HOMOGENEOUS CATALYTIC REACTION(EC')AT GENERATION/COLLECTION MICROELECIRODE

A new type of macro-micro-macro triple electrode is fabricated. The kinetic equation is obtained by using the decrease in collection current to determine the kinetic constant of homogeneous catalytic reaction, the method can be used to study homogeneous chemical reaction with any magnitude of kinetic constant, and overcomes the disadvantages that the microelectrode is only suitable for fast catalytic reaction.

Generation/collection mode of SECM with combined probe

Here we report a novel generation/collection operation mode of scanning electrochemical microscopy,in which a theta micropipette was employed to support two adjacent water/1,2-dichloroethane interfaces separated by the thin central glass wall：one acts as the generator while the other as the collector.The generation current,collection current and collection efficiency were enhanced significantly when the tip approached to an insulate substrate.

Secure Channel Estimation Using Norm Estimation Model for 5G Next Generation Wireless Networks

The emergence of next generation networks(NextG),including 5G and beyond,is reshaping the technological landscape of cellular and mobile networks.These networks are sufficiently scaled to interconnect billions of users and devices.Researchers in academia and industry are focusing on technological advancements to achieve highspeed transmission,cell planning,and latency reduction to facilitate emerging applications such as virtual reality,the metaverse,smart cities,smart health,and autonomous vehicles.NextG continuously improves its network functionality to support these applications.Multiple input multiple output(MIMO)technology offers spectral efficiency,dependability,and overall performance in conjunctionwithNextG.This article proposes a secure channel estimation technique in MIMO topology using a norm-estimation model to provide comprehensive insights into protecting NextG network components against adversarial attacks.The technique aims to create long-lasting and secure NextG networks using this extended approach.The viability of MIMO applications and modern AI-driven methodologies to combat cybersecurity threats are explored in this research.Moreover,the proposed model demonstrates high performance in terms of reliability and accuracy,with a 20%reduction in the MalOut-RealOut-Diff metric compared to existing state-of-the-art techniques.

Articles collection published in Neural Regeneration Research 2011

Neural Regeneration Research （NRR, ISSN 1675-5374, CN11-5422/R）, an English language journal published in China every ten days, is dedicated to presenting peer-reviewed, evidenced based scholarly research in neuroregeneration, including neural stem cells, nerve tissue engineering, gene therapy, and traditional Chinese medicine.

Resonantly enhanced second-and third-harmonic generation in dielectric nonlinear metasurfaces

Nonlinear dielectric metasurfaces provide a promising approach to control and manipulate frequency conversion optical processes at the nanoscale,thus facilitating both advances in fundamental research and the development of new practical applications in photonics,lasing,and sensing.Here,we employ symmetry-broken metasurfaces made of centrosymmetric amorphous silicon for resonantly enhanced second-and third-order nonlinear optical response.Exploiting the rich physics of optical quasi-bound states in the continuum and guided mode resonances,we comprehensively study through rigorous numerical calculations the relative contribution of surface and bulk effects to second-harmonic generation(SHG)and the bulk contribution to third-harmonic generation(THG) from the meta-atoms.Next,we experimentally achieve optical resonances with high quality factors,which greatly boosts light-matter interaction,resulting in about 550 times SHG enhancement and nearly 5000-fold increase of THG.A good agreement between theoretical predictions and experimental measurements is observed.To gain deeper insights into the physics of the investigated nonlinear optical processes,we further numerically study the relation between nonlinear emission and the structural asymmetry of the metasurface and reveal that the generated harmonic signals arising from linear sharp resonances are highly dependent on the asymmetry of the meta-atoms.Our work suggests a fruitful strategy to enhance the harmonic generation and effectively control different orders of harmonics in all-dielectric metasurfaces,enabling the development of efficient active photonic nanodevices.

In vivo label-free measurement of blood flow velocity symmetry based on dual line scanning third-harmonic generation microscopy excited at the 1700 nm window

Measurement of bloodflow velocity is key to understanding physiology and pathology in vivo.While most measurements are performed at the middle of the blood vessel,little research has been done on characterizing the instantaneous bloodflow velocity distribution.This is mainly due to the lack of measurement technology with high spatial and temporal resolution.Here,we tackle this problem with our recently developed dual-wavelength line-scan third-harmonic generation(THG)imaging technology.Simultaneous acquisition of dual-wavelength THG line-scanning signals enables measurement of bloodflow velocities at two radially symmetric positions in both venules and arterioles in mouse brain in vivo.Our results clearly show that the instantaneous bloodflow velocity is not symmetric under general conditions.

Natural high-porous diatomaceous-earth based self-floating aerogel for efficient solar steam power generation

The application of solar steam generation in seawater desalination is an effective way to solve the shortage of fresh water resources.At present,many kinds of photothermal conversion materials have been developed and used as evaporators in seawater desalination.However,some evaporators need additional thermal insulation or water supply devices to achieve efficient photothermal conversion.In addition,their complex,time consuming and no scalable preparation process,high cost of raw materials and poor salt resistance hinder the practical application of these evaporator.Owing to its distinctive nanoporous structure,diatomite as fossilized single-cells algae diatoms is a promising natural silica-based material for seawater desalination.They are taken from sea and that makes true sense to use them in the sea.Herein,we report the first example of synthesis robust three-dimensional(3D)natural-diatomite composite by assembling polyaniline nanoparticles covered diatomite into the polyvinyl alcohol pre-treated melamine foam frameworks and demonstrate its application as new evaporator for seawater desalination.The porous framework does not only improve the sunlight scattering efficiency,but also offer large network of channels for water transportation.The inherent mechanism behind salt desalination process involves the absorption of water molecules on the surface of the internal silica micro-nano pores,and evaporation under the heat induced by the polyaniline absorbed sunlight.Meanwhile,the metal ions are segregated by many available pores and channels to achieve the self-desalting effect.The developed evaporator possesses the superiority of multi-stage pore structure,strong hydrophilicity,low thermal conductivity,excellent light absorption,fast water transportation and salt-resistant crystallization as well as good durability.The evaporation rate without an additional device is found to be 1.689 kg m^(-2)h^(-1)under 1-Sun irradiation,and the energy conversion efficiency is as high as 95%.This work creates a platform and develops the prospect of employing green and sustainable natural-diatomite composite evaporator for practical applications of seawater desalination.

Multi-objective optimization and evaluation of supercritical CO_(2) Brayton cycle for nuclear power generation

The supercritical CO_(2) Brayton cycle is considered a promising energy conversion system for Generation IV reactors for its simple layout,compact structure,and high cycle efficiency.Mathematical models of four Brayton cycle layouts are developed in this study for different reactors to reduce the cost and increase the thermohydraulic performance of nuclear power generation to promote the commercialization of nuclear energy.Parametric analysis,multi-objective optimizations,and four decision-making methods are applied to obtain each Brayton scheme’s optimal thermohydraulic and economic indexes.Results show that for the same design thermal power scale of reactors,the higher the core’s exit temperature,the better the Brayton cycle’s thermo-economic performance.Among the four-cycle layouts,the recompression cycle(RC)has the best overall performance,followed by the simple recuperation cycle(SR)and the intercooling cycle(IC),and the worst is the reheating cycle(RH).However,RH has the lowest total cost of investment(C_(tot))of$1619.85 million,and IC has the lowest levelized cost of energy(LCOE)of 0.012$/(kWh).The nuclear Brayton cycle system’s overall performance has been improved due to optimization.The performance of the molten salt reactor combined with the intercooling cycle(MSR-IC)scheme has the greatest improvement,with the net output power(W_(net)),thermal efficiencyη_(t),and exergy efficiency(η_(e))improved by 8.58%,8.58%,and 11.21%,respectively.The performance of the lead-cooled fast reactor combined with the simple recuperation cycle scheme was optimized to increase C_(tot) by 27.78%.In comparison,the internal rate of return(IRR)increased by only 7.8%,which is not friendly to investors with limited funds.For the nuclear Brayton cycle,the molten salt reactor combined with the recompression cycle scheme should receive priority,and the gas-cooled fast reactor combined with the reheating cycle scheme should be considered carefully.

Quantitative effect of kerogen type on the hydrocarbon generation potential of Paleogene lacustrine source rocks,Liaohe Western Depression,China

Kerogen types exert a decisive effect on the onset and capacity of hydrocarbon generation of source rocks.Lacustrine source rocks in the Liaohe Western Depression are characterized by thick deposition,high total organic carbon(TOC)content,various kerogen types,and a wide range of thermal maturity.Consequently,their hydrocarbon generation potential and resource estimation can be misinterpreted.In this study,geochemical tests,numerical analysis,hydrocarbon generation kinetics,and basin modeling were integrated to investigate the differential effects of kerogen types on the hydrocarbon generation potential of lacustrine source rocks.Optimized hydrocarbon generation and expulsion(HGE)models of different kerogen types were established quantitatively upon abundant Rock-Eval/TOC/vitrinite reflectance(R_(o))datasets.Three sets of good-excellent source rocks deposited in the fourth(Es4),third(Es3),and first(Es1)members of Paleogene Shahejie Formation,are predominantly types I-II_(1),II_(1)-II_(2),and II-III,respectively.The activation energy of types I-II_(2)kerogen is concentrated(180-230 kcal/mol),whereas that of type III kerogen is widely distributed(150-280 kcal/mol).The original hydrocarbon generation potentials of types I,II_(1),II_(2),and III kerogens are 790,510,270,and 85 mg/g TOC,respectively.The Ro values of the hydrocarbon generation threshold for type I-III source rocks gradually increase from 0.42%to 0.74%,and Ro values of the hydrocarbon expulsion threshold increase from 0.49%to 0.87%.Types I and II_(1)source rocks are characterized by earlier hydrocarbon generation,more rapid hydrocarbon expulsion,and narrower hydrocarbon generation windows than types II_(2)and III source rocks.The kerogen types also affect the HGE history and resource potential.Three types(conventional,tight,and shale oil/gas)and three levels(realistic,expected,and prospective)of hydrocarbon resources of different members in the Liaohe Western Depression are evaluated.Findings suggest that the Es3 member has considerable conventional and unconventional hydrocarbon resources.This study can quantitatively characterize the hydrocarbon generation potential of source rocks with different kerogen types,and facilitate a quick and accurate assessment of hydrocarbon resources,providing strategies for future oil and gas exploration.

Endoscopic intramural cystogastrostomy for treatment of peripancreatic fluid collection: A viewpoint from a surgeon

Percutaneous or endoscopic drainage is the initial choice for the treatment of peripancreatic fluid collection in symptomatic patients.Endoscopic transgastric fenestration(ETGF)was first reported for the management of pancreatic pseu-docysts of 20 patients in 2008.From a surgeon’s viewpoint,ETGF is a similar procedure to cystogastrostomy in that they both produce a wide outlet orifice for the drainage of fluid and necrotic debris.ETGF can be performed at least 4 wk after the initial onset of acute pancreatitis and it has a high priority over the surgical approach.However,the surgical approach usually has a better success rate because surgical cystogastrostomy has a wider outlet(>6 cm vs 2 cm)than ETGF.However,percutaneous or endoscopic drainage,ETGF,and surgical approach offer various treatment options for peripancreatic fluid collection patients based on their conditions.

Customized Convolutional Neural Network for Accurate Detection of Deep Fake Images in Video Collections

The motivation for this study is that the quality of deep fakes is constantly improving,which leads to the need to develop new methods for their detection.The proposed Customized Convolutional Neural Network method involves extracting structured data from video frames using facial landmark detection,which is then used as input to the CNN.The customized Convolutional Neural Network method is the date augmented-based CNN model to generate‘fake data’or‘fake images’.This study was carried out using Python and its libraries.We used 242 films from the dataset gathered by the Deep Fake Detection Challenge,of which 199 were made up and the remaining 53 were real.Ten seconds were allotted for each video.There were 318 videos used in all,199 of which were fake and 119 of which were real.Our proposedmethod achieved a testing accuracy of 91.47%,loss of 0.342,and AUC score of 0.92,outperforming two alternative approaches,CNN and MLP-CNN.Furthermore,our method succeeded in greater accuracy than contemporary models such as XceptionNet,Meso-4,EfficientNet-BO,MesoInception-4,VGG-16,and DST-Net.The novelty of this investigation is the development of a new Convolutional Neural Network(CNN)learning model that can accurately detect deep fake face photos.

Prediction of corrosion rate for friction stir processed WE43 alloy by combining PSO-based virtual sample generation and machine learning

The corrosion rate is a crucial factor that impacts the longevity of materials in different applications.After undergoing friction stir processing(FSP),the refined grain structure leads to a notable decrease in corrosion rate.However,a better understanding of the correlation between the FSP process parameters and the corrosion rate is still lacking.The current study used machine learning to establish the relationship between the corrosion rate and FSP process parameters(rotational speed,traverse speed,and shoulder diameter)for WE43 alloy.The Taguchi L27 design of experiments was used for the experimental analysis.In addition,synthetic data was generated using particle swarm optimization for virtual sample generation(VSG).The application of VSG has led to an increase in the prediction accuracy of machine learning models.A sensitivity analysis was performed using Shapley Additive Explanations to determine the key factors affecting the corrosion rate.The shoulder diameter had a significant impact in comparison to the traverse speed.A graphical user interface(GUI)has been created to predict the corrosion rate using the identified factors.This study focuses on the WE43 alloy,but its findings can also be used to predict the corrosion rate of other magnesium alloys.

Application of DSAPSO Algorithm in Distribution Network Reconfiguration with Distributed Generation

With the current integration of distributed energy resources into the grid,the structure of distribution networks is becoming more complex.This complexity significantly expands the solution space in the optimization process for network reconstruction using intelligent algorithms.Consequently,traditional intelligent algorithms frequently encounter insufficient search accuracy and become trapped in local optima.To tackle this issue,a more advanced particle swarm optimization algorithm is proposed.To address the varying emphases at different stages of the optimization process,a dynamic strategy is implemented to regulate the social and self-learning factors.The Metropolis criterion is introduced into the simulated annealing algorithm to occasionally accept suboptimal solutions,thereby mitigating premature convergence in the population optimization process.The inertia weight is adjusted using the logistic mapping technique to maintain a balance between the algorithm’s global and local search abilities.The incorporation of the Pareto principle involves the consideration of network losses and voltage deviations as objective functions.A fuzzy membership function is employed for selecting the results.Simulation analysis is carried out on the restructuring of the distribution network,using the IEEE-33 node system and the IEEE-69 node system as examples,in conjunction with the integration of distributed energy resources.The findings demonstrate that,in comparison to other intelligent optimization algorithms,the proposed enhanced algorithm demonstrates a shorter convergence time and effectively reduces active power losses within the network.Furthermore,it enhances the amplitude of node voltages,thereby improving the stability of distribution network operations and power supply quality.Additionally,the algorithm exhibits a high level of generality and applicability.

Harnessing overlapped temperature-salinity gradient in solar-driven interfacial seawater evaporation for efficient steam and electricity generation

Solar-driven interfacial water evaporation(SIWE)offers a superb way to leverage concentrated solar heat to minimize energy dissipation during seawater desalination.It also engenders overlapped temperaturesalinity gradient(TSG)between water-air interface and adjacent seawater,affording opportunities of harnessing electricity.However,the efficiency of conventional SIWE technologies is limited by significant challenges,including salt passivation to hinder evaporation and difficulties in exploiting overlapped TSG simultaneously.Herein,we report self-sustaining hybrid SIWE for not only sustainable seawater desalination but also efficient electricity generation from TSG.It enables spontaneous circulation of salt flux upon seawater evaporation,inducing a self-cleaning evaporative interface without salt passivation for stable steam generation.Meanwhile,this design enables spatial separation and simultaneous utilization of overlapped TSG to enhance electricity generation.These benefits render a remarkable efficiency of90.8%in solar energy utilization,manifesting in co-generation of solar steam at a fast rate of 2.01 kg m^(-2)-h^(-1)and electricity power of 1.91 W m^(-2)with high voltage.Directly interfacing the hybrid SIWE with seawater electrolyzer constructs a system for water-electricity-hydrogen co-generation without external electricity supply.It produces hydrogen at a rapid rate of 1.29 L h^(-1)m^(-2)and freshwater with 22 times lower Na+concentration than the World Health Organization(WHO)threshold.

Highly Aligned Ternary Nanofiber Matrices Loaded with MXene Expedite Regeneration of Volumetric Muscle Loss

Current therapeutic approaches for volumetric muscle loss(VML)face challenges due to limited graft availability and insufficient bioactivities.To overcome these limitations,tissue-engineered scaffolds have emerged as a promising alternative.In this study,we developed aligned ternary nanofibrous matrices comprised of poly(lactide-co-ε-caprolactone)integrated with collagen and Ti_(3)C_(2)T_(x)MXene nanoparticles(NPs)(PCM matrices),and explored their myogenic potential for skeletal muscle tissue regeneration.The PCM matrices demonstrated favorable physicochemical properties,including structural uniformity,alignment,microporosity,and hydrophilicity.In vitro assays revealed that the PCM matrices promoted cellular behaviors and myogenic differentiation of C2C12 myoblasts.Moreover,in vivo experiments demonstrated enhanced muscle remodeling and recovery in mice treated with PCM matrices following VML injury.Mechanistic insights from next-generation sequencing revealed that MXene NPs facilitated protein and ion availability within PCM matrices,leading to elevated intracellular Ca^(2+)levels in myoblasts through the activation of inducible nitric oxide synthase(i NOS)and serum/glucocorticoid regulated kinase 1(SGK1),ultimately promoting myogenic differentiation via the m TOR-AKT pathway.Additionally,upregulated i NOS and increased NO–contributed to myoblast proliferation and fiber fusion,thereby facilitating overall myoblast maturation.These findings underscore the potential of MXene NPs loaded within highly aligned matrices as therapeutic agents to promote skeletal muscle tissue recovery.

Two stages power generation test of the hot dry rock exploration and production demonstration project in the Gonghe Basin,northeastern Qinghai-Tibet plateau,China

The Hot Dry Rock(HDR)is considered as a clean and renewable energy,poised to significantly contribute to the global energy decarbonization agenda.Many HDR projects worldwide have accumulated valuable experience in efficient drilling and completion,reservoir construction,and fracture simulation.In 2019,China Geological Survey(CGS)initiated a demonstration project of HDR exploration and production in the Gonghe Basin,aiming to overcome the setbacks faced by HDR projects.Over the ensuing four years,the Gonghe HDR project achieved the first power generation in 2021,followed by the second power generation test in 2022.After establishing the primary well group in the initial phase,two directional wells and one branch well were drilled.Noteworthy progress was made in successfully constructing the targeted reservoir,realizing inter-well connectivity,power generation and grid connection,implementing of the real-time micro-seismic monitoring.A closed-loop technical validation of the HDR exploration and production was completed.However,many technical challenges remain in the process of HDR industrialization,such as reservoir fracture network characterization,efficient drilling and completion,multiple fracturing treatment,continuous injection and production,as well as mitigation of induced seismicity and numerical simulation technology.

Recent advances in water collection based on solar evaporation

Solar evaporation attracted lots of attention due to its environment-friendly and high efficiency,which is a potential approach to collecting fresh water.Many efforts have been made to improve the evaporation rate in the open space.While the actual water collection rate is far less than the evaporation rate,especially in passive water collection,limiting its practical and scalable applications.In this review,we focus on freshwater collection based on solar evaporation.Firstly,heat and mass transfer behaviors on the evaporation side were summarized to improve evaporation performance,including heat transfer processes in thermal radiation,convection,and conduction;mass transfer processes in water supply,evaporation enthalpy,and salt rejection.Sequentially,subcooling,wettability,and geometry of the condensation side were discussed to improve water collection performance,which should be designed collaboratively with the evaporation side in a confined space.Finally,thermal recovery and electricity generation beyond water collection were also introduced,and some challenges still need to improve in the further for scalable and practical applications,including passive water collection rate,integrated system,and long-term issues.

Identifying multidisciplinary problems from scientific publications based on a text generation method

Purpose:A text generation based multidisciplinary problem identification method is proposed,which does not rely on a large amount of data annotation.Design/methodology/approach:The proposed method first identifies the research objective types and disciplinary labels of papers using a text classification technique;second,it generates abstractive titles for each paper based on abstract and research objective types using a generative pre-trained language model;third,it extracts problem phrases from generated titles according to regular expression rules;fourth,it creates problem relation networks and identifies the same problems by exploiting a weighted community detection algorithm;finally,it identifies multidisciplinary problems based on the disciplinary labels of papers.Findings:Experiments in the“Carbon Peaking and Carbon Neutrality”field show that the proposed method can effectively identify multidisciplinary research problems.The disciplinary distribution of the identified problems is consistent with our understanding of multidisciplinary collaboration in the field.Research limitations:It is necessary to use the proposed method in other multidisciplinary fields to validate its effectiveness.Practical implications:Multidisciplinary problem identification helps to gather multidisciplinary forces to solve complex real-world problems for the governments,fund valuable multidisciplinary problems for research management authorities,and borrow ideas from other disciplines for researchers.Originality/value:This approach proposes a novel multidisciplinary problem identification method based on text generation,which identifies multidisciplinary problems based on generative abstractive titles of papers without data annotation required by standard sequence labeling techniques.

The application of cellulosic-based materials on interfacial solar steam generation for highly efficient wastewater purification: A review

The world's population is growing,leading to an increasing demand for freshwater resources for drinking,sanitation,agriculture,and industry.Interfacial solar steam generation(ISSG)can solve many problems,such as mitigating the power crisis,minimizing water pollution,and improving the purification and desalination of seawater,rivers/lakes,and wastewater.Cellulosic materials are a viable and ecologically sound technique for capturing solar energy that is adaptable to a range of applications.This review paper aims to provide an overview of current advancements in the field of cellulose-based materials ISSG devices,specifically focusing on their applications in water purification and desalination.This paper examines the cellulose-based materials ISSG system and evaluates the effectiveness of various cellulosic materials,such as cellulose nanofibers derived from different sources,carbonized wood materials,and two-dimensional(2D)and 3D cellulosic-based materials from various sources,as well as advanced cellulosic materials,including bacterial cellulose and cellulose membranes obtained from agricultural and industrial cellulose wastes.The focus is on exploring the potential applications of these materials in ISSG devices for water desalination,purification,and treatment.The function,advantages,and disadvantages of cellulosic materials in the performance of ISSG devices were also deliberated throughout our discussion.In addition,the potential and suggested methods for enhancing the utilization of cellulose-based materials in the field of ISSG systems for water desalination,purification,and treatment were also emphasized.

Electron correlation in two-electron atoms:A Bohmian analysis of high-order harmonic generation in high-frequency domain

In studying interactions between intense laser fields and atoms or molecules,the role of electron correlation effects on the dynamical response is an important and pressing issue to address.Utilizing Bohmian mechanics(BM),we have theoretically explored the two-electron correlation characteristics while generating high-order harmonics in xenon atoms subjected to intense laser fields.We initially employed Bohmian trajectories to reproduce the dynamics of the electrons and subsequently utilized time-frequency analysis spectra to ascertain the emission time windows for high-order harmonics.Within these time windows,we classified the nuclear region Bohmian trajectories and observed that intense high-order harmonics are solely generated when paired Bohmian particles(BPs)concurrently appear in the nuclear region and reside there for a duration within a re-collision time window.Furthermore,our analysis of characteristic trajectories producing high-order harmonics led us to propose a two-electron re-collision model to elucidate this phenomenon.The study demonstrates that intense high-order harmonics are only generated when both electrons are in the ground state within the re-collision time window.This work discusses the implications of correlation effects between two electrons and offers valuable insights for studying correlation in multi-electron high-order harmonic generation.