Search

AbstractConstruction and demolition waste (CDW) has caused resource waste, environmental pollution and ecological damage, thus seriously threatening the construction industry's sustainable development. However, few studies provide a systematic framework for strategic analysis and planning of CDW management (CDWM) at the regional level, and empirical studies in typical Chinese first-tier cities are unavailable. This study thus aims to develop a systematic framework to analyze the internal and external conditions of regional CDWM practices through a Strength, Weakness, Opportunity and Threat (SWOT) analysis. Suzhou, a typical Chinese first-tier city whose CDWM practices are at the leading level across China, is selected for an empirical study to demonstrate the framework and investigate the critical success factors for CDWM. Data supporting this study are derived from various channels such as reviewing related regulations, laws, government reports, and published materials and interviewing related government staff and industry stakeholders. Based on SWOTs identified, five strategic recommendations were proposed for future improvements of CDWM practices in Suzhou. Findings from this study allow related stakeholders to deeply understand the current quo of CDWM in Suzhou, contributing to the city’s sustainable construction and circular economy. This study also provides valuable references for other similar cities for CDW strategic planning.

Recently, development of drug delivery systems for accurate delivery of antitumor drugs to tumor sites to improve their antitumor efficacy has attracted great interest in the area of cancer immunotherapy. In this report, an intelligent biodegradable hollow manganese dioxide (HMnO2) nanoparticle (NP) with a human umbilical cord mesenchymal stem cell (hUC-MSC) membrane coating was designed to exert efficient chemo-immunotherapy for cancer treatment. A TAT peptide-modified membrane structure was constructed for nuclear targeting. Our findings showed that this new nanoreactor inherited the active targeting capability of MSCs and exhibited tumoritropic accumulation significantly at the cancerous parts. Compared with other formulations, intravenous injection of the NPs markedly inhibited tumor growth, relapse, and metastasis. Moreover, we found that the NPs effectively boosted dendritic cell maturation and recruited effector T cells into tumors. Overall, this work demonstrates the great potential of applying MSC membrane-coated manganese dioxide NPs as nucleus-targeting nanocarriers in cancer chemo-immunotherapy.

Epilepsy (EP) is one of the most universal neurological disorders. This study investigated the mechanism of forkhead box protein O4 (FOXO4) on hippocampal neuronal damage in EP mice. Initially, the EP mouse model and the in vitro HT‐22 cell model were established. EP seizures and neuronal damage in mice were assessed. FOXO4, microRNA (miR)‐138‐5p, and rho‐associated coiled‐coil containing protein kinase 2 (ROCK2) levels in hippocampal tissues or HT‐22 cells were examined. The cell viability and apoptosis of HT‐22 cells were determined. The concentrations of oxidative stress markers and the levels of inflammatory cytokines in hippocampal tissues or HT‐22 cells were detected. We found that FOXO4 was poorly expressed in EP. FOXO4 overexpression alleviated hippocampal neuronal damage in EP mice and improved HT‐22 cell viability and inhibited apoptosis, and decreased oxidative stress and inflammation in hippocampal tissue and HT‐22 cells. The bindings of miR‐138‐5p to FOXO4 and ROCK2 were analyzed, which showed that FOXO4 promoted miR‐138‐5p via binding to the miR‐138‐5p promoter region, and miR‐138‐5p inhibited ROCK2 expression. Joint experiments showed that miR‐138‐5p suppression or ROCK2 overexpression reversed the alleviation of FOXO4 overexpression on hippocampal neuronal damage. FOXO4 inhibited ROCK2 expression via promoting miR‐138‐5p expression, thus alleviating hippocampal neuronal damage in EP mice.

Lung cancer is one of the most malignant tumors with fastest morbidity and mortality. Small cell lung cancer (SCLC) is the most malignant pathological type of lung cancer with early metastasis and poor prognosis. At present, there is a lack of effective indicators to predict prognosis of SCLC patients. Delta-like 3 protein (DLL3) is selectively expressed on the surface of SCLC and is involved in proliferation and invasion. Neuron-specific enolase (NSE) is an enolase isoenzyme that is generally regarded as a biomarker for SCLC and may correlate with stage of SCLC, prognosis and chemotherapy response. NSE can be influenced by different types of factors. To explore the associations between expression levels of DLL3 in tumor tissues with platinum/etoposide chemotherapy response, and assess the prognostic values of DLL3, NSE and other potential prognostic factors in advanced SCLC patients were herein studied. Ninety-seven patients diagnosed with SCLC in Zhongda Hospital from 2014 to 2020 were enrolled in the study. Serum NSE levels were tested using ELISA methods before any treatment. The expression of DLL3 in tumor tissue was detected by Immunohistochemistry (IHC). We investigated the relationship of DLL3 expression with chemotherapy and survival. Progression free survival (PFS) and overall survival (OS) were estimated by the Kaplan–Meier method. Multivariate Cox-proportional hazard regression was used to identify predictors of PFS and OS. DLL3 was detected in 84.5% (82/97) of all patients’ tumor samples by IHC, mainly located on the surface of SCLC cells. Lower DLL3 expression was associated with longer PFS and better chemotherapy response. OS had no significant differences. Multivariate analysis by Cox Hazard model showed that, high DLL3 expression and maximum tumor size >5 cm were independent risk factors for PFS, where NSE < 35 ng/mL and age < 70 were independent prognostic factors for OS. Early stage was independent prognostic factors for PFS and OS (P < .05 log-rank). DLL3 was expressed in the most of SCLCs. DLL3 expression level in the tumor and NSE level in the serum may be useful biomarkers to predict the prognosis of SCLC. DLL3 may be a potential therapeutic target for SCLC in the future.

AbstractThe improvement of the landslide susceptibility mapping (LSM) is a long-standing problem, as it provides basics for hazard mitigation. Recently, hybrid ensemble deep learning (DL) techniques have witnessed the potential for this purpose. In this paper, we proposed a novel ensemble DL model, namely GL-ResNet, which employs the conventional ResNet blocks for landslide feature extraction, long-short term memory (LSTM) structures for information storage, and a proposed GoogLeNet block (GBlk) to broaden model perception ability. To validate the model performance, a landslide inventory containing 1147 historical landslide polygons and the data of 12 landslide factors in the Wenchuan area in southwestern China, was presented and separated into training and validating dataset using a 7:3 randomly sampling ratio strategy. Based on AUC and Accuracy, GL-ResNet (0.96 and 0.909) outperformed logistic regression (0.92 and 0.851), support vector machines (0.94 and 0.884), deep belief networks (0.95 and 0.884), gated recurrent unit (0.94 and 0.884) and ResNet (0.95 and 0.894). We also explored the robustness of GL-ResNet for LSM. The results suggested that although GL-ResNet is sensitive to initial training conditions, it showed good robustness to model training method and sample ratios. In detail, GL-ResNet outperformed the conventional models in terms of fitting power and prediction performance by 0.03-0.04 and 0.02 respectively in most cases, with even greater differences in the limited training dataset.

Developing anodes with a high and stable energy density for both gravimetric and volumetric storage is vital for high-performance lithium/sodium-ion batteries. Herein, an SnSe/few-layered graphene (FLG) composite with a high tap density (2.3 g cm–3) is synthesized via the plasma-milling method, in which SnSe nanoparticles are strongly bound with the FLG matrix, owing to both Sn–C and Se–C bonds, to form nanosized primary particles and then assemble to microsized secondary granules. The FLG can effectively alleviate the large stress generated from the volume expansion of SnSe during cycling based on its superstrength. Furthermore, as demonstrated by the density-functional theory calculations, the Sn–C and Se–C co-bonding benefitting from the formation of substantial vacancy defects on the P-milling-synthesized FLG enables strong affinity between SnSe nanoparticles and the FLG matrix, preventing SnSe from aggregating and detaching even after long-term cycling. As an anode for lithium-ion batteries, it exhibits high gravimetric and volumetric capacities (864.8 mAh g–1and 1990 mAh cm–3at 0.2 A g–1), a high rate (612.6 mAh g–1even at 5.0 A g–1), and the longest life among the reported SnSe-based anodes (capacity retention of 92.8% after 2000 cycles at 1.0 A g–1). Subsequently, an impressive cyclic life (capacity retention of 91.6% after 1000 cycles at 1.0 A g–1) is also achieved for sodium-ion batteries. Therefore, the SnSe/FLG composite is a promising anode for high-performance lithium/sodium-ion batteries.

This study establishes a multi-objective optimization model for the capacity allocation of an urban rail transit network based on multi-source data on the Beijing metro passenger flow. The model considers the operating costs of trains and the expenses related to the waiting time of transferring passengers. The model constraints include the distribution characteristics of passenger flow, headway, load factor, and available trains. The capacity allocation scheme for 16 railway lines was obtained by adopting a model of the Beijing rail transit network and its passenger flow. We also analyzed the frequency at which Line 4 is reduced from 55 to 45 and the frequency at which Line 10 is reduced from 60 to 52 if a short turn is adopted. In addition, when the upper limit of the load factor increased from 60 to 70%, the operational costs were reduced by 4.6%, while the total passenger waiting time increased by 1%. The transfer costs changed the capacity optimization and allocation scheme, and the proportion of the transfer cost among the total costs increased when the time value increased.

Landslides induced by earthquakes and rainfall pose severe threats to the infrastructure of highways and high-speed railways. To plan an immediate emergency response, the location and scale of these landslides should be known beforehand. Traditionally, to detect multitemporal landslides induced by earthquakes and the long-term effects, along with other factors such as subsequent rainfall, one had to carry out image classification multiple times to calculate the variance information. The accuracy of that method is affected by accumulated errors from multiclassification, and the process is very time-consuming. In this paper, a semiautomatic approach is proposed for rapid mapping of multitemporal landslides. The approach can obtain the variance information of each landslide event in one detection process. In addition, slope units are introduced to separate the extracted conjoined landslides. The area of Chenjiaba, China, which is located in the highest seismic intensity zone of the Wenchuan earthquake in Beichuan and had strong rainfall 4 months after the earthquake, was selected as a case study to demonstrate the validity of this methodology. Accuracy assessment was carried out by comparing extracted landslides with a manually prepared landslide inventory map. Correctly detected were 90.1% and 94.2% of earthquake- and rainfall-induced landslides, respectively. Results show that this approach is capable of mapping temporal landslides efficiently and quickly.

ABSTRACTPublic transportation automatic fare collection (AFC) systems are able to continuously record large amounts of passenger travel information, providing massive, low-cost data for research on regulations pertaining to public transport. These data can be used not only to analyze characteristics of passengers’ trips but also to evaluate transport policies that promote a travel mode shift and emission reduction. In this study, models combining card, survey, and geographic information systems (GIS) data are established with a research focus on the private driving restriction policies being implemented in an ever-increasing number of cities. The study aims to evaluate the impact of these policies on the travel mode shift, as well as relevant carbon emission reductions. The private driving restriction policy implemented in Beijing is taken as an example. The impact of the restriction policy on the travel mode shift from cars to subways is analyzed through a model based on metro AFC data. The routing paths of these passengers are also analyzed based on the GIS method and on survey data, while associated carbon emission reductions are estimated. The analysis method used in this study can provide reference for the application of big data in evaluating transport policies.Implications: Motor vehicles have become the most prevalent source of emissions and subsequently air pollution within Chinese cities. The evaluation of the effects of driving restriction policies on the travel mode shift and vehicle emissions will be useful for other cities in the future. Transport big data, playing an important support role in estimating the travel mode shift and emission reduction considered, can help related departments to estimate the effects of traffic jam alleviation and environment improvement before the implementation of these restriction policies and provide a reference for relevant decisions.

Lithium iodide is mixed into the perovskite precursor solution as an additive. X‐ray diffraction, field‐emission scanning electron microscopy, steady‐state photoluminescence, ultraviolet–visible absorption spectra, and electrochemical impedance spectra are used to characterize and analyze the perovskite solar cells prepared from this solution. It is found that the LiI additive can improve the crystallinity and the quality of perovskite crystal, enhance the light absorbance and the charge carrier extraction of the perovskite films, and reduce the charge‐transfer resistance of the device. As a consequence, the open‐circuit voltage and the fill factor of the perovskite solar cells increase. Under optimal conditions, the LiI‐containing perovskite solar cell can achieve a power conversion efficiency of 16.53 % whereas the device based on a perovskite without added LiI has an efficiency of 14.22 % under the same experimental conditions. The simple process and significant improvement in the performance render this method promising. Into the Mix: Lithium iodide is introduced as an additive to the perovskite precursor solution. The addition effects the crystal growth of perovskite film, giving rise to increased crystallinity, which improves the quality and conductivity of the perovskite film and speeds up the charge transport in the device. The perovskite solar cell utilizing LiI gives rise to a power conversion efficiency that is considerably higher than a device based on a perovskite without added LiI.

Electromagnetic pulse and transient electromagnetic field have received a large concern. To guarantee the validity of the test results in transient field facilities, field uniformity is addressed and required in many international standards. This paper focuses on the implementation of such a measuring system according to the field uniformity requirements of MIL-STD-461F. Also the specific requirements are highlighted and the field sensor calibration is detailed. The measurement uncertainty budget of the field uniformity measuring system is briefly given.

Bike-sharing has shown its potential to improve irrational urban transportation structures and significantly reduce greenhouse gas emissions. This paper thus established a computation model to assess the greenhouse gas emission (GGE) reduction through bike-sharing based on the life cycle assessment (LCA) theory. Data collected from Shanghai, China, is selected for a case study to demonstrate and validate the model. Results indicate that promoting bike-sharing can significantly reduce the life cycle GGE (LCGGE) in the transportation sector. Findings from this study highlight the environmental benefits of bike-sharing, which provide valuable references for improving urban transportation systems and developing sustainable cities.

Although prefabrication is considered a sustainable construction technology that can reduce various construction waste, research on its potential for concrete formwork waste reduction is currently limited. This study proposes an approach integrating life cycle assessment (LCA) and building and information modelling (BIM) to quantify the possible life-cycle formwork waste reduction through prefabrication from a construction project, in which LCA serves as a systematic assessment framework and BIM provides the basic inventory for LCA. A typical reinforced concrete frame structural building located in Nanjing, China is chosen for a case study to demonstrate and validate the proposed approach. Results show that prefabrication can reduce formwork waste by 59.68%-71.83%, which mainly comes from straight walls and slabs. This figure can continuously increase to as high as 90% if the prefabrication is further applied and promoted. Findings from this study contribute to the understanding of the environmental benefits of prefabrication. This is of great significance for designers, engineers, and governments who are constantly seeking ways toward sustainable construction.

Abstract: This paper aims to design and develop a Distributed Virtual Geographic Environment (DVGE) system. A DVGE system is an Internet-based virtual 2D and 3D environment that provides users with a shared space and a collaborative platform for publishing multidimensional geo-data, and for simulating and analyzing complex geo-phenomena. Users logging into the system from different clients can share distributed geo-information resources, including geo-data and geo-models, and can complete collaborative tasks. Web service technology provides effective solutions for constructing DVGE systems because of its ability to support multi-platform, multi-architecture, and multi-program-language interoperability on the Internet, but also because of its ability to share programs, data, and software. This paper analyzes the characteristics, relevant technologies, and specifications of web services, such as grid services, Open Geo-data Interoperability Specifications (OpenGIS), and Geography Markup Languages (GML). The architecture and working mechanisms of the DVGE system based on web services are then elaborated. To demonstrate DVGE systems based on web services, we examine a case study of water pollution in Yangzhou City, Jiangsu Province, China, using a prototype DVGE system that is developed with Jbuilder9.0 and Java3D 1.0 packages, and the Weblogic platform 8.1. [Copyright &y& Elsevier]