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Purpose: In the present study, we aimed to assess the effectiveness and safety of immune-targeted therapy (IT) with or without transarterial chemoembolization (TACE) for advanced hepatocellular carcinoma (HCC) with portal vein tumor thrombosis (PVTT). Patients and methods: This was a multicenter retrospective study that included 265 HCC patients with PVTT (IT + TACE: 82, IT: 183). Overall survival (OS) and progression-free survival (PFS), as well as tumor responses and adverse events, were evaluated. Results: Patients in the IT + TACE group experienced significantly longer overall survival (OS) and progression-free survival (PFS) periods, compared with those in the IT group (OS 19.0 vs. 13.0 months, p < 0.001; PFS 12.0 vs. 7.3 months, p < 0.001). Multivariable analysis confirmed IT + TACE as an independent predictor for improved OS and PFS. Subgroup analysis demonstrated the benefits of IT + TACE in patients with rich PVTT blood supply. Preoperative imaging and DSA offered predictive value. Conclusions: TACE combined with IT provides a safe and effective treatment option for advanced-HCC patients with PVTT, particularly those with abundant PVTT blood supply.

Advanced composites are attracting increasing attention in industrial applications due to their excellent performance, i [...]

There exist conflicts of interest between upstream and downstream regions in flood control and drainage; how to balance these conflicts and achieve collaborative flood management remains an important scientific problem. To explore a balanced governance strategy, this study took the Demonstration Zone of Green and Integrated Ecological Development of the Yangtze River Delta, which consists of three separate administrative regions, as the research domain. Using evolutionary game theory, the study conducts a comparative analysis of the interests between upstream and downstream areas. It introduces external drivers, such as the intervention of higher-level administrative bodies and incentive-constraining policies, along with internal balancing mechanisms like bidirectional compensation. The goal is to explore collaborative strategies and cooperation mechanisms that can balance the conflicts of interest between upstream and downstream areas. Results indicate that: (1) The final collaborative strategy was closely related to factors such as the cost of conflict, the amount of two-way compensation, additional benefits of flood control and drainage, and the intensity of incentive constraints. (2) Incorporating a reasonable two-way compensation and reward and punishment mechanism into the evolutionary game theory model can promote the model to a stable strategy. (3) The external driving mechanisms aim to coordinate the conflicts between upstream and downstream regions through incentive or constraint policies, which help motivate and encourage proactive collaboration in flood control and drainage management. The internal balancing mechanism is responsible for compensating for economic losses caused by imbalances, thereby creating pressure that fosters regional cooperation in flood control and drainage governance. In a word, the collaborated management mechanism helps provide a more balanced strategy across different administrative regions.

The propagation of antibiotic resistance in environments, particularly aquatic environments that serve as primary pathways for antibiotic resistance genes (ARGs), poses significant health risks. The impact of nutrients, as key determinants of bacterial growth and metabolism, on the propagation of ARGs, particularly extracellular ARGs (eARGs), remains poorly understood. In this study, we collected microorganisms from the Yangtze River and established a series of microcosms to investigate how variations in nutrient levels and delivery frequency affect the relative abundance of intracellular ARGs (iARGs) and eARGs in bacterial communities. Our results show that the relative abundance of 7 out of 11 representative eARGs in water exceeds that of iARGs, while 8 iARGs dominate in biofilms. Notably, iARGs and eARGs consistently exhibited opposite responses to nutrient variation. When nutrient levels increased, iARGs in the water also increased, with the polluted group (COD = 333.3 mg/L, COD:N:P = 100:3:0.6, m/m) and the eutrophic group (COD = 100 mg/L, COD:N:P = 100:25:5, m/m) showing 1.2 and 3.2 times higher levels than the normal group (COD = 100 mg/L, COD:N:P = 100:10:2, m/m), respectively. In contrast, eARGs decreased by 6.7% and 8.4% in these groups. On the other hand, in biofilms, higher nutrient levels led to an increase in eARGs by 1.5 and 1.7 times, while iARGs decreased by 17.5% and 50.1% in the polluted and eutrophic groups compared to the normal group. Moreover, while increasing the frequency of nutrient delivery (from 1 time/10 d to 20 times/10 d) generally did not favor iARGs in either water or biofilm, it selectively enhanced eARGs in both. To further understand these dynamics, we developed an ARGs-nutrient model by integrating the Lotka–Volterra and Monod equations. The results highlight the complex interplay of bacterial growth, nutrient availability, and mechanisms such as horizontal gene transfer and secretion influencing ARGs’ propagation, driving the opposite trend between these two forms of ARGs. This contrasting response between iARGs and eARGs contributes to a dynamic balance that stabilizes bacterial resistance levels amid nutrient fluctuations. This study offers helpful implications regarding the persistence of bacterial resistance in the environment.

Ulcerative colitis (UC) is a typical inflammatory bowel disease (IBD), impairing the quality of life of patients. Dehydroevodiamine (DHE) is an active alkaloid isolated from Tetradium ruticarpum that exerts significant anti-inflammatory effects in gastrointestinal diseases. However, the effect and mechanisms of DHE on UC remain unclear. We performed a DSS-induced experimental UC rat model to reveal the efficacy and potential mechanisms of DHE on UC. HE and AB-PAS staining were used for the evaluation of pathologies, and 16S rRNA sequencing was used to detect changes in gut microbes. Metabolomics was used to detect changes in serum metabolites. Network pharmacology and transcriptomics were conducted to reveal the underlying mechanisms of DHE for UC. HuProt proteome microarrays, molecular docking, and SPR were used to reveal the targets of action of DHE. WB, RT-qPCR, and IHC were used to assess the action effects of DHE. DHE demonstrated significant alleviation of DSS-induced colitis symptoms in rats by suppressing inflammatory and oxidative stress responses, amending colonic barrier injury, and inhibiting apoptosis. In terms of gut microbial modulation, DHE decreased the abundance of Allobaculum, Clostridium, Escherichia, Enterococcus, and Barnesiella and increased the abundance of Lactobacillus, Bifidobacterium, and SMB5. Moreover, metabolomics suggested that the regulation of DHE in DSS-induced UC rats mainly involved aminoacyl-tRNA biosynthesis, vitamin B6 metabolism, phenylalanine, tyrosine, and so on. Mechanically, DHE alleviated UC in rats by targeting AKT1, thereby inhibiting the PI3K/AKT/NF-κB signaling pathway.

To measure the long-range transport of PCDD/Fs, a background sampling site at Mt. Lulin station (Taiwan) was selected based on meteorological information and its location relative to burning events in Southeast Asia. During regular sampling periods, a higher concentration of PCDD/Fs was recorded in 2008 at Mt. Lulin station during La Niña events, with levels reaching 390 fg I-TEQ/m3. In contrast, a higher concentration of 483 fg I-TEQ/m3 was observed in 2013 during biomass burning events. This indicates that La Niña affects the ambient PCDD/F concentrations. The ratio of ΣPCDD/ΣPCDF was 0.59, suggesting significant long-range transport contributions from 2007 to 2023. From 2007 to 2015, the predominant species was 2,3,4,7,8-PCDF, accounting for 25.3 to 39.6% of the total PCDD/Fs. From 2018 onward, 1,2,3,7,8-PCDD became more dominant, accounting for 15.0 to 27.1%. According to the results from the receptor model PMF (n = 150), the sources of PCDD/Fs were identified as dust storms and monsoon events (19.3%), anthropogenic activity (28.5%), and biomass burning events (52.2%). The PSCF values higher than 0.7 highlighted potential PCDD/F emission source regions for Mt. Lulin during biomass burning events, indicating high PSCF values in southern Thailand, Cambodia, and southern Vietnam.

The Dynamic Gait Event Identifier (DGEI) introduces a pioneering approach for real-time gait event detection that seamlessly aligns with the needs of embedded system design and optimization. DGEI creates a new standard for gait analysis by combining software and hardware co-design with real-time data analysis, using a combination of first-order difference functions and sliding window techniques. The method is specifically designed to accurately separate and analyze key gait events such as heel strike (HS), toe-off (TO), walking start (WS), and walking pause (WP) from a continuous stream of inertial measurement unit (IMU) signals. The core innovation of DGEI is the application of its dynamic feature extraction strategies, including first-order differential integration with positive/negative windows, weighted sleep time analysis, and adaptive thresholding, which together improve its accuracy in gait segmentation. The experimental results show that the accuracy rate of HS event detection is 97.82%, and the accuracy rate of TO event detection is 99.03%, which is suitable for embedded systems. Validation on a comprehensive dataset of 1550 gait instances shows that DGEI achieves near-perfect alignment with human annotations, with a difference of less than one frame in pulse onset times in 99.2% of the cases.

Huang-Qi (Astragali radix) is one of the most widely used herbs in traditional Chinese medicine, derived from the dried roots of Astragalus membranaceus or Astragalus membranaceus var. mongholicus. To date, more than 200 compounds have been reported to be isolated and identified in Huang-Qi. However, information pertaining to Huang-Qi breeding is considerably fragmented, with fundamental gaps in knowledge, creating a bottleneck in effective breeding strategies. This review systematically introduces Huang-Qi germplasm resources, genetic diversity, and genetic breeding, including wild species and cultivars, and summarizes the breeding strategy for cultivars and the results thereof as well as recent progress in the functional characterization of the structural and regulatory genes related to horticultural traits. Perspectives about the resource protection and utilization, breeding, and industrialization of Huang-Qi in the future are also briefly discussed.

The distribution of energetic ion flux in the ring current region, such as a meteorological cumulonimbus cloud, stores up the particle energy for a geomagnetic substorm. It is helpful to study the geomagnetic substorm mechanism by using a lunar base ENA imaging simulation of the dynamic evolution of the ring current, and establishing the corresponding relationship between key node events of the substorm. Based on the previous observation experience and our simulation results of the dynamic evolution of the ring current, we propose a macroscopic model of substorms related to the dynamic evolution of ring currents and present the possibility of confirming the causal sequence of some of those critical node events of substorms with the lunar base ENA imaging measurement. IBEX, operating in the ecliptic plane, may even give examples of the telemetry of ring current ion fluxes through ENA measurements during substorms/quiets.

HER2 (human epidermal growth factor receptor 2) is highly expressed in a variety of cancers, including breast, lung, gastric, and pancreatic cancers. Its amplification is linked to poor clinical outcomes. At the genetic level, HER2 is encoded by the ERBB2 gene (v-erb-b2 avian erythroblastic leukemia viral oncogene homolog 2), which is frequently mutated or amplified in cancers, thus spurring extensive research into HER2 modulation and inhibition as viable anti-cancer strategies. An impressive body of FDA-approved drugs, including anti-HER2 monoclonal antibodies (mAbs), antibody–drug conjugates (ADCs), and HER2-tyrosine kinase inhibitors (TKIs), have demonstrated success in enhancing overall survival (OS) and disease progression-free survival (PFS). Yet, drug resistance remains a persistent challenge and raises the risks of metastatic potential and tumor relapse. Research into alternative therapeutic options for HER2+ breast cancer therefore proves critical for adapting to this ever-evolving landscape. This review highlights current HER2-targeted therapies, discusses predictive biomarkers for drug resistance, and introduces promising emergent therapies—especially combination therapies—that are aimed at overcoming drug resistance in the context of HER2+ breast cancer.

Domestic animals have multiple phenotypes of skin and coat color, which arise from different genes and their products, such as proteins and metabolites responsible with melanin deposition. However, the complex regulatory network of melanin synthesis remains to be fully unraveled. Here, the skin and tongue tissues of Liangshan black sheep (black group) and Liangshan semi-fine-wool sheep (pink group) were collected, stained with hematoxylin–eosin (HE) and Masson–Fontana, and the transcriptomic and metabolomic data were further analyzed. We found a large deposit of melanin granules in the epidermis of the black skin and tongue. Transcriptome and metabolome analysis identified 744 differentially expressed genes (DEGs) and 443 differentially expressed metabolites (DEMs) between the pink and black groups. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analyses revealed the DEGs and DEMs were mainly enriched in the pathways of secondary metabolic processes, melanin biosynthesis processes, melanin metabolism processes, melanosome membranes, pigment granule membranes, melanosome, tyrosine metabolism, and melanogenesis. Notably, we revealed the gene ENSARG00020006042 may be a family member of YWHAs and involved in regulating melanin deposition. Furthermore, several essential genes (TYR, TYRP1, DCT, PMEL, MLANA, SLC45A2) were significantly associated with metabolite prostaglandins and compounds involved in sheep pigmentation. These findings provide new evidence of the strong correlation between prostaglandins and related compounds and key genes that regulate sheep melanin synthesis, furthering our understanding of the regulatory mechanisms and molecular breeding of pigmentation in sheep.

Adipose tissue dysfunction, which is associated with an increased risk of colorectal cancer (CRC), is a significant factor in the pathophysiology of obesity. Obesity-related inflammation and extracellular matrix (ECM) remodeling promote colorectal cancer metastasis (CRCM) by shaping the tumor microenvironment (TME). When CRC occurs, the metabolic symbiosis of tumor cells recruits adjacent adipocytes into the TME to supply energy. Meanwhile, abundant immune cells, from adipose tissue and blood, are recruited into the TME, which is stimulated by pro-inflammatory factors and triggers a chronic local pro-inflammatory TME. Dysregulated ECM proteins and cell surface adhesion molecules enhance ECM remodeling and further increase contractibility between tumor and stromal cells, which promotes epithelial-mesenchymal transition (EMT). EMT increases tumor migration and invasion into surrounding tissues or vessels and accelerates CRCM. Colorectal symbiotic microbiota also plays an important role in the promotion of CRCM. In this review, we provide adipose tissue and its contributions to CRC, with a special emphasis on the role of adipocytes, macrophages, neutrophils, T cells, ECM, and symbiotic gut microbiota in the progression of CRC and their contributions to the CRC microenvironment. We highlight the interactions between adipocytes and tumor cells, and potential therapeutic approaches to target these interactions.

Amorphous/crystalline high-entropy-alloy (HEA) composites show great promise as structural materials due to their exceptional mechanical properties. However, there is still a lack of understanding of the dynamic nanoindentation response of HEA composites at the atomic scale. Here, the mechanical behavior of amorphous/crystalline HEA composites under nanoindentation is investigated through a large-scale molecular dynamics simulation and a dislocation-based strength model, in terms of the indentation force, microstructural evolution, stress distribution, shear strain distribution, and surface topography. The results show that the uneven distribution of elements within the crystal leads to a strong heterogeneity of the surface tension during elastic deformation. The severe mismatch of the amorphous/crystalline interface combined with the rapid accumulation of elastic deformation energy causes a significant number of dislocation-based plastic deformation behaviors. The presence of surrounding dislocations inhibits the free slip of dislocations below the indenter, while the amorphous layer prevents the movement or disappearance of dislocations towards the substrate. A thin amorphous layer leads to great indentation force, and causes inconsistent stacking and movement patterns of surface atoms, resulting in local bulges and depressions at the macroscopic level. The increasing thickness of the amorphous layer hinders the extension of shear bands towards the lower part of the substrate. These findings shed light on the mechanical properties of amorphous/crystalline HEA composites and offer insights for the design of high-performance materials.

Springback error is a major obstacle in L-bending sheets via cold working. Although thermal processing can effectively reduce the springback phenomenon, it is challenging to heat the sheet globally due to the influence of working conditions. Therefore, this study applied local induction heating to reduce the springback of 45 steel sheets and investigated the effects of bending parameters on springback behavior. Initially, a thermodynamic coupling model and a static model were created utilizing the VOCE hardening model and the von Mises yield criterion in the ANSYS workbench 2022 R2 software. The springback behavior and stress distribution of the sheets were then investigated under different temperatures (room temperature and 800 °C) and bending angles (15°, 30°, 45°, 60°, 75°, and 90°). Simultaneously, the experiments were performed to investigate springback behavior and guarantee the accuracy of the model. The results indicate that the springback reached a minimum value at the 45° bending angle at room temperature while increasing with the increasing bending angle under 800 °C local heating. The springback under local heating can be decreased by 75.2% and the error of the bending angle can improve by 2–7° compared with samples processed in room temperature.

Epinephrine (EP) is a very important chemical transmitter in the transmission of nerve impulses in the central nervous system of mammals. Ascorbic acid (AA) is considered to be the most important extracellular fluid antioxidant and has important antioxidant properties in the cell. In this study, a series of transition metal–polyhistidine-carboxylated multi-wall carbon nanotube nanocomposites were synthesized, and their simultaneous catalytic effects on epinephrine and ascorbic acid were investigated. The results showed that nanocomposites based on iron ions had the highest catalytic activity. The prepared biosensor expressed high selectivity toward EP and AA with LOD values of 0.1 μΜ (AA) and 0.01 μΜ (EP), and sensitivity values of 4.18 μA mM−1 with a range of 0.001–5 mM (AA), 50.98 μA mM−1 with a range of 0.2–100 μM (EP), and 265.75 μA mM−1 with a range of 0.1–1.0 mM (EP). Moreover, it showed good stability, good repeatability and high selectivity in real sample detection. This work is a reference for the design of new electrochemical enzyme-free biosensors and the detection of biomarkers.

The Relief Degree of Land Surface (RDLS) is an important index to evaluate regional environment. It has a significant effect on the local climate, geologic hazards, the path and speed of fire spreading, the migrations of wild animals, and the runoff path and speed of precipitation. The forest-steppe ecotone in northern China is one of ecological fragile zones. In-depth study of the RDLS of the forest-steppe ecotone in northern China will help to implement ecological projects scientifically and promote the construction of the national ecological security barrier. The Shuttle Radar Topography Mission (SRTM-GL1 30 m) data were used to determine the optimal analysis window for RDLS based on the mean change-point method, and the elevation difference was extracted based on the window analysis method. The RDLS model was used to extract RDLS of the forest-steppe ecotone and analyzed with the help of a spatial auto-correlation model. The correlation between mean elevation, relative elevation difference, and RDLS was also analyzed. The results show that the optimal analysis window size for RDLS was 29 × 29, corresponding to an area of 0.76 km2. The RDLS under the optimal analysis window extracted from SRTM-GL1 (30 m) ranged from 0.084 to 3.516. The RDLS had significant spatial clustering, with high RDLS mainly distributed in the mountainous areas and low RDLS mainly distributed in mountain-to-plain transition zone; the RDLS between different administrative units and different watersheds had obvious variability. Overall, the RDLS was characterized as decreasing, increasing, and then decreasing from the south to north, while it was high in the west and low in the east. And the RDLS was linearly positively correlated with mean elevation and relative elevation difference. In the future, the implementation of major ecological projects in the forest-steppe ecotone in northern China, such as soil and water conservation, afforestation tree species selection, ecological corridor design, ecological management, geological disaster prevention, and forest fire prevention, should fully consider the local topographic conditions. These research results can provide topographic references for the implementation of ecological planning and engineering in this area and similar areas. It contributes to sustainable development and maximization of ecological benefits and promotes the establishment of a national ecological security barrier.

Accurate measurement and estimation of forest carbon sinks and fluxes are essential for developing effective national and global climate strategies aimed at reducing atmospheric carbon concentrations and mitigating climate change. Various errors arise during forest monitoring, especially measurement instability due to seasonal variations, which require to be adequately addressed in forest ecosystem research and applications. Seasonal fluctuations in temperature, precipitation, aerosols, and solar radiation can significantly impact the physical observations of mapping equipment or platforms, thereby reducing the data’s accuracy. Here, we review the technologies and equipment used for monitoring forest carbon sinks and carbon fluxes across different remote sensing platforms, including ground-based, airborne, and spaceborne remote sensing. We further investigate the uncertainties introduced by seasonal variations to the observing equipment, compare the strengths and weaknesses of various monitoring technologies, and propose the corresponding solutions and recommendations. We aim to gain a comprehensive understanding of the impact of seasonal variations on the accuracy of forest map data, thereby improving the accuracy of forest carbon sinks and fluxes.

H. perforatum, as one of the Traditional Chinese Medicinal materials, possesses a variety of pharmacological activities and high medicinal value. However, in recent years, the wild resources of H. perforatum have been severely depleted due to global climate change and human activities, and artificial cultivation faces problems such as unstable yield and active ingredient content. This poses a serious obstacle to the development and utilization of its resources. Therefore, this experiment took H. perforatum as the research object and used 894 distribution records of H. perforatum and 36 climatic environmental factors, using the MaxEnt model and GIS technology to explore the main climatic factors affecting the distribution of H. perforatum. Additionally, by utilizing the principles of ecological niche theory, the potential suitable distribution regions of H. perforatum across past, present, and future timelines were predicted, which can ascertain the dynamics of its spatial distribution patterns and the trend of centroid migration. The results indicate that the main environmental factors affecting the geographical distribution of H. perforatum are solar radiation in April (Srad4), solar radiation in September (Srad9), mean temperature of driest quarter (Bio9), solar radiation in November (Srad11), annual mean temperature (Bio1), and annual precipitation (Bio12). Under future climate scenarios, there is a remarkable trend of expansion in the suitable distribution areas of H. perforatum. The centroid migration indicates a trend of migration towards the northwest direction and high-altitude areas. These results can provide a scientific basis for formulating conservation and sustainable use management strategies for H. perforatum resources.

The functional tea CFT-1 has been introduced into China as a nutraceutical beverage according to the “Healthy China” national project. The effects on human hepatocellular carcinoma (HCC) cells remain unclear and were investigated with the functional tea extract (purity > 98%). The morphological changes in the cells were observed with microscopes. Cell proliferation, migration, cycle distribution, and apoptotic effects were assessed by MTT, Transwell assays, and flow cytometry, respectively, while telomerase inhibition was evaluated with telomerase PCR ELISA assay kits. The CFT-1 treatment resulted in cell shrinkage, nuclear pyknosis, and chromatin condensation. CFT-1 suppressed the growth of Hep3B cells with IC50 of 143 μg/mL by inducing apoptosis and G0/G1 arrest in Hep3B cells. As for the molecular mechanism, CFT-1 treatment can effectively reduce the telomerase activity. The functional tea extract inhibits cell growth in human HCC by inducing apoptosis and G0/G1 arrest, possibly through a reduction in telomerase activity. These results indicate that CFT-1 extract exhibited in vitro anticancer activities and provided insights into the future development and utilization of CFT-1 as functional foods to inhibit the proliferation of HCC cells.

As urbanization in China progresses, urban spatial development is transitioning from rapid expansion to more intensive and compact growth. This study examined the role of physical geography and environmental factors in shaping the urban spatial development in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA). Based on the current natural conditions, we selected evaluation indices from topography, hydrogeology, climatic conditions, and natural disasters. These indices were used to create a carrying capacity and suitability evaluation system for development land under natural constraints. Finally, the spatial development potential of the city was finalized by taking into account the current state of the built-up area of the city. Meanwhile, we employed the Optimal Parameters-based Geographical Detector and assessed the impact of 14 natural factors on the spatial development of urban built-up areas. In 2020, the GBA had 52,168.77 km2 of land suitable for construction, of which 34,241.13 km2 was highly suitable (61.29%) and 17,927.64 km2 was moderately suitable (32.09%). At the Bay Area level, 90.15% of the development potential remains untapped; at the city level, Zhaoqing City has the highest potential at 99.56%, while Macao has the lowest at 26.83%. Key factors influencing urban development include silty sand content, annual average relative humidity, and cumulative temperature above 0 °C, with varying impacts across different urban scales. At the Bay Area level, the silty sand content, annual average relative humidity, and cumulative temperature above 0 °C are the main influencing factors on the spatial development of urban built-up areas; at the city level, the main factors are annual average relative humidity and cumulative active temperature above 0 °C. This study reveals the important influence of natural environmental factors on urban spatial development, which is conducive to promoting sustainable development of land resources in GBA.

As one of the most significant research topics in robotics, microrobots hold great promise in biomedicine for applications such as targeted diagnosis, targeted drug delivery, and minimally invasive treatment. This paper proposes an enhanced YOLOv5 (You Only Look Once version 5) microrobot detection and tracking system (MDTS), incorporating a visual tracking algorithm to elevate the precision of small-target detection and tracking. The improved YOLOv5 network structure is used to take magnetic bodies with sizes of 3 mm and 1 mm and a magnetic microrobot with a length of 2 mm as the pretraining targets, and the training weight model is used to obtain the position information and motion information of the microrobot in real time. The experimental results show that the accuracy of the improved network model for magnetic bodies with a size of 3 mm is 95.81%, representing an increase of 2.1%; for magnetic bodies with a size of 1 mm, the accuracy is 91.03%, representing an increase of 1.33%; and for microrobots with a length of 2 mm, the accuracy is 91.7%, representing an increase of 1.5%. The combination of the improved YOLOv5 network model and the vision algorithm can effectively realize the real-time detection and tracking of magnetically controlled microrobots. Finally, 2D and 3D detection and tracking experiments relating to microrobots are designed to verify the robustness and effectiveness of the system, which provides strong support for the operation and control of microrobots in an in vivo environment.

The surface morphology of perovskite films significantly influences the performance of perovskite light-emitting diodes (PeLEDs). However, the thin perovskite thickness (~10 nm) results in low surface coverage on the substrate, limiting the improvement of photoelectric performance. Here, we propose a molecular additive strategy that employs pentafluorophenyl diphenylphosphinate (FDPP) molecules as additives. P=O and Pentafluorophenyl (5F) on FDPP can coordinate with Pb2+ to slow the crystallization process of perovskite and enhance surface coverage. Moreover, FDPP reduces the defect density of perovskite and enhances the crystalline quality. The maximum brightness, power efficiency (PE), and external quantum efficiency (EQE) of the optimal device reached 24,230 cd m−2, 82.73 lm W−1, and 21.06%, respectively. The device maintains an EQE of 19.79% at 1000 cd m−2 and the stability is further enhanced. This study further extends the applicability of P=O-based additives.

Computer-aided design usually gives inspirations and has become a vital strategy to develop novel pesticides through reconstructing natural lead compounds. Patulin, an unsaturated heterocyclic lactone mycotoxin, is a new natural PSII inhibitor and shows significant herbicidal activity to various weeds. However, some evidence, especially the health concern, prevents it from developing as a bioherbicide. In this work, molecular docking and toxicity risk prediction are combined to construct interaction models between the ligand and acceptor, and design and screen novel derivatives. Based on the analysis of a constructed patulin–Arabidopsis D1 protein docking model, in total, 81 derivatives are designed and ranked according to quantitative estimates of drug-likeness (QED) values and free energies. Among the newly designed derivatives, forty-five derivatives with better affinities than patulin are screened to further evaluate their toxicology. Finally, it is indicated that four patulin derivatives, D3, D6, D34, and D67, with higher binding affinity but lower toxicity than patulin have a great potential to develop as new herbicides with improved potency.

Due to the volume expansion effect during charge and discharge processes, the application of transition metal oxide anode materials in lithium-ion batteries is limited. Composite materials and carbon coating are often considered feasible improvement methods. In this study, three types of TiO2@Fe3O4@C microspheres with a core–double-shell structure, namely TFCS (TiO2@Fe3O4@C with 0.0119 g PVP), TFCM (TiO2@Fe3O4@C with 0.0238 g PVP), and TFCL (TiO2@Fe3O4@C with 0.0476 g PVP), were prepared using PVP (polyvinylpyrrolidone) as the carbon source through homogeneous precipitation and high-temperature carbonization methods. After 500 cycles at a current density of 2 C, the specific capacities of these three microspheres are all higher than that of TiO2@Fe2O3 with significantly improved cycling stability. Among them, TFCM exhibits the highest specific capacity of 328.3 mAh·g−1, which was attributed to the amorphous carbon layer effectively mitigating the capacity decay caused by the volume expansion of iron oxide during charge and discharge processes. Additionally, the carbon coating layer enhances the electrical conductivity of the TiO2@Fe3O4@C materials, thereby improving their rate performance. Within the range of 100 to 1600 mA·g−1, the capacity retention rates for TiO2@Fe2O3, TFCS, TFCM, and TFCL are 27.2%, 35.2%, 35.9%, and 36.9%, respectively. This study provides insights into the development of new lithium-ion battery anode materials based on Ti and Fe oxides with the abundance and environmental friendliness of iron, titanium, and carbon resources in TiO2@Fe3O4@C microsphere anode materials, making this strategy potentially applicable.

High-temperature tensile tests were developed to explore the flow features of an Al-Zn-Mg-Cu alloy. The fracture characteristics and microstructural evolution mechanisms were thoroughly revealed. The results demonstrated that both intergranular fractures and ductile fractures occurred, which affected the hot tensile fracture mechanism. During high-temperature tensile, the second phase (Al2CuMg) at the grain boundaries (GBs) promoted the formation and accumulation of dimples. With the continual progression of high-temperature tensile, the aggregation/coarsening of dimples along GBs appear, aggravating the intergranular fracture. The coalescence and coarsen of dimples are reinforced at higher tensile temperatures or lower strain rates. Considering the impact of microstructural evolution and dimple formation/coarsening on tensile stresses, a physical mechanism constitutive (PMC) equation is herein proposed. According to the validation and analysis, the predictive results were in preferable accordance with the testing data, showing the outstanding reconfiguration capability of the PMC model for high-temperature tensile features in Al–Zn–Mg–Cu alloys.

Red ginseng is widely used in food and pharmaceuticals due to its significant nutritional value. However, during the processing and storage of red ginseng, it is susceptible to grow mold and produce mycotoxins, generating security issues. This study proposes a novel approach using hyperspectral imaging technology and a 1D-convolutional neural network-residual-bidirectional-long short-term memory attention mechanism (1DCNN-ResBiLSTM-Attention) for pixel-level mycotoxin recognition in red ginseng. The “Red Ginseng-Mycotoxin” (R-M) dataset is established, and optimal parameters for 1D-CNN, residual bidirectional long short-term memory (ResBiLSTM), and 1DCNN-ResBiLSTM-Attention models are determined. The models achieved testing accuracies of 98.75%, 99.03%, and 99.17%, respectively. To simulate real detection scenarios with potential interfering impurities during the sampling process, a “Red Ginseng-Mycotoxin-Interfering Impurities” (R-M-I) dataset was created. The testing accuracy of the 1DCNN-ResBiLSTM-Attention model reached 96.39%, and it successfully predicted pixel-wise classification for other unknown samples. This study introduces a novel method for real-time mycotoxin monitoring in traditional Chinese medicine, with important implications for the on-site quality control of herbal materials.

Chimeric antigen receptor (CAR)-T cell immunotherapy represents a cutting-edge advancement in the landscape of cancer treatment. This innovative therapy has shown exceptional promise in targeting and eradicating malignant tumors, specifically leukemias and lymphomas. However, despite its groundbreaking successes, (CAR)-T cell therapy is not without its challenges. These challenges, particularly pronounced in the treatment of solid tumors, include but are not limited to, the selection of appropriate tumor antigens, managing therapy-related toxicity, overcoming T-cell exhaustion, and addressing the substantial financial costs associated with treatment. Nanomedicine, an interdisciplinary field that merges nanotechnology with medical science, offers novel strategies that could potentially address these limitations. Its application in cancer treatment has already led to significant advancements, including improved specificity in drug targeting, advancements in cancer diagnostics, enhanced imaging techniques, and strategies for long-term cancer prevention. The integration of nanomedicine with (CAR)-T cell therapy could revolutionize the treatment landscape by enhancing the delivery of genes in (CAR)-T cell engineering, reducing systemic toxicity, and alleviating the immunosuppressive effects within the tumor microenvironment. This review aims to explore how far (CAR)-T cell immunotherapy has come alone, and how nanomedicine could strengthen it into the future. Additionally, the review will examine strategies to limit the off-target effects and systemic toxicity associated with (CAR)-T cell therapy, potentially enhancing patient tolerance and treatment outcomes.

The magnetic shielding device, made of high-permeability soft magnetic material, is sensitive to external influences and requires a protective steel enclosure. A steel enclosure, being strongly ferrimagnetic, can alter the surrounding magnetic field distribution, thus impacting the shielding effectiveness. This study proposes a novel analytical approach to quantify this effect, which has not been previously researched. The method develops a simplified finite element simulation model based on the structural symmetry of the steel enclosure. By using this model, this study analyzes the impact of steel structures with varying heights, widths, and remanent magnetization values. The validity of the method is confirmed through experimental tests on steel buildings. The findings offer insights into the optimal placement of magnetic shielding systems and provide theoretical guidance for designing large-scale magnetic shielding devices.

With the rapid development of deep learning technology in recent years, convolutional neural networks have gained remarkable progress in SAR ship detection tasks. However, noise interference of the background and inadequate appearance features of small-scale objects still pose challenges. To tackle these issues, we propose a small ship detection algorithm for SAR images by means of a coordinate-aware mixed attention mechanism and spatial semantic joint context method. First, the coordinate-aware mixed attention mechanism innovatively combines coordinate-aware channel attention and spatial attention to achieve coordinate alignment of mixed attention features. In this way, attention with finer spatial granularity is conducive to strengthening the focusing ability on small-scale objects, thereby suppressing the background clutters accurately. In addition, the spatial semantic joint context method exploits the local and global environmental information jointly. The detailed spatial cues contained in the multi-scale local context and the generalized semantic information encoded in the global context are used to enhance the feature expression and distinctiveness of small-scale ship objects. Extensive experiments are conducted on the LS-SSDD-v1.0 and the HRSID dataset. The results with an average precision of 77.23% and 90.85% on the two datasets show the effectiveness of the proposed methods.

Sodium butyrate (SB) is a histone deacetylase inhibitor that can induce changes in gene expression and secondary metabolite titers by inhibiting histone deacetylation. Our preliminary analysis also indicated that SB significantly enhanced the biosynthesis of carotenoids in the Rhodotorula glutinis strain YM25079, although the underlying regulatory mechanisms remained unclear. Based on an integrated analysis of transcriptomics and metabolomics, this study revealed changes in cell membrane stability, DNA and protein methylation levels, amino acid metabolism, and oxidative stress in the strain YM25079 under SB exposure. Among them, the upregulation of oxidative stress may be a contributing factor for the increase in carotenoid biosynthesis, subsequently enhancing the strain resistance to oxidative stress and maintaining the membrane fluidity and function for normal cell growth. To summarize, our results showed that SB promoted carotenoid synthesis in the Rhodotorula glutinis strain YM25079 and increased the levels of the key metabolites and regulators involved in the stress response of yeast cells. Additionally, epigenetic modifiers were applied to produce fungal carotenoid, providing a novel and promising strategy for the biosynthesis of yeast-based carotenoids.

The nephrite belt in the Altun Mountain–Western Kunlun Mountain region, which extends about 1300 km in Xinjiang, NW China, is the largest nephrite deposit in the world. The Qiemo region in the Altun Mountains is a crucial nephrite-producing area in China, with demonstrated substantial prospects for future exploration. While existing research has extensively investigated secondary nephrite deposits in the Karakash River and native black nephrite deposits in Guangxi Dahua, a comprehensive investigation of black nephrite from original deposits in Xinjiang is lacking. Margou black-toned nephrite was recently found in primary deposits in Qiemo County, Xinjiang; this makes in-depth research on the characteristics of this mine necessary. A number of technical analytical methods such as polarizing microscopy, Ultra-Deep Three-Dimensional Microscope, electron microprobe, back-scattered electron image analysis, X-ray fluorescence, and inductively coupled plasma mass spectrometry were employed for this research. An experimental test was conducted to elucidate the chemical and mineralogical composition, further clarifying the genetic types of the black and black cyan nephrite from the Margou deposit in Qiemo, Xinjiang. The results reveal that the nephrite is mainly composed of tremolite–actinolite, characterized by Mg/(Mg + Fe2+) ratios ranging from 0.86 to 1.0. Minor minerals include diopside, epidote, pargasite, apatite, zircon, pyrite, and magnetite. Bulk-rock rare earth element (REE) patterns exhibit distinctive features, such as negative Eu anomalies (δEu = 0.00–0.17), decreasing light REEs, a relatively flat distribution of heavy REEs, and low total REE concentrations (1.6–38.9 μg/g); furthermore, the Cr (6–21 μg/g) and Ni (2.5–4.5 μg/g) contents are remarkably low. The magmatic influence of granite appears to be a fundamental factor in the genesis of the magnesian skarn hosting Margou nephrite. The distinctive black and black cyan colors are attributed to heightened iron content, mainly associated with FeO (0.08~6.29 wt.%). Analyses of the chemical composition allow Margou nephrite to be classified as typical of magnesian skarn deposits.

The estimation of the state of charge (SOC) in lithium-ion batteries is a crucial aspect of battery management systems, serving as a key indicator of the remaining available capacity. However, the inherent process and measurement noises created during battery operation pose significant challenges to the accuracy of SOC estimation. These noises can lead to inaccuracies and uncertainties in assessing the battery’s condition, potentially affecting its overall performance and lifespan. To address this problem, we propose a second-order central difference particle filter (SCDPF) method. This method leverages the latest observation data to enhance the accuracy and noise adaptability of SOC estimation. By employing an improved importance density function, we generate optimized particles that better represent the battery’s dynamic behavior. To validate the effectiveness of our proposed algorithm, we conducted comprehensive comparisons at both 25 °C and 0 °C under the new European driving cycle condition. The results demonstrate that the SCDPF algorithm exhibits a high accuracy and rapid convergence speed, with a maximum error which never exceeds 1.30%. Additionally, we compared the SOC estimations with both Gaussian and non-Gaussian noise to assess the robustness of our proposed algorithm. Overall, this study presents a novel approach to enhancing SOC estimation in lithium-ion batteries, addressing the challenges posed by the process itself and measurement noises.

In this study, we investigate Quantum Long Short-Term Memory and Quantum Gated Recurrent Unit integrated with Variational Quantum Circuits in modeling complex dynamical systems, including the Van der Pol oscillator, coupled oscillators, and the Lorenz system. We implement these advanced quantum machine learning techniques and compare their performance with traditional Long Short-Term Memory and Gated Recurrent Unit models. The results of our study reveal that the quantum-based models deliver superior precision and more stable loss metrics throughout 100 epochs for both the Van der Pol oscillator and coupled harmonic oscillators, and 20 epochs for the Lorenz system. The Quantum Gated Recurrent Unit outperforms competing models, showcasing notable performance metrics. For the Van der Pol oscillator, it reports MAE 0.0902 and RMSE 0.1031 for variable x and MAE 0.1500 and RMSE 0.1943 for y; for coupled oscillators, Oscillator 1 shows MAE 0.2411 and RMSE 0.2701 and Oscillator 2 MAE is 0.0482 and RMSE 0.0602; and for the Lorenz system, the results are MAE 0.4864 and RMSE 0.4971 for x, MAE 0.4723 and RMSE 0.4846 for y, and MAE 0.4555 and RMSE 0.4745 for z. These outcomes mark a significant advancement in the field of quantum machine learning.

Transit-oriented development (TOD) has been promoted and implemented worldwide through the efficient integration of rail transit stations and land use. However, the interactions between stations and the surrounding catchment areas (CAs) are characterized by different features of the built environment and regional development. Therefore, it is necessary to develop a quantitative classification method for rail transit stations based on the built environment within a CA and to identify the passenger flow characteristics of different types of stations to develop targeted planning and design policies. In this study, Line 1 and Line 2 within the third ring road of Xi’an City were taken as the objects, and a station classification system was constructed by taking station traffic levels and different building functions within the CA as the classification factors. Secondly, indicators of the built environment, such as six different types of functions, were calculated through refined vector modeling, and 30 typical stations were typologically analyzed. Furthermore, 10 typical types—totaling 11 stations—were selected for passenger flow monitoring, and the passenger flow characteristics of the different types of stations were summarized in terms of the dimensions of stations and exits. Finally, the correlations between the indicators of the built environment and passenger traffic for different functions were quantified. This study provides a basis for the future optimization of stations and the built environment, as well as station design and management.

Volatile organic compounds (VOCs) play a significant role in influencing the flavor quality of cherry tomatoes (Solanum lycopersicum var. cerasiforme). The scarcity of systematic analysis of VOCs in cherry tomatoes can be attributed to the constraints imposed by detection technology and other contributing factors. In this study, the cherry tomato cultivar var. ‘Zheyingfen1’ was chosen due to its abundant fruit flavor. Two detection technology platforms, namely the commonly employed headspace solid-phase microextraction—gas chromatography–mass spectrometry (HS-SPME-GC-MS) and the most advanced headspace solid-phase microextraction—full two-dimensional gas chromatography–time-of-flight mass spectrometry (HS-SPME-GC×GC-TOFMS), were employed in the analysis. The VOCs of cherry tomato cultivar var. ‘Zheyingfen1’ fruits at red ripening stage were detected. A combined total of 1544 VOCs were detected using the two aforementioned techniques. Specifically, 663 VOCs were identified by through the HS-SPME-GC-MS method, 1026 VOCs were identified by through the HS-SPME-GC×GC-TOFMS, and 145 VOCs were identified by both techniques. The identification of β-ionone and (E)-2-nonenal as the principal VOCs was substantiated through the application of the relative odor activity value (rOAV) calculation and subsequent analysis. Based on the varying contribution rates of rOAV, the analysis of sensory flavor characteristics revealed that cherry tomato cultivar var. ‘Zheyingfen1’ predominantly exhibited green and fatty attributes, accompanied by elements of fresh and floral flavor characteristics. In conclusion, our study conducted a comprehensive comparison of the disparities between these two methodologies in detecting VOCs in cherry tomato fruits. Additionally, we systematically analyzed the VOC composition and sensory flavor attributes of the cherry tomato cultivar var. ‘Zheyingfen1’. This research serves as a significant point of reference for investigating the regulatory mechanisms underlying the development of volatile flavor quality in cherry tomatoes.

Shallow gas reservoirs play a crucial role in the gas hydrate system. However, the factors influencing their distribution and their relationship with the gas hydrate system remain poorly understood. In this study, we utilize three-dimensional seismic data to show the fluid pathways and shallow gas reservoirs within the gas hydrate system in the Qiongdongnan Basin. From the deep to the shallow sections, four types of fluid pathways, including tectonic faults, polygonal faults, gas chimneys, and gas conduits, are accurately identified, indicating the strong spatial interconnection among them. The gas pipes are consistently found above the gas chimneys, which act as concentrated pathways for thermogenic gases from the deep sections to the shallow sections. Importantly, the distribution of the gas chimneys closely corresponds to the distribution of the Bottom Simulating Reflector (BSR) in the gas hydrate system. The distribution of the shallow gas reservoirs is significantly influenced by these fluid pathways, with four reservoirs located above tectonic faults and polygonal faults, while one reservoir is situated above a gas chimney. Furthermore, all four shallow gas reservoirs are situated below the BSR, and their distribution range exhibits minimal to no overlap with the distribution of the BSR. Our findings contribute to a better understanding of shallow gas reservoirs and the gas hydrate system, providing valuable insights for their future commercial development.

In this research, an ammonium perchlorate/polydopamine (AP/PDA) core–shell composite was prepared in a non-aqueous solution to reduce the mechanical sensitivity of ammonium perchlorate (AP). The result showed that the AP/PDA core–shell composite could be successfully constructed in ethyl acetate solution with an AP recovery rate that reached 86%. The mechanical sensitivity of the obtained AP/PDA core–shell composite was significantly reduced with a PDA content of only 0.76%. The DSC and TG also indicated that the coating of PDA showed catalytic activity in the thermal decomposition of AP with a lower decomposition temperature and a decreased Ea value of AP. Thus, this study proposed a simple strategy for achieving a good balanced between harnessing the energy and ensuring the safety of ammonium perchlorate by significantly reducing its mechanical sensitivity by using a very low polydopamine coating layer content, and this shows great potential for the design and fabrication of insensitive energetic composites for use in propellants.

The potential of potassium chloride (KCl) to be used as a substitute for sodium chloride (NaCl) was studied by monitoring the effects of salt treatment on thermal behavior, aggregation kinetics, rheological properties, and protein conformational changes. The results show that the addition of KCl can improve solubility, reduce turbidity and particle size, and positively influence rheological parameters such as apparent viscosity, consistency coefficient (K value), and fluidity index (n). These changes indicate delayed thermal denaturation. In addition, KCl decreased the content of β-sheet and random coil structures and increased the content of α-helix and β-turn structures. The optimal results were obtained with 2% KCl addition, leading to an increase in Tp up to 85.09 °C. The correlation results showed that Tp was positively correlated with solubility, α-helix and β-turn but negatively correlated with ΔH, turbidity, β-sheet and random coil. Overall, compared to NaCl, 2% KCl is more effective in delaying the thermal aggregation of LWE, and these findings lay a solid theoretical foundation for the study of sodium substitutes in heat-resistant liquid egg products.

The print head is one of the most critical components in an additive manufacturing (AM) system. It can significantly affect the quality of printed parts. Recently, because continuous carbon fiber-reinforced composites can have excellent mechanical properties, a relevant AM technique, fused filament fabrication (FFF), has been attracting increasing attention. This has extended the requirements demanded of print heads. To this end, different FFF extrusion methods have been rapidly developed based on various methods of impregnating fibers into the matrix for the corresponding print heads. Generally, these extrusion methods are of three types: single extrusion, in situ extrusion, and dual extrusion. All these methods face substantial challenges, such as the nozzle clogging and damage to the continuous carbon fibers during extrusion. These common issues still need to be fully addressed. This study’s aim is to summarize and discuss the different extrusion methods and their FFF specific components in terms of their advantages and disadvantages for continuous carbon fiber-reinforced composites.

Achieving precise control over the motion position and attitude direction of magnetic microrobots remains a challenging task in the realm of microrobotics. To address this challenge, our research team has successfully implemented synchronized control of a microrobot’s motion position and attitude direction through the integration of electromagnetic coils and permanent magnets. The whole drive system consists of two components. Firstly, a stepper motor propels the delta structure, altering the position of the end-mounted permanent magnet to induce microrobot movement. Secondly, a programmable DC power supply regulates the current strength in the electromagnetic coil, thereby manipulating the magnetic field direction at the end and influencing the permanent magnet’s attitude, guiding the microrobot in attitude adjustments. The microrobot used for performance testing in this study was fabricated by blending E-dent400 photosensitive resin and NdFeB particles, employing a Single-Layer 4D Printing System Using Focused Light. To address the microrobot drive system’s capabilities, experiments were conducted in a two-dimensional and three-dimensional track, simulating the morphology of human liver veins. The microrobot exhibited an average speed of 1.3 mm/s (movement error ± 0.5 mm). Experimental results validated the drive system’s ability to achieve more precise control over the microrobot’s movement position and attitude rotation. The outcomes of this study offer valuable insights for future electromagnetic drive designs and the application of microrobots in the medical field.

Photopolymers, especially acrylate-based ones with low cost and simple preparation, are promising materials for high-efficiency holographic gratings. However, it is still challenging to achieve high-performance gratings, due to the influences of many factors. In this work, we found that the dark reaction plays a critical role. The effect of the dark reaction on the optical properties of holographic gratings was investigated. Experimental results reveal that the diffraction efficiency of the gratings can be improved by a factor of three by involving the dark reaction process, and the highest diffraction efficiency for gratings can reach 97.8% after optimization. Therefore, the dark reaction can greatly enhance the optical performance of acrylate-based holographic gratings and other optical elements, thus holding great potential for many applications.

Thermal power units (TPUs) play a crucial role in accommodating the high penetration of renewable energy sources (RESs) like wind turbines (WTs) and photovoltaics (PVs). This paper proposes an evaluation framework to quantitatively analyze the flexibility potential of retrofitted TPUs in enhancing the accommodate capability of RESs through coupling integration and optimal scheduling. Firstly, the coordination framework for coupling TPUs with RESs is outlined, including a comprehensive analysis of benefits and implementation strategies. Secondly, an annual optimal scheduling model for TPUs and RESs is developed, incorporating deep peak regulation services, ladder-type constraints for retrofitted TPUs, and their operational characteristics before and after the coupling integration. Thirdly, indices to evaluate RES accommodation levels and TPU regulation capacities are proposed to quantify the performance of power sources. Finally, a real-world case study is conducted to demonstrate that integrating retrofitted TPUs with RESs through coupling significantly enhances RES utilization by 3.6% and boosts TPUs’ downward regulation capabilities by 32%.

This study combined inorganic α-hemihydrate gypsum (α-HHG) with organic polyacrylamide (PAM) hydrogel to create a novel α-HHG/PAM composite material. Through this facile composite strategy, this fabricated material exhibited a significantly longer initial setting time and higher mechanical strength compared to α-HHG. The effects of the addition amount and the concentration of PAM precursor solution on the flowability of the α-HHG/PAM composite material slurry, initial setting time, and mechanical properties of the hardened specimens were investigated. The structural characteristics of the composite material were examined using XRD, FE-SEM, and TGA. The results showed that the initial setting time of the α-HHG/PAM composite material was 25.7 min, which is an extension of 127.43% compared to that of α-HHG. The flexural strength and compressive strength of the oven-dried specimens were 23.4 MPa and 58.6 MPa, respectively, representing increases of 34.73% and 84.86% over values for α-HHG. The XRD, FE-SEM, and TGA results all indicated that the hydration of α-HHG in the composite material was incomplete. The incompleteness is caused by the competition between the hydration process of inorganic α-HHG and the gelation process of the acrylamide molecules for water, which hinders some α-HHG from entirely reacting with water. The enhanced mechanical strength of the α-HHG/PAM composite material results from the tight interweaving and integrating of organic and inorganic networks. This study provides a concise and efficient approach to the modification research of hemihydrate gypsum.

The direct-sown cotton after wheat harvest (DSCWH) cropping system has attracted wide attention due to reduced labor inputs compared to transplanting. However, the management strategy of slow-release nitrogen is unclear in such a system. This study aims to investigate the impact of different timings and dosages of slow-release nitrogen fertilizer on the yield, biomass accumulation and distribution, and nitrogen absorption and nitrogen utilization in the DSCWH cropping system. This study was investigated at the experimental farm of Yangzhou University, China in 2020 and 2021, with the short-season cotton variety “Zhongmian 50” used as experimental material. Three dosages of the slow-release nitrogen fertilizer (45 kg·ha−1, 90 kg·ha−1, and 135 kg·ha−1) were applied at two stages of growth (two-leaf and four-leaf). The results showed that applying a 90 kg·ha−1 dosage at the two-leaf stage achieved the highest yield, which was increased by 12.6% compared to the no-fertilization control. Applying 90 kg·ha−1 of the slow-release nitrogen at the two-leaf stage promoted biomass accumulation, especially in reproductive organs, and this increase in biomass of reproductive organs was attributed to optimum nitrogen accumulation in reproductive organs (80~140 kg·ha−1). In addition, when 90 kg·ha−1 was applied at the two-leaf stage, there was a significant enhancement in nitrogen recovery efficiency (NRE), nitrogen agronomic use efficiency (NAE), and nitrogen physiological efficiency (NPE), with increases of 7.2% to 13.0%, 5.7% to 5.8%, and 5.6% to 6.5%, respectively. These results revealed that applying slow-release nitrogen fertilizer with the optimal dosage at the seedling stage could significantly enhance nitrogen use efficiency, nitrogen accumulation and partitioning, and biomass accumulation and distribution, which ultimately resulted in a higher lint yield in DSCWH. Therefore, to optimize yield and NUE, 90 kg·ha−1 slow-release nitrogen applied at the two-leaf stage would be recommended in the direct-sown cotton after wheat harvest cropping system.

Abnormal expression of ACSL members 1, 3, 4, 5, and 6 is frequently seen in human cancer; however, their clinical relevance is unclear. In this study, we analyzed the expression of ACSLs and investigated the effects of the ACSL inhibitor Triacsin C (TC) in lung cancer. We found that, compared to normal human bronchial epithelial (NHBE) cells, ACSL1, ACSL4, and ACSL6 were highly expressed, while ACSL3 and ACSL5 were lost in the majority of lung cancer cell lines. ACSL activity was associated with the expression levels of the ACSLs. In primary lung tumors, a higher expression of ACSL1, ACSL4, and ACSL5 was significantly correlated with adenocarcinoma (ADC). Moreover, ACSL5 was significantly reversely related to the proliferation marker Ki67 in low-grade tumors, while ACSL3 was positively associated with Ki67 in high-grade tumors. Combination therapy with TC and Gemcitabine enhanced the growth-inhibitory effect in EGFR wild-type cells, while TC combined with EGFR-TKIs sensitized the EGFR-mutant cells to EGFR-TKI treatment. Taken together, the data suggest that ACSL1 may be a biomarker for lung ADC, and ACSL1, ACSL4, and ACSL5 may be involved in lung cancer differentiation, and TC, in combination with chemotherapy or EGFR-TKIs, may help patients overcome drug resistance.

In this research, the adsorption performance of individual atoms on the surface of monolayer graphene surface was systematically investigated using machine learning methods to accelerate density functional theory. The adsorption behaviors of over thirty different atoms on the graphene surface were computationally analyzed. The adsorption energy and distance were extracted as the research targets, and the basic information of atoms (such as atomic radius, ionic radius, etc.) were used as the feature values to establish the dataset. Through feature engineering selection, the corresponding input feature values for the input-output relationship were determined. By comparing different models on the dataset using five-fold cross-validation, the mathematical model that best fits the dataset was identified. The optimal model was further fine-tuned by adjusting of the best mathematical ML model. Subsequently, we verified the accuracy of the established machine learning model. Finally, the precision of the machine learning model forecasts was verified by the method of comparing and contrasting machine learning results with density functional theory. The results suggest that elements such as Zr, Ti, Sc, and Si possess some potential in controlling the interfacial reaction of graphene/aluminum composites. By using machine learning to accelerate first-principles calculations, we have further expanded our choice of research methods and accelerated the pace of studying element–graphene interactions.

Many studies have been conducted on the microbial reduction of Pd (II) to palladium nanoparticles (Pd-NPs) due to the environmental friendliness, low cost, and the decreased toxicity of Pd (II) ions. In this study, we investigate the reduction mechanism of Pd (II) by Bacillus megaterium Y-4 through proteomics. The data are available via ProteomeXchange with identifier PXD049711. Our results revealed that B. megaterium Y-4 may use the endogenous electron donor (NAD(P)H) generated by nirB, tdh, and fabG and reductase to reduce Pd (II) to Pd-NPs. The expression levels of fabG, tdh, gudB, and rocG that generate NAD(P)H were further increased, and the number of reduced Pd-NPs was further increased with the exogenous electron donor sodium formate. Endogenous electron mediators such as quinones and flavins in B. megaterium Y-4 can further enhance Pd (II) reduction. The findings provided invaluable information regarding the reduction mechanism of Pd (II) by B. megaterium Y-4 at the proteome level.

The silicon carbide (SiC) inverter brings great advantages to the motor drive systems of new energy vehicles; however, severe challenges to the bearings also happen. The high dc bus voltage and switching frequency of SiC inverter can increase the discharge frequency and energy when the bearing grease film collapses. As a result, the bearing suffers severe electric corrosion, and the service life of the motor drive system can be shortened. In this paper, the characteristics of common-mode voltage and bearing voltage are analyzed, firstly under space vector pulse width modulation (SVPWM). After that, the common-mode equivalent circuit model of the motor drive system is established. The frequency characteristics of bearing voltage are revealed, and the safe working area is determined. Then, the frequency characteristics of bearing voltage and current are verified based on IGBT and SiC inverters in experiments. After that, by designing a common-mode filter, the bearing voltage and current are significantly attenuated. Furthermore, the active zero state PWM (AZSPWM) is adopted to reduce the common-mode voltage from the inverter. At the same time, combined with the common-mode filter, the bearing voltage and current are further reduced. The experimental results show that the switching frequency has a decisive effect on the amplitude of bearing voltage and current. The bearing voltage can be attenuated to around half of the reference bearing voltage by using the common-mode filter and AZSPWM strategy, respectively. The combination of the common-mode filter and AZSPWM strategy can reduce the bearing voltage to around one-fourth of the reference bearing voltage, which can effectively reduce the breakdown time and discharge energy of the grease oil film.

Background: Accurate pre-surgical templating of the pelvic tilt (PT) angle is essential for hip and spine surgeries, yet the reliability of PT annotations is often compromised by human error, inherent subjectivity, and variations in radiographic quality. This study aims to identify challenges leading to inadequate annotations at a landmark dimension and evaluating their impact on PT. Methods: We retrospectively collected 115 consecutive sagittal radiographs for the measurement of PT based on two definitions: the anterior pelvic plane and a line connecting the femoral head’s centre to the sacral plate’s midpoint. Five annotators engaged in the measurement, followed by a secondary review to assess the adequacy of the annotations across all the annotators. Results: The outcomes indicated that over 60% images had at least one landmark considered inadequate by the majority of the reviewers, with poor image quality, outliers, and unrecognized anomalies being the primary causes. Such inadequacies led to discrepancies in the PT measurements, ranging from −2° to 2°. Conclusion: This study highlights that landmarks annotated from clear anatomical references were more reliable than those estimated. It also underscores the prevalence of suboptimal annotations in PT measurements, which extends beyond the scope of traditional statistical analysis and could result in significant deviations in individual cases, potentially impacting clinical outcomes.

Globally, forest ecosystems, especially subtropical forests, play a central role in biogeochemical cycles and climate regulation, demonstrating their irreplaceable function. The subtropical region of China, characterized by its unique forest ecosystem, complex terrain, climate heterogeneity, diverse vegetation types, and frequent human activities, underscores the importance of the in-depth study of its net primary productivity (NPP). This paper employs the eddy covariance–light use efficiency (EC-LUE) model to quantitatively estimate the gross primary productivity (GPP) of this region from 2001 to 2018, followed by an estimation of the actual net primary productivity (ANPP) using the carbon use efficiency (CUE). The results showed that over these 18 years, the annual average ANPP was 677.17 gC m−2 a−1, exhibiting an overall increasing trend, particularly in mountainous areas, reserves, and the cultivated lands of the northeastern plains, whereas a significant decrease was observed around the urban agglomerations on the southeast coast. Furthermore, the Thornthwaite memorial model was applied to calculate the potential net primary productivity (PNPP), and diverse scenarios were set to quantitatively evaluate the impact of climate change and human activities on the vegetation productivity in the study area. It was found that in areas where the ANPP increased, both human activities and climate change jointly influenced ANPP dynamics; in areas with a decreased ANPP, the impact of human activities was particularly significant. Additionally, the heterogeneous distribution of ANPP across different altitudinal gradients and the driving effects of various climatic factors were analyzed. Finally, a partial correlation analysis was used to examine the relationships between the temperature, precipitation, and ANPP. This study indicated that temperature and precipitation have a substantial impact on the growth and distribution of vegetation in the region, yet the extent of this influence shows considerable variation among different areas. This provides a robust scientific basis for further research and understanding of the carbon dynamics of subtropical forest ecosystems and their role in the global carbon cycle.