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Earthquake-triggered landslides represent a significant seismic-related disaster, posing threats to both the lives and property of individuals in affected areas. Furthermore, they can result in road and river blockages, as well as other secondary disasters, significantly impacting post-earthquake rescue efforts. Efficient, accurate, and rapid assessment of high-risk landslide zones carries important implications for decision making in disaster response and for mitigating potential secondary disasters. The high-intensity zones VII to IX of the Luding Ms6.8 earthquake on 5 September, 2022, were used as a case study here. Based on the simple Newmark model, the difference method and the cumulative displacement method were employed to assess earthquake-triggered landslides. The assessment results from both methods demonstrated that the areas posing an extremely high risk of earthquake-triggered landslides were predominantly situated on the western side of the Xianshuihe Fault. Verification using actual landslide data showed that both methods had high predictive accuracy, with the difference method slightly outperforming the cumulative displacement method. Moreover, this study recommends determining threshold values for each landslide risk interval having physical meanings using previous data on strong earthquakes when utilizing the difference method to assess the risk of earthquake-triggered landslides. [ABSTRACT FROM AUTHOR]

The Tibetan medicinal fruit E'seguo originates from two species, Malus toringoides (Rehd.) Hughes and Malus transitoria (Batal.) Schneid, both unique to the Hengduan Mountains. These species are predominantly found in high-altitude regions of Ganzi Prefecture, Sichuan Province, particularly in the Xianshui River and Yalong River basins. Malus toringoides (Rehd.) Hughes is far more abundant in both resource quantity and distribution compared to Malus transitoria (Batal.) Schneid. However, the nutritional and medicinal differences between the two remain unclear, which significantly impacts the development and utilization of E'seguo resources. This study aimed to measure the mineral content, nutritional components, and medicinal properties of E'seguo from 12 different regions of Ganzi Prefecture to explore the quality differences between these two species and across different regions. ICP-MS (Inductively Coupled Plasma Mass Spectrometry) was used to determine the mineral content, ultraviolet-visible spectrophotometry and potentiometric titration to analyze nutritional indicators, and HPLC (High-Performance Liquid Chromatography) to measure the medicinal components L-malic acid and 2-O-β-D-glucopyranosyl-L-ascorbic acid (AA-2βG). Results indicate that Malus transitoria (Batal.) Schneid contains higher levels of K, Ca, Zn, Mg, and Cu compared to Malus toringoides (Rehd.) Hughes, which has higher Fe and Mn content. Malus toringoides (Rehd.) Hughes from the Kangding and Litang regions showed the highest mineral content, with mineral elements primarily influencing polysaccharide levels, according to Mantel analysis. Nutritional and medicinal analyses revealed that Malus toringoides (Rehd.) Hughes outperformed Malus transitoria (Batal.) Schneid in all metrics except for the sugar-acid ratio. Given the mineral content and taste, Malus transitoria (Batal.) Schneid is better suited for consumption, while Malus toringoides (Rehd.) Hughes has superior medicinal properties, making it more appropriate for medicinal use. In the Malus transitoria (Batal.) Schneid regions, both Luhuo and Daofu are in the Xianshui River basin, with Daofu County producing the higher quality fruit. Among the nine Malus toringoides (Rehd.) Hughes regions, the M10 (Tuoba Township, Ganzi County) near the Yalong River had the highest overall score, followed by M7 (Yade Township, Luhuo County) and M6 (Keke, Xiala Tuo Town, Luhuo County), both of which are near the Xianshui River. In summary, Malus transitoria (Batal.) Schneid generally has higher mineral content, but Malus toringoides (Rehd.) Hughes has larger fruit and higher medicinal value, making the latter more suitable as a medicinal resource. At the same time, the medicinal quality of Xianshui River fruit was higher in the two watersheds of Malus toringoides (Rehd.) Hughes. [ABSTRACT FROM AUTHOR]

Ceramsite concrete is one of the most widely used lightweight concretes at present. Although mechanical properties of ceramsite concrete have been extensively discussed, its permeability characteristics are neglected in previous studies. Considering the importance of permeability resistance to concrete, the permeability grade and residual compressive strength after permeability of ceramsite concrete are analyzed in this study. The influence of ceramsite content and size on the permeability grade and residual strength of ceramsite concrete were investigated by the orthogonal experimental method. To further understand the above influence, an improved Bayesian framework for small sample data is also established to analyze the permeability grade and residual strength. Results show that the water–binder ratio and the content of 20–30 mm ceramsite aggregates are the most and least significant influencing factors affecting the permeability characteristics, respectively. The 5–10 mm and 10–20 mm ceramsite aggregates play secondary roles. Increasing 5–10 mm and 10–20 mm ceramsite aggregates is not helpful for improving the permeability resistance of ceramsite concrete. Compared with the orthogonal method, the proposed Bayesian framework is a useful tool for revealing the effects of various factors, which can cut the time cost and provide parameter visualization for the analysis process. Results show that the permeability resistance and residual strength of ceramsite concrete are improved significantly under optimal conditions. The permeability grade and residual strength are increased 200% and 80.3%, respectively. In addition, the residual strength may be more suitable for evaluating the permeability characteristics than the permeability grade. [ABSTRACT FROM AUTHOR]

Sound source identification technology based on a microphone array has many application scenarios. The compressive beamforming method has attracted much attention due to its high accuracy and high-resolution performance. However, for the far-field measurement problem of large microphone arrays, existing methods based on fixed grids have the defect of basis mismatch. Due to the large number of grid points representing potential sound source locations, the identification accuracy of traditional grid adjustment methods also needs to be improved. To solve this problem, this paper proposes a sound source identification method based on adaptive grid splitting and refinement. First, the initial source locations are obtained through a sparse Bayesian learning framework. Then, higher-weight candidate grids are retained, and local regions near them are split and updated. During the iteration process, Green's function and the source strength obtained in the previous iteration are multiplied to get the sound pressure matrix. The robust principal component analysis model of the Gaussian mixture separates and replaces the sound pressure matrix with a low-rank matrix. The actual sound source locations are gradually approximated through the dynamically adjusted sound pressure low-rank matrix and optimized grid transfer matrix. The performance of the method is verified through numerical simulations. In addition, experiments on a standard aircraft model are conducted in a wind tunnel and speakers are installed on the model, proving that the proposed method can achieve fast, high-precision imaging of low-frequency sound sources in an extensive dynamic range at long distances. [ABSTRACT FROM AUTHOR]

Research on dietary fatty acids (FAs) and lung health has reported skeptical findings. This study aims to examine the causal relationship between circulating FAs and Chronic Obstructive Pulmonary Disease (COPD) onset and exacerbation, using a two-sample Mendelian Randomization (MR) analysis. Strong and independent genetic variants of FAs were obtained from the UK Biobank of European ancestry. The exposure traits included saturated FA (SFA), poly- and mono-unsaturated FA (PUFA and MUFA), omega-3 and omega-6 PUFA, docosahexaenoic acid (DHA), and linoleic acid (LA), all expressed as total FA (TFA) percentages. Summary statistics for COPD outcomes were obtained from the FinnGen consortium including COPD, COPD hospitalization, COPD/asthma-related infections, COPD-related respiratory insufficiency, and COPD/asthma/interstitial lung disease (ILD)-related pneumonia. The inverse-variance weighted (IVW) was the primary MR approach. MR-Egger regression and MR-PRESSO were utilized to evaluate heterogeneity and pleiotropy. MR-PRESSO tests suggested no obvious horizontal pleiotropy. MR results by the IVW approach indicated that the genetically high SFA/TFA levels were associated with an increased risk of COPD/asthma/ILD-related pneumonia (OR: 1.275, 95%CI: 1.103–1.474, p for FDR = 0.002). No significant relationship was observed between other types of FAs and COPD outcomes. Our MR analysis suggests that there is weak evidence that the genetically predicted high SFA/TFA was associated with an increased risk of pneumonia. [ABSTRACT FROM AUTHOR]

Dark septate endophytes (DSE) commonly inhabit the root systems of plants that flourish in heavy metal-contaminated soils. Nevertheless, there is limited understanding regarding the overall response of medicinal plants to DSE under heavy metal stress. The present study utilized a non-sterile pot experiment to evaluate the beneficial impacts of DSE (Paraphoma chlamydocopiosa, Paraboeremia selaginellae, and Paraphoma radicina) inoculation on Astragalus mongholicus under cadmium (Cd) stress. At 0 mg Cd/kg soil, inoculation with DSE led to a significant increase in the total biomass of the host plant by up to 34.0%. Although plant biomass decreased at 5 mg Cd/kg soil and 10 mg Cd/kg soil, the total biomass of the host plant increased by up to 72.3% after DSE inoculation. The plant height, branch number, soil and plant analyzer development (SPAD) value, and biomass were not affected by Cd concentration after inoculation with P. chlamydocopiosa and P. selaginellae. DSE emerged as the most prominent explanatory variable (44.2%) for plant growth at 10 mg Cd/kg soil. Inoculation with P. chlamydocopiosa increased root length by 47.9% and root biomass by 74.1%, and inoculation with P. chlamydocopiosa and P. selaginellae increased the indole-3-acetic acid (IAA) content by 103.6% and 105.8%, respectively, at 10 mg Cd/kg soil. Additionally, P. radicina inoculation was preferred to increase the content of calycosin-7-O-glucoside, while P. chlamydocopiosa increased the content of formononetin. DSE enhanced the accumulation of Cd in the shoot, whereas P. radicina exhibited an inhibitory effect on Cd accumulation in the root system. P. chlamydocopiosa decreased the Cd translocation factor, while P. radicina increased the Cd translocation factor, which exceeded one. The interaction between DSE and soil factors significantly contributed to the host plant growth. DSE inoculation improved soil organic carbon content and inoculation with P. chlamydocopiosa, and P. selaginellae reduced available nitrogen content, regardless of the Cd stress. DSE inoculation reduced available phosphorus content at 10 mg Cd/kg soil. Importantly, P. radicina promote the performance and calycosin-7-O-glucoside accumulation of the host plant, and reduced Cd content in the roots at 5 mg Cd/kg soil. These data enhanced comprehension of the ecological function of DSE in heavy metal-contaminated soils and demonstrated the potential utility of DSE strains for cultivating medicinal plants. [ABSTRACT FROM AUTHOR]

Large-scale yield estimation in the field or plot during wheat grain filling can contribute to high-throughput plant phenotyping and precision agriculture. To overcome the challenges of poor yield estimation at a large scale and for multiple species, this study employed a combination of multispectral and RGB drones to capture images and generation of time-series data on vegetation indices and canopy structure information during the wheat grubbing period. Five machine learning methods, partial least squares, random forest, support vector regression machine, BP neural networks, and long and short-term memory networks were used. The yield estimation of wheat grain filling period data was executed using a long and short-term memory network based on the preferred machine learning model, with a particular focus on distinguishing different heat-tolerant genotypes of wheat. The results unveiled a declining trend in the spectral reflectance characteristics of vegetation indices as the filling period progressed. Among the time-series data of the wheat filling period, the long and short-term memory network exhibited the highest estimation effectiveness, surpassing the BP neural network, which displayed the weakest estimation performance, by an impressive improvement in R2 of 0.21. The three genotypes of wheat were categorized into heat-tolerant genotype, moderate heat-tolerant genotype, and heat-sensitive genotype. Subsequently, the long and short-term memory network, which exhibited the most accurate yield estimation effect, was selected for regression prediction. The results indicate that the yield estimation effect was notably better than that achieved without distinguishing genotypes. Among the wheat genotypes, the heat-sensitive genotype demonstrated the most accurate prediction with an R2 of 0.91 and RMSE% of 3.25%. Moreover, by fusing the vegetation index with canopy structure information, the yield prediction accuracy (R2) witnessed an overall enhancement of about 0.07 compared to using the vegetation index alone. This approach also displayed enhanced adaptability to spatial variation. In conclusion, this study successfully utilized a cost-effective UAV for data fusion, enabling the extraction of canopy parameters and the application of a long and short-term memory network for yield estimation in wheat with different heat-tolerant genotypes. These findings have significant implications for informed crop management decisions, including harvesting and contingency forecasting, particularly for vast wheat areas. [ABSTRACT FROM AUTHOR]

Owing to their structural diversity and mesoporous construction, metal–organic frameworks (MOFs) have been used as templates to prepare mesoporous metal oxides, which show excellent performance as anode materials for lithium-ion batteries (LIBs). Co-ZnO/C and Co-Co3O4/C nanohybrids were successfully synthesized based on a precursor of Co-doped MOF-5 by accurately controlling the annealing temperature and atmosphere. Experimental data proved that their electrochemical performance was closely associated with the material phase, especially for Co-ZnO/C, indicating that carbon skeleton materials can maintain a good restoration rate of over 99% after undergoing high-current density cycling. Meanwhile, Co-Co3O4/C nanohybrids showed an exceedingly high reversible capacity of 898 mAh∙g−1 at a current density of 0.1 C after 100 cycles. Their improved coulombic efficiency and superior rate capability contribute to a mesoporous structure, which provides pathways allowing for rapid Li+ diffusion and regulates volume change during charge and discharge processes. [ABSTRACT FROM AUTHOR]

Response surface tests were used to determine the optimal conditions for Bacillus subtilis solid-state fermentation of highland barley bran. The polyphenol composition and antioxidant activity of the fermented bran were also assessed. The results showed that the optimal fermentation conditions for highland barley bran were 10% inoculum, a liquid–feed ratio of 1.80, a fermentation temperature of 30 °C, and a fermentation time of 93.5 h. Under these conditions, the polyphenol content of highland barley bran was 12.43 mg/g. After fermentation, the ferulic acid content of the bran decreased, catechol and gallic acid contents increased significantly, and catechins shifted from the bound state to the free state. In addition, solid-state fermentation improved the antioxidant capacity of highland barley bran, and the DPPH• radical scavenging rate, Fe ion-reducing capacity, and hydroxyl radical scavenging rate of highland barley bran increased after fermentation. [ABSTRACT FROM AUTHOR]

Diagnosing agricultural machinery faults is critical to agricultural automation, and identifying vibration signals from faulty bearings is important for agricultural machinery fault diagnosis and predictive maintenance. In recent years, data–driven methods based on deep learning have received much attention. Considering the roughness of the attention receptive fields in Vision Transformer and Swin Transformer, this paper proposes a Shift–Deformable Transformer (S–DT) network model with multi–attention fusion to achieve accurate diagnosis of composite faults. In this method, the vibration signal is first transformed into a time–frequency graph representation through continuous wavelet transform (CWT); secondly, dilated convolutional residual blocks and efficient attention for cross–spatial learning are used for low–level local feature enhancement. Then, the shift window and deformable attention are fused into S–D Attention, which has a more focused receptive field to learn global features accurately. Finally, the diagnosis result is obtained through the classifier. Experiments were conducted on self–collected datasets and public datasets. The results show that the proposed S–DT network performs excellently in all cases. With a slight decrease in the number of parameters, the validation accuracy improves by more than 2%, and the training network has a fast convergence period. This provides an effective solution for monitoring the efficient and stable operation of agricultural automation machinery and equipment. [ABSTRACT FROM AUTHOR]

Excessive nitrogen application may adversely impact grain yield and quality of rice. This study aimed to evaluate the impact of several nitrogen-reduction strategies on the grain yield and quality of mechanically transplanted hybrid indica rice. Field experiments were performed in 2020 and 2021 using Yixiangyou2115 and Fyou498. The research investigated variations in grain yield and quality of rice under different nitrogen-reduction strategies, including NR1, balanced N reduction; NR2, N reduction in basal fertilizer; NR3, N reduction in tillering fertilizer; and NR4, N reduction in earing fertilizer, compared to the conventional nitrogen application for high-yield cultivation (CK). Compared to CK, the grain yield of rice decreased by 1.63% to 19.71% under nitrogen-reduction strategies. Relative to NR3 and NR4, NR1 and NR2 exhibited an increase in grain yield ranging from 1.81% to 22.51%, attributed to increases in panicle number (0.61% to 13.19%) and spikelet number per panicle (1.60% to 12.28%). Meanwhile, NR1 and NR2 also had relatively high LAI and dry matter accumulation in rice plants at maturity. Compared to CK, NR1 and NR2 improved the processing quality of rice grain, while NR3 and NR4 resulted in reduced processing quality. The chalkiness rate and chalkiness degree of rice under the NR1, NR3, and NR4 treatments were reduced by 2.97% to 23.73% and 3.35% to 52.49%, respectively, in comparison to CK. Additionally, the NR1 and NR4 treatments were linked to an increase in taste value by 1.44% to 3.66% and gel consistency by 13.87% to 46.01% relative to CK. These findings suggest that balanced nitrogen reduction can maintain a high yield while improving the appearance and eating quality of mechanically transplanted hybrid indica rice. This study offers a theoretical basis for rational nitrogen reduction and high-quality cultivation in rice. [ABSTRACT FROM AUTHOR]

Fe2O3/g-C3N4 nano-heterostructures for photocatalytic degradation of NOR (norfloxacin) were successfully prepared by combining co-precipitation and calcination methods. The g-C3N4, Fe2O3, and different composite ratios of Fe2O3/g-C3N4 (FeCNs) were characterized by XRD, SEM, XPS, UV-vis DRS, PL, and electrochemical tests, and the mechanism of photocatalytic degradation of NOR was analyzed. The results indicated that the semiconductor was attached to the surface of g-C3N4 in the form of α-Fe2O3 crystal with good crystalline structure. The composite of Fe2O3 with g-C3N4 increased the specific surface area of the material, effectively reduced the band gap, strengthened the photogenerated e−/h+ pair separation, and improved the photocatalytic performance of the composite. The photocatalytic degradation of NOR was consistent with the quasi-primary reaction kinetic model. Among them, FeCN-25wt% showed the optimal photocatalytic degradation of NOR (72.3%) with the largest degradation rate (k = 0.00900 min−1). The Fe2O3/g-C3N4 composite structure is inferred to be a Z-type heterojunction. [ABSTRACT FROM AUTHOR]

Understanding the historical groundwater recharge process and its influencing factors is crucial for effectively managing regional groundwater resources amidst future climate change. However, the availability of high-resolution hydroclimate archives remains severely limited. In this study, we used a 59 m chloride profile within the unsaturated loess zone to reconstruct the potential groundwater recharge (PGR) records spanning 273 years in a near-humid area on the Loess Plateau. Spectral analysis was employed to identify the principal influencing factors on PGR across various time scales. The reconstructed hydrological records revealed three wet periods and four dry periods from 1745 to 2007 AD, with PGR rates ranging from 66.7 to 222.4 mm yr−1 during wet periods and 20.0 to 66.7 mm yr−1 during dry periods. In addition, spectral analysis indicated multiple cycles, ranging from 2.1 to 50.0 years, within the PGR history. Temperature, precipitation, and sunspot activity emerged as the key factors governing the rate of PGR over the 3-year, 7-year, and 11-year time scales, respectively, highlighting the combined influence of solar activity and climate on the PGR process. These findings enhance our understanding of groundwater recharge and environmental climate dynamics in the near-humid loess unsaturated zone and other regions exhibiting similar hydroclimatic conditions. [ABSTRACT FROM AUTHOR]

Chemotherapy is an important factor leading to male infertility. It is crucial to discover safe and effective treatments to prevent male reproductive injury caused by chemotherapy. The Ganoderma lucidum polysaccharide peptide (GLPP) has multiple pharmacological activities. The purpose of this study was to determine whether GLPP could protect the male sperm production from chemotherapeutic injury using a mouse model, with testicular damage induced by cyclophosphamide (CP). CP (50 mg/kg/day) was injected intraperitoneally into male ICR mice gavaged with different doses of GLPP at certain spermatogenic stages. The experimental results showed that GLPP alleviated the CP-induced reduction in reproductive organ coefficients and sperm parameters and reduced the morphological damage of testicular tissues in a dose-dependent manner. GLPP significantly improved the reproductive index, sperm-related parameters, sex hormone levels, and histological testis architecture at different spermatogenic stages. Furthermore, GLPP significantly increased superoxide dismutase (SOD), glutathione (GSH), catalase (CAT), Nrf2, and HO-1, and decreased malondialdehyde (MDA) and Keap-1 in the testicular tissue, indicating reduced oxidative stress. In addition, GLPP limited CP-induced apoptosis via a reduction in Bax expression and increase in Bcl-2 expression. This study suggests that GLPP plays a protective role in spermatogenesis by reducing chemotherapeutic injury and might be developed into drug for male patients receiving chemotherapy. [ABSTRACT FROM AUTHOR]

Controlling carbon emissions is a global goal, and China is actively implementing carbon reduction measures. As a major agricultural nation, China has considerable potential for developing agricultural residues as renewable and environmentally friendly biomass energy. In this study, we obtained data on crop yields, crop-to-grain ratios, and livestock excretion coefficients to calculate the biomass resources of agricultural and livestock residues in Chinese provinces from 2013 to 2022. Crop residue biomass resources showed a distribution pattern with higher levels in the north than in the south and the east than in the west. Henan and Heilongjiang provinces consistently had the highest resource levels, exceeding 35 million tons annually for 10 years. The biomass resources from livestock residues were relatively abundant in Sichuan, Henan, Yunnan, Shandong, Hunan, and Inner Mongolia. Inner Mongolia, Sichuan, Shandong, and Henan had the greatest potential for CO2 emission reductions, primarily located in regions abundant in biomass resources and with high traditional energy consumption levels. ArcGIS was used to apply natural break classification to categorize the potential for emission reductions from agricultural and livestock residues across China from 2013 to 2022 into five classes. Based on factors such as crop planting area and livestock numbers, the spatiotemporal distribution of factors influencing the quantity of biomass resources was examined using Geographically and Temporally Weighted Regression. A tailored and integrated approach should be used for biomass, and the development of biomass energy should be promoted through policy support and technological innovation. [ABSTRACT FROM AUTHOR]

This study investigates the growth tolerance mechanisms of Chlorella pyrenoidosa to 3-fluorophenol and its removal efficiency by algal cells. Our results indicate that C. pyrenoidosa can tolerate up to 100 mg/L of 3-fluorophenol, exhibiting a significant hormesis effect characterized by initial inhibition followed by promotion of growth. In C. pyrenoidosa cells, the activities of superoxide dismutase (SOD) and catalase (CAT), as well as the levels of malondialdehyde (MDA) and reactive oxygen species (ROS), were higher than or comparable to the control group. Metabolic analysis revealed that the 3-fluorophenol treatment activated pathways, such as glycerol phospholipid metabolism, autophagy, glycosylphosphatidylinositol (GPI)-anchored protein biosynthesis, and phenylpropanoid biosynthesis, contributed to the stabilization of cell membrane structures and enhanced cell repair capacity. After 240 h of treatment, over 50% of 3-fluorophenol was removed by algal cells, primarily through adsorption. Thus, C. pyrenoidosa shows potential as an effective biosorbent for the bioremediation of 3-fluorophenol. [ABSTRACT FROM AUTHOR]

In the post-harvest phase, fruit is inexorably subjected to extrinsic stressors that expedite energy expenditure and truncate the storage lifespan. The present study endeavors to elucidate the response strategies of litchi to the alterations of energy state caused by 2,4-Dinitrophenol (DNP) treatment through energy metabolism and sugar metabolism. It was observed that the DNP treatment reduced the energy state of the fruit, exacerbated membrane damage and triggered rapid browning in the pericarp after 24 h of storage. Furthermore, the expression of genes germane to energy metabolism (LcAtpB, LcAOX1, LcUCP1, LcAAC1, and, LcSnRK2) reached their peak within the initial 24 h of storage, accompanied by an elevation in the respiratory rate, which effectively suppressed the rise in browning index of litchi pericarp. The study also posits that, to cope with the decrease of energy levels and membrane damage, litchi may augment the concentrations of fructose, glucose, inositol, galactose, and sorbose, thus safeguarding the canonical metabolic functions of the fruit. Collectively, these findings suggest that litchi can modulate energy and sugar metabolism to cope with fruit senescence under conditions of energy deficiency. This study significantly advances the understanding of the physiological responses exhibited by litchi fruit to post-harvest external stressors. [ABSTRACT FROM AUTHOR]

Retroviral integration is mediated by intasome nucleoprotein complexes wherein a pair of viral DNA ends are bridged together by a multimer of integrase (IN). Atomic-resolution structures of HIV-1 intasomes provide detailed insights into the mechanism of integration and inhibition by clinical IN inhibitors. However, previously described HIV-1 intasomes are highly heterogeneous and have the tendency to form stacks, which is a limiting factor in determining high-resolution cryo-EM maps. We have assembled HIV-1 intasomes in the presence of excess IN C-terminal domain protein, which was readily incorporated into the intasomes. The purified intasomes were largely homogeneous and exhibited minimal stacking tendencies. The cryo-EM map resolution was further improved to 2.01 Å, which will greatly facilitate structural studies of IN inhibitor action and drug resistance mechanisms. The C-terminal 18 residues of HIV-1 IN, which are critical for virus replication and integration in vitro, have not been well resolved in previous intasome structures, and its function remains unclear. We show that the C-terminal tail participates in intasome assembly, resides within the intasome core, and forms a small alpha helix (residues 271–276). Mutations that disrupt alpha helix integrity impede IN activity in vitro and disrupt HIV-1 infection at the step of viral DNA integration. [ABSTRACT FROM AUTHOR]

In the present study, the mitochondrial genomic characteristics of Acanthopsetta nadeshnyi have been reported and have depicted the phylogenetic relationship among Pleuronectidae. Combined with a comparative analysis of 13 PCGs, the TN93 model was used to review the neutral evolution and habitat evolution catalysis of the mitogenome to verify the distancing and purification selectivity of the mitogenome in Pleuronectidae. At the same time, a species differentiation and classification model based on mitogenome analysis data was established. This study is expected to provide a new perspective on the phylogenetic relationship and taxonomic status of A. nadeshnyi and lay a foundation for further exploration of environmental and biological evolutionary mechanisms. [ABSTRACT FROM AUTHOR]

The objective of basic oxygen furnace (BOF) steelmaking is to achieve molten steel with final carbon content, temperature, and phosphorus content meeting the requirements. Accurate prediction of the above properties is crucial for end-point control in BOF steelmaking. Traditional prediction models typically use multi-variable input and single-variable output approaches, neglecting the coupling relationships between different property indicators, making it difficult to predict multiple outputs simultaneously. Consequently, a multi-output prediction model based on the fusion of deep convolution and attention mechanism networks (FDCAN) is proposed. The model inputs include scalar data, such as the properties of raw materials and target molten steel, and time series data, such as lance height, oxygen supply intensity, and bottom air supply intensity during the blowing process. The FDCAN model utilizes a fully connected module to extract nonlinear features from scalar data and a deep convolution module to process time series data, capturing high-dimensional feature representations. The attention mechanism then assigns greater weight to significant features. Finally, multiple multi-layer perceptron modules predict the outputs—final carbon content, temperature, and phosphorus content. This structure allows FDCAN to learn complex relationships within the input data and between input and output variables. The effectiveness of the FDCAN model is validated using actual BOF steelmaking data, achieving hit rates of 95.14% for final carbon content within ±0.015 wt%, 84.72% for final temperature within ±15 °C, and 88.89% for final phosphorus content within ±0.005 wt%. [ABSTRACT FROM AUTHOR]

The increasing proliferation of space debris, intermittent space incidents, and the rapid emergence of massive LEO satellite constellations pose significant threats to satellites in orbit. Ground-based optical observations play a crucial role in space surveillance and space situational awareness (SSA). The Zhulong telescopic observation network stands as a pivotal resource in the realm of space object tracking and prediction. This publicly available network plays a critical role in furnishing essential data for accurately delineating and forecasting the orbit of space objects in Earth orbit. Comprising a sophisticated array of hardware components including precise telescopes, optical sensors, and image sensors, the Zhulong network synergistically collaborates to achieve unparalleled levels of precision in tracking and observing space objects. Central to the network's efficacy is its ability to extract positional information, referred to as angular data, from consecutive images. These angular data serve as the cornerstone for precise orbit determination and prediction. In this study, the CPF (Consolidated Prediction Format) orbit serves as the reference standard against which the accuracy of the angular data is evaluated. The findings reveal that the angular data error of the Zhulong network remains consistently below 3 arcseconds, attesting to its remarkable precision. Moreover, through the accumulation of angular data over time, coupled with the utilization of numerical integration and least squares methods, the Zhulong network facilitates highly accurate orbit determination and prediction for space objects. These methodologies leverage the wealth of data collected by the network to extrapolate trajectories with unprecedented accuracy, offering invaluable insights into the behavior and movement of celestial bodies. The results presented herein underscore the immense potential of electric optic telescopes in the realm of space surveillance. By harnessing the capabilities of the Zhulong network, researchers and astronomers can gain deeper insights into the dynamics of space objects, thereby advancing our understanding of the cosmos. Ultimately, the Zhulong telescopic observation network emerges as a pioneering tool in the quest to unravel the mysteries of the universe. [ABSTRACT FROM AUTHOR]

In the low-carbon era, photovoltaic power generation has emerged as a pivotal focal point. The inherent volatility of photovoltaic power generation poses a substantial challenge to the stability of the power grid, making accurate prediction imperative. Based on the integration of a backpropagation (BP) neural network and a genetic algorithm (GA), a prediction model was developed that contained two sub-models: no-rain and no-snow scenarios, and rain and snow scenarios. Through correlation analysis, the primary meteorological factors were identified which were subsequently utilized as inputs alongside historical power generation data. In the sub-model dedicated to rain and snow scenarios, variables such as rainfall and snowfall amounts were incorporated as additional input parameters. The hourly photovoltaic power generation output was served as the model's output. The results indicated that the proposed model effectively ensured accurate forecasts. During no-rain and no-snow weather conditions, the prediction error metrics showcased superior performance: the mean absolute percentage error (MAPE) consistently remained below 13%, meeting the stringent requirement of the power grid's tolerance level below 20%. Moreover, the normalized root mean square error (NRMSE) ranged between 6% and 9%, while the coefficient of determination (R2) exceeded 0.9. These underscored the remarkable prediction accuracy achieved by the model. Under rainy and snowy weather conditions, although MAPE slightly increased to the range of 14% to 20% compared to that of scenarios without rain and snow, it still adhered to the stringent requirement. NRMSE varied between 4.5% and 8%, and R2 remained consistently above 0.9, indicative of satisfactory model performance even in adverse weather conditions. The successful application of the proposed model in predicting hourly photovoltaic power generation output during winter in Henan Province bears significant practical implications for the advancement and integration of renewable energy technologies. [ABSTRACT FROM AUTHOR]

The field of electronic skin has received considerable attention due to its extensive potential applications in areas including tactile sensing and health monitoring. With the development of electronic skin devices, electronic skin can be attached to the surface of human skin for long-term health monitoring, which makes comfort an essential factor that cannot be ignored in the design of electronic skin. Therefore, this paper proposes an assessment method for evaluating the comfort of electronic skin based on neurodynamic analysis. The holistic analysis framework encompasses the mechanical model of the skin, the modified Hodgkin–Huxley model for the transduction of stimuli, and the gate control theory for the modulation and perception of pain sensation. The complete process, from mechanical stimulus to the generation of pain perception, is demonstrated. Furthermore, the influence of different factors on pain perception is investigated. Sensation and comfort diagrams are provided to assess the mechanical comfort of electronic skin. The comfort assessment method proposed in this paper provides a theoretical basis when assessing the comfort of electronic skin. [ABSTRACT FROM AUTHOR]

Compared to traditional biochar (BC), nano-biochar (NBC) boasts superior physicochemical properties, promising extensive applications in agriculture, ecological environments, and beyond. Due to its strong adsorption and migration properties, NBC may carry nutrients or pollutants to deeper soil layers or even groundwater, causing serious environmental risks. Nevertheless, the migration rules and mechanisms of NBC in soil are still unclear. Therefore, this study employed soil column migration experiments to systematically explore the migration rules and mechanisms of NBC under various flow rates, initial soil water contents, soil depths, and soil textures. The results showed that regulated by smaller particle size differences and greater surface charges, NBC exhibited a stronger migration ability compared with traditional BC. As the soil texture transitioned from fine to coarse, the migration capability of NBC significantly improved, driven by both pore structure and interaction forces as described by the DLVO theory. The migration ability of NBC was also greatly boosted as the soil transitioned from saturated to unsaturated conditions, primarily because of preferential flow. When the flow rate increased from 70% KS to 100% KS and 130% KS, the migration ability of NBC also increased accordingly, as changes in injection flow rates altered the velocity distribution of pore water. NBC in 25 cm soil columns was more prone to shallow retention compared with 10 cm soil columns, resulting in weaker overall migration ability. In addition, through fitting of the two-site kinetic model and related parameters, the penetration curves of NBC under various variable conditions were effectively characterized. These findings could offer valuable insights for NBC's future efficient, rational, and sustainable utilization, facilitating the evaluation and mitigation of its potential environmental risks. [ABSTRACT FROM AUTHOR]

Simple Summary: Because the Scavenger Receptor-C (SR-C) and Fibroblast Growth Factor Receptor (FGFR) of Spodoptera frugiperda (Sf-SR-C and Sf-FGFR) have formerly been determined as the receptors of the Bacillus thuringiensis Vip3Aa toxin in Sf9 cells, the mechanism of Vip3Aa binding to its receptor urgently needs to be demonstrated. In this study, we solved the crystal structure of the Sf-MAM domain at a resolution of 2.25 Å. Through structural docking analysis, we found that the Sf-MAM domain may not interact with the Vip3Aa protein. Using surface plasmon resonance (SPR) binding analysis, we further verified that both the Sf-MAM domain and the Sf-FGFR ectodomain could not bind to the Vip3Aa protein in vitro. Thus, the invasion mechanism of the Vip3Aa toxin into its host cells needs further study. Bacillus thuringiensis Vip3Aa has been widely used in transgenic crops to resist the erosion of insects. The Scavenger Receptor-C (SR-C) and Fibroblast Growth Factor Receptor (FGFR) of Spodoptera frugiperda (Sf-SR-C and Sf-FGFR) have formerly been identified as the cell receptors of Vip3Aa. However, the interaction mechanism of Vip3Aa binding to Sf-SR-C or Sf-FGFR is still unknown. Here, we purified the MAM domain of Sf-SR-C (Sf-MAM) and the Sf-FGFR ectodomain expressed extracellularly by Sf9 cells. We then solved the crystal structure of the Sf-MAM domain. Structure docking analysis of the Sf-MAM and Vip3Aa C-terminal domain (CTD) excluded the possibility of the two proteins binding. A further surface plasmon resonance (SPR) assay also revealed that the Sf-MAM and Sf-FGFR ectodomain could not bind to the Vip3Aa protein. Our results have raised the urgency of determining the authentic cell receptor for Vip3Aa. [ABSTRACT FROM AUTHOR]

Fibroblasts, among the most prevalent and widely distributed cell types in the human body, play a crucial role in defining tissue structure. They do this by depositing and remodeling extracellular matrixes and organizing functional tissue networks, which are essential for tissue homeostasis and various human diseases. Pulmonary hypertension (PH) is a devastating syndrome with high mortality, characterized by remodeling of the pulmonary vasculature and significant cellular and structural changes within the intima, media, and adventitia layers. Most research on PH has focused on alterations in the intima (endothelial cells) and media (smooth muscle cells). However, research over the past decade has provided strong evidence of the critical role played by pulmonary artery adventitial fibroblasts in PH. These fibroblasts exhibit the earliest, most dramatic, and most sustained proliferative, apoptosis-resistant, and inflammatory responses to vascular stress. This review examines the aberrant phenotypes of PH fibroblasts and their role in the pathogenesis of PH, discusses potential molecular signaling pathways underlying these activated phenotypes, and highlights areas of research that merit further study to identify promising targets for the prevention and treatment of PH. [ABSTRACT FROM AUTHOR]

Partitioning soil water balance (SWB) is an effective approach for deciphering the impacts of vegetation change on soil hydrological processes. Growing apple trees on the Loess Plateau, China, leads to a substantial deep soil water deficit, posing a serious threat to the sustainable development of apple production. However, the impact of deep-rooted apple trees on SWB remains poorly understood. In this study, we conducted a "Paired Plot" experiment to achieve this objective by decoupling SWB components using water stable isotopes, tritium, and soil water contents from deep soil cores (up to 25 m) under apple orchards with a stand age gradient of 8–23 years. The results showed that deep soil water storage under apple orchards was notably reduced compared to nearby farmland, showing a stand age-related pattern of deep soil water deficit (R2 = 0.91). By analyzing the changing patterns of SWB components, we found that the main factor driving this deficit is the water uptake process controlled by the deep root system. This process is triggered by the increased transpiration demand of apple trees and short-term water scarcity. These findings have implications for understanding soil water dynamics, sustainable agroforestry management, and soil water resources' protection in this region and other similar water-limited areas. [ABSTRACT FROM AUTHOR]

The stability performance of the buoy is an important parameter that should be taken into account when designing marine buoys. This paper introduces a theoretical and numerical analysis method to examine the stability of marine buoys, including analysis of the initial stability and large inclination stability by calculating the natural period, metacentric height, static stability, and dynamic stability, deriving the calculation process of the static stability lever in detail to obtain the righting moment, and so on, showing that the designed buoy in this paper has sufficient stability performance with theoretically excellent resistance performance to the wind and waves. Additionally, the hydrodynamic performance of the buoy at different heights is also further analyzed for structural optimization, which concluded that the buoy would have a more balanced stability performance when the buoy's width-to-height ratio is 0.375–0.5, hoping that the computational model and ideas used in this paper can provide a reference for the theoretical stability analysis and buoy design of other types of buoys. [ABSTRACT FROM AUTHOR]

In this study, Cu2+ modulated silver nanoclusters were constructed for the turn-on, label-free detection of L-histidine. Six Ag NCs protected by oligonucleotides (DNA-Ag NCs) were tested in a series of experiments. Finally, A-DAN-Ag NCs were chosen as the best candidate due to their excellent fluorescent properties. The fluorescence of A-DAN-Ag NCs was quenched using Cu2+ through energy or electron transfer. However, quenched fluorescence could be restored dramatically in the presence of L-histidine due to Cu2+ liberation from A-DAN-Ag NCs and because of the chelation between the imidazole group of L-histidine and Cu2+. The proposed sensor exhibited high selectivity towards L-histidine over other amino acids, with a limit of detection (LOD) of 0.096 μM ranging from 0 to 8 μM. The proposed sensor succeeded in detecting L-histidine in diluted human urine. Therefore, the sensor has promising practical applications in biological systems. [ABSTRACT FROM AUTHOR]

In recent years, the adverse effects of nanoplastics (NPs) and pyriproxyfen on aquatic environments have attracted widespread attention. However, research on their combined exposure to aquatic organisms could be more extensive. This work evaluated the acute and chronic toxic effects of polystyrene NPs (PS-NPs) and pyriproxyfen on Daphnia magna (D. magna) under their combined exposure conditions. The addition of PS-NPs within 24 h reduced the acute toxicity of pyriproxyfen to D. magna, resulting in an increase in the 24-h EC50 values of pyriproxyfen on D. magna from 0.24 mg/L to 0.35, 0.51, and 1.26 mg/L, respectively when 1, 5, and 10 mg/L of PS-NPs were added. Compared with PS-NPs, pyriproxyfen significantly disturbed the growth and reproduction of D. magna in the chronic toxicity test at 21 days. The adverse effects caused by pyriproxyfen were alleviated when PS-NPs and pyriproxyfen were co-exposed. In addition, it was observed that the addition of pyriproxyfen resulted in less PS-NPs uptake by D. magna using a time-gated imaging technique. These findings provide new insight into the combined toxic effects of NPs and pyriproxyfen on the reproduction and growth of D. magna, and it is important to understand the effects of complex pollutants on aquatic systems. Moreover, it has provided an important scientific basis for environmental protection and sustainable development. [ABSTRACT FROM AUTHOR]

The effects of nano-plastics (NPs) on aquatic organisms have drawn significant attention. Understanding the uptake and excretion of NPs by aquatic organisms can provide clearer insights into their behavior within organisms. And the effect of different food on the processes is unclear. Daphnia magna (D. magna) is considered as a model organism for assessing the ecological risks of NPs. This work observed the uptake and excretion of NPs by D. magna under different food supply conditions. The effects of three different types of foods (Chlorella sp., Euglena gracilis, and yeast powder) on the uptake and excretion of two concentrations of NPs (1 mg/L and 3 mg/L) by the D. magna were compared. A Time-Gated Imaging technique was used to quantify the NPs uptake mass by D. magna. The study results showed the inhibitory effect presented by food on the uptake of NPs by D. magna. The inhibitory ability of different foods varies, with similar levels observed in Chlorella sp. and E. gracilis, while the inhibitory effect of yeast powder was slightly weaker. The facilitating effect was presented by food on the excretion of NPs. The time constant of excretion of NPs by feeding yeast powder was about 4–5 min longer than that of two types of algae. These effects can be attributed to food occupying the intestine tract of D. magna and supplying energy. This work emphasizes the important role of food in evaluating the ecological effects of NPs and provides support for future research on the long-term risks of pollutants to aquatic organisms and environmental sustainability. [ABSTRACT FROM AUTHOR]

Hot-forming technology for 22MnB5 hot-forming steel (22MnB5 HF steel) plates has been widely used in the automobile manufacturing industry in recent years. Physical simulation and numerical modeling were carried out in order to determine the forming limit of a 22MnB5 steel plate for the stamping process. The deformation experiments were performed in a temperature range of 600~900 °C and a strain rate range of 0.1~10 s−1. In the uniaxial tensile tests, it was found that at the forming temperature of 600 °C, the condition of dynamic recrystallization was not fully reached, and thus the corresponding tensile strength was much larger than that at other deformation temperatures. In the numerical simulation of bulging experiments, it was found that 22MnB5 steel had good formability when the initial deformation temperature was high and the forming speed was low by using the instability criterion, combining the maximum punch force and strain path transition. The forming limit diagram of 22MnB5 steel at a temperature of 700 °C and tool speed of 25 mm/s was obtained by means of simulation and a hot stamping experiment. The establishment of the forming limit of the 22MnB5 steel plate can provide theoretical and technical guidance for the hot-forming process. [ABSTRACT FROM AUTHOR]

In recent years, the frequency and intensity of global extreme weather events have gradually increased, leading to significant changes in urban rainfall patterns. The uneven distribution of rainfall has caused varying degrees of water security issues in different regions. Accurately grasping the spatiotemporal distribution patterns of rainfall is crucial for understanding the hydrological cycle and predicting the availability of water resources. This study collected rainfall data every five minutes from 62 rain gauge stations in the main urban area of Kunming City from 2019 to 2021, constructing an unsupervised hybrid dimensionality reduction-clustering (HDRC) model. The model employs the Locally Linear Embedding (LLE) algorithm from manifold learning for dimensionality reduction of the data samples and uses the dynamic clustering K-Means algorithm for cluster analysis. The results show that the model categorizes the rainfall in the Kunming area into three types: The first type has its rainfall center distributed on the north shore of Dian Lake and the southern part of Kunming's main urban area, with spatial dynamics showing the rainfall distribution gradually developing from the Dian Lake water body towards the land. The second type's rainfall center is located in the northern mountainous area of Kunming, with a smaller spatial dynamic change trend. The water vapor has a relatively fixed and concentrated rainfall center due to the orographic uplift effect of the mountains. The third type's rainfall center is located in the main urban area of Kunming, with this type of rainfall showing smaller variations in all indicators, mainly occurring in May and September when the temperature is lower, related to the urban heat island effect. This research provides a general workflow for spatial rainfall classification, capable of mining the spatiotemporal distribution patterns of regional rainfall based on extensive data and generating typical samples of rainfall types. [ABSTRACT FROM AUTHOR]

Doubly coupled designs (DCDs) have better space-filling properties between the qualitative and quantitative factors than marginally coupled designs (MCDs) which are suitable for computer experiments with both qualitative and quantitative factors. In this paper, we propose a new class of DCDs, called group doubly coupled designs (GDCDs), and provide methods for constructing two forms of GDCDs, within-group doubly coupled designs and between-group doubly coupled designs. The proposed GDCDs can accommodate more qualitative factors than DCDs, when the subdesigns for the qualitative factors are symmetric. The subdesigns of qualitative factors are not asymmetric in the existing results on DCDs, and in this paper, we construct GDCDs with symmetric and asymmetric designs for the qualitative factors, respectively. Moreover, detailed comparisons with existing MCDs show that GDCDs have better space-filling properties between qualitative and quantitative factors. Finally, the methods are particularly easy to implement. [ABSTRACT FROM AUTHOR]

A growing number of large data sets have created challenges for the oil and gas industry in predicting reservoir parameters and assessing well productivity through efficient and cost-effective techniques. The design of drilling plans for a high-pressure tight-sand reservoir requires accurate estimations of pore pressure (Pp) and reservoir parameters. The objective of this study is to predict and compare the Pp of Huizhou Sag, Pearl River Mouth Basin, China, using conventional techniques and machine learning (ML) algorithms. We investigated the characteristics of low-permeability reservoirs by observing well-logging data sets and cores and examining thin sections under a microscope. In the reservoir zone, the average hydrocarbon saturation is 55%, and the average effective porosity is 11%. The tight sandstone reservoirs consist of fine- to extremely fine-grained argillaceous feldspathic sandstone. The mean absolute error for reservoir property prediction is 1.3%, 2.2%, and 4.8%, respectively, for effective porosity, shale volume, and water saturation. Moreover, the ML algorithm was employed to cross-check the validity of the prediction of Pp. Combining conventional and ML techniques with the core data demonstrates a correlation coefficient (R2) of 0.9587, indicating that ML techniques are the most effective in testing well data. This study shows that ML can effectively predict Pp at subsequent depths in adjacent geologically similar locations. Compared to conventional methods, a substantial data set and ML algorithms improve the precision of Pp predictions. [ABSTRACT FROM AUTHOR]

Breast cancer is a leading cause of cancer mortality in women worldwide. Using the Infinium MethylationEPIC BeadChip, we analyzed plasma sample methylation to identify the SRCIN1 gene in breast cancer patients. We assessed SRCIN1-related roles and pathways for their biomarker potential. To verify the methylation status, quantitative methylation-specific PCR (qMSP) was performed on genomic DNA and circulating cell-free DNA samples, and mRNA expression analysis was performed using RT‒qPCR. The results were validated in a Western population; for this analysis, the samples included plasma samples from breast cancer patients from the USA and from The Cancer Genome Atlas (TCGA) cohort. To study the SRCIN1 pathway, we conducted cell viability assays, gene manipulation and RNA sequencing. SRCIN1 hypermethylation was identified in 61.8% of breast cancer tissues from Taiwanese patients, exhibiting specificity to this malignancy. Furthermore, its presence correlated significantly with unfavorable 5-year overall survival outcomes. The levels of methylated SRCIN1 in the blood of patients from Taiwan and the USA correlated with the stage of breast cancer. The proportion of patients with high methylation levels increased from 0% in healthy individuals to 63.6% in Stage 0, 80% in Stage I and 82.6% in Stage II, with a sensitivity of 78.5%, an accuracy of 90.3% and a specificity of 100%. SRCIN1 hypermethylation was significantly correlated with increased SRCIN1 mRNA expression (p < 0.001). Knockdown of SRCIN1 decreased the viability of breast cancer cells. SRCIN1 silencing resulted in the downregulation of ESR1, BCL2 and various cyclin protein expressions. SRCIN1 hypermethylation in the blood may serve as a noninvasive biomarker, facilitating early detection and prognosis evaluation, and SRCIN1-targeted therapies could be used in combination regimens for breast cancer patients. [ABSTRACT FROM AUTHOR]

The Earth rotation parameters (ERP) play a crucial role in defining the global reference frame and the Global Navigation Satellite System (GNSS) is one of the important tools used to obtain ERP, including polar motion (PM), its rates, and length of day (LOD). The latest IGS Repro3 ERP products, which provided the IGS contribution to the latest ITRF2020, were generated without consideration of the Beidou Navigation Satellite System (BDS) observations. The global BDS, namely the BDS-3 constellation, has been completely constructed from July 2020 and the observing stations are evenly distributed globally now. Two couple dual-frequency combinations, including the B1I/B3I and B1C/B2a combinations, are commonly used for BDS-3 ionosphere-free combination usage. With the goal of identifying the optimal dual-frequency combination for BDS-3 ERP estimates for the future ITRF definition with a consideration of BDS-3, this research evaluated the performance of ERP estimation using B1I/B3I and B1C/B2a combinations. Firstly, we conducted a comparison of the ambiguity resolutions. The mean percentage of successfully resolved ambiguities for the BDS-3 B1C/B2a combination is 86.5%, surpassing that of B1I/B3I. The GNSS satellite orbits and ERP were estimated simultaneously, thus the accuracy of orbits could also reflect the performance of the ERP estimates. Subsequently, we validated the orbits of 22 BDS-3 Medium Earth Orbit (MEO) satellites using Satellite Laser Ranging (SLR), and the root mean square error (RMS) of the SLR residuals for the 3-day arc orbit with B1C/B2a signals was 5.72 cm, indicating superior accuracy compared with the B1I/B3I combination. Finally, we compared the performance of ERP estimation, considering both internal and external accuracy. For the internal accuracy, B1C/B2a-based solutions demonstrated a reduction in mean formal errors of approximately 17% for PM, 22% for LOD, and 21% for PM rates compared with B1I/B3I-based solutions. In terms of external accuracy, we compared BDS-3-derived ERP estimates with the IERS 20C04 products. The B1C/B2a combination exhibited a slightly better standard deviation performance and a significant reduction in mean bias by 56%, 54%, 39%, 64%, and 23% for X, Y polar motion, X, Y polar motion rates, and LOD, respectively, compared with B1I/B3I solutions. In conclusion, the results highlight the excellent signal quality for BDS-3 B1C/B2a and its superiority in ERP estimation when compared with the B1I/B3I combination. [ABSTRACT FROM AUTHOR]

Canonical autophagy is an evolutionarily conserved process that forms double-membrane structures and mediates the degradation of long-lived proteins (LLPs). Noncanonical autophagy (NCA) is an important alternative pathway involving the formation of microtubule-associated protein 1 light chain 3 (LC3)-positive structures that are independent of partial core autophagy proteins. NCA has been defined by the conjugation of ATG8s to single membranes (CASM). During canonical autophagy and NCA/CASM, LC3 undergoes a lipidation modification, and ATG16L1 is a crucial protein in this process. Previous studies have reported that the WDR domain of ATG16L1 is not necessary for canonical autophagy. However, our study found that WDR domain deficiency significantly impaired LLP degradation in basal conditions and slowed down LC3-II accumulation in canonical autophagy. We further demonstrated that the observed effect was due to a reduced interaction between ATG16L1 and FIP200/WIPI2, without affecting lysosome function or fusion. Furthermore, we also found that the WDR domain of ATG16L1 is crucial for chemical-induced NCA/CASM. The results showed that removing the WDR domain or introducing the K490A mutation in ATG16L1 significantly inhibited the NCA/CASM, which interrupted the V-ATPase-ATG16L1 axis. In conclusion, this study highlights the significance of the WDR domain of ATG16L1 for both canonical autophagy and NCA functions, improving our understanding of its role in autophagy. [ABSTRACT FROM AUTHOR]

Cold stress adversely impacts grape growth, development, and yield. Therefore, improving the cold tolerance of grape is an urgent task of grape breeding. The Jasmonic acid (JA) pathway responsive gene JAZ plays a key role in plant response to cold stress. However, the role of JAZ in response to low temperatures in grape is unclear. In this study, VvJAZ13 was cloned from the 'Pinot Noir' (Vitis vinefera cv. 'Pinot Noir') grape, and the potential interacting protein of VvJAZ13 was screened by yeast two-hybrid (Y2H). The function of VvJAZ13 under low temperature stress was verified by genetic transformation. Subcellular localization showed that the gene was mainly expressed in cytoplasm and the nucleus. Y2H indicated that VvF-box, VvTIFY5A, VvTIFY9, Vvbch1, and VvAGD13 may be potential interacting proteins of VvJAZ13. The results of transient transformation of grape leaves showed that VvJAZ13 improved photosynthetic capacity and reduced cell damage by increasing maximum photosynthetic efficiency of photosystem II (Fv/Fm), reducing relative electrolyte leakage (REL) and malondialdehyde (MDA), and increasing proline content in overexpressed lines (OEs), which played an active role in cold resistance. Through the overexpression of VvJAZ13 in Arabidopsis thaliana and grape calli, the results showed that compared with wild type (WT), transgenic lines had higher antioxidant enzyme activity and proline content, lower REL, MDA, and hydrogen peroxide (H2O2) content, and an improved ability of scavenging reactive oxygen species. In addition, the expression levels of CBF1-2 and ICE1 genes related to cold response were up-regulated in transgenic lines. To sum up, VvJAZ13 is actively involved in the cold tolerance of Arabidopsis and grape, and has the potential to be a candidate gene for improving plant cold tolerance. [ABSTRACT FROM AUTHOR]

The pathogenesis of carcinoma is believed to come from the combined effect of polygenic variation, and the initiation and progression of malignant tumors are closely related to the dysregulation of biological pathways. Quantifying the alteration in pathway activation and identifying coordinated patterns of pathway dysfunction are the imperative part of understanding the malignancy process and distinguishing different tumor stages or clinical outcomes of individual patients. In this study, we have conducted in silico pathway activation analysis using Riemannian manifold (RiePath) toward pan-cancer personalized characterization, which is the first attempt to apply the Riemannian manifold theory to measure the extent of pathway dysregulation in individual patient on the tangent space of the Riemannian manifold. RiePath effectively integrates pathway and gene expression information, not only generating a relatively low-dimensional and biologically relevant representation, but also identifying a robust panel of biologically meaningful pathway signatures as biomarkers. The pan-cancer analysis across 16 cancer types reveals the capability of RiePath to evaluate pathway activation accurately and identify clinical outcome-related pathways. We believe that RiePath has the potential to provide new prospects in understanding the molecular mechanisms of complex diseases and may find broader applications in predicting biomarkers for other intricate diseases. [ABSTRACT FROM AUTHOR]

The low-temperature fatigue crack propagation rate of 925A steel, as a rudder steel for polar special ships, has a crucial impact on the evaluation of the fatigue strength of polar ships. The purpose of this article is to study the fatigue crack propagation rate of 925A steel under different low-temperature conditions from room temperature (RT) to −60 °C. The material was subjected to fatigue crack propagation tests and stress intensity factor tests. The experimental tests were conducted according to the Chinese Standard of GB/T6398-2017. The results show that as the temperature decreases, the lifespan of 925A increases. Within a certain stress intensity factor, as the temperature decreases, the fatigue crack propagation rate decreases. At −60 °C, it exhibits ductile fracture; within normal polar temperatures, it can be determined that 925A meets the requirements for low-temperature fatigue crack propagation rates in polar regions. However, in some extreme polar temperatures below −60 °C, preventing brittle failure becomes a key focus of fatigue design. Finally, the fatigue crack propagation behavior at the microscale of 925A steel at low temperatures was described using fracture morphology. The experimental data can provide reference for the design of polar ships to further resist low-temperature fatigue and cold brittle fracture. [ABSTRACT FROM AUTHOR]

The current work introduces the synthesis of inorganic salt nano/micro-crystals during the reduction of hydrogen tetrachloroaurate(III) by Pluronic triblock copolymers (P123, PEO20–PPO70–PEO20). The morphologies and component were confirmed using an electron microscope with an electronic differential system (EDS), and the crystal structures were determined with X-ray diffraction (XRD). The morphologies highly depend on the concentrations of Pluronic and pH values. The mean size of the nanocrystal and hollow micro-crystal were controlled typically in the range of 32–150 nm (side length) and 1.4 μm, respectively. Different from the electrospray–ionization (EI) method, a model in which KCl forms a supersaturated solution in the micellar core of Pluronic is used to explain the formation process. This work provides the new insight that inorganic salt nanocrystals could be synthesized with the template of micelles in pure aqueous solutions. [ABSTRACT FROM AUTHOR]

The problem that the thermal safety of flexible electronic devices is difficult to evaluate in real time is addressed in this study by establishing a BP neural network (GA-BPNN) temperature prediction model based on genetic algorithm optimisation. The model uses a BP neural network to fit the functional relationship between the input condition and the steady-state temperature of the equipment and uses a genetic algorithm to optimise the parameter initialisation problem of the BP neural network. To overcome the challenge of the high cost of obtaining experimental data, finite element analysis software is used to simulate the temperature results of the equipment under different working conditions. The prediction variance of the GA-BPNN model does not exceed 0.57 °C and has good robustness, as the model is trained according to the simulation data. The study conducted thermal validation experiments on the temperature prediction model for this flexible electronic device. The device reached steady state after 1200 s of operation at rated power. The error between the predicted and experimental results was less than 0.9 °C, verifying the validity of the model's predictions. Compared with traditional thermal simulation and experimental methods, this model can quickly predict the temperature with a certain accuracy and has outstanding advantages in computational efficiency and integrated application of hardware and software. [ABSTRACT FROM AUTHOR]

The aging mechanism of 10% and 30% nickel-substituted manganese hexacyanoferrate cathode material in aqueous zinc-ion batteries has been explored through the advanced synchrotron-based two-dimensional X-ray fluorescence technique. Thanks to the two-dimension modality, not only were the metal concentration dynamics throughout the entire electrodes followed during the aging process, but their spatial distribution was also revealed, suggesting the route of the material transformation. The dissolution of Mn and Ni, as well as the penetration of Zn inside the framework were detected, while the Mn aggregations were found outside the hexacyanoferrate framework. Additionally, the possibility of conducting X-ray absorption spectroscopy measurements on the regions of interest made it possible to explore the chemical state of each metal, and furthermore, synchrotron-based powder X-ray diffraction demonstrated the gradual structural modification in 30% Ni-containing sample series in terms of the different phase formation. [ABSTRACT FROM AUTHOR]

Obesity, characterized by the excessive accumulation of adipose tissue, has emerged as a major public health concern worldwide. To develop effective strategies for treating obesity, it is essential to comprehend the biological properties of different adipose tissue types and their respective roles in maintaining energy balance. Adipose tissue serves as a crucial organ for energy storage and metabolism in the human body, with functions extending beyond simple fat storage to encompass the regulation of energy homeostasis and the secretion of endocrine factors. This review provides an overview of the key characteristics, functional differences, and interconversion processes among white adipose tissue (WAT), brown adipose tissue (BAT), and beige adipose tissue. Moreover, it delves into the molecular mechanisms and recent research advancements concerning the browning of WAT, activation of BAT, and whitening of BAT. Although targeting adipose tissue metabolism holds promise as a potential approach for obesity treatment, further investigations are necessary to unravel the intricate biological features of various adipose tissue types and elucidate the molecular pathways governing their interconversion. Such research endeavors will pave the way for the development of more efficient and targeted therapeutic interventions in the fight against obesity. [ABSTRACT FROM AUTHOR]

With the development of autonomous driving, consensus is gradually forming around vehicle–infrastructure cooperative (VIC) autonomous driving. The VIC environment-sensing system uses roadside sensors in collaboration with automotive sensors to capture traffic target information symmetrically from both the roadside and the vehicle, thus extending the perception capabilities of autonomous driving vehicles. However, the current target detection accuracy for feature fusion based on roadside LiDAR and automotive LiDAR is relatively low, making it difficult to satisfy the sensing requirements of autonomous vehicles. This paper proposes PAFNet, a VIC pillar attention fusion network for target detection, aimed at improving LiDAR target detection accuracy under feature fusion. The proposed spatial and temporal cooperative fusion preprocessing method ensures the accuracy of the fused features through frame matching and coordinate transformation of the point cloud. In addition, this paper introduces the first anchor-free method for 3D target detection for VIC feature fusion, using a centroid-based approach for target detection. In the feature fusion stage, we propose the grid attention feature fusion method. This method uses the spatial feature attention mechanism to fuse the roadside and vehicle-side features. The experiment on the DAIR-V2X-C dataset shows that PAFNet achieved a 6.92% higher detection accuracy in 3D target detection than FFNet in urban scenes. [ABSTRACT FROM AUTHOR]

Plastic pollution, particularly microplastic (MP) and nanoplastic (NP) pollution, has become a significant concern. This study explores the use of porous wood for filtration to remove MPs and NPs and investigates their removal mechanisms. Undecorated fir wood with a thickness of 4 mm achieves a 91% removal rate for model polystyrene (PS) MPs (2.6 μm) at a water flux of 198 L/m2h. However, its separation performance for NPs (255.8 and 50.9 nm) is poor. It also shows that fir wood (coniferous wood) has a higher PS removal rate than poplar wood (hard wood). With poly dimethyl diallyl ammonium chloride (PDDA) modification, both MPs and NPs are effectively removed, with NPs' removal rate increasing from <10% to 90% for PDDA/wood. Characterization results reveal that size-exclusive interception dominates for micron-sized particles, and electrostatic interaction is crucial for nanosized particles. Additionally, intercepted NPs have been used as a strong binder for hot-pressed wood to remarkably enhance the mechanical properties of wood, suggesting a novel recycle utilization of discarded wood filters. Overall, this renewable wood material offers a simple solution for tackling MP/NP pollution. [ABSTRACT FROM AUTHOR]

(1) Background: Nutrients play an essential role in bone health, whether in achieving peak bone mineral density (BMD) or maintaining bone health. This study explores the relationship between nutrient supply and femoral bone health at different ages. (2) Methods: A total of 5603 participants meeting the inclusion and exclusion criteria were included in this study using the National Health and Nutrition Examination Survey (NHANES) database from 2005 to 2010, 2013 to 2014, and 2017 to 2018. Femoral bone mineral density and bone status were dependent variables, and dietary nutrient intake and nutrient intake status were independent variables. The relationship between dietary nutrient intake and bone mineral density was explored, and the importance of nutrients affecting bone status was analyzed through a neural network model. At the same time, we investigated the relationship between nutrient intake and bone status. (3) Results: The peak of age and femoral bone mineral density appeared at 20 years old in our study. After grouping by age, logistic regression analysis showed that before 20 years old, without adjusting other variables, high-fat diet was more likely to have normal bone mass than appropriate fat diet (OR: 4.173, 95%CI: 1.007–17.289). After adjusting for all demographic factors, niacin intake (OR: 1.062, 95%CI: 1.019–1.108) was beneficial for normal bone mass, while vitamin B6 intake (OR: 0.627, 95%CI: 0.408–0.965) was not. After 20 years old, after adjusting for carbohydrate, protein, vitamin B6, niacin, dietary fat, vitamin B2, and vitamin B12, vitamin B2 intake (OR: 1.153, 95%CI: 1.04–1.278) was beneficial for normal bone mass, while vitamin B6 intake (OR: 0.842, 95%CI: 0.726–0.976) was not. After adjusting for all confounding factors, vitamin B2 intake (OR: 1.288, 95%CI: 1.102–1.506) was beneficial for normal bone mass. In addition, we found that even if there was no statistical significance, the effects of high-fat diet on bone mass were different at different ages. (4) Conclusions: By conducting an in-depth analysis of the NHANES database, this study reveals that dietary factors exert divergent effects on bone health across different age groups, implying the necessity of implementing tailored dietary strategies to maintain optimal bone health at distinct life stages. [ABSTRACT FROM AUTHOR]

Orychophragmus violaceus (L.) O. E. Schulz (Brassicaceae) is widely distributed and plentiful in China and has been widely used for its application in ornamental, oil, ecology, foraging, and food. Recent studies have revealed that the main components of Orychophragmus violaceus include flavonoids, alkaloids, phenylpropanoids, phenolic acids, terpenoids, etc., which have pharmacological activities such as antioxidation, antiradiation, antitumor, hepatic protection, antiferroptosis, anti-inflammatory, and antibacterial. In this paper, the nutritional value, chemical compositions, pharmacological activity, and application value of Orychophragmus violaceus are summarized by referring to the relevant domestic and international literature to provide a reference for further research, development, and utilization of Orychophragmus violaceus in the future. [ABSTRACT FROM AUTHOR]

Oil-immersed transformers play a pivotal role owing to their environmentally friendly characteristics, compact footprint, and cost-effectiveness. Ensuring the online monitoring of oil-immersed transformers is a fundamental measure to ensure the secure and stable operation of modern power systems. In this paper, metal particle cluster-doped SnS is firstly used in the adsorption and sensing of decomposition components (CO, C2H2) under fault conditions in oil-immersed transformers. The study comprehensively analyzed band structure, differential charge density, density of states, and molecular orbital theory to unveil the adsorption and sensing mechanisms of target gases. The findings suggest that the modification of metal particle clusters can enhance the surface electronic properties of single-layer SnS. In the regions of metal particle clusters and the gas–surface reaction area, electronic activity is significantly heightened, primarily attributed to the contribution of d-orbital electrons of the metal cluster structures. The modified SnS exhibits adsorption capacity in the following order: Ru3-SnS > Mo3-SnS > Au3-SnS. Additionally, the modified material demonstrates increased competitiveness for C2H2, with adsorption types falling under physical chemistry adsorption. Different metal elements exert diverse effects on the electronic distribution of the entire system, providing a theoretical foundation for the preparation of corresponding sensors. The findings in this work offer numerical insights for the further preparation and development of SnS nanosensors, concurrently shedding light on the online monitoring of faults in oil-immersed transformers. [ABSTRACT FROM AUTHOR]