The reconstruction of 3D object from a single image is an important task in the field of computer vision. In recent years, 3D reconstruction of single image using deep learning technology has ...achieved remarkable results. Traditional methods to reconstruct 3D object from a single image require prior knowledge and assumptions, and the reconstruction object is limited to a certain category or it is difficult to accomplish a good reconstruction from a real image. Although deep learning can solve these problems well with its own powerful learning ability, it also faces many problems. In this paper, we first discuss the challenges faced by applying the deep learning method to reconstruct 3D objects from a single image. Second, we comprehensively review encoders, decoders and training details used in 3D reconstruction of a single image. Then, the common datasets and evaluation metrics of single image 3D object reconstruction in recent years are introduced. In order to analyze the advantages and disadvantages of different 3D reconstruction methods, a series of experiments are used for comparison. In addition, we simply give some related application examples involving 3D reconstruction of a single image. Finally, we summarize this paper and discuss the future directions.
To better prevent the potential risks in Internet-based Supply Chain Financing (SCF) products, this paper optimizes and evaluates the Internet-based SCF-oriented Credit Risk Evaluation (CRE) method. ...Firstly, this paper summarizes 12 risk factors of SCF business, establishes a Risk Assessment Index System (RAIS) with good consistency and stability; then, the principles of Backpropagation (BP) Neural Network (NN) is expounded together with Support Vector Machines (SVM) and Genetic Algorithm (GA) model. Consequently, a CRE model is implemented by the NN tools in MATLAB based on the collection of multiple groups of SCF-oriented risk assessment samples. Subsequently, the assessment samples are trained and tested. Finally, the SCF-oriented CRE model is proposed and verified. The results show that the BP-GA model has presented high prediction consistency with the actual classification. According to the comparison of classification results of SVM, BP model, and BP-GA model, the classification accuracy of test samples of the proposed Internet-based SCF-oriented CRE system using BP-GA model reaches 97.19%; the Type I and Type II error rate of the CRE system based on BP-GA model is 7.2% and 14.21%, respectively. Therefore, a suitable SCF-oriented CRE method is put forward for China's commercial banks along with scientific and feasible suggestions to manage SCF-oriented credit risks more reasonably and effectively.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Cisplatin (
-diamminedichloroplatinum I) is a platinum-based drug, the mainstay of anticancer treatment for numerous solid tumors. Since its approval by the FDA in 1978, the drug has continued to be ...used for the treatment of half of epithelial cancers. However, resistance to cisplatin represents a major obstacle during anticancer therapy. Here, we review recent findings on how the mTORC1 pathway and autophagy can influence cisplatin sensitivity and resistance and how these data can be applicable for the development of new therapeutic strategies.
With the advances in micro-electronics, wireless sensor devices have been made much smaller and more integrated, and large-scale wireless sensor networks (WSNs) based the cooperation among the ...significant amount of nodes have become a hot topic. "Large-scale" means mainly large area or high density of a network. Accordingly the routing protocols must scale well to the network scope extension and node density increases. A sensor node is normally energy-limited and cannot be recharged, and thus its energy consumption has a quite significant effect on the scalability of the protocol. To the best of our knowledge, currently the mainstream methods to solve the energy problem in large-scale WSNs are the hierarchical routing protocols. In a hierarchical routing protocol, all the nodes are divided into several groups with different assignment levels. The nodes within the high level are responsible for data aggregation and management work, and the low level nodes for sensing their surroundings and collecting information. The hierarchical routing protocols are proved to be more energy-efficient than flat ones in which all the nodes play the same role, especially in terms of the data aggregation and the flooding of the control packets. With focus on the hierarchical structure, in this paper we provide an insight into routing protocols designed specifically for large-scale WSNs. According to the different objectives, the protocols are generally classified based on different criteria such as control overhead reduction, energy consumption mitigation and energy balance. In order to gain a comprehensive understanding of each protocol, we highlight their innovative ideas, describe the underlying principles in detail and analyze their advantages and disadvantages. Moreover a comparison of each routing protocol is conducted to demonstrate the differences between the protocols in terms of message complexity, memory requirements, localization, data aggregation, clustering manner and other metrics. Finally some open issues in routing protocol design in large-scale wireless sensor networks and conclusions are proposed.
Anthropogenic pressures can threaten lake and reservoir ecosystems, leading to harmful algal blooms that have become globally widespread. However, patterns of phytoplankton diversity change and ...community assembly over long-term scales remain unknown. Here, we explore biodiversity patterns in eukaryotic algal (EA) and cyanobacterial (CYA) communities over a century by sequencing DNA preserved in the sediment cores of seven lakes and reservoirs in the North Temperate Zone. Comparisons within lakes revealed temporal algal community homogenization in mesotrophic lakes, eutrophic lakes, and reservoirs over the last century but no systematic losses of α-diversity. Temporal homogenization of EA and CYA communities continued into the modern day probably due to time-lags related to historical legacies, even if lakes go through a eutrophication phase followed by a reoligotrophication phase. Further, algal community assembly in lakes and reservoirs was mediated by both deterministic and stochastic processes, while homogeneous selection played a relatively important role in recent decades due to intensified anthropogenic activities and climate warming. Overall, these results expand our understanding of global change effects on algal community diversity and succession in lakes and reservoirs that exhibit different successional trajectories while also providing a baseline framework to assess their potential responses to future environmental change.
Cytoplasmic incompatibility (CI) results when Wolbachia bacteria-infected male insects mate with uninfected females, leading to embryonic lethality. "Rescue" of viability occurs if the female harbors ...the same Wolbachia strain. CI is caused by linked pairs of Wolbachia genes called CI factors (CifA and CifB). The co-evolution of CifA-CifB pairs may account in part for the incompatibility patterns documented in insects infected with different Wolbachia strains, but the molecular mechanisms remain elusive. Here, we use X-ray crystallography and AlphaFold to analyze the CI factors from Wolbachia strain wMel called CidA
and CidB
. Substituting CidA
interface residues with those from CidA
(from strain wPip) enables the mutant protein to bind CidB
and rescue CidB
-induced yeast growth defects, supporting the importance of CifA-CifB interaction in CI rescue. Sequence divergence in CidA
and CidB
proteins affects their pairwise interactions, which may help explain the complex incompatibility patterns of mosquitoes infected with different wPip strains.
The process of recycling poly(ethylene terephthalate) (PET) remains a major challenge due to the enzymatic degradation of high-crystallinity PET (hcPET). Recently, a bacterial PET-degrading enzyme, ...PETase, was found to have the ability to degrade the hcPET, but with low enzymatic activity. Here we present an engineered whole-cell biocatalyst to simulate both the adsorption and degradation steps in the enzymatic degradation process of PETase to achieve the efficient degradation of hcPET. Our data shows that the adhesive unit hydrophobin and degradation unit PETase are functionally displayed on the surface of yeast cells. The turnover rate of the whole-cell biocatalyst toward hcPET (crystallinity of 45%) dramatically increases approximately 328.8-fold compared with that of purified PETase at 30 °C. In addition, molecular dynamics simulations explain how the enhanced adhesion can promote the enzymatic degradation of PET. This study demonstrates engineering the whole-cell catalyst is an efficient strategy for biodegradation of PET.
Purpose
Endobronchial intervention requires detailed modeling of pulmonary anatomical substructure, such as lung airway and artery-vein maps, which are commonly extracted from non-contrast computed ...tomography (NCCT) independently using automatic segmentation approaches. We aim to make the first attempt to jointly train a CNN-based model for airway and artery-vein segmentation along with synthetic contrast-enhanced CT (CECT) generation.
Methods
A multi-task framework is proposed to simultaneously generate three segmentation maps and synthesize CECTs. We first design a collaborative learning model with tissue knowledge interaction for lung airway and artery-vein segmentation. Meanwhile, a conditional adversarial training strategy is applied to generate CECTs from NCCTs guided by artery maps. Additionally, CECT identity and reconstruction help to regularize the model for plausible NCCT to CECT translation.
Results
Extensive experiments were conducted to evaluate the performance of the proposed framework based on three datasets (90 NCCTs for the airway task, 55 NCCTs for the artery-vein task and 100 CECTs for the artery task). The results demonstrate the effective improvement of our proposed method compared to other methods and configurations that can achieve more accurate segmentation maps (Dice score coefficients for these three tasks are: 93.6%, 80.7% and 82.4%, respectively) and realistic CECTs simultaneously. The ablation study further verifies the effectiveness of the components of the designed model.
Conclusion
This study demonstrates the model potential in multi-task learning that integrates anatomically relevant segmentation and performs NCCT to CECT translation. Such an interaction approach promotes mutually for both promising segmentation results and plausible synthesis.
Using DNA staining dyes such as SYBR Green I (SGI) and thioflavin T (ThT) to perform label-free detection of aptamer binding has been performed for a long time for both binding assays and biosensor ...development. Since these dyes are cationic, they can also adsorb to the wall of reaction vessels leading to unstable signals and even false interpretations of the results. In this work, the stability of the signal was first evaluated using ThT and the classic adenosine aptamer. In a polystyrene microplate, a drop in fluorescence was observed even when non-binding targets or water were added, whereas a more stable signal was achieved in a quartz cuvette. Equilibrating the system can also improve signal stability. In addition, a few polymers and surfactants were also screened, and 0.01% Triton X-100 was found to have the best protection effect against fluorescence signal decrease due to dye adsorption. Three aptamers for Hg
, adenosine, and cortisol were tested for their sensitivity and signal stability in the absence and presence of Triton X-100. In each case, the sensitivity was similar, whereas the signal stability was better for the surfactant. This study indicates that careful control experiments need to be designed to ensure reliable results and that the reliability can be improved by using Triton X-100 and a long equilibration time.
As one of the three elements of language, the study of grammar plays an important role in the field of linguistics and teaching Chinese as a foreign language. In the process of overseas teaching, the ...problem that Chinese learners think grammar is very difficult to learn, some teachers ignore grammar teaching or lack of effective teaching methods. Based on the practical problem, the authors try to explore a concise and clear Chinese grammar framework to help students build a knowledge structure that is easier to recognize and memorize, and improve the teaching quality of teachers of Chinese as a foreign language. This paper mainly tries to find out the principles of establishing the grammatical framework through the definition and research of the grammatical framework, and introduces the regularity, systematization and inspiration of scientific thinking into teaching, so as to open up a new way of thinking for Chinese grammar teaching. Using chart data analysis, understand students’ background, learning difficulties and reasons. Through the comparison of teaching effects between the experimental group and the control group, it is found that students have a deeper understanding and improvement of Chinese cognition and learning after the construction of the grammar framework. However, how to construct a Chinese grammar framework that is more conducive to teachers and students should be created and developed in the long-term exploration and practice.
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