Research on Practical Pathways of Strengthening Labor Education for College and University Students in the New Era

Labor education is an essential component of college and university education that can help students to develop a strong work ethic,acquire practical skills,and better understand the value of work.Strengthening labor education for college and university students is an urgent need of the high-quality development of the society and the internal requirement of promoting the all-round development of individuals.This study analyzes the importance of strengthening labor education for college and university students in the new era and proposes four practical pathways which draw on labor courses and campus activities,social practices,scientific research projects,and internships.After implementing these pathways,a survey of 967 students showed that students’understanding and awareness of labor was deepened,their hands-on skills and interests in science and labor practices were improved,and they became more cordially respectful to the working class.Taken together,the exploration and practice of these pathways helps college and university students to recognize their abilities,strengths,and interests,and guides them to form good labor habits that permeate all aspects of their studies and lives.

Transfer learning aided high-throughput computational design of oxygen evolution reaction catalysts in acid conditions

Sluggish oxygen evolution reaction(OER)in acid conditions is one of the bottlenecks that prevent the wide adoption of proton exchange membrane water electrolyzer for green hydrogen production.Despite recent advancements in developing high-performance catalysts for acid OER,the current electrocatalysts still rely on iridium-and ruthenium-based materials,urging continuous efforts to discover better performance catalysts as well as reduce the usage of noble metals.Pyrochlore structured oxide is a family of potential high-performance acid OER catalysts with a flexible compositional space to tune the electrochemical capabilities.However,exploring the large composition space of pyrochlore compounds demands an imperative approach to enable efficient screening.Here we present a highthroughput screening pipeline that integrates density functional theory calculations and a transfer learning approach to predict the critical properties of pyrochlore compounds.The high-throughput screening recommends three sets of candidates for potential acid OER applications,totaling 61 candidates from 6912 pyrochlore compounds.In addition to 3d-transition metals,p-block metals are identified as promising dopants to improve the catalytic activity of pyrochlore oxides.This work demonstrates not only an efficient approach for finding suitable pyrochlores towards acid OER but also suggests the great compositional flexibility of pyrochlore compounds to be considered as a new materials platform for a variety of applications.

Comprehensive integrated analysis of MR and DCE-MR radiomics models for prognostic prediction in nasopharyngeal carcinoma

Although prognostic prediction of nasopharyngeal carcinoma (NPC) remains a pivotal research area, the role of dynamic contrast-enhanced magnetic resonance (DCE-MR) has been less explored. This study aimed to investigate the role of DCR-MR in predicting progression-free survival (PFS) in patients with NPC using magnetic resonance (MR)- and DCE-MR-based radiomic models. A total of 434 patients with two MR scanning sequences were included. The MR- and DCE-MR-based radiomics models were developed based on 289 patients with only MR scanning sequences and 145 patients with four additional pharmacokinetic parameters (volume fraction of extravascular extracellular space (ve), volume fraction of plasma space (vp), volume transfer constant (Ktrans), and reverse reflux rate constant (kep) of DCE-MR. A combined model integrating MR and DCE-MR was constructed. Utilizing methods such as correlation analysis, least absolute shrinkage and selection operator regression, and multivariate Cox proportional hazards regression, we built the radiomics models. Finally, we calculated the net reclassification index and C-index to evaluate and compare the prognostic performance of the radiomics models. Kaplan-Meier survival curve analysis was performed to investigate the model’s ability to stratify risk in patients with NPC. The integration of MR and DCE-MR radiomic features significantly enhanced prognostic prediction performance compared to MR- and DCE-MR-based models, evidenced by a test set C-index of 0.808 vs 0.729 and 0.731, respectively. The combined radiomics model improved net reclassification by 22.9%-52.6% and could significantly stratify the risk levels of patients with NPC (p = 0.036). Furthermore, the MR-based radiomic feature maps achieved similar results to the DCE-MR pharmacokinetic parameters in terms of reflecting the underlying angiogenesis information in NPC. Compared to conventional MR-based radiomics models, the combined radiomics model integrating MR and DCE-MR showed promising results in delivering more accurate prognostic predictions and provided more clinical benefits in quantifying and monitoring phenotypic changes associated with NPC prognosis.

Research on Innovative Ways of Integrating Aesthetic Education with Ideological and Political Education in the New Era

Aesthetic education and ideological and political education undertake the educational responsibilities of educating people with beauty and cultivating people with morals,respectively.The innovation of aesthetic education and the reform of ideological and political education have common educational goals and target students.Integrating aesthetic education with ideological and political education can promote the overall healthy development of students,which has both historical and practical significance.In this paper,the importance and characteristics of integrating aesthetic education with ideological and political education in colleges and universities are analyzed from multiple dimensions,and four feasible ways of integrating aesthetic education with ideological and political education are proposed.The latter draws on extracurricular activities,emotional touch,a pleasant aesthetic atmosphere,and educational synergy to improve students’aesthetic literacy and cultivate correct ideological and political concepts among students.A survey of 1,047 students showed that the understanding and acceptance of ideological and political education were strengthened and improved after implementing these innovative integration ways.Taken together,the exploration and practice of these integration ways contribute to expanding the effect of ideological and political education in the new era and constitute important parts of the reform of college and university education in the new journey.

Random heterogeneous microstructure construction of composites via fractal geometry

The microstructures of a composite determine its macroscopic properties. In this study, microstructures with particles of arbitrary shapes and sizes are constructed by using several developed fractal geometry algorithms implemented in MATLAB. A two-dimensional (2D) quadrilateral fractal geometry algorithm is developed based on the modified Sierpinski carpet algorithm. Square-, rectangle-, circle-, and ellipse-based microstructure constructions are special cases of the 2D quadrilateral fractal geometry algorithm. Moreover, a three-dimensional (3D) random hexahedron geometry algorithm is developed according to the Menger sponge algorithm. Cube-and sphere-based mi-crostructure constructions are special cases of the 3D hexahedron fractal geometry algo-rithm. The polydispersities of fractal shapes and random fractal sub-units demonstrate significant enhancements compared to those obtained by the original algorithms. In ad-dition, the 2D and 3D algorithms mentioned in this article can be combined according to the actual microstructures. The verification results also demonstrate the practicability of these algorithms. The developed algorithms open up new avenues for the constructions of microstructures, which can be embedded into commercial finite element method soft-wares.

Insights into electrochemical CO_2 reduction on tin oxides from first-principles calculations

Density functional theory calculations were used to unravel the mechanism of CO_2 electroreduction on SnO_x surfaces. Under highly reducing conditions(<-0.6 V vs. RHE), the SnO(101) surface with oxygen vacancies is likely the active phase for CO_2 reduction. We showed that the proton-electron transfer to adsorbed *CO_2 forming *OCHO, a key intermediate for producing HCOOH, is energetically more favorable than the formation of *COOH, justifying the selectivity trends observed on Sn-based electrocatalysts. With linear scaling relations, we propose the free formation energy of *CO_2 at the oxygen vacancy as the reactivity descriptor. By engineering the strain of the SnO(101) surface, the selectivity towards HCOOH can be further optimized at reduced overpotentials.

METTL9-catalyzed histidine methylation of S100A9 suppresses the anti-Staphylococcus aureus activity of neutrophils

Dear Editor,Protein histidine methylation has been found to be a widespread post-translational modification(PTM)in mammalian cells and represents more than 13%of all protein methylation events in the human methylome(Ning et al.,2016;Kapell and Jakobsson,2021).Recently,we and other groups independently identified METTL9 as the first broad-specificity histidine N1 methyltransferase in mammals(Davydova et al.,2021;Lv et al.,2021).METTL9 methylates a variety of substrates with a common x-His-x-His motif(His is for histidine;the second x is preferably small amino acids:A/C/G/S)and catalyzes methyl transfer to the last histidine.

Associations between parental adherence to healthy lifestyles and cognitive performance in offspring:A prospective cohort study in China

Background:Previous studies have reported associations of specific maternal and paternal lifestyle factors with offspring’s cognitive development during early childhood.This study aimed to investigate the prospective associations between overall parental lifestyle and offspring’s cognitive performance during adolescence and young adulthood in China.Methods:We included 2531 adolescents aged 10-15 years at baseline in 2010 from the China Family Panel Studies.A healthy parental lifestyle score(ranged 0-5)was constructed based on the following five modifiable lifestyle factors:Smoking,drinking,exercise,sleep,and diet.Generalized estimating equation models were used to examine the association between baseline parental healthy lifestyle scores and offspring’s fluid and crystallized intelligence in subsequent years(2012,2014,2016,and 2018).Results:Offspring in the top tertile of parental healthy lifestyle scores performed better in overall fluid intelligence(multivariable-adjusted β=0.53,95%confidence interval[CI]:0.29-0.77)and overall crystallized intelligence(multivariable-adjusted β=0.35,95%CI:0.16-0.54)than those in the bottom tertile of parental healthy lifestyle scores.The results were similar after further adjustment for the offspring’s healthy lifestyle scores and persisted across the subgroups of parental socioeconomic status.Additionally,maternal and paternal healthy lifestyle scores were independently associated with better offspring’s cognitive performance,with significant contribution observed for paternal never-smoking,weekly exercise,and diversified diet.When both parents and offspring adhered to a healthier lifestyle,we observed the highest level of the offspring’s overall crystallized intelligence.Conclusions:Our study indicates that parental adherence to a healthier lifestyle is associated with significantly better offspring’s cognitive performance during adolescence and early adulthood,regardless of socioeconomic status.These findings highlight the potential cognitive benefits of promoting healthy lifestyles among parents of adolescents.

Biotransformation of 6:2 fluorotelomer sulfonate(6:2 FTS)in sulfur-rich media by Trametopsis cervina

Biotransformation of 6:2 fluorotelomer sulfonate(6:2 FTS)by two species of white-rot fungi,Pleurotus ostreatus(P.ostreatus)and Trametopsis cervina(T.cervina),was investigated in a sulfurrich medium designed to stimulate production of lignin-degrading enzymes.Degradation of 6:2 FTS was observed by T.cervina over the study period of 30 d,but not by P.ostreatus.Biotransformation rates were comparable to those found in other studies investigating mixed culture degradation in nonsulfur limiting media,with approximately 50 mol%of applied 6:2 FTS removed after 30 d.Stable transformation products were short-chain perfluorocarboxylic acids(PFCAs),including PFHxA(2.27 mol%),PFPeA(0.24 mol%),and PFBA(0.28 mol%).The main intermediate products include 5:2 sFTOH(16.3 mol%)and 5:3 FTCA(2.99 mol%),while 6:2 FTCA,6:2 FTuCA,and 5:2 ketone were also identified at low levels.Approximately 60 mol%of detected products were assigned to the major pathway to 5:2 ketone,and 40 mol%were assigned to the minor pathway to 5:3 FTCA.The overall molar balance was found to decrease to 75 mol%by Day 30,however,was closed to near 95 mol%with a theoretical estimation for the volatile intermediates in the headspace,5:2 ketone and 5:2 sFTOH.The different capabilities of the two white-rot fungal species for 6:2 FTS biotransformation in sulfur-rich media suggest that the enzyme processes of T.cervina to de-sulfonate 6:2 FTS may be unrelated to sulfur metabolism.

A review of the application of digital identity in the Metaverse

The development of the internet has immensely expanded people’s social scope,which has necessitated the utilization of digital identity.In regard to social networks,the utilization of anonymity or pseudonyms increases the attractiveness of the network.Nevertheless,because online payments,online transactions,and online assets are becoming prevalent features,virtualization is gradually exhibiting highly negative impacts.With respect to the Metaverse,digital identity is potentially a key factor,which can influence the balance that affects the association between anonymity and pseudonyms.To enhance the contemporary scenario and to facilitate the potential utilization of digital identity,this study considers the application of digital identity in the Metaverse,and it utilizes the“Enterprise IA”miniature model(Morey et al.).With regard to the current debate on digital identity,we analyzed the most prominent topic;thus,we explored the application rules pertaining to digital identity.We propose that the Metaverse is primarily characterized by its ability to digitalize the physical world.Furthermore,with respect to digital identity,the power of ownership still represents the fundamental issue.Using technologies such as blockchain and privacy filters,we can not only alter the governance logic and methods,but we can also balance the correlation between private rights and public interests.Thus,to solve the burgeoning identity trust crisis,individual competition for identity authorization rights,and privacy problems that characterize the Metaverse,we explore novel governance approaches.

Satellite UV-Vis spectroscopy:implications for air quality trends and their driving forces in China during 2005-2017

Abundances of a range of air pollutants can be inferred from satellite UV-Vis spectroscopy measurements by using the unique absorption signatures of gas species.Here,we implemented several spectral fitting methods to retrieve tropospheric NO_(2),SO_(2),and HCHO from the ozone monitoring instrument(OMI),with radiative simulations providing necessary information on the interactions of scattered solar light within the atmosphere.We analyzed the spatial distribution and temporal trends of satellite-observed air pollutants over eastern China during 2005-2017,especially in heavily polluted regions.We found significant decreasing trends in NO_(2) and SO_(2) since 2011 over most regions,despite varying temporal features and turning points.In contrast,an overall increasing trend was identified for tropospheric HCHO over these regions in recent years.Furthermore,generalized additive models were implemented to understand the driving forces of air quality trends in China and assess the effectiveness of emission controls.Our results indicated that although meteorological parameters,such as wind,water vapor,solar radiation and temperature,mainly dominated the day-to-day and seasonal fluctuations in air pollutants,anthropogenic emissions played a unique role in the long-term variation in the ambient concentrations of NO_(2),SO_(2),and HCHO in the past 13 years.Generally,recent declines in NO_(2) and SO_(2) could be attributed to emission reductions due to effective air quality policies,and the opposite trends in HCHO may urge the need to control anthropogenic volatile organic compound(VOC)emissions.

Artificial intelligence in gastric cancer:applications and challenges

Gastric cancer(GC)is one of the most common malignant tumors with high mortality.Accurate diagnosis and treatment decisions for GC rely heavily on human experts’careful judgments on medical images.However,the improvement of the accuracy is hindered by imaging conditions,limited experience,objective criteria,and inter-observer discrepancies.Recently,the developments of machine learning,especially deep-learning algorithms,have been facilitating computers to extract more information from data automatically.Researchers are exploring the far-reaching applications of artificial intelligence(AI)in various clinical practices,including GC.Herein,we aim to provide a broad framework to summarize current research on AI in GC.In the screening of GC,AI can identify precancerous diseases and assist in early cancer detection with endoscopic examination and pathological confirmation.In the diagnosis of GC,AI can support tumor-node-metastasis(TNM)staging and subtype classification.For treatment decisions,AI can help with surgical margin determination and prognosis prediction.Meanwhile,current approaches are challenged by data scarcity and poor interpretability.To tackle these problems,more regulated data,unified processing procedures,and advanced algorithms are urgently needed to build more accurate and robust AI models for GC.

New FeNiCrMo(P, C, B) high-entropy bulk metallic glasses with unusual thermal stability and corrosion resistance

New Fe(20–35) Ni(20) Cr(20–30) Mo(5–15)(P(0.6) C(0.2) B(0.2))(20) bulk metallic glasses with excellent thermal stability,strength, and corrosion resistance have been developed through the high-entropy alloy design strategy.The high-entropy bulk metallic glasses(HE-BMGs) possess larger supercooled liquid regions of ~69 K,higher crystallization onset temperatures of ~852 K, larger undercoolings of ~109 K, and more sluggish crystallization process upon heating than the conventional metallic glass benefited from the high mixing entropy effect. The HE-BMGs also exhibit ultrahigh strength of ~3.4 GPa, Vickers hardness of ~1107,and superior corrosion resistance in acids and Na Cl solutions by formation of highly stable Cr-and Moenriched passive films. The new metal-metalloid HE-BMG system and exceptional properties give the alloys good promise for both scientific and engineering applications.

Towards seamless environmental prediction-development of Pan-Eurasian EXperiment(PEEX)modelling platform

The Pan-Eurasian Experiment Modelling Platform(PEEX-MP)is one of the key blocks of the PEEX Research Programme.The PEEX MP has more than 30 models and is directed towards seamless envir-onmental prediction.The main focus area is the Arctic-boreal regions and China.The models used in PEEX-MP cover several main components of the Earth’s system,such as the atmosphere,hydrosphere,pedosphere and biosphere,and resolve the physicalchemicalbiological processes at different spatial and temporal scales and resolutions.This paper introduces and discusses PEEX MP multi-scale modelling concept for the Earth system,online integrated,forward/inverse,and socioeconomical modelling,and other approaches with a particular focus on applications in the PEEX geographical domain.The employed high-performance com-puting facilities,capabilities,and PEEX dataflow for modelling results are described.Several virtual research platforms(PEEXView,Virtual Research Environment,Web-based Atlas)for handling PEEX modelling and observational results are introduced.The over-all approach allows us to understand better physical-chemicalbiological processes,Earth’s system interactions and feedbacks and to provide valuable information for assessment studies on evaluating risks,impact,consequences,etc.for population,envir-onment and climate in the PEEX domain.This work was also one of the last projects of Prof.Sergej Zilitinkevich,who passed away on 15 February 2021.Since the finalization took time,the paper was actually submitted in 2023 and we could not argue that the final paper text was agreed with him.