Youngrandolph0055

These theoretical and numerical results may be helpful in making public policies to control HLB in orchards more effectively.Prostate adenocarcinoma (PRAD) is one of the most frequently diagnosed cancer in males. Previous studies had demonstrated long non-coding RNAs (lncRNAs) played crucial roles in human cancers. In present study, we reported ten disease-free survival time related lncRNAs in PRAD, including RP11-468E2.5, GS1-393G12.13, CTD-2228K2.7, RP11-783K16.13, RP11-631N16.4, CTC-435M10.12, RP11-1109F11.5, RP11-228B15.4, RP11-496I9.1, and RP11-95O2.5. Higher expression of these lncRNAs significantly correlates to shorter DFS time in patients with PRAD. We next constructed lncRNAs regulating PPI networks in PRAD. Bioinformatics analysis revealed these DFS-related lncRNAs were associated with the regulation of cell cycle, glucose metabolic process, histone modification, and RNA splicing. AR and SPOP were identified to be involved in regulating these lncRNAs expression in PRAD. The prognostic value and molecular functions of these lnRNAs in human diseases remained largely unknown. We thought this study for the first time demonstrated that they could act as novel potential biomarkers for PRAD.In supply chain management, fast and accurate decisions in supplier selection and order quantity allocation have a strong influence on the company's profitability and the total cost of finished products. In this paper, a novel and non-linear model is proposed for solving the supplier selection and order quantity allocation problem. The model is introduced for minimizing the total cost per time unit, considering ordering, purchasing, inventory, and transportation cost with freight rate discounts. Perfect rate and capacity constraints are also considered in the model. Since metaheuristic algorithms have been successfully applied in supplier selection, and due to the non-linearity of the proposed model, particle swarm optimization (PSO), genetic algorithm (GA), and differential evolution (DE), are implemented as optimizing solvers instead of analytical methods. The model is tested by solving a reference model using PSO, GA, and DE. The performance is evaluated by comparing the solution to the problem against other solutions reported in the literature. Experimental results prove the effectiveness of the proposed model, and demonstrate that metaheuristic algorithms can find lower-cost solutions in less time than analytical methods.The continuous predator-prey model is one of the main models studied in recent years. The dynamical properties of these models are so complex that it is an urgent topic to be studied. In this paper, we transformed a continuous predator-prey model with modified Leslie-Gower and Hollingtype III schemes into a discrete mode by using Euler approximation method. The existence and stability of fixed points for this discrete model were investigated. Flip bifurcation analyses of this discrete model was carried out and corresponding bifurcation conditions were obtained. Provided with these bifurcation conditions, an example was given to carry out numerical simulations, which shows that the discrete model undergoes flip bifurcation around the stable fixed point. In addition, compared with previous studies on the continuous predator-prey model, our discrete model shows more irregular and complex dynamic characteristics. The present research can be regarded as the continuation and development of the former studies.In this article, a delayed phytoplankton-zooplankton system with Allee effect and linear harvesting is proposed, where phytoplankton species protects themselves from zooplankton by producing toxin and taking shelter. First, the existence and stability of the possible equilibria of system are explored. Next, the existence of Hopf bifurcation is investigated when the system has no time delay. What's more, the stability of limit cycle is demonstrated by calculating the first Lyapunov number. Then, the condition that Hopf bifurcation occurs is obtained by taking the time delay describing the maturation period of zooplankton species as a bifurcation parameter. Furthermore, based on the normal form theory and the central manifold theorem, we derive the direction of Hopf bifurcation and the stability of bifurcating periodic solutions. In addition, by regarding the harvesting effort as control variable and employing the Pontryagin's Maximum Principle, the optimal harvesting strategy of the system is obtained. Finally, in order to verify the validity of the theoretical results, some numerical simulations are carried out.Purpose The present paper investigated the expression of TLR2 in serum of patients with pulmonary tuberculosis and lung cancer, and verifiedthe effect of TLR2 on the biological characteristics of lung cancer cells. Methods The common differentially expressed genes in tuberculosis and lung cancer samples were analyzed by edgeR. The intersection of genes was taken and the enrichment analysis and string interaction analysis were performed. The expression of TLR2, inflammatory factors IL6, IL17 and IL22 in serum of patients with pulmonary tuberculosis or lung cancer and lung cell were detected by ELISA. The mRNA and protein expression levels of TLR2, caspase-3, Bax and Bcl-2 were detected by qRT-PCR and Western blot. CCK-8, colony formation assay, transwell assay and flow cytometry were performed to detect the proliferation, invasion, migration and cells apoptosis of lung cancer cells. Results Bioinformatics analysis found that high expression of TLR2 is a core regulator in lung cancer and tuberculosis. TLR2 and inflammatory factors IL6, IL17, IL22 are highly expressed in the serum of patients with tuberculosis and lung cancer by ELISA.TLR2 is also highly expressed in lung cancer cells. Silencing TLR2 inhibited the growth, invasion and migration ability of cells, and the expression of IL6, IL17 and IL22. It also promoted the expression of caspase-3 and Baxwith the decreased expression of Bcl-2. Conclusion TLR2 and inflammatory factors IL6, IL17 and IL22 were highly expressed in the serum of patients with pulmonary tuberculosis and lung cancer. Silencing TLR2 could inhibit the growth, invasion and migration ability of lung cancer cells, and promote apoptosis.A robotic surgical system capable of performing minimally invasive surgery (MIS) is proposed in this paper. Based on the requirements of MIS, a compliant, seven- degrees of freedom (7-DOF) pneumatically actuated mechanism is designed. learn more A remote center of motion (RCM) as a parallelogram mechanism for holding the laparoscopic camera is also developed. The operating workspace of robotic surgical system is determined considering the physical constraints imposed by mechanical joints. The simulation results show that the robotic system meets the design requirement. This research will lay a good foundation for the development of a compliant surgical robot to assist in MIS.News claims that travel the Internet and online social networks (OSNs) originate from different, sometimes unknown sources, which raises issues related to the credibility of those claims and the drivers behind them. Fact-checking websites such as Snopes, FactCheck, and Emergent use human evaluators to investigate and label news claims, but the process is labor- and time-intensive. Driven by the need to use data analytics and algorithms in assessing the credibility of news claims, we focus on what can be generalized about evaluating human-labeled claims. We developed tools to extract claims from Snopes and Emergent and used public datasets collected by and published on those websites. Claims extracted from those datasets were supervised or labeled with different claim ratings. We focus on claims with definite ratings-false, mostly false, true, and mostly true, with the goal of identifying distinctive features that can be used to distinguish true from false claims. Ultimately, those features can be used to predict future unsupervised or unlabeled claims. We evaluate different methods to extract features as well as different sets of features and their ability to predict the correct claim label. By far, we noticed that OSN websites report high rates of false claims in comparison with most of the other website categories. The rate of reported false claims is higher than the rate of true claims in fact-checking websites in most categories. At the content-analysis level, false claims tend to have more negative tones in sentiments and hence can provide supporting features to predict claim classification.Efficient, reproducible and accountable single-particle cryo-electron microscopy structure determination is tedious and often impeded by the lack of a standardized procedure for data analysis and processing. To address this issue, we have developed the FMI Live Analysis and Reconstruction Engine (CryoFLARE). CryoFLARE is a modular open-source platform offering easy integration of new processing algorithms developed by the cryo-EM community. It provides a user-friendly interface that allows fast setup of standardized workflows, serving the need of pharmaceutical industry and academia alike who need to optimize throughput of their microscope. To consistently document how data is processed, CryoFLARE contains an integrated reporting facility to create reports. Live analysis and processing parallel to data acquisition are used to monitor and optimize data quality. Problems at the level of the sample preparation (heterogeneity, ice thickness, sparse particles, areas selected for acquisition, etc.) or misalignmentssily be set up for remote display connections and fast control of the acquisition status.Biosilica is a biogenic composite material produced by organisms like diatoms. Various biomolecules are tightly attached or incorporated into biosilica. Examples are special proteins termed silaffins and long-chain polyamines (LCPAs). Presumably, these biomolecules are involved in the biosilica formation process. Silaffins are highly phosphorylated zwitterions with LCPAs post-translationally attached to lysine residues. In the present work, we use distance-dependent solid-state NMR experiments, especially the 31P29Si Rotational Echo Double Resonance (REDOR) technique, to study the environment of phosphate moieties in biosilica and in vitro synthesized SiO2-based composites. In contrast to the heterogeneous mixtures of biomolecules found in native biosilica, the described in vitro silicification experiments make use of a single synthetic phosphopeptide and an LCPA of well-defined and uniform structure. The heteronuclear correlations measured from these silica composites provide reliable 31P-29Si dipolar second moments and information about the distribution of the phosphopeptide within the silica material. The calculated second moment indicates close contact between phosphopeptides and silica. The phosphopeptides are incorporated into the silica composite in a disperse manner. Moreover, the REDOR data acquired for diatom biosilica also imply that phosphate groups are part of the silica-organic interface in this material.Sulfur hexafluoride (SF6) is one of the most harmful greenhouse gases producing environmental risks. Therefore, developing ways of degrading SF6 without forming hazardous products is increasingly important. Herein, we demonstrate for the first time the plasmon-catalytic heterogeneous degradation of SF6 into nonhazardous MgF2 and MgSO4 products by nontoxic and sustainable plasmonic magnesium/magnesium oxide (Mg/MgO) nanoparticles, which are also effective as a plasmon-enhanced SF6 chemometric sensor. The main product depends on the excitation wavelength; when the localized surface plasmon resonance (LSPR) is in the ultraviolet, then MgF2 forms, while visible light LSPR results in MgSO4. Furthermore, Mg/MgO platforms can be regenerated in few seconds by hydrogen plasma treatment and can be reused in a new cycle of air purification. Therefore, this research first demonstrates effectiveness of Mg/MgO plasmon-catalysis enabling environmental remediation with the concurrent functionalities of monitoring, degrading, and detecting sulfur and fluorine gases in the atmosphere.