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Iris typhifolia Kitag is a perennial herbaceous species with high ornamental and applied value. Elucidating the mechanism of saline–alkali tolerance in Iris is crucial for their promotion in saline–alkali areas. Saline–alkali stress is one of the factors that affects plant growth, which has become a significant global issue. In this study, we measured the physiological and biochemical indexes of I. typhifolia, through germination and potting trials, to evaluate the resistance of I. typhifolia to different levels of artificial saline–alkali stress (0, 50, 100, 150, and 200 mmol·L−1). The results showed that artificial saline–alkali stress negatively impacted germination parameters, cell membrane integrity, and photosynthetic parameters. Different trends in osmoregulatory substances and endogenous hormones were observed. It was shown that I. typhifolia had a potential adaptability to the saline–alkali environment by enhancing its internal defense mechanism. Based on regression analyses, the germination threshold of I. typhifolia was calculated to be 87.15 mmol·L−1, which provided a theoretical basis for the application in soil saline–alkalization areas. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAVs) equipped with remote-sensing object-detection devices are increasingly employed across diverse domains. However, the detection of small, densely-packed objects against complex backgrounds and at various scales presents a formidable challenge to conventional detection algorithms, exacerbated by the computational constraints of UAV-embedded systems that necessitate a delicate balance between detection speed and accuracy. To address these issues, this paper proposes the Efficient Multidimensional Global Feature Adaptive Fusion Network (MGFAFNET), an innovative detection method for UAV platforms. The novelties of our approach are threefold: Firstly, we introduce the Dual-Branch Multidimensional Aggregation Backbone Network (DBMA), an efficient architectural innovation that captures multidimensional global spatial interactions, significantly enhancing feature distinguishability for complex and occluded targets. Simultaneously, it reduces the computational burden typically associated with processing high-resolution imagery. Secondly, we construct the Dynamic Spatial Perception Feature Fusion Network (DSPF), which is tailored specifically to accommodate the notable scale variances encountered during UAV operation. By implementing a multi-layer dynamic spatial fusion coupled with feature-refinement modules, the network adeptly minimizes informational redundancy, leading to more efficient feature representation. Finally, our novel Localized Compensation Dual-Mask Distillation (LCDD) strategy is devised to adeptly translate the rich local and global features from the higher-capacity teacher network to the more resource-constrained student network, capturing both low-level spatial details and high-level semantic cues with unprecedented efficacy. The practicability and superior performance of our MGFAFNET are corroborated by a dedicated UAV detection platform, showcasing remarkable improvements over state-of-the-art object-detection methods, as demonstrated by rigorous evaluations conducted using the VisDrone2021 benchmark and a meticulously assembled proprietary dataset. [ABSTRACT FROM AUTHOR]

In recent years, caffeic acid and its derivatives have received increasing attention due to their obvious physiological activities and wide distribution in nature. In this paper, to clarify the status of research on plant-derived caffeic acid and its derivatives, nuclear magnetic resonance spectroscopy data and possible biosynthetic pathways of these compounds were collected from scientific databases (SciFinder, PubMed and China Knowledge). According to different types of substituents, 17 caffeic acid and its derivatives can be divided into the following classes: caffeoyl ester derivatives, caffeyltartaric acid, caffeic acid amide derivatives, caffeoyl shikimic acid, caffeoyl quinic acid, caffeoyl danshens and caffeoyl glycoside. Generalization of their 13C-NMR and 1H-NMR data revealed that acylation with caffeic acid to form esters involves acylation shifts, which increase the chemical shift values of the corresponding carbons and decrease the chemical shift values of the corresponding carbons of caffeoyl. Once the hydroxyl group is ester, the hydrogen signal connected to the same carbon shifts to the low field (1.1~1.6). The biosynthetic pathways were summarized, and it was found that caffeic acid and its derivatives are first synthesized in plants through the shikimic acid pathway, in which phenylalanine is deaminated to cinnamic acid and then transformed into caffeic acid and its derivatives. The purpose of this review is to provide a reference for further research on the rapid structural identification and biofabrication of caffeic acid and its derivatives. [ABSTRACT FROM AUTHOR]

As the impact of climate change intensifies, meeting the energy demand of buildings in China's cold regions is becoming increasingly challenging, particularly in terms of cooling energy consumption. The effectiveness of integrating phase change material (PCM) into building envelopes for energy saving in China's cold regions is unclear. The aim of this study is to assess the effectiveness of PCM integration in building enclosures for energy efficiency in these regions. The research monitored and recorded indoor temperature data from typical residential cases from May to September. This measured data was then used to validate the accuracy of EnergyPlus22-1 software simulation models. Subsequently, the calibrated model was utilized to conduct a comparative analysis on the effects of PCM on indoor temperatures and cooling energy consumption across these regions. The results of these comparative analyses indicated that PCM can alleviate indoor overheating to varying degrees in severe cold regions of China. Focusing on north-facing bedrooms, applying PCMs reduced the duration of overheating in non-air-conditioned buildings in severe cold regions of China by 136 h (Yichun), 340 h (Harbin), 356 h (Shenyang), and 153 h (Dalian). In terms of cooling energy consumption, the energy saved by applying PCMs ranged from 1.48 to 13.83 kWh/m2. These results emphasize that the performance of PCM varies with climate change, with the most significant energy-saving effects observed in severe cold regions. In north-facing bedrooms in Harbin, the energy-saving rate was as high as 60.30%. Based on these results, the study offers guidance and recommendations for feasible passive energy-saving strategies for buildings in severe cold and cold regions of China in the face of climate change. Additionally, it provides practical guidance for applying PCMs in different climatic zones in China. [ABSTRACT FROM AUTHOR]

Endoscopy, a pervasive instrument for the diagnosis and treatment of hollow anatomical structures, conventionally necessitates the arduous manual scrutiny of seasoned medical experts. Nevertheless, the recent strides in deep learning technologies proffer novel avenues for research, endowing it with the potential for amplified robustness and precision, accompanied by the pledge of cost abatement in detection procedures, while simultaneously providing substantial assistance to clinical practitioners. Within this investigation, we usher in an innovative technique for the identification of anomalies in endoscopic imagery, christened as Context-enhanced Feature Fusion with Boundary-aware Convolution (GFFBAC). We employ the Context-enhanced Feature Fusion (CEFF) methodology, underpinned by Convolutional Neural Networks (CNNs), to establish equilibrium amidst the tiers of the feature pyramids. These intricately harnessed features are subsequently amalgamated into the Boundary-aware Convolution (BAC) module to reinforce both the faculties of localization and classification. A thorough exploration conducted across three disparate datasets elucidates that the proposition not only surpasses its contemporaries in object detection performance but also yields detection boxes of heightened precision. [ABSTRACT FROM AUTHOR]

By decomposing observed El Niño and La Niña events into a strong group and a weak group, respectively, we discovered that the strong La Niña group has its peak center more towards the west compared to the weak La Niña group, whereas the strong El Niño group has its peak center more towards the east compared to the weak El Niño group. The cause of this structure asymmetry is investigated through an ocean mixed-layer heat budget analysis. It was found that the asymmetry is closely linked to the longitudinal distribution of SST anomaly (SSTA) skewness along the equator, and is fundamentally caused by nonlinear dynamic heating, especially nonlinear horizontal temperature advection. It was demonstrated that near the equatorial central Pacific, the anomalous zonal and meridional currents generate negative nonlinear zonal and meridional temperature advection anomalies for both the El Niño and La Niña events, thus favoring a stronger La Niña and a weaker El Niño. Over the eastern Pacific, due to the dominant geostrophic zonal current anomalies and the southward shift of SSTA centers, nonlinear horizontal temperature advection anomalies tend to be positive for both the El Niño and La Niña, thus favoring a stronger growth of El Niño than La Niña. Nonlinear vertical temperature advection anomalies play minor roles in the central Pacific and tend to partially offset the nonlinear horizontal advection effect in the equatorial eastern Pacific. [ABSTRACT FROM AUTHOR]

During the sinking process, overflow generates an entrainment phenomenon, accompanied by the occurrence, development, and dissipation of vortices. In this paper, particle image velocimetry (PIV) technology is used to measure the flow fields of overflow sinking, invasion, and mixing. In order to quantitatively analyze the mixing and flow processes during the sinking of the overflow, vorticity, turbulence dissipation, Froude number, local Richardson number, and entrainment coefficient are calculated. In a stratified environment, the overflow entrains the environment fluid of lower density to reach a terminal height where their density equals that of their surroundings and then spread out horizontally. The experimental results show the terminal depth is related to the density of the overflow. The lower the density, the smaller the terminal depth. The turbulent dissipation mainly occurs in the area along the slope and during the process of invading flow to the surrounding. The extreme of the turbulent dissipation is corresponding to the maximum velocity shear and vorticity. At the point where the overflow crosses the sill and at the front end of the overflow, there will be a more obvious phenomenon of entrainment. The entrainment parameter is positively correlated with the density of overflow. These preliminary results would require additional experimental validation and data observation in order to assess their relevance for realistic flow regimes. [ABSTRACT FROM AUTHOR]

This paper studies motor structures and optimization methods for space robots, proposing an optimized stepped rotor bearingless switched reluctance motor (BLSRM) to solve the poor self-starting ability and significant torque fluctuation issues in traditional BLSRMs. Firstly, the advantages and disadvantages of the 12/14 hybrid stator pole type BLSRM were analyzed, and a stepped rotor BLSRM structure was designed. Secondly, the particle swarm optimization (PSO) algorithm was improved and combined with finite element analysis for motor structure parameter optimization. Subsequently, a performance analysis of the original and new motors was conducted using finite element analysis software, and the results showed that the stepped rotor BLSRM had an improved self-starting ability and significantly reduced torque fluctuation, verifying the effectiveness of the proposed motor structure and optimization method. [ABSTRACT FROM AUTHOR]

Significant developments have been made in the navigation of autonomous mobile robots within indoor environments; however, there still remain challenges in the face of poor map construction accuracy and suboptimal path planning, which limit the practical applications of such robots. To solve these challenges, an enhanced Rao Blackwell Particle Filter (RBPF-SLAM) algorithm, called Lidar-based RBPF-SLAM (LRBPF-SLAM), is proposed. In LRBPF, the adjacent bit poses difference data from the 2D Lidar sensor which is used to replace the odometer data in the proposed distribution function, overcoming the vulnerability of the proposed distribution function to environmental disturbances, and thus enabling more accurate pose estimation of the robot. Additionally, a probabilistic guided search-based path planning algorithm, gravitation bidirectional rapidly exploring random tree (GBI-RRT), is also proposed, which incorporates a target bias sampling to efficiently guide nodes toward the goal and reduce ineffective searches. Finally, to further improve the efficiency of navigation, a path reorganization strategy aiming at eliminating low-quality nodes and improving the path curvature of the path is proposed. To validate the effectiveness of the proposed method, the improved algorithm is integrated into a mobile robot based on a ROS system and evaluated in simulations and field experiments. The results show that LRBPF-SLAM and GBI-RRT perform superior to the existing algorithms in various indoor environments. [ABSTRACT FROM AUTHOR]

It is still a clinical challenge to sustain the remission of rheumatoid arthritis (RA); thus, identifying more effective and safer agents for RA treatment remains an urgent demand. We investigated the anti-arthritic activity and potential mechanism of action of sodium Danshensu (SDSS), a structurally representative water-soluble derivative of Danshen, on collagen-induced arthritis (CIA) mice. Our results showed that paw edema, synovium hyperplasia, bone destruction, and the serum levels of both IL-1β and IL-6 were ameliorated by SDSS (40 mg/kg·d) in CIA mice. In addition, there was no difference between SDSS and methotrexate (MTX, 2 mg/kg·3d) treatment in the above indicators. Further mechanism studies illustrated that SDSS inhibited IL-1β secretion by downregulating the HIF-1α/STAT3/NLRP3 pathway in macrophages. On the other hand, HIF-1α accumulation and HIF-1α/STAT3/NLRP3 pathway activation by IOX4 stimulation reduced the therapeutic effect of SDSS. These findings demonstrate that SDSS displays anti-arthritic activity in CIA mice and prevents proinflammatory cytokines secretion in macrophages by suppressing the HIF-1α/STAT3/NLRP3 pathway. [ABSTRACT FROM AUTHOR]

Due to global warming, the overheating risk in the severe cold region of China has attracted attention, but so far, no studies have examined summer overheating in this region. This paper aims to reveal the overheating risk in recent and future climates in the severe cold region of China. An 18-storey residential building in the severe cold region of China was monitored from May to September 2021 to validate the simulation data of the indoor temperature. Weather files of the typical meteorological year (TMY) from 2007 to 2020, observations in 2021, and forecasts for the climate in different carbon emission scenarios (2030, 2060) were used to simulate the indoor temperature and assess the overheating risk. The results revealed the severity of the overheating risk; the overheating hours in the south-facing bedroom were recorded as 884 h (24.07%) with the TMY weather data and 1043 h (28.40%) in 2030 and 1719 h (46.81%) in 2060 under the RCP8.5 carbon emission scenario. Thus, the low carbon emissions policy may significantly alleviate overheating. Moreover, to cope with climate change, it is suggested that the Chinese local design standards should consider the summer overheating risk and make the necessary adjustments. [ABSTRACT FROM AUTHOR]

Columnar apple was an important germplasm resource to develop compact cultivars for labor-saving cultivation and to study fruit tree architecture. MdCoL is a strong candidate gene for controlling the columnar phenotype in apple. In this study, a 2000 bp upstream region of MdCoL was cloned as a full-length promoter, named MdCoLp1. To gain a better understanding of the characterization of the MdCoL promoter, cis-acting elements and the binding sites of transcription factors were predicted and analyzed, and four binary expression vectors consisting of the GUS reporter gene under the control of the MdCoL promoter was transformed into Arabidopsis thaliana to analyze the response to abscisic acid (ABA), brassinosteroid (BR) and gibberellic acid (GA3) of MdCoL promoters. Multiple transcription factors involving TCP, BEL1 and BES1/BZR1 and other transcription factor (TF) binding sites were predicted on the promoter of MdCoL. Histochemical staining showed that both full-length and 5′ truncated promoters could initiate GUS expression. The GUS activity was the most in leaf and stem, and mainly concentrated in the fibrovascular tissue, followed by root, and the least activity was observed in silique and flower. In addition, MdCoL expression was mainly localized in the quiescent center (QC) and lateral root growing point of root tip and the vascular tissue of stem and leaf by in situ hybridization. The results of exogenous hormones treatment showed that ABA and BR could activate the activity of the MdCoL promoter, while GA3 had opposite effects. In columnar apple seedlings, ABA treatment could upregulate the expression of MdCoL, but GA3 and BR restrained the transcription level of MdCoL. These results provide the foundation for deciphering the regulatory network of hormones affecting MdCoL transcription. [ABSTRACT FROM AUTHOR]

In the context of the long-term coexistence between COVID-19 and human society, the implementation of personnel health monitoring in construction sites has become one of the urgent needs of current construction management. The installation of infrared temperature sensors on the helmets required to be worn by construction personnel to track and monitor their body temperature has become a relatively inexpensive and reliable means of epidemic prevention and control, but the accuracy of measuring body temperature has always been a problem. This study developed a smart helmet equipped with an infrared temperature sensor and conducted a simulated construction experiment to collect data of temperature and its influencing factors in indoor and outdoor construction operation environments. Then, a Partial Least Square–Back Propagation Neural Network (PLS-BPNN) temperature error compensation model was established to correct the temperature measurement results of the smart helmet. The temperature compensation effects of different models were also compared, including PLS-BPNN with Least Square Regression (LSR), Partial Least Square Regression (PLSR), and single Back Propagation Neural Network (BPNN) models. The results showed that the PLS-BPNN model had higher accuracy and reliability, and the determination coefficient of the model was 0.99377. After using PLS-BPNN model for compensation, the relative average error of infrared body temperature was reduced by 2.745 °C and RMSE was reduced by 0.9849. The relative error range of infrared body temperature detection was only 0.005~0.143 °C. [ABSTRACT FROM AUTHOR]

Nervonic acid (24:1 n-9, NA) plays a crucial role in the development of white matter, and it occurs naturally in human milk. This study aims to quantify NA in human milk at different lactation stages and compare it with the NA measured in infant formulae. With this information, optimal nutritional interventions for infants, especially newborns, can be determined. In this study, an absolute detection method that uses experimentally derived standard curves and methyl tricosanoate as the internal standard was developed to quantitively analyze NA concentration. The method was applied to the analysis of 224 human milk samples, which were collected over a period of 3–30 days postpartum from eight healthy Chinese mothers. The results show that the NA concentration was highest in colostrum (0.76 ± 0.23 mg/g fat) and significantly decreased (p < 0.001) in mature milk (0.20 ± 0.03 mg/g fat). During the first 10 days of lactation, the change in NA concentration was the most pronounced, decreasing by about 65%. Next, the NA contents in 181 commercial infant formulae from the Chinese market were compared. The NA content in most formulae was <16% of that found in colostrum and less than that found in mature human milk (p < 0.05). No significant difference (p > 0.05) was observed among NA content in formulae with different fat sources. Special attention was given to the variety of n-9 fatty acids in human milk during lactation, and the results indicated that interindividual variation in NA content may be primarily due to endogenous factors, with less influence from the maternal diet. [ABSTRACT FROM AUTHOR]

A novel control strategy that is based on iterative calculation of structural parameters is proposed for grid-connected inverter in this paper. The proposed strategy has a good dynamic performance, which makes it particularly suitable for the application of PV grid-connected generation. First, a second-order discretization mathematical model of grid-connected inverter control is established in the dq frame. The corresponding relation between the control signal and the output current is deduced in formulas. Then, the values of structural parameters in the formulas can be obtained through iterative calculation, which can further reduce the amount of calculation. After several iteration cycles, the structural parameters are approximately equal to their actual values and the inverter can be controlled as an open-loop system with its dynamic performance optimized. At last, simulation and experiments are performed. The results show that the static performance of the proposed strategy is as good as that of the classical ones, but its dynamic performance is improved significantly. [ABSTRACT FROM AUTHOR]

Object detection is challenging in large-scale images captured by unmanned aerial vehicles (UAVs), especially when detecting small objects with significant scale variation. Most solutions employ the fusion of different scale features by building multi-scale feature pyramids to ensure that the detail and semantic information are abundant. Although feature fusion benefits object detection, it still requires the long-range dependencies information necessary for small objects with significant scale variation detection. We propose a simple yet effective scale enhancement pyramid network (SEPNet) to address these problems. A SEPNet consists of a context enhancement module (CEM) and feature alignment module (FAM). Technically, the CEM combines multi-scale atrous convolution and multi-branch grouped convolution to model global relationships. Additionally, it enhances object feature representation, preventing features with lost spatial information from flowing into the feature pyramid network (FPN). The FAM adaptively learns offsets of pixels to preserve feature consistency. The FAM aims to adjust the location of sampling points in the convolutional kernel, effectively alleviating information conflict caused by the fusion of adjacent features. Results indicate that the SEPNet achieves an AP score of 18.9% on VisDrone, which is 7.1% higher than the AP score of state-of-the-art detectors RetinaNet achieves an AP score of 81.5% on PASCAL VOC.

Commonly used tests based on wild-type viruses, such as immunostaining, cannot meet the demands for rapid detection of viral replication, high-throughput screening for antivirals, as well as for tracking viral proteins or virus transport in real time. Notably, the development of replicating-competent reporter-expressing viruses (RCREVs) has provided an excellent option to detect directly viral replication without the use of secondary labeling, which represents a significant advance in virology. This article reviews the applications of RCREVs in diagnostic and molecular virology, including rapid neutralization tests, high-throughput screening systems, identification of viral receptors and virus-host interactions, dynamics of viral infections in vitro and in vivo, vaccination approaches and others. However, there remain various challenges associated with RCREVs, including pathogenicity alterations due to the insertion of a reporter gene, instability or loss of the reporter gene expression, or attenuation of reporter signals in vivo. Despite all these limitations, RCREVs have become powerful tools for both basic and applied virology with the development of new technologies for generating RCREVs, the inventions of novel reporters and the better understanding of regulation of viral replication.