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In addition to their practical and aesthetic qualities, ceramic teapots are highly decorative and stylish. Based on the theory of perceptual engineering, this study employs eye-tracking technology and semantic-difference methods to investigate user preferences for ceramic teapot shapes. Using eye-movement experiments, the study first determines users' visual attention to different morphological regions. Using the orthogonal alignment method, nine styling samples were developed by combining expert classification of classic and traditional teapot styling elements. By combining a semantic perception questionnaire with a satisfaction questionnaire, the study evaluated users' visual attention to these samples and their satisfaction with them. It was found that shapes characterized by classic, rounded, and proportional coordination were more in line with consumers' aesthetic preferences despite the differences in semantic evaluations among consumers of different genders and ages, which led to relatively consistent consumer satisfaction. The purpose of this study is not only to provide a scientific basis for styling ceramic teapots but also to assist designers in grasping the laws of consumer preference in order to create better products. [ABSTRACT FROM AUTHOR]

To tackle the issue of poor accuracy in single-snapshot data processing for Direction of Arrival (DOA) estimation in passive radar systems, this paper introduces a method for judiciously leveraging multi-snapshot data. This approach effectively enhances the accuracy of DOA estimation and spatial angle resolution in passive radar systems. Additionally, in response to the non-convex nature of the mixed norm, we propose a hyperbolic tangent model as a replacement, transforming the problem into a directly solvable convex optimization problem. The rationality of this substitution is thoroughly demonstrated. Lastly, through a comparative analysis with existing discrete grid DOA estimation methods, we illustrate the superiority of the proposed approach, particularly under conditions of medium signal-to-noise ratio, varying numbers of snapshots, and close target angles. This method is less affected by the number of array elements, and is more usable in practices verified in real-world scenarios. [ABSTRACT FROM AUTHOR]

Large TiN inclusions in nickel-based superalloys promote micropore formation, compromising the mechanical properties of the alloys. However, current research lacks a comprehensive coupled model that considers both solute element microsegregation and TiN precipitation specifically in nickel-based superalloys. This study investigated TiN precipitation during the solidification of IN718 alloys through a combined thermodynamic and kinetic approach. A modified Clyne–Kurz model was applied to account for multi-element microsegregation, enabling an integrated analysis of both microsegregation and precipitation processes. The results indicated that solute elements in the molten alloy segregated to varying degrees during solidification. At an initial nitrogen concentration of 25 ppm, TiN inclusions precipitated when the solid fraction reached 0.256, eventually resulting in a total TiN precipitation of 64 ppm by the end of solidification, while residual nitrogen in the liquid phase decreased to 1.3 ppm. Increasing the initial nitrogen concentration from 10 ppm to 40 ppm advanced the onset of TiN precipitation and raised the total amount from 16 ppm to 126 ppm. Further analysis indicated that cooling rates of 0.03 °C/s, 0.06 °C/s, and 0.18 °C/s did not significantly affect the final TiN accumulation. [ABSTRACT FROM AUTHOR]

High-internal-phase water-in-oil (W/O) emulsions generated in situ have garnered considerable attention as novel profile control systems. However, conventional emulsifiers are unreactive and poorly dispersed in water, necessitating large dosages and resulting in poor injectivity. In this study, we synthesized amphiphilic nanoparticles (SiO2–NH2–DAC NPs) containing amine and long-chain alkyl groups using a one-pot method and investigated the stabilized emulsion properties. Our results indicated that W/O emulsions with a water-to-oil ratio (WOR) of 7:3 to 8:2 could be prepared with just 0.1 wt% of SiO2–NH2–DAC NPs under neutral and basic conditions, with demulsification occurring under acidic conditions (pH = 2.1), demonstrating the pH-responsiveness of the W/O emulsions. The emulsion viscosity increased from 150 to 2555 mPa·s at different WORs. An additional 18.7% oil recovery was achieved using SiO2–NH2–DAC NPs in a heterogeneous core, highlighting their potential as a promising profile control candidate. [ABSTRACT FROM AUTHOR]

Accurate and timely extraction and evaluation of sandy land are essential for ecological environmental protection; it is urgent to do the research to support the sustainable development goals (SDGs) of Land Degradation Neutrality. This study used Sentinel-1 Synthetic Aperture Radar (SAR) data and Landsat 8 OLI multispectral data as the main data sources. Combining the rich spectral information from optical data and the penetrating advantages of radar data, a feature-level fusion method was employed to unveil the intrinsic nature of vegetative cover and accurately identify sandy land. Simultaneously, leveraging the results obtained from training with measured data, a comprehensive desertification assessment model was proposed, which combines multiple indicators to achieve a thorough evaluation of sandy land. The results showed that the method based on feature-level fusion achieved an overall accuracy of 86.31% in sandy land detection in Gansu Province, China. The integrated multi-indicator model C22_C/FVC is the ratio of correlation texture features of VH to vegetation cover based on which sandy land can be classified into three categories. When C22_C/FVC is less than 2.2, the pixel is classified as fixed sandy land. Pixels of semi-fixed sandy land have an indicator value between 2.2 and 5.2. Shifting sandy land has values greater than 5.2. Results showed that shifting sandy land and semi-fixed sandy land are the predominant types in Gansu Province, with 85,100 square kilometers and 87,100 square kilometers, respectively. The acreage of fixed sandy land was the least, 51,800 square kilometers. The method presented in this paper is robust for the detection and evaluation of sandy land from satellite imageries, which can potentially be applied for conducting high-resolution and large-scale detection and evaluation of sandy land. [ABSTRACT FROM AUTHOR]

Due to its distinctive structure and unique physicochemical properties, gallium nitride (GaN) has been considered a prospective candidate for lithium storage materials. However, its inferior conductivity and unsatisfactory cycle performance hinder the further application of GaN as a next-generation anode material for lithium-ion batteries (LIBs). To address this, cobalt (Co)-doped GaN (Co-GaN) nanowires have been designed and synthesized by utilizing the chemical vapor deposition (CVD) strategy. The structural characterizations indicate that the doped Co elements in the GaN nanowires exist as Co2+ rather than metallic Co. The Co2+ prominently promotes electrical conductivity and ion transfer efficiency in GaN. The cycling capacity of Co-GaN reached up to 495.1 mA h g−1 after 100 cycles. After 500 cycles at 10 A g−1, excellent cycling capacity remained at 276.6 mA h g−1. The intimate contact between Co-GaN nanowires and carbon paper enhances the conductivity of the composite. Density functional theory (DFT) calculations further illustrated that Co substitution changed the electron configuration in the GaN, which led to enhancement of the electron transfer efficiency and a reduction in the ion diffusion barrier on the Co-GaN electrode. This doping design boosts the lithium-ion storage performance of GaN as an advanced material in lithium-ion battery anodes and in other electrochemical applications. [ABSTRACT FROM AUTHOR]

This paper, grounded in the Stimulus–Organism–Response (SOR) model and event system theory, examines the mechanisms through which public recognition—specifically novel, disruptive, and critical recognition—of the intensity of food safety incidents influences willingness to engage in food safety governance. Risk perception is identified as a mediating variable, while risk communication serves as a moderating variable. Based on survey data, the study found that various forms of public recognition significantly impact governance willingness. Furthermore, risk perception plays a crucial mediating role, and risk communication has a notable moderating effect on the relationship between risk perception and food safety governance willingness. These findings illuminate the intrinsic connection between public recognition of food safety incidents and governance willingness, offering robust theoretical support and practical guidance for enhancing food safety governance. This research contributes to the ongoing improvement and optimization of food safety governance systems. [ABSTRACT FROM AUTHOR]

Glucocorticoids are known to influence hippocampal function, but their rapid non-genomic effects on specific neurons in the hippocampal trisynaptic circuit remain underexplored. This study investigated the immediate effects of glucocorticoids on CA1 and CA3 pyramidal neurons, and dentate gyrus (DG) granule neurons in rats using the patch-clamp technique. We found that a 5 min extracellular application of corticosterone significantly reduced action potential firing frequency in CA1 pyramidal neurons, while no effects were observed in CA3 or DG neurons. The corticosterone-induced inhibition in CA1 was blocked by the glucocorticoid receptor antagonist CORT125281, but remained unaffected by the mineralocorticoid receptor antagonist spironolactone. Notably, membrane-impermeable bovine serum albumin-conjugated dexamethasone mimicked corticosterone's effects on CA1 neurons, which exhibited prominent hyperpolarization-activated cyclic nucleotide-gated (HCN) channel currents. Pyramidal neurons in CA3 and granular neurons in the DG showed little HCN channel currents. Corticosterone enhanced HCN channel activity in CA1 neurons via glucocorticoid receptors, and the HCN channel inhibitor ZD7288 abolished corticosterone's suppressive effects on action potentials. These findings suggest that glucocorticoids selectively inhibit CA1 pyramidal neuron activity through HCN channels, providing new insight into the mechanisms of glucocorticoid action in hippocampal circuits. [ABSTRACT FROM AUTHOR]

Encouraging cities to take the lead in achieving carbon peak and carbon neutrality holds significant global implications for addressing climate change. However, existing studies primarily focus on the urban scale, lacking more comprehensive county-level analyses, which hampers the effective implementation of differentiated carbon mitigation policies. Therefore, this study focused on the Pearl River Delta urban agglomeration in China, adopting nighttime light data and socio-economic spatial data to estimate carbon emissions at the county level. Furthermore, trend analysis, spatial autocorrelation analysis, and Geodetector were adopted to elucidate the spatiotemporal patterns and influencing factors of county-level carbon emissions. Carbon emissions were predominantly concentrated in the counties on the eastern bank of the Pearl River Estuary. Since 2010, there has been a deceleration in the growth rate of carbon emissions in the region around the Pearl River Estuary, with some counties exhibiting declining trends. Throughout the study period, construction land expansion consistently emerged as a predominant factor driving carbon emission growth. Additionally, foreign direct investment, urbanization, and fixed asset investment each significantly contributed to the increased carbon emissions during different development periods. [ABSTRACT FROM AUTHOR]

A two-dimensional (2D) piston electro-hydraulic pump has been proposed further to enhance the power density of the electro-hydraulic pump. The 2D piston pump, characterized by high power density and a slender shape, is embedded within the stator of the motor in a co-rotor configuration where the piston and the motor's rotor are in tandem. The intimate design of the hydraulic pump and the motor results in a coupling between the two, with intricate relationships and influences existing between the geometric parameters of the piston pump and the dimensions of the motor's rotor. Based on the operational requirements and structure of the 2D piston pump, a permanent magnet synchronous motor (PMSM) designed for use with a 2D piston electro-hydraulic pump is developed. This study examines the impact of the motor's stator iron core geometric parameters on both the electromagnetic and mechanical properties of a PMSM and completes the necessary performance validations. The optimization objectives of the motor are determined through an analysis of the influence of the key parameters of the rotor and stator on torque, torque ripple, and motor loss. A surrogate optimization model is constructed using a metamodel of optimal prognosis (MOP) to optimize the torque, torque ripple, and motor loss. Evolutionary genetic algorithms are utilized to achieve the multi-objective optimization design. A finite element simulation is used to compare the electromagnetic performance of the initial motor and optimal motor. Based on the optimal motor parameters, a 2.5 kW motor prototype is manufactured, and the experimental results validate the feasibility and effectiveness of the motor design and optimization. [ABSTRACT FROM AUTHOR]

In the post-pandemic era, public space safety has emerged as a central public concern. As global public health awareness rose, traditional manual cleaning methods were increasingly inadequate for large-scale and high-standard cleaning requirements. Therefore, the design of a commercial cleaning robot that combined cleaning efficiency, environmental performance, and sustainability was essential to meet evolving societal demands. This paper systematically gathered and analyzed commercial cleaning robot functional requirements through a comprehensive investigation. According to the Kano model, functional requirements were categorized by attributes and their importance was quantified. Subsequently, using the QFD model, the design requirements for commercial cleaning robots were determined, and their significance weights were established. This identified the key design requirements. The results of this study indicated that the integration of the Kano and QFD models provided a novel perspective for the design of functional integration in commercial cleaning robots. Furthermore, it provided a practical methodological framework for addressing similar issues in the future. [ABSTRACT FROM AUTHOR]

Powdery mildew infection is a significant challenge in butternut squash (Cucurbita moschata) production during winter in Hainan, China. The tropical climate of Hainan promotes powdery mildew infection, resulting in substantial yield losses. By utilizing transcriptome and genome sequencing data, SNPs and potential genes associated with powdery mildew resistance in butternut squash were identified. The analysis of differentially expressed genes (DEGs) following powdery mildew infection revealed several genes involved in resistance, with particular focus on a resistance (R) gene cluster that may be linked to the observed resistance. Two MLO genes in clade V from Cucurbita moschata may not be directly associated with resistance in the two genotypes studied. These findings are expected to contribute to the development of genetic tools for improving powdery mildew resistance in Cucurbita crops, thereby reducing yield losses and enhancing the sustainability of butternut squash production in Hainan and other regions. [ABSTRACT FROM AUTHOR]

The field of evolutionary multitasking optimization (EMTO) has been a highly anticipated research topic in recent years. EMTO aims to utilize evolutionary algorithms to concurrently solve complex problems involving multiple tasks. Despite considerable advancements in this field, numerous evolutionary multitasking algorithms continue to use a single evolutionary search operator (ESO) throughout the evolution process. This strategy struggles to completely adapt to different tasks, consequently hindering the algorithm's performance. To overcome this challenge, this paper proposes multitasking evolutionary algorithms via an adaptive bi-operator strategy (BOMTEA). BOMTEA adopts a bi-operator strategy and adaptively controls the selection probability of each ESO according to its performance, which can determine the most suitable ESO for various tasks. In an experiment, BOMTEA showed outstanding results on two well-known multitasking benchmark tests, CEC17 and CEC22, and significantly outperformed other comparative algorithms. [ABSTRACT FROM AUTHOR]

In industrial production, the identification and characterization of micron-sized second phases, such as carbonitrides in alloys, hold significant importance for optimizing alloy compositions and processes. However, conventional methods based on threshold segmentation suffer from drawbacks, including low accuracy, inefficiency, and subjectivity. Addressing these limitations, this study introduced a carbonitride instance segmentation model tailored for various nickel-based superalloys. The model enhanced the YOLOv8n network structure by integrating the SPDConv module and the P2 small target detection layer, thereby augmenting feature fusion capability and small target detection performance. Experimental findings demonstrated notable improvements: the mAP50 (Box) value increased from 0.676 to 0.828, and the mAP50 (Mask) value from 0.471 to 0.644 for the enhanced YOLOv8n model. The proposed model for carbonitride detection surpassed traditional threshold segmentation methods, meeting requirements for precise, rapid, and batch-automated detection in industrial settings. Furthermore, to assess the carbonitride distribution homogeneity, a method for quantifying dispersion uniformity was proposed and integrated into a data processing framework for seamless automation from prediction to analysis. [ABSTRACT FROM AUTHOR]

Lithium-ion batteries are widely applied in the form of new energy electric vehicles and large-scale battery energy storage systems to improve the cleanliness and greenness of energy supply systems. Accurately estimating the state of power (SOP) of lithium-ion batteries ensures long-term, efficient, safe and reliable battery operation. Considering the influence of the parameter identification accuracy on the results of state of power estimation, this paper presents a systematic review of model parameter identification and state of power estimation methods for lithium-ion batteries. The parameter identification methods include the voltage response curve analysis method, the least squares method and so on. On this basis, the methods used for modeling and estimating the SOP of battery cells and battery packs are classified and elaborated, focusing on summarizing the research progress observed regarding the joint estimation method for multiple states of battery cells. In conclusion, future methods for estimating the SOP of lithium-ion batteries and their improvement targets are envisioned based on the application requirements for the safe management of lithium-ion batteries. [ABSTRACT FROM AUTHOR]

This experimental study investigated the influence of different turbine guide vane parameters on the ignition limit and light-round processes in a triple-dome combustor. It was found that for the triple-dome combustor, the minimum fuel/air ratios at the ignition limit all show a trend of initial decrease followed by subsequent increase with the growth of incoming air mass flow rate. The ignition fuel/air ratio decreases with the increase in turbine blockage ratio, and the optimal scheme is achieved with a blockage ratio of 0.8. Under the condition where the incoming air mass flow rate is 0.089 kg/s, the light-round time decreases with the increase in fuel/air ratio, and the light-round time of the combustor without guide vanes is shorter than that of the other schemes. With the increase in incoming air mass flow rate, the light-round time of the schemes with guide vanes is shortened. Under the same incoming air mass flow rate and fuel/air ratio, the increase in the blockage ratio will lead to an increase in the light-round time of the triple-dome combustor. [ABSTRACT FROM AUTHOR]

Highly integrated energy systems are on the rise due to increasing global demand. To capture the underlying physics of such interdisciplinary systems, we need a modern framework that unifies all forms of energy. Here, we apply modified Lagrangian mechanics to the description of multi-energy systems. Based on the minimum entropy production principle, we revisit fluid mechanics in the presence of both mechanical and thermal dissipations and propose using exergy flow as the unifying Lagrangian across different forms of energy. We illustrate our theoretical framework by modeling a one-dimensional system with coupled electricity and heat. We map the exergy loss rate in real space and obtain the total exergy changes. Under steady-state conditions, our theory agrees with the traditional formula but incorporates more physical considerations such as viscous dissipation. The integral form of our theory also allows us to go beyond steady-state calculations and visualize the local, time-dependent exergy flow density everywhere in the system. Expandable to a wide range of applications, our theoretical framework provides the basis for developing versatile models in integrated energy systems. [ABSTRACT FROM AUTHOR]

Exopolysaccharides (EPSs) are carbohydrate polymers that are synthesized and secreted into the extracellular during the growth of microorganisms. Bacillus thuringiensis (Bt) is a type of entomopathogenic bacterium, that produces various insecticidal proteins and EPSs. In our previous study, the EPSs produced by Bt strains were first found to enhance the toxicity of insecticidal crystal proteins against Plutella xylostella. However, the response of the intestinal bacterial communities of P. xylostella under the action of EPSs is still unelucidated. In this study, 16S rRNA amplicon sequencing was used to characterize the intestinal bacterial communities in P. xylostella treated with EPSs alone, Cry1Ac protoxin alone, and both the Cry1Ac protoxin and EPSs. Compared with the control group, alpha diversity indices, the Chao1 and ACE indices were significantly altered after treatment with EPSs alone, and no significant difference was observed between the groups treated with Cry1Ac protoxin alone and Cry1Ac protoxin + EPSs. However, compared with the gut bacterial community feeding on Cry1Ac protoxin alone, the relative abundance of 31 genera was significantly changed in the group treated with Cry1Ac protoxin and EPSs. The intestinal bacteria, through the oral of Cry1Ac protoxin and EPSs, significantly enhanced the toxicity of the Cry1Ac protoxin towards the axenic P. xylostella. In addition, the relative abundance of the 16S rRNA gene in the chloroplasts of Brassica campestris decreased after adding EPSs. Taken together, these results show the vital contribution of the gut microbiota to the Bt strain-killing activity, providing new insights into the mechanism of the synergistic insecticidal activity of Bt proteins and EPSs. [ABSTRACT FROM AUTHOR]

As one of the most important food crops, the potato is widely planted in the oasis agricultural region of Northwest China. To ascertain the impact of regulated deficit irrigation (RDI) on various facets including dry matter accumulation, tuber yield, quality and water use efficiency (WUE) of potato plants, a two-growth season field experiment under mulched drip irrigation was conducted in the desert oasis region of Northwest China. Water deficits, applied at the seedling, tuber formation, tuber expansion and starch accumulation stages, encompassed two distinctive levels: mild (55–65% of field capacity, FC) and moderate (45–55% FC) deficit, with full irrigation (65–75% FC) throughout the growing season as the control (CK). The results showed that water deficit significantly reduced (p < 0.05) above-ground dry matter, water consumption and tuber yield compared to CK, and the reduction increased with the increasing water deficit. A mild water deficit at the tuber formation stage, without significantly reducing (p > 0.05) yield, could significantly increase WUE and irrigation water use efficiency (IWUE), with two-year average increases of 25.55% and 32.33%, respectively, compared to CK. Water deficit at the tuber formation stage increased starch content, whereas water deficit at tuber expansion stage significantly reduced starch, protein and reducing sugar content. Additionally, a comprehensive evaluation showed that a mild water deficit at the tuber formation stage is the optimal RDI strategy for potato production, providing a good balance between yield, quality and WUE. The results of this study can provide theoretical support for efficient and sustainable potato production in the desert oasis regions of Northwest China. [ABSTRACT FROM AUTHOR]

In the passive bistatic radar (PBR) system, methods exist to address the issue of detecting weak targets without being influenced by non-ideal factors from adjacent strong targets. These methods utilize the sparsity in the delay-Doppler domain of the cross ambiguity function (CAF) to detect weak targets. However, the modeling and solving of this method involve substantial memory consumption and computational complexity. To address these challenges, this paper establishes a target detection model for PBR based on batch processing of sparse representation and recovery. This model partitions the CAF into blocks, identifies blocks requiring processing based on the presence of targets, and improves the construction and utilization of the measurement matrix. This results in a reduction in the computational complexity and memory resource requirements for sparse representation and recovery, and provides favorable conditions for parallel execution of the algorithm. Experimental results indicate that the proposed approach increases the number of blocks by a factor of four, and reduces the number of real multiplications by approximately an order of magnitude. Hence, compared with the traditional approach, the proposed approach enables fast and stable detection of weak targets. [ABSTRACT FROM AUTHOR]

This paper proposes a new type of omnidirectional mobile robot for land and air, which has three motion modes, combines the motion characteristics of land motion and air flight, has the ability to climb walls, and can be actively deformed to adapt to the working conditions according to the current working environment. The robot incorporates an innovative "rotor blade–single row omnidirectional wheel" composite structure, which is mainly characterized by a single row of continuous switching wheels covering the outside of each rotor blade, and does not need to provide additional power when moving on the ground and walls, relying on the driving force generated by the rotor blades to drive the continuous switching wheels driven by the rotor blades. This structure can effectively combine the land movement mode, wall crawling mode, and air flight mode, which reduces the energy consumption of the robot without increasing the weight, and we design a deformation device that can realize the transformation of the three modes into each other. This paper mainly focuses on the design of the robot structure and the analysis of the movement method, and the land omnidirectional movement experiments, wall crawling experiments, and air flight experiments were, respectively, carried out, and the results show that the proposed land and air omnidirectional mobile robot has the ability to adapt to the movement of each scene, and improves the upper limit of the robot's operation. [ABSTRACT FROM AUTHOR]

As important auxiliary equipment, rehabilitation robots are widely used in rehabilitation treatment and daily life assistance. The rehabilitation robot proposed in this paper is mainly composed of an omnidirectional mobile platform module, a lower limb exoskeleton module, and a support module. According to the characteristics of the robot's omnidirectional mobility and good stiffness, the overall kinematic model of the robot is established using the analytical method. Passive and active training control strategies for an omnidirectional mobile lower limb exoskeleton robot are proposed. The passive training mode facilitates the realization of the goal of walking guidance and assistance to the human lower limb. The active training mode can realize the cooperative movement between the robot and the human through the admittance controller and the tension sensor and enhance the active participation of the patient. In the simulation experiment, a set of optimal admittance parameters was obtained, and the parameters were substituted into the controller for the prototype experiment. The experimental results show that the admittance-controlled rehabilitation robot can perceive the patient's motion intention and realize the two walking training modes. In summary, the passive and active training control strategies based on admittance control proposed in this paper achieve the expected purpose and effectively improve the patient's active rehabilitation willingness and rehabilitation effect. [ABSTRACT FROM AUTHOR]

The Mongolian gerbil is a distinctive experimental animal in China, as its genetic qualities possess significant value in the field of medical biology research. Here, we aimed to establish an economical and efficient panel for genetic quality detection in Mongolian gerbils using single-nucleotide polymorphism (SNP) markers. To search for SNPs, we conducted whole-genome sequencing (WGS) in 40 Mongolian gerbils from outbred populations. Reliable screening criteria were established to preliminarily select SNPs with a wide genome distribution and high levels of polymorphism. Subsequently, a multiple-target regional capture detection system based on second-generation sequencing was developed for SNP genotyping. Based on the results of WGS, 219 SNPs were preliminarily selected, and they were established and optimized in a multiple-amplification system that included 206 SNP loci by genotyping three outbred populations. PopGen.32 analysis revealed that the average effective allele number, Shannon index, observed heterozygosity, expected heterozygosity, average heterozygosity, polymorphism information content, and other population genetic parameters of the Capital Medical University (CMU) gerbils were the highest, followed by those of Zhejiang gerbils and Dalian gerbils. Through scientific screening and optimization, we successfully established a novel, robust, and cost-effective genetic detection system for Mongolian gerbils by utilizing SNP markers for the first time. [ABSTRACT FROM AUTHOR]

Wind turbine blades are the core components responsible for efficient wind energy conversion and ensuring stability. To address challenges in wind turbine blade damage detection using image processing techniques such as complex image backgrounds, decreased detection performance due to high image resolution, prolonged inference time, and insufficient recognition accuracy, this study introduces an enhanced wind turbine blade damage detection model named WTDB-YOLOv8. Firstly, by incorporating the GhostCBS and DFSB-C2f modules, the aim is to reduce the number of model parameters while enhancing feature extraction capability. Secondly, by integrating the MHSA-C2f module, which incorporates a multi-head self-attention mechanism, the focus on global information is enabled, thereby mitigating irrelevant background interference and reducing the impact of complex backgrounds on damage detection. Lastly, adopting the Mini-BiFPN structure improves the retention of features for small target objects in shallow networks and reinforces the propagation of these features in deep networks, thereby enhancing the detection accuracy of small target damage and reducing false negative rates. Through training and testing on the Wind Turbine Blade Damage Dataset (WTBDD), the WTDB-YOLOv8 model achieves an average precision of 98.3%, representing a 2.2 percentage point improvement over the original YOLOv8 model. Particularly noteworthy is the increase in precision from 93.1% to 97.9% in small target damage detection. Moreover, the total parameter count of the model decreases from 3.22 million in YOLOv8 to 1.99 million, marking a reduction of 38.2%. Therefore, the WTDB-YOLOv8 model not only enhances the detection performance and efficiency of wind turbine blade damage but also significantly reduces the model parameter count, showcasing its practical advantages in engineering applications. [ABSTRACT FROM AUTHOR]

Recombinant adeno-associated virus (rAAV) has emerged as a prominent vector for in vivo gene therapy, owing to its distinct advantages. Accurate determination of the rAAV genome titer is crucial for ensuring the safe and effective administration of clinical doses. The evolution of the rAAV genome titer assay from quantitative PCR (qPCR) to digital PCR (dPCR) has enhanced accuracy and precision, yet practical challenges persist. This study systematically investigated the impact of various operational factors on genome titration in a single-factor manner, aiming to address potential sources of variability in the quantitative determination process. Our findings revealed that a pretreatment procedure without genome extraction exhibits superior precision compared with titration with genome extraction. Additionally, notable variations in titration results across different brands of dPCR instruments were documented, with relative standard deviation (RSD) reaching 23.47% for AAV5 and 11.57% for AAV8. Notably, optimal operations about DNase I digestion were identified; we thought treatment time exceeding 30 min was necessary, and there was no need for thermal inactivation after digestion. And we highlighted that thermal capsid disruption before serial dilution substantially affected AAV genome titers, causing a greater than ten-fold decrease. Conversely, this study found that additive components of dilution buffer are not significant contributors to titration variations. Furthermore, we found that repeated freeze–thaw cycles significantly compromised AAV genome titers. In conclusion, a comprehensive dPCR titration protocol, incorporating insights from these impact factors, was proposed and successfully tested across multiple serotypes of AAV. The results demonstrate acceptable variations, with the RSD consistently below 5.00% for all tested AAV samples. This study provides valuable insights to reduce variability and improve the reproducibility of AAV genome titration using dPCR. [ABSTRACT FROM AUTHOR]

Bacillus thuringiensis (Bt) secretes the nutritional insecticidal protein Vip3Aa11, which exhibits high toxicity against the fall armyworm (Spodoptera frugiperda). The Bt HD270 extracellular polysaccharide (EPS) enhances the toxicity of Vip3Aa11 protoxin against S. frugiperda by enhancing the attachment of brush border membrane vesicles (BBMVs). However, how EPS-HD270 interacts with Vip3Aa11 protoxin in vivo and the effect of EPS-HD270 on the toxicity of activated Vip3Aa11 toxin are not yet clear. Our results indicated that there is an interaction between mannose, a monosaccharide that composes EPS-HD270, and Vip3Aa11 protoxin, with a dissociation constant of Kd = 16.75 ± 0.95 mmol/L. When EPS-HD270 and Vip3Aa11 protoxin were simultaneously fed to third-instar larvae, laser confocal microscopy observations revealed the co-localization of the two compounds near the midgut wall, which aggravated the damage to BBMVs. EPS-HD270 did not have a synergistic insecticidal effect on the activated Vip3Aa11 protein against S. frugiperda. The activated Vip3Aa11 toxin demonstrated a significantly reduced binding capacity (548.73 ± 82.87 nmol/L) towards EPS-HD270 in comparison to the protoxin (34.96 ± 9.00 nmol/L). Furthermore, this activation diminished the affinity of EPS-HD270 for BBMVs. This study provides important evidence for further elucidating the synergistic insecticidal mechanism between extracellular polysaccharides and Vip3Aa11 protein both in vivo and in vitro. [ABSTRACT FROM AUTHOR]

Aimed at the problem of human–machine interaction between patients and robots in the process of using rehabilitation robots for rehabilitation training, this paper proposes a human–machine interactive control method based on an independently developed upper limb rehabilitation robot. In this method, the camera is used as a sensor, the human skeleton model is used to analyse the moving image, and the key points of the human body are extracted. Then, the three-dimensional coordinates of the key points of the human arm are extracted by depth estimation and spatial geometry, and then the real-time motion data are obtained, and the control instructions of the robot are generated from it to realise the real-time interactive control of the robot. This method can not only improve the adaptability of the system to individual patient differences, but also improve the robustness of the system, which is less affected by environmental changes. The experimental results show that this method can realise real-time control of the rehabilitation robot, and that the robot assists the patient to complete the action with high accuracy. The results show that this control method is effective and can be applied to the fields of robot control and robot-assisted rehabilitation training. [ABSTRACT FROM AUTHOR]

As an important cereal crop, maize is a versatile and multi-purpose crop, primarily used as a feed globally, but also is important as a food crop, and has other uses such as oil and industrial raw materials. Quality detection is an indispensable part of functional and usage classification, avoiding significant waste as well as increasing the added value of the product. The research on algorithms for real-time, accurate, and non-destructive identification and localization of corn kernels based on quality classification and equipped with non-destructive algorithms suitable for embedding in intelligent agricultural machinery systems is a key step in improving the effective utilization rate of maize kernels. The difference in maize kernel quality leads to significant differences in price and economic benefits. This algorithm reduced unnecessary waste caused by the low efficiency and accuracy of manual and mechanical detection. Image datasets of four kinds of maize kernel quality were established and each image contains a total of about 20 kernels of different quality randomly distributed. Based on the self-built dataset, the YOLOv7-tiny, as the backbone network, was used to design a maize kernel detection and recognition model named "YOLOv7-MEF". Firstly, the backbone feature layer of the algorithm was replaced by MobileNetV3 as the feature extraction backbone network. Secondly, ESE-Net was used to enhance feature extraction and obtain better generalization performance. Finally, the loss function was optimized and replaced with the Focal-EOIU loss function. The experiment showed that the improved algorithm achieved an accuracy of 98.94%, a recall of 96.42%, and a Frame Per Second (FPS) of 76.92 with a model size of 9.1 M. This algorithm greatly reduced the size of the model while ensuring high detection accuracy and has good real-time performance. It was suitable for deploying embedded track detection systems in agricultural machinery equipment, providing a powerful theoretical research method for efficient detection of corn kernel quality. [ABSTRACT FROM AUTHOR]

The interfacial effect is important for anodes of transition metal dichalcogenides (TMDs) to achieve superior lithium-ion storage performance. In this paper, a MoS2/FeS2 heterojunction is synthesized by a simple hydrothermal reaction to construct the interface effect, and the heterostructure introduces an inherent electric field that accelerates the de-embedding process of lithium ions, improves the electron transfer capability, and effectively mitigates volume expansion. XPS analysis confirms evident chemical interaction between MoS2 and FeS2 via an interfacial covalent bond (Mo–S–Fe). This MoS2/FeS2 anode shows a distinct interfacial effect for efficient interatomic electron migration. The electrochemical performance demonstrated that the discharge capacity can reach up to 1217.8 mA h g−1 at 0.1 A g−1 after 200 cycles, with a capacity retention rate of 72.9%. After 2000 cycles, the capacity retention is about 61.6% at 1.0 A g−1, and the discharge capacity can still reach 638.9 mA h g−1. Electrochemical kinetic analysis indicated an enhanced pseudocapacitance contribution and that the MoS2/FeS2 had sufficient adsorption of lithium ions. This paper therefore argues that this interfacial engineering is an effective solution for designing sulfide-based anodes with good electrochemical properties. [ABSTRACT FROM AUTHOR]

Previous studies have revealed the microbial metabolism of dietary choline in the gut, leading to its conversion into trimethylamine (TMA). Polymethoxyflavones (PMFs), exemplified by tangeretin, have shown efficacy in mitigating choline-induced cardiovascular inflammation. However, the specific mechanism by which these compounds exert their effects, particularly in modulating the gut microbiota, remains uncertain. This investigation focused on tangeretin, a representative PMFs, to explore its influence on the gut microbiota and the choline–TMA conversion process. Experimental results showed that tangeretin treatment significantly attenuated the population of CutC–active bacteria, particularly Clostridiaceae and Lactobacillus, induced by choline chloride in rat models. This inhibition led to a decreased efficiency in choline conversion to TMA, thereby ameliorating cardiovascular inflammation resulting from prolonged choline consumption. In conclusion, tangeretin's preventive effect against cardiovascular inflammation is intricately linked to its targeted modulation of TMA–producing bacterial activity. [ABSTRACT FROM AUTHOR]

The analysis of enantiomers in food has significant implications for food safety and human health. Conventional analytical methods employed for enantiomer analysis, such as gas chromatography and high-performance liquid chromatography, are characterized by their labor-intensive nature and lengthy analysis times. This review focuses on the development of rapid and reliable biosensors for the analysis of enantiomers in food. Electrochemical and optical biosensors are highlighted, along with their fabrication methods and materials. The determination of enantiomers in food can authenticate products and ensure their safety. Amino acids and chiral pesticides are specifically discussed as important chiral substances found in food. The use of sensors replaces expensive reagents, offers real-time analysis capabilities, and provides a low-cost screening method for enantiomers. This review contributes to the advancement of sensor-based methods in the field of food analysis and promotes food authenticity and safety. [ABSTRACT FROM AUTHOR]

In recent years, the surge in marine activities has increased the frequency of submarine pipeline failures. Detecting and identifying the buried conditions of submarine pipelines has become critical. Sub-bottom profilers (SBPs) are widely employed for pipeline detection, yet manual data interpretation hampers efficiency. The present study proposes an automated detection method for submarine pipelines using deep learning models. The approach enhances the YOLOv5s model by integrating Squeeze and Excitation Networks (SE-Net) and S2-MLPv2 attention modules into the backbone network structure. The Slicing Aided Hyper Inference (SAHI) module is subsequently introduced to recognize original large-image data. Experimental results conducted in the Yellow Sea region demonstrate that the refined model achieves a precision of 82.5%, recall of 99.2%, and harmonic mean (F1 score) of 90.0% on actual submarine pipeline data detected using an SBP. These results demonstrate the efficiency of the proposed method and applicability in real-world scenarios. [ABSTRACT FROM AUTHOR]

Various methods of longwall full mining with partial filling have been extensively researched to satisfy the specific mining needs of pressurized-coal and residual-coal resources. This study introduces three longwall partial-filling-mining techniques: room–pillar filling mining, parallel-strip filling mining, and vertical-strip filling mining. Numerical simulations are employed to evaluate the efficacy of these methods. The findings indicate that vertical-strip filling mining results in minimal surface deformation and a more uniform distribution of displacements. In practical operations, the effectiveness of filling largely depends on the choice of filling technology and materials. The research further includes an optimization analysis of the filling technology, emphasizing the composition of the coal-gangue-paste filling system and the refinement of its components. Additionally, the study aims to explore the optimization analysis of filling materials, specifically focusing on performance-optimization methods. The experimental results illustrate that optimizing the filling materials can enhance the performance of filling paste, improving both early-stage and long-term compressive strength. Moreover, the paper examines the quantitative characterization of paste-filling-mining subsidence at various stages in conjunction with theoretical knowledge. Subsequently, mining-subsidence-control measures are recommended to address the primary deformation factors across different stages. Through an in-depth examination of filling-method designs, enhancements in filling technology, and predictions regarding filling-mining subsidence, this research offers valuable insights for optimizing longwall partial-filling-mining methods. [ABSTRACT FROM AUTHOR]

Less attention was paid to the remediation of volatile organic compounds (VOCs) contaminated soil treated by thermal conduction heating (TCH) coupled with chemical oxidization. In this study, the lab-scale remediation experiments of trichloroethylene (TCE)-contaminated soil by TCH and TCH coupled with persulfate (TCH + PS) were performed to explore the influences of PS usage, temperature, reaction time, and the variation of soil properties. TCE was removed from contaminated soils using TCH with a temperature lower than boiling point, and the removal ratio of TCE reached 78.21% with a reaction time of 6h at 60 °C. In the TCH + PS treatments, the removal ratio increased to 87.60~99.50% when the PS dosage was increased from 7.0 mmol/kg to 17.5 mmol/kg at 60 °C. However, the usage efficiency of PS had no positive relationship with oxidant usage and temperature. The treatment with 14 mmol/kg PS after 3h at 50 °C had the highest PS usage ratio of 3.05. In addition, soil pH and soil organic matter (SOM) did not decrease significantly in the TCH-only treatment, while the content of SOM declined by almost 50% after the TCH + PS treatment. Overall, it was concluded that TCH + PS achieved higher removal efficiency, whereas TCH had less disturbance on soil pH and SOM. As such, the applicability of TCH-only or TCH + PS treatments is site-specific. [ABSTRACT FROM AUTHOR]

Nitrogen (N), an important element for crop growth, has a great impact on dry matter weight and yield. Currently, improving N fertilizer use rate is an urgent problem to be solved in agricultural production in the world. In this field experiment, a self-developed water-soluble polymer material (PPM) with water retention and slow-release characteristics was combined with different doses of N fertilizer (N300 (100% N), PN300 (PPM + 100% N), PN240 (PPM + 80% N), PN180 (PPM + 60% N), CK (no N and PPM)) to analyze the impacts on N uptake and use efficiency of wheat plants. The results showed that the combined application of PPM and N fertilizer significantly improved yield, plant height, biomass, and N uptake and use efficiency of drip irrigated wheat, and the PN240 group had the highest N use rate. In addition, the PN300 group had the highest yield. N use efficiency in the PN240 group was 40.23% higher than that in the N300 group. Therefore, the combined application of PPM and N fertilizer, especially PN240, can reduce the N fertilizer application rate by increasing N use efficiency. This study provides technical reference for improving the N use efficiency of drip-irrigated wheat in arid areas. [ABSTRACT FROM AUTHOR]

Bacterial infections pose a significant risk to human health. Magnolol, derived from Magnolia officinalis, exhibits potent antibacterial properties. Synthetic biology offers a promising approach to manufacture such natural compounds. However, the plant-based biosynthesis of magnolol remains obscure, and the lack of identification of critical genes hampers its synthetic production. In this study, we have proposed a one-step conversion of magnolol from chavicol using laccase. After leveraging 20 transcriptomes from diverse parts of M. officinalis, transcripts were assembled, enriching genome annotation. Upon integrating this dataset with current genomic information, we could identify 30 laccase enzymes. From two potential gene clusters associated with magnolol production, highly expressed genes were subjected to functional analysis. In vitro experiments confirmed MoLAC14 as a pivotal enzyme in magnolol synthesis. Improvements in the thermal stability of MoLAC14 were achieved through selective mutations, where E345P, G377P, H347F, E346C, and E346F notably enhanced stability. By conducting alanine scanning, the essential residues in MoLAC14 were identified, and the L532A mutation further boosted magnolol production to an unprecedented level of 148.83 mg/L. Our findings not only elucidated the key enzymes for chavicol to magnolol conversion, but also laid the groundwork for synthetic biology-driven magnolol production, thereby providing valuable insights into M. officinalis biology and comparative plant science. [ABSTRACT FROM AUTHOR]

Structurally well-defined compounds have advantages for quality control in plant biostimulant production and application processes. Humic acid (HA) is a biostimulant that significantly affects plant growth, and soil-dwelling Protaetia brevitarsis larva (PBLs) can rapidly convert agricultural waste into HA. In this study, we use PBLs as a model to investigate HA formation and screen for structurally well-defined HA-related plant biostimulant compounds. Dephasing magic angle spinning nuclear magnetic resonance (13C DD–MAS NMR) analysis indicated HA structural changes during PBL digestion; metabolic profiling detected seven HA-related aromatic ring-containing compounds. A total of six compounds that significantly stimulate plant growth were identified through plant experiments, and all six compounds demonstrate the ability to enhance seed germination. It is noteworthy that piperic acid exhibits a remarkable promotion of root growth in plants, a finding reported for the first time in this study. Thus, this study not only provides insights into the insect-mediated transformation of HA but also illustrates a new method for discovering structurally well-defined plant biostimulant compounds. [ABSTRACT FROM AUTHOR]

Lignin degradation is important for enhancing the digestibility and improving the nutritive quality of ruminant feeds. White rot fungi are well known for their bioconversion of lignocellulosic biomass. The objective of this paper was to evaluate whether Lentinus sajor-caju, Pleurotus ostreatus, Phyllotopsis rhodophylla, Pleurotus djamor, Pleurotus eryngii, and Pleurotus citrinopileatus treatments altered the chemical compositions of highland barley straw constituents and enhanced their nutritional value as a ruminant feed. All white rot fungi significantly increased the relative crude protein (CP), ethyl ether extract (EE), starch, soluble protein (SP), and non-protein nitrogen (NPN) contents but decreased the ash, neutral detergent fiber (NDF), acid detergent fiber (ADF), acid detergent lignin (ADL), and acid detergent insoluble protein (ADFIP) contents. In addition, L. sajor-caju treatment increased (p < 0.001) the levels of PA, PB2, PB3, CA, CB1, CB2, and CNSC, but reduced (p < 0.001) the PC and CC in the solid-state fermentation of highland barley straw. Maximum ligninlysis (50.19%) was optimally produced in the presence of 1.53% glucose and 2.29% urea at 22.72 ℃. The in vitro dry matter digestibility and total volatile fatty acid concentrations of fermented highland barley straw, as well as the fermentability, were optimized and improved with L. sajor-caju, which degraded the lignocellulose and improved the nutritional value of highland barley straw as a ruminant feed. [ABSTRACT FROM AUTHOR]

Copper oxides tend to agglomerate on the surface of CeO2, with a high amount of Cu. In this study, a CeO2 catalyst with a high CuO doping amount was treated with nitric acid to improve its catalytic performance for soot oxidation. The effect of acid etching on the structural properties of the CuO-doped CeO2 catalyst were elucidated. The characterization results indicated that aggregated CuO particles formed over CuCe. The acid etching resulted in a remarkable increase in the surface area of CuCe. Additionally, acid etching promoted the formation of surface-adsorbed oxygen species and oxygen vacancy, and reduced the content of CuOx species with weak interaction with CeO2. The soot temperature-programmed oxidation results show the acid etching of CuCe catalyst could reduce the T50 from 443 to 383 °C. The isothermal reaction results also suggest that acid etching of CuCe leads to an increase in reaction rate from 16.2 to 46.0 μmol min−1 g−1. [ABSTRACT FROM AUTHOR]

Zinc ion, one of the most important transition metal ions in living organisms, plays a crucial role in the homeostasis of the organism. The disorder of zinc is associated with many major diseases. It is highly desirable to develop selective and sensitive methods for the real-time detection of zinc ions. In this work, double-emitting fluorescent carbon dots (CDs) are prepared by a solvothermal method using glutathione, L-aspartic acid, and formamide as the raw materials. The carbon dots specifically recognize zine ions and produce a decrease in fluorescence intensity at 684 nm and an increase at 649 nm, leading to a ratiometric fluorescent sensor for zinc detection. Through surface modification and spectral analysis, the surface groups including carboxyl, carbonyl, hydroxyl, and amino groups, and C=N in heterocycles of CDs are revealed to synergistically coordinate Zn2+, inducing the structural changes in the emission site. The CDs can afford a low limit of detection of ~5 nM for Zn2+ detection with good linearity in the range of 0.02–5 μM, showing good selectivity as well. The results from real samples including fetal bovine serum, milk powder, and zinc gluconate oral solution indicated the good applicability of the CDs in the determination of Zn2+. [ABSTRACT FROM AUTHOR]

This study proposes and simulates a numerical analysis of a diamond racetrack microring resonator on a lithium niobate thin film, operating at a 1.55 µm wavelength. The single-mode conditions, transmission losses, and waveguide dispersions are systematically examined. The microring resonator's radius and gap size are computed and optimized. The designed racetrack microring resonator exhibits a high quality factor (Q-factor) and a high coupling efficiency of approximately 6100 and 95%, respectively, for the transverse TE mode in the C-band. This study achieves a resonant tunability of 1.84 pm/V near the 1.55 μm wavelength by harnessing the electro-optical effect of lithium niobate. [ABSTRACT FROM AUTHOR]

To reveal the coupled heat and mass transfer process during thermal desorption of oil-based drill cuttings, a numerical model of heat and mass transfer was established, which is divided into four components = evaporation. The C language programming catch-up method was used to solve the discrete equation, and the interactive effects of the oil-based drill cuttings' particle size, water content, oil content, content of light and heavy components in oil, heating temperature, heating time, and other operating parameters on the mass and heat transfer of the oil-based cutting particles were investigated. Results showed that the time at which the center point temperature of oil-based drill cuttings with radius of 1 mm and 5 mm reached 600 °C was 441 s and 63 s, respectively, and the temperature difference between the center and the surface increased with particle size. The desorption process of water, light components, and heavy components was not completed individually but mixed alternately. The duration of each desorption component was closely related to the temperature at the center of the oil-based drill cuttings. The smaller the particle size was, the lower the water and oil contents were, and the higher the heating temperature and time were. These conditions were beneficial to thermal desorption, mass transfer, and heat transfer. [ABSTRACT FROM AUTHOR]

The accurate prediction of groundwater inflow in tunnels in karst regions has been a difficult problem to overcome for a long time. This study proposes an equivalent fracture model that takes into account unsaturated seepage and fracture deformation to predict tunnel water inflow, which is constructed based on the TOUGH-FLAC3D framework. The proposed model with complete failure mechanisms of fracture, including shear failure and tensile failure, was applied to predict the water inflow of the Jianxing Tunnel in Guizhou Province to verify its effectiveness. The results indicate that the proposed numerical model was found to be comparable to on-site observations in predicting inflow rate. The inflow rate in a fractured network reaches a steady state faster than that in a non-fractured network. There is a significant difference of 100 times between the highest transient rate and the stable rate between the fracture network and the non-fractured model. The excavation-induced stress redistribution resulted in slip fracture occurring within a distance of approximately 8.2 m from the tunnel wall, which can increase the fracture width and in turn increases the amount of water flowing into the tunnel by about 50%. In addition, this paper also analyzes the impact of the factors of fracture density, incline angle, stress anisotropy, and initial fracture width on the inflow rate during tunnel construction. The study emphasizes the significance of considering deformable fractures and provides valuable insights for improving numerical tools for inflow prediction during tunnel construction. [ABSTRACT FROM AUTHOR]

Pericarp color is a crucial commercial trait influencing consumer preferences for bitter gourds. However, until now, the gene responsible for this trait has remained unidentified. In this study, we identified a gene (McAPRR2) controlling pericarp color via a genome-wide association study (GWAS) utilizing the resequencing data of 106 bitter gourd accessions. McAPRR2 exhibits three primary haplotypes: Hap1 is a wild type with a green pericarp, Hap2 is a SA (South Asian) and SEA (Southeast Asia) type with a green pericarp, and Hap3 is primarily a SEA type with a light green pericarp. The McAPRR2 haplotype is significantly correlated with both pericarp color and ecological type. Importantly, McAPRR2 with the light green pericarp demonstrated premature termination due to a 15 bp sequence insertion. The phylogenetic tree clustered according to pericarp color and ecological type, using SNPs located in the McAPRR2 gene and its promoter. High πwild/SEA and πSA/SEA values indicate high nucleotide diversity between wild and SEA types and between SA and SEA types in the McAPRR2 gene. The haplotypes, phylogenetic tree, and nucleotide diversity of McAPRR2 suggest that McAPRR2 has undergone domestication selection. This study identifies McAPRR2 as the key gene determining pericarp color in bitter gourds and introduces a novel insight that McAPRR2 is subject to domestication selection. [ABSTRACT FROM AUTHOR]

Bacillus thuringiensis (Bt) is the most widely used biopesticide worldwide and can produce several insecticidal crystal proteins and vegetative insecticidal proteins (Vips) at different growth stages. In our previous study, extracellular polysaccharides (EPSs) of Bt strain HD270 were found to enhance the insecticidal activity of Cry1Ac protoxin against Plutella xylostella (L.) and promote the binding of Cry1Ac to the intestinal brush border membrane vesicles (BBMVs). Whether the synergistic activity of Bt EPSs is common to other Cry1-type or Vip proteins is unclear, as is the potential synergistic mechanism. In this study, crude EPS-HD270 was found to increase the toxicity of Cry1-type toxins and Vip3Aa11 against different lepidopteran pests by approximately 2-fold. The purified EPS-HD270 also possessed synergistic activity against the toxicity of Cry1Ac and Vip3Aa11 against Spodoptera frugiperda (J.E. Smith) and Helicoverpa armigera (Hübner). Furthermore, we found that EPS-HD270 had a strong binding ability with Vip3Aa11 and promoted the binding of Vip3Aa11 to the BBMVs of H. armigera and S. frugiperda. Bt EPS-HD270 also protected Vip3Aa11 from proteolytic processing in larval midgut juice. Bt EPSs had universal synergistic effects on Cry1-type or Vip toxins against S. frugiperda and H. armigera. Bt EPS-HD270 exhibited synergistic activity with Vip3Aa through promotion of binding to BBMVs and protection from digestion by midgut protease. The results indicated that synergistic activity with Bt toxins was an important function of Bt EPSs, which was very different from other Bacillus spp. [ABSTRACT FROM AUTHOR]

Lithium-ion batteries are usually connected in series and parallel to form a pack for meeting the voltage and capacity requirements of energy storage systems. However, different pack configurations and battery module collector positions result in different equivalent connected resistances, leading to pack current inhomogeneity, which seriously reduces the lifetime and safety of the pack. Therefore, in order to quantitatively analyze the influence of the connected resistance on the current distribution, this study researched the initial cell current distribution of the parallel module by developing mathematical models of different configurations. Then, this study explored the influence of multiple module collector positions on the current inhomogeneity of the pack under the dynamic current condition. The results show that the inhomogeneity of cell current and discharge capacity in the pack with parallel modules connected in series can be improved by keeping each cell in a parallel module with the same distance to its module collector. Furthermore, the current homogeneity of the edge parallel modules in the pack is seriously affected by the position of the single module collector. Therefore, this study innovatively proposes the symmetrical multiple module collectors of the pack, which can greatly improve the current homogeneity of the edge parallel modules, thereby improving the lifetime and safety of the pack. [ABSTRACT FROM AUTHOR]

The rational design of the heterogeneous interfaces enables precise adjustment of the electronic structure and optimization of the kinetics for electron/ion migration in energy storage materials. In this work, the built-in electric field is introduced to the iron-based anode material (Fe2O3@TiO2) through the well-designed heterostructure. This model serves as an ideal platform for comprehending the atomic-level optimization of electron transfer in advanced lithium-ion batteries (LIBs). As a result, the core-shell Fe2O3@TiO2 delivers a remarkable discharge capacity of 1342 mAh g−1 and an extraordinary capacity retention of 82.7% at 0.1 A g−1 after 300 cycles. Fe2O3@TiO2 shows an excellent rate performance from 0.1 A g−1 to 4.0 A g−1. Further, the discharge capacity of Fe2O3@TiO2 reached 736 mAh g−1 at 1.0 A g−1 after 2000 cycles, and the corresponding capacity retention is 83.62%. The heterostructure forms a conventional p-n junction, successfully constructing the built-in electric field and lithium-ion reservoir. The kinetic analysis demonstrates that Fe2O3@TiO2 displays high pseudocapacitance behavior (77.8%) and fast lithium-ion reaction kinetics. The capability of heterointerface engineering to optimize electrochemical reaction kinetics offers novel insights for constructing high-performance iron-based anodes for LIBs. [ABSTRACT FROM AUTHOR]

SiC particle (SiCp) size has been found to significantly influence the hot workability of particle-reinforced aluminum matrix composites (AMC). In this work, therefore, three types of SiCp/6013 composites with different SiCp sizes (0.7, 5 and 15 μm) were prepared and then subjected to isothermal hot compression tests. In addition, constitutive analysis, processing maps and microstructural characterizations were used to reveal the influence of SiCp size on the hot workability of SiCp/6013 composite. The results showed that the values of hot deformation activation energy Q increased with decreasing SiCp size. Specifically, at lower temperatures (e.g., 350 and 400 °C), the highest peak stress was shown in the AMC with SiCp size of 0.7 μm (AMC-0.7), while in the AMC with SiCp size of 5 μm (AMC-5) at higher temperatures (e.g., 450 and 500 °C). This is because a finer SiCp size would lead to stronger dislocation pinning and grain refinement strengthening effects, and such effects would be weakened at higher temperatures. Further, dynamic softening mechanisms were found to transform from dynamic recovery to dynamic recrystallization with increasing SiCp size, and the dynamic recrystallization occurred more easily at higher temperatures and lower strain rates. Consequently, the instability zones of the composites are all mainly located in the deformation region with lower temperature and higher strain rate, and smaller SiCp results in larger instability zones. [ABSTRACT FROM AUTHOR]

A ground heat exchanger (GHE) can efficiently exploit geothermal energy, and a ground source heat pump (GSHP) is an important type of geothermal application. The distributed thermal response test (DTRT) is widely used to measure layered ground thermal properties for shallow GHEs, but nowadays, there is a lack of studies applying the DTRT to deep coaxial GHEs (DCGHEs). This study proposes a new parameter estimation method (PEM) by adopting the DTRT data of a DCGHE to estimate layered ground thermal properties and applies the proposed PEM to simulated DTRTs under different boundary conditions, and the estimated values of the layered ground thermal properties are compared with the true values. Under heat output rate or inlet temperature boundary conditions, the relative errors of the thermal conductivities and heat capacities of ground estimated using the proposed PEM are basically within 2% and 4%, respectively, except for shallower layers with a depth range of 0–800 m. The larger errors for shallower layers may be caused by weaker heat transfer between the fluid and ground, and the errors are basically lower for higher heat output rates. The predicted fluid temperature distributions during 120 d using the estimated values of the layered ground thermal properties match well with those using the true values. The results show that the proposed PEM is viable for DCGHE DTRT interpretation under heat output rate and inlet temperature boundary conditions, is a cost-effective way to establish key parameters for GSHP design, and would promote geothermal development. [ABSTRACT FROM AUTHOR]