Properties of focused Laguerre–Gaussian beam propagating in anisotropic ocean turbulence

We analyze the properties of a focused Laguerre–Gaussian(LG)beam propagating through anisotropic ocean turbulence based on the Huygens–Fresnel principle.Under the Rytov approximation theory,we derive the analytical formula of the channel capacity of the focused LG beam in the anisotropic ocean turbulence,and analyze the relationship between the capacity and the light source parameters as well as the turbulent ocean parameters.It is found that the focusing mirror can greatly enhance the channel capacity of the system at the geometric focal plane in oceanic turbulence.The results also demonstrate that the communication link can obtain high channel capacity by adopting longer beam wavelength,greater initial beam waist radius,and larger number of transmission channels.Further,the capacity of the system increases with the decrease of the mean squared temperature dissipation rate,temperature-salinity contribution ratio and turbulence outer scale factor,and with the increase of the kinetic energy dissipation rate per unit mass of fluid,turbulence inner scale factor and anisotropy factor.Compared to a Hankel–Bessel beam with diffraction-free characteristics and unfocused LG beam,the focused LG beam shows superior anti-turbulence interference properties,which provide a theoretical reference for research and development of underwater optical communication links using focused LG beams.

Experimental observation of Fermi-level flat band in novel kagome metal CeNi_(5)

Kagome materials are a class of material with a lattice structure composed of corner-sharing triangles that produce various exotic electronic phenomena,such as Dirac fermions,van Hove singularities,and flat bands.However,most of the known kagome materials have a flat band detached from the Fermi energy,which limits the investigation of the emergent flat band physics.In this work,by combining soft x-ray angle-resolved photoemission spectroscopy(ARPES)and the first-principles calculations,the electronic structure is investigated of a novel kagome metal CeNi_(5) with a clear dispersion along the kz direction and a Fermi level flat band in theΓ–K–M–Γplane.Besides,resonant ARPES experimental results indicate that the valence state of Ce ions is close to 4^(+),which is consistent with the transport measurement result.Our results demonstrate the unique electronic properties of CeNi_(5) as a new kagome metal and provide an ideal platform for exploring the flat band physics and the interactions between different types of flat bands by tuning the valence state of Ce ions.

Rethinking multi-spatial information for transferable adversarial attacks on speaker recognition systems

Adversarial attacks have been posing significant security concerns to intelligent systems,such as speaker recognition systems(SRSs).Most attacks assume the neural networks in the systems are known beforehand,while black-box attacks are proposed without such information to meet practical situations.Existing black-box attacks improve trans-ferability by integrating multiple models or training on multiple datasets,but these methods are costly.Motivated by the optimisation strategy with spatial information on the perturbed paths and samples,we propose a Dual Spatial Momentum Iterative Fast Gradient Sign Method(DS-MI-FGSM)to improve the transferability of black-box at-tacks against SRSs.Specifically,DS-MI-FGSM only needs a single data and one model as the input;by extending to the data and model neighbouring spaces,it generates adver-sarial examples against the integrating models.To reduce the risk of overfitting,DS-MI-FGSM also introduces gradient masking to improve transferability.The authors conduct extensive experiments regarding the speaker recognition task,and the results demonstrate the effectiveness of their method,which can achieve up to 92%attack success rate on the victim model in black-box scenarios with only one known model.

Virtually coupled train set control subject to space-time separation:A distributed economic MPC approach with emergency braking configuration

The emerging virtual coupling technology aims to operate multiple train units in a Virtually Coupled Train Set(VCTS)at a minimal but safe distance.To guarantee collision avoidance,the safety distance should be calculated using the state-of-the-art space-time separation principle that separates the Emergency Braking(EB)trajectories of two successive units during the whole EB process.In this case,the minimal safety distance is usually numerically calculated without an analytic formulation.Thus,the constrained VCTS control problem is hard to address with space-time separation,which is still a gap in the existing literature.To solve this problem,we propose a Distributed Economic Model Predictive Control(DEMPC)approach with computation efficiency and theoretical guarantee.Specifically,to alleviate the computation burden,we transform implicit safety constraints into explicitly linear ones,such that the optimal control problem in DEMPC is a quadratic programming problem that can be solved efficiently.For theoretical analysis,sufficient conditions are derived to guarantee the recursive feasibility and stability of DEMPC,employing compatibility constraints,tube techniques and terminal ingredient tuning.Moreover,we extend our approach with globally optimal and distributed online EB configuration methods to shorten the minimal distance among VCTS.Finally,experimental results demonstrate the performance and advantages of the proposed approaches.

Advances in the Study of Psychological Stress and Eating Behavior in Children and Adolescents

With the rapid development and change in society,children and adolescents are facing more and more psychological pressure,which comes not only from academic performance and interpersonal relationships but also from family environment,social expectations and other aspects.Psychological stress not only affects the mental health of children and adolescents but is also closely related to their eating behavior.Therefore,exploring the relationship between psychological stress and eating behaviors is of great significance in promoting the physical and mental health development of children and adolescents.Based on this,the study reviewed the research progress on the relationship between psychological stress and eating behavior of children and adolescents in recent years.The relationships between psychological stress and general eating behaviors,abnormal eating behaviors and eating disorders were successively reviewed,and the related physiological mechanisms were explored with a view to providing a scientific basis for mental health education and eating behavior intervention for children and adolescents.

The Efficacy of Electromyographic Biofeedback Combined with Swallowing Training on Post- Stroke Dysphagia

Objective:This paper focuses on the research and discussion of the efficacy of electromyographic biofeedback combined with swallowing training on post-stroke dysphagia.Methods:This study randomly sampled and analyzed 68 patients with post-stroke dysphagia from January 2023 to December 2023,34 cases of swallowing training intervention were grouped as the control group,and 34 cases of electromyography biofeedback combined with swallowing training intervention were grouped as the study group,and the clinical therapeutic effects of the two groups of patients after receiving the two different modes of intervention were compared.Results:The swallowing function of patients in both groups improved,and the VFSS score of patients in the seminar group was significantly higher than that of the control group,indicating that the clinical efficacy of the seminar group was more significant.The nasal feeding tube extraction rate,extraction time,and quality of life scores of the seminar group were better than those of the control group(P<0.05),which is of research value.Conclusion:For patients with post-stroke dysphagia,treatment with electromyography biofeedback combined with swallowing training mode can significantly improve their swallowing function.This effective intervention can not only shorten the time for patients to remove the nasal feeding tube but also help to improve the quality of life of patients,which is worth using.

Forced Inspiratory Flow Volume Curve in Patients with Obstructive Sleep Apnea-Hypopnea Syndrome

Objective: Obstructive sleep apnea-hypopnea syndrome (OSA) is a disease of obstructive apnea or hypopnea caused by a repeated partial or complete collapse of the upper airway during sleep. The inspiratory part of the flow-volume curve (F-V curve) can be used as an auxiliary means to evaluate upper airway obstruction in adults. This study is to evaluate the ability of the F-V curve to predict the OSA and explore inspiratory indicators related to airway obstruction during sleep. Methods: There were 332 patients included in this cross-sectional study, who were accompanied by snoring, daytime sleepiness and other symptoms, with suspicion of OSA. According to the nocturnal polysomnography, the subjects were distributed into mild to moderate OSA group, severe OSA group and non-OSA group. A pulmonary function test was used to collect the subjects’ spirometry and F-V curves. Results: There was no significant difference in a variety of indices derived from the F-V curve between OSA and normal subjects, including 25% inspiratory flow rate, middle inspiratory flow rate, 75% inspiratory flow rate, peak flow rate, and forced inspiratory flow rate in the first second. The pulmonary function parameters were significantly correlated with the weight, age and sex of the subjects. Conclusion: These findings suggest that the inspiratory curve of pulmonary function cannot evaluate the upper airway abnormalities in patients with obstructive apnea-hypopnea syndrome.

Mutual regulation of microglia and astrocytes after Gas6 inhibits spinal cord injury

Invasive inflammation and excessive scar formation are the main reasons for the difficulty in repairing nervous tissue after spinal cord injury.Microglia and astrocytes play key roles in the spinal cord injury micro-environment and share a close interaction.However,the mechanisms involved remain unclear.In this study,we found that after spinal cord injury,resting microglia(M0)were polarized into pro-inflammatory phenotypes(MG1 and MG3),while resting astrocytes were polarized into reactive and scar-forming phenotypes.The expression of growth arrest-specific 6(Gas6)and its receptor Axl were significantly down-regulated in microglia and astrocytes after spinal cord injury.In vitro experiments showed that Gas6 had negative effects on the polarization of reactive astrocytes and pro-inflammatory microglia,and even inhibited the cross-regulation between them.We further demonstrated that Gas6 can inhibit the polarization of reactive astrocytes by suppressing the activation of the Yes-associated protein signaling pathway.This,in turn,inhibited the polarization of pro-inflammatory microglia by suppressing the activation of the nuclear factor-κB/p65 and Janus kinase/signal transducer and activator of transcription signaling pathways.In vivo experiments showed that Gas6 inhibited the polarization of pro-inflammatory microglia and reactive astrocytes in the injured spinal cord,thereby promoting tissue repair and motor function recovery.Overall,Gas6 may play a role in the treatment of spinal cord injury.It can inhibit the inflammatory pathway of microglia and polarization of astrocytes,attenuate the interaction between microglia and astrocytes in the inflammatory microenvironment,and thereby alleviate local inflammation and reduce scar formation in the spinal cord.

Population-level economic burden of lung cancer in China:Provisional prevalence-based estimations,2017-2030

Objective:Population-level economic burden is essential for prioritizing healthcare resources and healthcare budget making in the future.However,little is known about the economic burden of lung cancer in China.Methods:A prevalence-based approach was adopted to estimate the economic burden of lung cancer,including direct expenditure(medical and non-medical)and indirect cost(disability and premature death).Data on direct expenditure and work-loss days per patient in each year post-diagnosis were obtained from two primary surveys.Other parameters were obtained from literatures and official reports.Projections were conducted based on varying parameters.All expenditure data were reported in United States dollars(USD)using 2017 value(exchange rate:1 USD=6.760 CNY),with the discount rate of 3%.Results:The total economic burden of lung cancer was estimated to be 25,069 million USD in China in 2017(0.121%of gross domestic productivity,GDP).The estimated direct expenditure was 11,098 million USD,up to1.43%of total healthcare expenditure for China,covering 10,303 million USD and 795 million USD for medical and non-medical expenditure,respectively.The estimated indirect cost was 13,971 million,including 1,517 million USD due to disability and 12,454 million USD due to premature death.Under current assumptions,the projected total economic burden would increase to 30.1 billion USD,40.4 billion USD,and 53.4 billion USD in 2020,2025,and 2030,accounting for 0.121%,0.131%,and 0.146%of China's GDP,respectively.However,if China meets the United Nation sustainable development goal of reducing premature death from non-communicable diseases by one-third by 2030,the total economic burden in 2030 would be 31.9 billion USD,0.087%of China's GDP.Conclusions:The economic burden of lung cancer in China in 2017 is substantial and more likely to increase significantly in the future.Policy makers need to take urgent actions in budget making for health systems.The economic burden could be alleviated by reducing the disease burden of lung cancer via effective control and prevention actions.

First genetic assessment of brackish water polychaete Tylorrhynchus heterochaetus: mitochondrial CO/sequences reveal strong genetic differentiation and population expansion in samples collected from southeast China and north Vietnam

Tylorrhynchus heterochaetus is a widespread benthic polychaete worm found in coastal brackish waters of the west Pacific.It has high ecological and economic value as a biomarker of water quality and as a high-quality feed in aquaculture and fisheries and is considered a delicacy in some areas of Asia.However,it has experienced a marked reduction in recent years due to overexploitation as well as changes in the environment and climate.Here,to comprehensively understand its genetic background and thus provide insights for better conservation and utilization of this species,we assessed the genetic variability and demographic history of T.heterochaetus individuals sampled from eight locations along the coasts of southeast China and north Vietnam based on mitochondrial cytochrome c oxidase I(COI)sequences.We observed high haplotype diversity(Hd),with an average of 0.926,but relatively low nucleotide diversity(π),with a mean of 0.032 across all samples.A total of 94 polymorphic sites and 85 haplotypes were identified among 320 individuals.The pairwise genetic distances among haplotypes ranged from 0.001 to 0.067,with the high intraspecific divergence possibly reflecting geographic isolation and gene pool fragmentation.Significant genetic structures were revealed among the studied locations;specifically,the eight locations could be treated as six genetically different populations based on pairwiseΦST results(0.026–0.951,P<0.01).A significant pattern of isolation-by-distance was detected between the genetic and geographic distances(r=0.873,P=0.001).Three geographic lineages were defined based on phylogenetic tree and network analyses of COI haplotypes.AMOVA results indicated that genetic variations mainly occurred among the three lineages(89.96%).Tests of neutrality and mismatch distribution suggested that T.heterochaetus underwent recent population expansion.These results provide the first report on the genetic status of T.heterochaetus and will be valuable for the management of genetic resources and better understanding of the ecology and evolution in this species.

Whole-genome sequencing provides insights into the genetic diversity and domestication of bitter gourd(Momordica spp.)

Bitter gourd(Momordica charantia)is a popular cultivated vegetable in Asian and African countries.To reveal the characteristics of the genomic structure,evolutionary trajectory,and genetic basis underlying the domestication of bitter gourd,we performed whole-genome sequencing of the cultivar Dali-11 and the wild small-fruited line TR and resequencing of 187 bitter gourd germplasms from 16 countries.The major gene clusters(Bi clusters)for the biosynthesis of cucurbitane triterpenoids,which confer a bitter taste,are highly conserved in cucumber,melon,and watermelon.Comparative analysis among cucurbit genomes revealed that the Bi cluster involved in cucurbitane triterpenoid biosynthesis is absent in bitter gourd.Phylogenetic analysis revealed that the TR group,including 21 bitter gourd germplasms,may belong to a new species or subspecies independent from M.charantia.Furthermore,we found that the remaining 166 M.charantia germplasms are geographically differentiated,and we identified 710,412,and 290 candidate domestication genes in the South Asia,Southeast Asia,and China populations,respectively.This study provides new insights into bitter gourd genetic diversity and domestication and will facilitate the future genomics-enabled improvement of bitter gourd.

Experimental demonstration of influence of underwater turbulence on ghost imaging

It is difficult to obtain a clear image in underwater turbulence environment with classical imaging methods due to the absorption, scattering, and underwater turbulence on the propagation beam.However, ghost imaging(GI), a nonlocally imaging technique, has shown the turbulence-free ability in atmospheric turbulence by exploiting the second-order correlation between the signal beam and the reference beam.In this paper, we experimentally investigate the imaging quality of GI affected by the underwater environment, where the underwater environment is simulated by a 1 m×0.4 m×0.4 m tank with distilled water.The water temperature is controlled by a heater inside the tank, and a temperature gradient is obtained by putting the heater at different positions of the tank.The water vibration is produced by a heavy force, and the turbid medium is obtained by dissolving very small specks of CaCO3 in the water.A set of Hadamard speckle pattern pairs are generated and modulated on the incident beam, and then the beam illuminates on an unknown object after passing through the simulated underwater environment.With the second-order correlations, the image is reconstructed under different temperature gradients, water vibration, and turbid medium ratios.The results show that GI has the turbulence-free ability under lower temperature gradient, water vibration, and turbid media.The structural similarity image measurement(SSIM)values of the reconstructed images only start to decrease when the temperature gradient is greater than 4.0℃.The same temperature gradient produced at the different positions has a little effect on the quality of the underwater GI.

Compressed ghost imaging based on differential speckle patterns

We propose a compressed ghost imaging scheme based on differential speckle patterns,named CGI-DSP.In the scheme,a series of bucket detector signals are acquired when a series of random speckle patterns are employed to illuminate an unknown object.Then the differential speckle patterns(differential bucket detector signals)are obtained by taking the difference between present random speckle patterns(present bucket detector signals)and previous random speckle patterns(previous bucket detector signals).Finally,the image of object can be obtained directly by performing the compressed sensing algorithm on the differential speckle patterns and differential bucket detector signals.The experimental and simulated results reveal that CGI-DSP can improve the imaging quality and reduce the number of measurements comparing with the traditional compressed ghost imaging schemes because our scheme can remove the environmental illuminations efficiently.

Leaching of lead from zinc leach residue in acidic calcium chloride aqueous solution

A process with potentially reduced environmental impacts and occupational hazards of lead-bearing zinc plant residue was studied to achieve a higher recovery of lead via a cost-effective and environmentally friendly process. This paper describes an optimization study on the leaching of lead from zinc leach residue using acidic calcium chloride aqueous solution. Six main process conditions, i.e., the solution pH value, stirring rate, concentration of CaC12 aqueous solution, liquid-to-solid （L/S） ratio, leaching temperature, and leaching time, were inves- tigated. The microstructure and components of the residue and tailing were characterized using scanning electron microscopy （SEM） and X-ray diffraction （XRD）. On the basis of experimental results, the optimum reaction conditions were determined to be a solution pH value of 1, a stirring rate of 500 r·min-1, a CaC12 aqueous solution concentration of 400 g·L-1, a liquid-to-solid mass ratio of 7：1, a leaching tempera- ture of 80℃, and a leaching time of 45 min. The leaching rate of lead under these conditions reached 93.79%, with an iron dissolution rate of 19.28%. Silica did not take part in the chemical reaction during the leaching process and was accumulated in the residue.

Handwritten digit recognition based on ghost imaging with deep learning

We present a ghost handwritten digit recognition method for the unknown handwritten digits based on ghost imaging(GI)with deep neural network,where a few detection signals from the bucket detector,generated by the cosine transform speckle,are used as the characteristic information and the input of the designed deep neural network(DNN),and the output of the DNN is the classification.The results show that the proposed scheme has a higher recognition accuracy(as high as 98%for the simulations,and 91%for the experiments)with a smaller sampling ratio(say 12.76%).With the increase of the sampling ratio,the recognition accuracy is enhanced.Compared with the traditional recognition scheme using the same DNN structure,the proposed scheme has slightly better performance with a lower complexity and non-locality property.The proposed scheme provides a promising way for remote sensing.

Electrochemical process for recovery of metallic Mn from waste LiMn_(2)O_(4)-based Li-ion batteries in NaCl−CaCl_(2)melts

new method is proposed for the recovery of Mn via the direct electrochemical reduction of LiMn_(2)O_(4) from the waste of lithium-ion batteries in NaCl−CaCl_(2) melts at 750°C.The results show that the LiMn_(2)O_(4) reduction process by the electrochemical method on the coated electrode surface occurs in three steps:Mn(IV)→Mn(III)→Mn(II)→Mn.The products of this electro-deoxidation are CaMn2O4,MnO,(MnO)x(CaO)1−x,and Mn.Metal Mn appears when the electrolytic voltage increases to 2.6 V,which indicates that increasing the voltage may promote the deoxidation reaction process.With the advancement of the three-phase interline(3PI),electric deoxygenation gradually proceeds from the outer area of the crucible to the core.At high voltage,the kinetic process of the reduction reaction is accelerated,which generates double 3PIs at different stages.

Integration of Communication and Computing in Blockchain-Enabled Multi-Access Edge Computing Systems

Blockchain and multi-access edge com-puting(MEC)are two emerging promising tech-nologies that have received extensive attention from academia and industry.As a brand-new information storage,dissemination and management mechanism,blockchain technology achieves the reliable transmis-sion of data and value.While as a new computing paradigm,multi-access edge computing enables the high-frequency interaction and real-time transmission of data.The integration of communication and com-puting in blockchain-enabled multi-access edge com-puting networks has been studied without a systemat-ical view.In the survey,we focus on the integration of communication and computing,explores the mu-tual empowerment and mutual promotion effects be-tween the blockchain and MEC,and introduces the resource integration architecture of blockchain and multi-access edge computing.Then,the paper sum-marizes the applications of the resource integration ar-chitecture,resource management,data sharing,incen-tive mechanism,and consensus mechanism,and ana-lyzes corresponding applications in real-world scenar-ios.Finally,future challenges and potentially promis-ing research directions are discussed and present in de-tail.

Whole-genome resequencing infers genomic basis of giant phenotype in Siamese fighting fish(Betta splendens)

Understanding the genetic basis of phenotypes is of importance in evolutionary biology and for genetic improvement of economically valuable animals.The giant phenotype of the fighting fish,Betta splendens,provides a unique opportunity to explore the genetic architecture of overgrowth in body size.As such,we re-sequenced and analyzed the genomes of 54 fighting fish.Genome-wide FST and selective sweep analyses using 3582429 DNA variants revealed three genomic regions at chr1,chr9,and chr11 that were associated with the giant phenotype.With a total length of~3.5 Mb,these regions showed high divergence between the giant and non-giant bettas.In contrast,no signature of selection was detected in the wild-type fish.Transcriptome analysis of brain and muscle samples from giant and normal bettas identified 14 candidate genes that were likely responsible for the giant phenotype.Overall,our data provide novel insights into the genetic basis of body size variation.The genome sequences,transcriptome sequences,DNA sequence variants,and candidate genes for body size provide valuable resources for further biological and evolutionary studies,as well as for rapid improvement in growth-related traits.

Machine Learning to Instruct Single Crystal Growth by Flux Method

Growth of high-quality single crystals is of great significance for research of condensed matter physics. The exploration of suitable growing conditions for single crystals is expensive and time-consuming, especially for ternary compounds because of the lack of ternary phase diagram. Here we use machine learning(ML) trained on our experimental data to predict and instruct the growth. Four kinds of ML methods, including support vector machine(SVM), decision tree, random forest and gradient boosting decision tree, are adopted. The SVM method is relatively stable and works well, with an accuracy of 81% in predicting experimental results. By comparison,the accuracy of laboratory reaches 36%. The decision tree model is also used to reveal which features will take critical roles in growing processes.

Diffraction deep neural network based orbital angular momentum mode recognition scheme in oceanic turbulence

Orbital angular momentum(OAM)has the characteristics of mutual orthogonality between modes,and has been applied to underwater wireless optical communication(UWOC)systems to increase the channel capacity.In this work,we propose a diffractive deep neural network(DDNN)based OAM mode recognition scheme,where the DDNN is trained to capture the features of the intensity distribution of the OAM modes and output the corresponding azimuthal indices and radial indices.The results show that the proposed scheme can recognize the azimuthal indices and radial indices of the OAM modes accurately and quickly.In addition,the proposed scheme can resist weak oceanic turbulence(OT),and exhibit excellent ability to recognize OAM modes in a strong OT environment.The DDNN-based OAM mode recognition scheme has potential applications in UWOC systems.