Search

Existing counting models predominantly operate on a specific category of objects, such as crowds and vehicles. The recent emergence of multi-modal foundational models, e.g. , Contrastive Language-Image Pre-training (CLIP), has facilitated class-agnostic counting. This involves counting objects of any given class from a single image based on textual instructions. However, CLIP-based class-agnostic counting models face two primary challenges. Firstly, the CLIP model lacks sensitivity to location information. It generally considers global content rather than the fine-grain location of objects. Therefore, adapting the CLIP model directly is suboptimal. Secondly, these models generally freeze pre-trained vision and language encoders, while neglecting the potential misalignment in the constructed hypothesis space. In this paper, we address these two issues in a unified framework termed Deep Spatial Prior Interaction (DSPI) network. The DSPI leverages the spatial-awareness ability of large-scale pre-trained object grounding models, i.e., Grounding DINO, to incorporate spatial location as an additional prior for a specific query class. This enables the network to be more specifically focused on the precise location of the objects. Additionally, to align the feature space across different modalities, we tailor a meta adapter that extracts textual information into an object query. This serves as an instruction for cross-modality matching. These two modules collaboratively ensure the alignment of multi-modal representations while preserving their discriminative nature. Comprehensive experiments conducted on a diverse set of benchmarks verify the superiority of the proposed model. The code is available at https://github.com/jinyongch/DSPI. • Integrate pre-trained multi-modal grounding model for spatial priors to enhance the attentiveness of vision encoder to specific object regions. • Tackle the misalignment issue between textual instructions and visual representations using the designed meta adapter to extract instructive descriptors from the text and transform them into an object query. • Demonstrate that DSPI model can extract distinctive representations aligned across various modalities, while also incorporating precise spatial information, to improve the generalization capability of counting model. [ABSTRACT FROM AUTHOR]

Three-Dimensional (3D) Massive multiple-input-multiple-output (MIMO) is a new and impressive concept. The beamforming in elevation and azimuth domains can reduce computational complexity as well as improve bandwidth efficiency. In this paper, we consider the application of a 3D massive MIMO system to connect (Internet of Things) IoT edge network. 3D massive MIMO system can support multiple single-antenna IoT devices simultaneously using the same time-frequency resources. Furthermore, an improved regularized zero-forcing precoding for 3D massive MIMO systems has been proposed. The precoding scheme is specifically designed for single-cell systems with imperfect channel state information. We provide complete mathematical modelling for the proposed scheme. We compare our proposed scheme with conventional zero-forcing and regularized zero-forcing in a large antenna regime. We provide simulations for bandwidth efficiency with respect to different parameters such as the number of antennas, angular spread, and cumulative distribution function. The simulation results show that the proposed scheme performs better than conventional schemes in terms of achievable rates as the number of antenna increase. Our proposed scheme can help to connect maximum IoT devices with improved bandwidth efficiency [ABSTRACT FROM AUTHOR]

Summary: Vehicular connectivity is a significant key contribution in vehicular ad‐hoc networks (VANETs). The inherent high dynamicity of vehicles is a serious challenge that affects automotive connectivity and disrupts inter‐vehicle communications stability. Vehicle‐to‐everything (V2X) communication enables vehicles to connect to any other networks and facilitates the evolutionary trend of automotive innovations toward autonomous internet‐enabled intelligent vehicles. In this article, we provide a systematic literature review (SLR) for vehicular connectivity and V2X communications by investigating 58 research articles from 2018 to 2023 in VANETs. We propose six fundamental research questions (RQs) and a taxonomy to systematize the study of the baseline articles and answer the crucial RQs. This SLR can be helpful for researchers as a complete study focusing on V2X analysis, making it possible to achieve Technical Aspects and New challenges. [ABSTRACT FROM AUTHOR]

Carbonized pollen grains of Typha (CPT) were widely used in clinical for antithrombosis, wound and bleeding in China. In order to ensure the role of drugs, it is very important to control the quality of drugs. However, there is a lack of monitoring methods in the process of charcoal preparation. To characterize the process of CPT, we used thermal analysis, scanning electron microscope (SEM), color measurement, Fourier transform infrared spectrometry (FTIR) and HPLC. In this study, 7 min was the optimal processing time and the heating process condition should be controlled under 272.35 ± 7.23 °C. This comprehensive strategy to depict the whole carbonizing process would provide new ideas for researches on quality control of Traditional Chinese Medicine (TCM) and processing theory of charcoal medicine. [ABSTRACT FROM AUTHOR]

Regional land subsidence is an integrated systematic issue related to multidisciplinary andbeing of global focus, and has been being a serious threat to the urban infrastructure,high-speed railway and the utilization of underground space, and restricting the sustainabledevelopment of society. The study of the regional subsidence evolution in Beijing Plain is ofgreat significance: it is necessary to reveal the regional land subsidence evolution law underthe background of Integration of Beijing-Tianjin-Hebei and the South-to-NorthWater Diversion. Furthermore, it can help to realize the scientific regulation ofregional subsidence and ensure the sustainable development of regional economy andsociety, which has a special significance and application prospect. Therefore theMT-InSAR method is used to obtain the regional ground subsidence time seriesinformation of the study area in three periods: Jun. 2003 ∼ Aug. 2010, Oct. 2010 ∼ Nov.2015, and May. 2015 ∼ Jun. 2018. Then equations are established based on thetime-overlapping information to complete the fusion of multi-platform time series, theinconsistence between different reference points is solved, simultaneously. Theresults show that, the maximum subsidence values in Beijing Plain are 690.6 mm,649.2 mm and 411.7 mm during the three periods, with maximum deformationrates of 100.6 mm/a, 130.0 mm/a and 142.3 mm/a, respectively. For the spatialdistribution and the evolution of the land subsidence field, the weighted spatialkernel density analysis, profile analysis, trend-surface analysis and profile-gradientanalysis are used to analyze the spatial-temporal evolution characteristics of theland subsidence field. In this case, land subsidence in Beijing Plain are thoroughlyanalyzed overall distribution characteristics and evolution process. Nine subsidencecenters are identified and the subsidence centers are connecting to form a mainsubsidence area in the northern part of Beijing Plain. The spatial clustering degree ofthe subsidence in the Beijing Plain indicates an overall heterogeneity in spatial.Moreover, the northern subsidence areas spread along the Nankou-Sunhe fault, and iscut into several subsidence centers by active faults, indicating that the regionalgeological structure has obvious control effect on the spatial distribution of landsubsidence areas. The evolution of the subsidence field: the northern subsidence areasspread along the northwest-southeast direction, and then expands to both the east andwest sides. Then through the distribution of subsidence areas and groundwaterfunnel, the InSAR based time series and the monitoring well based groundwater levelchanges, the correlations in spatial and responses between land subsidence field andgroundwater flow field are analyzed. The results show that the subsidence centerin the northern Beijing Plain is consistent with the groundwater drop funnel inspatial, with a similar downward trend over the whole observation time. Through theanalysis of well based results located in different areas, the long term groundwaterexploitation in the northern subsidence area has led to the continuous decline ofthe water level, resulting in the inelastic and permanent compaction; while for themonitoring wells located outside the subsidence area, the subsidence time seriesshow obvious elastic deformation characteristics as the groundwater level changes. [ABSTRACT FROM AUTHOR]

Crowd counting in congested scenes is a crucial yet challenging task in video surveillance and urban security system. The performance of crowd counting has been greatly boosted with the rapid development of deep learning. However, robust crowd counting in high-density environment with scale variations remains under-explored. To address this problem, we propose a dual attention-aware network ( DA 2 Net) for robust crowd counting in dense crowd scene with scale variations. Specifically, the DA 2 Net consists of two modules, namely Spatial Attention (SA) module and Channel Attention (CA) module. The SA module focuses on the spatial dependencies in the whole feature map to locate the heads accurately. The CA module attempts to handle the relations between channel maps and highlights the discriminative information in specific channels. Thus, it alleviates the mistaken estimation for background regions. The interactions between SA module and CA module provide the synergy which facilitates the learning of discriminative features with a focus on the essential head region. Experimental results on five benchmark datasets, i.e., ShanghaiTech, UCF_CC_50, UCF-QNRF, WorldExpo'10, and NWPU, demonstrate that the DA 2 Net can achieve the state-of-the-art performance on both accuracy and robustness. [ABSTRACT FROM AUTHOR]

To reveal the high-resolution atmospheric and statistical characteristics of haze events within the boundary layer (BL) in different months, this study conducted a combined detection experiment using a wind-profiling radar, a microwave radiometer, and an ambient particulate monitor on 1230 haze events occurring at Xianyang Airport from 2016 to 2021. First, the boundary layer heights (BLHs) of the haze events were calculated using the atmospheric refractive index structure constant, wind direction and speed, and these were verified against reanalysis data from ERA-Interim. Spatial–temporal evolution and statistical characteristics of temperature, and relative humidity and horizontal wind during haze events, were then analyzed. Finally, the relationships between the BLH and AQI (air quality index) and PM 2.5 during the haze events were analyzed. The results indicate that the average BLHs during haze events at Xianyang Airport were generally lower than 1000 m. Moreover, the average BLHs in December and January were distributed in the range of 200–600 m, and lower than that in June and July, in a range of 500–1100 m. Furthermore, the maximum value of the average BLH appears at 13:00–15:00. When the temperature was low in the morning, the stratification difference was small and the sensible heat flux between ground and air was still weak, leading to a low BLH value. Meanwhile, when the air quality was poor, the relative humidity was relatively large, and the corresponding AQI and PM 2.5 were very large. Subsequently, when the temperature gradually increased with time, the heat flux and the average BLH also gradually increased. Moreover, the relative humidity within the BL decreased, and the corresponding AQI and PM 2.5 also gradually decreased, with the corresponding air quality improving accordingly. The results obtained herein provide a key reference for the preparedness of haze events. [ABSTRACT FROM AUTHOR]

Biodegradable films are considered ideal alternatives to polyethylene films because of their advantages in increasing crop yield and controlling soil pollution. However, the influences of biodegradable film mulching on soil physicochemical environments and water productivity after long-term mulching remain poorly understood. Therefore, a field experiment after long-term mulching (since 2016) was conducted to explore the effects of black biodegradable film (BB), transparent biodegradable film (TB), and traditional polyethylene film (PE) on soil physicochemical environments, aboveground biomass accumulation, grain yield, evapotranspiration, and water productivity (WP) of maize in the 2021 and 2022 in the North China Plain. The results showed that polyethylene films and biodegradable films had a similar ability to preserve soil moisture, promote maize growth, reduce evapotranspiration, and increase WP. Moreover, the performances of BB were more equivalent to PE, and there was no significant difference on WP and yield under BB and PE. Compared with traditional flat planting without mulching (CK), BB and PE significantly increased yield (9.5 % and 12.7 % in 2021; 5.25 % and 6.37 % in 2022) and WP (11.54 % and 21.47 % in 2021; 24.28 % and 23.42 % in 2022). Film mulching treatments increased the soil organic carbon sequestration rate, and the content of soil organic carbon, microbial activity, and urease activity in the 0–20 cm soil layer compared with CK. According to structural equation modeling, the increasing soil water storage because of films mulching positively influenced yield by enhancing enzyme activities which were related to soil nutrients. Over all, these results showed that black biodegradable film is an ideal replacement for polyethylene films under long-term mulching conditions because of its comparable agronomic performance and influence on soil physicochemical environments in the North China Plain. • Long-term biodegradable film mulching (BDM) significantly impacted soil structure. • The effects of long-term BDM on soil physicochemical environments were similar to PE. • Effects of BDM and PE on the maize production were determined after long-term mulching. • The BDM and PE increased yield through affecting soil physicochemical environments. • Agronomic performance of the black BDM was more similar to PE than transparent BDM. [ABSTRACT FROM AUTHOR]

Remote sensing (RS) image dehazing holds significant importance in enhancing the quality and information extraction capability of RS imagery. The enhancement in image dehazing quality has progressively advanced alongside the evolution of convolutional neural network (CNN). Due to the fixed receptive field of CNN, there is insufficient utilization of contextual information on haze features in multi-scale RS images. Additionally, the network fails to adequately extract both local and global information of haze features. In addressing the above problems, in this paper, we propose an RS image dehazing network based on multi-scale large kernel convolution and hybrid attention (MKHANet). The network is mainly composed of multi-scale large kernel convolution (MSLKC) module, hybrid attention (HA) module and feature fusion attention (FFA) module. The MSLKC module fully fuses the multi-scale information of features while enhancing the effective receptive field of the network by parallel multiple large kernel convolutions. To alleviate the problem of uneven distribution of haze and effectively extract the global and local information of haze features, the HA module is introduced by focusing on the importance of haze pixels at the channel level. The FFA module aims to boost the interaction of feature information between the network's deep and shallow layers. The subjective and objective experimental results on on multiple RS hazy image datasets illustrates that MKHANet surpasses existing state-of-the-art (SOTA) approaches. The source code is available at https://github.com/tohang98/MKHA_Net. • Multi-scale large kernel convolution is introduced to enhance the effective receptive field. • Hybrid attention is used to enhance the extraction of features. • The feature fusion attention is used to enhance the interaction between different levels of the network layers. [ABSTRACT FROM AUTHOR]

Land subsidence is the ground surface response to underground space development, utilization and evolution. Presently, land subsidence has developed into a global, comprehensive and interdisciplinary complex systems problem. More than half a century has passed since the discovery of subsidence in the Beijing Plain in the 1960s. In this study, we investigate the land subsidence in the Beijing Plain over the period of 2003–2015 using ENVISAT ASAR and RADARSAT-2 interferometric datasets and the small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) technique. Furthermore, we introduced the data field model and index-based built-up index (IBI) to obtain the dynamic and static load information of the Beijing Plain. Then, based on a machine learning method, we selected the gradient lifting decision tree (GBDT) model to quantitatively analyze the contributions of groundwater level change, compressible deposit thickness and dynamic and static loads to land subsidence. The results showed that the maximum land subsidence rate was 122 and 141 mm/year in 2003–2010 and 2010–2015, respectively. Comparisons between the SBAS-InSAR results and leveling measurements showed that the minimum absolute error achieved was only 0.2 mm/year. We suggest that the groundwater exploitation in the third confined aquifer has greater impacts on land subsidence in the Beijing Plain than the other factors. The land subsidence likely occurred in compressible deposit thicknesses exceeding 90 m. Moreover, we found that the compressible thickness and groundwater level contributions to land subsidence exceeded 60%. Our results provide a scientific basis for the regulation and control of regional land subsidence. Unlabelled Image • The causes of land subsidence in Beijing Plain are complex. • The maximum land subsidence rate is 122 and 141 mm/year in 2003–2010 and 2010–2015. • The dynamic load by using a spatial data mining method of data field model. • The third confined aquifer groundwater has greater impacts on land subsidence. • Compressible thickness and groundwater contribution to land subsidence exceed 60%. [ABSTRACT FROM AUTHOR]

Highlights • The subsidence center was always located in the southeast of Chaoyang District 2011-2015, in Beijing, China. • The exploitation the second and the third confined aquifers had great impacts on the settlement development in Beijing. • The lag time between land subsidence and the groundwater level changes in the main exploration aquifer layers was 0.57–1.76 months. Abstract Land subsidence is rapidly developing across the Beijing Plain, China. Long-term intense overexploitation of groundwater is the main reason for land subsidence in Beijing. In this study, an optimized Small Baseline Subset (SBAS) interferometry method was developed to process 46 RADATSAT-2 images from 2011 to 2015 to investigate the spatial and temporal dynamics of land subsidence in the Beijing Plain. The lag time between land subsidence and groundwater exploitation was first analyzed by the Continuous Wavelet Transform (CWT) and Cross Wavelet Transform (XWT) methods Our study found that the maximum subsidence rate reached 141 mm per year. The analysis of the areas and volumes of the annual subsidence rates indicated that the overall deformation trend slowed down from 2011 to 2015. Our results indicate that the subsidence center is always located in the southeast of Chaoyang District from 2011 to 2015. The lag time between the observed subsidence and the groundwater level drops in the main exploration aquifer layers was 0.57–1.76 months. This information is helpful to reveal the mechanism of land subsidence and build hydrogeological model. [ABSTRACT FROM AUTHOR]

Tumor cell extravasation across endothelial barrier has been recognized as a pivotal event in orchestrating metastasis formation. This event is initiated by the interactions of extravasating tumor cells with endothelial cells (ECs). Therefore, targeting the crosstalk between tumor cells and ECs might be a promising therapeutic strategy to prevent metastasis. In this study, we demonstrated that Rh1, one of the main ingredients of ginseng, hindered the invasion of breast cancer (BC) cells as well as diminished the permeability of ECs both in vitro and in vivo, which was responsible for the attenuated tumor cell extravasation across endothelium. Noteworthily, we showed that ECs were capable of inducing the epithelial-mesenchymal transition (EMT) and invadopodia of BC cells that are essential for tumor cell migration and invasion through limiting the nuclear translocation of hematopoietically expressed homeobox (HHEX). The decreased nuclear HHEX paved the way for initiating the CCL20/CCR6 signaling axis, which in turn contributed to damaged endothelial junctions, uncovering a new crosstalk mode between tumor cells and ECs. Intriguingly, Rh1 inhibited the kinase activity of casein kinase II subunit alpha (CK2α) and further promoted the nuclear translocation of HHEX in the BC cells, which resulted in the disrupted crosstalk between chemokine (C-C motif) ligand 20 (CCL20) in the BC cells and chemokine (C-C motif) receptor 6 (CCR6) in the ECs. The prohibited CCL20-CCR6 axis by Rh1 enhanced vascular integrity and diminished tumor cell motility. Taken together, our data suggest that Rh1 serves as an effective natural CK2α inhibitor that can be further optimized to be a therapeutic agent for reducing tumor cell extravasation. [Display omitted] Inhibition of CK2α by Rh1 retarded the metastasis with restraining extravasation of BC cells across endothelial barrier via disrupting the HHEX/CCL20 signaling cascade. [ABSTRACT FROM AUTHOR]

Abstract The Tikhonov regularization is an effective method used for dynamic light scattering (DLS) data inversion. However, its inversion accuracy is low for the strong noise data. Based on filtering and Tikhonov regularization technology, we propose a filter-Tikhonov-L method. To begin with, this method uses the cubical smoothing algorithm with five-point approximation to filter out the noise of autocorrelation function (ACF). A new inversion problem is constructed by the filtered ACF, and then solved by Tikhonov regularization with L-curve criterion. This method combines the advantages of filtering and Tikhonov regularization technology, so that it has the high inversion accuracy. The simulation data of particles with particle size distribution (PSD) from 100 nm to 700 nm was implemented inversion studies. The investigation shows that filter-Tikhonov-L has a great advantage in peak position, relative error, the capability of recognizing double peaks and tolerance of noises. The inversion of experimental data also verifies this conclusion. [ABSTRACT FROM AUTHOR]

Three-dimensional massive multiple-input multiple-output (3D Massive MIMO) with a large number of small antennas embedded in a uniformly rectangular antenna array provides a significant improvement in the system’s bandwidth and energy efficiency. In this paper, we analyze the possible connectivity of internet of things (IoT) devices wirelessly through the applicability of 3D massive MIMO systems. A single-cell 3D massive MIMO system has been established to support a considerable number of IoT devices in the downlink. We provide detailed channel model for tranmission in azimuthal domain and elevation domain and framework and equations of bandwidth efficiency (BE) and energy efficiency for maximum ratio, zero-forcing, and improved zero-forcing (IZF) with enhanced connectivity. Meanwhiel, We also analyze the BE for the three precoding schemes by varying single-to-noise, angular spread, and the number of IoT users. Comprehensive simulations are performed by apply several antenna configuraions i.e. 8×8\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$8 \times 8$$\end{document}, 16×16\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$16 \times 16$$\end{document} and 32×32\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$32 \times 32$$\end{document}. Simulation results validate that, the derived IZF provides better results in terms of bandwidth and energy efficiency. Meanwhile, we emphasize that 3D massive MIMO is one of the most suitable ways to connect IoT devices wirelessly. [ABSTRACT FROM AUTHOR]

High temperature superconducting pulsed power transformer (HTSPPT) provides an efficient method for inductive energy storage and current multiplication. The primary inductor of HTSPPT used for energy storage is made of high temperature superconducting coils, and the secondary inductor used for current pulse generation is made of normal conductor coils. In the initial circuit, the secondary inductor generates current pulse by switching out the coupled primary superconducting inductor. However, during the switching period, the leakage flux caused by imperfect coupling and the sudden change in primary current induce a voltage across the opening switch which exceeds the affordability of modern solid-state switches. In previous studies, a half-cycle oscillatory discharge circuit is proposed to mitigate these problems by using a capacitor to recapture the energy in the leakage flux and to slow down the turnoff of current in the primary. However, there are still some problems should be settled. For example, the output pulse cannot be adjusted, the residual energy cannot be recovered and the capacitor branch circuit may have an impact on the charging process. In the paper, a modified discharge circuit topology is introduced to solve these problems. A multi-module system comprising of several HTSPPTs charging in series connection and discharging in parallel is also designed and simulated. This system can be used to power an electromagnetic emission device. [ABSTRACT FROM AUTHOR]

• The velocity of flow aerosol is obtained based on cumulants of the intensity autocorrelation function (ACF). • The flow velocity acquisition based on cumulants of ACF is used for both unimodal and bimodal distribution of aerosols. • In the inversion of dynamic light scattering for flow aerosol measurement, the noise widens the distribution, shifts the peak value, and increases the peak height ratio. In the dynamic light scattering (DLS) measurement for a flowing aerosol, an anemometer, is needed to measure the flow velocity to invert the aerosol particle size. In this work, a cumulative analysis method has been used to obtain the aerosol velocity through the light intensity autocorrelation function (ACF) based on the relation between the particle velocity and the second cumulant of the electric field ACF of flowing aerosol particles. Additionally, the particle size distribution (PSD) has been inversed by the regularization method, which enables the online measurement of flowing aerosol to be realized. The simulation results at different noise levels show that the accurate velocity and PSD for flowing aerosols can be obtained by the proposed method at low noise levels and high noise levels. It has been observed that higher noise causes the PSD broadening and the peak offset. For aerosol particles with a bimodal distribution, the increase of noise leads to the increase of peak height ratio and peak of small particles in bimodal distribution disappears, leaving only unimodal distribution. Furthermore, the increase of noise has no significant effect on the calculated velocity value both for unimodal and bimodal aerosol distributions. The experimental results of DLS measurements on unimodal and bimodal aerosols verified the above statements. [ABSTRACT FROM AUTHOR]

• As to reveal the scattering characteristics of Ka millimeter wave by sand particles, the integrated detection on dust storms over the Taklimakan Desert is first time to conduct with the Ka band MWR, the Grimm 180, the Laser Particle Size Analyzer and the visibility meter. • The complex permittivity of sand particle, the probability distribution function of sand particles, the number of sand particles and the attenuation coefficient were calculated based on the real observations. • The reflectivity factors of dust storm are calculated and analyzed, based on the power spectrum data detected by the MWR and the visibility data observed by the visibility meter. As to study the scattering characteristics of millimeter wave by sand particles, the integrated detection on dust storms over the Taklimakan Desert was the first time to conduct with the Ka band millimeter wave radar, the Grimm 180, the Laser Particle Size Analyzer and the visibility meter. The complex permittivity of sand particle (ε m), the probability distribution function of sand particles, the number of sand particles, the attenuation coefficient and the reflectivity factors were calculated by the observations of these instruments; moreover, the power spectrums of the dust storm, sunny day and precipitation were comparatively analyzed. The results showed that: the ε m of 35 GHz millimeter wave by sand particles is 3.0078-j0.0987. The probability distribution of sand particles conforms to lognormal distribution, with the mean of -2.352 and the standard deviation of 0.422. Furthermore, when the visibility drops from 3000 to 0 m, the number of sand particles rises from 2 × 105 to 1 × 106 in L · min−1 and the attenuation coefficient increases from 1 to 8 dB · km−1. The peak and the average values of power spectrums in dust storm are lower than those in precipitation, which indicates that the scattering ability of sand particles is less than that of precipitation particles. During the dust storms, the reflectivity factors range between -40 and 20 dBZ. These findings provide theoretical basis for the further study of the scattering properties of sand particles in the future. [ABSTRACT FROM AUTHOR]

[Display omitted] A stable metal-organic framework (MOF) nanofibrous membrane (NFM) was successfully fabricated by in situ growing H 3 PW 12 O 40 (PW 12) @UiO-66 crystals onto crosslinked polyacrylic acid (PAA)-poly (vinyl alcohol) (PVA) nanofibers prepared through electrospinning. Characterization with High-angle annular dark field-scanning transmission electron microscopy (HAADF-STEM), Fourier transform infrared (FT-IR), Powder X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS) confirmed that the crystallinity and structure of PW 12 @UiO-66 crystals maintained well on the PAA-PVA NFM. The as-prepared PAA-PVA/PW 12 @UiO-66 NFM can be used as a photocatalyst for simultaneous photocatalytic degradation of methyl orange (MO) and formaldehyde (FA) in aqueous solution. The possible mechanism was that electrons transferred from FA to MO via PAA-PVA/PW 12 @UiO-66 NFM, made the photodegradation of MO driven by the reductive pathway. At the same time, FA was oxidized due to the loss of electrons. PAA-PVA/PW 12 @UiO-66 NFM presented a satisfactory stability and reusability, mainly because the partially crosslinked PAA-PVA NFM can provide sufficient carboxyl groups for anchoring PW 12 @UiO-66 particles. Due to no separation process was needed for electrospun NFM after each photocatalytic cycle, the reuse process of PAA-PVA/PW 12 @UiO-66 NFM can be conducted more conveniently and rapidly compared with powdered MOFs photocatalysts. This work will be useful for the design of MOFs NFMs photocatalysts based on electrospinning applied to comprehensive treatment of organic pollutant wastewater. [ABSTRACT FROM AUTHOR]

A global geological phenomenon caused by natural or human activities is described as land subsidence. Groundwater extraction plays a significant part in causing land subsidence. Due to economic development, urban expansion, and rapid population expansion, the unscientific exploitation of groundwater in Beijing has been accelerated, which makes it the region with the fastest land subsidence rate in China. To study the spatial heterogeneity of land subsidence caused by groundwater aquifers level changes, the monitoring results of land subsidence in 2003–2010 years were analyzed by using PS-InSAR, based on ENVISAT ASAR in Beijing plain area. The maximum value of accumulated land subsidence in the study area is 707 mm, and in this study area multiple subsidence center areas have been formed. A GWR model based on a regular grid has been established by exploring the effects of unconfined aquifer (UA), first confined aquifer (FCA), second confined aquifer (SCA), third confined aquifer (TCA) on land subsidence and their spatial non-stationarity. The change of subsidence in all subsidence areas is positively related to the change of SCA water level. Except the fact that the main control factors of Liyuan and Songzhuang are the change of UA layer, the change of SCA is the main control factor of land subsidence in most subsidence areas. Though the contribution rate of SCA to land subsidence is the highest, the contribution rate of TCA has been increasing. It is predicted that the impact on land subsidence will increase year by year. The results of this will not only help to understand the spatial impact patterns of aquifers on land subsidence zones, but also to formulate optimal groundwater regulation and recharge policies. There is a scarcity of the consideration of the compressible layer in the study and it will become more comprehensive if further datasets are obtained. Unlabelled Image • Using Moran'I to test spatial autocorrelation • Building the GWR model to research on spatial nonstationarity • Spatial correlation between land subsidence and groundwater • Contribution degree of groundwater aquifers to land subsidence [ABSTRACT FROM AUTHOR]

Endothelial cell dysfunction caused by inflammation and even vascular leakage are important manifestations of blood stasis syndrome (BSS). Reversible regulation of vascular integrity to cure BSS has attracted considerable interest. Herein, a novel acidic polysaccharide (TPP-4) was purified and characterized from Typhae Pollen, a typical traditional Chinese medicine for treating BSS, especially for bleeding caused by blood stasis. A series of structural characterization methods, including spectroscopic methods (FT-IR and UV), chromatographic methods (HPGPC, HPAEC-PDA and GC-MS) and NMR, have been used to reveal the fine structure of TPP-4. TPP-4 was a homogeneous heteropolysaccharide comprised with RG-I backbone. TPP-4 showed fantastic activities in vascular integrity regulation both in vitro (HUVECs) and in vivo (zebrafish). Transcriptomics revealed that SOX7 and lipid metabolism were the potential targets. Lipidomics showed that TPP-4 could regulate lipid metabolism disorders caused by vascular inflammation, particularly affecting LPE levels. The above regulatory effects were furtherly demonstrated to be related with VEGFA/PI3K/mTOR signaling pathway through various molecular biological experiments., Competing Interests: Declaration of competing interest The authors report no conflicts of interest., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Object counting, defined as the task of accurately predicting the number of objects in static images or videos, has recently attracted considerable interest. However, the unavoidable presence of background noise prevents counting performance from advancing further. To address this issue, we created a group and graph attention network (GGANet) for dense object counting. GGANet is an encoder-decoder architecture incorporating a group channel attention (GCA) module and a learnable graph attention (LGA) module. The GCA module groups the feature map into several subfeatures, each of which is assigned an attention factor through the identical channel attention. The LGA module views the feature map as a graph structure in which the different channels represent diverse feature vertices, and the responses between channels represent edges. The GCA and LGA modules jointly avoid the interference of irrelevant pixels and suppress the background noise. Experiments are conducted on four crowd-counting datasets, two vehicle-counting datasets, one remote-sensing counting dataset, and one few-shot object-counting dataset. Comparative results prove that the proposed GGANet achieves superior counting performance.

The soil contains abundant and diverse microorganisms, which interrelate closely with the aboveground vegetation and impact the structure and function of the forest ecosystem. To explore the effect of vegetation diversity on soil microbial functional diversity in taiga forests, we selected significantly different important values of Larix gmelinii as experimental grouping treatments based on plant investigation from fixed plots in Da Xing'anling Mountains. Following that, we collected soil samples and applied the Biolog-ECO microplate method to investigate differences in carbon source utilization, features of functional diversity in soil microorganisms, and factors influencing them in taiga forests. The AWCD decreased as the important value of Larix gmelinii grew, and soil microorganisms preferred carboxylic acids, amino acids, and carbohydrates over polymers, phenolic acids, and amines. The Shannon and McIntosh indexes decreased significantly with the increase of the important value of Larix gmelinii ( p < 0.05) and were positively correlated with soil SOC, MBC, C/N, and pH, but negatively with TN, AP, and AN. Redundancy analysis revealed significant effects on soil microbial functional diversity from soil C/N, SOC, AP, MBC, TN, pH, AN, and WC. To sum up, heterogeneous habitats of taiga forests with different important values altered soil microbial functional diversity.

Background: The shortage of water resources and the increase of greenhouse gas emissions from soil seriously restrict the sustainable development of agriculture. Under the premise of ensuring a stable yield of winter wheat through a reasonable irrigation scenario, identifying a suitable straw returning method will have a positive effect on agricultural carbon sequestration and emission reduction in North China Plain., Results: Straw burying (SR) and straw mulching (SM) were adopted based on traditional tillage under in the winter wheat growing season of 2020-2021 and 2021-2022. Three irrigation scenarios were used for each straw returning method: no irrigation (I0), irrigation 60 mm at jointing stage (I1), and irrigation of 60 mm each at the jointing and heading stages (I2). Soil moisture, soil respiration rate, cumulative soil CO 2 emissions, yield, water use efficiency (WUE) and soil CO 2 emission efficiency (CEE) were mainly studied. The results showed that, compared to SM, SR improved the utilization of soil water and enhanced soil carbon sequestration. SR reduced soil respiration rate and cumulative soil CO 2 emissions in two winter wheat growing seasons, and increased yield by increasing spike numbers. In addition, with an increase in the amount of irrigation, soil CO 2 emissions and yield increased. Under SR-I1 treatment, WUE and CEE were the highest. SR-I1 increases crop yields at the same time as reducing soil CO 2 emissions., Conclusion: The combination of SR and irrigation 60 mm at jointing stage is a suitable straw returning irrigation scenario, which can improve water use and reduce soil CO 2 emission in NCP. © 2023 Society of Chemical Industry., (© 2023 Society of Chemical Industry.)

In this research, an image defogging algorithm is proposed for the electricity transmission line monitoring system in the smart city. The electricity transmission line image is typically situated in the top part of the image which is rather thin in size. Because the electricity transmission line is situated outside, there is frequently a sizable amount of sky in the backdrop. Firstly, an optimized quadtree segmentation method for calculating global atmospheric light is proposed, which gives higher weight to the upper part of the image with the sky region. This prevents interference from bright objects on the ground and guarantees that the global atmospheric light is computed in the top section of the image with the sky region. Secondly, a method of transmission calculation based on dark pixels is introduced. Finally, a detail sharpening post-processing based on visibility level and air light level is introduced to enhance the detail level of electricity transmission lines in the defogging image. Experimental results indicate that the algorithm performs well in enhancing the image details, preventing image distortion and avoiding image oversaturation., Competing Interests: MZ, ZS, CY, ZJ, and WC were employed by the State Grid Hubei Power Supply Limited Company Ezhou Power Supply Company. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Zhang, Song, Yang, Gao, Hu, Yuan, Jiang and Cheng.)

Four fractions of polysaccharides (TPP-1, TPP-2, TPP-3, and TPP-4) were isolated and purified from the pollen of Typha angustifolia L., and the structure of TPP-3 was furtherly determined by HPGPC (High Performance Gel Permeation Chromatography), monosaccharide composition analysis, methylation analysis and NMR (Nuclear Magnetic Resonance). TPP-3 was found to be a homogeneous heteropolysaccharide with an average molecular weight of 5.5 × 10 4  Da and composed of eight types of monosaccharides. The pro-angiogenic activities of TPP-3 were verified on HUVECs and VEGFR tyrosine kinase inhibitor II (VRI)-induced vascular defect zebrafish model. Furthermore, the underlying mechanism investigation showed that its pro-angiogenic activities were closely related with the activation of VEGF/PI3K/Akt signaling pathway., Competing Interests: Declaration of competing interest The authors report no conflicts of interest., (Copyright © 2022 Elsevier B.V. All rights reserved.)