Developing high-efficiency base editors by combining optimized synergistic core components with new types of nuclear localization signal peptide

The clustered regularly interspaced short palindromic repeats(CRISPR)–CRISPR-associated protein(Cas) system has been widely used for genome editing. In this system, the cytosine base editor(CBE) and adenine base editor(ABE) allow generating precise and irreversible base mutations in a programmable manner and have been used in many different types of cells and organisms. However, their applications are limited by low editing efficiency at certain genomic target sites or at specific target cytosine(C) or adenine(A) residues. Using a strategy of combining optimized synergistic core components, we developed a new multiplex super-assembled ABE(sABE) in rice that showed higher base-editing efficiency than previously developed ABEs. We also designed a new type of nuclear localization signal(NLS) comprising a FLAG epitope tag with four copies of a codon-optimized NLS(F4NLS^(r2)) to generate another ABE named F4NLS-sABE. This new NLS increased editing efficiency or edited additional A at several target sites. A new multiplex super-assembled CBE(sCBE) and F4NLS^(r2) involved F4NLS-sCBE were also created using the same strategy. F4NLS-sCBE was proven to be much more efficient than sCBE in rice. These optimized base editors will serve as powerful genome-editing tools for basic research or molecular breeding in rice and will provide a reference for the development of superior editing tools for other plants or animals.

Fingerprint Liveness Detection Based on Multi-Scale LPQ and PCA

Fingerprint authentication system is used to verify users' identification according to the characteristics of their fingerprints.However,this system has some security and privacy problems.For example,some artificial fingerprints can trick the fingerprint authentication system and access information using real users' identification.Therefore,a fingerprint liveness detection algorithm needs to be designed to prevent illegal users from accessing privacy information.In this paper,a new software-based liveness detection approach using multi-scale local phase quantity(LPQ) and principal component analysis(PCA) is proposed.The feature vectors of a fingerprint are constructed through multi-scale LPQ.PCA technology is also introduced to reduce the dimensionality of the feature vectors and gain more effective features.Finally,a training model is gained using support vector machine classifier,and the liveness of a fingerprint is detected on the basis of the training model.Experimental results demonstrate that our proposed method can detect the liveness of users' fingerprints and achieve high recognition accuracy.This study also confirms that multi-resolution analysis is a useful method for texture feature extraction during fingerprint liveness detection.

Multivariate time delay analysis based local KPCA fault prognosis approach for nonlinear processes

Currently, some fault prognosis technology occasionally has relatively unsatisfied performance especially for in- cipient faults in nonlinear processes duo to their large time delay and complex internal connection. To overcome this deficiency, multivariate time delay analysis is incorporated into the high sensitive local kernel principal component analysis. In this approach, mutual information estimation and Bayesian information criterion （BIC） are separately used to acquire the correlation degree and time delay of the process variables. Moreover, in order to achieve prediction, time series prediction by back propagation （BP） network is applied whose input is multivar- iate correlated time series other than the original time series. Then the multivariate time delayed series and future values obtained by time series prediction are combined to construct the input of local kernel principal component analysis （LKPCA） model for incipient fault prognosis. The new method has been exemplified in a sim- ple nonlinear process and the complicated Tennessee Eastman （TE） benchmark process. The results indicate that the new method has suoerioritv in the fault prognosis sensitivity over other traditional fault prognosis methods.

Measuring 3D face deformations from RGB images of expression rehabilitation exercises

Background The accurate(quantitative)analysis of 3D face deformation is a problem of increasing interest in many applications.In particular,defining a 3D model of the face deformation into a 2D target image to capture local and asymmetric deformations remains a challenge in existing literature.A measure of such local deformations may be a relevant index for monitoring the rehabilitation exercises of patients suffering from Par-kinson’s or Alzheimer’s disease or those recovering from a stroke.Methods In this paper,a complete framework that allows the construction of a 3D morphable shape model(3DMM)of the face is presented for fitting to a target RGB image.The model has the specific characteristic of being based on localized components of deformation.The fitting transformation is performed from 3D to 2D and guided by the correspondence between landmarks detected in the target image and those manually annotated on the average 3DMM.The fitting also has the distinction of being performed in two steps to disentangle face deformations related to the identity of the target subject from those induced by facial actions.Results The method was experimentally validated using the MICC-3D dataset,which includes 11 subjects.Each subject was imaged in one neutral pose and while performing 18 facial actions that deform the face in localized and asymmetric ways.For each acquisition,3DMM was fit to an RGB frame whereby,from the apex facial action and the neutral frame,the extent of the deformation was computed.The results indicate that the proposed approach can accurately capture face deformation,even localized and asymmetric deformations.Conclusion The proposed framework demonstrated that it is possible to measure deformations of a reconstructed 3D face model to monitor facial actions performed in response to a set of targets.Interestingly,these results were obtained using only RGB targets,without the need for 3D scans captured with costly devices.This paves the way for the use of the proposed tool in remote medical rehabilitation monitoring.

Improving the process forming limit considering forming defects in the transitional region in local loading forming of Ti-alloy rib-web components

The isothermal local loading forming technology provides a feasible way to form Ti-alloy large-scale rib-web components in aerospace and aviation fields.However,the local loading process forming limit is restricted by forming defects in the transitional region.In this work,the feasibility of controlling forming defects and improving the process forming limit by adjusting die parameters is explored through finite element（FE） simulation.It is found that the common cavum and folding defects in the transitional region are significantly influenced by the fillet radii of left rib and middle rib,respectively.The cavum and folding defects can be effectively controlled by increasing the fillet radii of left rib and middle rib,respectively.The process forming limits considering forming defects in the transitional region are determined by the stepwise searching method under various die parameters.Moreover,the relationship between the process forming limit and die parameters is developed through the response surface methodology（RSM）.The developed RSM models suggest that increasing the fillet radii of left and middle ribs is effective to improve the process forming limit during local loading forming of rib-web components.The results will provide technical basis for the design of die parameters and the reduction amount,which is of great importance to control forming defects and improve the process forming limit in local loading forming of Ti-alloy large-scale rib-web components.

Truncation method for calculating the resistance of ventilation air-conditioning duct systems under nonfully developed flow boundary conditions

Calculating the resistance of ventilation air-conditioning ducts under nonfully developed flow is a crucial problem that must be addressed. Based on the characteristics of the resistance in ventilation air-conditioning ducts, the truncation method-a computational method that is appropriate for nonfully developed flow boundary conditions-was proposed in this study. The resistance distributions in the upstream and downstream ducts from typical local components, including reducers, bends and tee ducts, were investigated. Using the resistance values of the local components under fully developed flow, the resistances that did not belong to nonfully developed flow were truncated and removed. Finally, the calculation steps of the proposed method were discussed, an engineering case study was presented, and the accuracy of the developed model was analyzed. The results showed that for the local components in the system (reducers, bends and tee ducts), their proportions of the total resistance exhibited similar trends under different width-to-height ratios. The resistance of these local components included upstream resistance, downstream resistance and their own resistance. The upstream resistance accounted for 2%–6% of the total resistance, whereas the downstream resistance of the reducers, bends and tee ducts accounted for 40%–60% of the total resistance. A functional relationship was established between the local resistance and cutoff distance of the reducers, bends and tee ducts. Hence, the truncation method can calculate the local resistance from the cutoff distance. Moreover, in the presented engineering case study, the error between the actual measured resistance values and those simulated with the truncation method was only 4.28%, which was far less than that of the results simulated with the traditional calculation methods (53.64%).