Zabuye Salt Lake solar pond in Tibet, China: Construction and operational experience

We describe the construction of the Zabuye Salt Lake solar pond and our experience during its operation. The salinity gradient was experimentally determined in the pond, which has a surface area of about 3588 m2, and different conditions and modes of operation. The method for establishing a salinity and temperature gradient can save large amounts of fresh water during the establishment of a temperature and salinity gradient in a solar pond. A technology to control solar pond operation was developed on the basis of our experimental results and is now being used to operate the pond

Molybdenum disulfide nanoflowers mediated anti-inflammation macrophage modulation for spinal cord injury treatment

Spinal cord injury (SCI) can cause locomotor dysfunctions and sensory deficits. Evidence shows that functional nanodrugs can regulate macrophage polarization and promote anti-inflammatory cytokine expression, which is feasible in SCI immunotherapeutic treatments. Molybdenum disulfide (MoS2) nanomaterials have garnered great attention as potential carriers for therapeutic payload. Herein, we synthesize MoS2@PEG (MoS2 = molybdenum disulfide, PEG = poly (ethylene glycol)) nanoflowers as an effective carrier for loading etanercept (ET) to treat SCI. We characterize drug loading and release properties of MoS2@PEG in vitro and demonstrate that ET-loading MoS2@PEG obviously inhibits the expression of M1-related pro-inflammatory markers (TNF-α, CD86 and iNOS), while promoting M2-related anti-inflammatory markers (Agr1, CD206 and IL-10) levels. In vivo, the mouse model of SCI shows that long-circulating ET-MoS2@PEG nanodrugs can effectively extravasate into the injured spinal cord up to 96 h after SCI, and promote macrophages towards M2 type polarization. As a result, the ET-loading MoS2@PEG administration in mice can protect survival motor neurons, thus, reducing injured areas at central lesion sites, and significantly improving locomotor recovery. This study demonstrates the anti-inflammatory and neuroprotective activities of ET-MoS2@PEG and promising utility of MoS2 nanomaterial-mediated drug delivery

Biological Characteristics of Severe Combined Immunodeficient Mice Produced by CRISPR/Cas9-Mediated Rag2 and IL2rg Mutation

Clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated (Cas)9 is a novel and convenient gene editing system that can be used to construct genetically modified animals. Recombination activating gene 2 (Rag2) is a core component that is involved in the initiation of V(D)J recombination during T- and B-cells maturation. Separately, the interleukin-2 receptor gamma chain gene (IL2rg) encoded the protein-regulated activity of natural killer (NK) cells and shared common receptors of some cytokines. Rag2 and IL2rg mutations cause immune system disorders associated with T-, B-, and NK cell function and some cytokine activities. In the present study, 2 single-guide RNAs (sgRNAs) targeted on Rag2 and IL2rg genes were microinjected into the zygotes of BALB/c mice with Cas9 messenger RNA (mRNA) to create Rag2/IL2rg-/- double knockout mice, and the biological characteristics of the mutated mice were subsequently analyzed. The results showed that CRISPR/Cas9-induced indel mutation displaced the frameshift of Rag2 and IL2rg genes, resulting in a decrease in the number of T-, B-, and NK cells and the destruction of immune-related tissues like the thymus and spleen. Mycobacterium tuberculosis 85B antigen could not induce cellular and humoral immune response in mice. However, this aberrant immune activity compromised the growth of several tumor heterogenous grafts in the mutated mice, including orthotopic and subcutaneous transplantation tumors. Thus, Rag2/IL2rg-/- knockout mice possessed features of severe combined immunodeficiency (SCID), which is an ideal model for human xenograft

Low-Complex Channel Estimation in Extra-Large Scale MIMO with the Spherical Wave Properties

This paper investigates the low-complex linear minimum mean squared error (LMMSE) channel estimation in an extra-large scale MIMO system with the spherical wave model (SWM). We model the extra-large scale MIMO channels using the SWM in the terahertz (THz) line-of-sight propagation, in which the transceiver is a uniform circular antenna array. On this basis, for the known channel covariance matrix (CCM), a low-complex LMMSE channel estimation algorithm is proposed by exploiting the spherical wave properties (SWP). Meanwhile, for the unknown CCM, a similar low-complex LMMSE channel estimation algorithm is also proposed. Both theoretical and simulation results show that the proposed algorithm has lower complexity without reducing the accuracy of channel estimation.Comment: 9 pages with 3 figures, accepted by Physical Communicatio

Latent Network Construction for Univariate Time Series Based on Variational Auto-Encode

Time series analysis has been an important branch of information processing, and the conversion of time series into complex networks provides a new means to understand and analyze time series. In this work, using Variational Auto-Encode (VAE), we explored the construction of latent networks for univariate time series. We first trained the VAE to obtain the space of latent probability distributions of the time series and then decomposed the multivariate Gaussian distribution into multiple univariate Gaussian distributions. By measuring the distance between univariate Gaussian distributions on a statistical manifold, the latent network construction was finally achieved. The experimental results show that the latent network can effectively retain the original information of the time series and provide a new data structure for the downstream tasks

Construction and Quality Assurance of Outstanding Applied Horticultural Talent Training Curriculum System under the Background of New Agricultural Science: A Case Study of Huaiyin Institute of Technology

Huaiyin Institute of Technology is taken as the research object. The content of horticulture curriculum system under the background of new agricultural science is constructed and elaborated, including theoretical curriculum system of "three platforms and seven curriculum groups" and practice system of "two platforms, three levels and four modules". Moreover, the quality assurance strategy of the curriculum system is discussed from three angles of enhancing professional emotion, enhancing professional practice and strengthening innovation ability, to reach the training objective of outstanding applied horticultural talents under the background of new agricultural science

Combination of super-resolution reconstruction and SGA-Net for marsh vegetation mapping using multi-resolution multispectral and hyperspectral images

Vegetation is crucial for wetland ecosystems. Human activities and climate changes are increasingly threatening wetland ecosystems. Combining satellite images and deep learning for classifying marsh vegetation communities has faced great challenges because of its coarse spatial resolution and limited spectral bands. This study aimed to propose a method to classify marsh vegetation using multi-resolution multispectral and hyperspectral images, combining super-resolution techniques and a novel self-constructing graph attention neural network (SGA-Net) algorithm. The SGA-Net algorithm includes a decoding layer (SCE-Net) to precisely fine marsh vegetation classification in Honghe National Nature Reserve, Northeast China. The results indicated that the hyperspectral reconstruction images based on the super-resolution convolutional neural network (SRCNN) obtained higher accuracy with a peak signal-to-noise ratio (PSNR) of 28.87 and structural similarity (SSIM) of 0.76 in spatial quality and root mean squared error (RMSE) of 0.11 and R2 of 0.63 in spectral quality. The improvement of classification accuracy (MIoU) by enhanced super-resolution generative adversarial network (ESRGAN) (6.19%) was greater than that of SRCNN (4.33%) and super-resolution generative adversarial network (SRGAN) (3.64%). In most classification schemes, the SGA-Net outperformed DeepLabV3 + and SegFormer algorithms for marsh vegetation and achieved the highest F1-score (78.47%). This study demonstrated that collaborative use of super-resolution reconstruction and deep learning is an effective approach for marsh vegetation mapping

Effect of Two-Step High Temperature Treatment on Phase Transformation and Microstructure of V-Bearing Bainitic Steel

The effects of VC precipitation on phase transformation, microstructure, and mechanical properties were studied by controlling two-step isothermal treatment, i.e., austenization followed by intercritical transformation. The results show that the bainite transformation time of 950 °C–860 °C treatment and 950 °C–848 °C treatment is shorter than that of 950 °C single-step treatment. This is related to the isothermal ferrite transformation in the intercritical transformation range. The formation of ferrite nuclei increases the density of medium temperature bainite nucleation sites and decrease the bainite nucleation activation energy. At the same time, a large number of VC particles are precipitated. The additional VC particles provide numbers of preferential nucleation sites. The toughness of the specimen treated at 950~870 °C is improved, which is related to the large proportion of high angle grain boundaries. High angle grain boundaries can hinder crack propagation or change the direction of crack propagation. The specimen treated at 950 °C–848 °C exhibits large proportion of low angle grain boundaries, which is beneficial for the strength improvement

Effect of Cold Rolling and Cryogenic Treatment on the Microstructure and Mechanical Properties of Fe–32Ni Alloy

In this work, the effects of cold rolling (CR) and cold rolling–cryogenic treatment (CR–CT) on the microstructure and mechanical properties of Fe–32Ni alloy were studied via optical microscopy methods, OM, SEM, XRD, TEM, tensile strength and hardness tester, and tensile testing. The results reveal the grain refinement in the alloy after rolling deformation. When the deformation is higher than 85%, the polygonal austenite grains become layered, and a small amount of martensite forms. Because of the inhibitory effect of cold-rolling deformation before cryogenic treatment on martensitic transformation, the amount of martensite form phase after cryogenic treatment decreases with the increase of deformation. The hardness and strength of the sample, independent of whether the cryogenic treatment is performed, increase with the increase of deformation degree. Under the same deformation rate, the hardness of the CR–CT sample is higher than that of the CR sample, which is related to the hard martensite phase with high dislocation density obtained during cryogenic treatment. The strain hardening behavior of the sample is greatly affected by the deformation degree. With the increase of true strain, the work hardening exponent of CR and CR–CT samples undergoing severe plastic deformation is lower than that at small deformation degree and low dislocation density, which is attributed to the earlier entanglement of high dislocations in CR and CR–CT samples with large deformation degrees