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The Dung Beetle Optimization (DBO) algorithm, a well-established swarm intelligence technique, has shown considerable promise in solving complex engineering design challenges. However, it is hampered by limitations such as suboptimal population initialization, sluggish search speeds, and restricted global exploration capabilities. To overcome these shortcomings, we propose an enhanced version termed Adaptive Spiral Strategy Dung Beetle Optimization (ADBO). Key enhancements include the application of the Gaussian Chaos strategy for a more effective population initialization, the integration of the Whale Spiral Search Strategy inspired by the Whale Optimization Algorithm, and the introduction of an adaptive weight factor to improve search efficiency and enhance global exploration capabilities. These improvements collectively elevate the performance of the DBO algorithm, significantly enhancing its ability to address intricate real-world problems. We evaluate the ADBO algorithm against a suite of benchmark algorithms using the CEC2017 test functions, demonstrating its superiority. Furthermore, we validate its effectiveness through applications in diverse engineering domains such as robot manipulator design, triangular linkage problems, and unmanned aerial vehicle (UAV) path planning, highlighting its impact on improving UAV safety and energy efficiency. [ABSTRACT FROM AUTHOR]

Object detection in aerial images plays a crucial role across diverse domains such as agriculture, environmental monitoring, and security. Aerial images present several challenges, including dense small objects, intricate backgrounds, and occlusions, necessitating robust detection algorithms. This paper addresses the critical need for accurate and efficient object detection in aerial images using a Transformer-based approach enhanced with specialized methodologies, termed DFS-DETR. The core framework leverages RT-DETR-R18, integrating the Cross Stage Partial Reparam Dilation-wise Residual Module (CSP-RDRM) to optimize feature extraction. Additionally, the introduction of the Detail-Sensitive Pyramid Network (DSPN) enhances sensitivity to local features, complemented by the Dynamic Scale Sequence Feature-Fusion Module (DSSFFM) for comprehensive multi-scale information integration. Moreover, Multi-Attention Add (MAA) is utilized to refine feature processing, which enhances the model's capacity for understanding and representation by integrating various attention mechanisms. To improve bounding box regression, the model employs MPDIoU with normalized Wasserstein distance, which accelerates convergence. Evaluation across the VisDrone2019, AI-TOD, and NWPU VHR-10 datasets demonstrates significant improvements in the mean average precision (mAP) values: 24.1%, 24.0%, and 65.0%, respectively, surpassing RT-DETR-R18 by 2.3%, 4.8%, and 7.0%, respectively. Furthermore, the proposed method achieves real-time inference speeds. This approach can be deployed on drones to perform real-time ground detection. [ABSTRACT FROM AUTHOR]

Considering the dilemma of obtaining economic and high-performance composites based on non-polar and main-chain-saturated ethylene propylene diene monomer rubber (EPDM), we proposed an effective and universal filler modification and nanocomposite preparation method. Specifically, the montmorillonite (MMT) surface was coated with polydopamine (PDA) to obtain DMMT, which was confirmed by XRD, XPS, FTIR, and TGA. After compounding DMMT gel with the solid EPDM via the gel compounding method, a silane coupling agent, vinyltrimethoxysilane, was introduced to construct covalent interactions between rubber and filler. Compared with the unmodified MMT filler EPDM, the EPDM/DMMT nanocomposite showed much fewer filler aggregates in the matrix. The highest tensile strength of the composites reached 6.5 MPa with 10 phr DMMT, almost 200% higher than that of pure EPDM. [ABSTRACT FROM AUTHOR]

Natural rubber (NR) composites have been widely applied in damping products to reduce harmful vibrations, while rubber with only a single composition barely meets performance requirements. In this study, rubber blend composites including various ratios of NR and styrene butadiene rubber (SBR) were prepared via the conventional mechanical blending method. The effects of the rubber components on the compression set, compression fatigue temperature rising and the thermal oxidative aging properties of the NR/SBR blend composites were investigated. Meanwhile, the dynamic mechanical thermal analyzer and rubber processing analyzer were used to characterize the dynamic viscoelasticity of the NR/SBR blend composites. It was shown that, with the increase in the SBR ratio, the vulcanization rate of the composites increased significantly, while the compression fatigue temperature rising of the composites decreased gradually from 47 °C (0% SBR ratio) to 31 °C (50% SBR ratio). The compression set of the composites remained at ~33% when the SBR ratio was no more than 20%, and increased gradually when the SBR ratio was more than 20%. [ABSTRACT FROM AUTHOR]

Objective: Metabolic reprogramming serves as a distinctive feature of cancer, impacting proliferation and metastasis, with aberrant glycosphingolipid expression playing a crucial role in malignancy. Nevertheless, limited research has investigated the connection between glycosphingolipid metabolism and pancreatic cancer. Methods: This study utilized a single-cell sequencing dataset to analyze the cell composition in pancreatic cancer tissues and quantified single-cell metabolism using a newly developed computational pipeline called scMetabolism. A gene signature developed from the differential expressed genes (DEGs), related to epithelial cell glycosphingolipid metabolism, was established to forecast patient survival, immune response, mutation status, and reaction to chemotherapy with pancreatic adenocarcinoma (PAAD). Results: The single-cell sequencing analysis revealed a significant increase in epithelial cell proportions in PAAD, with high glycosphingolipid metabolism occurring in the cancerous tissue. A six-gene signature prognostic model based on abnormal epithelial glycosphingolipid metabolism was created and confirmed using publicly available databases. Patients with PAAD were divided into high- and low-risk categories according to the median risk score, with those in the high-risk group demonstrating a more unfavorable survival outcome in all three cohorts, with higher rates of gene mutations (e.g., KRAS, CDKN2A), increased levels of immunosuppressive cells (macrophages, Th2 cells, regulatory T cells), and heightened sensitivity to Acetalax and Selumetinlb. Conclusions: Abnormal metabolism of glycosphingolipids in epithelial cells may promote the development of PAAD. A model utilizing a gene signature associated with epithelial glycosphingolipids metabolism has been established, serving as a valuable indicator for the prognostic stratification of patients with PAAD. [ABSTRACT FROM AUTHOR]

The Dung beetle optimization (DBO) algorithm, devised by Jiankai Xue in 2022, is known for its strong optimization capabilities and fast convergence. However, it does have certain limitations, including insufficiently random population initialization, slow search speed, and inadequate global search capabilities. Drawing inspiration from the mathematical properties of the Sinh and Cosh functions, we proposed a new metaheuristic algorithm, Sinh–Cosh Dung Beetle Optimization (SCDBO). By leveraging the Sinh and Cosh functions to disrupt the initial distribution of DBO and balance the development of rollerball dung beetles, SCDBO enhances the search efficiency and global exploration capabilities of DBO through nonlinear enhancements. These improvements collectively enhance the performance of the dung beetle optimization algorithm, making it more adept at solving complex real-world problems. To evaluate the performance of the SCDBO algorithm, we compared it with seven typical algorithms using the CEC2017 test functions. Additionally, by successfully applying it to three engineering problems, robot arm design, pressure vessel problem, and unmanned aerial vehicle (UAV) path planning, we further demonstrate the superiority of the SCDBO algorithm. [ABSTRACT FROM AUTHOR]

The dung beetle optimization (DBO) algorithm, a swarm intelligence-based metaheuristic, is renowned for its robust optimization capability and fast convergence speed. However, it also suffers from low population diversity, susceptibility to local optima solutions, and unsatisfactory convergence speed when facing complex optimization problems. In response, this paper proposes the multi-strategy improved dung beetle optimization algorithm (MDBO). The core improvements include using Latin hypercube sampling for better population initialization and the introduction of a novel differential variation strategy, termed "Mean Differential Variation", to enhance the algorithm's ability to evade local optima. Moreover, a strategy combining lens imaging reverse learning and dimension-by-dimension optimization was proposed and applied to the current optimal solution. Through comprehensive performance testing on standard benchmark functions from CEC2017 and CEC2020, MDBO demonstrates superior performance in terms of optimization accuracy, stability, and convergence speed compared with other classical metaheuristic optimization algorithms. Additionally, the efficacy of MDBO in addressing complex real-world engineering problems is validated through three representative engineering application scenarios namely extension/compression spring design problems, reducer design problems, and welded beam design problems. [ABSTRACT FROM AUTHOR]

Focused microwave breast hyperthermia (FMBH) employs a phased antenna array to perform beamforming that can focus microwave energy at targeted breast tumors. Selective heating of the tumor endows the hyperthermia treatment with high accuracy and low side effects. The effect of FMBH is highly dependent on the applied phased antenna array. This work investigates the effect of polarizations of antenna elements on the microwave-focusing results by simulations. We explore two kinds of antenna arrays with the same number of elements using different digital realistic human breast phantoms. The first array has all the elements' polarization in the vertical plane of the breast, while the second array has half of the elements' polarization in the vertical plane and the other half in the transverse plane, i.e., cross polarization. In total, 96 sets of different simulations are performed, and the results show that the second array leads to a better focusing effect in dense breasts than the first array. This work is very meaningful for the potential improvement of the antenna array for FMBH, which is of great significance for the future clinical applications of FMBH. The antenna array with cross polarization can also be applied in microwave imaging and sensing for biomedical applications. [ABSTRACT FROM AUTHOR]

FLOWERING LOCUS T (FT), belonging to the FT/TFL1 gene family, is an important gene regulating the flowering transition and inflorescence architecture during plant development. Given its importance to plant adaptation and crop improvement, FT has been extensively studied in related plant research; however, the specific role and underlying molecular mechanisms of FT in the continuous flowering of perennial plants remains elusive. Here, we isolated and characterized homologous FT genes from two Camellia species with different flowering-period phenotypes: CaFT was isolated from Camellia azalea, a precious species blooming in summer and flowering throughout the year, and CjFT was isolated from C. japonica, which blooms in winter and spring. The major difference in the genes between the two species was an additional five-amino acid repeat sequence in C. japonica. FT showed high expression levels in the leaves in both species from January to August, especially in April for C. japonica and in May for C. azalea. CaFT was expressed throughout the year in C. azalea, whereas CjFT was not expressed from September to December in C. japonica. The expression levels of FT in the floral buds were generally higher than those in the leaves. Overexpression of CaFT and CjFT in Arabidopsis indicated that both genes can activate downstream genes to promote flowering. Transgenic callus tissue was obtained by introducing the two genes into C. azalea through Agrobacterium-mediated transformation. Transcriptome and quantitative real-time polymerase chain reaction analyses indicated that both florigen FT genes promoted the expression of downstream genes such as AP1, FUL, and SEP3, and slightly up-regulated the expression of upstream genes such as CO and GI. The above results indicated that CaFT and CjFT played a role in promoting flowering in both camellia species. The expression pattern of CaFT in leaves suggested that, compared to CjFT, CaFT may be related to the annual flowering of C. azalea. [ABSTRACT FROM AUTHOR]

Purpose: Pancreatic cancer (PACA) is one of the most fatal malignancies worldwide. Immunotherapy is largely ineffective in patients with PACA. T-cell exhaustion contributes to immunotherapy resistance. We investigated the prognostic potential of T-cell exhaustion-related genes (TEXGs). Methods: A single-cell RNA (scRNA) sequencing dataset from Tumor Immune Single-Cell Hub (TISCH) and bulk sequencing datasets from the Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) were used to screen differentially expressed TEXGs. Kaplan–Meier survival, LASSO regression, and univariate/multivariate Cox regression analyses were performed to construct a TEXG risk model. This model was used to predict the prognosis, tumor immune microenvironment, and immunotherapy response. The PACA cohorts from the ICGC and GSE71729 datasets were used to validate the risk model. Pan-cancer expression of SPOCK2 was determined using the TISCH database. Results: A six-gene (SPOCK2, MT1X, LIPH, RARRES3, EMP1, and MEG3) risk model was constructed. Patients with low risk had prolonged survival times in both the training (TCGA-PAAD, n = 178) and validation (ICGC-PACA-CA, ICGC-PAAD-US, and GSE71729, n = 412) datasets. Multivariate Cox regression analysis demonstrated that the risk score was an independent prognostic variable for PACA. High-risk patients correlated with their immunosuppressive status. Immunohistochemical staining confirmed the changes in TEXGs in clinical samples. Moreover, pan-cancer scRNA sequencing datasets from TISCH analysis indicated that SPOCK2 may be a novel marker of exhausted CD8+ T-cells. Conclusion: We established and validated a T-cell exhaustion-related prognostic signature for patients with PACA. Moreover, our study suggests that SPOCK2 is a novel marker of exhausted CD8+ T cells. [ABSTRACT FROM AUTHOR]

The long-term durability of polymer components produced by additive manufacturing (AM) in marine conditions is poorly understood. Here, fused filament fabrication (FFF) of Ultem 9085 was conducted and accelerated aging was performed. Two printing orientations (−45/45° and 0/90°) and two sample types (ASTM D638 Type 1 and Type 4) were produced and subjected to accelerated aging in either seawater or air. Results from tensile tests showed that the elastic modulus, yield strength and ultimate tensile strength increased after seawater aging, whereas the elongation to failure decreased. Results of thermogravimetric analysis (TGA) and derivative–TGA curves indicated that hydrolysis occurred after seawater exposure to the polycarbonate (PC) component and changes in structure or hydrogen bonds formed in the polyetherimide (PEI) component. Differential scanning calorimetry showed that physical aging occurred after short exposure periods and low temperature. Longer exposures and higher temperatures resulted in increasing plasticization by water and scission of the PC molecules. Results from Raman suggest that hydrolysis of the PC occurred, with a reduction in free volume produced by physical aging or hydrogen bonding with water molecules. These results highlight that Ultem 9085 is susceptible to degradation in marine environments, and there are two primary mechanisms, including physical and chemical aging. Their specific contribution is highly sensitive to the aging temperature and require careful selection in accelerated aging evaluations. [ABSTRACT FROM AUTHOR]

Vibration isolation and wave manipulation play a significant role in helicopter applications, from small elastic devices for information processing to large solid structures for vibration control. The emergence of topological elastic metamaterials has opened up new possibilities for modulating vibrations and waves in solids. However, most designs are limited to laboratory settings due to complex manufacturing or low structural strength. In this study, we propose a topological elastic metamaterial with a stamping triangle whose orientation θ can be rotated to achieve topological phase transitions between −30° and 30°. Unlike traditional manufacturing methods, the utilization of stamping technology provides a cost-effective means of production, allowing for wider application across diverse industries. Moreover, the metamaterial has the capability to manipulate elastic waves along specific trajectories and effectively decrease common vibrations (more than 50 dB), typically occurring at a frequency of 24 Hz in helicopters. Our approach also enables the control of elastic wave propagation along interfaces through the emergence of topological edge states. The practical implementation of this design will enhance the confidence in using topological elastic metamaterials for vibration isolation and wave manipulation in helicopters. [ABSTRACT FROM AUTHOR]

A comprehensive review of symmetry and conditional symmetry is made from the core conception of symmetry and conditional symmetry. For a dynamical system, the structure of symmetry means its robustness against the polarity change of some of the system variables. Symmetric systems typically show symmetrical dynamics, and even when the symmetry is broken, symmetric pairs of coexisting attractors are born, annotating the symmetry in another way. The polarity balance can be recovered through combinations of the polarity reversal of system variables, and furthermore, it can also be restored by the offset boosting of some of the system variables if the variables lead to the polarity reversal of their functions. In this case, conditional symmetry is constructed, giving a chance for a dynamical system outputting coexisting attractors. Symmetric strange attractors typically represent the flexible polarity reversal of some of the system variables, which brings more alternatives of chaotic signals and more convenience for chaos application. Symmetric and conditionally symmetric coexisting attractors can also be found in memristive systems and circuits. Therefore, symmetric chaotic systems and systems with conditional symmetry provide sufficient system options for chaos-based applications. [ABSTRACT FROM AUTHOR]

With the Internet of Things (IoT) development, there is an increasing demand for multi-service scheduling for Mobile Edge Computing (MEC). We propose using polling for scheduling in edge computing to accommodate multi-service scheduling methods better. Given the complexity of asymmetric polling systems, we have used an information-theoretic approach to analyse the model. Firstly, we propose an asymmetric two-level scheduling approach with priority based on a polling scheduling approach. Secondly, the mathematical model of the system in the continuous time state is established by using the embedded Markov chain theory and the probability-generating function. By solving for the probability-generating function's first-order partial and second-order partial derivatives, we calculate the exact expressions of the average queue length, the average polling period, and the average delay with an approximate analysis of periodic query way. Finally, we design a simulation experiment to verify that our derived parameters are correct. Our proposed model can better differentiate priorities in MEC scheduling and meet the needs of IoT multi-service scheduling. [ABSTRACT FROM AUTHOR]

Confined catalytic realms and synergistic catalysis sites were constructed using bimetallic active centers in two-dimensional metal-organic frameworks (MOFs) to achieve highly selective oxygenation of cycloalkanes and alkyl aromatics with oxygen towards partly oxygenated products. Every necessary characterization was carried out for all the two-dimensional MOFs. The selective oxygenation of cycloalkanes and alkyl aromatics with oxygen was accomplished with exceptional catalytic performance using two-dimensional MOF Co-TCPPNi as a catalyst. Employing Co-TCPPNi as a catalyst, both the conversion and selectivity were improved for all the hydrocarbons investigated. Less disordered autoxidation at mild conditions, inhibited free-radical diffusion by confined catalytic realms, and synergistic C–H bond oxygenation catalyzed by second metal center Ni employing oxygenation intermediate R–OOH as oxidant were the factors for the satisfying result of Co-TCPPNi as a catalyst. When homogeneous metalloporphyrin T(4-COOCH3)PPCo was replaced by Co-TCPPNi, the conversion in cyclohexane oxygenation was enhanced from 4.4% to 5.6%, and the selectivity of partly oxygenated products increased from 85.4% to 92.9%. The synergistic catalytic mechanisms were studied using EPR research, and a catalysis model was obtained for the oxygenation of C–H bonds with O2. This research offered a novel and essential reference for both the efficient and selective oxygenation of C–H bonds and other key chemical reactions involving free radicals. [ABSTRACT FROM AUTHOR]

As an essential element of higher education, course planning at the program level is a complicated multi-criteria decision making (MCDM) problem. In addition, a course planning process tailored to sustainable development is exceptionally important to sustaining the quality of academic programs. However, there is a scarcity of research on the program course planning problem at the operational level due to a diverse set of stakeholder requirements in practice. Motivated by the challenge, this study proposes an innovative MCDM model for sustainable course planning based on He-Xie management theory. In the introduced framework, the best worst method (BWM) can obtain the optimal weights of sustainability competencies, which are then embedded into the fuzzy filter ranking (FFR) method to generate the ranking of candidate courses by each course module, considering the connectivity between courses and the development of sustainability competencies. Finally, multi-choice goal programming (MCGP) is adopted to allocate each selected course to a semester, aiming to balance total credits and average difficulty level among semesters as much as possible. The practicability and reliability of the proposed course planning model is validated through a case study of an undergraduate accounting program. Results show that the proposed framework is a feasible tool for course planning. This research extends the existing literature on course planning by explicitly capturing the fuzzy nature of human decision making and avoids underestimation of the decision. The implications of the paper are not restricted to developing a sustainable course plan for an accounting program. [ABSTRACT FROM AUTHOR]

Sonchus arvensis Linn. and Hemerocallis citrina Baroni. have been reported to improve body resistance. However, the underlying mechanism is not clear. In this study, Sonchus arvensis Linn. phenolic compounds (SAP) and Hemerocallis citrina Baroni. phenolic compounds (HCP) were extracted and their protective effects in Caenorhabditis elegans evaluated. SAP and HCP showed considerably different phenolic compositions. In the normal C. elegans model, HCP exhibited better effects in promoting growth than SAP. In the sucrose-incubated C. elegans model, both SAP and HCP showed positive effects against the high-sucrose-induced damage. In the stearic acid-incubated C. elegans model, both SAP and HCP improved lifespan, reproductive ability and growth, while HCP had a more evident effect than SAP on reproductive ability. The TGF-β signaling pathway was confirmed to be involved in the protective effects of SAP and HCP. The antioxidant ability of SAP was also found to be related to skn-1. Our study shows that both SAP and HCP have protective effects against high sucrose- or high stearic acid-induced damage. [ABSTRACT FROM AUTHOR]

One of the challenges in developing practical CO2 photoconversion catalysts is the design of materials with a low cost, high activity and good stability. In this paper, excellent photocatalysts based on TiO2, WO3, ZnO, Cu2O and CeO2 metal oxide materials, which are cost-effective, long-lasting, and easy to fabricate, are evaluated. The characteristics of the nanohybrid catalysts depend greatly on their architecture and design. Thus, we focus on outstanding materials that offer effective and practical solutions. Strategies to improve CO2 conversion efficiency are summarized, including heterojunction, ion doping, defects, sensitization and morphology control, which can inspire the future improvement in photochemistry. The capacity of CO2 adsorption is also pivotal, which varies with the morphological and electronic structures. Forms of 0D, 1D, 2D and 3DOM (zero/one/two-dimensional- and three-dimensional-ordered macroporous, respectively) are involved. Particularly, the several advantages of the 3DOM material make it an excellent candidate material for CO2 conversion. Hence, we explain its preparation method. Based on the discussion, new insights and prospects for designing high-efficient metallic oxide photocatalysts to reduce CO2 emissions are presented. [ABSTRACT FROM AUTHOR]

Porous organic polymers (POPs) have attracted much attention in numerous areas, including catalysis, adsorption and separation. Herein, POP supported Ziegler–Natta catalysts were designed for preparation of isotactic polypropylene (iPP). The POPs-based Ziegler–Natta catalysts exhibited the characteristic of broad molecular weight distribution (MWD > 11) with or without adding an extra internal electron donor. The added internal electron donor 3-methyl-5-tert-butyl-1,2-phenylene dibenzoate (ID-2) used in cat-2 showed good propylene polymerization activity of 15.3 × 106 g·PP/mol·Ti·h, high stereoregularity with 98.2% of isotacticity index and broad molecular weight distribution (MWD) of 12.3. Compared to the MgCl2-supported Ziegler–Natta catalysts (cat-4) with the same ID-2, cat-2 showed higher chain stereoregularity for propylene polymerization. As seen in the TREF results, the elution peak of PP-2 (124.0 °C, 91.7%) is 1.5 °C higher than the isotactic fraction from PP-4 (122.5 °C, 87.2%), and even 1.2 °C higher than PP-5 prepared from ID-3 with the characteristics of high stereoregularity. Moreover, the pentad methyl sequence mmmm of PP-2 (93.0%) from cat-2 is 0.5% higher than that of PP-4 from cat-4. XPS analysis revealed that the minute difference in binding energy of Ti, Mg, C and O atoms exist between the inorganic MgCl2 and the organic polymer based Z–N catalysts. The plausible interaction mechanism of active sites of Mg and Ti with the functional groups in the POP support and the added ID was proposed, which could be explained by their high stereoregularity and the broad molecular weight distribution of the POP-based Z–N catalysts. [ABSTRACT FROM AUTHOR]

In recent years, federated learning has been able to provide an effective solution for data privacy protection, so it has been widely used in financial, medical, and other fields. However, traditional federated learning still suffers from single-point server failure, which is a frequent issue from the centralized server for global model aggregation. Additionally, it also lacks an incentive mechanism, which leads to the insufficient contribution of local devices to global model training. In this paper, we propose a blockchain-based decentralized federated learning method, named BD-FL, to solve these problems. BD-FL combines blockchain and edge computing techniques to build a decentralized federated learning system. An incentive mechanism is introduced to motivate local devices to actively participate in federated learning model training. In order to minimize the cost of model training, BD-FL designs a preference-based stable matching algorithm to bind local devices with appropriate edge servers, which can reduce communication overhead. In addition, we propose a reputation-based practical Byzantine fault tolerance (R-PBFT) algorithm to optimize the consensus process of global model training in the blockchain. Experiment results show that BD-FL effectively reduces the model training time by up to 34.9% compared with several baseline federated learning methods. The R-PBFT algorithm can improve the training efficiency of BD-FL by 12.2%. [ABSTRACT FROM AUTHOR]

In this study, a gas chromatography–mass spectrometry (GC-MS) method was established for the determination of zearalenone and its five derivatives in feed, including zearalanone, α-zearalanol, β-zearalanol, α-zearalenol, and β-zearalenol. An effective immunoaffinity column was prepared for sample purification, which was followed by the silane derivatization of the eluate after an immunoaffinity chromatography analysis for target compounds by GC-MS. Matrix effects were corrected by an isotope internal standard of zearalenone in this method. The six analytes had a good linear relationship in the range of 2–500 ng/mL, and the correlation coefficients were all greater than 0.99. The limits of detection (LODs) and limits of quantification (LOQs) were less than 1.5 μg/kg and 5.0 μg/kg, respectively. The average spike recoveries for the six feed matrices ranged from 89.6% to 112.3% with relative standard deviations (RSDs) less than 12.6%. Twenty actual feed samples were analyzed using the established method, and at least one target was detected. The established GC-MS method was proven to be reliable and suitable for the determination of zearalenone and its derivatives in feed. [ABSTRACT FROM AUTHOR]

With the booming development of Internet of Things (IoT) and computer vision technology, running vision-based applications on IoT devices becomes an overwhelming tide. In vision-based applications, the Automatic License Plate Recognition (ALPR) is one of the fundamental services for smart-city applications such as traffic control, auto-drive and safety monitoring. However, existing works about ALPR usually assume that IoT devices have sufficient power to transmit the whole captured stream to edge servers via stable network links. Considering the limited resources of IoT devices and high-dynamic wireless links, this assumption is not suitable for realizing an efficient ALPR service on low-power IoT devices in real wireless edge networks. In this paper, we propose a link-aware frame selection scheme for ALPR service in dynamic edge networks aiming to reduce the transmission energy consumption of IoT devices. Specifically, we tend to select a few key frames instead of the whole stream and transmit them under good links. We propose a two-layer recognition frame selection algorithm to optimize the frame selection by exploiting both the video content variation and real-time link quality. The extensive results show that, by carefully selecting the offloaded frames to edge servers, our algorithm can significantly reduce the energy consumption of devices by 46.71 % and achieve 97.95 % recognition accuracy in the high-dynamic wireless link of the edge network. [ABSTRACT FROM AUTHOR]

The skin friction of a hypersonic vehicle surface can account for up to 50% of the total resistance, directly affecting the vehicle's effective range and load. A wind tunnel experiment is an important and effective method to optimize the aerodynamic shape of aircraft, and Micro-Electromechanical System (MEMS) skin friction sensors are considered the promising sensors in hypersonic wind tunnel experiments, owing to their miniature size, high sensitivity, and stability. However, the sensitive structure including structural appearance, a gap with the package shell, and flatness of the sensor will change the measured flow field and cause the accurate measurement of friction resistance. Aiming at the influence of sensor-sensitive structure on wall-flow characteristics and friction measurement accuracy, the two-dimensional and three-dimensional numerical models of the sensor in the hypersonic flow field based on Computational Fluid Dynamics (CFD) are presented respectively in this work. The model of the sensor is verified by using the Blathius solution of two-dimensional laminar flow on a flat plate. The results show that the sensor model is in good agreement with the Blathius solution, and the error is less than 0.4%. Then, the influence rules of the sensitive structure of the sensor on friction measurement accuracy under turbulent flow and laminar flow conditions are systematically analyzed using 3D numerical models of the sensor, respectively. Finally, the sensor-sensitive unit structure's design criterion is obtained to improve skin friction's measurement accuracy. [ABSTRACT FROM AUTHOR]

In this study, a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for simultaneous determination of deoxynivalenol, aflatoxin B1, zearalenone, ochratoxin A, T-2 toxin and fumonisin B1 in feed and feedstuff was established. The sample was extracted with an acetonitrile–water mixture (60:40, v/v), purified by an immunoaffinity column, eluted with a methanol–acetic acid mixture (98:2, v/v), and reconstituted with a methanol–water mixture (50:50, v/v) after drying with nitrogen. Finally, the reconstituted solution was detected by LC-MS/MS and quantified by isotope internal standard method. The six mycotoxins had a good linear relationship in a certain concentration range, the correlation coefficients were all greater than 0.99, the limits of detection were between 0.075 and 1.5 µg·kg−1, and the limits of quantification were between 0.5 and 5 µg·kg−1. The average spike recoveries in the four feed matrices ranged from 84.2% to 117.1% with relative standard deviations less than 11.6%. Thirty-six actual feed samples were analyzed for mycotoxins, and at least one mycotoxin was detected in each sample. The proposed method is reliable and suitable for detecting common mycotoxins in feed samples. [ABSTRACT FROM AUTHOR]

Simple Summary: The Bombyx mori nucleopolyhedrovirus (BmNPV) is a typical model baculovirus, representing one of the major pathogens of the silkworm. We reconstituted the virus in vitro and used it as a bait for immunoprecipitation experiments on cells and silkworm bodies, obtaining a database of proteins potentially interacting with BmNPV. This study provides a protein data reference for the screening of BmNPV receptors and the study of proteins that play a key role in the replication of BmNPV. It is also important to deal with the prevention of BmNPV in silkworms at the molecular level. Virus–host interactions are critical for virus replication, virulence, and pathogenicity. The Bombyx mori nucleopolyhedrovirus (BmNPV) is a typical model baculovirus, representing one of the most common and harmful pathogens in sericulture. Herein, we used co-immunoprecipitation to identify candidate proteins with potential interactions with BmNPV. First, a recombinant BV virus particle rBmBV-egfp-p64-3×flag-gp64sp was constructed using a MultiBac baculovirus multigene expression system. Co-immunoprecipitation experiments were then performed with the recombinant BV virus infected with BmN cells and Dazao silkworms. LC-MS/MS analysis revealed a total of 845 and 1368 candidate proteins were obtained from BmN cells and silkworm samples, respectively. Bioinformatics analysis (Gene Ontology, KEGG Pathway) was conducted for selection of proteins with significant enrichment for further confirmation of the effects on BmNPV replication. Overall, the results showed that SEC61 and PIC promoted the replication of BmNPV, while FABP1 inhibited the replication of BmNPV. In summary, this study reveals the potential proteins involved in BmNPV invasion and proliferation in the host and provides a platform for identifying the potential receptor proteins of BmNPV. [ABSTRACT FROM AUTHOR]

Lactoferrin (Ltf), a naturally active glycoprotein, possesses anti-inflammatory, anti-microbial, anti-tumor, and immunomodulatory activities. Many published studies have indicated that Ltf modulates the proliferation of stem cells. However, the role of Ltf in the proliferation of satellite cells, an important cell type in muscle regeneration, has not yet been reported. Here, by using Ltf systemic knockout mice, we illustrate the role of Ltf in skeletal muscle. Results shows that Ltf deficiency impaired proliferation of satellite cells (SCs) and the regenerative capability of skeletal muscle. Mechanistic studies showed that ERK1/2 phosphorylation was significantly downregulated after Ltf deletion in SCs. Simultaneously, the cell cycle-related proteins cyclin D and CDK4 were significantly downregulated. Intervention with exogenous recombinant lactoferrin (R-Ltf) at a concentration of 1000 μg/mL promoted proliferation of SCs. In addition, intraperitoneal injection of Ltf effectively ameliorated the skeletal muscle of mice injured by 1.2% BaCl2 solution. Our results suggest a protective effect of Ltf in the repair of skeletal muscle damage. Ltf holds promise as a novel therapeutic agent for skeletal muscle injuries. [ABSTRACT FROM AUTHOR]

In order to explore the aging process and mechanism of new and old asphalt in plant hot-mix recycled asphalt mixture during the mixing and use process, the liquid viscosity test and low-temperature bending creep test are carried out to test the dynamic viscosity, stiffness modulus, creep rate, and low-temperature flexibility of the matrix asphalt, recycled asphalt, and old and new asphalt after rolling thin film oven test (RTFOT) aging and pressurized aging vessel (PAV) aging. The macroscopic performance attenuation law of new and old asphalt during the aging process in thermal regeneration is compared and analyzed. After that, the aging process and mechanism of new and old asphalt are explored by infrared spectroscopy and differential calorimetric analysis scanning. The results show that RTFOT aging and PAV aging make the viscosity of recycled asphalt rise significantly and the low temperature performance decline rapidly. After RTFOT aging and PAV aging of new and old asphalt, the dynamic viscosity and low-temperature performance change range is much higher than that of the matrix asphalt. Some technical indicators are even closer to the recycled asphalt after aging, which proves that its aging speed is faster than that of the matrix asphalt. Meanwhile, the results of infrared spectroscopy and differential scanning calorimetry analysis show that in addition to the independent aging of new asphalt and recycled asphalt, there is also a chemical effect between them–that is, some active groups in recycled asphalt have a more obvious promotion effect on the aging process of new asphalt, here called "induced aging". This induced aging changes the aging mechanism of the matrix asphalt by changing the aging process of it, which greatly limits the popularization and application of thermal regeneration technology. [ABSTRACT FROM AUTHOR]

Porous organic polymers (POPs) are widely used in various areas such as adsorption, separation and catalysis. In the present work, ionic liquid-modified porous organic polymers (IL-POPs) synthesized by dispersion polymerization were applied to immobilize metallocene catalysts for olefin polymerization. The prepared IL-POPs were characterized by Fourier transform infrared spectrometer (FT-IR), nitrogen sorption porosimetry, X-ray photoelectron spectroscopy (XPS), thermal gravimetric analysis (TGA), inductively coupled plasma atomic emission spectrometer (ICP) and scanning electron microscope (SEM) analysis. The IL-POPs obtained pores with surface specific area (SSA) ranging from 16.9 m2/g to 561.8 m2/g, and total pore volume (TPV) ranging from 0.08 cm3/g to 0.71 cm3/g. The supported catalysts Zr/MAO@IL-POPs exhibit great activity (3700 kg PE/mol·Zr·bar·h) in ethylene polymerization, and the GPC-IR results show that the polyethylene has narrow molecular weight distribution (2.2 to 2.8). The DSC results show that the melting point of prepared polyethylene was as high as 138 °C, and the TREF analysis results indicate that they have similar chemical composition distribution with elution temperature at 100.5–100.7 °C. [ABSTRACT FROM AUTHOR]

An improved method based on the Hybrid Finite Element-Statistical Energy Analysis (FE-SEA) method and quasi-steady state theory is proposed to predict the response of spacecraft structure during the process of pyrotechnics separation. Firstly, the amplitude–frequency value of shock load is obtained by using time-frequency conversion technology. Then, according to the frequency response characteristics of each part of the spacecraft structure, a more accurate hybrid FE-SEA model is established. The piecewise loading method is used to predict the response of the hybrid model. Finally, the time domain response results are reconstructed, and the shock response spectrum (SRS) is calculated. Based on the test system of simulating pyroshock, the shock experiment of spacecraft structure is conducted. The high frequency and high velocity character of pyroshock could be effectively simulated, and an accurate shock force function could be obtained through the experiment. This indicates that the numerical results are in line with the ones of the experiment. The SRS obtained from experiments and calculations have similar trends and amplitudes. This conclusion verifies the rationality and sufficient accuracy of the novel method in this paper. The novel method presented in this paper greatly improves the computational efficiency. At the same time, it provides theoretical guidance for shock response prediction of spacecraft structure by steady-state methods. [ABSTRACT FROM AUTHOR]

Chaotic systems without equilibrium are of interest because they are the systems with hidden attractors. A nonequilibrium system with chaos is introduced in this work. Chaotic behavior of the system is verified by phase portraits, Lyapunov exponents, and entropy. We have implemented a real electronic circuit of the system and reported experimental results. By using this new chaotic system, we have constructed S-boxes which are applied to propose a novel image encryption algorithm. In the designed encryption algorithm, three S-boxes with strong cryptographic properties are used for the sub-byte operation. Particularly, the S-box for the sub-byte process is selected randomly. In addition, performance analyses of S-boxes and security analyses of the encryption processes have been presented. [ABSTRACT FROM AUTHOR]

Systems with many equilibrium points have attracted considerable interest recently. A chaotic system with a line equilibrium has been studied in this work. The system has infinite equilibria and exhibits coexisting chaotic attractors. The system with an infinite number of equilibria has been realized by an electronic circuit, which confirms the feasibility of the system. Based on such a system, we have developed a new S-Box generation algorithm. With the developed algorithm, two new S-Boxes are produced. Performance tests of S-Boxes are performed. The tests have shown that proposed S-Boxes have good performance results. [ABSTRACT FROM AUTHOR]

This paper investigates the F – M synchronization between non-identical fractional-order systems characterized by different dimensions and different orders. F – M synchronization combines the inverse generalized synchronization with the matrix projective synchronization. In particular, the proposed approach enables the F – M synchronization to be achieved between an n-dimensional master system and an m-dimensional slave system. The developed approach is applied to chaotic and hyperchaotic fractional systems with the aim of illustrating its applicability and suitability. A multiple-input multiple-output (MIMO) secure communication system is also developed by using the F – M synchronization and verified through computer simulations. [ABSTRACT FROM AUTHOR]

The initiating explosive shock environment of an aerospace mission has the characteristics of instantaneity, high amplitude and a wide frequency domain. An improved method based on the acceleration frequency response function (FRF) and virtual mode synthesis method (VMSS) is proposed to predict the pyroshock response of a spacecraft structure in a wide frequency domain. Firstly, the statistical energy analysis (SEA) model of the spacecraft structure was established, and the FRF and modal density of the model were obtained. Then, the paper explains how, due to the small number of modes in the low-frequency band, the calculation results of the SEA method in the low-frequency band were not accurate enough. The FRF of the SEA model in the low-frequency band was modified by an FRF test of the structure. Finally, the shock response spectrum (SRS) was obtained based on the VMSS and the modified FRF. A shock experiment on the spacecraft structure was conducted by using the shock experiment system, which is based on a light-gas gun. The accurate shock force function and acceleration response results were obtained. The numerical results based on the improved method are in line with those in the experiment. This verifies that the novel method can better grasp the response characteristics of the structure in the broadband domain. The novel method effectively improves the response prediction accuracy of the SEA model in the relatively low-frequency band. While ensuring the computational efficiency, more accurate shock response results in a wide frequency domain were obtained. The novel method presented in this paper provides support of numerical analysis for pyroshock response prediction of spacecraft structure in a wide frequency domain. [ABSTRACT FROM AUTHOR]

Micro-electromechanical system (MEMS) skin friction sensors are considered to be promising sensors in hypersonic wind tunnel experiments owing to their miniature size, high sensitivity, and stability. Aiming at the problem of short test duration (a few milliseconds) and heavy load in a shock wind tunnel, the fast readout circuit and the sensor head structures of a MEMS skin friction sensor are presented and optimized in this work. The sensor was fabricated using various micro-mechanical processes and micro-assembly technology based on visual alignment. Meanwhile, the sensor head structure was integrated with the fast readout circuit and tested by using a centrifugal force equivalent method. The calibration results show that this sensor provides good linearity, sensitivity, and stability. The measurement ranges are 0–2000 Pa with good performance. The resolution is better than 10 Pa at 3000 Hz detection frequency of the readout circuit for the sensor in ranges from 0 to 1000 Pa. In addition, the repeatability and linearity of static calibration for sensors are better than 1%. [ABSTRACT FROM AUTHOR]

The baculovirus display system (BDS), an excellent eukaryotic surface display technology that offers the advantages of safety, efficiency, and economy, is widely used in biomedicine. A previous study using rBacmid-Δgp64-ires-gp64 expressed in low copy numbers of the gp64 gene achieved high-efficiency expression and co-display of three fluorescent proteins (GFP, YFP, and mCherry). However, low expression of GP64 in recombinant baculoviruses also reduces the efficiency of recombinant baculovirus transduction into mammalian cells. In addition, the baculovirus promoter has no expression activity in mammalian cells and thus cannot meet the application requirements of baculoviral vectors for the BDS. Based on previous research, this study first determined the expression activity of promoters in insect Spodoptera frugiperda 9 cells and mammalian cells and successfully screened the very early promoter pie1 to mediate the co-expression of multiple genes. Second, utilizing the envelope display effect of the INVASIN and VSVG proteins, the efficiency of transduction of recombinant baculovirus particles into non-host cells was significantly improved. Finally, based on the above improvement, a recombinant baculovirus vector displaying four antigen proteins with high efficiency was constructed. Compared with traditional BDSs, the rBacmid-Δgp64 system exhibited increased display efficiency of the target protein by approximately 3-fold and induced an approximately 4-fold increase in the titer of serum antibodies to target antigens in Bal B/c mice. This study systematically explored the application of a new multi-gene co-display technology applicable to multi-vaccine research, and the results provide a foundation for the development of novel BDS technologies. [ABSTRACT FROM AUTHOR]

The survival and sustainability of regional species is constrained by habitat quality. In recent decades, the intensification of human activities on a global scale has had a profound impact on regional ecosystems and poses a serious threat to regional sustainable development. Scientific measurement of the drivers of habitat quality can provide important support for the development of effective biodiversity conservation and sustainable land-use policies. Taking the Hung River Valley as an example, the InVEST model was used to assess the habitat quality of the study area in 2000, 2005, 2010, 2015, and 2020 and to explore its spatial and temporal variation and distribution characteristics in combination with the spatial autocorrelation model, and the geographically weighted regression (GWR) model was used to explore the drivers of habitat quality change. The results show the following: (1) The overall habitat quality shows an increasing trend during 2000–2020, but the expansion of construction land in the central region plays a dominant role in the degradation of regional habitat quality. (2) The "Guide-Ledu" line is the dividing line of habitat quality in the Hung River Valley, with a general distribution of "south is good, north is bad" and "south is hot, north is cold". (3) Natural factors such as slope and elevation basically shape the overall distribution pattern of habitat quality, while urbanisation factors such as population density, gross domestic product, and the night-time lighting index are generally negatively correlated with habitat quality. The results of the study can reveal the linkage between ecosystems and land-use change in the context of urbanisation. [ABSTRACT FROM AUTHOR]

Developing sustainable routes for the synthesis of zeolites is still a vital and challenging task in zeolite scientific community. One of the typical examples is sustainable synthesis of aluminosilicate EU-1 zeolite, which is not very efficient and environmental-unfriendly under hydrothermal condition due to the use of a large amount of water as solvent. Herein, we report a sustainable synthesis route for aluminosilicate EU-1 zeolite without the use of solvent for the first time. The physicochemical properties of the obtained EU-1 zeolite are characterized by powder X-ray diffraction (XRD), scanning electron microscopy (SEM), thermogravimetry-differential thermal analysis (TG-DTA), N2 sorption, inductively coupled plasma (ICP) analysis, and solid nuclear magnetic resonance (NMR), which show the product has high crystallinity, uniform morphology, large BET surface area, and four-coordinated aluminum species. Moreover, the impact of synthesis conditions is investigated in detail. The sustainable synthesis of aluminosilicate EU-1 zeolite under solvent-free [ABSTRACT FROM AUTHOR]

Porous organic polymers (POPs) have proven to be an efficient support in the olefin polymerization catalyst field. In this paper, nano TiO2 beads were used to modulate the pore structure, bulk density, and surface morphology and flowability of the prepared POPs. With the incorporation of the hydrophilic nano TiO2 beads, the prepared TiO2/POP supports obtained reasonable specific surface area (100–300 m2/g) and higher bulk density (0.26–0.35 g/mL) and flowability than the pure POP supports. The results show that bulk density of the prepared TiO2/POP particles increased when adding an increased amount of TiO2, and when 37.5% TiO2 (weight percent to the total comonomers divinylbenzene (DVB) and 2-hydroxyethyl methacrylate (HEMA)) and 3:1 DVB/HEMA (molar ratio) were added, highly flowable TiO2/POP composites (POP-6 and POP-7) were obtained. With the modulation of the nano TiO2 template during the support synthesis, the prepared POP-7 particles successfully achieved a normal distribution with a narrow particle size distribution (PSD) of 0.717 and average particle size of 24.1 μm, a specific surface area (SSA) of 279 m2/g, and relatively high bulk density of 0.30 g/mL. Furthermore, all the prepared TiO2/POP supports obtained higher ethylene polymerization activity than silica gel-supported commercial metallocene catalyst. The immobilized (n-BuCp)2ZrCl2/MAO@POP-7 catalyst exhibited the highest ethylene polymerization activity of 4794 kg PE/mol Zr.bar.h and productivity of 389 g PE/g cat, more than twice that of the commercial counterpart. Even higher catalyst productivity (3197 g PE/g cat) and bulk density of the produced PE (0.36 g/mL) could be obtained in higher ethylene partial pressure at 80 °C for 2 h, and the prepared TiO2/POP catalyst shows no obvious Zr+ active sites decay during the ethylene polymerization. [ABSTRACT FROM AUTHOR]

(1) Background: A suitable scaffold with adapted mechanical and biological properties for ligament tissue engineering is still missing. (2) Methods: Different scaffold configurations were characterized in terms of morphology and a mechanical response, and their interactions with two types of stem cells (Wharton's jelly mesenchymal stromal cells (WJ-MSCs) and bone marrow mesenchymal stromal cells (BM-MSCs)) were assessed. The scaffold configurations consisted of multilayer braids with various number of silk layers (n = 1, 2, 3), and a novel composite scaffold made of a layer of copoly(lactic acid-co-(e-caprolactone)) (PLCL) embedded between two layers of silk. (3) Results: The insertion of a PLCL layer resulted in a higher porosity and better mechanical behavior compared with pure silk scaffold. The metabolic activities of both WJ-MSCs and BM-MSCs increased from day 1 to day 7 except for the three-layer silk scaffold (S3), probably due to its lower porosity. Collagen I (Col I), collagen III (Col III) and tenascin-c (TNC) were expressed by both MSCs on all scaffolds, and expression of Col I was higher than Col III and TNC. (4) Conclusions: the silk/PLCL composite scaffolds constituted the most suitable tested configuration to support MSCs migration, proliferation and tissue synthesis towards ligament tissue engineering. [ABSTRACT FROM AUTHOR]

Land cover is an important variable of the terrestrial ecosystem that provides information for natural resources management, urban sprawl detection, and environment research. To classify land cover with high-spatial-resolution multispectral remote sensing imagery is a difficult problem due to heterogeneous spectral values of the same object on the ground. Fully convolutional networks (FCNs) are a state-of-the-art method that has been increasingly used in image segmentation and classification. However, a systematic quantitative comparison of FCNs on high-spatial-multispectral remote imagery was not yet performed. In this paper, we adopted the three FCNs (FCN-8s, Segnet, and Unet) for Gaofen-2 (GF2) satellite imagery classification. Two scenes of GF2 with a total of 3329 polygon samples were used in the study area and a systematic quantitative comparison of FCNs was conducted with red, green, blue (RGB) and RGB+near infrared (NIR) inputs for GF2 satellite imagery. The results showed that: (1) The FCN methods perform well in land cover classification with GF2 imagery, and yet, different FCNs architectures exhibited different results in mapping accuracy. The FCN-8s model performed best among the Segnet and Unet architectures due to the multiscale feature channels in the upsampling stage. Averaged across the models, the overall accuracy (OA) and Kappa coefficient (Kappa) were 5% and 0.06 higher, respectively, in FCN-8s when compared with the other two models. (2) High-spatial-resolution remote sensing imagery with RGB+NIR bands performed better than RGB input at mapping land cover, and yet the advantage was limited; the OA and Kappa only increased an average of 0.4% and 0.01 in the RGB+NIR bands. (3) The GF2 imagery provided an encouraging result in estimating land cover based on the FCN-8s method, which can be exploited for large-scale land cover mapping in the future. [ABSTRACT FROM AUTHOR]

Polypropylene (PP) is one of the most widely used polymers. In this paper, three types of PPs including random PP, impact PP, and impact PP with high clarity, were prepared through a 75 kg/h pilot-scale Spheripol II process. The three produced PPs were produced by the selection or combination the two loops and gas phase reactor and controlling the comonomer and hydrogen concentrations. The three prepared PPs then were pelleted with the clarified nucleating agent NX 8000 and tested for mechanical, thermal, and optical properties. Their molecular structures and rubber phase size were also investigated by GPC, 13C NMR, temperature rising elution fractionation (TREF), XRD, SEM analysis, etc. The results showed that the random PP (PP-1) and the impact PP with high clarity (PP-3) obtained excellent optical transparency with a haze of 12.5% and 13.5% due to their small rubber phase size (roughly ≤ 100 nm), while the impact PP (PP-2) obtained bad transparency with a haze of 98.8% due to the large rubber phase size (about 1 μm) caused by the poor thermal compatibility with the PP matrix. The rubber phase content and ethylene/propylene sequence distributions of the three PPs varied much and resulted in different impact strengths and stiffness properties. PP-2 had a high impact strength of 14.5 kJ/m2 due to the rubber phase generated in the gas phase reactor. Except for the optical transparency, PP-3 gained stiffness and toughness, with 914 MPa of flexural modulus and 25.1 kJ/m2 of impact strength due to the unique molecular structure of its rubber phase. [ABSTRACT FROM AUTHOR]

Canopy cover is an important vegetation attribute used for many environmental applications such as defining management objectives, thinning and ecological modeling. However, the estimation of canopy cover from high spatial resolution imagery is still a difficult task due to limited spectral information and the heterogeneous pixel values of the same canopy. In this paper, we compared the capacity of two high spatial resolution sensors (SPOT6 and GF2) using three ensemble learning models (Adaptive Boosting (AdaBoost), Gradient Boosting (GDBoost), and random forest (RF)), to estimate canopy cover (CC) in a Chinese northern subtropics forest. Canopy cover across 97 plots was measured across 41 needle forest plots, 24 broadleaf forest plots, and 32 mixed forest plots. Results showed that (1) the textural features performed more importantly than spectral variables according to the number of variables in the top ten predictors in estimating canopy cover (CC) in both SPOT6 and GF2. Moreover, the vegetation indices in spectral variables had a lower relative importance value than the band reflectance variables. (2) GF2 imagery outperformed SPOT6 imagery in estimating CC when using the ensemble learning model in our data. On average across the models, the R2 was almost 0.08 higher for GF2 over SPOT6. Likewise, the average RMSE and average MAE were 0.002 and 0.01 lower in GF2 than in SPOT6. (3) The ensemble learning model showed good results in estimating CC, yet the different models performed a little differently in the results. Additionally, the GDBoost model performed the best of all the ensemble learning models with R2 = 0.92, root mean square error (RMSE) = 0.001 and mean absolute error (MAE) = 0.022. [ABSTRACT FROM AUTHOR]

The application potential of nanoscale zero valent iron (nZVI) in wastewater treatment is huge and has attracted a lot of attention. In this study, the composite material BC-nZVI was prepared by emulsion of nZVI and biomass-activated carbon (BC) under the mechanical agitation condition, and was characterized by SEM-EDX, XRD, XPS, and FTIR. The decontamination abilities of BC-nZVI were tested by the removal of total chromium (Cr) from electroplating wastewater. The results showed that the removal efficiencies of Cr in the electroplating wastewater by nZVI particles can be effectively improved when supported with BC, but cannot be improved in its storage capacity. The chemical adsorption process between the Cr and BC-nZVI is the main rate-limiting step in the removal of total Cr from wastewater, and multiple parameters such as dosage, pH, and initial concentration of Cr was found to affect the rate. [ABSTRACT FROM AUTHOR]

Polyolefin is the most widely used and versatile commodity polymer. In this work, three types of polyolefin-based elastomers (PBEs) were adopted to toughen a high-flow polypropylene to improve its overall performance. The chain microstructures of these PBEs, including ethylene/1-octene (E/O) random copolymer from Dow Chemical′s polyolefin elastomer (POE), olefin block copolymers (OBCs) of E/O from Dow, and ethylene/propylene random copolymer from ExxonMobil's propylene-based elastomer, were elucidated by GPC, 13C NMR, TREF, and DSC techniques. The mechanical, thermal and optical properties, and morphology analysis of the PP/PBE blends were also studied to investigate the toughening mechanism of these PBEs. The results showed that all three types of PBEs can effectively improve the Izod impact strength of the PP/PBE blends by the addition of the rubber compositions, at the cost of the stiffness. PBE-1 and PBE-2 were found to have a great stiffness–toughness balance with about 1700 MPa of flexural modulus, about 110 °C of HDT and 3.6 kJ/m2 of impact strength on the prepared PP/PBE blends by forming separated rubber phase and refined spherulite crystals. As a result, the OBC with alternating hard and soft segments could achieve a similar toughening effect as the E/P random copolymer. Surprisingly, no obvious rubber phase separation was observed in the PP/PBE-4 blend, which might be due to the good compatibility of the E/P random chains with the isotactic PP; therefore, the PP/PBE blend obtains great toughness performance and optical transparency with the highest Izod impact strength of 4.2 kJ/m2 and excellent transparency. [ABSTRACT FROM AUTHOR]

MEMS-based skin friction sensors are used to measure and validate skin friction and its distribution, and their advantages of small volume, high reliability, and low cost make them very important for vehicle design. Aiming at addressing the accuracy problem of skin friction measurements induced by existing errors of sensor fabrication and assembly, a novel fabrication technology based on visual alignment is presented. Sensor optimization, precise fabrication of key parts, micro-assembly based on visual alignment, prototype fabrication, static calibration and validation in a hypersonic wind tunnel are implemented. The fabrication and assembly precision of the sensor prototypes achieve the desired effect. The results indicate that the sensor prototypes have the characteristics of fast response, good stability and zero-return; the measurement ranges are 0–100 Pa, the resolution is 0.1 Pa, the repeatability accuracy and linearity are better than 1%, the repeatability accuracy in laminar flow conditions is better than 2% and it is almost 3% in turbulent flow conditions. The deviations between the measured skin friction coefficients and numerical solutions are almost 10% under turbulent flow conditions; whereas the deviations between the measured skin friction coefficients and the analytical values are large (even more than 100%) under laminar flow conditions. The error resources of direct skin friction measurement and their influence rules are systematically analyzed. [ABSTRACT FROM AUTHOR]

Detecting microbial interactions is essential to the understanding of the structure and function of the gut microbiome. In this study, microbial co-occurrence patterns were inferred using a random matrix theory based approach in the gut microbiome of mice in response to chondroitin sulfate disaccharide (CSD) under healthy and stressed conditions. The exercise stress disrupted the network composition and microbial co-occurrence patterns. Thirty-four Operational Taxonomic Units (OTU) were identified as module hubs and connectors, likely acting as generalists in the microbial community. Mucispirillumschaedleri acted as a connector in the stressed network in response to CSD supplement and may play a key role in bridging intimate interactions between the host and its microbiome. Several modules correlated with physiological parameters were detected. For example, Modules M02 (under stress) and S05 (stress + CSD) were strongly correlated with blood urea nitrogen levels (r = 0.90 and −0.75, respectively). A positive correlation between node connectivity of the OTUs assigned to Proteobacteria with superoxide dismutase activities under stress (r = 0.57, p < 0.05) provided further evidence that Proteobacteria can be developed as a potential pathological marker. Our findings provided novel insights into gut microbial interactions and may facilitate future endeavor in microbial community engineering. [ABSTRACT FROM AUTHOR]

A map without equilibrium has been proposed and studied in this paper. The proposed map has no fixed point and exhibits chaos. We have investigated its dynamics and shown its chaotic behavior using tools such as return map, bifurcation diagram and Lyapunov exponents' diagram. Entropy of this new map has been calculated. Using an open micro-controller platform, the map is implemented, and experimental observation is presented. In addition, two control schemes have been proposed to stabilize and synchronize the chaotic map. [ABSTRACT FROM AUTHOR]

Today, four-dimensional chaotic systems are attracting considerable attention because of their special characteristics. This paper presents a non-equilibrium four-dimensional chaotic system with hidden attractors and investigates its dynamical behavior using a bifurcation diagram, as well as three well-known entropy measures, such as approximate entropy, sample entropy, and Fuzzy entropy. In order to stabilize the proposed chaotic system, an adaptive radial-basis function neural network (RBF-NN)–based control method is proposed to represent the model of the uncertain nonlinear dynamics of the system. The Lyapunov direct method-based stability analysis of the proposed approach guarantees that all of the closed-loop signals are semi-globally uniformly ultimately bounded. Also, adaptive learning laws are proposed to tune the weight coefficients of the RBF-NN. The proposed adaptive control approach requires neither the prior information about the uncertain dynamics nor the parameters value of the considered system. Results of simulation validate the performance of the proposed control method. [ABSTRACT FROM AUTHOR]