Can the development of digital construction reduce enterprise carbon emission intensity? New evidence from Chinese construction enterprises

IntroductionWith the rapid development of digital technology and its deep integration with the engineering and construction field, digital construction has become an effective way for low-carbon transformation in the construction industry. However, there is a gap of empirical research between digital construction and carbon emissions. MethodsThis paper empirically investigates the impact of digital construction level on carbon emission intensity and the mechanism of action by using the two-way fixed effects model and mechanism testing based on the panel data of 52 Shanghai and Shenzhen A-share listed companies in China’s construction industry from 2015 to 2021. ResultsThe findings indicate that the improvement of digital construction level can significantly decrease the carbon emission intensity of construction enterprises, and the conclusions still hold after robustness tests and discussions on endogeneity issues such as replacing core explanatory variables, replacing models, using instrumental variables method, system GMM model and difference in differences model. According to a mechanism analysis, digital construction can curb carbon emission intensity by enhancing the R&D innovation capacity and total factor productivity of enterprises. Furthermore, the heterogeneity analysis shows that the improvement of digital construction level in state-owned enterprises as well as civil engineering construction enterprises can better contribute to reducing carbon emission intensity. DiscussionThis paper will provide a reference for the synergistic optimization of digital construction development and carbon emissions reduction in construction enterprises. The research conclusions are going to promote the digital transformation of the construction industry to accelerate the achievement of the carbon peaking and carbon neutrality goals

Rocks Coding, Not Development--A Human-Centric, Experimental Evaluation of LLM-Supported SE Tasks

Recently, large language models (LLM) based generative AI has been gaining momentum for their impressive high-quality performances in multiple domains, particularly after the release of the ChatGPT. Many believe that they have the potential to perform general-purpose problem-solving in software development and replace human software developers. Nevertheless, there are in a lack of serious investigation into the capability of these LLM techniques in fulfilling software development tasks. In a controlled 2 x 2 between-subject experiment with 109 participants, we examined whether and to what degree working with ChatGPT was helpful in the coding task and typical software development task and how people work with ChatGPT. We found that while ChatGPT performed well in solving simple coding problems, its performance in supporting typical software development tasks was not that good. We also observed the interactions between participants and ChatGPT and found the relations between the interactions and the outcomes. Our study thus provides first-hand insights into using ChatGPT to fulfill software engineering tasks with real-world developers and motivates the need for novel interaction mechanisms that help developers effectively work with large language models to achieve desired outcomes.Comment: The paper has been accepted by FS

SpecDETR: A Transformer-based Hyperspectral Point Object Detection Network

Hyperspectral target detection (HTD) aims to identify specific materials based on spectral information in hyperspectral imagery and can detect point targets, some of which occupy a smaller than one-pixel area. However, existing HTD methods are developed based on per-pixel binary classification, which limits the feature representation capability for point targets. In this paper, we rethink the hyperspectral point target detection from the object detection perspective, and focus more on the object-level prediction capability rather than the pixel classification capability. Inspired by the token-based processing flow of Detection Transformer (DETR), we propose the first specialized network for hyperspectral multi-class point object detection, SpecDETR. Without the backbone part of the current object detection framework, SpecDETR treats the spectral features of each pixel in hyperspectral images as a token and utilizes a multi-layer Transformer encoder with local and global coordination attention modules to extract deep spatial-spectral joint features. SpecDETR regards point object detection as a one-to-many set prediction problem, thereby achieving a concise and efficient DETR decoder that surpasses the current state-of-the-art DETR decoder in terms of parameters and accuracy in point object detection. We develop a simulated hyperSpectral Point Object Detection benchmark termed SPOD, and for the first time, evaluate and compare the performance of current object detection networks and HTD methods on hyperspectral multi-class point object detection. SpecDETR demonstrates superior performance as compared to current object detection networks and HTD methods on the SPOD dataset. Additionally, we validate on a public HTD dataset that by using data simulation instead of manual annotation, SpecDETR can detect real-world single-spectral point objects directly

Command Filter Backstepping Sliding Model Control for Lower-Limb Exoskeleton

A command filter adaptive fuzzy backstepping control strategy is proposed for lower-limb assisting exoskeleton. Firstly, the human-robot model is established by taking the human body as a passive part, and a coupling torque is introduced to describe the interaction between the exoskeleton and human leg. Then, Vicon motion capture system is employed to obtain the reference trajectory. For the purpose of obviating the “explosion of complexity” in conventional backstepping, a second-order command filter is introduced into the sliding mode control strategy. The fuzzy logic systems (FLSs) are also applied to handle with the chattering problem by estimating the uncertainties and disturbances. Furthermore, the stability of the closed-loop system is proved based on the Lyapunov theory. Finally, simulation results are presented to illustrate the effectiveness of the control strategy

Ecological Discourse Analysis and Ecological Diplomacy Analysis of Coverage about Beijing Winter Olympics Based on Transitivity System

This study aims to interpret the ecological meaning of discourse from system-functional linguistics perspective and analyses the ecological diplomacy ideas embedded in reporting, and to guide people to develop an ecological consciousness of living in harmony with nature through the analysis of ecological orientations. The study explores the ecological factors in the participant, process and environmental components. The results show that in terms of participant role distribution, material process participants and relational process participants account for the largest proportion. In terms of transitivity processes, the focus is on the use of material and relational processes. In terms of the distribution of circumstantial element, there are significant differences in the use of ecological discourse in coverage. The idea of ecological diplomacy is also implicitly reflected in the coverage

High Impedance Arc Fault Modelling in Offshore Oil Platform Power Grid

In offshore oil platform power grid, high impedance arc fault occurs frequently. The fault characteristics of high- impedance arc information are weak and difficult to detect, which may not cause the protection method to activate. Therefore, it is important to detect and clear the high impedance fault. In the high impedance case, usually, the arc fault occurs. In the research, the arc model was established using the typical Cassie model and the high impedance arc fault characteristics in offshore oil platform power grids were analysed. An improved arc fault detection method using the phase angle difference between zero sequence voltage and zero sequence current was proposed to extract fault characteristics. This method requires limited detection information and high accuracy to solve the problem of small current and voltage changes in high-resistance arc faults. The offshore oil platform power grid and the arc were modelled using electromagnetic transients software PSCAD/EMTDC. The simulation results show that the arc model and fault detection method work well

Transcriptome analysis reveals the molecular basis of the response to acute hypoxic stress in blood clam Scapharca broughtonii

Hypoxia tolerance and adaptive regulation are important for aquatic animals, especially for species with poor mobility, such as most bivalves. Previous studies have confirmed that the blood clam Scapharca broughtonii has strong hypoxia resistance. However, the molecular mechanism supporting its hypoxic tolerance is still largely limited. To further screen the genes and their potential regulation of hypoxia tolerance, the transcriptome changes of S. broughtonii after acute hypoxic stress were explored by RNA sequencing. In this study, the average value of Q30 is 92.89%, indicating that the quality of sequencing is relatively high. The Unigenes obtained were annotated using four databases, namely Interpo, KEGG, Swisspro and TrEMBL. The annotation rates in these four databases were 71.82%, 75.95%, 92.98%, and 79.26%, respectively. And also, there were 649 DEGs in group B (dissolved oxygen (DO) of 2.5 mg/L) compared with group D (DO of 7.5 mg/L), among which 252 were up-regulated, and 397 were down-regulated. There were 965 DEGs in group A (DO of 0.5 mg/L), 2.5 mg/L, and 7.5 mg/L, compared with group B, among which 530 were up-regulated, and 435 were down-regulated. Meanwhile, there were 2,040 DEGs in group A compared with group D, among which 901 were up-regulated, and 1,139 were down-regulated. The main metabolic-related pathways of KEGG enriched in this study included Insulin secretion, Insulin signaling pathway, MAPK signal transduction pathway, and PPAR signaling pathway. These pathways may be critical metabolic pathways to solve energy demand and rebuild energy balance in S. broughtonii under hypoxic conditions. This study preliminarily clarified the response of S. broughtonii to hypoxia stress on the molecular levels, providing a reference for the following study on the response laws of related genes and pathways under environmental stress of S. broughtonii

Acoustic characterization for creep behaviors of marine sandy hydrate-bearing sediment

Marine natural gas hydrate (NGH) is a promising substitutive low‑carbon energy resource, whereas NGH‑production induced geoengineering concerns remain challenging. Advanced forecast of possible geoengineering risks is the fundamental for eco‑friendly NGH exploitation. Reservoir creep deformation is an early symptom of the geoengineering risks. However, whether the creep deformation behaviors of the NGH‑bearing strata is predictable remains controversial. In this study, a series of multi‑step loading creep test are conducted for sandy gas hydrate bearing sediment (GHBS) samples, during which the ultrasonic responses are recorded simultaneously. The acoustic velocity, compression‑to‑shear velocity ratio, Poission’s ratio, main frequency, and main frequency amplitude are used to characterize creep failures of the GHBS for the first time. Combining analyses of the creep behaviors and acoustic responses yield the following conclusions. Firstly, the long‑term strength derived from creeping test is 0.45–0.60 times of the shear strength derived from triaxial shearing. Ignoring the creep effect might underestimate the scale and intensity of possible geoengineering risks during long‑term NGH exploitation. Secondly, the acoustic velocity increases gently and then decreases continuously during creeping. Once the accelerated creep appears, the acoustic velocity plummets significantly, together with a sudden decrease in the compression‑to‑shear velocity ratio, and fluctuations in the main frequency and its amplitude. Furthermore, the main frequency and its amplitude shall fluctuate abruptly prior to the emergence of the accelerated creep. Therefore, we anticipate that the combination of abnormal fluctuations of main frequency and its amplitude can be used as early‑warning indicators for possible creep failure of the GHBS. The results might have great significance for in‑situ detection and prediction of possible reservoir failure during long‑term NGH exploitation.Scientific Reports, 13(1), art. no. 22199; 2023journal articl

A tumorigenic index for quantitative analysis of liver cancer initiation and progression.

Primary liver cancer develops from multifactorial etiologies, resulting in extensive genomic heterogeneity. To probe the common mechanism of hepatocarcinogenesis, we interrogated temporal gene expression profiles in a group of mouse models with hepatic steatosis, fibrosis, inflammation, and, consequently, tumorigenesis. Instead of anticipated progressive changes, we observed a sudden molecular switch at a critical precancer stage, by developing analytical platform that focuses on transcription factor (TF) clusters. Coarse-grained network modeling demonstrated that an abrupt transcriptomic transition occurred once changes were accumulated to reach a threshold. Based on the experimental and bioinformatic data analyses as well as mathematical modeling, we derived a tumorigenic index (TI) to quantify tumorigenic signal strengths. The TI is powerful in predicting the disease status of patients with metabolic disorders and also the tumor stages and prognosis of liver cancer patients with diverse backgrounds. This work establishes a quantitative tool for triage of liver cancer patients and also for cancer risk assessment of chronic liver disease patients

Concurrent Disruption of the Ras/MAPK and NF-κB Pathways Induces Circadian Deregulation and Hepatocarcinogenesis.

UNLABELLED: The Ras/Erk and NF-κB pathways play critical roles in cell proliferation and are known to drive oncogenesis when overactivated. Herein we report a gatekeeper function of the two pathways by working in synergy to suppress liver tumorigenesis. Hepatocyte-specific deletion of both Shp2/Ptpn11 and Ikkβ in mice, which promote Ras/Erk and NF-κB signaling, respectively, exacerbated chemical carcinogenesis and even triggered spontaneous development of hepatocellular carcinoma (HCC). We show that the unanticipated severe tumor phenotype was contributed collectively by severe cholestasis, metabolic changes, upregulated cell-cycle progression, and disruption of circadian rhythm in mutant hepatocytes. Remarkably, human HCCs with dysregulated circadian gene expression displayed downregulation of Ras/Erk and NF-κB signaling and poor prognosis. Together, these data indicate that at the ground state, the two central pathways, previously known as oncogenic, cooperate to sustain tumor-suppressive physiologic homeostasis and to prevent hepatic damage. Disruption of this intricate signaling network is carcinogenic in the liver. IMPLICATIONS: We demonstrate here that basal levels of the Ras/MAPK and NF-κB pathways, while promoting tumorigenesis if overactivated, are required to maintain physiologic homeostasis and regulate circadian rhythm in the liver, which are antitumorigenic