Multi-channel ARMA Signal Covariance Intersection Fusion Kalman Predictor

AbstractFor multi-channel ARMA signal with two sensors and unknown cross-covariances between the local Kalman predicting errors, based on the transformation of ARMA signal model to the state space model, a covariance intersection (CI) fusion steady-state Kalman signal predictor is presented. The accuracy comparison of CI Kalman signal fuser with the Kalman fuser weighted by matrices, diagonal matrices, and scalars is given. The geometric interpretation of accuracy relations is given by the covariance ellipses. Its accuracy is higher than that of each local Kalman predictor, and lower than that of optimal Kalman predictor weighted by matrices. A Monte-Carlo simulation results show its effectiveness and its actual accuracy is close to that of the optimal fuser weighted by matrices

A high-performance hardware architecture of an image matching system based on the optimised SIFT algorithm

The Scale Invariant Feature Transform (SIFT) is one of the most popular matching algorithms in the field of computer vision. It takes over many other algorithms because features detected are fully invariant to image scaling and rotation, and are also shown to be robust to changes in 3D viewpoint, addition of noise, changes in illumination and a sustainable range of affine distortion. However, the computational complexity is high, which prevents it from achieving real-time. The aim of this project, therefore, is to develop a high-performance image matching system based on the optimised SIFT algorithm to perform real-time feature detection, description and matching. This thesis presents the stages of the development of the system. To reduce the computational complexity, an alternative to the grid layout of standard SIFT is proposed, which is termed as SRI-DASIY (Scale and Rotation Invariant DAISY). The SRI-DAISY achieves comparable performance with the standard SIFT descriptor, but is more efficient to be implemented using hardware, in terms of both computational complexity and memory usage. The design takes only 7.57 µs to generate a descriptor with a system frequency of 100 MHz, which is equivalent to approximately 132,100 descriptors per second and is of the highest throughput when compared with existing designs. Besides, a novel keypoint matching strategy is also presented in this thesis, which achieves higher precision than the widely applied distance ratio based matching and is computationally more efficient. All phases of the SIFT algorithm have been investigated, including feature detection, descriptor generation and descriptor matching. The characterisation of each individual part of the design is carried out and compared with the software simulation results. A fully stand-alone image matching system has been developed that consists of a CMOS camera front-end for image capture, a SIFT processing core embedded in a Field Programmable Logic Array (FPGA) device, and a USB back-end for data transfer. Experiments are conducted by using real-world images to verify the system performance. The system has been tested by integrating into two practical applications. The resulting image matching system eliminates the bottlenecks that limit the overall throughput of the system, and hence allowing the system to process images in real-time without interruption. The design can be modified to adapt to the applications processing images with higher resolution and is still able to achieve real-time

A high-performance hardware architecture of an image matching system based on the optimised SIFT algorithm

The Scale Invariant Feature Transform (SIFT) is one of the most popular matching algorithms in the field of computer vision. It takes over many other algorithms because features detected are fully invariant to image scaling and rotation, and are also shown to be robust to changes in 3D viewpoint, addition of noise, changes in illumination and a sustainable range of affine distortion. However, the computational complexity is high, which prevents it from achieving real-time. The aim of this project, therefore, is to develop a high-performance image matching system based on the optimised SIFT algorithm to perform real-time feature detection, description and matching. This thesis presents the stages of the development of the system. To reduce the computational complexity, an alternative to the grid layout of standard SIFT is proposed, which is termed as SRI-DASIY (Scale and Rotation Invariant DAISY). The SRI-DAISY achieves comparable performance with the standard SIFT descriptor, but is more efficient to be implemented using hardware, in terms of both computational complexity and memory usage. The design takes only 7.57 µs to generate a descriptor with a system frequency of 100 MHz, which is equivalent to approximately 132,100 descriptors per second and is of the highest throughput when compared with existing designs. Besides, a novel keypoint matching strategy is also presented in this thesis, which achieves higher precision than the widely applied distance ratio based matching and is computationally more efficient. All phases of the SIFT algorithm have been investigated, including feature detection, descriptor generation and descriptor matching. The characterisation of each individual part of the design is carried out and compared with the software simulation results. A fully stand-alone image matching system has been developed that consists of a CMOS camera front-end for image capture, a SIFT processing core embedded in a Field Programmable Logic Array (FPGA) device, and a USB back-end for data transfer. Experiments are conducted by using real-world images to verify the system performance. The system has been tested by integrating into two practical applications. The resulting image matching system eliminates the bottlenecks that limit the overall throughput of the system, and hence allowing the system to process images in real-time without interruption. The design can be modified to adapt to the applications processing images with higher resolution and is still able to achieve real-time

Animal waste use and implications to agricultural greenhouse gas emissions in the United States

Acknowledgements: Z. Q. and S. D. have been partially supported by the National Basic Research Program of China (2016YFA0602701), the National Natural Science Foundation of China (41975113), and the Guangdong Provincial Department of Science and Technology (2019ZT08G090). The input of P. S. contributed to the following projects: DEVIL (NE/M021327/1) and Soils-R-GRREAT (NE/P019455/1). Data availability: The data that support the findings of this study are openly available at the following URL/DOI: https://greet.es.anl.gov/. Publisher Copyright: © 2021 The Author(s). Published by IOP Publishing Ltd. Creative Commons Attribution 4.0 license, Original content from this work may be used under the terms of the . Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.Peer reviewedPublisher PD

Genetic Diversity Analysis of Hypsizygus marmoreus

Hypsizygus marmoreus is an industrialized edible mushroom. In the present paper, the genetic diversity among 20 strains collected from different places of China was evaluated by target region amplification polymorphism (TRAP) analysis; the common fragment of TRAPs was sequenced and analyzed. Six fixed primers were designed based on the analysis of H. marmoreus sequences from GenBank database. The genomic DNA extracted from H. marmoreus was amplified with 28 TRAP primer combinations, which generated 287 bands. The average of amplified bands per primer was 10.27 (mean polymorphism is 69.73%). The polymorphism information content (PIC) value for TRAPs ranged from 0.32 to 0.50 (mean PIC value per TRAP primer combination is 0.48), which indicated a medium level of polymorphism among the strains. A total of 36 sequences were obtained from TRAP amplification. Half of these sequences could encode the known or unknown proteins. According to the phylogenetic analysis based on TRAP result, the 20 strains of H. marmoreus were classified into two main groups

Metagenomic insights into the abundance and composition of resistance genes in aquatic environments:Influence of stratification and geography

A global survey was performed with 122 aquatic metagenomic DNA datasets (92 lake water and 30 seawater) obtained from the Sequence Read Archive (SRA). Antibiotic resistance genes (ARGs) and metal resistance genes (MRGs) were derived from the dataset sequences via bioinformatic analysis. The relative abundances of ARGs and MRGs in lake samples were in the ranges ND (not detected)-1.34x10(0) and 1.22x10(-3) -1.98x10(-1) copies per 16S rRNA, which were higher than those in seawater samples. Among ARGs, multidrug resistance genes and bacitracin resistance genes had high relative abundances in both lake and sea water samples. Multimetal resistance genes, mercury resistance genes and copper resistance genes had the greatest relative abundance for MRGs. No significant difference was found between epilimnion and hypolimnion in abundance or the Shannon diversity index for ARGs and MRGs. Principal coordinates analysis and permutational multivariate analysis of variance (PERMANOVA) test showed that stratification and geography had significant influence on the composition of ARGs and MRGs in lakes (p < 0.05, PERMANOVA). Coastal seawater samples had significantly greater relative abundance and a higher Shannon index for both ARGs and MRGs than deep ocean and Antarctic seawater samples (p < 0.05, Kruskal-Wallis one-way ANOVA), suggesting that human activity may exert more selective pressure on ARGs and MRGs in coastal areas than those in deep ocean and Antarctic seawater

Prognostic Value of MicroRNA-20b in Acute Myeloid Leukemia

Acute myeloid leukemia (AML) is a highly heterogeneous disease that requires fine-grained risk stratification for the best prognosis of patients. As a class of small non-coding RNAs with important biological functions, microRNAs play a crucial role in the pathogenesis of AML. To assess the prognostic impact of miR-20b on AML in the presence of other clinical and molecular factors, we screened 90 AML patients receiving chemotherapy only and 74 also undergoing allogeneic hematopoietic stem cell transplantation (allo-HSCT) from the Cancer Genome Atlas (TCGA) database. In the chemotherapy-only group, high miR-20b expression subgroup had shorter event-free survival (EFS) and overall survival (OS, both P < 0.001); whereas, there were no significant differences in EFS and OS between high and low expression subgroups in the allo-HSCT group. Then we divided all patients into high and low expression groups based on median miR-20b expression level. In the high expression group, patients treated with allo-HSCT had longer EFS and OS than those with chemotherapy alone (both P < 0.01); however, there were no significant differences in EFS and OS between different treatment subgroups in the low expression group. Further analysis showed that miR-20b was negatively correlated with genes in "ribosome," "myeloid leukocyte mediated immunity," and "DNA replication" signaling pathways. ORAI2, the gene with the strongest correlation with miR-20b, also had significant prognostic value in patients undergoing chemotherapy but not in the allo-HSCT group. In conclusion, our findings suggest that high miR-20b expression is a poor prognostic indicator for AML, but allo-HSCT may override its prognostic impact

Flexoelectricity-stabilized ferroelectric phase with enhanced reliability in ultrathin La:HfO2 films

Doped HfO2 thin films exhibit robust ferroelectric properties even for nanometric thicknesses, are compatible with current Si technology and thus have great potential for the revival of integrated ferroelectrics. Phase control and reliability are core issues for their applications. Here we show that, in (111)-oriented 5%La:HfO2 (HLO) epitaxial thin films deposited on (La0.3Sr0.7)(Al0.65Ta0.35)O3 substrates, the flexoelectric effect, arising from the strain gradient along the films normal, induces a rhombohedral distortion in the otherwise Pca21 orthorhombic structure. Density functional calculations reveal that the distorted structure is indeed more stable than the pure Pca21 structure, when applying an electric field mimicking the flexoelectric field. This rhombohedral distortion greatly improves the fatigue endurance of HLO thin films by further stabilizing the metastable ferroelectric phase against the transition to the thermodynamically stable non-polar monoclinic phase during repetitive cycling. Our results demonstrate that the flexoelectric effect, though negligibly weak in bulk, is crucial to optimize the structure and properties of doped HfO2 thin films with nanometric thicknesses for integrated ferroelectric applications

Regulation of Wnt Singaling Pathway by Poly (ADP-Ribose) Glycohydrolase (PARG) Silencing Suppresses Lung Cancer in Mice Induced by Benzo(a)pyrene Inhalation Exposure

Benzo(a)pyrene (BaP) is a polycyclic aromatic hydrocarbon that specifically causes cancer and is widely distributed in the environment. Poly (ADP-ribosylation), as a key post-translational modification in BaP-induced carcinogenesis, is mainly catalyzed by poly (ADP-ribose) glycohydrolase (PARG) in eukaryotic organisms. Previously, it is found that PARG silencing can counteract BaP-induced carcinogenesis in vitro, but the mechanism remained unclear. In this study, we further examined this process in vivo by using heterozygous PARG knockout mice (PARG+/−). Wild-type and PARG+/− mice were individually treated with 0 or 10 μg/m3 BaP for 90 or 180 days by dynamic inhalation exposure. Pathological analysis of lung tissues showed that, with extended exposure time, carcinogenesis and injury in the lungs of WT mice was progressively worse; however, the injury was minimal and carcinogenesis was not detected in the lungs of PARG+/− mice. These results indicate that PARG gene silencing protects mice against lung cancer induced by BaP inhalation exposure. Furthermore, as the exposure time was extended, the protein phosphorylation level was down-regulated in WT mice, but up-regulated in PARG+/− mice. The relative expression of Wnt2b and Wnt5b mRNA in WT mice were significantly higher than those in the control group, but there was no significant difference in PARG+/− mice. Meanwhile, the relative expression of Wnt2b and Wnt5b proteins, as assessed by immunohistochemistry and Western blot analysis, was significantly up-regulated by BaP in WT mice; while in PARG+/− mice it was not statistically affected. Our work provides initial evidence that PARG silencing suppresses BaP induced lung cancer and stabilizes the expression of Wnt ligands, PARG gene and Wnt ligands may provide new options for the diagnosis and treatment of lung cancer