Resting-state brain network remodeling after different nerve reconstruction surgeries:a functional magnetic resonance imaging study in brachial plexus injury rats

Distinct brain remodeling has been found after different nerve reconstruction strategies,including motor representation of the affected limb.However,differences among reconstruction strategies at the brain network level have not been elucidated.This study aimed to explore intranetwork changes related to altered peripheral neural pathways after different nerve reconstruction surgeries,including nerve repair,endto-end nerve transfer,and end-to-side nerve transfer.Sprague–Dawley rats underwent complete left brachial plexus transection and were divided into four equal groups of eight:no nerve repair,grafted nerve repair,phrenic nerve end-to-end transfer,and end-to-side transfer with a graft sutured to the anterior upper trunk.Resting-state brain functional magnetic resonance imaging was obtained 7 months after surgery.The independent component analysis algorithm was utilized to identify group-level network components of interest and extract resting-state functional connectivity values of each voxel within the component.Alterations in intra-network resting-state functional connectivity were compared among the groups.Target muscle reinnervation was assessed by behavioral observation(elbow flexion)and electromyography.The results showed that alterations in the sensorimotor and interoception networks were mostly related to changes in the peripheral neural pathway.Nerve repair was related to enhanced connectivity within the sensorimotor network,while end-to-side nerve transfer might be more beneficial for restoring control over the affected limb by the original motor representation.The thalamic-cortical pathway was enhanced within the interoception network after nerve repair and end-to-end nerve transfer.Brain areas related to cognition and emotion were enhanced after end-to-side nerve transfer.Our study revealed important brain networks related to different nerve reconstructions.These networks may be potential targets for enhancing motor recovery.

Three-Stage Transfer Learning with AlexNet50 for MRI Image Multi-Class Classification with Optimal Learning Rate

In radiology,magnetic resonance imaging(MRI)is an essential diagnostic tool that provides detailed images of a patient’s anatomical and physiological structures.MRI is particularly effective for detecting soft tissue anomalies.Traditionally,radiologists manually interpret these images,which can be labor-intensive and time-consuming due to the vast amount of data.To address this challenge,machine learning,and deep learning approaches can be utilized to improve the accuracy and efficiency of anomaly detection in MRI scans.This manuscript presents the use of the Deep AlexNet50 model for MRI classification with discriminative learning methods.There are three stages for learning;in the first stage,the whole dataset is used to learn the features.In the second stage,some layers of AlexNet50 are frozen with an augmented dataset,and in the third stage,AlexNet50 with an augmented dataset with the augmented dataset.This method used three publicly available MRI classification datasets:Harvard whole brain atlas(HWBA-dataset),the School of Biomedical Engineering of Southern Medical University(SMU-dataset),and The National Institute of Neuroscience and Hospitals brain MRI dataset(NINS-dataset)for analysis.Various hyperparameter optimizers like Adam,stochastic gradient descent(SGD),Root mean square propagation(RMS prop),Adamax,and AdamW have been used to compare the performance of the learning process.HWBA-dataset registers maximum classification performance.We evaluated the performance of the proposed classification model using several quantitative metrics,achieving an average accuracy of 98%.

CoTCPP integrates with BiOBr microspheres for improved solar-driven CO_(2)reduction performance

CO_(2) photoreduction into carbon-based chemicals has been considered as an appropriate way to alleviate the energy issue and greenhouse effect.Herein,the 5,10,15,20-tetra(4-carboxyphenyl)porphyrin cobalt(II)(CoTCPP)has been integrated with BiOBr microspheres and formed the CoTCPP/BiOBr composite.The as-prepared CoTCPP/BiOBr-2 composite shows optimized photocatalytic performance for CO_(2) conversion into CO and CH_(4) upon irradiation with 300 W Xe lamp,which is 2.03 and 2.58 times compared to that of BiOBr,respectively.The introduced CoTCPP significantly enhanced light absorption properties,promoted rapid separation of photogenerated carriers and boosted the chemisorption of CO_(2) molecules.The metal Co^(2+) at the center of the porphyrin molecules also acts as adsorption center for CO_(2) molecules,accelerating the CO_(2) conversion into CO and CH_(4).The possible mechanism of CO_(2) photoreduction was explored by in-situ FT-IR spectra.This work offers a new possibility for the preparation of advanced photocatalysts.

Brachioradialis tendon transfer and palmaris longus tendon graft for thumb avulsion:A case report and review of literature

BACKGROUND Thumb replantation following complete traumatic avulsion requires complex techniques to restore function,especially in cases of avulsion at the level of the metacarpophalangeal joint(MCP I)and avulsion of the flexor pollicis longus(FPL)at the musculotendinous junction.Possible treatments include direct tendon suture or tendon transfer,most commonly from the ring finger.To optimize function and avoid donor finger complications,we performed thumb replantation with flexion restoration using brachioradialis(BR)tendon transfer with palmaris longus(PL)tendon graft.CASE SUMMARY A 20-year-old left-handed male was admitted for a complete traumatic left thumb amputation following an accident while sliding from the top of a handrail.The patient presented with skin and bone avulsion at the MCP I,avulsion of the FPL tendon at the musculotendinous junction(zone 5),avulsion of the extensor pollicis longus tendon(zone T3),and avulsion of the thumb’s collateral arteries and nerves.The patient was treated with two stage thumb repair.The first intervention consisted of thumb replantation with MCP I arthrodesis,resection of avulsed FPL tendon and implantation of a silicone tendon prosthesis.The second intervention consisted of PL tendon graft and BR tendon transfer.Follow-up at 10 months showed good outcomes with active interphalangeal flexion of 70°,grip strength of 45 kg,key pinch strength of 15 kg and two-point discrimination threshold of 4 mm.CONCLUSION Flexion restoration after complete thumb amputation with FPL avulsion at the musculotendinous junction can be achieved using BR tendon transfer with PL tendon graft.

Processing,microstructure,and mechanical properties of wire arc additively-manufactured AZ91 magnesium alloy using cold arc process

Thin walls of an AZ91 magnesium alloy with fine equiaxed grains were fabricated via cold arc-based wire arc additive manufacturing(CA-WAAM),and the droplet transfer behaviours,microstructures,and mechanical properties were investigated.The results showed that the cold arc process reduced splashing at the moment of liquid bridge breakage and effectively shortened the droplet transfer period.The microstructures of the deposited samples exhibited layered characteristics with alternating distributions of coarse and fine grains.During layer-by-layer deposition,the β-phase precipitated and grew preferentially along grain boundaries,while the fineη-Al_(8)Mn_(5)phase was dispersed in the α-Mg matrix.The mechanical properties of the CA-WAAM deposited sample showed isotropic characteristics.The ultimate tensile strength and elongation in the building direction(BD)were 282.7 MPa and 14.2%,respectively.The microhardness values of the deposited parts were relatively uniform,with an average value of HV 69.6.

Spatiotemporal variation and influencing factors of desertification sensitivity on the Qinghai-Xizang Plateau,China

Due to irrational human activities and extreme climate,the Qinghai-Xizang Plateau,China,faces a serious threat of desertification.Desertification has a detrimental effect on the ecological environment and socioeconomic development.In this study,the desertification sensitivity index(DSI)model was established by integrating the spatial distance model and environmentally sensitive area index evaluation method,and then the model was used to quantitatively analyze the spatial and temporal characteristics of desertification sensitivity of the Qinghai-Xizang Plateau from 1990 to 2020.The results revealed that:(1)a general increasing tendency from southeast to northwest was identified in the spatial distribution of desertification sensitivity.The low-sensitivity areas were mostly concentrated in the Hengduan and Nyaingqêntanglha mountains and surrounding forest and meadow areas.The high-sensitivity areas were located mainly in the Kunlun and Altun mountains and surrounding decertified areas.The center of gravity of all types of desertification-sensitive areas moved to the northwest,and the desertification sensitivity showed a decreasing trend as a whole;(2)the area of highly sensitive desertification areas decreased by 8.37%,with extreme sensitivity being the largest change among the sensitivity types.The desertification sensitivity transfer was characterized by a greater shift to lower sensitivity levels(24.56%)than to higher levels(2.03%),which demonstrated a declining trend;(3)since 1990,the change in desertification sensitivity has been dominated by the stabilizing type Ⅰ(29.30%),with the area of continuously increasing desertification sensitivity accounting for only 1.10%,indicating that the management of desertification has achieved positive results in recent years;and(4)natural factors have had a more significant impact on desertification sensitivity on the Xizang Plateau,whereas socioeconomic factors affected only localized areas.The main factors influencing desertification sensitivity were vegetation drought tolerance and aridity index.Studying spatiotemporal variations in desertification sensitivity and its influencing factors can provide a scientific foundation for developing strategies to control desertification on the Qinghai-Xizang Plateau.Dividing different desertification-sensitive areas on the basis of these patterns of change can facilitate the formulation of more targeted management and protection measures,contributing to ecological construction and sustainable economic development in the area.

Optimizing distribution of multiple tuned mass dampers for building structures with inverse element exchange method

Multiple tuned mass dampers(MTMDs)reduce dynamic response with multiple specified frequencies of building structures.Many optimization algorithms for placement design exist,though they rarely conform to code-based verification nor produce high quality solutions without high computational effort and high complexity.This study proposes an inverse element exchange method(IEEM)with multi-level programming and compares it to a single tuned mass damper(STMD)and uniform distribution of multiple tuned mass dampers in the frequency and time domains.A ten-story shear building is used for the numerical case study.The results show that the proposed method can offer improvement over the STMD,uniform distribution of multiple tuned mass dampers,and distribution optimized by genetic algorithms(GA)with regard to minimizing the interstory drift ratio(IDR)in both the frequency and time domains and the time consumption for optimization.

An Energy Management System with Mobile Energy Station Based Wireless Energy Transfer:System Design and Prototype Implementation

In indoor environments,various batterypowered Internet of Things(IoT)devices,such as remote controllers and electronic tags on high-level shelves,require efficient energy management.However,manually monitoring remaining energy levels and battery replacement is both inadequate and costly.This paper introduces an energy management system for indoor IoT,which includes a mobile energy station(ES)for enabling on-demand wireless energy transfer(WET)in radio frequency(RF),some energy receivers(ERs),and a cloud server.By implementing a two-stage positioning system and embedding energy receivers into traditional IoT devices,we robustly manage their energy storage.The experimental results demonstrate that the energy receiver can harvest a minimum power of 58 mW.

IDS-INT:Intrusion detection system using transformer-based transfer learning for imbalanced network traffic

A network intrusion detection system is critical for cyber security against llegitimate attacks.In terms of feature perspectives,network traffic may include a variety of elements such as attack reference,attack type,a subcategory of attack,host information,malicious scripts,etc.In terms of network perspectives,network traffic may contain an imbalanced number of harmful attacks when compared to normal traffic.It is challenging to identify a specific attack due to complex features and data imbalance issues.To address these issues,this paper proposes an Intrusion Detection System using transformer-based transfer learning for Imbalanced Network Traffic(IDS-INT).IDS-INT uses transformer-based transfer learning to learn feature interactions in both network feature representation and imbalanced data.First,detailed information about each type of attack is gathered from network interaction descriptions,which include network nodes,attack type,reference,host information,etc.Second,the transformer-based transfer learning approach is developed to learn detailed feature representation using their semantic anchors.Third,the Synthetic Minority Oversampling Technique(SMOTE)is implemented to balance abnormal traffic and detect minority attacks.Fourth,the Convolution Neural Network(CNN)model is designed to extract deep features from the balanced network traffic.Finally,the hybrid approach of the CNN-Long Short-Term Memory(CNN-LSTM)model is developed to detect different types of attacks from the deep features.Detailed experiments are conducted to test the proposed approach using three standard datasets,i.e.,UNsWNB15,CIC-IDS2017,and NSL-KDD.An explainable AI approach is implemented to interpret the proposed method and develop a trustable model.

A single micro-LED manipulation system based on micro-gripper

Micro-LEDs(μLEDs)have advantages in terms of brightness,power consumption,and response speed.In addition,they can also be used as micro-sensors implanted in the body via flexible electronic skin.One of the key techniques involved in the fabrication ofμLED-based devices is transfer printing.Although numerous methods have been proposed for transfer printing,improving the yield ofμLED arrays is still a formidable task.In this paper,we propose a novel method for improving the yield ofμLED arrays transferred by the stamping method,using an innovative design of piezoelectrically driven asymmetric micro-gripper.Traditional grippers are too large to manipulateμLEDs,and therefore two micro-sized cantilevers are added at the gripper tips.AμLED manipulation system is constructed based on the micro-gripper together with a three-dimensional positioning system.Experimental results using this system show that it can be used successfully to manipulateμLED arrays.

Decade Milestone Advancement of Defect-Engineered g-C_(3)N_(4) for Solar Catalytic Applications

Over the past decade, graphitic carbon nitride(g-C_(3)N_(4)) has emerged as a universal photocatalyst toward various sustainable carbo-neutral technologies. Despite solar applications discrepancy, g-C_(3)N_(4) is still confronted with a general fatal issue of insufficient supply of thermodynamically active photocarriers due to its inferior solar harvesting ability and sluggish charge transfer dynamics. Fortunately, this could be significantly alleviated by the “all-in-one” defect engineering strategy, which enables a simultaneous amelioration of both textural uniqueness and intrinsic electronic band structures. To this end, we have summarized an unprecedently comprehensive discussion on defect controls including the vacancy/non-metallic dopant creation with optimized electronic band structure and electronic density, metallic doping with ultraactive coordinated environment(M–N_(x), M–C_(2)N_(2), M–O bonding), functional group grafting with optimized band structure, and promoted crystallinity with extended conjugation π system with weakened interlayered van der Waals interaction. Among them, the defect states induced by various defect types such as N vacancy, P/S/halogen dopants, and cyano group in boosting solar harvesting and accelerating photocarrier transfer have also been emphasized. More importantly, the shallow defect traps identified by femtosecond transient absorption spectra(fs-TAS) have also been highlighted. It is believed that this review would pave the way for future readers with a unique insight into a more precise defective g-C_(3)N_(4) “customization”, motivating more profound thinking and flourishing research outputs on g-C_(3)N_(4)-based photocatalysis.

Causal Analysis Between Rice Growth and Cadmium Accumulation and Transfer under Arbuscular Mycorrhizal Inoculation

Cadmium(Cd)contamination in rice has been a serious threat to human health.To investigate the effects of arbuscular mycorrhizal fungi(AMF)on the Cd translocation in rice,a controlled pot experiment was conducted.The results indicated that AMF significantly increased rice biomass,with an increase of up to 40.0%,particularly in root biomass by up to 68.4%.Notably,the number of prominent rice individuals also increased,and their plasticity was enhanced following AMF inoculation.AMF led to an increase in the net photosynthetic rate and antioxidant enzyme activity of rice.In the AMF treatment group,the Cd concentration in the rice roots was significantly higher(19.1%‒68.0%)compared with that in the control group.Conversely,the Cd concentration in the rice seeds was lower in the AMF treatment group,indicating that AMF facilitated the sequestration of Cd in rice roots and reduced Cd accumulation in the seeds.Path coefficients varied across different treatments,suggesting that AMF inoculation reduced the direct impact of soil Cd concentration on the total Cd accumulation in seeds.The translocation of Cd was consistently associated with simultaneous growth dilution and compensatory accumulation as a result of mycorrhizal effects.Our study quantitatively analyzed this process through path analysis and clarified the causal relationship between rice growth and Cd transfer under the influence of AMF.

Post-acute ischemic stroke hyperglycemia aggravates destruction of the blood-brain barrier

Post-acute ischemic stroke hyperglycemia increases the risk of hemorrhagic transformation,which is associated with blood-brain barrier disruption.Brain microvascular endothelial cells are a major component of the blood-brain barrier.Intercellular mitochondrial transfer has emerged as a novel paradigm for repairing cells with mitochondrial dysfunction.In this study,we first investigated whether mitochondrial transfer exists between brain microvascular endothelial cells,and then investigated the effects of post-acute ischemic stroke hyperglycemia on mitochondrial transfer between brain microvascular endothelial cells.We found that healthy brain microvascular endothelial cells can transfer intact mitochondria to oxygen glucose deprivation-injured brain microvascular endothelial cells.However,post-oxygen glucose deprivation hyperglycemia hindered mitochondrial transfer and exacerbated mitochondrial dysfunction.We established an in vitro brain microvascular endothelial cell model of the blood-brain barrier.We found that post-acute ischemic stroke hyperglycemia reduced the overall energy metabolism levels of brain microvascular endothelial cells and increased permeability of the blood-brain barrier.In a clinical study,we retrospectively analyzed the relationship between post-acute ischemic stroke hyperglycemia and the severity of hemorrhagic transformation.We found that post-acute ischemic stroke hyperglycemia serves as an independent predictor of severe hemorrhagic transformation.These findings suggest that post-acute ischemic stroke hyperglycemia can aggravate disruption of the blood-brain barrier by inhibiting mitochondrial transfer.

Hybrid-Vlasov simulation of soft X-ray emissions at the Earth’s dayside magnetospheric boundaries

Solar wind charge exchange produces emissions in the soft X-ray energy range which can enable the study of near-Earth space regions such as the magnetopause,the magnetosheath and the polar cusps by remote sensing techniques.The Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)and Lunar Environment heliospheric X-ray Imager(LEXI)missions aim to obtain soft Xray images of near-Earth space thanks to their Soft X-ray Imager(SXI)instruments.While earlier modeling works have already simulated soft X-ray images as might be obtained by SMILE SXI during its mission,the numerical models used so far are all based on the magnetohydrodynamics description of the space plasma.To investigate the possible signatures of ion-kinetic-scale processes in soft Xray images,we use for the first time a global hybrid-Vlasov simulation of the geospace from the Vlasiator model.The simulation is driven by fast and tenuous solar wind conditions and purely southward interplanetary magnetic field.We first produce global X-ray images of the dayside near-Earth space by placing a virtual imaging satellite at two different locations,providing meridional and equatorial views.We then analyze regional features present in the images and show that they correspond to signatures in soft X-ray emissions of mirrormode wave structures in the magnetosheath and flux transfer events(FTEs)at the magnetopause.Our results suggest that,although the time scales associated with the motion of those transient phenomena will likely be significantly smaller than the integration time of the SMILE and LEXI imagers,mirror-mode structures and FTEs can cumulatively produce detectable signatures in the soft X-ray images.For instance,a local increase by 30%in the proton density at the dayside magnetopause resulting from the transit of multiple FTEs leads to a 12%enhancement in the line-of-sight-and time-integrated soft X-ray emissivity originating from this region.Likewise,a proton density increase by 14%in the magnetosheath associated with mirror-mode structures can result in an enhancement in the soft X-ray signal by 4%.These are likely conservative estimates,given that the solar wind conditions used in the Vlasiator run can be expected to generate weaker soft X-ray emissions than the more common denser solar wind.These results will contribute to the preparatory work for the SMILE and LEXI missions by providing the community with quantitative estimates of the effects of small-scale,transient phenomena occurring on the dayside.

Improvement of High-Speed Detection Algorithm for Nonwoven Material Defects Based on Machine Vision

Defect detection is vital in the nonwoven material industry,ensuring surface quality before producing finished products.Recently,deep learning and computer vision advancements have revolutionized defect detection,making it a widely adopted approach in various industrial fields.This paper mainly studied the defect detection method for nonwoven materials based on the improved Nano Det-Plus model.Using the constructed samples of defects in nonwoven materials as the research objects,transfer learning experiments were conducted based on the Nano DetPlus object detection framework.Within this framework,the Backbone,path aggregation feature pyramid network(PAFPN)and Head network models were compared and trained through a process of freezing,with the ultimate aim of bolstering the model's feature extraction abilities and elevating detection accuracy.The half-precision quantization method was used to optimize the model after transfer learning experiments,reducing model weights and computational complexity to improve the detection speed.Performance comparisons were conducted between the improved model and the original Nano Det-Plus model,YOLO,SSD and other common industrial defect detection algorithms,validating that the improved methods based on transfer learning and semi-precision quantization enabled the model to meet the practical requirements of industrial production.

Recent advances in high charge density triboelectric nanogenerators

Triboelectric materials with high charge density are the building-block for the commercial application of triboelectric nanogenerators(TENGs).Unstable dynamic processes influence the change of the charge density on the surface and inside of triboelectric materials.The charge density of triboelectric materials depends on the surface and the internal charge transfer processes.The focus of this review is on recent advances in high charge density triboelectric materials and advances in the fabrication of TENGs.We summarize the existing strategies for achieving high charge density in triboelectric materials as well as their fundamental properties.We then review current optimization methods for regulating dynamic charge transfer processes to increase the output charge density:first,increasing charge injection and limiting charge dissipation to achieve a high average surface charge density,and second,regulating the internal charge transfer process and storing charge in triboelectric materials to increase the output charge density.Finally,we present the challenges and prospects in developing high-performance triboelectric materials.

Effects of projectile parameters on the momentum transfer and projectile melting during hypervelocity impact

The effects of projectile/target impedance matching and projectile shape on energy,momentum transfer and projectile melting during collisions are investigated by numerical simulation.By comparing the computation results with the experimental results,the correctness of the calculation and the statistical method of momentum transfer coefficient is verified.Different shapes of aluminum,copper and heavy tungsten alloy projectiles striking aluminum,basalt,and pumice target for impacts up to 10 km/s are simulated.The influence mechanism of the shape of the projectile and projectile/target density on the momentum transfer was obtained.With an increase in projectile density and length-diameter ratio,the energy transfer time between the projectile and targets is prolonged.The projectile decelerates slowly,resulting in a larger cratering depth.The energy consumed by the projectile in the excavation stage increased,resulting in lower mass-velocity of ejecta and momentum transfer coefficient.The numerical simulation results demonstrated that for different projectile/target combinations,the higher the wave impedance of the projectile,the higher the initial phase transition velocity and the smaller the mass of phase transition.The results can provide theoretical guidance for kinetic impactor design and material selection.

Construction of Pd-doped RuO_(2) nanosheets for efficient and stable acidic water oxidation

RuO_(2) has been considered a potential alternative to commercial IrO_(2) for the oxygen evolution reaction(OER)due to its superior intrinsic activity.However,its inherent structure dissolution in acidic environments restricts its commercial applications.In this study,we report a novel Pd-doped ruthenium oxide(Pd–RuO_(2))nanosheet catalyst that exhibits improved activity and stability through a synergistic effect of Pd modulation of Ru electronic structure and the two-dimensional structure.The catalyst exhibits excellent performance,achieving an overpotential of only 204 mVat a current density of 10 mA cm^(-2).Impressively,after undergoing 8000 cycles of cyclic voltammetry testing,the overpotential merely decreased by 5 mV.The PEM electrolyzer with Pd0.08Ru0.92O_(2) as an anode catalyst survived an almost 130 h operation at 200 mA cm^(-2).To elucidate the underlying mechanisms responsible for the enhanced stability,we conducted an X-ray photoelectron spectroscopy(XPS)analysis,which reveals that the electron transfer from Pd to Ru effectively circumvents the over-oxidation of Ru,thus playing a crucial role in enhancing the catalyst's stability.Furthermore,density functional theory(DFT)calculations provide compelling evidence that the introduction of Pd into RuO_(2) effectively modulates electron correlations and facilitates the electron transfer from Pd to Ru,thereby preventing the overoxidation of Ru.Additionally,the application of the two-dimensional structure effectively inhibited the aggregation and growth of nanoparticles,further bolstering the structural integrity of the catalyst.

Assessments of Data-Driven Deep Learning Models on One-Month Predictions of Pan-Arctic Sea Ice Thickness

In recent years,deep learning methods have gradually been applied to prediction tasks related to Arctic sea ice concentration,but relatively little research has been conducted for larger spatial and temporal scales,mainly due to the limited time coverage of observations and reanalysis data.Meanwhile,deep learning predictions of sea ice thickness(SIT)have yet to receive ample attention.In this study,two data-driven deep learning(DL)models are built based on the ConvLSTM and fully convolutional U-net(FC-Unet)algorithms and trained using CMIP6 historical simulations for transfer learning and fine-tuned using reanalysis/observations.These models enable monthly predictions of Arctic SIT without considering the complex physical processes involved.Through comprehensive assessments of prediction skills by season and region,the results suggest that using a broader set of CMIP6 data for transfer learning,as well as incorporating multiple climate variables as predictors,contribute to better prediction results,although both DL models can effectively predict the spatiotemporal features of SIT anomalies.Regarding the predicted SIT anomalies of the FC-Unet model,the spatial correlations with reanalysis reach an average level of 89%over all months,while the temporal anomaly correlation coefficients are close to unity in most cases.The models also demonstrate robust performances in predicting SIT and SIE during extreme events.The effectiveness and reliability of the proposed deep transfer learning models in predicting Arctic SIT can facilitate more accurate pan-Arctic predictions,aiding climate change research and real-time business applications.

Coherent optical frequency transfer via 972-km fiber link

We demonstrate coherent optical frequency dissemination over a distance of 972 km by cascading two spans where the phase noise is passively compensated for.Instead of employing a phase discriminator and a phase locking loop in the conventional active phase control scheme,the passive phase noise cancellation is realized by feeding double-trip beat-note frequency to the driver of the acoustic optical modulator at the local site.This passive scheme exhibits fine robustness and reliability,making it suitable for long-distance and noisy fiber links.An optical regeneration station is used in the link for signal amplification and cascaded transmission.The phase noise cancellation and transfer instability of the 972-km link is investigated,and transfer instability of 1.1×10^(-19)at 10^(4)s is achieved.This work provides a promising method for realizing optical frequency distribution over thousands of kilometers by using fiber links.