Miracle-dz/UniFAR-FTUs huggingface dataset:
Object Detection in High-Resolution Panchromatic Images Using Deep Models and Spatial Template Matching

Automatic object detection from remote sensing images has attracted a significant attention due to its importance in both military and civilian fields. However, the low confidence of the candidates restricts the recognition of potential objects, and the unreasonable predicted boxes result in false positives (FPs). To address these issues, an accurate and fast object detection method called the refined single-shot multibox detector (RSSD) is proposed, consisting of a single-shot multibox detector (SSD), a refined network (RefinedNet), and a class-specific spatial template matching (STM) module. In the training stage, fed with augmented samples in diverse variation, the SSD can efficiently extract multiscale features for object classification and location. Meanwhile, RefinedNet is trained with cropped objects from the training set to further enhance the ability to distinguish each class of objects and the background. Class-specific spatial templates are also constructed from the statistics of objects of each class to provide reliable object templates. During the test phase, RefinedNet improves the confidence of potential objects from the predicted results of SSD and suppresses that of the background, which promotes the detection rate. Furthermore, several grotesque candidates are rejected by the well-designed class-specific spatial templates, thus reducing the false alarm rate. These three parts constitute a monolithic architecture, which contributes to the detection accuracy and maintains the speed. Experiments on high-resolution panchromatic (PAN) images of satellites GaoFen-2 and JiLin-1 demonstrate the effectiveness and efficiency of the proposed modules and the whole framework.
Real frequency tearing layers with parallel dynamics and the effect on error field locking and resistive wall modes

The response to tearing perturbations of a resonant layer within a toroidal plasma often includes real frequencies. These real frequencies are of importance not only for the stability of the tearing mode but also for determining the response to an error field, including locking torques, and the stability properties when interacting with a resistive wall. Unfortunately, including the physics which drives these frequencies can make the model highly complicated and mask the root physics mechanisms driving the response, making it difficult to draw connections between the physics mechanisms occurring in different regimes. In this paper, we present a simple and intuitive method to derive the tearing mode layer properties in various regimes of resistive MHD with the key physics effects of pressure gradient, toroidal field line curvature and parallel dynamics, focusing on two important regimes: The resistive-inertial (RI) and the viscoresistive (VR) regimes. The usual Glasser effect, a toroidal effect which involves real frequencies, has been discussed only in the context of the RI regime. We find that it occurs in the VR regime as well. Based on these results and the presence of real frequencies in many other tearing regimes, we reach the conclusion that real frequencies in tearing modes are the rule rather than the exception. We also find that the existence of tearing modes with real frequencies in the VR and RI regimes is related to nearby electrostatic resistive interchange modes, themselves with real frequencies. Another important effect we find is that the threshold for the destabilization of resistive wall tearing modes is significantly lowered by plasma rotation in the presence of real frequency layers.The response to tearing perturbations of a resonant layer within a toroidal plasma often includes real frequencies. These real frequencies are of importance not only for the stability of the tearing mode but also for determining the response to an error field, including locking torques, and the stability properties when interacting with a resistive wall. Unfortunately, including the physics which drives these frequencies can make the model highly complicated and mask the root physics mechanisms driving the response, making it difficult to draw connections between the physics mechanisms occurring in different regimes. In this paper, we present a simple and intuitive method to derive the tearing mode layer properties in various regimes of resistive MHD with the key physics effects of pressure gradient, toroidal field line curvature and parallel dynamics, focusing on two important regimes: The resistive-inertial (RI) and the viscoresistive (VR) regimes. The usual Glasser effect, a toroidal effect which invol.
Analytical Models for the Electromagnetic Scattering From Isolated Targets in Bistatic Configuration: Geometrical Optics Solution

In this article, we present a fully analytical model for the evaluation of the electromagnetic (EM) field scattered from a composite target in a generic bistatic configuration. The scenario comprises a rectangular parallelepiped target with smooth dielectric faces lying over a rough background surface, modeled as a stochastic process. The single- and multiple-bounce scattering contributions arising from the target, the rough background, and their interactions have been derived under the Kirchhoff approximation (KA)–geometrical optics (GO) solution. This framework enables the evaluation of the bistatic radar cross section (RCS) of the considered composite target via closed-form expressions. The proposed model exhibits good agreement with the literature results based on accurate and well-established numerical methods. Our analytical model is therefore proposed as a valid alternative to numerical techniques, being able to provide reliable results at a negligible computational burden. Finally, the role of the main scene parameters, i.e., target orientation, surface roughness, and polarization in the bistatic RCS of the target, have been analyzed and discussed.
Topology control and opportunistic routing in underwater sensor networks

Cerca de 2/3 da superficie do planeta Terra e coberta por oceanos. Estimasse que 95% do volume desses ambientes ainda permanece desconhecido. Nesse contexto, redes de sensores sem fio sub-aquaticas (RSSFAs) vem se mostrando como uma tecnologia viavel para o monitoramento e exploracao de ambientes aquaticos. Entretanto, esse tipo de rede apresenta baixo desempenho em termos de coleta de dados, latencia e consumo de energia, dada as caracteristicas da comunicacao acustica sub-aquatica. Neste trabalho, e proposto solucoes combinadas de controle de topologia e roteamento oportunistico para melhorar a coleta de dados e prolongar o tempo de vida de RSSFAs. Resultados de simulacao mostram que o desempenho de protocolos de roteamento oportunistico, essenciais em RSSFAs, e melhorado significativamente com o controle da topologia da rede, levando a um incremento da taxa de entrega dos dados e reducao do gasto de energia da rede.
BM3D-GT&AD: an improved BM3D denoising algorithm based on Gaussian threshold and angular distance

Block-matching and three-dimensional filtering (BM3D) is generally considered as a milestone for its outstanding performance in the area of image denoising. However, it still suffers from the loss of image detail due to the utilisation of hard thresholding on transform domain during the phase of the basic estimate. In the frequency domain, a large amount of image detail information is in high frequency, which tends to be mixed with noise. Since its low amplitude is below the threshold, some image detail is filtered out with the noise. To retain more details, this study proposes an improved BM3D. It adopts an adaptable threshold with the core of Gaussian function during hard thresholding, which can filter out more noise while retaining more high-frequency information. When grouping, the normalised angular distance is taken as a measure of similarity to relieve the interference of noise further and achieve a higher peak signal-to-noise ratio (PSNR). The experimental results show that under the background of Gaussian noise with standard deviation of 20-60, the PSNR of denoised images (with a large amount of detail), applied with the authors' improved algorithm, can be improved by 0.1 - 0.4dB compared with original BM3D.
Effects of cold atmospheric plasma irradiation on Arabidopsis seedlings

Cold (non-thermal) atmospheric pressure plasma generates heat, light and other stimulants including chemically or electrically active species. While plasma irradiation has been used for sterilization, other biological applications have been reported. In addition to killing bacteria and other cells, growth enhancement in plants has been documented. Arabidopsis is a model plant and its genome information was revealed many years ago. In this research, Arabidopsis seedlings were treated with plasma and its effects on seedling growth was observed. With plasma treatment, Arabidopsis seedlings of two different backgrounds, Columbia (Col) and Landsberg erectra (Ler), showed different resistance. Abnormal leaves without chlorophylls were found only among Col seedlings. Milder plasma irradiation resulted in a wider growth deviation compared with untreated seedlings: some seedlings showed retarded growth while others showed enhanced growth. For growth enhancement of plants, plasma irradiation on seedlings was not as effective as irradiation on seeds.
Two-fluid sources in F (T ) theory of gravity

We have investigated two-fluid cosmological models in [Formula: see text] theory of gravity. [Formula: see text] theory is an extension of teleparallel theory of gravity, where [Formula: see text] is the torsion scalar. In this paper, we formulated new idea about [Formula: see text] theory of gravity with the help of two fluids: one fluid is matter field modeling material content of the Universe and another fluid is radiation field modeling the cosmic microwave background. Some geometric aspects of the [Formula: see text] model are discussed with the help of MATLAB.
Ferroelectric behavior in vinylidene chloride copolymers

Abstract Ferroelectric behavior was observed in the crystalline copolymers of vinylidene chloride (VDC) with vinylchloride (VC) and with methylacrylate (MA). A D-E hysteresis loop for P(VDC/VC) copolymer observed at above its glass transition temperature indicates the ferroelectricity of this copolymer. The remanent polarization was between 30 and 122 mC/m2, and pyroelectric constants of the copolymers was stable up to almost their melting points. The results of FTIR and XRD suggested that the electric behaviors of P(VDC/VC) copolymers were caused by the orientation of C-Cl dipoles in VDC chains in the crystal region to form a polar structure in a high electric field.
Leader-following scaled consensus of second-order multi-agent systems under directed topologies

ABSTRACT This paper investigates the leader-following scaled consensus problem of second-order multi-agent systems under directed topologies. Three novel leader-following scaled consensus protocols are designed. First, a novel scaled consensus protocol is proposed. It can guarantee the velocity of each agent in one sub-group exactly follow that of a leader, and the follower agents achieve scaled consensus. Second, another proposed protocol enables the agents' positions and velocities of one sub-group accurately track those of a leader, and the follower agents achieve scaled consensus. Third, consider the case where the leader's states available to one or multiple followers and the leader travels with a varying velocity, a novel scaled consensus tracking protocol is proposed. Sufficient and necessary conditions are obtained to guarantee scaled consensus tracking for the three cases,respectively. Finally, simulation examples are made to verify the effectiveness of the theoretical results.
Magnetoelectric composite coupled by bonding material in energy trapping vibration for RF/microwave devices

In this work, the magnetoelectric (ME) coupling and electrical impedance of thickness extensional vibration mode in ME composite are investigated. The piezoelectric and magnetostrictive layers are adhered by epoxy, which acts as a central substrate layer, and the vibration is trapped by the electrodes located at the center of the piezoelectric material so as to generate energy trapping vibration mode. Parametric studies are performed to evaluate the influences of epoxy thickness and electrode dimensions on ME coupling and electrical impedance. It is found that the ME coupling increases to a peak value as the central epoxy thickness increases, and then it decreases because of the clamping effect. Therefore, an optimal thickness of the epoxy layer exits to achieve the maximum ME effect. In the converse ME effect, the electrical impedance decreases and then increases vs the thickness increase of the central substrate. In addition, the electrical impedance declines as the electrode radius increases. It is numerically demonstrated that good impedance matching can be achieved by properly design of the electrode dimensions.
Observer-Based Unknown Input Estimator of Wave Excitation Force for a Wave Energy Converter

Several energy maximization control approaches for point-absorber wave-energy converter (PAWEC) systems require knowledge of the wave excitation force (WEF) that is not measurable during the PAWEC operation. Many WEF estimators have been proposed based on stochastic PAWEC modeling using the Kalman filter (KF), extended KF (EKF), or receding-horizon estimation. Alternatively, a deterministic WEF estimator is proposed here based on the fast unknown input estimation (FUIE) concept. The WEF is estimated as an unknown input obviating the requirement to represent its dynamics. The proposed observer-based unknown input estimator (OBUIE) inherits the capability of estimating fast-changing signals from the FUIE, which is important when considering irregular wave conditions. Unlike preceding methods, the OBUIE is designed based on a PAWEC model, including the nonlinear viscous drag force. It has been shown that the nonlinear viscous drag force is essential for accurate PAWEC model description, within the energy maximization control role. The performance of the proposed estimator is evaluated in terms of PAWEC conversion efficiency in a single degree-of-freedom PAWEC device operating in regular and irregular waves. Simulation results are obtained using MATLAB to evaluate the estimator under different control methods and subject to parametric uncertainty.
PTU-058 Machine Learning Creates A Simple Endoscopic Classification System For Detecting Dysplasia In Barrett’s Oesophagus With I-scan Imaging And Opens The Way To Standardised Training And Assessment Of Competence

Introduction Barrett’s oesophagus (BE) is the pre-cursor for oesophageal adenocarcinoma. Endoscopic surveillance is performed to detect dysplasia in BE as it is likely to be amenable to curative treatment. Current surveillance relies on white-light endoscopy to obtain 4-quadrant biopsies through every 2cm of the BE segment. This samples less than 5% of the BE epithelium and is likely to miss dysplasia. A novel endoscopic image enhancement technology, i-Scan (PENTAX HOYA, Japan), has been developed to improve lesion recognition in the gastrointestinal tract (GIT). i-Scan uses post-processing light filtering to provide real-time analysis and enhancement of the mucosa and microvasculature. We evaluated the accuracy of i-Scan using a mucosal (M) and vascular (V) classification system for BE amongst 3 expert (consultant) endoscopists. Machine learning (ML) generates simple rules, known as a decision tree, to improve dysplasia detection and validate our classification system. To our knowledge, ML has never been applied for dysplasia detection in the GIT. Methods High definition video recordings were collected from patients with non-dysplastic (ND-BE) and dysplastic (D-BE) BE undergoing endoscopy at UCLH. A protocol was used to record areas of interest after which a matched biopsy was taken to confirm the histological diagnosis. In a blinded manner, videos were shown to 3 expert endoscopists who interpreted them based on their M and V patterns, presence of nodularity, ulceration and suspected diagnosis. Acetic acid (ACA) was used in some cases. Data was inputted into the WEKA package to construct a decision tree for dysplasia prediction. Results Videos from 47 patients (13 before and after ACA) were collected (24 ND-BE, 23 D-BE). Cases in which ACA was used, 7 had ND-BE and 6 D-BE. Experts’ average accuracy for dysplasia prediction was 72.2% (66.7–76.7%). ACA did not improve dysplasia detection. In 5 cases all 3 experts failed to detect D-BE. Using ML, the most important attribute was the lesions’ V pattern. If this was reported abnormal (irregular, dilated vessels) by more than one doctor, the lesion was D-BE (accuracy 79%). If D-BE was predicted despite the V pattern being reported abnormal by one or fewer experts, the lesion was still D-BE and vice versa. Conclusion Experts can diagnose D-BE in up to three-quarters of cases using i-Scan. ML can define rules learnt from expert opinion that predict dysplasia with a similar level of accuracy and are easier to learn than conventional classification systems. They could be used to train non-expert endoscopists in dysplasia detection and then used for blinded assessment of accuracy. Disclosure of Interest None Declared.
Chaos in a classical limit of the Sachdev-Ye-Kitaev model

We study chaos in a classical limit of the Sachdev-Ye-Kitaev (SYK) model obtained in a suitably defined large-S limit. The low-temperature Lyapunov exponent is found to depend linearly on temperature, with a slope that is parametrically different than in the quantum case: it is proportional to N/S. The classical dynamics can be understood as the rotation of an N-dimensional body with a random inertia tensor, corresponding to the random couplings of the SYK Hamiltonian. This allows us to find an extensive number of fixed points, corresponding to the body's principal axes of rotation. The thermodynamics is mapped to the p-spin model with p=2, which exhibits a spin glass phase at low temperature whose presence does not preclude the existence of chaos.
Static and dynamic output feedback stabilisation of descriptor fractional order systems

In this study, output feedback control is utilised to stabilise descriptor fractional order systems (FOS) with the fractional order belonging to and , respectively. Firstly, by the restricted equivalent transformations, a new necessary and sufficient condition of admissibility for descriptor FOS with is presented. Then, based on the methods of singular value decomposition, static and dynamic output feedback stabilisers of descriptor FOS with and are obtained, respectively. Finally, four numerical examples are provided to verify the effectiveness of the proposed approaches.
Bayesian modelling of marked point processes with incomplete records: volcanic eruptions

Modelling point processes with incomplete records is a challenging problem, especially when the degree of record completeness varies over time. For volcanic eruption records, we expect the degree of missingness to depend on both the time and the size of an eruption. We propose a time‐varying intensity function for a marked point process to model the non‐stationary variation of the observed point process caused by missing data. We apply this model to global and regional volcanic eruption records and use Bayesian inference to obtain hazard estimates and their uncertainties based on the observed incomplete records, to carry out residual analysis and to provide forecasts.
Multiscale second-order Poincar\'e inequalities in probability.

Consider an ergodic stationary random field $A$ on the ambient space $\mathbb R^d$. In a companion article, we introduced the notion of multiscale (first-order) functional inequalities, which extend standard functional inequalities like Poincar\'e, covariance, and logarithmic Sobolev inequalities in the probability space, while still ensuring strong concentration properties. We also developed a constructive approach to these functional inequalities, proving their validity for prototypical examples including Gaussian fields, Poisson random tessellations, and random sequential adsorption (RSA) models, which do not satisfy standard functional inequalities. In the present contribution, we turn to second-order Poincar\'e inequalities \`a la Chatterjee: while first-order inequalities quantify the distance to constants for nonlinear functions $Z(A)$ in terms of their local dependence on the random field $A$, second-order inequalities quantify their distance to normality. For the above-mentioned examples, we prove the validity of suitable multiscale second-order Poincar\'e inequalities. In particular, applied to RSA models, these functional inequalities allow to complete and improve previous results by Schreiber, Penrose, and Yukich on the jamming limit, and to propose and fully analyze a more efficient algorithm to approximate the latter.
Optimization and Simulation-Time Reduction of Adaptive Antenna Array Employing Schelkunoff Nulling Theory

In electronic warfare systems, the optimization of the adaptive antenna array’s parameters toward achieving a certain null or maximum at specific directions could consume a long time. This may be crucial especially when a quick reaction is required before the spatial situation changes. In this work, a novel technique based on the Schelkunoff theory of incorporating nulls into the array factor (AF) expression is presented. It is shown that by introducing these nulls in the AF, the number of unknown array coefficients to be optimized is reduced. Hence, the optimization processing time is considerably decreased compared to the conventional all parameters technique, without impairing other radiation pattern characteristics such as the beamwidth or the side lobe level.
Acquisition of Hyperspectral Data with Colloidal Quantum Dots

Hyperspectral sensors, combining the functions of photon detection with ultrahigh spectral resolution in a single device, have emerged as a new class of devices with significant potential for applications that rely on the input of optical information. Despite continued advancement, the widespread use of infrared hyperspectral sensors is still limited primarily due to the high cost associated with the growth and processing of epitaxial semiconductors, such as HgCdTe, InSb, and superlattices. Here, it is shown that colloidal quantum dots (CQDs) provide a promising route toward low‐cost, compact, and sensitive infrared hyperspectral sensors with tunable sensing ranges. In total, 64 narrowband channels with full‐width at half‐maxima down to ≈30 cm−1 can be realized by directly integrating CQDs sensors with a distributed Bragg mirror filter array. The results of high‐resolution spectra measurement with resolving power up to 180 and acquisition of a hyperspectral image cube in the short‐wave infrared range, benefitting from the fast (≈120 ns) and sensitive (>1010 Jones) performance of the CQDs sensors, are experimentally demonstrated.
Comparison of Stratified Primary Care Management for Low Back Pain with Current Best Practice (STarTBack): A Randomised Controlled Trial

Ziel Die Studie untersuchte, ob bei lumbalen Rückenschmerzen Physiotherapiemit Gliederung der Probanden in Subgruppen nach Risiko im Vergleich zu aktueller bewährter Vorgehensweise sowohl klinisch als auch wirtschaftlich einen erhöhten Nutzen zeigt. Dabei galt es in Bezug auf die Risikogruppen folgende Aussagen zu testen: ▶ Minimaler Therapieansatz bei Lowrisk-Patienten zeigt keine schlechteren klinischen Ergebnisse als gegenwärtige Therapie. ▶ Zuweisung zur Physiotherapie bei Medium-risk-Patienten zeigt bessere klinische Ergebnisse als gegenwärtige Therapie. ▶ Systematische Zuweisung zur Physiotherapie mit erweitertem psychologischen Ansatz bei High-risk-Patienten zeigt bessere klinische Ergebnisse als gegenwärtige Therapie.