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Wild soybean (Glycine soja), a relative of cultivated soybean, shows high adaptability to adverse environmental conditions. We identified and characterized a wild soybean transcription factor gene, GsWRKY40, that promotes plant salt stress. GsWRKY40 was highly expressed in wild soybean roots and was up-regulated by salt treatment. GsWRKY40 was localized in nucleus and demonstrated DNA-binding activities but without transcriptional activation. Mutation and overexpression of GsWRKY40 altered salt tolerance of Arabidopsis plants. To understand the molecular mechanism of GsWRKY40 in regulating plant salt resistance, we screened a cDNA library and identified a GsWRKY40 interacting protein GsbHLH92 by using yeast two-hybrid approach. The physical interaction of GsWRKY40 and GsbHLH92 was confirmed by co-immunoprecipitation (co-IP), GST pull-down, and bimolecular fluorescence complementation (BiFC) techniques. Intriguingly, co-overexpression of GsWRKY40 and GsbHLH92 resulted in higher salt tolerance and lower ROS levels than overexpression of GsWRKY40 or GsbHLH92 in composite soybean plants, suggesting that GsWRKY40 and GsbHLH92 may synergistically regulate plant salt resistance through inhibiting ROS production. qRT-PCR data indicated that the expression level of GmSPOD1 gene encoding peroxidase was cooperatively regulated by GsWRKY40 and GsbHLH92, which was confirmed by using a dual luciferase report system and yeast one-hybrid experiment. Our study reveals a pathway that GsWRKY40 and GsbHLH92 collaboratively up-regulate plant salt resistance through impeding GmSPOD1 expression and reducing ROS levels, providing a novel perspective on the regulatory mechanisms underlying plant tolerance to abiotic stresses.

The effects of different dietary lipid levels on lipid accumulation, inflammatory response, serum bio-chemical index and histological features of intestine and hepatopancreas of O. macrolepis was experimentally evaluated in an eight-weeks study. Fish (initial weight 50.11 ± 2.86 g) were fed with five iso-nitrogenous diets (around 390 g/kg protein) varying with lipid level (5%, 7%, 9%, 11%, 13%, being LL5, LL7, LL9, LL11, and LL13 respectively) in triplicates. Results showed that the content of crude lipid in carcass and hepatopancreas were not affected by dietary lipid levels (P > 0.05). Serum ALT, TP, HDL-c and MDA, etc., were not significantly affected by diets (P > 0.05), while serum total antioxidant capacity in LL9 and LL11 groups were significantly higher than the other groups (P 0.05), while the height of intestine villus showed the higher trend in LL9 compared with other groups. The relative expression of lipid metabolism related genes (ppar α, cpt-1α, fas, and hsl) and immune response related genes (tlr 22, nrf 2, tnfα, and il-γ) in the hepatopancreas of fish fed diets differing in their crude lipid levels were not significantly different (P > 0.05). The results suggested that a proper dietary lipid level of 9%–11% could maintain higher antioxidant and health status of adult O.macrolepis.

Levulinic acid, a hydrolysis product of lignocellulose, can be metabolized into important compounds in the field of medicine and pesticides by engineered strains of Saccharomyces cerevisiae. Levulinic acid, as an intermediate product widely found in the conversion process of lignocellulosic biomass, has multiple applications. However, its toxicity to Saccharomyces cerevisiae reduces its conversion efficiency, so screening Saccharomyces cerevisiae genes that can tolerate levulinic acid becomes the key. By creating a whole-genome knockout library and bioinformatics analysis, this study used the phenotypic characteristics of cells as the basis for screening and found the HMX1 gene that is highly sensitive to levulinic acid in the oxidative stress pathway. After knocking out HMX1 and treating with levulinic acid, the omics data of the strain revealed that multiple affected pathways, especially the expression of 14 genes related to the cell wall and membrane system, were significantly downregulated. The levels of acetyl-CoA and riboflavin decreased by 1.02-fold and 1.44-fold, respectively, while the content of pantothenic acid increased. These findings indicate that the cell wall-membrane system, as well as the metabolism of acetyl-CoA and riboflavin, are important in improving the resistance of Saccharomyces cerevisiae to levulinic acid. They provide theoretical support for enhancing the tolerance of microorganisms to levulinic acid, which is significant for optimizing the conversion process of lignocellulosic biomass to levulinic acid.

Abstract In bioethanol production, the main by-product, 5-hydroxymethylfurfural (HMF), significantly hinders microbial fermentation. Therefore, it is crucial to explore genes related to HMF tolerance in Saccharomyces cerevisiae for enhancing the tolerance of ethanol fermentation strains. A comprehensive analysis was conducted using genome-wide deletion library scanning and SGAtools, resulting in the identification of 294 genes associated with HMF tolerance in S. cerevisiae. Further KEGG and GO enrichment analysis revealed the involvement of genes OCA1 and SIW14 in the protein phosphorylation pathway, underscoring their role in HMF tolerance. Spot test validation and subcellular structure observation demonstrated that, following a 3-h treatment with 60 mM HMF, the SIW14 gene knockout strain exhibited a 12.68% increase in cells with abnormal endoplasmic reticulum (ER) and a 22.41% increase in the accumulation of reactive oxygen species compared to the BY4741 strain. These findings indicate that the SIW14 gene contributes to the protection of the ER structure within the cell and facilitates the clearance of reactive oxygen species, thereby confirming its significance as a key gene for HMF tolerance in S. cerevisiae.

Landslides, prevalent in mountainous areas, are typically triggered by tectonic movements, climatic changes, and human activities. They pose catastrophic risks, especially when occurring near settlements and infrastructure. Therefore, detecting, monitoring, and predicting landslide deformations is essential for geo-risk mitigation. The mainstream of the previous studies have often focused on deterministic models for immediate landslide prediction. However, in most of them, the aspect of prediction uncertainties are not sufficiently addressed. This paper introduces an innovative probabilistic prediction method using a Variational Autoencoder (VAE) combined with Gated Recurrent Unit (GRU) to forecast landslide deformations from a generative standpoint. Our approach consists of two main elements: firstly, training the VAE-GRU model to maximize the variational lower bound on the likelihood of historical precipitation data; secondly, using the learned approximated posterior distribution to predict imminent deformations from a generative angle. To assess the prediction quality, we use four widely-used metrics: Prediction Interval Coverage Probability (PICP), Prediction Interval Normalized Average Width (PINAW), Coverage Width-Based Criterion (CWC), and Prediction Interval Normalized Root Mean Square Width (PINRW). The results demonstrate that our proposed VAE-GRU framework surpasses traditional state-of-the-art (SOTA) probabilistic deformation prediction algorithms in terms of accuracy and reliability.

Engineering Saccharomyces cerevisiae for biodegradation and transformation of industrial toxic substances such as catechol (CA) has received widespread attention, but the low tolerance of S. cerevisiae to CA has limited its development. The exploration and modification of genes or pathways related to CA tolerance in S. cerevisiae is an effective way to further improve the utilization efficiency of CA. This study identified 36 genes associated with CA tolerance in S. cerevisiae through genome-wide identification and bioinformatics analysis and the ERG6 knockout strain (ERG6Δ) is the most sensitive to CA. Based on the omics analysis of ERG6Δ under CA stress, it was found that ERG6 knockout affects pathways such as intrinsic component of membrane and pentose phosphate pathway. In addition, the study revealed that 29 genes related to the cell wall-membrane system were up-regulated by more than twice, NADPH and NADP+ were increased by 2.48 and 4.41 times respectively, and spermidine and spermine were increased by 2.85 and 2.14 times, respectively, in ERG6Δ. Overall, the response of cell wall-membrane system, the accumulation of spermidine and NADPH, as well as the increased levels of metabolites in pentose phosphate pathway are important findings in improving the CA resistance. This study provides a theoretical basis for improving the tolerance of strains to CA and reducing the damage caused by CA to the ecological environment and human health.

Low-light imaging capabilities are in urgent demand in many fields, such as security surveillance, night-time autonomous driving, wilderness rescue, and environmental monitoring. The excellent performance of SPAD devices gives them significant potential for applications in low-light imaging. This article presents a 64 (rows) × 128 (columns) SPAD image sensor designed for low-light imaging. The chip utilizes a three-dimensional stacking architecture and microlens technology, combined with compact gated pixel circuits designed with thick-gate MOS transistors, which further enhance the SPAD’s photosensitivity. The configurable digital control circuit allows for the adjustment of exposure time, enabling the sensor to adapt to different lighting conditions. The chip exhibits very low dark noise levels, with an average DCR of 41.5 cps at 2.4 V excess bias voltage. Additionally, it employs a denoising algorithm specifically developed for the SPAD image sensor, achieving two-dimensional grayscale imaging under 6 × 10−4 lux illumination conditions, demonstrating excellent low-light imaging capabilities. The chip designed in this paper fully leverages the performance advantages of SPAD image sensors and holds promise for applications in various fields requiring low-light imaging capabilities.

In order to research the characteristics of minitype neutron reference radiation field regulated by ISO 8529 series standards, Monte Carlo simulation method was applied to calculate the ratio of room-scattered neutron response to the direct neutron response, neutron fluence and energy spectra in the radiation field. Firstly, the characteristics of the field were investigated from the four physical factors as shielding materials, field sizes, shielding thicknesses and borated polyethylene with different boron contents. Secondly, the response of sphere instrument with different diameters in the field and the influence of instrument on the field were analyzed. The results showed that minitype neutron reference radiation field with a size of 2 m × 2 m × 2 m, a shielding material of 5 % borated polyethylene and a shielding thickness of 10 cm was expected to be used for the calibration of neutron measuring instrument.

Summary: Fibrosis disrupts tissue balance and links to severe illnesses, impairing organ function and, in some cases, even fatality. The interaction between M2 macrophages and fibroblasts is vital for tissue equilibrium. Transforming growth factor β1 (TGF-β1) released by M2 macrophages plays a central role in fibrosis, regulating fibroblast activity and extracellular matrix metabolism. Targeting TGF-β1 is key to fibrosis treatment. In our study using three fibroblast cell lines, we reveal that the M2 macrophage transcription factor SP1 enhances binding to the TGF-β1 promoter motif, promoting TGF-β1 transcription and activating fibroblasts (This process does not involve changes in DNA methylation levels surrounding the motif sequence). The zinc fingers in SP1’s DNA-binding domain 3 are crucial for this binding. In vivo, targeting SP1 in rat ligaments significantly reduces extracellular matrix accumulation. Our findings highlight SP1 as a promising target for regulating tissue extracellular matrix and combating fibrosis.

With the development of biometric identification technology, finger vein identification has received more and more widespread attention for its security, efficiency, and stability. However, because of the performance of the current standard finger vein image acquisition device and the complex internal organization of the finger, the acquired images are often heavily degraded and have lost their texture characteristics. This makes the topology of the finger veins inconspicuous or even difficult to distinguish, greatly affecting the identification accuracy. Therefore, this paper proposes a finger vein image recovery and enhancement algorithm using atmospheric scattering theory. Firstly, to normalize the local over-bright and over-dark regions of finger vein images within a certain threshold, the Gamma transform method is improved in this paper to correct and measure the gray value of a given image. Then, we reconstruct the image based on atmospheric scattering theory and design a pixel mutation filter to segment the venous and non-venous contact zones. Finally, the degraded finger vein images are recovered and enhanced by global image gray value normalization. Experiments on SDUMLA-HMT and ZJ-UVM datasets show that our proposed method effectively achieves the recovery and enhancement of degraded finger vein images. The image restoration and enhancement algorithm proposed in this paper performs well in finger vein recognition using traditional methods, machine learning, and deep learning. The recognition accuracy of the processed image is improved by more than 10% compared to the original image.

More than 100,000 dams have been built in China and their safety conditions have drawn more attention to the stakeholders due to large socioeconomic effects, such as economic losses and casualties caused by dam incidents. Dam safety assessment was closely related to the safety conditions of various indicators and associated weights. However, traditional methods tended to adopt either the subjective weighting method (SWM) or the objective weighting method (OWM) to assess the weights of indicators, leading to an unreliable assessment of dam safety. To this end, this study proposed the game theory (GT)-based dam safety performance measure (DSPM) method to evaluate the safety level of dams. To assess the weights of all associated indicators of dams, the GT method that was used to capture the advantages of both the SWM and OWM was developed. The weights of each indicator were considered as variables and their values were obtained based on MATLAB. The DSPM that followed the form of the power-exponential function was proposed to assess dam safety. The whole method was exemplified by the five dams and the effectiveness of the proposed method was verified by comparing it with the code-based method (i.e., SL 258-2017). The results showed that the weights of indicators based on the analytic hierarchy process (AHP) method and the CRiteria Importance Through Intercriteria Correlation (CRITIC) method were different. The maximum and minimum percentage differences between the weights based on AHP and CRITIC methods were 107.4% and 3.1%, respectively, revealing that the weights obtained from only one method were unreliable. The proposed GT method was suitable for assessing the weights. Obtained superiority and inferiority rankings (SIRs) based on the GT-based DSPM and the code-based methods were consistent, which showed the effectiveness of the GT-based DSPM method. The code-based method concerning the dam safety levels was too rough to capture the dam performance accurately; the proposed method gave a more detailed classification, which provided important information on wise investments for the stakeholders when enhancing the performance of deficient dams.

As an important branch of computed tomography (CT), industrial CT is used widely in many fields, such as aerospace, military industry, and geological analysis fields, because of its advantages of high resolution, repeatability, and wide detection range. On the basis of thorough investigation and study, this paper summarizes three typical industrial CT technologies (i.e., seismic wave CT, resistivity CT, and electromagnetic wave CT) as well as the comprehensive geophysical exploration methods used in the geosciences. The current applications of industrial CT in pore structure studies, gas hydrate studies, digital core construction, and geological utilization and storage of carbon dioxide are introduced. The development trend of industrial CT in the geosciences is also discussed.

Rock and mineral samples contain a large amount of high-density metal substances, which often lead to metal artifacts in CT images and seriously affect the parameters analysis accuracy of rock and mineral samples. In order to improve the quality of CT images and suppress metal artifacts, in this paper we propose a dual-domain adaptive network-based metal artifact reduction algorithm for CT images of rock samples (DDA-CNN-MAR). The metal artifacts are suppressed by the projection domain network and the image domain network successively, and the dual domain processing results are adaptively fused to realize the end-to-end mapping from images with artifacts to artifact-free images. The algorithm is based on the residual encoder-decoder network model (RED-CNN), which is easy to extract features and restore image details. The dual-domain structure can adaptively adjust the weights of the projection domain (artifact suppression) and image domain (detail inpainting) to obtain optimal reduction results. The experimental results show that, compared with the RED-CNN metal artifact denoising method in the image domain, the MSE of the image corrected by the DDA-CNN-MAR method is reduced by 2.570, while the PSNR and SSIM are increased by 1.218 dB and 0.018 respectively, which effectively improves the CT image quality.

Nanofluidics is the study on the behavior of fluid flow in a nanoscale-confined channel with at least one characteristic dimension smaller than 100 nm. Nanofluidics can exhibit unique physical phenomena such as ultrafast water transport, surface charges control ion transport that cannot be observed at microscales or in bulk structures. A significant growth of attention in nanofluidics was achieved due to the representative phenomena and effects, which make them potentially useful in osmosis energy generation, nanofluidic diodes or transistors, desalination, biology, and other applications. In the past few years, the fabricating nanofluidic channels is burgeoning throughout the globe and can be widely used for energy conversion due to the rapid advancement of micro- and nanotechnology. This review mainly focused on the research progress of the nanofabrication methods of nanofluidic channels, including nanolithography, microelectromechanical system(MEMS) based techniques, nanofluidic channels based on nanomaterials, and other natural nanofluidic materials. The preparation methods including electron beam lithography, focused ion beam lithography, scanning probe lithography, extreme ultraviolet lithography, interference lithography, and sacrificial layer releasing were discussed in detail. The advantages and disadvantages of each nanofabrication method were pointed out. Following that, the recent application progress of nanofluidics from five aspects was summarized: in salt differenatial energy conversion, responsive ionic gate, sensors of ion detection, sensing of single molecules, and water desalination. Finally, the current challenges were discussed, and the fantastic opportunities and perspectives in the fabrication of nanofluidic channels were prospected, such as high cost, reliability and stability need to beimproved, etc.

The complex structure of Neogene mudstone plays an important role in geological disasters. A close relationship exists between the mechanisms of mudstone landslides and the disintegration characteristics of rocks. Therefore, understanding the disintegration characteristics of Neogene mudstone at different depths is crucial for enhancing engineering safety and assessing landslide stability. This study employed Neogene mudstone from different depths to perform disintegration and plastic limit experiments and revealed the sliding mechanisms of landslides involving Neogene mudstone, providing theoretical support for mitigating mudstone geological disasters. Our results demonstrate that Neogene mudstone from different depths experiences varied stress conditions and pore water pressure due to geological actions, significantly affecting the disintegration characteristics. By ignoring the factors of the slip surface, the slake durability index of mudstone decreases with increasing burial depth, while the plasticity limit index tends to rise. The influence of groundwater, geo-stress, and pore structure on Neogene mudstones at different depths results in overall weak stability and disintegration. Landslide occurrences are likely connected to the mechanical properties of mudstones at the slip surface, where a low slake durability index and higher plasticity index make the mudstones prone to fracturing, breaking, and disintegrating once in contact with water.

To discern the indiscernibles is the main purpose of Danto’s philosophy of art. Influenced by analytical philosophy, Zen Buddhism, and symbolism, three ways of discernment can be identified in Danto’s text: the external discernment, the internal discernment, and the middle discernment, which, roughly speaking, mean a discernment by means of examining the object, self-reflection or enlightenment, and the relation between experience and expression, in Danto’s terms, the aboutness and embodiment, respectively. However, neither analytic philosophy and its external discernment nor Zen and its internal discernment can distinguish the indiscernible indeed, only symbolism and its middle discernment have the potential to do so. Unfortunately, Danto was so indulged in analytical philosophy and Zen that he could not see this promise from symbolism.

Abstract There is a potential correlation between G-protein-coupled receptor-associated sorting protein 1 (GASP1) and breast tumorigenesis. However, its biological function and underlying molecular mechanism in breast cancer have not been clearly delineated. Here, we demonstrated that GASP1 was highly expressed in breast cancers, and patients harboring altered GASP1 showed a worse prognosis than those with wild-type GASP1. Functional studies showed that GASP1 knockout significantly suppressed malignant properties of breast cancer cells, such as inhibition of cell proliferation, colony formation, migration, invasion and xenograft tumor growth in nude mice as well as induction of G1-phase cell cycle arrest, and vice versa. Mechanistically, GASP1 inhibited proteasomal degradation of insulin-like growth factor 1 receptor (IGF1R) by competitively binding to IGF1R with ubiquitin E3 ligase MDM2, thereby activating its downstream signaling pathways such as NF-κB, PI3K/AKT, and MAPK/ERK pathways given their critical roles in breast tumorigenesis and progression. IGF1, in turn, stimulated GASP1 expression by activating the PI3K/AKT pathway, forming a vicious cycle propelling the malignant progression of breast cancer. Besides, we found that GASP1 knockout obviously improved the response of breast cancer cells to paclitaxel. Collectively, this study demonstrates that GASP1 enhances malignant behaviors of breast cancer cells and decreases their cellular response to paclitaxel by interacting with and stabilizing IGF1R, and suggests that it may serve as a valuable prognostic factor and potential therapeutic target in breast cancer.

Intervertebral disc degeneration (IDD) is a primary contributor to low back pain. Immune cells play an extremely important role in modulating the progression of IDD by interacting with disc nucleus pulposus (NP) cells and extracellular matrix (ECM). Encased within the annulus fibrosus, healthy NP is an avascular and immune-privileged tissue that does not normally interact with macrophages. However, under pathological conditions in which neovascularization is established in the damaged disc, NP establishes extensive crosstalk with macrophages, leading to different outcomes depending on the different microenvironmental stimuli. M1 macrophages are a class of immune cells that are predominantly pro-inflammatory and promote inflammation and ECM degradation in the NP, creating a vicious cycle of matrix catabolism that drives IDD. In contrast, NP cells interacting with M2 macrophages promote disc tissue ECM remodeling and repair as M2 macrophages are primarily involved in anti-inflammatory cellular responses. Hence, depending on the crosstalk between NP and the type of immune cells (M1 vs. M2), the overall effects on IDD could be detrimental or regenerative. Drug or surgical treatment of IDD can modulate this crosstalk and hence the different treatment outcomes. This review comprehensively summarizes the interaction between macrophages and NP, aiming to highlight the important role of immunology in disc degeneration.

It is highly significant from a research standpoint and a valuable practice to identify diseases, symptoms, drugs, examinations, and other medical entities in medical text data to support knowledge maps, question and answer systems, and other downstream tasks that can provide the public with knowledgeable answers. However, when contrasted with other languages like English, Chinese words lack a distinct dividing line, and medical entities have problems such as long length and multiple entity types nesting. Therefore, to address these issues, this study suggests a medical named entity recognition (NER) approach that combines part-of-speech and stroke features. First, the text is fed into the BERT pre-training model to get the semantic representation of the text, while the part-of-speech feature vector is obtained using the part-of-speech dictionary, and the stroke feature of the text is extracted through a convolution neural network (CNN). The word vector is then joined with the part-of-speech and stroke feature vectors, respectively, and input into the BiLSTM and CRF layer for training. Additionally, to balance the disparity in data volume across several types of entities, the class-weighted loss function is included in the loss function. According to the experimental findings, our model’s F1 score on the CCKS2019 dataset reaches 78.65%, and the recognition performance exceeds many existing algorithms.

The ontology of artworks tells us that a work of art, for example, a painting, cannot be identified as either physical or mental object. By the same token, this paper argues the working of art or artistic labor cannot be identified as either physical or mental labor. However, the works and workings of art are regarded as either physical or mental in the prevailing aesthetic theory. The main reason is that classical Western metaphysics is bifurcated. However, traditional Chinese division of ontological categories is not a bifurcation but a trifurcation, which consists of dao道, xiang象, and qi器. This tripartite distinction avoids substantivism, while at the same time providing a framework that encompasses both the objective and the subjective face of the art work, by means of a dynamic exchange between the two poles. This paper shifts our perspective from classical Western metaphysics to traditional Chinese metaphysics and sets up a dialogue between Chinese and Western aesthetics. The ontological status of works and workings of art is neither physical nor mental, but the “betweenness” of the two.

For the hilly-plain-wetland complex ecosystem in the cold region of Northeast China, in order to solve the problems, which include the scarcity of surface rainfall stations and the inability to provide accurate surface precipitation for hydrological process simulation, based on the observed precipitation of rainfall stations, three remote sensing precipitation products are taken as objects of evaluation. They include TRMM (Tropical Rainfall Measuring Mission) 3B42V7,3B42RT and CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data,CHIP). In this paper, the observation data of rainfall stations and IDWP precipitation data interpolated by IDW (Inverse Distance Weighted) are used as true value of precision comparison, and the detection accuracy of remote sensing precipitation products from 2001 to 2010 is evaluated on the time scale (day, month and quarter) and spatial scale in Naoli River Basin.The results of the study indicated that 3B42V7 and CHIP have a high detection accuracy for precipitation, and their CC (correlation coefficient) values are 0.47 and 0.49 respectively in daily time scale. The accuracy of their observation for monthly precipitation is better than that of daily precipitation, and the CC are 0.85 and 0.87 respectively. The multi-year average precipitation at different grid positions in the basin is overestimated by 3B42RT, and its evaluation results are poor at different time scales. For the precipitation intensity range of (0,20], the observed results of 3B42V7 and rainfall station are close to each other. For the precipitation intensity ranges of (0,1) and (50,+∞), 3B42RT and CHIP have overestimated or underestimated the precipitation in different degrees. Based on the above analysis results, 3B42RT can be considered as data that can detect whether precipitation occurs on different spatial positions in the basin. 3B42V7 and CHIP can be applied to flood forecasting and non-point source pollution control in cold regions. HIGHLIGHTS The research area of this paper is a hilly-plain-wetland complex ecosystem, and its climate state is complex, so there are few studies on this research area.; This paper studies the change of remote sensing precipitation with topography.; This paper makes a statistical analysis of the error changes of remote sensing precipitation;

In the construction industry, the labor shortage is a global issue. Characterized by the forming process of layered extrusion and rapid solidification, 3D concrete printing (3DCP) technology begins to be used in digital concrete construction to minimize the demand for manpower. However, the utilization of 3DCP in full-scale architectural constructions is still in its infancy, involving many manual processes like rebars-binding and formwork-making, which reduces the benefits of construction automation that should be brought by such technology. Therefore, this study proposes a design-to-printing workflow to 3D print the entire structure of a farmhouse in Wujiazhuang (WJZ) village. Firstly, design strategies are built up by a series of multi-disciplinary research, including printing system development, site planning, material design, and structure evaluation. Secondly, construction strategies involving printing process organization and man-hour-saving construction methods are utilized in the 3D printing process. By applying the introduced workflow, the project saves 62.4 % of human resources compared with the traditional reinforced concrete (RC) method, and the participation of 3D printing technologies arises from 18.3 % in the common 3DCP scenario to 76.5 % in this project. The on-site construction duration of the WJZ farmhouse is also reduced by 24.5 % in comparison with the unplanned construction process.

Aflatoxins are potent carcinogenic compounds, mainly produced by fungi species of the genus Aspergillus in the soil. Because of their stability, they are difficult to remove completely, even under extreme conditions. Aflatoxin contamination is one of the main causes of safety in peanuts, maize, wheat and other agricultural products. Aflatoxin contamination originates from the soil. Through the investigation of soil properties and soil microbial distribution, the sources of aflatoxin are identified, aflatoxin contamination is classified and analysed, and post-harvest crop detoxification and corresponding contamination prevention measures are identified. This includes the team’s recent development of the biofungicide ARC-BBBE (Aflatoxin Rhizobia Couple-B. amyloliquefaciens, B. laterosporu, B. mucilaginosus, E. ludwiggi) for field application and nanomaterials for post-production detoxification of cereals and oilseed crops, providing an effective and feasible approach for the prevention and control of aflatoxin contamination. Finally, it is hoped that effective preventive and control measures can be applied to a large number of cereal and oilseed crops.

Controversy over the geodynamic interpretation of the early Paleozoic granites in the South China Block constrains understanding of tectonic–magmatic evolution. In this paper, we present zircon U-Pb age, Hf isotope, and major and trace element data of the early Paleozoic granites in the Jilongjie region, south-central Hunan Province. A sample that yielded a weighted average 206Pb/238U age of 425 ± 3 Ma falls into the post-collisional granite field in the classification discriminant of magmatic rocks. Geochemical features indicate that the Jilongjie pluton is a shoshonitic metaluminous rock. The Jilongjie pluton’s chondrite-normalized rare earth element patterns exhibit a slight enrichment of light rare earth elements (LREEs) relative to heavy rare earth elements (HREEs) with (La/Yb)N ratios of 15.1–23.7 and weak Eu anomalies (Eu/Eu* = 0.68–0.78). Zircon Hf isotope results show εHf(t) ranging from −9.94 to −0.69. Jilongjie granite’s parent magma originated from a mixing of crust-derived felsic and mantle-derived mafic magmas, which then underwent fractional crystallization during its ascent. Jilongjie granite was generated through a post-collisional extensional setting associated with delamination of the thickened lithosphere.

AbstractPreexisting fissures within a natural rock mass significantly affect the mechanical responses of underground engineering rocks when subjected to coupled static-dynamic loads. Understanding the dynamic mechanical responses of prestressed fissured rocks is beneficial for optimizing the stability of rock engineering structures. Based on the split Hopkinson pressure bar (SHPB) device, a series of coupled static-dynamic compression tests were systematically performed to investigate the mechanical properties, the failure behaviors, the fragment characteristics, and the energy dissipation of unparallel-fissured rocks. Results show that the coupled dynamic strength increases with the applied strain rate for a given static prestress, while the elastic modulus does not exhibit any clear loading rate dependence. Under the given strain rate, the fissured sandstone has the highest strength under the static prestress of 0.6 uniaxial compressive strength (σs), followed by the static prestress of 0.4 σs, 0.2 σs, and 0.8 σs. The failure modes of fissured sandstone highly depend on the dynamic strain rate, and the ultimate failure pattern gradually changes from the mixed tensile-shear failure mode to the shear failure dominant mode with increasing strain rate. With an increasing dynamic strain rate, fissured rocks should absorb more energy in a short time, which results in more crack formation in the failure process. A higher static prestress can induce greater energy dissipation density and energy utilization efficiency when the static prestress is less than 0.8 σs. In addition, the relationships between energy dissipation and mechanical response of fissured sandstones under coupled static-dynamic loads are established and discussed.

Glioblastoma multiforme (GBM) has been identified as a frequently occurring adult primary brain cancer that is highly aggressive. Currently, the prognostic outcome for GBM patients is dismal, even with intensive treatment, and the median overall survival (OS) is 14.6 months. Immunotherapy, which is specific at the cellular level and can generate persistent immunosurveillance, is now becoming a promising tool to treat diverse cancers. However, the complicated nature of the tumor microenvironment (TME) makes it challenging to develop anti-GBM immunotherapy because several cell types, cytokines, and signaling pathways are involved in generating the immunosuppressive environment. Novel immunotherapies can illustrate novel tumor-induced immunosuppressive mechanisms. Here, we used unsupervised clustering analysis to identify different subtypes of immune cell infiltration that actuated different prognoses, biological actions, and immunotherapy responses. Gene cluster A, with a hot immune cell infiltration phenotype, had high levels of immune-related genes (IRGs), which were associated with immune pathways including the interferon-gamma response and interferon-alpha response, and had low IDH1 and ATRX mutation frequencies. Gene cluster B, a cold immune cell infiltration subtype, exhibited a high expression of the KCNIP2, SCRT1, CPLX2, JPH3, UNC13A, GABRB3, ARPP21, DLGAP1, NRXN1, DLL3, CA10, MAP2, SEZ6L, GRIA2, and GRIA4 genes and a low expression of immune-related genes, i.e., low levels of immune reactivity. Our study highlighted the complex interplay between immune cell infiltration and genetic mutation in the establishment of the tumor immune phenotype. Gene cluster A was identified as an important subtype with a better prognosis and improved immunotherapy response.

BackgroundListeria monocytogenes is an important food-borne bacterium. It rarely infects patients with complete immunity and causes meningocephalitis. Patients with severe Listeria encephalitis always experience a bad prognosis.Case PresentationA 39-year-old male patient was admitted to our hospital due to fever for more than 10 days and disturbance of consciousness accompanied by convulsions for 2 days. Metagenomic next-generation sequencing (mNGS) results showed L. monocytogenes in both cerebrospinal fluid (CSF) and blood, indicating L. monocytogenes encephalitis. Autoimmune encephalitis and central nervous system (CNS) demyelinating autoantibodies in the CSF also showed positive results. The case was finally diagnosed as severe Listeria encephalitis with complicated or secondary autoimmune encephalitis and CNS demyelinating diseases.ConclusionsIt is necessary to carry out infection and immunity screening in patients with severe encephalitis, especially for immunocompromised patients. mNGS plays a pivotal role in screening patients with severe and difficult neurological diseases.

Salt stress is one of the most devastating environmental factors threatening soybean growth and yield. However, the molecular link between salt stress and epigenetics has not been well-elucidated in soybean. In this study, from the wild soybean cDNA library, we isolated a GsSnRK1 kinase interacting protein (GsMSTY1) which is phylogenetically homologous with histone acetyltransferase MYST family with unknown function. GsMSTY1 gene is dominantly expressed in wild soybean roots and is highly responsive to abiotic stresses. GsMYST1 was able to be phosphorylated at the Ser44 site by GsSnRK1 and demonstrated in vivo acetyltransferase activity in transgenic soybean roots revealed by an anti-H4ace antibody. A transcription factor protein GsNAC83 was identified to interact with both GsMYST1 and GsSnRK1, and GsNAC83 could recruit the GsMYST1-GsSnRK1 module to COR15B gene promoter determined by ChIP-qPCR assay. To dissect the molecular functions of this ternary complex, we treated the transgenic soybean roots with salt stress and found that the stress could activate GsSnRK1, and the activated GsSnRK1 subsequently phosphorylated GsMYST1 to enhance its acetyltransferase activity which may epigenetically promote the target gene expression. To explore the physiological functions, we coexpressed GsSnRK1 and GsMYST1 genes in soybean hairy roots and found that only GsSnRK1(wt)/GsMYST1(wt) but not the mutant genes could promote soybean resistance to salt stress, implicating that phosphorylation of GsMYST1 is required for it to acetylate histone H4 on the target genes to upregulate expression of the stress-related genes. Our data shed new light on the functions of the GsSnRK1-GsMYST1-GsNAC83 module and its regulatory mechanism on plant tolerance to abiotic stresses.

The petrogenesis of A-type granites with different occurrences in the Nanling Range remains unclear. In this study, a case study of the Jiuyishan complex massif and Xianghualing intrusive stocks was conducted to determine this problem. The Jiuyishan complex massif is composed of four units (Jinjiling, Pangxiemu, Shaziling and Xishan). These four units have similar zircon U-Pb ages of approximately 153 Ma, with high Zr + Nb + Ce + Y contents (>350 ppm), high 10,000 Ga/Al ratios (>2.6), and a high crystallization temperature, indicating A-type affinities. They show a gradual change in lithology and geochemistry, implying a fractional crystallization process. These units also have similar εNd(t) values (−8.2 to −5.8) and zircon εHf(t) values (−7.5 to −2.2) except for the Shaziling MMEs (mafic microgranular enclaves) (−14.2 to 4.8), demonstrating their lower crustal source. However, the Shaziling unit may have contributed mantle-derived magma based on the geochemical data of its hosted MMEs. In comparison, the two Xianghualing intrusive stocks have similar geochemical features but exhibit highly evolved features (high Rb, U, Y, Ta and Nb contents and low Eu, Ba, Sr, P, Ti, Ca, Mg and Fe contents, with V-shaped REE distribution patterns). They have different zircon U-Pb ages of approximately 160 Ma and 155 Ma. The two stocks also have similar whole-rock εNd(t) values (−6.5 to −5.7) and zircon εHf(t) values (−7.6 to −2.7) and equally illustrate a lower crustal source region. Combining with their vertical zonation, they may have experienced remarkable fractional crystallization with possible assimilation processes. We propose that the Jiuyishan complex and Xianghualing stocks have two distinct fractional crystallization mechanisms during their formation. The Jiuyishan complex was formed by in situ crystal mush fractionation, while the Xianghualing stocks were formed by flowage differentiation during magma ascent or gravitational settling during magma solidification after emplacement. However, more than one mechanism affected the fractional crystallization processes of these granitic rocks.

In this work, we developed and validated two novel imaging geometries of benchtop multi-pinhole X-ray fluorescence computed tomography (XFCT) systems with Geant4 Toolkit. One of the Monte Carlo (MC) models utilized a fan beam source to illuminate a single slice of the object, a detector and a multi-pinhole collimator to image each slice’s X-ray fluorescence (XRF). The other model consisted of a cone-beam X-ray source (designed as a 5 mm wide fan beam to reduce simulation time) to scan the whole object, two detectors and two multi-pinhole collimators to image the emissions. The phantom used in the simulations included four sections, each with three cone-shaped gold nanoparticle (GNP) inserts (5 mm in height, 3 mm in diameter across the top) with center-to-center distances of 4 mm, 4.5 mm and 4.86 mm. The GNPs concentration was 0.1 wt. %, 0.3 wt. %, 0.5 wt. % and 0.7 wt. %, respectively. The diameter of the multi-pinhole collimator was 1 mm. Performance was evaluated for pinhole-detector-distance (PDD) of 5 cm, 3.5 cm and 2.5 cm, and the results for different object layers and for single pinhole and multi-pinhole (9 pinholes) imaging were compared. The data showed that results worsened with decreasing GNPs insert diameters and with decreasing PDD (object-pinhole-distance was fixed). The multi-pinhole configurations performed better than a single pinhole. The detection limit for the first multi-pinhole operation was 0.21 wt. %; the second was 0.24 wt. %. Detection limits for the single pinhole were 0.32 wt. % and 0.35 wt. %, respectively. The first MC model could acquire 2D slice images of the object without rotation and the second MC model could image the 3D object efficiently. These two novel multi-pinhole systems could potentially provide a bioimaging modality for nanomedical applications.

The public and social health burdens of ischemic stroke have been increasing worldwide. Hyperglycemia leads to a greater risk of stroke. This increased risk is commonly seen among patients with diabetes and is in connection with worsened clinical conditions and higher mortality in patients with acute ischemic stroke (AIS). Therapy for stroke focuses mainly on restoring cerebral blood flow (CBF) and ameliorating neurological impairment caused by stroke. Although choices of stroke treatment remain limited, much advance have been achieved in assisting patients in recovering from ischemic stroke, along with progress of recanalization therapy through pharmacological and mechanical thrombolysis. However, it is still necessary to develop neuroprotective therapies for AIS to protect the brain against injury before and during reperfusion, prolong the time window for intervention, and consequently improve neurological prognosis. Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are broadly regarded as effective drugs in the treatment of type 2 diabetes mellitus (T2DM). Preclinical data on GLP-1 and GLP-1 RAs have displayed an impressive neuroprotective efficacy in stroke, Parkinson's disease (PD), Alzheimer's disease (AD), Amyotrophic lateral sclerosis (ALS), and other neurodegenerative diseases. Based on the preclinical studies in the past decade, we review recent progress in the biological roles of GLP-1 and GLP-1 RAs in ischemic stroke. Emphasis will be placed on their neuroprotective effects in experimental models of cerebral ischemia stroke at cellular and molecular levels.

In a recent study, the PD-1 inhibitor has been widely used in clinical trials and shown to improve various cancers. However, PD-1/PD-L1 inhibitors showed a low response rate and were effective for only a small number of cancer patients. Thus, it is important to figure out the issue about the low response rate of immunotherapy. Here, we performed ssGSEA and unsupervised clustering analysis to identify three clusters (clusters A, B, and C) according to different immune cell infiltration status, prognosis, and biological action. Of them, cluster C showed a better survival rate, higher immune cell infiltration, and immunotherapy effect, with enrichment of a variety of immune active pathways including T and B cell signal receptors. In addition, it showed more significant features associated with immune subtypes C2 and C3. Furthermore, we used WGCNA analysis to confirm the cluster C-associated genes. The immune-activated module highly correlated with 111 genes in cluster C. To pick candidate genes in SD/PD and CR/PR patients, we used the least absolute shrinkage (LASSO) and SVM-RFE algorithms to identify the targets with better prognosis, activated immune-related pathways, and better immunotherapy. Finally, our analysis suggested that there were six genes with KLRC3 as the core which can efficiently improve immunotherapy responses with greater efficacy and better prognosis, and our study provided clues for further investigation about target genes associated with the higher response rate of immunotherapy.

To investigate the heavy metal contamination of soil in a uranium mining area in northern Guangdong, a physicochemical evaluation method was used to evaluate the contaminated soil near the pit and tailings pond of the uranium mining area, determine its heavy metal content and evaluate its ecological risk using the Nemerow integrated contamination index, ground accumulation index and potential ecological risk index. The results show that the average content of nine heavy metal elements in the soil of the uranium mining area exceeds the background value of red soil in Guangdong Province. Three pollution evaluation indices all indicate that Cd, As and U have serious pollution and high ecological risk, while the remaining elements are weakly polluted and the potential ecological risk of the six sampling sites all show very strong risk. On this basis, soil ecotoxicity was evaluated using ostracods (Cypridopsis vidua and Heterocypris sp.), Vibrio fischeri and Vicia faba L. Higher concentrations of heavy metals at individual sites (T1, T2, P2) resulted in higher mortality of ostracods, higher inhibition of Vibrio fischeri luminescence and a significant reduction in germination and pigmentation of broad beans. The results of the biotoxicity evaluation were consistent with the results of the physicochemical evaluation, allowing for a more direct and comprehensive evaluation of the ecotoxic effects of uranium and heavy metals in the mine soils.

The weighted mean temperature of the troposphere, Tm, is a key parameter in GNSS meteorology. It can be routinely derived based on meteorological data from radiosonde (RS) or numerical weather models. Alternatively, it can be also derived through a least-squares model of the ratio between the precipitable water vapor from RS data and the zenith wet delay estimates from GNSS measurement in the precise point positioning mode. In this last case, we found anomalous Tm values for the remote sub-tropical humid location of the Tahiti Island in the South Pacific Ocean and traced these anomalous values to anomalous zenith total delays (ZTD) that seem to have an accuracy poorer by one order of magnitude than the claimed accuracy of ZTD delays from worldwide databases. The possible causes of these discrepancies are discussed.

In the latest version of ISO 4037-1:2019 standard, the minimum dimension of a gamma radiation reference field was not clearly specified, which makes the construction of a minitype gamma reference radiation field lack of scientific basis. This paper carried out the research on the relationship between the scattering contribution and physical factors of the reference radiation regulated by ISO 4037-1. LS-SVM was applied to construct the relational model between physical factors and scattering contribution based on the data simulated by Monte Carlo method. Then the minimum dimension of collimated reference radiation field is obtained by PSO algorithm. For Co-60 source, the minimum size of the radiation field obtained is 93 cm(L)×40 cm(W)×40 cm(H). For Cs-137 source, the minimum size of the radiation field obtained is 153 cm(L)×47 cm (W)×47 cm(H). The results meet the requirements of the standard based on the model and provides a technical reference for the design of a minitype reference radiation field.

The energy crisis and environmental pollution have promoted the rapid development of renewable solar technology. Building integrated photovoltaics (BIPV) is an important field for the future development of solar energy. This review presents the mechanical property studies of existing BIPV and analyzes its research status to offer advice for engineering applications. By analyzing the types and mechanical characteristics of solar cells in the existing BIPV and determining the load conditions that need to be considered in different application modes, this paper summarizes the relevant existing studies at the photovoltaic material, cell and component levels and offers corresponding suggestions for mechanical research, which consequently results in the proposal of a new BIPV structure. Since the mechanical properties of BIPV have seldom been studied, and research on practical engineering applications is lacking, further comprehensive and in-depth research is needed to promote the safe and reliable application and popularization of photovoltaic building integration.

Wind turbines are widely installed as the new source of cleaner energy production. Dynamic and random stress imposed on the generator bearing of a wind turbine may lead to overheating and failure. In this paper, a data-driven approach for condition monitoring of generator bearings using temporal temperature data is presented. Four algorithms, the support vector regression machine, neural network, extreme learning machine, and the deep belief network are applied to model the bearing behavior. Comparative analysis of the models has demonstrated that the deep belief network is most accurate. It has been observed that the bearing failure is preceded by a change in the prediction error of bearing temperature. An exponentially-weighted moving average (EWMA) control chart is deployed to trend the error. Then a binary vector containing the abnormal errors and the normal residuals are generated for classifying failures. LS-SVM based classification models are developed to classify the fault bearings and the normal ones. The proposed approach has been validated with the data collected from 11 wind turbines.

Hemicellulose-based hydrogels are three-dimensional networks formed by crosslinking hydrophilic polymers with tunable swelling behavior,acceptable biocompatibility and mechanical properties,and have received much attention in the field of soft materials especially in hemicellulose-based materials.Herein,recent advances and developments in hemicellulose-based hydrogels were reviewed.The preparation methods,mechanism of their gelation process,and the performance of the hemicellulose-based hydrogels were presented from both chemical and physical cross-linking approaches,while the differences in various initiation systems such as light,enzyme,microwave irradiation and glow discharge electrolysis plasma in chemical cross-linking were compared.The latest applications of hemicellulose-based hydrogels in drug-controlled release,wound dressing,water purification,3D printing dispersions, etc,were introduced, respectively.Finally,the challenges in the development of hemicellulose-based hydrogels were summarized briefly and future prospect was also given,which provides a reference for the synthesis of new hemicellulose-based hydrogels.

Potential risk of X-ray radiation from computed tomography (CT) has been a concern of the public. However, simply decreasing the dose will degrade quality of the CT images and compromise diagnostic performance. In this paper, we propose a noise learning generative adversarial network coupling with least squares, structural similarity and L1 losses for low-dose CT denoising. In our method, noise distributed in the input low-dose CT image is learned by the generator network and then subtracted from the input to generate the final denoised version. The denoised CT images are penalized by the least squares loss function, and they are pulled toward boundary of the decision even though they are classified as normal-dose CT. Least squares stabilize the training process without regularization. Structural similarity and L1 losses are utilized to keep textural details and sharpness of the denoised CT images respectively. Experiments and results show that our method can effectively suppress noise and remove artifacts compared with the state-of-the-art methods. The texture statistical properties, which include mean, standard deviation, uniformity, and entropy, further confirm that the generated noise-reduced CT image is as close as to that of the normal-dose counterpart.

Polychromatic source X-ray fluorescence computed tomography (XFCT) is a novel imaging method, which is applied for the diagnosis and treatment studies of early stage cancer. In this paper, we propose a fast multi-pinhole L-shell XFCT imaging system to reduce the scan time and radiation dose, which has potential in detecting lower concentration of contrast agents (gold nanoparticles, GNPs). Two kinds of phantoms - the concentration-phantom 1 and the size-phantom 2 are designed to verify imaging performance for low-concentration and small-size ROI. The scanning processes are simulated by Geant4, and images are reconstructed by Optimized EM-TV algorithm. It is concluded that this imaging system is more sensitive in detecting low concentration GNPs than K-shell imaging system. Simulation experiments show the reconstructed images can achieve the highest CNR both for phantom 1 and phantom 2 with iterating 10 times. The detection limit can reach 0.16% when pinhole radius is 0.08mm.

The spectral computed tomography (CT) based on photon counting detectors can collect the incident photons with different energy ranges. However, due to the low photon counts in narrow energy bin and the unhomogeneous response problem of detector cells, there are severe noise and ring artifacts in reconstructed spectral CT images. We proposed an image denoising and ring artifacts removal method via improved Fully Convolutional Pyramid Residual Network (FCPRN). In our study, we scanned a mouse specimen with spectral CT based on photon counting detector, and reconstructed mouse CT images as data set. Then we use the data set to train our network for image denoising and ring artifacts removal. Experimental results demonstrated that the proposed method could reduce noise and suppress ring artifacts of spectral CT images concurrently in different energy ranges. And the performance of the FCPRN is better than that of some networks for CT image denoising.

Semantic segmentation networks focus on the scene parsing of an unrestricted open scene. The typical segmentation architectures are stacks consisting of convolutional layers, which are used to extract semantic features. The feature map dimension is sharply changed at sampling units for most of networks, which ensure effective propagation of the gradient in deep nets. In this article, we proposed a state-of-the-art network model named Fully Convolutional Pyramidal Networks (FC-PRNet), which employs pyramidal residual structure to change the feature map dimension at all convolutional layers. This design is an effective way of improving generalization ability and optimizing parameters, and FC-PRNet could achieve excellent capability of semantic extraction. We used urban scene benchmark CamVid and KITTI dataset to test our network, the experimental results show that FC-PRNet achieves better results without any pre-training or post-treatment module. Moreover, due to smart construction of pyramidal residual structures, FC-PRNet has less parameters than other existing networks trained on these datasets.

Under the influence of the linguistic turn in philosophy, contemporary Western philosophers typically limit their thinking on pluralism to the realm of language. This sort of pluralism can be named as pluralism of significance. I propose another version of pluralism in light of Confucianism, which extends the concerns from the realm of language to the realm of experience – I call it pluralism of presence. In this article, I first expound the aforementioned two versions of pluralism on the basis of Hans-Georg Moeller’s semiotic trichotomy. I then argue that the conflict between multiculturalism and cultural identity in today’s globalized world and the failure of pluralism of significance in resolving this conflict can be overcome by pluralism of presence. Finally, I show a possibility of reconciliation between pluralism of significance and pluralism of presence.

To maximize energy extraction, the nacelle of a wind turbine follows the wind direction. Accurate prediction of wind direction is vital for yaw control. A tandem hybrid approach to improve the prediction accuracy of the wind direction data is developed. The proposed approach in this paper includes the bilinear transformation, effective data decomposition techniques, long-short-term-memory recurrent neural networks (LSTM-RNNs), and error decomposition correction methods. In the proposed approach, the angular wind direction data is firstly transformed into time-series to accommodate the full range of yaw motion. Then, the continuous transformed series are decomposed into a group of subseries using a novel decomposition technique. Next, for each subseries, the wind directions are predicted using LSTM-RNNs. In the final step, it decomposed the errors for each predicted subseries to correct the predicted wind direction and then perform inverse bilinear transformation to obtain the final wind direction forecasting. The robustness and effectiveness of the proposed approach are verified using data collected from a wind farm located in Huitengxile, Inner Mongolia, China. Computational results indicate that the proposed hybrid approach outperforms the other single approaches tested to predict the nacelle direction over short-time horizons. The proposed approach can be useful for practical wind farm operations.

To assess the lipid requirements of O. macrolepis broodstock, five iso-nitrogenous diets (39 g kg−1) with five lipid levels, 50 (5 L), 70 (7 L), 90 (9 L),110 (11 L), and 130 (13 L; g kg−1), were made. A total of 105 three-year-old individuals (50.11 ± 2.86 g per fish) were divided into five groups (triplicate per group) and were fed with the diets, respectively, for eight weeks. Then, the fish were sampled, and items were determined. The results showed that growth rate and feed efficiency ratio were not significantly affected by diets (p > 0.05). A clear dose–response effect of dietary lipid was observed on somatic indexes of gonad indexes of the O. macrolepis brookstock, with the highest values corresponding to fish fed 9 and 11 g kg−1 lipids, in contrast, gonad indexes were reduced as dietary lipid moved away from this level. The other somatic indexes, such as viscerosomatic index, perivisceral fat index, etc., were not significantly affected by diets (p > 0.05). The content of crude lipid and crude protein in carcass, hepatopancreas, and gonad were not significantly affected by dietary lipid levels (p > 0.05). The gonad fatty acids of 16:0 and 22:6n-3 decreased and 18:2n-6 increased with the increasing lipid level, being significantly altered by diets (p < 0.05). The histological features of the gonad showed no significant difference among the five diets (p > 0.05). The relative expression of sex steroid-synthesizing proteins (fshr, 3β-hsd, 17β-hsd, aro., and star.) in the gonad of fish was most significantly highly expressed in the 9 L and 11 L groups (p < 0.05). The results suggested that a proper dietary lipid level of 90–110 g kg−1 could maintain gonad development of O. macrolepis broodstock without affecting growth performance.

It is an essential measure for workers to wear safety helmets when entering the construction site to prevent head injuries caused by object collision and falling. This paper proposes a lightweight algorithm for helmet-wearing detection based on YOLOV5, which is faster and more robust for helmet detection in natural construction scenarios. In this paper, the MCA attention mechanism is embedded in the backbone network to help the network extract more productive information, reduce the missed detection rate of small helmet objects and improve detection accuracy. In order to ensure the safety of workers in construction, it is necessary to detect whether the construction workers are wearing safety helmets in real-time to achieve monitoring on-site. A channel pruning strategy is proposed on the MCA-YOLOv5 algorithm to compress it, realizing the optimal large-scale model into ultrasmall models for real-time detection on embedded or mobile devices. The experimental results on the public data set show that the model parameter volume is reduced by 87.2%, and the detection speed is increased by 53.5%, even though the MCA-YOLOv5-light reduces the mAP slightly.

An extensive study has been conducted on a series of AlGaN/GaN high electron mobility transistor (HEMT) samples using metalorganic vapour phase epitaxy, to investigate the influence of growth modes for GaN buffer layers on device performance. The unintentional doping concentration and screw dislocation density are significantly lower in the samples grown with our special two-dimensional (2D) growth approach, compared to a widely-used two-step method combining the 2D and 3D growth. The GaN buffer layers grown by the 2D growth approach have achieved an unintentional doping density of 2 × 1014 cm−3, two orders lower than 1016 cm−3 of the GaN samples grown using a conventional two-step method. High-frequency capacitance measurements show that the samples with lower unintentional doping densities have lower buffer leakage and higher breakdown limits. This series of samples have attained sub-nA/mm leakages, a high breakdown limit of 2.5 MV/cm, and a saturation current density of about 1.1 A/mm. It indicates that our special 2D growth approach can effectively lessen the unintentional doping in GaN buffer layers, leading to low buffer leakage and high breakdown limits of GaN/AlGaN HEMTs.

The development of uranium mines has been necessary to obtain abundant and scarce uranium resources, but they also bring inevitable radioactive contamination to the surrounding soil, rivers and lakes. This paper explores the sensitivity of Cypridopsis vidua to the radioactive element uranium and the heavy elements cadmium and copper with single and combined acute toxicity experiments and combined toxicity model predictions. The results from the single toxicity experiments showed that the degree of toxic effects was cadmium > copper > uranium. The combined toxicity experiments showed that the compound toxicity of U-Cd and U-Cu was higher than the weakest component and lower than the strongest component, whereas the compound toxicity of Cd-Cu was higher than either of its components. When the overall proportion of a more toxic metal was increased, its mixed toxicity also increased, and vice versa. Combined toxicity predictions showed that the U-Cd combination was best described by the concentration additive (CA) model, the independent action (IA) model was more applicable to the Cd-Cu combination, and the most applicable model for the U-Cu combination changed depending on the concentration gradient. The acute toxicity data from this study provide a reference for the development of wastewater discharge standards for uranium mines, enriches the data related to the toxicity of uranium for ostracods and deepens the understanding of the threat of uranium pollution to aquatic ecosystems.

Heavy silicon-doping in GaN generally causes a rough surface and saturated conductivity, while heavily silicon-doped n++-AlGaN with ≤5% aluminum can maintain an atomically flat surface and exhibit enhanced conductivity. Given this major advantage, we propose using multiple pairs of heavily silicon-doped n++-Al0.01Ga0.99N and undoped GaN instead of widely used multiple pairs of heavily silicon-doped n++-GaN and undoped GaN for the fabrication of a lattice-matched distributed Bragg reflector (DBR) by using an electrochemical (EC) etching technique, where the lattice mismatch between Al0.01Ga0.99N and GaN can be safely ignored. By means of using the EC etching technique, the n++-layers can be converted into nanoporous (NP) layers whilst the undoped GaN remains intact, leading to a significantly high contrast in refractive index between NP-layer and undoped GaN and thus forming a DBR. Our work demonstrates that the NP-Al0.01Ga0.99N/undoped GaN-based DBR exhibits a much smoother surface, enhanced reflectivity and a wider stopband than the NP-GaN/undoped GaN-based DBR. Furthermore, the NP-Al0.01Ga0.99N/undoped GaN-based DBR sample with a large size (up to 1 mm in width) can be obtained, while a standard NP-GaN/undoped GaN-based DBR sample obtained is typically on a scale of a few 100 μm in width. Finally, a series of DBR structures with high performance, ranging from blue to dark yellow, was demonstrated by using multiple pairs of n++-Al0.01Ga0.99N and undoped GaN.