Ensuring the authenticity of the conservation and reuse of modern industrial heritage architecture: a case study of the large machine factory, China

The Large Machine Factory (LMF) was built in the complex historical context of the late Qing Dynasty (1840–1912). Its space and construction faithfully record the architectural and cultural fusion between Chinese and western traditions and mark the beginning of modern architectural techniques in China. Through historical data and empirical studies, the historical background and architectural characteristics of the LMF were analyzed, and interventions aimed at ensuring authenticity were established. The cultural significance and results of construction were considered two crucial elements in terms of outstanding characteristics. Comprehensive inspection and assessment strategies were discussed, with minimal intervention and interpretation principles. Preventive reinforcement of the foundation, complementary reinforcement of the main structures, restoration of the historic façade and environment, and adaptive spatial interventions were found to be effective ways to ensure authenticity. The principles of minimal intervention and interpretability, which include prevention, recognizability, invisibility, subsidiarity, and intertextuality, were proposed through a comparison with the literature and practical experience. This study provides an appropriate technical reference for ensuring authenticity in the conservation and reuse of modern historic buildings with complex contexts. We propose a new understanding of intervention principles and suggest a guiding intervention path that avoids the complexities arising from the generalized interpretations of authenticity.Postprint (published version

SuperLine3D: Self-supervised Line Segmentation and Description for LiDAR Point Cloud

Poles and building edges are frequently observable objects on urban roads, conveying reliable hints for various computer vision tasks. To repetitively extract them as features and perform association between discrete LiDAR frames for registration, we propose the first learning-based feature segmentation and description model for 3D lines in LiDAR point cloud. To train our model without the time consuming and tedious data labeling process, we first generate synthetic primitives for the basic appearance of target lines, and build an iterative line auto-labeling process to gradually refine line labels on real LiDAR scans. Our segmentation model can extract lines under arbitrary scale perturbations, and we use shared EdgeConv encoder layers to train the two segmentation and descriptor heads jointly. Base on the model, we can build a highly-available global registration module for point cloud registration, in conditions without initial transformation hints. Experiments have demonstrated that our line-based registration method is highly competitive to state-of-the-art point-based approaches. Our code is available at https://github.com/zxrzju/SuperLine3D.git.Comment: 17 pages, ECCV 2022 Accepte

Experimental study of an organic Rankine cycle system with radial inflow turbine and R123

A new micro radial inflow turbine is developed fora mini organic Rankine cycle (ORC) system in this study. With R123 as the working fluid, the turbine operational characteristics and performance are investigated by experiments. Based on the experimental data, the maximum rotational speed of the radial inflow turbine reaches53564r/min, and the maximum output power of the turbine is3.386kW and the maximum electric power reaches1.884kW. When the turbine rotational speed is34586r/min, the system isentropic and electromechanical efficiencies achieve the maximum values of 83.6% and65.3% respectively. Both the turbine isentropic and thermal efficiencies increase with the heat source temperature

Identification and characterization of novel amphioxus microRNAs by Solexa sequencing

An analysis of amphioxus miRNAs suggests an expansion of miRNAs played a key role in the evolution of chordates to vertebrate

Systematic meta-analyses, field synopsis and global assessment of the evidence of genetic association studies in colorectal cancer

Objective: To provide an understanding of the role of common genetic variations in colorectal cancer (CRC) risk, we report an updated field synopsis and comprehensive assessment of evidence to catalogue all genetic markers for CRC (CRCgene2). Design: We included 869 publications after parallel literature review and extracted data for 1063 polymorphisms in 303 different genes. Meta-Analyses were performed for 308 single nucleotide polymorphisms (SNPs) in 158 different genes with at least three independent studies available for analysis. Scottish, Canadian and Spanish data from genome-wide association studies (GWASs) were incorporated for the meta-Analyses of 132 SNPs. To assess and classify the credibility of the associations, we applied the Venice criteria and Bayesian False-Discovery Probability (BFDP). Genetic associations classified as â € positive' and â € less-credible positive' were further validated in three large GWAS consortia conducted in populations of European origin. Results: We initially identified 18 independent variants at 16 loci that were classified as â € positive' polymorphisms for their highly credible associations with CRC risk and 59 variants at 49 loci that were classified as â € less-credible positive' SNPs; 72.2% of the â € positive' SNPs were successfully replicated in three large GWASs and the ones that were not replicated were downgraded to â € less-credible' positive (reducing the â € positive' variants to 14 at 11 loci). For the remaining 231 variants, which were previously reported, our meta-Analyses found no evidence to support their associations with CRC risk. Conclusion: The CRCgene2 database provides an updated list of genetic variants related to CRC risk by using harmonised methods to assess their credibility.</p

The pervasive effects of recombinant Fasciola gigantica Ras-related protein Rab10 on the functions of goat peripheral blood mononuclear cells

Background: Fasciola gigantica-induced immunomodulation is a major hurdle faced by the host for controlling infection. Here, we elucidated the role of F. gigantica Ras-related protein Rab10 (FgRab10) in the modulation of key functions of peripheral blood mononuclear cells (PBMCs) of goats.Methods: We cloned and expressed recombinant FgRab10 (rFgRab10) protein and examined its effects on several functions of goat PBMCs. Protein interactors of rFgRab10 were predicted in silico by querying the databases Intact, String, BioPlex and BioGrid. In addition, a total energy analysis of each of the identified interactions was also conducted. Gene Ontology (GO) enrichment analysis was carried out using FuncAssociate 3.0.Results: The FgRab10 gene (618 bp), encodes 205-amino-acid residues with a molecular mass of ~23 kDa, had complete nucleotide sequence homology with F. hepatica Ras family protein gene (PIS87503.1). The rFgRab10 protein specifically cross-reacted with anti-Fasciola antibodies as shown by Western blot and immunofluorescence analysis. This protein exhibited multiple effects on goat PBMCs, including increased production of cytokines [interleukin-2 (IL-2), IL-4, IL-10, transforming growth factor beta (TGF-β) and interferon gamma (IFN-γ)] and total nitric oxide (NO), enhancing apoptosis and migration of PBMCs, and promoting the phagocytic ability of monocytes. However, it significantly inhibited cell proliferation. Homology modelling revealed 63% identity between rFgRab10 and human Rab10 protein (Uniprot ID: P61026). Protein interaction network analysis revealed more stabilizing interactions between Rab proteins geranylgeranyltransferase component A 1 (CHM) and Rab proteins geranylgeranyltransferase component A 2 (CHML) and rFgRab10 protein. Gene Ontology analysis identified RabGTPase mediated signaling as the most represented pathway.Conclusions: rFgRab10 protein exerts profound influences on various functions of goat PBMCs. This finding may help explain why F. gigantica is capable of provoking recognition by host immune cells, less capable of destroying this successful parasite

Effect of polypropylene thick/basalt composite fibers on the mechanical properties of large dose slag fly ash concrete

In this experiment, the effects of polypropylene thick fiber (PPTF) with different volume admixtures (0, 0.05%, 0.10%, 0.15%, 0.20%, 0.25%) on the compressive strength, splitting tensile strength and bending strength of large admixture of slag fly ash concrete were investigated with short-cut basalt fiber (BF) as a reference. The results show that the polypropylene thick fiber can work well with basalt fiber and improve its strengthening effect of single admixture. And 0.10% of polypropylene thick fiber and 0.10% of basalt fibers by volume have the best strengthening effect on the mechanical properties of the large amount of slag fly ash concret

Characterization of Pollutant Emissions from Typical Material Handling Equipment Using a Portable Emission Measurement System

Non-road equipment has been an important source of pollutants that negatively affect air quality in China. An accurate emission inventory for non-road equipment is therefore required to improve air quality. The objective of this paper was to characterize emissions from typical diesel-fueled material handling equipment (loaders and cranes) using a portable emission measurement system. Instantaneous, modal, and composite emissions were quantified in this study. Three duty modes (idling, moving, and working) were used. Composite emission factors were estimated using modal emissions and time-fractions for typical duty cycles. Results showed that emissions from loaders and cranes were higher and more variable for the moving and working modes than the idling mode. The estimated fuel-based CO, HC, NO, and PM2.5 composite emission factors were 21.7, 2.7, 38.2, and 3.6 g/(kg-fuel), respectively, for loaders, and 8.7, 2.4, 28.3, and 0.3 g/(kg-fuel), respectively, for cranes. NO emissions were highest and should be the main focus for emission controls. CO, HC, NO, and PM2.5 emissions measured were different from emission factors in the US Environmental Protection Agency NONROAD model and the Chinese National Guideline for Emission Inventory Development for Non-Road Equipment. This indicates that improving emission inventory accuracy for non-road equipment requires more real-world emission measurements