Research and Validation of CF/PEEK-Based Truss Rod Crimping and Pultruding Process for On-Orbit Isoform Forming.

A crimping and pultruding forming process for truss rods using Carbon Fiber (CF)/Polyether-Ether-Ketone (PEEK) prepreg tape as the raw material is proposed to address the problem of continuous manufacturing of space trusses on orbit. The proposed process provides material rods for continuous truss manufacturing. Through numerical simulation and experimental verification, the effects of relevant parameters on the forming process are determined, an efficient method of rod curl pultrusion, in-rail, equal material forming is proposed, and the structural configuration of the rod curl pultrusion forming mold is determined. The equivalent macroscopic mechanical properties of unidirectional CF/PEEK prepreg strips are considered, and the rod-forming process is investigated. Rod samples with different process parameters are prepared, and several tests are conducted on them. The results show that the forming load pull is negatively correlated with the temperature at the same forming speed, and forming speed is positively correlated with the forming load pull at a certain temperature. Temperature and speed affect the surface quality of the rod, the density of the material filling, and the mechanical properties of the rod. The optimal forming process parameters are determined through numerical simulation and experimental verification. The developed molding technology has the advantages of high efficiency, low energy consumption, and high integration. It reduces manufacturing costs and improves manufacturing efficiency, so it can serve as a new and effective solution for the manufacturing of high-performance truss rods in the aerospace field.

Electrospun multi-chamber core-shell nanofibers and their controlled release behaviors: A review.

Core-shell structure is a concentric circle structure found in nature. The rapid development of electrospinning technology provides more approaches for the production of core-shell nanofibers. The nanoscale effects and expansive specific surface area of core-shell nanofibers can facilitate the dissolution of drugs. By employing ingenious structural designs and judicious polymer selection, specialized nanofiber drug delivery systems can be prepared to achieve controlled drug release. The synergistic combination of core-shell structure and materials exhibits a strong strategy for enhancing the drug utilization efficiency and customizing the release profile of drugs. Consequently, multi-chamber core-shell nanofibers hold great promise for highly efficient disease treatment. However, little attention concentration is focused on the effect of multi-chamber core-shell nanofibers on controlled release of drugs. In this review, we introduced different fabrication techniques for multi-chamber core-shell nanostructures, including advanced electrospinning technologies and surface functionalization. Subsequently, we reviewed the different controlled drug release behaviors of multi-chamber core-shell nanofibers and their potential needs for disease treatment. The comprehensive elucidation of controlled release behaviors based on electrospun multi-chamber core-shell nanostructures could inspire the exploration of novel controlled delivery systems. Furthermore, once these fibers with customizable drug release profiles move toward industrial mass production, they will potentially promote the development of pharmacy and the treatment of various diseases. This article is categorized under: Therapeutic Approaches and Drug Discovery > Emerging Technologies.

Contactless screening for sleep apnea with breathing vibration signals based on modified U-Net.

BACKGROUND: Obstructive sleep apnea (OSA) is a chronic sleep disorder characterized by frequent cessations or reductions of breathing during sleep. Polysomnography (PSG) is a definitive diagnostic tool for OSA. The costly and obtrusive nature of PSG and poor access to sleep clinics have created a demand for accurate home-based screening devices. METHODS: This paper proposes a novel OSA screening method based solely on breathing vibration signals with a modified U-Net, allowing patients to be tested at home. Sleep recordings over a whole night are collected in a contactless manner, and sleep apnea-hypopnea events are labeled by a deep neural network. The apnea-hypopnea index (AHI) calculated from events estimation is then used to screen for the apnea. The performance of the model is tested by event-based analysis and comparing the estimated AHI with the manually obtained values. RESULTS: The accuracy and sensitivity of sleep apnea events detection are 97.5% and 76.4%, respectively. The mean absolute error of AHI estimation for the patients is 3.0 events/hour. The correlation between the ground truth AHI and predicted AHI shows an R2 of 0.95. In addition, 88.9% of all participants are classified into correct AHI categories. CONCLUSIONS: The proposed scheme has great potential as a simple screening tool for sleep apnea. It can accurately detect potential OSA and help the patients to be referred for differential diagnosis of home sleep apnea test (HSAT) or polysomnographic evaluation.

DSCA-Net: A depthwise separable convolutional neural network with attention mechanism for medical image segmentation.

Accurate segmentation is a basic and crucial step for medical image processing and analysis. In the last few years, U-Net, and its variants, have become widely adopted models in medical image segmentation tasks. However, the multiple training parameters of these models determines high computation complexity, which is impractical for further applications. In this paper, by introducing depthwise separable convolution and attention mechanism into U-shaped architecture, we propose a novel lightweight neural network (DSCA-Net) for medical image segmentation. Three attention modules are created to improve its segmentation performance. Firstly, Pooling Attention (PA) module is utilized to reduce the loss of consecutive down-sampling operations. Secondly, for capturing critical context information, based on attention mechanism and convolution operation, we propose Context Attention (CA) module instead of concatenation operations. Finally, Multiscale Edge Attention (MEA) module is used to emphasize multi-level representative scale edge features for final prediction. The number of parameters in our network is 2.2 M, which is 71.6% less than U-Net. Experiment results across four public datasets show the potential and the dice coefficients are improved by 5.49% for ISIC 2018, 4.28% for thyroid, 1.61% for lung and 9.31% for nuclei compared with U-Net.

Design and Mechanical Characterisation of a Large Truss Structure for Continuous Manufacturing in Space.

In this paper, large space structures are essential components of significant equipment in orbits, such as megawatt-class solar power plants and long baseline interferometry. However, to realize the in-space fabrication of such megastructures, the primary consideration is the continuous fabrication of the structure. In this paper, we propose and design a structural form that differs from the minimum constituent unit shape of conventional truss structures by using an efficient winding and weaving method to construct truss structures. The continuously buildable one-dimensional truss's structural design and mechanical properties are investigated. The parameters affecting the fundamental frequency of the truss structure are analyzed through modeling, simulation and experimental verification of the continuously buildable 1D truss. It is concluded that this configuration truss can be built continuously in space. The most influential factors on the fundamental truss frequency are the truss section spacing, the total truss length and the truss-specific stiffness. The simulated and theoretical values of the truss's static stiffness and vibration frequency have minor errors, which provide a basis for the configuration design for the continuous manufacturing of large truss structures in space.

Magnetotelluric evidence for the multi-microcontinental composition of eastern South China and its tectonic evolution.

The tectonic boundaries and geodynamic evolution of the South China Block are widely debated. While the community largely agrees on the occurrence of the collision between the Yangtze and Cathaysia Blocks, the lack of ultrahigh-pressure metamorphic rocks and obscurity of the boundary lead to inconsistencies among the abundant geological and geophysical data. We present three profiles that reveal the geoelectrical structure of eastern South China. Distinct conductive interfaces oriented NE-SW are identified in the geoelectrical lithosphere, which separate the region into six parts. To interpret our observations and resultant model, we develop and propose a mechanism of "microcontinent interaction". Our new model justifies the prior proposed models of 'block collision' and additionally proposes 'multi-terrane accretion-collision' to address the tectonic evolution.

[Development Review of Novel Laparoscope Technology].

The proportion of laparoscopic surgeries is continuously increasing in general surgeries. Along with the development and application, new image sensor and digital image processing technology accelerated the emergence of novel laparoscope in recent years. Stereoscopic laparoscope (3D) appearing make the space orientation more accurate. new imaging methods and new structure design satisfy more clinical requirements; combination with optical technology (NBI technique, PDD technique, ICG technique) make intraoperative diagnosis possible.

An Investigation on the Effect of Extremely Low Frequency Pulsed Electromagnetic Fields on Human Electrocardiograms (ECGs).

For this investigation, we studied the effects of extremely low frequency pulse electromagnetic fields (ELF-PEMF) on the human cardiac signal. Electrocardiograms (ECGs) of 22 healthy volunteers before and after a short duration of ELF-PEMF exposure were recorded. The experiment was conducted under single-blind conditions. The root mean square (RMS) value of the recorded data was considered as comparison criteria. We also measured and analysed four important ECG time intervals before and after ELF-PEMF exposure. Results revealed that the RMS value of the ECG recordings from 18 participants (81.8% of the total participants) increased with a mean value of 3.72%. The increase in ECG voltage levels was then verified by a second experimental protocol with a control exposure. In addition to this, we used hyperbolic T-distributions (HTD) in the analysis of ECG signals to verify the change in the RR interval. It was found that there were small shifts in the frequency-domain signal before and after EMF exposure. This shift has an influence on all frequency components of the ECG signals, as all spectrums were shifted. It is shown from this investigation that a short time exposure to ELF-PEMF can affect the properties of ECG signals. Further study is needed to consolidate this finding and discover more on the biological effects of ELF-PEMF on human physiological processes.

Semiautomatic segmentation of liver metastases on volumetric CT images.

PURPOSE: Accurate segmentation and quantification of liver metastases on CT images are critical to surgery/radiation treatment planning and therapy response assessment. To date, there are no reliable methods to perform such segmentation automatically. In this work, the authors present a method for semiautomatic delineation of liver metastases on contrast-enhanced volumetric CT images. METHODS: The first step is to manually place a seed region-of-interest (ROI) in the lesion on an image. This ROI will (1) serve as an internal marker and (2) assist in automatically identifying an external marker. With these two markers, lesion contour on the image can be accurately delineated using traditional watershed transformation. Density information will then be extracted from the segmented 2D lesion and help determine the 3D connected object that is a candidate of the lesion volume. The authors have developed a robust strategy to automatically determine internal and external markers for marker-controlled watershed segmentation. By manually placing a seed region-of-interest in the lesion to be delineated on a reference image, the method can automatically determine dual threshold values to approximately separate the lesion from its surrounding structures and refine the thresholds from the segmented lesion for the accurate segmentation of the lesion volume. This method was applied to 69 liver metastases (1.1-10.3 cm in diameter) from a total of 15 patients. An independent radiologist manually delineated all lesions and the resultant lesion volumes served as the "gold standard" for validation of the method's accuracy. RESULTS: The algorithm received a median overlap, overestimation ratio, and underestimation ratio of 82.3%, 6.0%, and 11.5%, respectively, and a median average boundary distance of 1.2 mm. CONCLUSIONS: Preliminary results have shown that volumes of liver metastases on contrast-enhanced CT images can be accurately estimated by a semiautomatic segmentation method.

Automated matching and segmentation of lymphoma on serial CT examinations.

In patients with lymphoma, identification and quantification of the tumor extent on serial CT examinations is critical for assessing tumor response to therapy. In this paper, we present a computer method to automatically match and segment lymphomas in follow-up CT images. The method requires that target lymph nodes in baseline CT images be known. A fast, approximate alignment technique along the x, y, and axial directions is developed to provide a good initial condition for the subsequent fast free form deformation (FFD) registration of the baseline and the follow-up images. As a result of the registration, the deformed lymph node contours from the baseline images are used to automatically determine internal and external markers for the marker-controlled watershed segmentation performed in the follow-up images. We applied this automated registration and segmentation method retrospectively to 29 lymph nodes in 9 lymphoma patients treated in a clinical trial at our cancer center. A radiologist independently delineated all lymph nodes on all slices in the follow-up images and his manual contours served as the "gold standard" for evaluation of the method. Preliminary results showed that 26/29 (89.7%) lymph nodes were correctly matched; i.e., there was a geometrical overlap between the deformed lymph node from the baseline and its corresponding mass in the follow-up images. Of the matched 26 lymph nodes, 22 (84.6%) were successfully segmented; for these 22 lymph nodes, several metrics were calculated to quantify the method's performance. Among them, the average distance and the Hausdorff distance between the contours generated by the computer and those generated by the radiologist were 0.9 mm (stdev. 0.4 mm) and 3.9 mm (stdev. 2.1 mm), respectively.

Marker-controlled watershed for lymphoma segmentation in sequential CT images.

Segmentation of lymphoma containing lymph nodes is a difficult task because of multiple variables associated with the tumor's location, intensity distribution, and contrast to its surrounding tissues. In this paper, we present a reliable and practical marker-controlled watershed algorithm for semi-automated segmentation of lymphoma in sequential CT images. Robust determination of internal and external markers is the key to successful use of the marker-controlled watershed transform in the segmentation of lymphoma and is the focus of this work. The external marker in our algorithm is the circle enclosing the lymphoma in a single slice. The internal marker, however, is determined automatically by combining techniques including Canny edge detection, thresholding, morphological operation, and distance map estimation. To obtain tumor volume, the segmented lymphoma in the current slice needs to be propagated to the adjacent slice to help determine the external and internal markers for delineation of the lymphoma in that slice. The algorithm was applied to 29 lymphomas (size range, 9-53 mm in diameter; mean, 23 mm) in nine patients. A blinded radiologist manually delineated all lymphomas on all slices. The manual result served as the "gold standard" for comparison. Several quantitative methods were applied to objectively evaluate the performance of the segmentation algorithm. The algorithm received a mean overlap, overestimation, and underestimation ratios of 83.2%, 13.5%, and 5.5%, respectively. The mean average boundary distance and Hausdorff boundary distance were 0.7 and 3.7 mm. Preliminary results have shown the potential of this computer algorithm to allow reliable segmentation and quantification of lymphomas on sequential CT images.

Lymph node segmentation from CT images using fast marching method.

Accurate lymph node size analysis is important medically. This paper presents an improved fast marching method to perform semi-automatic segmentation for lymph node from CT images. In this work, we have incorporated the gray scale information of the target region into the fast marching speed term and have given a hard constraint for the stop criteria, instead of only using the spatial image gradient, to remedy the 'boundary leaking' problem of the traditional fast marching method. Various experimental results are provided to demonstrate the effectiveness of the proposed method.