Revisiting Enlightenment Universalism:18th-Century Lessons on Nonliteral Translations and Transcultural Storytelling

A large number of transcultural fictions appeared in the 18th century,providing us with an important entry into discussing the task of comparative literature today.The 18th-century Oriental tales,stories authored by European writers that adapted from or modeled themselves after loose translations of folk tales from the East,practiced a kind of mental shapeshifting,blurring the boundaries between East and West.The same kind of cross-cultural identification is visible in many other literary narratives from the same period,indicative of a fluid,universalist politics regarding Europe's relations with the Orient that requires reevaluation.18th-century transcultural fictions suggest a few tactics for mediating between the necessity of establishing grounds of comparison and the need to draw distinctions.In its search for ways of breaking through the stronghold of cultural nationalism,comparative literature in its contemporary incarnation does well to rethink Enlightenment universalism as encoded in the literary landscape of 18th century Europe.

从同文馆到北京大学:近代中国“Peking University”概念考论

从晚清到民国,“Peking University”的指称对象先后包括京师同文馆、汇文书院、京师大学堂、私立燕京大学和国立北京大学五所驻京高等教育机构,其中既有国立最高学府,也有私立教会学校。虽然部分属于非正式名称,但仍具有广泛社会影响。语言概念的重叠带来话语表达中的歧义,同时也投射出多元复杂的历史图景。依据档案、报刊、辞书、回忆录等材料,返回历史现场,梳理近代中国“Peking University”概念的生成和流变,从中考察新式教育的引入、中西观念的互动及文化空间的形成,有助于探求译名背后的知识建构、教育转型与社会变迁。

Intelligent Recognition Using Ultralight Multifunctional Nano‑Layered Carbon Aerogel Sensors with Human‑Like Tactile Perception

Humans can perceive our complex world through multi-sensory fusion.Under limited visual conditions,people can sense a variety of tactile signals to identify objects accurately and rapidly.However,replicating this unique capability in robots remains a significant challenge.Here,we present a new form of ultralight multifunctional tactile nano-layered carbon aerogel sensor that provides pressure,temperature,material recognition and 3D location capabilities,which is combined with multimodal supervised learning algorithms for object recognition.The sensor exhibits human-like pressure(0.04–100 kPa)and temperature(21.5–66.2℃)detection,millisecond response times(11 ms),a pressure sensitivity of 92.22 kPa^(−1)and triboelectric durability of over 6000 cycles.The devised algorithm has universality and can accommodate a range of application scenarios.The tactile system can identify common foods in a kitchen scene with 94.63%accuracy and explore the topographic and geomorphic features of a Mars scene with 100%accuracy.This sensing approach empowers robots with versatile tactile perception to advance future society toward heightened sensing,recognition and intelligence.

A core-satellite self-assembled SERS aptasensor containing a“biological-silent region”Raman tag for the accurate and ultrasensitive detection of histamine

Herein,a novel interference-free surface-enhanced Raman spectroscopy(SERS)strategy based on magnetic nanoparticles(MNPs)and aptamer-driven assemblies was proposed for the ultrasensitive detection of histamine.A core-satellite SERS aptasensor was constructed by combining aptamer-decorated Fe_(3)O_(4)@Au MNPs(as the recognize probe for histamine)and complementary DNA-modified silver nanoparticles carrying 4-mercaptobenzonitrile(4-MBN)(Ag@4-MBN@Ag-c-DNA)as the SERS signal probe for the indirect detection of histamine.Under an applied magnetic field in the absence of histamine,the assembly gave an intense Raman signal at“Raman biological-silent”region due to 4-MBN.In the presence of histamine,the Ag@4-MBN@Ag-c-DNA SERS-tag was released from the Fe_(3)O_(4)@Au MNPs,thus decreasing the SERS signal.Under optimal conditions,an ultra-low limit of detection of 0.65×10^(-3)ng/mL and a linear range 10^(-2)-10^5 ng/mL on the SERS aptasensor were obtained.The histamine content in four food samples were analyzed using the SERS aptasensor,with the results consistent with those determined by high performance liquid chromatography.The present work highlights the merits of indirect strategies for the ultrasensitive and highly selective SERS detection of small biological molecules in complex matrices.

The Jiao Tong University Spectroscopic Telescope Project

The Jiao Tong University Spectroscopic Telescope(JUST)is a 4.4-meter f/6.0 segmented-mirror telescope dedicated to spectroscopic observations.The JUST primary mirror is composed of 18 hexagonal segments,each with a diameter of 1.1 m.JUST provides two Nasmyth platforms for placing science instruments.One Nasmyth focus fits a field of view of 10′and the other has an extended field of view of 1.2°with correction optics.A tertiary mirror is used to switch between the two Nasmyth foci.JUST will be installed at a site at Lenghu in Qinghai Province,China,and will conduct spectroscopic observations with three types of instruments to explore the dark universe,trace the dynamic universe,and search for exoplanets:(1)a multi-fiber(2000 fibers)medium-resolution spectrometer(R=4000-5000)to spectroscopically map galaxies and large-scale structure;(2)an integral field unit(IFU)array of 500 optical fibers and/or a long-slit spectrograph dedicated to fast follow-ups of transient sources for multi-messenger astronomy;(3)a high-resolution spectrometer(R~100000)designed to identify Jupiter analogs and Earth-like planets,with the capability to characterize the atmospheres of hot exoplanets.

Improving innovation and entrepreneurship education in higher institutions: the impact of "Mass Entrepreneurship and Innovation" education on undergraduates' entrepreneurial intentions

The exploration of the way"mass entrepreneurship and innovation"(MEI)education influences students'aspirations to become entrepreneurs has grown into an important area of analysis in studies related to higher education.This research intends to examine the consequences of MEI education on students'tendency towards entrepreneurship,and to put forward methods for augmenting the teaching of innovation and entrepreneurship in private higher educational establishments.To achieve this objective,questionnaires and semi-structured interviews were employed in the study,which involved a total of 197 students and five education experts.The statistical analysis of the questionnaire data revealed that MEI education was positively related to students'entrepreneurial intentions,and that both entrepreneurial experience and family entrepreneurial background played moderating roles in this relationship.The interview findings indicated that private universities could enhance educational reforms by designing talent training programs,developing diversified curricula,and developing more professional entrepreneurial platforms to encourage students'entrepreneurial intentions.This study offers fresh insights for improving and perfecting the mechanism of innovation and entrepreneurship education in private universities.

Single-atom catalysts supported on graphene/electride heterostructures for the enhanced sulfur reduction reaction in lithium-sulfur batteries

Single-atom catalysts(SACs)hold great promise in addressing the sluggish kinetics of the sulfur reduction reaction(SRR)in lithium-sulfur(Li-S)batteries for their unique catalytic activity and maximum atom efficiency.While these SACs must be dispersed on solid substrates,the underlying support is usually limited to carbon materials that have a poor ability to modulate the coordination environment and electronic structures of single atoms,and consequently their catalytic activity toward the SRR is restricted.Here we propose two-dimensional(2D)graphene/electride heterostructu res as substrates to enhance the catalytic activities of SACs for Li-S batteries.2D electrides featuring the anionic electron gas on their surface enable efficient electron transfer to SACs,which alters their electronic structures,resulting in the shifts of the d orbital and Fermi levels.This unique electronic structure decreases the filling of antibonding states such that the bonding with adsorbates at active sites is enhanced.We demonstrate the enhanced catalytic performance of SACs in terms of the Gibbs free energy of SRR and Li_(2)S dissociation.In addition,a universal descriptor for the rapid screening of SACs is established by a linear regression fitting method.This work provides a new design strategy to modulate SAC activity through electrides for Li-S batteries.

Floquet spectrum and universal dynamics of a periodically driven two-atom system

We investigate the Floquet spectrum and excitation properties of a two-ultracold-atom system with periodically driven interaction in a three-dimensional harmonic trap.The interaction between the atoms is changed by varying the s-wave scattering length in two ways,the cosine and the square-wave modulations.It is found that as the driving frequency increases,the Floquet spectrum exhibits two main features for both modulations,the accumulating and the spreading of the quasienergy levels,which further lead to different dynamical behaviors.The accumulation is associated with collective excitations and the persistent growth of the energy,while the spread indicates that the energy is bounded at all times.The initial scattering length,the driving frequency and amplitude can all significantly change the Floquet spectrum as well as the dynamics.However,the corresponding relation between them is valid universally.Finally,we propose a mechanism for selectively exciting the system to one specific state by using the avoided crossing of two quasienergy levels,which could guide preparation of a desired state in experiments.

Unprecedented JWST Observations Contest Cosmological Canons

After more than 18 months of nearly flawless operation,the James Webb Space Telescope(JWST)continues to deliver amazement,making unexpected discoveries,adding new wrinkles to known phenomena,and calling into question long-held theories of how the universe works.“The instruments are working amazingly well,in essentially all cases better than expected,”said Garth Illingworth,professor emeritus of astronomy and astrophysics at the University of California,Santa Cruz(CA,USA),and one of the three originators of the mission over three decades ago.“It has exceeded every one of its performance requirements,which is truly amazing when you think about how complex it is.”That complexity has included three decades of planning,design,and construction,followed by launch and maneuvering 1.5106 km from Earth to its second Lagrange(L2)orbit,unfolding and locking into position the 18 segments of its 6.5 m diameter main mirror,and deploying 8 motors,90 cables,and some 400 pulleys to unfurl its fragile sunshield[1,2].

Statistical Properties and Cosmological Applications of Fast Radio Bursts

Fast radio burst(FRB)is a type of extragalactic radio signal characterized by millisecond duration,extremely high brightness temperature,and large dispersion measure.It remains a mystery in the universe.Advancements in instrumentation have led to the discovery of 816 FRB sources and 7622 bursts from 67 repeating FRBs(https://blinkverse.alkaidos.cn/).This field is undergoing rapid development,rapidly advancing our understanding of the physics of FRBs as new observational data accumulates.The accumulation of data has also promoted exploration of our universe.In this review,we summarize the statistical analysis and cosmological applications using large samples of FRBs,including the energy functions,the waiting time distributions of repeating FRBs,probe of missing baryons and circumgalactic medium in the universe,measurements of cosmological parameters,exploration of the epoch of re-ionization history,and research of the gravitational lensing of FRBs.

A general synthetic strategy for N, P co-doped graphene supported metal-rich noble metal phosphides for hydrogen generation

The exploitation of electrocatalysts with high activity and durability for HER is desirable for future energy systems,but it is still a challenge.NMPs have attracted increasing attentions,but the preparation process often needs toxic regents or dangerous reaction conditions.Herein,we develop a general green method to fabricate metal-rich NMPs anchored on NPG through pyrolyzing DNA cross-linked complexes.The obtained Ru_(2) P-NPG exhibits an ultrasmall overpotential of 7 mV at 10 mA cm^(2) and ultralow Tafel slope of 33 mV dec^(-1) in 1.0 mol L?1 KOH,even better than that of commercial Pt/C.In addition,Ru 2 P-NPG also shows low overpotentials of 29 and 78 mV in 0.5 mol L^(-1) H_(2)SO_(4) and 1.0 mol L^(-1) PBS,respectively.The superior activity can be attributed to the ultrafine dispersion of Ru 2 P nanoparticles for more accessible sites,more defects formed for abundant active sites,the two-dimensional plane structure for accelerated electron transfer and mass transport,as well as the regulation of electron distribution of the catalyst.Moreover,the synthetic method can also be applied to prepare other metal-rich noble metal phosphides(Pd_(3)P-NPG and Rh_(2)P-NPG),which also exhibits high activity for HER.This work provides an effective strategy for designing NMP-based electrocatalysts.

Comparison of vergence mechanisms between university students with good and poor sleep quality

AIM:To compare the vergence mechanisms between good and poor sleepers in university students.METHODS:A total of 64 university students were recruited in this study.The validated Malay version of Pittsburgh Sleep Quality Index questionnaire(PSQI-M)was used to measure the participants’sleep quality over the past month.Participants were categorized as good sleepers(n=32)and poor sleepers(n=32)based on the PSQI-M scores.Heterophoria and fusional vergences were measured at distance and near.Mann-Whitney U test was used to compare heterophoria,negative fusional vergence(NFV),and positive fusional vergence(PFV)at distance and near between good and poor sleepers.Spearman correlation analysis was used to study the relationship between PSQI-M score and PFV at distance.RESULTS:Both distance and near heterophorias were not significantly different between good and poor sleepers(P>0.05).There was a difference in distance PFV(P<0.05)between good and poor sleepers,but not in distance NFV,near NFV,and near PFV(P>0.05).Distance PFV was negatively correlated with PSQI-M score(rs=-0.33,P<0.05).CONCLUSION:University students with poor sleep quality demonstrates a reduced ability to maintain fusion with increasing convergence demand at distance.Sleep quality assessment during binocular vision examination in university students is recommended.

Information Conductivity:Universal Performance Measure for Semantic Communications

As a novel paradigm,semantic communication provides an effective solution for breaking through the future development dilemma of classical communication systems.However,it remains an unsolved problem of how to measure the information transmission capability for a given semantic communication method and subsequently compare it with the classical communication method.In this paper,we first present a review of the semantic communication system,including its system model and the two typical coding and transmission methods for its implementations.To address the unsolved issue of the information transmission capability measure for semantic communication methods,we propose a new universal performance measure called Information Conductivity.We provide the definition and the physical significance to state its effectiveness in representing the information transmission capabilities of the semantic communication systems and present elaborations including its measure methods,degrees of freedom,and progressive analysis.Experimental results in image transmission scenarios validate its practical applicability.

Enhanced Temporal Correlation for Universal Lesion Detection

Universal lesion detection(ULD)methods for computed tomography(CT)images play a vital role in the modern clinical medicine and intelligent automation.It is well known that single 2D CT slices lack spatial-temporal characteristics and contextual information compared to 3D CT blocks.However,3D CT blocks necessitate significantly higher hardware resources during the learning phase.Therefore,efficiently exploiting temporal correlation and spatial-temporal features of 2D CT slices is crucial for ULD tasks.In this paper,we propose a ULD network with the enhanced temporal correlation for this purpose,named TCE-Net.The designed TCE module is applied to enrich the discriminate feature representation of multiple sequential CT slices.Besides,we employ multi-scale feature maps to facilitate the localization and detection of lesions in various sizes.Extensive experiments are conducted on the DeepLesion benchmark demonstrate that thismethod achieves 66.84%and 78.18%for FS@0.5 and FS@1.0,respectively,outperforming compared state-of-the-art methods.

A New Double Layer Multi-Secret Sharing Scheme

Cryptography is deemed to be the optimum strategy to secure the data privacy in which the data is encoded ahead of time before sharing it.Visual Secret Sharing(VSS)is an encryption method in which the secret message is split into at least two trivial images called’shares’to cover it.However,such message are always targeted by hackers or dishonest members who attempt to decrypt the message.This can be avoided by not uncovering the secret message without the universal share when it is presented and is typically taken care of,by the trusted party.Hence,in this paper,an optimal and secure double-layered secret image sharing scheme is proposed.The proposed share creation process contains two layers such as threshold-based secret sharing in the first layer and universal share based secret sharing in the second layer.In first layer,Genetic Algorithm(GA)is applied to find the optimal threshold value based on the randomness of the created shares.Then,in the second layer,a novel design of universal share-based secret share creation method is proposed.Finally,Opposition Whale Optimization Algorithm(OWOA)-based optimal key was generated for rectange block cipher to secure each share.This helped in producing high quality reconstruction images.The researcher achieved average experimental outcomes in terms of PSNR and MSE values equal to 55.154225 and 0.79365625 respectively.The average PSNRwas less(49.134475)and average MSE was high(1)in case of existing methods.

Detection Algorithm of Laboratory Personnel Irregularities Based on Improved YOLOv7

Due to the complex environment of the university laboratory,personnel flow intensive,personnel irregular behavior is easy to cause security risks.Monitoring using mainstream detection algorithms suffers from low detection accuracy and slow speed.Therefore,the current management of personnel behavior mainly relies on institutional constraints,education and training,on-site supervision,etc.,which is time-consuming and ineffective.Given the above situation,this paper proposes an improved You Only Look Once version 7(YOLOv7)to achieve the purpose of quickly detecting irregular behaviors of laboratory personnel while ensuring high detection accuracy.First,to better capture the shape features of the target,deformable convolutional networks(DCN)is used in the backbone part of the model to replace the traditional convolution to improve the detection accuracy and speed.Second,to enhance the extraction of important features and suppress useless features,this paper proposes a new convolutional block attention module_efficient channel attention(CBAM_E)for embedding the neck network to improve the model’s ability to extract features from complex scenes.Finally,to reduce the influence of angle factor and bounding box regression accuracy,this paper proposes a newα-SCYLLA intersection over union(α-SIoU)instead of the complete intersection over union(CIoU),which improves the regression accuracy while increasing the convergence speed.Comparison experiments on public and homemade datasets show that the improved algorithm outperforms the original algorithm in all evaluation indexes,with an increase of 2.92%in the precision rate,4.14%in the recall rate,0.0356 in the weighted harmonic mean,3.60%in the mAP@0.5 value,and a reduction in the number of parameters and complexity.Compared with the mainstream algorithm,the improved algorithm has higher detection accuracy,faster convergence speed,and better actual recognition effect,indicating the effectiveness of the improved algorithm in this paper and its potential for practical application in laboratory scenarios.

Extensive numerical simulations on competitive growth between the Edwards–Wilkinson and Kardar–Parisi–Zhang universality classes

Extensive numerical simulations and scaling analysis are performed to investigate competitive growth between the linear and nonlinear stochastic dynamic growth systems, which belong to the Edwards–Wilkinson(EW) and Kardar–Parisi–Zhang(KPZ) universality classes, respectively. The linear growth systems include the EW equation and the model of random deposition with surface relaxation(RDSR), the nonlinear growth systems involve the KPZ equation and typical discrete models including ballistic deposition(BD), etching, and restricted solid on solid(RSOS). The scaling exponents are obtained in both the(1 + 1)-and(2 + 1)-dimensional competitive growth with the nonlinear growth probability p and the linear proportion 1-p. Our results show that, when p changes from 0 to 1, there exist non-trivial crossover effects from EW to KPZ universality classes based on different competitive growth rules. Furthermore, the growth rate and the porosity are also estimated within various linear and nonlinear growths of cooperation and competition.

Investigating the Evolution of Amati Parameters with Redshift

Gamma-ray bursts(GRBs) are among the brightest objects in the Universe and, hence, can be observed up to a very high redshift. Properly calibrated empirical correlations between intensity and spectral correlations of GRBs can be used to estimate the cosmological parameters. However, the possibility of the evolution of GRBs with redshift is a long-standing puzzle. In this work, we used 162 long-duration GRBs to determine whether GRBs below and above a certain redshift have different properties. The GRBs are split into two groups, and we fit the Amati relation for each group separately. Our findings demonstrate that estimations of the Amati parameters for the two groups are substantially dissimilar. We perform simulations to investigate whether the selection effects could cause the difference. Our analysis shows that the differences may be either intrinsic or due to systematic errors in the data, and the selection effects are not their true origin. However, in-depth analysis with a new data set comprised of 119 long GRBs shows that intrinsic scatter may partly be responsible for such effects.

Short-term displacement prediction for newly established monitoring slopes based on transfer learning

This study makes a significant progress in addressing the challenges of short-term slope displacement prediction in the Universal Landslide Monitoring Program,an unprecedented disaster mitigation program in China,where lots of newly established monitoring slopes lack sufficient historical deformation data,making it difficult to extract deformation patterns and provide effective predictions which plays a crucial role in the early warning and forecasting of landslide hazards.A slope displacement prediction method based on transfer learning is therefore proposed.Initially,the method transfers the deformation patterns learned from slopes with relatively rich deformation data by a pre-trained model based on a multi-slope integrated dataset to newly established monitoring slopes with limited or even no useful data,thus enabling rapid and efficient predictions for these slopes.Subsequently,as time goes on and monitoring data accumulates,fine-tuning of the pre-trained model for individual slopes can further improve prediction accuracy,enabling continuous optimization of prediction results.A case study indicates that,after being trained on a multi-slope integrated dataset,the TCN-Transformer model can efficiently serve as a pretrained model for displacement prediction at newly established monitoring slopes.The three-day average RMSE is significantly reduced by 34.6%compared to models trained only on individual slope data,and it also successfully predicts the majority of deformation peaks.The fine-tuned model based on accumulated data on the target newly established monitoring slope further reduced the three-day RMSE by 37.2%,demonstrating a considerable predictive accuracy.In conclusion,taking advantage of transfer learning,the proposed slope displacement prediction method effectively utilizes the available data,which enables the rapid deployment and continual refinement of displacement predictions on newly established monitoring slopes.

IOL Master 700与Lenstar LS900对高度近视合并白内障患者术前生物测量及人工晶状体计算的比较

目的:比较IOL Master 700与Lenstar LS900对高度近视合并白内障患者术前眼生物测量的差异性、相关性、一致性及人工晶状体(IOL)度数计算的准确性。方法:回顾性研究。收集2021-03/2023-03于陆军特色医学中心眼科行白内障超声乳化联合IOL植入手术的高度近视合并白内障患者136例136眼,平均年龄57.38±8.08岁。根据眼轴长度(AL)将患者分为3组:A组(26 mm≤AL≤28 mm)41眼,B组(28 mm30 mm)52眼。术前分别使用两种仪器测量AL、平均角膜曲率(Km)、前房深度(ACD)、晶状体厚度(LT)和白到白距离(WTW)。所有患者均采用Barrett UniversalⅡ公式计算IOL度数,个性化选择适宜的预留屈光度,比较两种仪器的预测屈光误差(PE)和绝对屈光误差(AE)。结果:三组患者中Lenstar LS900测量的AL和ACD均大于IOL Master 700测量值(均P<0.05),且两种仪器测量AL的平均差值C组>B组>A组。两种仪器测量LT、Km与WTW值均无差异(均P>0.05)。两种仪器所得各组生物参数均具有正相关性(均r>0.9,P<0.05)且一致性较好(95%LoA范围较窄)。两种仪器计算的AE无差异(P>0.05),但IOL Master 700计算的PE小于Lenstar LS900(P<0.05),且前者远视偏移百分比更低。结论:在高度近视合并白内障患者中,Lenstar LS900测量AL值大于IOL Master 700,且该差异随着AL的增加而增大,两种仪器对IOL的计算均具有良好的预测性,但IOL Master 700术后屈光误差更小,远视偏移百分比更低。