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The intelligent monitoring of cutting tools used in the manufacturing industry is steadily becoming more convenient. To accurately predict the state of tools and tool breakages, this study proposes a tool wear prediction technique based on multi-sensor information fusion. First, the vibrational, current, and cutting force signals transmitted during the machining process were collected, and the features were extracted. Next, the Kalman filtering algorithm was used for feature fusion, and a predictive model for tool wear was constructed by combining the ResNet and long short-term memory (LSTM) models (called ResNet-LSTM). Experimental data for thin-walled parts obtained under various machining conditions were utilized to monitor the changes in tool conditions. A comparison between the ResNet and LSTM tool wear prediction models indicated that the proposed ResNet-LSTM model significantly improved the prediction accuracy compared to the individual LSTM and ResNet models. Moreover, ResNet-LSTM exhibited adaptive noise reduction capabilities at the front end of the network for signal feature extraction, thereby enhancing the signal feature extraction capability. The ResNet-LSTM model yielded an average prediction error of 0.0085 mm and a tool wear prediction accuracy of 98.25%. These results validate the feasibility of the tool wear prediction method proposed in this study. [ABSTRACT FROM AUTHOR]

The aim of this paper is to investigate the mechanism of an electric current-assisted superplastic deformation on 3Y-TZP in an oxygen-lean atmosphere. The experiments were performed with different electric currents in the range of 0~5 A. The results show that the flow stress of 3Y-TZP during the deformation was significantly decreased by the combination of Joule heating and the applied current effect. The microstructures of the deformed specimens were all equiaxed grains without an obvious preferential grain growth. The stress exponent n = 2.05~2.61 suggested that the dominant deformation of 3Y-YZP with/without the electric current was grain boundary sliding at 1400 °C. The activation energy of the deformation which decreased from 465 kJ mol−1 to 315 kJ mol−1 by the electric current indicated that the lattice diffusion of Zr cation during the deformation was enhanced. And the deformation rate of 3Y-TZP with the electric current may be controlled by the grain boundary diffusion of Zr cation. [ABSTRACT FROM AUTHOR]

Cyclic di-GMP (c-di-GMP) is a second messenger of intracellular communication in bacterial species, which widely modulates diverse cellular processes. However, little is known about the c-di-GMP network in filamentous multicellular cyanobacteria. In this study, we preliminarily investigated the c-di-GMP turnover proteins in Arthrospira based on published protein data. Bioinformatics results indicate the presence of at least 149 potential turnover proteins in five Arthrospira subspecies. Some proteins are highly conserved in all tested Arthrospira, whereas others are specifically found only in certain subspecies. To further validate the protein catalytic activity, we constructed a riboswitch-based c-di-GMP expression assay system in Escherichia coli and confirmed that a GGDEF domain protein, Adc11, exhibits potential diguanylate cyclase activity. Moreover, we also evaluated a protein with a conserved HD-GYP domain, Ahd1, the expression of which significantly improved the swimming ability of E. coli. Enzyme-linked immunosorbent assay also showed that overexpression of Ahd1 reduced the intracellular concentration of c-di-GMP, which is presumed to exhibit phosphodiesterase activity. Notably, meta-analyses of transcriptomes suggest that Adc11 and Ahd1 are invariable. Overall, this work confirms the possible existence of a functional c-di-GMP network in Arthrospira, which will provide support for the revelation of the biological function of the c-di-GMP system in Arthrospira. [ABSTRACT FROM AUTHOR]

Inserting modification layers at the diamond/Al interface is an effective technique in improving the interfacial thermal conductance (ITC) of the composite. However, few study reports the effect of interfacial structure on the thermal conductivity (TC) of diamond/Al composites at room temperature. Herein, the scattering-mediated acoustic mismatch model, suitable for evaluating the ITC at room temperature, is utilized to predict the TC performance of the diamond/Al composite. According to the practical microstructure of the composites, the reaction products at diamond/Al interface on the TC performance are concerned. Results indicate that the TC of the diamond/Al composite is dominantly affected by the thickness, the Debye temperature and the TC of the interfacial phase, meeting with multiple documented results. This work provides a method to assess the interfacial structure on the TC performance of metal matrix composite at room temperature. [ABSTRACT FROM AUTHOR]

In the present study, two effective methods, the Exp-function method and He's frequency formulation, are employed to investigate the dynamic behaviors of the (3+1)-dimensional Boiti–Leon–Manna–Pempinelli equation, which is used widely to describe the incompressible fluid. A variety of the wave structures, including the dark wave, bright-dark wave and periodic wave solutions, are successfully constructed. Compared with the results attained by the methods, the obtained solutions are all new and have not been presented in the other literature. The diverse wave structures of the solutions are presented through numerical results in the form of three-dimensional plots and two-dimensional curves. It reveals that the proposed methods are powerful and straightforward, which are expected to be helpful for the study of travelling-wave theory in fluid. [ABSTRACT FROM AUTHOR]

Glaesserella parasuis (G. parasuis.) is the etiological pathogen of Glässer's disease, which causes high economic losses to the pig industry. The heme-binding protein A precursor (HbpA) was a putative virulence-associated factor proposed to be potential subunit vaccine candidate in G. parasuis. In this study, three monoclonal antibodies (mAb) 5D11, 2H81, and 4F2 against recombinant HbpA (rHbpA) of G. parasuis SH0165 (serotype 5) were generated by fusing SP2/0-Ag14 murine myeloma cells and spleen cells from BALB/c mice immunized with the rHbpA. Indirect enzyme-linked immunosorbent assay (ELISA) and indirect immunofluorescence assay (IFA) demonstrated that the antibody designated 5D11 showed a strong binding affinity with the HbpA protein and was chosen for subsequent experiments. The subtypes of the 5D11 were IgG1/κ chains. Western blot analysis showed that mAb 5D11 could react with all 15 serotype reference strains of G. parasuis. None of the other bacteria tested reacted with 5D11. In addition, a linear B-cell epitope recognized by 5D11 was identified by serial truncations of HbpA protein and then a series of truncated peptides were synthesized to define the minimal region that was required for mAb 5D11 binding. The 5D11 epitope was located on amino acids 324-LPQYEFNLEKAKALLA-339 by testing the 5D11 monoclonal for reactivity with 14 truncations. The minimal epitope 325-PQYEFNLEKAKALLA-339 (designated EP-5D11) was pinpointed by testing the mAb 5D11 for reactivity with a series of synthetic peptides of this region. The epitope was highly conserved among G. parasuis strains, confirmed by alignment analysis. These results indicated that mAb 5D11 and EP-5D11 might potentially be used to develop serological diagnostic tools for G. parasuis. Three-dimensional structural analysis revealed that amino acids of EP-5D11 were in close proximity and may be exposed on the surface of the HbpA protein. [ABSTRACT FROM AUTHOR]

This paper outlines a study into the exact solutions of the (2+1)-dimensional Heisenberg ferromagnetic spin chain equation that is used to illustrate the ferromagnetic materials of magnetic ordering by applying two recent techniques, namely, the Sardar-subequation method and extended rational sine–cosine and sinh–cosh methods. Abundant exact solutions such as the bright soliton, dark soliton, combined bright–dark soliton, singular soliton and other periodic wave solutions expressed by the generalized trigonometric, generalized hyperbolic, trigonometric and hyperbolic functions are obtained. The numerical results are illustrated in the form of 3D plots, 2D contours and 2D curves by choosing proper parametric values to interpret the physical behavior of the model. The obtained results in this work are expected to provide a rich platform for constructing the soliton solutions of PDEs in physics. [ABSTRACT FROM AUTHOR]

The widespread adoption of intelligent devices has led to the generation of vast amounts of Global Positioning System (GPS) trajectory data. One of the significant challenges in this domain is to accurately identify stopping points from GPS trajectory data. Traditional clustering methods have proven ineffective in accurately identifying non-stopping points caused by trailing or round trips. To address this issue, this paper proposes a novel density peak clustering algorithm based on coherence distance, incorporating temporal and entropy constraints, referred to as the two-step DPCC-TE. The proposed algorithm introduces a coherence index to integrate spatial and temporal features, and imposes temporal and entropy constraints on the clusters to mitigate local density increase caused by slow-moving points and back-and-forth movements. Moreover, to address the issue of interactions between subclusters after one-step clustering, a two-step clustering algorithm is proposed based on the DPCC-TE algorithm. Experimental results demonstrate that the proposed two-step clustering algorithm outperforms the DBSCAN-TE and one-step DPCC-TE methods, and achieves an accuracy of 95.49% in identifying stopping points. [ABSTRACT FROM AUTHOR]

At present, most quadruped robots can move quickly and steadily on both flat and undulating ground; however, natural environments are complex and changeable, so it is important for a quadruped robot to be able to jump over obstacles immediately. Inspired by the jumping movement of quadruped animals, we present aerial body posture adjustment laws and generate animal-like jumping trajectories for a quadruped robot. Then, the bionic reference trajectories are optimized to build a trajectory library of a variety of jumping motions based on the kinematic and dynamic constraints of the quadruped robot. The model predictive control (MPC) method is employed by the quadruped robot to track the optimized trajectory to achieve jumping behavior. The simulations show that the quadruped robot can jump over an obstacle of 40 cm in height. The effectiveness of the animal-like jump control method is verified. [ABSTRACT FROM AUTHOR]

Simple Summary: Identifying bird species is crucial in various bird monitoring tasks. In this study, we implemented a bird species recognition method based on visual features by convolutional neural networks. This paper proposed an attention-guided data enhancement method and a decoupled knowledge distillation model compression method. Using the two methods, we created a novel and efficient lightweight fine-grained bird classification model. The model not only achieved high accuracy in bird classification but was also user-friendly for edge devices such as mobile. Our work may be useful for bird species recognition and bird biodiversity monitoring. Classifying birds accurately is essential for ecological monitoring. In recent years, bird image classification has become an emerging method for bird recognition. However, the bird image classification task needs to face the challenges of high intraclass variance and low inter-class variance among birds, as well as low model efficiency. In this paper, we propose a fine-grained bird classification method based on attention and decoupled knowledge distillation. First of all, we propose an attention-guided data augmentation method. Specifically, the method obtains images of the object's key part regions through attention. It enables the model to learn and distinguish fine features. At the same time, based on the localization–recognition method, the bird category is predicted using the object image with finer features, which reduces the influence of background noise. In addition, we propose a model compression method of decoupled knowledge distillation. We distill the target and nontarget class knowledge separately to eliminate the influence of the target class prediction results on the transfer of the nontarget class knowledge. This approach achieves efficient model compression. With 67% fewer parameters and only 1.2 G of computation, the model proposed in this paper still has a 87.6% success rate, while improving the model inference speed. [ABSTRACT FROM AUTHOR]

This paper provides an investigation on nonlinear dynamic behaviors of the (3+1)-dimensional B-type Kadomtsev—Petviashvili equation, which is used to model the propagation of weakly dispersive waves in a fluid. With the help of the Cole—Hopf transform, the Hirota bilinear equation is established, then the symbolic computation with the ansatz function schemes is employed to search for the diverse exact solutions. Some new results such as the multi-wave complexiton, multi-wave, and periodic lump solutions are found. Furthermore, the abundant traveling wave solutions such as the dark wave, bright-dark wave, and singular periodic wave solutions are also constructed by applying the sub-equation method. Finally, the nonlinear dynamic behaviors of the solutions are presented through the 3-D plots, 2-D contours, and 2-D curves and their corresponding physical characteristics are also elaborated. To our knowledge, the obtained solutions in this work are all new, which are not reported elsewhere. The methods applied in this study can be used to investigate the other PDEs arising in physics. [ABSTRACT FROM AUTHOR]

A new local fractional modified Benjamin–Bona–Mahony equation is proposed within the local fractional derivative in this study for the first time. By defining some elementary functions via the Mittag–Leffler function (MLF) on the Cantor sets (CSs), a set of nonlinear local fractional ordinary differential equations (NLFODEs) is constructed. Then, a fast algorithm namely Yang's special function method is employed to find the non-differentiable (ND) exact solutions. By this method, we can extract abundant exact solutions in just one step. Finally, the obtained solutions on the CS are outlined in the form of the 3-D plot. The whole calculation process clearly shows that Yang's special function method is simple and effective, and can be applied to investigate the exact ND solutions of the other local fractional PDEs. [ABSTRACT FROM AUTHOR]

The objective of this paper is to study the issue of the projection uniformity of asymmetric fractional factorials. On the basis of level permutation and mixture discrepancy, the average projection mixture discrepancy to measure the uniformity for low-dimensional projection designs is defined, the uniformity pattern and minimum projection uniformity criterion are presented for evaluating and comparing any asymmetric factorials. Moreover, lower bounds to uniformity pattern have been obtained, and some illustrative examples are also provided. [ABSTRACT FROM AUTHOR]

This study presents a statistical analysis of the ionospheric irregularities and topside ionospheric scintillation at low and middle latitudes by using in situ electron density and upward-looking total electron content data measured by the Swarm constellation during 2014–2021. The main purpose of this study is to determine whether the phase scintillation could present similar seasonal, longitudinal, latitudinal, local time, and solar activity features as the in situ ionospheric irregularities do at low and middle latitudes, and how the irregularities affect the phase scintillation. The results are summarized as follows: (1) At low latitudes, the occurrence rate of equatorial plasma irregularities (EPIs) at the equinoxes and December solstice peaks before midnight, but during the June solstice, the EPIs mainly occur after midnight. The occurrence rate of EPIs has a positive correlation with solar activity. The distribution of topside scintillation occurrence is relatively consistent with EPIs, but during the June solstice, the scintillation occurrence rate remains at a very low level. (2) The midlatitude irregularities mainly occur after midnight, and their occurrence rate is negatively correlated with solar activity. Midlatitude irregularities mainly occur during the solstices, concentrated over the Pacific region during the June solstice and over the Pacific American sector during the December solstice. Especially, the distribution of midlatitude irregularities has hemispheric asymmetry, with a higher occurrence rate in the winter hemisphere. However, the occurrence of midlatitude scintillation is comparable in both hemispheres during the June solstice, and it concentrates in the southern hemisphere during the December solstice. (3) The EPIs concentrate more at the altitudes of Swarm A, while the midlatitude irregularities mainly occur at the altitudes of Swarm B. [ABSTRACT FROM AUTHOR]

This study focuses on investigating the modified Benjamin-Bona-Mahony equation that is used to model the long wave in nonlinear dispersive media of the optical illusion field. Two effective techniques, the variational direct method and He's frequency formulation method, are employed to seek the travelling wave solutions. Using these two techniques, abundant exact solutions such as the bright wave, bright-dark wave, bright-like wave, kinky-bright wave and periodic wave solutions, are obtained. The 3-D contours and 2-D curves are drawn to present the dynamic physical behaviors of the solutions by assigning the proper parameters. It shows that the proposed methods are effective but simple and only need one or two steps to construct the exact solutions, which are expected to provide some new insights to study the travelling wave solutions of the PDEs arising in physics. [ABSTRACT FROM AUTHOR]

In this paper, the integrable (2+1)-dimensional Maccari system (MS), which can model many complex phenomena in hydrodynamics, plasma physics and nonlinear optics, is investigated by the variational approach (VA). This proposed approach that based on the variational theory and Ritz-like method can construct the explicit solutions via the stationary conditions only taking two steps. Finally, the dynamic behaviors of the solutions are exhibited by choosing the appropriate parameters through the 3-D and density plots. It can be seen that the proposed method is concise and straightforward, and can be adopted to study the travelling wave theory in physics. [ABSTRACT FROM AUTHOR]

Cinnamic acid (CA) was successfully incorporated into Zn-Al layered double hydroxide (LDH) through coprecipitation. The CA moiety was stabilized in the interlayer space through not only electrostatic interaction but also intermolecular π-π interaction. It was noteworthy that the CA arrangement was fairly independent of the charge density of LDH, showing the important role of the layer–CA and CA-CA interactions in molecular stabilization. Computer simulations using the Monte Carlo method as well as analytical approaches including infrared, UV-vis spectroscopy, and differential scanning calorimetry showed the existence of intermolecular interaction. In order to reinforce molecular stabilization, a neutral derivative of CA, cinnamaldehyde (CAD), was additionally incorporated into LDH. It was clearly shown that CAD played a role as a π-π interaction mediator to enhance the stabilization of CA. The time-dependent release of CA from LDH was first governed by the layer charge density of LDH; however, the existence of CAD provided additional stabilization to the CA arrangement to slow down the release kinetics. [ABSTRACT FROM AUTHOR]

Simple Summary: The synthesis of natural or non-natural products in microorganisms frequently involves multiple genes or pathways. Enhancing and balancing the expression of these genes is essential to prevent growth inhibition and product synthesis blockage resulting from the accumulation of intermediate products, thereby effectively increasing the yield of target products. However, there is a deficiency in robust tools for balancing gene expression in Bacillus subtilis. Herein, we identified a 5′ UTR sequence that enhances gene expression levels. The library constructed from this sequence enables a broad spectrum of gene variations. Utilizing this library to construct a synthesized rib operon markedly boosts riboflavin production. Therefore, a novel 5′ UTR sequence was screened and characterized, supplementing the synthetic biology toolkit for B. subtilis. The application of synthetic biology tools to modulate gene expression to increase yield has been thoroughly demonstrated as an effective and convenient approach in industrial production. In this study, we employed a high-throughput screening strategy to identify a 5′ UTR sequence from the genome of B. subtilis 168. This sequence resulted in a 5.8-fold increase in the expression level of EGFP. By utilizing the 5′ UTR sequence to overexpress individual genes within the rib operon, it was determined that the genes ribD and ribAB serve as rate-limiting enzymes in the riboflavin synthesis pathway. Constructing a 5′ UTR library to regulate EGFP expression resulted in a variation range in gene expression levels exceeding 100-fold. Employing the same 5′ UTR library to regulate the expression of EGFP and mCherry within the operon led to a change in the expression ratio of these two genes by over 10,000-fold. So, employing a 5′ UTR library to modulate the expression of the rib operon gene and construct a synthetic rib operon resulted in a 2.09-fold increase in riboflavin production. These results indicate that the 5′ UTR sequence identified and characterized in this study can serve as a versatile synthetic biology toolkit for achieving complex metabolic network reconstruction. This toolkit can facilitate the fine-tuning of gene expression to produce target products. [ABSTRACT FROM AUTHOR]

Efficient flotation beneficiation heavily relies on accurate flotation condition recognition based on monitored froth video. However, the recognition accuracy is hindered by limitations of extracting temporal features from froth videos and establishing correlations between complex multi-modal high-order data. To address the difficulties of inadequate temporal feature extraction, inaccurate online condition detection, and inefficient flotation process operation, this paper proposes a novel flotation condition recognition method named the multi-modal temporal hypergraph neural network (MTHGNN) to extract and fuse multi-modal temporal features. To extract abundant dynamic texture features from froth images, the MTHGNN employs an enhanced version of the local binary pattern algorithm from three orthogonal planes (LBP-TOP) and incorporates additional features from the three-dimensional space as supplements. Furthermore, a novel multi-view temporal feature aggregation network (MVResNet) is introduced to extract temporal aggregation features from the froth image sequence. By constructing a temporal multi-modal hypergraph neural network, we encode complex high-order temporal features, establish robust associations between data structures, and flexibly model the features of froth image sequence, thus enabling accurate flotation condition identification through the fusion of multi-modal temporal features. The experimental results validate the effectiveness of the proposed method for flotation condition recognition, providing a foundation for optimizing flotation operations. [ABSTRACT FROM AUTHOR]

Thin-walled aluminum alloy parts are widely used in the aerospace field because of their favorable characteristics that cater to various applications. However, they are easily deformed during milling, leading to a low pass rate of workpieces. On the basis of on-machine measurement (OMM) and surrogate stiffness models (SSMs), we developed an iterative optimization compensation method in this study to overcome the machining deformation of thin-walled parts. In the error compensation process, the time-varying factors of workpiece stiffness and the impact of prediction model errors were considered. First, we performed machining deformation simulation and information extraction on the key nodes of the machined surface, and an SSM containing the stiffness information of discrete nodes of each cutting layer was established. Subsequently, the machining errors were monitored through intermittent OMM to suppress the adverse impact of prediction model errors. Further, an interlayer correction coefficient was introduced in the compensation process to iteratively correct the prediction model error of each node in the SSM along the depth direction, and a correction coefficient between parts was introduced to realize the iterative correction of the prediction model for the same node position between different parts. Finally, the feasibility of the proposed method was verified through multiple sets of actual machining experiments on thin-walled parts with added pads. [ABSTRACT FROM AUTHOR]

The combination of wet-lab experimental data on multi-site combinatorial mutations and machine learning is an innovative method in protein engineering. In this study, we used an innovative sequence-activity relationship (innov'SAR) methodology based on novel descriptors and digital signal processing (DSP) to construct a predictive model. In this paper, 21 experimental (R)-selective amine transaminases from Aspergillus terreus (AT-ATA) were used as an input to predict higher thermostability mutants than those predicted using the existing data. We successfully improved the coefficient of determination (R2) of the model from 0.66 to 0.92. In addition, root-mean-squared deviation (RMSD), root-mean-squared fluctuation (RMSF), solvent accessible surface area (SASA), hydrogen bonds, and the radius of gyration were estimated based on molecular dynamics simulations, and the differences between the predicted mutants and the wild-type (WT) were analyzed. The successful application of the innov'SAR algorithm in improving the thermostability of AT-ATA may help in directed evolutionary screening and open up new avenues for protein engineering. [ABSTRACT FROM AUTHOR]

In this study, two types of cemented tailings backfill (CTB) were prepared by breaking up the waste clay bricks (WCB) from dismantled buildings and replacing part of the cement with brick powder and part of the tailings with brick aggregate. The mechanical properties of the modified CTB were investigated. The results showed that the strength of CTB with 10% brick powder content increased by 16.24% at the curing age of 28 days, while the content of 20% brick powder only decreased by 0.11%. The strength of the brick aggregate with less than 20% content can be increased at each curing age, and the strength of the 15% brick aggregate at the curing age of 7 d and 28 d is increased by 65.54 and 58.8%. The failure strain of the CTB-containing brick powder decreases with the extension of the curing time, and the failure strain of the CTB-containing brick aggregate decreases significantly at the curing age of 7 days. In addition, a three-stage damage constitutive model was established based on the results obtained in the present study, and the laboratory test results of CTB under uniaxial compression were effectively described with high confidence. [ABSTRACT FROM AUTHOR]

The progression and remission of cervical spondylotic myelopathy (CSM) are quite unpredictable due to the ambiguous pathomechanisms. Spontaneous functional recovery (SFR) has been commonly implicated in the natural course of incomplete acute spinal cord injury (SCI), while the evidence and underlying pathomechanisms of neurovascular unit (NVU) compensation involved in SFR remains poorly understood in CSM. In this study, we investigate whether compensatory change of NVU, in particular in the adjacent level of the compressive epicenter, is involved in the natural course of SFR, using an established experimental CSM model. Chronic compression was created by an expandable water-absorbing polyurethane polymer at C5 level. Neurological function was dynamically assessed by BBB scoring and somatosensory evoked potential (SEP) up to 2 months. (Ultra)pathological features of NVUs were presented by histopathological and TEM examination. Quantitative analysis of regional vascular profile area/number (RVPA/RVPN) and neuroglial cells numbers were based on the specific EBA immunoreactivity and neuroglial biomarkers, respectively. Functional integrity of blood spinal cord barrier (BSCB) was detected by Evan blue extravasation test. Although destruction of the NVU, including disruption of the BSCB, neuronal degeneration and axon demyelination, as well as dramatic neuroglia reaction, were found in the compressive epicenter and spontaneous locomotor and sensory function recovery were verified in the modeling rats. In particular, restoration of BSCB permeability and an evident increase in RVPA with wrapping proliferated astrocytic endfeet in gray matter and neuron survival and synaptic plasticity were confirmed in the adjacent level. TEM findings also proved ultrastructural restoration of the NVU. Thus, NVU compensation changes in the adjacent level may be one of the essential pathomechanisms of SFR in CSM, which could be a promising endogenous target for neurorestoration. [ABSTRACT FROM AUTHOR]

Vibration signal analysis is the most common technique used for mechanical vibration monitoring. By using vibration sensors, the fault prognosis of rotating machinery provides a way to detect possible machine damage at an early stage and prevent property losses by taking appropriate measures. We first propose a digital integrator in frequency domain by combining fast Fourier transform with digital filtering. The velocity and displacement signals are, respectively, obtained from an acceleration signal by means of two digital integrators. We then propose a fast method for the calculation of the envelope spectra and instantaneous frequency by using the spectral properties of the signals. Cepstrum is also introduced in order to detect the unidentifiable periodic signal in the power spectrum. Further, a fault prognosis algorithm is presented by exploiting these spectral analyses. Finally, we design and implement a visualized real-time vibration analyzer on a Raspberry Pi embedded system, where our fault prognosis algorithm is the core algorithm. The real-time signals of acceleration, velocity, displacement of vibration, as well as their corresponding spectra and statistics, are visualized. The developed fault prognosis system has been successfully deployed in a water company. [ABSTRACT FROM AUTHOR]

Chinese Herbal Medicines (CHMs) can be identified by experts according to their odors. However, the identification of these medicines is subjective and requires long-term experience. The samples of Acanthopanacis Cortex and Periplocae Cortex used were dried cortexes, which are often confused in the market due to their similar appearance, but their chemical composition and odor are different. The clinical use of the two herbs is different, but the phenomenon of being confused with each other often occurs. Therefore, we used an electronic nose (E-nose) to explore the differences in odor information between the two species for fast and robust discrimination, in order to provide a scientific basis for avoiding confusion and misuse in the process of production, circulation and clinical use. In this study, the odor and volatile components of these two medicinal materials were detected by the E-nose and by gas chromatography–mass spectrometry (GC-MS), respectively. An E-nose combined with pattern analysis methods such as principal component analysis (PCA) and partial least squares (PLS) was used to discriminate the cortex samples. The E-nose was used to determine the odors of the samples and enable rapid differentiation of Acanthopanacis Cortex and Periplocae Cortex. GC-MS was utilized to reveal the differences between the volatile constituents of Acanthopanacis Cortex and Periplocae Cortex. In all, 82 components including 9 co-contained components were extracted by chromatographic peak integration and matching, and 24 constituents could be used as chemical markers to distinguish these two species. The E-nose detection technology is able to discriminate between Acanthopanacis Cortex and Periplocae Cortex, with GC-MS providing support to determine the material basis of the E-nose sensors' response. The proposed method is rapid, simple, eco-friendly and can successfully differentiate these two medicinal materials by their odors. It can be applied to quality control links such as online detection, and also provide reference for the establishment of other rapid detection methods. The further development and utilization of this technology is conducive to the further supervision of the quality of CHMs and the healthy development of the industry. [ABSTRACT FROM AUTHOR]

The YfeA gene, belonging to the well-conserved ABC (ATP-binding cassette) transport system Yfe, encodes the substrate-binding subunit of the iron, zinc, and manganese transport system in bacteria. As a potential vaccine candidate in Glaesserella parasuis, the functional mechanisms of YfeA in the infection process remain obscure. In this study, vaccination with YfeA effectively protected the C56BL6 mouse against the G. parasuis SC1401 challenge. Bioinformatics analysis suggests that YfeA is highly conserved in G. parasuis, and its metal-binding sites have been strictly conserved throughout evolution. Stimulation of RAW 264.7 macrophages with YfeA verified that toll-like receptors (TLR) 2 and 4 participated in the positive transcription and expression of pro-inflammatory cytokines IL-1β, IL-6, and TNF-α. The activation of TLR2 and TLR4 utilized the MyD88/MAL and TRIF/TRAM pairs to initiate TLRs signaling. Furthermore, YfeA was shown to stimulate nuclear translocation of NF-κB and activated diverse mitogen-activated protein (MAP) kinase signaling cascades, which are specific to the secretion of particular cytokine(s) in murine macrophages. Separate blocking TLR2, TLR4, MAPK, and RelA (p65) pathways significantly decreased YfeA-induced pro-inflammatory cytokine production. In addition, YfeA-stimulated RAW 264.7 produces the pro-inflammatory hallmark, reactive oxygen species (ROS). In conclusion, our findings indicate that YfeA is a novel pro-inflammatory mediator in G. parasuis and induces TLR2 and TLR4-dependent pro-inflammatory activity in RAW 264.7 macrophages through P38, JNK-MAPK, and NF-κB signaling pathways. [ABSTRACT FROM AUTHOR]

In this paper, we propose the fractal (2 + 1)-dimensional Zakharov–Kuznetsov equation based on He's fractal derivative for the first time. The fractal generalized variational formulation is established by using the semi-inverse method and two-scale fractal theory. The obtained fractal variational principle is important since it not only reveals the structure of the traveling wave solutions but also helps us study the symmetric theory. The finding of this paper will contribute to the study of symmetry in the fractal space. [ABSTRACT FROM AUTHOR]

This paper presents results from experimental work on mechanical properties of geopolymer concrete, mortar and paste prepared using fly ash and blended slag. Compressive strength, splitting tensile strength and flexural strength tests were conducted on large sets of geopolymer and ordinary concrete, mortar and paste after exposure to elevated temperatures. From Thermogravimetric analyzer (TGA), X-ray diffraction (XRD), Scanning electron microscope (SEM) test results, the geopolymer exhibits excellent resistance to elevated temperature. Compressive strengths of C30, C40 and C50 geopolymer concrete, mortar and paste show incremental improvement then followed by a gradual reduction, and finally reach a relatively consistent value with an increase in exposure temperature. The higher slag content in the geopolymer reduces residual strength and the lower exposure temperature corresponding to peak residual strength. Resistance to elevated temperature of C40 geopolymer concrete, mortar and paste is better than that of ordinary concrete, mortar and paste at the same grade. XRD, TGA and SEM analysis suggests that the heat resistance of C–S–H produced using slag is lower than that of sulphoaluminate gel (quartz and mullite, etc.) produced using fly ash. This facilitates degradation of C30, C40 and C50 geopolymer after exposure to elevated temperatures. [ABSTRACT FROM AUTHOR]

The resonance property of a magnetic vortex contained within a micron-sized square Py dot was detected using an amplitude-modulated magnetic field excitation technique. We found a significant modulation of the resonant spectra as the external magnetic field changes. The Lorentzian-like spectrum changes from a peak to a dip via a transition of anti-Lorentzian-like spectra. By conducting the micromagnetic simulations, we confirmed that the transition behavior results from the unusual resistance change depending on the vortex core center position. Additionally, the power dependence of the anti-Lorentzian-like spectra revealed a fairly persistent coexistence of peak and dip. Thus, the tunable spectra suggest one way to develop an integratable radiofrequency microcircuits. [ABSTRACT FROM AUTHOR]

In this work, we fabricate and characterize an energy-efficient anomalous Hall sensor based on soft-magnetic FexPt1−x thin films with a large anomalous Hall angle. By varying the composition of the FexPt1−x alloy, its layer thickness and interfacial materials, the magnetization is tuned to be near the spin transition between the perpendicular and in-plane reorientations. We performed magneto-transport and noise characterizations on anomalous Hall sensors with a small sensing area of 20 × 20 µm2 in the 180 to 350 K temperature range. We found the best performance in a 1.25-nm-thick Fe0.48Pt0.52 sandwiched by two 1.6-nm-thick MgO layers at room temperature. The sensor has a large anomalous Hall angle of 1.95%. Moreover, it has the best field detectability of 237.5 nT/√Hz at 1 Hz and 15.3 nT/√Hz at 10 kHz, as well as a high dynamic reserve of 112.0 dB. These results suggest that the FexPt1−x alloy system is suitable for energy-efficient anomalous Hall sensors, particularly in micro-sensing applications. [ABSTRACT FROM AUTHOR]

The heterogeneous Fenton-like reaction has been receiving increasing attention for its inexpensiveness and high efficiency in water treatment. In this study, a novel strategy was proposed for preparing spherical ZVI/Mn-C bimetallic catalysts with a high activity for a Fenton-like reaction by using the ammonium alginate assisted sol–gel method coupled with a carbothermic reduction. The results showed that the obtained ZVI/Mn-C spheres had a uniform size, smooth surface and good sphericity, and the particle size of ZVI was limited to about 30 nm by the carbon layer. Among all catalysts, the ZVI/Mn-C-31 catalyst exhibited the highest phenol degradation efficiency in the Fenton-like process, and almost 100% phenol degradation efficiency was achieved under neutral pH at room temperature within 5 min. Moreover, the ZVI/Mn-C-31/H2O2 system showed a 100% degradation efficiency for removing a wide range of aromatic pollutants, including catechol, resorcinol and o-nitrophenol. Moreover, the radicals-scavenging experiment illustrated that the ·OH played a key factor in mineralizing the organic matters, and the ·O2− generated from the MnO-H2O2 system accelerated the conversion rate of ferric iron to ferrous iron. Due to the synergistic effects between ZVI and MnO, the ZVI/Mn-C-31 catalyst performed excellently in the Fenton-like reaction at an extended pH range. [ABSTRACT FROM AUTHOR]

Autism spectrum disorder (ASD) cases have increased rapidly in recent decades, which is associated with various genetic abnormalities. To provide a better understanding of the genetic factors in ASD, we assessed the global scientific output of the related studies. A total of 2944 studies published between 1997 and 2018 were included by systematic retrieval from the Web of Science (WoS) database, whose scientific landscapes were drawn and the tendencies and research frontiers were explored through bibliometric methods. The United States has been acting as a leading explorer of the field worldwide in recent years. The rapid development of high-throughput technologies and bioinformatics transferred the research method from the traditional classic method to a big data-based pipeline. As a consequence, the focused research area and tendency were also changed, as the contribution of de novo mutations in ASD has been a research hotspot in the past several years and probably will remain one into the near future, which is consistent with the current opinions of the major etiology of ASD. Therefore, more attention and financial support should be paid to the deciphering of the de novo mutations in ASD. Meanwhile, the effective cooperation of multi-research centers and scientists in different fields should be advocated in the next step of scientific research undertaken. [ABSTRACT FROM AUTHOR]

Equatorial plasma bubbles (EPBs) occur frequently in low-latitude areas and have a non-negligible impact on navigation satellite signals. To systematically analyze the effects of a single EPB event on multi-frequency signals of GPS, Galileo, GLONASS, and BDS, all-sky airglow images over South China are jointly used to visually determine the EPB structure and depletion degree. The results reveal that scintillations, or GNSS signal fluctuations, are directly linked to EPBs and that the intensity of scintillation is positively correlated with the airglow depletion intensity. The center of the airglow depletion often corresponds to stronger GNSS scintillation, while the edge of the bubble, which is considered to have the largest density gradient, corresponds to relatively smaller scintillation instead. This work also systematically analyzes the responses of multi-constellation and multi-frequency signals to EPBs. The results show that the L2 and L5 frequencies are more susceptible than the L1 frequency is. For different constellations, Galileo's signal has the best tracking stability during an EPB event compared with GPS, GLONASS, and BDS. The results provide a reference for dual-frequency signal selection in precise positioning or TEC calculation, that is, L1C and L2L for GPS, L1C and L5Q for Galileo, L1P and L2C for GLONASS, and L1P and L5P for BDS. Notably, BDS-2 is significantly weaker than BDS-3. And inclined geosynchronous orbit (IGSO) satellites have abnormal data error rates, which should be related to the special signal path trajectory of the IGSO satellite. [ABSTRACT FROM AUTHOR]

Different levels of EspP2 expression are seen in strains of Glaesserella parasuis with high and low pathogenicity. As a potential virulence factor for G. parasuis, the pathogenic mechanism of EspP2 in infection of host cells is not clear. To begin to elucidate the effect of EspP2 on virulence, we used G. parasuis SC1401 in its wild-type form and SC1401, which was made EspP2-deficient. We demonstrated that EspP2 causes up-regulation of claudin-1 and occludin expression, thereby promoting the adhesion of G. parasuis to host cells; EspP2-deficiency resulted in significantly reduced adhesion of G. parasuis to cells. Transcriptome sequencing analysis of EspP2-treated PK15 cells revealed that the Rap1 signaling pathway is stimulated by EspP2. Blocking this pathway diminished occludin expression and adhesion. These results indicated that EspP2 regulates the adhesion of Glaesserella parasuis via Rap1 signaling pathway. [ABSTRACT FROM AUTHOR]

Simple Summary: The mandibular gland is one of the main glands used by worker bees to synthesize and secrete royal jelly. To investigate the development patterns of the mandibular gland and the molecular regulatory mechanisms involved in royal jelly secretion, we dissected the mandibular glands of Apis mellifera carnica worker bees of different ages (3, 6, 9, 12, and 16 d) and performed morphological and transcriptomic analyses. Microscopy revealed that the mandibular glands likely completed development in the early stages. There were no significant differences in the structural morphology or organelles involved in the secretion of royal jelly at different ages. Although the condition of the mandibular glands from 3 to 16 d could not be classified based on morphological changes, transcriptomic data showed that the process of royal jelly secretion by the mandibular gland (3–16 d) could be divided into three stages with different expression patterns: 3–6 d, 9–12 d, and 16 d. These results elucidate the genetic basis of the involvement of the mandibular gland in the process of royal jelly secretion in Apis mellifera. The mandibular gland in worker bees synthesizes and secretes the organic acids present in royal jelly, and its development directly affects yield and quality. Therefore, we aimed to analyze the differences in morphology and gene expression in the mandibular glands of Apis mellifera carnica worker bees of different ages (3, 6, 9, 12, and 16 d). We dissected their mandibular glands and performed morphological and transcriptomic analyses to investigate the development of the mandibular gland and the molecular regulatory mechanisms involved in royal jelly secretion. Microscopy revealed that mandibular gland development is likely completed in the early stages. There were no significant differences in the structural morphology or organelles involved in the secretion of royal jelly at different ages. Transcriptomics revealed a total of 1554 differentially expressed genes, which were mainly involved in fat metabolism, lipid transport, and energy metabolism. The extracellular matrix–receptor interaction pathway was significantly enriched and contributed to the royal jelly secretion process. These results elucidate the genetic basis of the role of the mandibular gland in royal jelly secretion in A. mellifera and provide a reference for the genetic improvement of bees with high royal jelly production in the future. [ABSTRACT FROM AUTHOR]

In a variety of motor models, the effects of iron-loss (ILS) on motor control accuracy and efficiency are generally ignored. This makes it difficult for the motor control system to obtain accurate control parameters (especially on high speed and low load conditions), and limits the improvement of motor control accuracy. This paper aims to clarify the influence of different ILS modeling and observation methods on motor control performance. Three equivalent models of motors with iron losses are compared. These models are: A parallel model, a series model and the simplified traditional model. Three tests are conducted to obtain the effect of ILS perturbation on ILS estimation results, and then to derive the sensitivity of the motor state and torque to the perturbation. These test conditions include: Ideal no-load, heavy-load, locked-rotor, and ILS perturbations during speed regulation. Simulation results show that the impedance and excitation characteristics of the series model and the parallel model are similar, and the traditional model has the best speed regulation smoothness. The ILS estimation errors of the series model is nearly constant and easy to compensate. For accurate ILS observation results, the series model can achieve better control accuracy. [ABSTRACT FROM AUTHOR]

The ultrasonic guided wave technique is extensively used for nondestructive structural testing, and one of the key steps is to extract a single mode with certain purity from multi-order mixed modes. In this paper, the propagation of ultrasonic guided waves in the cylindrical rod is simulated first; the appropriate broadband excitation signal is selected to excite the multi-order modes in a specific frequency range; and the time–space signal containing multi-order modes is converted to the frequency-wavenumber domain signal by two-dimensional Fourier transform. In the frequency-wavenumber domain, the frequency-wavenumber ridge is extracted from the multi-mode frequency-wavenumber domain based on the dynamic programming method, and then the time-domain signal corresponding to a single mode can be reconstructed. By comparing the excited multi-order mode and the separated single mode with the theoretical results, it is observed that the two results are consistent. Thus, the employed mode-excitation method can accurately excite the multi-order modes in rod structures. Furthermore, the proposed method enables the separation of a single-mode wave with high purity, providing a foundation for future utilization of isolated modes. [ABSTRACT FROM AUTHOR]

Magnetic topological insulators (MTIs) are a group of materials that feature topological band structures with concurrent magnetism, which can offer new opportunities for technological advancements in various applications, such as spintronics and quantum computing. The combination of topology and magnetism introduces a rich spectrum of topological phases in MTIs, which can be controllably manipulated by tuning material parameters such as doping profiles, interfacial proximity effect, or external conditions such as pressure and electric field. In this paper, we first review the mainstream MTI material platforms where the quantum anomalous Hall effect can be achieved, along with other exotic topological phases in MTIs. We then focus on highlighting recent developments in modulating topological properties in MTI with finite-size limit, pressure, electric field, and magnetic proximity effect. The manipulation of topological phases in MTIs provides an exciting avenue for advancing both fundamental research and practical applications. As this field continues to develop, further investigations into the interplay between topology and magnetism in MTIs will undoubtedly pave the way for innovative breakthroughs in the fundamental understanding of topological physics as well as practical applications. [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]

Simple Summary: This study clarified that in the tumor microenvironment, tumor cell-derived TGF-β1 induces the appearance of an IGFBP7+ CAFs subgroup, and its higher IGFBP7 extracellular secretion level accelerated the progression of tumors. Our work suggests that IGFBP7 is a novel predictive marker for clinical outcomes in gastric cancer patients. Patients with infiltrative-type gastric cancer (GC) (Ming's classification) have a poor prognosis due to more metastasis and recurrence. Cancer-associated fibroblasts (CAFs) in infiltrative-type extracellular matrix (ECM) have specific characteristics compared with those of expansive types with respect to metastasis, but the mechanism is still unclear. Based on our proteomics data, TCGA data analysis, and immunohistochemical staining results, significantly higher expression of IGFBP7 was observed in GC, especially in the infiltrative type, and was associated with a poor prognosis. Combining single-cell transcriptome data from GEO and multiple immunofluorescence staining on tissue showed that the differential expression of IGFBP7 mainly originated from myofibroblastic CAFs, the subgroup with higher expression of PDGFRB and α-SMA. After treating primary normal fibroblasts (NFs) with conditional medium or recombined protein, it was demonstrated that XGC-1-derived TGF-β1 upregulated the expression of IGFBP7 in the cells and its secretion via the P-Smad2/3 pathway and mediated its activation with higher FAP, PDGFRB, and α-SMA expression. Then, either conditional medium from CAFs with IGFBP7 overexpression or recombined IGFBP7 protein promoted the migration, invasion, colony formation, and sphere growth ability of XGC-1 and MGC-803, respectively. Moreover, IGFBP7 induced EMT in XGC-1. Therefore, our study clarified that in the tumor microenvironment, tumor-cell-derived TGF-β1 induces the appearance of the IGFBP7+ CAF subgroup, and its higher IGFBP7 extracellular secretion level accelerates the progression of tumors. [ABSTRACT FROM AUTHOR]

The Jimbo-Miwa equation (JME) that describes certain interesting (3+1)-dimensional waves in plasma physics is studied in this work. The Hirota bilinear equation is developed via the Cole-Hopf transform. Then, the symbolic computation, together with the ansatz function schemes, are utilized to seek exact solutions. Some new solutions, such as the multi-wave complexiton solution (MWCS), multi-wave solution (MWS) and periodic lump solution (PLS), are successfully constructed. Additionally, different types of travelling wave solutions (TWS), including the dark, bright-dark and singular periodic wave solutions, are disclosed by employing the sub-equation method. Finally, the physical characteristics and interaction behaviors of the extracted solutions are depicted graphically by assigning appropriate parameters. The obtained outcomes in this paper are more general and newer. Additionally, they reveal that the used methods are concise, direct, and can be employed to study other partial differential equations (PDEs) in physics. [ABSTRACT FROM AUTHOR]

Simple Summary: With the change in meat sheep breeding from traditional farming to large-scale, intensified modern breeding practices, the environmental air quality in sheep barns has gradually started to receive more attention. CO2 concentration is an important environmental indicator in the ambient air of sheep sheds; when excess CO2 accumulates, it can lead to chronic hypoxia, lethargy, loss of appetite, weakness, and stress in sheep, which seriously endangers their healthy growth. Therefore, an accurate understanding of the trend of CO2 concentration changes in sheep housing and the precise regulation of their breeding environment are essential to ensure the welfare of sheep. Inspired by developments in deep learning technology in recent years, we propose a method to predict CO2 mass concentration in sheep barns based on the RF-PSO-LSTM model. The experimental results show that our proposed model has a root mean square error (RMSE) of 75.422 μg·m−3, a mean absolute error (MAE) of 51.839 μg·m−3, and a coefficient of determination (R2) of 0.992. The data predicted by the model are similar to the real data of a sheep barn; in fact, the prediction is better. Our proposed method can provide a reference for the prediction and regulation of ambient air quality in meat sheep barns. In large-scale meat sheep farming, high CO2 concentrations in sheep sheds can lead to stress and harm the healthy growth of meat sheep, so a timely and accurate understanding of the trend of CO2 concentration and early regulation are essential to ensure the environmental safety of sheep sheds and the welfare of meat sheep. In order to accurately understand and regulate CO2 concentrations in sheep barns, we propose a prediction method based on the RF-PSO-LSTM model. The approach we propose has four main parts. First, to address the problems of data packet loss, distortion, singular values, and differences in the magnitude of the ambient air quality data collected from sheep sheds, we performed data preprocessing using mean smoothing, linear interpolation, and data normalization. Second, to address the problems of many types of ambient air quality parameters in sheep barns and possible redundancy or overlapping information, we used a random forests algorithm (RF) to screen and rank the features affecting CO2 mass concentration and selected the top four features (light intensity, air relative humidity, air temperature, and PM2.5 mass concentration) as the input of the model to eliminate redundant information among the variables. Then, to address the problem of manually debugging the hyperparameters of the long short-term memory model (LSTM), which is time consuming and labor intensive, as well as potentially subjective, we used a particle swarm optimization (PSO) algorithm to obtain the optimal combination of parameters, avoiding the disadvantages of selecting hyperparameters based on subjective experience. Finally, we trained the LSTM model using the optimized parameters obtained by the PSO algorithm to obtain the proposed model in this paper. The experimental results show that our proposed model has a root mean square error (RMSE) of 75.422 μg·m−3, a mean absolute error (MAE) of 51.839 μg·m−3, and a coefficient of determination (R2) of 0.992. The model prediction curve is close to the real curve and has a good prediction effect, which can be useful for the accurate prediction and regulation of CO2 concentration in sheep barns in large-scale meat sheep farming. [ABSTRACT FROM AUTHOR]

Purpose: To quantify the structural changes in choroidal vessels and to observe choroid microstructural changes in different age and sex groups in a healthy Chinese population. Methods: Enhanced depth imaging optical coherence tomography (EDI-OCT) was employed to analyze the luminal area, stromal area, total choroidal area, subfoveal choroidal thickness (SFCT), choroidal vascularity index (CVI), large choroidal vessel layer (LCVL), choriocapillaris–medium choroidal vessel layer, and LCVL/SFCT of the choroid in the subfoveal macular area within 1500 μm of the macula. We analyzed the age- and sex-related changes in the subfoveal choroidal structure. Results: A total of 1566 eyes from 1566 healthy individuals were included. The mean age of the participants was 43.62 ± 23.29 years, the mean SFCT of healthy individuals was 269.30 ± 66.43 μm, LCVL/SFCT percentage was 77.21 ± 5.84%, and the mean macular CVI was 68.39 ± 3.15%. CVI was maximum in the 0–10 years group, decreasing with age, and the lowest values occurred in the >80 years group; LCVL/SFCT was the lowest in the 0–10 years group, increasing with age and reaching a maximum in the >80 years group. CVI showed a significant negative correlation with age, and LCVL/SFCT showed a significant positive correlation with age. There was no statistically significant difference between males and females. Interrater and intrarater reliability was less variable with CVI than with SFCT. Conclusions: The choroidal vascular area and CVI decreased with age in the healthy Chinese population, of which the age-related decrease in vascular components maybe dominated by the decrease in choriocapillaris and medium choroidal vessels. Sex had no effect on CVI. The CVI of healthy populations showed better consistency and reproducibility when compared with SFCT. [ABSTRACT FROM AUTHOR]

Simple Summary: The timely and accurate detection of ewe estrus behavior in precision animal husbandry is an important research topic. The timely detection of estrus ewes in mutton sheep breeding can not only protect the welfare of ewes themselves, but also improve the interests of breeding enterprises. With the continuous increase in the scale of mutton sheep breeding and the gradual intensification of breeding methods, the traditional manual detection methods require high labor intensity, and the contact sensor detection methods will cause stress reaction problems in ewes. In recent years, the rapid development of deep learning technology has brought on new possibilities. We propose a method for the recognition ewe estrus based on a multi-target detection layer neural network. The results show that the method can meet the requirements of timely and accurate detection of ewe estrus behavior in large-scale mutton sheep breeding. There are some problems with estrus detection in ewes in large-scale meat sheep farming: mainly, the manual detection method is labor-intensive and the contact sensor detection method causes stress reactions in ewes. To solve the abovementioned problems, we proposed a multi-objective detection layer neural network-based method for ewe estrus crawling behavior recognition. The approach we proposed has four main parts. Firstly, to address the problem of mismatch between our constructed ewe estrus dataset and the YOLO v3 anchor box size, we propose to obtain a new anchor box size by clustering the ewe estrus dataset using the K-means++ algorithm. Secondly, to address the problem of low model recognition precision caused by small imaging of distant ewes in the dataset, we added a 104 × 104 target detection layer, making the total target detection layer reach four layers, strengthening the model's ability to learn shallow information and improving the model's ability to detect small targets. Then, we added residual units to the residual structure of the model, so that the deep feature information of the model is not easily lost and further fused with the shallow feature information to speed up the training of the model. Finally, we maintain the aspect ratio of the images in the data-loading module of the model to reduce the distortion of the image information and increase the precision of the model. The experimental results show that our proposed model has 98.56% recognition precision, while recall was 98.04%, F1 value was 98%, mAP was 99.78%, FPS was 41 f/s, and model size was 276 M, which can meet the accurate and real-time recognition of ewe estrus behavior in large-scale meat sheep farming. [ABSTRACT FROM AUTHOR]

Objective: Anxiety symptoms are persistent in Parkinson's disease (PD), but the underlying neural substrates are still unclear. In the current study, we aimed to explore the underlying neural mechanisms in PD patients with anxiety symptoms. Methods: 42 PD-A patients, 41 PD patients without anxiety symptoms (PD-NA), and 40 healthy controls (HCs) were recruited in the present study. All the subjects performed 3.0T fMRI scans. The fractional amplitude of low-frequency fluctuation (fALFF) analysis was used to investigate the alterations in neural activity among the three groups. A Pearson correlation analysis was performed between the altered fALFF value of the PD-A group and anxiety scores. Results: Compared with HCs, PD-A patients had higher fALFF values in the left cerebellum, cerebellum posterior lobe, bilateral temporal cortex, and brainstem and lower fALFF values in the bilateral inferior gyrus, bilateral basal ganglia areas, and left inferior parietal lobule. Moreover, between the two PD groups, PD-A patients showed higher fALFF values in the right precuneus and lower fALFF values in the bilateral inferior gyrus, bilateral basal ganglia areas, left inferior parietal lobule, and left occipital lobe. Furthermore, Pearson's correlation analysis demonstrated that the right precuneus and left caudate were correlated with the Hamilton Anxiety Rating Scale scores. Conclusion: Our study found that anxiety symptoms in PD patients may be related to alterations of neurological activities in multiple brain regions. Furthermore, these may be critical radiological biomarkers for PD-A patients. Therefore, these findings can improve our understanding of the pathophysiological mechanisms underlying PD-A. [ABSTRACT FROM AUTHOR]

Simple Summary: Studies have shown that SPP1 plays an important role in the progression of certain tumors, but the specific functional mechanism in gastric cancer (GC) is still unclear. Our goal was to reveal the prognostic value of SPP1 in GC and its role in the GC tumor microenvironment based on multi-transcriptomic analysis. We demonstrated that a high expression of SPP1 contributed to advanced gastric TNM stages and a poor prognosis for advanced GC patients, providing a solution to the controversy regarding the clinical relevance of SPP1 in GC. Furthermore, we found that SPP1+ macrophages were unique to GC cancerous tissues and cancer cell-containing regions, and that the SPP1/CD44-mediated crosstalk between SPP1+ macrophages and cancer cells formed a specific niche to accelerate the malignant progression of GC, which may serve as a therapeutic target with fewer side-effects in GC. GC is a fatal disease with high heterogeneity and invasiveness. Recently, SPP1 has been reported to be involved in the tumor progression of multiple human cancers; however, the role of SPP1 in GC heterogeneity and whether it is associated with the invasiveness and mortality of GC remain unclear. Here, we combined multiple RNA sequencing approaches to evaluate the impact of SPP1 on GC. Through bulk RNA sequencing (bulk RNA-seq) and immunohistochemistry (IHC), we found that SPP1 was highly expressed in GC, and high levels of SPP1 were associated with macrophage infiltration, an advanced tumor stage, and higher mortality for advanced GC patients. Furthermore, through simultaneous single-cell and spatial analysis, we demonstrated that SPP1+ macrophages are tumor-specific macrophages unique to cancer and enriched in the deep layer of GC tissue. Cell—cell communication analysis revealed that SPP1/CD44 interactions between SPP1+ macrophages and their localized tumor epithelial cells could activate downstream target genes in epithelial cells to promote dynamic changes in intratumor heterogeneity. Moreover, these activated genes were found to be closely associated with poor clinical GC outcomes and with cancer-related pathways that promote GC progression, as shown by survival analysis and enrichment analysis, respectively. Collectively, our study reveals that tumor-specific SPP1+ macrophages drive the architecture of intratumor heterogeneity to evolve with tumor progression and that SPP1 may serve as a prognostic marker for advanced GC patients, as well as a potential therapeutic target for GC. [ABSTRACT FROM AUTHOR]

The bore hole is sealed from a sealing hole: the surrounding coal fracture permeability and grout cementation form a new consolidated body and coal material. In this paper, the characteristics of the macroscopic compressive strength, microscopic interface bending, porosity, and fractal dimension of the consolidated body were studied, and the structure strength relationship between loading rates, porosity, fractal dimension, and uniaxial compressive strength (UCS) was established. The results show that the loading rates had a great and consistent effect on the macro- and micro-mechanical properties of the consolidated body. Macroscopically, in the range of 0.1~0.4 mm/min, the UCS and elastic modulus of the solidified body increased with the increase in the loading rate, and there was a critical loading rate (η = 0.4 mm/min). At the microscale, with the increase in loading rates, the interface bending phenomenon, porosity, fractal dimension, and UCS of the grout and coal were consistent, showing a trend of increasing first and then decreasing. The fractal dimension was linearly correlated with the UCS and porosity. The loading rates, porosity, fractal dimension, and UCS had a multivariate nonlinear regression distribution. [ABSTRACT FROM AUTHOR]

Wood vinegar, a by-product of wood pyrolysis, is mostly discarded. Wood vinegar has a phytotoxic effect and could be potentially used as a naturally derived herbicide for weed control. The objective of this research was to evaluate the efficacy of wood vinegar from the pyrolysis of apple (Malus × domestica Borkh.) tree branch wastes to control weeds. The wood vinegar concentrations required to inhibit 50% motherwort (Leonurus cardiaca L.), redroot pigweed (Amaranthus retroflexus L.), Spanish needles (Bidens pilosa L.), and tall fescue (Festuca arundinacea L.) seed germination measured 0.51%, 0.48%, 0.16%, and 1.1%, respectively. The wood vinegar application rates (spray volume) required to provide 50% control of motherwort and Spanish needles measured 1911 L ha−1 and 653 L ha−1, respectively, while the highest evaluated rate at 4000 L ha−1 controlled 35% tall fescue by 10 days after treatment (DAT). Common purslane (Portulaca oleracea L.) control increased as the wood vinegar application rate increased from 500 L ha−1 to 2000 L ha−1. Wood vinegar was more effective in dark than light conditions for controlling common purslane. By 5 DAT, averaged over application rates, wood vinegar provided 95% and 87% control of common purslane in dark and light conditions, respectively. These findings suggest that wood vinegar obtained from the pyrolysis of apple tree branches could be used for weed management. [ABSTRACT FROM AUTHOR]

Echovirus 3 (E3), a serotype of human enterovirus B (HEV-B), causes severe diseases in infants. Here, we determined the structures of E3 with a monoclonal antibody (MAb) 6D10 by cryo-EM to comprehensively understand the specificities and the immunological characteristic of this serotype. The solved cryo-EM structures of the F-, A-, and E-particles of E3 bound with 6D10 revealed the structural features of the virus–antibody interface. Importantly, the structures of E-particles bound with 6D10 revealed for the first time the nature of the C-terminus of VP1 for HEV-Bs at the structural level. The highly immunogenic nature of this region in the E-particles provides new strategies for vaccine development for HEV-Bs. [ABSTRACT FROM AUTHOR]

Electric-field control of spin dynamics is significant for spintronic device applications. Thus far, effectively electric-field control of magnetic order, magnetic damping factor and spin–orbit torque (SOT) has been studied in magnetic materials, but the electric field control of spin relaxation still remains unexplored. Here, we use ionic liquid gating to control spin-related property in the ultra-thin (4 nm) heavy metal (HM) platinum (Pt) and ferromagnetic insulator (FMI) yttrium iron garnet (Y3Fe5O12, YIG) heterostructure. It is found that the anomalous Hall effect (AHE), spin relaxation time and spin diffusion length can be effectively controlled by the electric field. The anomalous Hall resistance is almost twice as large as at 0 voltage after applying a small voltage of 5.5 V. The spin relaxation time can vary by more than 50 percent with the electric field, from 41.6 to 64.5 fs. In addition, spin relaxation time at different gate voltage follows the reciprocal law of the electron momentum scattering time, which indicates that the D'yakonov–Perel' mechanism is dominant in the Pt/YIG system. Furthermore, the spin diffusion length can be effectively controlled by an ionic gate, which can be well explained by voltage-modulated interfacial spin scattering. These results help us to improve the interface spin transport properties in magnetic materials, with great contributions to the exploration of new physical mechanisms and spintronics device. [ABSTRACT FROM AUTHOR]