Effective gene-delivery systems for primary human T cell engineering are useful tools for both basic research and clinical immunotherapy applications. Pseudovirus-based systems and ...electro-transfection are the most popular strategies for genetic material transduction. Compared with viral-particle-mediated approaches, electro-transfection is theoretically safer, because it does not promote transgene integration into the host genome. Additionally, the simplicity and speed of the procedure increases the attractiveness of electroporation. Here, we developed and optimized an electro-transfection method for the production of engineered chimeric antigen receptor (CAR)-T cells.
Stimulation of T cells had the greatest effect on their transfection, with stimulation of cells for up to 3 days substantially improving transfection efficiency. Additionally, the strength of the external electric field, input cell number, and the initial amount of DNA significantly affected transfection performance. The voltage applied during electroporation affected plasmid permeation and was negatively correlated with the number of viable cells after electroporation. Moreover, higher plasmid concentration increased the proportion of positively transfected cells, but decreased cell viability, and for single-activated cells, higher cell density enhanced their viability. We evaluated the effects of two clinically relevant factors, serum supplementation in the culture medium and cryopreservation immediately after the isolation of peripheral blood lymphocytes. Our findings showed that our protocol performed well using xeno-free cultured, fresh T cells, with application resulting in a lower but acceptable transfection efficiency of cells cultured with fetal bovine serum or thawed cells. Furthermore, we described an optimized procedure to generate CAR-T cells within 6 days and that exhibited cytotoxicity toward targeted cells.
Our investigation of DNA electro-transfection for the use in human primary T cell engineering established and validated an optimized method for the construction of functional CAR-T cells.
Recognizing fine-grained sub-categories such as birds and dogs is extremely challenging due to the highly localized and subtle differences in some specific parts. Most previous works rely on object / ...part level annotations to build part-based representation, which is demanding in practical applications. This paper proposes an automatic fine-grained recognition approach which is free of any object / part annotation at both training and testing stages. Our method explores a unified framework based on two steps of deep filter response picking. The first picking step is to find distinctive filters which respond to specific patterns significantly and consistently, and learn a set of part detectors via iteratively alternating between new positive sample mining and part model retraining. The second picking step is to pool deep filter responses via spatially weighted combination of Fisher Vectors. We conditionally pick deep filter responses to encode them into the final representation, which considers the importance of filter responses themselves. Integrating all these techniques produces a much more powerful framework, and experiments conducted on CUB-200-2011 and Stanford Dogs demonstrate the superiority of our proposed algorithm over the existing methods.
•Heating surface structure has strong influences on both boiling and condensation.•Equal-width grooved heating surface has the best performance.•Optimum filling ratio existence is confirmed of phase ...change chamber experimentally.•Condensation thermal resistance is the dominant heat transfer resistance.
The influences of the heating surface structure of phase change chamber on heat transfer characteristics are studied by using smooth, equal-width and variable cross-sectional area grooved heating surfaces, and visualization is made of the boiling-condensation coexisting phase change phenomena inside the chamber. The experimental results confirm that there is an optimum working fluid filling ratio for the phase change chamber to acquire its best performance. The optimum filling ratio for the smooth and equal-width grooved heating surface phase change chamber is found to be 36.0% and 11.4%, respectively. The experimental results also disclose that the equal-width grooved heating surface has the best performance and the overall heat transfer coefficient of the phase change chamber is augmented by more than 44% over the smooth heating surface. Although the thermal resistance of condensation is the dominant of the overall heat transfer resistance, it is proved that enhancing boiling is still an efficient way due to the strong interactions between the boiling and condensation processes inside the phase change chamber.
In this paper, we propose a robust framework for building extraction in visible band images. We first get an initial classification of the pixels based on an unsupervised presegmentation. Then, we ...develop a novel conditional random field (CRF) formulation to achieve accurate rooftops extraction, which incorporates pixel-level information and segment-level information for the identification of rooftops. Comparing with the commonly used CRF model, a higher order potential defined on segment is added in our model, by exploiting region consistency and shape feature at segment level. Our experiments show that the proposed higher order CRF model outperforms the state-of-the-art methods both at pixel and object levels on rooftops with complex structures and sizes in challenging environments.
Distinguishing between natural images (NIs) and computer-generated (CG) images by naked human eyes is difficult. In this paper, we propose an effective method based on a convolutional neural network ...(CNN) for this fundamental image forensic problem. Having observed the rather limited performance of training existing CCNs from scratch or fine-tuning pre-trained network, we design and implement a new and appropriate network with two cascaded convolutional layers at the bottom of a CNN. Our network can be easily adjusted to accommodate different sizes of input image patches while maintaining a fixed depth, a stable structure of CNN, and a good forensic performance. Considering the complexity of training CNNs and the specific requirement of image forensics, we introduce the so-called local-to-global strategy in our proposed network. Our CNN derives a forensic decision on local patches, and a global decision on a full-sized image can be easily obtained via simple majority voting. This strategy can also be used to improve the performance of existing methods that are based on hand-crafted features. Experimental results show that our method outperforms existing methods, especially in a challenging forensic scenario with NIs and CG images of heterogeneous origins. Our method also has good robustness against typical post-processing operations, such as resizing and JPEG compression. Unlike previous attempts to use CNNs for image forensics, we try to understand what our CNN has learned about the differences between NIs and CG images with the aid of adequate and advanced visualization tools.
This paper deals with the sensitivity analysis of structural acoustic performance in presence of non-proportional damping and optimal layout design of the damping layer of vibrating shell structures ...under harmonic excitations. The structural system with a partially-covered damping layer has a non-proportional global damping matrix. Therefore, the method of complex mode superposition in the state space is employed in the dynamic response analysis. The sound pressure is calculated with the structural response solution by using the boundary element method. In this context, an adjoint variable scheme for the design sensitivity analysis of sound pressure is developed. In the optimal design problem, the design objective is to minimize the structural vibration-induced sound pressure at a specified point in the acoustic medium by distributing a given amount of damping material. An artificial damping material model that has a similar form as in the SIMP approach is employed, and the relative densities of the damping material are considered as design variables. Numerical examples are given to illustrate the validity and efficiency of this approach. The influences of the excitation frequency, the damping coefficients and the locations of the reference point on the optimal topologies are also discussed.
► Complex mode superposition for response analysis under non-proportional damping. ► Dynamic equations first mapped into reduced modal space for improving efficiency. ► Sensitivity analysis of acoustic radiation is developed in conjunction with BEM. ► An artificial damping material model is employed in the topology optimization.
Recent advances in materials science and nanotechnology have lead to considerable interest in constructing ion‐channel‐mimetic nanofluidic systems for energy conversion and storage. The conventional ...viewpoint suggests that to gain high electrical energy, the longitudinal dimension of the nanochannels (L) should be reduced so as to bring down the resistance for ion transport and provide high ionic flux. Here, counterintuitive channel‐length dependence is described in nanofluidic osmotic power generation. For short nanochannels (with length L < 400 nm), the converted electric power persistently decreases with the decreasing channel length, showing an anomalous, non‐Ohmic response. The combined thermodynamic analysis and numerical simulation prove that the excessively short channel length impairs the charge selectivity of the nanofluidic channels and induces strong ion concentration polarization. These two factors eventually undermine the osmotic power generation and its energy conversion efficiency. Therefore, the optimal channel length should be between 400 and 1000 nm in order to maximize the electric power, while balancing the efficiency. These findings reveal the importance of a long‐overlooked element, the channel length, in nanofluidic energy conversion and provide guidance to the design of high‐performance nanofluidic energy devices.
Anomalous channel‐length dependence is discovered in nanofluidic osmotic power generation. In contrast to conventional long nanofluidic devices, if the channel length is further reduced to below 400 nm, the output power decreases with decreasing channel length, showing anomalous, non‐Ohmic response. These findings reveal the importance of the long‐overlooked element, the channel length, in nanofluidic energy conversion.
Light-weight cellular materials with periodic repetitive microstructures are widely used in various fields due to their superior mechanical/multi-physical performances. As the microstructural design ...problem is known to have multiple local minima, most gradient-based topology optimization methods significantly depend on the initial guess of the microstructural geometry, thus requiring the designer’s experiences. This paper presents an effective gradient-free framework for periodic microstructure design, which exhibits powerful global searching capabilities and requires no sensitivity information. The proposed framework combines the material-field series-expansion (MFSE) topology representation of periodic microstructures and the sequential Kriging-based optimization algorithm. The MFSE method decouples the topological representation from the finite element discretization, and describes a relatively complex microstructural topology with high-quality boundary description using a greatly reduced number of design variables. Based on the Kriging surrogate model, a solution scheme is suggested to solve material microstructural topology optimization successively in a sequence of sub-optimization problems with self-adaptive design spaces. With the present gradient-free optimization method, high-performance cellular materials that approach the H-S upper bound with porosities from 0.2 to 0.6, or that achieve negative Poisson’s ratios of -0.94 in the principal directions for materials with square symmetry, are obtained without prior knowledge of the optimum microstructural topology.
Illustration: A gradient-free topological design methods for periodic cellular material microstructures is proposed. This optimization method requires no experienced-based guesses of the initial microstructural topologies and requires no sensitivity information. Microstructure geometries with high-quality boundaries and high performances are obtained with the present method. Display omitted
•A gradient-free microstructural topology optimization method for cellular materials is proposed.•This method does not require experience-based guesses of the initial design and the sensitivity information.•The performances of the optimized cellular materials approach the H-S upper bound.•This method provides high-quality microstructural boundary descriptions.
This paper investigates a robust topology optimization method for structural dynamic problems by considering random diffuse-region widths between different material phases using a phase-field model. ...Herein, the spatial distribution of the widths of diffuse regions in a multi-material structure is first represented by a random field and then discretized into uncorrelated stochastic variables using the expansion optimal linear estimation method; stochastic response analysis is then conducted with polynomial chaos expansion. Furthermore, a robust topology optimization formulation of structural dynamic problems is proposed on the basis of the phase-field method, where the design domain is represented with the phase-field function and the explicit phase-field curve is updated by solving the Allen–Cahn equation. A weighted summation of the mean value and standard deviation of the structural dynamic performance is taken as the objective function of the robust optimization problem, where three types of the dynamic performance functions are considered, including the structural dynamic compliance, the fundamental frequency or frequency gap, and the transient displacement under impact loads. The stochastic structural dynamic responses and the corresponding sensitivities are evaluated by polynomial chaos expansion based on finite element analysis at each sampling point. Numerical examples show that the proposed method generates meaningful optimal topologies for structural dynamic robust optimization problems with the framework of the phase-field method. Additionally, some influence factors that affect the optimal solutions are discussed.
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