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Summary For tobacco strips used in cigarette production, the stem content is an important quality index to assess the impurity level of the cut leaves. The presented work developed a nondestructive detection method of stems in cut leaf agricultural products by the low energy X-ray imaging. The algorithm of stem image processing and weight calculation principle was established, and then a machine vision system with X-ray imaging and image analysis was set up to verify the quantitative detection method. The results showed that the relative error of the detection method ranged from −3.64% to 2.76%. The determination of stems with a different morphology, such as the thick stem, were also realized based on the image analysis. The accuracy of determining thick stem and long stem was 94.67% and 99.33%, respectively. The developed method is superior to the current ISO detection method of tobacco stem in leaves under the same testing conditions in terms of accuracy and efficiency, which could be applied as an effective online detection method to monitor the quality of processed leaf for cigarette production.

The Lower Cretaceous Bashijiqike Formation of the Kuqa Depression is made up of ultra-deeply buried sandstones in fold-and-thrust belts. Few researches have linked diagenetic processes with structure. To fill this gap, a comprehensive analysis integrating diagenesis with structure pattern, fracture and in situ stress is performed following a structural diagenetic approach. The results show that the pore spaces include residual intergranular pores, intergranular and intragranular dissolution pores, and micro-fractures. The sandstones experienced a high degree of mechanical compaction, but compaction is limited in well-sorted rocks or abundant in rigid quartz grains. The most volumetrically important diagenetic minerals are calcites. The framework grains experienced a varied degree of dissolution, and intergranular and intragranular dissolution pores are formed. Special attention is paid on the dissolution associated with the fracture planes. Large numbers of natural fractures are cemented by carbonate cements, which limit fluid flow. In addition, the presence of fracture enhances dissolution and the fracture planes are enlarged by dissolution. Cementation and dissolution can occur simultaneously in fracture surfaces, and the enlarged fracture surfaces can be cemented by late-stage cements. The in situ stress magnitudes are calculated using well logs. The horizontal stress difference (Δσ) determines the degree of mechanical compaction, and rocks associated with low Δσ experienced a low degree of compaction, and these contain preserved intergranular pores. Natural fractures are mainly related to the low Δσ layers. The presence of intergranular and intragranular dissolution pores is mainly associated with the fractured zones. The high-quality reservoirs with intergranular pores or fractures are related to low Δσ layers. The structural diagenesis researches above help the prediction of reservoir quality in ultra-deep sandstones and reduce the uncertainty in deep natural gas exploration in the Kuqa Depression.

Vehicle detection based on remote sensing images is of great significance to intelligent traffic management and smart city planning. The performances of the mainstream vehicle detection methods such as Fast-RCNN, SSD, FCRN, etc. are mainly affected by their extracted features, whose richness and robustness can be enhanced by introducing pre-training models from other datasets. However, the weights of the pre-training models used in traditional methods like FCRN, only shallow-tuned from the weights of another database training, without deep optimization from random initialization. This letter proposes a new pre-training and random-initialized fusion network (PRFN): the random initialization model and the pre-training model are connected in parallel, and an encoder is used to fuse their features, thereby improving the richness of features and the robustness of the model. We evaluate four different combination patterns of the pre-training and random initialized models, and the effect of the fusion feature encoder. Experiments show the parallel concatenating pattern with the fusion feature encoder achieves the best performance than other patterns. We test on three datasets, our PRFN exceeds the traditional methods, and, respectively, 1.23%, 1.04%, 0.94% higher than the baseline. All codes are available from https://github.com/LHKRobert/PRFN.

Road detection based on remote sensing images is of great significance to intelligent traffic management. The performances of the mainstream road detection methods are mainly determined by their extracted features, whose richness and robustness can be enhanced by fusing features of different types and cross-layer connections. However, the features in the existing mainstream model frameworks are often similar in the same layer by the single-task training, and the traditional cross-layer fusion ways are too simple to obtain an efficient effect, so more complex fusion ways besides concatenation and addition deserve to be explored. Aiming at the above defects, we propose a dual-task network (DTnet) for road detection and cross-layer graph fusion module (CGM): the DTnet consists of two parallel branches for road area and edge detection, respectively, while enhancing the feature diversity by fusing features between two branches through our designed feature bridge modules (FBM). The CGM improves the cross-layer fusion effect by a complex feature stream graph, and four graph patterns are evaluated. Experimental results on three public datasets demonstrate that our method effectively improves the final detection result.

Finding new ways to prevent and reduce the incidence of dementia is a serious world problem. This study aimed to perform imaging comparisons between pre- and post-meridian sinew therapy using arterial spin labeling (ASL) and resting-state functional MRI (rs-fMRI). Meanwhile, the results were studied to provide imaging evidence to support the effect of this meridian sinew therapy to slow down the brain aging and to reveal the related neurological mechanisms. Eighteen sub-healthy volunteers were selected as subjects. Three treatment strategies were adopted, acupuncture (group A), myofascial release (group B), and the integrated acupuncture and myofascial release (group C). The subjects were assigned to receive the three treatment modalities sequentially. 3T MRI examinations were provided before and after each treatment, including routine brain MRI plain scan, ASL and rs-fMRI scan. Compared with the results before and after treatment, the number of brain regions with increased cerebral blood flow (CBF) values in the group A, group B, and group C were respectively 1, 15 and 10 brain regions, all including the right cingulate gyrus. And rs-fMRI showed that multiple brain regions was activated, mainly temporal lobe and frontal lobe. The independent component analysis showed that the right intraorbital superior frontal gyrus and the occipital region was activated. Meridian sinew therapy can increase CBF and enhance neuronal activity in brain regions significantly associated with cognitive and memory functions, which may be the main targets where it actions on to achieve “Xingshen Yizhi (waking up the spirit and reinforcing thinking activity)” effect. The combination of ASL and rs-fMRI may be an effective imaging modality for future quantitative monitoring of the preventive and therapeutic effects of the meridian sinew therapy.

Deep-UV (DUV) nonlinear optical (NLO) materials are of vital importance to demanding DUV laser applications; however, those with a large NLO coefficient, wide band gap, and sufficient phase-matching ability are rare. In this work, by combining π-conjugated B3O6 groups and distort AlO3F tetrahedra, we successfully designed and synthesized two fluoroaluminoborates, RbAlB3O6F (RABF) and Cs0.5Rb0.5AlB3O6F (CRABF). In addition, the solid solution CsxRb1-xAlB3O6F (0.2 < x < 0.8) polycrystalline samples were obtained by the standard solid-state reaction. It was shown that all these compounds are NLO-active and possess short UV cutoff edges (

Nonlinear optical (NLO) crystals are key materials for solid-state lasers, which play an important role in modern science and technology. Recently, metal oxyfluorides have attracted much attention for next-generation NLO materials, in particular those used in the deep ultraviolet (DUV) and middle-infrared (MIR) regions. The incorporation of additional fluorine atoms allows new oxyfluoride-based NLO materials to span a more varied structure design palette than the oxide-only analogs. Therefore, metal oxyfluorides combine the advantages of fluorides and oxides, achieving wide transparent windows, large NLO coefficients, phase-match abilities, and high laser damage threshold values. For example, fluorooxoborates, fluorophosphates, fluorooxosilicophosphates, fluoroiodates, and fluorotellurites display new structural types and enhanced NLO performances. In this review, recently reported oxyfluoride NLO crystals are discussed. Their synthesis approaches, crystal chemistry, NLO performance, and structure–property relationship are reviewed. In addition, open challenges in both the synthesis and crystal growth of oxyfluorides are proposed. This work would provide a useful perspective on the exploration of next-generation NLO candidates with high performances to meet the urgent demands in DUV and MIR regions.

Second-order nonlinear optical (NLO) materials that can alter the wavelength of lasers have attracted significant attention for their optoelectronic applications. Recent research suggests that benzene-like structure units, such as [B3O6] and [C3N3O3] rings, are promising building units to construct new NLO materials with excellent optical properties. In this feature article, we will introduce the recent development of benzene-like ring based NLO materials with a highlight of our contributions, illustrating how to optimize the conjugated π system, including arrangement modes, different linkers, and isoelectronic species, to tune the band gap and NLO properties.

The crystal structure of a new cesium trithiocyanurate compound, Cs4(HC3N3S3)2·4H2O, was determined by X-ray diffraction analysis. Cs4(HC3N3S3)2·4H2O crystallizes in the space group Pnma, with cell parameters a = 21.961(5) A, b = 11.928(3) A, and c = 8.903(2) A. Its structure consists of crosswise arranged (HC3N3S3)2− units, and Cs+ cations and H2O molecules are located in the voids. The title compound was characterized by IR and UV–vis diffuse reflectance spectroscopy and thermal analysis. In addition, electrochemical impedance spectrum measurements were performed and revealed that the title compound exhibits proton conduction with the conductivity on the order of 10−4 S cm−1. The electronic structure and calculated optical anisotropy of Cs4(HC3N3S3)2·4H2O were also reported, which demonstrated that the compound exhibits a very large birefringence (Δn = 0.236@800 nm).

The single-cell RNA sequencing provides a way to obtain marker genes of different cells, which lays the foundation for discovering new cell types. The general strategy of achieving this goal is to build a clustering pipeline and derive differentially expressed genes, followed by the cell type enrichment analysis and driving force analysis. Throughout the entire analysis process, clustering models and appropriate methods of dimension reduction are two vital and challenging tasks. In this study, we present a novel method LAK (a computational pipeline for single-cell RNA-seq data clustering analysis using Lasso and K-means based feature selection method) that can be applied to single-cell RNA-seq data by selecting the candidate genes. To deal with the sparse high-dimensional data, we integrated Lasso penalty into clustering method for single-cell RNA-seq data as the feature selection method, which extracts out the genes that have an actual effect on clustering. We also improved the parameter selection algorithm to search the appropriate parameters automatically by binary search according to the size of the data. Compared with other computational approaches, LAK obtains a better performance in reliability, stability, convenience and accuracy applied to the real datasets, the simulation data, and the datasets with a large number of dropout events.

The design of new beryllium-free deep-ultraviolet nonlinear optical materials is important but challenging. Here, we describe a new strategy to search for such materials based on rational selection of fundamental structural units. By combining asymmetric AlO3F tetrahedra and π-conjugated B3O6 rings, a new aluminum borate fluoride, CsAlB3O6F was obtained. It exhibits excellent linear and nonlinear optical properties including a high optical transmittance with a cut-off edge shorter than 190 nm, large second harmonic generation intensities (2.0× KH2PO4, KDP), and suitable birefringence for phase-matching under 200 nm. It also has good thermal stability and can be synthesized easily in an open system., A new potential deep-ultraviolet nonlinear optical material CsAlB3O6F was designed by a rational selection of fundamental structural units. This material does not require toxic raw materials and can be grown in an open system.

The Lower Cretaceous Bashijiqike Formation of Kuqa depression is ultra-deeply buried sandstone in fold-and-thrust belts. Few researches link diagenetic processes with structure. To fill this gap, a comprehensive analysis integrating diagenesis with structure pattern, fracture and in situ stress is performed following a structural diagenetic approach. The results show that the pore spaces include residual intergranular pores, intergranular and intragranular dissolution pores, and micro-fractures. The sandstones experienced a high degree of mechanical compaction, and compaction is limited in well-sorted rocks or abundant in rigid quartz grains. The most volumetrically important diagenetic minerals are calcites. The framework grains experienced a varied degree of dissolution, and intergranular and intragranular dissolution pores are formed. Special aims are paid on the dissolution associated with the fracture planes. Most natural fractures are cemented by carbonate cements, which limit fluid flow. In addition, presences of fracture enhance dissolution, and the fracture planes are enlarged by dissolution. Cementation and dissolution can occur simultaneously in fracture surfaces, and the enlarged fracture surfaces can be cemented by late-stage cements. The in situ stress magnitudes are calculated using well logs. The horizontal stress difference (Δσ) determines the degree of mechanical compaction, and rocks associated with low Δσ experienced a low degree of compaction, and there contain preserved intergranular pores. Natural fractures are mainly related to the low Δσ layers. The presences of intergranular and intragranular dissolution pores are mainly associated with the fractured zones. The high quality reservoirs with intergranular pores or fractures are related to low Δσ layers. The structural diagenesis researches above help the prediction of reservoir quality in ultra-deep sandstones, and reduce the uncertainty in deep natural gas exploration in Kuqa depression.

Common fragile sites (CFSs) are specific breakage-prone genomic regions and are present frequently in cancer cells. The (E2-independent) E3 ubiquitin-conjugating enzyme FATS (fragile site-associated tumor suppressor) has antitumor activity in cancer cells, but the function of FATS in immune cells is unknown. Here, we report a function of FATS in tumor development via regulation of tumor immunity. Fats−/− mice show reduced subcutaneous B16 melanoma and H7 pancreatic tumor growth compared with WT controls. The reduced tumor growth in Fats−/− mice is macrophage dependent and is associated with a phenotypic shift of macrophages within the tumor from tumor-promoting M2-like to antitumor M1-like macrophages. In addition, FATS deficiency promotes M1 polarization by stimulating and prolonging NF-κB activation by disrupting NF-κB/IκBα negative feedback loops and indirectly enhances both CD4+ T helper type 1 (Th1) and cytotoxic T lymphocyte (CTL) adaptive immune responses to promote tumor regression. Notably, transfer of Fats−/− macrophages protects mice against B16 melanoma. Together, these data suggest that FATS functions as an immune regulator and is a potential target in cancer immunotherapy., The role of common fragile site associated genes such as FATS in the immune system is unclear. Here the authors show that deletion of Fats in a mouse tumour model leads to reduced tumour growth and change of macrophage phenotype from an M2-like to M1-like function.

Muscle redox disturbances and oxidative stress have emerged as a common pathogenetic mechanism and potential therapeutic intervention in some muscle diseases. Parthenolide (PTL), a sesquiterpene lactone found in large amounts in the leaves of feverfew, possesses anti-inflammatory, anti-migraine, and anticancer properties. Although PTL was reported to alleviate cancer cachexia and improve skeletal muscle characteristics in a cancer cachexia model, its actions on oxidative stress-induced damage in C2C12 myoblasts have not been reported and the regulatory mechanisms have not yet been defined. In our study, PTL attenuated H2 O2 -induced growth inhibition and morphological changes. Furthermore, PTL exhibited scavenging activity against reactive oxygen species and protected C2C12 cells from apoptosis in response to H2 O2 . Meanwhile, PTL suppressed collapse of the mitochondrial membrane potential, thereby contributing to normalizing H2 O2 -induced autophagy flux and mitophagy, correlating with inhibiting degradation of mitochondrial marker protein TIM23, the increase in LC3-II expression and the reduction of mitochondria DNA. Besides its protective effect on mitochondria, PTL also prevented H2 O2 -induced lysosomes damage in C2C12 cells. In addition, the phosphorylation of p53, cathepsin B, and Bax/Bcl-2 protein levels, and the translocation of Bax from the cytosol to mitochondria induced by H2 O2 in C2C12 cells was significantly reduced by PTL. In conclusion, PTL modulates oxidative stress-induced mitophagy and protects C2C12 myoblasts against apoptosis, suggesting a potential protective effect against oxidative stress-associated skeletal muscle diseases.

With the rapid development of power internet of things and the continuous improvement of the State Grid Company's requirements for the safe operation of the station, there are more and more monitoring systems for power transmission and transformation pipe gallary in engineering application. The information between multiple systems is relatively isolated. The workload of the operation and maintenance personnel increases dramatically, and the operation safety risk increases accordingly. In order to improve the perception ability, remote operation and maintenance level of the station, it is necessary to study a kind of management platform for information sharing. Based on mqtt protocol and using microservice architecture, the design makes function module plug-and-play possible. An edge autonomy technology of IOT is proposed to integrate intelligent substation and internet of things which can improve the high reliability of the system operation and ensure the security and stability of the power system.

Microglia are innate immune cells in the central nervous system (CNS), that supplies neurons with key factors for executing autophagosomal/lysosomal functions. Macroautophagy/autophagy is a cellular catabolic process that maintains cell balance in response to stress-related stimulation. Abnormal autophagy occurs with many pathologies, such as cancer, and autoimmune and neurodegenerative diseases. Hence, clarification of the mechanisms of autophagy regulation is of utmost importance. Recently, researchers presented microRNAs (miRNAs) as novel and potent modulators of autophagic activity. Here, we found that Mir223 deficiency significantly ameliorated CNS inflammation, demyelination and the clinical symptoms of experimental autoimmune encephalomyelitis (EAE) and increased resting microglia and autophagy in brain microglial cells. In contrast, the autophagy inhibitor 3-methylademine (3-MA) aggravated the clinical symptoms of EAE in wild-type (WT) and Mir223-deficienct mice. Furthermore, it was confirmed that Mir223 deficiency in mice increased the protein expression of ATG16L1 (autophagy related 16-like 1 [S. cerevisiae]) and LC3-II in bone marrow-derived macrophage cells compared with cells from WT mice. Indeed, the cellular level of Atg16l1 was decreased in BV2 cells upon Mir223 overexpression and increased following the introduction of antagomirs. We also showed that the 3’ UTR of Atg16l1 contained functional Mir223-responsive sequences and that overexpression of ATG16L1 returned autophagy to normal levels even in the presence of Mir223 mimics. Collectively, these data indicate that Mir223 is a novel and important regulator of autophagy and that Atg16l1 is a Mir223 target in this process, which may have implications for improving our understanding of the neuroinflammatory process of EAE. Abbreviations: 3-MA: 3-methylademine; ACTB/β-actin: actin, beta; ATG: autophagy related; ATG16L1: autophagy related 16-like 1 (S. cerevisiae); BECN1: beclin 1, autophagy related; CNR2: cannabinoid receptor 2 (macrophage); CNS: central nervous system; CQ: chloroquine; EAE: experimental autoimmune encephalomyelitis; FOXO3: forkhead box O3; GAPDH: glyceraldehyde-3-phosphate dehydrogenase; H&E: hematoxylin and eosin; ITGAM: integrin alpha M; LPS: lipoplysaccharide; MAP1LC3/LC3: microtubule-associated protein 1 light chain 3; miRNAs: microRNAs; MS: multiple sclerosis; PPARG: peroxisome proliferator activated receptor gamma; PTPRC: protein tyrosine phosphatase, receptor type, C; RA: rheumatoid arthritis; SQSTM1: sequestosome 1; TB: tuberculosis; TIMM23: translocase of inner mitochondrial membrane 23; TLR: toll-like receptor.

Reflux welding is widely used in SMT (surface patch technology) During this production process, the quality of the product is essential to maintain the temperature and the furnace speed required by the process. The furnace temperature curve in the furnace is an important form of reaction welding process. In order to improve the process efficiency of the return furnace, the heating welding process model is established based on the Fourier heat conduction law,1 D heat conduction model and Newton cooling law and draws the furnace temperature curve model. Then, the upper boundary of the conveyor speed using the boundary analysis and multiple target planning, and further explore the research and optimization direction of subsequent process flow. At the same time, this paper examines and analyzes the modeling process and results, and effectively demonstrates the scientific nature and accuracy of the model. Finally, the paper analyzes the significance of the above model and research in chip processing.

Aiming at the problems of traditional wireless communication network security vulnerability monitoring systems such as low monitoring accuracy and time-consuming, a machine learning-based intelligent monitoring system for wireless communication network security vulnerabilities is proposed. In the hardware design of the monitoring system, based on the overall architecture of the wireless communication network and the data characteristics of the wireless communication network, it is divided into a vulnerability data collection module, a vulnerability data scanning module, and a network security vulnerability intelligent monitoring module. In the vulnerability data collection module, the wireless data collector is used to collect vulnerability data in the vulnerability database, and according to the attributes of the vulnerability data, the XSS vulnerability detection plug-in is connected to the vulnerability scanner to scan for wireless communication network vulnerabilities; When the communication network vulnerability data signal is traced, the system session operation of monitoring the vulnerability data. The software part introduces the neural network algorithm in the machine learning intelligent algorithm to process the hidden data in the security vulnerability data. The experimental results show that the wireless communication network security vulnerability intelligent monitoring system based on machine learning can effectively improve the system monitoring accuracy and the efficiency of wireless communication network security vulnerability monitoring.