Correcting Climate Model Sea Surface Temperature Simulations with Generative Adversarial Networks:Climatology,Interannual Variability,and Extremes

Climate models are vital for understanding and projecting global climate change and its associated impacts.However,these models suffer from biases that limit their accuracy in historical simulations and the trustworthiness of future projections.Addressing these challenges requires addressing internal variability,hindering the direct alignment between model simulations and observations,and thwarting conventional supervised learning methods.Here,we employ an unsupervised Cycle-consistent Generative Adversarial Network(CycleGAN),to correct daily Sea Surface Temperature(SST)simulations from the Community Earth System Model 2(CESM2).Our results reveal that the CycleGAN not only corrects climatological biases but also improves the simulation of major dynamic modes including the El Niño-Southern Oscillation(ENSO)and the Indian Ocean Dipole mode,as well as SST extremes.Notably,it substantially corrects climatological SST biases,decreasing the globally averaged Root-Mean-Square Error(RMSE)by 58%.Intriguingly,the CycleGAN effectively addresses the well-known excessive westward bias in ENSO SST anomalies,a common issue in climate models that traditional methods,like quantile mapping,struggle to rectify.Additionally,it substantially improves the simulation of SST extremes,raising the pattern correlation coefficient(PCC)from 0.56 to 0.88 and lowering the RMSE from 0.5 to 0.32.This enhancement is attributed to better representations of interannual,intraseasonal,and synoptic scales variabilities.Our study offers a novel approach to correct global SST simulations and underscores its effectiveness across different time scales and primary dynamical modes.

Next‑Generation Green Hydrogen: Progress and Perspective from Electricity, Catalyst to Electrolyte in Electrocatalytic Water Splitting

Green hydrogen from electrolysis of water has attracted widespread attention as a renewable power source.Among several hydrogen production methods,it has become the most promising technology.However,there is no large-scale renewable hydrogen production system currently that can compete with conventional fossil fuel hydrogen production.Renewable energy electrocatalytic water splitting is an ideal production technology with environmental cleanliness protection and good hydrogen purity,which meet the requirements of future development.This review summarizes and introduces the current status of hydrogen production by water splitting from three aspects:electricity,catalyst and electrolyte.In particular,the present situation and the latest progress of the key sources of power,catalytic materials and electrolyzers for electrocatalytic water splitting are introduced.Finally,the problems of hydrogen generation from electrolytic water splitting and directions of next-generation green hydrogen in the future are discussed and outlooked.It is expected that this review will have an important impact on the field of hydrogen production from water.

Prediction of sepsis within 24 hours at the triage stage in emergency departments using machine learning

BACKGROUND:Sepsis is one of the main causes of mortality in intensive care units(ICUs).Early prediction is critical for reducing injury.As approximately 36%of sepsis occur within 24 h after emergency department(ED)admission in Medical Information Mart for Intensive Care(MIMIC-IV),a prediction system for the ED triage stage would be helpful.Previous methods such as the quick Sequential Organ Failure Assessment(qSOFA)are more suitable for screening than for prediction in the ED,and we aimed to fi nd a light-weight,convenient prediction method through machine learning.METHODS:We accessed the MIMIC-IV for sepsis patient data in the EDs.Our dataset comprised demographic information,vital signs,and synthetic features.Extreme Gradient Boosting(XGBoost)was used to predict the risk of developing sepsis within 24 h after ED admission.Additionally,SHapley Additive exPlanations(SHAP)was employed to provide a comprehensive interpretation of the model's results.Ten percent of the patients were randomly selected as the testing set,while the remaining patients were used for training with 10-fold cross-validation.RESULTS:For 10-fold cross-validation on 14,957 samples,we reached an accuracy of 84.1%±0.3%and an area under the receiver operating characteristic(ROC)curve of 0.92±0.02.The model achieved similar performance on the testing set of 1,662 patients.SHAP values showed that the fi ve most important features were acuity,arrival transportation,age,shock index,and respiratory rate.CONCLUSION:Machine learning models such as XGBoost may be used for sepsis prediction using only a small amount of data conveniently collected in the ED triage stage.This may help reduce workload in the ED and warn medical workers against the risk of sepsis in advance.

Timing and Single-pulse Study of Pulsar J1909+0122 Discovered by CRAFTS

We report the discovery of PSR J1909+0122 by the Five-hundred-meter Aperture Spherical Radio Telescope(FAST)as part of the Commensal Radio Astronomy FAST Survey.PSR J1909+0122 has a spin period of 1.257 s and a dispersion measure of 186.2 pc cm^(-3).The averaged pulse profile shows two distinct components.We performed a single-pulse study based on a one-hour observation at 1.25 GHz on 2021 August 23.We used a threshold of 5σ_(ep) to measure the nulling fraction(NF)as 63%±1.5%.The longitude-resolved fluctuation spectra and fast Fourier transform spectra of the binary sequences revealed the quasi-periodicity of nulling with a period of 30 rotation periods.We examined the reliability of the periodicity by comparing it to random noise injection.The NF,E,and modulation periodicity P_(M) of PSR J1909+0122 were compared with other periodic nulling pulsars,showing that the source of J1909+0122 has the second largest NF in the population.Long-term timing observations over six months were used to derive the phase-connected ephemeris of this pulsar.The measured P and P values disfavor dipolar geometry for polar gap models,and the prediction for a space-charge-limited flow model in the case of inverse Compton scattering is only just above the death line.In this work,PSR J1909+0122 has revealed possible correlations between nulling behavior and pulsar properties,which will help to shed light on the pulsar emission mechanism and its temporal evolution in future observations.

碳酸类护肤品的功效评测

二氧化碳是一种人体可产生的气体,无毒、无害,且对人体的生理功能具有重要作用,利用二氧化碳改善身体健康目前已有广泛的应用。含有二氧化碳或在使用过程中能够产生二氧化碳的碳酸类护肤品已成为目前护肤品行业关注的热点产品之一。产品中存在的或使用时产生的二氧化碳能进入皮肤,引起波尔效应,进而达到护肤的目的。使用VISIACR皮肤检测仪和MoistureMeterSC皮肤表面水含量测量仪详细研究了碳酸类护肤品对血液循环、毛孔、护肤品吸收的影响,并对碳酸类护肤品对皮肤的深层清洁作用进行了探讨。结果显示,碳酸类护肤品可暂时性改善皮肤局部微循环,促进毛孔扩张,进而为后续护肤产品中功效成分的吸收提供条件。同时,碳酸类护肤品导致的短暂性的毛孔扩张有利于黑头排出体外,达到皮肤深层清洁的目的。碳酸类护肤品有望通过加速皮肤血液循环、促进功效成分吸收、有效清除皮肤深层的垃圾和废物,从根本上解决基本皮肤问题。

QoS Prediction Model of Cloud Services Based on Deep Learning

Dear editor,This letter presents a deep learning-based prediction model for the quality-of-service(QoS)of cloud services.Specifically,to improve the QoS prediction accuracy of cloud services,a new QoS prediction model is proposed,which is based on multi-staged multi-metric feature fusion with individual evaluations.The multi-metric features include global,local,and individual ones.Experimental results show that the proposed model can provide more accurate QoS prediction results of cloud services than several state-of-the-art methods.

MULTIPLE SOLUTIONS OF SOME ELLIPTIC SYSTEMS WITH LINEAR COUPLINGS

In this paper,we study the existence of nontrivial solutions to the elliptic system {-△u=λv+Fu(x,u,v),x∈Ω,-△v=λu+Fv(x,u,v),x∈Ω,u=v=0,x∈∂Ω,where Ω■R^(N) is bounded with a smooth boundary.By the Morse theory and the Gromoll-Meyer pair,we obtain multiple nontrivial vector solutions to this system.

Comparison of sample temperature effect on femtosecond and nanosecond laser-induced breakdown spectroscopy

In this paper,we investigated the emission spectra of plasmas produced from femtosecond and nanosecond laser ablations at different target temperatures in air.A brass was selected as ablated target of the experiment.The results indicated that spectral emission intensity and plasma temperature showed similar trend for femtosecond and nanosecond lasers,and the two parameters were improved by increasing the sample temperature in both cases.Moreover,the temperature of nanosecond laser-excited plasma was higher compared with that of femtosecond laser-excited plasma,and the increase of the plasma temperature in the case of nanosecond laser was more evident.In addition,there was a significant difference in electron density between femtosecond and nanosecond laser-induced plasmas.The electron density for femtosecond laser decreased with increasing the target temperature,while for nanosecond laser,the electron density was almost unchanged at different sample temperatures.

Application of Simulation Technology in Military Education

Based on the teaching characteristics in military academies,simulation technology has been applied in their teaching methods.The issues faced in the application of virtual simulation technology to relevant professional teaching in armed police academies are analyzed in this article.Secondly,in view of the difficulties encountered in the organization and implementation of practical teaching as well as in the development of the current teaching,this article explores the impact of simulation technology in its application in teaching methods,training practices,and teaching channels.

Engineered nanoparticles for precise targeted drug delivery and enhanced therapeutic efficacy in cancer immunotherapy

The advent of cancer immunotherapy has imparted a transformative impact on cancer treatment paradigms by harnessing the power of the immune system.However,the challenge of practical and precise targeting of malignant cells persists.To address this,engineered nanoparticles(NPs)have emerged as a promising solution for enhancing targeted drug delivery in immunotherapeutic interventions,owing to their small size,low immunogenicity,and ease of surface modification.This comprehensive review delves into contemporary research at the nexus of NP engineering and immunotherapy,encompassing an extensive spectrum of NP morphologies and strategies tailored toward optimizing tumor targeting and augmenting therapeutic effectiveness.Moreover,it underscores the mechanisms that NPs leverage to bypass the numerous obstacles encountered in immunotherapeutic regimens and probes into the combined potential of NPs when co-administered with both established and novel immunotherapeutic modalities.Finally,the review evaluates the existing limitations of NPs as drug delivery platforms in immunotherapy,which could shape the path for future advancements in this promising field.

High-efficient removal of tetracycline in water via porous magnetic Ce/Fe photocomposite under visible light

Tetracycline is a typical antibiotic commonly used in various industries which is eco-toxic and quickly causes bacterial resistance.Therefo re,studying the efficient removal of tetracycline is necessary to protect the water environment.Herein,a novel Ce/Fe nanoparticle composite(1CCFO)was prepared by the sol-gel method and its removal effects of tetracycline under visible light were performed.The relationship between physicochemical properties of catalyst and photocatalytic degradation effects of tetracycline was analyzed based on a series of characterizations data such as X-ray diffraction(XRD),Raman spectro scopy,a vibrating sample magnetometer(VSM),scanning electron microscopy(SEM),Brunauer-Emmett-Teller(BET)method,X-ray photoelectron spectroscopy(XPS),and ultraviolet-visible(UV-Vis)spectroscopy.The results show that Ce/Fe photocatalyst possesses a large specific surface area,good visible light response,abundant oxygen vacancies and excellent redox performance,exhibiting good adsorption capacity,remarkable catalytic performance and stability.The optimal conditions for tetracycline removal were explored through orthogonal experiments.About 88%of tetracycline can be photodegraded in 1 h under optimal conditions.The possible decomposition pathways,main reactive oxygen species and suitable mechanism of the photocatalytic system were studied by liquid chromatography-mass spectro metry(LC-MS),an electron spin resonance(ESR)spectrometer and free radical quenching experiments.The results show that 1CCFO has an efficient degradation effect on tetracycline under visible light,which provides a feasible method to improve the performance of 1CCFO.

Locally generalised multi-agent reinforcement learning for demand and capacity balancing with customised neural networks

Reinforcement Learning(RL)techniques are being studied to solve the Demand and Capacity Balancing(DCB)problems to fully exploit their computational performance.A locally gen-eralised Multi-Agent Reinforcement Learning(MARL)for real-world DCB problems is proposed.The proposed method can deploy trained agents directly to unseen scenarios in a specific Air Traffic Flow Management(ATFM)region to quickly obtain a satisfactory solution.In this method,agents of all flights in a scenario form a multi-agent decision-making system based on partial observation.The trained agent with the customised neural network can be deployed directly on the corresponding flight,allowing it to solve the DCB problem jointly.A cooperation coefficient is introduced in the reward function,which is used to adjust the agent’s cooperation preference in a multi-agent system,thereby controlling the distribution of flight delay time allocation.A multi-iteration mechanism is designed for the DCB decision-making framework to deal with problems arising from non-stationarity in MARL and to ensure that all hotspots are eliminated.Experiments based on large-scale high-complexity real-world scenarios are conducted to verify the effectiveness and efficiency of the method.From a statis-tical point of view,it is proven that the proposed method is generalised within the scope of the flights and sectors of interest,and its optimisation performance outperforms the standard computer-assisted slot allocation and state-of-the-art RL-based DCB methods.The sensitivity analysis preliminarily reveals the effect of the cooperation coefficient on delay time allocation.

Templated synthesis of patterned gold nanoparticle assemblies for highly sensitive and reliable SERS substrates

Formation of plasmonic structure in closely packed assemblies of metallic nanoparticles(NPs)is essential for various applications in sensing,renewable energy,authentication,catalysis,and metamaterials.Herein,a surface-enhanced Raman scattering(SERS)substrate is fabricated for trace detection with ultrahigh sensitivity and stability.The SERS substrate is constructed from a simple yet robust strategy through in situ growth patterned assemblies of Au NPs based on a polymer brush templated synthesis strategy.Benefiting from the dense and uniform distribution of Au NPs,the resulting Au plasmonic nanostructure demonstrates a very strong SERS effect,while the outer polymer brush could restrict the excessive growth of Au NPs and the patterned design could achieve uniform distribution of Au NPs.As results,an ultra-low limit of detection(LOD)of 10^(−15)M,which has never been successfully detected in other work,is determined for 4-acetamidothiophenol(4-AMTP)molecules and the Raman signals in the random region show good signal homogeneity with a low relative standard deviation(RSD)of 7.2%,indicating great sensitivity and reliability as a SERS substrate.The LOD values of such Au plasmonic nanostructures for methylene blue,thiram,and R6G molecules can also reach as low as 10^(−10)M,further indicating that the substrate has a wide range of applicability for SERS detection.With the help of finite difference time domain simulations(FDTD)calculation,the electric field distribution of the Au plasmonic nanostructures is simulated,which quantitatively matches the experimental observations.Moreover,the Au plasmonic nanostructures show good shelf stability for at least 10 months of storage in an ambient environment,indicating potentials for practical applications.

Recent advances in fluorinated polymers:synthesis and diverse applications

Fluorinated polymers exhibit a unique combination of attributes,including chemical inertness,low surface energy,exceptional weather resistance,and intriguing electrical properties.This mini review provides an overview of recent advancements in the research of fluorinated polymers,highlighting the development of synthetic strategies for novel fluorinated polymers and their diverse applications in various fields.Traditional fluorinated polyolefins can be modified through chemical methods to produce functional materials.Copolymerization of fluorinated olefins with non-fluorinated monomers effectively addresses synthesis challenges,yielding main-chain fluoro-containing polymers with specific functional groups.Additionally,recent studies have revealed that free radical(co)polymerization of fluorinated(meth)acrylate monomers leads to new fluorinated polymers with enhanced solubility,processability,and structural diversity.Capitalizing on these new synthetic strategies,a range of fluorinated polymer materials has been developed for a multitude of applications,including flexible electrodes,alternating current(AC)electroluminescent devices,energy storage capacitors,triboelectric nanogenerators,and lithium batteries.With their customized structures and excellent properties,fluorinated polymers hold significant promise to uncover more potential applications in the era of flexible and wearable electronics.

Hydrophobic,Hemostatic and Durable Nanofiber Composites with a Screw‑Like Surface Architecture for Multifunctional Sensing Electronics

MXene-decorated textile composites have attracted tremendous attention,due to their possible applications in wearable sensing electronics.However,the easy oxidation,low strain sensitivity and poor water-proof performance restrict the applications of MXene-based smart textiles.Here,we developed a flexible and hydrophobic polymer nanofibrous composite with a screw-like structure by assembling MXene nanosheets onto a prestretched polyurethane(PU)nanofiber surface and subsequent fluorination treatment.The thin hydrophobic fluorosilane layer can greatly prevent the MXene shell from being oxidized and simultaneously endow the nanofiber composite with good hemostatic performance.The wrinkled MXene shell with the screw-like structure enhances the sensitivity of MXene@PU nanofiber composite(HMPU)toward strain,and the hydrophobic strain sensor exhibits a high gauge factor(324.4 in the strain range of 85–100%),and can detect different human movements.In virtue of its excellent water-proof performance,HMPU can function normally in corrosive and underwater conditions.In addition,the resistance of HMPU exhibits a negative temperature coefficient;thus,HMPU shows potential for monitoring temperature and providing a temperature alarm.The multifunctional HMPU shows broad application prospects in smart wearable electronics.

Pure annihilation decays of B^(s)_(0)→a^(+)_(0)a^(−)_(0)and B^(0)_(d)→K^(∗+)_(0)K^(∗−)_(0)in the PQCD approac

We study the CP-averaged branching fractions and the CP-violating asymmetries in the pure annihilation decays of B^(s)_(0)→a^(+)_(0)a^(−)_(0)and B^(0)_(d)→K^(∗+)_(0)K^(∗−)_(0),where a_(0)[K^(∗)_(0)]denotes the scalar a_(0)(980)and a_(0)(1450)[K^(∗)_(0)(800)(orκ)and K^(∗)_(0)(1430)],with the perturbative QCD factorization approach under the assumption of two-quark structure for the a_(0)and K^(∗)_(0)states.The numerical results show that the branching ratios of the B^(0)_(d)→K^(∗+)_(0)K^(∗−)_(0)decays are in the order of 10^(−6),while the decay rates of the B^(s)_(0)→a^(+)_(0)a^(−)_(0)modes are in the order of 10−5.In light of the measured modes with the same quark components in the pseudoscalar sector,namely,B^(0)_(d)→K^(+)k_(-)and B^(0)_(s)→π^(+)π_(−),the predictions for the considered decay modes in this work are expected to be measured at the Large Hadron Collider beauty and/or Belle-Ⅱexperiments in the(near)future.Meanwhile,it is of great interest to find that the twist-3 distribution amplitudesφ^(S)andφ^(T)with inclusion of the Gegenbauer polynomials for the scalar a_(0)(1450)and K^(∗)_(0)(1430)states in scenario 2 contribute slightly to the branching ratios while significantly to the CP violations in the B^(0)_(d)→K^(∗)_(0)(1430)+K^(∗)_(0)(1430)−and B^(0)_(s)→a_(0)(1450)+a_(0)(1450)−decays,which indicates that,compared to the asymptoticφ^(S)andφ^(T),these Gegenbauer polynomials could change the strong phases evidently in these pure annihilation decay channels.These predictions await for the future confirmation experimentally,which could further provide useful information to help explore the inner structure of the scalars and shed light on the annihilation decay mechanism.