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The petal blight disease of alpine Rhododendron severely impacts the ornamental and economic values of Rhododendron. Plant secondary metabolites play a crucial role in resisting pathogenic fungi, yet research on metabolites in alpine Rhododendron petals that confer resistance to pathogenic fungi is limited. In the present study, the secondary metabolites in Rhododendron delavayi, R. agastum, and R. irroratum petals with anti-pathogenic activity were screened through disease index analysis, metabolomic detection, the mycelial growth rate, and metabolite spraying experiments. Disease index analysis revealed that R. delavayi petals exhibited the strongest disease resistance, while R. agastum showed the weakest, both under natural and experimental conditions. UHPLC-QTOF-MS/MS analysis identified 355 and 274 putative metabolites in positive and negative ion modes, respectively. The further antifungal analysis of differentially accumulated baicalein, diosmetin, and naringenin showed their half-inhibitory concentrations (IC50) against Neopestalotiopsis clavispora to be 5000 mg/L, 5000 mg/L, and 1000 mg/L, respectively. Spraying exogenous baicalein, diosmetin, and naringenin significantly alleviated petal blight disease caused by N. clavispora infection in alpine Rhododendron petals, with the inhibition rates exceeding 64%. This study suggests that the screened baicalein, diosmetin, and naringenin, particularly naringenin, can be recommended as inhibitory agents for preventing and controlling petal blight disease in alpine Rhododendron. [ABSTRACT FROM AUTHOR]

Newborn lambs are susceptible to pathogenic bacterial infections leading to enteritis, which affects their growth and development and causes losses in sheep production. It has been reported that N6-methyladenosine (m6A) is closely related to innate immunity, but the effect of m6A on sheep small intestinal epithelial cells (IECs) and the mechanism involved have not been elucidated. Here, we investigated the effects of m6A on lipopolysaccharide (LPS)-induced inflammatory responses, apoptosis and oxidative stress in primary sheep IECs. First, the extracted IECs were identified by immunofluorescence using the epithelial cell signature protein cytokeratin 18 (CK18), and the cellular activity of IECs induced by different concentrations of LPS was determined by the CCK8 assay. Meanwhile, LPS could induce the upregulation of mRNA and protein levels of IECs cytokines IL1β, IL6 and TNFα and the apoptosis marker genes caspase-3, caspase-9, Bax, and apoptosis rate, reactive oxygen species (ROS) levels and mRNA levels of CAT, Mn-SOD and CuZn-SOD, and METTL3 were found to be upregulated during induction. It was hypothesized that METTL3 may have a potential effect on the induction of IECs by LPS. Overexpression and knockdown of METTL3 in IECs revealed that a low-level expression of METTL3 could reduce the inflammatory response, apoptosis and ROS levels in LPS-induced IECs to some extent. The results suggest that METTL3 may be a genetic marker for potential resistance to cellular damage. [ABSTRACT FROM AUTHOR]

Simple Summary: Glyoxalase domain-containing protein 4 (GLOD4), a member of the glyoxalase gene family, is widely expressed in Leydig cells and its primary function within the Leydig cells remains unknown. GLOD4 expression in other species is often associated with functions such as cell proliferation, cell cycle, and detoxification. We therefore explored the relevant elements of Leydig cells. We speculate that GLOD4 may regulate testicular development and spermatogenesis by increasing the number of Leydig cells and regulation of testosterone secretion. The expression pattern of GLOD4 in the testis and its regulatory effect on testicular cells was explored in goats to enhance our understanding of spermatogenesis and improve reproduction in breeding rams. In this study, we demonstrated the localization of GLOD4 in testicular cells using immunohistochemistry and subcellular localization analyses. Subsequently, we analyzed the GLOD4 expression pattern in four age-based groups (0, 6, 12, and 18 months old) using real-time quantitative polymerase chain reaction (qRT-PCR) and protein blotting. Finally, we performed GLOD4 silencing and overexpression studies in Leydig cells (LCs) and explored the effects on cell proliferation, the cell cycle, steroid hormone secretion and the expression of candidate testosterone hormone-regulated genes. GLOD4 was mainly expressed in Leydig cells, and the subcellular localization results showed that the GLOD4 protein was mainly localized in the cytoplasm and nucleus. Silencing of GLOD4 significantly suppressed the mRNA expression levels of the testosterone secretion-related genes CYP11A1, 3β-HSD, and CYP17A1 and the mRNA expression levels of cell cycle-related genes CDK6, PCNA, and Cyclin E. Moreover, the cell cycle was blocked at the G2/M phase after GLOD4 silencing, which significantly suppressed testosterone secretion. In contrast, GLOD4 overexpression significantly increased the mRNA expression levels of the testosterone secretion-related genes CYP11A1, 3β-HSD, and CYP17A1 and increased the expression of the cell cycle-related genes CDK6, PCNA, and Cyclin E. Moreover, GLOD4 overexpression promoted the cell cycle from G0/G1 phases to enter the S phase and G2/M phases, promoted the secretion of testosterone. Taken together, our experimental results indicate that GLOD4 may affect the development of cells in Qianbei Ma goats of different ages by influencing the cell cycle, cell proliferation, and testosterone hormone synthesis. These findings enhance our understanding of the functions of GLOD4 in goats. [ABSTRACT FROM AUTHOR]

Simple Summary: In this study, we address the inefficiencies and animal welfare concerns associated with the traditional manual measurements of cattle dimensions by introducing a non-contact, automated measurement method. This method utilizes an improved keypoint detection model coupled with unilateral depth imaging technology. By improved the keypoint detection model, we have improved the model's capability of processing critical cattle features. Subsequently, cattle body keypoints identified through conditional filtering of the depth image are optimized. Finally, these keypoints are integrated with various algorithms to compute the body size parameters of the cattle. In tests conducted on 23 beef cattle, the mean relative errors for body height, lumbar height, body length, and chest girth were 1.28%, 3.02%, 6.47%, and 4.43%, respectively. This research is of great significance for enhancing animal welfare and contributes to the sustainable development of modern livestock farming. Traditional measurement methods often rely on manual operations, which are not only inefficient but also cause stress to cattle, affecting animal welfare. Currently, non-contact cattle dimension measurement usually involves the use of multi-view images combined with point cloud or 3D reconstruction technologies, which are costly and less flexible in actual farming environments. To address this, this study proposes an automated cattle dimension measurement method based on an improved keypoint detection model combined with unilateral depth imaging. Firstly, YOLOv8-Pose is selected as the keypoint detection model and SimSPPF replaces the original SPPF to optimize spatial pyramid pooling, reducing computational complexity. The CARAFE architecture, which enhances upsampling content-aware capabilities, is introduced at the neck. The improved YOLOv8-pose achieves a mAP of 94.4%, a 2% increase over the baseline model. Then, cattle keypoints are captured on RGB images and mapped to depth images, where keypoints are optimized using conditional filtering on the depth image. Finally, cattle dimension parameters are calculated using the cattle keypoints combined with Euclidean distance, the Moving Least Squares (MLS) method, Radial Basis Functions (RBFs), and Cubic B-Spline Interpolation (CB-SI). The average relative errors for the body height, lumbar height, body length, and chest girth of the 23 measured beef cattle were 1.28%, 3.02%, 6.47%, and 4.43%, respectively. The results show that the method proposed in this study has high accuracy and can provide a new approach to non-contact beef cattle dimension measurement. [ABSTRACT FROM AUTHOR]

This paper primarily studies the path planning problem for UAV formations guided by semantic map information. Our aim is to integrate prior information from semantic maps to provide initial information on task points for UAV formations, thereby planning formation paths that meet practical requirements. Firstly, a semantic segmentation network model based on multi-scale feature extraction and fusion is employed to obtain UAV aerial semantic maps containing environmental information. Secondly, based on the semantic maps, a three-point optimization model for the optimal UAV trajectory is established, and a general formula for calculating the heading angle is proposed to approximately decouple the triangular equation of the optimal trajectory. For large-scale formations and task points, an improved fuzzy clustering algorithm is proposed to classify task points that meet distance constraints by clusters, thereby reducing the computational scale of single samples without changing the sample size and improving the allocation efficiency of the UAV formation path planning model. Experimental data show that the UAV cluster path planning method using angle-optimized fuzzy clustering achieves an 8.6% improvement in total flight range compared to other algorithms and a 17.4% reduction in the number of large-angle turns. [ABSTRACT FROM AUTHOR]

Air pollution has recently gained much attention from the general population. Despite pollution control being an issue in both urban and rural regions, most of the available research has concentrated on urban districts. Hence, investigations into how urban–rural transition affects PM2.5 are warranted within the framework of urban–rural integration. Using the Yellow River Basin as a case study, this study employed the entropy method and Analytic Hierarchy Process (AHP) to uncover the extent of urban–rural transformation. It then used the spatial autocorrelation method to investigate the spatiotemporal features of PM2.5 and the spatial econometric model to investigate the mechanisms that influence the relationship between urban–rural transformation and PM2.5. The results are as follows: (1) The level of urban–rural transformation shows an obvious upward trend with time. The development has progressed from asymmetrical north-east and south-west elevations to a more balanced pattern of north-east, middle-east, and west-west elevations. (2) The PM2.5 concentration increased steadily, then fluctuated, and finally decreased. Notably, the general pattern has not changed much, and it is high in the east and low in the west. (3) Different subsystems of the urban–rural transformation have different impacts on air pollution at different stages. The influence of industrial transformation (IT) on PM2.5 showed an inverted "N-shaped" curve of negative–negative–changes, and the industrial structure played a leading role in the spatiotemporal evolution of PM2.5. An inverted "U-shaped" curve forms the left side of the impact of population transition (PT) on PM2.5. Land transformation (LT) has a "U-shaped" curve for its effect on PM2.5. This study provides a new perspective on the topic of PM2.5 and its connection to urban–rural integration, which is crucial to understanding the dynamics of this shift. To achieve the goal of high-quality development, this study supports regional initiatives to reduce PM2.5 emissions in the Yellow River Basin. Moreover, the results of this study can provide a reference for decision-makers in the world's densely populated areas that suffer from serious air pollution. [ABSTRACT FROM AUTHOR]

Salinity is a common abiotic stress that limits crop productivity. Although there is a wealth of evidence suggesting that miRNA and lncRNA play important roles in the response to salinity in rice seedlings and reproductive stages, the mechanism by which competing endogenous RNAs (ceRNAs) influence salt tolerance and yield in rice has been rarely reported. In this study, we conducted full whole-transcriptome sequencing of rice panicles during the reproductive period to clarify the role of ceRNAs in the salt stress response and yield. A total of 214 lncRNAs, 79 miRNAs, and 584 mRNAs were identified as differentially expressed RNAs under salt stress. Functional analysis indicates that they play important roles in GO terms such as response to stress, biosynthesis processes, abiotic stimuli, endogenous stimulus, and response to stimulus, as well as in KEGG pathways such as secondary metabolite biosynthesis, carotenoid biosynthesis, metabolic pathways, and phenylpropanoid biosynthesis. A ceRNA network comprising 95 lncRNA–miRNA–mRNA triplets was constructed. Two lncRNAs, MSTRG.51634.2 and MSTRG.48576.1, were predicted to bind to osa-miR172d-5p to regulate the expression of OsMYB2 and OsMADS63, which have been reported to affect salt tolerance and yield, respectively. Three lncRNAs, MSTRG.30876.1, MSTRG.44567.1, and MSTRG.49308.1, may bind to osa-miR5487 to further regulate the expression of a stress protein (LOC_Os07g48460) and an aquaporin protein (LOC_Os02g51110) to regulate the salt stress response. This study is helpful for understanding the underlying molecular mechanisms of ceRNA that drive the response of rice to salt stress and provide new genetic resources for salt-resistant rice breeding. [ABSTRACT FROM AUTHOR]

Accurate evaluation of retinopathy of prematurity (ROP) severity is vital for screening and proper treatment. Current deep-learning-based automated AI systems for assessing ROP severity do not follow clinical guidelines and are opaque. The aim of this study is to develop an interpretable AI system by mimicking the clinical screening process to determine ROP severity level. A total of 6100 RetCam Ⅲ wide-field digital retinal images were collected from Guangdong Women and Children Hospital at Panyu (PY) and Zhongshan Ophthalmic Center (ZOC). A total of 3330 images of 520 pediatric patients from PY were annotated to train an object detection model to detect lesion type and location. A total of 2770 images of 81 pediatric patients from ZOC were annotated for stage, zone, and the presence of plus disease. Integrating stage, zone, and the presence of plus disease according to clinical guidelines yields ROP severity such that an interpretable AI system was developed to provide the stage from the lesion type, the zone from the lesion location, and the presence of plus disease from a plus disease classification model. The ROP severity was calculated accordingly and compared with the assessment of a human expert. Our method achieved an area under the curve (AUC) of 0.95 (95% confidence interval [CI] 0.90–0.98) in assessing the severity level of ROP. Compared with clinical doctors, our method achieved the highest F1 score value of 0.76 in assessing the severity level of ROP. In conclusion, we developed an interpretable AI system for assessing the severity level of ROP that shows significant potential for use in clinical practice for ROP severity level screening. [ABSTRACT FROM AUTHOR]

Arthropods play a crucial role in ecological processes and agricultural productivity. Soil physicochemical properties, indicators of soil health, are closely linked to arthropod communities. Gravel-sand mulching, commonly employed in arid farming, initially enhances water retention and temperature regulation but may contribute to land degradation with prolonged use. This study investigated how varying tillage durations affected soil properties and arthropod diversity under gravel-sand mulching. The analysis employed multiple comparison methods, covariance analysis (ANCOVA), non-metric multidimensional scaling (NMDS), and redundancy analysis (RDA). The results indicated that while soil fertility was better preserved in cultivated fields compared to in the desert grassland, arthropod diversity significantly decreased with longer cultivation periods. A total of 1099 arthropods from 79 species were sampled, by Barber trap. The highest diversity was observed in native grassland (NG), with 305 arthropods from 39 species, while tillage 21 years (GPS-21Y) exhibited the lowest diversity, with only 103 arthropods from 6 species. Dominant species included the carnivores Labidura japonica and Cataglyphis aenes. The analysis revealed low similarity in arthropod communities between GPS-21Y and other fields and high similarity in soil physicochemical properties between NG and the transition zone (STZ). RDA showed available potassium (APP) was negatively correlated with arthropod species diversity and concentration, total Nitrogen (TN) was positively correlated with arthropod species diversity but negatively correlated with species concentration, total phosphorus (TP) was negatively correlated with arthropod species diversity and concentration. This study provides insights into the relationship between maintaining soil fertility and supporting arthropod diversity in grassland agriculture. While soil fertility and arthropod diversity were correlated, continuous cropping practices negatively impacted arthropod diversity, offering valuable information for pest management and sustainable agricultural practices. [ABSTRACT FROM AUTHOR]

Accurately recognizing apples in complex environments is essential for automating apple picking operations, particularly under challenging natural conditions such as cloudy, snowy, foggy, and rainy weather, as well as low-light situations. To overcome the challenges of reduced apple target detection accuracy due to branch occlusion, apple overlap, and variations between near and far field scales, we propose the Rep-ViG-Apple algorithm, an advanced version of the YOLO model. The Rep-ViG-Apple algorithm features a sophisticated architecture designed to enhance apple detection performance in difficult conditions. To improve feature extraction for occluded and overlapped apple targets, we developed the inverted residual multi-scale structural reparameterized feature extraction block (RepIRD Block) within the backbone network. We also integrated the sparse graph attention mechanism (SVGA) to capture global feature information, concentrate attention on apples, and reduce interference from complex environmental features. Moreover, we designed a feature extraction network with a CNN-GCN architecture, termed Rep-Vision-GCN. This network combines the local multi-scale feature extraction capabilities of a convolutional neural network (CNN) with the global modeling strengths of a graph convolutional network (GCN), enhancing the extraction of apple features. The RepConvsBlock module, embedded in the neck network, forms the Rep-FPN-PAN feature fusion network, which improves the recognition of apple targets across various scales, both near and far. Furthermore, we implemented a channel pruning algorithm based on LAMP scores to balance computational efficiency with model accuracy. Experimental results demonstrate that the Rep-ViG-Apple algorithm achieves precision, recall, and average accuracy of 92.5%, 85.0%, and 93.3%, respectively, marking improvements of 1.5%, 1.5%, and 2.0% over YOLOv8n. Additionally, the Rep-ViG-Apple model benefits from a 22% reduction in size, enhancing its efficiency and suitability for deployment in resource-constrained environments while maintaining high accuracy. [ABSTRACT FROM AUTHOR]

To explore the yield-increasing mechanism of mechanized potato planting with corn straw mulching, a two-year (2021 and 2022) field experiment was conducted to study the effects of mechanized no-tillage with straw mulching on potato yield and water use efficiency. This experiment included mechanized no-tillage potato planting with corn straw mulch covering (JG), plastic film mulching (HM), and open flat planting (CK). The results showed that mechanical no-tillage with straw mulching significantly affected soil water content in the 0–100 cm soil layer, yield, and water use efficiency (p < 0.05). There was no significant difference in yield between JG and HM, but it was significantly higher than that of CK. The yield of JG was 3.09~12.27% higher than that of CK. The yield increase was mainly achieved by increasing the potato weight per plant (0.697~0.862 **) and the average single potato weight (0.048~0.631). The tuber weight per plant was positively correlated with the plant height at the seedling stage (0.03~0.92 **) and positively correlated with the dry weight of stems and leaves at the tuber expansion stage and starch accumulation stage (0.74 **~0.95 **). It was negatively correlated with the number of branches at the tuber formation stage (−0.33~−0.88 **). Compared with CK, JG could significantly improve the water use efficiency of potatoes and reduce water consumption during the whole growth period of crops. In 2021, JG was 6.5% higher than CK, and HM was 6.88% lower than CK. In 2022, JG and HM increased water use efficiency by 26.17% and 14.50% compared with CK. When HM is applied in heavy soil areas, soil compaction can easily occur, which affects seedling emergence and reduces yield. At the same time, JG has strong adaptability to soil types and good yield stability. It can be seen that JG is a green and efficient mechanized potato cultivation technology suitable for dry farming areas. [ABSTRACT FROM AUTHOR]

In IoT systems, the goal of multiview detection for multiple visual sensor networks is to use multiple camera perspectives to address occlusion challenges with multiview aggregation being a crucial component. In these applications, data from various interconnected cameras are combined to create a detailed ground plane feature. This feature is formed by projecting convolutional feature maps from multiple viewpoints and fusing them using uniform weighting. However, simply aggregating data from all cameras is not ideal due to different levels of occlusion depending on object positions and camera angles. To overcome this, we introduce QMVDet, a new query-based learning multiview detector, which incorporates an innovative camera-aware attention mechanism for aggregating multiview information. This mechanism selects the most reliable information from various camera views, thus minimizing the confusion caused by occlusions. Our method simultaneously utilizes both 2D and 3D data while maintaining 2D–3D multiview consistency to guide the multiview detection network's training. The proposed approach achieves state-of-the-art accuracy on two leading multiview detection benchmarks, highlighting its effectiveness for IoT-based multiview detection scenarios. [ABSTRACT FROM AUTHOR]

In this work, 1.5-level interconnections of RF microsystems with good RF performance, integration process compatibility, and high reliability are developed to meet the future demand for wireless communication microsystems in the millimeter wave band. Numerical models of 1.5-level interconnections based on solder balls with different diameters are established and analyzed using HFSS. The optimized structure parameters of 0.2 mm diameter Sn96.5Ag3Cu0.5 (SAC305) solder balls and 0.3 mm diameter Sn63Pb37 solder balls are selected for the interconnection between glass micro substrates and silicon micro substrates and between silicon micro substrates and HTCC substrates, respectively. Integration process parameters of the vertical interconnection are optimized. The micro substrate interconnection samples manufactured based on optimized integration methods and parameters show high reliability. [ABSTRACT FROM AUTHOR]

Wool is generated by hair follicles (HFs), which are crucial in defining the length, diameter, and morphology of wool fibers. However, the regulatory mechanism of HF growth and development remains largely unknown. Dermal papilla cells (DPCs) are a specialized cell type within HFs that play a crucial role in governing the growth and development of HFs. This study aims to investigate the proliferation and induction ability of ovine DPCs to enhance our understanding of the potential regulatory mechanisms underlying ovine HF growth and development. Previous research has demonstrated that microRNA-181a (miR-181a) was differentially expressed in skin tissues with different wool phenotypes, which indicated that miR-181a might play a crucial role in wool morphogenesis. In this study, we revealed that miR-181a inhibited the proliferation and induction ability of ovine DPCs by quantitative Real-time PCR (qRT-PCR), cell counting Kit-8 (CCK-8), 5-ethynyl-2′-deoxyuridine (EdU), flow cytometry, and alkaline phosphatase staining. Then, we also confirmed G protein subunit alpha i2 (GNAI2) is a target gene of miR-181a by dual luciferase reporter assay, qRT-PCR, and Western blot, and that it could promote the proliferation and induction ability of ovine DPCs. In addition, GNAI2 could also activate the Wnt/β-Catenin signaling pathway in ovine DPCs. This study showed that miR-181a can inhibit the proliferation and induction ability of ovine DPCs by targeting GNAI2 through the Wnt/β-Catenin signaling pathway. [ABSTRACT FROM AUTHOR]

To address the high complexity and low accuracy issues of traditional methods in mixed coal vitrinite identification, this paper proposes a method based on an improved DeepLabv3+ network. First, MobileNetV2 is used as the backbone network to reduce the number of parameters. Second, an atrous convolution layer with a dilation rate of 24 is added to the ASPP (atrous spatial pyramid pooling) module to further increase the receptive field. Meanwhile, a CBAM (convolutional block attention module) attention mechanism with a channel multiplier of 8 is introduced at the output part of the ASPP module to better filter out important semantic features. Then, a corrective convolution module is added to the network's output to ensure the consistency of each channel's output feature map for each type of vitrinite. Finally, images of 14 single vitrinite components are used as training samples for network training, and a validation set is used for identification testing. The results show that the improved DeepLabv3+ achieves 6.14% and 3.68% improvements in MIOU (mean intersection over union) and MPA (mean pixel accuracy), respectively, compared to the original DeepLabv3+; 12% and 5.3% improvements compared to U-Net; 9.26% and 4.73% improvements compared to PSPNet with ResNet as the backbone; 5.4% and 9.34% improvements compared to PSPNet with MobileNetV2 as the backbone; and 6.46% and 9.05% improvements compared to HRNet. Additionally, the improved ASPP module increases MIOU and MPA by 3.23% and 1.93%, respectively, compared to the original module. The CBAM attention mechanism with a channel multiplier of 8 improves MIOU and MPA by 1.97% and 1.72%, respectively, compared to the original channel multiplier of 16. The data indicate that the proposed identification method significantly improves recognition accuracy and can be effectively applied to mixed coal vitrinite identification. [ABSTRACT FROM AUTHOR]

A seeding machine for planting potatoes in double rows on large ridges in the cold and arid regions of northwest China was designed and built at Gansu Agricultural University. The machine is capable to achieve the integrated operations of ridge formation, mulching, hole punching, and the precise covering of holes on the film. The key components were analyzed and designed, and the link lengths of the crank film-piercing and hole-punching mechanism were refined using MATLAB R2022a software. The structures and working parameters of the film-piercing and hole-punching mechanism, the dual-opening punching and seeding mechanism, the ridge-forming and soil-covering mechanism, and the seed-casting device were designed. The dynamics of the ridge-forming and soil-covering were simulated using the discrete element method to capture the effects of different machine parameters on the soil covering operation. Field tests showed that the full soil-covering rate of film holes, the qualified rate of hole spacing, the hole misalignment rate, the degree of damage to the light-receiving surface of the film, and the qualified rate of sowing depth under the film were 94.8%, 87.6%, 4.3%, 33.4%, and 95.6%, respectively. These indicators met the requirements of industry standards, and the test results met the design and actual operation requirements, enabling the integrated operations of ridge formation, mulching, hole punching, sowing on the film, and the accurate soil covering of the holes. [ABSTRACT FROM AUTHOR]

The concept of major function-oriented zones is highly compatible with the idea of spatially synergistic carbon reduction. In this study, 2005–2020 is taken as the research period, and 305 counties in the Yangtze River Delta (YRD) region are taken as the research unit. The S0M-K-means clustering model and GeoDetector are adopted on the basis of carbon emission/absorption accounting to analyse the spatial and temporal variations in the carbon balance in the YRD region. Furthermore, carbon balance zoning and influencing factors are analysed. Then, a regional spatially synergistic carbon reduction pathway is proposed. The results show that carbon absorption in the YRD region struggles to offset carbon emissions; the regional carbon imbalance is gradually becoming worse; and each county's carbon emission/absorption shows a significant spatial imbalance. Optimised development zones and key development zones are high-value agglomerations of carbon emissions, while the main sources of carbon sinks in the YRD region are the key ecological functional zones. The YRD region has 87 high carbon control zones, 167 carbon emission optimisation zones, and 51 carbon sink functional zones, which are further subdivided into 9 types of carbon balance zones in accordance with the major function-oriented zones (MFOZs). Based on the driving factors of carbon balance changes in the YRD region, this study proposes differentiated spatially synergistic carbon reduction paths for each zone in accordance with the carbon balance zones. As the Yangtze River Delta is an essential engine for China's economic development, the study of its carbon balance is highly relevant in formulating differentiated low-carbon development pathways for each functional zone and promoting regional spatially synergistic carbon reduction to realise the target of "dual-carbon" development. [ABSTRACT FROM AUTHOR]

Aiming to address the A* algorithm's issues of traversing a large number of nodes, long search times, and large turning angles in path planning, a strategy for multiple improvements to the A* algorithm is proposed. Firstly, the calculation of the heuristic function is refined by utilizing the Octile distance instead of traditional distance, which more accurately predicts the optimal path length. Additionally, environmental constraints are introduced to adaptively adjust the weight of the heuristic function, balancing the trade-off between search speed and path length. Secondly, the bidirectional jump point search method is integrated, allowing simultaneous path searches from both directions. This significantly reduces path search times and the number of nodes traversed. Finally, the path undergoes two rounds of smoothing using a path smoothing strategy until the final path is generated. To validate the effectiveness of the improved A* algorithm, simulations are conducted on ten types of grid maps. Results demonstrate that the improved A* algorithm markedly decreases path search times while maintaining path length, with greater speed improvements observed as the map size increases. Furthermore, the improved algorithm is applied in experiments with mobile robots, achieving significant reductions in average path search times of 79.04% and 37.41% compared to the traditional A* algorithm and the JPS algorithm, respectively. This enhancement effectively meets the requirements for rapid path planning in mobile robotics applications. [ABSTRACT FROM AUTHOR]

Transmission electron microscopy was used to analyze individual aerosol particles collected in Lanzhou (urban site) and its surrounding areas (rural site) in early 2023. The results revealed that from the pre-Spring Festival period to the Spring Festival period, the main pollutants at the urban site decreased significantly, while the PM2.5 and SO2 concentrations increased at the rural site. During the entire sampling period, the main particles at the urban site were organic matter (OM), secondary inorganic aerosols (SIA), and OM-SIA particles, while those at the rural site were OM, SIA, and soot particles. The degree of external mixing of single particles in both sites increased from the pre-Spring Festival period to the Spring Festival period. The proportion of the OM particles increased by 11% at the urban site, and the proportion of SIA particles increased by 24% at the rural site. During the Spring Festival, the aging of the soot particles was enhanced at the urban site and weakened at the rural site. At the urban site, the SIA particle size was more strongly correlated with the thickness of the OM coating during the pre-Spring Festival period, while the correlation was stronger at the rural site during the Spring Festival. [ABSTRACT FROM AUTHOR]

This document is a summary of a special issue of the journal Processes titled "Process Monitoring and Fault Diagnosis." The issue explores the application of data analytic techniques to enhance stable operation and safety in chemical processes and related industries. The collection of research papers covers various topics, including process fault detection, bearing fault diagnosis, remaining useful life prediction, and more. The papers introduce cutting-edge methodologies and demonstrate their reliability through validation. The issue aims to foster communication and the development of advanced process monitoring techniques. [Extracted from the article]

This study concerned the in situ investigation of the defect evolution and fracture mechanism of additively manufactured (AM) Ti-6Al-4V under uniaxial tensile tests. In order to achieve this, microstructure characterization was initially carried out in order to identify the defects within the matrix of the candidate material. In situ testing was then performed, focusing on the spherical defect to observe its evolution under tensile loading. It was found that, before the fracture stage, the geometric evolution of the spherical defect towards an ellipse shape was dominated by the load in the tensile direction. In addition, the slip band density was found to be aggravated near the spherical defect due to the geometric discontinuity-induced stress concentration. During the fracture process, the defect geometry evolved as an irregular shape, which was mainly attributed to the micro-void-induced localized multi-axial stress state. The fracture analysis indicated that defects play a key role in crack initiation, leading to the fracture of LPBF materials. [ABSTRACT FROM AUTHOR]

Despite the advantages of using lightweight and non-corrosive carbon fiber reinforced polymer (CFRP) reinforcements in concrete structures, their widespread adoption has been limited due to concerns regarding the brittle failure of CFRP rupture and its relatively softer load-deflection stiffness. This work offers logical solutions to these two crucial problems: using aggregate coating to strengthen the CFRP-concrete bond and ultimately the load-deflection stiffness, and using CFRP-concrete debonding propagation to create pseudo-ductile behavior. Subsequently, the concrete cracking behavior, the apparent CFRP modulus with aggregates, and the post-peak capacity and deflection of three-dimensional (3D) CFRP-reinforced concrete are all described by equations derived from experiments. These formulas will be helpful in the future design of non-prismatic concrete components for low-impact building projects. The potential of this innovative design scheme in terms of increased capacity and deflections with less concrete material is demonstrated through comparisons between non-prismatic CFRP-reinforced concrete and measured steel reinforced equivalency. [ABSTRACT FROM AUTHOR]

Background: Thomas Cullen described bleeding abnormalities and dysmenorrhea as the "expected" presentations of adenomyomas. Adenomyosis is included within the FIGO classification of structural causes of abnormal uterine bleeding (AUB). Nevertheless, this long-standing association has been questioned by some authors who reported a high incidence of adenomyosis in uteri removed for indications other than AUB or dysmenorrhea. Here, we examine evidence for the link between adenomyosis and AUB. Methods: A comprehensive Medline literature review of all publications to October 2023. Results: Sixty-three articles were identified and included in the review. Despite a large body of studies, the available literature does not provide conclusive evidence of a link between adenomyosis and AUB. This is because of unsuitable study design, or poor characterization of the study population or of the inclusion or exclusion criteria. Additional challenges arise because of the lack of agreed criteria for diagnosing adenomyosis and the often absence of detailed assessment of menstrual blood loss. Adenomyosis often coexists with other conditions that have also been linked to similar symptoms, and many cases of adenomyosis are asymptomatic. Conclusion: Most of the existing literature and studies that addressed treatment outcome of adenomyosis started from the premise that a link between the condition and AUB had been proven. Yet, published information shows that aspects such a relationship is still uncertain. Further research is needed to address the relation between AUB and adenomyosis burden (or subtypes), distribution, and concomitant pathology. [ABSTRACT FROM AUTHOR]

High-sensitivity fluorescence monitoring has been widely used in agriculture and environmental science. However, the active fluorescence detection information of leaf segments mainly focuses on total chlorophyll, and the fluorescence information of chlorophyll a, chlorophyll b, and some other pigments has not been explored. This only considers the fluorescence spectrum characteristics at a single wavelength or the fluorescence integral from a range of wavelength regions and does not completely consider the linkage relation between the excitation, emission, and interference information. In this paper, the three-dimensional fluorescence spectrum, containing the excitation and emission fluorescence spectra, and the corresponding multiple pigment characteristics from the upgraded LOPEX_ZJU database were collected. The linkages of excitation and emission of the three-dimensional fluorescence spectra of these pigments were analyzed for the newly built multiple pigment 3-D fluorescence spectral indices (3-D FSIs), including those of chlorophyll a, chlorophyll b, carotenoid, anthocyanin, and flavonoid 3-D FSIs. Then, these pigment inversion models were established and validated. The results show that the 3-D FSIs performances for the photosynthetic pigment content inversion (including chlorophyll a and b, and carotenoids) were much better than those for the photo-protective pigments (including anthocyanins and flavonoids) from the 3-D fluorescence spectra of these plant leaves. Here, the 3-D fluorescence normalization index (FNI ((F430,690 − F430,763)/(F430,690 + F430,763))) for the chlorophyll a inversion model has a high accuracy, the RMSE is 2.96 μg/cm2, and the 3-D fluorescence reciprocal difference index (FRI (F650,704/F650,668) for the chlorophyll b model has an encouraging RMSE (2.01 μg/cm2). The RMSE of the 3-D fluorescence ratio index (FRI (F500,748/F500,717)) for the carotenoid inversion is 3.77 μg/cm2 RMSE. Only FRI (F370,615/F370,438) was selected for the modeling and validating evaluation of the leaf Flas content inversion, but the evaluation metrics were not good, with an RMSE (151.13 μg/cm2). For Ants, although there was a 3-D FSI (FRDI (1/F540,679 − 1/F540,557)), and its evaluation metrics, with an RMSE (2.8 μg/cm2), were at or over 0.05 level, the validating evaluation metric VC (98.3577%) was not encouraging. These results showed that fluorescence, as a nondestructive and efficient detection method, could determine the contents of chlorophyll a, chlorophyll b, and carotenoid in plant leaves, providing a new method to detect plant information. It can also provide a potential chance for the fluorescence images of fine photo-protective pigments, especially chlorophyll a and b, using the special active fluorescence excitation light source and a few fluorescence imaging channels from the optimal FSIs. [ABSTRACT FROM AUTHOR]

Despite the significant impacts of biomass burning (BB) on global climate change and regional air pollution, there is a relative lack of research on the temporal trends and geographic patterns of BB in Northeast China (NEC). This study investigates the spatial–temporal distribution of BB and its impact on the atmospheric environment in the NEC region during 2004 to 2023 based on remote sensing satellite data and reanalyzed data, using the Siegel's Repeated Median Estimator and Mann–Kendall test for trend analysis, HDBSCAN to identify significant BB change regions, and Moran's Index to examine the spatial autocorrelation of BB. The obtained results indicate a fluctuating yet overall increasing BB trend, characterized by annual increases of 759 for fire point counts (FPC) and 12,000 MW for fire radiated power (FRP). BB predominantly occurs in the Songnen Plain (SNP), Sanjiang Plain (SJP), Liaohe Plain (LHP), and the transitional area between SNP and the adjacent Greater Khingan Mountains (GKM) and Lesser Khingan Mountains (LKM). Cropland and urban areas exhibit the highest growth in BB trends, each surpassing 60% (p < 0.05), with the most significant growth cluster spanning 68,634.9 km2. Seasonal analysis shows that BB peaks in spring and autumn, with spring experiencing the highest severity. The most critical periods for BB are March–April and October–November, during which FPC and FRP contribute to over 80% of the annual total. This trend correlates with spring planting and autumn harvesting, where cropland FPC constitutes 71% of all land-cover types involved in BB. Comparative analysis of the aerosol extinction coefficient (AEC) between areas with increasing and decreasing BB indicates higher AEC in BB increasing regions, especially in spring, with the vertical transport of BB reaching up to 1.5 km. County-level spatial autocorrelation analysis indicates high–high clustering in the SNP and SJP, with a notable resurgence of autocorrelation in the SNP, suggesting the need for coordinated provincial prevention and control efforts. Finally, our analysis of the impact of BB on atmospheric pollutants shows that there is a correlation between FRP and pollutants, with correlations for PM2.5, PM10, and CO of 0.4, 0.4, and 0.5, respectively. In addition, the impacts of BB vary by region and season, with the most significant impacts occurring in the spring, especially in the SNP, which requires more attention. In summary, considering the escalating BB trend in NEC and its significant effect on air quality, this study highlights the urgent necessity for improved monitoring and strategic interventions. [ABSTRACT FROM AUTHOR]

This study reports new types of passive mode-locked Er-doped fiber laser (EDFL) based on a segment of doped fiber saturable absorber (DFSA) with Tm/Ho-doped fiber (THDF), Yb-doped fiber (YDF), and Er-doped fiber (EDF). By employing THDF-SA, a bright pulse sequence with a fundamental repetition rate of 17.86 MHz was obtained. In addition, various mode-locked output states, including dark pulses, dark–bright pulse pairs, bright–dark pulse pairs, and second-harmonic pulses, were obtained through polarization modulation and gain modulation, and the orthogonality of dark–bright pulses in both polarization directions was verified. Furthermore, using EDF-SA and YDF-SA, dark pulses and dark–bright pulses were obtained. A comparison of the three experiments revealed that THDF-SA effectively reduces the mode-locked threshold and improves the average output power. Compared with bright pulses, dark pulses offer several advantages such as resisting noise, increasing propagation speed, and suppressing nonlinear scattering (such as pulse-intrinsic Raman scattering); thus, the EDFL can find broad application in long-distance transmission, precision measurement, and other fields. [ABSTRACT FROM AUTHOR]

This study aims to improve the accuracy of predicting the severity of traffic accidents by developing an innovative traffic accident risk prediction model—StackTrafficRiskPrediction. The model combines multidimensional data analysis including environmental factors, human factors, roadway characteristics, and accident-related meta-features. In the model comparison, the StackTrafficRiskPrediction model achieves an accuracy of 0.9613, 0.9069, and 0.7508 in predicting fatal, serious, and minor accidents, respectively, which significantly outperforms the traditional logistic regression model. In the experimental part, we analyzed the severity of traffic accidents under different age groups of drivers, driving experience, road conditions, light and weather conditions. The results showed that drivers between 31 and 50 years of age with 2 to 5 years of driving experience were more likely to be involved in serious crashes. In addition, it was found that drivers tend to adopt a more cautious driving style in poor road and weather conditions, which increases the margin of safety. In terms of model evaluation, the StackTrafficRiskPrediction model performs best in terms of accuracy, recall, and ROC–AUC values, but performs poorly in predicting small-sample categories. Our study also revealed limitations of the current methodology, such as the sample imbalance problem and the limitations of environmental and human factors in the study. Future research can overcome these limitations by collecting more diverse data, exploring a wider range of influencing factors, and applying more advanced data analysis techniques. [ABSTRACT FROM AUTHOR]

In recent years, all-inorganic perovskite solar cells have become a research hotspot in the field of photovoltaics due to their excellent stability and optoelectronic performance, and the power conversion efficiency has increased from the initial 2.9% to over 20%. This article briefly introduces the development of cesium lead-based all-inorganic perovskite solar cells (CsPbX3-IPSC), including the characteristics of CsPbX3 perovskite materials, the preparation methods, and the structure and working principle of IPSCs. Different optimization strategies for preparing high optoelectronic performance and high-stability IPSCs, such as element doping and interface modification, are discussed. The development and application prospects of IPSCs are also summarized. [ABSTRACT FROM AUTHOR]

The new technique of filming in autumn and planting directly through the plastic film in spring is an effective method for water-saving and drought-resistant commercial potato production. However, there are currently no supporting film-drilling seeders available. To address this, a new potato seeder machine has been specifically designed for planting potatoes in the dryland, hilly, and mountainous areas of northwest China. This machine can perform top mulching and hole planting in both the autumn and spring seasons. This innovative potato seeder accomplishes several tasks simultaneously: seeding, inoculation (if desired), hole punching through the mulch film, seed placement, and soil covering. The machine features an optimized spoon-chain seeder with an eccentric coupling mechanism that ensures the hole-punching device stays perpendicular to the ground throughout planting, minimizing damage to the mulch film. Additionally, a dedicated seeding valve opening and closing mechanism was designed to extend the opening time of the hole-forming device's movable mouth beyond the potato's falling time, guaranteeing successful seed placement. Furthermore, a soil-covering device specifically designed for use with mulch film ensures proper soil retention after seeding. Through computer-aided design (RecurDyn V9R5 software) analysis, the hole-punching device's penetrating angle was optimized to minimize the tearing of the mulch film during entry into and exit from the soil. Rigorous field testing demonstrated the machine's effectiveness. The seeder achieved a 92% success rate for proper planting depth, an 88% success rate for accurate seed potato spacing, a 98% success rate for avoiding overplanting, and a 99% success rate for eliminating missed planting spots. These field test results meet or exceed national and industry standards, validating the machine's design goals. In essence, this innovative potato seeder, with its eccentric coupling mechanism, offers a one-pass solution for potato seeding, inoculation (optional), planting, and soil covering, significantly improving efficiency. [ABSTRACT FROM AUTHOR]

Wear can occur in flat die pelletizers, often reducing service life. This study explores the issue of die hole wear in the pelletizing process of a standard Total Mixed Ration (TMR) feed. The selected TMR formulation comprises varying proportions of corn, alfalfa hay, and quinoa. A coupled DEM-FEM analysis was used to examine stress–strain conditions in various die hole regions at different material ratios, predict the fatigue life of flat die materials in the pelletizing process, and validate the accuracy of investigating flat die wear through friction wear tests. It was found that the entrance of the die hole experiences the most severe conditions in terms of equivalent stress and elastic strain. The fatigue life is shortest at the entrance, with a maximum equivalent stress of 42.8 MPa, a maximum equivalent elastic strain of 2.5 × 10−3, and a minimum fatigue life stress cycle of 5.0 × 105. In contrast, the equivalent stress and equivalent elastic strain at the middle and upper parts of the die hole are minimal, with an equivalent stress of 4.8 MPa and a minimum equivalent elastic strain of 2.8 × 10−4. Material wear tests revealed that the most severe wear on the flat die specimen occurred when the ratio of corn, alfalfa hay, and quinoa straw was 7:2:1, consistent with the findings from the DEM-FEM coupling method. The pelleting process, arising from the contact between the material and metal, encompasses adhesive wear, abrasive wear, and fatigue wear. [ABSTRACT FROM AUTHOR]

Genome selection (GS) technology is an important means to improve the genetic improvement of dairy cows, and the mining and application of functional genes and loci for important traits is one of the important bases for accelerating genetic improvement. Our previous study found that the apolipoprotein A5 (APOA5) and AKT serine/threonine kinase 3 (AKT3) genes were differentially expressed in the liver tissue of Chinese Holstein cows at different lactation stages and influenced milk component synthesis and metabolism, so we considered these two genes as the candidates affecting milk production traits. In this study, we found in total six single nucleotide polymorphisms (SNPs), three in APOA5 and three in AKT3. Subsequent association analysis showed that the six SNPs were significantly associated with milk yield, fat yield, protein yield, or fat percentage (p ≤ 0.05). Three SNPs in APOA5 formed a haplotype block, which was found to be significantly associated with milk yield, fat yield, and protein yield (p ≤ 0.05). In addition, four SNPs were proposed to be functional mutations affecting the milk production phenotype, of which three, 15:g.27446527C>T and 15:g.27447741A>G in APOA5 and 16:g.33367767T>C in AKT3, might change the transcription factor binding sites (TFBSs), and one is a missense mutation, 15:g.27445825T>C in APOA5, which could alter the secondary structure and stability of mRNA and protein. In summary, we demonstrated the genetic effects of APOA5 and AKT3 on milk production traits, and the valuable SNPs could be used as available genetic markers for dairy cattle's GS. [ABSTRACT FROM AUTHOR]

This paper presents the design of an integrated potato-planting machine capable of full-film covering, creating micro-ditches on ridges, and covering seed rows with soil. The machine addresses the challenges of traditional methods, allowing for mechanized planting with complete film coverage and individual seed row soil covering. The key components of the prototype were analyzed and designed. This includes the seeding system, the pointed wing-shaped trencher for creating micro-ditches, and the straddling film-mulching device. Additionally, the operating mechanism of these core components was analyzed. Field trials demonstrated an 85% success rate for seed depth placement under the film. The machine also achieved a 90% qualified index for seed potato spacing, with a 6% repetitive seeding rate and a 3% missed seeding rate. Furthermore, the qualified rate for covered soil width on seed rows was 94%, and the qualified rate for covered soil thickness was 93%. The adjacent row spacing achieved an 88% success rate. The degree of mechanical damage to the exposed surface of the mulch film was minimal, at only 30.2 mm2/m2. These results meet all the national and industry standards. The successful field trials confirm the effectiveness of the machine in performing integrated fertilization, sowing, ridging, full-film covering, and seed row soil covering. Compared to traditional methods, this machine significantly reduces labor intensity for farmers and enhances the economic value of potato planting. [ABSTRACT FROM AUTHOR]

Simple Summary: Dermal papilla cells (DPCs) play a key role in the growth and development of hair follicles, and their number can regulate the shape and size of hair. Previous studies found that the BMP7 gene is differentially expressed in Hu sheep lamb skin of different pattern types and plays a key role in the proliferation of Hu sheep DPCs. However, the molecular mechanism of the differential expression of the BMP7 gene remains unclear. Here, we aim to investigate the cause of the BMP7 gene differentially expressed in Hu sheep lamb skin of different pattern types. Our findings demonstrate that DNA methylation modification can affect the expression of the BMP7 gene and can regulate the proliferation and cell cycle of Hu sheep DPCs. Previous studies have shown that the BMP7 gene is differentially expressed in Hu sheep lamb skin of different pattern types, and its expression level is significantly correlated with hair follicle indices of different pattern types, but the molecular mechanism of the differential expression of the BMP7 gene remains unclear. This study investigated the effect of DNA methylation on the transcriptional expression of BMP7. Firstly, we found that the mRNA expression of the BMP7 gene and the activity of the core promoter of the BMP7 gene were upregulated after 5-Aza-Deoxycytidine-induced demethylation treatment using qRT-PCR and double luciferase reporter assay. Then, we found that the proliferation of Hu sheep DPCs in vitro was promoted after 5-Aza-Deoxycytidine-induced demethylation treatment through qRT-PCR, CCK-8, and EdU assay, and that the overexpression of DNMT1 in DPCs induced the opposite effect. In addition, the results of the cell cycle assay reveal that the percentage of cells in the S phase was increased after 5-Aza-Deoxycytidine-induced demethylation treatment, and that the percentage of cells in the S phase was decreased after overexpression of DNMT1 in DPCs. This study indicated that the differential expression of the BMP7 gene in different patterns of Hu sheep lamb skin may be regulated by DNA methylation modification. In addition, DNA methylation can regulate the proliferation and cell cycle of DPCs in Hu sheep. [ABSTRACT FROM AUTHOR]

There is still a lack of high-precision and large-scale soil ammonium nitrogen (NH4+-N), nitrate nitrogen (NO3−-N) and available phosphorus (AP) in alpine grasslands at least on the Qinghai–Xizang Plateau, which may limit our understanding of the sustainability of alpine grassland ecosystems (e.g., changes in soil NH4+-N, NO3−-N and AP can affect the sustainability of grassland productivity, which in turn may alter the sustainability of livestock development), given that nitrogen and phosphorus are important limiting factors in alpine regions. The construction of big data mining models is the key to solving the problem mentioned above. Therefore, observed soil NH4+-N, NO3−-N and AP at 0–10 cm and 10–20 cm, climate data (air temperature, precipitation and radiation) and/or normalized vegetation index (NDVI) data were used to model NH4+-N, NO3−-N and AP in alpine grasslands of Xizang under fencing and grazing conditions. Nine algorithms, including random forest algorithm (RFA), generalized boosted regression algorithm (GBRA), multiple linear regression algorithm (MLRA), support vector machine algorithm (SVMA), recursive regression tree algorithm (RRTA), artificial neural network algorithm (ANNA), generalized linear regression algorithm (GLMA), conditional inference tree algorithm (CITA), and eXtreme gradient boosting algorithm (eXGBA), were used. The RFA had the best performance among the nine algorithms. Climate data based on the RFA can explain 78–92% variation of NH4+-N, NO3−-N and AP under fencing conditions. Climate data and NDVI together can explain 83–93% variation of NH4+-N, NO3−-N and AP under grazing conditions based on the RFA. The absolute values of relative bias, linear slopes, R2 and RMSE values between simulated soil NH4+-N, NO3−-N and AP based on RFA were ≤8.65%, ≥0.90, ≥0.91 and ≤3.37 mg kg−1, respectively. Therefore, random forest algorithm can be used to model soil available nitrogen and phosphorus based on observed climate data and/or normalized difference vegetation index in Xizang's grasslands. The random forest models constructed in this study can be used to obtain a long-term (e.g., 2000–2020) raster dataset of soil available nitrogen and phosphorus in alpine grasslands on the whole Qinghai–Tibet Plateau. The raster dataset can explain changes in grassland productivity from the perspective of nitrogen and phosphorus constraints across the Tibetan grasslands, which can provide an important basis for the sustainable development of grassland ecosystem itself and animal husbandry on the Tibetan Plateau. [ABSTRACT FROM AUTHOR]

Sulforaphane (SFN) is a natural isothiocyanate derived from cruciferous vegetables such as broccoli, Brussels sprouts, and cabbage. SFN plays a crucial role in maintaining redox homeostasis by interacting with the active cysteine residues of Keap1, leading to the dissociation and activation of NRF2 in various diseases. In this study, our objective was to investigate the impact of SFN on oxidative stress and pyroptosis in Mycobacterium tuberculosis (Mtb)-infected macrophages. Our findings demonstrated that Mtb infection significantly increased the production of iNOS and ROS, indicating the induction of oxidative stress in macrophages. However, treatment with SFN effectively suppressed the expression of iNOS and COX-2 and reduced MDA and ROS levels, while enhancing GSH content as well as upregulating NRF2, HO-1, and NQO-1 expression in Mtb-infected RAW264.7 macrophages and primary peritoneal macrophages from WT mice. These results suggest that SFN mitigates oxidative stress by activating the NRF2 signaling pathway in Mtb-infected macrophages. Furthermore, excessive ROS production activates the NLRP3 signaling pathway, thereby promoting pyroptosis onset. Further investigations revealed that SFN effectively suppressed the expression of NLRP3, Caspase-1, and GSDMD, IL-1β, and IL-18 levels, as well as the production of LDH, suggesting that it may exhibit anti-pyroptotic effects through activation of the NRF2 signaling pathway and reductions in ROS production during Mtb infection. Moreover, we observed that SFN also inhibited the expression of NLRP3, ASC, Caspase1, and IL-1β along with LDH production in Mtb-infected primary peritoneal macrophages from NFR2−/− mice. This indicates that SFN can directly suppress NLRP3 activation and possibly inhibit pyroptosis initiation in an NRF2-independent manner. In summary, our findings demonstrate that SFN exerts its inhibitory effects on oxidative stress by activating the NRF2 signaling pathway in Mtb-infected macrophages, while it may simultaneously exert anti-pyroptotic properties through both NRF2-dependent and independent mechanisms targeting the NLRP3 signaling pathway. [ABSTRACT FROM AUTHOR]

The complex process of aging leads to a gradual deterioration in the function of cells, tissues, and the entire organism, thereby increasing the risk of disease and death. Nicotinamide N-methyltransferase (NNMT) has attracted attention as a potential target for combating aging and its related pathologies. Studies have shown that NNMT activity increases over time, which is closely associated with the onset and progression of age-related diseases. NNMT uses S-adenosylmethionine (SAM) as a methyl donor to facilitate the methylation of nicotinamide (NAM), converting NAM into S-adenosyl-L-homocysteine (SAH) and methylnicotinamide (MNA). This enzymatic action depletes NAM, a precursor of nicotinamide adenine dinucleotide (NAD+), and generates SAH, a precursor of homocysteine (Hcy). The reduction in the NAD+ levels and the increase in the Hcy levels are considered important factors in the aging process and age-related diseases. The efficacy of RNA interference (RNAi) therapies and small-molecule inhibitors targeting NNMT demonstrates the potential of NNMT as a therapeutic target. Despite these advances, the exact mechanisms by which NNMT influences aging and age-related diseases remain unclear, and there is a lack of clinical trials involving NNMT inhibitors and RNAi drugs. Therefore, more in-depth research is needed to elucidate the precise functions of NNMT in aging and promote the development of targeted pharmaceutical interventions. This paper aims to explore the specific role of NNMT in aging, and to evaluate its potential as a therapeutic target. [ABSTRACT FROM AUTHOR]

Background: Chronic obstructive pulmonary disease (COPD) is characterized, at least in part, by autoimmunity through amplified T helper 1 and 17 (Th1 and Th17) immune responses. The loss of immune tolerance controlled by programmed death-ligand 1 (PD-L1) may contribute to this. Objectives: We studied the tolerogenic role of PD-L1+ dendritic cells (DCs) and their subtypes in relation to specific T cell immunity and the clinical phenotypes of COPD. Methods: We used flow cytometry to analyze PD-L1 expression by the DCs and their subtypes in the peripheral blood mononuclear cells (PBMCs) from normal participants and those with COPD. T cell proliferation and the signature cytokines of T cell subtypes stimulated with elastin as autoantigens were measured using flow cytometry and enzyme-linked immunosorbent assays (ELISA), respectively. Measurement and main results: A total of 83 participants were enrolled (normal, n = 29; COPD, n = 54). A reduced PD-L1+ conventional dendritic cell 1 (cDC1) ratio in the PBMCs of the patients with COPD was shown (13.7 ± 13.7%, p = 0.03). The decrease in the PD-L1+ cDC1 ratio was associated with a rapid decline in COPD (p = 0.02) and correlated with the CD4+ T cells (r = −0.33, p = 0.02). This is supported by the NCBI GEO database accession number GSE56766, the researchers of which found that the gene expressions of PD-L1 and CD4, but not CD8 were negatively correlated from PBMC in COPD patients (r = −0.43, p = 0.002). Functionally, the PD-L1 blockade enhanced CD4+ T cell proliferation stimulated by CD3/elastin (31.2 ± 22.3%, p = 0.04) and interleukin (IL)-17A production stimulated by both CD3 (156.3 ± 54.7, p = 0.03) and CD3/elastin (148 ± 64.9, p = 0.03) from the normal PBMCs. The PD-L1 blockade failed to increase IL-17A production in the cDC1-depleted PBMCs. By contrast, there was no significant change in interferon (IFN)-γ, IL-4, or IL-10 after the PD-L1 blockade. Again, these findings were supported by the NCBI GEO database accession number GSE56766, the researchers of which found that only the expression of RORC, a master transcription factor driving the Th17 cells, was significantly negatively correlated to PD-L1 (r = −0.33, p = 0.02). Conclusions: Circulating PD-L1+ cDC1 was reduced in the patients with COPD, and the tolerogenic role was suppressed with susceptibility to self-antigens and linked to rapid decline caused by Th17-skewed chronic inflammation. [ABSTRACT FROM AUTHOR]

Background: There has been considerable progress in our understanding of endometriosis, but its pathophysiology remains uncertain. Uncovering the underlying mechanism of the rare instances of endometriosis reported in early postmenarcheal years and in girls before menarche can have wide implications. Methods: We conducted a literature review of all relevant articles on Medline. Results: In the review, we explore the pathogenetic theories of premenarcheal endometriosis, the role of retrograde menstruation in the adult and its potential role in early-onset disease, as well as the factors that argue against the existence of a link between early-onset endometriosis (EOE) and neonatal uterine bleeding (NUB). Conclusions: As with endometriosis in adult women, the pathogenesis of early-onset disease remains unclear. A link between NUB and EOE is plausible, but there are considerable challenges to collating supporting evidence. The state of our understanding of early uterine development and of the pathophysiology of NUB leaves many unknowns that need exploration. These include proof of the existence of viable endometrial cells or endometrial mesenchymal stem cells in NUB, their passage to the pelvic cavity, their possible response to steroids, and whether they can reside within the pelvic cavity and remain dormant till menarche. [ABSTRACT FROM AUTHOR]

In this study, a neural network and a multi-objective genetic algorithm were used to optimize the geometric parameters of segmented thermoelectric generators (TEGs) with trapezoidal legs, including the cold end width of thermoelectric (TE) legs (Wc), the ratios of cold-segmented length to the total lengths of the n- and p-legs (Sn,c and Sp,c), and the width ratios of the TE legs between the hot end and the cold end of the n- and p-legs (Kn and Kp). First, a neural network with high prediction accuracy was trained based on 5000 sets of parameters and the corresponding output power values of the TEGs obtained from finite element simulations. Then, based on the trained neural network, the multi-objective genetic algorithm was applied to optimize the geometric parameters of the segmented TEGs with the objectives of maximizing the output power (P) and minimizing the semiconductor volume (V). The optimal geometric parameters for different semiconductor volumes were obtained, and their variations were analyzed. The results indicated that the optimal Sn,c, Sp,c, Kn, and Kp remained almost unchanged when V increased from 52.8 to 216.2 mm3 for different semiconductor volumes. This work provides practical guidance for the design of segmented TEGs with trapezoidal legs. [ABSTRACT FROM AUTHOR]

As one of the key components of an aeroengine, turbine blisk endures complex coupling loads under a harsh operational environment so that the reliability of turbine blisk directly influences the safe operation of aeroengine. It is urgent to precisely perform the reliability estimation of a complex blisk structure. To address this issue, an enhanced Moving Neural Network Framework (MNNF) is proposed by integrating compact support region theory, improve sooty tern optimization algorithm (ISTOA), and Bayesian regularization strategy into artificial neural network. The compact support region theory is applied to select the efficient samples for modeling from the training samples set, the ISTOA is to determine the optimal compact support region, and Bayesian regularization thought is utilized to improve the generalization ability of neural network model. The operational reliability assessment of aeroengine blisk is performed with the consideration of transient loads to verify the proposed MNNF method. It is shown that the reliability degree of turbine blisk stain is 0.9984 when the allowable value is 5.2862 × 10−3 m. In line with the comparison of methods, the developed MNNF approach has 0.99738 in root means square error, 3.1634 × 10−4 m in goodness of fit, 0.423 s in modeling time, 99.99% in simulation precision, and 0.496 s in simulation time under 10,000 simulations, which are superior to all other methods (i.e., 99.96%, 99.91%, 99.93%, 99.97%, and 99.97% in simulation precision and 16.27%, 4.82%, 30.07%, 39.87%, and 23.59% in simulation efficiency, for the response surface method (RSM), Kriging, support vector machine (SVM), back propagation-artificial neural network (BP-NN), and BP-NN based on particle swarm optimization (BP-PSO) methods, respectively). It is demonstrated that the MNNF method holds excellent modeling and simulation performances. The efforts of this study provide promising tools and insights into the reliability design of complex structures, and enrich and develop reliability theory. [ABSTRACT FROM AUTHOR]

Traditional methods for harvesting medicinal materials with long roots, like Astragalus membranaceus, require extensive soil excavation, leading to problems like inefficient soil separation, low stemming rates, and blockages in conveyor chains. To address these challenges, this study introduces a prototype machine capable of digging, separating soil, crushing soil, and collecting the medicinal materials in one continuous process. The paper focuses on the machine's design and working principle, with theoretical analysis and calculations for key components like the digging shovel, multi-stage conveyor, and soil-crushing device. Specific structural parameters were determined, and the screening efficiency of the roller screen was analyzed using EDEM 2020 software, comparing scenarios with and without rollers. A motion model for the medicinal materials during conveyance was established, allowing for the determination of optimal linear velocity and mounting angle for the conveyor. Additionally, a motion model for the second-stage conveyor chain and rear soil-crushing device was used to optimize their placement, ensuring efficient soil crushing without affecting the thrown Astragalus. Compared to traditional Chinese medicine diggers, this machine boasts superior resistance reduction and soil-crushing capabilities. Compared with traditional harvesters, the drag-reducing and soil-crushing device of this machine is more efficient, reducing the damage to Astragalus during the harvesting process, reducing the labor intensity of farmers, and improving the quality and efficiency of Astragalus harvesting. Field experiments have shown that when the operating speed of the prototype is 1.0 m/s and the roller-screen speed is 130~150 rpm, the operating performance is optimal, and comparative experiments can be conducted under the optimal parameters. From the experimental results, it can be seen that the improved equipment has increased the bright-stem rate by about 4%, the digging and loosening rate by 97.42%, and the damage rate by 2.44%. The equipment design meets the overall design requirements, and all experimental indicators meet national and industry standards. This provides a reference for the optimization and improvement of the soil-crushing device and the structure of the Astragalus membranaceus harvester. [ABSTRACT FROM AUTHOR]

Simple Summary: Sheep diarrhea is one of the most common illnesses in sheep farming and diarrhea in sheep caused by E. coli occupies a significant proportion of them. E. coli F17 is one of the main members of E. coli causing diarrhea in sheep. This study is devoted to improving the resistance of sheep itself to E. coli F17. This study provides theoretical support for the solution of E. coli F17-caused diarrhea in sheep. Diarrhea is the most common issue in sheep farms, typically due to pathogenic Escherichia coli (E. coli) infections, such as E. coli F17. microRNA, a primary type of non-coding RNA, has been shown to be involved in diarrhea caused by pathogenic E. coli. To elucidate the profound mechanisms of miRNA in E. coli F17 infections, methods such as E. coli F17 adhesion assay, colony counting assay, relative quantification of bacterial E. coli fimbriae gene expression, indirect immune fluorescence (IF), Cell Counting Kit-8 (CCK-8), 5-ethynyl-2′-deoxyuridine (EdU), Western blotting (WB), and scratch assay were conducted to investigate the effect of miR-329b-5p overexpression/knock-down on E. coli F17 susceptibility of sheep intestinal epithelial cells (IECs). The findings indicated that miR-329b-5p enhances the E. coli F17 resistance of sheep IECs to E.coli F17 by promoting adhesion between E. coli F17 and IEC, as well as IEC proliferation and migration. In summary, miR-329b-5p plays a crucial role in the defense of sheep IECs against E. coli F17 infection, providing valuable insights into its mechanism of action. [ABSTRACT FROM AUTHOR]

Flower color is an important ornamental feature that is often modulated by the contents of flavonoids. Chalcone synthase is the first key enzyme in the biosynthesis of flavonoids, but little is known about the role of R. delavayi CHS in flavonoid biosynthesis. In this paper, three CHS genes (RdCHS1-3) were successfully cloned from R. delavayi flowers. According to multiple sequence alignment and a phylogenetic analysis, only RdCHS1 contained all the highly conserved and important residues, which was classified into the cluster of bona fide CHSs. RdCHS1 was then subjected to further functional analysis. Real-time PCR analysis revealed that the transcripts of RdCHS1 were the highest in the leaves and lowest in the roots; this did not match the anthocyanin accumulation patterns during flower development. Biochemical characterization displayed that RdCHS1 could catalyze p-coumaroyl-CoA and malonyl-CoA molecules to produce naringenin chalcone. The physiological function of RdCHS1 was checked in Arabidopsis mutants and tobacco, and the results showed that RdCHS1 transgenes could recover the color phenotypes of the tt4 mutant and caused the tobacco flower color to change from pink to dark pink through modulating the expressions of endogenous structural and regulatory genes in the tobacco. All these results demonstrate that RdCHS1 fulfills the function of a bona fide CHS and contributes to flavonoid biosynthesis in R. delavayi. [ABSTRACT FROM AUTHOR]

In addressing the challenges associated with low convergence accuracy and unstable optimization results in the original gazelle optimization algorithm (GOA), this paper proposes a novel approach incorporating chaos mapping termed multi-strategy particle swarm optimization with gazelle optimization algorithm (MPSOGOA). In the population initialization stage, segmented mapping is integrated to generate a uniformly distributed high-quality population which enhances diversity, and global perturbation of the population is added to improve the convergence speed in the early iteration and the convergence accuracy in the late iteration. By combining particle swarm optimization (PSO) and GOA, the algorithm leverages individual experiences of gazelles, which improves convergence accuracy and stability. Tested on 35 benchmark functions, MPSOGOA demonstrates superior performance in convergence accuracy and stability through Friedman tests and Wilcoxon signed-rank tests, surpassing other metaheuristic algorithms. Applied to engineering optimization problems, including constrained implementations, MPSOGOA exhibits excellent optimization performance. [ABSTRACT FROM AUTHOR]

Integrated rice-fish farming has emerged as a novel agricultural production pattern to address global food security challenges. Aiming to determine the optimal, scientifically sound, and sustainable stocking density of red claw crayfish (Cherax quadricarinatus) in an integrated rice-crayfish farming system, we employed Illumina high-throughput 16S rRNA gene sequencing to evaluate the impact of different stocking densities of red claw crayfish on the composition, diversity, function, and co-occurrence network patterns of soil bacterial communities. The high stocking density of red claw crayfish reduced the diversity and evenness of the soil bacterial community during the mid-culture stage. Proteobacteria, Actinobacteria, and Chloroflexi emerged as the most prevalent phyla throughout the experimental period. Low stocking densities initially boosted the relative abundance of Actinobacteria in the paddy soil, while high densities did so during the middle and final stages. There were 90 distinct functional groups identified across all the paddy soil samples, with chemoheterotrophy and aerobic chemoheterotrophy being the most abundant. Low stocking densities initially favored these functional groups, whereas high densities enhanced their relative abundances in the later stages of cultivation. Medium stocking density of red claw crayfish led to a more complex bacterial community during the mid- and final culture stages. The experimental period showed significant correlations with soil bacterial communities, with total nitrogen (TN) and total phosphorus (TP) concentrations emerging as primary factors contributing to the alterations in soil bacterial communities. In summary, our findings demonstrated that integrated rice-crayfish farming significantly impacted the soil microbiomes and environmental factors at varying stocking densities. Our study contributed to theoretical insights into the profound impact of integrated rice-crayfish farming with various stocking densities on bacterial communities in paddy soils. [ABSTRACT FROM AUTHOR]

Integration of inverter-based distributed energy resources (DERs) is reshaping the landscape of distribution grids to fulfill the socioeconomic, environmental, and sustainability goals. Addressing the technological challenges of DER grid integration requires an adaptive communication layer for efficient DER management and control. This transition has given rise to a cyberphysical system (CPS) architecture within the distribution system, causing new vulnerabilities for cyberphysical attacks. To better address potential threats, this paper presents a comprehensive risk assessment framework for cyberphysical security in distribution grids with grid-edge DERs. The framework incorporates a detailed CPS model accounting for dynamic DER characteristics within the distribution grid. It identifies vulnerabilities in DER communication systems, models attack scenarios, and addresses communication latency crucial for inverter control timescales. Subsequently, the quantification of attack impacts employs an attack probability model including both the vulnerability and criticality of cyber components. The proposed risk assessment framework was validated through testing on the modified IEEE 13-node and 123-node test feeders. [ABSTRACT FROM AUTHOR]

In this study, the microstructural evolution of a Ti-15Mo medical alloy was investigated, when the in situ cyclic tensile strain had 2% amplitude and the tension–compression cyclic deformation had 1%, 2%, and 3% amplitude. The Vickers hardness and wear resistance of the alloy were also optimized due to the grain-refining effect after cyclic deformation and annealing. The twinning-induced plasticity (TWIP) was considered the main deformation mechanism of the Ti-15Mo alloy during the tensile–compressive cycle deformation with suitable strain amplitude. The {332}<113> twins and boundaries were the main contributors to the grain refinement. The optimal microstructure, hardness, and wear resistance were obtained in the alloy deformed by tension–compression cyclic strain with a 3% strain amplitude. The wear resistance of the annealed alloy in Hank's solution was excellent in contrast to the original Ti-15Mo alloy due to its reasonable microstructure and hardness. It is clear that abundant twins were formed and retained in the coarse grains of the original alloy after cyclic deformation and annealing, which provided the expected refined grains and performance. [ABSTRACT FROM AUTHOR]

Traditional data-driven soft sensor methods can be regarded as an optimization process to minimize the predicted error. When applying the mean squared error as the objective function, the model tends to be trained to minimize the global errors of overall data samples. However, there are deviations in data from practical operation, in which the model performance in the estimation of the local variations in the target parameter worsens. This work presents a solution to this challenge by considering higher-order moments of prediction residuals, which enables the evaluation of deviations of the residual distribution from the normal distribution. By embedding constraints on the distribution of residuals into the objective function, the model tends to converge to the state where both stationary and deviation data can be accurately predicted. Data from the Tennessee Eastman process and an industrial cracking furnace are considered to validate the performance of the proposed modeling method. [ABSTRACT FROM AUTHOR]

The Yulong copper deposit in Tibet is a typical porphyry copper deposit, with about 30 million tons of copper oxide ore in the surface layer. However, more than 40% of the copper resources are in a combination state, resulting in an extraction efficiency of only 50% for copper via the hydrometallurgical process. In this study, the process mineralogy of the combined copper oxide ore was systematically investigated and a calcium fluoride-enhanced leaching process is proposed to increase the leaching efficiency of the combined copper ore. The process mineralogy of the combined copper oxide ore was analyzed using various testing techniques, including chemical analysis, X-ray diffraction, and a process mineralogy parameter testing system (Mineral Liberation Analysis). The results revealed that limonite accounted for 86.12% of the sample, and 63.51% of the copper resource existed in the form of combined copper oxide in limonite. However, it is difficult for the uniformly distributed combined copper oxide in limonite to sufficiently make contact with sulfuric acid, which is the leaching agent, resulting in low copper leaching efficiency. The enhanced leaching behavior of the combined copper oxide ores was also investigated, thereby determining effective and economical enhanced leaching conditions. Under optimal conditions, at a grinding fineness ratio of −0.074 mm (accounting for 85%), liquid-solid ratio of 4:1, sulfuric acid concentration of 50 g/L, temperature of 30 °C, CaF2 dosage of 1% of the ore mass, and leaching time of 4 h, the copper leaching efficiency increased to 60.57%, which was 7.34% higher than that of atmospheric pressure leaching. Finally, the enhanced leaching slag was analyzed using an electron probe microanalyzer. It indicated that fluorine ions can erode the combined copper oxide ore and facilitate the diffusion of hydrogen ions inside the limonite, thereby achieving a strengthening effect. [ABSTRACT FROM AUTHOR]