Search Results (25)

Detecting defects in transmission line insulators is crucial to prevent power grid failures as power systems continue to expand. This study introduces YOL011n-SSA, an enhanced insulator defect detection technique method that addresses the challenges of effectively identifying flaws in complex environments. First, this study incorporates the StarNet network into the backbone of the model. By stacking multiple layers of star operations, the model reduces both parameter count and model size, improving its adaptability to real-time object detection tasks. Secondly, the SOPN feature pyramid network is introduced into the neck part of the model. By optimizing the multi-scale feature fusion of the richer information obtained after expanding the channel dimension, the detection efficiency for low-resolution images and small objects is improved. Then, the ADown module was adopted to improve the backbone and neck parts of the model. It effectively reduces parameter count and significantly lowers the computational cost by implementing downsampling operations between different layers of the feature map, thereby enhancing the practicality of the model. Meanwhile, by introducing the NWD to improve the evaluation index of the loss function, the detection model’s capability in assessing the similarities among various small-object defects is enhanced. Experimental results were obtained using an expanded dataset based on a public dataset, incorporating three types of insulator defects under complex environmental conditions. The results demonstrate that the YOLO11n-SSA algorithm achieved an mAP@0.5 of 0.919, an mAP@0.5:0.95 of 70.7%, a precision of 0.95, and a recall of 0.875, representing improvements of 3.9%, 5.5%, 2%, and 5.7%, respectively, when compared to the original YOLO1ln method. The detection time per image is 0.0134 s. Compared to other mainstream algorithms, the YOLO11n-SSA algorithm demonstrates superior detection accuracy and real-time performance. Full article

SQM-ISS is a detector that will search from the International Space Station for massive particles possibly present among the cosmic rays. Among them, we mention strange quark matter, Q-Balls, lumps of fermionic exotic compact stars, Primordial Black Holes, mirror matter, Fermi balls, etc. These compact, dense objects would be much heavier than normal nuclei, have velocities of galaxy-bound systems, and would be deeply penetrating. The detector is based on a stack of scintillator and piezoelectric elements which can provide information on both the charge state and mass, with the additional timing information allowing to determine the speed of the particle, searching for particles with velocities of the order of galactic rotation speed (v ≲ 250 km/s). In this work, we describe the apparatus and its observational capabilities. Full article

Background: The arterial input function (AIF) is vital for myocardial blood flow quantification in cardiac MRI to indicate the input time–concentration curve of a contrast agent. Inaccurate AIFs can significantly affect perfusion quantification. Purpose: When only saturated and biased AIFs are measured, this work investigates multiple ways of leveraging tissue curve information, including using AIF + tissue curves as inputs and optimizing the loss function for deep neural network training. Methods: Simulated data were generated using a 12-parameter AIF mathematical model for the AIF. Tissue curves were created from true AIFs combined with compartment-model parameters from a random distribution. Using Bloch simulations, a dictionary was constructed for a saturation-recovery 3D radial stack-of-stars sequence, accounting for deviations such as flip angle, T2* effects, and residual longitudinal magnetization after the saturation. A preliminary simulation study established the optimal tissue curve number using a bidirectional long short-term memory (Bi-LSTM) network with just AIF loss. Further optimization of the loss function involves comparing just AIF loss, AIF with compartment-model-based parameter loss, and AIF with compartment-model tissue loss. The optimized network was examined with both simulation and hybrid data, which included in vivo 3D stack-of-star datasets for testing. The AIF peak value accuracy and $k^{trans}$ results were assessed. Results: Increasing the number of tissue curves can be beneficial when added tissue curves can provide extra information. Using just the AIF loss outperforms the other two proposed losses, including adding either a compartment-model-based tissue loss or a compartment-model parameter loss to the AIF loss. With the simulated data, the Bi-LSTM network reduced the AIF peak error from −23.6 ± 24.4% of the AIF using the dictionary method to 0.2 ± 7.2% (AIF input only) and 0.3 ± 2.5% (AIF + ten tissue curve inputs) of the network AIF. The corresponding $k^{trans}$ error was reduced from −13.5 ± 8.8% to −0.6 ± 6.6% and 0.3 ± 2.1%. With the hybrid data (simulated data for training; in vivo data for testing), the AIF peak error was 15.0 ± 5.3% and the corresponding $k^{trans}$ error was 20.7 ± 11.6% for the AIF using the dictionary method. The hybrid data revealed that using the AIF + tissue inputs reduced errors, with peak error (1.3 ± 11.1%) and $k^{trans}$ error (−2.4 ± 6.7%). Conclusions: Integrating tissue curves with AIF curves into network inputs improves the precision of AI-driven AIF corrections. This result was seen both with simulated data and with applying the network trained only on simulated data to a limited in vivo test dataset. Full article

The market for electric vehicles (EVs) has been growing in popularity, and by 2027, it is predicted that the market valuation will reach $869 billion. To support the growth of EVs in public road safety, advances in battery safety research for EV application should achieve low-cost, lightweight, and high safety protection. In this research, the development of a lightweight, crashworthy battery protection system using an excellent energy absorption capability is carried out. The lightweight structure was developed by using metastructure constructions with an arrangement of repeated lattice cellular structures. Three metastructure configurations (bi-stable, star-shaped, double-U) with their geometrical variables (thickness, inner spacing, cell stack) and material types (stainless steel, aluminium, and carbon steel) were evaluated until the maximum Specific Energy Absorptions (SEA) value was attained. The Finite Element Method (FEM) is utilised to simulate the mechanics of impact and calculate the optimum SEA of the various designs using machine learning methodology. Latin Hypercube Sampling (LHS) was used to derive the design variation by dividing the variables into 100 samples. The machine learning optimisation method utilises the Artificial Neural Networks (ANN) and Non-dominated Sorting Genetic Algorithm-II (NSGA-II) to forecast the design that produces maximum SEA. The optimum control variables are star-shaped cells consisting of one vertical unit cell using aluminium material with a cross-section thickness of 2.9 mm. The optimum design increased the SEA by 5577% compared to the baseline design. The accuracy of the machine learning prediction is also verified using numerical simulation with a 2.83% error. Four different sandwich structure configurations are then constructed using the optimal geometry for prismatic battery protection subjected to ground impact loading conditions. An optimum configuration of $6\times 4\times 1$ core cells arrangement results in a maximum displacement of 7.33 mm for the prismatic battery in the ground impact simulation, which is still less than the deformation threshold for prismatic battery safety of 10.423 mm. It is shown that the lightweight metastructure is very efficient for prismatic battery protection subjected to ground impact loading conditions. Full article

Star image registration is the most important step in the application of astronomical image differencing, stacking, and mosaicking, which requires high robustness, accuracy, and real-time capability on the part of the algorithm. At present, there are no high-performance registration algorithms available in this field. In the present paper, we propose a star image registration algorithm that relies only on radial module features (RMF) and rotation angle features (RAF) while providing excellent robustness, high accuracy, and good real-time performance. The test results on a large amount of simulated and real data show that the comprehensive performance of the proposed algorithm is significantly better than the four classical baseline algorithms as judged by the presence of rotation, insufficient overlapping area, false stars, position deviation, magnitude deviation, and complex sky background, making it a more ideal star image registration algorithm than current alternatives. Full article

Structure and reversibility of cross-link junctions play pivotal roles in determining the nature of thermoreversible gelation and dynamic mechanical properties of the produced polymer networks. We attempt to theoretically explore new types of sol–gel transitions with mechanical sharpness by allowing cross-links to grow without upper bound. We consider thermoreversible gelation of the primary molecules R{A${}_f$} carrying the number f of low molecular weight functional groups (gelators) A. Gelators A are assumed to form supramolecular assemblies. Some examples are: telechelic polymers ($f=2$) carrying $\pi$–$\pi$ stacking benzene derivatives at their both ends, and trifunctional star molecules ($f=3$) bearing multiple hydrogen-bonding gelators. The sol–gel transition of the primary molecules becomes sharper with the cooperativity parameter of the stepwise linear growth of the cross-links. There is a polymerization transition (crossover without singularity) of the junctions in the postgel region after the gel point is passed. If the gelator A tends to form supramolecular rings competitively with linear chains, there is another phase transition in the deep postgel region where the average molecular weight of the rings becomes infinite (Bose–Einstein condensation of rings). As a typical example of binary cross-links where gelators A and B form mixed junctions, we specifically consider metal-coordinated binding of ligands A by metal ions B. Two types of multi-nuclear supramolecular complexes are studied: (i) linear stacking (ladder) of the sandwich A${}_2$B units, and (ii) linear train of egg-box A${}_4$B units. To find the strategy towards experimental realization of supramolecular cross-links, the average molecular weight, the gel fraction, the average length of the cross-link junctions are numerically calculated for all of these models as functions of the functionality f, the concentration of the solute molecules, and the temperature. Potential candidates for the realization of these new types of thermoreversible gelation are discussed. Full article

In 1T-TaS${}_{2-x}$Se${}_x$, the charge density wave (CDW) state features a star of David lattice that expands across layers as the system becomes commensurate upon cooling. The layers can also order along the c-axis, and different stacking orders have been proposed. Using neutron scattering on powder samples, we compared the stacking order previously observed in 1T-TaS${}_2$ when the system is doped with Se. While at low temperature, a 13c layer sequence stacking was observed in TaS${}_2$; this type of ordering was not evident with doping. Doping with Se results in a metallic state in which the Mott transition is suppressed, which may be linked to the absence of layer stacking. Full article

Nanosatellites have established their importance in low-Earth orbit (LEO), and it is common for student teams to build them for educational and technology demonstration purposes. The next challenge is the technology maturity for deep-space missions. The LEO serves as a relevant environment for maturing the spacecraft design. Here we present the ESTCube-2 mission, which will be launched onboard VEGA-C VV23. The satellite was developed as a technology demonstrator for the future deep-space mission by the Estonian Student Satellite Program. The ultimate vision of the program is to use the electric solar wind sail (E-sail) technology in an interplanetary environment to traverse the solar system using lightweight propulsion means. Additional experiments were added to demonstrate all necessary technologies to use the E-sail payload onboard ESTCube-3, the next nanospacecraft targeting the lunar orbit. The E-sail demonstration requires a high-angular velocity spin-up to deploy a tether, resulting in a need for a custom satellite bus. In addition, the satellite includes deep-space prototypes: deployable structures; compact avionics stack electronics (including side panels); star tracker; reaction wheels; and cold–gas propulsion. During the development, two additional payloads were added to the design of ESTCube-2, one for Earth observation of the Normalized Difference Vegetation Index and the other for corrosion testing in the space of thin-film materials. The ESTCube-2 satellite has been finished and tested in time for delivery to the launcher. Eventually, the project proved highly complex, making the team lower its ambitions and optimize the development of electronics, software, and mechanical structure. The ESTCube-2 team dealt with budgetary constraints, student management problems during a pandemic, and issues in the documentation approach. Beyond management techniques, the project required leadership that kept the team aware of the big picture and willing to finish a complex satellite platform. The paper discusses the ESTCube-2 design and its development, highlights the team’s main technical, management, and leadership issues, and presents suggestions for nanosatellite and nanospacecraft developers. Full article

This paper proposes a new adaptive controller for three-wheeled mobile robots (3WMRs) called the ABHSMC controller. This ABHSMC controller is developed through a cooperative approach, combining a backstepping controller and a Radial Basis Function (RBF) neural network-based Hierarchical Sliding Mode Controller (HSMC). Notably, the RBF neural network exhibits the remarkable capability to estimate both the uncertainty components of the model and systematically adapt its parameters, leading to enhanced output trajectory responses. A novel navigational model, constructed by the connection to the adaptive BHSMC controller, Timed Elastic Band (TEB) Local Planner, and A-star (A*) Global Planner, is called ABHSMC navigation stack, and it is applied to effectively solve the tracking issue and obstacle avoidance for the 3-Wheeled Mobile Robot (3WMR). The simulation results implemented in the Matlab/Simulink platform demonstrate that the 3WMRs can precisely follow the desired trajectory, even in the presence of disturbances and changes in model parameters. Furthermore, the controller’s reliability is endorsed on our constructed self-driving car model. The achieved experimental results indicate that the proposed navigational structure can effectively control the actual vehicle model to track the desired trajectory with a small enough error and avoid a sudden obstacle simultaneously. Full article

In the context of the Eu:CROPIS mission requirements, this paper aims to test and validate an intra-spacecraft wireless transmission carried between two SpW-to-UWB Wireless Interface Units (WIUs). The WIUs are designed to replace the on-board SpaceWire (SpW) connections of a spacecraft network. The novelty of this solution resides in prototyping and testing proprietary TRL6 WIUs for the implementation of both PDHU and CDHU units, which constitute a spacecraft network. The validation test scenarios employed in this paper were designed under the Eu:CROPIS mission system requirements as defined by the WiSAT-3 European Space Agency (ESA)-funded project. The SpW-to-UWB WIUs run a custom-built ISA100 over an IEEE 802.15.4 UWB PHY layer communication stack. The WIUs are evaluated based on four mission-specific performance test scenarios: (1) the link setup test, (2) the end-to-end delay test, (3) the maximum data rate test and (4) the housekeeping test. The validation test scenarios of the WIUs are carried out with the use of STAR-Dundee SpW-capable equipment. The test results demonstrate the reliability of the deployed SpW-to-UWB WIUs devices for UWB wireless communications carried out within a space shuttle. The SpW data were successfully transmitted across the intra-spacecraft wireless network in all experimental tests. The technology can be considered to be at the maturity level TRL6 (functionality demonstrated in relevant environment) for LEO missions. Full article

The extraordinary material graphene arrived in the fields of engineering and science to instigate a material revolution in 2004. Graphene has promptly risen as the super star due to its outstanding properties. Graphene is an allotrope of carbon and is made up of sp²-bonded carbon atoms placed in a two-dimensional honeycomb lattice. Graphite consists of stacked layers of graphene. Due to the distinctive structural features as well as excellent physico-chemical and electrical conductivity, graphene allows remarkable improvement in the performance of electrospun nanofibers (NFs), which results in the enhancement of promising applications in NF-based sensor and biomedical technologies. Electrospinning is an easy, economical, and versatile technology depending on electrostatic repulsion between the surface charges to generate fibers from the extensive list of polymeric and ceramic materials with diameters down to a few nanometers. NFs have emerged as important and attractive platform with outstanding properties for biosensing and biomedical applications, because of their excellent functional features, that include high porosity, high surface area to volume ratio, high catalytic and charge transfer, much better electrical conductivity, controllable nanofiber mat configuration, biocompatibility, and bioresorbability. The inclusion of graphene nanomaterials (GNMs) into NFs is highly desirable. Pre-processing techniques and post-processing techniques to incorporate GNMs into electrospun polymer NFs are precisely discussed. The accomplishment and the utilization of NFs containing GNMs in the electrochemical biosensing pathway for the detection of a broad range biological analytes are discussed. Graphene oxide (GO) has great importance and potential in the biomedical field and can imitate the composition of the extracellular matrix. The oxygen-rich GO is hydrophilic in nature and easily disperses in water, and assists in cell growth, drug delivery, and antimicrobial properties of electrospun nanofiber matrices. NFs containing GO for tissue engineering, drug and gene delivery, wound healing applications, and medical equipment are discussed. NFs containing GO have importance in biomedical applications, which include engineered cardiac patches, instrument coatings, and triboelectric nanogenerators (TENGs) for motion sensing applications. This review deals with graphene-based nanomaterials (GNMs) such as GO incorporated electrospun polymeric NFs for biosensing and biomedical applications, that can bridge the gap between the laboratory facility and industry. Full article

In 1794, French Engineer Claude Chappe coordinated the deployment of a network of dozens of optical semaphores. These formed “strings” that were hundreds of kilometers long, allowing for nationwide telegraphy. The Chappe telegraph inspired future developments of long-range telecommunications using electrical telegraphs and, later, digital telecommunication. Long-range wireless networks are used today for the Internet of Things (IoT), including industrial, agricultural, and urban applications. The long-range radio technology used today offers approximately 10 km of range. Long-range IoT solutions use “star” topology: all devices need to be within range of a gateway device. This limits the area covered by one such network to roughly a disk of a 10 km radius. In this article, we demonstrate a 103 km low-power wireless multi-hop network by combining long-range IoT radio technology with Claude Chappe’s vision. We placed 11 battery-powered devices at the former locations of the Chappe telegraph towers, hanging under helium balloons. We ran a proprietary protocol stack on these devices so they formed a 10-hop multi-hop network: devices forwarded the frames from the “previous” device in the chain. This is, to our knowledge, the longest low power multi-hop wireless network built to date, demonstrating the potential of combining long-range radio technology with multi-hop technology. Full article

Application of quantitative dynamic contrast-enhanced (DCE) MRI in mouse models of abdominal cancer is challenging due to the effects of RF inhomogeneity, image corruption from rapid respiratory motion and the need for high spatial and temporal resolutions. Here we demonstrate a DCE protocol optimized for such applications. The method consists of three acquisitions: (1) actual flip-angle B₁ mapping, (2) variable flip-angle T₁ mapping and (3) acquisition of the DCE series using a motion-robust radial strategy with k-space weighted image contrast (KWIC) reconstruction. All three acquisitions employ spoiled radial imaging with stack-of-stars sampling (SoS) and golden-angle increments between the views. This scheme is shown to minimize artifacts due to respiratory motion while simultaneously facilitating view-sharing image reconstruction for the dynamic series. The method is demonstrated in a genetically engineered mouse model of pancreatic ductal adenocarcinoma and yielded mean perfusion parameters of K^trans = 0.23 ± 0.14 min⁻¹ and v_e = 0.31 ± 0.17 (n = 22) over a wide range of tumor sizes. The SoS-sampled DCE method is shown to produce artifact-free images with good SNR leading to robust estimation of DCE parameters. Full article

Compared with hyperpolarized noble gas MRI, oxygen-enhanced lung imaging is a cost-effective approach to investigate lung function. In this study, we investigated the feasibility of free-breathing phase-resolved oxygen-enhanced pulmonary MRI based on a 3D stack-of-stars ultra-short echo time (UTE) sequence. We conducted both computer simulation and in vivo experiments and calculated percent signal enhancement maps of four different respiratory phases on four healthy volunteers from the end of expiration to the end of inspiration. The phantom experiment was implemented to verify simulation results. The respiratory phase was segmented based on the extracted respiratory signal and sliding window reconstruction, providing phase-resolved pulmonary MRI. Demons registration algorithm was applied to compensate for respiratory motion. The mean percent signal enhancement of the average phase increases from anterior to posterior region, matching previous literature. More details of pulmonary tissues were observed on post-oxygen inhalation images through the phase-resolved technique. Phase-resolved UTE pulmonary MRI shows the potential as a valuable method for oxygen-enhanced MRI that enables the investigation of lung ventilation on middle states of the respiratory cycle. Full article

The aim of this study is the preparation of star-shaped branched polyamides (sPA6) with low melt viscosity, but also with improved mechanical properties by reactive extrusion. This configuration has been obtained by grafting a tri-functional, three-armed molecule: 5-aminoisophthalic-acid, used as a linking agent (LA). The balance between the fluidity, polarity and mechanical properties of sPA6s is the reason why these materials have been investigated for the impregnation of fabrics in the manufacture of thermoplastic composites. For these impregnation processes, the low viscosity of the melt has allowed the processing parameters (temperature, pressure and time) to be reduced, and its new microstructure has allowed the mechanical properties of virgin thermoplastic resins to be maintained. A significant improvement in the ultrasonic welding processes of the composites was also found when an energy director based on these materials was applied at the interface. In this work, an exhaustive microstructural characterization of the obtained sPAs is presented and related to the final properties of the composites obtained by film stacking. Full article