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Due to the influence of geometric factors, the temperature and humidity profile of lidar's near-field signal was warped when sensing the air environment. In order to perform geometric factor correction on near-field signals, this article proposes different correction solutions for the Mie and Raman scattering channels. Here, the Mie scattering channel used the Raman method to invert the aerosol backscatter coefficient and correct the extinction coefficient in the transition zone. The geometric factor was the ratio of the measured signal to the forward-computed vibration Raman scattering signal. The aerosol optical characteristics were reversed using the corrected echo signal, and the US standard atmospheric model was added to the missing signal in the blind zone, reflecting the aerosol evolution process. The stability and dependability of the proposed algorithm were validated by the consistency between the visibility provided by the Environmental Protection Agency and the visibility acquired via lidar retrieval data. The near-field humidity data were supplemented by the interpolation method in the Raman scattering channel to reflect the water vapor transfer process in the temporal dimension. The measured transmittance curve of the filter, the theoretical normalized spectrum, and the sounding data were used to compute the delay geometric factor. The temperature was retrieved and the near-field signal distortion issue was resolved by applying the corrected quotient of the temperature channel. The proposed algorithm exhibited robustness and universality, enhancing the system's detection accuracy compared to the temperature and humidity data constantly recorded by the probes in the meteorological gradient tower, which have a high correlation with the lidar observation data. The comparison between lidar data and instrument monitoring data showed that the proposed algorithm could effectively correct distorted echo signals in the transition zone, which was of great value for promoting the application of lidar in the meteorological monitoring of the urban canopy layer. [ABSTRACT FROM AUTHOR]

Inner Mongolia, a major region in China for growing sugar beet, faces challenges caused by unscientific water and fertilizer management. This mismanagement restricts the improvement of sugar beet yield and quality and exacerbates water waste and environmental pollution. This study aims to evaluate the effects of reduced water and fertilizer on the growth and physiological metabolism of sugar beet taproot. Field experiments were conducted in Ulanqab, Inner Mongolia, in 2022 and 2023, using a split-plot design with three levels each of fertilization and irrigation. The study analyzed the effects of reduced water and fertilizer treatments on fresh taproot weight, respiration rate, energy metabolism, respiratory enzyme activity, and gene expression in sugar beet taproot. It was found that a 10% reduction in fertilizer significantly increased the beet taproot fresh weight. Further research revealed that during the rapid leaf growth phase and the taproot and sugar growth period, a 10% reduction in fertilizer upregulated HK and IDH gene expression and downregulated G6PDH gene expression in the beet taproot. This increased HK and IDH activities, decreased G6PDH activity, enhanced the activity of the EMP-TCA pathway, and inhibited the PPP. Taproot weight was positively correlated with the respiration rate, ATP content, EC, and ATPase, HK, and IDH activities, thereby increasing the taproot growth rate and taproot fresh weight, with an average increase of 4.0% over two years. These findings introduce a novel method for optimizing fertilizer use, particularly beneficial in water-scarce regions. Implementing this strategy could help farmers in western Inner Mongolia and similar areas improve crop yield and sustainability. This study offers new insights into resource-efficient agricultural practices, highlighting the importance of customized fertilization strategies tailored to local environmental conditions. [ABSTRACT FROM AUTHOR]

Differential absorption lidar is an advanced tool for investigating tropospheric ozone transport and development. High-quality differential absorption lidar data are the basis for studying the temporal and spatial evolution of ozone pollution. We assessed the quality of the ozone data generated via differential absorption lidar. By correcting the ozone lidar profile in real-time with an atmospheric correction term and comparing the lidar data to ozone data collected using an unmanned aerial vehicle (UAV), we quantified the statistical error of the ozone lidar data in the vertical direction and determined that the data from the two instruments were generally in agreement. To verify the reliability of the ozone lidar system and the atmospheric correction algorithm, we conducted a long-term comparison experiment using data from the Canton Tower. Over the two months, the UAV and lidar data were consistent with one another, which confirmed the viability of the ozone lidar optomechanical structure and the atmospheric correction algorithm, both in real-time and over a given time duration. In addition, we also quantified the relationship between statistical error and signal-to-noise ratio. When the SNR is less than 10, the corresponding statistical error is about 40%. The statistical error was less than 15% when the signal-to-noise ratio was greater than 20, and the statistical error was mostly less than 8% when the signal-to-noise ratio was greater than 40. In general, the statistical error of the differential absorption lidar data was inversely proportional to the signal-to-noise ratio of each echo signal. [ABSTRACT FROM AUTHOR]

Reducing resistance to surface friction is challenging in the field of engineering. Natural biological systems have evolved unique functional surfaces or special physiological functions to adapt to their complex environments over centuries. Among these biological wonders, fish, one of the oldest in the vertebrate group, have garnered attention due to their exceptional fluid dynamics capabilities. Fish skin has inspired innovation in reducing surface friction due to its unique structures and material properties. Herein, drawing inspiration from the unique properties of fish scales, a periodic array of fish scales was fabricated by laser ablation on a polished aluminum template. The morphology of the biomimetic fish scale surface was characterized using scanning electron microscopy and a white-light interfering profilometer. Drag reduction performance was measured in a closed circulating water tunnel. The maximum drag reduction was 10.26% at a Reynolds number of 39,532, and the drag reduction performance gradually decreased with an increase in the distance between fish scales. The mechanism of the biomimetic drag reduction surface was analyzed using computational fluid dynamics. Streamwise vortices were generated at the valley of the biomimetic fish scale, replacing sliding friction with rolling friction. These results are expected to provide a foundation for in-depth analysis of the hydrodynamic performance of fish and serve as new inspiration for drag reduction and antifouling. [ABSTRACT FROM AUTHOR]

This paper investigated the inhibitory effect of Sesamol (Ses) on Pestalotiopsis neglecta. The potential inhibitory mechanisms were explored by observing changes in cell morphology, measuring alterations in cell membrane-related indices, as well as energy metabolism-related indices and changes in enzyme activities related to virulence. The results show that Ses completely inhibited the growth of P. neglecta at 600 μg/mL (minimum inhibitory concentration and minimum fungicidal concentration), with an EC50 of 142 ± 13.22 μg/mL. As observed with scanning electron microscopy (SEM) and transmission electron microscopy (TEM), Ses treatment resulted in the breakage and crumpling of P. neglecta cell membrane and organelle lysis. Ergosterol content and the total lipid in P. neglecta treated with 300 μg/mL Ses was 91.52% and 54% of that in the control groups, respectively. In addition, spores were stained, increased leakage of intracellular constituents at 260 nm, and decreased extracellular pH. This suggests damage to the cell membrane integrity and permeability. Furthermore, Ses decreased the ATP levels and key enzymes in the tricarboxylic acid (TCA) cycle, indicating interference with the fungal energy metabolism. Moreover, the activities of polygalacturonase (PG) and endoglucanase (EG) of P. neglecta treated with 300 μg/mL of Ses were only 28.20% and 29.13% of that in the control groups, respectively, indicating that Ses can reduce the virulence of P. neglecta. In conclusion, our results show that Ses should be considered as a potential plant-derived fungicide due to its ability to disrupt the morphology of P. neglecta, damage cell membrane integrity and permeability in P. neglecta, interfere with energy metabolism, and reduce its virulence, ultimately affecting the fungal growth. [ABSTRACT FROM AUTHOR]

With the swift advancement of wearable electronics and artificial intelligence, the integration of electronic devices with the human body has advanced significantly, leading to enhanced real-time health monitoring and remote disease diagnosis. Despite progress in developing stretchable materials with skin-like mechanical properties, there remains a need for materials that also exhibit high optical transparency. Supercapacitors, as promising energy storage devices, offer advantages such as portability, long cycle life, and rapid charge/discharge rates, but achieving high capacity, stretchability, and transparency simultaneously remains challenging. This study combines the stretchable, transparent polymer PEDOT:PSS with MnO2 nanoparticles to develop high-performance, stretchable, and transparent supercapacitors. PEDOT:PSS films were deposited on a PDMS substrate using a spin-coating method, followed by electrochemical deposition of MnO2 nanoparticles. This method ensured that the nanosized MnO2 particles were uniformly distributed, maintaining the transparency and stretchability of PEDOT:PSS. The resulting PEDOT:PSS/MnO2 nanoparticle electrodes were gathered into a symmetric device using a LiCl/PVA gel electrolyte, achieving an areal capacitance of 1.14 mF cm−2 at 71.2% transparency and maintaining 89.92% capacitance after 5000 cycles of 20% strain. This work presents a scalable and economical technique to manufacturing supercapacitors that combine high capacity, transparency, and mechanical stretchability, suggesting potential applications in wearable electronics. [ABSTRACT FROM AUTHOR]

Urban crowd flow prediction is an important task for transportation systems and public safety. While graph convolutional networks (GCNs) have been widely adopted for this task, existing GCN-based methods still face challenges. Firstly, they employ fixed receptive fields, failing to account for urban region heterogeneity where different functional zones interact distinctly with their surroundings. Secondly, they lack mechanisms to adaptively adjust spatial receptive fields based on temporal dynamics, which limits prediction performance. To address these limitations, we propose an Adaptive Receptive Field Graph Convolutional Network (ARFGCN) for urban crowd flow prediction. ARFGCN allows each region to independently determine its receptive field size, adaptively adjusted and learned in an end-to-end manner during training, enhancing model prediction performance. It comprises a time-aware adaptive receptive field (TARF) gating mechanism, a stacked 3DGCN, and a prediction layer. The TARF aims to leverage gating in neural networks to adapt receptive fields based on temporal dynamics, enabling the predictive network to adapt to urban regional heterogeneity. The TARF can be easily integrated into the stacked 3DGCN, enhancing the prediction. Experimental results demonstrate ARFGCN's effectiveness compared to other methods. [ABSTRACT FROM AUTHOR]

Stance detection is a crucial task in natural language processing and social computing, focusing on classifying expressed attitudes towards specific targets based on the input text. Conventional methods predominantly view stance detection as a task of target-oriented, sentence-level text classification. On popular social media platforms like Twitter, users often express their opinions through hashtags in addition to textual content within tweets. However, current methods primarily treat hashtags as data retrieval labels, neglecting to effectively utilize the semantic information they carry. In this paper, we propose a large language model knowledge-enhanced stance detection framework (LKESD) for stance detection. LKESD contains three main components: an instruction-prompted background knowledge acquisition module (IPBKA) that retrieves background knowledge of hashtags by providing handcrafted prompts to large language models (LLMs); a graph convolutional feature-enhancement module (GCFEM) is designed to extract the semantic representations of words that frequently co-occur with hashtags in the dataset by leveraging textual associations; an a knowledge fusion network (KFN) is proposed to selectively integrate graph representations and LLM features using a prompt-tuning framework. Extensive experimental results on three benchmark datasets demonstrate that our LKESD method outperforms 2.7% on all setups over compared methods, validating its effectiveness in stance detection tasks. [ABSTRACT FROM AUTHOR]

When there is vegetation on the beach or main channel bed, it will have a significant impact on the river channel. This study was based on physical model experiments to investigate the flow conditions of the Jinhu section of the Huaihe River estuary, revealing the influence of reed vegetation on water flow resistance. A new comprehensive roughness formula was proposed, and the predictive effectiveness of the formula was verified. The theoretical results indicate that under the condition of vegetation not being submerged, the comprehensive roughness is directly proportional to the square root of vegetation density in areas with vegetation coverage, the square root of water surface vegetation coverage, and the 2/3 power of the hydraulic radius. The bottom slope does not affect it. Under the condition of vegetation inundation, the comprehensive roughness is smaller than that under the condition of no inundation. The experimental prediction results of the influence of reeds on roughness indicate that the measured roughness values and theoretical roughness calculation values are in good agreement. Under the same operating conditions, the roughness gradually decreases with an increase in flow rate. Under the full-reed working condition, the calculated roughness value and the measured roughness value have the same trend of change, both decreasing with the increase in flow rate. The experimental prediction results of the influence of reeds on the relationship between water level and flow rate show that the roughness value of 0 increases with the increase in reed grass surface coverage rate Ki, and an increase in Ki can lead to an increase in comprehensive roughness. [ABSTRACT FROM AUTHOR]

In the evolving landscape of portable electronics, there is a critical demand for components that meld stretchability with optical transparency, especially in supercapacitors. Traditional materials fall short in harmonizing conductivity, stretchability, transparency, and capacity. Although poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) stands out as an exemplary candidate, further performance enhancements are necessary to meet the demands of practical applications. This study presents an innovative and effective method for enhancing electrochemical properties by homogeneously incorporating Ru(III) into PEDOT:PSS. These Ru(III) PEDOT:PSS complexes are readily synthesized by dipping PEDOT:PSS films in RuCl3 solution for no longer than one minute, leveraging the high specific capacitance of Ru(III) while minimizing interference with transmittance. The supercapacitor made with this Ru(III) PEDOT:PSS complex demonstrated an areal capacitance of 1.62 mF cm−2 at a transmittance of 73.5%, which was 155% higher than that of the supercapacitor made with PEDOT:PSS under comparable transparency. Notably, the supercapacitor retained 87.8% of its initial capacitance even under 20% tensile strain across 20,000 cycles. This work presents a blueprint for developing stretchable and transparent supercapacitors, marking a significant stride toward next-generation wearable electronics. [ABSTRACT FROM AUTHOR]

The amorphous form of poorly soluble drugs is physically unstable and prone to crystallization, resulting in decreased solubility and bioavailability. However, the conventional accelerated stability test for amorphous drugs is time-consuming and inaccurate. Therefore, there is an urgent need to develop rapid and accurate stability assessment technology. This study used the antitumor drug nilotinib free base as a model drug. The degree of disorder and physical stability in the amorphous form was assessed by applying the pair distribution function (PDF) and principal component analysis (PCA) methods based on powder X-ray diffraction (PXRD) data. Specifically, the assessment conditions, such as the PDF interatomic distance range, PXRD detector type, and PXRD diffraction angle range were also optimized. The results showed that more reliable PCA data could be obtained when the PDF interatomic distance range was 0–15 Å. When the PXRD detector was a semiconductor-type detector, the PDF data obtained were more accurate than other detectors. When the PXRD diffraction angle range was 5–40°, the intermolecular arrangement of the amorphous drugs could be accurately predicted. Finally, the accelerated stability test also showed that under the above-optimized conditions, this method could accurately and rapidly assess the degree of disorder and physical stability in the amorphous form of drugs, which has obvious advantages compared with the accelerated stability test. [ABSTRACT FROM AUTHOR]

The purpose of this study was to resolve the issue of physical instability in amorphous solid drugs, which can result in unwanted crystallization, affecting solubility and dissolution rates. The focus was on precipitating physically stable amorphous forms of the nilotinib free base, an anticancer drug, by monitoring preparation conditions such as precipitation temperature and filter cake thickness. A comprehensive set of characterization techniques, including powder X-ray diffraction (PXRD), differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), and focused beam reflectance measurement (FBRM), were used. These were supplemented by advanced data analysis methods that incorporated pair distribution function (PDF), reduced crystallization temperature (Rc), and principal component analysis (PCA) to evaluate the physical stability of the amorphous samples. Results emphasized that optimal physical stability was achieved when amorphous solids were prepared at a precipitation temperature of 10 °C and a filter cake thickness of 4 cm. Moreover, the integration of PDF analysis with Rc values was confirmed as an innovative approach for assessing physical stability, thus offering enhanced efficiency and accuracy over conventional accelerated stability testing methods. [ABSTRACT FROM AUTHOR]

Investigating public attitudes on social media is crucial for opinion mining systems. Stance detection aims to predict the attitude towards a specific target expressed in a text. However, effective neural stance detectors require substantial training data, which are challenging to curate due to the dynamic nature of social media. Moreover, deep neural networks (DNNs) lack explainability, rendering them unsuitable for scenarios requiring explanations. We propose a distantly supervised explainable stance detection framework (DS-ESD), comprising an instruction-based chain-of-thought (CoT) method, a generative network, and a transformer-based stance predictor. The CoT method employs prompt templates to extract stance detection explanations from a very large language model (VLLM). The generative network learns the input-explanation mapping, and a transformer-based stance classifier is trained with VLLM-annotated stance labels, implementing distant supervision. We propose a label rectification strategy to mitigate the impact of erroneous labels. Experiments on three benchmark datasets showed that our model outperformed the compared methods, validating its efficacy in stance detection tasks. This research contributes to the advancement of explainable stance detection frameworks, leveraging distant supervision and label rectification strategies to enhance performance and interpretability. [ABSTRACT FROM AUTHOR]

Probiotics are beneficial for intestinal diseases. Research shows that probiotics can regulate intestinal microbiota and alleviate inflammation. Little research has been done on the effects of probiotics on colitis in mice. The purpose of this study was to investigate the inhibitory effect of the strains isolated and screened from the feces of healthy piglets on the enteritis of rocitrobacter. The compound ratio of isolated Lactobacillus L9 and Enterococcus faecalis L16 was determined, and the optimal compound ratio was selected according to acid production tests and bacteriostatic tests in vitro. The results showed that when the ratio of Lactobacillus L9 to Enterococcus faecalis L16 was 4:1, the pH value was the lowest, and the antibacterial diameter was the largest. Then, in animal experiments, flow cytometry was used to detect the number of T lymphocytes in the spleen and mesenteric lymph nodes of mice immunized with complex lactic acid bacteria. The results showed that the number of T lymphocytes in the spleen and mesenteric lymph nodes of mice immunized with complex lactic acid bacteria significantly increased, which could improve the cellular immunity of mice. The microbiota in mouse feces were sequenced and analyzed, and the results showed that compound lactic acid bacteria could increase the diversity of mouse microbiota. It stabilized the intestinal microbiota structure of mice and resisted the damage of pathogenic bacteria. The combination of lactic acid bacteria was determined to inhibit the intestinal colitis induced by Citrobacter, improve the cellular immune response of the body, and promote the growth of animals. [ABSTRACT FROM AUTHOR]

Amorphous solids exhibit enhanced solubility and dissolution rates relative to their crystalline counterparts. However, attaining optimal bioavailability presents a challenge, primarily due to the need to maintain the physical stability of amorphous solids. Moreover, the precise manner in which precipitation parameters, including the feeding rate of the anti-solvent, agitation speed, and aging time, influence the physical stability of amorphous solids remains incompletely understood. Consequently, this study aimed to investigate these three parameters during the precipitation process of the anticancer drug, nilotinib free base. The physical stability of the resultant samples was evaluated by employing characterization techniques including powder X-ray diffraction (PXRD), differential scanning calorimetry (DSC), focused beam reflectance measurement (FBRM), and data analysis methods such as pair distribution function (PDF), reduced crystallization temperature (Rc), and principal component analysis (PCA). This study's findings indicated that amorphous solids exhibited the greatest physical stability under particular conditions, namely a feeding rate of 5 mL/min, an agitation speed of 500 rpm, and an aging time of 10 min. Furthermore, the physical stability of the amorphous solids was primarily influenced by particle size and distribution, molecular interactions, microstructure, surface area, and interfacial energy. Notably, the parameters involved in the anti-solvent precipitation process, including the feeding rate of the anti-solvent, agitation speed, and aging time, exerted a significant impact on these factors. Consequently, they directly affected the physical stability of amorphous solids. Hence, this study comprehensively elucidated the mechanistic influence of these operational parameters on the physical stability of amorphous solids during the anti-solvent precipitation process. [ABSTRACT FROM AUTHOR]

In this paper, we propose the design and simulation of a dielectric horn antenna using the metamaterial method; this antenna has a double-layer dielectric waveguide transmission structure. With the continuous development of microwave feed sources, the traditional waveguide systems are no longer able to meet today's antenna requirements. Consequently, dielectric-loading technology is gradually being applied to design horns. A key advantage of this antenna is its significantly expanded bandwidth of 163.3%. Furthermore, when compared to ridge horns, this dielectric-loaded horn demonstrates superior radiation properties across the entire frequency band, including aperture efficiency (95% in the L band, 65.4% in the S band, 41.5% in the C band, and 28.7% in the X band) and cross-polarization isolation (≥51.6 dB). In addition, before researching the theory of dielectric-loading technology, the modes of the horns should be analyzed. This helps us to better control the hybrid mode. The metamaterial method was applied to achieve stable dielectric properties. We finally conducted experiments on the antenna to validate the relevant theories and feasibility. [ABSTRACT FROM AUTHOR]

Northern China faces water scarcity, restricting water usage in place across Inner Mongolia's western region. The integrated irrigation and fertilization model for sugar beet is undergoing rapid development and application in production. However, there is a concerning trend in production where the frequency of irrigation and fertilization is being increased blindly, resulting in the wastage of valuable water and fertilizer resources. Limiting water and fertilizer usage is an effective approach to improve sugar beet production efficiency. Sugar beets are a significant sugar crop in China. A split-plot design was employed to examine the impact of reducing water and fertilizer use on sucrose metabolism in sugar beet root. Our study was performed at the Ulanqab Institute of Agricultural and Forestry Sciences in Inner Mongolia from 2022 to 2023. Three levels of fertilization and irrigation were utilized. We investigated the interactions between irrigation and fertilization on sucrose accumulation in sugar beet root. We examined key enzyme activities involved in sucrose metabolism alongside their gene expression levels. The findings suggested that reducing irrigation by 15%, fertilization by 10%, or both irrigation by 15% and fertilization by 10%, increased sucrose concentrations of sugar beets compared to the control group administered conventional water and fertilizer. Over the two-year period, the average sucrose concentration increased by 0.45, 0.57, and 0.65 degrees, respectively, under each treatment. Subsequent research verified that appropriately reducing water and fertilizer can regulate the expression of enzyme genes, thus influencing enzyme activity. Moreover, due to the higher efficiency of enzyme synthesis compared to decomposition, it contributed to an increase in net enzyme activity. These findings suggest that an appropriate reduction of water and fertilizer can improve sucrose synthesis rates and increase the sucrose concentration in sugar beets, providing a theoretical basis for environmentally friendly generation and enhanced efficiency in sugar beet growth. [ABSTRACT FROM AUTHOR]

Cu-Be alloys exhibit excellent comprehensive performance in electrics, thermotics, and mechanics, and hence, they attract much attention. Among them, low-Be copper alloys are more environmentally friendly and promising. This study explores the effects of different Ni contents and heat treatment parameters on the properties, microstructures, and precipitates of Cu-0.2 wt% Be-x wt% Ni (0 < x < 2.0) alloys. The experimental results demonstrate that the fast cooling rate of cast alloys during solidification contributes to retention of the solute atoms in the copper matrix, which is beneficial for subsequent solid solution treatment. Furthermore, solid solution treatment slightly reduces the electrical conductivities, microhardness values, and compressive yield strengths of Cu-0.2 wt% Be-1.0/1.6 wt% Ni alloys. The optimal solution temperature and time are about 925 ℃ and 60 min, respectively. Aging treatment significantly increases the electrical conductivities, microhardness values, and compressive yield strengths of Cu-0.2 wt% Be-1.0/1.6 wt% Ni alloys. The best aging temperature is around 450 ℃. However, the properties of Cu-0.2 wt%Be-0.4 wt%Ni alloys remain unaffected by solution and aging treatments. Around x = 1.0, Cu-0.2 wt% Be-x wt% Ni alloys possess the best comprehensive properties, which are about 72%IACS of electrical conductivity, 241 HV of microhardness, and 281MPa of compressive yield strength, respectively. TEM and EDS analyses reveal that the precipitate evolution of Cu-0.2 wt% Be-1.0 wt% Ni alloys with aging time is GP zones → γ″ → γ′. Notably, a distinct double-peak age strengthening phenomenon emerges with Cu-0.2 wt% Be-1.0/1.6 wt% Ni alloys. The precipitation of plenty of GP zones at the early stage of aging should account for the first strengthening peak, and the strengthening mechanism transformation of the γ″ or γ′ phase from shear to Orowan should induce the second strengthening peak. This work may help to design new low-Be copper alloys and their preparation processes. [ABSTRACT FROM AUTHOR]

Investigating public attitudes towards social media is crucial for opinion mining systems to gain valuable insights. Stance detection, which aims to discern the attitude expressed in an opinionated text towards a specific target, is a fundamental task in opinion mining. Conventional approaches mainly focus on sentence-level classification techniques. Recent research has shown that the integration of background knowledge can significantly improve stance detection performance. Despite the significant improvement achieved by knowledge-enhanced methods, applying these techniques in real-world scenarios remains challenging for several reasons. Firstly, existing methods often require the use of complex attention mechanisms to filter out noise and extract relevant background knowledge, which involves significant annotation efforts. Secondly, knowledge fusion mechanisms typically rely on fine-tuning, which can introduce a gap between the pre-training phase of pre-trained language models (PLMs) and the downstream stance detection tasks, leading to the poor prediction accuracy of the PLMs. To address these limitations, we propose a novel prompt-based stance detection method that leverages the knowledge acquired using the chain-of-thought method, which we refer to as PSDCOT. The proposed approach consists of two stages. The first stage is knowledge extraction, where instruction questions are constructed to elicit background knowledge from a VLPLM. The second stage is the multi-prompt learning network (M-PLN) for knowledge fusion, which learns model performance based on the background knowledge and the prompt learning framework. We evaluated the performance of PSDCOT on publicly available benchmark datasets to assess its effectiveness in improving stance detection performance. The results demonstrate that the proposed method achieves state-of-the-art results in in-domain, cross-target, and zero-shot learning settings. [ABSTRACT FROM AUTHOR]

Under climate change, the frequency of drought-flood abrupt alternation (DFAA) events is increasing in Southeast China. However, there is limited research on the evolution characteristics of DFAA in this region. This study evaluated the effectiveness of the drought and flood indexes including SPI (Standardized Precipitation Index), SPEI (Standardized Precipitation Evapotranspiration Index), and SWAP (Standardized Weighted Average Precipitation Index) in identifying DFAA events under varying days of antecedent precipitation. Additionally, the evolution characteristics of DFAA events in Fujian Province from 1961 to 2021 were explored. The results indicate that (1) SPI-12d had the advantages of high effectiveness, optimal generalization accuracy, and strong generalization ability of identification results, and it can be used as the optimal identification index of DFAA events in Southeast China. (2) There was an overall increase in DFAA events at a rate of 1.8 events/10a. The frequency of DFAA events showed a gradual increase from the northwest to the southeast. (3) DTF events were characterized by moderate drought to flood, particularly in February, July, and August, while FTD events were characterized by light/moderate flood to drought, with more events occurring from June to October. (4) DTF event intensity increased in the northern and western regions from 1961 to 2021. For FTD events, the intensity notably increased in the western region from 1961 to 2001, while a significant increase occurred in all regions except the central region from 2001 to 2021. These findings emphasize the need for precautionary measures to address the increasing frequency and severity of DFAA events in Southeast China. [ABSTRACT FROM AUTHOR]

Titanium alloy pressure spherical–cylindrical shells enable the effective utilization of the strength of spherical and cylindrical pressure-resistant shell components. In this study, a numerical simulation of the residual stress of a titanium alloy butt-welding plate was conducted by employing sequential coupling and a temperature heat source model. The results of welding residual stress analysis agreed well with the experimental results reported in the literature. Subsequently, the welding residual stress of a titanium alloy pressure spherical–cylindrical shell was calculated and analyzed using the same method. Finally, the influence of residual stress on the ultimate bearing capacity of the shell was assessed. On the inner surface of the shell, the horizontal welding residual tensile stress, perpendicular to the weld path, exhibited a bimodal distribution. The longitudinal welding residual tensile stresses were higher than the horizontal welding residual stress. Near the weld on the outer shell surface, higher longitudinal welding residual tensile stresses existed, whereas the horizontal welding residual stress was compressive. Both the inner and outer shell surfaces exhibited significant longitudinal residual tensile stresses along the weld path, though residual compressive stresses existed on both surfaces. The influence of welding residual stress on the ultimate load-bearing capacity of the shell was minimal. [ABSTRACT FROM AUTHOR]

Expansive soils are distributed across a wide area in China, and land transport and surface construction will inevitably involve these soils. To mitigate the deficiencies of single-method expansive soil modification, it is highly important to adopt the use of polyvinyl alcohol (PVA) to improve expansive soils and enhance the strength and toughness of modified soils. In addition, solidification technology can be utilized for the resource utilization of expansive soils. In this study, triaxial testing is employed to evaluate the mechanical properties of solidified soil. When the confining pressure is the same and with increasing PVA content, soil particles and PVA combine to form a cemented substance, which fills the internal pores of the soil samples, enhances the cohesion between soil particles, and improves the bearing capacity of the soil. The stress–strain curve for the modified soil first increases and then decreases. The shear strength peaks at a PVA content of 3%. Based on the improved soil with a 3% PVA content, GDS dynamic triaxial tests were carried out to investigate the effects of different confining pressures and frequencies on the dynamic stress–strain curves, dynamic modulus of elasticity, and variation rule for the damping ratio of the improved soil. The results show that the dynamic stress–strain curve for the improved soil increases with increasing confining pressure and frequency and that the dynamic stress–strain backbone curves exhibit significant nonlinearities at different frequencies and circumferential pressures. The dynamic elastic modulus increases with increasing confining pressure and frequency and decreases gradually with increasing dynamic strain. The initial dynamic modulus of elasticity increases with increasing envelope pressure and frequency but is less affected by frequency, and the damping ratio decreases with increasing confining pressure and frequency. Soil treatment can improve the pore distribution, inhibit the extension of soil cracks, and enhance soil compactness. [ABSTRACT FROM AUTHOR]

SLAM (simultaneous localization and mapping) technology incorporating QR code navigation has been widely used in the mobile robotics industry. However, the particle kidnapping problem, positioning accuracy, and navigation time are still urgent issues to be solved. In this paper, a SLAM fused QR code navigation method is proposed and an improved adaptive Monte Carlo positioning algorithm is used to fuse the QR code information. Firstly, the generation and resampling methods of initialized particle swarms are improved to improve the robustness and weights of the swarms and to avoid the kidnapping problem. Secondly, the Gmapping scan data and the data generated by the improved AMCL algorithm are fused using the extended Kalman filter to improve the accuracy and stability of the state estimation. Finally, in terms of the positioning system, Gmapping is used to obtain QR code data as marker positions on static maps, and the improved adaptive Monte Carlo localization particle positioning algorithm is matched with a library of QR code templates, which corrects for offset distances and achieves precise point-to-point positioning under grey-valued raster maps. The experimental results show that the particles encountered with kidnapping can be quickly adjusted in position, with a 68.73% improvement in adjustment time, 64.27% improvement in navigation and positioning accuracy, and 42.81% reduction in positioning time. [ABSTRACT FROM AUTHOR]

The literature on sustainable competitive advantages and performance has grown extensively in organizations over the last three decades. However, sustainable competitive advantages have received limited attention from scholars in academic institutions. To contribute to the literature, this research examines how knowledge-oriented leadership stimulates team performance through innovation, eventually directing towards a sustainable competitive advantage in higher education institutions (HEIs). The data was gathered from 64 team leaders and 303 team members from Pakistan's HEIs to assess the model. The results indicate that knowledge-oriented leadership significantly enhances team performance, with this association partially mediated by the speed of innovation. At the same time, no mediating role is observed for the quality of innovation. In addition, team performance and its relationship with a sustainable competitive advantage originated positively. As a result, HEIS should promote knowledge-oriented leadership as a crucial strategy for managing the complex dynamics of innovation, team performance, and sustainable competitive advantages. These institutions should prioritize appointing knowledge-oriented leaders to enhance innovation, team performance, and sustainable competitive advantages. Further implications are conferred. [ABSTRACT FROM AUTHOR]

The proliferation of smart devices in the 5G era of industrial IoT (IIoT) produces significant traffic data, some of which is encrypted malicious traffic, creating a significant problem for malicious traffic detection. Malicious traffic classification is one of the most efficient techniques for detecting malicious traffic. Although it is a labor-intensive and time-consuming process to gather large labeled datasets, the majority of prior studies on the classification of malicious traffic use supervised learning approaches and provide decent classification results when a substantial quantity of labeled data is available. This paper proposes a semi-supervised learning approach for classifying malicious IIoT traffic. The approach utilizes the encoder–decoder model framework to classify the traffic, even with a limited amount of labeled data available. We sample and normalize the data during the data-processing stage. In the semi-supervised model-building stage, we first pre-train a model on a large unlabeled dataset. Subsequently, we transfer the learned weights to a new model, which is then retrained using a small labeled dataset. We also offer an edge intelligence model that considers aspects such as computation latency, transmission latency, and privacy protection to improve the model's performance. To achieve the lowest total latency and to reduce the risk of privacy leakage, we first create latency and privacy-protection models for each local, edge, and cloud. Then, we optimize the total latency and overall privacy level. In the study of IIoT malicious traffic classification, experimental results demonstrate that our method reduces the model training and classification time with 97.55% accuracy; moreover, our approach boosts the privacy-protection factor. [ABSTRACT FROM AUTHOR]

In order to better understand the extrusion process mechanism of plant protein inside a barrel, the parameter changes and flow characteristics of fluids under conveying, kneading block and reversing elements were investigated with numerical simulation. The results showed that the shear rate increased obviously with the increase in pitch; the shear rate value of the reversing element was larger, while that of the kneading block was the opposite. The screw combinations of conveying, kneading blocks and reversing elements all have a certain degree of mixing effect on the particles, and the reduction in pitch can effectively increase the mixing effect of the particles. The conveying element can provide a relatively constant acceleration for the particles, due to the pumping capability and pressure buildup as the pitch increases. The kneading block and the reversing element can increase the leakage flow between the discs and backflow, resulting in an extension of the residence time distribution that facilitates fluid interaction in the barrel and improves the dispersion of the particles. The restraint by the reversing element on the particles is obviously weaker than that of the kneading block and shows a higher particle mixing degree. Overall, the influence of different elements on the flow condition, mixing degree and residence time is significantly different, which improves the process controllability and provides references for potential applications to meet multiple demands. [ABSTRACT FROM AUTHOR]

Ligand-based virtual screening (LBVS) is a promising approach for rapid and low-cost screening of potentially bioactive molecules in the early stage of drug discovery. Compared with traditional similarity-based machine learning methods, deep learning frameworks for LBVS can more effectively extract high-order molecule structure representations from molecular fingerprints or structures. However, the 3D conformation of a molecule largely influences its bioactivity and physical properties, and has rarely been considered in previous deep learning-based LBVS methods. Moreover, the relative bioactivity benchmark dataset is still lacking. To address these issues, we introduce a novel end-to-end deep learning architecture trained from molecular conformers for LBVS. We first extracted molecule conformers from multiple public molecular bioactivity data and consolidated them into a large-scale bioactivity benchmark dataset, which totally includes millions of endpoints and molecules corresponding to 954 targets. Then, we devised a deep learning-based LBVS called EquiVS to learn molecule representations from conformers for bioactivity prediction. Specifically, graph convolutional network (GCN) and equivariant graph neural network (EGNN) are sequentially stacked to learn high-order molecule-level and conformer-level representations, followed with attention-based deep multiple-instance learning (MIL) to aggregate these representations and then predict the potential bioactivity for the query molecule on a given target. We conducted various experiments to validate the data quality of our benchmark dataset, and confirmed EquiVS achieved better performance compared with 10 traditional machine learning or deep learning-based LBVS methods. Further ablation studies demonstrate the significant contribution of molecular conformation for bioactivity prediction, as well as the reasonability and non-redundancy of deep learning architecture in EquiVS. Finally, a model interpretation case study on CDK2 shows the potential of EquiVS in optimal conformer discovery. The overall study shows that our proposed benchmark dataset and EquiVS method have promising prospects in virtual screening applications. [ABSTRACT FROM AUTHOR]

Additional and alternative sustainable food resources are needed as the global human population increases. Marine fishes have long provided essential nutrients, such as omega-3 long-chain (≥C20) polyunsaturated fatty acids (n-3 LC-PUFA), protein, and vitamins to meet human dietary requirements and feed for agricultural production. Many current commercial fish stocks are depleted or fully exploited, but oceanic mesopelagic fishes, particularly the myctophids (lanternfishes), represent a potentially very large and unfished resource. This review analysed the literature on nutritional and biochemical compositions of myctophids as a first step towards understanding the health benefits and risks of consuming them. We found that myctophids have high levels of protein (11–23% wet weight, WW) and variable lipid content (0.5–26% WW). In most species, desirable triacylglycerols or phospholipids dominated over less-desirable wax esters, and most have abundant amounts of health-promoting n-3 LC-PUFA, such as DHA and EPA. Myctophids have low levels of heavy metals and persistent organic pollutants. Most nutritional information is available for species from the Pacific and Southern Oceans and for the genera Benthosema, Electrona, and Diaphus. Myctophids generally possess favourable nutritional profiles, but major gaps in knowledge regarding their stock assessment, ecology and the economic viability for their harvest are barriers to developing sustainable fisheries. [ABSTRACT FROM AUTHOR]

The development of non-enzymatic and highly active electrocatalysts for glucose oxidation with excellent durability for blood glucose sensors has aroused widespread concern. In this work, we report a fast, simple, and low-cost NaBH4 reduction method for preparing ultrafine ternary PtPdCu alloy nanowires (NWs) with a 3D network nanostructure. The PtPdCu NWs catalyst presents significant efficiency for glucose oxidation-reduction (GOR), reaching an oxidative peak-specific activity of 0.69 mA/cm2, 2.6 times that of the Pt/C catalyst (0.27 mA/cm2). Further reaction mechanism investigations show that the NWs have better conductivity and smaller electron transfer resistance. Density functional theory (DFT) calculations reveal that the alloying effect of PtPdCu could effectively enhance the adsorption energy of glucose and reduce the activation energy of GOR. The obtained NWs also show excellent stability over 3600 s through a chronoamperometry test. These self-supported ultrafine PtPdCu NWs with 3D networks provide a new functional material for building blood glucose sensors and direct glucose fuel cells. [ABSTRACT FROM AUTHOR]

As a biological macromolecule, the superantigen staphylococcal enterotoxin C2 (SEC2) is one of the most potent known T-cell activators, and it induces massive cytotoxic granule production. With this property, SEC2 and its mutants are widely regarded as immunomodulating agents for cancer therapy. In a previous study, we constructed an MHC-II-independent mutant of SEC2, named ST-4, which exhibits enhanced immunocyte stimulation and antitumor activity. However, tumor cells have different degrees of sensitivity to SEC2/ST-4. The mechanisms of immune resistance to SEs in cancer cells have not been investigated. Herein, we show that ST-4 could activate more powerful human lymphocyte granule-based cytotoxicity than SEC2. The results of RNA-seq and atomic force microscopy (AFM) analysis showed that, compared with SKOV3 cells, the softer ES-2 cells could escape from SEC2/ST-4-induced cytotoxic T-cell-mediated apoptosis by regulating cell softness through the CDC42/MLC2 pathway. Conversely, after enhancing the stiffness of cancer cells by a nonmuscle myosin-II-specific inhibitor, SEC2/ST-4 exhibited a significant antitumor effect against ES-2 cells by promoting perforin-dependent apoptosis and the S-phase arrest. Taken together, these data suggest that cell stiffness could be a key factor of resistance to SEs in ovarian cancer, and our findings may provide new insight for SE-based tumor immunotherapy. [ABSTRACT FROM AUTHOR]

In order to solve the problem of poor dispersion and stability of mixed metal hydroxide (MMH), a kind of mixed metal hydroxide-like compound (MMHlc) gel was synthesized for use as the base mud in drilling fluid instead of bentonite gel. Na2CO3, Na2SiO3, and C17H33CO2Na were used as precipitants to form MMHlc with larger interlayer spacing and smaller particle size. MMHlc was synthesized by the coprecipitation method at 25 °C with a metal molar ratio of Mg:Al:Fe = 3:1:1. The performance evaluation of the treated drilling fluid showed that MMHlc (S2) synthesized using Na2SiO3 as the precipitant had the characteristics of low viscosity, low filtration, and a high dynamic plastic ratio at 25 °C, which fully met the requirements of oil field application, and it maintained its excellent properties after being aged at 250 °C for 16 h. Linear expansion and rolling recovery experiments showed that the S2 sample had excellent rheological properties and good inhibition. X-ray diffraction and FT-IR experiments showed that S2 had the most complete crystal structure, its interlayer distance was large, and its ion exchange capacity was strong. The thermogravimetric experiment showed that the S2 crystal was stable and the temperature resistance of the crystal could reach 340 °C. Zeta potential, particle size analysis, SEM, and TEM results showed that S2 is a nanomaterial with a complete morphology and uniform distribution. The drilling fluid of this formula had the characteristics of low viscosity, low filtration loss, and a high dynamic plastic ratio, and it met the conditions for oil field application. Considering these results, the new MMH prepared by our research institute is a drilling fluid material that can be used at ultra-high temperatures and can provide important support for drilling ultra-deep wells. [ABSTRACT FROM AUTHOR]

Owing to the combination of bitumen aging, traffic loading, and environmental factors, the performance of asphalt will gradually deteriorate with time. However, characterizing the deterioration is still challenging. Aiming to reveal how the performance of asphalt pavement deteriorates with time, the AASHTO design equation was applied to investigate the evolution trend of pavement performance by adopting a reliability method in terms of freeze–thaw cycles. It was found that the combination of the rate of evolution and curvature could identify the abrupt change points and significant variation stages. Risk analysis was introduced to provide a novel method to evaluate the pavement performance evolution by identifying the change of the hazard rate and the cumulative hazard rate. It was found that the evolution curve of asphalt pavement strength reliability could be divided linearly during its life cycle, which can be extended to any n-stage linear deterioration model according to the actual situation. Moreover, reliability levels for pavement strength were also proposed in this research according to the integrated pavement travel and structure performance. [ABSTRACT FROM AUTHOR]

Chaos has been one of the most effective cryptographic sources since it was first used in image-encryption algorithms. This paper closely examines the development process of chaos-based image-encryption algorithms from various angles, including symmetric and asymmetric algorithms, block ciphers and stream ciphers, and integration with other technologies. The unique attributes of chaos, such as sensitivity to initial conditions, topological transitivity, and pseudo-randomness, are conducive to cross-referencing with other disciplines and improving image-encryption methods. Additionally, this paper covers practical application scenarios and current challenges of chaotic image encryption, thereby encouraging researchers to continue developing and complementing existing situations, and may also serve as a basis of future development prospects for chaos-based image encryption. [ABSTRACT FROM AUTHOR]

Network security situational awareness is based on the extraction and analysis of big data, and by understanding these data to evaluate the current network security status and predict future development trends, provide feedback to decision-makers to make corresponding countermeasures, and achieve security protection for the network environment. This article focuses on artificial intelligence, summarizes the related definitions and classic models of network security situational awareness, and provides an overview of artificial intelligence. Starting from the method of machine learning, it specifically introduces the research status of neural-network-based network security situational awareness and summarizes the research work in recent years. Finally, the future development trends of network security situational awareness are summarized, and its prospects. [ABSTRACT FROM AUTHOR]

Microplastics (MPs) are receiving increasing attention because of their potential harm to the environment and human health. This research aims to summarize the abundance, toxicological effects, and analysis methods of MPs, as well as present their current status and trends in scientific research. Bibliometric analysis confirmed a substantial rise in annual research papers on MPs, predominantly over the previous nine years. The central research areas relating to MPs include distribution, sources, toxic effects, analytical approaches, and adsorption of MPs with other pollutants. Airborne MPs are a primary source of microplastic pollution in remote areas. Humans may inhale and ingest MPs, leading to the accumulation of these particles in their bodies. Additionally, microplastics can have biological toxicity that poses a potential threat to human health. Standard procedures for sampling and both qualitative and quantitative analysis of microplastics in various environmental media must be established urgently to enable effective comparison of experimental conclusions. [ABSTRACT FROM AUTHOR]

A water quality parameter retrieval scheme based on the UAV push-broom hyperspectral images was designed and validated for assessing the ecological health of Zhang Wei Xin River in Dezhou distinct, China. First, a UAV carrying a push-broom hyperspectral imager that is lightweight and has a small size was used to acquire high spatial and hyperspectral resolution images. Then, the mosaicked reflectance data of the whole river were produced by a seamless image mosaicking method with high geometrical accuracy and spectral fidelity. Next, the in-field measurements of different parameters and the corresponding spectral reflectance from the mosaicked images at the sampling points were used to build the water quality parameter retrieval models for total phosphorus (TP), chlorophyll a (Chla), and total suspended solids (TSS). To validate the model, the retrieval results of the testing sampling points were compared with the measured parameters. The coefficients of determination R2 of TP, Chla, and TSS were 0.886, 0.918, and 0.968, respectively. The retrieved TP, Chla, and TSS maps showed that the water pollution of Zhang Wei Xin River is serious, the total phosphorus exceeds the standard, and the water body is in a state of eutrophication. The UAV-based hyperspectral remote sensing technique provides a cost-effective method for inland water monitoring at a local scale with high accuracy. [ABSTRACT FROM AUTHOR]

Aneuploidy is usually more detrimental than altered ploidy of the entire set of chromosomes. To explore the regulatory mechanism of gene expression in aneuploidy, we analyzed the transcriptome sequencing data of metafemale Drosophila. The results showed that most genes on the X chromosome undergo dosage compensation, while the genes on the autosomal chromosomes mainly present inverse dosage effects. Furthermore, long noncoding RNAs (lncRNAs) have been identified as key regulators of gene expression, and they are more sensitive to dosage changes than mRNAs. We analyzed differentially expressed mRNAs (DEGs) and differentially expressed lncRNAs (DELs) in metafemale Drosophila and performed functional enrichment analyses of DEGs and the target genes of DELs, and we found that they are involved in several important biological processes. By constructing lncRNA-mRNA interaction networks and calculating the maximal clique centrality (MCC) value of each node in the network, we also identified two key candidate lncRNAs (CR43940 and CR42765), and two of their target genes, Sin3A and MED1, were identified as inverse dosage modulators. These results suggest that lncRNAs play an important role in the regulation of genomic imbalances. This study may deepen the understanding of the gene expression regulatory mechanisms in aneuploidy from the perspective of lncRNAs. [ABSTRACT FROM AUTHOR]

The South-to-North Water Diversion Project (SNWDP) is one of the largest cross-basin and cross-region water transfer projects in the world. The Danjiangkou reservoir area, a haven of diverse species, serves as a core water source for the Central Line of the SNWDP. Yet, less research has been conducted on changes in land use and ecosystem services (ESs) in the Danjiangkou reservoir area in the context of the implementation of the SNWDP and other national projects. In this study, we aim to reveal evolutions of land uses and ESs in the Danjiangkou reservoir area and the response of ESs to natural and socio-economic factors. This is essential to enhance the regional sustainable management of the Danjiangkou reservoir area. Based on classified land use maps and the InVEST model, we first analyzed the land use changes and evaluated three typical types of ESs (i.e., water yield (WY), carbon storage (CS) and habitat quality (HQ)) in the Danjiangkou reservoir area during 2000 to 2018. Then, we detected the spatial clustering characteristics and tradeoffs and synergistic relationships of multiple ESs through hot spot analysis and correlation analysis. Finally, we adopt the geographical detector model (GDM) to identify key driving factors of ESs changes. The results show that: (1) During 2000–2018, the area of arable land and woodland decreased by 1.65% and 0.8%, respectively, while the proportion of construction land and water area increased by 1.31% and 1.39%, respectively. (2) The greatest decrease was in WY, decreasing by 59%, while the change in HQ was relatively stable, but showed spatial heterogeneity. (3) The northern, southern and western districts of the reservoir area showed mainly synergies among multiple ESs, while other regions showed mainly trade-offs. (4) Road network density, proportion of construction land and normalized difference vegetation index are the leading factors for ESs variations. These findings can provide reference for formulating more reasonable ecological protection strategies, so as to realize the sustainable management of SNWDP and its headwaters region. [ABSTRACT FROM AUTHOR]

Series-winding three-phase PMSMs have a higher bus voltage utilization than the conventional three-phase PMSMs with star connection. This topology is suitable for applications with a limited bus voltage. However, the zero-sequence current controller will reduce the bus voltage utilization of the series-winding PMSMs, which causes problems in the flux-weakening controller design. The conventional flux-weakening control algorithms will cause the series-winding PMSMs to enter the overmodulation region early and degrade the performance of the zero-sequence current suppression algorithm. In this paper, a new flux-weakening controller with a dynamic fundamental voltage limit (FW-DFVL) is designed for the series-winding three-phase PMSM traction system. Firstly, the space vector modulation method combines the proposed virtual zero-sequence vectors to realize both the fundamental current generation and the zero-sequence current suppression. The accurate bus voltage utilization in the fundamental current subspace can be derived from the proposed modulation method. Secondly, the gradient descent method generates the flux-weakening d-axis reference current with the dynamic fundamental voltage, which will converge faster than the conventional PI-based flux-weakening control scheme. Thirdly, the flux-weakening controller in the overmodulation region is also designed where the zero-sequence current will no longer be suppressed. The bus voltage utilization is Vdc in this operation mode. Finally, both the simulation and experimental results are utilized to verify the effectiveness of the proposed FW-DFVL, where faster dynamic performance and higher bus utilization are observed. [ABSTRACT FROM AUTHOR]

Modified clay (MC) technology is the most effective method to control harmful algal blooms (HABs) and has been widely testified in many countries in recent decades. Although dissolved algal organic matter (dAOM) has been found to be abundant in HAB-affected waters, little is known about its effect on MC flocculation. Prorocentrum donghaiense was chosen as the model organism in this study. The flocculation of MC with different concentrations of dAOM was observed by particle image velocimeter, and the removal efficiency of MC to microalgae was determined using a fluorometer. The results showed that a small amount of dAOM resulted in faster flocculation, larger flocs, higher floc strength and better floc regeneration capacity, and the removal efficiency of microalgae by MC could reach about 80%. However, large amounts of dAOM produced during the occurrence of HABs could inhibit the flocculation of MC, and the removal efficiency of microalgae was only about 35%. Furthermore, with the increase of dAOM, the zeta potential of MC particles decreases from 1.56 mV to −18.9 mV, and the repulsive force between the particles also increases. The examination of 18-angle laser light scattering gel permeation chromatography and specific ultraviolet absorption (SUVA254) revealed that some hydrophobic organic macromolecules preferred to attach to MC and increase MC flocculation at a tiny amount of dAOM, while a higher concentration of dAOM would inhibits flocculation by reducing surface activity and intergranular repulsion. According to the findings of this study, the dosage of MC must be increased in order to obtain the best algal removal efficiency with MC. [ABSTRACT FROM AUTHOR]

Highly integrated three-dimensional magnetic sensors have just been developed and have been used in some fields, such as angle measurement of moving objects. The sensor used in this paper is a three-dimensional magnetic sensor with three Hall probes highly integrated inside; 15 sensors are used to design the sensor array and then measure the magnetic field leakage of the steel plate; the three-dimensional component characteristics of the magnetic field leakage are used to determine the defect area. Pseudo-color imaging is the most widely used in the imaging field. In this paper, color imaging is used to process magnetic field data. Compared with analyzing the three-dimensional magnetic field information obtained directly, this paper converts the magnetic field information into color image information through pseudo-color imaging and then obtains the color moment characteristic values of the color image in the defect area. Moreover, the least-square support-vector machine and particle swarm optimization (PSO-LSSVM) algorithm are used to quantitatively identify the defects. The results show that the three-dimensional component of the magnetic field leakage can effectively determine the area range of defects, and it is feasible to use the color image characteristic value of the three-dimensional magnetic field leakage signal to identify defects quantitatively. Compared with a single component, the three-dimensional component can effectively improve the identification rate of defects. [ABSTRACT FROM AUTHOR]

The performance of asphalt pavement will deteriorate gradually due to oxidation, also named the ageing of asphalt binders. In this study, the research progress on the multiscale evaluation of asphalt aging behaviour in the past decade was reviewed to further analyse the evolution law of asphalt aging behaviour and determine the asphalt aging mechanism. Firstly, artificial aging methods were introduced, the factors affecting asphalt aging behaviour were analysed, and the changes of asphalt properties before and after aging were identified. Secondly, the methods and research progress in terms of the evaluation of asphalt aging degrees were summarised from the macro-, mesoscopic-, micro-, and nanoscales. Finally, considering extensively studied rheological properties as an example, the correlations among the rheological properties of asphalt in the aging process and the conventional physical properties, chemical composition, microscopic properties, nano-molecular dynamics, and other parameters were analysed. The results show that various scales are interrelated, and the multiscale evaluation of asphalt aging can provide a more comprehensive prediction of the extent of asphalt aging. The correlation between multiple scales enables a thorough analysis of the mechanism of asphalt aging and the evaluation of asphalt aging behaviour at multiple scales. [ABSTRACT FROM AUTHOR]

It remains controversial to choose anesthesia for transcatheter aortic valve implantation (TAVI). A meta-analysis of cohort studies was conducted to assess the efficacy and safety of local anesthesia (LA) compared to general anesthesia (GA) in TAVI. All relevant studies published from 1 January 2002, to 31 June 2022, were searched in Ovid, PubMed, Embase, Web of Science, and Cochrane Library. A total of 34 studies involving 23,480 patients were included in the meta-analysis. TAVI with LA was associated with a significant reduction in hospital stay [WMD = −2.48, 95% CI (−2.80, −2.16), p < 0.00001], operative [WMD = −12.25, 95% CI (−13.73, −10.78), p < 0.00001] and fluoroscopy time [WMD = −3.30, 95% CI (−5.40, −1.19), p = 0.002], and an increased risk of acute kidney injury [OR = 1.31, 95% CI (1.01, 1.69), p = 0.04] and a reduced incidence of major bleeding [OR = 0.59, 95% CI (0.46, 0.75), p < 0.0001] and the use of cardiovascular drugs [OR = 0.17, 95% CI (0.05, 0.57), p = 0.004]. No differences were found between LA and GA for 30-day mortality, procedural success rate, myocardial infarction, permanent pacemaker implantation, paravalvular leak, shock, and cerebrovascular events. Overall, 4.4% of LA converted to GA. Based on current evidence, our results suggested that LA strategies reduced hospital stay, operative time, fluoroscopy time, cardiovascular drug consumption, and major bleeding rates in patients undergoing TAVI but led to increased acute kidney injury rates. Further studies and randomized trials are required to verify the presented findings and to identify patients who might benefit from LA. [ABSTRACT FROM AUTHOR]

For 3D printing based on Digital Light Processing (DLP) technology, the tradeoff of size and resolution remains challenging due to the limitations of the existing techniques. Therefore, we propose an approach to improve the feature resolution without sacrificing the part size. It is achieved by changing the projection distance and then adjusting the projection resolution and format, which is different from the previous printing principle of fixed resolution. To achieve this process, the tripteron 3-Degree-of-Freedom (3-DoF) parallel mechanism is innovatively applied to the DLP 3D printing structure, which simplifies the control process. Since the projection is fixed on the motion platform, the projection distance changes as the platform moves in space. Then the PLC-based program is developed according to the motion process, which successfully runs on the established prototype. Finally, the experiments are designed through the orthogonal method to optimize the molding process parameters. The effectiveness of the approach is verified by the feature forming comparison experiment. The results show that it can reduce the size of features by about 1.3 times through adjusting the projection resolution under the same size parts. Our method provides a new way for solving the contradiction, but more research needs to be done. [ABSTRACT FROM AUTHOR]

In recent years, wireless sensor networks have been used in a wide range of indoor localization-based applications. Although promising, the existing works are dependent on a large number of anchor nodes to achieve localization, which brings the issues of increasing cost and additional maintenance. Inspired by the cross-technology communication, an emerging technique that enables direct communication among heterogeneous wireless devices, we propose an anchor-free distributed method, which leverages the installed Wi-Fi APs to range instead of traditional anchor nodes. More specifically, for the asymmetric coverage of Wi-Fi and ZigBee nodes, we first design a progressive method, where the first unknown node estimates its location based on two Wi-Fi APs and a sink node, then once achieving its position, it acts as the alternative sink node of the next hop node. This process is repeated until the new members can obtain their positions. Second, as a low-power technology, ZigBee signal may be submerged in strong signal such as Wi-Fi. To overcome this problem, a maximum prime number is deployed to be the Wi-Fi broadcasting period based on the numerical analysis theory. Among many of prime numbers, we have the opportunity to select an appropriate one to achieve full coverage with the relatively small packet collisions. Last, simulations and experiments are performed to evaluate the proposal. The evaluation results show that the proposal can achieve decimeter level accuracy without deploying any anchor node. Moreover, the proposal demonstrates the anti-interference ability in the crowded open spectrum environment. [ABSTRACT FROM AUTHOR]

Integrated Motor Drives (IMDs) have recently received extensive attention. In electric vehicles (EVs), electric propulsion aircraft, and ship propulsion systems, integrated motors have the great potential to replace traditional motors with the distinct merits of compact size, high power density, high efficiency, and high-cost effectiveness. This paper investigates and reviews integrated motor drives' development and critical technologies. It not only reveals the research progress of the motor structure, converter, volume optimization, heat dissipation design, and weakening electromagnetic interference of integrated motor drives but also explores in detail the applications of wide-bandgap semiconductors and the integration of LCL filters. In addition, this paper also puts forward the concept of integrated motor drive integration level and establishes a corresponding quantitative method to evaluate IMDs integration level. In the future, integrated wireless motor drives will have a broad scope of research and application. IMDs systems will play an important role in applications requiring high power density, providing solutions to motor system size and heat dissipation problems. This overview will help clarify the opportunities, challenges, and future development of IMDs. [ABSTRACT FROM AUTHOR]

Solid-free drilling fluid has more advantages as a new type of drilling fluid compared with traditional drilling fluid, such as improving drilling efficiency, protecting oil and not having clay particles clog the oil and gas layer. In this study, Zn/Cu/Fe-doped magnesium–aluminum hydroxide (Mg-Al MMH) was prepared using the co-precipitation method and evaluated in solid-free drilling fluid. The inhibition mechanism of synthesized hydroxide was analyzed by X-ray diffraction, laser particle-size analysis and thermogravimetric analysis. The samples were directly used as drilling fluid base muds for performance evaluation. The results showed that the linear expansion rate of 4% M6-Fe was only 12.32% at room temperature within 2 h, that the linear expansion rate was 20.28% at 90 °C and that the anti-swelling rate was 81.16% at room temperature, indicating that it has a strong inhibition ability at both room temperature and at high temperatures. Meanwhile, the possibility of multi-mixed metal hydroxide as a drilling fluid base mud is discussed in this study. We found that 4% M6-Fe exhibited low viscosity, a high YP/PV ratio and high temperature resistance, and its apparent viscosity retention rate reached 100% rolled at 200 °C for 16 h, with a YP/PV ratio of 2.33. [ABSTRACT FROM AUTHOR]

This paper introduces a miniaturized system in package (SIP) for a Ku-band four-channel RF transceiver front-end. The SIP adopts the packaging scheme of an inner heat-dissipation gasket and multi-layer substrate in the high temperature co-fired ceramics (HTCC) shell with a metal heat sink at the bottom. The gasket effectively solves the heat-dissipation problem of high-power transceiver chips, and the multi-layer substrate achieves the interconnection between multiple chips. Within the limited size of 14.0 × 14.0 × 2.5 mm3, the SIP integrates five bidirectional amplifier chips, an amplitude-phase control multi-function chip, and two power modulation chips to realize the Ku-band four-channel RF transceiver front-end. Transmitting power over 0.5 W (27dBm) and receiving noise figure of 3.4 dB are achieved in the Ku-band. The efficient heat dissipation, high air tightness, and excellent integration are simultaneously realized in this SIP. The measurement results show that the performance is stable in the receiving and transmitting states, and the SIP based on HTCC technology has specific prospects for radar transceiver application. [ABSTRACT FROM AUTHOR]