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Synthetic aperture radar (SAR) has emerged as a promising technology for monitoring crop plant height due to its ability to capture the geometric properties of crops. Radar vegetation index (RVI) has been extensively utilized for qualitative and quantitative remote sensing monitoring of vegetation growth dynamics. However, the combination of crop, growing environment, and temporal dynamics makes crop monitoring data a complex task. Despite the relatively simple underlying mechanisms of this phenomenon, there is still a need for more research to identify specific vegetation structures that correspond to changes in the response of vegetation indices. Building upon this premise, this study utilized a dynamic monitoring model to conduct dynamic monitoring of plant height for three common crops: rice, wheat, and maize. The findings revealed that (1) models developed for specific spatial and temporal scales of particular crop varieties may not accurately predict crop growth in different regions or with different varieties in a timely manner, due to growth variations; (2) these models maintain accuracy over a range of plant heights, such as rice at around 70cm, wheat at around 50cm, and maize at around 150cm; (3) among the three crops, planting density was identified as the main factor influencing the differences in RVI response. This research contributes to our comprehension of the dynamic response of RVI to different growth conditions in crops, and offers valuable insights and references for agricultural monitoring.

The FecB gene is one of those responsible for regulating reproductive traits in sheep. This experiment was designed to explore the impact of SNPs (single nucleotide polymorphisms) within the FecB gene on both the reproductive and body size performance of sheep. In this experiment, two SNP sites were identified as C413217T and A431965G. Through analysis of genetic diversity and correlations, we aimed to identify combinations of genotypes and haplotypes that influence reproductive performance and body size performance. The most prominent genotypes associated with lambing performance were identified as AA and CT, with the dominant haplotype combination being AACT. For body size performance, the dominant genotypes were AA and CC, while the dominant haplotype combination was AACC. These advantageous genotypes and haplotype combinations are conducive to promoting the selection and improvement of sheep breeds, advancing the progress of sheep genetic breeding, and providing theoretical support for the breeding of higher-fertility sheep.

The article compares two works — «Manchurian Princess» by Russian emigrant writer A. Heidok and «Spring in a Small Town» by Chinese writer Xiao Hong, which were created in approximately the same epoch and reproduce the same place of action — the north-east of China. Heidok’s work appealed to the mystical ideas of Chinese culture (the idea of reincarnation); Xiao Hong’s work was deeply influenced by Russian classical literature. Both stories present a story of tragic love, which breaks the traditions of a conservative society and radically changes the lives of the characters. The meaning of the characters’ lives lies in returning to the true nature of man — love, because only in it does existence find meaning; at the same time, the theme of love is closely intertwined with the theme of death. In both works there is an intersection of different epochs — the past and the present; at the same time, it is the past that determines the course of events of the present. Specific situations of the characters’ lives are revealed in a broad historical and cultural space, which allows the author to put before the readers the most important ethical and philosophical problems. A. Heidok’s story shows how life in the previous birth influences the actions of a person in subsequent births; in Xiao Hong’s story «the past» is the power of tradition, which does not allow a girl to get an education and determine her own destiny.

Permafrost has been warming and thawing globally, with subsequent effects on the climate, hydrology, and the ecosystem. However, the permafrost thermal state variation in the northern lower limit of the permafrost zone (Xidatan) on the Qinghai–Tibet Plateau (QTP) is unclear. This study attempts to explore the changes and variability in this permafrost using historical (1970–2019) and future projection datasets from remote-sensing-based land surface temperature product (LST) and climate projections from Earth system model (ESM) outputs of the Coupled Model Intercomparison Project Phase 5 and 6 (CMIP5, CMIP6). Our model considers phase-change processes of soil pore water, thermal-property differences between frozen and unfrozen soil, geothermal flux flow, and the ground ice effect. Our model can consistently reproduce the vertical ground temperature profiles and active layer thickness (ALT), recognizing permafrost boundaries, and capture the evolution of the permafrost thermal regime. The spatial distribution of permafrost and its thermal conditions over the study area were controlled by elevation with a strong influence of slope orientation. From 1970 to 2019, the mean annual ground temperature (MAGT) in the region warmed by 0.49 ∘C in the continuous permafrost zone and 0.40 ∘C in the discontinuous permafrost zone. The lowest elevation of the permafrost boundary (on the north-facing slopes) rose approximately 47 m, and the northern boundary of discontinuous permafrost retreated southwards by approximately 1–2 km, while the lowest elevation of the permafrost boundary remained unchanged for the continuous permafrost zone. The warming rate in MAGT is projected to be more pronounced under shared socioeconomic pathways (SSPs) than under representative concentration pathways (RCPs), but there are no distinct discrepancies in the areal extent of the continuous and discontinuous permafrost and seasonally frozen ground among SSP and RCP scenarios. This study highlights the slow delaying process of the response of permafrost in the QTP to a warming climate, especially in terms of the areal extent of permafrost distribution.

Intro: HIV-associated neurocognitive disorders (HAND) are a significant factor impacting the quality of life in HIV-1 patients. Kynurenic acid (KYNA), derived from tryptophan (Trp) in a physiological state, is a neuroprotective molecule associated with astrocytes. Previous results suggested KYNA level in the brain of HIV-1 gp120 transgenic mice (Tg mice) fed with Trp is higher than that in the control group, and Tg mice were successfully established for simulating the HAND. In this study, Morris Water Maze (MWM) to determine behavioral changes in mice, evaluating the effect of KYNA on cognitive impairment in Tg mice. Methods: The mice were randomly numbered and divided into four groups (n=10): WT, WT+0.1%Trp, Tg mice, and Tg mice+0.1%Trp, fed for one month by grouping. All groups of mice intake water and food freely during this period. The data of the incubation period, crossing times, and the quadrant residence time were recorded by MWM and analyzed with SPSS 22.0. Findings: The residence time of the Tg mice+Trp group in the hidden platform quadrant was increased (P0.05). And it extended the incubation period of WT group without a statistical difference (P>0.05). Ultimately, the platform crossing times of both gp120+Trp group and WT+Trp group without a statistical difference (P>0.05). Those results suggested that MWM assessing learning and cognitive ability is feasible. Conclusion: MWM could evaluate the protective effect of KYNA on cognitive impairment in HIV-1 gp120 transgenic mice.

Selin Co, located within permafrost regions surrounded by glaciers, has exhibited the greatest increase in water storage among all the lakes on the Tibetan Plateau over the last 50 years. Most of the increased lake water volume has been attributed to increased precipitation and the accelerated melting of glacier ice, but these processes are still not sufficient to close the water budget with the expansion of Selin Co. Ground ice meltwater released by thawing permafrost due to continuous climate warming over the past several decades is regarded as another source of lake expansion. This study presents the first attempt to quantify the water contribution of ground ice melting to the expansion of Selin Co by evaluating the ground surface deformation. We monitored the spatial distribution of surface deformation in the Selin Co basin using the small baseline subset (SBAS) interferometric synthetic aperture radar (InSAR) technique and compared the results with the findings of field surveys. Then, the ground ice meltwater volume in the watershed was calculated based on the cumulated settlement. Finally, this volume was compared with the lake volume change during the same period, and the contribution ratio was derived. SBAS-InSAR monitoring during 2017–2020 illustrated widespread and large subsidence in the upstream section of the Zhajiazangbu subbasin, where widespread continuous permafrost is present. The terrain subsidence rate was normally between 5 and 20 mm a−1, indicating rapid ground ice loss in the region. The ground ice meltwater was released at a rate of ∼57×106 m3 a−1, and the rate of increase in lake water storage was ∼485×106 m3 a−1 during the same period, with ground ice meltwater contributing ∼12 % of the lake volume increase. This study contributes to explaining the rapid expansion of Selin Co and equilibrating the water balance at the watershed scale. More importantly, the proposed method can be extended to other watersheds underlain by permafrost and help in understanding the hydrological changes in these watersheds.

Relict permafrost presents an ideal opportunity to understand the impacts of climatic warming on the ground thermal regime since it is characterized by a mean annual ground temperature close to 0 ∘C and relatively thin permafrost. The long-term and continuous observations of permafrost thermal state and climate background are of great importance to reveal the links between the energy balance on hourly to annual timescales, to evaluate the variations in permafrost thermal state over multiannual periods and to validate the remote sensing dataset. We present 11 years of meteorological and soil data from the Mahan Mountain relict permafrost site of northeastern Qinghai–Tibet Plateau. The meteorological data comprise air and land surface temperature, relative humidity, wind speed and direction, shortwave and longwave downwards and upwards radiation, water vapor pressure, and precipitation on a half-hour timescale. The active layer data include daily soil temperature and soil volumetric water content at five different depths. The permafrost data consist of the ground temperature at 20 different depths up to 28.4 m. The high-quality and long-term datasets are expected to serve as accurate forcing data in land surface models and evaluate remote-sensing products for a broader geoscientific community. The datasets are available from the National Tibetan Plateau/Third Pole Environment Data Center (https://doi.org/10.11888/Cryos.tpdc.271838, Wu and Xie, 2021).

Permafrost has great influences on the climatic, hydrological, and ecological systems on the Qinghai–Tibet Plateau (QTP). The changing permafrost and its impact have been attracting great attention worldwide like never before. More observational and modeling approaches are needed to promote an understanding of permafrost thermal state and climatic conditions on the QTP. However, limited data on the permafrost thermal state and climate background have been sporadically reported in different pieces of literature due to the difficulties of accessing and working in this region where the weather is severe, environmental conditions are harsh, and the topographic and morphological features are complex. From the 1990s, we began to establish a permafrost monitoring network on the QTP. Meteorological variables were measured by automatic meteorological systems. The soil temperature and moisture data were collected from an integrated observation system in the active layer. Deep ground temperature (GT) was observed from boreholes. In this study, a comprehensive dataset consisting of long-term meteorological, GT, soil moisture, and soil temperature data was compiled after quality control from an integrated, distributed, and multiscale observation network in the permafrost regions of QTP. The dataset is helpful for scientists with multiple study fields (i.e., climate, cryospheric, ecology and hydrology, meteorology science), which will significantly promote the verification, development, and improvement of hydrological models, land surface process models, and climate models on the QTP. The datasets are available from the National Tibetan Plateau/Third Pole Environment Data Center (https://data.tpdc.ac.cn/en/disallow/789e838e-16ac-4539-bb7e-906217305a1d/, last access: 24 August 2021, https://doi.org/10.11888/Geocry.tpdc.271107, Lin et al., 2021).

Extensive and rigorous model intercomparison is of great importance before model application due to the uncertainties in current land surface models (LSMs). Without considering the uncertainties in forcing data and model parameters, this study designed an ensemble of 55 296 experiments to evaluate the Noah LSM with multi-parameterization (Noah-MP) for snow cover events (SCEs), soil temperature (ST) and soil liquid water (SLW) simulation, and investigated the sensitivity of parameterization schemes at a typical permafrost site on the Qinghai–Tibet Plateau (QTP). The results showed that Noah-MP systematically overestimates snow cover, which could be greatly resolved when adopting the sublimation from wind and a semi-implicit snow/soil temperature time scheme. As a result of the overestimated snow, Noah-MP generally underestimates ST, which is mostly influenced by the snow process. A systematic cold bias and large uncertainties in soil temperature remain after eliminating the effects of snow, particularly in the deep layers and during the cold season. The combination of roughness length for heat and under-canopy (below-canopy) aerodynamic resistance contributes to resolving the cold bias in soil temperature. In addition, Noah-MP generally underestimates top SLW. The runoff and groundwater (RUN) process dominates the SLW simulation in comparison to the very limited impacts of all other physical processes. The analysis of the model structural uncertainties and characteristics of each scheme would be constructive to a better understanding of the land surface processes in the permafrost regions of the QTP as well as to further model improvements towards soil hydrothermal regime modeling using LSMs.

Laser scanning or photogrammetry are useful individual techniques for digital documentation of cultural heritage sites. However, these techniques are of limited usage if cultural heritage such as the Great Wall is in harsh geographical conditions. The Great Wall is usually built on the ridge with cliffs on both sides, so it is very difficult to construct scaffolding. Therefore, the three-dimensional (3D) data obtained from the traditional 3D laser scanning is not complete. As UAV cannot enter the enemy tower, the 3D structure data inside the enemy tower with unmanned aerial vehicle (UAV) photogrammetry is missing. In order to explore effective methods to completely collect the 3D data of cultural heritage under harsh geographical environment, this study focuses on establishing a 3D model and the associated digital documentation for the No.15 enemy tower of the New Guangwu Great Wall using a combination of terrestrial laser scanning and UAV photogrammetry. This paper proposes an integrated data collection method and reduces the layout of image control points using RTK-UAV technology, which improved work efficiency and reduced work risks as well. In this paper, the internal structure data of the Great Wall enemy tower was collected by laser scanning, the external structure data was collected by UAV photogrammetry, and data fusion was based on ICP algorithm. Finally, we obtained the complete and high quality 3D digital documentation of the Great Wall enemy tower, the data can be displayed digitally and help heritage experts complete the Great Wall's restoration. This study demonstrates the potential of integrating terrestrial laser scanning and UAV photogrammetry in 3D digital documentation of cultural heritage sites.

Understanding the composition, temporal variability and source apportionment of volatile organic compounds (VOCs) is necessary for determining effective control measures to minimize VOCs and their related photochemical pollution. To provide a comprehensive analysis of VOC sources and their contributions to ozone (O3) formation in the Yangtze River Delta (YRD) – a region experiencing the highest rates of industrial and economic development in China – we conducted a 1-year sampling exercise using a thermal desorption GC (gas chromatography) system for the first time at an urban site in Nanjing (JAES site). Alkanes were the dominant group at the JAES site, contributing ∼53 % to the observed total VOCs, followed by aromatics (∼17 %), acetylene (∼17 %) and alkenes (∼13 %). We identified seasonal variability in total VOCs (TVOCs) with maximum and minimum concentrations in winter and summer, respectively. Morning and evening peaks and a daytime trough were identified in the diurnal VOC patterns. We identified VOC sources using positive matrix factorization (PMF) and assessed their contributions to photochemical O3 formation by calculating the O3 formation potential (OFP) based on the mass concentrations and maximum incremental reactivities of VOCs. The PMF model identified five dominant VOC sources, with highest contributions from diesel vehicular exhaust (34±5 %), followed by gasoline vehicular exhaust (27±3 %), industrial emissions (19±2 %), fuel evaporation (15±2 %) and biogenic emissions (4±1 %). The results of the OFP calculation inferred that VOCs from industrial and vehicular emissions were found to be the dominant precursors for OFP, particularly the VOC species of xylenes, toluene and propene, and top priority should be given to these for the alleviation of photochemical smog. Our results therefore highlight that priority should be given to limited VOC sources and species for effective control of O3 formation in Nanjing.

To develop multifunctional delivery systems of targeted properties for biomedical applications, hybrid fiber-nanoparticle matrices capable of controlled and monitored nanoparticles (NPs) delivery properties were prepared. Firstly, electropinning technique was applied to produce carbon nanotubes (CNTs) incorporated biodegradable poly(ϵ-caprolactone)/gelatin (PG) polymer fibers (PGC fibers). Subsequently, the photoluminescent mesoporous silica nanoparticles (PLMSNs) were electrostatically attached on the surface of PGC fibers to form a localized delivery platform. The PGC-PLMSNs fibers can emit red light under excitation at ~395 nm, 465 nm, and ~533 nm. Additionally, under NIR (808 nm) irradiation, PGC-PLMSNs fibers revealed good photothermal effect. PLMSNs loading efficiency onto the PGC fibers and PLMSNs release kinetics were assessed by TG method. More importantly, the 808 nm NIR irradiation enabled remarkably promoted PLMSNs release rate, validating the typical NIR-triggered release properties. Meanwhile, PLMSNs released from the composite fibers could be optically monitored by decrease in the intensity of red emission. These results suggest the possibility to develop the localized therapeutic device that may inspire other means of treatment method for cancer therapy.

It is difficult to extract grassland accurately by traditional classification methods, such as supervised method based on pixels or objects. This paper proposed a new method combing the multi-level segmentation with CART (classification and regression tree) model. The multi-level segmentation which combined the multi-resolution segmentation and the spectral difference segmentation could avoid the over and insufficient segmentation seen in the single segmentation mode. The CART model was established based on the spectral characteristics and texture feature which were excavated from training sample data. Xilinhaote City in Inner Mongolia Autonomous Region was chosen as the typical study area and the proposed method was verified by using visual interpretation results as approximate truth value. Meanwhile, the comparison with the nearest neighbor supervised classification method was obtained. The experimental results showed that the total precision of classification and the Kappa coefficient of the proposed method was 95 % and 0.9, respectively. However, the total precision of classification and the Kappa coefficient of the nearest neighbor supervised classification method was 80 % and 0.56, respectively. The result suggested that the accuracy of classification proposed in this paper was higher than the nearest neighbor supervised classification method. The experiment certificated that the proposed method was an effective extraction method of grassland information, which could enhance the boundary of grassland classification and avoid the restriction of grassland distribution scale. This method was also applicable to the extraction of grassland information in other regions with complicated spatial features, which could avoid the interference of woodland, arable land and water body effectively.

The Tibetan Plateau (TP) has the largest areas of permafrost terrain in the mid- and low-latitude regions of the world. Some permafrost distribution maps have been compiled but, due to limited data sources, ambiguous criteria, inadequate validation, and deficiency of high-quality spatial data sets, there is high uncertainty in the mapping of the permafrost distribution on the TP. We generated a new permafrost map based on freezing and thawing indices from modified Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperatures (LSTs) and validated this map using various ground-based data sets. The soil thermal properties of five soil types across the TP were estimated according to an empirical equation and soil properties (moisture content and bulk density). The temperature at the top of permafrost (TTOP) model was applied to simulate the permafrost distribution. Permafrost, seasonally frozen ground, and unfrozen ground covered areas of 1.06 × 106 km2 (0.97–1.15 × 106 km2, 90 % confidence interval) (40 %), 1.46 × 106 (56 %), and 0.03 × 106 km2 (1 %), respectively, excluding glaciers and lakes. Ground-based observations of the permafrost distribution across the five investigated regions (IRs, located in the transition zones of the permafrost and seasonally frozen ground) and three highway transects (across the entire permafrost regions from north to south) were used to validate the model. Validation results showed that the kappa coefficient varied from 0.38 to 0.78 with a mean of 0.57 for the five IRs and 0.62 to 0.74 with a mean of 0.68 within the three transects. Compared with earlier studies, the TTOP modelling results show greater accuracy. The results provide more detailed information on the permafrost distribution and basic data for use in future research on the Tibetan Plateau permafrost.

The T-cell immunoglobulin and mucin domain (TIM) family is associated with autoimmune diseases, but its expression level in the immune cells of systemic lupus erythematosus (SLE) patients is not known. The aim of this study was to investigate whether the expression of TIM-3 mRNA is associated with pathogenesis of SLE. Quantitative real-time reverse transcription-polymerase chain reaction analysis (qRT-PCR) was used to determine TIM-1, TIM-3, and TIM-4 mRNA expression in peripheral blood mononuclear cells (PBMCs) from 132 patients with SLE and 62 healthy controls. The PBMC surface protein expression of TIMs in PBMCs from 20 SLE patients and 15 healthy controls was assayed by flow cytometry. Only TIM-3 mRNA expression decreased significantly in SLE patients compared with healthy controls (P0.05). SLE patients with lupus nephritis (LN) had a significantly lower expression of TIM-3 mRNA than those without LN (P=0.001). There was no significant difference in the expression of TIM-3 mRNA within different classes of LN (P>0.05). Correlation of TIM-3 mRNA expression with serum IgA was highly significant (r=0.425, P=0.004), but was weakly correlated with total serum protein (rs=0.283, P=0.049) and serum albumin (rs=0.297, P=0.047). TIM-3 mRNA expression was weakly correlated with the Systemic Lupus Erythematosus Disease Activity Index (SLEDAI; rs=-0.272, P=0.032). Our results suggest that below-normal expression of TIM-3 mRNA in PBMC may be involved in the pathogenesis of SLE.

The T-cell immunoglobulin and mucin domain (TIM) family is associated with autoimmune diseases, but its expression level in the immune cells of systemic lupus erythematosus (SLE) patients is not known. The aim of this study was to investigate whether the expression of TIM-3 mRNA is associated with pathogenesis of SLE. Quantitative real-time reverse transcription-polymerase chain reaction analysis (qRT-PCR) was used to determine TIM-1, TIM-3, and TIM-4 mRNA expression in peripheral blood mononuclear cells (PBMCs) from 132 patients with SLE and 62 healthy controls. The PBMC surface protein expression of TIMs in PBMCs from 20 SLE patients and 15 healthy controls was assayed by flow cytometry. Only TIM-3 mRNA expression decreased significantly in SLE patients compared with healthy controls (P0.05). SLE patients with lupus nephritis (LN) had a significantly lower expression of TIM-3 mRNA than those without LN (P=0.001). There was no significant difference in the expression of TIM-3 mRNA within different classes of LN (P>0.05). Correlation of TIM-3 mRNA expression with serum IgA was highly significant (r=0.425, P=0.004), but was weakly correlated with total serum protein (rs=0.283, P=0.049) and serum albumin (rs=0.297, P=0.047). TIM-3 mRNA expression was weakly correlated with the Systemic Lupus Erythematosus Disease Activity Index (SLEDAI; rs=-0.272, P=0.032). Our results suggest that below-normal expression of TIM-3 mRNA in PBMC may be involved in the pathogenesis of SLE.

Potato virus X coat protein (PVXCP) is, through communication with host proteins, involved in processes such as virus movement and symptom development. Here, we report that PVXCP also interacts with the precursor of plastocyanin, a protein involved in photosynthesis, both in vitro and in vivo. Yeast two-hybrid analysis indicated that PVXCP interacted with only the plastocyanin transit peptide. In subsequent bimolecular fluorescence complementation assays, both proteins were collocated within chloroplasts. Western blot analyses of chloroplast fractions showed that PVXCP could be detected in the envelope, stroma, and lumen fractions. Transmission electron microscopy demonstrated that grana were dilated in PVX-infected Nicotiana benthamiana. Furthermore, virus-induced gene silencing of plastocyanin by prior infection of N. benthamiana using a Tobacco rattle virus vector reduced the severity of symptoms that developed following subsequent PVX infection as well as the accumulation of PVXCP in isolated chloroplasts. However, PVXCP could not be detected in pea chloroplasts in an in vitro re-uptake assay using the plastocyanin precursor protein. Taken together, these data suggest that PVXCP interacts with the plastocyanin precursor protein and that silencing the expression of this protein leads to reduced PVXCP accumulation in chloroplasts and ameliorates symptom severity in host plants.