Reduced-order modeling using Dynamic Mode Decomposition and Least Angle Regression

Dynamic Mode Decomposition (DMD) yields a linear, approximate model of a system's dynamics that is built from data. We seek to reduce the order of this model by identifying a reduced set of modes that best fit the output. We adopt a model selection algorithm from statistics and machine learning known as Least Angle Regression (LARS). We modify LARS to be complex-valued and utilize LARS to select DMD modes. We refer to the resulting algorithm as Least Angle Regression for Dynamic Mode Decomposition (LARS4DMD). Sparsity-Promoting Dynamic Mode Decomposition (DMDSP), a popular mode-selection algorithm, serves as a benchmark for comparison. Numerical results from a Poiseuille flow test problem show that LARS4DMD yields reduced-order models that have comparable performance to DMDSP. LARS4DMD has the added benefit that the regularization weighting parameter required for DMDSP is not needed.Comment: 14 pages, 2 Figures, Submitted to AIAA Aviation Conference 201

Lateral Response of Bridge Pile Groups in Liquefiable Soil with Surface Non-Liquefiable Layer Using Shaking Table Test

This paper conducts a shaking table test study on seismic response of low-cap pile groups and bridge structure in liquefiable ground. The soil profile in the test consisted of the horizontal saturated sand layer overlaid the silty clay layer. The base was excited by three different El Centro earthquake events. The preliminary liquefaction characteristics of ground firstly were analyzed. The bending moment of the pile was mainly introduce in the note. There’s no doubt that the shaking table test provided the necessary groundwork to study lateral response of bridge pile groups in liquefiable soil with surface non-liquefiable layer

Measurement of HbA1c and HbA2 by Capillarys 2 Flex Piercing HbA1c programme for simultaneous management of diabetes and screening for thalassemia

Introduction: Thalassemia could interfere with some assays for haemoglobin A1c (HbA1c) measurement, therefore, it is useful to be able to screen for thalassemia while measuring HbA1c. We used Capillarys 2 Flex Piercing (Capillarys 2FP) HbA1c programme to simultaneously measure HbA1c and screen for thalassemia. Materials and methods: Samples from 498 normal controls and 175 thalassemia patients were analysed by Capillarys 2FP HbA1c programme (Sebia, France). For method comparison, HbA1c was quantified by Premier Hb9210 (Trinity Biotech, Ireland) in 98 thalassaemia patients samples. For verification, HbA1c from eight thalassaemia patients was confirmed by IFCC reference method. Results: Among 98 thalassaemia samples, Capillarys 2FP did not provide an HbA1c result in three samples with HbH due to the overlapping of HbBart’s with HbA1c fraction; for the remaining 95 thalassaemia samples, Bland-Altman plot showed 0.00 ± 0.35% absolute bias between two systems, and a significant positive bias above 7% was observed only in two HbH samples. The HbA1c values obtained by Capillarys 2FP were consistent with the IFCC targets (relative bias below ± 6%) in all of the eight samples tested by both methods. For screening samples with alpha (α-) thalassaemia silent/trait or beta (β-) thalassemia trait, the optimal HbA2 cut-off values were ≤ 2.2% and > 2.8%, respectively. Conclusions: Our results demonstrated the Capillarys 2FP HbA1c system could report an accurate HbA1c value in thalassemia silent/trait, and HbA2 value (≤ 2.2% for α-thalassaemia silent/trait and > 2.8% for β-thalassemia trait) and abnormal bands (HbH and/or HbBart’s for HbH disease, HbF for β-thalassemia) may provide valuable information for screening

RNA-binding protein RALY reprogrammes mitochondrial metabolism via mediating miRNA processing in colorectal cancer

Objective: Dysregulated cellular metabolism is a distinct hallmark of human colorectal cancer (CRC). However, metabolic programme rewiring during tumour progression has yet to be fully understood. Design: We analysed altered gene signatures during colorectal tumour progression, and used a complex of molecular and metabolic assays to study the regulation of metabolism in CRC cell lines, human patient-derived xenograft mouse models and tumour organoid models. Results: We identified a novel RNA-binding protein, RALY (also known as hnRNPCL2), that is highly associated with colorectal tumour aggressiveness. RALY acts as a key regulatory component in the Drosha complex, and promotes the post-transcriptional processing of a specific subset of miRNAs (miR-483, miR-676 and miR-877). These miRNAs systematically downregulate the expression of the metabolism-associated genes (ATP5I, ATP5G1, ATP5G3 and CYC1) and thereby reprogramme mitochondrial metabolism in the cancer cell. Analysis of The Cancer Genome Atlas (TCGA) reveals that increased levels of RALY are associated with poor prognosis in the patients with CRC expressing low levels of mitochondrion-associated genes. Mechanistically, induced processing of these miRNAs is facilitated by their N6-methyladenosine switch under reactive oxygen species (ROS) stress. Inhibition of the m6A methylation abolishes the RALY recognition of the terminal loop of the pri-miRNAs. Knockdown of RALY inhibits colorectal tumour growth and progression in vivo and in organoid models. Conclusions: Collectively, our results reveal a critical metabolism-centric role of RALY in tumour progression, which may lead to cancer therapeutics targeting RALY for treating CRC

Structural Stiffness Identification Based on the Extended Kalman Filter Research

For the response acquisition of the structure section measuring points, the method of identifying the structural stiffness parameters is developed by using the extended Kalman filter. The state equation of structural system parameter is a nonlinear equation. Dispersing the structural dynamic equation by using Newmark-β method, the state transition matrix of discrete state equation is deduced and the solution of discrete state equation is simplified. The numerical simulation shows that the error of structural recognition doesnot exceed 5% when the noise level is 3%. It meets the requirements of the error limit of the engineering structure, which indicates that the derivation described in this paper has the robustness for the structural stiffness recognition. Shear structure parameter identification examples illustrate its applicability, and the method can also be used to identify physical parameters of large structure

Research on shipborne aided navigation system based on enhanced traffic environment perception

The traditional shipborne navigation system uses a two-dimensional electronic chart as a platform to integrate and control a variety of electronic navigation equipment information. It cannot intuitively restore the actual traffic environment or fundamentally improve the perception ability of the crew in poor visibility conditions. This paper proposes integrating three-dimensional simulations and real ship driving systems and presents research on "virtual-real" and "dynamic-static" ship navigation technology and equipment. In the proposed method, the hydrologic factors, topographic features, waterways, traffic dynamics, and ship driving information are effectively integrated, with a focus on achieving key advancements such as the integration of simulations and real ship driving as well as multi-source information fusion. A multi-angle, all-around, multi-level visual display for water traffic environments in poor visibility conditions is provided to enhance the ability of crews to perceive their traffic environments and thereby to provide auxiliary navigation for ships in complex weather conditions.</p

Research on Laboratory Testing Method of Fatigue Performance of Semi-Rigid Base Considering Spatial Stress State

In order to accurately assess the fatigue performance of semi-rigid base layers, this paper proposes a novel fatigue testing method for semi-rigid base layers that takes into account the spatial stress state. Based on this method, the fatigue performance of three types of reinforced semi-rigid base-layer materials (steel wire mesh, plastic geogrid, and fiberglass) was tested and compared with unreinforced materials. The fatigue strain evolution patterns of these materials were analyzed, and a fatigue strain characteristic value at the limit state was proposed as an evaluation index for the fatigue failure of base layer materials. The results showed that in terms of fatigue performance, plastic geogrid > steel wire mesh > fiberglass > unreinforced specimens. The development of tensile strain can be approximately classified into a three-stage growth pattern, consisting of “curve + straight line + curve”. For the unreinforced specimens, the three stages of bending strain accounted for 10%, 70%, and 20% of the total fatigue life, respectively. The fatigue failure stages of the three types of reinforced materials had similar proportional ranges, representing 5%, 75%, and 20% of the total fatigue life, respectively. The fatigue strain characteristic values for plastic geogrid, steel wire mesh, fiberglass, and unreinforced specimens were 371 με, 280 με, 280 με, and 195 με, respectively. In summary, the use of reinforced materials within semi-rigid base layers enhances their fatigue performance, providing new insights and methods for extending the service life of road surfaces and offering scientific guidance for the practical application of reinforced materials in semi-rigid base layer road surfaces’ fatigue performance

Deep Temporal–Spatial Aggregation for Video-Based Facial Expression Recognition

The proposed method has 30 streams, i.e., 15 spatial streams and 15 temporal streams. Each spatial stream corresponds to each temporal stream. Therefore, this work correlates with the symmetry concept. It is a difficult task to classify video-based facial expression owing to the gap between the visual descriptors and the emotions. In order to bridge the gap, a new video descriptor for facial expression recognition is presented to aggregate spatial and temporal convolutional features across the entire extent of a video. The designed framework integrates a state-of-the-art 30 stream and has a trainable spatial&ndash;temporal feature aggregation layer. This framework is end-to-end trainable for video-based facial expression recognition. Thus, this framework can effectively avoid overfitting to the limited emotional video datasets, and the trainable strategy can learn to better represent an entire video. The different schemas for pooling spatial&ndash;temporal features are investigated, and the spatial and temporal streams are best aggregated by utilizing the proposed method. The extensive experiments on two public databases, BAUM-1s and eNTERFACE05, show that this framework has promising performance and outperforms the state-of-the-art strategies

Single-stranded DNA-binding proteins regulate the abundance of LIM domain and LIM domain-binding proteins

The LIM domain-binding protein Ldb1 is an essential cofactor of LIM-homeodomain (LIM-HD) and LIM-only (LMO) proteins in development. The stoichiometry of Ldb1, LIM-HD, and LMO proteins is tightly controlled in the cell and is likely a critical determinant of their biological actions. Single-stranded DNA-binding proteins (SSBPs) were recently shown to interact with Ldb1 and are also important in developmental programs. We establish here that two mammalian SSBPs, SSBP2 and SSBP3, contribute to an erythroid DNA-binding complex that contains the transcription factors Tal1 and GATA-1, the LIM domain protein Lmo2, and Ldb1 and binds a bipartite E-box-GATA DNA sequence motif. In addition, SSBP2 was found to augment transcription of the Protein 4.2 (P4.2) gene, a direct target of the E-box-GATA-binding complex, in an Ldb1-dependent manner and to increase endogenous Ldb1 and Lmo2 protein levels, E-box-GATA DNA-binding activity, and P4.2 and β-globin expression in erythroid progenitors. Finally, SSBP2 was demonstrated to inhibit Ldb1 and Lmo2 interaction with the E3 ubiquitin ligase RLIM, prevent RLIM-mediated Ldb1 ubiquitination, and protect Ldb1 and Lmo2 from proteasomal degradation. These results define a novel biochemical function for SSBPs in regulating the abundance of LIM domain and LIM domain-binding proteins

Geochemical Characteristics and Development Model of the Coal-Measure Source Rock in the Kuqa Depression of Tarim Basin

The development model of the coal-measure source rock may be different from that of the lacustrine source rock. The depositional environment of the coal-measure source rock is dominated by weak oxidation and weak reduction, and the majority of the organic material originates from terrestrial higher plants. Taking the Jurassic coal-measure source rock in the Kuqa Depression as the research object, the geochemical characteristics of the source rock are comprehensively analyzed, the primary controlling elements of source rock development are made clear, and the development model of the coal-measure source rock is established. This study contributes to the field of source rock prediction and oil and gas exploration. The lithology of the coal-measure source rock in the Kuqa Depression is mainly mudstone, carbonaceous mudstone, and coal, which are medium- to good-quality source rocks, and the organic matter type is mainly II2 and III. Terrestrial organic matter is a key factor in controlling the formation of coal-measure source rocks, and the sedimentation rate also has a certain influence. The redox degree of the depositional environment, water salinity, and clay mineral content has little influence on the development of coal-measure source rocks. By integrating the main control factors, the development model of the coal-measure source rock is established. It is considered that the development model and distribution characteristics of the coal-measure source rock are different from the traditional understanding of lacustrine source rocks, and it is pointed out that the coal-measure source rock in the gentle slope zone is more developed than the sag area