国家自然科学基金面上项目的遴选标准及其规范化探讨

同行评议的决策机制中,获取同行专家提供的评议意见很重要,管理者如何基于评议意见做出科学决策也同样不可忽视。国家自然科学基金项目管理者面对大量的项目,且每个项目包含有多个同行专家的评议意见,如何汇总项目的评议意见并从众多项目中优中选优开展项目遴选,倘若没有科学且可把握的遴选标准,遴选过程的不规范、不科学必然事实上将对获取的同行专家评议意见打折扣。因此,建立科学、规范的项目遴选标准,减少遴选过程中可能存在的随意性,避免其中人为因素干扰,是确保同行评议制度公正性的重要环节。

Evaluating the stability and volumetric flowback rate of proppant packs in hydraulic fractures using the lattice Boltzmann-discrete element coupling method

The stability and mobility of proppant packs in hydraulic fractures during hydrocarbon production are numerically investigated by the lattice Boltzmann-discrete element coupling method(LB-DEM).This study starts with a preliminary proppant settling test,from which a solid volume fraction of 0.575 is calibrated for the proppant pack in the fracture.In the established workflow to investigate proppant flowback,a displacement is applied to the fracture surfaces to compact the generated proppant pack as well as further mimicking proppant embedment under closure stress.When a pressure gradient is applied to drive the fluid-particle flow,a critical aperture-to-diameter ratio of 4 is observed,above which the proppant pack would collapse.The results also show that the volumetric proppant flowback rate increases quadratically with the fracture aperture,while a linear variation between the particle flux and the pressure gradient is exhibited for a fixed fracture aperture.The research outcome contributes towards an improved understanding of proppant flowback in hydraulic fractures,which also supports an optimised proppant size selection for hydraulic fracturing operations.

Hypoglycemic mechanism of Tegillarca granosa polysaccharides on type 2 diabetic mice by altering gut microbiota and regulating the PI3K-akt signaling pathwaye

Type 2 diabetes mellitus(T2DM)is a complex metabolic disease threatening human health.We investigated the effects of Tegillarca granosa polysaccharide(TGP)and determined its potential mechanisms in a mouse model of T2DM established through a high-fat diet and streptozotocin.TGP(5.1×10^(3) Da)was composed of mannose,glucosamine,rhamnose,glucuronic acid,galactosamine,glucose,galactose,xylose,and fucose.It could significantly alleviate weight loss,reduce fasting blood glucose levels,reverse dyslipidemia,reduce liver damage from oxidative stress,and improve insulin sensitivity.RT-PCR and Western blotting indicated that TGP could activate the phosphatidylinositol-3-kinase/protein kinase B signaling pathway to regulate disorders in glucolipid metabolism and improve insulin resistance.TGP increased the abundance of Allobaculum,Akkermansia,and Bifidobacterium,restored the microbiota abundance in the intestinal tracts of mice with T2DM,and promoted short-chain fatty acid production.This study provides new insights into the antidiabetic effects of TGP and highlights its potential as a natural hypoglycemic nutraceutical.

Cross-Dimension Attentive Feature Fusion Network for Unsupervised Time-Series Anomaly Detection

Time series anomaly detection is crucial in various industrial applications to identify unusual behaviors within the time series data.Due to the challenges associated with annotating anomaly events,time series reconstruction has become a prevalent approach for unsupervised anomaly detection.However,effectively learning representations and achieving accurate detection results remain challenging due to the intricate temporal patterns and dependencies in real-world time series.In this paper,we propose a cross-dimension attentive feature fusion network for time series anomaly detection,referred to as CAFFN.Specifically,a series and feature mixing block is introduced to learn representations in 1D space.Additionally,a fast Fourier transform is employed to convert the time series into 2D space,providing the capability for 2D feature extraction.Finally,a cross-dimension attentive feature fusion mechanism is designed that adaptively integrates features across different dimensions for anomaly detection.Experimental results on real-world time series datasets demonstrate that CAFFN performs better than other competing methods in time series anomaly detection.

科技支撑云南种业高质量创新发展的对策建议

种子是农业的“芯片”。2020年12月,中央经济工作会议将“解决好种子问题”列入八大重点任务之一,提出“要开展种源‘卡脖子’技术攻关,立志打一场种业翻身仗”。作为世界粮食生产大国,我国在育种技术领域创新能力明显不足,种业安全战略面临严峻挑战。本文在分析国内外作物育种技术发展历程、产业现状、技术热点及发展趋势的基础上,针对云南省作物育种现状及存在问题,研究提出了科技支撑云南种业高质量创新发展的相关建议。

Postnatal development of rat retina:a continuous observation and comparison between the organotypic retinal explant model and in vivo development

The organotypic retinal explant culture has been established for more than a decade and offers a range of unique advantages compared with in vivo experiments and cell cultures.However,the lack of systematic and continuous comparison between in vivo retinal development and the organotypic retinal explant culture makes this model controversial in postnatal retinal development studies.Thus,we aimed to verify the feasibility of using this model for postnatal retinal development studies by comparing it with the in vivo retina.In this study,we showed that postnatal retinal explants undergo normal development,and exhibit a consistent structure and timeline with retinas in vivo.Initially,we used SOX2 and PAX6 immunostaining to identify retinal progenitor cells.We then examined cell proliferation and migration by immunostaining with Ki-67 and doublecortin,respectively.Ki-67-and doublecortin-positive cells decreased in both in vivo and explants during postnatal retinogenesis,and exhibited a high degree of similarity in abundance and distribution between groups.Additionally,we used Ceh-10 homeodomain-containing homolog,glutamate-ammonia ligase(glutamine synthetase),neuronal nuclei,and ionized calcium-binding adapter molecule 1 immunostaining to examine the emergence of bipolar cells,Müller glia,mature neurons,and microglia,respectively.The timing and spatial patterns of the emergence of these cell types were remarkably consistent between in vivo and explant retinas.Our study showed that the organotypic retinal explant culture model had a high degree of consistency with the progression of in vivo early postnatal retina development.The findings confirm the accuracy and credibility of this model and support its use for long-term,systematic,and continuous observation.

Stability mechanism and control of the pumpable supports in longwall recovery room

The load-bearing performance(LBP)of pumpable supports(PPS)is crucial for the stability of longwall pre-driven recovery room(PRR)surrounding rock.However,the unbalanced bearing coefficient(UBC)of the PPS(undertaking unequal load along the mining direction)has not been investigated.A mechanical model of the PRR was established,considering the main roof cantilever beam structure,to derive an assessment formula for the load,the failure criteria,and the UBC of the PPS.Subsequently,the generation mechanisms,and influencing factors of the UBC were revealed.Global sensitivity analysis shows that the main roof hanging length(l_(2))and the spacing between the PPS(r)significantly impact the UBC.A novel design of the PPS and the coupling control technology were proposed and applied to reduce the UBC of the PPS in the adjacent longwall PRR.Monitor results showed no failure of the PPS at the test site,with the UBC(ζ)reduced to 1.1 consistent with the design value(1.15)basically,fully utilizing the collaborative LBP of the PPS.Finally,the maximum roof-to-floor convergence of the PRR was 234 mm,effectively controlling the stability of the surrounding rock of the PRR and ensuring the mining equipment recovery.

Efficient stabilization of dredged sludge with high water content using an improved bio-carbonation of reactive magnesia cement method

This study proposed an improved bio-carbonation of reactive magnesia cement(RMC)method for dredged sludge stabilization using the urea pre-hydrolysis strategy.Based on unconfined compression strength(UCS),pickling-drainage,and scanning electron microscopy(SEM)tests,the effects of prehydrolysis duration(T),urease activity(UA)and curing age(CA)on the mechanical properties and microstructural characteristics of bio-carbonized samples were systematically investigated and analyzed.The results demonstrated that the proposed method could significantly enhance urea hydrolysis and RMC bio-carbonation to achieve efficient stabilization of dredged sludge with 80%high water content.A significant strength increment of up to about 1063.36 kPa was obtained for the bio-carbonized samples after just 7 d of curing,which was 2.64 times higher than that of the 28-day cured ordinary Portland cement-reinforced samples.Both elevated T and UA could notably increase urea utilization ratio and carbonate ion yield,but the resulting surge in supersaturation also affected the precipitation patterns of hydrated magnesia carbonates(HMCs),which weakened the cementation effect of HMCs on soil particles and further inhibited strength enhancement of bio-carbonized samples.The optimum formula was determined to be the case of T?24 h and UA?10 U/mL for dredged sludge stabilization.A 7-day CA was enough for bio-carbonized samples to obtain stable strength,albeit slightly affected by UA.The benefits of high efficiency and water stability presented the potential of this method in achieving dredged sludge stabilization and resource utilization.This investigation provides informative ideas and valuable insights on implementing advanced bio-geotechnical techniques to achieve efficient stabilization of soft soil,such as dredged sludge.

A Two-Layer Encoding Learning Swarm Optimizer Based on Frequent Itemsets for Sparse Large-Scale Multi-Objective Optimization

Traditional large-scale multi-objective optimization algorithms(LSMOEAs)encounter difficulties when dealing with sparse large-scale multi-objective optimization problems(SLM-OPs)where most decision variables are zero.As a result,many algorithms use a two-layer encoding approach to optimize binary variable Mask and real variable Dec separately.Nevertheless,existing optimizers often focus on locating non-zero variable posi-tions to optimize the binary variables Mask.However,approxi-mating the sparse distribution of real Pareto optimal solutions does not necessarily mean that the objective function is optimized.In data mining,it is common to mine frequent itemsets appear-ing together in a dataset to reveal the correlation between data.Inspired by this,we propose a novel two-layer encoding learning swarm optimizer based on frequent itemsets(TELSO)to address these SLMOPs.TELSO mined the frequent terms of multiple particles with better target values to find mask combinations that can obtain better objective values for fast convergence.Experi-mental results on five real-world problems and eight benchmark sets demonstrate that TELSO outperforms existing state-of-the-art sparse large-scale multi-objective evolutionary algorithms(SLMOEAs)in terms of performance and convergence speed.

Learning to Branch in Combinatorial Optimization With Graph Pointer Networks

Traditional expert-designed branching rules in branch-and-bound(B&B) are static, often failing to adapt to diverse and evolving problem instances. Crafting these rules is labor-intensive, and may not scale well with complex problems.Given the frequent need to solve varied combinatorial optimization problems, leveraging statistical learning to auto-tune B&B algorithms for specific problem classes becomes attractive. This paper proposes a graph pointer network model to learn the branch rules. Graph features, global features and historical features are designated to represent the solver state. The graph neural network processes graph features, while the pointer mechanism assimilates the global and historical features to finally determine the variable on which to branch. The model is trained to imitate the expert strong branching rule by a tailored top-k Kullback-Leibler divergence loss function. Experiments on a series of benchmark problems demonstrate that the proposed approach significantly outperforms the widely used expert-designed branching rules. It also outperforms state-of-the-art machine-learning-based branch-and-bound methods in terms of solving speed and search tree size on all the test instances. In addition, the model can generalize to unseen instances and scale to larger instances.

Numerical simulation of melt flow and temperature field during DC casting 2024 aluminium alloy under different casting conditions

Casting speed,casting temperature and secondary cooling water flow rate are the main process parameters affecting the DC casting process.These parameters significantly influence the flow and temperature fields during casting,which are crucial for the quality of the ingot and can determine the success or failure of the casting operation.Numerical simulation,with the advantages of low cost,rapid execution,and visualized results,is an important method to study and optimize the DC casting process.In the present work,a simulation model of DC casting 2024 aluminum alloy was established,and the reliability of the model was verified.Then,the influence of casting parameters on flow field and temperature field was studied in detail by numerical simulation method.Results show that with the increase of casting speed,the melt flow becomes faster,the depths of slurry zone and mushy zone increase,and the variation of slurry zone depth is greater than that of mushy zone.With an increase in casting temperature,the melt flow rate increases,the depth of the slurry zone becomes shallower,and the depth of the mushy zone experiences only minor changes.The simulation results further indicate that the increase of the flow rate of the secondary cooling water slightly reduces the depths of both slurry and mushy zone.

Biomimetic Integrated Nanozyme for Flare and Recurrence of Gouty Arthritis

Flare and multiple recurrences pose significant challenges in gouty arthritis.Traditional treatments provide temporary relief from inflammation but fail to promptly alleviate patient pain or effectively prevent subsequent recurrences.It should also be noted that both anti-inflammation and metabolism of uric acid are necessary for gouty arthritis,calling for therapeutic systems to achieve these two goals simultaneously.In this study,we propose a biomimetic integrated nanozyme,HMPB-Pt@MM,comprising platinum nanozyme and hollow Prussian blue.It demonstrates anti-inflammatory properties by eliminating reactive oxygen species and reducing infiltration of inflammatory macrophages.Additionally,it rapidly targets inflamed ankles through the camouflage of macrophage membranes.Furthermore,HMPB-Pt@MM exhibits urate oxidase-like capabilities,continuously metabolizing locally elevated uric acid concentrations,ultimately inhibiting multiple recurrences of gouty arthritis.In summary,HMPB-Pt@MM integrates ROS clearance with uric acid metabolism,offering a promising platform for the treatment of gouty arthritis.

Understanding Bonding Nature of α-Keggin Polyoxometalates[XW_(12)O_(40)]^(n−)(X=Al,Si,P,S):A Generalized Superatomic Perspective

α-Keggin polyoxometalates(POMs)[XW_(12)O_(40)]^(n−)(X=Al,Si,P,S)are widely used in batteries owing to their remarkable redox activity.However,the mechanism underlying the applications appears inconsistent with the widely accepted covalent bonding nature.Here,first-principles calculations show that XW_(12)are core–shell structures composed of a shell and an XO_(4)^(n−)core,both are stabilized by covalent interactions.Interestingly,owing to the presence of a substantial number of electrons in W_(12)O_(36)shell,the frontier molecular orbitals of XW_(12)are not only strongly delocalized but also exhibit superatomic properties with high-angular momentum electrons that do not conform to the Jellium model.Detailed analysis indicates that energetically high lying filled molecular orbitals(MOs)have reached unusually high-angular momentum characterized by quantum number K or higher,allowing for the accommodation of numerous electrons.This attribute confers strong electron acceptor ability and redox activity to XW_(12).Moreover,electrons added to XW_(12)still occupy the K orbitals and will not cause rearrangement of the MOs,thereby maintaining the stability of these structures.Our findings highlight the structure–activity relationship and provide a direction for tailor-made POMs with specific properties at atomic level.

Washed microbiota transplantation for Crohn’s disease:A metagenomic,metatranscriptomic,and metabolomic-based study

BACKGROUND Fecal microbiota transplantation(FMT)is a promising therapeutic approach for treating Crohn’s disease(CD).The new method of FMT,based on the automatic washing process,was named as washed microbiota transplantation(WMT).Most existing studies have focused on observing the clinical phenomena.However,the mechanism of action of FMT for the effective management of CD-particularly in-depth multi-omics analysis involving the metagenome,metatranscriptome,and metabolome-has not yet been reported.AIM To assess the efficacy of WMT for CD and explore alterations in the microbiome and metabolome in response to WMT.METHODS We conducted a prospective,open-label,single-center clinical study.Eleven CD patients underwent WMT.Their clinical responses(defined as a decrease in their CD Activity Index score of>100 points)and their microbiome(metagenome,metatranscriptome)and metabolome profiles were evaluated three months after the procedure.RESULTS Seven of the 11 patients(63.6%)showed an optimal clinical response three months post-WMT.Gut microbiome diversity significantly increased after WMT,consistent with improved clinical symptoms.Comparison of the metagenome and metatranscriptome analyses revealed consistent alterations in certain strains,such as Faecalibac-terium prausnitzii,Roseburia intestinalis,and Escherichia coli.In addition,metabolomics analyses demonstrated that CD patients had elevated levels of various amino acids before treatment compared to the donors.However,levels of vital amino acids that may be associated with disease progression(e.g.,L-glutamic acid,gamma-glutamyl-leucine,and prolyl-glutamine)were reduced after WMT.CONCLUSION WMT demonstrated therapeutic efficacy in CD treatment,likely due to the effective reconstruction of the patient’s microbiome.Multi-omics techniques can effectively help decipher the potential mechanisms of WMT in treating CD.

Half-metallic ferromagneticWeyl fermions related to dynamic correlations in the zinc-blende compound VAs

The realization of 100%polarized topologicalWeyl fermions in half-metallic ferromagnets is of particular importance for fundamental research and spintronic applications.Here,we theoretically investigate the electronic and topological properties of the zinc-blende compound VAs,which was deemed as a half-metallic ferromagnet related to dynamic correlations.Based on the combination of density functional theory and dynamical mean field theory,we uncover that the half-metallic ferromagnet VAs exhibits attractive Weyl semimetallic behaviors which are very close to the Fermi level in the DFT+U regime with effect U values ranging from 1.5 eV to 2.5 eV.Meanwhile,we also investigate the magnetization-dependent topological properties;the results show that the change of magnetization directions only slightly affects the positions of Weyl points,which is attributed to the weak spin–orbital coupling effects.The topological surface states of VAs projected on semi-infinite(001)and(111)surfaces are investigated.The Fermi arcs of all Weyl points are clearly visible on the projected Fermi surfaces.Our findings suggest that VAs is a fully spin-polarized Weyl semimetal with many-body correlated effects in the effective U values range from 1.5 eV to 2.5 eV.

Deformation and mutual influence of two cylindrical water columns in tandem subjected to shock wave

The interaction between shock waves and multiple cylinders,referred to as shock–cylinder interaction(SCI),is an important phenomenon in science and engineering.However,its underlying physical mechanisms remain unclear.This study entailed the numerical simulation of the aerobreakup of two tandem water columns subjected to a high-speed gas flow by using an adaptive mesh refinement(AMR)-based diffusion-interface model.The objective was to elucidate the changes in water–column deformation patterns over a wide range of Weber numbers.Statistical analysis was performed to examine the deformation of the water columns in vertical directions.Results reveal distinct deformation patterns between the two columns as the Weber number increases.Additionally,an extended exponential stretching law model was devised,and its improved capability to predict the deformation patterns was demonstrated.

A combination of straw incorporation and polymer-coated urea offsets soil ammonia and nitrous oxide emissions in winter wheat fields

The combined effects of straw incorporation(SI)and polymer-coated urea(PCU)application on soil ammonia(NH_(3))and nitrous oxide(N_(2)O)emissions from agricultural fields have not been comprehensively evaluated in Northwest China.We conducted a two-year field experiment to assess the effects of combining SI with either uncoated urea(U)or PCU on soil NH_(3)emissions,N_(2)O emissions,winter wheat yields,yield-scaled NH_(3)(/NH_(3)),and yield-scaled N_(2)O(/N_(2)O).Five treatments were investigated,no nitrogen(N)fertilizer(N_(0)),U application at 150 kg N ha-1 with and without SI(SI+U and S_(0)+U),and PCU application at 150 kg N ha^(-1) with and without SI(SI+PCU and S_(0)+PCU).The results showed that the NH_(3);emissions increased by 20.98-34.35%following Sl compared to straw removal,mainly due to increases in soil ammonium(NH_(4)^(+)-N)content and water-flled pore space(WFPS).SI resulted in higher N_(2)O emissions than under the So scenario by 13.31-49.23%due to increases in soil inorganic N(SIN)contents,WFPS,and soil microbial biomass.In contrast,the PCU application reduced the SIN contents compared to the U application,reducing the NH_(3)and N_(2)O emissions by 45.99-58.07 and 18.08-53.04%,respectively.Moreover,no significant positive effects of the SI or PCU applications on the winter wheat yield were observed.The lowest /NH_(3) and /N_(2)O values were observed under the S_(0)+PCU and SI+PCU treatments.Our results suggest that single PCU applications and their combination with straw are the optimal agricultural strategies for mitigating gaseous N emissions and maintaining optimal winter wheat yields in Northwest China.

Design of pH-responsive antimicrobial peptide melittin analog-camptothecin conjugates for tumor therapy

Melittin,a classical antimicrobial peptide,is a highly potent antitumor agent.However,its significant toxicity seriously hampers its application in tumor therapy.In this study,we developed novel melittin analogs with pH-responsive,cell-penetrating and membranelytic activities by replacing arginine and lysine with histidine.After conjugation with camptothecin(CPT),CPT-AAM-1 and CPT-AAM-2 were capable of killing tumor cells by releasing CPT at low concentrations and disrupting cell membranes at high concentrations under acidic conditions.Notably,we found that the C-terminus of the melittin analogs was more suitable for drug conjugation than the N-terminus.CPT-AAM-1 significantly suppressed melanoma growth in vivo with relatively low toxicity.Collectively,the present study demonstrates that the development of antitumor drugs based on pH-responsive antimicrobial peptide-drug conjugates is a promising strategy.

使用深度学习在CTA扫描卷下实现主动脉夹层分类和直径测量的双功能系统

Acute aortic dissection is one of the most life-threatening cardiovascular diseases,with a high mortality rate.Its prevalence ranges from 0.2%to 0.8%in humans,resulting in a significant number of deaths due to being missed in manual examinations.More importantly,the aortic diameter—a critical indicator for surgical selection—significantly influences the outcomes of surgeries post-diagnosis.Therefore,it is an urgent yet challenging mission to develop an automatic aortic dissection diagnostic system that can recognize and classify the aortic dissection type and measure the aortic diameter.This paper offers a dual-functional deep learning system called aortic dissections diagnosis-aiding system(DDAsys)that enables both accurate classification of aortic dissection and precise diameter measurement of the aorta.To this end,we created a dataset containing 61190 computed tomography angiography(CTA)images from 279 patients from the Division of Cardiovascular Surgery at Tongji Hospital,Wuhan,China.The dataset provides a slice-level summary of difficult-to-identify features,which helps to improve the accuracy of both recognition and classification.Our system achieves a recognition F1 score of 0.984,an average classification F1 score of 0.935,and the respective measurement precisions for ascending and descending aortic diameters are 0.994 mm and 0.767 mm root mean square error(RMSE).The high consistency(88.6%)between the recommended surgical treatments and the actual corresponding surgeries verifies the capability of our system to aid clinicians in developing a more prompt,precise,and consistent treatment strategy.

Effect of temperature and time on the precipitation ofκ-carbides in Fe-28Mn-10Al-0.8C low-density steels:Aging mechanism and its impact on material properties

In low-density steel,κ-carbides primarily precipitate in the form of nanoscale particles within austenite grains.However,their precipitation within ferrite matrix grains has not been comprehensively explored,and the second-phase evolution mechanism during aging remains unclear.In this study,the crystallographic characteristics and morphological evolution ofκ-carbides in Fe-28Mn-10Al-0.8C(wt%)low-density steel at different aging temperatures and times and the impacts of these changes on the steels’microhardness and properties were comprehensively analyzed.Under different heat treatment conditions,intragranularκ-carbides exhibited various morpho-logical and crystallographic characteristics,such as acicular,spherical,and short rod-like shapes.At the initial stage of aging,acicularκ-carbides primarily precipitated,accompanied by a few spherical carbides.κ-Carbides grew and coarsened with aging time,the spherical carbides were considerably reduced,and rod-like carbides coarsened.Vickers hardness testing demonstrated that the material’s hardness was affected by the volume fraction,morphology,and size ofκ-carbides.Extended aging at higher temperatures led to an increase in carbide size and volume fraction,resulting in a gradual rise in hardness.During deformation,the primary mechanisms for strengthening were dislocation strengthening and second-phase strengthening.Based on these findings,potential strategies for improving material strength are proposed.