Visualizing the impact of Covid-19 vaccine passports on pedestrian access to metro stations in Hong Kong

Pedestrian infrastructures in Hong Kong enable multilevel city life in a vertical metropolis plagued by land scarcity. Public spaces integrated into pedestrian networks play an indispensable role in neighbourhood accessibility. We visualize the impact of the Covid-19 vaccine passport (VP) restrictions on the use of public space on pedestrian accessibility to all 97 metro stations in Hong Kong. Pedestrians without a vaccine passport (PwoVP) need to walk significantly longer alternative routes. Specifically, VP-related access restrictions to indoor walkways have doubled the shortest travel time for PwoVP and a 50% reduction in accessibility of two-thirds of stations

Discrete dynamics analysis for nonlinear collocated multivariable mass-damper-spring intelligent mechanical vibration systems

A new time-discretization method for the development of nonlinear collocated multivariable mass-damper-spring (MDS) intelligent mechanical vibration systems is proposed. It is based on the Runge-Kutta series expansion method and zero-order hold assumption. In this paper, we show that the mathematical structure of the new discretization scheme is explored and characterized in order to represent the discrete dynamics properties for nonlinear collocated multivariable MDS intelligent mechanical vibration systems. In particular, the decent effects of the time-discretization method on key properties of nonlinear multivariable MDS mechanical vibration systems, such as discrete zero dynamics and asymptotic stability, are examined. The resulting time-discretization provides discrete dynamics behavior for nonlinear MDS mechanical vibration systems, which enabling the application of existing controller design techniques. The ideas presented here generalize well-known results from the linear case to nonlinear plants

LATFormer: Locality-Aware Point-View Fusion Transformer for 3D Shape Recognition

Recently, 3D shape understanding has achieved significant progress due to the advances of deep learning models on various data formats like images, voxels, and point clouds. Among them, point clouds and multi-view images are two complementary modalities of 3D objects and learning representations by fusing both of them has been proven to be fairly effective. While prior works typically focus on exploiting global features of the two modalities, herein we argue that more discriminative features can be derived by modeling ``where to fuse''. To investigate this, we propose a novel Locality-Aware Point-View Fusion Transformer (LATFormer) for 3D shape retrieval and classification. The core component of LATFormer is a module named Locality-Aware Fusion (LAF) which integrates the local features of correlated regions across the two modalities based on the co-occurrence scores. We further propose to filter out scores with low values to obtain salient local co-occurring regions, which reduces redundancy for the fusion process. In our LATFormer, we utilize the LAF module to fuse the multi-scale features of the two modalities both bidirectionally and hierarchically to obtain more informative features. Comprehensive experiments on four popular 3D shape benchmarks covering 3D object retrieval and classification validate its effectiveness

Transcriptome-wide identification and characterization of microRNAs in diverse phases of wood formation in Populus trichocarpa

We applied miRNA expression profiling method to Populus trichocarpa stems of the three developmental stages, primary stem (PS), transitional stem (TS), and secondary stem (SS), to investigate miRNA species and their regulation on lignocellulosic synthesis and related processes. We obtained 892, 872, and 882 known miRNAs and 1727, 1723, and 1597 novel miRNAs, from PS, TS, and SS, respectively. Comparisons of these miRNA species among different developmental stages led to the identification of 114, 306, and 152 differentially expressed miRNAs (DE-miRNAs), which had 921, 2639, and 2042 candidate target genes (CTGs) in the three respective stages of the same order. Correlation analysis revealed 47, 439, and 71 DE-miRNA-CTG pairs of high negative correlation in PS, TS, and SS, respectively. Through biological process analysis, we finally identified 34, 6, and 76 miRNA-CTG pairs from PS, TS, and SS, respectively, and the miRNA target genes in these pairs regulate or participate lignocellulosic biosynthesis-related biological processes: cell division and differentiation, cell wall modification, secondary cell wall biosynthesis, lignification, and programmed cell death processes. This is the first report on an integrated analysis of genome-wide mRNA and miRNA profilings during multiple phases of poplar stem development. Our analysis results imply that individual miRNAs modulate secondary growth and lignocellulosic biosynthesis through regulating transcription factors and lignocellulosic biosynthetic pathway genes, resulting in more dynamic promotion, suppression, or regulatory circuits. This study advanced our understanding of many individual miRNAs and their essential, diversified roles in the dynamic regulation of secondary growth in woody tree species

Discrete dynamics analysis for nonlinear collocated multivariable mass-damper-spring intelligent mechanical vibration systems

A new time-discretization method for the development of nonlinear collocated multivariable mass-damper-spring (MDS) intelligent mechanical vibration systems is proposed. It is based on the Runge-Kutta series expansion method and zero-order hold assumption. In this paper, we show that the mathematical structure of the new discretization scheme is explored and characterized in order to represent the discrete dynamics properties for nonlinear collocated multivariable MDS intelligent mechanical vibration systems. In particular, the decent effects of the time-discretization method on key properties of nonlinear multivariable MDS mechanical vibration systems, such as discrete zero dynamics and asymptotic stability, are examined. The resulting time-discretization provides discrete dynamics behavior for nonlinear MDS mechanical vibration systems, which enabling the application of existing controller design techniques. The ideas presented here generalize well-known results from the linear case to nonlinear plants

Improvement of the Asymptotic Properties of Zero Dynamics for Sampled-Data Systems in the Case of a Time Delay

It is well known that the existence of unstable zero dynamics is recognized as a major barrier in many control systems, and deeply limits the achievable control performance. When a continuous-time system with relative degree greater than or equal to three is discretized using a zero-order hold (ZOH), at least one of the zero dynamics of the resulting sampled-data model is obviously unstable for sufficiently small sampling periods, irrespective of whether they involve time delay or not. Thus, attention is here focused on continuous-time systems with time delay and relative degree two. This paper analyzes the asymptotic behavior of zero dynamics for the sampled-data models corresponding to the continuous-time systems mentioned above, and further gives an approximate expression of the zero dynamics in the form of a power series expansion up to the third order term of sampling period. Meanwhile, the stability of the zero dynamics is discussed for sufficiently small sampling periods and a new stability condition is also derived. The ideas presented here generalize well-known results from the delay-free control system to time-delay case