The liver, as the body's primary organ for maintaining internal balance, is composed of numerous hexagonal liver lobules, each sharing a uniform architectural framework. These liver lobules serve as the basic structural and functional units of the liver, comprised of central veins, hepatic plates, hepatic sinusoids, and minute bile ducts. Meanwhile, within liver lobules, distinct regions of hepatocytes carry out diverse functions. The in vitro construction of liver lobule models, faithfully replicating their structure and function, holds paramount significance for research in liver development and diseases. Presently, two primary technologies for constructing liver lobule models dominate the field: 3D bioprinting and microfluidic techniques. 3D bioprinting enables precise deposition of cells and biomaterials, while microfluidics facilitates targeted transport of cells or other culture materials to specified locations, effectively managing culture media input and output through micro-pump control, enabling dynamic simulations of liver lobules. In this comprehensive review, we provide an overview of the biomaterials, cells, and manufacturing methods employed by recent researchers in constructing liver lobule models. Our aim is to explore strategies and technologies that closely emulate the authentic structure and function of liver lobules, offering invaluable insights for research into liver diseases, drug screening, drug toxicity assessment, and cell replacement therapy.
Based on the drawing software in AutoCAD,introduces a method for developing the demonstration system for the creation of intersecting line in mechanical drawing. Using the demonstration system, the difficulties in teaching the course of mechanical drawing are effectively surmounted, and students' imagination of three dimensional bodies can be enriched, the superiority of present system over ordinary hanging chart and slide show is obvious. The method for developing this system is simple, the system has strong interactive ability and convenience for further enhancement and modification.
The community detection problem is modeled as multi-objective optimization problem, and a classic NSGA-II (nondominated sorting genetic algorithm) is adopted to optimize this problem, which overcomes the resolution problem in the process of modularity density optimization and the parameter adjustment in the process of general modularity density optimization. In this case, a set of Pareto solutions with different partitioning results can be obtained in one time, which can be chosen by the decision maker. Besides that, the crossover and mutation operators take the neighborhood information of the vertices of networks into consideration, which matches up with the property of real world complex networks. The graph based on coding scheme confirms the self-adjustment of the community numbers, rather than sets up in advance. All the experiment results indicate that NSGA-II based algorithm can detect the construction of community effectively.
Anomaly detection from a driver's perspective when driving is important to autonomous vehicles. As a part of Advanced Driver Assistance Systems (ADAS), it can remind the driver about dangers in a timely manner. Compared with traditional studied scenes such as a university campus and market surveillance videos, it is difficult to detect an abnormal event from a driver's perspective due to camera waggle, abidingly moving background, drastic change of vehicle velocity, etc. To tackle these specific problems, this paper proposes a spatial localization constrained sparse coding approach for anomaly detection in traffic scenes, which first measures the abnormality of motion orientation and magnitude, respectively, and then fuses these two aspects to obtain a robust detection result. The main contributions are threefold, as follows. 1) This work describes the motion orientation and magnitude of the object, respectively, in a new way, which is demonstrated to be better than the traditional motion descriptors. 2) The spatial localization of an object is taken into account considering the sparse reconstruction framework, which utilizes the scene's structural information and outperforms the conventional sparse coding methods. 3) Results of motion orientation and magnitude are adaptively weighted and fused by a Bayesian model, which makes the proposed method more robust and able to handle more kinds of abnormal events. The efficiency and effectiveness of the proposed method are validated by testing on nine difficult video sequences that we captured ourselves. Observed from the experimental results, the proposed method is more effective and efficient than the popular competitors and yields a higher performance.
A novel image retrieval approach based on the statistical model of Q-shift dual-tree complex wavelet transform(Q-shift DT-CWT) is proposed.Q-shift DT-CWT can provide a group delay of 1/4 of a sample period,and satisfy the usual 2-band filterbank constraints of no aliasing and perfect reconstruction,so it can give much better directional selectivity and shift invariance.In order to reduce dimensions,the coefficient histogram of the Q-shift DTCWT is fitted with generalized Gaussian distribution(GGD),which overcomes the shortcomings of low classification nicety and low image retrieval precise of image feature described by the mean and variance of the images.The Kullback-Leibler distance(KLD) theory provides a justified way of combining distances into an overall similarity measurement,so this theory is applied to image retrieval based on GGD model,which overcomes the low retrieval precise of the normalized Euclidean distance.Extensive experiments from Brodatz texture images clearly show the superiority of the novel approach,which achieves 3.75 percent higher than that based on the combination of DT-CWT and 22.56 percent more than that based on combination of Gabor.
Abstract Aiming at the problem that the image of patrol inspection is affected by angle and distance, the target of small size accessory equipment in the image is small, and the recognition rate of current algorithm is low. An improved Faster-RCNN detection algorithm for small size accessory equipment of patrol image is proposed. By adjusting the structure of Faster-RCNN network, we can overcome the shortcomings of the current algorithm. Firstly, the deep residual network ResNet50 is used to replace VGG16 network. At the same time, the bottom and high-level features of convolution network are applied to the selection of candidate regions, so as to improve the utilization of effective information of targets, and then to improve the detection precision of small-sized targets. The results show that the detection accuracy of the improved Faster-RCNN model is 4.2% higher than that of the original algorithm.
Navigation aids can help people conduct daily wayfinding activities. However, because of cognitive limitations that can emerge with age, it is not clear how different navigation aids impact wayfinding behaviors and spatial memory in older adults. In Experiment 1, 66 older adults and 65 younger adults participated. They were asked to make turn decisions when the navigation aid was a map, a map plus self-updating (Global Positioning System [GPS]), or a text. After the wayfinding task, they completed two spatial memory tasks recalling scenes and drawing the routes. Results showed that younger adults outperformed older adults on most outcome measures. The text and the GPS conditions benefited older adults' wayfinding behaviors more than the map condition, as indicated by route decision accuracies and reaction times. However, the map condition was associated with better route memory than the text condition. Experiment 2 aimed to replicate the results using more complex environments. Sixty-three older adults and 66 younger adults participated. The advantage of the text over the map conditions was again found in wayfinding behaviors for older adults. However, no difference was found between the map and the text conditions in route memory. No difference was found between the GPS and the map conditions in any outcome measures. Overall, our results showed the relative strengths and weaknesses of different navigation aids and the interactive effects between the type of navigation aid, age, outcome measure, and environmental complexity. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
'/%3e%3cuse xlink:href='%23a' transform='rotate(23.036 .093 25.536)'/%3e%3cuse xlink:href='%23a' transform='rotate(45.87 1.273 16.18)'/%3e%3cuse xlink:href='%23a' transform='rotate(69.945 .996 12.078)'/%3e%3cuse xlink:href='%23a' transform='rotate(20.66 -19.689 31.932)'/%3e%3c/svg%3e)