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The nature of liquid-to-glass transition is a major puzzle in science. A similar challenge exists in glass-to-liquid transition, i.e., glass melting, especially for the poorly investigated surface effects. Here, we assemble colloidal glasses by vapor deposition and melt them by tuning particle attractions. The structural and dynamic parameters saturate at different depths, which define a surface liquid layer and an intermediate glassy layer. The power-law growth of both layers and melting front behaviors at different heating rates are similar to crystal premelting and melting, suggesting that premelting and melting can be generalized to amorphous solids. The measured single-particle kinetics reveal various features and confirm theoretical predictions for glass surface layer.

The strength $ σ_{y}(D)$ of a polycrystal can decrease or increase with the grain diameter $D$, i.e., the famous Hall-Petch (HP) and inverse-Hall-Petch (IHP) behaviors, respectively. However, $ σ_{y}(D)$ under thick grain boundaries (GBs) (i.e., GB thickness $l>1$ particle) and $ σ_{y}(l)$ have rarely been explored. Here we measure them by systematically varying $D$ and $l$ of two-dimensional glass-crystal composites in simulations. We demonstrate that increasing $l$ and decreasing $D$ have similar effects on reducing dislocation motions and promoting GB deformations. Consequently, the classical HP-IHP behaviors of $ σ_{y}(D,l=1)$ and our generalized HP-IHP behaviors of $ σ_{y}(D,l)$ share similar mechanisms and can be unified as $ σ_{y}$ ($A_\textrm{GB}/A_\textrm{tot}$), where $A_\textrm{GB}/A_\textrm{tot}$ is the fraction of the amorphous region. The results reveal a way to exceed the maximum strength of normal polycrystals. The generalized HP-IHP behaviors of $ σ_{y}(D,l)$ should be similar in 2D and 3D, except that the HP effect in 3D is stronger.

Automated interior construction progress monitoring (ICPM) has gained increasing academic attention. This emerging research field faces numerous technical challenges that have been noted in previous studies but lack a holistic examination to analyze these challenges and their potential impacts. This study addresses this gap by conducting a systematic review of ICPM technical challenges, collecting related literature from Scopus, Web of Science, and ScienceDirect databases, and utilizing the Preferred Reporting Items for Systematic Reviews and Meta-Analyzes (PRISMA) framework for filtering and selecting literature. The filtration results in 44 strongly related technical papers. Alongside summarizing these challenges, the study explores their impacts on the entire ICPM automation process and proposes innovative solutions. Specifically, this study highlights the key phases of ICPM automation development, including data acquisition, 3D reconstruction, as-planned modeling, as-built modeling, progress comparison, and progress quantification, and subsequently identifies challenges for each phase, totaling 11 major challenges composed of 41 subchallenges. The data acquisition phase is found to have the most and most severe challenges, and challenges in other phases also impact the automation system performance. This review encompasses the identification of potential issues and proposes corresponding solutions, enabling future researchers to anticipate challenges and develop more advanced and user-friendly monitoring systems. [ABSTRACT FROM AUTHOR]

Despite efforts to prevent and correct unsafe behavior on construction sites, such behavior persists among construction workers. Much of what makes unsafe behavior so difficult to eradicate is its contagious nature. The contagion pattern of unsafe behavior is not only based on the group characteristics of construction workers but also influenced by government regulatory agencies (GRA) and general contractors (GC). In this study, we established a contagion model of construction workers' unsafe behavior based on group-level factors and the dual influence of GRA and GC and employed evolutionary game theory and epidemic models to explore the contagion patterns and interventions of unsafe behavior. We find that, although the strong and weak regulation strategies by GRA suppress the contagion of unsafe behavior, the strong regulation strategy exhibits a better preventive effect; further, the active management strategies by GC have a dampening effect on the contagion of unsafe behavior and vice versa, enhanced perceived social benefits of GRA prevent unsafe behavior more than enhanced perceived image loss, and a high degree of group identity perception effectively inhibits the contagion of unsafe behavior when construction workers have relatively high levels of safety awareness. By portraying the contagion state of construction workers' unsafe behavior in actual situations, this study provides a theoretical basis for the decision-making of GRA and GC and helps to improve the work efficiency of GRA as well as the safety management level of GC. [ABSTRACT FROM AUTHOR]

Climate change is increasingly exacerbating water shortages worldwide. Among the various repercussions of water scarcity, notably in developing countries, the most critical are the decline in social sustainability and the widening inequality within farming communities. In response, irrigation reforms aimed at establishing farmer-managed networks have been introduced to foster equitable water distribution and enhance the livelihood and food security of underprivileged farmers. However, these reforms have largely fallen short of achieving their social sustainability goals. A significant factor in this shortfall is the farmers' limited capacity and reluctance to assume roles typically filled by bureaucracy under institutional reforms. This study explores farmers' willingness to engage in a World Bank-assisted participatory irrigation infrastructure program. We utilized questionnaire surveys and hierarchical analysis to evaluate how various factors influence farmers' willingness to participate. The findings indicate a multifaceted challenge that intensifies in communities fragmented by socioeconomic and political divides. Particularly, the predominance of large landowners in agricultural communities and the absence of sufficient bureaucratic support for participation are key impediments. Our research offers comprehensive insights into the regional sociopolitical obstacles obstructing farmer involvement in government-led participatory projects. It also guides policymakers in grasping the intricate interplay between program design, execution, and contextual elements, which is crucial for the sustainable development of resource-stressed areas. [ABSTRACT FROM AUTHOR]

The march toward fusing business with sustainability is articulated with the hope of offering solutions to global environmental degradation. Green innovation is often regarded as an effective strategy to induce double externality with positive innovation and environmental spillovers. Despite numerous research works on determinants of green innovation, the key question, however, whether and how organizational improvisation exerts its influence on innovatively being green is still unsolved. On this basis, the current study seeks to demonstrate a connection between organizational improvisation and corporate green innovation. According to the presented theoretical framework, organizational improvisation, which serves as a catalyst for improving learning processes, promotes green innovation. Furthermore, dynamic capabilities mediate this relationship, and top management risk aversion could weaken the successful transformation of substantive innovation and being green. Empirical evidence is found based on a sample of Chinese manufacturing firms with a moderated mediation analysis. These results extend the understanding of the role of improvisation in green achievements towards the fusion of unplanned change and order. [ABSTRACT FROM AUTHOR]

Green buildings have gained increasing momentum during the past decade, evidenced by an uptick in green building construction worldwide. To facilitate green building development, it is crucial to understand the current geographical distribution of green buildings, thereby identifying emerging markets and opportunities for future growth. However, very few studies investigated the spatial characteristics of the green building market and the factors influencing the distribution of green buildings. By examining the national green building market in the United States, we studied the spatial distribution patterns and significant influencing factors of the county-level US green building markets. Cluster mapping and hot spots of the green building markets were identified through spatial autocorrelation analysis. A spatial regression model with high performance (R2 of 0.83) was developed to identify the significant influencing factors. We found a statistically significant clustering phenomenon of county-level US green building markets. The spatial error model reveals that three factors, namely, the number of housing units, gross domestic product, and the local green building company index, significantly influence the number of green buildings at the county level. We also found that the county-level green building market is influenced by these factors of not only the host county, but also the neighboring counties. Our findings provide a useful reference for stakeholders' decision-making process concerning local green building market development. [ABSTRACT FROM AUTHOR]

The assembly of prefabricated components is a critical process in prefabricated building construction, influencing both progress and accuracy. However, the assembly sequence planning and optimization (ASPO) of prefabricated components have yet to receive sufficient attention from researchers, and current research has displayed limited automation and poor generalization capabilities. Therefore, this paper proposes a framework for intelligently generating assembly sequences for prefabricated components based on graph databases and matrices. The framework utilizes an adjacency matrix and interference matrix-based modeling method to comprehensively describe the connections and constraint relationships between components, enabling better evaluation of assembly difficulty during optimization. The graph database serves as the central hub for data exchange, facilitating component information storage, automatic querying, and summarization. The obtained assembly sequence and progress plan are fed back into the graph database. To accomplish assembly sequence optimization, a genetic algorithm based on the double-elite strategy is employed. Furthermore, the effectiveness of the proposed framework is validated through an actual engineering case. The results demonstrate that the framework can effectively find an optimal assembly sequence to mitigate the assembly challenge of a prefabricated building. [ABSTRACT FROM AUTHOR]

The digital revolution has swept the world, but the construction industry, the backbone of the global economy, has lagged. Government policy is expected to promote the development of digital technologies centered around building information modeling (BIM) in the construction industry. However, how digital technology–related policies diffuse within a country and influence innovation regionally remains unknown. Using 2011–2019 panel data from 31 provinces in mainland China, we found that BIM policy diffuses not only vertically among national and regional governments, but also horizontally among neighboring regional governments, both of which accelerate the adoption of BIM policy in various regions across the country. We also found that there is a causal relationship between regional BIM policies and related BIM innovation. Further, the positive influence of policies on innovation is more significant in regions with low economic development and high openness levels. This study not only contributes to understanding the impact of policy diffusion on BIM innovation, but also offers insights into the research on policies and innovation of digital technology in the construction industry from a macro perspective. The empirical evidence provides a practical reference for policymakers to accelerate the adoption of digital technology policy within the country and promote technological innovation. [ABSTRACT FROM AUTHOR]

Traditional models that employ CNNs as encoders do not sufficiently combine high-level features and low-level features. However, high-level features are rich in semantic information but lack spatial detail, while low-level features are the opposite. Therefore, the integrated utilization of multi-level features and the bridging of the gap between them is crucial to promote the accuracy of semantic segmentation. To address this issue, we presented communicating mutual attention (CMA) and communicating self-attention (CSA) modules to enhance the interaction and fusion of different levels of feature maps. On the one hand, CMA aggregates the global context information of high-level features into low-level features and embeds the spatial detail localization characteristics of low-level features in high-level features. On the other hand, the CSA module is deployed to integrate the spatially detailed representation of low-level features into the attention map of high-level features. We have experimented with the communicating attention network (CANet), a U-net-like network composed of multiple CMA and CSA modules, on the ISPRS Vaihingen and Potsdam datasets with mean F1-scores of 89.61% and 92.60%, respectively. The results demonstrate that CANet embodies superior performance in the semantic segmentation task of remote sensing of images. [ABSTRACT FROM AUTHOR]

Public-private partnerships (PPPs) have become an important option for financing urban rail transit (URT) projects. To ensure the effective operation of URT projects and better serve the public, governments must select suitable operators as part of private-sector consortiums to achieve successful PPP implementations, but they often face a dilemma in choosing between local URT groups and nonlocal operators. In this study, we examine the key factors that determine governments' operator choices for URT PPP (URT3P) projects with a two-stage approach. A four-dimensional (4D) indicator system containing 20 factors was first developed, and least absolute shrinkage and selection operator (LASSO) regression was applied to analyze one of the largest regional URT data sets in China. Five key factors that significantly influence operator selection are identified, including project operation duration, government-business relationships, private-sector entity organization type, private-sector entity ownership type, and whether the private-sector entity owns an operating firm. This study contributes to the body of knowledge on URT3P project management, and this systematic approach can be used by local governments to select suitable operating partners in similar exploratory contexts. [ABSTRACT FROM AUTHOR]

Based on the Foucauldian concept of governmentality, this paper overcomes the atomistic view of external stakeholder engagement research to examine the specific conditions under which community engagement in urban infrastructure public-private partnerships (PPPs) can be transformational and create social value with and for communities. In particular, it shows that a transformational approach to community engagement is, in practice, closer to a form of governance that emphasizes involved stakeholders' responsibility. It traces this line of argument through the literature and practice of social enterprises and other hybrid collaborations in the private sector. Conceptually, it contributes to a political and transformational understanding of community engagement within the context of public-private partnerships. First, by proposing a "governmentality analytical framework" for understanding and uncovering the often purposefully concealed dynamic power relations in the engagement process between the state, communities, and private investors. Second, by proposing a set of guiding principles on how to: empower communities to be organized; reconfigure the institutional environment to offer incentives and reliability; and design public-private partnerships as hybrid organizations capable of including other actors, such as non-governmental organizations. [ABSTRACT FROM AUTHOR]

Incomplete premelting at the edges of monolayer colloidal crystals is triggered by a bulk solid-solid phase transition and truncated by a mechanical instability that induces homogeneous bulk melting of the crystal; these observations challenge existing theories of two-dimensional melting. Surface melting in a model system When a crystal melts, it typically melts from the surfaces, starting with the formation of liquid-like 'premelt' surface layers at temperatures slightly below the melting point. In an effort to understand the mechanistic details of this process, Yilong Han and colleagues have investigated the melting behaviour of two-dimensional (monolayer, two-layer and three-layer) colloidal crystals -- model systems whose dynamics can be followed at the single particle level. They observe a variety of surface premelting, bulk-melting and solid-solid phase-transition phenomena, the interplay of which challenges current premelting and melting theories. Crystal surfaces typically melt into a thin liquid layer at temperatures slightly below the melting point of the crystal. Such surface premelting is prevalent in all classes of solids and is important in a variety of metallurgical, geological and meteorological phenomena.sup.1. Premelting has been studied using X-ray diffraction.sup.2 and differential scanning calorimetry.sup.3, but the lack of single-particle resolution makes it hard to elucidate the underlying mechanisms. Colloids are good model systems for studying phase transitions.sup.4 because the thermal motions of individual micrometre-sized particles can be tracked directly using optical microscopy.sup.5. Here we use colloidal spheres with tunable attractions to form equilibrium crystal-vapour interfaces, and study their surface premelting behaviour at the single-particle level. We find that monolayer colloidal crystals exhibit incomplete premelting at their perimeter, with a constant liquid-layer thickness. In contrast, two- and three-layer crystals exhibit conventional complete melting, with the thickness of the surface liquid diverging as the melting point is approached. The microstructures of the surface liquids differ in certain aspects from what would be predicted by conventional premelting theories. Incomplete premelting in the monolayer crystals is triggered by a bulk isostructural solid-solid transition and truncated by a mechanical instability that separately induces homogeneous melting within the bulk. This finding is in contrast to the conventional assumption that two-dimensional crystals melt heterogeneously from their free surfaces.sup.3,6 (that is, at the solid-vapour interface). The unexpected bulk melting that we observe for the monolayer crystals is accompanied by the formation of grain boundaries, which supports a previously proposed grain-boundary-mediated two-dimensional melting theory.sup.7. The observed interplay between surface premelting, bulk melting and solid-solid transitions challenges existing theories of surface premelting and two-dimensional melting., Author(s): Bo Li [sup.1] , Feng Wang [sup.1] , Di Zhou [sup.1] , Yi Peng [sup.1] , Ran Ni [sup.2] [sup.3] , Yilong Han [sup.1] Author Affiliations: (1) Department of [...]