Decentralized optimal H fusion estimation for multi-sensor networked systems with two-channel hybrid attacks.

The article aims at the decentralized optimal H fusion estimation issue for multi-sensor networked systems with insecure network communications, where hybrid attacks consisting of stochastic deception and denial-of-service attacks happen on both the sensor-to-local filter channel and the local filter-to-fusion center channel simultaneously. Some random variables obeying Bernoulli distributions are utilized to depict the hybrid attacks existing in two classes of communication channels in a unified framework. Relying on a novel augmentation method, the fusion estimation error system with globally internal dynamics is obtained.

Preparation and Properties of Lightweight Aggregates from Discarded AlO-ZrO-C Refractories.

Refractory materials are an important pillar for the stable development of the high-temperature industry. A large amount of waste refractories needs to be further disposed of every year, so it is of great significance to carry out research on the recycling of used refractories. In this work, lightweight composite aggregate was prepared by using discarded AlO-ZrO-C refractories as the main raw material, and the performance of the prepared lightweight aggregate was improved by adjusting the calcination temperature and introducing light calcined magnesia additives.

Distributed Optimal and Self-Tuning Filters Based on Compressed Data for Networked Stochastic Uncertain Systems with Deception Attacks.

In this study, distributed security estimation problems for networked stochastic uncertain systems subject to stochastic deception attacks are investigated. In sensor networks, the measurement data of sensor nodes may be attacked maliciously in the process of data exchange between sensors. When the attack rates and noise variances for the stochastic deception attack signals are known, many measurement data received from neighbour nodes are compressed by a weighted measurement fusion algorithm based on the least-squares method at each sensor node.

Circular RNA circZCCHC6 contributes to tumorigenesis by regulating LPCAT1 via miR-433-3p in non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) is one of the leading causes of cancer-associated mortality worldwide. Circular RNA (circRNA) circZCCHC6 has been reported to be upregulated in the plasma from NSCLC patients. This study is designed to explore the role and mechanism of circZCCHC6 in NSCLC.

A dumbbell probe-based dual signal amplification strategy for sensitive detection of multiple DNA methyltransferases.

We demonstrate for the first time the integration of a dumbbell probe with dual signal amplification for the simultaneous detection of multiple DNA methyltransferases (MTases). This method is very sensitive with a detection limit of 2.15 × 10 U mL for DNA adenine methyltransferase (Dam) and 3.

Dephosphorylation-directed tricyclic DNA amplification cascades for sensitive detection of protein tyrosine phosphatase.

We develop a new fluorescence method for the sensitive detection of protein tyrosine phosphatase 1B (PTP1B) based on dephosphorylation-directed tricyclic DNA amplification cascades. This method exhibits good specificity and high sensitivity with a detection limit of 0.24 pM.

Fano-like chiroptical response in plasmonic heterodimer nanostructures.

Plasmonic chirality has attracted more and more attention recently due to the enhanced chiroptical response and its potential applications in biosensing. Plasmonic Fano resonance arises from the interference between a dark narrow resonance and a bright broad resonance, and it provides a new paradigm to control the plasmon mode interactions. Even though a strong circular dichroism (CD) effect has been predicted in chiral nanostructures with a Fano resonance, there are few experimental studies, and the correlation between the two effects is unclear.

Self-Tuning Distributed Fusion Filter for Multi-Sensor Networked Systems with Unknown Packet Receiving Rates, Noise Variances, and Model Parameters.

In this study, we researched the problem of self-tuning (ST) distributed fusion state estimation for multi-sensor networked stochastic linear discrete-time systems with unknown packet receiving rates, noise variances (NVs), and model parameters (MPs). Packet dropouts may occur when sensor data are sent to a local processor. A Bernoulli distributed stochastic variable is adopted to depict phenomena of packet dropouts.

Expression profile of microRNAs in bronchoalveolar lavage fluid of rats as predictors for smoke inhalation injury.

Smoke inhalation injury (SII) is an independent risk factor for morbidity and mortality in patients with severe burns, however, the underlying mechanisms of SII are still not fully understood. In our study, we established an advanced rat model of SII based on the previous work, and explored the dynamic changes of pathophysiology and inflammatory factors during 28days post SII. We also measured the different expressions of miRNAs in bronchoalveolar lavage fluid (BALF) between SII and normal control rats by miRNA microarray.

Advances in Multi-Sensor Information Fusion: Theory and Applications 2017.

The information fusion technique can integrate a large amount of data and knowledge representing the same real-world object and obtain a consistent, accurate, and useful representation of that object. The data may be independent or redundant, and can be obtained by different sensors at the same time or at different times. A suitable combination of investigative methods can substantially increase the profit of information in comparison with that from a single sensor.

Dynamic Tracking Human Mesenchymal Stem Cells Tropism following Smoke Inhalation Injury in NOD/SCID Mice.

Multiple preclinical evidences have supported the potential value of mesenchymal stem cells (MSCs) for treatment of acute lung injury (ALI). However, few studies focus on the dynamic tropism of MSCs in animals with acute lung injury. In this study, we track systemically transplanted human bone marrow-derived mesenchymal stem cells (hBMSCs) in NOD/SCID mice with smoke inhalation injury (SII) through bioluminescence imaging (BLI).

In Vivo Tracking of Systemically Administered Allogeneic Bone Marrow Mesenchymal Stem Cells in Normal Rats through Bioluminescence Imaging.

Recently, mesenchymal stem cells (MSCs) are increasingly used as a panacea for multiple types of disease short of effective treatment. Dozens of clinical trials published demonstrated strikingly positive therapeutic effects of MSCs. However, as a specific agent, little research has focused on the dynamic distribution of MSCs after in vivo administration.

State Estimation for a Class of Non-Uniform Sampling Systems with Missing Measurements.

This paper is concerned with the state estimation problem for a class of non-uniform sampling systems with missing measurements where the state is updated uniformly and the measurements are sampled randomly. A new state model is developed to depict the dynamics at the measurement sampling points within a state update period. A non-augmented state estimator dependent on the missing rate is presented by applying an innovation analysis approach.

Evaluating the nucleus effect on the dynamic indentation behavior of cells.

The effect of the nucleus on the cell mechanical behavior was investigated based on the dynamic indentation response of cells under a spherical tip. A "two-component" cell model (including cytoplasm and nucleus) is used, and the dynamic indentation behavior is studied by a semiempirical method, which is established based on fitting the numerical simulation results of the quasi-static indentation response of cells. We found that the "routine analysis" (based on the Hertz's contact solution of homogeneous model) significantly overestimated the nucleus effect on the overall cell indentation response due to the effects of the Hertz contact radius and the substrate stiffening.

Multisensor optimal information fusion input white noise deconvolution estimators.

The unified multisensor optimal information fusion criterion weighted by matrices is rederived in the linear minimum variance sense, where the assumption of normal distribution is avoided. Based on this fusion criterion, the optimal information fusion input white noise deconvolution estimators are presented for discrete time-varying linear stochastic control system with multiple sensors and correlated noises, which can be applied to seismic data processing in oil exploration. A three-layer fusion structure with fault tolerant property and reliability is given.

[The three-dimensional nonlinear finite element analysis of force system of the "rocking-chair archwire"].

Objective: The purpose of this study was to qualitatively and quantitatively analyze the initial force system of "rocking-chair archwire" on every tooth.

Methods: Three-dimensional finite element model of "rocking-chair archwire" was set up, and nonlinear method was used to analyze the force system.

Results: The archwire exerted intruding force, labial force, lingual-root torque and mesial-labial moment on incisors; Extruding force, lingual-root torque and mesial-labial moment were applied on canines and premolars; The archwire also created intruding force, buccal force, buccal-root torque and mesial-labial moment on molars.