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Vision transformers (ViT) detectors excel in processing natural images. However, when processing remote sensing images (RSIs), ViT methods generally exhibit inferior accuracy compared to approaches based on convolutional neural networks (CNNs). Recently, researchers have proposed various structural optimization strategies to enhance the performance of ViT detectors, but the progress has been insignificant. We contend that the frequent scarcity of RSI samples is the primary cause of this problem, and model modifications alone cannot solve it.

To address this, we introduce a faster RCNN-based approach, termed QAGA-Net, which significantly enhances the performance of ViT detectors in RSI recognition. Initially, we propose a novel quantitative augmentation learning (QAL) strategy to address the sparse data distribution in RSIs. This strategy is integrated as the QAL module, a plug-and-play component active exclusively during the model’s training phase. Subsequently, we enhanced the feature pyramid network (FPN) by introducing two efficient modules: a global attention (GA) module to model long-range feature dependencies and enhance multi-scale information fusion, and an efficient pooling (EP) module to optimize the model’s capability to understand both high and low frequency information. Importantly, QAGA-Net has a compact model size and achieves a balance between computational efficiency and accuracy.

We verified the performance of QAGA-Net by using two different efficient ViT models as the detector’s backbone. Extensive experiments on the NWPU-10 and DIOR20 datasets demonstrate that QAGA-Net achieves superior accuracy compared to 23 other ViT or CNN methods in the literature. Specifically, QAGA-Net shows an increase in mAP by 2.1% or 2.6% on the challenging DIOR20 dataset when compared to the top-ranked CNN or ViT detectors, respectively.

This paper highlights the impact of sparse data distribution on ViT detection performance. To address this, we introduce a fundamentally data-driven approach: the QAL module. Additionally, we introduced two efficient modules to enhance the performance of FPN. More importantly, our strategy has the potential to collaborate with other ViT detectors, as the proposed method does not require any structural modifications to the ViT backbone.

The purpose of this paper is to explore the evolvement of investors’ behavior in stock market dynamically on the basis of non-cooperative strategy applied by investors in complex networks.

Using modeling and simulation research method, this study designs and conducts a mathematical modeling and its simulation experiment of financial market behavior according to research’s basic norms of complex system theory and methods. Thus the authors acquire needed and credible experimental data.

The conclusions drawn in this paper are as follows. The dynamical evolution of investors’ trading behavior is not only affected by the stock market network structure, but also by the risk dominance degree of certain behavior. The dynamics equilibrium of trading behavior’s evolvement is directly influenced by the risk dominance degree of certain behavior, connectivity degree and the heterogeneity of the stock market networks.

This paper focuses on the dynamical evolvement of investors’ behavior on the basis of the hypothesis that common investors prefer to mimic their network neighbors’ behavior through different analysis by the strategy of anti-coordination game in complex network. While the investors’ preference and the beliefs among them are not easy to quantify, that is deterministic or stochastic as the environment changes, and is heterogeneous definitely. Thus, these limitations should be broken through in the future research.

This paper aims to address the dynamical evolvement of investors’ behavior in stock market networks on the principle of non-cooperative represented by anti-coordination game in networks for the first time, considering that investors prefer to mimic their network neighbors’ behavior through different analysis by the strategy of differential choosing in every time step. The methodology designed and used in this study is a pioneering and exploratory experiment.

This paper aims to clarify the CO₂ emissions of global construction industries under the consideration of different patterns of international trade and thus to draw a comprehensive picture for understanding the international paths of CO₂ transfer to global construction industries.

This research inventories the CO₂ emissions induced by the final demand of 15 economies for construction products and explores the CO₂ intensities of these economies based on a multi-regional input–output model. This paper further decomposes CO₂ emissions into four components based on different patterns of international trade to estimate the roles of four patterns of international trade in shaping the environmental pressures from global construction industries.

The results indicate that the CO₂ intensities of the construction industries in Russia, India and China were higher than those in other economies, and the CO₂ intensities of global construction industries experienced a decline over the years 2000–2014. The decomposition analysis demonstrates that domestic and foreign CO₂ emissions accounted for 42.67 and 54.23%, respectively, of the CO₂ emissions of the construction industries in the 15 economies during the period 2000–2007. Although the major part of the CO₂ emissions of the construction industries come from domestic production systems, the final demand for construction products in the 15 economies caused substantial emissions in other economies. Further decomposition by upstream industrial production source indicates that 58.65% of domestic emissions and 66.53% of foreign emissions can be traced back to the electricity industry.

Although the major patterns of CO₂ emissions of the construction industry have been identified in this paper, the difficulty of understanding the relationship between upstream production industries or countries and the construction industry deserves more attention in the future research.

Previous research on inventorying CO₂ emissions has generally been limited to evaluating the impact of industrial consumption activities on national or global emission accounting, tending to ignore the effects of different international trade patterns on the change in industrial CO₂ emissions. This research is the first attempt to account for and decompose the CO₂ emissions of global construction industries under consideration of the effects of different patterns of international trade on environmental pressures. The decomposition and upstream industrial distributions of different patterns of CO₂ emission provide a comprehensive picture for better understanding of the emission pattern and source of the CO₂ emissions of global construction industries. The research outcomes reveal how the final demand of a country for construction products induces CO₂ emissions in both domestic and foreign systems, thus providing basic information and references for policy adjustment and strategy design in relation to mitigation of climate change and sustainable development.

This paper aims to better understand the linkage between CO₂ emitters and industrial consumers. The border-crossing frequency is applied to calculate the average number of steps that a country takes in relation to the CO₂ emissions of its construction industry. The maximum border-crossing frequency and declining speed of CO₂ transfer are used to reveal the relationship between the length of production chains and the transfer efficiency of construction products.

This paper maps the CO₂ transfer that accompanies global production chains using the frequency of border crossing in the production processes of construction products. As the basic analysis framework, a multi-regional input–output model is adopted to analyse the average border-crossing frequency of CO₂ transfer. Additionally, indicators including the maximum border-crossing frequency and declining speed of CO₂ transfer are employed. Also, the maximum border-crossing frequency and declining speed of CO₂ transfer are used to reveal the relationship between the length of production chains and the transfer efficiency of construction products.

The results indicate that 85.49% of the CO₂ in construction products needs to be processed in at least one country, reflecting that direct trade is the major pattern of transfer of CO₂ from primary producers in global construction industries. The maximum border-crossing frequency is 4.88 for 15 economies, meaning that construction products cross the international borders up to 4.88 times before they are absorbed by the final users. The scale of the average border-crossing frequency ranged from 1.16 to 1.87 over 2000–2014, indicating that the original construction products crossed the international borders at least 1.16 times to satisfy the final demand of the consuming countries.

The data from the economic MRIO tables in the WIOD are only available until 2014, which is a limitation for conducting this research in recent years.

The fragmentation of production is not only reshaping global trade patterns, but also leading to the separation of CO₂ emitters and final consumers in production chains. A growing number of studies have focussed on the impact of production fragmentation on accounting for regional and national CO₂ emissions, but little research has been done at the scale of a specific industry. The major contribution of this paper lies in mapping the CO₂ emissions that accompany the production chains of construction products from the perspectives of both magnitude and length. Additionally, this paper is the first to propose using maximum border-crossing frequency and declining speed to analyse the characteristics of global production chains induced by the final demand of major economies for construction products.

This study aims to examine the cutting performance of a coated carbide tool during the boring of 1Cr17Ni2 martensitic stainless steel, with a focus on how the tool’s structural parameters, particularly the nose radius, affect the wear patterns, wear volume and lifetime of the cutting tool, and related mechanisms.

A full factorial boring experiment with three factors at two levels was conducted to analyze systematically the impact of cutting parameters on the tool wear behavior. The evolution of tool wear over the machining time was recorded, and the influences of the cutting parameters and nose radius on wear behavior of the tool were examined.

The results show that higher cutting parameters lead to significant wear or plastic deformation at the tool nose. When the cutting depth is less than the nose radius, the tool wear tends to be minimized. Larger nose radius tools have weaker chip-breaking but greater strength and wear resistance. Higher cutting parameters reduce wear for the tools with larger nose radius, maintaining their integrity. Wear mechanisms are primarily abrasive, adhesive and diffusion wear. Furthermore, the full-factorial analysis of variance revealed that for the tool with r_ε = 0.4 mm and 0.8 mm, the factors contributing the most to tool wear were cutting speed (38.76%) and cutting depth (86.43%), respectively.

This study is of great significance for selection of cutting tools and cutting parameters for boring 1Cr17Ni2 martensitic stainless-steel parts.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2024-0266/

The purpose of this paper is to maraging 18Ni-300 steel fabricate by powder bed based selective laser melting (SLM) process. Microstructure and mechanical properties of the maraging steel part before and after heat treatment at a slow cooling rate were investigated.

The microstructure of the printed part was observed by optical microscopy and scanning electron microscopy. The phases were determined by X-ray diffraction. The surface roughness of the part was recorded by a profilometer. The tensile properties and microhardness of the parts before and after heat treatment were characterized by an electronic universal tensile testing machine and a Vickers hardness tester, respectively.

Maraging 18Ni-300 steel part comprised of the martensitic phase and a small fraction of austenite phase. After heat treatment, the volume fraction of austenite slightly increased. The surface roughness of the part was about 96 µm. The printed part was dense, but irregular pores were present. The yield strength, ultimate tensile strength (UTS), elongation and Young’s modulus of as-fabricated parts were 554.7 MPa, 1173.1 MPa, 10.9% and 128.9 GPa, respectively. The yield strength, UTS, elongation and Young’s modulus of as-treated parts were 2065 MPa, 2225 MPa, 4.2% and 142.5 GPa, respectively. The microhardness values of surface and cross-section of the as-fabricated part were 407.1 HV and 443.0 HV, respectively. After short-time heat treatment, the microhardness values of the surface and cross-section of the part were 542.7 HV and 567.3 HV, respectively. After long-time heat treatment, the microhardness values of the surface and cross-section of the part were 524.4 HV and 454.8 HV, respectively. The microhardness and tensile strength increased significantly with decreasing elongation due to the changes in phases and microstructure of the parts after heat treatment.

This work studied the effect of heat treatment at 550°C combined with a subsequent slow cooling rate on microstructure and mechanical properties of maraging 18Ni-300 steel obtained by the powder bed based SLM process.

The water evaporation rate (WER) is not only crucial for fabric drying, but also an important parameter affecting cooling from a body wearing sweat wetted clothing. The purpose of this paper is to predict the WERs of wet textile materials in a pre-defined environment.

The maximum water evaporation rate (WER_max) from a saturated surface in a pre-defined environment was first predicted based on the Lewis relationship between the evaporative and the convective heat transfer in this paper. The prediction results were validated by the comparisons with experimental measurements in various environments obtained in this paper and reported in the literature.

Experiment results show that the ratios of WERs to WER_max are lower than 100 percent but higher than 50 percent, which confirmed that the prediction of WER_max is reliable. The temperature decrease of the wet material surface due to evaporation was considered to account for the difference between measured WERs and the WERmax, and the WER variation among materials. The lower ratios of WERs to WER_max in the higher wind condition were speculated to be due to the greater temperature decrease caused by the increased evaporation.

It provides a reliable way to obtain both WER_max and WER (WER_max multiplied by a proper ratio), which can be useful in clothing physiological modeling to predict clothing comfort.

This study contributes to the understanding of the evaporation process of textile materials.

This paper aims to examine the relationship between the audit of outgoing leading officials' natural resource accountability and environmental governance, as well as the internal mechanism of audit of outgoing leading officials' natural resource accountability that plays a role in national environmental governance.

Based on city-level panel data from 2012 to 2015, this paper adopts a difference-in-difference model to examine the role of government audit in national governance from an environmental perspective. Furthermore, using a mediating effect model, the study sheds light on the internal mechanism of audit of outgoing leading officials’ natural resource accountability that plays a role in national environmental governance.

This paper finds that: the implementation of the audit of outgoing leading officials’ natural resource accountability has significantly improved the water quality of the pilot area, but its effects on waste gas and smoke are not obvious; environmental supervision partly plays a mediating role in the improvement of regional environmental governance by the audit of outgoing leading officials’ natural resource accountability; the audit of outgoing leading officials’ natural resource accountability can complement the incentive mechanism of promotion. The older the local officials are, the more obvious the effect of the audit of outgoing leading officials’ natural resource accountability on the environmental quality of the pilot areas is.

This paper reveals the role of government audit from the perspective of environmental governance. It provides empirical evidence for policy regarding the audit of outgoing leading officials' natural resource accountability.

Previous literature tends to combine postponement and modularity or view them as parallel factors to achieve mass customization (MC) while ignoring the sequence of a firm to design and implement operations and supply chain strategy. Based on a customer-oriented strategy and theories of organizational information processing theory, three-dimensional (3D) concurrent engineering and resource dependency, the purpose of this paper is to propose a sequential model reflecting the sequence of practices as well as an overview picture for a firm to achieve MC.

The model links three company antecedents – postponement orientation, operational alignment and information sharing, to three company supply chain practices – product and process modularity and supplier segmentation. These practices, in turn, lead to the company’s MC capabilities. The proposed model is tested with a data set collected from automotive suppliers in China and in the USA. Structural equation modeling is used to analyze the data and test the model.

The results suggest that, for suppliers to achieve MC, postponement orientation and operational alignment are vital antecedents. The results also reveal the important responsibility and role of information sharing practices in coordinating suppliers’ modularity practices.

This research provides three findings that are of value to both academicians and practitioners of supply chain management. First, this study originally proposed and empirically tested that a postponement orientation is an antecedent of product and process modularity and supplier segmentation to achieve MC in the automotive sector, contrary to the traditional view of parallel relationships for both. Second, it developed and verified measures of operational alignment and supplier segmentation for future research use. Third, the vital role of information sharing to coordinate internal and external supply chain practices to achieve MC is empirically supported.

This study investigates the credit supervision issue in rural e-commerce. By studying the trading strategies of buyers and sellers under different credit supervision measures and the impact of different pricing strategies on the trading strategies of both parties, this paper proposes regulatory suggestions for the increasingly severe credit problems in rural e-commerce.

In the online agricultural product transaction between farmers and consumers, both parties' decision-making is a dynamic process. Using the copying dynamic model of the evolutionary game, this study establishes two evolutionary game models to explore the factors affecting credit supervision in the rural e-commerce transaction process. Then, the study provides corresponding countermeasures and suggestions.

First, credit supervision measures implemented by rural e-commerce platforms and the Government's legal system construction and infrastructure construction guarantees influence both parties' trust choices in rural e-commerce transactions. Second, price is a key factor affecting both parties' trading strategies. In the case of relatively fair prices, the higher the proportion of farmers who choose “low price” and “honest transaction” strategies, the easier that is for consumers to choose to trust farmers. In contrast, the higher the price, the higher the proportion of consumers who choose the “trust farmers” strategy, and the more willing farmers are to choose honest transactions.

This work develops a new approach for analyzing rural e-commerce credit supervision. Moreover, this study helps establish and improve the credit supervision mechanism of rural e-commerce and further realize the long-term sustainable development of the rural economy.