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The power transmission tower’s ground electrode defect will affect its normal current dispersion function and threaten the power system’s safe and stable operation and even personal safety. Aiming at the problem that the buried grounding grid is difficult to be detected, this paper proposes a method for identifying the ground electrode defects of transmission towers based on single-side multi-point excited ultrasonic guided waves. The geometric model, ultrasonic excitation model, and physical model are established, and the feasibility of ultrasonic guided wave detection is verified through the simulation and experiment. In actual inspection, it is equally important to determine the specific location of the defect. Therefore, a multi-point excitation method is proposed to determine the defect’s actual position by combining the ultrasonic guided wave signals at different excitation positions. Besides, the precise quantification of flat steel grounding electrode defects is achieved through the feature extraction-neural network method. Field test results show that, compared with the commercial double-sided excitation transducer, the single-sided excitation transducer proposed in this paper has a lower defect quantization error in defect quantification. The average quantization error is reduced by approximately 76%.

Recently, the generative adversarial network (GAN) has been widely used to obtain the real high-frequency details of images. This spurs the application of GAN in super-resolution reconstruction. However, GAN is unstable in the training process, for the following two reasons: Firstly, the discriminator in GAN keeps the positive (true) and negative (false) criteria of the generated samples unchanged throughout the learning process, without considering the gradual quality improvement of the generated samples (Sometimes, the generated samples are even more realistic than the real samples). To solve the above problems, this paper proposes a super-resolution model based on positive-unlabeled (PU)-GAN-Charbon (SRPUGAN-Charbon). The proposed model includes one generator network that synthetizes super-resolution images and one discriminator network trained to distinguish super-resolution images from real high-resolution images. In addition, the Charbonnier loss function was called to handle the outliers in super-resolution images, and retain the low-frequency features of super-resolution images. Extensive experiments were conducted on three benchmark databases, including BSDS500, Set5, and Set14. The results show that the proposed SRPUGAN-Charbon method is superior to the most advanced methods in terms of visual effect, peak signal-to-noise ratio (PSNR), and structural similarity (SSIM).

Haohan Zhou,1,2,* Jiayi Tian,3,* Hongyu Sun,1 Jiaying Fu,1 Nan Lin,1 Danni Yuan,1 Li Zhou,3 Meihui Xia,3 Liankun Sun1 1Key Laboratory of Pathobiology, Ministry of Education, Department of Pathophysiology, College of Basic Medical Sciences, Jilin University, Changchun, 130021, People’s Republic of China; 2Department of Orthopaedic Oncology, Changzheng Hospital, Second Military Medical University, Shanghai, 200000, People’s Republic of China; 3First Hospital, Jilin University, Changchun, 130021, People’s Republic of China*These authors contributed equally to this workCorrespondence: Liankun Sun, Key Laboratory of Pathobiology, Ministry of Education, Department of Pathophysiology, College of Basic Medical Sciences, Jilin University, Changchun, 130021, People’s Republic of China, Email sunlk@jlu.edu.cn Meihui Xia, First Hospital, Jilin University, Changchun, 130021, People’s Republic of China, Email xiamh@jlu.edu.cnPurpose: Magnetic iron oxide nanoparticle (MNP) drug delivery system is a novel promising therapeutic option for cancer treatment. Material issues such as fabrication and functionalized modification have been investigated; however, pharmacologic mechanisms of bare MNPs inside cancer cells remain obscure. This study aimed to explore a systems pharmacology approach to understand the reaction of the whole cell to MNPs and suggest drug selection in MNP delivery systems to exert synergetic or additive anti-cancer effects.Methods: HeLa and SiHa cell lines were used to estimate the properties of bare MNPs in cervical cancer through 3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide (MTT) and enzyme activity assays and cellular fluorescence imaging. A systems pharmacology approach was utilized by combining bioinformatics data mining with clinical data analysis and without a predefined hypothesis. Key genes of the MNP onco-pharmacologic mechanism in cervical cancer were identified and further validated through transcriptome analysis with quantitative reverse transcription PCR (qRT-PCR).Results: Low cytotoxic activity and cell internalization of MNP in HeLa and SiHa cells were observed. Lysosomal function was found to be impaired after MNP treatment. Protein tyrosine kinase 2 beta (PTK2B), liprin-alpha-4 (PPFIA4), mothers against decapentaplegic homolog 7 (SMAD7), and interleukin (IL) 1B were identified as key genes relevant for MNP pharmacology, clinical features, somatic mutation, and immune infiltration. The four key genes also exhibited significant correlations with the lysosome gene set. The qRT-PCR results showed significant alterations in the expression of the four key genes after MNP treatment in HeLa and SiHa cells.Conclusion: Our research suggests that treatment of bare MNPs in HeLa and SiHa cells induced significant expression changes in PTK2B, PPFIA4, SMAD7, and IL1B, which play crucial roles in cervical cancer development and progression. Interactions of the key genes with specific anti-cancer drugs must be considered in the rational design of MNP drug delivery systems.Keywords: drug delivery, anti-cancer drugs, PTK2B, PPFIA4, SMAD7, IL1B

Focusing on the unneglectable error of testing results for the rough surface material by the Priest-Germer (PG) model, the basic model assumption, modeling process, parameters inversion and fitting results are analyzed, and the cause for the error is found out. Taking the physical fact that evanescent wave existing in the fine structured surface as the basis, and ignoring the penetration depth and phase delay, a new assumed surface configuration which is integrated into micro-hemispheroid is created. Then, a new reflectance function is built, the inner scatter function is refined, and a new polarized bidirectional reflection distribution model(pBRDF) is established. Illuminated by full spectrum light in a laboratory, the spectrum testing data of dual-directional reflectance for surface is acquired, and the performance of the PG model and the new model is compared. The result indicates that the new model error in the radiance and the degree of linear polarization (DOLP) is respectively about 35% and 59% of that of the PG model.

Liquid-phase transmission electron microscopy (LPTEM) technique has been used to perform a wide range of in situ and operando studies. While most studies are based on the sample contrast change in the liquid, acquiring high qualitative results in the native liquid environment still poses a challenge. Herein, we present a novel and facile method to perform high-resolution and analytical electron microscopy studies in a liquid flow cell. This technique is based on removing the liquid from the observation area by a flow of gas. It is expected that the proposed approach can find broad applications in LPTEM studies.

Microcontact printing, polymer pen lithography, and their variations have attracted interests from a broad spectrum of research fields as a result of the feasibility of defining patterns in micro- and nanoscales. In this work, we have proposed and demonstrated a novel lithography method, named plasma-assisted microcontact printing (PA-μCP). Unlike the previous printing methods, where a direct contact is normally required for the transport of liquid-phase inks, plasma-deposited fluorocarbon (FC) has been employed in PA-μCP as the ink material, which can be transferred from the stamp to substrates through a thermal evaporation process. The geometry of the patterns can be modified by adjusting the design of stamp patterns and the contact time, and transferred FC patterns can be used directly as an etch mask to create microstructures in the substrate materials. We have demonstrated the possibility of performing multi-patterning with PA-μCP, where FC patterns can be generated conformally on structured substrates. Because the height of FC patterns is closely related to the local pattern designs, PA-μCP can be used for grayscale patterning. As a proof of concept, Fabry-Perot planar cavities are fabricated with grayscale PA-μCP for structure color printing. We believe PA-μCP is distinguished from conventional techniques by its printing mechanism, which can pave the way for convenient fabrication of photonic, electronic, and biological devices.

Defining and visualizing the three-dimensional (3D) structures of pharmaceuticals provides a new and important tool to elucidate the phenomenal behavior and underlying mechanisms of drug delivery systems. The mechanism of drug release from complex structured dosage forms, such as bilayer osmotic pump tablets, has not been investigated widely for most solid 3D structures. In this study, bilayer osmotic pump tablets undergoing dissolution, as well as after dissolution in a desiccated solid state were examined, and visualized by synchrotron radiation micro-computed tomography (SR-μCT). In situ formed 3D structures at different in vitro drug release states were characterized comprehensively. A distinct movement pattern of NaCl crystals from the push layer to the drug layer was observed, beneath the semi-permeable coating in the desiccated tablet sample. The 3D structures at different dissolution time revealed that the pushing upsurge in the bilayer osmotic pump tablet was directed via peripheral “roadways”. Typically, different regions of the osmotic front, infiltration region, and dormant region were classified in the push layer during the dissolution of drug from tablet samples. According to the observed 3D microstructures, a “subterranean river model” for the drug release mechanism has been defined to explain the drug release mechanism.

It is challenging to apply deep learning in professional fields that lack big data support, especially in industrial nondestructive testings (NDT). To solve this problem, one feasible solution is to introduce the concept of NDT physics into a deep neural network to compensate for the network's poor predictive abilities when trained on small datasets. Therefore, we propose a physics-informed deep neural network, named GuwNet, using a unidirectional oblique-focusing (UOF) high-frequency, high-order shear horizontal guided wave electromagnetic acoustic transducer (EMAT) to quantify microcrack defects more accurately. We study the quantification principle of microcrack defects suitable for UOF-EMAT, and propose a network using physical knowledge regarding this theory including the network structure and loss functions design. Compared with traditional nonphysics-informed methods, the length, depth, and direction of the quantification errors are reduced to 0.127 mm, 0.279% dt, and 1.843', respectively, and the average quantification error is reduced by more than 80%

According to numerous laboratory experiments and field applications, polymer flooding can effectively modify the liquid absorption profile and increase the sweep efficiency, thereby enhancing the oil recovery. However, long-term injection of polymers decreases the effective permeability of the reservoir and plugs the formation pores, resulting in irreversible reservoir damage. In the development process, polymer types and concentrations must be selected according to the reservoir to avoid problems such as plugging of the formation pores. This study was aimed at clarifying the degree of plugging and the injection limit of the reservoir when a salt-resistant polymer (SRP) is used in production processes of the Daqing Oilfield. To this end, oil displacement experiments, dynamic and static adsorption experiments, and SEM observations were performed using representative reservoir fluid and core samples. The static adsorption of "medium-molecular" SRP reached equilibrium after 36 h, and the saturated adsorption capacity was 3.56 mg/g, which was approximately 2-5 times the dynamic adsorption capacity. For medium-molecular SRP, with a molecular mass of 7 million, the lower limit of the core permeability was 20-40 mD. When the permeability was less than 100 mD, the SRP concentration injected into the core could not exceed 900 mg/L. The oil displacement capacity of SRP decreased owing to the macromolecular hydration radius and the strong aggregation effect of SRP. Polymer adsorption and the retention of sand-carrying critically decreased water permeability. This study provides insights into SRP flooding under different geological conditions in the Daqing Oilfield and can help clarify the molecular mass and concentration of polymers with changes in the reservoir conditions.

We propose a physics-informed doubly fed cross-residual network (DfedResNet) suitable for MFL defect detection based on deep learning. Physics-based MFL defect quantification theory is studied and integrated into loss functions during the neural network training. DfedResNet quantifies defects in MFL data and automatically extracts deep features of defects. The experimental results show that it effectively achieves high-precision quantification of defect length, width, and depth simultaneously, especially defect depth. Moreover, it considers data from all three dimensions during network training, and use the originally measured magnetic signal data in place of recognized images to avoid defect information loss and further improve the quantification accuracy. The deep DfedResNet model proposed in this paper reduces defect length and width quantification errors to within 0.3 mm and defect depth quantification errors to within 0.4% t. In addition, compared with other network structures and traditional algorithms, DfedResNet improves defect quantification accuracy by 1-2 orders.

Two-dimensional (2D) metal organic frameworks (MOFs) are emerging as low-cost oxygen evolution reaction (OER) electrocatalysts, however, suffering aggregation and poor operation stability. Herein, ultrafine Fe3O4 nanoparticles (diameter: 6 ± 2 nm) are homogeneously immobilized on 2D Ni based MOFs (Ni-BDC, thickness: 5 ± 1 nm) to improve the OER stability. Electronic structure modulation for enhanced catalytic activity is studied via adjusting the amount of Fe3O4 nanoparticles on Ni-BDC. The optimal Fe3O4/Ni-BDC achieves the best OER performance with an overpotential of 295 mV at 10 mA cm-2, a Tafel slope of 47.8 mV dec-1 and a considerable catalytic durability of more than 40 h (less than 5 h for Ni-BDC alone). DFT calculations confirm that the active sites for Fe3O4/Ni-BDC are mainly contributed by Fe species with a higher oxidation state, and the potential-determining step (PDS) is the formation of the adsorbed O* species, which are facilitated in the composite.

High-entropy oxides (HEOs) with a multi-component single-phase structure are considered as promising electrocatalysts for the oxygen evolution reaction due to their good catalytic activity and tailorable electrochemical properties.

A highly active electrochemical amphiphilic POM–CNT nanohybrid using non-covalent interactions for highly efficient detection of H2O2 is reported. The synergy between POMs and CNTs results in 10 times higher current response than pristine POM.

Changes in structure of oral solid dosage forms (OSDF) elementally determine the drug release and its therapeutic effects. In this research, synchrotron radiation X-ray micro-computed tomography was utilized to visualize the 3D structure of enteric coated pellets recovered from the gastrointestinal tract of rats. The structures of pellets in solid state and in vitro compendium media were measured. Pellets in vivo underwent morphological and structural changes which differed significantly from those in vitro compendium media. Thus, optimizations of the dissolution media were performed to mimic the appropriate in vivo conditions by introducing pepsin and glass microspheres in media. The sphericity, pellet volume, pore volume and porosity of the in vivo esomeprazole magnesium pellets in stomach for 2 h were recorded 0.47, 1.55 × 108 μm3, 0.44 × 108 μm3 and 27.6%, respectively. After adding pepsin and glass microspheres, the above parameters in vitro reached to 0.44, 1.64 × 108 μm3, 0.38 × 108 μm3 and 23.0%, respectively. Omeprazole magnesium pellets behaved similarly. The structural features of pellets between in vitro media and in vivo condition were bridged successfully in terms of 3D structures to ensure better design, characterization and quality control of advanced OSDF., Graphical abstract The differences in dynamic structure of enteric pellets during dissolution in vitro and in vivo were first observed. By introducing pepsin and glass microspheres into pharmacopoeia medium, the structures of pellets were bridged.Image 1

V2O5/MWCNT hybrid system has been developed and investigated as cathode in LIBs. The developed electrode shows superior performance as compare to pristine V2O5 and V2O5/rGO hybrid structure due to the synergy between V2O5 and MWCNT.

High-entropy materials (HEMs) have attracted extensive interests in exploring multicomponent systems for highly efficient and durable catalysts. Tuning composition and configuration of HEMs provides untapped opportunities for accessing better catalytic performance. Herein, we report three amorphous high-entropy transition metal oxides catalysts with uniform composition through a simple and controllable liquid phase non-equilibrium reduction method. The self-made catalyst FeCoNiMnBOx exhibits excellent oxygen evolution performance, including a low overpotential (266 mV at 10 mA cm−2), small Tafel slope (64.5 mV dec-1) and extremely high stability (only 3.71% increase of potential after 100 h test and no current decay after cyclic voltammetry of 31,000 cycles). The outstanding performance can be attributed to the in-situ electrochemical activation induced surface reconstruction to form a stable oxyhydroxide surface layer, the cocktail effect (multi-metal synergy) brought by high entropy, and the advantages of amorphous structure itself. The outstanding catalytic properties of the new high-entropy amorphous metal oxide, as well as its advantages of low cost and simple preparation, suggest its great potential in water splitting.

An amorphous FeCoNiBOx catalyst is fabricated and exhibits remarkable oxygen evolution reaction electrocatalytic properties.

Objectives Major infectious disease has become a serious threat to people’s health worldwide. As the world’s largest healthcare workforce and the core forces fighting against the epidemic, nurses are on the frontline of this battle. A number of ethical issues have given rise to numerous concerns that have largely affected nurses in different ways as they respond to the epidemic. In addition, excessive expectations from people can exert undue pressure, which can easily lead to burnout in nurses. Methods In this consensus, the expert panel method was used to develop and reach a consensus. The members involved in the formation of the consensus included an expert discussion panel and a consensus writing expert group, a methodologist, and four secretaries. After 16 rounds of online expert consultation and two rounds of expert panel meetings, the writing team analyzed and reviewed the 78 amendments suggested by the experts to develop a consensus on nursing ethics for prevention and control of major infectious disease outbreaks based on the ethical vision of life care. Results This expert consensus focuses on five essential domains: the responsibilities and rights of nurses, the nurse-patient relationship, the doctor-nurse relationship, and the relationship between society and nurses throughout the epidemic. Conclusions We hope this consensus can help nurses better understand and respond to the ethical issues and challenges in public health emergencies, and raise reasonable public expectations of the roles and responsibilities of nurses in these situations.

Producing green hydrogen in a cost-competitive manner via water electrolysis will make the long-held dream of meeting energy needs with hydrogen instead of fossil fuel a reality. Although platinum-based catalysts show good performance towards hydrogen evolution reaction (HER), the high cost and scarce abundance challenge their economic viability for large-scale implementation. Here, we engineer high fractions of stacking fault defects in MoNi nanosheets to form a high-performance electrocatalyst (d-MoNi) through a combined chemical and thermal reduction strategy. Using d-MoNi as an electrode for HER afforded ultralow overpotential of 63 and 120 mV at current densities of -500 and -1000 mA cm-2 in 1 M KOH, respectively. Besides, the stacking fault defect-rich d-MoNi exhibits 4 orders of magnitude higher turnover frequency than benchmark 20% Pt/C, together with excellent durability (>100 h) at high current density of 1000 mA cm-2, making it one of the best-performing non-platinum catalysts for HER. The experimental and theoretical results reveal that the abundant stacking faults in d-MoNi induce a compressive strain, decreasing the proton adsorption energy and promoting the concomitant combination of adsorbed hydrogen into molecular hydrogen and the desorption of the molecular hydrogen, therefore enhancing the HER performance. This work provides a new synthetic route to engineer defective metal and metal alloy electrocatalysts for emerging applications in electrochemical energy conversion and storage.

Fine-scale genetic background characterization of ethnolinguistically diverse populations can gain new insights into the population admixture processes, which is essential for evolutionary and medical genomic research. However, the genetic diversity and population history of southern Chinese indigenous people and their interaction with historic incomers keep unknown. Here, we genotyped 700K genome-wide SNPs from four Guizhou populations belonging to Tai-Kadai (TK), Hmong-Mien (HM), and Tibeto-Burman language families and merged them with publicly available data from 218 modern and ancient East Asian groups to perform one comprehensive demographical and evolutionary history reconstruction. We found that Guizhou populations harbored a strong genetic substructure correlated with language categories. We comprehensively characterized the genetic signatures of geographically diverse HM people and identified the unique HM genetic lineage in Southwest China and Southeast Asia as their shared ancestry component in the demographical history reconstruction. Our identified admixture signatures and times further supported the hypothesis that the HM people originated from Yungui Plateau and then southward migration during the historical period. Admixture models focused on Sino-Tibetan and TK people supported their intense interaction and harbored the most extensive gene flows consistent with their shared linguistic and cultural characteristics and lifestyles. Estimates of identity-by-descent sharing and effective population size showed the extensive population stratification and gene flow events in different time scales. This work focuses on the genetic features of high-density SNP markers, presents one complete landscape of the evolutionary history of ethnolinguistically different southern Chinese populations, and fills the gap of missing diversity in South China.

Managing outbreaks of alien plant pests is key to preserving biodiversity and safeguarding crop production. Zoning strategies are applied by plant health authorities to tailor measures to the risk of spread in relation to distance from the outbreak epicentre and the biology of the pest. Here we synthesize information on outbreak management to evaluate the diversity and consistency of such approaches. We collected information on the zoning strategies of 121 outbreaks of 25 plant pests in the European Union (EU). According to the organism’s presence and the measures applied, five zones were distinguished: an infested zone (83% of cases), a buffer zone (76%), a clear-cutting zone (28%), an eradication zone (1%) and a containment zone (1%). Infested zones and buffer zones were adjacent non-overlapping zones, while the clear-cutting zone, eradication zone or containment zone was within either the infested zone or buffer zone. A combination of infested and buffer zones was used in 51% of recorded cases. Measures differed within different zones. Destruction of infested plants in the infested zone was done in 78% of the cases, while surveillance was always applied in the buffer zone. Regulation of an organism at EU level led to a convergence of zoning strategies applied by different member states. Regulations often prescribed the greatest widths used before regulations were issued. Further analyses are needed to explore the efficacy of different strategies including the costs of each strategy. Such analyses should combine insight from practice with bio-economic modelling.

TMS used as high-capacity anodes in Li-ion batteries are thoroughly reviewed.

Metal antimony (Sb) is a promising anode material of potassium-ion batteries (PIBs) for its high theoretical capacity but limited by its inferior cycle stability due to the serious volume expansion during cycling. Herein, we design and construct a kind of low-crystalline Sb nanoparticles coated with amorphous Sb2O3 and dispersed into three-dimensional porous carbon via a strategy involving NaCl template-assisted in-situ pyrolysis and subsequent low-temperature heat-treated in air. Significantly, the crystallinity and ratio of Sb/Sb2O3 have been precisely tuned and controlled, and the optimized sample of HTSb@Sb2O3@C-4 displays a high reversible specific capacity of 543.9 mAh g−1 at 0.1 A g−1, superior rate capability and excellent cycle stability (~273 mAh g−1 at 2 A g−1 after 2000 cycles) as an anode of PIBs. The outstanding potassium-ion storage performance can be ascribed to the appropriate crystallinity and the multiple-buffer-matrix structure comprising an interconnected porous conductive carbon to relieve the volume changes and suppress the aggregation of Sb, a Sb nanoparticle core to shorten the ion transport pathways and decrease the mechanical stress, and a low-crystalline Sb2O3 as the shell to consolidate the interface between Sb and carbon as well as facilitate the rapid electron transport. The dynamic analysis shows that the composite is mainly controlled by pseudocapacitance mechanism. This work provides a novel thought to design high-performance composite electrode in energy storage devices.

High entropy oxides (HEOs), as a new type of single-phase multielement solid solution materials, have shown many attractive features and promising application prospect in the energy storage field. Herein, six-element HEOs (CoNiZnFeMnLi)3O4 and (CoNiZnCrMnLi)3O4 with spinel structure are successfully prepared by conventional solid-phase method and present outstanding lithium storage performances due to the synergy effect of various electrochemically active elements and the entropy stabilization. By contrast, (CoNiZnFeMnLi)3O4 delivers higher initial discharge specific capacity of 1104.3 mAh·g−1, better cycle stability (84% capacity retention after 100 cycles at 100 mA·g−1) and rate performance (293 mAh·g−1 at 2000 mA·g−1) in the half-cell. Moreover, the full-cell assembled with (CoNiZnFeMnLi)3O4 and LiCoO2 provides a reversible specific capacity of 260.2 mAh·g−1 after 100 cycles at 500 mA·g−1. Ex situ X-ray diffraction reveals the electrochemical reaction mechanism of HEOs (CoNiZnFeMnLi)3O4, and the amorphous phase and the large amount of oxygen vacancies were obtained after the initial discharge process, which are responsible for the excellent cycle and rate performance. This research puts forward fresh insights for the development of advanced energy storage materials for high-performance batteries.

BACKGROUND Severe acute pancreatitis (SAP) is a deadly inflammatory disease with complex pathogenesis and lack of effective therapeutic options. N6-methyladenosine (m6A) modification of circRNAs plays important roles in physiological and pathological processes. However, the roles of m6A circRNA in the pathological process of SAP remains unknown. AIM To identify transcriptome-wide map of m6A circRNAs and to determine their biological significance and potential mechanisms in SAP. METHODS The SAP in C57BL/6 mice was induced using 4% sodium taurocholate salt. The transcriptome-wide map of m6A circRNAs was identified by m6A-modified RNA immunoprecipitation sequencing. The biological significance of circRNAs with differentially expressed m6A peaks was evaluated through gene ontology and Kyoto Encyclopedia of Genes and Genomes analysis. The underlying mechanism of m6A circRNAs in SAP was analyzed by constructing of m6A circRNA-microRNA networks. The expression of demethylases was determined by quantitative polymerase chain reaction and western blot to deduce the possible mechanism of reversible m6A process in SAP. RESULTS Fifty-seven circRNAs with differentially expressed m6A peaks were identified by m6A-modified RNA immunoprecipitation sequencing, of which 32 were upregulated and 25 downregulated. Functional analysis of these m6A circRNAs in SAP found some important pathways involved in the pathogenesis of SAP, such as regulation of autophagy and protein digestion. In m6A circRNA–miRNA networks, several important miRNAs participated in the occurrence and progression of SAP were found to bind to these m6A circRNAs, such as miR-24-3p, miR-26a, miR-92b, miR-216b, miR-324-5p and miR-762. Notably, the total m6A level of circRNAs was reduced, while the demethylase alkylation repair homolog 5 was upregulated in SAP. CONCLUSION m6A modification of circRNAs may be involved in the pathogenesis of SAP. Our findings may provide novel insights to explore the possible pathogenetic mechanism of SAP and seek new potential therapeutic targets for SAP.

Cylindrical permalloy nanowire arrays are prepared by employing anodic aluminum oxide (AAO) template-assisted electrochemical deposition method. To prepare high-quality permalloy nanowire, the effects of different deposition parameters (pulse current density, concentration and pH value of the electrolyte, and deposition temperature) on the chemical composition, uniformity, and magnetic properties of the nanowires are systematically investigated. A high-quality permalloy nanowire with good magnetic properties of $${M}_{\text{S}}\approx 5.7\times {10}^{5}\, \mathrm{A}/\mathrm{m}$$ and $$\alpha \approx 0.04$$ has been successfully prepared by optimizing the preparation scheme, which can provide technical support for mass production of cylindrical permalloy nanowire for spintronic devices.

High-entropy oxides (HEOs) with numerous functional features such as high structure stability and superionic conductivity are considered as promising candidates of electrode materials for lithium-ion batteries (LIBs). In this study, a series of single-phase spinel-structured high-entropy oxides (FeCoNiCrMnXLi)3O4 (X = Cu, Mg, Zn) consisted of seven metal elements at equal molar ratio were synthesized by solid phase method. In-situ high-temperature XRD technique was used to investigate the structure evolution of (FeCoNiCrMnZnLi)3O4 and a single-phase HEO was acquired at 900 °C. As the anode of LIBs, all the HEOs (FeCoNiCrMnXLi)3O4 display excellent cyclic stability and rate capability owe to the expedite three-dimensional Li+ transport pathways of spinel structure, the entropy-dominated phase stabilization effect together with the abundant oxygen vacancies introduced by the incorporation of Li+. In comparison, the (FeCoNiCrMnZnLi)3O4 anode containing electrochemical active Zn with tetrahedral coordination structure shows better electrochemical lithium storage performances among the three samples. The ex-situ XRD of (FeCoNiCrMnZnLi)3O4 during the discharge/charge procedure shows an amorphous state structure after the first lithiation process and it retained for the de-lithiation process. This work provides a new strategy to design high-entropy energy-storage material and pave the way for understanding the storage mechanism of HEOs.

Fault zones accommodate relative motion between tectonic blocks and control earthquake nucleation. Nanocrystalline fault rocks are ubiquitous in “principal slip zones” indicating that these materials are determining fault stability. However, the rheology of nanocrystalline fault rocks remains poorly constrained. Here, we show that such fault rocks are an order of magnitude weaker than their microcrystalline counterparts when deformed at identical experimental conditions. Weakening of the fault rocks is hence intrinsic, it occurs once nanocrystalline layers form. However, it is difficult to produce “rate weakening” behavior due to the low measured stress exponent, n, of 1.3 ± 0.4 and the low activation energy, Q, of 16,000 ± 14,000 J/mol implying that the material will be strongly “rate strengthening” with a weak temperature sensitivity. Failure of the fault zone nevertheless occurs once these weak layers coalesce in a kinematically favored network. This type of instability is distinct from the frictional instability used to describe crustal earthquakes., Extremely fine-grained fault rocks are intrinsically weak and behave as fluids even at low temperatures and fast deformation rates. Local production of fine-grained material during fault movement can lead to an earthquake instability.

Graphite is a widely used anode material in commercial lithium-ion batteries (LIBs), but its low theoretical specific capacity and extremely low redox potential limit its application in high-performance lithium-ion batteries. However, developing lithium-ion battery anode with high specific capacity and suitable working potential is still challenging. At present, conductive polymers with excellent properties and graphite-like structures are widely used in the field of electrochemistry, but their Li

In recent years, counterfeit luxury products have become a major concern for consumers worldwide. The reason for the proliferation of counterfeit products is that the manufacturing and distribution process is not transparent to consumers and this information can be easily falsified or altered by others. To solve this problem, this paper proposes the development of a management system using blockchain and smart contract technology to solve the problems of data forgery and data tampering, while tracking the information related to luxury products and ensuring the accuracy and authenticity of the relevant data, to achieve the purpose of luxury product anti-counterfeiting. When using Hyperledger Fabric to deploy the blockchain and execute smart contracts, all information related to the production and logistics process of luxury goods will be uploaded to the blockchain. No human intervention is required to create a complete, traceable, tamper-proof, and trusted repository. Compared to previous work, this paper combines blockchain technology with specific processes in the supply chain, employing a variety of security methods to secure the communication process. Moreover, our proposed solution is more flexible in transmission, with more secure protocols also making data harder to tamper with and falsify, thereby solving the problem of forgery and tracking of luxury products.

UNSTRUCTURED AI is undoubtedly revolutionizing medical research and patient care with various applications in several fields. Chronic disease nursing care, an important part of clinical management, has benefited much from AI in many ways. It is important to understand the principles that make it workable before using artificial intelligence, not to blindly replace all work with AI. Nurses are the main force of symptom group research, expanding from the diabetes to other chronic disease, they are mainly responsible for patients daily symptom and vital signs record. However, many AI research currently exclude nurses from the development phase and only include them in the use and feedback population. The overall design of the symptom analysis and long-term management approach cannot be done without the guidance and supervision of nurses, but currently nurses are not sufficiently involved, which may be related to the fact that nursing staff have less understanding of AI compared to other researchers and are not yet clear about the value of their role in AI. Therefore, it is very necessary to explore the role points of nurses in symptom analysis and long-term management, and to analyze the breakthrough points of nurses' work in AI in the future by drawing on the latest research in these two areas.