Search

Endowing tactile feedback for prosthetic hands is profound for upper‐limb amputees. However, existing prosthetic hands are generally not in possession of the embedded sensory feedback. Herein, a flexible tactile sensor array which can be integrated into an untethered soft prosthetic hand to achieve static and dynamic discrimination tasks is presented. The flexible piezoresistive sensory arrays with 25 sensor units which can be arranged on five fingers of the soft prosthetic hand are fabricated. According to the collected large‐scale tactile dataset (including pressure distribution and pressure magnitude) during different grasping tasks, a learning‐based classification model that can reveal the correspondences between tactile information and object attributes while interacting with touched objects is developed. To transfer tactile information extracted from tactile sensor arrays, a wearable vibrotactile feedback band with a spatial coding feedback strategy is implemented by selectively activating vibrotactile motors located on the skin of the upper arm. In a set of tests performed by an individual with transradial amputation and eight able‐bodied subjects, the soft prosthetic hand integrated with tactile sensor arrays can help the users regain finger tactile sensation, discriminate grasped objects, and achieve real‐time dynamic rolling detection. [ABSTRACT FROM AUTHOR]

CO2pre-injection during hydraulic fracturing is an important method for the development of medium to deep heavy oil reservoirs. It reduces the interfacial tension and viscosity of crude oil, enhances its flowability, maintains reservoir pressure, and increases reservoir drainage capacity. Taking the Badaowan Formation as an example, in this study a detailed three-dimensional geomechanical model based on static data from well logging interpretations is elaborated, which can take into account both vertical and horizontal geological variations and mechanical characteristics. A comprehensive analysis of the impact of key construction parameters on Pre-CO2based fracturing (such as cluster spacing and injection volume), is therefore conducted. Thereafter, using optimized construction parameters, a non-structured grid for dynamic development prediction is introduced, and the capacity variations of different production scenarios are assessed. On the basis of the simulation results, reasonable fracturing parameters are finally determined, including cluster spacing, fracturing fluid volume, proppant concentration, and well spacing. [ABSTRACT FROM AUTHOR]

Purpose: Autostereoscopic displays have become increasingly common, but their impact on ocular dimensions remains unknown. We sought to identify changes in the crystalline lens dimensions induced by autostereoscopic three‐dimensional (3D) viewing. Methods: Forty young adults (age: 22.6 ± 2.0 years, male/female: 15/25) were consecutively enrolled and randomly divided into two groups (3D and two‐dimensional [2D] viewing groups) to watch a 30‐min movie clip displayed in 3D or 2D mode on a tablet computer. The lens thickness (LT), diameter, curvature, decentration and tilt were measured with anterior segment optical coherence tomography under both non‐accommodating (static) and accommodating conditions. Results: In the static condition, the LT decreased by 0.03 ± 0.03 mm (p < 0.001) and the anterior radius of curvature (ARC) increased by 0.49 ± 0.59 mm (p = 0.001) post‐3D viewing. In contrast, following 2D viewing, the ARC decreased by 0.23 ± 0.25 mm (p = 0.001). Additionally, the increase in the steep ARC post‐3D viewing was greater in high‐myopic eyes than low to moderate myopic eyes (p = 0.04). When comparing the accommodative with the static (non‐accommodative) condition, for 3D viewing the lens decentration decreased (−0.03 ± 0.05 mm, p = 0.02); while for 2D viewing, the posterior curvature radius (−0.14 ± 0.20 mm, p = 0.006) and diameter (−0.13 ± 0.20 mm, p = 0.01) decreased. Conclusions: Viewing with the autostereoscopic 3D tablet could temporally decrease the thickness and curvature of the lens under non‐accommodating conditions. However, its long‐term effect requires further exploration. [ABSTRACT FROM AUTHOR]

Purpose: To develop a deep learning–based approach to reduce the scan time of multipool CEST MRI for Parkinson's disease (PD) while maintaining sufficient prediction accuracy. Method: A deep learning approach based on a modified one‐dimensional U‐Net, termed Z‐spectral compressed sensing (CS), was proposed to recover dense Z‐spectra from sparse ones. The neural network was trained using simulated Z‐spectra generated by the Bloch equation with various parameter settings. Its feasibility and effectiveness were validated through numerical simulations and in vivo rat brain experiments, compared with commonly used linear, pchip, and Lorentzian interpolation methods. The proposed method was applied to detect metabolism‐related changes in the 6‐hydroxydopamine PD model with multipool CEST MRI, including APT, CEST@2 ppm, nuclear Overhauser enhancement, direct saturation, and magnetization transfer, and the prediction performance was evaluated by area under the curve. Results: The numerical simulations and in vivo rat‐brain experiments demonstrated that the proposed method could yield superior fidelity in retrieving dense Z‐spectra compared with existing methods. Significant differences were observed in APT, CEST@2 ppm, nuclear Overhauser enhancement, and direct saturation between the striatum regions of wild‐type and PD models, whereas magnetization transfer exhibited no significant difference. Receiver operating characteristic analysis demonstrated that multipool CEST achieved better predictive performance compared with individual pools. Combined with Z‐spectral CS, the scan time of multipool CEST MRI can be reduced to 33% without distinctly compromising prediction accuracy. Conclusion: The integration of Z‐spectral CS with multipool CEST MRI can enhance the prediction accuracy of PD and maintain the scan time within a reasonable range. [ABSTRACT FROM AUTHOR]

Purpose: To explore the use of autologous astigmatic lenticule reshaping and rotation surgery to correct high astigmatism in conjunction with excimer laser technology to correct residual refractive error. Methods: Six patients with high astigmatism (8 eyes, all with astigmatism from −5.50 to −11.00 diopters [D]) seeking refractive error correction were enrolled. The following methods were used to correct refractive errors that could not be corrected by a single conventional surgery: (1) cutting of a customized lens using FLEx technology, (2) lifting of the corneal flap and reshaping the autologous astigmatic lenticule in situ using an excimer laser, and (3) rotation of the autologous astigmatic lenticule by 90°. Uncorrected distance visual acuity, subjective refraction, corneal topography, and anterior segment optical coherence tomography were performed preoperatively and postoperatively. Results: The efficacy and safety indices at 6 months postoperatively were 0.93 ± 0.18 and 1.06 ± 0.11, respectively, the spherical equivalent remained stable and close to emmetropia (−0.13 ± 0.70 D) from 1 to 6 months postoperatively, postoperative astigmatism was generally mildly undercorrected (−1.22 ± 0.43 D), and the difference in corneal curvatures at 2 mm from the apex of the cornea was significantly reduced compared to preoperatively (P <.05); however, the corresponding values at 1 and 3 mm showed no difference. Conclusions: Correction of high astigmatism with autologous astigmatic lenticule reshaping and rotation surgery is tissue-sparing, predictable, and significantly improves postoperative visual acuity and quality. This method is feasible and safe, with predictability requiring further study. This novel surgical approach has potential for patients with high astigmatism that cannot be corrected by conventional refractive surgery. [J Refract Surg. 2024;40(8):e554–e561.] [ABSTRACT FROM AUTHOR]

BACKGROUND: Wearable trunk exoskeletons hold immense potential in fields such as healthcare and industry. Previous research has indicated that intention recognition control plays a crucial role in users' daily use of exoskeletons. OBJECTIVE: This review aims to discuss the characteristics of intention recognition control schemes for intelligent trunk exoskeletons under different control objectives over the past decade. METHODS: Considering the relatively late development of active trunk exoskeletons, we selected papers published in the last decade (2013 to 2023) from the Web of Science, PubMed, and IEEE Xplore databases. In total, 50 articles were selected and examined based on four control objectives. RESULTS: In general, we found that researchers focus on trunk exoskeleton devices designed for assistance and motor augmentation, which rely more on body movement signals as a source for intention recognition. CONCLUSION: Based on these results, we identify and discuss several promising research directions that may help to attain a widely accepted control methods, thereby advancing further development of trunk exoskeleton technology. [ABSTRACT FROM AUTHOR]