Search Results (493)

Breast cancer is the leading cause of cancer-related mortality among women world-wide, and early screening is critical for improving patient survival. Medical imaging plays a central role in breast cancer screening, diagnosis, and treatment monitoring. However, conventional imaging modalities—including mammography, ultrasound, and magnetic resonance imaging—face limitations such as low diagnostic specificity, relatively slow imaging speed, ionizing radiation exposure, and dependence on exogenous contrast agents. Photoacoustic imaging (PAI), a novel hybrid imaging technique that combines optical contrast with ultrasonic spatial resolution, has shown great promise in addressing these challenges. By revealing anatomical, functional, and molecular features of the breast tumor microenvironment, PAI offers high spatial resolution, rapid imaging, and minimal operator dependence. This review outlines the fundamental principles of PAI and systematically examines recent advances in its application to breast cancer screening, diagnosis, and therapeutic evaluation. Furthermore, we discuss the translational potential of PAI as an emerging breast imaging modality, complementing existing clinical techniques. Full article

The extended operation of high-speed railways has led to an increased incidence of tunnel lining defects, with falling debris posing a significant safety threat. Within tunnels, single-train passage and trains-crossing events constitute the most frequent operational scenarios, both generating extreme aerodynamic environments that alter debris trajectories from free fall. To systematically investigate the aerodynamic differences and underlying mechanisms governing falling debris behavior under these two distinct conditions, a three-dimensional computational fluid dynamics (CFD) model (debris–air–tunnel–train) was developed using an improved delayed detached eddy simulation (IDDES) turbulence model. Comparative analyses focused on the translational and rotational motions as well as the aerodynamic load coefficients of the debris in both single-train and trains-crossing scenarios. The mechanisms driving the changes in debris aerodynamic behavior are elucidated. Findings reveal that under single-train operation, falling debris travels a greater distance compared with trains-crossing conditions. Specifically, at train speeds ranging from 250–350 km/h, the average flight distances of falling debris in the X and Z directions under single-train conditions surpass those under trains crossing conditions by 10.3 and 5.5 times, respectively. At a train speed of 300 km/h, the impulse of C_Fx and C_Fz under single-train conditions is 8.6 and 4.5 times greater than under trains-crossing conditions, consequently leading to the observed reduction in flight distance. Under the conditions of trains crossing, the falling debris is situated between the two trains, and although the wind speed is low, the flow field exhibits instability. This is the primary factor contributing to the reduced flight distance of the falling debris. However, it also leads to more pronounced trajectory deviations and increased speed fluctuations under intersection conditions. The relative velocity (CRV) on the falling debris surface is diminished, resulting in smaller-scale vortex structures that are more numerous. Consequently, the aerodynamic load coefficient is reduced, while the fluctuation range experiences an increase. Full article

In modern vehicles, Autonomous Driving Systems (ADSs) are designed to operate partially or fully without human intervention. The ADS pipeline comprises multiple layers, including sensors, perception, localization, mapping, path planning, and control. The Robot Operating System (ROS) is a widely adopted framework that supports the modular development and integration of these layers. Among them, the path-planning and control layers remain particularly challenging due to several limitations. Classical path planners often struggle with non-smooth trajectories and high computational demands. Meta-heuristic optimization algorithms have demonstrated strong theoretical potential in path planning; however, they are rarely implemented in real-time ROS-based systems due to integration challenges. Similarly, traditional PID controllers require manual tuning and are unable to adapt to system disturbances. This paper proposes a ROS-based ADS architecture composed of eight integrated nodes, designed to address these limitations. The path-planning node leverages a meta-heuristic optimization framework with a cost function that evaluates path feasibility using occupancy grids from the Hector SLAM and obstacle clusters detected through the DBSCAN algorithm. A dynamic goal-allocation strategy is introduced based on the LiDAR range and spatial boundaries to enhance planning flexibility. In the control layer, a modified Pure Pursuit algorithm is employed to translate target positions into velocity commands based on the drift angle. Additionally, an adaptive PID controller is tuned in real time using the Differential Evolution (DE) algorithm, ensuring robust speed regulation in the presence of external disturbances. The proposed system is practically validated on a four-wheel differential drive robot across six scenarios. Experimental results demonstrate that the proposed planner significantly outperforms state-of-the-art methods, ranking first in the Friedman test with a significance level less than 0.05, confirming the effectiveness of the proposed architecture. Full article

This study aimed to investigate the dynamic characteristics of shafts joined by friction welding and to update their finite element models. The first five bending mode resonance frequencies, damping ratios, and mode shapes of SAE 304 steel beams, friction-welded at three different rotational speeds (1200, 1500, and 1800 rpm), were determined using the Experimental Modal Analysis method. This approach allowed for an examination of how the dynamic properties of friction-welded beams change at varying rotational speeds. A slight decrease in resonance frequency values was observed with the transition from lower to higher rotational speeds. The largest difference of 3.28% was observed in the first mode, and the smallest difference of 0.19% was observed in the second mode. Different trends in damping ratios were observed for different modes. In the first, second, and fourth modes, damping ratios tended to increase with increasing rotational speeds, while they tended to decrease in the third and fifth modes. The largest difference was calculated as 52.83% in the third vibration mode. However, no significant change in mode shapes was observed for different rotational speeds. Based on the examined Modal Assurance Criterion (MAC) results, cross-comparisons of the mode shapes obtained for all three different speeds yielded a minimum similarity of 93.8%, reaching up to 99.9%. For model updating, a Frequency Response Assurance Criterion (FRAC)-based method utilizing frequency response functions (FRFs) was employed. Initially, a numerical model of the welded shaft was created using MATLAB-R2015a, based on the Euler–Bernoulli beam theory. Since rotational coordinates were not used in the EMA analyses, static model reduction was performed on the numerical model to reduce the effect of rotational coordinates to translational coordinates. For model updating, experimentally obtained FRFs from EMA and FRFs from the numerical model were used. The equivalent modulus of elasticity and equivalent density of the friction weld region were used as updating parameters. Successful results were achieved by developing an algorithm that ensured the convergence of the numerical model’s FRFs and natural frequencies. Full article

Liquid biopsy (LB) has gained attention as a valuable approach for cancer diagnostics, providing a minimally invasive option compared to conventional tissue biopsies and helping to overcome issues related to patient discomfort and procedural invasiveness. Recent advances in biosensor technologies, particularly photonic sensors, have improved the accuracy, speed, and real-time capabilities for detecting circulating biomarkers in biological fluids. Incorporating these tools into clinical practice facilitates more informed therapeutic choices and contributes to tailoring treatments to individual patient profiles. This review highlights the clinical potential of LB, examines technological limitations, and outlines future research directions. Departing from traditional biosensor focused reviews, it adopts a reverse-mapping approach grounded in clinically relevant tumor biomarkers. Specifically, biomarkers associated with prevalent cancers, such as breast, prostate, and lung cancers, serve as the starting point for identifying the most suitable photonic sensing platforms. The analysis underscores the need to align sensor design with the physicochemical properties of each biomarker and the operational requirements of the application. No photonic platform is universally optimal; rather, each exhibits specific strengths depending on performance metrics such as sensitivity, limit of detection, and easy system integration. Within this framework, the review provides a comprehensive assessment of emerging photonic biosensors and outlines key priorities to support their effective clinical translation in cancer diagnostics. Full article

In the era of precision medicine, effective data visualisation plays a pivotal role in supporting clinical decision-making by translating complex, multidimensional datasets into intuitive and actionable insights. This paper explores the foundational principles of visual perception, with a specific focus on pre-attentive attributes such as colour, shape, size, orientation, and spatial position, which are processed automatically by the human visual system. Drawing from cognitive psychology and perceptual science, we demonstrate how these attributes can enhance the clarity and usability of medical visualisations, reducing cognitive load and improving interpretive speed in high-stakes clinical environments. Through detailed case studies and visual examples, particularly within the field of oncology, we highlight best practices and common pitfalls in the design of dashboards, nomograms, and interactive platforms. We further examine the integration of advanced tools—such as genomic heatmaps and temporal timelines—into multidisciplinary workflows to support personalised care. Our findings underscore that visually intelligent design is not merely an aesthetic concern but a critical factor in clinical safety, efficiency, and communication, advocating for user-centred and evidence-based approaches in the development of health data interfaces. Full article

Background/Objectives: Australian terrestrial mammals that fall within the critical weight range (35 g–5.5 kg) have experienced large population declines due to a combination of habitat loss and modification, and the introduction of non-native cats, dogs, and foxes. Because running speed typically increases with body size, predators are usually faster but less agile than their prey due to the biomechanical trade-offs between speed and agility. Quantifying the maximum locomotor capacities of Australian mammals in the critical weight range, and the magnitude of the trade-off between speed and agility, can aid in estimating species’ vulnerability to predation. Methods: To do this, we quantified the trade-off between speed and agility in both males and females (n = 36) of a critical weight range species, the northern brown bandicoot (Isoodon macrourus), and determined if there was an influence of morphology on locomotor performance. Results: When turning, individuals who had higher turn approach speeds, and higher within-turn speeds, had greater turning radii and lower angular velocities, meaning a decrease in overall maneuverability. Females were more agile and exhibited greater turning speeds at similar turning radii than males. For both sexes, individuals with longer relative hind digits had relatively faster sprint speeds, while those with longer forearms had relatively smaller turning radii and higher agility. Conclusions: Due to the constrained limb morphology of the bandicoot species, these findings could translate across this group to provide a better understanding of their escape performance and risk of predation. Full article

The rising share of wind generation in power systems, driven by the need to decarbonise the energy sector, is changing the relationship between wind speed and electricity prices. In the case of Poland, this relationship has not been thoroughly investigated, particularly in the aftermath of the restrictive legal changes introduced in 2016, which halted numerous onshore wind investments. Studying this relationship remains necessary to understand the broader market effects of wind speed on electricity prices, especially considering evolving policies and growing interest in renewable energy integration. In this context, this paper analyses wind speed, wind generation, and other relevant datasets in relation to electricity prices using multiple statistical methods, including correlation analysis, regression modelling, and artificial neural networks. The results show that wind speed is a significant factor in setting electricity prices (with a correlation coefficient reaching up to −0.7). The findings indicate that not only is it important to include wind speed as an electricity price indicator, but it is also worth investing in wind generation, since higher wind output can be translated into lower electricity prices. This study contributes to a better understanding of how natural variability in renewable resources translates into electricity market outcomes under policy-constrained conditions. Its innovative aspect lies in combining statistical and machine learning techniques to quantify the influence of wind speed on electricity prices, using updated data from a period of regulatory stagnation. Full article

With the ongoing development of lightweight automobiles, research on new aluminum alloys and welding technology has gained significant attention. Friction stir welding (FSW) is a solid-state joining technique for welding aluminum alloys without melting. In this study, novel squeeze-cast Al-Si-Mg-Fe-Zn alloys with different Zn contents (0, 3.4, 6.5, and 8.3 wt%) were friction stir welded (FSWed) at a translational speed of 200 mm/min and a rotational speed of 800 rpm. These parameters were chosen based on the observations of visually sound welds, defect-free and fine-grained microstructures, homogeneous secondary phase distribution, and low roughness. Zn can affect the microstructure of Al-Si-Mg-Fe-Zn alloys, including the grain size and the content of secondary phases, leading to different mechanical and corrosion behavior. Adding different Zn contents with Mg forms the various amount of MgZn₂, which has a significant strengthening effect on the alloys. Softening observed in the weld zones of the alloys with 0, 3.4, and 6.5 wt% Zn is primarily attributed to the reduction in Kernel Average Misorientation (KAM) and a decrease in the Si phase and MgZn₂. Consequently, the mechanical strengths of the FSWed joints are lower as compared to the base material. Conversely, the FSWed alloy with 8.3 wt% Zn exhibited enhanced mechanical properties, with hardness of 116.3 HV_0.2, yield strength (YS) of 184.4 MPa, ultimate tensile strength (UTS) of 226.9 MP, percent elongation (EL%) of 1.78%, and a strength coefficient exceeding 100%, indicating that the joint retains the strength of the as-cast one, due to refined grains and more uniformly dispersed secondary phases. The highest corrosion resistance of the FSWed alloy with 6.5%Zn is due to the smallest grain size and KAM, without MgZn₂ and the highest percentage of {111} texture (24.8%). Full article

Herein, an integrated system is developed based on knitted strain sensors for real-time translation of sign language into text and audio voices. To investigate how the structural characteristics of the knit affect the electrical performance, the position of the conductive yarn and the presence or absence of elastic yarn are set as experimental variables, and five distinct sensors are manufactured. A comprehensive analysis of the electrical and mechanical performance, including sensitivity, responsiveness, reliability, and repeatability, reveals that the sensor with a plain-plated-knit structure, no elastic yarn included, and the conductive yarn positioned uniformly on the back exhibits the best performance, with a gauge factor (GF) of 88. The sensor exhibited a response time of less than 0.1 s at 50 cycles per minute (cpm), demonstrating that it detects and responds promptly to finger joint bending movements. Moreover, it exhibits stable repeatability and reliability across various angles and speeds, confirming its optimization for sign language recognition applications. Based on this design, an integrated textile-based system is developed by incorporating the sensor, interconnections, snap connectors, and a microcontroller unit (MCU) with built-in Bluetooth Low Energy (BLE) technology into the knitted glove. The complete system successfully recognized 12 Korean Sign Language (KSL) gestures in real time and output them as both text and audio through a dedicated application, achieving a high recognition accuracy of 98.67%. Thus, the present study quantitatively elucidates the structure–performance relationship of a knitted sensor and proposes a wearable system that accounts for real-world usage environments, thereby demonstrating the commercialization potential of the technology. Full article

Hallux valgus (HV) is described as a lateral deviation of the great toe at the first metatarsophalangeal joint (MTP), which is a very common foot deformity in the clinic. This deformity extends beyond localized foot mechanics to affect the entire lower extremity kinetic chain, potentially increasing dynamic instability during locomotion. This study aimed to characterize the kinematics of ankle and knee joints during walking in HV patients compared to controls. In total, 23 patients with bilateral HV and matched healthy controls were recruited. The 6-DOF kinematics data of ankles and knees were collected using a joint motion function analysis system while level walking at adaptive speed. HV patients demonstrated significant kinematic alterations in the ankle joint at IC, including decreased varus by 2.87° (p < 0.001), decreased internal rotation by 1.77° (p = 0.035), and decreased plantarflexion by 4.39° (p < 0.001) compared with healthy subjects. Concurrent compensatory changes in the knee joint included increased varus rotation by 1.41° (p = 0.023), reduced anterior translation by 0.84 mm (p < 0.001), and increased lateral translation by 0.26 mm (p = 0.036). HV patients showed increased ankle dorsiflexion of 3.61° (p = 0.06) and decreased ankle internal rotation of 2.69° (p = 0.043), with concurrent increased knee internal rotation of 2.59° (p = 0.009) at SPF. The ripple effect during walking in the HV population may elevate the risk of knee pathologies. These findings may inform both conservative management strategies and post-surgical rehabilitation regimens. Full article

In order to improve the uniformity of microwave heating, moving components are often added to the cavity. For higher uniformity or greater industrial processing capacity, samples often perform large-scale movements such as rotating and lifting motion or translational motion on a conveyor belt. The microwave heating algorithm based on the ray-casting method (RCM), as proposed in previous studies, can calculate moving complex-shaped samples, but the calculation efficiency is low when the sample moves on a large scale due to the large refined mesh area. To solve this problem, this study introduced a moving mesh combined with the RCM for calculation purposes. A microwave oven model with a rotating and lifting turntable was selected for the analysis. First, the calculation area was divided into a sliding mesh and a telescopic mesh area. The telescopic mesh area was stretched or compressed at different times, which was equivalent to the translational motion of the sample. Then, the electromagnetic parameters were assigned to each mesh point in combination with the boundary recognition algorithm based on the ray-casting method, and the horizontal motion was calculated while calculating the large-scale translation. The proposed method only needs to refine the mesh in the horizontal motion area, which reduces the number of overall meshes. The electromagnetic field distribution obtained by the model during the heating process was verified by the discrete position method. The surface temperature distribution and the real-time curve of the center point temperature were further compared with the RCM. The results show that the average error of the sample center temperature is 2.5% and the calculation time was reduced to 9.8%, which verified the accuracy and efficiency of the proposed method. Finally, the influence of different lifting and rotating speeds on the heating effect was further explored. Full article

Polarized light imaging (PLI) has been effective in visualizing and quantifying collagen content. Collagen-specific data are often overlaid over the tissue image for visualization. However, such contextual tissue images are typically in grayscale and lack important color information, limiting the usefulness of PLI in imaging the stained histology slides and for surgical guidance. The objective of this study was to develop a robust and easy-to-implement PLI technique to capture both true color and birefringent collagen data, and we call it ColorPOL. ColorPOL uses only one polarization-sensitive camera to capture information at 75 frames per second. The true color images were synthesized from individual RGB images, and collagen-specific information (fiber orientation and retardance) was derived from the green channel image. We implemented ColorPOL in transmission mode on an upright microscope and in reflection mode for wide-field thick tissue imaging. The color images in both implementations provided valuable color tissue context that facilitated the identification and localization of collagen content. Additionally, we demonstrated that in reflection mode, the high imaging speed enabled us to record and visualize continuous deformations of the collagenous tissues (tendons, sciatic nerves, and blood vessels) overlaid on the processed collagen-specific information. Robust performance and flexible configuration will make ColorPOL a valuable tool in basic research and translational applications. Full article

The authors have designed a gyro-system for orientation (guidance) and stabilization, with two gimbals and a rotor in magnetic suspension (AMB—Active Magnetic Bearing) usable for self-guided rockets. The gyro-system (DGMSGG—double gimbal magnetic suspension gyro-system for guidance) orients and stabilizes the target coordinator’s axis (CT) and, at the same time, the AMB–rotor’s axis so that they overlap the guidance line (the target line). DGMSGG consists of two decoupled systems: one for canceling the AMB–rotor translations along the precession axes (induced by external disturbing forces), the other for canceling the AMB–rotor rotations relative to the CT-axis (induced by external disturbing moments) and, at the same time, for controlling the gimbals’ rotations, so that the AMB–rotor’s axis overlaps the guidance line. The nonlinear DGMSGG model is decomposed into two sub-models: one for the AMB–rotor’s translation, the other for the AMB–rotor’s and gimbals’ rotation. The second sub-model is described first by nonlinear state equations. This model is reduced to a second order nonlinear matrix—vector form with respect to the output vector. The output vector consists of the rotation angles of the AMB–rotor and the rotation angles of the gimbals. For this purpose, a differential geometry method, based on the use of the output vector’s gradient with respect to the nonlinear state functions, i.e., based on Lie derivatives, is used. This equation highlights the relative degree (equal to 2) with respect to the variables of the output vector and allows for the use of the dynamic inversion method in the design of stabilization and guidance controllers (of P.I.D.- and PD-types), as well as in the design of the related linear state observers. The controller of the subsystem intended for AMB–rotor’s translations control is chosen as P.I.D.-type, which leads to the cancellation of both its translations and its translation speeds. The theoretical results are validated through numerical simulations, using Simulink/Matlab models. Full article

Bis- and trisphosphines incorporating methylene and aryl spacers readily adsorb on the surface of porous activated carbon (AC). The adsorption can be performed in the absence of solvents, even when the phosphines have high melting points, or from solutions. The diverse phosphines Ph₂PCH₂PPh₂ (dppm), Ph₂P(CH₂)₂PPh₂ (dppe), Ph₂P(CH₂)₃PPh₂ (dppp), Ph₂P(p-C₆H₄)PPh₂ (dppbz), and (Ph₂PCH₂)₃CCH₃ (tdme) were adsorbed in submonolayers on AC. The adsorbed phosphines were studied by ³¹P MAS (magic angle spinning) NMR spectroscopy, and their mobilities on the surface were confirmed by determining the ³¹P T₁ relaxation times. All phosphine groups of each bis- and trisphosphine molecule are in contact with the surface, and the molecules exhibit translational mobility as one unit. All phosphines used here are air-stable. Once a submonolayer is created on the AC surface, oxygen from the air is co-adsorbed and transforms all phosphines quantitatively into phosphine oxides at room temperature. The oxidation proceeds in a consecutive manner with the oxidation of one phosphine group after another until the fully oxidized species are formed. Studies of the kinetics are based on integrating the signals in the solution ³¹P NMR spectra. High temperatures and low surface coverages increase the speed of the oxidation, while light and acid have no impact. The oxidation is fast and complete within one hour for 10% surface coverage at room temperature. In order to study the mechanism and slow down the oxidation, a higher surface coverage of 40% was applied. No unwanted P(V) side products or water adducts were observed. The clean phosphine oxides could be recovered in high yields by washing them off of the AC surface. The oxidation is based on radical activation of O₂ on the AC surface due to delocalized electrons on the AC surface. This is corroborated by the result that AIBN-derived radicals enable the air oxidation of PPh₃ in solution at 65 °C. When the air-stable complex (CO)₂Ni(PPh₃)₂ is applied to the AC surface and exposed to the air, OPPh₃ forms quantitatively. The new surface-assisted air oxidation of phosphines adsorbed on AC renders expensive and hazardous oxidizers obsolete and opens a synthetic pathway to the selective mono-oxidation of bis- and trisphosphines. Full article