The study expects to solve the problems of insufficient labeling, high input dimension, and inconsistent task input distribution in traditional lifelong machine learning. A new deep learning model is ...proposed by combining feature representation with a deep learning algorithm. First, based on the theoretical basis of the deep learning model and feature extraction. The study analyzes several representative machine learning algorithms, and compares the performance of the optimized deep learning model with other algorithms in a practical application. By explaining the machine learning system, the study introduces two typical algorithms in machine learning, namely ELLA (Efficient lifelong learning algorithm) and HLLA (Hierarchical lifelong learning algorithm). Second, the flow of the genetic algorithm is described, and combined with mutual information feature extraction in a machine algorithm, to form a composite algorithm HLLA (Hierarchical lifelong learning algorithm). Finally, the deep learning model is optimized and a deep learning model based on the HLLA algorithm is constructed. When K = 1200, the classification error rate reaches 0.63%, which reflects the excellent performance of the unsupervised database algorithm based on this model. Adding the feature model to the updating iteration process of lifelong learning deepens the knowledge base ability of lifelong machine learning, which is of great value to reduce the number of labels required for subsequent model learning and improve the efficiency of lifelong learning.
In order to solve the shortcomings of the existing mathematical expressions of the user’s personalized recommendation search and to increase the accuracy of the user’s personalized information ...recommendation, in this study, the collaborative filtering algorithm, the related theory of fuzzy sets, and the evaluation methods were introduced at first. Then, the establishment of collaborative filtering model and working principle, user similarity measure, generation of mathematical expression recommendation list, design of mathematical expression recommendation model and implementation of function were introduced. Finally, the application of the collaborative filtering algorithm in the user’s personalized information recommendation mathematical expression was verified by collecting data. The results showed that the recommendation mathematical expression model based on collaborative filtering algorithm had higher accuracy in collecting user personalized information, and the accuracy of the system was higher than other recommendation algorithms, which can better meet the individual needs of users. This research can provide a fast and convenient way for users to search for personalized information, and has a good guiding significance for the retrieval and recommendation of informational scientific and technical literature.
The human mitochondrial ssDNA-binding protein (mtSSB) is a homotetrameric protein, involved in mtDNA replication and maintenance. Although mtSSB is structurally similar to SSB from Escherichia coli ...(EcoSSB), it lacks the C-terminal disordered domain, and little is known about the biophysics of mtSSB–ssDNA interactions. Here, we characterized the kinetics and thermodynamics of mtSSB binding to ssDNA by equilibrium titrations and stopped-flow kinetic measurements. We show that the mtSSB tetramer can bind to ssDNA in two distinct binding modes: (SSB)30 and (SSB)60, defined by DNA binding site sizes of 30 and 60 nucleotides, respectively. We found that the binding mode is modulated by magnesium ion and NaCl concentration, but unlike EcoSSB, the mtSSB does not show negative intersubunit cooperativity. Global fitting of both the equilibrium and kinetic data afforded estimates for the rate and equilibrium constants governing the formation of (SSB)60 and (SSB)30 complexes and for the transitions between the two binding modes. We found that the mtSSB tetramer binds to ssDNA with a rate constant near the diffusion limit (2 × 109m−1 s−1) and that longer DNA (≥60 nucleotides) rapidly wraps around all four monomers, as revealed by FRET assays. We also show that the mtSSB tetramer can directly transfer from one ssDNA molecule to another via an intermediate with two DNA molecules bound to the mtSSB. In conclusion, our results indicate that human mtSSB shares many physicochemical properties with EcoSSB and that the differences may be explained by the lack of an acidic, disordered C-terminal tail in human mtSSB protein.
Although great progress has been made in the diagnosis and treatment of acute myocardial infarction (AMI) in recent years, its morbidity and mortality are still relatively high. In this study, we ...explain that the function of Sestrin2 gene in Anxiety and Depression Myocardial infarction and its possible mechanism. 26 patients with Anxiety and Depression Myocardial infarction (ADMI) and 26 normal volunteers were collected from our hospital. All mice anaesthetized using 50 mg/kg of pentobarbital sodium and the left anterior descending arteries (LAD) were ligated to induce myocardial infarction. H9c2 cells were stimulated with 5% oxygen (O2) and 5% carbon dioxide (CO2) and 90% N2 for 24 h. The serum expression of Sestrin2 in patients with ADMI was up-regulated. Sestrin2 gene up-regulation reduced collagen I/II and KEAP1 mRNA expressions, and increased GPX4 and Nrf2 mRNA expressions in vitro model of AMI. Down-regulation of Sestrin2 increased collagen I/II and KEAP1 mRNA expressions, and decreased GPX4 and Nrf2 mRNA expressions in vitro model of AMI. These data confirmed that Sestrin2 reduced inflammation and ferroptosis in model of ADMI by LKB1-mediated AMPK activation. This infers that Sestrin2 is potential target to be used in the treatment of premature AMI.
Glioma is the most common tumor of the central nervous system (CNS), with a 5-year survival rate of <35%. Drug therapy, such as chemotherapeutic and immunotherapeutic agents, remains one of the main ...treatment modalities for glioma, including temozolomide, doxorubicin, bortezomib, cabazitaxel, dihydroartemisinin, immune checkpoint inhibitors, as well as other approaches such as siRNA, ferroptosis induction,
. However, the filter function of the blood-brain barrier (BBB) reduces the amount of drugs needed to effectively target CNS tumors, making it one of the main reasons for poor drug efficacies in glioma. Thus, finding a suitable drug delivery platform that can cross the BBB, increase drug aggregation and retainment in tumoral areas and avoid accumulation in non-targeted areas remains an unsolved challenge in glioma drug therapy. An ideal drug delivery system for glioma therapy should have the following features: (1) prolonged drug life in circulation and effective penetration through the BBB; (2) adequate accumulation within the tumor (3) controlled-drug release modulation; (4) good clearance from the body without significant toxicity and immunogenicity, etc. In this regard, due to their unique structural features, nanocarriers can effectively span the BBB and target glioma cells through surface functionalization, providing a new and effective strategy for drug delivery. In this article, we discuss the characteristics and pathways of different nanocarriers for crossing the BBB and targeting glioma by listing different materials for drug delivery platforms, including lipid materials, polymers, nanocrystals, inorganic nanomaterials,
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In this paper, the nonparaxial solitons in a dimensionless coupled nonlinear Schrödinger system with cross-phase modulation, which enables the propagation of ultra-broad nonparaxial pulses in a ...birefringent optical waveguide are studied. By noticing that the system is a non-integrable one, and also diverse forms of solitary wave solutions by using the Hirota’s bilinear scheme are reached. The binary bell polynomials and bilinear transformation and also the related theorem for getting to the bilinear form of nonlinear system are noticed. In particular, five forms of function solution including soliton, bright soliton, singular soliton, periodic wave and singular form of solutions are investigated. To achieve this, an illustrative example of the coupled nonlinear Helmholtz systems is provided to demonstrate the feasibility and reliability of the procedure is used in this study. The effect of the free parameters on the behavior of acquired figures of a few obtained solutions for two nonlinear rational exact cases was also discussed. We believe that our results would pave a way for future research generating optical memories based on the nonparaxial solitons.
Thunder is a discharge phenomenon that often occurs in nature. Due to its physical influences such as strong current, high temperature, strong shock waves, and strong electromagnetic radiation, it ...has a huge destructive effect instantly, which may bring serious threats to people’s lives and property safety. This study aimed to study the lightning discharge numerical simulation and active protection based on the quantum heuristic evolutionary algorithm and proposed to apply the lightning discharge numerical simulation to the prevention of lightning disasters. This article gives a detailed description of the quantum algorithm, the generation, and harm of lightning discharge. The genetic algorithm is used to optimize the lightning data simulation algorithm, and the optimization process is introduced in detail. In addition, this article conducts related experiments on lightning discharge numerical simulation and active protection. The experimental results show that targeted active protection and effective numerical simulation are important measures to prevent lightning disasters. Active lightning protection measures can reduce lightning by 30%. Losses are caused by disasters.
A facial expression recognition (FER) algorithm is built on the advanced convolutional neural network (CNN) to improve the current FER algorithms’ recognition rate. The advanced CNN model (the ...ExpressionNet model), containing two continuous convolutional (Conv) layers and one maximum cache layer, is obtained through the AlexNet CNN. The proposed algorithm is compared with the SingleNet model, CNN with three Conv layers, and the AlexNet model through simulation experiments. The experiment results show that the ExpressionNet model takes the longest training time and test time, followed by the AlexNet and the SingleNet. In terms of recognition rate, ExpressionNet (77%) is superior to AlexNet (72.5%) and SingleNet (69.5%); however, its convergence rate is slightly slower than the other two models. The ExpressionNet model has only one layer more than that of the AlexNet model. Therefore, the advanced CNN-based FER algorithm is of great significance to theoretical research and practical application of the FER technology.
Ticagrelor is the first reversibly binding oral P2Y12 receptor antagonist to inhibit platelet activation and has been approved by the Food and Drug Administration for the treatment of coronary artery ...disease. At present, the other pharmacological functions of ticagrelor remain poorly understood. The NOD-, LRR-, and pyrin domain-containing protein 3 (NLRP3) inflammasome plays a critical role in the innate immune system, but its excessive activation also contributes to the pathogenesis of complex diseases. In this study, we systematically examined the effects of ticagrelor on the NLRP3 inflammasome and found that ticagrelor inhibits NLRP3 inflammasome activation in macrophages independent of its classic inhibitory effect on the P2Y12 signaling pathway. Further mechanistic studies demonstrate that ticagrelor attenuates the oligomerization of apoptosis-associated speck-like protein containing a CARD (ASC) by blocking chloride efflux, an effect achieved through the degradation of chloride intracellular channel proteins (CLICs) and blockade of the translocation of CLICs to the plasma membrane. Moreover, experiments on lipopolysaccharide-induced sepsis and alum-induced peritonitis in mice confirmed that ticagrelor mitigates the severity of systemic inflammation independent of P2Y12 receptor antagonism. Importantly, oral administration of ticagrelor rapidly and strongly inhibited NLRP3 inflammasome activation in peripheral blood mononuclear cells from patients with acute coronary syndrome. Overall, our study reveals a novel pharmacological function of ticagrelor in addition to its classic antiplatelet properties, which suggests that ticagrelor may serve as a potential therapeutic agent for use in NLRP3-associated diseases.
The quality of Innovation and Entrepreneurship Education (IEE) in higher institutions is closely related to the degree to which the undergraduates (UGs) absorb relevant innovation and ...entrepreneurship knowledge and their entrepreneurial motivation. Thus, an effective Evaluation of Educational Quality (EEQ) is essential. In particular, fault tree analysis (FTA), a common EEQ approach, has some disadvantages, such as fault data reliance and insufficient uncertainties handleability. Thereupon, this article first puts forward a theoretical model based on the deep learning (DL) method to analyze the factors of IEE quality; consequently, based on the traditional FTA, fuzzy fault tree analysis (FFTA) is proposed to evaluate the reliability of IEE classroom teaching for college teachers and students. Finally, based on the top event of entrepreneurial teaching failure, the hyper-ellipsoid model is implemented to restrict the interval probability of basic events and describe the deviation of uncertain events. Furthermore, the model accuracy is verified by a questionnaire survey (QS), based upon which the factors of IEE quality are analyzed. The results show that the designed QS has good reliability, validity, and fitness; the path coefficients of cooperative ability to critical thinking and innovative thinking are 0.9 and 0.66, respectively, indicating that the students' cooperative ability plays a vital role in the classroom teaching. By calculation, the probability of "teaching failure" in entrepreneurial classroom teaching is 0.395, 3, 0.462, and 5. To sum up, the proposed method can effectively and quantitatively evaluate the quality of IEE in higher institutions, thus providing a certain basis for formulating relevant improvement strategies. The purpose is to provide important technical support for improving the IEE quality.
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