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This paper primarily investigates enhanced object detection techniques for indoor service mobile robots. Robot operating systems (ROS) supply rich sensor data, which boost the models’ ability to generalize. However, the model’s performance might be hindered by constraints in the processing power, memory capacity, and communication capabilities of robotic devices. To address these issues, this paper proposes an improved you only look once version 5 (YOLOv5)-Lite object detection algorithm based on efficient multi-scale attention and bounding box regression combined with ROS. The algorithm incorporates efficient multi-scale attention (EMA) into the traditional YOLOv5-Lite model and replaces the C3 module with a lightweight C3Ghost module to reduce computation and model size during the convolution process. To enhance bounding box localization accuracy, modified precision-defined intersection over union (MPDIoU) is employed to optimize the model, resulting in the ROS–YOLOv5–FleetEMA model. The results indicated that relative to the conventional YOLOv5-Lite model, the ROS–YOLOv5–FleetEMA model enhanced the mean average precision (mAP) by 2.7% post-training, reduced giga floating-point operations per second (GFLOPS) by 13.2%, and decreased the params by 15.1%. In light of these experimental findings, the model was incorporated into ROS, leading to the development of a ROS-based object detection platform that offers rapid and precise object detection capabilities.

It is common knowledge that immunoglobulin (Ig) is produced by B lymphocytes and mainly functions as an antibody. However, it has been shown recently that myeloblasts from acute myeloid leukemia (AML) could also express Ig and that AML-Ig played a role in leukemogenesis and AML progression. The difference between Ig from myeloblasts and B cells has not been explored. Studying the characteristics of the Ig repertoire in myeloblasts and B cells will be helpful to understand the function and significance of AML-Ig. We performed 5′ RACE-related PCR coupled with PacBio sequencing to analyze the Ig repertoire in myeloblasts and B cells from Chinese AML patients. Myeloblasts expressed all five classes of IgH, especially Igγ, with a high expression frequency. Compared with B-Ig in the same patient, AML-Ig showed different biased V(D)J usages and mutation patterns. In addition, the CDR3 length distribution of AML-Ig was significantly different from those of B-Ig. More importantly, mutations of AML-IgH, especially Igμ, Igα, and Igδ, were different from that of B-IgH in each AML patient, and the mutations frequently occurred at the sites of post-translational modification. AML-Ig has distinct characteristics of variable regions and mutations, which may have implications for disease monitoring and personalized therapy.

In order to address the issues of excessive brittle intermetallic compounds (IMC) formation in the TC4 brazed joints, two types of novel Ti-Zr-Cu-Ni-Sn amorphous braze fillers were designed. The microstructure and shear strength of the TC4/Ti-Zr-Ni-Cu-Sn/TC4 brazed joints were studied by scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffractometer (XRD) and electronic universal materials testing machine. The results show that the optimized Ti35Zr25Ni15Cu20Sn5 braze filler whose chemical composition is closer to the eutectic point possesses a lower melting point compared with the equiatomic Ti23.75Zr23.75Ni23.75Cu23.75Sn5. This was beneficial to the sufficient diffusion of Cu and Ni elements with the base metal during brazing and reduces the residual (Ti,Zr)2(Ni,Cu) content in the joint, which helps to improve the joint performance. The room-temperature and high-temperature shear strength of the TC4 brazed joints using the near eutectic component Ti35Zr25Ni15Cu20Sn5 filler reached a maximum of 472 MPa and 389 MPa at 970 °C/10 min, which was 66% and 48% higher than that of the TC4 joints brazed with the equiatomic Ti23.75Zr23.75Ni23.75Cu23.75Sn5 braze filler. Microstructural evolution and the corresponding mechanical response were in-depth discussed.

Unauthorized unmanned aerial vehicles (UAVs) pose threats to public safety and individual privacy. Traditional object-detection approaches often fall short during their application in anti-UAV technologies. To address this issue, we propose the YOLOv7-GS model, which is designed specifically for the identification of small UAVs in complex and low-altitude environments. This research primarily aims to improve the model’s detection capabilities for small UAVs in complex backgrounds. Enhancements were applied to the YOLOv7-tiny model, including adjustments to the sizes of prior boxes, incorporation of the InceptionNeXt module at the end of the neck section, and introduction of the SPPFCSPC-SR and Get-and-Send modules. These modifications aid in the preservation of details about small UAVs and heighten the model’s focus on them. The YOLOv7-GS model achieves commendable results on the DUT Anti-UAV and the Amateur Unmanned Air Vehicle Detection datasets and performs to be competitive against other mainstream algorithms.

The intricate relationships between plants and insects are essential for understanding ecological dynamics. Among these interactions, HIPVs serve as a pivotal defense mechanism. Our findings reveal the highly conserved nature of the GOX gene within the Lepidoptera order, highly expressed in the salivary glands of S. frugiperda, and its role in mediating maize’s defense responses. Notably, salivary GOX activity expression significantly decreases subsequent gene knockout. The presence of GOX in the saliva of S. frugiperda significantly modulates the emission of HIPVs during maize consumption. This research delineates that GOX selectively inhibits the emission of certain green leaf volatiles (GLVs) while concurrently enhancing the release of terpene volatiles. This study unveils a novel mechanism whereby S. frugiperda utilizes GOX proteins in OS to modulate volatile emissions from maize, offering fresh perspectives on the adaptive evolution of phytophagous insects and their interactions with their preferred host plants.

Human–object interaction (HOI) detection identifies a “set of interactions” in an image involving the recognition of interacting instances and the classification of interaction categories. The complexity and variety of image content make this task challenging. Recently, the Transformer has been applied in computer vision and received attention in the HOI detection task. Therefore, this paper proposes a novel Part Refinement Tandem Transformer (PRTT) for HOI detection. Unlike the previous Transformer-based HOI method, PRTT utilizes multiple decoders to split and process rich elements of HOI prediction and introduces a new part state feature extraction (PSFE) module to help improve the final interaction category classification. We adopt a novel prior feature integrated cross-attention (PFIC) to utilize the fine-grained partial state semantic and appearance feature output obtained by the PSFE module to guide queries. We validate our method on two public datasets, V-COCO and HICO-DET. Compared to state-of-the-art models, the performance of detecting human–object interaction is significantly improved by the PRTT.

The triboelectric nanogenerator (TENG), as a novel energy harvesting technology, has garnered widespread attention. As a relatively young field in nanogenerator research, investigations into various aspects of the TENG are still ongoing. This review summarizes the development and dissemination of the fundamental principles of triboelectricity generation. It outlines the evolution of triboelectricity principles, ranging from the fabrication of the first TENG to the selection of triboelectric materials and the confirmation of the electron cloud overlapping model. Furthermore, recent advancements in TENG application scenarios are discussed from four perspectives, along with the research progress in performance optimization through three primary approaches, highlighting their respective strengths and limitations. Finally, the paper addresses the major challenges hindering the practical application and widespread adoption of TENGs, while also providing insights into future developments. With continued research on the TENG, it is expected that these challenges can be overcome, paving the way for its extensive utilization in various real-world scenarios.

Alkaline coal mine drainage represents one of the most critical issues in the coal industry, driven by complex hydro-biogeochemical processes. However, the interplay of hydrogeochemical and biogeochemical interactions in alkaline coal mine drainage is still poorly understood. To this end, water samples were systematically collected from alkaline coal mine drainage sites from five coal mining areas in Chongqing coal mining district, located in southwestern China. Hydrogeochemical analyses showed that the main water type of the coal mine drainage sample was HCO3-SO4~K-Na, which primarily originated from local meteoric water. The microbial community compositions in the studied alkaline coal drainage were critically associated with sulfate, bicarbonate, DOC, nitrate, and pH, and linked to three putative keystone genera via network analysis (Thiothrix, Methylophilaceae_MM1, and an unclassified genus from Comamonadaceae family). Functional predictions from FAPROTAX suggested a high abundance of metabolic pathways involving the oxidation of sulfide and sulfur compounds, potentially underscoring their importance in controlling sulfate enrichment in alkaline coal mine drainage. Interestingly, members of the Methylomonadaceae family (methanotrophs) and the Methylotenera genus (methylotrophs) had positive Spearman correlations with both ammonium and sulfate, potentially inferring that the enhanced activities of methanotrophs might help capture methane in the alkaline coal mine drainage. This study further enhances our comprehension of the intricate interplay between hydrogeochemical and biogeochemical interactions in alkaline coal mine drainage, contributing to the carbon budget.

[Objective] The spatial and temporal distribution characteristics of land use carbon sources/sinks in the Huainan mining area from 2000 to 2020 were analyzed, in order to provide a basis for Huainan City’s territorial spatial planning and future low-carbon regulation policy formulation. [Methods] The study was conducted in the Huainan mining area. Grid-scale land use data in 2000, 2010, and 2020 were used to quantify the spatial and temporal patterns of carbon sources/sinks/emissions under different stages of land use change development. The spatial patterns of carbon sources/sinks/emissions were determined based on coldspots and hotspots. [Results] ① From 2000 to 2020, the land use type shifted from a single land use type to multiple land use types at the same time. The area of construction land increased, leading to an enhanced carbon source effect, a relatively weaker carbon sink effect, and a continuous increase in carbon emissions, with an annual increase in carbon sources of 2.76×106 t, an annual increase in carbon sinks of only 130 t, and an annual increase in carbon emissions of 2.76×106 t. ② The spatial distribution characteristics of carbon sources and emissions were basically the same, with the central built-up area and the northwest mining area being the main concentration areas of carbon sources and emissions. Carbon sinks were mainly concentrated in the eastern and western fringe areas and the western mining area. ③ The central built-up area of the study area was a significant hotspot area for carbon sources and emissions, dominated by significant hotspot change characteristics. Significant coldspots were mainly located in the eastern and western marginal areas of the study area and in the northwest part of the mining area. [Conclusion] Greater attention should be given to the carbon emission reduction and low carbon effect of the Huainan mining area in the large plain area of farm land in the north, as well as to controlling the mining of coal resources, to the development of construction land, and to rapid restoration of subsidized water areas. With the rapid increase of urbanization in Southern China, the area of productive carbon absorption capacity from forest land and grassland should be moderately increased to avoid unlimited expansion of construction land.

How soil sulfur (S) transformation processes and S availability respond to nitrogen (N) addition and precipitation increment are still not clearly understood in grassland ecosystems. Thus, we examined the inorganic S fractions, organic S and available S in the soil. We also measured the S concentrations in the above-ground tissues of six plant species under N and water addition in a semi-arid steppe. Nitrogen addition promoted soil acidification and the transformation of inorganic S fractions as demonstrated by the dissolution of insoluble S into soluble S and adsorbed S, therefore increasing soil S availability. This resulted in significant increases in plant S concentrations, except Leymus chinensis, under N addition. Water addition accelerated the transformation of soil S fractions through increasing the abundances of S cycling genes and enzyme-encoding sulfate reduction genes. Specifically, water addition increased the ratio of soluble S to adsorbed S. Additionally, higher soil organic S and soil total S concentrations under water addition treatment could also be due to increased S return from above-ground plant biomass, sulfate input from irrigation water, and S transported from deep soil layers by plant roots. However, water addition decreased the tissue S concentrations of Stipa krylovii and Leymus chinensis, possibly due to the dilution effect caused by enhanced biomass production. Nitrogen and water addition synergistically accelerated soil S cycling and transformations, which could mitigate ecosystem S deficiency and enlarge soil S pools in semi-arid grasslands.

ObjectivesThe most frequent cause of kidney damage in systemic lupus erythematosus (SLE) is lupus nephritis (LN), which is also a significant risk factor for morbidity and mortality. Lactate metabolism and protein lactylation might be related to the development of LN. However, there is still a lack of relative research to prove the hypothesis. Hence, this study was conducted to screen the lactate-related biomarkers for LN and analyze the underlying mechanism.MethodsTo identify differentially expressed genes (DEGs) in the training set (GSE32591, GSE127797), we conducted a differential expression analysis (LN samples versus normal samples). Then, module genes were mined using WGCNA concerning LN. The overlapping of DEGs, critical module genes, and lactate-related genes (LRGs) was used to create the lactate-related differentially expressed genes (LR-DEGs). By using a machine-learning algorithm, ROC, and expression levels, biomarkers were discovered. We also carried out an immune infiltration study based on biomarkers and GSEA.ResultsA sum of 1259 DEGs was obtained between LN and normal groups. Then, 3800 module genes in reference to LN were procured. 19 LR-DEGs were screened out by the intersection of DEGs, key module genes, and LRGs. Moreover, 8 pivotal genes were acquired via two machine-learning algorithms. Subsequently, 3 biomarkers related to lactate metabolism were obtained, including COQ2, COQ4, and NDUFV1. And these three biomarkers were enriched in pathways ‘antigen processing and presentation’ and ‘NOD-like receptor signaling pathway’. We found that Macrophages M0 and T cells regulatory (Tregs) were associated with these three biomarkers as well.ConclusionOverall, the results indicated that lactate-related biomarkers COQ2, COQ4, and NDUFV1 were associated with LN, which laid a theoretical foundation for the diagnosis and treatment of LN.

IntroductionAs a renewable forest resource, bamboo plays a role in sustainable forest development. However, traditional cutting systems, selection cutting (SeC) and clear-cutting (ClC), result in an unsustainable production of bamboo forests due to labor-consuming or bamboo degradation. Recently, a strip clear-cutting (StC) was theoretically proposed to promote the sustainability of bamboo production, while little is known about its application consequence.MethodsBased on a 6-year experiment, we applied the strip clear-cutting system in a typical running bamboo (Phyllostachys glauca McClure) forest to assess its feasibility and sustainability. Using SeC and ClC as controls, we set three treatments with different strip widths (5 m, 10 m, and 20 m) for strip clear-cutting, simplified as StC-5, StC-10, and StC-20, respectively. Then, we investigated leaf physiological traits, bamboo size and productivity, population features, and economic benefits for all treatments.ResultsThe stands managed by StC had high eco-physiological activities, such as net photosynthetic rate (Pn), photosynthetic nitrogen use efficiency (PNUE), and photosynthetic phosphorus use efficiency (PPUE), and thus grew well, achieved a large diameter at breast height (DBH), and were tall. The stand biomass of StC (8.78 t hm-2 year-1) was 1.19-fold and 1.49-fold greater than that of SeC and ClC, respectively, and StC-10 and StC-20 were significantly higher than SeC or ClC (p< 0.05). The income and profit increased with the increase in stand density and biomass, and StC-20 and StC-10 were significantly higher than SeC or ClC (p< 0.05). Using principal components analysis and subordinate function analysis, we constructed a composite index to indicate the sustainability of bamboo forests. For the sustainability assessment, StC-10 had the highest productive sustainability (0.59 ± 0.06) and the second highest economic sustainability (0.59 ± 0.11) in all cutting treatments. StC-10 had the maximum overall sustainability, with a value of 0.53 ± 0.02, which was significantly higher than that of ClC (p< 0.05).ConclusionThe results verified that StC for Phyllostachys glauca forests is feasible and sustainable as its sustainability index outweighs those of traditional cutting systems (SeC and ClC), and 10 m is the optimum distance for the strip width of StC. Our findings provide a new cutting system for managing other running bamboo forests sustainably.

The damage characteristics of fused silica were investigated under low-temporal coherence light (LTCL). It was found that the laser-induced damage threshold (LIDT) of fused silica for the LTCL was lower than that of the single longitudinal mode pulse laser, and for the LTCLs, the LIDTs decrease with the increasing of laser bandwidth, which is not consistent with the temporal spike intensity. This is due to the nonlinear self-focusing effect and multi-pulse accumulation effect. The specific reasons were analyzed based on theoretical simulation and experimental study. This research work is helpful and of great significance for the construction of high-power LTCL devices.

In this work, we proposed a triboelectric nanogenerator (TENG) based on cellulose nanocrystal (CNC)/gelatin composite film (CG-TENG) to monitor the posture and movements of athletes during jumping training. The triboelectric layers comprise a polytetrafluoroethylene film (which carries a negative charge) and a CNC/gelatin composite film (manifesting a positive charge). The CNC is derived from recycled wasted boxes using the traditional sulfuric acid hydrolysis method and is incorporated into the gelatin film as a nanoscale additive. By utilizing an external load resistance measuring 20 MΩ, it is possible to attain an all-time high instantaneous power of 583 µW. The electrical output of the CG-TENG demonstrates notable stability and endurance, as it maintains a consistent pattern during a duration of more than 30 000 cycles. By capitalizing on sustainable and green materials, the CG-TENG paves the way for innovative sports monitoring solutions, amplifying the potential for human physiological signal tracking.

BackgroundThe etiology of recurrent spontaneous abortion (RSA) remains elusive despite specific investigations affirming the association between RSA and thyroid autoimmunity (TAI). This study explores the immunological and metabolic profiles of RSA patients exhibiting positive thyroid antibodies and their connection with the rates of first-trimester miscarriage and live births. The aim is to provide further guidance for clinical interventions.MethodsA retrospective analysis included 478 women with RSA. Thyroid profile, thyroid peroxidase antibodies, and anti-thyroglobulin antibodies were measured in all participants. The clinical characteristics and pregnancy outcomes of RSA women were compared between thyroid autoimmunity (TAI)-positive and TAI-negative patients. Significant factors associated with adverse pregnancy outcomes and risk prediction models were explored in TAI-positive patients. Correlation analysis was used to identify specific metabolic or immune biomarkers associated with thyroid autoantibodies.ResultsThe prevalence of TAI was 18.6%. Compared with women without TAI, the thyroid-stimulating hormone (TSH) concentration of TAI-positive RSA was significantly higher (2.80 ± 2.98 vs 1.89 ± 1.17, p=0.006). After 28 weeks, the live birth rate of the TAI-positive group was lower than that of the TAI-negative group, with statistical significance (p

PurposeThis study aimed to clarify the effect of early glucocorticoid (GC) application on achieving minimal manifestation (MM) status or better in the treatment of myasthenia gravis (MG) in the early clinical phase.MethodsA retrospective analysis was performed using data from 336 patients with MG who received GC therapy from January 2015 to September 2022 in the Zhengzhou University Henan Institute of Medical and Pharmaceutical Sciences Myasthenia Gravis Biobank (ZMB). Patients were divided into two groups: the early mono-GC group (treated with GC within 6 months of MG onset) and the delayed mono-GC group.ResultsKaplan–Meier analysis showed that the early mono-GC group achieved MM status earlier and more frequently than the delayed mono-GC group (log-rank test, p = 0.0082; hazard ratio [HR], 1.66; p = 0.011). The early mono-GC group had a lower maintenance oral GC dose than the delayed mono-GC group. In multivariate Cox regression analysis, early mono-GC (HR, 1.50; p = 0.043), early-onset MG (EOMG) (HR, 1.74; p = 0.034), and ocular MG (OMG) (HR, 1.90; p = 0.007) were associated with MM status or better. In conclusion, early mono-GC, EOMG, and OMG were positive predictors of treatment goals. In EOMG, OMG, and acetylcholine receptor antibody-positive MG (AChR-MG) subgroups, the maintenance oral GC doses in the early mono-GC group were significantly lower than the doses in the delayed mono-GC group (p < 0.05).ConclusionEarly intervention with GC led to better long-term outcomes and reduced the necessary maintenance dose of oral GC for patients with MG. EOMG and OMG were positive predictors of MM status or better with mono-GC.

In this work, an efficient and green approach has been presented to prepare carbon quantum dots (CQDs) from watermelon juice through a microfluidic steam-based method, with a view to enabling continuous production at scale, i.e., to save time, costs, or energy as compared to conventional production using an autoclave. The evolution of the product formation through multifarious intermediates generated in different stages of the reaction process was characterized. Computational fluid dynamics simulations reveal the pressure and velocity profiles in the microchannel to exert process control. These determine the quality of the obtained CQDs by influencing the particle size transformations and manifold chemicals along the microchannel axis. The optimal reaction conditions and reaction mechanism for the synthesis of CQDs were investigated. Additionally, the synthesized CQDs demonstrated good fluorescence properties as well as a specific response to NO2−{\text{NO}}_{2}^{-} in both fluorescence and spectrophotometric modes, providing great potential for their application in environmental monitoring.

In order to develop lithium-ion batteries with high energy density, prelithium technology has attracted extensive attention. Li5FeO4was successfully prepared by molten salt method with LiNO3-LiOH mixed lithium salt as reaction medium and lithium source, and nano Fe2O3 as iron source in this work. Li5FeO4 as cathode prelithiation additive is applied to lithium-ion batteries. The synthesis conditions of Li5FeO4 were optimized by orthogonal experiment, and the effect of synthesis conditions on the electrochemical properties of the material was discussed. Li5FeO4 was added to the surface of LiFePO4 positive electrode and assembled with graphite negative electrode to form a full cell. Its effect on the electrochemical performance of the full cells and the mechanism of reducing the initial capacity loss of lithium-ion batteries were studied. The results show that Li5FeO4 cathode prelithiation additives with high purity, small particle size and outstanding electrochemical performance can be prepared by molten salt method. When Li5FeO4 with a mass fraction of 2.8%(based on the percentage of active materials mass) was added, the discharge specific capacity of first cycle for the LiFePO4/graphite full cell was 150 mAh·g-1 at 0.05 C, which was 8.5% higher than that without adding, after 100 cycles at 0.2 C. the capacity still increased by 7.1%, and the irreversible capacity of the svstem was restored.

Abstract MEMS resonators exhibit rich dynamic behaviors under the internal resonance regime. In this work, we present a novel MEMS bifurcation sensor that exploits frequency unlocking due to a 1:3 internal resonance between two electrostatically coupled micro-resonators. The proposed detection mechanism allows the sensor to operate in binary (digital) and analog modes, depending on whether the sensor merely detects a significant jump event in the peak frequency upon unlocking or measures the shift in the peak frequency after unlocking and uses it in conjunction with a calibration curve to estimate the corresponding change in stimulus. We validate the success of this sensor paradigm by experimentally demonstrating charge detection. High charge resolutions are achieved in binary mode, up to 0.137 fC, and in analog mode, up to 0.01 fC. The proposed binary sensor enables extraordinarily high detection resolutions due to the excellent frequency stability under internal resonance and the high signal-to-noise ratio of the shift in peak frequency. Our findings offer new opportunities for high-performance ultrasensitive sensors.

Abstract In this paper, we study the X(3860) production associated with $$J/\psi $$ J / ψ via $$e^{+}e^{-}$$ e + e - annihilation at the next-to-leading-order (NLO) accuracy in $$\alpha _s$$ α s , within the nonrelativistic QCD (NRQCD) framework. With the hypothesis of $$J^{PC}_{X(3860)}=0^{++}$$ J X ( 3860 ) PC = 0 + + , the predictions of $$\sigma _{e^{+}e^{-} \rightarrow J/\psi +X(3860)}$$ σ e + e - → J / ψ + X ( 3860 ) agree well with the Belle measurements, whereas the results following the $$2^{++}$$ 2 + + assignment significantly undershoot the data. This is consistent with the Belle’s conclusion that the $$0^{++}$$ 0 + + hypothesis is favored over the $$2^{++}$$ 2 + + hypothesis for X(3860). Despite fitting the data of the total cross section, the NRQCD predictions seem to be incompatible with the measured $$J/\psi $$ J / ψ angular distributions. We simultaneously calculate the cross section of $$e^{+}e^{-} \rightarrow J/\psi +X(3940)$$ e + e - → J / ψ + X ( 3940 ) under the assumption of $$J^{PC}_{X(3940)}=0^{-+}$$ J X ( 3940 ) PC = 0 - + , discovering the consistency of the NRQCD predictions with the light-cone results as well as the experiment.

Abstract Background Previous clinical trials indicated the addition of anti‐PD‐1 antibody remarkably improved the efficacy of trastuzumab and chemotherapy in patients with HER2‐positive gastric/gastroesophageal junction (GEJ) cancer. However, no real‐world experiences have been reported yet. Methods We retrospectively analyzed 1212 patients with gastric/GEJ cancer treated at Nanjing Drum Tower Hospital between 2019 and 2022. Among 138 patients with HER2‐positive gastric/GEJ cancer, 47 patients receiving at least two doses of the combination regimen with anti‐PD‐1 antibody, trastuzumab, and chemotherapy were recruited in the study population, and 38 out of 47 patients with measurable disease were included in the efficacy population. Progression‐free survival (PFS), objective response rate (ORR), disease control rate (DCR), and toxicity profiles were reported. Results In the study population, 37 (78.7%) received the study therapy as a first‐line treatment. In the efficacy population, the ORR and DCR were 76.3% and 94.7%, respectively. The overall median PFS was 9.1 months (95% confidence interval [CI] 6.3–11.9 months). For the first‐line treatment, the mPFS was 10 months, and 7 months for the second‐line. Among 14 patients who failed the study treatment, three (21.4%) developed brain metastasis as the first failure site. No significant association was found between PFS and the expression of PD‐L1. 22.2% of patients developed grade 3 treatment‐related adverse events (TRAEs). No treatment‐related grade ≥4 adverse events or deaths occurred. Conclusion This real‐world study validated the combination regimen's high efficacy and good tolerance in patients with HER2‐positive gastric/GEJ cancer. An increased incidence of brain metastasis was observed in patients who failed this regimen.

As a result of the uneven growth of rice, unbalanced vibration of threshing drum caused by stalk entanglement in combine harvester is more and more severe. In order to reveal the influence of unbalanced excitation on the roller axis locus during rice threshing, the stability of threshing drum was studied. The dynamic signal test and analysis system are used to test the axial trajectory of threshing drum. At the same time, the influence of the unbalanced excitation caused by the axis winding on the axis trajectory is analyzed by the experimental results. Axis locus rules under no-load and threshing conditions are obtained. In order to simulate the axial and radial distribution of unbalanced excitation along the threshing drum, the counterweight was distributed on the threshing drum instead of the entangled stalk. Then, the definite effect of unbalanced excitation on the rotating stability of threshing drum is analyzed. Results show that the amplitude of stem winding along the grain drum is larger in the vertical direction and smaller in the horizontal direction when compared with the unloaded state under 200 g weight. It was found that the amplitude in both horizontal and vertical directions decreased after 400 g and 600 g counterweights were added, respectively, to simulate the radial distribution of stalk winding along the grain barrel. Finally, it can be seen that with the increase in the weight of the counterweight, the characteristics of the trajectory misalignment of the threshing cylinder axis become more and more obvious. This study can provide reference for reducing the unbalanced excitation signal of threshing drum and improving driving comfort.

UDP-glycosyltransferases (UGTs) are a diverse superfamily of enzymes. Insects utilize uridine diphosphate-glucose (UDP-glucose) as a glycosyl donor for glycosylation in vivo, involved in the glycosylation of lipophilic endosymbionts and xenobiotics, including phytotoxins. UGTs act as second-stage detoxification metabolizing enzymes, which are essential for the detoxification metabolism of insecticides and benzoxazine compounds. However, the UGT genes responsible for specific glycosylation functions in S. frugiperda are unclear at present. In this study, we utilized CRISPR/Cas9 to produce a SfUGT50A15-KO strain to explore its possible function in governing sensitivity to chemical insecticides or benzoxazinoids. The bioassay results suggested that the SfUGT50A15-KO strain was significantly more sensitive to chlorantraniliprole, emamectin benzoate, and benzoxazinoids than the wild-type strains. This finding suggests that the overexpression of the SfUGT50A15 gene may be linked to S. frugiperda resistance to pesticides (chlorantraniliprole and emamectin benzoate) as well as benzoxazinoids (BXDs).

Feeding rates serve as a vital indicator for adjusting the working parameters of the combine harvester. A non-invasive diagnostic approach to predicting the feed rates of combine harvesters by collecting vibration signals of the inclined conveyor was introduced in this study. To establish a feed rate prediction model, the correlation between feeding rates and vibration signal characteristics was investigated. Vibration signal characteristics in both the time domain and frequency domain were also analyzed in detail. The RMS (root mean square) value and the total RMS value of the one-third octave extracted from the vibration signal were utilized to establish a feed rate prediction model, and field tests were conducted to verify the model performance. The experimental results indicated that the relative errors of the established model range from 3.1% to 4.9% when harvesting rice. With the developed feed rate prediction system, the control system of the combine harvester can acquire feed rate information in real time, and the working parameters can be adjusted in advance, thereby, it can be expected to greatly enhance the working performance of the combine harvesters.

Aquaporin-4 (AQP4) is a water channel protein that links the astrocytic endfeet to the blood-brain barrier (BBB) and regulates water and potassium homeostasis in the brain, as well as the glymphatic clearance of waste products that would otherwise potentiate neurological diseases. Recently, translational readthrough was shown to generate a C-terminally extended variant of AQP4, known as AQP4x, which preferentially localizes around the BBB through interaction with the scaffolding protein α-syntrophin, and loss of AQP4x disrupts waste clearance from the brain. To investigate the function of AQP4x, we generated a novel AQP4 mouse line (AllX) to increase relative levels of the readthrough variant above the ~15% of AQP4 in the brain of wild-type (WT) mice. We validated the line and assessed characteristics that are affected by the presence of AQP4x, including AQP4 and α-syntrophin localization, integrity of the BBB, and neurovascular coupling. We compared AllXHom and AllXHet mice to WT and to previously characterized AQP4 NoXHet and NoXHom mice, which cannot produce AQP4x. An increased dose of AQP4x enhanced perivascular localization of α-syntrophin and AQP4, while total protein expression of the two was unchanged. However, at 100% readthrough, AQP4x localization and the formation of higher order complexes were disrupted. Electron microscopy showed that overall blood vessel morphology was unchanged except for an increased proportion of endothelial cells with budding vesicles in NoXHom mice, which may correspond to a leakier BBB or altered efflux that was identified in NoX mice using MRI. These data demonstrate that AQP4x plays a small but measurable role in maintaining BBB integrity as well as recruiting structural and functional support proteins to the blood vessel. This also establishes a new set of genetic tools for quantitatively modulating AQP4x levels.

PurposeTo verify the International Chronic Ocular Graft-Versus-Host Disease (ICCGVHD) Group diagnostic criteria and establish an easy-to-use and reliable diagnosis model for quick identification of chronic oGVHD.MethodsThis study included 180 patients (355 eyes) who underwent allogeneic hematopoietic stem cell transplantation (allo-HSCT) and visited the Peking University Third Hospital Cornea and Ocular Surface Disease Specialist Clinic from July 2020 to February 2021. The proportion of chronic oGVHD was 76.06% (279/355).ResultsFive complaints, including eye dryness, photophobia, foreign body sensation, eye redness, and burning sensation; six ophthalmic examinations, including Ocular Surface Disease Index (OSDI) score, corneal fluorescein staining (CFS), tear break-up time (TBUT), Schirmer’s test score without anesthesia, conjunctival score, tear meniscus height, and non-ocular GVHD-involved organs were significantly different between patients with chronic oGVHD and control group (p

PurposeEffective Altruism (EA) has become one of the most prominent socio-philosophical movements of recent years. EA is also facing intense scrutiny due to the business practices of some of its most prominent adherents. On the other hand, the dark triad traits of Machiavellianism, narcissism and psychopathy have been getting increasing attention in entrepreneurship research. There is growing evidence that these traits can motivate entrepreneurial intention. We therefore sought to investigate if there was a connection between the entrepreneurship discourse in EA and traits corresponding to dark triad behavior.Design/methodology/approachUsing a discursive analytic method, we investigated the discursive threads on entrepreneurship in EA over a 10-year period.FindingsWhile we believe EA brings a much-needed perspective to the overall debate on doing good, we found ample evidence that it might have promoted the sort of dark triad behavior which some evidence suggests can lead to financial success, but can equally lead to the type of morally bankrupt, unethical and even illegal practices of some entrepreneurs. We also discovered a somewhat temporal dimension in EA’s discourse on entrepreneurship, beginning with discourse encouraging some risk taking and entrepreneurship, before moving on to discourses on the benefits of having a smart and illicit character, and ending with a focus on aggressive risk taking.OriginalityThe findings contribute to the still nascent debate on dark personality traits in entrepreneurship, and enriches the theoretical advancement of the field. However, our research differs from prior studies which were almost exclusively focused on the firm. Instead, we examine this phenomenon within a highly influential belief system/philosophical movement.

Abstract Background Short-term researches have studied the change of the center of rotation (COR) after the Bryan Cervical disc arthroplasty (CDA). But there is a lack of long-term studies focusing on the location of COR and its influence after surgery. Methods Clinical and radiographic materials of patients who received CDA were retrospectively reviewed. Written informed consents were obtained. Clinical outcome was accessed by Japanese Orthopaedic Association (JOA), Neck Disability Index (NDI), and Odom’s scale. Radiographic evaluation underwent before surgery, at early (3 months) follow-up and final (minimal 10 years) follow-up. The ROM of the global cervical spine and index level, the functional spine unit (FSU) angle and C2-C7 angle were measured. COR was identified and its coordinates were calculated. The absolute change of COR-x and COR-y were compared in subgroup analysis. Results Sixty patients were included, with an average age of 55.9 ± 8.1 years old. The mean duration of follow up was 135.1 ± 16.1 (120–155) months. JOA, NDI and Odom’s scale showed significant improvements at 10 years after surgery. The COR of index level was located in the posterior superior half of the caudal vertebral body. Following the implant of Bryan Disc, the COR shifted forward and downward. During the 10-year follow-up, the location of COR remained stable. ROM at the index level decreased from 10.6 ± 4.0° preoperatively to 9.3 ± 4.0° at the early follow-up (p = 0.03). The ROM at the index level remained unchanged from early follow-up to the final follow-up (9.3 ± 4.0° vs 9.5 ± 5.2°, p = 0.80). In subgroup analysis, larger changes of both COR-x and COR-y were related with decreased ROM. Conclusions Our study illustrated that Bryan CDA could achieved favorable clinical and radiographic outcome over a minimal 10-year follow-up. The reduction of the flexion-extension ROM may be correlated with a more deviated postoperative COR. More attention should be paid to preoperative design and intraoperative technique to obtain a more native COR.

Automatic 2D vision-based defect detection on sealing nail (SealN) surfaces is challenging due to interference of complex backgrounds with non-homogeneous and low contrast between foreground and background. Inspired by an interesting observation that the albedo domain recovered by the uncalibrated photometric stereo (UPS) shows obvious differences and significant abruptness between defects’ and non-defects’ regions, we develop a novel semantic-guided variational model (SGVM) to conditional extract structural defects from albedo map. Specifically, SGVM utilizes one developed global regularized label indicator to semantically guide one local regularized relative Gaussian filter (RGF) for achieving large-scale structures (i.e., defects) preservation and small-scale textures (i.e., background) suppression. Furthermore, defects can be efficiently extracted by thresholding the structure map within the label indicator. Additionally, experimental results on numerous challenging defect images reveal that the proposed SGVM outperforms the existing advanced 2D methods in terms of defect extraction.

Depth estimation for light field (LF) images is the cornerstone of many applications of light field cameras, such as 3D reconstruction, defects inspection, face liveness detection, and so forth. In recent years, convolutional neural network (CNN) has dominated the primary workhorse for depth estimation. However, the interpretability of the network and the accuracy of the depth estimation results still need to be improved. This paper uses the conditional random field (CRF) theory to explain and model the LF depth estimation. Further, from the perspective of sequence analysis, we extract the sequence features of epipolar plane image (EPI) patches with recurrent neural network (RNN) and serve as the unary term of the energy function in the CRF. Then, a unified neural network (called as LFRNN) is designed to solve the CRF and get the disparity map. Our LFRNN builds upon two-stage architecture, involving a local depth estimation and a depth refinement. In the first part, we design an RNN to analyze the vector sequences in EPI patches and obtain local disparity values. There are two thinking behind the design of this part. The first is the general principle that the slope of the straight line in the EPI is inversely proportional to the depth; the second is our unique observation that those straight lines are distributed in vector sequences. In the second part, continuous CRF is used to optimize the output of the first part. We train LFRNN on a synthetic LF dataset and test it on both synthetic and real-world LF datasets. Quantitative and qualitative results validate the superior performance of our LFRNN over the state-of-the-art methods.