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Trichoderma is a widely recognized plant-growth-promoting fungus that has been extensively utilized in various agricultural applications. However, research on the economic production of Trichoderma spores and their effects on tea cuttings must be further advanced. In this study, T. guizhouense NJAU 4742 (NJAU 4742) emerged as a growth-promoting strain for tea cuttings, and the spore-production conditions of NJAU 4742 attained through solid-state fermentation (SSF) using tea residues were optimized. In a pot experiment, nursery substrates containing different concentrations of NJAU 4742 spores were tested for their influence on tea cutting growth and the rhizosphere fungal community. The optimal conditions for spore yield were determined as a 7:3 (w/w) ratio of tea residue to rice bran, a material thickness of 3 cm, an inoculum concentration of 15% (v/w), and an incubation time of 4 days, resulting in a spore count of 1.8 × 109 CFU/g. Applying NJAU 4742 spore products significantly increased the biomass of tea cuttings and influenced the fungal community composition. Moreover, higher concentrations of NJAU 4742 spores yielded better growth performance, and applying nursery substrate with 1.0 × 107 CFU/mL spores was the most economically viable option. Notably, among the top ten fungal genera with the highest relative abundance, Trichoderma showed a positive correlation with the fresh weight of tea cuttings, while the others exhibited a negative correlation. Overall, utilizing tea residue for SSF to produce NJAU 4742 was a feasible approach, and the application of NJAU 4742 spores enhanced the growth of tea cuttings by increasing the relative abundance of Trichoderma. [ABSTRACT FROM AUTHOR]

Refined lithology identification is an essential task, often constrained by the subjectivity and low efficiency of classical methods. Computer-aided automatic identification, while useful, has seldom been specifically geared toward refined lithology identification. In this study, we introduce Rock-ViT, an innovative machine learning approach. Its architecture, enhanced with supervised contrastive loss and rooted in visual Transformer principles, markedly improves accuracy in identifying complex lithological patterns. To this end, we have collected public datasets and implemented data augmentation, aiming to validate our method using sandstone as a focal point. The results demonstrate that Rock-ViT achieves superior accuracy and effectiveness in the refined lithology identification of sandstone. Rock-ViT presents a new perspective and a feasible approach for detailed lithological analysis, offering fresh insights and innovative solutions in geological analysis. [ABSTRACT FROM AUTHOR]

Tool wear is a crucial factor in machining as it directly impacts surface quality and indirectly decreases machining efficiency, which leads to significant economic losses. Hence, monitoring tool wear state is of the utmost importance for achieving high performance and efficient machining. Although monitoring tool wear state using a single sensor has been validated in laboratory settings, it has certain drawbacks such as limited feature information acquisition and inability to learn important features adaptively. These limitations pose challenges to quickly extending the monitoring function of tool wear state of the machine tools. To solve these problems, this paper proposes a double-attention deep learning network based on vibroacoustic signal fusion feature infographics. The first solution is the construction of novel infographics using tool-intrinsic characteristics and multi-domain fusion features of multi-sensor inputs, which includes correlation analysis, principal component analysis, and feature fusion. The second solution is to build a novel deep network with a double-attention module and a spatial pyramid pooling module which can accurately and quickly identify tool wear state by successfully extracting critical spatial data from the infographics at various scales. The validity of the network is examined through an interpretability analysis based on the class activation graph. In terms of the tool wear status recognition task, the F1 score of the double-attention model based on an information graph is 11.61% higher than Resnet18, and peak recognition accuracy reaches 97.98%. [ABSTRACT FROM AUTHOR]

Neuroblastoma (NB) is the most common extracranial solid tumor that affects developing nerve cells in the fetus, infants, and children. miR-124 is a microRNA (miRNA) enriched in neuronal tissues, and VAMP3 (vesicle-associated membrane protein 3) has been reported to be an miR-124 target, although the relationship between NB and miR-124 or VAMP3 is unknown. Our current work identified that miR-124 levels are high in NB cases and that elevated miR-124 correlates with worse NB outcomes. Conversely, depressed VAMP3 correlates with worse NB outcomes. To investigate the mechanisms by which miR-124 and VAMP3 regulate NB, we altered miR-124 or VAMP3 expression in human NB cells and observed that increased miR-124 and reduced VAMP3 stimulated cell proliferation and suppressed apoptosis, while increased VAMP3 had the opposite effects. Genome-wide mRNA expression analyses identified gene and pathway changes which might explain the NB cell phenotypes. Together, our studies suggest that miR-124 and VAMP3 could be potential new markers of NB and targets of NB treatments. [ABSTRACT FROM AUTHOR]

In the coherent signal environments caused by multipath propagation, the interference suppression performance of the global navigation satellite systems (GNSS) receivers decreases sharply. In this paper, a robust space-time adaptive processing (STAP) method for GNSS receivers is proposed to suppress interferences in coherent signal environments, by using the modified space-time two-dimensional iterative adaptive approach (ST2D-IAA) spectrum estimation. This method applies the IAA algorithm to the ST2D signal model of GNSS receivers, and further modifies the ST2D-IAA algorithm to accurately estimate the power spectrum and noise power simultaneously. The space-time interference-plus-noise covariance matrix (STINCM) is reconstructed by using the estimated power spectrum and noise power in the interference angle region. Based on the reconstructed STINCM, we construct the STAP beamforming optimization problem for the space-time steering vector (STSV) error vector, and further correct the STSV of GNSS signal. Finally, the weight vector of STAP beamforming is calculated by using the reconstructed STINCM and the corrected STSV of GNSS signal. Simulation results show that the proposed method can suppress interferences in coherent signal environments and outperforms the current methods. [ABSTRACT FROM AUTHOR]

Utilizing mycoremediation is an important direction for managing heavy metal pollution. Zn2+ pollution has gradually become apparent, but there are few reports about its pollution remediation. Here, the Zn2+ remediation potential of Paraisaria dubia, an anamorph of the entomopathogenic fungus Ophiocordyceps gracilis, was explored. There was 60% Zn2+ removed by Paraisaria dubia mycelia from a Zn2+-contaminated medium. To reveal the Zn2+ tolerance mechanism of Paraisaria dubia, transcriptomic and metabolomic were executed. Results showed that Zn2+ caused a series of stress responses, such as energy metabolism inhibition, oxidative stress, antioxidant defense system disruption, autophagy obstruction, and DNA damage. Moreover, metabolomic analyses showed that the biosynthesis of some metabolites was affected against Zn2+ stress. In order to improve the tolerance to Zn2+ stress, the metabolic mechanism of metal ion transport, extracellular polysaccharides (EPS) synthesis, and microcycle conidiation were activated in P. dubia. Remarkably, the formation of microcycle conidiation may be triggered by reactive oxygen species (ROS) and mitogen-activated protein kinase (MAPK) signaling pathways. This study supplemented the gap of the Zn2+ resistance mechanism of Paraisaria dubia and provided a reference for the application of Paraisaria dubia in the bioremediation of heavy metals pollution. [ABSTRACT FROM AUTHOR]

Glioblastoma (GBM) is a primary brain tumor of unknown etiology. It is extremely aggressive, incurable and has a short average survival time for patients. Therefore, understanding the precise molecular mechanisms of this diseases is essential to establish effective treatments. In this study, we cloned and sequenced a splice variant of the hydroxysteroid 11-β dehydrogenase 1 like gene (HSD11B1L) and named it HSD11B1L-181. HSD11 B1L-181 was specifically expressed only in GBM cells. Overexpression of this variant can significantly promote the proliferation, migration and invasion of GBM cells. Knockdown of HSD11B1L-181 expression inhibited the oncogenic potential of GBM cells. Furthermore, we identified the direct interaction of parkin with HSD11B1L-181 by screening the GBM cDNA expression library via yeast two-hybrid. Parkin is an RBR E3 ubiquitin ligase whose mutations are associated with tumorigenesis. Small interfering RNA treatment of parkin enhanced the proliferative, migratory and invasive abilities of GBM. Finally, we found that the alkaloid peiminine from the bulbs of Fritillaria thunbergii Miq blocks the interaction between HSD11B1L-181 and parkin, thereby lessening carcinogenesis of GBM. We further confirmed the potential of peiminine to prevent GBM in cellular, ectopic and orthotopic xenograft mouse models. Taken together, these findings not only provide insight into GBM, but also present an opportunity for future GBM treatment. [ABSTRACT FROM AUTHOR]

This paper presents a method of simulating a capacitive sensor using COMSOL Multiphysics. A petal-form sensitive electrode structure applied to a capacitive angle sensor was simulated using COMSOL software; the angle was calculated using sines and cosines with capacitance value to fill in the simulation of the capacitive angle sensor. First, according to the construction principle of the sensor structure, a GeoGebra graphing calculator with theoretical analysis and expression of function was used to obtain the two-dimensional structure of the target petal-form sensitive structure. Second, the holistic structural model was completed by importing it into COMSOL Multiphysics and setting the electrical and mechanical rotation parameters, which realized the simulation of the rotation process. Finally, because errors were found, the structure design was improved by introducing an angle between the partition domain, and the simulation errors were reduced. The resulting curves and calculated angles were consistent with the theory; the simulation results showed that the maximum angle difference value was 0.0175° and the minimum angle difference value was 0.0018° of a single cycle structure. [ABSTRACT FROM AUTHOR]

Hydrogen has the potential to be one of the solutions that can address environmental pollution and greenhouse emissions from traditional fossil fuels. However, high costs hinder its large-scale commercialization, particularly for enabling devices such as proton exchange membrane fuel cells (PEMFCs). The precious metal Pt is indispensable in boosting the oxygen reduction reaction (ORR) in cathode electrocatalysts from the most crucial component, i.e., the membrane electrode assembly (MEA). MEAs account for a considerable amount of the entire cost of PEMFCs. To address these bottlenecks, researchers either increase Pt utilization efficiency or produce MEAs with enhanced performance but less Pt. Only a few reviews that explain the approaches are available. This review summarizes advances in designing nanocatalysts and optimizing the catalyst layer structure to achieve low-Pt loading MEAs. Different strategies and their corresponding effectiveness, e.g., performance in half-cells or MEA, are summarized and compared. Finally, future directions are discussed and proposed, aiming at affordable, highly active, and durable PEMFCs. [ABSTRACT FROM AUTHOR]

The antispoofing method using the direction-of-arrival (DOA) feature can effectively improve the application security of the global navigation satellite system (GNSS) receivers. In this paper, a sparse reconstruction approach based on a coprime array of antennas is proposed to provide reliable DOA estimation under a GNSS spoofing attack. Specifically, the self-coherence property of genuine satellite signals and spoofing was fully exploited to construct a denoised covariance matrix that enables DOA estimation before receiver despreading. Based on this, an equivalent uniform linear array (ULA) was generated from the constructed covariance matrix via virtual array interpolation. By applying the ideal of sparse reconstruction to an equivalent ULA signal, the preliminary DOA estimation results could be obtained without the need for a number of signals. Considering that the sparse estimation technique suffers from basis mismatch effects, we designed an optimization problem with respect to off-grid error to compensate the initial DOA such that the performance loss of DOA estimation could be reduced. Numerical examples demonstrated the advantages of the proposed method in terms of degrees-of-freedom (DOFs), resolution and accuracy. [ABSTRACT FROM AUTHOR]

Generating topological microstructures on the surface of cortical bone to establish a suitable microenvironment can guide bone cells to achieve bone repair. Single-point diamond tools (SPDTs) have advantages in efficiency and flexibility to fabricate surface microstructures. However, the cutting force during ploughing cannot be predicted and controlled due to the special properties of cortical bone. In this paper, a novel cutting model for ploughing cortical bone using an SPDT was established, and we comprehensively considered the shear stress anisotropy of the bone material and the proportional relationship between the normal force and the tangential force. Then, the orthogonal cutting experiment was used to verify the model. The results show that the error of calculated value and the experimental data is less than 5%. The proposed model can be used to assist the fabrication of microstructures on cortical bone surface using an SPDT. [ABSTRACT FROM AUTHOR]