Long-range electron synergy over Pt_(1)-Co_(1)/CN bimetallic single-atom catalyst in enhancing charge separation for photocatalytic hydrogen production

The development of novel single-atom catalysts with optimal electron configuration and economical noble-metal cocatalyst for efficient photocatalytic hydrogen production is of great importance,but still challenging.Herein,we fabricate Pt and Co single-atom sites successively on polymeric carbon nitride(CN).In this Pt_(1)-Co_(1)/CN bimetallic single-atom catalyst,the noble-metal active sites are maximized,and the single-atomic Co_(1)N_4sites are tuned to Co_(1)N_3sites by photogenerated electrons arising from the introduced single-atomic Pt_(1)N_4sites.Mechanism studies and density functional theory(DFT)calculations reveal that the 3d orbitals of Co_(1)N_3single sites are filled with unpaired d-electrons,which lead to the improved visible-light response,carrier separation and charge migration for CN photocatalysts.Thereafter,the protons adsorption and activation are promoted.Taking this advantage of long-range electron synergy in bimetallic single atomic sites,the photocatalytic hydrogen evolution activity over Pt_(1)-Co_(1)/CN achieves 915.8 mmol g^(-1)Pt h^(-1),which is 19.8 times higher than Co_(1)/CN and 3.5 times higher to Pt_(1)/CN.While this electron-synergistic effect is not so efficient for Pt nanoclusters.These results demonstrate the synergistic effect at electron-level and provide electron-level guidance for the design of efficient photocatalysts.

Topological properties of tetratomic Su-Schrieffer-Heeger chains with hierarchical long-range hopping

We propose a new generalized Su–Schrieffer–Heeger model with hierarchical long-range hopping based on a onedimensional tetratomic chain. The properties of the topological states and phase transition, which depend on the cointeraction of the intracell and intercell hoppings, are investigated using the phase diagram of the winding number. It is shown that topological states with large positive/negative winding numbers can readily be generated in this system. The properties of the topological states can be verified by the ring-type structures in the trajectory diagram of the complex plane. The topological phase transition is strongly related to the opening(closure) of an energy bandgap at the center(boundaries) of the Brillouin zone. Finally, the non-zero-energy edge states at the ends of the finite system are revealed and matched with the bulk–boundary correspondence.

Generalized uncertainty principle from long-range kernel effects:The case of the Hawking black hole temperature

We prove the existence of an analogy between spatial long-range interactions,which are of the convolution-type introduced in non-relativistic quantum mechanics,and the generalized uncertainty principle predicted from quantum gravity theories.As an illustration,black hole temperature effects are discussed.It is observed that for specific choices of the moment's kernels,cold black holes may emerge in the theory.

Ag、Cu、Au、Ni、Pd、Pt的Long-range Finis-Sinclair势构建及其二元合金形成焓的计算

构建了fcc金属Cu、Ag、Au、Ni、Pd、Pt的Long-range Finnis-Sinclair势,并利用晶格常数、体弹性模量和金属的内聚能的实验数据拟合了这几种金属的Long-range Finnis-Sinclair势参数;利用Miedema理论和所构建的原子间相互作用势计算了Cu,Ag,Au,Ni,Pd,Pt的二元合金的形成焓.对两种计算结果进行了比较,并与已有的实验结果进行了比较.结果表明,使用Long-range Finnis-Sinclair势计算合金的形成焓能够得到令人满意的结果.

SwinFusion: Cross-domain Long-range Learning for General Image Fusion via Swin Transformer

This study proposes a novel general image fusion framework based on cross-domain long-range learning and Swin Transformer,termed as SwinFusion.On the one hand,an attention-guided cross-domain module is devised to achieve sufficient integration of complementary information and global interaction.More specifically,the proposed method involves an intra-domain fusion unit based on self-attention and an interdomain fusion unit based on cross-attention,which mine and integrate long dependencies within the same domain and across domains.Through long-range dependency modeling,the network is able to fully implement domain-specific information extraction and cross-domain complementary information integration as well as maintaining the appropriate apparent intensity from a global perspective.In particular,we introduce the shifted windows mechanism into the self-attention and cross-attention,which allows our model to receive images with arbitrary sizes.On the other hand,the multi-scene image fusion problems are generalized to a unified framework with structure maintenance,detail preservation,and proper intensity control.Moreover,an elaborate loss function,consisting of SSIM loss,texture loss,and intensity loss,drives the network to preserve abundant texture details and structural information,as well as presenting optimal apparent intensity.Extensive experiments on both multi-modal image fusion and digital photography image fusion demonstrate the superiority of our SwinFusion compared to the state-of-theart unified image fusion algorithms and task-specific alternatives.Implementation code and pre-trained weights can be accessed at https://github.com/Linfeng-Tang/SwinFusion.

A Long-Range Generalized Predictive Control Algorithm for a DFIG Based Wind Energy System

This paper presents a new Long-range generalized predictive controller in the synchronous reference frame for a wind energy system doubly-fed induction generator based. This controller uses the state space equations that consider the rotor current and voltage as state and control variables, to execute the predictive control action. Therefore, the model of the plant must be transformed into two discrete transference functions, by means of an auto-regressive moving average model, in order to attain a discrete and decoupled controller, which makes it possible to treat it as two independent single-input single-output systems instead of a magnetic coupled multiple-input multiple-output system. For achieving that, a direct power control strategy is used, based on the past and future rotor currents and voltages estimation. The algorithm evaluates the rotor current predictors for a defined prediction horizon and computes the new rotor voltages that must be injected to controlling the stator active and reactive powers. To evaluate the controller performance, some simulations were made using Matlab/Simulink. Experimental tests were carried out with a small-scale prototype assuming normal operating conditions with constant and variable wind speed profiles. Finally, some conclusions respect to the dynamic performance of this new controller are summarized.

The influence of magnetic field on the beam quality of relativistic electron beam long-range propagation in near-Earth environment

In recent years,it has been proposed to use satellite-mounted radio-frequency(RF)accelerators to produce high-current relativistic electron beams to complete debris removal tasks.However,when simulating the long-range propagation(km-range)process of the electron beam,it is difficult to directly use the particle-in-cell method to simultaneously consider the space charge effect of beam and the influence of the geomagnetic field.Owing to these limitations,in this paper,we proposed a simplified method.The ps-range electronic micropulses emitted by the RF accelerator were transmitted and fused to form a ns-range electron beam;then,combined with the improved moving window technology,the model was constructed to simulate the long-range propagation process of the relativistic electron beam in near-Earth environment.Finally,by setting the direction of movement of the beam to be parallel,perpendicular and at an inclination of 3°to the magnetic field,we analyzed and compared the effects of the applied magnetic fields in different directions on the quality of the beam during long-range propagation.The simulation results showed that the parallel state of the beam motion and magnetic fields should be achieved as much as possible to ensure the feasibility of the space debris removal.

Dynamics of the Random Ising Model with Long-Range Interaction

Critical dynamics of the random Ising model with long-range interaction decaying as r-(d+σ) where d is the dimensionality) is studied by the theoretic renormalization-group approach. The system is released to an evolution within a model A dynamics. Asymptotic scaling laws are studied in a frame of the expansion in = 2σ - d. In dimensions d ＜ 2σ. the dynamic exponent z is calculated to the second order in at the random fixed point.

Long-range Correlations in Iodide Cluster Aggregates

The morphology of tin iodide deposits grown during gas-solid transformation demonstrated longrange correlations. These iodide deposits include basically two kinds of forms: fractal structure and dendritic-like structure. The fractal structure was a sort of tin iodide cluster aggregation.Each fractal structure was composed of numerous tin iodide clusters that connected or disconnected with each other. The average size of fractal structures is between 10 and 22 μm. The dendritic-like structure was also composed of many tin iodide clusters. These clusters aggregated and formed a dendritic

Exact solutions of non-Hermitian chains with asymmetric long-range hopping under specific boundary conditions

We study the one-dimensional general non-Hermitian models with asymmetric long-range hopping and explore how to analytically solve the systems under some specific boundary conditions.Although the introduction of long-range hopping terms prevents us from finding analytical solutions for arbitrary boundary parameters,we identify the existence of exact solutions when the boundary parameters fulfill some constraint relations,which give the specific boundary conditions.Our analytical results show that the wave functions take simple forms and are independent of hopping range,while the eigenvalue spectra display rich model-dependent structures.Particularly,we find the existence of a special point coined as pseudo-periodic boundary condition,for which the eigenvalues are the same as those of the periodical system when the hopping parameters fulfill certain conditions,whereas the eigenstates display the non-Hermitian skin effect.

Physical properties of relativistic electron beam during long-range propagation in space plasma environment

It is known that ion channel can effectively limit the radial expansion of an artificial electron beam during its longrange propagation in the space plasma environment.Most prior studies discussed the focusing characteristics of the beam in the ion channel,but the establishment process and transient properties of the ion channel itself,which also plays a crucial role during the propagation of the relativistic electron beam in the plasma environment,were commonly neglected.In this study,a series of two-dimensional(2D)particle-in-cell simulations is performed and an analytical model of ion channel oscillation is constructed according to the single-particle motion.The results showed that when the beam density is higher than the density of plasma environment,ion channel can be established and always continues to oscillate periodically over the entire propagation.Multiple factors,including the beam electron density,initial beam radius,and the plasma density can affect the oscillation properties of ion channel.Axial velocity of the beam oscillates synchronously with the ion channel and this phenomenon will finally develop into a two-stream instability which can seriously affect the effective transport for relativistic electron beam.Choosing appropriate beam parameters based on various plasma environments may contribute to the improvement of the stability of ion channel.Additionally,radial expansion of the beam can be limited by ion channel and a stable long-range propagation in terrestrial atmosphere may be achieved.

Edge states enhanced by long-range hopping:An analytical study

We analyze the behavior of edge states in long-range(LR)interacting systems.In terms of lattice model Hamiltonian with the LR coupling,we determine analytically the condition of existence of edge states within the transfer matrix method(TMM).The expressions we obtain are general and hold for any choice of the LR hopping.The reason why edge states can appear is the transfer matrix in the bulk different from that in the boundary layers.Our predictions are in good agreement with numerical results by exact diagonalization.Our result is helpful in solving novel edge states in oneand two-dimensional(2D)superconductors with LR hopping and pairing.

Lagrangian formulation of continuum with internal long-range interactions

Based on a new definition of nonlocal variable,this paper establishes the Lagrangian formulation for continuum with internal long-range interactions.Distinguished from the existing theories,the nonlocal term in the Lagrangian formulation automatically satisfies the zero mean condition determined by the action and reaction law.By this formulation,elastic wave in a rod with the internal long-range interactions is investigated.The dispersion of the elastic wave is predicted.

Some Thoughts upon Long-Range Interaction and Entangled States

The problems of long-range interaction and associated questions on entangled states are reconsidered in terms of a recently developed revised quantum electrodynamic theory by the author, as being applied to subatomic systems. There are indications that the theories of relativity and quantum mechanics do not necessarily have to be in conflict. But more investigations are required for a full understanding to be obtained on these problems.

Long-range Dependence Characteristics of Forest Biological Disasters in China against the Background of Climate Change

Forest biological disasters(FBD) seriously impact energy flow and material cycling in forest ecosystems,while the underlying causes of FBD are complex. These disasters involve large areas and cause tremendous losses. As a result,the occurrence of FBDs in China( CFBD) threatens the country's ability to realize its strategic target of increasing both forested area(40 million ha) and forest volume(1.3 billion m^3) from 2005 to 2020. Collectively,China has officially named this effort to increase forest area and volume the "Two Increases" as national goals related to forestry. Based on Hurst index analysis from fractal theory,we analyzed the time series of the occurrence area and related data of FBDs from 1950 to 2007 to quantitatively determine the patterns of the macro occurrence of FBDs in China. Results indicates that,the time series of( CFBD) areas is fractal( self-affinity fractal dimension D = 1. 3548),the fluctuation of( CFBD) areas is positively correlated( auto-correlation coefficient C = 0. 2170),and the occurrence of the time series of( CFBD) is long-range dependent( Hurst index H =0. 6416),showing considerably strong trend of increases in FBDC area. Three different methods were further carried out on the original time series,and its two surrogate series generated by function surrogate in library t series,and function Surrogate Data in library in Wavelet software R,so as to analyze the reliability of Hurst indexes. The results showed that the Hurst indices calculated using different estimation methods were greater than 0. 5,ranging from 0. 64 to 0. 97,which indicated that the change of occurrence area data of FBDs was positively autocorrelated.The long-range dependence in forest biological disasters in China is obvious,and the spatial extent of FBDs tended to increase during this study period indicating this trend should be expected to persistent and worsen in the future.

Combined treatment promotes the long-range axon regeneration to right brain targets

Axons in the peripheral nervous system(PNS)can regenerate after injury.However,the adult mammalian central nervous system(CNS)loses the intrinsic regrowth ability.No robust axon regeneration occurs spontaneously after nerve injury,which was clearly observed by Ramon y Cajal in the early 20^(th) century(1,2).Due to lack

Long-Range Dependencies Learning Based on Nonlocal 1D-Convolutional Neural Network for Rolling Bearing Fault Diagnosis

In the field of data-driven bearing fault diagnosis,convolutional neural network(CNN)has been widely researched and applied due to its superior feature extraction and classification ability.However,the convolutional operation could only process a local neighborhood at a time and thus lack the ability of capturing long-range dependencies.Therefore,building an efficient learning method for long-range dependencies is crucial to comprehend and express signal features considering that the vibration signals obtained in a real industrial environment always have strong instability,periodicity,and temporal correlation.This paper introduces nonlocal mean to the CNN and presents a 1D nonlocal block(1D-NLB)to extract long-range dependencies.The 1D-NLB computes the response at a position as a weighted average value of the features at all positions.Based on it,we propose a nonlocal 1D convolutional neural network(NL-1DCNN)aiming at rolling bearing fault diagnosis.Furthermore,the 1D-NLB could be simply plugged into most existing deep learning architecture to improve their fault diagnosis ability.Under multiple noise conditions,the 1D-NLB improves the performance of the CNN on the wheelset bearing data set of high-speed train and the Case Western Reserve University bearing data set.The experiment results show that the NL-1DCNN exhibits superior results compared with six state-of-the-art fault diagnosis methods.

Spin waves and phase transition on a magnetically frustrated square lattice with long-range interactions

We investigate the effects of long-range interactions on the spin wave spectra and the competition between magnetic phases on a frustrated square lattice with large spin S.Applying the spin wave theory and assisted with symmetry analysis,we obtain analytical expressions for spin wave spectra of competing Neel and(π,0)stripe states of systems containing anyorder long-range interactions.In the specific case of long-range interactions with power-law decay,we find surprisingly that the staggered long-range interaction suppresses quantum fluctuation and enlarges the ordered moment,especially in the Neel state,and thus extends its phase boundary to the stripe state.Our findings illustrate the rich possibilities of the roles of long-range interactions,and advocate future investigations in other magnetic systems with different structures of interactions.

Ultrasensitive biosensors based on long-range surface plasmon polariton and dielectric waveguide modes

An ultrasensitive biosensor based on hybrid structure and composed of long-range surface plasmon polariton(LRSPP) and dielectric planar waveguide(PWG) modes is proposed. Both PWG and LRSPP modes have strong resonances to form strong coupling between the two modes, and the two modes can couple to enhance sensitivity of sensors. In the hybrid structure, PWG is composed of cytop–Si–cytop multilayers and the LRSPP configuration is composed of cytop–metal–sensing medium multilayer slabs. The highest imaging sensitivities of 2264 and3619 RIU-1were realized in the proposed sensors based on Au and Al-monolayer graphene, respectively, which are nearly 1.2 and 1.9 times larger than the 1910 RIU-1sensitivity of the conventional LRSPR sensor(LRSPP sensor). Moreover, it is demonstrated that the PWG-coupled LRSPP biosensor is applicable to the sensing medium,with refractive index in the vicinity of 1.34.

Long-range atmospheric transport and alpine condensation of short-chain chlorinated paraffins on the southeastern Tibetan Plateau

Pristine alpine regions are ideal regions for investigating the long-range atmospheric transport and cold trapping effects of short chain chlorinated paraffins(SCCPs).The concentrations and alpine condensation of SCCPs were investigated in lichen samples collected from the southeastern Tibetan Plateau.The concentrations of SCCPs ranged from 3098 to 6999 ng/g lipid weight(lw)and appeared to have an increasing trend with altitude.For congeners,C10 dominated among all the congener groups.The different environmental behavior for different congener groups was closely related to their octanol-air partition coefficient(Koa).C10 congeners showed an increasing trend with altitude,whereas C13 congeners were negatively correlated with altitude.Volumetric bioconcentration factors(BCF)of SCCPs reached 8.71 in lichens,which were higher than other semivolatile organic compounds(SVOCs)such as organochlorine pesticides(OCPs),polybrominated diphenyl ethers(PBDEs),polychlorinated biphenyls(PCBs),and hexabromocyclododecane(HBCD).These results suggested that SCCPs were prone to accumulate in the lichen from the air and provided evidence for the role of lichens as a suitable atmospheric indicator in the Tibetan Plateau.