Search Results (154)

Three-dimensional (3D) computational fluid dynamic (CFD) simulations have been performed to investigate the complex flow features and stripping of fluid materials from a cylindrical water drop at the late-stage in a Shock Liquid Drop Interaction (SLDI) process when the drop’s downstream end experiences compression after it is impacted by a supersonic shock wave ($Ma$ = 1.47). The drop trajectory/breakup has been simulated using a Lagrangian model and the unsteady Reynolds-averaged Navier–Stokes (URANS) approach has been employed for simulating the ambient airflow. The Kelvin–Helmholtz Rayleigh–Taylor (KHRT) breakup model has been used to capture the liquid drop fragmentation process and a coupled level-set volume of fluid (CLSVOF) method has been applied to investigate the topological transformations at the air/water interface. The predicted changes of the drop length/width/area with time have been compared against experimental measurements, and a very good agreement has been obtained. The complex flow features and the qualitative characteristics of the material stripping process in the compression phase, as well as disintegration and flattening of the drop are analyzed via comprehensive flow visualization. Characteristics of the drop distortion and fragmentation in the stripping breakup mode, and the development of turbulence at the later stage of the shock drop interaction process are also examined. Finally, this study investigated the effect of increasing $Ma$ on the breakup of a water drop by shear stripping. The results show that the shed fluid materials and micro-drops are spread over a narrower distribution as $Ma$ increases. It illustrates that the flattened area bounded by the downstream separation points experienced less compression, and the liquid sheet suffered a slower growth. Full article

Object detection is a mature problem in autonomous driving, with pedestrian detection being one of the first commercially deployed algorithms. It has been extensively studied in the literature. However, object detection is relatively less explored for fisheye cameras used for surround-view near-field sensing. The standard bounding-box representation fails in fisheye cameras due to heavy radial distortion, particularly in the periphery. In this paper, a generic object detection framework is implemented using the base YOLO (You Only Look Once) detector to systematically explore various object representations using the public WoodScape dataset. First, we implement basic representations, namely the standard bounding box, the oriented bounding box, and the ellipse. Secondly, we implement a generic polygon and propose a novel curvature-adaptive polygon, which obtains an improvement of 3 mAP (mean average precision) points. A polygon is expensive to annotate and complex to use in downstream tasks; thus, it is not practical to use it in real-world applications. However, we utilize it to demonstrate that the accuracy gap between the polygon and the bounding box representation is very high due to strong distortion in fisheye cameras. This motivates the design of a distortion-aware optimal representation of the bounding box for fisheye images, which tend to be banana-shaped near the periphery. We derive a novel representation called a curved box and improve it further by leveraging vanishing-point constraints. The proposed curved box representations outperform the bounding box by 3 mAP points and the oriented bounding box by 1.6 mAP points. In addition, the camera geometry tensor is formulated to provide adaptation to non-linear fisheye camera distortion characteristics and improves the performance further by 1.4 mAP points. Full article

In the first part of this paper, we introduce the marine copepod Calanus finmarchicus, its lifecycle and ecology, and describe the technologies developed for harvesting and extracting oil from this copepod. Calanus oil has a unique composition, with its fatty acids—including a high concentration of long-chain omega-3 polyunsaturated fatty acids (PUFAs) and monounsaturated fatty acids (MUFAs)—bound to long chain fatty alcohols in the form of wax esters. In the second part of this paper, we review pre-clinical and clinical studies conducted over the last two decades, which demonstrate the potential health benefits of Calanus oil. These studies highlight its role in preventing obesity-related metabolic distortions, such as inflammation and reduced insulin sensitivity. Full article

This article presents a Synthetic-Aperture Distributed Phased Array (SADPA) framework to address emitter localization challenges in dynamic environments. Building on Distributed Synthetic-Aperture Radar (DSAR) principles, SADPA integrates distributed phased arrays with motion-induced phase compensation, enabling coherent aperture synthesis beyond physical array limits. By analytically modeling and compensating nonlinear phase variations caused by platform motion, we resolve critical barriers to signal integration while extending synthetic apertures. An improved MUSIC algorithm jointly estimates emitter positions and phase distortions, overcoming parameter coupling inherent in moving systems. To quantify fundamental performance limits, the Cramer–Rao bound (CRB) is derived as a theoretical benchmark. Numerical simulations demonstrate the SADPA framework’s superior performance in multi-source resolution and positioning accuracy; it achieves 0.012 m resolution at 10 GHz for emitters spaced 0.01 m apart. The system maintains consistent coherent gain exceeding 30 dB across both the 1.5 GHz communication and 10 GHz radar bands. Monte Carlo simulations further reveal that the MUSIC-DPD algorithm within the SADPA framework attains minimum positioning error (RMSE), with experimental results closely approaching the theoretical CRB. Full article

Harmonic functions are renowned for their application in the analysis of minimal surfaces. These functions are also very important in applied mathematics. Any harmonic function in the open unit disk $\mathbb{U}=\left\{z\in \mathbb{C}:\left|z\right|<1\right\}$ can be written as a sum $f=h+\overline{g}$, where h and g are analytic functions in $\mathbb{U}$ and are called the analytic part and the co-analytic part of f, respectively. In this paper, the harmonic shear $f=h+\overline{g}\in S_{\mathcal{H}}$ and its rotation $f^{\mu }$ by $\mu \left(\mu \in \mathbb{C},\left|\mu \right|=1\right)$ are considered. Bounds are established for this rotation $f^{\mu }$, specific inequalities that define the Jacobian of $f^{\mu }$ are obtained, and the integral representation is determined. Full article

In this paper, a novel class of meromorphic functions associated with the Mittag–Leffler function $E_{\mu ,\vartheta }\left(z\right)$ is introduced using the Hilbert space operator. In the punctured symmetric domain ${⋓}^{\ast }$, essential properties of this class are systematically investigated. These properties include coefficient inequalities, growth and distortion bounds, as well as weighted and arithmetic mean estimates. Furthermore, the extreme points and radii of geometric properties such as close-to-convexity, starlikeness, and convexity are analyzed in detail. Additionally, the Hadamard product (or convolution) is explored to demonstrate the algebraic structure and stability of the introduced function class under this operation. Integral mean inequalities are also established to provide further insights into the behavior of these functions within the given domain. Full article

This paper introduces a new class of harmonic functions defined through a generalized symmetric q-differential that acts on both the analytic and co-analytic parts of the function. By combining concepts from symmetric q-calculus and geometric function theory, we develop a framework that extends several well-known operators as special cases. The main contributions of this study include new criteria for harmonic univalence, sharp coefficient bounds, distortion theorems, and covering results. Our operator offers increased flexibility in modeling symmetric structures, with potential applications in complex analysis, fractional calculus, and mathematical physics. To support these theoretical developments, we provide concrete examples and highlight potential directions for future research, including extensions to higher-dimensional settings. Full article

We report the synthesis and characterization of five novel metal complexes. Three of them are vanadium complexes with the general formula [VO(Lⁿ)₂], where Lⁿ are Schiff bases derived from the condensation of 2-carbaldehyde-8-hydroxyquinoline with either 4-(2-aminoethyl)morpholine (L¹), 3-morpholinopropylamine (L²) or 1-(2-aminoethyl)piperidine (L³). The two other metal complexes are [Ni(L¹)₂] and [Fe(L¹)₂]Cl. They were characterized by analytical, spectroscopic (Fourier transform infrared, UV-visible absorption), and mass spectrometric techniques as well as by single-crystal X-ray diffraction (for all [VO(Lⁿ)₂] complexes and [Ni(L¹)₂]). While, in the crystal structure, the V(IV)O complexes show distorted square–pyramidal geometry with the ligands bound as bidentate through quinolate NO donors, the Ni(II) complex shows octahedral geometry with two ligand molecules coordinated through NNO donors. Stability studies in aqueous media revealed that the vanadium complexes are not stable, undergoing oxidation to VO₂(L), which was corroborated by ⁵¹V NMR and MS. This behavior is also observed in organic media, though at a significantly slower rate. The Ni complex exhibited small spectral changes over time in aqueous media. Nonetheless, all compounds show enhanced stability in the presence of bovine serum albumin (BSA). Fluorescence studies carried out for the Ni(II) and Fe(III) complexes indicate reversible binding to albumin. The cytotoxicity of the L¹ metal complexes was assessed on melanoma (B16F10 and A375) and colon cancer (CT-26 and HCT-116) cell lines, with 5-fluorouracil (5-FU) as a reference drug. The V- and Ni complexes showed the lowest IC₅₀ values (<10 μM) in either A375 or HCT-116 cells after 48 h of incubation, while the Fe(III) complex presented minimal antiproliferative effects. The complexes were generally more cytotoxic to human than murine cancer cells. Synergistic in vitro studies with 5-FU revealed antagonism in most cases, except in A375 cells, where an additive effect was observed for the combination with the V-complex. Overall, these compounds show promising potential for cancer treatment, mostly for melanoma. Full article

Ship object detection in synthetic aperture radar (SAR) images is both an important and challenging task. Previous methods based on horizontal bounding boxes struggle to accurately locate densely packed ships oriented in arbitrary directions, due to variations in scale, aspect ratio, and orientation, thereby requiring other forms of object representation, like rotated bounding boxes (OBBs). However, most deep learning-based OBB detection methods share a single-stage paradigm to improve detection speed, often at the expense of accuracy. In this paper, we propose a simple yet effective two-stage detector dubbed ORPSD, which enjoys good accuracy and efficiency owing to two key designs. First, we design a novel encoding scheme based on outer-rectangle projection (ORP) for the OrpRPN stage, which could efficiently generate high-quality oriented proposals. Second, we propose a convex quadrilateral rectification (CQR) method to rectify distorted shape proposals into rectangles by finding the outer rectangle based on the minimum area, ensuring correct proposal orientation. Comparative experiments on the challenging public benchmarks RSSDD and RSAR demonstrate the superiority of our ORPDet over previous OBB-based detectors in terms of both detection accuracy and efficiency. Full article

A constrained version of Talagrand’s transportation inequality is established, which reveals an intrinsic connection between the Gaussian distortion-rate-perception functions with limited common randomness under the Kullback–Leibler divergence-based and squared Wasserstein-2 distance-based perception measures. This connection provides an organizational framework for assessing existing bounds on these functions. In particular, we show that the best-known bounds of Xie et al. are nonredundant when examined through this connection. Full article

The Carlson–Shaffer operator plays an important role in the geometric theory of analytic functions. It is associated with the hypergeometric function and the incomplete beta function. The Carlson–Shaffer operator generalizes various other linear operators, such as the Ruscheweyh derivative operator, the Bernardi–Libera–Livingston operator, and the Srivastava–Owa operator. Ideas in the theory of analytic functions are often symmetrically transferred to the theory of harmonic functions. By using the Carlson–Shaffer operator, we introduce a class of harmonic functions defined by weak subordination. Next, we give some necessary and sufficient coefficient conditions for the class of functions. Furthermore, we determine coefficient estimates, distortion bounds, extreme points, and radii of starlikeness and convexity for the defined class. Full article

This article reviews results from the literature illustrating the bottlenecks and tradeoffs of integrated sensing and communication (ISAC) through the lens of information theory, thus offering a distinct perspective compared to recent works that focus on signal processing, wireless communications, or other related overviews. Different models and scenarios are considered and compared. For example, scenarios where radar sensing is performed at the communication and radar transmitter (mono-static ISAC) and scenarios where the radar receiver differs from the radar transmitter (called bi-static radar). Similarly, we discuss ISAC bottlenecks and tradeoffs both in slowly-varying environments where the main sensing target is described by a single parameter and accordingly, sensing performance is described by detection error probabilities, as well as in fast-varying environments, where the sensing targets are described by vectors and thus vector-valued performance measures such as average distortions like mean-squared errors are used to determine sensing performances. This overview article further also considers limitations and opportunities in network ISAC environments, such as collaborative or interactive sensing, and the influence of secrecy and privacy requirements on ISAC systems, a line of research that has received growing interest over the last few years. For all these scenarios, we provide and discuss precise models and their limitations and provide either bounds or full characterizations of the fundamental information-theoretic performance limits of these systems. Further extensions as well as important open research directions are also discussed. Full article

This study presents an enhanced Faster R-CNN framework that incorporates elliptical bounding boxes to significantly improve building detection in off-nadir imagery, effectively reducing severe geometric distortions caused by oblique sensor angles. Off-nadir imagery enhances architectural detail capture and reduces occlusions, but conventional bounding boxes, such as axis-aligned and rotated bounding boxes, often fail to localize buildings distorted by extreme perspectives. We propose a hybrid method integrating elliptical bounding boxes for curved structures and rotated bounding boxes for tilted buildings, achieving more precise shape approximation. In addition, our model incorporates a squeeze-and-excitation mechanism to refine feature representation, suppress background noise, and enhance object boundary alignment, leading to superior detection accuracy. Experimental results on the BONAI dataset demonstrate that our approach achieves a detection rate of 91.96%, significantly outperforming axis-aligned bounding boxes (65.75%) and rotated bounding boxes (87.13%) in detecting irregular and distorted buildings. By providing a highly robust and adaptable detection strategy, our approach establishes a new standard for accurate and shape-aware building recognition in off-nadir imagery, significantly improving the detection of distorted, rotated, and irregular structures. Full article

We consider the problem of successive-refinement coding for lossy compression of individual sequences, namely, compression in two stages, where in the first stage, a coarse description at a relatively low rate is sent from the encoder to the decoder, and in the second stage, an additional coding rate is allocated in order to refine the description and thereby improve the reproduction. Our main result is in establishing outer bounds (converse theorems) for the rate region where we limit the encoders to be finite-state machines in the spirit of Ziv and Lempel’s 1978 model. The matching achievability scheme is conceptually straightforward. We also consider the more general multiple description coding problem on a similar footing and propose achievability schemes that are analogous to the well-known El Gamal–Cover and the Zhang–Berger achievability schemes of memoryless sources and additive distortion measures. Full article

Reversible data hiding typically relies on two main techniques: prediction-error expansion and histogram shifting. These techniques complement each other to facilitate effective data embedding by defining non-positive and non-negative thresholds, thereby reducing distortion. The goal is to minimize overflow and underflow pixels by constraining thresholds appropriately. Managing these pixels remains challenging as they must be mapped within the payload. While double modification testing can eliminate the location map for some images, it is highly complex and struggles with images near intensity limits. In this paper, we show that the non-positive and non-negative thresholds for each predicted value are bounded by their infimum and supremum. By restricting the thresholds to these bounds, we maximize the number of embeddable pixels while minimizing the location map size. Moreover, our approach enables the rapid determination of the first operating thresholds and the development of encoding and decoding formulas for RDH without modification. Performance comparisons with established algorithms demonstrate the advantages of our proposed method. Full article