374 research outputs found
A Novel Human-Based Meta-Heuristic Algorithm: Dragon Boat Optimization
(Aim) Dragon Boat Racing, a popular aquatic folklore team sport, is
traditionally held during the Dragon Boat Festival. Inspired by this event, we
propose a novel human-based meta-heuristic algorithm called dragon boat
optimization (DBO) in this paper. (Method) It models the unique behaviors of
each crew member on the dragon boat during the race by introducing social
psychology mechanisms (social loafing, social incentive). Throughout this
process, the focus is on the interaction and collaboration among the crew
members, as well as their decision-making in different situations. During each
iteration, DBO implements different state updating strategies. By modelling the
crew's behavior and adjusting the state updating strategies, DBO is able to
maintain high-performance efficiency. (Results) We have tested the DBO
algorithm with 29 mathematical optimization problems and 2 structural design
problems. (Conclusion) The experimental results demonstrate that DBO is
competitive with state-of-the-art meta-heuristic algorithms as well as
conventional methods
EAFP-Med: An Efficient Adaptive Feature Processing Module Based on Prompts for Medical Image Detection
In the face of rapid advances in medical imaging, cross-domain adaptive
medical image detection is challenging due to the differences in lesion
representations across various medical imaging technologies. To address this
issue, we draw inspiration from large language models to propose EAFP-Med, an
efficient adaptive feature processing module based on prompts for medical image
detection. EAFP-Med can efficiently extract lesion features of different scales
from a diverse range of medical images based on prompts while being flexible
and not limited by specific imaging techniques. Furthermore, it serves as a
feature preprocessing module that can be connected to any model front-end to
enhance the lesion features in input images. Moreover, we propose a novel
adaptive disease detection model named EAFP-Med ST, which utilizes the Swin
Transformer V2 - Tiny (SwinV2-T) as its backbone and connects it to EAFP-Med.
We have compared our method to nine state-of-the-art methods. Experimental
results demonstrate that EAFP-Med ST achieves the best performance on all three
datasets (chest X-ray images, cranial magnetic resonance imaging images, and
skin images). EAFP-Med can efficiently extract lesion features from various
medical images based on prompts, enhancing the model's performance. This holds
significant potential for improving medical image analysis and diagnosis
Performance enhancement of the soft robotic segment for a trunk-like arm
Introduction: Trunk-like continuum robots have wide applications in manipulation and locomotion. In particular, trunk-like soft arms exhibit high dexterity and adaptability very similar to the creatures of the natural world. However, owing to the continuum and soft bodies, their performance in payload and spatial movements is limited.Methods: In this paper, we investigate the influence of key design parameters on robotic performance. It is verified that a larger workspace, lateral stiffness, payload, and bending moment could be achieved with adjustments to soft materials’ hardness, the height of module segments, and arrayed radius of actuators.Results: Especially, a 55% increase in arrayed radius would enhance the lateral stiffness by 25% and a bending moment by 55%. An 80% increase in segment height would enlarge 112% of the elongation range and 70 % of the bending range. Around 200% and 150% increments in the segment’s lateral stiffness and payload forces, respectively, could be obtained by tuning the hardness of soft materials. These relations enable the design customization of trunk-like soft arms, in which this tapering structure ensures stability via the stocky base for an impact reduction of 50% compared to that of the tip and ensures dexterity of the long tip for a relatively larger bending range of over 400% compared to that of the base.Discussion: The complete methodology of the design concept, analytical models, simulation, and experiments is developed to offer comprehensive guidelines for trunk-like soft robotic design and enable high performance in robotic manipulation
MRI Lesion Load of Cerebral Small Vessel Disease and Cognitive Impairment in Patients With CADASIL
Background and objective: Cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is the best known and the most common monogenic small vessel disease (SVD). Cognitive impairment is an inevitable feature of CADASIL. Total SVD score and global cortical atrophy (GCA) scale were found to be good predictors of poor cognitive performance in community-dwelling adults. We aimed to estimate the association between the total SVD score, GCA scale and the cognitive performance in patients with CADASIL.Methods: We enrolled 20 genetically confirmed CADASIL patients and 20 controls matched by age, gender, and years of education. All participants underwent cognitive assessments to rate the global cognition and individual domain of executive function, information processing speed, memory, language, and visuospatial function. The total SVD score and GCA scale were rated.Results: The CADASIL group performed worse than the controls on all cognition measures. Neither global cognition nor any separate domain of cognition was significantly different among patients grouped by total SVD score. Negative correlations between the GCA score and cognitive performance were observed. Approximately 40% of the variance was explained by the total GCA score in the domains of executive function, information processing speed, and language. The superficial atrophy score was associated with poor performance in most of the domains of cognition. Adding the superficial atrophy score decreased the prediction power of the deep atrophy score on cognitive impairment alone.Conclusions: The GCA score, not the total SVD score, was significantly associated with poor cognitive performance in patients with CADASIL. Adding the superficial atrophy score attenuated the prediction power of the deep atrophy score on cognitive impairment alone
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