聚合物三腔微管挤出口模结构对胀大变形的影响

聚合物熔体的模内流动状态与模外胀大变形直接影响微挤出制品的成型质量。文中基于Carreau模型,采用数值模拟方法,研究了聚合物三腔微管挤出过程中口模壁厚差与空心度结构特征对胀大变形行为的影响。结果表明,影响挤出胀大变形程度的关键因素是口模出口附近的轴向速度分布;内外壁厚差会导致较大壁厚位置处对应的型坯厚度增大,而较小壁厚位置处的型坯厚度减小,壁厚差变化对薄壁区域壁厚变形影响较大,达到91.4%;空心度减小能提升口模出口附近轴向速度分布均匀性,减小了70.1%的变形程度;基于胀大变形规律逆向补偿设计了口模形状与尺寸,明显改善了制品成型质量。研究结果对聚合物多腔微管的口模结构优化设计具有理论意义与工程应用价值。

基于IHHT‑RF的配电网单相接地故障选线方法

小电流系统发生单相接地故障时故障特征易受高接地过渡电阻、小初相角等弱故障条件影响而导致选线准确率低。为此,提出一种基于改进希尔伯特黄变换—随机森林(improved Hilbert⁃Huang transform⁃random forest,IHHT⁃RF)的配电网单相接地故障选线方法。首先,提取每条线路在故障发生时的电流暂态信号,通过IHHT提取纯净的暂态电气量,构造标准差、能量熵和幅值畸变度3类特征向量;然后,将特征向量输入RF分类器建立故障选线模型,把故障选线问题转化为二分类问题;最后,将测量数据输入RF分类器中得出分类结果,实现故障线路的自动识别。仿真结果表明,该选线方法综合利用暂态信号的幅值、频率和能量等特征信息,不受弱故障条件、馈线结构等因素的影响,能有效提高故障选线的准确率,具有较强的适应性和可靠性。

MXene Hollow Spheres Supported by a C–Co Exoskeleton Grow MWCNTs for Efficient Microwave Absorption

High-performance microwave absorption(MA) materials must be studied immediately since electromagnetic pollution has become a problem that cannot be disregarded. A straightforward composite material, comprising hollow MXene spheres loaded with C–Co frameworks, was prepared to develop multiwalled carbon nanotubes(MWCNTs). A high impedance and suitable morphology were guaranteed by the C–Co exoskeleton, the attenuation ability was provided by the MWCNTs endoskeleton, and the material performance was greatly enhanced by the layered core–shell structure. When the thickness was only 2.04 mm, the effective absorption bandwidth was 5.67 GHz, and the minimum reflection loss(RLmin) was-70.70 d B. At a thickness of 1.861 mm, the sample calcined at 700 ℃ had a RLmin of-63.25 d B. All samples performed well with a reduced filler ratio of 15 wt%. This paper provides a method for making lightweight core–shell composite MA materials with magnetoelectric synergy.

The MORC2 p.S87L mutation reduces proliferation of pluripotent stem cells derived from a patient with the spinal muscular atrophy-like phenotype by inhibiting proliferation-related signaling pathways

Mutations in the microrchidia CW-type zinc finger protein 2(MORC2)gene are the causative agent of Charcot-Marie-Tooth disease type 2Z(CMT2Z),and the hotspot mutation p.S87L is associated with a more seve re spinal muscular atrophy-like clinical phenotype.The aims of this study were to determine the mechanism of the severe phenotype caused by the MORC2 p.S87L mutation and to explore potential treatment strategies.Epithelial cells were isolated from urine samples from a spinal muscular atrophy(SMA)-like patient[MORC2 p.S87L),a CMT2Z patient[MORC2 p.Q400R),and a healthy control and induced to generate pluripotent stem cells,which were then differentiated into motor neuron precursor cells.Next-generation RNA sequencing followed by KEGG pathway enrichment analysis revealed that differentially expressed genes involved in the PI3K/Akt and MAP K/ERK signaling pathways were enriched in the p.S87L SMA-like patient group and were significantly downregulated in induced pluripotent stem cells.Reduced proliferation was observed in the induced pluripotent stem cells and motor neuron precursor cells derived from the p.S87L SMA-like patient group compared with the CMT2Z patient group and the healthy control.G0/G1 phase cell cycle arrest was observed in induced pluripotent stem cells derived from the p.S87L SMA-like patient.MORC2 p.S87Lspecific antisense oligonucleotides(p.S87L-ASO-targeting)showed significant efficacy in improving cell prolife ration and activating the PI3K/Akt and MAP K/ERK pathways in induced pluripotent stem cells.Howeve r,p.S87L-ASO-ta rgeting did not rescue prolife ration of motor neuron precursor cells.These findings suggest that downregulation of the PI3K/Akt and MAP K/ERK signaling pathways leading to reduced cell proliferation and G0/G1 phase cell cycle arrest in induced pluripotent stem cells might be the underlying mechanism of the severe p.S87L SMA-like phenotype.p.S87L-ASO-targeting treatment can alleviate disordered cell proliferation in the early stage of pluripotent stem cell induction.

Artificial Intelligence Meets Flexible Sensors:Emerging Smart Flexible Sensing Systems Driven by Machine Learning and Artificial Synapses

The recent wave of the artificial intelligence(AI)revolution has aroused unprecedented interest in the intelligentialize of human society.As an essential component that bridges the physical world and digital signals,flexible sensors are evolving from a single sensing element to a smarter system,which is capable of highly efficient acquisition,analysis,and even perception of vast,multifaceted data.While challenging from a manual perspective,the development of intelligent flexible sensing has been remarkably facilitated owing to the rapid advances of brain-inspired AI innovations from both the algorithm(machine learning)and the framework(artificial synapses)level.This review presents the recent progress of the emerging AI-driven,intelligent flexible sensing systems.The basic concept of machine learning and artificial synapses are introduced.The new enabling features induced by the fusion of AI and flexible sensing are comprehensively reviewed,which significantly advances the applications such as flexible sensory systems,soft/humanoid robotics,and human activity monitoring.As two of the most profound innovations in the twenty-first century,the deep incorporation of flexible sensing and AI technology holds tremendous potential for creating a smarter world for human beings.

麝香草酚三甲氧基肉桂酸酯抑制黑色素生成、转移及AGEs合成的功效研究

基于皮肤细胞模型研究了麝香草酚三甲氧基肉桂酸酯的美白功效,采用CCK-8法和观察细胞状态检测麝香草酚三甲氧基肉桂酸酯对B16-F10细胞活率的影响;分别采用NaOH裂解法和多巴氧化法分析B16-F10细胞中黑色素含量和酪氨酸酶活性变化;采用细胞划痕法和Transwell小室法测定B16-F10细胞迁移能力变化;利用荧光分析法检测体外糖化实验中荧光性AGEs含量变化。结果表明麝香草酚三甲氧基肉桂酸酯质量浓度在10μg/mL及以下时对细胞活率没有明显影响,并且在10μg/mL时对黑色素合成、酪氨酸酶活性以及细胞迁移能力抑制率最高;200μg/mL时在体外对荧光性AGEs生成的抑制率达到97.75%。研究结果表明麝香草酚三甲氧基肉桂酸酯可以明显抑制黑色素的生成并抑制酪氨酸酶的活性,具有较好的美白功效;由于其同时具有较好的抗糖化能力,可作为潜在的抗衰老原料。

Effect of antioxidants on the efficiency of jet milling and the powder characteristics of Sm2Co17 permanent magnets

This study investigated the effect of antioxidants on the grinding efficiency,magnetic powder characteristics,microstructure,and magnetic properties of 2:17 type SmCo permanent magnet materials.The results show that adding antioxidants helps improve the dispersion among magnetic powders,leading to a 33.3%decrease in jet milling time and a 15.8%increase in magnet powder production yield.Additionally,adding antioxidants enhances the oxidation resistance of the magnetic powders.After being stored in a constant temperature air environment at 25C for 48 h,the O content in the powder decreased by 33%compared to samples without antioxidants.While in the magnet body,the O content decreased from 0.21 wt.%to 0.14 wt.%,which helps increase the effective Sm content and domain wall pinning uniformity in the magnet.Excellent magnetic properties were obtained in the magnet with added antioxidants:B_(r)=11.6 kGs,SF=79.6%,H_(cj)=16.8 kOe,and(BH)_(max)=32.5 MGOe.

Application of geophysical methods in fine detection of urban concealed karst:A case study of Wuhan City,China

The construction of modern livable cities faces challenges in karst areas,including ground collapse and engineering problems.Wuhan,with a population of 13.74×10^(6) and approximately 1161 km^(2)of soluble rocks in the urban area of 8569.15 km^(2),predominantly consists of concealed karst areas where occasional ground collapse events occur,posing significant threats to underground engineering projects.To address these challenges,a comprehensive geological survey was conducted in Wuhan,focusing on major karstrelated issues.Geophysical methods offer advantages over drilling in detecting concealed karst areas due to their efficiency,non-destructiveness,and flexibility.This paper reviewed the karst geological characteristics in Wuhan and the geophysical exploration methods for karst,selected eight effective geophysical methods for field experimentation,evaluated their suitability,and proposed method combinations for different karst scenarios.The results show that different geophysical methods have varying applicability for karst detection in Wuhan,and combining multiple methods enhances detection effectiveness.The specific recommendations for method combinations provided in this study serve as a valuable reference for karst detection in Wuhan.

Application of machine learning in perovskite materials and devices:A review

Metal-halide hybrid perovskite materials are excellent candidates for solar cells and photoelectric devices.In recent years,machine learning(ML)techniques have developed rapidly in many fields and provided ideas for material discovery and design.ML can be applied to discover new materials quickly and effectively,with significant savings in resources and time compared with traditional experiments and density functional theory(DFT)calculations.In this review,we present the application of ML in per-ovskites and briefly review the recent works in the field of ML-assisted perovskite design.Firstly,the advantages of perovskites in solar cells and the merits of ML applied to perovskites are discussed.Secondly,the workflow of ML in perovskite design and some basic ML algorithms are introduced.Thirdly,the applications of ML in predicting various properties of perovskite materials and devices are reviewed.Finally,we propose some prospects for the future development of this field.The rapid devel-opment of ML technology will largely promote the process of materials science,and ML will become an increasingly popular method for predicting the target properties of materials and devices.

In situ observation of the phase transformation kinetics of bismuth during shock release

A time-resolved x-ray diffraction technique is employed to monitor the structural transformation of laser-shocked bismuth.Results reveal a retarded transformation from the shock-induced Bi-Ⅴphase to a metastable Bi-Ⅳphase during the shock release,instead of the thermodynamically stable Bi-Ⅲphase.The emergence of the metastable Bi-Ⅳphase is understood by the competitive interplay between two transformation pathways towards the Bi-Ⅳand Bi-Ⅲ,respectively.The former is more rapid than the latter because the Bi-Ⅴto B-Ⅳtransformation is driven by interaction between the closest atoms while the Bi-Ⅴto B-Ⅲtransformation requires interaction between the second-closest atoms.The nucleation time for the Bi-Ⅴto Bi-Ⅳtransformation is determined to be 5.1±0.9 ns according to a classical nucleation model.This observation demonstrates the importance of the formation of the transient metastable phases,which can change the phase transformation pathway in a dynamic process.

Cu,N codoped carbon nanosheets encapsulating ultrasmall Cu nanoparticles for enhancing selective 1,2-propanediol oxidation

In the selective oxidation of biomass-based 1,2-propanediol(PDO)with oxygen as the terminal oxidant,it is challenging to improve the lactic acid(LA)selectivity for nonnoble metal nanoparticles(NPs)due to their limited oxygen reduction rate and easy C-C cleavage.Given the high economic feasibility of nonnoble metals,i.e.,Cu,in this work,copper and nitrogen codoped porous carbon nanosheets encapsulating ultrafine Cu nanoparticles(Cu@Cu-N-C)were developed to realize highly selective of PDO oxidation to LA.The carbon-encapsulated ultrasmall Cu^(0)NPs in Cu@Cu-N-C have high PDO dehydrogenation activity while N-coordinated Cu(Cu-N)sites are responsible for the high oxygen reduction efficacy.Therefore,the performance of catalytic PDO conversion to LA is optimized by a proposed pathway of PDO→hydroxylacetone→lactaldehyde→LA.Specifically,the enhanced LA selectivity is 88.5%,and the PDO conversion is up to 75.1%in an O_(2)-pressurized reaction system(1.0 MPa O_(2)),superior to other Cu-based catalysts,while in a milder nonpressurized system(O_(2)flow rate of 100 mL min-1),a remarkable LA selectivity(94.2%)is obtained with 39.8%PDO conversion,2.2 times higher than that of supported Au nanoparticles(1%Au/C).Moreover,carbon encapsulation offers Cu@Cu-N-C with strong leaching resistance for better recycling.

Genome-wide association study identifies 12 new genetic loci associated with growth traits in pigs

Growth traits are among the most important economic traits in pigs and are regulated by polygenes with complex regulatory mechanisms.As the major indicators of growth performance,the backfat thickness(BFT),loin eye area(LEA),and days to 100 kg(D100)traits are commonly used to the genetics improvement in pigs.However,the available genetic markers for these traits are limited.To uncover novel loci and candidate genes associated with growth performance,we collected the phenotypic information of BFT,LEA,and D100 in 1,186 pigs and genotyped all these individuals using the Neogen GGP porcine 80K BeadChip.We performed a genome-wide association study(GWAS)using 4 statistical models,including mixed linear models(MLM),fixed and random model circulating probability unification(FarmCPU),settlement of MLM under progressively exclusive relationships(SUPER),Bayesian-information and linkage-disequilibrium Iteratively nested keyway(Blink),and identified 5,3,and 6 high-confidence single nucleotide polymorphisms(SNPs)associated with BFT,LEA,and D100,respectively.Variant annotation and quantitative trait locus(QTL)mapping analysis suggested that6 genes(SKAP2,SATB1,PDE7B,PPP1R16B,WNT3,and WNT9B)were potentially associated with growth performance in pigs.Transcriptome analysis suggested that the expression of Src Kinase Associated Phosphoprotein 2(SKAP2)was higher in prenatal muscles than in postnatal muscles,and the expression of Phosphodiesterase 7B(PDE7B)continuously increased during the prenatal stages and gradually decreased after birth,implying their potential roles in prenatal skeletal muscle development.Overall,this study provides new candidate loci and genes for the genetic improvement of pigs.

Modelling analysis embodies drastic transition among global potential natural vegetations in face of changing climate

Potential natural vegetation(PNV)is a valuable reference for ecosystem renovation and has garnered increasing attention worldwide.However,there is limited knowledge on the spatio-temporal distributions,transitional processes,and underlying mechanisms of global natural vegetation,particularly in the case of ongoing climate warming.In this study,we visualize the spatio-temporal pattern and inter-transition procedure of global PNV,analyse the shifting distances and directions of global PNV under the influence of climatic disturbance,and explore the mechanisms of global PNV in response to temperature and precipitation fluctuations.To achieve this,we utilize meteorological data,mainly temperature and precipitation,from six phases:the Last Inter-Glacial(LIG),the Last Glacial Maximum(LGM),the Mid Holocene(MH),the Present Day(PD),2030(20212040)and 2090(2081–2100),and employ a widely-accepted comprehensive and sequential classification sy–stem(CSCS)for global PNV classification.We find that the spatial patterns of five PNV groups(forest,shrubland,savanna,grassland and tundra)generally align with their respective ecotopes,although their distributions have shifted due to fluctuating temperature and precipitation.Notably,we observe an unexpected transition between tundra and savanna despite their geographical distance.The shifts in distance and direction of five PNV groups are mainly driven by temperature and precipitation,although there is heterogeneity among these shifts for each group.Indeed,the heterogeneity observed among different global PNV groups suggests that they may possess varying capacities to adjust to and withstand the impacts of changing climate.The spatio-temporal distributions,mutual transitions and shift tendencies of global PNV and its underlying mechanism in face of changing climate,as revealed in this study,can significantly contribute to the development of strategies for mitigating warming and promoting re-vegetation in degraded regions worldwide.

Embedded high-quality ternary GaAs_(1−x)Sb_(x) quantum dots in GaAs nanowires by molecular-beam epitaxy

Semiconductor quantum dots are promising candidates for preparing high-performance single photon sources.A basic requirement for this application is realizing the controlled growth of high-quality semiconductor quantum dots.Here,we report the growth of embedded GaAs_(1−x)Sb_(x) quantum dots in GaAs nanowires by molecular-beam epitaxy.It is found that the size of the GaAs_(1−x)Sb_(x) quantum dot can be well-defined by the GaAs nanowire.Energy dispersive spectroscopy analyses show that the antimony content x can be up to 0.36 by tuning the growth temperature.All GaAs_(1−x)Sb_(x) quantum dots exhibit a pure zinc-blende phase.In addition,we have developed a new technology to grow GaAs passivation layers on the sidewalls of the GaAs_(1−x)Sb_(x) quantum dots.Different from the traditional growth process of the passivation layer,GaAs passivation layers can be grown simultaneously with the growth of the embedded GaAs_(1−x)Sb_(x) quantum dots.The spontaneous GaAs passivation layer shows a pure zinc-blende phase due to the strict epitaxial relationship between the quantum dot and the passivation layer.The successful fabrication of embedded high-quality GaAs_(1−x)Sb_(x) quantum dots lays the foundation for the realization of GaAs_(1−x)Sb_(x)-based single photon sources.

Enhanced magnetic anisotropy and high hole mobility in magnetic semiconductor Ga_(1-x-y)Fe_(x)Ni_(y)Sb

(Ga,Fe)Sb is a promising magnetic semiconductor(MS)for spintronic applications because its Curie temperature(T_(C))is above 300 K when the Fe concentration is higher than 20%.However,the anisotropy constant Ku of(Ga,Fe)Sb is below 7.6×10^(3)erg/cm^(3)when Fe concentration is lower than 30%,which is one order of magnitude lower than that of(Ga,Mn)As.To address this issue,we grew Ga_(1-x-y)Fe_(x)Ni_(y)Sb films with almost the same x(≈24%)and different y to characterize their magnetic and electrical transport properties.We found that the magnetic anisotropy of Ga_(0.76-y)Fe_(0.24)Ni_(y)Sb can be enhanced by increasing y,in which Ku is negligible at y=1.7%but increases to 3.8×10^(5)erg/cm^(3)at y=6.1%(T_(C)=354 K).In addition,the hole mobility(μ)of Ga_(1-x-y)Fe_(x)Ni_(y)Sb reaches 31.3 cm^(2)/(V∙s)at x=23.7%,y=1.7%(T_(C)=319 K),which is much higher than the mobility of Ga_(1-x)Fe_(x)Sb at x=25.2%(μ=6.2 cm^(2)/(V∙s)).Our results provide useful information for enhancing the magnetic anisotropy and hole mobility of(Ga,Fe)Sb by using Ni co-doping.

BaTiO_(3)/p-GaN/Au self-driven UV photodetector with bipolar photocurrent controlled by ferroelectric polarization

Ferroelectric materials are promising candidates for ultraviolet photodetectors due to their ferroelectric effect.In this work,a BaTiO_(3)/p-GaN/Au hybrid heterojunction-Schottky self-driven ultraviolet photodetector was fabricated with excellent bipolar photoresponse property.At 0 V bias,the direction of the photocurrent can be switched by flipping the depolarization field of BaTiO_(3),which allows the performance of photodetectors to be controlled by the ferroelectric effect.Meanwhile,a relatively large responsivity and a fast response speed can be also observed.In particular,when the depolarization field of BaTiO_(3) is in the same direction of the built-in electric field of the Au/p-GaN Schottky junction(up polarized state),the photodetector exhibits a high responsivity of 18 mA/W at 360 nm,and a fast response speed of<40 ms at 0 V.These findings pave a new way for the preparation of high-performance photodetectors with bipolar photocurrents.

First-principles study of structural and electronic properties of multiferroic oxide Mn_(3)TeO_(6) under high pressure

Mn_(3)TeO_(6)(MTO) has been experimentally found to adopt a P2_(1)/In structure under high pressure,which exhibits a significantly smaller band gap compared to the atmospheric R3 phase.In this study,we systematically investigate the magnetism,structural phase transition,and electronic properties of MTO under high pressure through first-principles calculations.Both R3 and P2_(1)/n phases of MTO are antiferromagnetic at zero temperature.The R3 phase transforms to the P2_(1)/n phase at 7.5 8 GPa,accompanied by a considerable volume collapse of about 6.47%.Employing the accurate method that combines DFT+U/and GW,the calculated band gap of R3 phase at zero pressure is very close to the experimental values,while that of the P2_(1)/n phase is significantly overestimated.The main reason for this difference is that the experimental study incorrectly used the Kubelka-Munk plot for the indirect band gap to obtain the band gap of the P2_(1)/n phase instead of the Kubelka-Munk plot for the direct band gap.Furthermore,our study reveals that the transition from the R3 phase to the P2_(1)/n phase is accompanied by a slight reduction in the band gap.

An Efficient and Provably Secure SM2 Key-Insulated Signature Scheme for Industrial Internet of Things

With the continuous expansion of the Industrial Internet of Things(IIoT),more andmore organisations are placing large amounts of data in the cloud to reduce overheads.However,the channel between cloud servers and smart equipment is not trustworthy,so the issue of data authenticity needs to be addressed.The SM2 digital signature algorithm can provide an authentication mechanism for data to solve such problems.Unfortunately,it still suffers from the problem of key exposure.In order to address this concern,this study first introduces a key-insulated scheme,SM2-KI-SIGN,based on the SM2 algorithm.This scheme boasts strong key insulation and secure keyupdates.Our scheme uses the elliptic curve algorithm,which is not only more efficient but also more suitable for IIoT-cloud environments.Finally,the security proof of SM2-KI-SIGN is given under the Elliptic Curve Discrete Logarithm(ECDL)assumption in the random oracle.

Study on the effect of four kinds of raw materials in hypertonic dehydration cell model

It aims to investigate the protective effects of sodium hyaluronate,panthenol,Portulaca oleracea L.and Calendula officinalis L.on hyperosmotic dehydration-induced injury of human immortalized keratinocytes(HaCaT).The safety mass concentrations of four raw materials were screened by detecting cell viability,and the secretion of hyaluronic acid(HA)was determined using the ELISA method.The expression of HaCaT barrier function related genes(OVOL1,EREG,TGM1,TGM2,IVL,IRF6,THBS1,CASP14)was detected at the mRNA level to explore the regulatory effect of four raw materials on these genes.The results demonstrate that pretreatment with the four kinds of raw materials could increase the cell viability after hyperosmotic dehydration,promote the secretion of HA,and improve the expression of barrier function related genes after hyperosmotic dehydration,among which panthenol and Calendula officinalis L.are better.The results show that the four raw materials have a certain protective effect on the hyperosmotic dehydration cell model,which provides data support for its application in cosmetics.

IoV environment exploring coordination:A federated learning approach

Exploring open fields with coordinated unmanned vehicles is popular in academia and industries.One of the most impressive applicable approaches is the Internet of Vehicles(lov).The IoV connects vehicles,road infrastructures and communication facilities to provide solutions for exploration tasks.However,the coordination of acquiring information from multi-vehicles may risk data privacy.To this end,sharing high-quality experiences instead of raw data has become an urgent demand.This paper employs a Deep Reinforcement Learning(DRL)method to enable IoVs to generate training data with prioritized experience and states,which can support the IoV to explore the environment more efficiently.Moreover,a Federated Learning(FL)experience sharing model is established to guarantee the vehicles'privacy.The numerical results show that the proposed method presents a better successful sharing rate and a more stable convergence within the comparison of fundamental methods.The experiments also suggest that the proposed method could support agents without full information to achieve the tasks.