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Finding the most interesting areas of an image is the aim of saliency detection. Conventional methods based on low-level features rely on biological cues like texture and color. These methods, however, have trouble with processing complicated or low-contrast images. In this paper, we introduce a deep neural network-based saliency detection method. First, using semantic segmentation, we construct a pixel-level model that gives each pixel a saliency value depending on its semantic category. Next, we create a region feature model by combining both hand-crafted and deep features, which extracts and fuses the local and global information of each superpixel region. Third, we combine the results from the previous two steps, along with the over-segmented superpixel images and the original images, to construct a multi-level feature model. We feed the model into a deep convolutional network, which generates the final saliency map by learning to integrate the macro and micro information based on the pixels and superpixels. We assess our method on five benchmark datasets and contrast it against 14 state-of-the-art saliency detection algorithms. According to the experimental results, our method performs better than the other methods in terms of F-measure, precision, recall, and runtime. Additionally, we analyze the limitations of our method and propose potential future developments. [ABSTRACT FROM AUTHOR]

Simple Summary: This review is focused on the role of root exudates on beneficial rhizobacterial colonization. The dynamic interaction between root exudates and rhizobacteria is influenced by plant genotype, development, environmental biotic factors, and abiotic factors. Bacterial-specific metabolism plays crucial roles in rhizosphere competence and rhizobacterial colonization ability. Diverse types of root exudates serve as nutrients, signals, or antimicrobial substances, facilitating root colonization by beneficial bacteria. Certain secondary metabolites selectively promote root colonization by bacteria with specialized functions. Soil-beneficial microbes in the rhizosphere play important roles in improving plant growth and health. Root exudates play key roles in plant–microbe interactions and rhizobacterial colonization. This review describes the factors influencing the dynamic interactions between root exudates and the soil microbiome in the rhizosphere, including plant genotype, plant development, and environmental abiotic and biotic factors. We also discuss the roles of specific metabolic mechanisms, regulators, and signals of beneficial soil bacteria in terms of colonization ability. We highlight the latest research progress on the roles of root exudates in regulating beneficial rhizobacterial colonization. Organic acids, amino acids, sugars, sugar alcohols, flavonoids, phenolic compounds, volatiles, and other secondary metabolites are discussed in detail. Finally, we propose future research objectives that will help us better understand the role of root exudates in root colonization by rhizobacteria and promote the sustainable development of agriculture and forestry. [ABSTRACT FROM AUTHOR]

In recent years, data-driven deep networks have demonstrated remarkable detection performance for infrared small targets. However, continuously increasing the depth of neural networks to enhance performance has proven impractical. Consequently, the integration of prior physical knowledge related to infrared small targets within deep neural networks has become crucial. It aims to improve the models' awareness of inherent physical characteristics. In this paper, we propose a novel dual-domain prior-driven deep network (DPDNet) for infrared small-target detection. Our method integrates the advantages of both data-driven and model-driven methods by leveraging the prior physical characteristics as the driving force. Initially, we utilize the sparse characteristics of infrared small targets to boost their saliency at the input level of the network. Subsequently, a high-frequency feature extraction module, seamlessly integrated into the network's backbone, is employed to excavate feature information. DPDNet simultaneously emphasizes the prior sparse characteristics of infrared small targets in the spatial domain and their prior high-frequency characteristics in the frequency domain. Compared with previous CNN-based methods, our method achieves superior performance while utilizing fewer convolutional layers. It has a performance of 78.64% IoU, 95.56 Pd, and 2.15 × 10−6 Fa on the SIRST dataset. [ABSTRACT FROM AUTHOR]

Combustion instability is a common thermoacoustic coupling problem in combustion systems, and the pressure oscillations generated inevitably damage the combustion system. Studying the mechanism of combustion instability, especially the triggering problem of combustion instability, is particularly important for understanding combustion instability. This article adopts experimental research methods. The flame transfer function and flame describing function governing pressure pulsation were hereby measured to study the effect of heat release rate fluctuation on acoustic disturbance. By triggering combustion instability through ignition, the growth process of combustion instability was also studied. The results showed that flame pulsation amplitude shows a complex curvature when the frequency is lower than 200 Hz, while the growth rate of pulsation amplitude monotonically decreases as frequencies increase above 200 Hz. According to the considerable self−excited combustion instability tests, the oscillation amplitudes in the limit cycle state are generally greater than 0.4, while the pressure amplitudes in the limited state are less than 0.2, thus verifying the concept of a trigger threshold for low−frequency oscillation. In addition, analysis of the growth rate, the pressure and the attractor of the heat release pulsation observed after the triggering of combustion instability reveals that the triggering of combustion instability is a gradual coupling process between oscillation pressure and heat release rate pulsation. [ABSTRACT FROM AUTHOR]

The abnormal heating of composite insulators on transmission lines frequently occurs, seriously threatening the power grid's safe and stable operation. For different types of abnormal heating composite insulators, undifferentiated replacement wastes a lot of labor and material resources. This study explores the abnormal heating composite insulators under different environmental humidity and wind speed conditions. The heating and discharge of composite insulators are observed, and the heating range, heating shape, and temperature rise (ΔT) are analyzed. The abnormal heating of the sheath-aging composite insulator is related to the aging of the silicone rubber and the environmental humidity. The partial discharge caused by the core rod's defect is the primary source of the temperature rise in the decay-like insulator. The heating range of the contaminated insulator is connected to the environmental humidity, and the ΔT increases with the salt density. The ΔT and heating range of the three types of abnormal heating increase with the ambient humidity. The heating phenomenon under low humidity is an important characteristic that distinguishes decay-like and contaminated insulators from sheath-aging insulators. Therefore, the on-site infrared inspection should be carried out in sunny and windless weather to prevent the impact of high humidity and wind speed on infrared temperature measurement. [ABSTRACT FROM AUTHOR]

Simple Summary: In the clinical diagnosis of lung cancer, doctors mainly rely on pathological images to make decisions about the patient's condition. Therefore, pathology diagnosis is known as the gold standard for disease diagnosis. In recent years, convolutional neural networks have been widely used for computer-aided diagnosis to relieve the work pressure of pathologists. However, this method still faces two problems: from the perspective of clinical application, the current neural network model can only perform simple lung cancer type detection; From the perspective of model design, the strategy adopted by researchers to improve the accuracy of diagnosis is often to carry out complex model design, which will cause the model parameters to be too large to be clinically deployed. In this study, we first prepared a lung cancer dataset that can provide more complex cancer information to the model. Then, using only a novel visual activation function, the ability of convolutional neural networks to detect interclass and intraclass differences in cancer pathological images is enhanced. Lung cancer is one of the most common malignant tumors in human beings. It is highly fatal, as its early symptoms are not obvious. In clinical medicine, physicians rely on the information provided by pathology tests as an important reference for the final diagnosis of many diseases. Therefore, pathology diagnosis is known as the gold standard for disease diagnosis. However, the complexity of the information contained in pathology images and the increase in the number of patients far outpace the number of pathologists, especially for the treatment of lung cancer in less developed countries. To address this problem, we propose a plug-and-play visual activation function (AF), CroReLU, based on a priori knowledge of pathology, which makes it possible to use deep learning models for precision medicine. To the best of our knowledge, this work is the first to optimize deep learning models for pathology image diagnosis from the perspective of AFs. By adopting a unique crossover window design for the activation layer of the neural network, CroReLU is equipped with the ability to model spatial information and capture histological morphological features of lung cancer such as papillary, micropapillary, and tubular alveoli. To test the effectiveness of this design, 776 lung cancer pathology images were collected as experimental data. When CroReLU was inserted into the SeNet network (SeNet_CroReLU), the diagnostic accuracy reached 98.33%, which was significantly better than that of common neural network models at this stage. The generalization ability of the proposed method was validated on the LC25000 dataset with completely different data distribution and recognition tasks in the face of practical clinical needs. The experimental results show that CroReLU has the ability to recognize inter- and intra-class differences in cancer pathology images, and that the recognition accuracy exceeds the extant research work on the complex design of network layers. [ABSTRACT FROM AUTHOR]

As basalt fiber has better mechanical properties and stability than glass fiber, cross arms made of continuous basalt-fiber-reinforced epoxy matrix composites are capable of meeting the mechanical requirements in the event of typhoons and broken lines in coastal areas, mountainous areas and other special areas. In this paper, continuous basalt-fiber-reinforced epoxy matrix composites were used to fabricate the core rods and composite cross arms. The results verified that basalt fiber composite cross arms can meet the strict requirements of transmission lines in terms of quality and reliability. In addition to high electrical insulation performance, the flexural modulus and the flexural strength of basalt fiber core rods are 1.8 and 1.06 times those of glass fiber core rods, respectively. Basalt fiber core rods were found to be much better load-bearing components compared to glass fiber core rods. However, the leakage current and the result of scanning electron microscopy (SEM) analysis reveal that the interface bonding strength between basalt fibers and the matrix resin is weak. A 3D reconstruction of micro-CT indicates that the volume of pores inside basalt fiber core rods accounts for 0.0048% of the total volume, which is greater than the 0.0042% of glass fiber rods. Therefore, improving the interface bond between basalt fibers and the resin can further improve the properties of basalt fiber core rods. [ABSTRACT FROM AUTHOR]

In order to promote the application of composite insulators in coastal areas with high temperature, high humidity and high salt, it is of great importance to develop matrix resin with salt corrosion resistance for composite core rods. In this study, bisphenol A epoxy resin was modified by blending with alicyclic epoxy resin (2021P). Three different proportions of 2021P/DGEBA blend resins (0% 2021P/DGEBA, 10% 2021P/DGEBA and 20% 2021P/DGEBA) were prepared, and the high salt medium corrosion test was carried out. The physicochemical (FTIR, DMA, TGA) and electrical properties (dielectric loss, leakage current and breakdown field strength) of the blend resin before and after aging were tested and analyzed, and the optimal blend proportion was determined. The results showed that after salt aging, the Tg of 0% 2021P/DGEBA decreased to 122.99 °C, while the Tg of 10% 2021P/DGEBA reached 134.89 °C; The leakage current of 0% 2021P/DGEBA increased to 48.994 μA, while that of 10% 2021P/DGEBA only increased to 44.549 μA; The breakdown field strength of 0% 2021P/DGEBA dropped to 40.36 kv/mm, while that of 10% 2021P/DGEBA only dropped to 43.63 kv/mm. The introduction of 2021P enhanced the salt corrosion resistance of the blend resin, which could hinder the penetration, diffusion and erosion of external media (such as Na+, Cl−, H2O, etc.) to the matrix resin. The comprehensive properties of 10% 2021P/DGEBA blend system reached the best, which was better than other blending resins, showing great application potential. [ABSTRACT FROM AUTHOR]

In order to investigate the effect of gradient interface on the mechanical properties of Cu/WCP functional gradient materials, digital image correlation technique was used to analyze the mechanical characteristics of laminated Cu/WCP functional gradient material under tension load in the layer direction. In this paper, the deformation information of the specimens is obtained by the digital image correlation method. In order to obtain high-precision measurement results, speckle patterns with small spots and uniform distribution are prepared on the specimen surface by using small sample speckle preparation technology. The tensile experimental results showed that the incorporation of WC particles significantly improved the stiffness and strength of Cu/WCP composites. Meanwhile, the plastic strain and plastic strain rate are non-uniform in each layer of the five-layer Cu/WCP functional gradient material under the tension load along the layer direction. The plastic strain and plastic strain rate in each layer gradually increase along with the decreasing direction of WC content. It is found, from the analysis of experimental results, the existence of the gradient interface has an obvious inhibitory effect on the increase in plastic strain rate along the decreasing direction of WC content, and the specimen fracture location also has a certain relationship with the plastic strain rate, which reflects the important influence of the gradient interface on the mechanical properties of Cu/WCP functional gradient materials. [ABSTRACT FROM AUTHOR]

To address the challenge of balancing the mechanical, thermal insulation, and flame-retardant properties of building insulation materials, this study presented a facile approach to modify the rigid polyurethane foam composites (RPUFs) via commercial expandable graphite (EG), ammonium polyphosphate (APP), and silica aerogel (SA). The resulting EG/APP/SA/RPUFs exhibited low thermal conductivity close to neat RPUF. However, the compressive strength of the 6EG/2APP/SA/RPUF increased by 49% along with achieving a V-0 flame retardant rating. The residual weight at 700 °C increased from 19.2 wt.% to 30.9 wt.%. Results from cone calorimetry test (CCT) revealed a 9.2% reduction in total heat release (THR) and a 17.5% decrease in total smoke production (TSP). The synergistic flame-retardant mechanism of APP/EG made significant contribution to the excellent flame retardant properties of EG/APP/SA/RPUFs. The addition of SA played a vital role in reducing thermal conductivity and enhancing mechanical performance, effectively compensating for the shortcomings of APP/EG. The cost-effective EG/APP/SA system demonstrates a positive ternary synergistic effect in achieving a balance in RPUFs properties. This study provides a novel strategy aimed at developing affordable building wall insulation material with enhanced safety features. [ABSTRACT FROM AUTHOR]

Scene-matching navigation is one of the essential technologies for achieving precise navigation in satellite-denied environments. Selecting suitable-matching areas is crucial for planning trajectory and reducing yaw. Most traditional selection methods of suitable-matching areas use hierarchical screening based on multiple feature indicators. However, these methods rarely consider the interrelationship between different feature indicators and use the same set of screening thresholds for different categories of images, which has poor versatility and can easily cause mis-selection and omission. To solve this problem, a suitable-matching areas' selection method based on multi-level saliency is proposed. The matching performance score is obtained by fusing several segmentation levels' salient feature extraction results and performing weighted calculations with the sub-image edge density. Compared with the hierarchical screening methods, the matching performance of the candidate areas selected by our algorithm is at least 22.2% higher, and it also has a better matching ability in different scene categories. In addition, the number of missed and wrong selections is significantly reduced. The average matching accuracy of the top three areas selected by our method reached 0.8549, 0.7993, and 0.7803, respectively, under the verification of multiple matching algorithms. Experimental results show this paper's suitable-matching areas' selection method is more robust. [ABSTRACT FROM AUTHOR]

The Lewy bodies and Lewy neurites are key pathological hallmarks of Parkinson's disease (PD). Single-point mutations associated with familial PD cause α-synuclein (α-Syn) aggregation, leading to the formation of Lewy bodies and Lewy neurites. Recent studies suggest α-Syn nucleates through liquid–liquid phase separation (LLPS) to form amyloid aggregates in a condensate pathway. How PD-associated mutations affect α-Syn LLPS and its correlation with amyloid aggregation remains incompletely understood. Here, we examined the effects of five mutations identified in PD, A30P, E46K, H50Q, A53T, and A53E, on the phase separation of α-Syn. All other α-Syn mutants behave LLPS similarly to wild-type (WT) α-Syn, except that the E46K mutation substantially promotes the formation of α-Syn condensates. The mutant α-Syn droplets fuse to WT α-Syn droplets and recruit α-Syn monomers into their droplets. Our studies showed that α-Syn A30P, E46K, H50Q, and A53T mutations accelerated the formation of amyloid aggregates in the condensates. In contrast, the α-Syn A53E mutant retarded the aggregation during the liquid-to-solid phase transition. Finally, we observed that WT and mutant α-Syn formed condensates in the cells, whereas the E46K mutation apparently promoted the formation of condensates. These findings reveal that familial PD-associated mutations have divergent effects on α-Syn LLPS and amyloid aggregation in the phase-separated condensates, providing new insights into the pathogenesis of PD-associated α-Syn mutations. [ABSTRACT FROM AUTHOR]

Basalt fiber (BF) has a high mechanical strength, excellent temperature resistance, good chemical stability, low energy consumption, and an environmentally friendly production process. In addition, BF-reinforced polymers (BFRPs) have good corrosion resistance and designability; thus, they meet the application requirements of electrical equipment, such as new conductors, insulating pull rods, and composite cross-arms. However, there are still a series of technical issues in the mass production of BF, and the stability of the products needs to be further improved. Therefore, the research on the production, modification, and application of BF is necessary. This paper discusses the chemical composition and production technology of BF, describes the morphology and properties of BF, summarizes the interface problems and modification methods of composites, and finally, introduces the application prospects of BF in the field of electrical materials, which is expected to provide a reference for the application and promotion of BFRP in the future. [ABSTRACT FROM AUTHOR]

Traditional monitoring methods cannot obtain the overall thermal information for power transformers. To solve this problem, a distributed fiber optic sensor (DFOS) was creatively applied inside an operating 35 kV power transformer by highly integrating with the electromagnetic wires. Then, the transformer prototype with totally global sensing capability was successfully developed and it was qualified for power grid application through the strict ex-factory tests. The as designed optical fiber sensor works stably all the time with a temperature accuracy of ±0.2 °C and spatial positioning accuracy of 0.8 m. Based on the obtained internal temperature distribution, Gaussian convolution was further applied for the signal processing and hereby, the hotspots for all the windings and iron cores could be accurately traced. The hottest points were located at 89.1% (55 °C) of the high voltage winding height and 89.7% (77.5 °C) of the low voltage winding height. The actual precise hotspot location corrected the traditional cognition on the transformer windings and it would serve as an essential reference for the manufactures. This new nondestructive internal sensing and condition monitoring method also exhibits a promising future for the DFOS applying in the high-voltage electrical apparatus industry. [ABSTRACT FROM AUTHOR]

In order to realize distributed measurement of transformer winding temperature and deformation, a transformer winding modification scheme with a built-in distributed optical fiber was designed. By laying a single-mode fiber and a multi-mode fiber on the transformer winding, the Brillouin optical time domain reflection technique (BOTDR) and the Raman optical time domain reflection technique (ROTDR) are used to measure the strain and temperature of the winding to complete the more accurate winding deformation detection. The accuracy of strain and temperature sensing of this scheme was verified by simulation. Then, according to the scheme, a winding model was actually wound, and the deformation and temperature rise tests were carried out. The test results show that this scheme can not only realize the deformation detection and positioning of the winding, but can also realize the measurement of the winding temperature; the temperature measurement accuracy reached ±0.5 °C, the strain measurement accuracy was 200 με, and spatial resolution was up to 5 m. In this experiment, the deformation location with the precision of 2 turns was realized on the experimental winding. [ABSTRACT FROM AUTHOR]

The rapid development of deep neural networks has attracted significant attention in the infrared and visible image fusion field. However, most existing fusion models have many parameters and consume high computational and spatial resources. This paper proposes a fast and efficient recursive fusion neural network model to solve this complex problem that few people have touched. Specifically, we designed an attention module combining a traditional fusion knowledge prior with channel attention to extract modal-specific features efficiently. We used a shared attention layer to perform the early fusion of modal-shared features. Adopting parallel dilated convolution layers further reduces the network's parameter count. Our network is trained recursively, featuring minimal model parameters, and requires only a few training batches to achieve excellent fusion results. This significantly reduces the consumption of time, space, and computational resources during model training. We compared our method with nine SOTA methods on three public datasets, demonstrating our method's efficient training feature and good fusion results. [ABSTRACT FROM AUTHOR]

Winding overheating is a common fault in a transformer. To detect the temperature, the most widely used method is a point-type measurement, but traditional measurement methods cannot obtain the whole temperature distribution in a transformer. Taking this into consideration, a new method with which to measure the temperature of transformer windings was proposed. Based on Raman scattering, a new fibre-optic composite winding model was developed. The feasibility of the model was verified by electrical as well as temperature, field simulation and power frequency resistance testing. To assess the practicality and accuracy of the new model, a distributed optical fibre temperature measurement platform was built, and a series of experiments were designed. According to the data collected, the temperature measurement error based on the method could be limited to 1 °C while the positioning accuracy error was within 1 m, which meant that the new approach can satisfy the requirements of transformer winding temperature measurement and locate hot spots in the winding. [ABSTRACT FROM AUTHOR]

The temperature distribution and deformation of the transformer windings cannot be measured in a distributed manner by the traditional method and failure location cannot be performed. To solve these problems, we present a transformer winding temperature and strain based on a distributed optical fibre sensing detection method. The design of the optical fibre winding composite model is developed and simulated winding temperature rise test and local deformation test distinguish between measuring the winding temperature and the strain curve. The test results show that the distributed optical fibre can transmit wire strain efficiently. Optical fibres, in the process of winding, have a certain pre-stress. Using the Brillouin–Raman joint measuring method, one can effectively extract the optical fibre temperature and strain information and measure the length of the winding direction of the temperature and strain distribution curve to a temperature measurement precision of ±2 °C and strain detection accuracy of ±50 με. The system can carry out local hot spot and deformation localisation, providing new ideas for the transformer winding state monitoring technology. [ABSTRACT FROM AUTHOR]

In this paper, smog meteorological conditions in the natural environment is simulated by the salt fog method. The study of the alternating current (AC) discharge characteristics of rod-plane short air gaps in salt fog environments has important guiding significance for how to strengthen the external insulation strength of ultra-high voltage (UHV) transmission lines and electrical equipment in smog environments. The rod-plane short air gap is selected as the model to simulate the extremely uneven electric field. The AC discharge test is carried out in the salt fog environment with different conductivity, and the finite element method (FEM) is used to simulate the distribution of electric field in air gap under salt fog environment conditions. The results show that under clean fog conditions the AC discharge voltage in the air gap increased by 15.1% to 35.5% compared to that under dry conditions. With the increased conductivity of salt fog, the AC discharge voltage in air gap decreased by 4.1% to 9.2% compared to that under clean fog conditions, and the reduction is within 10%. The distortion of the electric field and the adsorption of free electrons in the gap by droplets lead to the decrease of the electric field intensity in the air gap. With the increase of the conductivity, the electric field intensity in the air gap increases slightly. Meanwhile, the influence of salt fog and its conductivity on the AC discharge voltage of rod-plane short air gap is examined, becoming saturated with the increase of the gap distance and the conductivity of salt fog. [ABSTRACT FROM AUTHOR]

Fc-glycosite-specific antibody–drug conjugation represents a promising direction for the preparation of site-specific antibody–drug conjugates (ADCs). In the present research, we conducted a systemic evaluation of two endoglycosidase-catalyzed chemoenzymatic glycoengineering technologies to prepare glycosite-specific ADCs. In the first two-step approach, the antibody was deglycosylated and then reglycosylated with a modified intact N-glycan oxazoline. In the second one-pot approach, antibodies were deglycosylated and simultaneously glycosylated with a functionalized disaccharide oxazoline. For the comprehensive evaluation, we first optimized and scaled-up the preparation of azido glycan oxazolines. Afterwards, we proved that the one-pot glycan-remodeling approach was efficient for all IgG subclasses. Subsequently, we assembled respective ADCS using two technology routes, with two different linker-payloads combinations, and performed systemic in vitro and in vivo evaluations. All the prepared ADCs achieved high homogeneity and illustrated excellent stability in buffers with minimum aggregates, and exceptional stability in rat serum. All ADCs displayed a potent killing of BT-474 breast cancer cells. Moving to the mouse study, the ADCs prepared from two technology routes displayed potent and similar efficacy in a BT-474 xenograft model, which was comparable to an FDA-approved ADC generated from random conjugation. These ADCs also demonstrated excellent safety and did not cause body weight loss at the tested dosages. [ABSTRACT FROM AUTHOR]

The corona onset characteristic of bundle conductors is an important limiting factor for the design of UHV AC power lines in high-altitude areas. An experimental study on the corona characteristics of 8 × LGJ630, 6 × LGJ720, 8 × LGJ720 and 10 × LGJ720 bundle conductors commonly used in UHV power lines under dry and wet conductor conditions, as well as artificial moderate and heavy rain conditions, was conducted in Ping'an County, Xining City (elevation 2200 m). By using the tangent line method, the corona onset voltages and onset electric field of four types of conductors at high altitudes are obtained for the first time. In addition, the calculation model of corona onset voltage considering the outer strands' effect on the electric field and the geometric factor in the corona cage in high altitude areas is established. The comparison of the calculation results and experimental results under dry conditions verifies the model's correctness. Based on the results, an optimal selection scheme for high altitudes is proposed. The roughness coefficient was also calculated and analysed: the roughness coefficient of bundled conductors was between 0.59 and 0.77, and the roughness coefficient of the wet conductor was between the dry and rainy conditions. Both the experimental data and the calculation model can provide a reference for conductor selection for UHV AC power lines for use in high-altitude areas. [ABSTRACT FROM AUTHOR]

Driving behavior recognition can provide an important reference for the intelligent vehicle industry and probe vehicle-based traffic estimation. The identification of driving behavior using mobile sensing techniques such as smartphone- and vehicle-mounted terminals has gained significant attention in recent years. The present work proposed the monitoring of longitudinal driving behavior using a machine learning approach with the support of an on-board unit (OBU). Specifically, based on velocity, three-axis acceleration and three-axis angular velocity data were collected by a mobile vehicle terminal OBU; through the process of data preprocessing and feature extraction, seven machine learning algorithms, including support vector machine (SVM), random forest (RF), k-nearest neighbor algorithm (KNN), logistic regression (LR), BP neural network (BPNN), decision tree (DT), and the Naive Bayes (NB), were applied to implement the classification and monitoring of the longitudinal driving behavior of probe vehicles. The results show that the three classifiers SVM, RF and DT achieved good performances in identifying different longitudinal driving behaviors. The outcome of the present work could contribute to the fields of traffic management and traffic safety, providing important support for the realization of intelligent transport systems and the improvement of driving safety. [ABSTRACT FROM AUTHOR]

Prosocial behavior plays a vital role in adolescents' well-being and social functioning, with the recall of early emotional experiences being a major influence. Positive experiences such as early memories of warmth and safeness (EMWS) contribute to prosocial interpersonal characteristics, whereas adverse experiences such as child psychological abuse and neglect (CPAN) lead to social withdrawal or behavioral problems. The direct effects of EMWS and CPAN on prosocial behavior were investigated in this study, along with the mediation effect of psychological suzhi and the moderation effect of subjective socioeconomic status (SSS). A sample of 948 adolescents (Mage = 14.05 years, SD = 1.68 years; 43.6% females) was randomly recruited to complete self-report questionnaires. Correlation results indicated that EMWS promoted prosocial behavior, whereas CPAN was negatively associated with prosocial behavior. Path analyses confirmed the mediating role of psychological suzhi on the effects of EMWS and CPAN on prosocial behavior. SSS was shown to moderate the effects of EMWS on prosocial behavior and CPAN on psychological suzhi. Compared to lower SSS, higher SSS would reinforce the positive impact of EMWS on prosocial behavior and exacerbate the negative impact of CPAN on psychological suzhi. The current study provided new insight into understanding the underlying mechanisms of prosocial behavior from the perspective of early emotional experiences. [ABSTRACT FROM AUTHOR]

In this study, full iron tailings concrete (FITC) was created using iron tailings from a tailings pond in Qian'an, China. Iron tailings account for 86.8% of the total mass of solid raw materials in the FITC. To enable large-scale use of FITC, a comprehensive investigation of the structural behaviour of full-iron tailing-reinforced concrete (FITRC) specimens is warranted. Therefore, eight rectangular reinforced concrete (RC) columns with conventional reinforced concrete (CRC) as a control were tested to investigate the effects of section dimensions, initial eccentricities, and concrete strengths, on the structural behaviour of FITRC columns under large eccentric short-term loading. The experimental and analytical results indicated that the sectional strain of the FITRC columns satisfied the plane-section assumption under short-term loading, and the lateral deflection curve agreed well with the half-sinusoidal curve. In addition, the FITRC columns exhibited a slightly lower cracking load and lower ultimate load capacity than the CRC columns, and the crack widths were larger than those of the CRC columns. The reduction in the load capacity observed in the FITRC was within the permissible range stated in the design code, thereby satisfying the code requirements. The deformation coefficients of the FITRC and CRC columns were identical, and the cracking and ultimate loads calculated according to the current code and theories were in good agreement with the measured results. [ABSTRACT FROM AUTHOR]

Bird pest control has become a major task for the operation and maintenance of distribution network lines. Epoxy resin that cures quickly at room temperature can be used to coat locations where birds frequently build their nests. However, epoxy resin has enormous internal stress and is brittle, so it is essential to toughen it. In this paper, for a room temperature curing system composed of polyurethane-modified epoxy resin and a polythiol curing agent, three kinds of particles, i.e., Al2O3, SiO2, and Mg(OH)2, were used to modify a polyurethane modified epoxy resin. Orthogonal experiments were designed to study the effects of different fillers on the comprehensive properties of polyurethane-modified epoxy resins. The experimental results showed that there were not only independent effects of different kinds if particles on the resin, but also synergistic effects of multiple particles. Nanoparticles can reduce the defects introduced by microparticles to a certain extent and improve the mechanical and electrical properties of the resin. The overall performance of the resin was optimized when the amounts of SiO2, Al2O3, and Mg(OH)2 were 1.7%, 2.5%, and 7%, respectively. The tensile strength of the resin was increased by 70%, the elongation at a break by 67.53%, and the breakdown strength by 20.31% compared with before the addition of filler. The microscopic morphology and thermal properties of the resin before and after the addition of filler were also studied. Adding fillers caused more cracks to absorb part of the energy when the resin matrix was stressed and increased the rigidity of the resin matrix and the resin's glass transition temperature (Tg) by 13.48 °C. Still, the temperature corresponding to the maximum rate of weight loss (Tmax) remained unchanged. [ABSTRACT FROM AUTHOR]

Carcinoma ex pleomorphic adenoma (Ca ex PA) is a rare malignant tumor that arises from a primary or recurrent benign pleomorphic adenoma (PA). Ca ex PA has an aggressive behavior and poor prognosis. To date, there are no standardized therapeutic methods. Herein, we reported a case of a 57-year-old Chinese female with Ca ex PA of the submandibular gland. After surgery, cervical lymph nodes recurred, and multiple distant metastases were detected. During the treatment, she received multiple chemotherapies and radiotherapy but suffered from multidrug resistance and repeated disease progression. Hence, PD-1 inhibitor (sintilimab), in combination with anlotinib, was administered, which resulted in better control of pulmonary metastases compared to the other treatment regimens. This provided an alternative treatment option for Ca ex PA of the submandibular gland patients with failed multiple therapies. [ABSTRACT FROM AUTHOR]

The accurate segmentation of the paraspinal muscle in Magnetic Resonance (MR) images is a critical step in the automated analysis of lumbar diseases such as chronic low back pain, disc herniation and lumbar spinal stenosis. However, the automatic segmentation of multifidus and erector spinae has not yet been achieved due to three unusual challenges: (1) the muscle boundary is unclear; (2) the gray histogram distribution of the target overlaps with the background; (3) the intra- and inter-patient shape is variable. We propose to tackle the problem of the automatic segmentation of paravertebral muscles using a deformed U-net consisting of two main modules: the residual module and the feature pyramid attention (FPA) module. The residual module can directly return the gradient while preserving the details of the image to make the model easier to train. The FPA module fuses different scales of context information and provides useful salient features for high-level feature maps. In this paper, 120 cases were used for experiments, which were provided and labeled by the spine surgery department of Shengjing Hospital of China Medical University. The experimental results show that the model can achieve higher predictive capability. The dice coefficient of the multifidus is as high as 0.949, and the Hausdorff distance is 4.62 mm. The dice coefficient of the erector spinae is 0.913 and the Hausdorff distance is 7.89 mm. The work of this paper will contribute to the development of an automatic measurement system for paraspinal muscles, which is of great significance for the treatment of spinal diseases. [ABSTRACT FROM AUTHOR]

As a lightweight and highly insulating composite material, epoxy resin syntactic foam is increasingly widely used for insulation filling in electrical equipment. To avoid core burning and cracking, which are prone to occur during the casting process, the epoxy resin-based syntactic foam insulation materials with high thermal conductivity and low coefficient of thermal expansion are required for composite insulation equipment. The review is divided into three sections concentrating on the two main aspects of modifying the thermal properties of syntactic foam. The mechanism and models, from the aspects of thermal conductivity and coefficient of thermal expansion, are presented in the first part. The second part aims to better understand the methods for modifying the thermal properties of syntactic foam by adding functional fillers, including the addition of thermally conductive particles, hollow glass microspheres, negative thermal expansion filler and fibers, etc. The third part concludes by describing the existing challenges in this research field and expanding the applicable areas of epoxy resin-based syntactic foam insulation materials, especially cross-arm composite insulation. [ABSTRACT FROM AUTHOR]

Chemotaxis, the ability of motile bacteria to direct their movement in gradients of attractants and repellents, plays an important role during the rhizosphere colonization by rhizobacteria. The rhizosphere is a unique niche for plant–microbe interactions. Root exudates are highly complex mixtures of chemoeffectors composed of hundreds of different compounds. Chemotaxis towards root exudates initiates rhizobacteria recruitment and the establishment of bacteria–root interactions. Over the last years, important progress has been made in the identification of root exudate components that play key roles in the colonization process, as well as in the identification of the cognate chemoreceptors. In the first part of this review, we summarized the roles of representative chemoeffectors that induce chemotaxis in typical rhizobacteria and discussed the structure and function of rhizobacterial chemoreceptors. In the second part we reviewed findings on how rhizobacterial chemotaxis and other root–microbe interactions promote the establishment of beneficial rhizobacteria-plant interactions leading to plant growth promotion and protection of plant health. In the last part we identified the existing gaps in the knowledge and discussed future research efforts that are necessary to close them. [ABSTRACT FROM AUTHOR]