A Novel Efficient Prediction Method for Microscopic Stresses of Periodic Beam-like Structures

This paper presents a novel superposition method for effectively predicting the microscopic stresses of heterogeneous periodic beam-like structures. The efficiency is attributed to using the microscopic stresses of the unit cell problem under six generalized strain states to construct the structural microscopic stresses. The six generalized strain states include one unit tension strain, two unit bending strains, one unit torsion strain, and two linear curvature strains of a Timoshenko beam. The six microscopic stress solutions of the unit cell problem under these six strain states have previously been used for the homogenization of composite beams to equivalent Timoshenko beams (Acta. Mech. Sin. 2022, 38, 421520), and they are employed in this work. In the first step of achieving structural stresses, two stress solutions concerning linear curvatures are transformed into two stress solutions concerning unit shear strains by linearly combining the stresses under two unit bending strains. Then, the six stress solutions corresponding to six generalized unit beam strains are combined together to predict the structural microscopic stresses, in which the six stress solutions serve as basic stresses. The last step is to determine the coefficients of these six basic stress solutions by the principle of the internal work equivalence. It is found that the six coefficients, in terms of the product of the inverse of the effective stiffness matrix and the macroscopic internal force column vector, are the actual generalized strains of the equivalent beam under real loads. The obtained coefficients are physically reasonable because the basic stress solutions are produced by the generalized unit strains. Several numerical examples show that the present method, combining the solutions of the microscopic unit cell problem with the solutions of the macroscopic equivalent beam problem, can accurately and effectively predict the microscopic stresses of whole composite beams. The present method is applicable to composite beams with arbitrary periodic microstructures and load conditions

A Novel Efficient Prediction Method for Microscopic Stresses of Periodic Beam-like Structures

This paper presents a novel superposition method for effectively predicting the microscopic stresses of heterogeneous periodic beam-like structures. The efficiency is attributed to using the microscopic stresses of the unit cell problem under six generalized strain states to construct the structural microscopic stresses. The six generalized strain states include one unit tension strain, two unit bending strains, one unit torsion strain, and two linear curvature strains of a Timoshenko beam. The six microscopic stress solutions of the unit cell problem under these six strain states have previously been used for the homogenization of composite beams to equivalent Timoshenko beams (Acta. Mech. Sin. 2022, 38, 421520), and they are employed in this work. In the first step of achieving structural stresses, two stress solutions concerning linear curvatures are transformed into two stress solutions concerning unit shear strains by linearly combining the stresses under two unit bending strains. Then, the six stress solutions corresponding to six generalized unit beam strains are combined together to predict the structural microscopic stresses, in which the six stress solutions serve as basic stresses. The last step is to determine the coefficients of these six basic stress solutions by the principle of the internal work equivalence. It is found that the six coefficients, in terms of the product of the inverse of the effective stiffness matrix and the macroscopic internal force column vector, are the actual generalized strains of the equivalent beam under real loads. The obtained coefficients are physically reasonable because the basic stress solutions are produced by the generalized unit strains. Several numerical examples show that the present method, combining the solutions of the microscopic unit cell problem with the solutions of the macroscopic equivalent beam problem, can accurately and effectively predict the microscopic stresses of whole composite beams. The present method is applicable to composite beams with arbitrary periodic microstructures and load conditions

Differences in the phenotypes and transcriptomic signatures of chimeric antigen receptor T lymphocytes manufactured via electroporation or lentiviral transfection

Chimeric antigen receptor (CAR)-T cell therapy is an innovative treatment for CD19-expressing lymphomas. CAR-T cells are primarily manufactured via lentivirus transfection or transposon electroporation. While anti-tumor efficacy comparisons between the two methods have been conducted, there is a current dearth of studies investigating the phenotypes and transcriptome alterations induced in T cells by the two distinct manufacturing methods. Here, we established CAR-T signatures using fluorescent imaging, flow cytometry, and RNA-sequencing. A small fraction of CAR-T cells that were produced using the PiggyBac transposon (PB CAR-T cells) exhibited much higher expression of CAR than those produced using a lentivirus (Lenti CAR-T cells). PB and Lenti CAR-T cells contained more cytotoxic T cell subsets than control T cells, and Lenti CAR-T cells presented a more pronounced memory phenotype. RNA-sequencing further revealed vast disparities between the two CAR-T cell groups, with PB CAR-T cells exhibiting greater upregulation of cytokines, chemokines, and their receptors. Intriguingly, PB CAR-T cells singularly expressed IL-9 and fewer cytokine release syndrome-associated cytokines when activated by target cells. In addition, PB CAR-T cells exerted faster in vitro cytotoxicity against CD19-expressing K562 cells but similar in vivo anti-tumor efficacy with Lenti CAR-T. Taken together, these data provide insights into the phenotypic alterations induced by lentiviral transfection or transposon electroporation and will attract more attention to the clinical influence of different manufacturing procedures

CRISPR/Cas9-Mediated Disruption of <i>Endo16</i> Cis-Regulatory Elements in Sea Urchin Embryos

Sea urchins have become significant mariculture species globally, and also serve as invertebrate model organisms in developmental biology. Cis-regulatory elements (enhancers) control development and physiology by regulating gene expression. Mutations that affect the function of these sequences may contribute to phenotypic diversity. Cis-regulatory targets offer new breeding potential for the future. Here, we use the CRISPR/Cas9 system to disrupt an enhancer of Endo16 in developing Lytechinus variegatus embryos, in consideration of the thorough research on Endo16’s regulatory region. We designed six gRNAs against Endo16 Module A (the most proximal region of regulatory sequences, which activates transcription in the vegetal plate and archenteron, specifically) and discovered that Endo16 Module A-disrupted embryos failed to undergo gastrulation at 20 h post fertilization. This result partly phenocopies morpholino knockdowns of Endo16. Moreover, we conducted qPCR and clone sequencing experiments to verify these results. Although mutations were not found regularly from sequencing affected individuals, we discuss some potential causes. In conclusion, our study provides a feasible and informative method for studying the function of cis-regulatory elements in sea urchins, and contributes to echinoderm precision breeding technology innovation and aquaculture industry development

Crosstalk Defect Detection Method Based on Salient Color Channel Frequency Domain Filtering

Display crosstalk defect detection is an important link in the display quality inspection process. We propose a crosstalk defect detection method based on salient color channel frequency domain filtering. Firstly, the salient color channel in RGBY is selected by the maximum relative entropy criterion, and the color quaternion matrix of the displayed image is formed with the Lab color space. Secondly, the image color quaternion matrix is converted into the logarithmic spectrum in the frequency domain through the hyper-complex Fourier transform. Finally, Gaussian threshold band-pass filtering and hyper-complex inverse Fourier transform are used to separate the low-contrast defects and background of the display image. The experimental results show that the accuracy of the proposed algorithm reaches 96% for a variety of crosstalk defect detection. Compared with the current advanced defect detection algorithms, the effectiveness of the proposed method for low-contrast crosstalk defect detection is confirmed

Disentangled Dynamic Deviation Transformer Networks for Multivariate Time Series Anomaly Detection

Graph neural networks have been widely used by multivariate time series-based anomaly detection algorithms to model the dependencies of system sensors. Previous studies have focused on learning the fixed dependency patterns between sensors. However, they ignore that the inter-sensor and temporal dependencies of time series are highly nonlinear and dynamic, leading to inevitable false alarms. In this paper, we propose a novel disentangled dynamic deviation transformer network (D3TN) for anomaly detection of multivariate time series, which jointly exploits multiscale dynamic inter-sensor dependencies and long-term temporal dependencies to improve the accuracy of multivariate time series prediction. Specifically, to disentangle the multiscale graph convolution, we design a novel disentangled multiscale aggregation scheme to better represent the hidden dependencies between sensors to learn fixed inter-sensor dependencies based on static topology. To capture dynamic inter-sensor dependencies determined by real-time monitoring situations and unexpected anomalies, we introduce a self-attention mechanism to model dynamic directed interactions in various potential subspaces influenced by various factors. In addition, complex temporal correlations across multiple time steps are simulated by processing the time series in parallel. Experiments on three real datasets show that the proposed D3TN significantly outperforms the state-of-the-art methods

Redox-tunable isoindigos for electrochemically mediated carbon capture

Abstract Efficient CO2 separation technologies are essential for mitigating climate change. Compared to traditional thermochemical methods, electrochemically mediated carbon capture using redox-tunable sorbents emerges as a promising alternative due to its versatility and energy efficiency. However, the undesirable linear free-energy relationship between redox potential and CO2 binding affinity in existing chemistry makes it fundamentally challenging to optimise key sorbent properties independently via chemical modifications. Here, we demonstrate a design paradigm for electrochemically mediated carbon capture sorbents, which breaks the undesirable scaling relationship by leveraging intramolecular hydrogen bonding in isoindigo derivatives. The redox potentials of isoindigos can be anodically shifted by >350 mV to impart sorbents with high oxygen stability without compromising CO2 binding, culminating in a system with minimised parasitic reactions. With the synthetic space presented, our effort provides a generalisable strategy to finetune interactions between redox-active organic molecules and CO2, addressing a longstanding challenge in developing effective carbon capture methods driven by non-conventional stimuli