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The high-salinity environments in salt lakes can significantly affect the durability of reinforced concrete. However, there needs to be more reports on the corrosion characteristics of the rebars under salt lake environments, which play a crucial role in studying the deterioration of concrete structures. This study meticulously investigated how temperature variations and changes in water-cement ratios affect the corrosion of rebars in high-salinity lake water conditions, which not only supplements the existing research gap in salt lake conditions but also offers insights for predicting the service life of concrete structures under such circumstances. Reinforced concrete specimens with water-cement ratios of 0.49, 0.54, and 0.60 were tested in both the atmospheric zone and dry–wet cycling zone at temperatures of 15 °C, 30 °C, 35 °C, and 40 °C. A three-electrode system was utilized to monitor the corrosion potentials of the rebars, while the linear polarization method was employed to determine the polarization resistance. The time to corrosion initiation, threshold chloride concentration, and corrosion current density were determined and discussed. The results indicated that temperature and salinity did not significantly affect the corrosion potentials of rebars. However, corrosion initiation occurred much faster under salt lakes than in marine environments, with initiation times averaging around 100 days. Furthermore, it was found that the corrosion rate tended to increase as the temperature and water-cement ratio increased. Additionally, the rebars in the atmospheric zone exhibited lower threshold chloride concentration than those in the dry–wet cycling zone at temperatures of 30 °C, 35 °C, and 40 °C, and higher temperatures corresponded to more significant differences in threshold chloride concentration between the two zones. Lower water-cement ratios were shown to delay corrosion initiation and increase the threshold chloride concentration, suggesting the effectiveness in mitigating rebar corrosion in high-salinity environments. [ABSTRACT FROM AUTHOR]

In a deforming partially molten rock, melt concentrates into a grain‐scale melt pocket aligned at a preferred orientation (melt‐preferred orientation, or MPO). However, observing this texture alone provides limited information on the 3D orientation and geometry of these melt pockets, which are critical parameters for estimating permeability. Here, we modeled the MPO of experimentally deformed peridotites by simulating melt streaks arising from melt pockets of various shapes and 3D orientations. The model aims to identify 3D distribution and characteristics of melt pockets that could account for the observed length, thickness, and the probability of melt streaks. Results show that melt pockets at preferred orientation exhibit greater length, thickness, and number density compared to those perpendicular. These results can be incorporated into the simulation of melt flow through individual melt pockets, which allows us to estimate the permeability corresponding to the observed MPO. We found that the permeability of vertically compressed peridotites increases with increasing compressive strain and a more elongated and thickened shape for melt pocket aligned at preferred orientation. The vertical permeability in the sample with 30% compressive strain is at least 40 times larger than that of an undeformed sample. For peridotites deformed under simple shear, the permeability exhibits an anisotropy of at least three. Such anisotropic permeability, coupled with the formation of melt‐rich bands and other melt channels, is believed to cause lateral melt focusing beneath mid‐ocean ridges. Plain Language Summary: The distribution of melt at the grain scale controls the permeability in partially molten rock. While observe melt streaks on thin sections show variations in length and thickness with respect to the orientation, the geometry and distribution of melt pockets in 3D are poorly constrained. Here, we use an improved statistical model to identify the dependence of melt pocket dimensions as functions of orientation. We further calculate melt flux through individual melt streaks and estimate permeability corresponding to the observed melt distribution texture. We found that deformation in the mantle can significantly accelerate melt extraction and potentially bend the melt flow using anisotropic permeability. Key Points: We parameterized the 3D shapes and orientations of melt pockets under the constraints of observed melt‐preferred orientation (MPO)Permeability in peridotites deformed under vertical compression increases with compressive strain and demonstrates anisotropy up to twoPermeability in peridotites deformed under simple shear demonstrates anisotropy of at least three [ABSTRACT FROM AUTHOR]

Plant Myeloblastosis (MYB) proteins function crucially roles upon variegated abiotic stresses. Nonetheless, their effects and mechanisms in rose (Rosa chinensis) are not fully clarified. In this study, we characterized the effects of rose RcMYB8 under salt and drought tolerances. For induction of the RcMYB8 expression, NaCl and drought stress treatment were adopted. Rose plants overexpressing RcMYB8 displayed enhanced tolerance to salinity and drought stress, while silencing RcMYB8 resulted in decreased tolerance, as evidenced by lowered intra-leaf electrolyte leakage and callose deposition, as well as photosynthetic sustainment under stressed conditions. Here, we further show that RcMYB8 binds similarly to the promoters of RcPR5/1 and RcP5C51 in vivo and in vitro. Inhibiting RcP5CS1 by virus-induced gene silencing led to decreased drought tolerance through the reactive oxygen species (ROS) homeostatic regulation. RcP5CS1-silenced plants showed an increase in ion leakage and reduce of proline content, together with the content of malondialdehyde (MDA) increased, lowered activities of Catalase (CAT), peroxidase (POD) and superoxide dismutase (SOD). Our study highlights the transcriptional modulator role of RcMYB8 in drought and salinity tolerances, which bridges RcPR5/1 and RcP5CS1 by promoting ROS scavenging. Besides, it is probably applicable to the rose plant engineering for enhancing their abiotic stress tolerances. [ABSTRACT FROM AUTHOR]

A 24-GHz frequency modulated continuous wave (FMCW) radar system with self-packaged six-port Butler matrix receiver using substrate integrated suspended line (SISL) platform is proposed in this article. Since all active and passive components are integrated on the SISL platform using the standard printed circuit board (PCB) process, the proposed system is highly integrated with low cost. The system is composed of a transmitting (TX) antenna, a Butler matrix with a receiving (RX) antenna array, a single pole four throw (SP4T) switch, a low noise amplifier (LNA), and a six-port receiver. The Butler matrix and SP4T switch are implemented for beam scanning, which has the advantages of low loss and compact size. The SISL-based six-port receiver is designed for quadrature downconversion. The supporting digital signal processing algorithms are also proposed for the calculation and display of multiple targets information. The radar system has shown excellent performance in the measurement of indoor environment, including range, velocity, and direction of arrival (DOA). The proposed radar provides a new solution for a transceiver system. [ABSTRACT FROM AUTHOR]

Construction site layout planning (CSLP) is a typical problem in construction site management that urgently needs to be solved. A reasonable construction site layout can improve efficiency and reduce costs and unnecessary loss of time. To solve the CSLP problem, some emerging optimization algorithms and enhanced mathematical models have been developed. The building information model (BIM) provides data support for the implementation of previous research. However, manually extracting and modifying parameters from the BIM for use in optimization algorithms is cumbersome in practical applications, wasting considerable time and human resources. In this paper, we propose a framework of automated prefabricated building CSLP to realize the integration of the BIM and an optimization algorithm, which utilizes the Dynamo visual programming platform to create an information channel between the BIM and the optimization algorithm. A typical and practical case, which is optimized by the genetic algorithm (GA) and particle swarm optimization (PSO), is demonstrated to validate the proposed approach and to show an effective reduction in material transportation cost and unnecessary loss of time. [ABSTRACT FROM AUTHOR]

The location information of entities in construction sites, such as workers and construction machines, is valuable in project management and safety. Therefore, as nonintrusive and accurate solutions, various vision-based methods have been proposed to track entities in construction sites and obtain their three-dimensional (3D) coordinates. However, most existing vision-based methods realize 3D localizations by basing entity matching on the epipolar line, which brings instability in entity matching due to the calculation error of the epipolar line or failure to match entities when multiple entities are located on the same epipolar. To solve this problem, a novel framework based on reidentification is proposed to automatically match workers across two camera views, thereby obtaining their 3D coordinates in construction sites. In this framework, deep-learning-based computer vision algorithms are firstly used to detect and track workers in two camera views. Then, the reidentification (ReID) algorithm is applied to utilize tracked workers' visual features to match the workers across both two camera views and different frames. As a result, for every matched pair, the worker's pixel locations in two camera views can be obtained to calculate the 3D coordinates through triangulation. The implementation of videos recorded from a real construction project proves the feasibility and accuracy of this framework. Specifically, through utilizing the ReID algorithm to match workers, the framework achieves competitive results on workers matching with precision, recall, and accuracy of more than 99%, 93%, and 93%. Furthermore, it also effectively addresses the practical problems of ID repetition and ID switching. Meanwhile, this paper extends the application scenarios of reidentification algorithms in construction sites, thereby contributing to the future application of multiple-camera vision-based methods in construction sites. [ABSTRACT FROM AUTHOR]

Effective data interoperability and schedule analysis play a significant role in improving the management of prefabricated buildings. However, there is a lack of efficient strategies and comprehensive approaches for data interoperability and data-based automated schedule analysis. This paper intends to promote prefabricated buildings' management by solving these two problems via developing an IFC-based framework consisting of three parts. Firstly, this framework proposed a mechanism to establish an IFC-based 4D construction management information model of prefabricated buildings. Furthermore, a non-relational database—graph database—is introduced to twin this model into a task-centered network to realize the interoperation of construction information among different participants. Finally, graph database-based strategies to update data, automatically analyze construction schedules and visualize the 4D construction management information model are described. The proposed framework is validated in a prefabricated engineering case. In this case, an IFC-based and graph database-based 4D construction management information model is established through IFC standard's extension. The graph database-based analysis of the model automatically recognizes the engineering case's critical path information, delay analysis information, and schedule network analysis information. It is illustrated that this framework can successfully establish a unified IFC-based information model of prefabricated buildings' construction management to prompt effective data interoperability. In addition, the application of this IFC-based information model in graph database can automatically analyze the construction schedules to prevent possible delays in advance. In short, the significance of this paper is to innovatively propose an IFC-based and graph data-based information model to solve the difficulties of ineffective data interoperation and unautomated schedule analysis in prefabricated buildings' construction management. This study can be the digital foundation of further IFC-based digital twin. [ABSTRACT FROM AUTHOR]

Clinopyroxene and orthopyroxene are the two major repositories of rare-earth elements (REE) in spinel peridotites. Most geochemical studies of REE in mantle samples focus on clinopyroxene. Recent advances in in situ trace element analysis have made it possible to measure REE abundance in orthopyroxene. The purpose of this study is to determine what additional information one can learn about mantle processes from REE abundances in orthopyroxene coexisting with clinopyroxene in residual spinel peridotites. To address this question, we select a group of spinel peridotite xenoliths (9 samples) and a group of abyssal peridotites (12 samples) that are considered residues of mantle melting and that have major element and REE compositions in the two pyroxenes reported in the literature. We use a disequilibrium double-porosity melting model and the Markov chain Monte Carlo method to invert melting parameters from REE abundance in the bulk sample. We then use a subsolidus reequilibration model to calculate REE redistribution between clinopyroxene and orthopyroxene at the extent of melting inferred from the bulk REE data and at the closure temperature of REE in the two pyroxenes. We compare the calculated results with those observed in clinopyroxene and orthopyroxene in the selected peridotitic samples. Results from our two-step melting followed by subsolidus reequilibration modeling show that it is more reliable to deduce melting parameters from REE abundance in the bulk peridotite than in clinopyroxene. We do not recommend the use of REE in clinopyroxene alone to infer the degree of melting experienced by the mantle xenolith. In general, HREE in clinopyroxene and LREE in orthopyroxene are more susceptible to subsolidus redistribution. The extent of redistribution depends on the modes of clinopyroxene and orthopyroxene in the sample and thermal history experienced by the peridotite. By modeling subsolidus redistribution of REE between orthopyroxene and clinopyroxene after melting, we show that it is possible to discriminate mineral mode of the starting mantle and cooling rate experienced by the peridotitic sample. We conclude that endmembers of the depleted MORB mantle and the primitive mantle are not homogeneous in mineral mode. A modally heterogeneous peridotitic starting mantle provides a simple explanation for the large variations of mineral mode observed in mantle xenoliths and abyssal peridotites. Finally, using different starting mantle compositions in our simulations, we show that composition of the primitive mantle is more suitable for modeling REE depletion in cratonic mantle xenoliths than the composition of the depleted MORB mantle. [ABSTRACT FROM AUTHOR]

Large silicic eruptions result from rapid evacuation of large, upper crustal reservoirs of silicic magmas. These silicic magmas are thought to be replenished by melt extracted from underlying crystal-rich source mushes, but the timescales and mechanisms of such melt extraction are unclear. Geochemical observations suggest that the replenishing melt is often more primitive than the eruptives and must thus cool and crystallize to generate the highly silicic magmas that eventually lead to large eruptions. Motivated by these observations, we use thermal models to explore the replenishment conditions capable of building an eruptible silicic reservoir to generate a large eruption. Results show that the minimum melt replenishment rate required for a silicic reservoir to start growing increases with the effective thermal diffusivity of the overlying crust and decreases with the depth of the reservoir. For an eruptible reservoir at 6 km depth to grow, the initial replenishment rate needs to be greater than 2 × 10-9 m/s. High replenishment rates are required to provide enough advected heat to counterbalance rapid heat loss and consequent freezing that would prevent the eruptible reservoir from growing. However, these high initial replenishment rates must then subside over time for the eruptible reservoir to cool, crystallize, and evolve to highly silicic melts. Thermal histories of some natural systems suggest assembly of large eruptible reservoirs in <20 kyr. The rapid replenishment followed by its decay suggests that replenishment was triggered by a pronounced but ephemeral increase in the porosity and permeability of the underlying crystal-rich source mush, allowing for rapid melt expulsion. We speculate that this perturbation may be driven by the sudden incursion of deep-seated, hotter magmas into the base of the crystal-rich source mush. [ABSTRACT FROM AUTHOR]

In this correspondence, we investigate unmanned aerial vehicle (UAV)-base stations (BSs) assisted and received signal strength (RSS) based mobile station (MS) localization. A practical air-to-ground path loss model is utilized, where the path loss exponent (PLE) varies with the elevation angle and altitude of UAV, and the accurate PLE estimate is often difficult to obtain. With unknown and unequal PLEs for different UAVs, the UAVs assisted localization problem becomes nonlinear and non-convex, which cannot be solved by the existing methods. We propose a piecewise convex approximation aided localization (PCAL) approach to convert the localization problem into linear and convex, without requiring the knowledge of PLE. The proposed PCAL approach with unknown and unequal PLEs achieves much higher accuracy than the existing methods which require perfectly known and equal PLE, due to its higher robustness against shadowing. In addition, a grid search aided ambiguity elimination (GSAE) method, which is more effective than the state-of-the-art methods, is proposed to determine the final MS localization estimate based on multiple tentative estimates derived from PCAL. The effectiveness of PCAL is also verified by the Cramer-Rao lower bound (CRLB) derived. [ABSTRACT FROM AUTHOR]

Cyber–physical systems (CPSs) are generally considered to be the next generation of engineered systems. However, the actual application of CPSs in the Architecture, Engineering and Construction (AEC) industry is still at a low level. The sensing method in the construction process plays a very important role in the establishment of CPSs. Therefore, the purpose of this paper is to discuss the application potential of computer vision-based sensing methods and provide practical suggestions through a literature review. This paper provides a review of the current application of CPSs in the AEC industry, summarizes the current knowledge gaps, and discusses the problems with the current construction site sensing approach. Considering the unique advantages of the computer vision (CV) method at the construction site, the application of CV for different construction entities was reviewed and summarized to achieve a CV-based construction site sensing approach for construction process CPSs. The potential of CPS can be further stimulated by providing rich information from on-site sensing using CV methods. According to the review, this approach has unique advantages in the specific environment of the construction site. Based on the current knowledge gap identified in the literature review, this paper proposes a novel concept of visual-based construction site sensing method for CPS application, and an architecture for CV-based CPS is proposed as an implementation of this concept. The main contribution of this paper is to propose a CPS architecture using computer vision as the main information acquisition method based on the literature review. This architecture innovatively introduces computer vision as a sensing method of construction sites, and realizes low-cost and non-invasive information acquisition in complex construction scenarios. This method can be used as an important supplement to on-site sensing to further promote the automation and intelligence of the construction process. [ABSTRACT FROM AUTHOR]

In order to enhance the bioactivity and wear resistance of titanium (Ti) and its alloy for use as an implant surface, a multilayer Ca/P (calcium/phosphorus) bio-ceramic coating on a Ti6Al4V alloy surface was designed and prepared by a laser cladding technique, using the mixture of hydroxyapatite (HA) powder and Ti powder as a cladding precursor. The main cladding process parameters were 400 W laser power, 3 mm/s scanning speed, 2 mm spot diameter and 30% lapping rate. When the Ca/P ceramic coating was immersed in simulated body fluid (SBF), ion exchange occurred between the coating and the immersion solution, and hydroxyapatite (HA) was induced and deposited on its surface, which indicated that the Ca/P bio-ceramic coating had good bioactivity. The volume wear of Ca/P ceramic coating was reduced by 43.2% compared with that of Ti6Al4V alloy by the pin-disc wear test, which indicated that the Ca/P bio-ceramic coating had better wear resistance. [ABSTRACT FROM AUTHOR]

Currently, construction projects are getting more complex, applying more information and communication technologies (ICT), while few studies use real-time data to dynamically optimize construction. The purpose of this article is to study the current development status of the optimization applied dynamically in the construction phase and their potential for applying real data collected by ICT. This article reviews 72 relevant optimization methods and identified some of the ICT research studies that can provide them with dynamic data. The dynamic triggering mode of each research is first analyzed, then its dynamic way, dynamic data, data resource, optimization object, and method are identified and formulated. The results reveal the great value of dynamic optimization in dealing with the complicated and uncertain contextual conditions in construction. Different dynamic triggering modes have different affinities with real data. Then, through the analysis of ICT articles, the huge potential of these dynamic optimization methods in applying real data is shown. This paper points out the most practical dynamic mode for engineers or managers to continuously apply optimization methods to solve dynamic problems in construction, and put forward scientific questions for related researchers: How does one combine ICT with the event dynamics or uncertain parameters? Based on this, the research gap of this area is identified a conceptual solution is proposed. [ABSTRACT FROM AUTHOR]