Gradient-based particle filter algorithm for an ARX model with nonlinear communication output

A stochastic gradient (SG)-based particle filter (SG-PF) algorithm is developed for an ARX model with nonlinear communication output in this paper. This ARX model consists of two submodels, one is a linear ARX model and the other is a nonlinear output model. The process outputs (outputs of the linear submodel) transmitted over a communication channel are unmeasurable, while the communication outputs (outputs of the nonlinear submodel) are available, and both of the twotype outputs are contaminated by white noises. Based on the rich input data and the available communication output data, a SG-PF algorithm is proposed to estimate the unknown process outputs and parameters of the ARX model. Furthermore, a direct weight optimization method and the Epanechnikov kernel method are extended to modify the particle filter when the measurement noise is a Gaussian noise with unknown variance and the measurement noise distribution is unknown. The simulation results demonstrate that the SG-PF algorithm is effective

Characterization of severe fever with thrombocytopenia syndrome in rural regions of Zhejiang, China.

Severe fever with thrombocytopenia syndrome virus (SFTSV) infections have recently been found in rural regions of Zhejiang. A severe fever with thrombocytopenia syndrome (SFTS) surveillance and sero-epidemiological investigation was conducted in the districts with outbreaks. During the study period of 2011-2014, a total of 51 SFTSV infection cases were identified and the case fatality rate was 12% (6/51). Ninety two percent of the patients (47/51) were over 50 years of age, and 63% (32/51) of laboratory confirmed cases occurred from May to July. Nine percent (11/120) of the serum samples from local healthy people without symptoms were found to be positive for antibodies to the SFTS virus. SFTSV strains were isolated by culture using Vero, and the whole genomic sequences of two SFTSV strains (01 and Zhao) were sequenced and submitted to the GenBank. Homology analysis showed that the similarity of the target nucleocapsid gene from the SFTSV strains from different geographic areas was 94.2-100%. From the constructed phylogenetic tree, it was found that all the SFTSV strains diverged into two main clusters. Only the SFTSV strains from the Zhejiang (Daishan) region of China and the Yamaguchi, Miyazakj regions of Japan, were clustered into lineage II, consistent with both of these regions being isolated areas with similar geographic features. Two out of eight predicted linear B cell epitopes from the nucleocapsid protein showed mutations between the SFTSV strains of different clusters, but did not contribute to the binding ability of the specific SFTSV antibodies. This study confirmed that SFTSV has been circulating naturally and can cause a seasonal prevalence in Daishan, China. The results also suggest that the molecular characteristics of SFTSV are associated with the geographic region and all SFTSV strains can be divided into two genotypes

Biomineralization stimulated peri-titanium implants prepared by selective laser melting

AbstractTitanium implants prepared by selective laser melting (SLM), a method of additive manufacturing, were subjected to implantation in beagle dogs for two and four weeks. Argon ion beam-polished cross sections of the implants after in vivo tests were characterized by scanning electron microscope (SEM) to evaluate the bone–implant interface and the early peri-implant biomineralization with sufficiently improved resolution. Two bone mineralization mechanisms were disclosed. As early as two weeks after implantation, a layer of new bone was found to form directly on the implant surface and bone in-growth was also observed. Osseointegration was found to establish partly at the tip of the implants. After healing for four weeks it was found that osseointegration was established around the entire tip of the implants, whereas only partly at the third thread region of the implants. The experimental evidences observed reveal that an inherent highly porous surface of the titanium implants generated by selective laser melting is favorable for new bone apposition

Circumventing qPCR inhibition to amplify miRNAs in plasma

Background: Circulating microRNAs (c-miRNAs) have be identified in saliva, urine and blood, which has led to increasing interest in their development as biomarkers for diverse diseases including cancers. One of the key advantages of c-miRNAs over other biomarkers is the ability to be amplified and quantified by quantitative PCR (qPCR). However, at phlebotomy when whole blood is dispensed into heparinized tubes, residual levels of the anti-coagulant lithium heparin may remain in the plasma and hence with RNA isolated from the plasma. This can confound the detection of c-miRNAs by qPCR because it inhibits reverse transcriptase (RT). Here we present a procedure, modified from earlier techniques, to detect c-miRNAs in plasma that improves sensitivity and streamlines performance.Findings: Treatment of total RNA isolated from human blood plasma with Bacteroides heparinase I during reverse transcription at 37°C for one hour improved sensitivity and performance of the qPCR. This is in comparison to no treatment or treatment of the RNA prior to RT, which is the current suggested method and exposes plasma to Flavobacterium heparinum heparinase I for up to 2 hours before RT. This modest alteration improved qPCR performance and resulted in lowered threshold cycles (C) for detection of the target sequence, candidate c-miRNA biomarkers, and controls. It also reduced the expense and number of processing steps, shortening the duration of the assay and minimizing exposure of RNA to elevated temperatures.Conclusion: Incorporating Bacteroides heparinase I treatment into conventional RT protocols targeting c-miRNA in plasma can be expected to expedite the discovery of biomarkers

BatmanNet: Bi-branch Masked Graph Transformer Autoencoder for Molecular Representation

Although substantial efforts have been made using graph neural networks (GNNs) for AI-driven drug discovery (AIDD), effective molecular representation learning remains an open challenge, especially in the case of insufficient labeled molecules. Recent studies suggest that big GNN models pre-trained by self-supervised learning on unlabeled datasets enable better transfer performance in downstream molecular property prediction tasks. However, they often require large-scale datasets and considerable computational resources, which is time-consuming, computationally expensive, and environmentally unfriendly. To alleviate these limitations, we propose a novel pre-training model for molecular representation learning, Bi-branch Masked Graph Transformer Autoencoder (BatmanNet). BatmanNet features two tailored and complementary graph autoencoders to reconstruct the missing nodes and edges from a masked molecular graph. To our surprise, BatmanNet discovered that the highly masked proportion (60%) of the atoms and bonds achieved the best performance. We further propose an asymmetric graph-based encoder-decoder architecture for either nodes and edges, where a transformer-based encoder only takes the visible subset of nodes or edges, and a lightweight decoder reconstructs the original molecule from the latent representation and mask tokens. With this simple yet effective asymmetrical design, our BatmanNet can learn efficiently even from a much smaller-scale unlabeled molecular dataset to capture the underlying structural and semantic information, overcoming a major limitation of current deep neural networks for molecular representation learning. For instance, using only 250K unlabelled molecules as pre-training data, our BatmanNet with 2.575M parameters achieves a 0.5% improvement on the average AUC compared with the current state-of-the-art method with 100M parameters pre-trained on 11M molecules.Comment: 11 pages, 3 figure

Enhanced nucleation and precipitation hardening in Al-Mg-Si(-Cu) alloys with minor Cd additions

This work reports a novel effect of impurity element Cd on enhancing the precipitation kinetics and increasing the peak hardness of Al–Mg–Si(–Cu) alloys during artificial ageing. It is found that the number density of age hardening Mg–Si(–Cu) precipitates is greatly increased by Cd addition (~0.06 at.%) at both the under-aged and peak-aged stages. A systematic study on the precipitation behaviour by high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) shows that most Mg–Si(–Cu) precipitates in the Cd-containing Al–Mg–Si alloys are associated with Cd-rich precipitates and have highly disordered structures. It is also found that the formation of Q'/C-like sub-units in Mg–Si(–Cu) precipitates is significantly promoted by Cd additions. To explore the nucleation mechanism under the influence of Cd addition, atom probe tomography (APT) is applied to study the solute clustering behaviour in the early stages of artificial ageing, and density functional theory (DFT) calculations are used to evaluate the binding energies of different solute-vacancy complexes and therefore the formation kinetics of Mg–Si–Cd clusters.acceptedVersio

Effect of heat input on nanomechanical properties of wire-arc additive manufactured Al 4047 alloys

Heat input is one of the most important process parameters during additive manufacturing (AM). It is of great significance to understand the effect of heat input on the microstructure and nanomechanical properties, as well as the underlying mechanisms. Wire-arc additive manufactured (WAAM-ed) Al 4047 alloys under different heat inputs were produced and studied in this work. The as-manufactured Al alloys showed hypoeutectic microstructure that consisted of primary Al (α-Al) dendrite and ultrafine Al–Si eutectic. The effect of heat input on hardness and strain rate sensitivity (SRS) were investigated through nanoindentation. The nanohardness decreased with the increasing heat input, in accordance with the trend of yield strength and microhardness in the previous studies, in which the mechanism was usually explained by the grain growth model and Hall-Petch relationship. This work suggests a distinct mechanism regarding the effect of heat input on nanohardness, which is the enhanced solid solution strengthening produced by lower heat input. In addition, the heat input had little effect on the SRS and activation volume. It is hoped that this study leads to new insights into the understanding of the relation between heat input and nanomechanical properties, and further benefits to improve the targeted mechanical properties and engineering applications of the AM-ed materials.publishedVersio

Improving acid resistance of Escherichia coli base on the CfaS-mediated membrane engineering strategy derived from extreme acidophile

Industrial microorganisms used for the production of organic acids often face challenges such as inhibited cell growth and reduced production efficiency due to the accumulation of acidic metabolites. One promising way for improving the acid resistance of microbial cells is to reconstruct their membranes. Herein, the overexpression of cfa2 from extreme acidophile endowed E. coli with high-performance on resistance to the acid stress. The engineered strain M1-93-Accfa2, constructed by CRISPR/Cas9-mediated chromosome integration, also exhibited a significantly higher resistance to severe acid stress. The analysis of fatty acid profiles indicated that the proportion of Cy-19:0 in the cell membrane of M1-93-Accfa2 increased by 5.26 times compared with the control, while the proportion of C18:1w9c decreased by 5.81 times. Correspondingly, the permeability and fluidity of the membrane decreased significantly. HPLC analysis demonstrated that the contents of intracellular glutamic acid, arginine, methionine and aspartic acid of M1-93-Accfa2 were 2.59, 2.04, 22.07 and 2.65 times that of the control after environmental acidification, respectively. Meanwhile, transmission electron microscopy observation indicated that M1-93-Accfa2 could maintain a plumper cell morphology after acid stimulation. M1-93-Accfa2 also exhibited higher-performance on the resistance to organic acids, especially succinic acid stress. These results together demonstrated the great potential of M1-93-Accfa2 constructed here in the production of organic acids