Distributed filtering of networked dynamic systems with non-gaussian noises over sensor networks: A survey

summary:Sensor networks are regarded as a promising technology in the field of information perception and processing owing to the ease of deployment, cost-effectiveness, flexibility, as well as reliability. The information exchange among sensors inevitably suffers from various network-induced phenomena caused by the limited resource utilization and complex application scenarios, and thus is required to be governed by suitable resource-saving communication mechanisms. It is also noteworthy that noises in system dynamics and sensor measurements are ubiquitous and in general unknown but can be bounded, rather than follow specific Gaussian distributions as assumed in Kalman-type filtering. Particular attention of this paper is paid to a survey of recent advances in distributed filtering of networked dynamic systems with non-Gaussian noises over sensor networks. First, two types of widely employed structures of distributed filters are reviewed, the corresponding analysis is systematically addressed, and some interesting results are provided. The inherent purpose of adding consensus terms into the distributed filters is profoundly disclosed. Then, some representative models characterizing various network-induced phenomena are reviewed and their corresponding analytical strategies are exhibited in detail. Furthermore, recent results on distributed filtering with non-Gaussian noises are sorted out in accordance with different network-induced phenomena and system models. Another emphasis is laid on recent developments of distributed filtering with various communication scheduling, which are summarized based on the inherent characteristics of their dynamic behavior associated with mathematical models. Finally, the state-of-the-art of distributed filtering and challenging issues, ranging from scalability, security to applications, are raised to guide possible future research

Recent Advances in Model-Based Fault Diagnosis for Lithium-Ion Batteries: A Comprehensive Review

Lithium-ion batteries (LIBs) have found wide applications in a variety of fields such as electrified transportation, stationary storage and portable electronics devices. A battery management system (BMS) is critical to ensure the reliability, efficiency and longevity of LIBs. Recent research has witnessed the emergence of model-based fault diagnosis methods in advanced BMSs. This paper provides a comprehensive review on the model-based fault diagnosis methods for LIBs. First, the widely explored battery models in the existing literature are classified into physics-based electrochemical models and electrical equivalent circuit models. Second, a general state-space representation that describes electrical dynamics of a faulty battery is presented. The formulation of the state vectors and the identification of the parameter matrices are then elaborated. Third, the fault mechanisms of both battery faults (incl. overcharege/overdischarge faults, connection faults, short circuit faults) and sensor faults (incl. voltage sensor faults and current sensor faults) are discussed. Furthermore, different types of modeling uncertainties, such as modeling errors and measurement noises, aging effects, measurement outliers, are elaborated. An emphasis is then placed on the observer design (incl. online state observers and offline state observers). The algorithm implementation of typical state observers for battery fault diagnosis is also put forward. Finally, discussion and outlook are offered to envision some possible future research directions.Comment: Submitted to Renewable and Sustainable Energy Reviews on 09-Jan-202

Experiment Research on Deformation Mechanism of CNT Film Material

Nanometer composite usually has multilevel structure, and deformation mechanism of its multilevel structure is the hot spot at present. The paper studies deformation mechanism of multilevel structure of CNT film material under tension loading and its influence on film mechanical properties by jointing multiscale experiment methods such as tensile test, digital image correlation, SEM observation, and in situ micro-Raman spectroscopy. The result shows that, during film loading process, the deformation of CNTs inside the film endures elastic elongation and glide successively, with very small axial elongation, which is about 7% of film deformation; the deformation of CNT bundle network structure endures deformation mechanism such as CNT bundle extension, rotation, and glide, and this structure deformation occupies about 93% of film deformation that large structure deformation makes CNT film have good toughness; during film loading process, the formation of CNT bundle long chain and glide mechanism in the chains help to improve film strength and toughness

Comprehensive transcriptome analysis of peripheral blood unravels key lncRNAs implicated in ABPA and asthma

Allergic bronchopulmonary aspergillosis (ABPA) is a complex hypersensitivity lung disease caused by a fungus known as Aspergillus fumigatus. It complicates and aggravates asthma. Despite their potential associations, the underlying mechanisms of asthma developing into ABPA remain obscure. Here we performed an integrative transcriptome analysis based on three types of human peripheral blood, which derived from ABPA patients, asthmatic patients and health controls, aiming to identify crucial lncRNAs implicated in ABPA and asthma. Initially, a high-confidence dataset of lncRNAs was identified using a stringent filtering pipeline. A comparative mutational analysis revealed no significant difference among these samples. Differential expression analysis disclosed several immune-related mRNAs and lncRNAs differentially expressed in ABPA and asthma. For each disease, three sub-networks were established using differential network analysis. Many key lncRNAs implicated in ABPA and asthma were identified, respectively, i.e., AL139423.1-201, AC106028.4-201, HNRNPUL1-210, PUF60-218 and SREBF1-208. Our analysis indicated that these lncRNAs exhibits in the loss-of-function networks, and the expression of which were repressed in the occurrences of both diseases, implying their important roles in the immune-related processes in response to the occurrence of both diseases. Above all, our analysis proposed a new point of view to explore the relationship between ABPA and asthma, which might provide new clues to unveil the pathogenic mechanisms for both diseases

Integrated Analysis of Transcriptome and Metabolome Reveals the Mechanism of Chlorine Dioxide Repressed Potato (Solanum tuberosum L.) Tuber Sprouting

Sprouting is an irreversible deterioration of potato quality, which not only causes loss in their commercial value but also produces harmful toxins. As a popular disinfectant, ClO2 can inhibit the sprouting of potato tubers. Using transcriptomic and metabolomic approaches to understand the repressive mechanism of ClO2 in potato sprouting is yet to be reported. Sequencing the transcriptome and metabolome of potatoes treated with ClO2 in this study revealed a total of 3,119 differentially expressed genes, with 1,247 and 1,872 genes showing down- and upregulated expression, respectively. The majority of the downregulated genes were associated with plant hormone signal transduction, whereas upregulated differential genes were associated primarily with biological processes, such as phenylpropanoid biosynthesis and the mitogen-activated protein kinase (MAPK) signaling pathway. Metabonomic assays identified a total of 932 metabolites, with 33 and 52 metabolites being down- and upregulated, respectively. Downregulated metabolites were mostly alkaloids, amino acids, and their derivatives, whereas upregulated metabolites were composed mainly of flavonoids and coumarins. Integrated transcriptomic and metabolomic analyses showed that many different metabolites were regulated by several different genes, forming a complex regulatory network. These results provide new insights for understanding the mechanism of ClO2-mediated repression of potato sprouting

The p.V37I Exclusive Genotype Of GJB2: A Genetic Risk-Indicator of Postnatal Permanent Childhood Hearing Impairment

Postnatal permanent childhood hearing impairment (PCHI) is frequent (0.25%–0.99%) and difficult to detect in the early stage, which may impede the speech, language and cognitive development of affected children. Genetic tests of common variants associated with postnatal PCHI in newborns may provide an efficient way to identify those at risk. In this study, we detected a strong association of the p.V37I exclusive genotype of GJB2 with postnatal PCHI in Chinese Hans (P = 1.4×10−10; OR 62.92, 95% CI 21.27–186.12). This common genotype in Eastern Asians was present in a substantial percentage (20%) of postnatal PCHI subjects, and its prevalence was significantly increased in normal-hearing newborns who failed at least one newborn hearing screen. Our results indicated that the p.V37I exclusive genotype of GJB2 may cause subclinical hearing impairment at birth and increases risk for postnatal PCHI. Genetic testing of GJB2 in East Asian newborns will facilitate prompt detection and intervention of postnatal PCHI