“疯癫”叙事下的精神困境——以《人面桃花》为例

《人面桃花》一改作者前期对各种创新手法的尝试,选择"疯癫"叙事的方式思考人类当下的生存困境。这里的"疯癫"指的是与正常"规范"的行为与思想相对峙,它们在语言、精神空缺、梦境方面的表现影响了整个叙述过程,而这种有别于常人的行为在某种程度上产生了一种精神救赎的可能。

《人间词话》经典化历程反思——兼论文学经典的生成机制及生存境遇

文学经典化研究应涉及文学经典的生成机制和当代生存境遇。《人间词话》作为现代文论的转型之作是探讨文学经典化的典型个案。时代风尚、批评阐释、政治意识形态、教育传播等是影响《人间词话》经典化进程的主要因素。在后文学经典时代,传统文学经典的生存境遇不容乐观,但挑战与机遇并存。

水库消落带植物多样性空间格局预测模型及环境解释--基于XGBoost-SHAP模型框架

生物多样性的监测与预测对实现生物多样性保护及其可持续管理至关重要。传统方法通过实地调查来构建环境与生物多样性之间的多变量关系模型。空间大数据技术及机器和深度学习算法的发展为探索环境-生物多样性关系和预测生物多样性空间格局提供了新的视角和方法。构建了一种基于XGBoost算法的预测模型,融合实地调查的植物多样性数据和来自多源数据库的环境变量数据,分别构建了气候、地形、土壤、水文和人类活动5类共34个环境变量与植物群落物种丰富度、物种多样性和谱系多样性的关系模型,对丹江口水库消落带的植物多样性空间格局进行预测,同时结合SHAP框架确定关键环境因素;并进一步预测2050年水库消落带的植物多样性空间格局。研究表明,XGBoost算法在预测水库消落带植物多样性方面表现较好,3个多样性指标中谱系多样性的预测模型展现了最优的预测能力,而物种多样性预测模型的预测能力相对较低。结合SHAP分析发现年平均水淹时长、人类足迹与最冷季平均气温是影响消落带植物群落物种丰富度、物种多样性和谱系多样性的关键环境因素,其中年平均水淹时长的影响最为显著,随着年平均水淹时长增加,物种丰富度、物种多样性和谱系多样性降低。本研究构建的可解释预测模型可有效揭示消落带的植物多样性空间格局,为消落带生物多样性的保护和可持续管理提供科学依据,为生物多样性的监测和管理提供了新方法,对评估全球变化对生态系统的影响并促进生物多样性保护有重要意义。

粤港澳大湾区科技园地域性设计研究综述

文章综述了大湾区科技园地域性设计的理论研究进展;基于科技园地域性设计实践分类标准,对案例的类型及特点进行梳理;提出研究展望,以期为我国高质量发展背景下科技园的地域性设计提供参考。

许德公人参黄精杏麦饮对小鼠免疫增强活性研究

目的探究许德公人参黄精杏麦饮对小鼠免疫功能的作用,阐明其免疫增强的作用机制。检测各浓度许德公人参黄精杏麦饮对脾脏淋巴细胞的安全浓度、脾淋巴细胞因子分泌水平变化、淋巴细胞亚群的变化。方法将40只BALB/c小鼠随机分为4组(n=10),包括空白对照组,许德公人参黄精杏麦饮高、中、低剂量(1.2、0.6、0.3 mg/g)组,给药28 d后检测小鼠胸腺及脾脏指数,然后通过脾淋巴细胞转化实验、免疫器官组织学观察、小鼠血清免疫细胞因子水平变化、淋巴细胞亚群分布变化,评价许德公人参黄精杏麦饮的免疫调节作用。结果干预后的脾脏淋巴细胞的安全浓度最优为500μg/mL;淋巴细胞CD_(4)^(+)/CD_(8)^(+)的比例显著升高。此外,脾脏淋巴细胞分泌白细胞介素2(interleukin-2,IL-2)、白细胞介素6(interleukin-6,IL-6)、γ干扰素(interferon-γ,IFN-γ)及肿瘤坏死因子α(tumor necrosis factor-α,TNF-α)水平均得到不同程度的上调。与空白对照组比较,高剂量许德公人参黄精杏麦饮能明显增加小鼠免疫器官脾脏指数(P<0.05);低、中、高剂量许德公人参黄精杏麦饮均能促进淋巴细胞增殖反应(P<0.05);小鼠脾脏白髓生发中心和边缘区淋巴细胞增生明显;能持续诱导脾脏淋巴细胞中CD_(4)^(+)和CD_(8)^(+)高表达。结论许德公人参黄精杏麦饮可以显著增强机体免疫力,其预防和治疗免疫功能失调相关疾病有较好的应用前景。

Skin care efficacy study of recombinant humanized collagen based on in vitro level

Studying the skin care efficacy of recombinant humanized collagen based on in vitro level.The stability of the recombinant humanized collagen was first analyzed by treating at different temperatures,then its skincare efficacy based on in vitro level was evaluated by detecting the inhibition rate of elastase,the inhibition rate of collagenase,the protein content of type I collagen in human fibroblasts,the inhibition of reactive oxygen species(ROS)with human keratinocytes,and the effects of the recombinant humanized collagen on the expression of hyaluronic acid(HA),filaggrin(FLG)and transglutaminase 1(TGM1)in keratinocytes.The results showed that recombinant humanized collagen was able to maintain stability at temperatures below 70℃.With regard to its skincare efficacy,recombinant humanized collagen could inhibit elastase and collagenase activities and promote the increase of type I collagen content in human fibroblasts.It also showed good inhibition of ROS in keratinocytes in vitro and could increase the expression of HA,FLG,and TGM1 in keratinocytes.In short,the recombinant humanized collagen exhibited a favourable skin care effect in vitro level.This study proved that it has potential firming,anti-wrinkle,moisturizing,and repairing efficacy,and is a valuable cosmetic raw material.

Is platinum-loaded titania the best material for dye-sensitized hydrogen evolution under visible light?

A dye-sensitized photocatalyst combining Pt-loaded TiO_(2) and Ru(Ⅱ)tris-diimine sensitizer(RuP)was constructed and its activity for photochemical hydrogen evolution was compared with that of Pt-intercalated HCa_(2)Nb_(3)O_(10) nanosheets.When the sacrificial donor ethylenediaminetetraacetic acid(EDTA)disodium salt dihydrate was used,RuP/Pt/TiO_(2) showed higher activity than RuP/Pt/HCa_(2)Nb_(3)O_(10).In contrast,when NaI(a reversible electron donor)was used,RuP/Pt/TiO_(2) showed little activity due to back electron transfer to the electron acceptor(I_(3)-),which was gener-ated as the oxidation product of I-.By modification with anionic polymers(sodium poly(styrenesulfonate)or sodium polymethacrylate)that could inhibit the scavenging of conduction band electrons by I_(3)-,the H_(2) production activity from aqueous NaI was improved,but it did not exceed that of RuP/Pt/HCa_(2)Nb_(3)O_(10).Transient absorption measurements showed that the rate of semiconductor-to-dye back electron transfer was slower in the case of TiO_(2) than HCa_(2)Nb_(3)O_(10),but the electron transfer reaction to I3-was much faster.These results indicate that Pt/TiO_(2) is useful for reactions with sacrificial reductants(e.g.,EDTA),where the back electron transfer reaction to the more reducible product can be neglected.However,more careful design of the catalyst will be nec-essary when a reversible electron donor is employed.

Enabling Technologies for Autonomous Robotic Systems in Manufacturing

Research of autonomous manufacturing systems is motivated both by the new technical possibilities of cyber-physical systems and by the practical needs of the industry.Autonomous operation in semi-structured industrial environments can now be supported by advanced sensor technologies,digital twins,artificial intelligence and novel communication techniques.These enable real-time monitoring of production processes,situation recognition and prediction,automated and adaptive(re)planning,teamwork and performance improvement by learning.This paper summarizes the main requirements towards autonomous industrial robotics and suggests a generic workflow for realizing such systems.Application case studies will be presented from recent practice at HUN-REN SZTAKI in a broad range of domains such as assembly,welding,grinding,picking and placing,and machining.The various solutions have in common that they use a generic digital twin concept as their core.After making general recommendations for realizing autonomous robotic solutions in the industry,open issues for future research will be discussed.

Status of clinical applications of artificial intelligence in echocardiography

Artificial intelligence(AI)technology has been increasingly used in medical field with its rapid developments.Echocardiography is one of the best imaging methods for clinical diagnosis of heart diseases,and combining with AI could further improve its diagnostic efficiency.Though the applications of AI in echocardiography remained at a relatively early stage,a variety of automated quantitative and analytical techniques were rapidly emerging and initially entered clinical practice.The status of clinical applications of AI in echocardiography were reviewed in this article.

Network analysis of the relationships between depressive symptoms and social participation activities among Chinese older adults and its implications for nursing

Objective:Network analysis was used to explore the complex inter-relationships between social participation activities and depressive symptoms among the Chinese older population,and the differences in network structures among different genders,age groups,and urban-rural residency would be compared.Methods:Based on the 2018 wave of the Chinese Longitudinal Healthy Longevity Survey(CLHLS),12,043 people aged 65 to 105 were included.The 10-item Center for Epidemiologic Studies Depression(CESD)Scale was used to assess depressive symptoms and 10 types of social participation activities were collected,including housework,tai-chi,square dancing,visiting and interacting with friends,garden work,reading newspapers or books,raising domestic animals,playing cards or mahjong,watching TV or listening to radio,and organized social activities.R 4.2.1 software was used to estimate the network model and calculate strength and bridge strength.Results:21.60%(2,601/12,043)of the participants had depressive symptoms.The total social participation score was negatively associated with depressive symptoms after adjusting for sociodemographic factors.The network of social participation and depressive symptoms showed that“D9(Inability to get going)”and“S9(Watching TV and/or listening to the radio)”had the highest strength within depressive symptoms and social participation communities,respectively,and“S1(Housework)”,“S9(Watching TV and/or listening to the radio)”,and“D5(Hopelessness)”were the most prominent bridging nodes between the two communities.Most edges linking the two communities were negative.“S5(Graden work)-D5(Hopelessness)”and“S6(Reading newspapers/books)-D4(Everything was an effort)”were the top 2 strongest negative edges.Older females had significantly denser network structures than older males.Compared to older people aged 65e80,the age group 81e105 showed higher network global strength.Conclusions:This study provides novel insights into the complex relationships between social participation and depressive symptoms.Except for doing housework,other social participation activities were found to be protective for depression levels.Different nursing strategies should be taken to prevent and alleviate depressive symptoms for different genders and older people of different ages.

Deep learning models semi-automatic training system for quality control of transthoracic echocardiography

Objective To explore the value of deep learning(DL)models semi-automatic training system for automatic optimization of clinical image quality control of transthoracic echocardiography(TTE).Methods Totally 1250 TTE videos from 402 patients were retrospectively collected,including 490 apical four chamber(A4C),310 parasternal long axis view of left ventricle(PLAX)and 450 parasternal short axis view of great vessel(PSAX GV).The videos were divided into development set(245 A4C,155 PLAX,225 PSAX GV),semi-automated training set(98 A4C,62 PLAX,90 PSAX GV)and test set(147 A4C,93 PLAX,135 PSAX GV)at the ratio of 5∶2∶3.Based on development set and semi-automatic training set,DL model of quality control was semi-automatically iteratively optimized,and a semi-automatic training system was constructed,then the efficacy of DL models for recognizing TTE views and assessing imaging quality of TTE were verified in test set.Results After optimization,the overall accuracy,precision,recall,and F1 score of DL models for recognizing TTE views in test set improved from 97.33%,97.26%,97.26%and 97.26%to 99.73%,99.65%,99.77%and 99.71%,respectively,while the overall accuracy for assessing A4C,PLAX and PSAX GV TTE as standard views in test set improved from 89.12%,83.87%and 90.37%to 93.20%,90.32%and 93.33%,respectively.Conclusion The developed DL models semi-automatic training system could improve the efficiency of clinical imaging quality control of TTE and increase iteration speed.

Research on fast detection method of infrared small targets under resourceconstrained conditions

Infrared small target detection is a common task in infrared image processing.Under limited computa⁃tional resources.Traditional methods for infrared small target detection face a trade-off between the detection rate and the accuracy.A fast infrared small target detection method tailored for resource-constrained conditions is pro⁃posed for the YOLOv5s model.This method introduces an additional small target detection head and replaces the original Intersection over Union(IoU)metric with Normalized Wasserstein Distance(NWD),while considering both the detection accuracy and the detection speed of infrared small targets.Experimental results demonstrate that the proposed algorithm achieves a maximum effective detection speed of 95 FPS on a 15 W TPU,while reach⁃ing a maximum effective detection accuracy of 91.9 AP@0.5,effectively improving the efficiency of infrared small target detection under resource-constrained conditions.

Recovery after ischemic stroke:Effects of FuekFone home-based program on upper limb and cognitive function

Objectives:This study aimed to explore the effects of the“FuekFone(F.F.)home-based program”on the upper limb and cognitive function of ischemic stroke patients after discharge.Methods:A single group pre-and post-test design was conducted.A total of 40 patients with recovery after ischemic stroke were recruited from two university hospitals in Thailand.The study was conducted between June 2022 and January 2023.Participants underwent a six-week“F.F.home-based program,”which combined an upper limb and cognitive function rehabilitation device with Android games,including stationary barrel,adventure walk,adventure stroll,sliding barrel,sauce squeeze,and cut objects.Each game has different difficulty levels.Patients can perform corresponding exercises through the games according to their conditions under the guidance of medical staff.The patients played for 24 min per time,4 min each game,three days a week.The second week,let the patients play games for 30 min per time,5 min each game,3 days a week.Then,in the 3e6 weeks,let the patients play games for 1 h per time,10 min each game,5 days a week.At the pre-and post-intervention,the Thai version of the National Institutes of Health Stroke Scale(NIHSS),the Motor Assessment Scale,and the Montreal Cognitive Assessment(MoCA score)were administered to patients at discharge and at 2,4,and 6 weeksafter discharge,and the results were compared.Results:All participants completed this program.Participants had statistically improved upper limb function(upper arm function score,hand movements score,advanced hand activities score,total Motor Assessment Scale score)and MoCA score at 2,4,and 6 weeks after discharge(P<0.001).In the comparison of upper limb function and cognitive function at each of the study times,we found statistically improved upper limb function(upper arm function score,hand movements score,advanced hand activities score,total Motor Assessment Scale score)and MoCA score at 4,and 6 weeks after discharge when compared to after discharge and 2 weeks after discharge,respectively(P<0.05).Conclusions:Continuing care of patients post-stroke after discharge from hospital,such as F.F.homebased program should be applied at home to enhance upper limb and cognitive function.

四川中江塔梁子东汉崖墓M3石刻画像墨书“襄人”新说

四川中江塔梁子东汉崖墓M3石刻画像上出现的“襄人”,学界或以为是胡人,或以为是西南地区的少数民族族称,尚无定论。长沙走马楼西汉简中出现的“襄人”为人名而非族称,且秦汉简牍与玺印中多有以“胡人”“越人”“赵人”“市人”“央人”“里人”“外人”“圣人”“异人”等以“某人”为名的取名现象。通过考察M3石刻画像主题与墨书“襄人”的位置,结合目前出土的汉代画像石榜题、工作性铭文的特点,可以确定M3石刻画像上墨书的“襄人”应为工匠题名,与“胡人舞蹈图”的主题内容应无关。“襄人人名说”可解决长久以来对M3“胡人舞蹈图”上端墨书“襄人”内涵的争论,消除此前各说对M3石刻画像石主题与“襄人”解释之间的抵牾。

Improved YOLOv8-Based Target Detection Algorithm for UAV Aerial Image

In response to the challenge of low detection accuracy and susceptibility to missed and false detections of small targets in unmanned aerial vehicles(UAVs)aerial images,an improved UAV image target detection algorithm based on YOLOv8 was proposed in this study.To begin with,the CoordAtt attention mechanism was employed to enhance the feature extraction capability of the backbone network,thereby reducing interference from backgrounds.Additionally,the BiFPN feature fusion network with an added small object detection layer was used to enhance the model's ability to perceive for small objects.Furthermore,a multi-level fusion module was designed and proposed to effectively integrate shallow and deep information.The use of an enhanced MPDIoU loss function further improved detection performance.The experimental results based on the publicly available VisDrone2019 dataset showed that the improved model outperformed the YOLOv8 baseline model,mAP@0.5 improved by 20%,and the improved method improved the detection accuracy of the model for small targets.

Optical-neural Stimulation in Non-human Primates:Modulating Brain Function and Behavior

Optical-neural stimulation,which encompasses cutting-edge techniques such as optogenetics and infrared neurostimulation,employs distinct mechanisms to modulate brain function and behavior.These advanced neuromodulation techniques offer accurate manipulation of targeted areas,even selectively modulating specific neurons,in the brain.This makes it possible to investigate the cause-and-effect connections between neural activity and behavior,allowing for a better comprehension of the intricate brain dynamics towards complex environments.Non-human primates serve as an essential animal model for investigating these complex functions in brain research,bridging the gap between the basic research and clinical applications.One of the earliest optical studies utilizing optogenetic neuromodulation in monkeys was conducted in 2009.Since then,the optical-neural stimulations have been effectively applied in non-human primates.This review summarises recent research that employed optogenetics or infrared neurostimulation techniques to regulate brain function and behavior in non-human primates.The current state of optical-neural stimulations discussed here demonstrates their efficacy in advancing the understanding of brain systems.Nevertheless,there are still challenges that need to be addressed before they can fully achieve their potential.

Artificial intelligence models based on non-contrast chest CT for measuring bone mineral density

Objective To observe the value of artificial intelligence(AI)models based on non-contrast chest CT for measuring bone mineral density(BMD).Methods Totally 380 subjects who underwent both non-contrast chest CT and quantitative CT(QCT)BMD examination were retrospectively enrolled and divided into training set(n=304)and test set(n=76)at a ratio of 8∶2.The mean BMD of L1—L3 vertebrae were measured based on QCT.Spongy bones of T5—T10 vertebrae were segmented as ROI,radiomics(Rad)features were extracted,and machine learning(ML),Rad and deep learning(DL)models were constructed for classification of osteoporosis(OP)and evaluating BMD,respectively.Receiver operating characteristic curves were drawn,and area under the curves(AUC)were calculated to evaluate the efficacy of each model for classification of OP.Bland-Altman analysis and Pearson correlation analysis were performed to explore the consistency and correlation of each model with QCT for measuring BMD.Results Among ML and Rad models,ML Bagging-OP and Rad Bagging-OP had the best performances for classification of OP.In test set,AUC of ML Bagging-OP,Rad Bagging-OP and DL OP for classification of OP was 0.943,0.944 and 0.947,respectively,with no significant difference(all P>0.05).BMD obtained with all the above models had good consistency with those measured with QCT(most of the differences were within the range of Ax-G±1.96 s),which were highly positively correlated(r=0.910—0.974,all P<0.001).Conclusion AI models based on non-contrast chest CT had high efficacy for classification of OP,and good consistency of BMD measurements were found between AI models and QCT.

The enlightenment of artificial intelligence large-scale model on the research of intelligent eye diagnosis in traditional Chinese medicine

Eye diagnosis is a method for inspecting systemic diseases and syndromes by observing the eyes.With the development of intelligent diagnosis in traditional Chinese medicine(TCM);artificial intelligence(AI)can improve the accuracy and efficiency of eye diagnosis.However;the research on intelligent eye diagnosis still faces many challenges;including the lack of standardized and precisely labeled data;multi-modal information analysis;and artificial in-telligence models for syndrome differentiation.The widespread application of AI models in medicine provides new insights and opportunities for the research of eye diagnosis intelli-gence.This study elaborates on the three key technologies of AI models in the intelligent ap-plication of TCM eye diagnosis;and explores the implications for the research of eye diagno-sis intelligence.First;a database concerning eye diagnosis was established based on self-su-pervised learning so as to solve the issues related to the lack of standardized and precisely la-beled data.Next;the cross-modal understanding and generation of deep neural network models to address the problem of lacking multi-modal information analysis.Last;the build-ing of data-driven models for eye diagnosis to tackle the issue of the absence of syndrome dif-ferentiation models.In summary;research on intelligent eye diagnosis has great potential to be applied the surge of AI model applications.

Self-supervised learning artificial intelligence noise reduction technology based on the nearest adjacent layer in ultra-low dose CT of urinary calculi

Objective To observe the value of self-supervised deep learning artificial intelligence(AI)noise reduction technology based on the nearest adjacent layer applicated in ultra-low dose CT(ULDCT)for urinary calculi.Methods Eighty-eight urinary calculi patients were prospectively enrolled.Low dose CT(LDCT)and ULDCT scanning were performed,and the effective dose(ED)of each scanning protocol were calculated.The patients were then randomly divided into training set(n=75)and test set(n=13),and a self-supervised deep learning AI noise reduction system based on the nearest adjacent layer constructed with ULDCT images in training set was used for reducing noise of ULDCT images in test set.In test set,the quality of ULDCT images before and after AI noise reduction were compared with LDCT images,i.e.Blind/Referenceless Image Spatial Quality Evaluator(BRISQUE)scores,image noise(SD ROI)and signal-to-noise ratio(SNR).Results The tube current,the volume CT dose index and the dose length product of abdominal ULDCT scanning protocol were all lower compared with those of LDCT scanning protocol(all P<0.05),with a decrease of ED for approximately 82.66%.For 13 patients with urinary calculi in test set,BRISQUE score showed that the quality level of ULDCT images before AI noise reduction reached 54.42%level but raised to 95.76%level of LDCT images after AI noise reduction.Both ULDCT images after AI noise reduction and LDCT images had lower SD ROI and higher SNR than ULDCT images before AI noise reduction(all adjusted P<0.05),whereas no significant difference was found between the former two(both adjusted P>0.05).Conclusion Self-supervised learning AI noise reduction technology based on the nearest adjacent layer could effectively reduce noise and improve image quality of urinary calculi ULDCT images,being conducive for clinical application of ULDCT.

兮甲盘铭文“其进人”句的断读问题辨析

兮甲盘铭文的释读基本上是确定的,但“其进人”前后如何点断,学者们存在分歧。文章在梳理总结前人观点的基础上,从语义、词性、句法多方面分析比较,认为“其进人”当属下读。该句意为“(淮夷)进贡人力、进行交易不敢不到次、市上,敢不听从命令,当被处以刑罚”。