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NGC 5128 (Centaurus A), the closest giant elliptical galaxy outside the Local Group to the Milky Way, is one of the brightest extragalactic radio sources. It is distinguished by a prominent dust lane and powerful jets, driven by a supermassive black hole at its core. Using previously identified long-period variable (LPV) stars from the literature, this study aims to reconstruct the star formation history (SFH) of two distinct regions in the halo of NGC 5128. These regions reveal remarkably similar SFHs, despite being located about 28 kpc apart on opposite sides of the galaxy's center. In Field 1, star formation rates (SFRs) show notable increases at approximately 800 Myr and 3.8 Gyr ago. Field 2 exhibits similar peaks at these times, along with an additional rise around 6.3 Gyr ago. The increase in SFR around 800 Myr ago is consistent with earlier research suggesting a merger event. Since no LPV catalog exists for the central region of NGC 5128, we focused our investigation on its outer regions, which has provided new insights into the complex evolutionary history of this cornerstone galaxy. The SFH traced by LPVs supports a scenario in which multiple events of nuclear activity have triggered episodic, jet-induced star formation., Comment: 6 pages, 4 figures, To be published in Communications of BAO (ComBAO) more...

Generating coherent optical frequency combs in micro-ring resonators with Kerr nonlinearity has remarkably advanced the fundamental understanding and applications of temporal dissipative solitons. However, the spectrum of such soliton combs is restricted to the conventional definition of combs as phase-locked, equidistant lines in frequency. Here, we introduce a new class of floquet topological soliton combs that emerge in two-dimensional arrays of strongly coupled resonators engineered using floquet topology. Specifically, we demonstrate novel incommensurate combs where the comb lines are not equidistant but remain phase-locked. These incommensurate combs are generated by self-organized, phase-locked floquet topological soliton molecules that circulate the edge of the array. We show that these floquet topological solitons are robust and they navigate around defects, allowing for agile tunability of the comb line spacing. Our results introduce a new paradigm in using floquet engineering to generate unconventional frequency combs beyond those achievable with single or weakly coupled resonators. more...

In the field of medical sciences, reliable detection and classification of brain tumors from images remains a formidable challenge due to the rarity of tumors within the population of patients. Therefore, the ability to detect tumors in anomaly scenarios is paramount for ensuring timely interventions and improved patient outcomes. This study addresses the issue by leveraging deep learning (DL) techniques to detect and classify brain tumors in challenging situations. The curated data set from the National Brain Mapping Lab (NBML) comprises 81 patients, including 30 Tumor cases and 51 Normal cases. The detection and classification pipelines are separated into two consecutive tasks. The detection phase involved comprehensive data analysis and pre-processing to modify the number of image samples and the number of patients of each class to anomaly distribution (9 Normal per 1 Tumor) to comply with real world scenarios. Next, in addition to common evaluation metrics for the testing, we employed a novel performance evaluation method called Patient to Patient (PTP), focusing on the realistic evaluation of the model. In the detection phase, we fine-tuned a YOLOv8n detection model to detect the tumor region. Subsequent testing and evaluation yielded competitive performance both in Common Evaluation Metrics and PTP metrics. Furthermore, using the Data Efficient Image Transformer (DeiT) module, we distilled a Vision Transformer (ViT) model from a fine-tuned ResNet152 as a teacher in the classification phase. This approach demonstrates promising strides in reliable tumor detection and classification, offering potential advancements in tumor diagnosis for real-world medical imaging scenarios., Comment: This work has been submitted to the Elsevier for possible publication more...

This paper presents a visual-inertial-based control strategy to address the task space control problem of robot manipulators. To this end, an observer-based hybrid controller is employed to control end-effector motion. In addition, a hybrid observer is introduced for a visual-inertial navigation system to close the control loop directly at the Cartesian space by estimating the end-effector pose. Accordingly, the robot tip is equipped with an inertial measurement unit (IMU) and a stereo camera to provide task-space feedback information for the proposed observer. It is demonstrated through the Lyapunov stability theorem that the resulting closed-loop system under the proposed observer-based controller is globally asymptotically stable. Besides this notable merit (global asymptotic stability), the proposed control method eliminates the need to compute inverse kinematics and increases trajectory tracking accuracy in task-space. The effectiveness and accuracy of the proposed control scheme are evaluated through computer simulations, where the proposed control structure is applied to a 6 degrees-of-freedom long-reach hydraulic robot manipulator. more...

This paper aims to address the open problem of designing a globally stable vision-based controller for robot manipulators. Accordingly, based on a hybrid mechanism, this paper proposes a novel task-space control law attained by taking the gradient of a potential function in SE(3). The key idea is to employ the Visual Simultaneous Localization and Mapping (VSLAM) algorithm to estimate a robot pose. The estimated robot pose is then used in the proposed hybrid controller as feedback information. Invoking Barbalats lemma and Lyapunov's stability theorem, it is guaranteed that the resulting closed-loop system is globally asymptotically stable, which is the main accomplishment of the proposed structure. Simulation studies are conducted on a six degrees of freedom (6-DOF) robot manipulator to demonstrate the effectiveness and validate the performance of the proposed VSLAM-based control scheme. more...

This paper examines the global convergence problem of SLAM algorithms, an issue that faces topological obstructions. This is because the state-space of attitude dynamics is defined on a non-contractible manifold: the special orthogonal group of order three SO(3). Therefore, this paper presents a novel, gradient-based hybrid observer to overcome these topological obstacles. The Lyapunov stability theorem is used to prove the globally asymptotic convergence of the proposed algorithm. Finally, comparative analyses of two simulations were conducted to evaluate the performance of the proposed scheme and to demonstrate the superiority of the proposed hybrid observer to a smooth observer., Comment: 7 pages, 8 figures, conference more...