Search

Building information modeling (BIM) technology can organically combine data modeling and virtual reality, and compare them with actual construction objects to realize the smart collaboration of entity and the model in the construction processes, greatly reducing early stage mistakes and improve construction efficiency. This paper proposed an automation system framework of smart construction based on BIM technology and collaboration platform, and discussed the element configuration of smart construction based on BIM technology and collaboration platform, and finally elaborated the working mechanism of automated system based on BIM technology and collaboration platform. The study results show that the automation system based on the BIM technology and collaboration platform supports the rapid construction of large-scale three-dimensional scenes and the precise integration of multi-source data, and can bring together construction information and asset information from different sources to form an open, safe, and accessible digital environment. The application of smart construction technology in construction cost management has brought huge economic benefits, construction efficiency has been increased by 65%, construction period has been shortened by 30%, labor intensity has been reduced by 27%, and labor productivity has been increased by 39%, which has brought considerable indirect benefits to construction projects.

The relevance of the study stems from the Chinese government’s focus on developing cultural, economic partnerships with Asia-Pacific states. It is the Huaqiao who have contributed to this process, for example, there are many investors who balance the flow of money between China and other countries, as well as scholars who share scientific knowledge with Chinese citizens.Aim. Based on the above, the aim of the study is to analyse the current position of the Chinese diaspora in the economic and political spheres of life in Southeast Asia.Tasks. In order to successfully realise the objective, it is necessary to solve the research tasks:to describe the essence of the concept of “diaspora” in the academic literature, as well as its specific features;to consider the role of huaqiao in the formation of China’s external image;to evaluate the degree of Chinese business activity in trade of the countries under consideration;4) to study the degree of Chinese diasporas’ participation in political life of the states of residence.Methods. Analysis and synthesis of literary sources (while studying the concept of “diaspora”), historical method (while describing three main waves of Chinese diaspora migration and studying Chinese settlement in different parts of South-East Asia), descriptive method (while studying the place of Chinese diaspora in political and economic life of South-East Asia) were used as main research methods.Results. The research results have been summarised according to the level of representation of the positive image of the Chinese as a result of the Huaqiao’s economic and political actions.Conclusions. Firstly, about 75% of overseas Chinese, or 28 million people, live in modern Southeast Asian countries.Secondly, within the framework of the business activities of the Chinese diaspora, the most significant factor of influence is the association of Chinese enterprises in the “bamboo network” and expansion of areas of cooperation with each other.Third, the Chinese diaspora has different rights these days depending on the form of government and state structure of the country.

The effective removal of tar is a major challenge for biomass gasification. Schemes based on chemical looping gasification (CLG) offer a promising alternative for converting biomass into syngas with low tar content. The present work examined the influence of a Ni-modified oxygen carrier (OC) on the benzene conversion rate, hydrogen yield, carbon deposition rate, and yield of combustible gas products under various experimental conditions in the CLG of benzene as a model biomass tar compound. After modification, the NiFe2O4 OC exhibited good catalytic and oxidation performance. With the increase in reaction temperature and Ni loading, the hydrogen yield, benzene conversion rate, and carbon deposition rate all increased gradually. With the increase of weight hourly space velocity (WHSV), the benzene conversion rate decreased from 89.75% to 81.1%. which indicated that the oxidation capacity of the OC to benzene decreased. Meanwhile, the addition of steam significantly eliminated the carbon deposition, which decreased to 2.62% at an S/C ratio of 1.48. During the long-term experiment, the oxidation activity and catalytic activity of the OC each exhibit a slight decreased, which was possibly due to the sintering and agglomeration of the OC. Finally, the cracking mechanism of the tar model compound benzene was proposed.

Abstract Green retrofit PPP projects of traditional apartment complexes play an important role in promoting the green and low-carbon transformation of the construction industry and achieving China's "double carbon" goals. The integrated retrofit of apartment complexes presupposes that the resident groups agree to the retrofit. Therefore, it is necessary to study the evolutionary mechanism of residents' intention to green retrofit and the transformation process of their behavior, and to explore how to enhance residents' intention to participate. First, the dissemination model of residents' intention to green retrofit is constructed. Then, the strategic interaction among government, social capitals and residents under the PPP model is introduced into the dissemination model to define the state transformation probability of resident groups. Finally, the evolution laws of residents' intention to green retrofit are analyzed. The results show that: (1) the behavior of government regulation and social capitals' effort to retrofit can motivate the number of the resident agreeing to green retrofit to meet the proportional limit, (2) the faster the government chooses the strategy of regulation and the social capitals choose the strategy of effort to retrofit, the faster the number of residents agreeing to green retrofit reaches a steady state, (3) when the level of government publicity and education is too low, the cost of government regulation or the subsidy given to residents is too high, the green retrofit of traditional apartment complexes cannot be achieved. The research conclusions can provide a reference for the government to formulate green retrofit policies.

Recent studies have suggested that ABC transporters are the main receptors of Cry toxins. However, the receptors of many Cry toxins have not been identified. In this study, we used a heterologous cell expression system to identify Bombyx mori ABC transporter subfamily C members (BmABCCs) that function as receptors for five Cry toxins active in Lepidopteran insects: Cry1Aa, Cry1Ca, Cry1Da, Cry8Ca, and Cry9Aa. All five Cry toxins can use multiple ABCCs as low-efficiency receptors, which induce cytotoxicity only at high concentrations. Surface plasmon resonance analysis revealed that the KD values between the toxins and BmABCC1 and BmABCC4 were 10−5 to 10−9 M, suggesting binding affinities 8- to 10,000-fold lower than those between Cry1Aa and BmABCC2, which are susceptibility-determining receptors for Cry1Aa. Bioassays in BmABCC-knockout silkworm strains showed that these low-efficiency receptors are not involved in sensitivity to Cry toxins. The findings suggest that each family of Cry toxins uses multiple BmABCCs as low-efficiency receptors in the insect midgut based on the promiscuous binding of their receptor-binding regions. Each Cry toxin seems to have evolved to utilize one or several ABC transporters as susceptibility-determining receptors.

The presence of another planetary companion in a transiting exoplanet system can impact its transit light curve, leading to sinusoidal transit-timing variations (TTV). By utilizing both χ ^2 and rms analysis, we have combined the TESS observation data with an N -body simulation to investigate the existence of an additional planet in the system and put a limit on its mass. We have developed CMAT, an efficient and user-friendly tool for fitting transit light curves and calculating TTV with a theoretical period, based on which we can give a limit on its hidden companion’s mass. We use 260 hot Jupiter systems from the complete TESS data set to demonstrate the use of CMAT. Our findings indicate that, for most systems, the upper mass limit of a companion planet can be restricted to several Jupiter masses. This constraint becomes stronger near resonance orbits, such as the 1:2, 2:1, 3:1, and 4:1 mean-motion resonance, where the limit is reduced to several Earth masses. These findings align with previous studies suggesting that a lack of companion planets with resonance in hot Jupiter systems could potentially support the high-eccentricity migration theory. Additionally, we observed that the choice between χ ^2 or rms method does not significantly affect the upper limit on companion mass; however, χ ^2 analysis may result in weaker restrictions but is statistically more robust compared to rms analysis in most cases.

Many hot Jupiters may experience orbital decays, which are manifested as long-term transit-timing variations. We have analyzed 7068 transits from the Transiting Exoplanet Survey Satellite (TESS) for a sample of 326 hot Jupiters. These new mid-transit-time data allow us to update ephemerides for these systems. By combining the new TESS transit-timing data with archival data, we searched for possible long-term variations in the orbital period in these hot Jupiters using a linear and a quadratic ephemeris model. We identified 26 candidates that exhibit possible long-term variations of the orbital period, including 18 candidates with decreasing orbital periods and eight candidates with increasing orbital periods. Among them, 12 candidates failed our leave-one-out cross validation test and thus should be considered to be marginal candidates. In addition to tidal interaction, alternative mechanisms such as apsidal precession, the Rømer effect, and the Applegate effect could also contribute to the variations during the observed period. The ephemerides derived in this work are useful for scheduling follow-up observations for these hot Jupiters in the future. The Python code ( PdotQuest , https://github.com/AeoN400/PdotQuest ) used to generate the ephemerides is made available online.

With increased demand for various chemical raw materials, sudden pollution incidents are more prone to occur during their transportation and usage, threatening the environment and human health. In this study, discarded tea stalks were recycled into composite materials (FSC-X00: X represents the calcination temperature) by impregnating tea stalks in Fe2+ solution combined with subsequent calcination. X-ray diffractometer (XRD) and X-ray photoelectron spectroscopy (XPS) patterns verified the existence of Fe0 and Fe2O3, and Fe2O3 was gradually reduced to Fe0 when the calcination temperature was raised from 700 °C to 900 °C. FSC-X00 was adopted as a heterogeneous catalyst for activating H2O2 to quickly degrade phenol in the water system. The degradation experiments indicated that FSC-600 exhibited superior degradation performance for phenol (20 mg/L) within 5 min and 80% total organic carbon (TOC) removal rate at pH = 3 within 30 min. The effects of the calcination temperature, the pH value and the amount of H2O2 on the degradation efficiency were investigated. Competing experiments showed that fulvic acid (FA) and inorganic salts Na+ had little effect on the degradation performance. The FSC-600 catalyst can be reused by thermal reduction. In addition, it was found that FSC-600 has a good degradation effect on ciprofloxacin (CIP), norfloxacin (NOR) and enrofloxacin (ENR), indicating that FSC-600 catalysts are a promising candidate for quick degradation of organic pollutants by Fenton reaction. Electron paramagnetic resonance (EPR) spectra analysis indicated that •OH is the dominant reactive oxygen species (ROS) and part 1O2 from O2 also participated in the degradation. This study provides an example of creating catalysts from organic solid waste for use in emergency treatment for phenol. HIGHLIGHTS Fe@Fe2O3-loaded biochar (FSC-600) was prepared by waste tea stalks and FeSO4 combined with calcinations.; FSC-600-H2O2 exhibited superior degradation performance for phenol, ciprofloxacin, norfloxacin and enrofloxacin in a short period.; Mechanism analysis indicates that •OH is the dominant ROS and a little 1O2 from O2 also participated the degradation.;

We discuss the problem of accountability when multiple parties cooperate towards an end result, such as multiple companies in a supply chain or departments of a government service under different authorities. In cases where a fully trusted central point does not exist, it is difficult to obtain a trusted audit trail of a workflow when each individual participant is unaccountable to all others. We propose AudiWFlow, an auditing architecture that makes participants accountable for their contributions in a distributed workflow. Our scheme provides confidentiality in most cases, collusion detection, and availability of evidence after the workflow terminates. AudiWFlow is based on verifiable secret sharing and real-time peer-to-peer verification of records; it further supports multiple levels of assurance to meet a desired trade-off between the availability of evidence and the overhead resulting from the auditing approach. We propose and evaluate two implementation approaches for AudiWFlow. The first one is fully distributed except for a central auxiliary point that, nevertheless, needs only a low level of trust. The second one is based on smart contracts running on a public blockchain, which is able to remove the need for any central point but requires integration with a blockchain.

Abstract Due to the difficulty and time‐consumption in locating short‐distance transmission lines for deep‐sea offshore wind farm (DOWF)，this paper proposes a novel double‐terminal fault location method by using Stockwell‐transform (ST) and random‐forest (RF). After the fault type and branch are accurately determined, the accurate transmission line fault location is located. Firstly, Stockwell‐transform is employed to extract fault eigenvalues from the collected wind turbine (WT) current signals, which will reduce the sensitivity of eigenvalues to noise. And the Pearson correlation coefficient (PCC) is introduced to remove duplicate eigenvalues. Secondly, the reserved fault eigenvalues are taken as inputs to the different random‐forest to classify fault types and identify the fault branch, respectively. Finally, the double‐terminal fault location principle is established in fault negative sequence network (only ABCG uses positive sequence components). Newton‐Raphson method (NRM) is used to eliminate the influence of asynchrony data, which implies an accurate transmission line fault location for deep‐sea offshore wind farm. More than 4000 fault cases data obtained by Simulink simulation verify the feasibility and performance of the proposed method. The results show that the proposed location method has a high fault recognition rate and is immune to fault inception angle, resistance, location and noise.

Abstract Background Degeneration of the intervertebral discs are very common diseases, indicating the specific or malignant changes in intervertebral disc component, structure and function. Imaging examination is currently used to evaluate the severity of lumbar intervertebral disc degeneration. This study was designed to investigate the diagnostic value of 3D LAVA-Flex in lumbar intervertebral disc degeneration. Material and methods Sagittal 3D LAVA-Flex and T2WI scans were performed in 45 patients with lumbar intervertebral disc degeneration. On T2WI, the degenerated intervertebral disc in every patient was evaluated using Pfirrmann grade. Then, the patients were re-evaluated using 3D LAVA-Flex with considerations of the distinction of nucleus pulposus and annulus fibrosus, hypointense signal of intervertebral disc and height of intervertebral disc. The evaluation results were compared between 3D LAVA-Flex and T2WI. Virtual endoscopy was also performed to evaluate the degenerated intervertebral disc. Results The intermediate–intense signal of nucleus pulposus and complete ring-shaped hyperintense signal of annulus fibrosus were found and the distinction of nucleus pulposus and annulus fibrosus was clear in the normal intervertebral disc on 3D LAVA-Flex. The incidence of linear hypointensity of narrowed intervertebral space (65/91) was higher than that of normal intervertebral space (4/134) (P = 0.000). A good consistency was shown between the LAVA-Flex grade and T2WI-based Pfirrmann grade. Virtual endoscopy based on 3D LAVA-Flex could help clearly show the anatomic relationship between the degenerated disc and intervertebral foramen. Conclusions 3D LAVA-Flex and T2WI show similar efficacy in evaluating lumbar intervertebral disc degeneration. 3D LAVA-Flex-based virtual endoscopy possesses great potential in the study of intervertebral disc abnormalities.

High definition video application has drawn a lot of interest both from academy and industry. The relevant latest video coding technology, H.265/HEVC has been a promising area for video steganography. In this paper, we present a novel and efficient video steganography method based on transform block decision for H.265. In order to improve the visual quality of carrier video, we analyze the embedding error of data hiding with modifying partitioning parameters of CB, PB and TB, and modify the transform block decision to embed secret message and update corresponding residuals synchronously. In order to limit embedding error, we utilize an efficient embedding mapping rule which can embed N (N>1) bits message and at most modify one bit transform partitioning flag. Our experimental results show that the proposed method can achieve better visual quality, larger embedding capacity and less bit-rate increase than state-of-the-art researches.

Heterogeneous Electron-Fenton (HEF) has been recognized as a prospective solution in tackling refractory organic contaminants. Nevertheless, the low production efficiency of H2O2 and external addition of H2O2 or Fe2+ limit its wide application. In this work, the bi-functional Fe/CeO2 composites were designed to achieve the simultaneous generation of H2O2 and •OH. The electro-catalysis experiments indicate Fe/CeO2 composites present 97% degradation efficiency for 17 mg/L phenol within 0.5 h and it still presented good degradation performance in high salinity condition. The H2O2 yield produced by Fe, CeO2, and Fe/CeO2 revealed that CeO2 and Fe/CeO2 have similar H2O2 productivity about 24 mg/L h−1, suggesting that H2O2 is mainly produced by CeO2. O2-TPD profiles, XPS and Raman spectra indicate that the relative amount of oxygen deficient region (Ov) and chemisorbed oxygen in Fe/CeO2 composites is higher than that in CeO2, which promote the adsorption of O2. Then the effective O2 adsorption can ensure the subsequent electrocatalysis of O2 to H2O2. The impedance measurement shows that Fe/CeO2 composite exhibits excellent conductivity, enabling the transporting of electron. EPR experiments and radical scavenging experiments disclosed that the primary reactive species was •OH, proving the in-situ activation of H2O2 to •OH by Fe/CeO2 composites. This work should offer new insights about the rational design of bi-functional catalyst towards simultaneous generation and activation H2O2 to •OH, thus improving electrocatalytic performance.

Ground surface roughness is difficult to predict through a physical model due to its complex influencing factors. BP neural networks (BPNNs), a promising method, have been widely applied in the prediction of surface roughness. This paper uses the concept of BPNN to predict ground surface roughness considering the state of the grinding wheel. However, as the number of input parameters increases, the local optimum solution of the model that arises is more serious. Therefore, “identify factors” are designed to judge the iterative state of the model, whilst “memory factors” are designed to store the best weights during network training. The iterative termination conditions of the model are improved, and the learning rate and update rules of the weights are adjusted to avoid the local optimal solution. The results show that the prediction accuracy of the presented model is higher and more stable than the traditional model. Under three types of iteration steps, the average prediction accuracy is improved from 0.071, 0.065, 0.066 to 0.049, 0.042, 0.039 and the standard deviation of prediction decreased from 0.0017, 0.0166, 0.0175 to 0.0017, 0.0070, 0.0076, respectively. Therefore, the proposed method provides guidance for improving the global optimization ability of BPNNs and developing more accurate models for predicting surface roughness.

The crack distribution characteristics in grinding damage have a significant impact on subsequent polishing efficiency and part strength. Grinding tests were carried out on fused quartz using grinding wheels with different wear states. The results showed that the cracks produced by sharp abrasive grits were mainly near chevron cracks and had no preferred direction. However, the blunt abrasive grits produced near partial cone cracks had a preferred direction. At a depth of 96.7 μm from the surface, the amount of cracks in the range of 50°~90° with an inclination angle between the crack and the cutting direction could reach 88.9%. The statistical results showed that the depth and total length of cracks produced by sharp grits were larger than those produced by blunt grits (the maximum crack depth difference was about 40 μm). Therefore, it was concluded that sharp abrasive grits were not conducive to damage control. The findings of this research enhance our understanding of the formation mechanism of grinding damage.

This work develops a toolbox called WDSchain on MATLAB that can simulate blockchain on water distribution systems (WDS). WDSchain can import data from Excel and EPANET water modelling software. It extends the EPANET to enable simulation blockchain of the hydraulic data at any intended nodes. Using WDSchain will strengthen network automation and the security in WDS. WDSchain can process time-series data with two simulation modes: (1) static blockchain, which takes a snapshot of one-time interval data of all nodes in WDS as input and output into chained blocks at a time, and (2) dynamic blockchain, which takes all simulated time-series data of all the nodes as input and establishes chained blocks at the simulated time. Five consensus mechanisms are developed in WDSchain to provide data at different security levels using PoW, PoT, PoV, PoA, and PoAuth. Five different sizes of WDS are simulated in WDSchain for performance evaluation. The results show that a trade-off is needed between the system complexity and security level for data validation. The WDSchain provides a methodology to further explore the data validation using Blockchain to WDS. The limitations of WDSchain do not consider selection of blockchain nodes and broadcasting delay compared to commercial blockchain platforms.

The mainstream method used for the analysis of task functional Magnetic Resonance Imaging (fMRI) data, is to obtain task-related active brain regions based on generalized linear models. Machine learning as a data-driven technical method is increasingly used in fMRI data analysis. The language task data, including math task and story task, of the Human Connectome Project (HCP) was used in this work. We chose a linear support vector machine as a classifier to classify math and story tasks and compared them with the activated brain regions of a SPM statistical analysis. As a result, 13 of the 25 regions used for classification in SVM were activated regions, and 12 were non-activated regions. In particular, the right Paracentral Lobule and right Rolandic Operculum which belong to non-activated regions, contributed most to the classification. Therefore, the differences found in machine learning can provide a new understanding of the physiological mechanisms of brain regions under different tasks.

Background: Alzheimer’s disease (AD) is a common neurodegenerative disease in which the brain undergoes alterations for decades before symptoms become obvious. Subjective cognitive decline (SCD) have self-complain of persistent decline in cognitive function especially in memory but perform normally on standard neuropsychological tests. SCD with the presence of AD pathology is the transitional stage 2 of Alzheimer’s continuum, earlier than the prodromal stage, mild cognitive impairment (MCI), which seems to be the best target to research AD. In this study, we aimed to detect the transformational patterns of the intrinsic brain activity as the disease burden got heavy.Method: In this study, we enrolled 44 SCD, 55 amnestic MCI (aMCI), 47 AD dementia (d-AD) patients and 57 normal controls (NC) in total. A machine learning classification was utilized to detect identification accuracies between groups by using ALFF, fALFF, and fusing ALFF with fALFF features. Then, we measured the amplitude of the low-frequency fluctuation (ALFF) and fractional ALFF (fALFF) levels in three frequency bands (classic: 0.01–0.1 Hz; slow-5: 0.01–0.027 Hz; and slow-4: 0.027–0.073 Hz) and compared alterations in patients with NC.Results: In the machine learning verification, the identification accuracy of SCD, aMCI, d-AD from NC was higher when fused ALFF and fALFF features (76.44, 81.94, and 91.83%, respectively) than only using ALFF or fALFF features. Several brain regions showed significant differences in ALFF/fALFF within these bands among four groups: brain regions presented decreasing trend of values, including the Cingulum_Mid_R (aal), bilateral inferior cerebellum lobe, bilateral precuneus, and the Cingulum_Ant_R (aal); increasing trend of values were detected in the Hippocampus_L (aal), Frontal_Mid_Orb_R (aal), Frontal_Sup_R (aal) and Paracentral_Lobule_R (aal) as disease progressed. The normalized ALFF/fALFF values of these features were significantly correlated with the neuropsychological test scores.Conclusion: This study revealed gradual disturbances in intrinsic brain activity as the disease progressed: the normal objective performance in SCD may be dependent on compensation; as disease advanced, the cognitive function gradually impaired and decompensated in aMCI, severer in d-AD. Our results indicated that the ALFF and fALFF may help detect the underlying pathological mechanism in AD continuum.Clinical Trial Registration:ClinicalTrials.gov, identifier NCT02353884 and NCT02225964.

Doxorubicin hydrochloride (DOX) is an effective anticancer agent for leukemia chemotherapy, although its clinical use has been limited because of its side effects such as cardiotoxicity, alopecia, vomiting, and leucopenia. Attention has been focussed on developing new drug carriers with high adsorption capacity and rapid adsorption rate in order to minimize the side effects of DOX. Graphene oxide (GO), a new type of nanomaterial in the carbon family, was prepared by Hummers method and used as adsorbent for DOX from aqueous solution. The physico-chemical properties of GO were characterized by transmission electron microscope (TEM), Fourier transform infrared spectroscopy (FTIR), zeta potential, and element analysis. The adsorption properties of DOX on GO were studied as a function of contact time, adsorbent dosage, temperature and pH value. The results showed that GO had a maximum adsorption capacity of 1428.57 mg/g and the adsorption isotherm data fitted the Langmuir model. The kinetics of adsorption fits a pseudo-second-order model. The thermodynamic studies indicate that the adsorption of DOX on GO is spontaneous and endothermic in nature.