Search

The growth and biological decline of alfalfa may be linked to the rhizosphere microbiome. However, plant–microbe interactions in the rhizosphere of alfalfa and associated microbial community variations with stand age remain elusive. This study explored the successional pattern of rhizosphere microbial communities across different aged alfalfa stands and its relationship with alfalfa decline. Rhizosphere soils were collected from 2- and 6-year-old alfalfa stands. Control soils were collected from interspaces between alfalfa plants in the same stands. Soil bacterial and fungal communities were characterized by 16S and ITS rRNA gene sequencing, respectively. Specific microbial taxa colonized the rhizosphere soils, but not the control soils. The rhizosphere-specific taxa mainly included potentially beneficial genera (e.g., Dechloromonas, Verrucomicrobium) in the young stand and harmful genera (e.g., Peziza, Campylocarpon) in the old stand. Alfalfa roots regulated soil microbial communities by selective promotion or inhibition of distinct taxa. The majority of time-enriched taxa were reported as harmful fungi, whose relative abundances were negatively correlated with plant traits. Time-depleted taxa were mostly known as beneficial bacteria, which had relative abundances positively correlated with plant traits. The relative abundances of functional bacterial genes associated with vancomycin biosynthesis, zeatin biosynthesis, and amino acid metabolism trended lower in rhizosphere soils from the old stand. An upward trend was observed for fungal pathogens and wood saprotrophs with increasing stand age. The results suggest that root activity drives the negative succession of rhizosphere microbial communities during alfalfa decline in old stands.

Rural collectively owned commercial construction land marketization (RCCCLM), a land policy that is still being piloted despite being allowed by law, has been regarded as an indispensable policy tool that can meet the land demand for rural development. This study aims to analyze the typical modes and key paths of RCCCLM for rural transformation theoretically and practically. We developed an innovative theoretical framework of “Situation-Structure-Implementation-Outcome” to illustrate the relationship between RCCCLM and rural transformation. By tracing the process of the impact of RCCCLM on rural transformation in typical areas, this study fills the gap in existing research that has not yet explored the theoretical mechanisms between RCCCLM and rural transformation. The results show that a combination of such factors as geographical location and rural land use status brings about three major ways of RCCCLM, namely, local marketization, adjustive marketization and consolidation-based marketization, to promote rural transformation. The influencing mechanism of RCCCLM on rural transformation mainly concerns rights granting, rural land use structure reshaping, the transformation of farmers’ livelihood and improvement in rural governance capacity. Rural transformation follows a basic rule and phased characteristics of evolving from single function to multiple functions, and RCCCLM displays a differentiated driving effect on the evolution of rural functions in different stages of rural development. These findings will provide new insights into rural land use and rural transformation in China and other developing countries and help solve the bottlenecks in rural transformation.

Eliminating poverty and achieving social justice are global concerns. China has focused on common prosperity. Comprehensive land consolidation is a potential policy tool that can contribute to common prosperity, but its effectiveness and implementation methods are yet to be verified and discussed. Therefore, we construct an analytical framework to understand how comprehensive land consolidation promotes common prosperity. The pilot area for comprehensive land consolidation in Ningbo City is used as a qualitative case study. The research results indicate that comprehensive land consolidation focuses on development and sharing to promote high-quality socio-economic development, social fairness, and justice. The paths for achieving development included the following: (1) a network governance structure consisting of multiple entities to enhance land governance; (2) various consolidation activities were conducted at the town scale to optimize the functionality and spatial pattern of public spaces; and (3) enabling the flow of urban and rural factors for improved resource allocation efficiency and providing an impetus for industrial development. The paths for achieving sharing included clarifying collective land ownership and promoting land transactions to provide diverse land values and ensure a shared distribution. This research provides new insights applicable to other Chinese cities and numerous developing countries engaged in land consolidation to address social distribution issues.

Against the backdrop of an urban-rural dual structure, governance structure significantly influences the fairness and sharing of land value increment profits from land consolidation in various regions. This paper develops a spatial-institutional analytical framework, reflects on the traditional government-led land quota planning management mechanism and advocates optimizing governance structures in land consolidation to facilitate urban-rural element flows and the sharing of land value increment profits. This paper selects two comprehensive land consolidation cases in the Fenghua District and Cixi City of Ningbo, representing government-led and village collective self-organized governance structures. The research shows that the Fenghua case adopts a government-led state-owned enterprise coordinated governance structure, which state-owned enterprises bear operational risks and the majority of profit sharing, while village collectives, as landowners, are insufficiently protected in benefit sharing. The Cixi case employs a government-embedded village-town governance structure, with the village collectives as the main operating body, allowing collective construction land to enter the market to ensure the sharing of community profits. Both governance structures promote the bidirectional flow of urban-rural land resource elements; the former significantly drives urban development, while the latter ensures better benefit sharing for village collectives. The research proposes that optimizing governance structures and improving land quota allocation mechanisms can further stimulate various entities’ participation in land consolidation and land value activation.

Unmanned aerial vehicles (UAVs) can support low-cost, highly mobile communications while making it possible to establish dedicated terrestrial networks. To overcome the pointing error (PE) and beam misalignment of millimeter-wave large-scale multiple-input multiple-output/free-space optics (MIMO/FSO) caused by UAV jitter, a millimeter-wave massive MIMO/FSO hybrid beamforming method based on tensor train decomposition is proposed. This approach is used for reconfigurable intelligent surface (RIS) network-assisted UAV millimeter-wave massive MIMO/FSO to improve system spectral efficiency. Firstly, the high-dimensional channel of RIS-assisted millimeter-wave massive MIMO/FSO in UAV is represented as a low-dimensional channel by tensor training decomposition. Secondly, the two-way gated recursive unit attention neural network model can effectively solve the FSO PE caused by UAV jitter, and the fast fading channel and Doppler frequency shift are estimated by the Fast Cyclic Tensor Power Method (FCTPM) based on tensor training decomposition. Finally, the RIS phase shift matrix is optimized by singular value decomposition. The hybrid beamforming and RIS phase-shift matrices were estimated by using the low-complexity phase extraction alternating minimization method to solve the beam misalignment problem. Simulation results show that by using the proposed method, the spectrum utilization rate is improved by 23.6% compared with other methods.

With the rise of social networks, more and more users share their location on social networks. This gives us a new perspective on the study of user movement patterns. In this paper, we solve the trajectory re-identification task by identifying human movement patterns and then linking unknown trajectories to the user who generated them. Existing solutions generally focus on the location point and the location point information, or a single trajectory, and few studies pay attention to the information between the trajectory and the trajectory. For this reason, in this paper, we propose a new model based on a contrastive distillation network, which uses a contrastive distillation model and attention mechanisms to capture latent semantic information for trajectory sequences and focuses on common key information between pairs of trajectories. Combined with the trajectory library composed of historical trajectories, it not only reduces the number of candidate trajectories but also improves the accuracy of trajectory re-identification. Our extensive experiments on three real-world location-based social network (LBSN) datasets show that our method outperforms existing methods.

Fire checking is indispensable for guaranteeing the fire safety of buildings as it reviews the compliance of the building with fire codes and regulations. Automated Compliance Checking (ACC) systems that check building data utilizing Building Information Modeling (BIM) against fire codes have emerged as an active field of research. Substantial efforts have focused on analyzing the properties of the building components. However, the analysis of the spatial geometric relationships of building components has received inadequate attention. The present study proposes a novel ACC system leveraging Natural Language Processing (NLP) techniques to review the spatial geometric relationships of building components in BIM models. First, a framework for a BIM-based ACC system is delineated and decomposes ACC into three constituent subtasks: building model parsing, code knowledge translation, and compliance check result reporting. Second, an approach for structured processing of spatial geometric stipulations in fire codes using NLP is presented to review the geometric relationships between components in building models. Finally, the system’s performance is assessed by testing fire code compliance across various building types utilizing BIM models. The empirical findings demonstrate that the system achieves superior recall compared with the manually formulated gold standard, with the ACC system enabling quick, accurate, and comprehensive automated compliance checking.

Reconfigurable intelligent surface (RIS)-assisted millimeter-wave (mmWave) communication systems relying on hybrid beamforming structures are capable of achieving high spectral efficiency at a low hardware complexity and with low power consumption. Tensor-based joint beamforming with low-cost ultrasonic and RIS-assisted Dual-Hop Hybrid free space optical (FSO) mm Wave massive Multiple Input Multiple Output (MIMO) of vehicle-to-everything (V2X) is proposed. To address the occlusion problem for high-speed mobility of the vehicle, an RIS-assisted mixed FSO-MIMO V2X system is proposed. The low-cost ultrasonic array signal model is developed to solve the accurate direction-of-arrival (DOA) estimation. The ultrasonic-assisted RIS phase shift matrix based on subspace self-organizing iterations is designed to track the beam direction between RIS and vehicle. Specifically, the associated bandwidth-efficiency maximization problem is transformed into a series of subproblems, where the subarray of phase shifters and RIS elements is jointly optimized to maximize each subarray’s rate. The vehicle motion state is transformed into a two-dimensional model for prior distribution to calculate the particle weights of the RIS phase. Multi-vehicle Tucker tensor decomposition is used to describe the high-dimensional beam space. We conceive a multi-vehicle joint optimization method for designing the hybrid beamforming matrix of the base station (BS) and the passive beamforming matrix of the RIS. A cascaded channel decomposition method based on Singular Value Decomposition (SVD) is used to obtain the combined matrix beamforming of BS and vehicle. Our simulation results demonstrate the superiority of the proposed method compared to its traditional counterparts.

Navigation networks are a common form of indoor map that provide the basis for a wide range of indoor location-based services, intelligent tasks for indoor robots, and three-dimensional (3D) geographic information systems. The majority of current indoor navigation networks are manually modeled, resulting in a laborious and fallible process. Building Information Modeling (BIM) captures design information, allowing for the automated generation of indoor maps. Most existing BIM-based navigation systems for floor-level wayfinding rely on well-defined spatial semantics, and do not adapt well to buildings with irregular 3D shapes, which can make cross-floor path generation difficult. This research introduces an innovative approach to generating 3D indoor navigation networks automatically from BIM data using image thinning, which is referred to as GINIT. Firstly, GINIT extracts grid-based maps for floors from BIM data using only two types of semantics, i.e., slabs and doors. Secondly, GINIT captures cross-floor paths from building components by projecting 3D forms onto a 2D image, thinning the 2D image to capture the 2D projection path, and crossing over the 2D routes with 3D routes to restore the 3D path. Finally, to demonstrate the effectiveness of GINIT, experiments were conducted on three real-world multi-floor buildings, evaluating its performance across eight types of cross-layer architectural component. GINIT overcomes the dependency of space definitions in current BIM-based navigation network generation schemes by introducing image thinning. Due to the adaptability of navigation image thinning to any binary image, GINIT is capable of generating navigation networks from building components with diverse 3D shapes. Moreover, the current studies on indoor navigation network extraction mainly use geometry theory, while this study is the first to generate 3D indoor navigation networks automatically using image thinning theory. The results of this study will offer a unique perspective and foster the exploration of imaging theory applications of BIM.

Simultaneous transmitting and reflecting reconfigurable intelligent surfaces (STAR-RISs) can reflect signals and transmissive signals simultaneously and can extend the coverage of signals. A conventional RIS mainly focuses on the case where the signal source and the target are on the same side. In this paper, a STAR-RIS-assisted non-orthogonal multiple access (NOMA) downlink communication system is considered to maximize the achievable rate for users by jointly optimizing the power-allocation coefficients, active beamforming, and STAR-RIS beamforming under the mode-switching (MS) protocol. The critical information of the channel is first extracted using the Uniform Manifold Approximation and Projection (UMAP) method. Based on the key extracted channel features, STAR-RIS elements and users are clustered individually using the fuzzy C-mean clustering (FCM) method. The alternating optimization method decomposes the original optimization problem into three sub-optimization problems. Finally, the sub-problems are converted to unconstrained optimization methods using penalty functions for the solution. Simulation results show that when the number of elements of RIS is 60, the achievable rate of the STAR-RIS–NOMA system is about 18% higher than that of the RIS–NOMA system.

The intercropping patterns of protected cultivations have been widely used to increase productivity and sustainability in modern agriculture. However, there have been few studies of wolfberry intercropping cultivated by clean tillage. We introduced 10 forages into wolfberry cultivation through land productivity and an interspecific competitiveness analysis, and we screened out the appropriate intercropping modes to provide a scientific basis for wolfberry green cultivation and pasture production. The results showed that the wolfberry–forage intercropping land equivalent ratio (LER) of greenhouse and field tests increased from 29% to 59% and from 62% to 170%, respectively, when compared with the monoculture weighted mean, showing significant yield advantages (p < 0.05), particularly in wolfberry–mangold, wolfberry–ryegrass, wolfberry–alfalfa, and wolfberry–clover. The aggressivity of interspecific competitiveness analysis showed that the forage introduction did not affect the dominant competitive position of wolfberry. In addition, wolfberry–forage intercropping could promote the monetary advantage index (MAI). Wolfberry–mangold, wolfberry–ryegrass, and wolfberry–alfalfa performed well, with MAI values of 827.63, 994.18, and 1918.57 for fruit and 2106.54, 1706.27, and 3103.13 for biomass, respectively. Finally, wolfberry–mangold, wolfberry–ryegrass, and wolfberry–alfalfa were screened out, which can form a new mode of wolfberry and forage production.

Capital outflow during industrialization and urbanization is a primary reason for global rural recession, and China is no exception. Since China focuses on the integrated development of urban and rural areas, urban-rural capital flow affects the transformation and sustainable development of rural areas. However, few studies have focused on this issue. Based on long-term field observations of Wufang Village in Shanghai, we established an analytical framework to describe how urban-rural capital flow promotes rural reconstruction. The research results show that the influx of urban industrial and commercial capital results in market-oriented organization and reconstruction focusing on land, industry, and capital: (1) Land-use optimization changes the land ownership and spatial structure of rural areas and improves the spatial value of rural areas. (2) Industrial development is focused on diverse development and the integration of primary, secondary, and tertiary industries in rural areas. (3) Capital investment is performed by a consortium of state-owned enterprises, private enterprises, and rural collective enterprises—which jointly invest, obtain revenue, and share profits—while considering the balance between attracting capital to rural areas and achieving independent development. The experience of Wufang Village has implications for the rural transformation policies of other large cities in China and other countries in Asia and Africa during urbanization.

BIM is one of the main technical ways to realize building informatization, and the model’s texture is essential to its style design during BIM construction. However, the texture maps provided by mainstream BIM software are not realistic enough and monotonous to meet the actual needs of users for the model style. Therefore, an interior furniture BIM style restoration method was proposed based on image retrieval and object location using convolutional neural network. First, two types of furniture images, namely grayscale contour images from BIM software and real images from the Internet, were collected to train the following network model. Second, a multi-feature weighted fusion neural network model based on an attention mechanism (AM-rVGG) was proposed, which focused on the structural information of furniture images to retrieve the most similar real image, and then some furniture image patches from the retrieved one were generated with object location and random cropping techniques as the candidate texture maps of the furniture BIM. Finally, the candidate ones were fed back into the BIM software to realize the restoration of the furniture BIM style. The experimental results showed that the average retrieval accuracy of the proposed network model was 83.1%, and the obtained texture maps could effectively restore the real style of the furniture BIM. This work provides a new idea for restoring the realism in other BIM.

Porous 2024Al-Al3Zr composites were prepared by in situ and spatial scaffolding methods. As the Al3Zr content increased from 5 wt.% to 30 wt.%, the binding of the powder in the pore wall increased and the defects in the composites decreased. The yield strength of the composites reached 28.11 MPa and the energy absorption capacity was 11.68 MJ/m3 at a Zr content of 20 wt.%, when the composites had the best compression and energy absorption performance. As the space scaffold content increased from 50% to 70%, the porosity of the composites then increased from 53.51% to 70.70%, but the apparent density gradually decreased from 1.46 g/cm3 to 0.92 g/cm3, leading to a gradual decrease in their compressive properties. In addition, by analysing the compression fracture morphology, the increase of Al3Zr will reduce the stress concentration and hinder the crack growth, while too much Al3Zr will lead to brittleness and reduce the performance.

The root of Millettia speciosa Champ. (MSCP) is used in folk medicine and is popular as a soup ingredient. The root is composed of the rhizome and radix, but only the radix has been used as a food. Thus, it is very important to compare the chemical components and antioxidant activities between the rhizome and radix. The extracts were analyzed by UHPLC-Q-Exactive Orbitrap-MS and multivariate analysis, and the antioxidant activities were evaluated by 2,20-azinobis (3-ethylbenzothiazo-line-6-sulfonic acid) diammonium salt (ABTS) and 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging assays. Ninety-one compounds were detected simultaneously and temporarily identified. Ten compounds were identified as chemical markers to distinguish the rhizome from the radix. The antioxidant activities of the radix were higher than the rhizome. Correlation analysis showed that uvaol-3-caffeate, 3-O-caffeoyloleanolic acid, and khrinone E were the main active markers for antioxidant activity, which allowed for the rapid differentiation of rhizomes and the radix. Therefore, it could be helpful for future exploration of its material base and bioactive mechanism. In addition, it would be considered to be used as a new method for the quality control of M. speciosa.

Mechanical, electrical, and plumbing (MEP) systems are crucial to a building, which directly affect the building safety, energy saving, and operational efficiency. Building information models (BIMs) help engineers to view the connection structure of MEP elements, reducing the time for reading drawings and training costs. However, existing MEP systems bring a tremendous challenge to monitoring due to issues with the complicated spatial structure, large scale, and intuitiveness. In addition, there is still a lack of feasible methods to model a representative graph in MEP systems. To address this problem, this study proposes an approach to model a directed representative graph of MEP systems using BIM data. The proposed approach contains two parts, the representative edge extraction and the direction identification. Firstly, MEP elements are converted into triangular meshes on which boundary points are extracted. Secondly, representative sets are developed to extract the representative points. Thirdly, representative points are connected to generate representative edges. Meanwhile, there are topological connection relationships among MEP elements and the flow directions of MEP ports, all of which are extracted to obtain the graph direction based on Industry Foundation Classes (IFC). Subsequently, representative edges and directions are combined to obtain the directed representative graph. Finally, experiments of directed representative graph extraction are evaluated on six BIM models. The experimental results show that directed representative graphs are extracted successfully. Furthermore, a simulated system is developed to integrate the directed representative graph and the Internet of Things (IoT) to realize the intelligent monitoring of MEP systems. The proposed directed representative graph model lays a solid foundation for the development of MEP systems monitoring management in smart buildings.

Indoor maps lay the foundation for most indoor location-based services (LBS). Building Information Modeling (BIM) data contains multiple dimensional computer-aided design information. Some studies have utilized BIM data to automatically extract 3D indoor maps. A complete 3D indoor map consists of both floor-level maps and cross-floor paths. Currently, the floor-level indoor maps are mainly either grid-based maps or topological maps, and the cross-floor path generation schemes are not adaptive to building elements with irregular 3D shapes. To address these issues, this study proposes a novel scheme to extract an accurate 3D indoor map with any shape using BIM data. Firstly, this study extracts grid-based maps from BIM data and generates the topological maps directly through the grid-based maps using image thinning. A novel hybrid indoor map, termed Grid-Topological map, is then formed by the grid-based maps and topological maps jointly. Secondly, this study obtains the cross-floor paths from cross-floor building elements by a four-step process, namely X-Z projection, boundary extraction, X-Z topological path generation, and path-BIM intersection. Finally, experiments on eight typical types of cross-floor building elements and three multi-floor real-world buildings were conducted to prove the effectiveness of the proposed scheme, the average accuracy rates of the evaluated paths are higher than 88%. This study will advance the 3D indoor maps generation and inspire the application of indoor maps in indoor LBS, indoor robots, and 3D geographic information systems.

Monopolar spindle 1 (Mps1), a dual-specific kinase, is related to the proper execution of chromosome biorientation and mitotic checkpoint signaling. The overexpression of Mps1 promotes the occurrence of cancer or the survival of aneuploid cancer cells, in other words, the reduction of Mps1 will severely reduce the viability of human cancer cells. Therefore, Mps1 is a potential target for cancer treatment. Recently, a series of novel pyrido [3,4-d] pyrimidine derivatives targeting Mps1 with high biological activity were synthesized. The crystal structure of Mps1 in complex with pyrido [3,4-d] pyrimidine derivatives was also reported, but there were no specific mechanism studies for this series of small molecule inhibitors. In this study, complexes binding modes were probed by molecular docking and further validated by molecular dynamics simulations and the molecular mechanics/generalized Born surface area (MM/GBSA) method. The results indicated that the van der Waals interactions and the nonpolar solvation energies were responsible to the basis for favorable binding free energies, all inhibitors interacted with residues I531, V539, M602, C604, N606, I607, L654, I663, and P673 of Mps1. By analyzing the hydrogen bonds, we found the residues G605 and K529 in Mps1 formed stable hydrogen bonds with compounds, it was more conducive to activities of Mps1 inhibitors. According to the above analysis, we further designed five new compounds. We found that compounds IV and V were better potential Mps1 inhibitors through docking and ADMET prediction. The obtained new insights not only were helpful in understanding the binding mode of inhibitors in Mps1, but also provided important references for further rational design of Mps1 inhibitors.

Efficient vehicle-to-everything (V2X) communications improve traffic safety, enable autonomous driving, and help to reduce environmental impacts. To achieve these objectives, accurate channel estimation in highly mobile scenarios becomes necessary. However, in the V2X millimeter-wave massive MIMO system, the high mobility of vehicles leads to the rapid time-varying of the wireless channel and results in the existing static channel estimation algorithms no longer applicable. In this paper, we propose a sparse Bayes tensor and DOA tracking inspired channel estimation for V2X millimeter wave massive MIMO system. Specifically, by exploiting the sparse scattering characteristics of the channel, we transform the channel estimation into a sparse recovery problem. In order to reduce the influence of quantization errors, both the receiving and transmitting angle grids should have super-resolution. We obtain the measurement matrix to increase the resolution of the redundant dictionary. Furthermore, we take the low-rank characteristics of the received signals into consideration rather than singly using the traditional sparse prior. Motivated by the sparse Bayes tensor, a direction of arrival (DOA) tracking method is developed to acquire the DOA at the next moment, which equals the sum of the DOA at the previous moment and the offset. The obtained DOA is expected to provide a significant angle information update for tracking fast time-varying vehicular channels. The proposed approach is evaluated over the different speeds of the vehicle scenarios and compared to the other methods. Simulation results validated the theoretical analysis and demonstrate that the proposed solution outperforms a number of state-of-the-art researches.

In recent decades, global social and economic development has resulted in substantial land-use transitions. This was first observed with respect to losses of forested land, attracting worldwide concern. Forest transitions have an important impact on global ecology, whilst farmland transitions are key in terms of global food security. However, research into farmland transitions is lacking, particularly with respect to mechanistic analysis. Using data on China’s farmland areas between 1950 and 2017, we investigated the transitional characteristics, and triggers, of farmland change through linear regression analysis. Furthermore, based on the Advocacy Coalition Framework, we reveal the internal mechanism of these transitions. Our main findings are as follows: (1) between 1950 and 2017, China’s farmland area exhibited significant growth, and there were two transitions, namely in 1984 and 2004; (2) macroscopic economic and social changes determine the overall evolution of the farmland area; (3) there were two advocacy coalitions in the farmland transition policy subsystem—the farmland supplement and farmland consumption coalitions; (4) under the influence of macroscopic economic and social development, external events play a catalytic role in the transitions, and relatively stable parameters have an indirect but lasting effect in terms of transition outcomes.