叙事学理论构成、支流与核心概念揆要

叙事学是一门几乎等长于人类历史的学问,尽管这一学科概念是在20世纪60年代结构主义思潮影响下才正式提出。西方经典叙事学、西方修辞叙事学、西方后经典叙事学与中国传统叙事理论是叙事理论的四大构成,各有话语体系。红线理论、猎鹰理论、冰山理论、“高概念”理论等是对于叙事艺术作品创作颇有启发的叙事理论。

基于环境DNA宏条形码的青岚湖自然保护区鱼类组成及分布特征

为探究在不同引物、不同参考数据库下环境DNA技术检测结果的差异,于2021年4月,采用环境DNA宏条形码技术分析了青岚湖鱼类多样性。选取16S rRNA及Cytb 2种引物,NCBI及本地数据库2种数据库,分别进行比对注释。结果表明:在青岚湖29个采样点中,共检测到7目15科43属64种鱼类,其中在16S-NCBI情形下获得4目9科19属20种鱼类,在16S-本地数据库情形下获得6目13科27属38种鱼类,在Cytb-NCBI情形下获得4目6科16属19种鱼类,在Cytb-本地数据库情形下获得2目5科15属20种鱼类。在青岚湖29个采样点中,鱼类更多地分布于湖面宽阔的中间地带(如S31附近),且南部较北部更少,鱼种的分布呈现一定的空间相似性。就研究区域而言,选择16S rRNA引物及本地数据库可以获得更全面的鱼类物种。通过与青岚湖鱼类历史数据比对发现,环境DNA技术在研究区域具有较强的适用性,如能选择适当的引物和本地数据库,可以更全面地反映研究区域的物种组成情况。

PNIPAm温敏纳米纤维膜:交联作用下的形貌稳定性和响应行为

聚N-异丙基丙烯酰胺(PNIPAm)交联温敏纳米纤维膜作为一种相变温度易于控制的新兴响应性材料,克服了传统PNIPAm块状水凝胶的生产成本高、响应速率慢和PNIPAm非交联温敏纳米纤维耐水性差的缺点,受到广泛研究并应用于智能开关、温度致动器、水油分离、药物、细胞控制释放和伤口敷料等领域。形貌稳定性和快速响应性是温敏纳米纤维膜在重复体积变化过程中最大的挑战,同时也作为评价PNIPAm温敏纳米纤维膜的实用性最重要指标引起了人们广泛的关注。本文全面综述了PNIPAm温敏纳米纤维膜近二十年来国内外的突破性进展和非交联作用下PNIPAm温敏纳米纤维膜的形貌变化和响应性,重点综合分析了物理和化学交联中交联反应类型、交联度、交联时间和交联分子量对PNIPAm温敏纳米纤维膜的形貌稳定性和响应行为的影响,为之后纤维膜的交联处理提供了理论支持,并对PNIPAm温敏纳米纤维膜的发展及应用前景进行了展望。

鄂尔多斯盆地大牛地气田马五_(6~10)亚段沉积相高频演化特征

鄂尔多斯盆地大牛地气田马五_(6~10)亚段沉积微相高频变化,分布特征尚不明确,严重制约了天然气勘探与开发。综合利用岩心、薄片、测井及野外露头等资料,详细分析了该地区马五_(6~10)亚段碳酸盐岩岩石类型及测井响应特征,划分了4种沉积微相,进一步分析了该地区马五_(6~10)亚段高频沉积相演化特征。研究表明,马五期海平面整体呈下降趋势,发育局限台地亚相,云坪、膏云坪、灰云坪微相在空间上彼此相邻,纵向上相互叠置,随海平面的涨落沉积微相在膏云坪、云坪和云坪、灰云坪、云灰坪之间频繁转化。马五_(10)、马五_(8)、马五_(7)^(2)、马五_(6)^(1)亚段主要发育膏云坪和云坪微相,马五_(9)亚段主要发育云坪和灰云坪微相,马五_(7)^(1)、马五_(6)^(2)亚段主要发育膏云坪、云坪及灰云坪微相,马五_(6)^(3)亚段则由西向东依次发育膏云坪、云坪、灰云坪、云灰坪微相。研究区海平面升降控制了沉积亚相的演化,更为高频的次级海平面变化控制着沉积微相快速变化。鄂尔多斯盆地大牛地气田马五_(6~10)亚段沉积相高频演化特征研究,将有力支撑大牛地气田马家沟组深部天然气资源的开发动用,同时为大牛地气田马家沟组沉积模式研究提供依据。

中药天然产物代谢活化的化学性质可能与其毒性相关

确保中药(TCM)的安全性一直是医疗保健领域中长期存在的普遍挑战。对天然产品的毒理学复杂性进行细致的研究至关重要,特别是这些物质的代谢转化以及随后产生的反应性中间体。这一生化过程是多种毒性表现的起源,包括肝毒性、肾毒性、肺毒性和遗传毒性。在TCM中分类的化合物,包括吡咯里西啶生物碱、蒽醌、呋喃萜类、烯基苯、双苄基异喹啉生物碱、黄酮类和甲氧基二苯基衍生物,在代谢激活后表现出一系列有害机制。这篇综述提供了这些化合物通过代谢激活引起毒性的途径的全面描述。这篇综述强调了天然产物代谢激活中涉及的化学机制,这些机制可能触发毒性级联反应,而不仅仅是表面现象。此外,这项研究通过深入探讨代谢激活引起的毒性机制,丰富了现有文献。总之,这篇综述强调了仔细研究毒性机制的重要性,并为合理和安全使用中药提供了见解。

冷轧变形对CoCrNi中熵合金显微组织和力学性能的影响

中熵合金具有多种优异性,同时具有高强度和延展性。冷轧变形是提高中熵合金力学性能的一种即经济又有效的方法。对CoCrNi中熵合金进行室温不同变形量(25%,37.5%,50%,62.5%,75%)的冷轧,通过X射线衍射分析、显微组织分析和拉伸试验研究了室温下不同变形量对合金显微组织和力学性能的影响。结果表明:在室温不同变形量冷轧下CoCrNi中熵合金的组织仍为单一的FCC结构。CoCrNi中熵合金室温抗拉强度较低,随着变形量的增加,抗拉强度显著提升,但延展性相比铸态变差。

《共产党宣言》中自我革命向度研究

《共产党宣言》中的自我革命思想由资本主义特定的时代背景、无产阶级转向自觉斗争的理论需要、马克思主义理论的革命性和批判性基调三方“合力”推动形成。其所内蕴的政党建设要旨与历史使命、理论的开放性与科学性品格、以人民为中心的发展思想与不断革命的策略,是对无产阶级政党自我革命何以可能、何以必然、何以实现的回答。深析《共产党宣言》中的自我革命思想,对新时代以自我革命纯净政党本质、锻造始终走在时代前列的马克思主义执政党、将自我革命引向纵深具有强烈的现实关照和重要的启示意义。

Alkyl dimethyl betaine activates the low-temperature collection capacity of sodium oleate for scheelite

The impact of alkyl dimethyl betaine (ADB) on the collection capacity of sodium oleate (NaOl) at low temperatures was evaluated using flotation tests at various scales. The low-temperature synergistic mechanism of ADB and NaOl was explored by infrared spectroscopy, X-ray photoelectron spectroscopy, surface tension measurement, foam performance test, and flotation reagent size measurement.The flotation tests revealed that the collector mixed with octadecyl dimethyl betaine (ODB) and NaOl in a mass ratio of 4:96 exhibited the highest collection capacity. The combined collector could increase the scheelite recovery by 3.48% at low temperatures of 8–12℃. This is particularly relevant in the Luanchuan area, which has the largest scheelite concentrate output in China. The results confirmed that ODB enhanced the collection capability of NaOl by improving the dispersion and foaming performance. Betaine can be introduced as an additive to NaOl to improve the recovery of scheelite at low temperatures.

Multimodal Machine Learning Guides Low Carbon Aeration Strategies in Urban Wastewater Treatment

The potential for reducing greenhouse gas(GHG)emissions and energy consumption in wastewater treatment can be realized through intelligent control,with machine learning(ML)and multimodality emerging as a promising solution.Here,we introduce an ML technique based on multimodal strategies,focusing specifically on intelligent aeration control in wastewater treatment plants(WWTPs).The generalization of the multimodal strategy is demonstrated on eight ML models.The results demonstrate that this multimodal strategy significantly enhances model indicators for ML in environmental science and the efficiency of aeration control,exhibiting exceptional performance and interpretability.Integrating random forest with visual models achieves the highest accuracy in forecasting aeration quantity in multimodal models,with a mean absolute percentage error of 4.4%and a coefficient of determination of 0.948.Practical testing in a full-scale plant reveals that the multimodal model can reduce operation costs by 19.8%compared to traditional fuzzy control methods.The potential application of these strategies in critical water science domains is discussed.To foster accessibility and promote widespread adoption,the multimodal ML models are freely available on GitHub,thereby eliminating technical barriers and encouraging the application of artificial intelligence in urban wastewater treatment.

A Fault-Tolerant Mobility-Aware Caching Method in Edge Computing

Mobile Edge Computing(MEC)is a technology designed for the on-demand provisioning of computing and storage services,strategically positioned close to users.In the MEC environment,frequently accessed content can be deployed and cached on edge servers to optimize the efficiency of content delivery,ultimately enhancing the quality of the user experience.However,due to the typical placement of edge devices and nodes at the network’s periphery,these components may face various potential fault tolerance challenges,including network instability,device failures,and resource constraints.Considering the dynamic nature ofMEC,making high-quality content caching decisions for real-time mobile applications,especially those sensitive to latency,by effectively utilizing mobility information,continues to be a significant challenge.In response to this challenge,this paper introduces FT-MAACC,a mobility-aware caching solution grounded in multi-agent deep reinforcement learning and equipped with fault tolerance mechanisms.This approach comprehensively integrates content adaptivity algorithms to evaluate the priority of highly user-adaptive cached content.Furthermore,it relies on collaborative caching strategies based onmulti-agent deep reinforcement learningmodels and establishes a fault-tolerancemodel to ensure the system’s reliability,availability,and persistence.Empirical results unequivocally demonstrate that FTMAACC outperforms its peer methods in cache hit rates and transmission latency.

Real-time arrival picking of rock microfracture signals based on convolutional-recurrent neural network and its engineering application

Accurately picking P-and S-wave arrivals of microseismic(MS)signals in real-time directly influences the early warning of rock mass failure.A common contradiction between accuracy and computation exists in the current arrival picking methods.Thus,a real-time arrival picking method of MS signals is constructed based on a convolutional-recurrent neural network(CRNN).This method fully utilizes the advantages of convolutional layers and gated recurrent units(GRU)in extracting short-and long-term features,in order to create a precise and lightweight arrival picking structure.Then,the synthetic signals with field noises are used to evaluate the hyperparameters of the CRNN model and obtain an optimal CRNN model.The actual operation on various devices indicates that compared with the U-Net method,the CRNN method achieves faster arrival picking with less performance consumption.An application of large underground caverns in the Yebatan hydropower station(YBT)project shows that compared with the short-term average/long-term average(STA/LTA),Akaike information criterion(AIC)and U-Net methods,the CRNN method has the highest accuracy within four sampling points,which is 87.44%for P-wave and 91.29%for S-wave,respectively.The sum of mean absolute errors(MAESUM)of the CRNN method is 4.22 sampling points,which is lower than that of the other methods.Among the four methods,the MS sources location calculated based on the CRNN method shows the best consistency with the actual failure,which occurs at the junction of the shaft and the second gallery.Thus,the proposed method can pick up P-and S-arrival accurately and rapidly,providing a reference for rock failure analysis and evaluation in engineering applications.

Proactive Caching at the Wireless Edge:A Novel Predictive User Popularity-Aware Approach

Mobile Edge Computing(MEC)is a promising technology that provides on-demand computing and efficient storage services as close to end users as possible.In an MEC environment,servers are deployed closer to mobile terminals to exploit storage infrastructure,improve content delivery efficiency,and enhance user experience.However,due to the limited capacity of edge servers,it remains a significant challenge to meet the changing,time-varying,and customized needs for highly diversified content of users.Recently,techniques for caching content at the edge are becoming popular for addressing the above challenges.It is capable of filling the communication gap between the users and content providers while relieving pressure on remote cloud servers.However,existing static caching strategies are still inefficient in handling the dynamics of the time-varying popularity of content and meeting users’demands for highly diversified entity data.To address this challenge,we introduce a novel method for content caching over MEC,i.e.,PRIME.It synthesizes a content popularity prediction model,which takes users’stay time and their request traces as inputs,and a deep reinforcement learning model for yielding dynamic caching schedules.Experimental results demonstrate that PRIME,when tested upon the MovieLens 1M dataset for user request patterns and the Shanghai Telecom dataset for user mobility,outperforms its peers in terms of cache hit rates,transmission latency,and system cost.

Application of deep learning methods combined with physical background in wide field of view imaging atmospheric Cherenkov telescopes

The High Altitude Detection of Astronomical Radiation(HADAR)experiment,which was constructed in Tibet,China,combines the wide-angle advantages of traditional EAS array detectors with the high-sensitivity advantages of focused Cherenkov detectors.Its objective is to observe transient sources such as gamma-ray bursts and the counterparts of gravitational waves.This study aims to utilize the latest AI technology to enhance the sensitivity of HADAR experiments.Training datasets and models with distinctive creativity were constructed by incorporating the relevant physical theories for various applications.These models can determine the type,energy,and direction of the incident particles after careful design.We obtained a background identification accuracy of 98.6%,a relative energy reconstruction error of 10.0%,and an angular resolution of 0.22°in a test dataset at 10 TeV.These findings demonstrate the significant potential for enhancing the precision and dependability of detector data analysis in astrophysical research.By using deep learning techniques,the HADAR experiment’s observational sensitivity to the Crab Nebula has surpassed that of MAGIC and H.E.S.S.at energies below 0.5 TeV and remains competitive with conventional narrow-field Cherenkov telescopes at higher energies.In addition,our experiment offers a new approach for dealing with strongly connected,scattered data.

Analytical solutions of turbulent boundary layer beneath forward-leaning waves

As a typical nonlinear wave,forward-leaning waves can be frequently encountered in the near-shore areas,which can impact coastal sediment transport significantly.Hence,it is of significance to describe the characteristics of the boundary layer beneath forward-leaning waves accurately,especially for the turbulent boundary layer.In this work,the linearized turbulent boundary layer model with a linear turbulent viscosity coefficient is applied,and the novel expression of the near-bed orbital velocity that has been worked out by the authors for forward-leaning waves of arbitrary forward-leaning degrees is further used to specify the free stream boundary condition of the bottom boundary layer.Then,a variable transformation is found so as to make the equation of the turbulent boundary layer model be solved analytically through a modified Bessel function.Consequently,an explicit analytical solution of the turbulent boundary layer beneath forward-leaning waves is derived by means of variable separation and variable transformation.The analytical solutions of the velocity profile and bottom shear stress of the turbulent boundary layer beneath forward-leaning waves are verified by comparing the present analytical results with typical experimental data available in the previous literature.

Numerical study on the cavity dynamics for vertical water entries of twin spheres

In this study, a three dimensional(3D) numerical model of six-degrees-of-freedom(6DOF) is applied to simulate the water entries of twin spheres side-by-side at different lateral distances and time intervals.The turbulence structure is described using the shear-stress transport k-ω(SST k-ω) model, and the volume of fluid(VOF) method is used to track the complex air-liquid interface. The motion of spheres during water entry is simulated using an independent overset grid. The numerical model is verified by comparing the cavity evolution results from simulations and experiments. Numerical results reveal that the time interval between the twin water entries evidently affects cavity expansion and contraction behaviors in the radial direction. However, this influence is significantly weakened by increasing the lateral distance between the two spheres. In synchronous water entries, pressure is reduced on the midline of two cavities during surface closure, which is directly related to the cavity volume. The evolution of vortexes inside the two cavities is analyzed using a velocity vector field, which is affected by the lateral distance and time interval of water entries.

Alkaline sphingomyelinase deficiency impairs intestinal mucosal barrier integrity and reduces antioxidant capacity in dextran sulfate sodium-induced colitis

BACKGROUND Ulcerative colitis is a chronic inflammatory disease of the colon with an unknown etiology.Alkaline sphingomyelinase(alk-SMase)is specifically expressed by intestinal epithelial cells,and has been reported to play an anti-inflammatory role.However,the underlying mechanism is still unclear.AIM To explore the mechanism of alk-SMase anti-inflammatory effects on intestinal barrier function and oxidative stress in dextran sulfate sodium(DSS)-induced colitis.METHODS Mice were administered 3%DSS drinking water,and disease activity index was determined to evaluate the status of colitis.Intestinal permeability was evaluated by gavage administration of fluorescein isothiocyanate dextran,and bacterial translocation was evaluated by measuring serum lipopolysaccharide.Intestinal epithelial cell ultrastructure was observed by electron microscopy.Western blotting and quantitative real-time reverse transcription-polymerase chain reaction were used to detect the expression of intestinal barrier proteins and mRNA,respectively.Serum oxidant and antioxidant marker levels were analyzed using commercial kits to assess oxidative stress levels.RESULTS Compared to wild-type(WT)mice,inflammation and intestinal permeability in alk-SMase knockout(KO)mice were more severe beginning 4 d after DSS induction.The mRNA and protein levels of intestinal barrier proteins,including zonula occludens-1,occludin,claudin-3,claudin-5,claudin-8,mucin 2,and secretory immunoglobulin A,were significantly reduced on 4 d after DSS treatment.Ultrastructural observations revealed progressive damage to the tight junctions of intestinal epithelial cells.Furthermore,by day 4,mitochondria appeared swollen and degenerated.Additionally,compared to WT mice,serum malondialdehyde levels in KO mice were higher,and the antioxidant capacity was significantly lower.The expression of the transcription factor nuclear factor erythroid 2-related factor 2(Nrf2)in the colonic mucosal tissue of KO mice was significantly decreased after DSS treatment.mRNA levels of Nrf2-regulated downstream antioxidant enzymes were also decreased.Finally,colitis in KO mice could be effectively relieved by the injection of tertiary butylhydroquinone,which is an Nrf2 activator.CONCLUSION Alk-SMase regulates the stability of the intestinal mucosal barrier and enhances antioxidant activity through the Nrf2 signaling pathway.

Analysis of Intraspecies Diversity of Rice Reveals Variation Patterns of Oryza sativa Basic Leucine Zippers

The basic leucine zipper(bZIP)is an important class of transcription factors in plants,playing a critical role in plant growth and development and responses to biotic and abiotic stress.Due to gene presence/absence variations,it is limited to identify bZIP genes based on the reference genome.Therefore,we performed the bZIP gene family analysis in the rice pan-genome.By employing a rice pan-genome,ninety-four OsbZIPs(72 core genes and 22 variable genes)were identified and divided into 11 groups in a phylogenetic tree.Based upon Ka/Ks values in 33 accessions,OsbZIPs were subjected to different selection pressures during domestication.The analysis of the effects of structural variations(SVs)on gene expression,gene structure,and conserved domains showed that SVs could significantly alter the expression levels of certain OsbZIPs,leading to gene truncation and the emergence of numerous atypical genes.Thirty-four differentially expressed OsbZIPs were identified by analyzing RNA-seq data of the Xanthomonas oryzae pv.oryzae(Xoo)infection susceptible(IR24)and resistant(IRBB67)lines under high temperature,and by counting the number of differentially expressed OsbZIPs in different subgroups.These Osb-ZIPs were found to respond to Xoo infection at an early stage and may not be involved in the mechanism of Xa4 and Xa7 resistance to Xoo.The multiple variation patterns of OsbZIP genes provide new insights into the OsbZIP genes in rice.These results provide new resources and offer new directions for functional studies of OsbZIPs.

Pulse rate estimation based on facial videos:an evaluation and optimization of the classical methods using both self-constructed and public datasets

Pulse rate is one of the important characteristics of traditional Chinese medicine pulse diagnosis,and it is of great significance for determining the nature of cold and heat in diseases.The prediction of pulse rate based on facial video is an exciting research field for getting palpation information by observation diagnosis.However,most studies focus on optimizing the algorithm based on a small sample of participants without systematically investigating multiple influencing factors.A total of 209 participants and 2,435 facial videos,based on our self-constructed Multi-Scene Sign Dataset and the public datasets,were used to perform a multi-level and multi-factor comprehensive comparison.The effects of different datasets,blood volume pulse signal extraction algorithms,region of interests,time windows,color spaces,pulse rate calculation methods,and video recording scenes were analyzed.Furthermore,we proposed a blood volume pulse signal quality optimization strategy based on the inverse Fourier transform and an improvement strategy for pulse rate estimation based on signal-to-noise ratio threshold sliding.We found that the effects of video estimation of pulse rate in the Multi-Scene Sign Dataset and Pulse Rate Detection Dataset were better than in other datasets.Compared with Fast independent component analysis and Single Channel algorithms,chrominance-based method and plane-orthogonal-to-skin algorithms have a more vital anti-interference ability and higher robustness.The performances of the five-organs fusion area and the full-face area were better than that of single sub-regions,and the fewer motion artifacts and better lighting can improve the precision of pulse rate estimation.

Research progress on the effect of pyroptosis on the occurrence,development,invasion and metastasis of colorectal cancer

Pyroptosis is a type of programmed cell death mediated by gasdermines(GSDMs).The N-terminal domain of GSDMs forms pores in the plasma membrane,causing cell membrane rupture and the release of cell contents,leading to an inflammatory response and mediating pyrodeath.Pyroptosis plays an important role in inflammatory diseases and malignant tumors.With the further study of pyroptosis,an increasing number of studies have shown that the pyroptosis pathway can regulate the tumor microenvironment and antitumor immunity of colorectal cancer and is closely related to the occurrence,development,treatment and prognosis of colorectal cancer.This review aimed to explore the molecular mechanism of pyroptosis and the role of pyroptosis in the occurrence,development,treatment and prognosis of colorectal cancer(CRC)and to provide ideas for the clinical diagnosis and treatment of CRC.

The MtRGF6 Peptide Differentially Regulates Root Development and Symbiotic Nodulation of Medicago truncatula and Lotus japonicus

Rhizobia induces nitrogen-fixing nodules in legumes used in agricultural production,providing a direct source of combined nitrogen to leguminous crops.Small peptides,such as CLAVATA3/EMBRYO SURROUNDING REGION peptides(CLE),are known to regulate the formation and development of nitrogen-fixing nodules in legumes.Root meristem growth factor(RGF)peptides from Medicago truncatula not only regulate root develop-ment but also modulate nodulation symbiosis with Sinorhizobium meliloti.However,the impact of RGF peptides from one leguminous species on the others remains unclear.In this study,we investigate the effects of the RGF family peptide MtRGF6p from M.truncatula on nodulation symbiosis and root development in Lotus japonicus.The MtRGF6 gene is predominantly expressed in the root nodules of M.truncatula and shows low identity with RGF homologous genes from L.japonicus.The gene promoter is active in the primordia of root nodules and lat-eral roots,as well as in young nodules and roots,and the meristem,infection,and nitrogen-fixing regions of the mature nodule.Chemically synthesized MtRGF6p promoted primary root growth in M.truncatula but sup-pressed the growth of L.japonicus primary roots.The peptide negatively affected the initiation of nodule primor-dia,the formation of infection threads,and nodulation in both legumes,with a low dosage showing effects on L.japonicus compared to M.truncatula.These results suggest that the MtRGF6 peptide from M.truncatula may serve as an inter-species signal affecting the root organ development of L.japonicus.