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The construction industry is witnessing an increasing adoption of virtual reality (VR) technology for training and education purposes. Given this trend, it becomes essential to critically investigate the impact it has on learners, especially when compared to traditional paper-based learning method. In this paper, the authors developed a close-to-reality virtual system using the Unity3D game engine. Participants engage in learning safety protocols, operating a virtual crane, and assembling a steel structure within this environment. Corresponding paper-based instructional materials were also developed for comparison. The study involved 16 participants who were randomly assigned to either the VR training or the traditional paper-based training, their brainwaves data were recorded through electroencephalography (EEG) headset during the training progress to assess their emotions. Results show that an individual is most likely to experience exciting emotions when they are training in the VR system compared with the traditional training method. The correlation with actual safety performance, however, remains unclear and requires further investigation. 

A THz radar, with its wide bandwidth, is capable of high‐resolution imaging down to the centimeter scale. In this study, a THz radar is applied to detect hydrometeors generated in a spray chamber. The observed backscattering signals show fluctuations at centimeter scales, indicating various hydrometeor distribution patterns along the radar beam. A co‐located High‐Speed Imaging (HSI) sensor is used to measure the Drop Size Distributions (DSD) in the spray chamber. The radar sampling beam is well aligned with the HSI probes, allowing an objective comparison between the remote sensing and in situ observations. In this study, the observed radar power is compared with the power estimated from the HSI measurements. Results show great consistency, with power difference smaller than 0.5 dB. This study demonstrates the feasibility and great potential of using a THz radar for ultra‐high‐resolution observations of clouds in a laboratory facility, and in the real atmosphere. 

We study uniformly random lozenge tilings of general simply connected polygons. Under a technical assumption that is presumably generic with respect to polygon shapes, we show that the local statistics around a cusp point of the arctic curve converge to the Pearcey process. This verifies the widely predicted universality of edge statistics in the cusp case. Together with the smooth and tangent cases proved by Aggarwal‐Huang and Aggarwal‐Gorin, these are believed to be the three types of edge statistics that can arise in a generic polygon. Our proof is via a local coupling of the random tiling with nonintersecting Bernoulli random walks (NBRW). To leverage this coupling, we establish an optimal concentration estimate for the tiling height function around the cusp. As another step and also a result of potential independent interest, we show that the local statistics of NBRW around a cusp converge to the Pearcey process when the initial configuration consists of two parts with proper density growth, via careful asymptotic analysis of the determinantal formulas.

 

A building must meet various requirements during the design and construction process to ensure the benefits of stakeholders and well-being of construction workers and occupants. These requirements may come from different functional areas such as structure, electricity, and fire protection, and focus on different building materials, such as concrete, steel, and glass. They may overlap or even conflict with each other. In order to identify the sources and focus of building code requirements and further clarify the relationships between them, this paper presents some recent results on using graphic convolutional networks (GCN) to classify building code requirements. One hundred building code provisions were randomly selected from the International Building Code 2015 and labeled into six categories manually, and a cutting-edge GCN model was trained to classify them. Experimental results showed an average precision of 91.67% and an average recall of 94.44% when 10% of the data was used for testing, which is comparable to the 84.30% precision and 97.30% recall of the state-of-the-art machine learning-based approaches applied on construction document classification. The effect of the size of training data on testing accuracy was also discussed in this paper. 

We prove multi-point correlation bounds in$$\mathbb {Z}^d$$$Z^d$for arbitrary$$d\ge 1$$$d\ge 1$with symmetrized distances, answering open questions proposed by Sims–Warzel (Commun Math Phys 347(3):903–931, 2016) and Aza–Bru–Siqueira Pedra (Commun Math Phys 360(2):715–726, 2018). As applications, we prove multi-point correlation bounds for the Ising model on$$\mathbb {Z}^d$$$Z^d$, and multi-point dynamical localization in expectation for uniformly localized disordered systems, which provides the first examples of this conjectured phenomenon by Bravyi–König (Commun Math Phys 316(3):641–692, 2012) .

 

Graphene's wetting transparency offers promising avenues for creating multifunctional devices by allowing real‐time wettability control on liquid substrates via the flow of different liquids beneath graphene. Despite its potential, direct measurement of floating graphene's wettability remains a challenge, hindering the exploration of these applications. The current study develops an experimental methodology to assess the wetting transparency of single‐layer graphene (SLG) on liquid substrates. By employing contact angle measurements and Neumann's Triangle model, the challenge of evaluating the wettability of floating free‐suspended single‐layer graphene is addressed. The research reveals that for successful contact angle measurements, the testing and substrate liquids must be immiscible. Using diiodomethane as the testing liquid and ammonium persulfate solution as liquid substrate, the study demonstrates the near‐complete wetting transparency of graphene. Furthermore, it successfully showcases the feasibility of real‐time wettability control using graphene on liquid substrates. This work not only advances the understanding of graphene's interaction with liquid interfaces but also suggests a new avenue for the development of multifunctional materials and devices by exploiting the unique wetting transparency of graphene.

 

Challenged by the prevalent workforce shortage, the construction industry is picking up interest in using robotic arms in construction operations, especially in the context of modular construction and prefabrication. However, the lack of systematic investigations into integrating robotic arms with mobile systems to enhance mobility and operational range has been identified as one main research gap. Stationary robotic arms have inherent limitations in their range, making mobility a critical need. To address that issue, in this paper, the authors proposed a mobile construction robotic system to facilitate their use in the automation of timber frame assembly operation. The authors simulated the system to assess the interactions and coordination among its various components, and to identify potential areas for improvement. This study showcased the effectiveness of the new system design in improving the timber construction automation process and reveals its potential for further exploration in the realm of mobile construction robotics. 

Diffuse Intrinsic Pontine Glioma (DIPG) is a highly aggressive and fatal pediatric brain cancer. One pre-requisite for tumor cells to infiltrate is adhesion to extracellular matrix (ECM) components. However, it remains largely unknown which ECM proteins are critical in enabling DIPG adhesion and migration and which integrin receptors mediate these processes. Here, we identify laminin as a key ECM protein that supports robust DIPG cell adhesion and migration. To study DIPG infiltration, we developed a DIPG-neural assembloid model, which is composed of a DIPG spheroid fused to a human induced pluripotent stem cell-derived neural organoid. Using this assembloid model, we demonstrate that knockdown of laminin-associated integrins significantly impedes DIPG infiltration. Moreover, laminin-associated integrin knockdown improves DIPG response to radiation and HDAC inhibitor treatment within the DIPG-neural assembloids. These findings reveal the critical role of laminin-associated integrins in mediating DIPG progression and drug response. The results also provide evidence that disrupting integrin receptors may offer a novel therapeutic strategy to enhance DIPG treatment outcomes. Finally, these results establish DIPG-neural assembloid models as a powerful tool to study DIPG disease progression and enable drug discovery.