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In this paper, we choose some methods to study the spatial distribution, such as the standard ellipse method, kernel density estimation method, spatial autocorrelation analysis, topographic position index, geographic connection, and other mathematical models to analyze the distribution of Dong wind and rain bridges in northern Guizhou. In order to analyze the construction wisdom of Dong wind and rain bridges, this paper designs a function with wind and rain bridge images as the target and constructs a convolutional neural network-based wind and rain bridge image generation model by encoding and decoding the defined target and adjusting the hyperparameters. After analysis, 21 Dong villages in northern Gui are distributed in the range of 122~749m above sea level, with an average altitude of 385.19m and a kernel density index of 0.3. The model value of this paper can reach up to about 6.2, which can clearly generate images of wind and rain bridges, and then analyze the construction wisdom of wind and rain bridges.

Abstract Ancient Chinese books are of great significance to historical research and cultural inheritance. Unfortunately, many of these books have been damaged and corroded in the process of long-term transmission. The restoration by digital preservation of ancient books is a new method of conservation. Traditional character restoration methods ensure the visual consistency of character images through character features and the pixels around the damaged area. However, reconstructing characters often causes errors, especially when there is large damage in critical locations. Inspired by human’s imitation writing behavior, a two-branch structure character restoration network EA-GAN (Example Attention Generative Adversarial Network) is proposed, which is based on a generative adversarial network and fuses reference examples. By referring to the features of the example character, the damaged character can be restored accurately even when the damaged area is large. EA-GAN first uses two branches to extract the features of the damaged and example characters. Then, the damaged character is restored according to neighborhood information and features of the example character in different scales during the up-sampling stage. To solve problems when the example and damaged character features are not aligned and the convolution receptive field is too small, an Example Attention block is proposed to assist in restoration. Qualitative and quantitative analysis experiments are carried out on a self-built dataset MSACCSD and real scene pictures. Compared with current inpainting networks, EA-GAN can get the correct text structure through the guidance of the additional example in the Example Attention block. The peak signal-to-noise ratio (PSNR) and the structural similarity (SSIM) value increased by 9.82% and 1.82% respectively. The learned perceptual image patch similarity (LPIPS) value calculated by Visual Geometry Group (VGG) network and AlexNet decreased by 35.04% and 16.36% respectively. Our method obtained better results than the current inpainting methods. It also has a good restoration effect in the face of untrained characters, which is helpful for the digital preservation of ancient Chinese books.

The rural cultural space, though enhanced by policies like rural revitalization, faces challenges such as weakened cultural inheritance, insufficient depth, and homogenous planning. This study, focusing on Ping'an Village in Longsheng County, Guangxi, utilizes local knowledge theory to analyze and address these issues. The aim is to propose a development strategy for improving the cultural space system, enhancing cultural potential, and refining the mechanism system. This research aspires to offer insights for the protection and development of cultural spaces in other villages.

To enable personalized medicine, it is important yet highly challenging to accurately predict disease-causing mutations in target proteins at high throughput. Previous computational methods have been developed using evolutionary information in combination with various biochemical and structural features of protein residues to discriminate neutral vs. deleterious mutations. However, the power of these methods is often limited because they either assume known protein structures or treat residues independently without fully considering their interactions. To address the above limitations, we build upon recent progress in machine learning, network analysis, and protein language models, and develop a sequences-based variant site prediction workflow based on the protein residue contact networks: 1. We employ and integrate various methods of building protein residue networks using state-of-the-art coevolution analysis tools (RaptorX, DeepMetaPSICOV, and SPOT-Contact) powered by deep learning. 2. We use machine learning algorithms (Random Forest, Gradient Boosting, and Extreme Gradient Boosting) to optimally combine 20 network centrality scores to jointly predict key residues as hot spots for disease mutations. 3. Using a dataset of 107 proteins rich in disease mutations, we rigorously evaluate the network scores individually and collectively (via machine learning). This work supports a promising strategy of combining an ensemble of network scores based on different coevolution analysis methods (and optionally predictive scores from other methods) via machine learning to predict hotspot sites of disease mutations, which will inform downstream applications of disease diagnosis and targeted drug design. [ABSTRACT FROM AUTHOR]

Mibavademab (previously known as REGN4461), a fully human monoclonal antibody, is being investigated for the treatment of conditions associated with leptin deficiency. Here, we report pharmacokinetics (PKs), pharmacodynamics, and immunogenicity from a phase I study in healthy participants (NCT03530514). In part A, lean or overweight healthy participants were randomized to single‐ascending‐dose cohorts of 0.3, 1.0, 3.0, 10, and 30 mg/kg intravenous (i.v.), or 300 and 600 mg subcutaneous doses of mibavademab or placebo. In part B, overweight or obese participants were randomized to receive multiple doses of mibavademab (15 mg/kg i.v. loading dose and 10 mg/kg i.v. at weeks 3, 6, and 9) or placebo, stratified by body mass index and baseline leptin levels: low leptin (<5 ng/mL) or relatively low leptin (5–8 ng/mL in men and 5–24 ng/mL in women). Fifty‐six and 55 participants completed the single‐ascending‐dose and multiple‐dose parts, respectively. In the single‐ascending‐dose cohorts, mibavademab PKs were nonlinear with target‐mediated elimination, greater than dose‐proportional increases in exposure, and there were no dose‐dependent differences in total soluble leptin receptor (sLEPR) levels in serum over time. Following multiple‐dose administration of mibavademab in participants with leptin <8 ng/mL, lower mean mibavademab concentrations, higher mean total sLEPR concentrations, and larger mean decreases in body weight than in the relatively low leptin cohorts were observed. Baseline leptin was correlated with mibavademab PKs and pharmacodynamics. No treatment‐emergent anti‐mibavademab antibodies were observed in any mibavademab‐treated participant. Results from this study collectively inform further development of mibavademab to treat conditions associated with leptin deficiency. [ABSTRACT FROM AUTHOR]

Rural landscape heritage faces issues of landscape character homogenization and unclear protection boundaries. We propose combining landscape character assessment (LCA) methods to identify the characteristics and areas of heritage, aiming to preserve the diversity and integrity of the landscape. This paper focuses on the Li River Basin as the study area, presenting a method for identifying characteristics and areas of rural landscape heritage. It is divided into four steps: selection and spatial scope identification of rural landscape heritage, identification of natural character areas, identification of cultural character areas, and identification and analysis of character areas of rural landscape heritage. Firstly, cultural relic units, traditional villages, and intangible cultural heritage as sources of rural landscape heritage were selected by utilizing the Minimum Cumulative Resistance model (MCR) to calculate the spatial scope of rural landscape heritage. Secondly, clustering and automatic partition methods were employed to classify the Li River Basin into four types of natural character areas. Thirdly, cultural core areas and buffer areas were determined based on the heritage source hierarchy and cultural features. Fourthly, by overlaying heritage spatial ranges, natural character areas, and cultural character areas, 2 levels of heritage areas, 7 types of heritage cultural areas, and 43 heritage character units were obtained. This method not only provides a comprehensive framework for the identification of characteristics and areas for rural landscape heritage but also enhances the integrity of data selection in landscape character assessment methods at the cultural level. [ABSTRACT FROM AUTHOR]

The Longshou Shan, located in western China, plays a crucial role in connecting the Tarim Continent with the North China Craton. It provides valuable insights into the Cenozoic intracontinental deformation, the complex dynamics of Eurasian tectonics, and the relationship between the pre-Cenozoic Tethys and Central Asian orogenic systems. Consequently, comprehending the evolution of the Phanerozoic era in this region holds immense significance. Zircon (U-Th)/He (ZHe) dating was conducted on three granite samples (n = 18) collected from the Longshou Shan. The ZHe dates of these granite rocks range from 7.2 to 517.7 Ma, showing a negative correlation with eU values. Furthermore, a limestone sample from the Longshou Shan yielded ZHe (n = 4) ages of 172.0–277.1 Ma and AHe (n = 4) ages of 17–111.9 Ma. The area has undergone complex tectonic processes involving multiple phases of uplift and burial. Using both forward and inverse modeling methods, we aim to establish plausible thermal histories. Our models reveal: (1) Late Paleozoic unroofing; (2) Early Mesozoic cooling and Late Mesozoic regional stabilization; and (3) Cenozoic reheating and subsequent cooling. By investigating the intricate thermal history of the Longshou Shan through multi-method modeling, we compare different approaches and assess the capabilities of single ZHe dating for understanding a thermal history. This research contributes to unraveling the region's geological complexities and aids in evaluating various modeling methods. [ABSTRACT FROM AUTHOR]

Aspect-based sentiment analysis (ABSA) aims to automatically identify the sentiment polarity of specific aspect words in a given sentence or document. Existing studies have recognised the value of interactive learning in ABSA and have developed various methods to precisely model aspect words and their contexts through interactive learning. However, these methods mostly take a shallow interactive way to model aspect words and their contexts, which may lead to the lack of complex sentiment information. To solve this issue, we propose a Lightweight Multilayer Interactive Attention Network (LMIAN) for ABSA. Specifically, we first employ a pre-trained language model to initialise word embedding vectors. Second, an interactive computational layer is designed to build correlations between aspect words and their contexts. Such correlation degree is calculated by multiple computational layers with neural attention models. Third, we use a parameter-sharing strategy among the computational layers. This allows the model to learn complex sentiment features with lower memory costs. Finally, LMIAN conducts instance validation on six publicly available sentiment analysis datasets. Extensive experiments show that LMIAN performs better than other advanced methods with relatively low memory consumption. [ABSTRACT FROM AUTHOR]

Under the policy of cultural tourism integration, the huge economic and social benefits brought by night tourism are gradually recognized. Based on the compatibility, in response to the needs of cultural heritage protection and night tourism development in the Southwest Dong area, a driving mechanism for night tourism and cultural heritage live protection with the spirit of place as the core is proposed. Taking the Huangdu Dong Village in Hunan as an example, the research explored the traditional night culture of Dong Village, analysed the development status of night tourism, and proposed interactive development strategies for Dong Village night tourism and cultural heritage protection, which will help the destination resource allocation shift from space expansion to time expansion and accelerate its innovative development on the basis of the protection of the authenticity of cultural heritage. The research has certain reference significance for the survival of traditional culture and the innovative development of tourism in ethnic minority villages.

Healthy living space is the guarantee of high quality of life, dong Village is one of the few minority living space environment adaptation wisdom of the living carrier. By virtue of its healthy ecosystem and the smart wisdom of residents, it is connected with or adapted to the natural environment to create a healthy and livable living space under low-technology conditions. Taking The Gaoxiu Dong Village as the research object, this paper analyzes the environmental adaptation wisdom of the spatial elements such as road system, drum tower space and residential building in Gaoxiu Dong Village, so as to show the spatial form beauty, functional practical beauty and national characteristic beauty of Dong Village. From the perspective of health, it analyzes the adaptive form and mode of human living space, and inherits the wisdom of building with respect to nature and environment.

To overcome the disadvantages of the MoS2 anode for LIBs in terms of low intrinsic conductivity, poor mechanical stability, and adverse reaction with electrolytes, a 3D multilevel heterostructure (VANS-MoS2-CNTs) has been successfully prepared by a simple hydrothermal method followed by thermal treatment. VANS-MoS2-CNTs are made up of 2D vertically aligned MoS2 nanosheets (VANS) and 1D sandwich C-MoS2-C nanotubes (CNTs). The sandwich-like nanotube is the core part, which is made up of the MoS2 nanotube covered by carbon layers on both side surfaces. Due to the special heterostructure, VANS-MoS2-CNTs have good conductivity, high structured stability, and excellent Li+/electron transport, resulting in high discharge capacity (1587 mAh/g at a current density of 0.1 A/g), excellent rate capacity (1330 and 730 mAh/g at current densities of 0.1 and 2 A/g, respectively), and good cyclic stability (1270 mAh/g at 0.1 A/g after 100 cycles). [ABSTRACT FROM AUTHOR]

We investigate the present‐day strike‐slip faulting and intracontinental deformation of North China using horizontal GPS velocities and a block modeling strategy. The data demonstrate that the fault slip rates and block rotations in North China can be better constrained using GPS velocities where the influence of groundwater extraction has been reduced by applying median spatial filtering of the velocity field. The modeled senses of motion and slip rates on active faults are generally in good agreement with the geological estimates. The left‐lateral slip rate along the boundary fault of Weihe Graben is apparently lower than the differential motion between the South China Block and Ordos Block. The missing left‐lateral slip is accommodated by the counterclockwise rotation of the Ordos Block. The sinistral slip rate along the eastern segment of the Altyn Tagh‐Haiyuan‐Qinling fault system decreases eastward from ∼1.0 to ∼0 mm/yr, much slower than that expected in the fast eastward extrusion hypothesis. We interpret the systematic counterclockwise rotation of blocks and left/right‐lateral faulting in North China to be driven both by the left‐lateral shear between the South China Block to the south and Yinshan‐Yanshan Block to the north and a push from the Tibetan Plateau on the southwestern margin of the Ordos Block. Plain Language Summary: North China is in a complex tectonic regime with all types of faults (strike‐slip, normal, and thrust faults) around its margins and internal blocks rotating counterclockwise. Why and how such a complex deformation occurs in North China is a crucial scientific question but unsolved. Based on the newly improved GPS data, we quantitatively determined the present‐day fault slip rates and block rotations in and around North China. Our research indicates a low left‐lateral slip rate (0–1.0 mm/yr) along faults between North China and South China, in contrast to much faster values (8 to >10 mm/yr) given in previous studies and expected by the continental escape hypothesis. Therefore, we propose that the complex tectonic deformation in North China is mainly driven by both left‐lateral shear between South China and Yinshan‐Yanshan Block and an eastward push from the Tibetan Plateau at the southwestern margin of the Ordos Block in western North China. Key Points: Geodetic data are used to obtain fault slip rates on North China using a carefully regularized block model and noise‐reduced GPS velocitiesLeft‐lateral slip rate at the eastern termination of the South China Block extrusion boundary decreases eastward from ∼1.0 to ∼0 mm/yrRight‐later shear in the Shanxi Graben results from a combination of block rotations and relative motions [ABSTRACT FROM AUTHOR]

Borehole shrinkage and collapse are likely to occur when downhole testing is conducted in soft or loose sandy soils, resulting in testing interruption. To prevent this situation from occurring, installing casing in the borehole is a common approach. However, in actual testing, the quality of the signal obtained from measuring points within the depth of the casing is often not ideal, and there is still no clear and unified justification for the causes of interference generated by the casing. Therefore, the team attempt to investigate and elucidate the impact of casing through on-site experiments and numerical simulations. Firstly, on-site tests on the impact of different materials of casing on the wave velocity test utilizing the downhole method are conducted, the waveform characteristics of the measurement points inside the PVC casing and steel casing boreholes are analyzed, and the usability of the test results are evaluated. Next, the contact state between shallow soil and casing is changed, and its impact on the waveform characteristics of signal at different depth measurement points is analyzed. Then, the ABAQUS finite element software is utilized to establish a three-dimensional finite element model for wave velocity testing using the casing method, and the dynamic response of the measuring points on the casing wall inside the hole under surface excitation is solved. By numerically simulating different casing materials, the contact state between the casing and the hole wall, and the presence of low wave velocity filling soil around the casing, the variation patterns of the affected measurement point signals in the time and frequency domains are investigated. Furthermore, combined with the measured data, the impact characteristics of the casing on the results of the wave velocity testing using the downhole method are systematically explored. This research can provide some insights for the application and data interpretation of signals in the downhole methods of cased wells. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) scholars and mediciners have reported AI systems that accurately detect medical imaging and COVID-19 in chest images. However, the robustness of these models remains unclear for the segmentation of images with nonuniform density distribution or the multiphase target. The most representative one is the Chan-Vese (CV) image segmentation model. In this paper, we demonstrate that the recent level set (LV) model has excellent performance on the detection of target characteristics from medical imaging relying on the filtering variational method based on the global medical pathology facture. We observe that the capability of the filtering variational method to obtain image feature quality is better than other LV models. This research reveals a far-reaching problem in medical-imaging AI knowledge detection. In addition, from the analysis of experimental results, the algorithm proposed in this paper has a good effect on detecting the lung region feature information of COVID-19 images and also proves that the algorithm has good adaptability in processing different images. These findings demonstrate that the proposed LV method should be seen as an effective clinically adjunctive method using machine-learning healthcare models. [ABSTRACT FROM AUTHOR]

Minority settlements have good local landscape features and rich cultural heritage. However, due to complex geographical conditions and lagging economic development, there are many potential security threats in their human settlements. Based on the landscape ecological security pattern theory, aiming at eliminating the practical dilemma of frequent fires and difficult rescue in mountainous settlements in southwestern China, this paper proposes a planning idea to improve the settlement environment’s own disaster resilience and ecological endurance ability through the adjustment of landscape pattern. Taking the reconstruction planning and design of Xiaozhai Village in Longji of Guangxi province as an example, based on the geographical structure and resource characteristics of the village, a four-in-one landscape fire security pattern for mountain settlement is constructed, including building group, road evacuation system, natural fire protection network of water system and biological fire protection forest belt. The study provides a reference for the protection, renewal and re-planning of minority settlement.