multiplicative and additive white noise is investigated. We find that the signal-to-noise ratio is a non-monotonic function of the delayed times and of the amplitude of the driving square-wave signal, as well as of the asymmetry and correlation rate of the dichotomous noise. In addition, the SNR varies non-monotonically with the system parameters and the intensities of the multiplicative and additive noise.
Fluorescence and Absorption Spectra of the L -System in the Case of Raman Resonance

Analytic formulas are obtained that describe the fluorescence and absorption spectra of the Λ -sys- tem in the case of Raman resonance for unequal intensities of the fields and nonzero one-photon detuning in the rotating wave approximation in the limit of the saturating field. It is shown that, along with a group of Lorentzian lines, the spectra contain an alternating non-Lorentzian part caused by the quantum specificity of the dynamics of the Λ -system, which is of fundamental importance for an adequate explanation of important physical features, such as the decay of spectral line wings, the position of maxima of spectral lines, and the behavior of the absorption coefficient of a probe field near laser frequencies. The relation between theoretical models describing the stationary and nonstationary dynamics of formation of the response of individual atoms is considered, and the possibility of the universal use of the phenomenological stationary model is substantiated.
Will Digital Immortality Replace Religion?

ABSTRACT In this article, I show why the Christian faith, which is, among other things, a response to the need for life’s meaning and an anticipation of eternal life, will not become superfluous in case digital immortality is achieved. I also deepen a view that emerges from this debate, which is the view of both Christian religion and transhumanism as promises of happiness. I argue that they differ from each other in that Christian religion, unlike transhumanism, requires everybody to commit themselves to moral growth.
Fine structure of the pulsar decameter radiation as the probe of the propagation media

Pulsars radiate short pulsed signals (a typical period of an ordinary pulsar is about 1 s) that are good probes of propagation media. Propagation medium includes pulsar magnetosphere, interstellar medium (ISM), interplanetary medium (IPM) and the Earth's ionosphere, it has turbulent nature with variation of the electron density along the line-of-sight. During pulses propagation they are influenced by free electrons, irregularities of the electron concentration and magnetic field. It causes the propagation effects that are called frequency dispersion delay, scattering and the Faraday rotation respectively. At low frequencies all the propagation effects are most contrasted and this imposes restrictions on the pulsar observations in this frequency range. In fact, we are able to investigate only the nearest to the Earth pulsars with low dispersion measures (DM, describes amount of free electrons on the line of sight). Fortunately, at low frequency about 1 – 2 % of all pulsar pulses are ten or hundred times more intensive than average pulses. This phenomenon is called the pulsar anomalously intense pulses (AIP) [1] and gives opportunities to study fine structures of pulsar individual pulses at these frequencies. Fine structure of the pulsar radiation is short pulses inside the main pulse, it was detected by Hankins [2]. Characteristic time scale of the fine structure is frequency dependent, at decameters it is the widest, in the paper [3] authors detected the fine structure of pulsar B0809+74 with time-scale 2 – 4 ms, using radio telescope UTR-2.
The Impact of Antenna Array Calibration Errors on MIMO and Multi-Channel Synthetic Aperture Radar Imaging

In radar imaging, any lateral resolution is either attained using antenna arrays or by synthetic aperture radar (SAR) principles. Recently, the combination of both approaches to a multi-channel SAR (MCSAR) has gained increased attention. However, antenna arrays are impaired by unknown calibration errors, particularly phase errors, amplification deviations, mutual coupling, and phase center position deviation of the antenna element. Since, first, established calibration procedures are often non-ideal and, second, the calibration parameters usually vary over time due to aging and changes in temperature, calibration errors distort the measurements during the radar operation. Therefore, current research focuses on finding new practical calibration procedures. However, hardly any research has been conducted to analyze the basic effects which erroneous calibration parameters have on the reconstructed image in MCSAR or MIMO radar. In this work, we analyze the effects of multiple calibration error types on MCSAR and MIMO radar imaging. Both measurement principles lead to periodic error patterns, resulting in deterministic distortions. The derived relations can be used to precisely predict the position and number of ghost targets caused by calibration errors for known measurement setups and targets. For this, no information about the actual calibration errors is required. Furthermore, worst-case distortion levels are provided for different bounded errors allowing rough estimates of the impact of different error types on the image's distortion level. The findings are validated via measurements using a 76$\,$GHz FMCW MIMO radar.
Gibbs Fields with Multiple Pairwise Pixel Interactions for Texture Simulation and Segmentation

Modelling of spatially homogeneous and piecewise-homogeneous image textures by novel Markov and non-Markov Gibbs random fields with multiple pairwise pixel interactions is briefly overviewed. These models allow for learning both the structure and strengths (Gibbs potentials) of the interactions from a given training sample. The learning is based on first analytic and then stochastic approximation of the maximum likelihood estimates (MLE) of the potentials. A novel learning approach, giving explicit, to scaling factors, estimates of the potentials, is outlined. It exploits the conditional MLE provided that the training sample may rank a feasible top place within the parent population in its total Gibbs energy. The models embed both simulation and segmentation of the grayscale piecewise-homogeneous textures into the same Bayesian framework exploiting a controllable simulated annealing to generate the desired texture or its region map. Experimental results in simulating and segmenting various natural textures are presented and discussed.
Pansharpening Model of Transferable Remote Sensing Images Based on Feature Fusion and Attention Modules

The purpose of the panchromatic sharpening of remote sensing images is to generate high-resolution multispectral images through software technology without increasing economic expenditure. The specific method is to fuse the spatial information of a high-resolution panchromatic image and the spectral information of a low-resolution multispectral image. This work proposes a novel model for generating high-quality multispectral images. This model uses the feature domain of the convolution neural network to fuse multispectral and panchromatic images so that the fused images can generate new features so that the final fused features can restore clear images. Because of the unique feature extraction ability of convolution neural networks, we use the core idea of convolution neural networks to extract global features. To extract the complementary features of the input image at a deeper level, we first designed two subnetworks with the same structure but different weights, and then used single-channel attention to optimize the fused features to improve the final fusion performance. We select the public data set widely used in this field to verify the validity of the model. The experimental results on the GaoFen-2 and SPOT6 data sets show that this method has a better effect in fusing multi-spectral and panchromatic images. Compared with the classical and the latest methods in this field, our model fusion obtained panchromatic sharpened images from both quantitative and qualitative analysis has achieved better results. In addition, to verify the transferability and generalization of our proposed model, we directly apply it to multispectral image sharpening, such as hyperspectral image sharpening. Experiments and tests have been carried out on Pavia Center and Botswana public hyperspectral data sets, and the results show that the model has also achieved good performance in hyperspectral data sets.
Alternative mRNA Splicing and Promising Therapies in Cancer

Cancer is among the leading causes of mortality worldwide. While considerable attention has been given to genetic and epigenetic sources of cancer-specific cellular activities, the role of alternative mRNA splicing has only recently received attention as a major contributor to cancer initiation and progression. The distribution of alternate mRNA splicing variants in cancer cells is different from their non-cancer counterparts, and cancer cells are more sensitive than non-cancer cells to drugs that target components of the splicing regulatory network. While many of the alternatively spliced mRNAs in cancer cells may represent “noise” from splicing dysregulation, certain recurring splicing variants have been shown to contribute to tumor progression. Some pathogenic splicing disruption events result from mutations in cis-acting splicing regulatory sequences in disease-associated genes, while others may result from shifts in balance among naturally occurring alternate splicing variants among mRNAs that participate in cell cycle progression and the regulation of apoptosis. This review provides examples of cancer-related alternate splicing events resulting from each step of mRNA processing and the promising therapies that may be used to address them.
On the validation, stability and control of certain biological systems

This thesis is concerned with the long-term behavior of certain mathematical models describing predator-prey interactions, virus propagation in vivo and integrated pest management strategies. Of interest are the stability and impulsive controllability of such models, since the corresponding mathematical findings are then easily interpretable in terms of biological concepts with major relevance such as disease endemicity, species extinction or permanence and pest eradication. Threshold conditions for the global stability of the equilibria are obtained by means of Lyapunov’s direct method combined with LaSalle invariance principle. These results, stated in terms of a biologically significant key parameter called the basic reproduction number, are then reconfirmed by using monotonicity methods. The models of concern are formulated in a general way, no specialization being made, for instance, on the incidence rate of the infection and on the removal rate of the virus (for the virus model) or on the functional response of the predator (for the predator-prey model). This makes the findings are applicable to a large class of real-life interactions. Also, threshold conditions with immediate biological significance which guarantee the global success of integrated pest management strategies are derived using Floquet theory. The corresponding impulsive controllability results are then obtained by using comparison arguments. Also, a bifurcation analysis is performed via an operator theoretic approach and some situations leading to a chaotic behavior of the solutions are investigated by means of numerical simulations.
Gain stability improvement of a wideband antenna using an artificial magnetic conductor

In this paper, a novel artificial magnetic conductor (AMC) reflector is proposed for gain stability enhancement of a low‐profile wideband bowtie antenna (operates at C‐band). Two AMC reflectors are investigated: the first one is based on a standard square patch cell while the second one is based on a novel cell geometry called modified cross shape (MCS). The two units' cell geometries are studied and optimized to achieve the desirable performances, namely; low‐profile, wide impedance bandwidth, and gain stability. The proposed antenna structure with 5 × 8 MCS unit cells is fabricated and measured. The results show a significant steady gain compared to similar work in the literature. The fabricated structure presents a low thickness of 0.084 λL (λL is the guided wavelength at the lowest frequency, i.e., 3.94 GHz) with 0.85 dB of gain variation over a wide impedance bandwidth of about 50% (3.94–6.61 GHz).
A NEW IMAGE ENCRYPTION METHOD BASED ON A 6D HYPERCHAOTIC MAP AND GENETIC OPERATORS

This paper presents a novel and secure image encryption method. The plain image’s pixels are confused using the N-point crossover operation of genetic algorithms. Randomly paired rows and columns are determined by the two state variables of a six-dimensional hyperchaotic map. The number of crossover points, which are calculated by the two other state variables of the hyperchaotic map, differ from each other for each row or column pair. The crossover positions are specified according to the number of crossover points with the help of the last two state variables. The proposed algorithm generates the diffusion stage’s encryption key using the SHA-256 hash value of the plain image. Mutation and crossover operators are implemented using the 16-bit subblocks of the 256-bit hash value. The scrambled image’s pixels are altered with the generated encryption key and previously encrypted pixels. Keyspace and sensitivity, histogram, correlation, information entropy, differential, data loss, noise attack, and computational time analyzes are performed to test the safety and effectiveness of the encryption method. The experiments and simulation results show that the proposed encryption technique is highly secure and efficient since it can resist various attacks.
Spatial Distribution of Drug-Resistant Mycobacterium tuberculosis Infections in Rural Eastern Cape Province of South Africa

Tuberculosis (TB), an infectious airborne disease caused by Mycobacterium tuberculosis (Mtb), is a serious public health threat reported as the leading cause of morbidity and mortality worldwide. South Africa is a high-TB-burden country with TB being the highest infectious disease killer. This study investigated the distribution of Mtb mutations and spoligotypes in rural Eastern Cape Province. The Mtb isolates included were 1157 from DR-TB patients and analysed by LPA followed by spoligotyping of 441 isolates. The distribution of mutations and spoligotypes was done by spatial analysis. The rpoB gene had the highest number of mutations. The distribution of rpoB and katG mutations was more prevalent in four healthcare facilities, inhA mutations were more prevalent in three healthcare facilities, and heteroresistant isolates were more prevalent in five healthcare facilities. The Mtb was genetically diverse with Beijing more prevalent and largely distributed. Spatial analysis and mapping of gene mutations and spoligotypes revealed a better picture of distribution.
A Robust Zero-watermarking Scheme for Image Based on Block Compressive Sensing and Arnold Transformation ⋆

A zero-watermarking scheme based on block compressive sensing and Arnold transformation is proposed. The proposed scheme uses important features of original image and the meaningful copyright information to construct zero watermark. The original image is divided into several sub-blocks according to the copyright information. Each sub-block is observed in accordance with the compressive sensing. Meanwhile, Arnold transform is applied to preprocess the binarization copyright information. The above observations should be normalized then. Finally, this scheme generates the zero watermark via performing a logical operation, an exclusive-or (XOR) operation, on the normalized observations and the preprocessed copyright information. Experimental results demonstrate that this scheme not only possesses the robust ability to resist on image-manipulation attacks under consideration but also, in average, is superior to other existing methods being considered in the paper. Also, The acquired zero watermark has good discrimination. The proposed scheme has the characteristic of low computational complexity.
Human Face-shaped Planar Antenna for 5G sub-6 GHz Application

This paper presents a planar antenna for the fifth generation (5G) sub-6 GHz communication application. The layout of the proposed antenna consists of a human face-shaped radiating element and defected ground, and is fed by a microstrip line. The simulation and measured results confirmed the radiation element matched correctly with the ground, which helped the antenna to work over 3.25 to 5.05 GHz (43.4%). The antenna also has moderate gain, good efficiency, and revealed symmetric radiation behavior, making it a potential contender for 5G wireless communication.
TPIPD: A Robust Model for Online VPN Traffic Classification

VPN has posed many difficulties for network security management. In this paper, we develop a robust method to classify the VPN traffic. Firstly, we investigate the VPN transmission process and find the turning packet interval (Named as TPI) is a valuable feature for VPN traffic classification. Then we employ the probability distribution of TPI to improve the robustness of classification process, which is named as TPIPD. Secondly, we evaluate our method using the ISCXVPN2016 dataset and find our method has higher classification accuracy compared with other related methods. We also find the distribution of the first few TPIs can be used to represent that of the entire TPIs of specific flow, thus our method can be used for online traffic classification. As TPIPD is a kind of probability feature, it is more robust than other traditional features. Finally, the experiments verify our methods can be used for mice flow identification.
Design of A Quadrature Signal Generator with Filtering Response Using Stub-Loaded Resonators

This paper presents a new filtering quadrature signal generator, which can realize the conversion from single-ended signal to four quadrature signals with filtering response. Two different coupled-line topologies, i.e., parallel coupled-line and anti-parallel coupled-line with short-circuited end are discussed to achieve the desired 90° phase difference. Moreover, with resorting to the electric field distribution of a $\lambda$/2 open-circuited transmission line, the inherent out-of-phase characteristic can be obtained. Based on the above discussion, a four-way quadrature signal generator with filtering response can then be realized using coupled stub-loaded resonators. Measured results show that the designed four-way filtering quadrature signal generator operates at 2.0 GHz with 0.5 dB magnitude imbalance and $90 \pm 5^{\circ}$ phase difference.
Bearing-only Tracking Using Bank of MAP Estimators

Nonlinear estimation problems, such as bearing-only tracking, are often addressed using linearized estimators (e.g., the extended Kalman filter (EKF)). The resulting linearization errors of these estimators as well as their inability to track multimodal probability density functions (pdfs) greatly diminish their performance. To address these issues, we employ relinearization provided by the batch maximum a posteriori (MAP) estimator to reduce linearization errors, and introduce a general estimation framework (a bank of MAP estimators) to track multiple modes of the posterior pdf. The key idea of this approach is to convert the nonlinear cost function into polynomial form and then to analytically compute all its stationary points for the current time step. Using the local minima as the most probable hypotheses of the state trajectory effectively focuses available computational resources. In addition, we employ pruning and marginalization to control the computational cost. Monte Carlo simulations and real-world experiments show that the proposed approach significantly outperforms the EKF, the standard batch MAP estimator, and the particle filter (PF), in terms of accuracy and consistency.
Together we will rise? Perceptions of instrumentality and normalization as motivations for joint collective action among the disadvantaged

The current research examines joint collective action between advantaged and disadvantaged groups, from the perspective of the latter. We hypothesize that joint action poses a dilemma which lies in the tension between perceived instrumentality of joint action (i.e., ability to promote the disadvantaged’s goals) and perceived normalization (i.e., its tendency to blur power relations). We test this idea across three studies in the United States and Israel/Palestine. In Study 1 ( n = 361) we manipulated perceptions of joint action from the perspective of a hypothetical character, and in Study 2 ( n = 378) we presented participants with an article highlighting the risk and benefit of joint activism. Results showed that perceived instrumentality increases, whereas perceived normalization decreases joint action tendencies. In Study 3 ( n = 240), we described a joint action event that taps into some of the themes that induce concerns about normalization. We found that normalization perceptions feed into perceptions of instrumentality, and this occurred mainly among high identifiers, for whom the dilemma is most salient. The implications of these findings for understanding the complexity of joint collective action from the perspective of the disadvantaged are discussed.
Aligned multi-walled carbon nanotube-reinforced composites: processing and mechanical characterization

Carbon nanotubes have been the subject of considerable attention because of their exceptional physical and mechanical properties. These properties observed at the nanoscale have motivated researchers to utilize carbon nanotubes as reinforcement in composite materials. In this research, a micro-scale twin-screw extruder was used to achieve dispersion of multi-walled carbon nanotubes in a polystyrene matrix. Highly aligned nanocomposite films were produced by extruding the polymer melt through a rectangular die and drawing the film prior to cooling. Randomly oriented nanocomposites were produced by achieving dispersion first with the twin-screw extruder followed by pressing a film using a hydraulic press. The tensile behaviour of the aligned and random nanocomposite films with 5 wt. % loading of nanotubes were characterized. Addition of nanotubes increased the tensile modulus, yield strength and ultimate strengths of the polymer films, and the improvement in elastic modulus with the aligned nanotube composite is five times greater than the improvement for the randomly oriented composite.