Computer-Aided Detection and Characterization of Micro-Dynamic Responses of a Large Deployable Precision Structure

A programmable origami-inspired space deployable structure with curved surfaces

Background: This study aimed to compare the reproducibility and reliability of the AI-supported WebCeph and app-aided OneCeph cephalometric analysis programs with a manual analysis method and to evaluate the analysis times. Methods: The study material consisted of pretreatment lateral cephalograms from 110 cases. Cephalometric analyses were performed manually, using the WebCeph program, and using the OneCeph application. A total of 11 skeletal, 6 dental, and 3 soft tissue parameters were measured. Cephalometric analyses of 30 randomly selected cases were performed again using three methods. The analysis times were recorded. Results: The WebCeph program and OneCeph application are highly compatible with the manual analysis method in terms of all parameters, except for SN measurement. It was found that the WebCeph program and the OneCeph application demonstrated moderate agreement in U1-NA distance measurement, while statistically high agreement was observed among all three methods for other dental parameters. It was determined that there was a moderate agreement among the methods in terms of nasolabial angle, whereas a statistically high level of agreement was found for the other soft tissue parameters. The analysis time was found to be the lowest in the WebCeph program and the highest in the manual analysis method. Conclusions: The WebCeph program and OneCeph application showed a high degree of compatibility with the manual analysis method, except for SN, SNA, Gonial angle, Articular angle, U1-NA distance and nasolabial angle measurements. Due to the higher correlation between OneCeph and the manual method, it can be concluded that the OneCeph application is the best alternative to the manual method.

Elastic Memory Composite (EMC) materials exhibit many favorable qualities for deployable space structures and have piqued a broad interest within America's deployable space structures industry. EMC materials are similar to traditional fiber-reinforced composites except for the use of a thermoset shape memory resin that enables EMC materials to achieve much higher failure strains than traditional composites when exercised through a very specific thermomechanical load cycle. This unique behavior is exploited in the development of EMC structural components that exhibit very high packaging-strain capability while guaranteeing predictable postdeployment structural performance. This paper presents a review of the current state of development of EMC technologies and EMC deployable space structure components. The paper is intended primarily to help potential users of EMC materials develop a better understanding of the special capabilities of EMC materials and considerations that must be applied while engineering with EMC materials.

Shape memory polymers (SMPs) are a new type of smart material, they perform large reversible deformation with a certain external stimulus (e.g., heat and electricity). The properties (e.g., stiffness, strength and other mechanically static or quasi-static load-bearing capacity) are primarily considered for conventional resin-based composite materials which are mainly used for structural materials. By contrast, the mechanical actuating performance with finite deformation is considered for the shape memory polymers and their composites which can be used for both structural materials and functional materials. For shape memory polymers and their composites, the performance of active deformation is expected to further promote the development in smart active deformation structures, such as deployable space structures and morphing wing aircraft. The shape memory polymer composites (SMPCs) are also one type of High Strain Composite (HSC). The space deployable structures based on carbon fiber reinforced shape memory polymer composites (SMPCs) show great prospects. Considering the problems that SMPCs are difficult to meet the practical applications in space deployable structures in the recent ten years, this paper aims to research the mechanics of deformation, and failure of SMPCs. In the overall view of the shape memory polymer material’s nonlinearity (nonlinearity and stress softening in the process of pre-deformation and recovery, relaxation in storage process, irreversible deformation), by the multiple verifications among theory, finite element and experiments, one obtains the deformation and mechanism for the process of “pre-deformation, energy storage and actuation and its non-fracture constraint domain. Then, the parameters of SMPCs will be optimized. Theoretical analysis is realized by the strain energy function, additionally considering the interaction strain energy between the fiber and the matrix. For the common resin-based or soft-material-based composites under pure bending deformation, we expect to uniformly explain the whole process of buckling occurrence, evolution and finally failure, especially for the early evolution characteristics of fiber microbuckling inside the microstructures. The research results are meaningful for the practical applications for SMPC deployable structures in space. Considering the deformation mechanisms of SMPCs, the local post-microbuckling is required for the unidirectional fiber reinforced composite materials, at the conditions of its large geometrical deflection. The cross section of SMPC is divided into three areas: non-buckling stretching area, non-buckling compressive area, and buckling compressive area. Three variables are considered: critical buckling position, and neutral plane, the fiber buckling half-wavelength. Considering the condition of the small strain and large displacement, the strain energy expression of the SMP/fiber system was derived, which contains two types, e.g., strain energy of SMP and fiber. According to the minimum energy principle, the expression for all key parameters were derived, including the critical buckling curvature, neutral plane position, the buckling half-wavelength, fiber buckling amplitude, and strain.

The amplification status of human epidermal growth factor receptors 2 (HER2) genes is strongly associated with clinical outcome in patients with breast cancer. The American Society of Clinical Oncology Tumor Marker Guidelines Panel has recommended routine testing of HER2 status on all newly diagnosed metastatic breast cancers since 2001. Although fluorescent in situ hybridization (FISH) technology provides superior accuracy as compared with other approaches, current manual FISH analysis methods are somewhat subjective, tedious, and may introduce interreader variability. The goal of this preliminary study is to develop and test a computer-aided detection (CAD) scheme to assess HER2 status using FISH images. Forty FISH images were selected for this study from our genetic laboratory. The CAD scheme first applies an adaptive, iterative threshold method followed by a labeling algorithm to segment cells of possible interest. A set of classification rules is then used to identify analyzable interphase cells and discard nonanalyzable cells due to cell overlapping and/or other image staining debris (or artifacts). The scheme then maps the detected analyzable cells onto two other gray scale images corresponding to the red and green color of the original image followed by application of a raster scan and labeling algorithms to separately detect the HER-2/neu ("red") and CEP17 ("green") FISH signals. A simple distance based criterion is applied to detect and merge split FISH signals within each cell. The CAD scheme computes the ratio between independent "red" and "green" FISH signals of all analyzable cells identified on an image. If the ratio is ≥ 2.0, the FISH image is assumed to have been acquired from a HER2+ case; otherwise, the FISH image is assumed to have been acquired from HER2- case. When we applied the CAD scheme to the testing dataset, the average computed HER2 amplification ratios were 1.06±0.25 and 2.53±0.81 for HER2- and HER2+ samples, respectively. The results show that the CAD scheme has the ability to automatically detect HER2 status using FISH images. The success of CAD-guided FISH image analysis could result in a more objective, consistent, and efficient approach in determining HER2 status of breast cancers.

BackgroundThe use of artificial intelligence (AI) can revolutionize health care, but this raises risk concerns. It is therefore crucial to understand how clinicians trust and accept AI technology. Gastroenterology, by its nature of being an image-based and intervention-heavy specialty, is an area where AI-assisted diagnosis and management can be applied extensively.ObjectiveThis study aimed to study how gastroenterologists or gastrointestinal surgeons accept and trust the use of AI in computer-aided detection (CADe), computer-aided characterization (CADx), and computer-aided intervention (CADi) of colorectal polyps in colonoscopy.MethodsWe conducted a web-based questionnaire from November 2022 to January 2023, involving 5 countries or areas in the Asia-Pacific region. The questionnaire included variables such as background and demography of users; intention to use AI, perceived risk; acceptance; and trust in AI-assisted detection, characterization, and intervention. We presented participants with 3 AI scenarios related to colonoscopy and the management of colorectal polyps. These scenarios reflect existing AI applications in colonoscopy, namely the detection of polyps (CADe), characterization of polyps (CADx), and AI-assisted polypectomy (CADi).ResultsIn total, 165 gastroenterologists and gastrointestinal surgeons responded to a web-based survey using the structured questionnaire designed by experts in medical communications. Participants had a mean age of 44 (SD 9.65) years, were mostly male (n=116, 70.3%), and mostly worked in publicly funded hospitals (n=110, 66.67%). Participants reported relatively high exposure to AI, with 111 (67.27%) reporting having used AI for clinical diagnosis or treatment of digestive diseases. Gastroenterologists are highly interested to use AI in diagnosis but show different levels of reservations in risk prediction and acceptance of AI. Most participants (n=112, 72.72%) also expressed interest to use AI in their future practice. CADe was accepted by 83.03% (n=137) of respondents, CADx was accepted by 78.79% (n=130), and CADi was accepted by 72.12% (n=119). CADe and CADx were trusted by 85.45% (n=141) of respondents and CADi was trusted by 72.12% (n=119). There were no application-specific differences in risk perceptions, but more experienced clinicians gave lesser risk ratings.ConclusionsGastroenterologists reported overall high acceptance and trust levels of using AI-assisted colonoscopy in the management of colorectal polyps. However, this level of trust depends on the application scenario. Moreover, the relationship among risk perception, acceptance, and trust in using AI in gastroenterology practice is not straightforward.

Thin-walled structures utilizing the release of stored strain energy for self-deployment have gained popularity in deployable space structures. However, the integration of traditional rigid or bulky sensors to monitor their mechanical behavior presents challenges due to large local deformations and strains involved in folding and deployment. Here we introduce a concept of structural electronic skin (e-skin) that is soft, lightweight, and designed for sensing the folding and deployment of tape-spring hinges. The e-skin demonstrates the capability to accommodate significant hinge deformation and enables multimodal sensing, including strain measurements, motion sensing, and dynamics monitoring. The research showcases a promising approach that leverages the design and manufacturing of soft electronics to fulfill the requirements of thin, lightweight, and soft functional devices for multifunctionality in deployable space structures.

Stereological methods, using the principle of point counting and unbiased counting frames, for the estimation of muscle area, total fibre area, number of muscle fibres and mean fibre area are described in detail. Their practical application is demonstrated on cross-sections of the rat soleus muscles. It is shown that the efficiency of these methods is high and their results are comparable with those achieved by the conventional manual and image analysis methods. The main advantages of two-dimensional stereological methods in muscle morphometry are pointed out: measurements are made directly on specimens under the microscope and in the simplest implementation do not require sophisticated and expensive technical equipment. Furthermore, unbiased results are obtained, no segmentation and edge effect problems arise and the quantity of work invested in stereological estimation is reasonable. Based upon the study of the efficiency of used stereological methods, a suitable test system for muscle morphometry is proposed.

Deployable space structure control using adaptive predictive controller with notch filter

Purpose: This study aims to reveal research trends by revealing the evaluation in this field by making a holistic analysis of academic studies that have examined the concepts of innovation and productivity in the last five decades. This analysis aims to reveal the general structure of academic studies that deal with the concepts of innovation and productivity. Methodology: Articles searched in the ‘‘Social Science Citation Index (SSCI)’’, ‘‘Science Citation Index Expanded (SCI-EXPANDED)’’ and ‘‘Emerging Sources Citation Index (ESCI)’’ in the ‘‘Web of Science (WoS)’’ database, researching innovation and productivity together between 1980-2023. It was analysed and mapped using the VOSviewer 1.6.19 software and manual methods. Co-occurrence Keyword Analysis, Document Co-citation Analysis and manual analysis methods were used in the mapping. Findings: This study reveals how research in innovation and productivity has developed over the last five decades and what trends it has. It has been determined that the most published areas are Economy, Management and Business. The most frequently used keywords were found to be "innovation", "productivity", "research-and-development", "growth", "performance" and "impact". The most published topics on a cluster basis are "impact", "innovation and productivity", "growth", "research and development" and "performance", respectively. In the document co-citation analysis, it was determined that the publication in which all publications were linked included the study titled "Research, Innovation and Productivity: an econometric analysis at the firm level", published by Crépon et al. (1998). This information can be a valuable resource for future research and policy-making and can be used to drive innovation and productivity progress. Originality: While the study is the first and only content analysis to reveal the combined trends in this field by examining the "innovation and productivity" studies together, it is thought that the results obtained can guide researchers and professionals.

Accurate islet quantification has proven difficult to standardize in a good manufacturing practices (GMP) approved manner. The influence of assessment variables from both manual and computer-assisted digital image analysis (DIA) methods were compared using calibrated, standardized microspheres or islets alone. Additionally, a mixture of microspheres and exocrine tissue was used to evaluate the variability of both the current, internationally recognized, manual method and a novel GMP-friendly purity- and volume-based method (PV) evaluated by DIA in a semiclosed, culture bag system. Computer-assisted DIA recorded known microsphere size distribution and quantities accurately. By using DIA to evaluate islets, the interindividual manually evaluated percent coefficients of variation (CV%; n=14) were reduced by almost half for both islet equivalents (IEs; 31% vs. 17%, P=0.002) and purity (20% vs. 13%, P=0.033). The microsphere pool mixed with exocrine tissue did not differ from expected IE with either method. However, manual IE resulted in a total CV% of 44.3% and a range spanning 258 k IE, whereas PV resulted in CV% of 10.7% and range of 60 k IE. Purity CV% for each method were similar approximating 10.5% and differed from expected by +7% for the manual method and +3% for PV. The variability of standard counting methods for islet samples and clinical quantities of microspheres mixed with exocrine tissue were reduced with DIA. They were reduced even further by use of a semiclosed bag system compared with standard manual counting, thereby facilitating the standardization of islet evaluation according to GMP standards.

Space structures, such as space station, solar arrays, deployable and inflatable structures are large and flexible. These structures undergo orbital rigid body motion and large structural deformations under space environmental loadings. In this paper, a finite element methodology based on the parallel reference frames, which combines features of the floating frame of reference and the absolute coordinate formulations, has been developed to study the large deformation, non- linear, coupled orbital and 3-D structural response of an orbiting flexible structures. The analytical formulation consists of two sets of reference frames: one is the fixed coordinate system which describes the location of the second coordinate system; the second set, whose axes are parallel to the first set and is attached to the mass center of the structure, describes the local position of the body. The formulation includes both bending and axial structural flexibilities. Applications and results of this formulation have been presented for dynamics of a flexible beam-type orbiting structure. Results in terms of time variation of structural displacement, orbital, and attitude responses are presented and discussed.

The article describes the local deformation method to determine the tension of cord and thin membrane elements in space deployable structure as antenna reflector. Possible measuring instrument model, analytical and numerical solutions and experimental results are presented. The boundary effects on measurement results of metallic mesh reflector surface tension are estimated. The study case depicting non-uniform reflector surface tension is considered.

Radiomics has a long-standing history in breast imaging with computer-aided detection (CAD) for screening mammography developed in the late 20th century. Although conventional CAD had widespread adoption, the clinical benefits for experienced breast radiologists were debatable due to high false-positive marks and subsequent increased recall rates. The dramatic growth in recent years of artificial intelligence-based analysis, including machine learning and deep learning, has provided numerous opportunities for improved modern radiomics work in breast imaging. There has been extensive radiomics work in mammography, digital breast tomosynthesis, MRI, ultrasound, PET-CT, and combined multimodality imaging. Specific radiomics outcomes of interest have been diverse, including CAD, prediction of response to neoadjuvant therapy, lesion classification, and survival, among other outcomes. Additionally, the radiogenomics subfield that correlates radiomics features with genetics has been very proliferative, in parallel with the clinical validation of breast cancer molecular subtypes and gene expression assays. Despite the promise of radiomics, there are important challenges related to image normalization, limited large unbiased data sets, and lack of external validation. Much of the radiomics work to date has been exploratory using single-institution retrospective series for analysis, but several promising lines of investigation have made the leap to clinical practice with commercially available products. As a result, breast radiologists will increasingly be incorporating radiomics-based tools into their daily practice in the near future. Therefore, breast radiologists must have a broad understanding of the scope, applications, and limitations of radiomics work.

Finite element modeling of flexible articulated systems has been one of the major development axes at the Aerospace Laboratory of the University of Liege (Belgium) since 1985. The resulting MECANO software [16] (integrated in the larger finite element package SAMCEF) has already demonstrated its powerfulness to simulate motion and dynamics of complex mechanical systems of various natures such as landing gears, energy release springs, gear box transmissions, missile ejection systems, vehicle suspensions, ski bindings, deployable space structures, etc ...