Thin shell structures are widely used in the aerospace, automotive and mechanical engineering industries. They are ideal candidates for the isogeometric analysis paradigm profiting from the ...smoothness of the geometry model, and the higher order approximation and higher continuity properties of NURBS. To model complex shell structures which need to be assembled from multiple patches, the bending stiffness should be maintained across the patch interfaces. We propose a variationally consistent weak coupling method for thin-walled shell patches. The method overcomes the need for C1-continuity along the patch interface to ensure a corresponding geometric continuity in the deformed configuration and a correct transfer of bending moments across the interface. Importantly, it allows a blended coupling of shells based on different mathematical models, e.g. Kirchhoff–Love and solid-like shell models. The proposed approach retains the high level of accuracy of single patch solutions and reveals its potential for authentic multi-patch NURBS modeling. We illustrate the good performance of the method for pure Kirchhoff–Love shell models and blended shell models with various examples. The presented approach supports local model refinements where e.g. full 3D stress states are of interest, and further opens the door for the coupling of laminated composites belonging to different lamina theories.
•We propose a weak coupling method for thin Kirchhoff–Love NURBS shell patches.•G1-continuity is preserved thus preventing hinge effects of C0-continuous patches.•Our method retains prescribed angles of folded shells structures.•We consider a blended coupling of solid-like patches and KL shell patches.•We demonstrate convergence and accuracy with several numerical studies and examples.
Background In medical imaging, the integration of deep-learning-based semantic segmentation algorithms with preprocessing techniques can reduce the need for human annotation and advance disease ...classification. Among established preprocessing techniques, Contrast Limited Adaptive Histogram Equalization (CLAHE) has demonstrated efficacy in improving segmentation algorithms across various modalities, such as X-rays and CT. However, there remains a demand for improved contrast enhancement methods considering the heterogeneity of datasets and the various contrasts across different anatomic structures. Method This study proposes a novel preprocessing technique, ps-KDE, to investigate its impact on deep learning algorithms to segment major organs in posterior-anterior chest X-rays. Ps-KDE augments image contrast by substituting pixel values based on their normalized frequency across all images. We evaluate our approach on a U-Net architecture with ResNet34 backbone pre-trained on ImageNet. Five separate models are trained to segment the heart, left lung, right lung, left clavicle, and right clavicle. Results The model trained to segment the left lung using ps-KDE achieved a Dice score of 0.780 (SD = 0.13), while that of trained on CLAHE achieved a Dice score of 0.717 (SD = 0.19), p <0.01. ps-KDE also appears to be more robust as CLAHE-based models misclassified right lungs in select test images for the left lung model. The algorithm for performing ps-KDE is available at https://github.com/wyc79/ps-KDE . Discussion Our results suggest that ps-KDE offers advantages over current preprocessing techniques when segmenting certain lung regions. This could be beneficial in subsequent analyses such as disease classification and risk stratification.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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•China’s urban green space loss in 2003–2015 was equivalent to losing an area of 46.4 soccer fields per day.•Every 1 million growth of urban residents accompanied a decline of ...50.9 ± 3.33 m2 green space per capita.•The cooling of green space increased while the area of cooling space decreased.•Urban residents locating outside the cooling space increased by 4.23 × 106 people per year.
Urban green spaces (UGSs) reduce the surrounding temperature and create cooling areas as a buffer between people and high temperatures, thus helping residents adapt to the warming climate. However, the accessibility of UGS cooling services to the residents of cities remains largely unknown, which hinders decision-making regarding the formulation of climate adaptation and urban greening schemes. In the present study, we estimated the number of residents who accessed UGSs for cooling by analyzing the annual changes in such cooling areas during summer across 315 Chinese cities from 2003 to 2015. Approximately 93.3% of the cities showed significant decreasing trends (p < 0.05) of the total UGS area; as such the UGS coverage dropped from 12.23 ± 0.32% in 2003 to 7.69 ± 0.22% in 2015. Consequently, with the prevalent loss of UGS, the coverage of cooling spaces decreased from 32.55 ± 0.76% in 2003 to 24.39 ± 0.60% in 2015. This has formed a spatial mismatch between the growing urban population and the remaining UGSs. Accordingly, the number of residents of areas outside these cooling spaces increased by 4.23 million per year. In particular, the shortage of cooling services was more significant in cities with < 20,000 USD gross domestic product per capita and < 5 million residents than in the rest of the cities. To minimize the adverse impacts of increasing temperatures, focused greening plans are warranted, specifically in underdeveloped cities.
General target detection with deep learning has made tremendous strides in the past few years. However, small target detection sometimes is associated with insufficient sample size and difficulty in ...extracting complete feature information. For safety during autonomous driving, remote signs and pedestrians need to be detected from driving scenes photographed by car cameras. In the early period of a medical lesion, because of the small area of the lesion, target detection is of great significance to detect masses and tumors for accurate diagnosis and treatment. To deal with these problems, we propose a novel deep learning model, named CenterNet for small targets (ST-CenterNet). First of all, due to the lack of visual information on small targets in the dataset, we extracted less discriminative features. To overcome this shortcoming, the proposed selective small target replication algorithm (SSTRA) was used to realize increasing numbers of small targets by selectively oversampling them. In addition, the difficulty of extracting shallow semantic information for small targets results in incomplete target feature information. Consequently, we developed a target adaptation feature extraction module (TAFEM), which was used to conduct bottom-up and top-down bidirectional feature extraction by combining ResNet with the adaptive feature pyramid network (AFPN). The improved new network model, AFPN, was added to solve the problem of the original feature extraction module, which can only extract the last layer of the feature information. The experimental results demonstrate that the proposed method can accurately detect the small-scale image of distributed targets and simultaneously, at the pixel level, classify whether a subject is wearing a safety helmet. Compared with the detection effect of the original algorithm on the safety helmet wearing dataset (SHWD), we achieved mean average precision (mAP) of 89.06% and frames per second (FPS) of 28.96, an improvement of 18.08% mAP over the previous method.
Phosphorescent material is widely used in light-emitting devices and in the monitoring of cell phenomena. Anthraquinone compounds (AQs), as important phosphorescent materials, have potential ...applications as emitters for highly efficient organic light-emitting diodes (OLEDs). Therefore, the accurate calculation of the phosphorescence energy of anthraquinone compounds is particularly important. This study mainly analyzes the phosphorescence energy calculation method of anthraquinone compounds. The time-dependent density functional theory (TDDFT) and the unrestricted density functional theory (UDFT) with seven functionals are selected to calculate the phosphorescence of AQs, taking the high-precision coupled-cluster singles and doubles (CC2) method as a reference. The results showed that the mean unsigned error (MUE) of UDFT was 0.14
, which was much smaller than that of TDDFT at 0.29
. Therefore, UDFT was more suitable for calculating the phosphorescence energy of AQs. The results obtained by different functionals indicate that the minimum MUE obtained by M06-2X was 0.14
. More importantly, the diffuse function in the basis set played an important role in calculating the phosphorescence energy in the M06-HF functional. In the BDBT, FBDBT, and BrBDBT, when M06-HF selected the basis set containing a diffuse function, the differences with CC2 was 0.02
, which is much smaller than the one obtained without a diffuse function at 0.80
. These findings might be of great significance for the future study of the phosphorescence energy of organic molecules.
Chondroitin sulfate (CS) is a natural macromolecule polysaccharide that is extensively distributed in a wide variety of organisms. CS is of great interest to researchers due to its many in vitro and ...in vivo functions. CS production derives from a diverse number of sources, including but not limited to extraction from various animals or fish, bio-synthesis, and fermentation, and its purity and homogeneity can vary greatly. The structural diversity of CS with respect to sulfation and saccharide content endows this molecule with distinct complexity, allowing for functional modification. These multiple functions contribute to the application of CS in medicines, biomaterials, and functional foods. In this article, we discuss the preparation of CS from different sources, the structure of various forms of CS, and its binding to other relevant molecules. Moreover, for the creation of this article, the functions and applications of CS were reviewed, with an emphasis on drug discovery, hydrogel formation, delivery systems, and food supplements. We conclude that analyzing some perspectives on structural modifications and preparation methods could potentially influence future applications of CS in medical and biomaterial research.
To explore the effects of a 'Rebuilding Myself' intervention on enhancing the adaptability of cancer patients to return to work.
A single-center, single-blind, randomized controlled trial design was ...used. Eligible patients who were receiving routine hospital treatment were recruited from the university-affiliated hospital in our city. Patients in the control group only received usual care, while patients in the intervention group received additional 'Rebuilding Myself' intervention. Adaptability to return to work, self-efficacy of returning to work, mental resilience, quality of life and work ability were measured at baseline, the 6th and 12th of the intervention. The general estimation equations were used to compare the overall changes of each outcome index between the two groups at different time points. Considering that there may be patient shedding and rejection, Per-Protocol and Intention-to-Treat analysis were used to analyze the data in this study.
There were statistically significant differences between the two groups of patients in the cancer patients' adaptability to return to work, self-efficacy to return to work, mental resilience, work abilities, the physical, emotional, cognitive function, fatigue, insomnia and overall health status dimensions of quality of life (P < 0.05). And no significant difference was found in other dimensions (P > 0.05). The group effect, time effect, and interaction effect of patients' return to work adaptability and return to work self-efficacy were statistically significant in both groups (P < 0.05). Mental resilience, working ability, and quality of life had obvious time effect and interaction effect (P < 0.05).
This intervention could improve cancer patients' adaptability to return to work, self-efficacy to return to work, mental resilience, work abilities and quality of life. And it can be further expanded to improve the adaptability of patients to return to work, then to help patients achieve comprehensive rehabilitation.
The application of 'Rebuilding Myself' interventions can effectively improve the adaptability of cancer patients returning to work.
This study was registered at the Chinese Clinical Trial Registry (Registration number: ChiCTR2200057943) on 23 March, 2022.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
L-arginine (Arg), a semi-essential amino acid, has recently been shown to attenuate inflammatory response during cardiovascular disease. NLRP3 inflammasome serves a central role in amplification of ...cellular inflammation. In this study, we aimed to confirm the modulatory effect of Arg on NLRP3 inflammasome and the underlying mechanisms in vascular endothelial cells (ECs). Arg suppressed NLRP3 inflammasome activation in ECs stimulated with lipopolysaccharide (LPS) and adenosine triphosphate (ATP). Moreover, treatment with Arg increased the expression of the deacetylase sirtuin 1 (SIRT1) in ECs. Importantly, knockdown of SIRT1 abolished the inhibitory potential of Arg on the activation of NLRP3 inflammasome. Further study indicated that Arg also alleviated LPS plus ATP-induced the generation of reactive oxygen species (ROS) in ECs. In addition, Arg may regulate NLRP3 inflammasome activation partly through suppression of ROS production. In combination, we speculate that Arg exerts an inhibitory effect on the activation of NLRP3 inflammasome in ECs, which may be partly mediated by SIRT1 and ROS.
This work explores the electronic structure as well as the reactivity of singlet diradicals, making use of multistate density functional theory (MSDFT). In particular, we show that a minimal active ...space of two electrons in two orbitals is adequate to treat the relative energies of the singlet and triplet adiabatic ground state as well as the first singlet excited state in many cases. This is plausible because dynamic correlation is included in the first place in the optimization of orbitals in each determinant state via block-localized Kohn-Sham density functional theory. In addition, molecular fragment, i.e., block-localized Kohn-Sham orbitals, are optimized separately for each determinant, providing a variational diabatic representation of valence bond-like states, which are subsequently used in nonorthogonal state interactions (NOSIs). The computational procedure and its performance are illustrated on some prototypical diradical species. It is shown that NOSI calculations in MSDFT can be used to model bond dissociation and hydrogen-atom transfer reactions, employing a minimal number of configuration state functions as the basis states. For p- and s-types of diradicals, the closed-shell diradicals are found to be more reactive than the open-shell ones due to a larger diabatic coupling with the final product state. Such a diabatic representation may be useful to define reaction coordinates for electron transfer, proton transfer and coupled electron and proton transfer reactions in condensed-phase simulations.
In this study, raw and sappanwood-dyed silks were exposed to varying concentrations of acetic acid vapor to investigate aging degradation by colorimetry, SEM, FTIR, ATR-FTIR, and HPLC. The findings ...illustrate that acetic acid gas could lead to increase in color difference, decrease in the relative contents of crystalline regions, and changes in amino acid contents. Therefore, the aging process could be characterized as a progressive procedure: (i) initial stages were marked by color changes, (ii) gradual acid hydrolysis occurred within the protein crystalline region in the intermediate phase, and (iii) diverse trends of increase or decrease in different amino acids prevailed during the final stage of aging. Additionally, raw and sappanwood-dyed silks deteriorated further with acetic acid solution. Colorimetry and SEM showed more severe damage in dyed silk with rougher surfaces and more fiber breakage, indicating that acidic gas in water could cause greater damage and highlighted greater vulnerability of dyed silk. This study innovatively used multiple analytical methods to explore the long-term effects of acidic environments on silk and filled gaps in gas-induced aging research. It emphasized the necessity and importance of addressing gas pollution in museums and sounded the alarm of its damaging effects on silk artifacts.
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