Search

Active transportation and lifestyles are important components of a sustainable city. Greenways play a crucial role in providing conducive environments for jogging. To investigate the influence of micro-scale characteristics on perceived jogging supportiveness (PJS), 230 video clips of greenways within Fuzhou City were collected as samples. PJS was evaluated using a Likert scale, perceptual characteristics were assessed through a semantic difference scale, and physical characteristics were computed via semantic segmentation. By employing SHAP values and dependence plots within an XGBoost framework, the findings reveal the following: (1) Regarding perceptual characteristics, continuity, culture, and facility affordance exhibit the highest relative importance to PJS (|SHAP| ≥ 0.1). Continuity, naturalness, and vitality generally have positive impacts on PJS, while disturbance is negative. Facility affordance, scale, culture, openness, and brightness demonstrate more complex nonlinear influences that suggest optimal value ranges. (2) Concerning physical characteristics, fences, motor vehicles, and surface material are deemed most influential (|SHAP| ≥ 0.1). The presence of fences, walls, and construction generally negatively affect PJS, while excessive openness is also unfavorable. Comfortable road surfaces are associated with higher levels of PJS. Natural elements and the presence of people and vehicles have promoting effects up to certain thresholds, but beyond that point, they exert opposite influences. Finally, suggestions for designing greenways that encourage jogging are proposed. This study provides practical references for optimizing greenway design to promote active transportation and lifestyles, reinforcing the contribution of green infrastructure to public health in sustainable cities. [ABSTRACT FROM AUTHOR]

The aim of this study is to reveal the effects of multilevel visual characteristics of greenways on thermal perception in hot and humid regions during summer and to explore the potential of visual design to enhance psychological thermal comfort. Data on light (L), color (C), plant richness (PR), space openness (SO), scenic view (SV), thermal sensation (TS), and thermal preference (TP) were collected through questionnaires (n = 546). Computer vision technology was applied to measure the green view index (GVI), sky view index (SVI), paving index (PI), spatial enclosure (SE), and water index (WI). Using the hill climbing algorithm in R to construct a Bayesian network, model validation results indicated prediction accuracies of 0.799 for TS and 0.838 for TP. The results showed that: (1) SE, WI, and SV significantly positively influence TS, while L significantly negatively influences TS (R2 = 0.6805, p-value < 0.05); (2) WI, TS, and SV significantly positively influence TP (R2 = 0.759, p-value < 0.05). [ABSTRACT FROM AUTHOR]

Underwater sonar is the primary remote sensing and imaging modality within turbid environments with poor visibility. The two-dimensional (2-D) images of a target near the air–sea interface (or resting on a hard seabed), acquired by forward-scan sonar (FSS), are generally corrupted by the ghost and sometimes mirror components, formed by the multipath propagation of transmitted acoustic beams. In the processing of the 2-D FSS views to generate an accurate three-dimensional (3-D) object model, the corrupted regions have to be discarded. The sonar tilt angle and distance from the sea surface are two important parameters for the accurate localization of the ghost and mirror components. We propose a unified optimization technique for improving both the measurements of these two parameters from inexpensive sensors and the accuracy of a 3-D object model using 2-D FSS images at known poses. The solution is obtained by the recursive updating of sonar parameters and 3-D object model. Utilizing the 3-D object model, we can enhance the original images and generate synthetic views for arbitrary sonar poses. We demonstrate the performance of our method in experiments with the synthetic and real images of three targets: two dominantly convex coral rocks and a highly concave toy wood table. [ABSTRACT FROM AUTHOR]

In this study, indigo carmine (IC)-calcium carbonate lakes with different crystalline forms of calcium carbonate were prepared through co-precipitation methods, and the properties of these lakes and their formation mechanisms were investigated. The results showed that amorphous calcium carbonate (ACC) exhibited the smallest particle size and the largest specific surface area, resulting in the highest adsorption efficiency. Vaterite, calcite, and aragonite followed after ACC in decreasing order of adsorption efficiency. Kinetic analysis and isothermal analysis revealed the occurrence of chemisorption and multilayer adsorption during formation of the lakes. The FTIR and Raman spectra suggested participation of sulfonic acid groups in chemisorption. Appearance of IC significantly altered TGA curves by changing weight loss rate before decomposition of calcium carbonate. EDS analysis revealed the adsorption of IC predominantly happened on the surface of calcium carbonate particles rather than the interior. [ABSTRACT FROM AUTHOR]

This study aimed to elucidate responses of the bacterial structure and diversity of the rhizosphere in flowering broomcorn millet after rehydration following drought stress. In this study, the broomcorn millet varieties 'Hequ red millet' (A1) and 'Yanshu No.10′ (A2), known for their different drought tolerance levels, were selected as experimental materials. The plants were subjected to rehydration after drought stress at the flowering stage, while normal watering (A1CK and A2CK) served as the control. Soil samples were collected at 10 days (A11, A21, A1CK1, and A2CK1) and 20 days (A12, A22, A1CK2, and A2CK2) after rehydration. High-throughput sequencing technology was employed to investigate the variations in bacterial community structure, diversity, and metabolic functions in the rhizosphere of the broomcorn millet at different time points following rehydration. The findings indicated that the operational taxonomic units (OTUs) of bacteria in the rhizosphere of broomcorn millet were notably influenced by the duration of treatment, with a significant decrease in OTUs observed after 20 days of rehydration. However, bacterial Alpha diversity was not significantly impacted by rehydration following drought stress. The bacterial community in the rhizosphere of broomcorn millet was mainly composed of Actinobacteria and Proteobacteria. After rewatering for 10 to 20 days after drought stress, the abundance of Sphingomonas and Aeromicrobium in the rhizosphere soil of the two varieties of broomcorn millet decreased gradually. Compared with Yanshu No.10, the abundance of Pseudarthrobacter in the rhizosphere of Hequ red millet gradually increased. A Beta diversity analysis revealed variations in the dissimilarities of the bacterial community which corresponded to different rehydration durations. The relative abundance of bacterial metabolic functions in the rhizosphere of broomcorn millet was lower after 20 days of rehydration, compared to measurements after 10 days of rehydration. This observation might be attributed to the exchange of materials between broomcorn millet and microorganisms during the initial rehydration stage to repair the effects of drought, as well as to the enrichment of numerous microorganisms to sustain the stability of the community structure. This study helps to comprehend the alterations to the bacterial structure and diversity in the rhizosphere of broomcorn millet following drought stress and rehydration. It sheds light on the growth status of broomcorn millet and its rhizosphere microorganisms under real environmental influences, thereby enhancing research on the drought tolerance mechanisms of broomcorn millet. [ABSTRACT FROM AUTHOR]

In order to clarify the effect of different fertilizers on foxtail millet quality under low nitrogen conditions, we used JGNo.21 and LZGNo.2 as experimental materials and set up five treatments, including non-fertilization, nitrogen, phosphorus, compound, and organic fertilizers, to study the regulation of different fertilizer types on agronomic traits, nutrient fractions, and pasting characteristics of foxtail millet under low nitrogen conditions. Compared with the control, all of the fertilizers improved the agronomic traits of JGNo.21 to a certain extent. Nitrogen and compound fertilizer treatments reduced the starch content of JGNo.21; the starch content was reduced by 0.55% and 0.07% under nitrogen and compound fertilizers treatments. Phosphorus and organic fertilizers increased starch content, and starch content increased by 0.50% and 0.56% under phosphorus and organic fertilizer treatments. The effect of each fertilizer treatment on protein content was completely opposite to that of starch; different fertilizer treatments reduced the fat content of JGNo.21 and increased the fiber content. Among them, nitrogen and phosphorus fertilizers increased the yellow pigment content; the yellow pigment content increased by 1.21% and 2.64% under nitrogen and phosphorus fertilizer treatments. Organic and compound fertilizers reduced the content of yellow pigment; the yellow pigment content was reduced by 3.36% and 2.79% under organic and compound fertilizer treatments. Nitrogen and organic fertilizers increased the fat content of LZGNo.2; the fat content increased by 2.62% and 1.98% under nitrogen, organic fertilizer treatment. Compound and phosphorus fertilizer decreased the fat content; the fat content decreased by 2.16% and 2.90% under compound and phosphorus fertilizer treatment. Different fertilizer treatments reduced the cellulose and yellow pigment content of LZGNo.2. The content of essential, non-essential, and total amino acids of JGNo.21 was increased under compound and nitrogen fertilizer treatments and decreased under organic and phosphorus fertilizer treatments. The content of essential, non-essential, and total amino acids of LZGNo.2 was significantly higher under compound, nitrogen, and organic fertilizer treatments compared with control and significantly decreased under phosphorus fertilizer treatments. Nitrogen and compound fertilizer treatments significantly reduced the values of peak viscosity, trough viscosity, breakdown viscosity, final viscosity, setback viscosity, and pasting time of each index of JGNo.21; phosphorus and organic fertilizer treatments improved the values of each index. In contrast, the pasting viscosity of LZGNo.2 increased under phosphorus fertilizer treatment and decreased under nitrogen fertilizer treatment. Reasonable fertilization can improve the quality of foxtail millet, which provides a scientific theoretical basis for improving the quality of foxtail millet. [ABSTRACT FROM AUTHOR]

For mobile robots, the high-precision integrated calibration and structural robustness of multi-sensor systems are important prerequisites for ensuring healthy operations in the later stage. Currently, there is no well-established validation method for the calibration accuracy and structural robustness of multi-sensor systems, especially for dynamic traveling situations. This paper presents a novel validation method for the calibration accuracy and structural robustness of a multi-sensor mobile robot. The method employs a ground–object–air cooperation mechanism, termed the "ground surface simulation field (GSSF)—mobile robot -photoelectric transmitter station (PTS)". Firstly, a static high-precision GSSF is established with the true north datum as a unified reference. Secondly, a rotatable synchronous tracking system (PTS) is assembled to conduct real-time pose measurements for a mobile vehicle. The relationship between each sensor and the vehicle body is utilized to measure the dynamic pose of each sensor. Finally, the calibration accuracy and structural robustness of the sensors are dynamically evaluated. In this context, epipolar line alignment is employed to assess the accuracy of the evaluation of relative orientation calibration of binocular cameras. Point cloud projection and superposition are utilized to realize the evaluation of absolute calibration accuracy and structural robustness of individual sensors, including the navigation camera (Navcam), hazard avoidance camera (Hazcam), multispectral camera, time-of-flight depth camera (TOF), and light detection and ranging (LiDAR), with respect to the vehicle body. The experimental results demonstrate that the proposed method offers a reliable means of dynamic validation for the testing phase of a mobile robot. [ABSTRACT FROM AUTHOR]

A novel, highly efficient terahertz fully polarized transmission line is designed by two-dimensional tellurium photonic crystals consisting of square lattice rod arrays with a complete photonic bandgap. The TE and TM photonic bandgaps of the tellurium photonic crystals, which are computed by plane wave expansion, happen to coincide, and the complete photonic bandgap covers from 2.894 to 3.025 THz. The function of the designed waveguide is simulated by the finite element method, and the transmission characteristics are optimized by accurately adjusting its structural parameters. The transmission efficiency of the waveguide for TE mode achieves a peak value of −0.34 dB at a central frequency of 2.950 THz and keeps above −3 dB from 2.82 THz to 3.02 THz, obtaining a broad relative bandwidth of about 6.84 percent. The operating bandwidth of the tellurium photonic crystals' waveguide for TM mode is narrower than that of TE mode, whose relative bandwidth is about 4.39 percent or around 2.936 THz above −5 dB. The designed terahertz photonic crystals' waveguide can transmit both TE and TM waves, and not only can it be used as a high-efficiency transmission line, but it also provides a promising approach for implementing fully polarized THz devices for future 6G communication systems. [ABSTRACT FROM AUTHOR]

Infrared (IR) imaging-based detection systems are of vital significance in the domains of early warning and security, necessitating a high level of precision and efficiency in infrared small moving target detection. IR targets often appear dim and small relative to the background and are easily buried by noise and difficult to detect. A novel high-speed spatial–temporal saliency model (HS-STSM) based on a guided filter (GF) is proposed, which innovatively introduces GF into IR target detection to extract the local anisotropy saliency in the spatial domain, and substantially suppresses the background region as well as the bright clutter false alarms present in the background. Moreover, the proposed model extracts the motion saliency of the target in the temporal domain through vectorization of IR image sequences. Additionally, the proposed model significantly improves the detection efficiency through a vectorized filtering process and effectively suppresses edge components in the background by integrating a prior weight. Experiments conducted on five real infrared image sequences demonstrate the superior performance of the model compared to existing algorithms in terms of the detection rate, noise suppression, real-time processing, and robustness to the background. [ABSTRACT FROM AUTHOR]

Cotton Verticillium wilt is mainly caused by the fungus Verticillium dahliae, which threatens the production of cotton. Its pathogen can survive in the soil for several years in the form of microsclerotia, making it a destructive soil-borne disease. The accurate, sensitive, and rapid detection of V. dahliae from complex soil samples is of great significance for the early warning and management of cotton Verticillium wilt. In this study, we combined the loop-mediated isothermal amplification (LAMP) with CRISPR/Cas12a technology to develop an accurate, sensitive, and rapid detection method for V. dahliae. Initially, LAMP primers and CRISPR RNA (crRNA) were designed based on a specific DNA sequence of V. dahliae, which was validated using several closely related Verticillium spp. The lower detection limit of the LAMP-CRISPR/Cas12a combined with the fluorescent visualization detection system is approximately ~10 fg/μL genomic DNA per reaction. When combined with crude DNA-extraction methods, it is possible to detect as few as two microsclerotia per gram of soil, with the total detection process taking less than 90 min. Furthermore, to improve the method's user and field friendliness, the field detection results were visualized using lateral flow strips (LFS). The LAMP-CRISPR/Cas12a-LFS system has a lower detection limit of ~1 fg/μL genomic DNA of the V. dahliae, and when combined with the field crude DNA-extraction method, it can detect as few as six microsclerotia per gram of soil, with the total detection process taking less than 2 h. In summary, this study expands the application of LAMP-CRISPR/Cas12a nucleic acid detection in V. dahliae and will contribute to the development of field-deployable diagnostic productions. [ABSTRACT FROM AUTHOR]

In the contemporary tramp shipping industry, route optimization and scheduling are directly linked to enhancements in operations, economics, and the environment, making them key factors for the effective management of maritime transportation. To enhance effective ship-to-cargo matching and the refinement of maritime transportation itineraries, this paper introduces a time efficiency and carbon dioxide emission multi-objective optimization algorithm named ETE-SRSP (efficiency–time–emission multi-optimization algorithm). ETE-SRSP incorporates several factors, including the initial positions of ships, time windows for loading and unloading operations, and varying sailing speeds. Within the ETE-SRSP framework, pioneering an approach that integrates ballast and laden sailing velocities as decisional parameters, it employs a multi-objective optimization technique to investigate the intricate interplay between temporal efficiency and carbon dioxide emissions. Additionally, the model's proficiency in mitigating emissions and managing costs is clearly demonstrated through the optimization of these objectives, thereby offering a robust framework for decision support. The experimental results show that the optimal sailing speeds derived from the ETE-SRSP, under typical time-weight scenarios, can achieve an optimal balance between emission reduction and cost control. In summary, this study underscores the optimization strategy's potential to effectively address the maritime sector's need for economic growth and ecological conservation, showcasing its practical value in the industry. [ABSTRACT FROM AUTHOR]

Ecological industrial parks (EIPs) play a pivotal role as primary drivers of China's industrial green transformation, facilitating the enhancement of urban carbon emission efficiency (UCEE) and the realization of green sustainable development. This study empirically investigates the effects of EIP policies on UCEE through quasi-natural experiments, utilizing data from 282 prefecture-level cities in China spanning from 2006 to 2021. Employing a multi-period difference-in-difference (DID) method, the findings are as follows: (1) The implementation of EIP policies leads to a 2.5% average increase in UCEE. (2) Event analysis reveals certain lagging characteristics in the promoting effect of EIP policies on the carbon emission efficiency of pilot cities. (3) EIP construction primarily enhances UCEE by reinforcing agglomeration effects and elevating innovation ability. (4) The promoting effect of EIP construction is more pronounced in the eastern and central regions, as well as in non-resource-based cities within different regions. Drawing from the empirical results, this study provides pertinent recommendations for EIP construction, offering theoretical guidance to policymakers and managers in crafting sustainable development strategies. [ABSTRACT FROM AUTHOR]

In recent years, there has been significant growth in location-based services (LBSs) and applications. These services empower users to transmit their location data to location service providers, thereby facilitating the provisioning of pertinent resources and services. However, in order to prevent malicious users from sending fake location data, users must attest to their location for service providers, namely, through a proof of location (PoL). Such a proof should additionally prevent attackers from being able to obtain users' identity and location information through it. In this paper, we propose an efficient privacy-preserving proof of location (PPPoL) scheme. The scheme is based on the standard cryptographic primitives, including Group Time-based One-Time Password (GTOTP) and public key encryption, which achieves entity privacy, location privacy, and traceability. Unlike the previous GTOTP-based PPPoL scheme, our scheme enables instant location verification with additional hash operations. To encourage the active participation of witnesses in location proofs, we propose an incentive mechanism based on smart contracts. Additionally, we implement a proof of concept of our PPPoL scheme on an Android device. Our experimental results show that proof generation and verification time are on the order of milliseconds. Meanwhile, the total overhead for the incentive mechanism amounts to 0.0011 ETH. This result is practical for mobile device-based LBSs. [ABSTRACT FROM AUTHOR]

This study prepared a novel β-carotene colorant lake using calcium carbonate (CaCO3) and investigated the lake formation process and its basic characteristics. Kinetic adsorption analysis confirmed that medium pH (9.3) and medium temperature (40 °C) were more suitable for lake preparation, while desorption occurred, possibly due to crystalline transformation of CaCO3. The isothermal analysis and model fitting results suggested that the β-carotene and CaCO3 particles combined via a monolayer adsorption process driven by physical force. Electrostatic attraction likely participated in the process due to the net negative surface charges of β-carotene dispersion and positively charged groups on the CaCO3 particle surfaces. Ethanol, ultrasonic treatment, and drying method significantly influenced the immobilization efficiency (IE) of β-carotene in the lake and light stability of the lake, without affecting its crystal form. The thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC) curves confirmed absorption of β-carotene onto CaCO3. Fourier-transform infrared spectroscopy (FTIR) and X-ray photoelectron spectroscopy (XPS) analyses indicated no obvious chemical bonds between β-carotene and CaCO3. Energy-dispersive spectroscopy (EDS) confirmed the presence of β-carotene on surfaces but not in the interior of the CaCO3 particles. The adsorption of β-carotene by calcium carbonate was further confirmed to be a physical adsorption on surface. [ABSTRACT FROM AUTHOR]

Having emerged as strategic focal points in industrial transformation and technological innovation, intelligent machine tools are pivotal in the field of intelligent manufacturing. Accurately forecasting emerging technologies within this domain is crucial for guiding intelligent manufacturing's evolution and fostering rapid innovation. However, prevailing research methodologies exhibit limitations, often concentrating on popular topics at the expense of lesser-known yet significant areas, thereby impacting the accurate identification of research priorities. The complex, systemic, and interdisciplinary nature of intelligent machine tool technology challenges traditional research approaches, particularly in assessing technological maturity and intricate interactions. To overcome these challenges, we propose a novel framework that leverages technological communities for a comprehensive analysis. This approach clusters data into specific topics which are reflective of the technology system, facilitating detailed investigations within each area. By refining community analysis methods and integrating structural and interactive community features, our framework significantly improves the precision of emerging technology predictions. Our research not only validates the framework but also projects key emerging technologies in intelligent machine tools, offering valuable insights for business leaders and scholars alike. [ABSTRACT FROM AUTHOR]

Market convergence challenges socially sustainable supply chain management (SSSCM) due to the increasing competition. Identifying market convergence trends allows companies to respond quickly to market changes and improve supply chain resilience (SCR). Conventional approaches are one-sided and biased and cannot predict market convergence trends comprehensively and accurately. To address this issue, we propose a framework based on info2vec that solves the problem of matching multidimensional data by using the technology layer as the focal layer and the supply chain as the supporting layer. The framework enriches the supply chain dimension with the technology dimension. A knowledge graph is constructed to facilitate cross-domain information connectivity by integrating different data sources. The nodes in the knowledge graph were characterized using a representation learning algorithm, which enhanced feature mining during supply chain and market convergence. Changes in market demand were predicted based on link prediction experiments. Market convergence has an impact on firm cooperation and, thus, on SCR. The framework recommends potential technological and innovative cooperation opportunities for firms. In this way, it has been demonstrated to improve SSSCM through network resilience experiments. This method predicts market convergence efficiently based on the supply chain knowledge graph, which provides decision support for enterprise development. [ABSTRACT FROM AUTHOR]

The flowering stage is a critical period for water sensitivity and quality formation of broomcorn millets. However, the effects and mechanisms of drought stress on the quality formation of broomcorn millets are not clear. We used the drought-resistant variety Hequ red millet (H) and the drought-sensitive variety Yanshu No. 10 (Y) were used as materials for drought stress treatment during the flowering stage, metabolomics and physiological methods were used to study the differences in protein, starch, amino acids, medium and medium-long chain fatty acids, and their response characteristics to drought in broomcorn millet. The results showed that different genotypes of broomcorn millets exhibited different response mechanisms in the face of drought stress. In Hequ red millet, drought stress significantly increased the contents of amylopectin (2.57%), pyridoxine (31.89%), and anthocyanin, and significantly decreased the contents of water-soluble protein (5.82%), glutelin (10.07%), thiamine (14.95%) and nicotinamide (23.01%). In Yanshu No. 10, drought significantly decreased amylose by 6.05%, and significantly increased riboflavin and nicotinamide contents by 21.11% and 32.59%. Correlation analysis showed that total starch and amylose were highly significantly positively correlated with methyl palmitate; negatively correlated with amylopectin, vitamins, proteins, free amino acids, and medium-long chain fatty acids; and amylopectin was significantly positively correlated with water-soluble protein, riboflavin, and pyridoxine. Water-soluble protein and glutelin were significantly positively correlated with most free amino acids, medium-long chain fatty acids, and nicotinamide. Thiamine showed significant positive correlation with nicotinamide and significant negative correlation with pyridoxine. Riboflavin was significantly positively correlated with nicotinamide, pyridoxine, and water-soluble protein, and pyridoxine was significantly positively correlated with water-soluble protein. Hequ red millet transforms into amylopectin by consuming water-soluble protein and glutelin, and improves drought resistance by accumulating pyridoxine, and changes its physicochemical properties by decreasing the content of amylose and protein and elevating the content of amylopectin. Yanshu No. 10 resisted drought by catabolizing lipids to produce fatty acids and by consuming amylose for conversion into other metabolites. The present study helps to understand the response of the nutritional quality of millets to drought stress at the flowering stage and provides a theoretical basis for the selection and breeding of superior varieties of millets and drought resistance research. [ABSTRACT FROM AUTHOR]

Point cloud semantic segmentation is of utmost importance in practical applications. However, most existing methods have evolved to be incredibly intricate, leading to a rise in complexity that has made them increasingly impractical for real-world utilization. The escalating complexity of these methods has resulted in a deterioration in their efficiency and ease of implementation, making them less suitable for use in time-sensitive and resource-constrained environments. Towards this issue, we propose an efficient and lightweight segmentation method, able to achieve a remarkable performance in terms of both segmentation accuracy, training speed, and space consumption. Specifically, we first propose to adopt random sampling to replace the original one to obtain more efficiency. Moreover, a lightweight decoding module and an improved bilateral enhancement (BAE) module are developed to further improve the performance. The proposed method achieved a 73.6% and 60.7% mIoU on the S3DIS and Semantickitti datasets, respectively. In the future, the random sampling and the proposed BAE module can be adopted in a more concise and lightweight network to achieve faster and more-accurate point cloud segmentation. [ABSTRACT FROM AUTHOR]

Drought stress restricts plant growth and development. The flowering stage is a period of abundant microbial diversity in the rhizosphere of broomcorn millet. However, the diversity and community structure of rhizosphere fungi during the flowering stage of broomcorn millet and the response mechanism to drought stress are still unclear. In this study, two broomcorn millet varieties, 'Hequ red millet' (A1) and 'Yanshu No.10′ (A2), with different drought resistances, were used as experimental materials. Using the pot water control method, drought treatment at the flowering stage was carried out, and normal watering (A1CK, A2CK) was used as the control. High-throughput sequencing technology was used to study the diversity and structural changes in rhizosphere fungi in broomcorn millet. The results show that the number of fungi OTUs in the A1, A2, A1CK and A2CK samples were 445, 481, 467 and 434, respectively, of which 331 OTUs were shared by all groups. The fungal community in the rhizosphere of broomcorn millet was mainly composed of Ascomycota and Basidiomycota. Drought treatment significantly reduced the abundance of Mortierella and significantly increased the abundance of Phoma. The abundance of Nectriaceae in the rhizosphere soil of 'Hequ Red millet' was significantly increased. The abundance of Pseudocercospora in the rhizosphere soil of 'Yanshu No.10′ was higher, and the lower was Hypocreales and Nectriaceae. However, there was no significant difference in the alpha diversity of fungal communities in the four treatments, and the fungal community structure between A2 and A1CK was more similar, whereas the difference between A1 and A2CK was larger. Correlation analysis showed that drought stress had little effect on the interaction of rhizosphere fungi, and metabolic functions such as nucleotide metabolism and electron transport in rhizosphere fungi accounted for a relatively high proportion. The results show that the diversity and community structure of rhizosphere fungi were less affected by drought, which may have been due to the close interaction between species, which made the fungal community more stable under drought stress, and the difference in planting varieties may have affected the enriched rhizosphere fungal species. [ABSTRACT FROM AUTHOR]

The filamentation temperature-sensitive H (FtsH) gene family is critical in regulating plant chloroplast development and photosynthesis. It plays a vital role in plant growth, development, and stress response. Although FtsH genes have been identified in a wide range of plants, there is no detailed study of the FtsH gene family in soybean (Glycine max). Here, we identified 34 GmFtsH genes, which could be categorized into eight groups, and GmFtsH genes in the same group had similar structures and conserved protein motifs. We also performed intraspecific and interspecific collinearity analysis and found that the GmFtsH family has large-scale gene duplication and is more closely related to Arabidopsis thaliana. Cis-acting elements analysis in the promoter region of the GmFtsH genes revealed that most genes contain developmental and stress response elements. Expression patterns based on transcriptome data and real-time reverse transcription quantitative PCR (qRT-PCR) showed that most of the GmFtsH genes were expressed at the highest levels in leaves. Then, GO enrichment analysis indicated that GmFtsH genes might function as a protein hydrolase. In addition, the GmFtsH13 protein was confirmed to be localized in chloroplasts by a transient expression experiment in tobacco. Taken together, the results of this study lay the foundation for the functional determination of GmFtsH genes and help researchers further understand the regulatory network in soybean leaf development. [ABSTRACT FROM AUTHOR]

Light field imaging involves reconstructing a 4D light field from a 3D focal stack, which makes it challenging to reconstruct the light field from incomplete projection data. To address this problem, a linear projection system is established to model the focal stack imaging process using discrete refocusing equations. Based on this system, we propose the block Landweber iterative method to find the least-squares solution. This method computes the sparse matrix while iterating, which overcomes the problem of data storage. The 2-norm of the block matrix is utilized as the weighted matrix to normalize every block matrix on an identical scale, delivering an effective relaxation strategy under the convergence condition in the inconsistent case, which yields better reconstruction results and accelerates the convergence speed. The experimental results based on the image quality assessments of reference and non-reference images show that our method achieved better reconstruction results compared to other relevant common methods, even with fewer focal stacks and higher angle resolution. [ABSTRACT FROM AUTHOR]

Kudzu root (Pueraria lobate (Willd.) Ohwi, KR) is an edible plant with rich nutritional and medicinal values. Over the past few decades, an ample variety of biological effects of Pueraria isoflavone have been evaluated. Evidence has shown that Pueraria isoflavone can play an active role in antioxidant, anti-inflammatory, anti-cancer, neuroprotection, and cardiovascular protection. Over 50 isoflavones in kudzu root have been identified, including puerarin, daidzein, daidzin, 3′-hydroxy puerarin, and genistein, each with unambiguous structures. However, the application of these isoflavones in the development of functional food and health food still depends on the extraction, purification and identification technology of Pueraria isoflavone. In recent years, many green and novel extraction, purification, and identification techniques have been developed for the preparation of Pueraria isoflavone. This review provides an updated overview of these techniques, specifically for isoflavones in KR since 2018, and also discusses and compares the advantages and disadvantages of these techniques in depth. The intention is to provide a research basis for the green and efficient extraction, purification, and identification of Pueraria isoflavone and offers investigators a valuable reference for future studies on the KR. [ABSTRACT FROM AUTHOR]

Detecting infrared (IR) small moving targets in complex scenes quickly, accurately, and robustly remains a challenging problem in the current research field. To address this issue, this paper proposes a novel spatial–temporal block-matching patch-tensor (STBMPT) model based on a low-rank sparse decomposition (LRSD) framework. This model enhances the traditional infrared patch-tensor (IPT) model by incorporating joint spatial–temporal sampling to exploit inter-frame information and constructing a low-rank patch tensor using image block matching. Furthermore, a novel prior-weight calculation is introduced, utilizing the eigenvalues of the local structure tensor to suppress interference such as strong edges, corners, and point-like noise from the background. To improve detection efficiency, the tensor is constructed using a matching group instead of using a traditional sliding window. Finally, the background and target components are separated using the alternating direction method of multipliers (ADMM). Qualitative and quantitative experimental analysis in various scenes demonstrates the superior detection performance and efficiency of the proposed algorithm for detecting infrared small moving targets in complex scenes. [ABSTRACT FROM AUTHOR]

Despite significant advancements in remote sensing object tracking (RSOT) in recent years, achieving accurate and continuous tracking of tiny-sized targets remains a challenging task due to similar object interference and other related issues. In this paper, from the perspective of feature enhancement and a better feature matching strategy, we present a tracker SiamTM specifically designed for RSOT, which is mainly based on a new target information enhancement (TIE) module and a multi-level matching strategy. First, we propose a TIE module to address the challenge of tiny object sizes in satellite videos. The proposed TIE module goes along two spatial directions to capture orientation and position-aware information, respectively, while capturing inter-channel information at the global 2D image level. The TIE module enables the network to extract discriminative features of the targets more effectively from satellite images. Furthermore, we introduce a multi-level matching (MM) module that is better suited for satellite video targets. The MM module firstly embeds the target feature map after ROI Align into each position of the search region feature map to obtain a preliminary response map. Subsequently, the preliminary response map and the template region feature map are subjected to the Depth-wise Cross Correlation operation to get a more refined response map. Through this coarse-to-fine approach, the tracker obtains a response map with a more accurate position, which lays a good foundation for the prediction operation of the subsequent sub-networks. We conducted extensive experiments on two large satellite video single-object tracking datasets: SatSOT and SV248S. Without bells and whistles, the proposed tracker SiamTM achieved competitive results on both datasets while running at real-time speed. [ABSTRACT FROM AUTHOR]

Under different temperatures and pressures, the physical parameters of drilling fluid will change, resulting in inaccurate drilling hydraulic calculations. Aiming to address the problem of the traditional rheological prediction method needing to first determine the rheological model, this paper proposed a method for first predicting the readings of the rheometer and then determining the rheological model. The model established in this paper adopted a parameter-free method, which expands the application range of the model. Rheology experiments were carried out on the three types of oil-based drilling fluids collected at the well site. The model in this paper was verified based on the experimental data. The results showed that, compared with the traditional drilling fluid rheological prediction method, the model established in this paper had a better prediction effect, with an average error of 4.85%, and the average error reduction ranges from 3.8% to 8.3%. The model established in this paper is able to provide theoretical support for accurate hydraulic calculation. [ABSTRACT FROM AUTHOR]

Individual tree detection for urban forests in subtropical environments remains a great challenge due to the various types of forest structures, high canopy closures, and the mixture of evergreen and deciduous broadleaved trees. Existing treetop detection methods based on the canopy-height model (CHM) from UAV images cannot resolve commission errors in heterogeneous urban forests with multiple trunks or strong lateral branches. In this study, we improved the traditional local-maximum (LM) algorithm using a dual Gaussian filter, variable window size, and local normalized correlation coefficient (NCC). Specifically, we adapted a crown model of maximum/minimum tree-crown radii and an angle strategy to detect treetops. We then removed and merged the pending tree vertices. Our results showed that our improved LM algorithm had an average user accuracy (UA) of 87.3% (SD± 4.6), an average producer accuracy (PA) of 82.8% (SD± 4.1), and an overall accuracy of 93.3% (SD± 3.9) for sample plots with canopy closures less than 0.5. As for the sample plots with canopy closures from 0.5 to 1, the accuracies were 78.6% (SD± 31.5), 73.8% (SD± 10.3), and 68.1% (SD± 12.7), respectively. The tree-height estimation accuracy reached more than 0.96, with an average RMSE of 0.61 m. Our results show that the UAV-image-derived CHM can be used to accurately detect individual trees in mixed forests in subtropical cities like Shanghai, China, to provide vital tree-structure parameters for precise and sustainable forest management. [ABSTRACT FROM AUTHOR]

The Trihelix is a plant-specific transcription factor family and has critical roles in plant growth and development and stress resistance. There is less information about Trihelix transcription factor genes and their potential functions in strawberries (Fragaria vesca). In the present study, we performed a detailed bioinformatics analysis of the Trihelix family in strawberries including physicochemical properties, chromosomal location, exon–intron distribution, domain arrangement, and subcellular localization. Thirty Trihelix family members were identified and divided into five subfamilies. The expression of FvTrihelix genes in different tissues/organs, i.e., root, stolon, leaf, flower, and fruit, was measured in strawberries after infection with Colletotrichum. gloeosporioides and foliar applications of salicylic acid (SA) and jasmonic acid (JA). Most of the genes showed differential expression responses following C. gloeosporioides infection and hormone treatments (SA and JA), suggesting critical roles in disease resistance and hormonal signaling pathways. As anticipated, the ectopic expression of FvTrihelix6 in Arabidopsis thaliana increased resistance against Colletotrichum. higginsianum infection. FvTrihelix6 protein was localized in the nucleus. We surmise that FvTrihelix6 enhances resistance against pathogens through the SA and JA signaling pathways. This study provides novel insights into the strawberry Trihelix transcription factor genes and new candidates for disease-resistance breeding of strawberries. [ABSTRACT FROM AUTHOR]

Inspired by the gradual collapse of carbon chain and the gradual release of organic elements into the external environment during the degradation of biodegradable polymers, a novel biodegradable polymer slow-release fertilizer containing nutrient nitrogen and phosphorus (PSNP) was prepared in this study. PSNP contains phosphate fragment and urea formaldehyde (UF) fragment, which are prepared by solution condensation reaction. Under the optimal process, the nitrogen (N) and P2O5 contents of PSNP were 22% and 20%, respectively. The expected molecular structure of PSNP was confirmed by SEM, FTIR, XRD, and TG. PSNP can release N and phosphorus (P) nutrients slowly under the action of microorganisms, and the cumulative release rates of N and P in 1 month were only 34.23% and 36.91%, respectively. More importantly, through soil incubation experiment and leaching experiment, it was found that UF fragments released in the degradation process of PSNP can strongly complex soil high-valence metal ions, thus inhibiting the phosphorus nutrient released by degradation to be fixed in the soil and ultimately effectively increasing the soil available P content. Compared with ammonium dihydrogen phosphate (ADP), a small molecule phosphate fertilizer that is easily soluble, the available P content of PSNP in the 20–30 cm soil layer is almost twice that of ADP. Our study provides a simple copolymerization method to prepare PSNP with excellent slow-release N and P nutrients, which can promote the development of sustainable agriculture. [ABSTRACT FROM AUTHOR]

The rate of penetration (ROP) is an important indicator affecting the drilling cost and drilling performance. Accurate prediction of the ROP has important guiding significance for increasing the drilling speed and reducing costs. Recently, numerous studies have shown that machine learning techniques are an effective means to accurately predict the ROP. However, in petroleum engineering applications, its robustness and generalization cannot be guaranteed. The traditional empirical model has good robustness and generalization ability. Based on the quantification of data similarity, this paper establishes a hybrid model combining a machine learning method and an empirical method, which combines the high prediction accuracy of the machine learning method with the good robustness and generalization of the empirical method, overcoming the shortcomings of any single model. The AE-ED (the Euclidean Distance between the input data and reconstructed data from the autoencoder model) is defined to measure the data similarity, and according to the data similarity of each new piece of input data, the hybrid model chooses the corresponding single model to calculate. The results show that the hybrid model is better than any single model, and all the evaluation indicators perform better, making it more suitable for the ROP prediction in this field. [ABSTRACT FROM AUTHOR]

An urban agglomeration is the engine of regional and national economic growth, but also causes many ecological and environmental issues that emerge from massive land changes. In this study, the spatiotemporal evolution of an urban agglomeration was quantified and its impacts on the urban and regional landscape patterns were evaluated. It showed that the urbanized land area of the Pearl River Delta Urban Agglomeration (PRDUA) in China nearly quadrupled, having linearly increased from 1819.8 km2 to 7092.2 km2 between 1985 and 2015. The average annual growth rate presented a bimodal wave-like pattern through time, indicating that the PRDUA has witnessed two rounds of the urbanization process. The growth modes (e.g., leapfrog, edge-expansion, infilling) were detected and they exhibited co-existing but alternating dominating patterns during urbanization, demonstrating that the spatiotemporal evolution of the urban development of the PRDUA follows the "spiral diffusion-coalescence" hypothesis. The morphology of the PRDUA presented an alternating dispersal-compact pattern over time. The city-level and regional-level landscape patterns changed synchronously with the spatiotemporal evolution of the PRDUA over time. The urbanization of the PRDUA increased both the complexity and aggregation of the landscape, but also resulted in an increasing fragmentation and decreasing connectivity of the natural landscape in the Pearl River Delta region. These findings are helpful for better understanding how urban agglomerations evolve and in providing insights for regional urban planning and sustainable land management. [ABSTRACT FROM AUTHOR]

Blueberry is the source of a variety of bioactive substances, including phenolic compounds, such as anthocyanins, pterostilbene, phenolic acids, etc. Several studies have revealed that polyphenols in blueberry have important bioactivities in maintaining health, such as antioxidant and anti-tumor activities, immune regulation, the prevention of chronic diseases, etc. Therefore, these phenolic compounds in blueberries have been widely used in the field of healthcare, and the extraction, isolation, and purification of phenolic compounds are the prerequisites for their utilization. It is imperative to systematically review the research progress and prospects of phenolic compounds present in blueberries. Herein, the latest progress in the extraction, purification, and analysis of phenolic compounds from blueberries is reviewed, which can in turn provide a foundation for further research and usage of blueberries. [ABSTRACT FROM AUTHOR]

Plant chitinases (EC 3.2.1.14) are pathogenesis-related (PR) proteins and are well studied in many plant species. However, little is known about the genomic organization and expression of chitinase genes in strawberries (Fragaria vesca). Here, 23 FvChi genes were identified in the genome of strawberry (F. vesca) and divided into GH18 and GH19 subfamilies based on phylogenetic relationships. A detailed bioinformatics analysis of the FvChi genes was performed, including gene physicochemical properties, chromosomal location, exon–intron distribution, domain arrangement, and subcellular localization. Twenty-two FvChi genes showed upregulation after Colletotrichum gloeosporioides infection. Following the exogenous application of SA, FvChi-3, 4, and 5 showed significant changes in expression. The ectopic expression of FvChi-14 in Arabidopsis thaliana increased resistance to C. higginsianum via controlling the SA and JA signaling pathway genes (AtPR1, AtICS1, AtPDF1.2, and AtLOX3). The FvChi-14 protein location was predicted in the cell wall or extracellular matrix. We speculate that FvChi-14 is involved in disease resistance by regulating the SA and JA signaling pathways. The findings of this study provide a theoretical reference for the functional studies of FvChi genes and new candidates for strawberry stress resistance breeding programs. [ABSTRACT FROM AUTHOR]

With the continuous growth in global energy demand, the exploration and development of hydrates has been the focus of increasing attention, and the accurate evaluation of the mechanical properties of hydrate layers has become particularly important. In this study, using a self-developed hydrate sample preparation device and hydrate triaxial seepage test platform, triaxial shear tests were carried out using the in situ synthesis method for hydrate sediment in the laboratory, and the stress–strain curves of hydrate sediment with different levels of saturation were obtained. By analyzing the stress–strain curve, the mechanical parameters of hydrate sediment were calculated and simulated using ABAQUS (2021, Dassault systemes, Vélizy Villacoublay France) finite element software. Several p-y curves were calculated and compared with the simulation results, and the p-y curve correction method of the hydrate layer in a shallow seabed was obtained. It was found that the strength of the hydrate sediment increased with an increase in saturation. At the same time, an increase in confining pressure and a decrease in temperature also increased the strength of hydrate deposits. Through comparison with the existing API (American Petroleum Institute) standard p-y curve, it was found that its strength is low because the existence of the hydrate improves the formation strength. [ABSTRACT FROM AUTHOR]

In the combat system, infrared target detection is an important issue worthy of study. However, due to the small size of the target in the infrared image, the low signal-to-noise ratio of the image and the uncertainty of motion, how to detect the target accurately and quickly is still difficult. Therefore, in this paper, an infrared method of detecting small moving targets based on a coarse-to-fine structure (MCFS) is proposed. The algorithm mainly consists of three modules. The potential target extraction module first smoothes the image through a Laplacian filter and extracts the prior weight of the image by the proposed weighted harmonic method to enhance the target and suppress the background. Then, the local variance feature map and local contrast feature map of the image are calculated through a multiscale three-layer window to obtain the potential target region. Next, a new robust region intensity level (RRIL) algorithm is proposed in the spatial-domain weighting module. Finally, the temporal-domain weighting module is established to enhance the target positions by analyzing the kurtosis features of temporal signals. Experiments are conducted on real infrared datasets. Through scientific analysis, the proposed method can successfully detect the target, at the same time, the ability to suppress the background and the ability to improve the target has reached the maximum, which verifies the effectiveness of the algorithm. [ABSTRACT FROM AUTHOR]

Fly ash (FA) usually causes air and soil pollution due to wind erosion. However, most FA field surface stabilization technologies have long construction periods, poor curing effects, and secondary pollution. Therefore, there is an urgent need to develop an efficient and environmentally friendly curing technology. Polyacrylamide (PAM) is an environmental macromolecular chemical material for soil improvement, and Enzyme Induced Carbonate Precipitation (EICP) is a new friendly bio-reinforced soil technology. This study attempted to use chemical, biological, and chemical-biological composite treatment solutions to solidify FA, and the curing effect was evaluated by testing indicators, such as unconfined compressive strength (UCS), wind erosion rate (WER), and agglomerate particle size. The results showed that due to the viscosity increase in the treatment solution, with the increase in PAM concentration, the UCS of the cured samples increased first (from 41.3 kPa to 376.1 kPa) and then decreased slightly (from 376.1 kPa to 367.3 kPa), while the wind erosion rate of the cured samples decreased first (from 39.567 mg/(m2·min) to 3.014 mg/(m2·min)) and then increased slightly (from 3.014 mg/(m2·min) to 3.427 mg/(m2·min)). Scanning electron microscopy (SEM) indicated that the network structure formed by PAM between the FA particles improved the physical structure of the sample. On the other hand, PAM increased the nucleation sites for EICP. Due to the stable and dense spatial structure formed by the "bridging" effect of PAM and the cementation of CaCO3 crystals, the mechanical strength, wind erosion resistance, water stability, and frost resistance of the samples cured by PAM-EICP were increased significantly. The research will provide curing application experience and a theoretical basis for FA in wind erosion areas. [ABSTRACT FROM AUTHOR]

Nitric oxide (NO) is a gaseous free radical that has been become a potential tool to maintain the quality of postharvest horticultural produce. It plays important roles in delaying ripening, alleviating chilling injury, preventing browning, and enhancing disease resistance. The regulatory function of NO is achieved through the post-transcriptional modification of proteins, such as tyrosine nitration, S-nitrosylation, and nitroalkylation. Secondly, NO can also induce the expression of stress-related genes by synergistically interacting with other signaling substances, such as Ca2+, ethylene (ETH), salicylic acid (SA), and jasmonic acid (JA). Here, research progress on the role of NO and its donors in regulating the quality of postharvest fruits and vegetables under storage is reviewed. The function of NO crosstalk with other phytohormones is summarized. Future research directions for NO commercial application and the endogenous NO regulatory mechanism are also discussed. [ABSTRACT FROM AUTHOR]

Germanium-tin (GeSn) alloy is considered a promising candidate for a Si-based short-wavelength infrared range (SWIR) detector and laser source due to its excellent carrier mobility and bandgap tunability. Pulsed laser annealing (PLA) is one of the preeminent methods for preparing GeSn crystal films with high Sn content. However, current reports have not systematically investigated the effect of different pulse-width lasers on the crystalline quality of GeSn films. In addition, the intensity of the spot follows the gaussian distribution. As a result, various regions would have different crystalline properties. Therefore, in this study, we first provide the Raman spectra of several feature regions in the ablation state for single spot processing with various pulse-width lasers (continuous-wave, nanosecond, femtosecond). Furthermore, the impact of laser pulse width on the crystallization characteristics of GeSn film is explored for different single-spot processing states, particularly the Sn content incorporated into GeSn crystals. The transient heating time of the film surface and the faster non-equilibrium transition of the surface temperature inhibit the segregation of the Sn component. By comparing the Raman spectra of the pulsed laser, the continuous-wave laser shows the most acute Sn segregation phenomenon, with the lowest Sn content of approximately 2%. However, the femtosecond laser both ensures crystallization of the film and effective suppression of Sn expulsion from the lattices, and the content of Sn is 8.07%, which is similar to the origin of GeSn film. [ABSTRACT FROM AUTHOR]

Accurate identification of overflow fluid types facilitates timely and effective handling of onsite overflow accidents. Research into identifying the type of overflow fluid is limited, and there are only simple calculation models that do not consider enough effects; additionally, accuracy needs to be improved and the identification method is not perfect. If there is no drilling data, it is impossible to identify the overflow fluid. Therefore, this paper modifies the density calculation model of overflow fluid by considering the influence of the temperature, pressure field, and two-phase flow model, making the calculation result more accurate and universal, and puts forward a comprehensive method for auxiliary identification based on gas logging interpretation. This paper uses the gas state equation to verify the accuracy of the overflow density model; after verification using data from more than 20 overflowing wells, the method was found to be practical and had an accuracy rate of more than 90%. Thus, this study and the proposed method can provide guidance for dealing with overflow accidents in the field and any follow-up research. [ABSTRACT FROM AUTHOR]

Isoflavone-rich legumes, including soy, are used for food production, as dietary supplements and in traditional medicine. Soy consumption correlates negatively with benign prostatic hyperplasia (BPH) and voiding symptoms. However, isoflavone effects on the prostate are hardly known. Here, we examined the effects on human prostate smooth muscle contractions and stromal cell growth, which are driving factors of voiding symptoms in BPH. Smooth muscle contractions were induced in prostate tissues from radical prostatectomy. Growth-related functions were studied in cultured stromal cells (WPMY-1). Neurogenic, α1-adrenergic and non-adrenergic contractions were strongly inhibited with 50 µM and by around 50% with 10 µM genistein. Daidzein inhibited neurogenic contractions using 10 and 100 µM. Agonist-induced contractions were inhibited by 100 µM but not 10 µM daidzein. A combination of 6 µM genistein with 5 µM daidzein still inhibited neurogenic and agonist-induced contractions. Proliferation of WPMY-1 cells was inhibited by genistein (>50%) and daidzein (<50%). Genistein induced apoptosis and cell death (by seven-fold relative to controls), while daidzein induced cell death (6.4-fold) without apoptosis. Viability was reduced by genistein (maximum: 87%) and daidzein (62%). In conclusion, soy isoflavones exert sustained effects on prostate smooth muscle contractions and stromal cell growth, which may explain the inverse relationships between soy-rich nutrition, BPH and voiding symptoms. [ABSTRACT FROM AUTHOR]

The on-demand release of antibacterial components due to pH variations caused by acidogenic/cariogenic bacteria is a possible design for smart antibacterial restorative materials. This study aimed to fabricate pH-responsive Zn2+-releasing glass particles and evaluate their solubilities, ion-releasing characteristics, and antibacterial properties in vitro. Three kinds of silicate-based glass particles containing different molar ratios of Zn (PG-1: 25.3; PG-2: 34.6; PG-3: 42.7 mol%) were fabricated. Each particle was immersed in a pH-adjusted medium, and the solubility and concentration of the released ions were determined. To evaluate the antibacterial effect, Streptococcus mutans was cultured in the pH-adjusted medium in the presence of each particle, and the bacterial number was counted. The solubility and concentration of Zn2+ released in the medium increased with a decrease in medium pH. PG-3 with a greater content of Zn demonstrated higher concentrations of released Zn2+ compared with PG-1 and PG-2. PG-2 exhibited bactericidal effects at pH 5.1, whereas PG-3 demonstrated bactericidal effects at pH values of 5.1 and 6.1, indicating that PG-3 was effective at inhibiting S. mutans even under slightly acidic conditions. The glass particle with 42.7 mol% Zn may be useful for developing smart antibacterial restoratives that contribute to the prevention of diseases such as caries on root surfaces with lower acid resistance. [ABSTRACT FROM AUTHOR]

The RPW8s (Resistance to Powdery Mildew 8) are atypical broad-spectrum resistance genes that provide resistance to the powdery mildew fungi. Powdery mildew of rubber tree is one of the serious fungal diseases that affect tree growth and latex production. However, the RPW8 homologs in rubber tree and their role of resistance to powdery mildew remain unclear. In this study, four RPW8 genes, HbRPW8-a, b, c, d, were identified in rubber tree, and phylogenetic analysis showed that HbRPW8-a was clustered with AtRPW8.1 and AtRPW8.2 of Arabidopsis. The HbRPW8-a protein was localized on the plasma membrane and its expression in rubber tree was significantly induced upon powdery mildew infection. Transient expression of HbRPW8-a in tobacco leaves induced plant immune responses, including the accumulation of reactive oxygen species and the deposition of callose in plant cells, which was similar to that induced by AtRPW8.2. Consistently, overexpression of HbRPW8-a in Arabidopsis thaliana enhanced plant resistance to Erysiphe cichoracearum UCSC1 and Pseudomonas syringae pv. tomato DC30000 (PstDC3000). Moreover, such HbRPW8-a mediated resistance to powdery mildew was in a salicylic acid (SA) dependent manner. Taken together, we demonstrated a new RPW8 member in rubber tree, HbRPW8-a, which could potentially contribute the resistance to powdery mildew. [ABSTRACT FROM AUTHOR]

It is a novel idea to fabricate wood-inorganic composites by utilizing the transpiration of bionic trees to realize the self-assembly of inorganic precursors in wood formation. We selected a 10-year-old poplar and diffused the solvent or sol containing SiO2 precursor into the xylem via the slow-release drip method. In combination with the moisture in xylem, reactions such as hydrolysis, polycondensation and self-assembly were induced in order to form wood inorganic composites. It was found, through microscopic observation, that such inorganic substances were yellowish brown and widely existed in vessels, wood fibers and ray cells. For the new grown wood, the fiber–tissue ratio and cell wall thickness underwent an increase, while the vessel diameter and tissue ratio experienced a decline. Moreover, such change was related to the concentration of precursors. EDS analysis proved that the elemental composition of sediments in wood cells was C, O, Si, K and Ca. XPS confirmed that the newly formed wood contained silicon oxide, illustrating that the standing tree slow-release drip technology could induce wood to fabricate inorganic composites. [ABSTRACT FROM AUTHOR]

Wood permeability and compressibility are affected by cell wall structure and chemical composition. These properties can be improved by appropriate wood pretreatments. Low-density poplar wood was converted to a more dense structure by the following steps: First, lignin and hemicellulose were removed using a mixture of NaOH and Na2SO3. Second they were impregnated with polyethylene glycol (PEG, mean molecular weight of 1200), nano-SiO2, and a silane coupling agent at atmospheric temperature and pressure. Finally, impregnated wood was compressed at 150 °C. Results showed that the tracheid lumens on the transverse section of the compressed wood almost vanished. Specifically, the lumens in the wood cells, especially those that were compressed, were almost completely filled with PEG. In FTIR, the asymmetric absorption peaks of Si–O–Si at 1078–1076 cm−1 were clearly observed, which confirms the existence of bonding between nano-SiO2 and wood. The highest melting enthalpy and crystallization enthalpy showed a heat storage capacity of modified wood, which were 20.7 and 9.8 J/g, respectively. Such phase change capabilities may have potential applications in regulating the rate of change of room temperature. In summary, the modified wood could be utilized as material for construction to conserve energy. [ABSTRACT FROM AUTHOR]

It is still a challenge to overcome the extended setting process of pure Ca-silicate as root canal fillers. We investigated the effects of attapulgite (a basic hydrous silicate of magnesium and aluminum) and ball-milling liquid medium on the self-curing properties of conventional β-dicalcium silicate (C2Si)-based cements. It was shown that a minor amount of attapulgite nanofibers (1–4%) had only a slight influence on setting time but caused a large increase in compressive resistance and structural stability. In particular, the ball milling media with different acetone/water ratios (3:0, 2:1, 1:2, 0:3) could directly influence the particle size distribution of C2Si powders, and the co-existence of liquid media (2:1 or 1:2) may be beneficial for shortening the setting time, enhancing early-stage compressive strength, and significantly improving the anti-microleakage ability of cement. Moreover, the composite cements also exhibited appreciable antibacterial efficacy in vitro. These findings demonstrated that the physicochemical properties of the Ca-silicate powders could be tuned by adding a minor amount of inorganic silicate nanofibers and a simple ball milling condition, and such a facile strategy is favorable for developing novel (pre-mixed) Ca silicate-based cements as root canal sealers. [ABSTRACT FROM AUTHOR]

Infrared imaging plays an important role in space-based early warning and anti-missile guidance due to its particular imaging mechanism. However, the signal-to-noise ratio of the infrared image is usually low and the target is moving, which makes most of the existing methods perform inferiorly, especially in very complex scenes. To solve these difficulties, this paper proposes a novel multi-frame spatial–temporal patch-tensor (MFSTPT) model for infrared dim and small target detection from complex scenes. First, the method of simultaneous sampling in spatial and temporal domains is adopted to make full use of the information between multi-frame images, establishing an image-patch tensor model that makes the complex background more in line with the low-rank assumption. Secondly, we propose utilizing the Laplace method to approximate the rank of the tensor, which is more accurate. Third, to suppress strong interference and sparse noise, a prior weighted saliency map is established through a weighted local structure tensor, and different weights are assigned to the target and background. Using an alternating direction method of multipliers (ADMM) to solve the model, we can accurately separate the background and target components and acquire the detection results. Through qualitative and quantitative analysis, experimental results of multiple real sequences verify the rationality and effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

As an emerging nano energy technology, nanogenerators have been developed rapidly, which makes it crucial to analyze the evolutionary pathways of advanced technology in this field to help estimate the development trend and direction. However, some limitations existed in previous studies. On the one hand, previous studies generally made use of the explicit correlation of data such as citation and cooperation between patents and papers, which ignored the rich semantic information contained in them. On the other hand, the progressive evolutionary process from scientific grants to academic papers and then to patents was not considered. Therefore, this paper proposes a novel framework based on a separated three-layer knowledge graph with several time slices using grant data, paper data, and patent data. Firstly, by the representation learning method and clustering algorithm, several clusters representing specific technologies in different layers and different time slices can be obtained. Then, by calculating the similarity between clusters of different layers, the evolutionary pathways of advanced technology from grants to papers and then to patents is drawn. Finally, this paper monitors the pathways of some developed technologies, which evolve from grants to papers and then to patents, and finds some emerging technologies under research. [ABSTRACT FROM AUTHOR]

The impervious surface area (ISA) is a key indicator of urbanization, which brings out serious adverse environmental and ecological consequences. The ISA is often estimated from remotely sensed data via spectral mixture analysis (SMA). However, accurate extraction of ISA using SMA is compromised by two major factors, endmember spectral variability and plant phenology. This study developed a novel approach that incorporates phenology with Fisher transformation into a conventional linear spectral mixture analysis (PF-LSMA) to address these challenges. Four endmembers, high albedo, low albedo, evergreen vegetation, and seasonally exposed soil (H-L-EV-SS) were identified for PF-LSMA, considering the phenological characteristic of Shanghai. Our study demonstrated that the PF-LSMA effectively reduced the within-endmember spectral signature variation and accounted for the endmember phenology effects, and thus well-discriminated impervious surface from seasonally exposed soil, enhancing the accuracy of ISA extraction. The ISA fraction map produced by PF-LSMA (RMSE = 0.1112) outperforms the single-date image Fisher transformed unmixing method (F-LSMA) (RMSE = 0.1327) and the other existing major global ISA products. The PF-LSMA was implemented on the Google Earth Engine platform and thus can be easily adapted to extract ISA in other places with similar climate conditions. [ABSTRACT FROM AUTHOR]

The importance of corporate responsibility for society and environments is emphasized by increasing influence of firms on various stakeholders. Firms strengthen environmental, social, and governance (ESG) activities, which are critical elements for sustainable management. However, there are inconsistent findings on the relationship between ESG activities and firms' financial performance in prior studies because of the lack of full consideration of internal mechanisms and external conditions. To overcome this limitation, this study investigates the mediating effect of non-financial performance and the moderating effect of the institutional environment on the relationship between firms' ESG activities and their financial performance in a unified moderated mediation model. Samples for empirical analyses were collected by a survey from 304 small and medium-sized Chinese manufacturers. The results of a mediation analysis reveal that each ESG activity has a positive effect on firms' financial performance, and the impact of ESG activities on financial performance is completely mediated by non-financial performance. The results of a moderated mediation analysis further indicate that the mediating effect varies depending on the level of institutional pressure from the government, consumers, and competitors. The study suggests the need for interdisciplinary research in sustainable management and institutional theory and emphasizes the importance of sustainable management for performance improvement in a changing environment. [ABSTRACT FROM AUTHOR]

Here, we explored the influences of thyme microcapsules on the growth, gene expression, and histamine accumulation by Proteus bacillus isolated from smoked horsemeat sausage. RT-qPCR was employed to evaluate the gene expression level of histidine decarboxylase (HDC) cascade-associated genes. We used HPLC to monitor histamine concentration both in pure culture as well as in the processing of smoked horsemeat sausage. Results showed that histamine accumulation was suppressed by thyme microcapsule inhibitory effect on the histamine-producing bacteria and the reduction in the transcription of hdcA and hdcP genes. Besides, compared with thyme essential oil (EO), thyme microcapsules exhibited higher antibacterial activity and had a higher score for overall acceptance. Therefore, the addition of thyme microcapsules in Xinjiang smoked horsemeat sausage inhibits histamine accumulation. [ABSTRACT FROM AUTHOR]

Electric buses have many significant advantages, such as zero emissions and low noise and energy consumption, making them play an important role in saving the operation cost of bus companies and reducing urban traffic pollution emissions. Therefore, in recent years, many cities in the world dedicate to promoting the electrification of public transport vehicles. Whereas due to the limitation of on-board battery capacity, the driving range of electric buses is relatively short. The accurate estimation of energy consumption on the electric bus routes is the premise of conducting bus scheduling and optimizing the layout of charging facilities. This study collected the actual operation data of three electric bus routes in Meihekou City, China, and established the support vector machine regression (SVR) model by taking the state of charge (SOC), trip travel time, mean environment temperature and air-conditioning operation time as the independent variables; while the energy consumptions of the route operations served as the dependent variables. Furthermore, the grey wolf optimization (GWO) algorithm was adopted to select the optimal parameters of the proposed model. Finally, a support vector machine regression model based on the grey wolf optimization algorithm (GWO-SVR) is proposed. Three real bus lines were taken as examples to validate the model. The results show that the mean average percentage error is 14.47% and the mean average error is 0.7776. In addition, the estimation accuracy and training time of the proposed model are superior to the genetic algorithm-back propagation neural network model and grid-search support vector machine regression model. [ABSTRACT FROM AUTHOR]