Extention of Time Limit Mandated by SIPO(as basically limited to one extention and for two months at most)

The State Intellectual Poperty Office has announcedan amendment to Sec.5,Paragrph 4.2.of Chapter 7 ofExamination Guidelines.According to the newregulations,for making a respon to an office actionduring the prosecution of a patent application,only a firstrequest for a two-month extension of time can be basicallyallowed upon payment of official fee of RMB300(aboutUSD36).For further extension after the first one,onlyanother request for one or two months,at most twomonths,would be possibly petitioned together with a copyof the client’s instructions of the further extension and

Lateral earth pressure of granular backfills on retaining walls with expanded polystyrene geofoam inclusions under limited surcharge loading

Existing studies have focused on the behavior of the retaining wall equipped with expanded polystyrene(EPS)geofoam inclusions under semi-infinite surcharge loading rather than limited surcharge loading.In this paper,the failure mode and the earth pressure acting on the rigid retaining wall with EPS geofoam inclusions and granular backfills(henceforth referred to as EPS-wall),under limited surcharge loading are investigated through two-and three-dimensional model tests.The testing results show that different from the sliding of almost all the backfill in the EPS-wall under semi-infinite surcharge loading,only an approximately triangular backfill slides in the wall under limited surcharge loading.The distribution of the lateral earth pressure on the EPS-wall under limited surcharge loading is non-linear,and the distribution changes from the increase of the wall depth to the decrease with the increase of the limited surcharge loading.An approach based on the force equilibrium of a differential element is developed to predict the lateral earth pressure behind the EPS-wall subjected to limited surcharge loading,and its performance was fully validated by the three-dimensional model tests.

Access to novel anti-diabetic agents in resource limited settings:A brief commentary

The prevalence of diabetes mellitus is increasing in resource limited settings.Simultaneously,there has been an increase in the number of novel therapies for the management of diabetes mellitus.However,use of novel antidiabetic therapies is limited because of major market access challenges in resource limited settings.Niching products to those patients with the highest absolute risk for major adverse cardiovascular outcomes,and thus most likely to benefit from the therapy,are less likely to have negative budget impact for funders.To improve access,and reduce morbidity and mortality,requires alignment amongst key stakeholders including patient advocacy groups,health care professional councils,national departments of health,the pharmaceutical industry,treasury and finance departments.

Performance Limits and Advancements in Single 2D Transition Metal Dichalcogenide Transistor

Two-dimensional(2D)transition metal dichalcogenides(TMDs)allow for atomic-scale manipulation,challenging the conventional limitations of semiconductor materials.This capability may overcome the short-channel effect,sparking significant advancements in electronic devices that utilize 2D TMDs.Exploring the dimension and performance limits of transistors based on 2D TMDs has gained substantial importance.This review provides a comprehensive investigation into these limits of the single 2D-TMD transistor.It delves into the impacts of miniaturization,including the reduction of channel length,gate length,source/drain contact length,and dielectric thickness on transistor operation and performance.In addition,this review provides a detailed analysis of performance parameters such as source/drain contact resistance,subthreshold swing,hysteresis loop,carrier mobility,on/off ratio,and the development of p-type and single logic transistors.This review details the two logical expressions of the single 2D-TMD logic transistor,including current and voltage.It also emphasizes the role of 2D TMD-based transistors as memory devices,focusing on enhancing memory operation speed,endurance,data retention,and extinction ratio,as well as reducing energy consumption in memory devices functioning as artificial synapses.This review demonstrates the two calculating methods for dynamic energy consumption of 2D synaptic devices.This review not only summarizes the current state of the art in this field but also highlights potential future research directions and applications.It underscores the anticipated challenges,opportunities,and potential solutions in navigating the dimension and performance boundaries of 2D transistors.

A Stroke-Limitation AMD Control System with Variable Gain and Limited Area for High-Rise Buildings

Collisions between a moving mass and an anti-collision device increase structural responses and threaten structural safety.An active mass damper(AMD)with stroke limitations is often used to avoid collisions.However,a strokelimited AMD control system with a fixed limited area shortens the available AMD stroke and leads to significant control power.To solve this problem,the design approach with variable gain and limited area(VGLA)is proposed in this study.First,the boundary of variable-limited areas is calculated based on the real-time status of the moving mass.The variable gain(VG)expression at the variable limited area is deduced by considering the saturation of AMD stroke.Then,numerical simulations of a stroke-limited AMD control system with VGLA are conducted on a high-rise building structure.These numerical simulations show that the proposed approach has superior strokelimitation performance compared with a stroke-limited AMD control system with a fixed limited area.Finally,the proposed approach is validated through experiments on a four-story steel frame.

Exploring device physics of perovskite solar cell via machine learning with limited samples

Perovskite solar cells(PsCs)have developed tremendously over the past decade.However,the key factors influencing the power conversion efficiency(PCE)of PSCs remain incompletely understood,due to the complexity and coupling of these structural and compositional parameters.In this research,we demon-strate an effective approach to optimize PSCs performance via machine learning(ML).To address chal-lenges posed by limited samples,we propose a feature mask(FM)method,which augments training samples through feature transformation rather than synthetic data.Using this approach,squeeze-and-excitation residual network(SEResNet)model achieves an accuracy with a root-mean-square-error(RMSE)of 0.833%and a Pearson's correlation coefficient(r)of 0.980.Furthermore,we employ the permu-tation importance(PI)algorithm to investigate key features for PCE.Subsequently,we predict PCE through high-throughput screenings,in which we study the relationship between PCE and chemical com-positions.After that,we conduct experiments to validate the consistency between predicted results by ML and experimental results.In this work,ML demonstrates the capability to predict device performance,extract key parameters from complex systems,and accelerate the transition from laboratory findings to commercialapplications.

Charge transport properties and variable photo-switching of three-terminal Cs_(2)AgBiBr_(6)device

In this study,we present an in-depth exploration of charge transport phenomena and variable photo-switching characteristics in a novel double-perovskite-based three-terminal device.The Cs_(2)AgBiBr_(6)thin film(TF)was synthesized through a three-step thermal evaporation process followed by precise open-air annealing,ensuring superior film quality as confirmed by structural and morphological characterizations.Photoluminescence spectroscopy revealed distinct emissions at 2.28 and 2.07 eV,indicative of both direct and indirect electronic transitions.Our device exhibited space-charge limited current(SCLC)behaviour beyond 0.35 V,aligning with the relationship Current(I)∝Voltage(V)^(m),where the exponent m transitioned from≤1 to>1.Detailed analysis of Schottky parameters within the trap-filled limit(TFL)regime was conducted,accounting for variations in temperature and optical power.Significantly,the self-powered photodetector demonstrated outstanding performance under illumination.The sensitivity of the device was finely tunable via the applied bias voltages at the third terminal.Notably,an optimal bias voltage of±100μV yielded maximum responsivity(R)of 0.48 A/W and an impressive detectivity(D*)of 1.07×10^(9)Jones,highlighting the potential of this double-perovskite-based device for advanced optoelectronic applications.

Data-driven methods for predicting the representative temperature of bridge cable based on limited measured data

Cable-stayed bridges have been widely used in high-speed railway infrastructure.The accurate determination of cable’s representative temperatures is vital during the intricate processes of design,construction,and maintenance of cable-stayed bridges.However,the representative temperatures of stayed cables are not specified in the existing design codes.To address this issue,this study investigates the distribution of the cable temperature and determinates its representative temperature.First,an experimental investigation,spanning over a period of one year,was carried out near the bridge site to obtain the temperature data.According to the statistical analysis of the measured data,it reveals that the temperature distribution is generally uniform along the cable cross-section without significant temperature gradient.Then,based on the limited data,the Monte Carlo,the gradient boosted regression trees(GBRT),and univariate linear regression(ULR)methods are employed to predict the cable’s representative temperature throughout the service life.These methods effectively overcome the limitations of insufficient monitoring data and accurately predict the representative temperature of the cables.However,each method has its own advantages and limitations in terms of applicability and accuracy.A comprehensive evaluation of the performance of these methods is conducted,and practical recommendations are provided for their application.The proposed methods and representative temperatures provide a good basis for the operation and maintenance of in-service long-span cable-stayed bridges.

Supplementary Information to“Balancing the quantum speed limit and instantaneous energy cost in adiabatic quantum evolution”

I.SUPPLEMENTARY NOTE 1:THEORETICAL MATERIALS.The quantum speed limit(QSL)is essential for quantum computing and quantum communication,referring to the minimum time required for a quantum system to evolve from one state to another.Two well-known forms of the QSL are the Mandelstam-Tamm(MT)relation TqsL≥πh/2△E[S1]and the Margolus-Levitin(ML)relation TqsL≥πh/2(E)[S2]where Tqst is denoted as the QSL time,h is the reduced Planck's constant,△E is the energy uncertainty(standard deviation)of the system,and(E)is the average energy of the system above its ground state.Both of relations provide a lower bound on the evolution time.

Cosmology-Independent Photon Mass Limits from Localized Fast Radio Bursts by Using Artificial Neural Networks

A hypothetical photon mass m_(γ) can produce a frequency-dependent vacuum dispersion of light, which leads to an additional time delay between photons with different frequencies when they propagate through a fixed distance. The dispersion measure and redshift measurements of fast radio bursts(FRBs) have been widely used to constrain the rest mass of the photon. However, all current studies analyzed the effect of the frequency-dependent dispersion for massive photons in the standard ΛCDM cosmological context. In order to alleviate the circularity problem induced by the presumption of a specific cosmological model based on the fundamental postulate of the masslessness of photons, here we employ a new model-independent smoothing technique, artificial neural network(ANN), to reconstruct the Hubble parameter H(z) function from 34 cosmic-chronometer measurements.By combining observations of 32 well-localized FRBs and the H(z) function reconstructed by ANN, we obtain an upper limit of m_(γ) ≤ 3.5 × 10^(-51)kg, or equivalently m_(γ) ≤ 2.0 × 10^(-15)eV/c^(2)(m_(γ) ≤ 6.5 × 10^(-51)kg, or equivalently m_(γ) ≤ 3.6 × 10^(-15)eV/c_(2)) at the 1σ(2σ) confidence level. This is the first cosmology-independent photon mass limit derived from extragalactic sources.

Proteomic response of Phaeocystis globosa to nitrogen limitation

Phaeocystis globosa is an important unicellular eukaryotic alga that can also form colonies.P.globosa can cause massive harmful algal blooms and plays an important role in the global carbon or sulfur cycling.Thus far,the ecophysiology of P.globosa has been investigated by numerous studies.However,the proteomic response of P.globosa to nitrogen depletion remains largely unknown.We compared four protein preparation methods of P.globosa for two-dimensional electrophoresis(2-DE)(Urea/Triton X-100 with trichloroacetic acid(TCA)/acetone precipitation;TCA/acetone precipitation;Radio Immuno Precipitation Assay(RIPA)with TCA/acetone precipitation;and Tris buffer).Results show that the combination of RIPA with TCA/acetone precipitation had a clear gel background and showed the best protein spot separation effect,based on which the proteomic response to nitrogen depletion was studied using 2-DE.In addition,we identified six differentially expressed proteins whose relative abundance increased or decreased more than 1.5-fold(P<0.05).Most proteins could not be identified,which might be attributed to the lack of genomic sequences of P.globosa.Under nitrogen limitation,replication protein-like,RNA ligase,and sn-glycerol-3-phosphate dehydrogenase were reduced,which may decrease the DNA replication level and ATP production in P.globosa cells.The increase of endonucleaseⅢand transcriptional regulator enzyme may affect the metabolic and antioxidant function of P.globosa cells and induce cell apoptosis.These findings provide a basis for further proteomic study of P.globosa and the optimization of protein preparation methods of marine microalgae.

The impact of toroidal mode coupling on high-density discharges in J-TEXT

Density limit has long been a widely studied issue influencing the operating range of tokamaks.The rapid growth of the m/n=2/1(where m and n are poloidal and toroidal mode numbers,respectively)tearing mode is generally regarded as a primary precursor to the density limit disruption.In this experiment,the coupling of the m/n=1/1 mode and the m/n=2/1 mode in highdensity plasma was observed.During a sawtooth cycle,the frequencies of the two modes gradually converge until they become equal.After that,toroidal coupling occurs between the 1/1 and 2/1 modes,resulting in a mutually fixed phase relationship.With the occurrence of toroidal coupling,the 2/1 mode is stabilized.Prior to the disruption,the cessation of the 1/1 and 2/1 mode coupling,along with the rapid growth in the amplitude of the 2/1 mode,can be observed.Additionally,under the same parameters,comparing discharges with or without the 1/1 mode,it is found that the presence of the 1/1 mode leads to higher plasma density and temperature parameters.

Role of intravascular ultrasound and optical coherence tomography in intracoronary imaging for coronary artery disease:a systematic review

Coronary angiography has long been the standard for coronary imaging,but it has limitations in assessing vessel wall anatomy and guiding percutaneous coronary intervention(PCI).Intracoronary imaging techniques like intravascular ultrasound(IVUS)and optical coherence tomography(OCT)can overcome these limitations.IVUS uses ultrasound and OCT uses near-infrared light to visualize coronary pathology in unique ways due to differences in temporal and spatial resolution.These techniques have evolved to offer clinical utility in plaque characterization and vessel assessment during PCI.Meta-analyses and adjusted observational studies suggest that both IVUS and OCT-guided PCI correlate with reduced cardiovascular risks compared to angiographic guidance alone.While IVUS demonstrates consistent clinical outcome benefits,OCT evidence is less robust.IVUS has progressed from early motion detection to high-resolution systems,with smaller compatible catheters.OCT utilizes near infrared light to achieve unparalleled resolutions,but requires temporary blood clearance for optimal imaging.Enhanced visualization and guidance make IVUS and OCT well-suited for higher risk PCI in patients with diabetes and chronic kidney disease by allowing detailed visualization of complex lesions and ensuring optimal stent deployment and positioning in PCI for patients with type 2 diabetes and chronic kidney disease,improving outcomes.IVUS and recent advancements in zero-and low-contrast OCT techniques can reduce nephrotoxic contrast exposure,thus helping to minimize PCI complications in these high-risk patient groups.IVUS and OCT provide valuable insights into coronary pathophysiology and guide interventions precisely compared to angiography alone.Both have comparable clinical outcomes,emphasizing the need for tailored imaging choices based on clinical scenarios.Continued refinement and integration of intravascular imaging will likely play a pivotal role in optimizing coronary interventions and outcomes.This systematic review aims to delve into the nuances of IVUS and OCT,highlighting their strengths and limitations as PCI adjuncts.

STABILITY OF THE RAREFACTION WAVE IN THE SINGULAR LIMIT OF A SHARP INTERFACE PROBLEM FOR THE COMPRESSIBLE NAVIER-STOKES/ALLEN-CAHN SYSTEM

This paper is concerned with the global well-posedness of the solution to the compressible Navier-Stokes/Allen-Cahn system and its sharp interface limit in one-dimensional space.For the perturbations with small energy but possibly large oscillations of rarefaction wave solutions near phase separation,and where the strength of the initial phase field could be arbitrarily large,we prove that the solution of the Cauchy problem exists for all time,and converges to the centered rarefaction wave solution of the corresponding standard two-phase Euler equation as the viscosity and the thickness of the interface tend to zero.The proof is mainly based on a scaling argument and a basic energy method.

Effects of phosphorus limitation on sinking velocities of phytoplankton during summer in the Changjiang River Estuary

The sinking of phytoplankton is critical to organic matter transportation in the ocean and it is an essential process for the formation of coastal hypoxic zones.This study was based on a field investigation conducted during the summer of 2022 in the Changjiang River(Yangtze River) Estuary(CJE) and its adjacent waters.The settling column method was employed to measure the sinking velocity(SV) of different size fractions of phytoplankton at the surface of the sea and to analyze their environmental control mechanisms.The findings reveal significant spatial variation in phytoplankton SV(-0.55-2.41 m/d) within the CJE.High-speed sinking was predominantly observed in phosphate-depleted regions beyond the CJE front.At the same time,an upward trend was more commonly observed in the phosphate-rich regions near the CJE mouth.The SV ranges for different sizefractionated phytoplankton,including micro-(>20 μm),nano-(2-20 μm),and picophytoplankton(0.7-2 μm),were-0.50-4.74 m/d,-1.04-1.59 m/d,and-1.24-1.65 m/d,respectively.Correlation analysis revealed a significant negative correlation between SV and dissolved inorganic phosphorus(DIP),implying that the influence of DIP contributes to SV.The variations in phytoplankton alkaline phosphatase activity suggested a significant increase in SV across all size fractions in the event of phosphorus limitation.Phytoplankton communities with limited photo synthetic capacity(maximum photochemical efficience,Fv/Fm <0.3) were found to have higher SV than that of communities with strong capacity,suggesting a link between sinking and alterations in physiological conditions due to phosphate depletion.The findings from the in situ phosphate enrichment experiments confirmed a marked decrease in SV following phosphate supplementation.These findings suggest that phosphorus limitation is the primary driver of elevated SV in the CJE.This study enhances the comprehension of the potential mechanisms underlying hypoxic zone formation in the CJE,providing novel insights into how nearshore eutrophication influences organic carbon migration.

INCOMPRESSIBLE LIMIT OF IDEAL MAGNETOHYDRODYNAMICS IN A DOMAIN WITH BOUNDARIES

We study the incompressible limit of classical solutions to compressible ideal magneto-hydrodynamics in a domain with a flat boundary.The boundary condition is characteristic and the initial data is general.We first establish the uniform existence of classical solutions with respect to the Mach number.Then,we prove that the solutions converge to the solution of the incompressible MHD system.In particular,we obtain a stronger convergence result by using the dispersion of acoustic waves in the half space.

Influence of joint spacing and rock characteristics on the toppling stability of cut rock slope through a simplified limit equilibrium method

Toppling failure of rock mass/soil slope is an important geological and environmental problem.Clarifying its failure mechanism under different conditions has great significance in engineering.The toppling failure of a cutting slope occurred in a hydropower station in Kyushu,Japan illustrates that the joint characteristic played a significant role in the occurrence of rock slope tipping failure.Thus,in order to consider the mechanical properties of jointed rock mass and the influence of geometric conditions,a simplified analytical approach based on the limit equilibrium method for modeling the flexural toppling of cut rock slopes is proposed to consider the influence of the mechanical properties and geometry condition of jointed rock mass.The theoretical solution is compared with the numerical solution taking Kyushu Hydropower Station in Japan as one case,and it is found that the theoretical solution obtained by the simplified analysis method is consistent with the numerical analytical solution,thus verifying the accuracy of the simplified method.Meanwhile,the Goodman-Bray approach conventionally used in engineering practice is improved according to the analytical results.The results show that the allowable slope angle may be obtained by the improved Goodman-Bray approach considering the joint spacing,the joint frictional angle and the tensile strength of rock mass together.

Monolithic Convex Limiting for Legendre-Gauss-Lobatto Discontinuous Galerkin Spectral-Element Methods

We extend the monolithic convex limiting(MCL)methodology to nodal discontinuous Galerkin spectral-element methods(DGSEMS).The use of Legendre-Gauss-Lobatto(LGL)quadrature endows collocated DGSEM space discretizations of nonlinear hyperbolic problems with properties that greatly simplify the design of invariant domain-preserving high-resolution schemes.Compared to many other continuous and discontinuous Galerkin method variants,a particular advantage of the LGL spectral operator is the availability of a natural decomposition into a compatible subcellflux discretization.Representing a highorder spatial semi-discretization in terms of intermediate states,we performflux limiting in a manner that keeps these states and the results of Runge-Kutta stages in convex invariant domains.In addition,local bounds may be imposed on scalar quantities of interest.In contrast to limiting approaches based on predictor-corrector algorithms,our MCL procedure for LGL-DGSEM yields nonlinearflux approximations that are independent of the time-step size and can be further modified to enforce entropy stability.To demonstrate the robustness of MCL/DGSEM schemes for the compressible Euler equations,we run simulations for challenging setups featuring strong shocks,steep density gradients,and vortex dominatedflows.

Metabolic dysfunction-associated steatotic liver disease:The question of long-term high-normal alanine aminotransferase as a screening test

The growing prevalence of metabolic dysfunction-associated steatotic liver disease(MASLD)is being driven by the obesity epidemic.The quest for solutions continues particularly with regard to early detection.This editorial comments on the utility of long-term high-normal alanine aminotransferase(ALT)in screening for MASLD.Chen et al found that new onset MASLD can be detected by repetitively high normal ALT.Implicit in this concept is the question of what should be the accepted upper limit of normal(ULN)for ALT.It was previously set at 40 IU/L based on studies that included people with subclinical liver disease but the new consensus is 30/19 U/L in healthy males/females.Thus,when Chen et al defines the ULN as 40 U/L,others may view it as excessively high.It is important to recognize the variables affecting ULN e.g.instrumentation,diurnal variations,exercise and ageing.These variables matter when the distinctions are subtle e.g.normal vs high-normal.In this regard,the utility of long-term high normal ALT as a disease marker could be enhanced by combining it with other biomarkers,imaging and MASLD genetics to create machine learning classifiers.All in all,Chen et al’s work on long-term high normal ALT as a marker of new-onset MASLD deserves merit.

Developing a novel big dataset and a deep neural network to predict the bearing capacity of a ring footing

The accurate prediction of the bearing capacity of ring footings,which is crucial for civil engineering projects,has historically posed significant challenges.Previous research in this area has been constrained by considering only a limited number of parameters or utilizing relatively small datasets.To overcome these limitations,a comprehensive finite element limit analysis(FELA)was conducted to predict the bearing capacity of ring footings.The study considered a range of effective parameters,including clay undrained shear strength,heterogeneity factor of clay,soil friction angle of the sand layer,radius ratio of the ring footing,sand layer thickness,and the interface between the ring footing and the soil.An extensive dataset comprising 80,000 samples was assembled,exceeding the limitations of previous research.The availability of this dataset enabled more robust and statistically significant analyses and predictions of ring footing bearing capacity.In light of the time-intensive nature of gathering a substantial dataset,a customized deep neural network(DNN)was developed specifically to predict the bearing capacity of the dataset rapidly.Both computational and comparative results indicate that the proposed DNN(i.e.DNN-4)can accurately predict the bearing capacity of a soil with an R2 value greater than 0.99 and a mean squared error(MSE)below 0.009 in a fraction of 1 s,reflecting the effectiveness and efficiency of the proposed method.