Deep learning for determining pure isotropic proton spectra from solidstate spectra

Recently,an article on ^(1)H solid-state NMR spectra was published,in which the authors proposed a deep learning approach to infer the pure isotropic proton NMR spectra obtained at an infinite magic angle spinning(MAS)rate.This approach even allowed to obtain,by far,the best resolved ^(1)H spectra of molecular solids[1](https://doi.org/10.1002/anie.202216607).Deep learning based artificial intelligence is developing rapidly,and its application is deepening.Currently,there are many applications of deep learning in the field of magnetic resonance,such as the reconstruction of the under-sampled multidimensional spectra[2-4],the deconvolution of two-dimensional NMR spectra[5]and noise suppression and weak peak retrial[6],etc.

Tunable spectral continuous shift of high-order harmonic generation in atoms by a plasmon-assisted shaping pulse

We delve into the phenomenon of high-order harmonic generation within a helium atom under the influence of a plasmon-assisted shaping pulse.Our findings reveal an intriguing manipulation of the frequency peak position in the harmonic emission by adjusting the absolute phase parameter within the frequency domain of the shaping pulse.This phenomenon holds potential significance for experimental setups necessitating precisely tuned single harmonics.Notably,we observe a modulated shift in the created harmonic photon energy,spanning an impressive range of 1.2 eV.This frequency peak shift is rooted in the asymmetry exhibited by the rising and falling edges of the laser pulse,directly influencing the position of the peak frequency emission.Our study quantifies the dependence of this tuning range and the asymmetry of the laser pulse,offering valuable insights into the underlying mechanisms driving this phenomenon.Furthermore,our investigation uncovers the emergence of semi-integer order harmonics as the phase parameter is altered.We attribute this discovery to the intricate interference between harmonics generated by the primary and secondary return cores.This observation introduces an innovative approach for generating semi-integer order harmonics,thus expanding our understanding of high-order harmonic generation.Ultimately,our work contributes to the broader comprehension of complex phenomena in laser-matter interactions and provides a foundation for harnessing these effects in various applications,particularly those involving precise spectral control and the generation of unique harmonic patterns.

Wavelength calibration and spectral analysis of vacuum ultraviolet spectroscopy in EAST

A vacuum ultraviolet(VUV)spectroscopy with a focal length of 1 m has been engineered specifically for observing edge impurity emissions in Experimental Advanced Superconducting Tokamak(EAST).In this study,wavelength calibration for the VUV spectroscopy is achieved utilizing a zinc lamp.The grating angle and charge-coupled device(CCD)position are carefully calibrated for different wavelength positions.The wavelength calibration of the VUV spectroscopy is crucial for improving the accuracy of impurity spectral data,and is required to identify more impurity spectral lines for impurity transport research.Impurity spectra of EAST plasmas have also been obtained in the wavelength range of 50–300 nm with relatively high spectral resolution.It is found that the impurity emissions in the edge region are still dominated by low-Z impurities,such as carbon,oxygen,and nitrogen,albeit with the application of fulltungsten divertors on the EAST tokamak.

Core level excitation spectra of La and Mn ions in LaMnO3

Manganese-based perovskite is popular for research on ferromagnetic materials,and its spectroscopic studies are essential for understanding its electronic structure,dielectric,electrical,and magnetic properties.In this paper,the M-edge spectra of La ions and the M-edge,L-edge,and K-edge spectra of Mn ions in LaMnO3 are calculated by considering both the free-ion multiplet calculation and the crystal field effects.We analyze spectral shapes,identify peak origins,and estimate the oxidation states of La and Mn ions in LaMnO3 theoretically.It is concluded that La ions in LaMnO3 predominantly exist in the trivalent state,while Mn ions exist primarily in the trivalent state with a minor presence of tetravalent ions.Furthermore,the calculated spectra are in better conformity with the experimental spectra when the proportion of Mn3+is 90%and Mn4+is 10%.This article enhances our comprehension of the oxidation states of La and Mn within the crystal and also provides a valuable guidance for spectroscopic investigations of other manganates.

Scientific data products and the data pre-processing subsystem of the Chang'e-3 mission

The Chang＇e-3 （CE-3） mission is China＇s first exploration mission on the surface of the Moon that uses a lander and a rover. Eight instruments that form the scientific payloads have the following objectives： （1） investigate the morphological features and geological structures at the landing site; （2） integrated in-situ analysis of minerals and chemical compositions; （3） integrated exploration of the structure of the lunar interior; （4） exploration of the lunar-terrestrial space environment, lunar sur- face environment and acquire Moon-based ultraviolet astronomical observations. The Ground Research and Application System （GRAS） is in charge of data acquisition and pre-processing, management of the payload in orbit, and managing the data products and their applications. The Data Pre-processing Subsystem （DPS） is a part of GRAS. The task of DPS is the pre-processing of raw data from the eight instruments that are part of CE-3, including channel processing, unpacking, package sorting, calibration and correction, identification of geographical location, calculation of probe azimuth angle, probe zenith angle, solar azimuth angle, and solar zenith angle and so on, and conducting quality checks. These processes produce Level 0, Level 1 and Level 2 data. The computing platform of this subsystem is comprised of a high-performance computing cluster, including a real-time subsystem used for processing Level 0 data and a post-time subsystem for generating Level 1 and Level 2 data. This paper de- scribes the CE-3 data pre-processing method, the data pre-processing subsystem, data classification, data validity and data products that are used for scientific studies.

High Speed Regular Expression Matching Engine with Fast Pre-Processing

Regular expression matching is playing an important role in deep inspection. The rapid development of SDN and NFV makes the network more dynamic, bringing serious challenges to traditional deep inspection matching engines. However, state-of-theart matching methods often require a significant amount of pre-processing time and hence are not suitable for this fast updating scenario. In this paper, a novel matching engine called BFA is proposed to achieve high-speed regular expression matching with fast pre-processing. Experiments demonstrate that BFA obtains 5 to 20 times more update abilities compared to existing regular expression matching methods, and scales well on multi-core platforms.

Measured load spectra of the bearing in high-speed train gearbox under different gear meshing conditions

The load spectrum is a crucial factor for assess-ing the fatigue reliability of in-service rolling element bear-ings in transmission systems.For a bearing in a high-speed train gearbox,a measurement technique based on strain detection of bearing outer ring was used to instrument the bearing and determine the time histories of the distributed load in the bearing under different gear meshing conditions.Accordingly,the load spectrum of the total radial load car-ried by the bearing was compiled.The mean value and class interval of the obtained load spectrum were found to vary non-monotonously with the speed and torque of gear mesh-ing,which was considered to be caused by the vibration of the shaft and the bearing cage.As the realistic service load input of bearing life assessment,the measured load spectrum under different gear meshing conditions can be used to pre-dict gearbox bearing life realistically based on the damage-equivalent principle and actual operating conditions.

Multi-foci metalens for spectra and polarization ellipticity recognition and reconstruction

Multispectral and polarized focusing and imaging are key functions that are vitally important for a broad range of optical applications.Conventional techniques generally require multiple shots to unveil desired optical information and are implemented via bulky multi-pass systems or mechanically moving parts that are difficult to integrate into compact and integrated optical systems.Here,a design of ultra-compact transversely dispersive metalens capable of both spectrum and polarization ellipticity recognition and reconstruction in just a single shot is demonstrated with both coherent and incoherent light.Our design is well suited for integrated and high-speed optical information analysis and can significantly reduce the size and weight of conventional devices while simplifying the process of collecting optical information,thereby promising for various applications,including machine vision,minimized spectrometers,material characterization,remote sensing,and other areas which require comprehensive optical analysis.

Pre-processing filter design at transmitters for IBI mitigation in an OFDM system

In order to meet the demands for high transmission rates and high service quality in broadband wireless communication systems, orthogonal frequency division multiplexing （OFDM） has been adopted in some standards. However, the inter-block interference （IBI） and inter-carrier interference （ICI） in an OFDM system affect the performance. To mitigate IBI and ICI, some pre-processing approaches have been proposed based on full channel state information （CSI）, which improved the system performance. A pre-processing filter based on partial CSI at the transmitter is designed and investigated. The filter coefficient is given by the optimization processing, the symbol error rate （SER） is tested, and the computation complexity of the proposed scheme is analyzed. Computer simulation results show that the proposed pre-processing filter can effectively mitigate IBI and ICI and the performance can be improved. Compared with pre-processing approaches at the transmitter based on full CSI, the proposed scheme has high spectral efficiency, limited CSI feedback and low computation complexity.

The Role of Combined OSR and SDF Method for Pre-Processing of Microarray Data that Accounts for Effective Denoising and Quantification

Microarray data is inherently noisy due to the noise contaminated from various sources during the preparation of microarray slide and thus it greatly affects the accuracy of the gene expression. How to eliminate the effect of the noise constitutes a challenging problem in microarray analysis. Efficient denoising is often a necessary and the first step to be taken before the image data is analyzed to compensate for data corruption and for effective utilization for these data. Hence preprocessing of microarray image is an essential to eliminate the background noise in order to enhance the image quality and effective quantification. Existing denoising techniques based on transformed domain have been utilized for microarray noise reduction with their own limitations. The objective of this paper is to introduce novel preprocessing techniques such as optimized spatial resolution (OSR) and spatial domain filtering (SDF) for reduction of noise from microarray data and reduction of error during quantification process for estimating the microarray spots accurately to determine expression level of genes. Besides combined optimized spatial resolution and spatial filtering is proposed and found improved denoising of microarray data with effective quantification of spots. The proposed method has been validated in microarray images of gene expression profiles of Myeloid Leukemia using Stanford Microarray Database with various quality measures such as signal to noise ratio, peak signal to noise ratio, image fidelity, structural content, absolute average difference and correlation quality. It was observed by quantitative analysis that the proposed technique is more efficient for denoising the microarray image which enables to make it suitable for effective quantification.

Detection of Rice Yellow Mottle at the Asymptomatic Stage by Hyperspectral Fluorescence and Reflectance Spectroscopies

Rice yellow mottle is considered the most destructive disease threatening rice production in Africa. Early detection of this infection in rice is essential to limit its expansion and proliferation. However, there is no research devoted to the spectral detection of rice yellow mottle virus (RYMV) infection, especially in the asymptomatic or early stages. This work proposes the use of hyperspectral fluorescence and reflectance data at leaf level for the detection of this disease in asymptomatic stages. A greenhouse experiment was therefore conducted to collect hyperspectral fluorescence and reflectance data at different stages of infection. These data allowed to calculate nine vegetation indices: one from fluorescence spectra and eight from reflectance spectra. A t-test made it possible to identify, from the second day after infection, four relevant reflectance vegetation indices to discriminate healthy leaves from those infected: these are Photochemical Reflectance Index (PRI), Transformed Chlorophyll Absorption in Reflectance Index (TCARI), Structure Intensive Pigment Index (SIPI) and Simple Ratio Pigment Index (SRPI). The fluorescence index was less sensitive in detecting infection. The four significant vegetation indices for the detection of RYMV were then used to build and evaluate models for discriminating plants according to their health status by the supervised classification of support vector machine (SVM) at different stages of infection. The maximum overall accuracy is 92.5% six days after inoculation (6 DAI). The sixth day after inoculation would be the adequate day to detect RYMV. This plants discrimination was validated by the mean reflectance spectra and by the histograms showing the differences between the average reflectance vegetation indices values of the two types of plants. Our results demonstrate the feasibility of differentiating RYMV-infected samples. They suggest that support vector machine learning models could be developed to diagnose RYMV-infected plants based on vegetation indices derived from spectral profiles at early stages of disease development.

Predicting nitrogen use efficiency,nitrogen loss and dry matter intake of individual dairy cows in late lactation by including mid‑infrared spectra of milk samples

Background Nitrate leaching to groundwater and surface water and ammonia volatilization from dairy farms have negative impacts on the environment.Meanwhile,the increasing demand for dairy products will result in more pollution if N losses are not controlled.Therefore,a more efficient,and environmentally friendly production system is needed,in which nitrogen use efficiency(NUE)of dairy cows plays a key role.To genetically improve NUE,extensively recorded and cost-effective proxies are essential,which can be obtained by including mid-infrared(MIR)spectra of milk in prediction models for NUE.This study aimed to develop and validate the best prediction model of NUE,nitrogen loss(NL)and dry matter intake(DMI)for individual dairy cows in China.Results A total of 86 lactating Chinese Holstein cows were used in this study.After data editing,704 records were obtained for calibration and validation.Six prediction models with three different machine learning algorithms and three kinds of pre-processed MIR spectra were developed for each trait.Results showed that the coefficient of determination(R2)of the best model in within-herd validation was 0.66 for NUE,0.58 for NL and 0.63 for DMI.For external validation,reasonable prediction results were only observed for NUE,with R2 ranging from 0.58 to 0.63,while the R2 of the other two traits was below 0.50.The infrared waves from 973.54 to 988.46 cm−1 and daily milk yield were the most important variables for prediction.Conclusion The results showed that individual NUE can be predicted with a moderate accuracy in both within-herd and external validations.The model of NUE could be used for the datasets that are similar to the calibration dataset.The prediction models for NL and 3-day moving average of DMI(DMI_a)generated lower accuracies in within-herd validation.Results also indicated that information of MIR spectra variables increased the predictive ability of models.Additionally,pre-processed MIR spectra do not result in higher accuracy than original MIR spectra in the external validation.These models will be applied to large-scale data to further investigate the genetic architecture of N efficiency and further reduce the adverse impacts on the environment after more data is collected.

Spectra-assisted laser focusing in quantitative analysis of laser-induced breakdown spectroscopy for copper alloys

Laser-induced breakdown spectroscopy(LIBS)is a capable technique for elementary analysis,while LIBS quantitation is still under development.In quantitation,precise laser focusing plays an important role because it ensures the distance between the laser and samples.In the present work,we employed spectral intensity as a direct way to assist laser focusing in LIBS quantitation for copper alloys.It is found that both the air emission and the copper line could be used to determine the position of the sample surface by referencing the intensity maximum.Nevertheless,the fine quantitation was only realized at the position where the air emission(e.g.O(I)777.4 nm)reached intensity maximum,and also in this way,a repeatable quantitation was successfully achieved even after 120 days.The results suggested that the LIBS quantitation was highly dependent on the focusing position of the laser,and spectra-assisted focusing could be a simple way to find the identical condition for different samples’detection.In the future,this method might be applicable in field measurements for LIBS analysis of solids.

Four-Electron Systems in the Impurity Hubbard Model. Second Triplet State. Spectra of the System in the ν-Dimensional Lattice Zν

We consider an energy operator of four-electron system in the Impurity Hubbard model with a coupling between nearest-neighbors. The spectrum of the systems in the second triplet state in a ν-dimensional lattice is investigated. For investigation the structure of essential spectra and discrete spectrum of the energy operator of four-electron systems in an impurity Hubbard model, for which the momentum representation is convenient. In addition, we used the tensor products of Hilbert spaces and tensor products of operators in Hilbert spaces and described the structure of essential spectrum and discrete spectrum of the energy operator of four-electron systems in an impurity Hubbard model for the second triplet state of the system. The investigations show that the essential spectrum of the system consists of the union of no more than sixteen segments, and the discrete spectrum of the system consists of no more than eleven eigenvalues.

Time-resolved K-shell x-ray spectra of nanosecond laser-produced titanium tracer in gold plasmas

A study of a nanosecond laser irradiation on the titanium-layer-buried gold planar target is presented. The timeresolved x-ray emission spectra of titanium tracer are measured by a streaked crystal spectrometer. By comparing the simulated spectra obtained by using the FLYCHK code with the measured titanium spectra, the temporal plasma states, i.e.,the electron temperatures and densities, are deduced. To evaluate the feasibility of using the method for the characterization of Au plasma states, the deduced plasma states from the measured titanium spectra are compared with the Multi-1D hydrodynamic simulations of laser-produced Au plasmas. By comparing the measured and simulated results, an overall agreement for the electron temperatures is found, whereas there are deviations in the electron densities. The experiment–theory discrepancy may suggest that the plasma state could not be well reproduced by the Multi-1D hydrodynamic simulation, in which the radial gradient is not taken into account. Further investigations on the spectral characterization and hydrodynamic simulations of the plasma states are needed. All the measured and FLYCHK simulated spectra are given in this paper as datasets. The datasets are openly available at http://www.doi.org/10.57760/sciencedb.j00113.00032.

Diagnostics of laser-induced plasma on carbon-based polymer material using atomic and molecular emission spectra

Time-integrated optical emission analysis of laser-induced plasma on Teflon is presented.Plasma was induced under atmospheric pressure air using transversely excited atmospheric CO_(2) laser pulses.Teflon is a C-based polymer that is,among other things,interesting as a substrate for laser-induced breakdown spectroscopy analysis of liquid samples.This study aimed to determine the optimal experimental conditions for obtaining neutral and ionized C spectral lines and C2 and CN molecular band emission suitable for spectrochemical purposes.Evaluation of plasma parameters was done using several spectroscopic techniques.Stark profiles of appropriate C ionic lines were used to determine electron number density.The ratio of the integral intensity of ionic-to-atomic C spectral lines was used to determine the ionization temperature.A spectral emission of C2 Swan and CN violet bands system was used to determine the temperature of the colder,peripheral parts of plasma.We critically analyzed the use of molecular emission bands as a tool for plasma diagnostics and suggested methods for possible improvements.

基于密度泛函理论对团簇CrPS_(4)的光谱分析

为快速、高效得到物质的谱图数据,利用计算化学方法,根据拓扑学原理,利用密度泛函理论,对团簇CrPS_(4)10种优化构型的红外光谱、拉曼光谱、偶极矩以及极化率进行了分析,并利用构型2^((4))的理论红外谱图与前人所得实际光谱图进行了对比。结果显示:CrPS_(4)红外光谱的波峰大致分布在300~700 cm^(-1)范围内,拉曼光谱的波峰范围主要分布在200~700 cm^(-1)范围内;团簇CrPS_(4)振动形式为伸缩振动时,其对入射光的吸收强度较大;在频率较低的波段,CrPS_(4)更易发生红外吸收,在频率较高的波段,更易发生拉曼散射;总偶极矩的排列顺序为2^((2))>6^((4))>4^((2))>3^((2))>3^((4))>4^((4))>1^((2))>2^((4))>5^((4))>1^((4)),偶极矩越大,红外活性越强;极化率大小关系满足5^((4))<1^((4))<6^((4))<4^((4))<3^((4))<1^((2))<2^((4))<2^((2))<3^((2))<4^((2)),极化率越大,拉曼活性越强;所有构型的3大主轴中,XX轴的极化率均大于YY轴与ZZ轴;构型2^((4))的理论光谱图与实际结果对比发现,两者光谱图波峰频率基本吻合,实验与理论分析互为补充。

桑沟湾春季有色溶解有机物吸收光谱特性及空间分布特征

为探究有色溶解有机物(CDOM)光学性质如何示踪海水中溶解有机物组分的动态信息,实验利用紫外可见吸收光谱手段,分区域测定了桑沟湾春季水体及表层沉积物间隙水中CDOM的吸收光谱特征,探讨了CDOM的来源组成、空间分布特征、迁移转化过程及其与养殖活动的关系。结果显示,(1)波长为355 nm的吸收系数[a(355)]范围为0.23~9.09/m,不同水层空间分布差异显著,表层和底层均从近岸区向贝藻区逐渐降低,在海带区升高后向外海逐渐降低;海带区从表层向底层先降低后升高,高密度、规模化的海带养殖释放了大量的CDOM,各区域沉积物间隙水a(355)是其表层、中层和底层之和的1.3~2.5倍,CDOM在沉积物间隙水中富集并逐渐累积。(2)光谱斜率(S_(275~295))范围为0.013~0.036,外海区和海带区S_(275~295)均值显著高于其他各区,海带区和外海区CDOM中海源有机质占主要成分,而近岸区以陆源有机质为主;近岸区CDOM中的腐殖酸类物质含量从表层到底层逐渐降低,沉积物中积累的富里酸类物质含量较高,海带区和外海区呈相反趋势。(3)比紫外吸光度(SUVA_(254))范围为4.60~14.10 L/(mg·m),贝类区、贝藻区和藻类区SUVA_(254)均呈现出从表层到底层逐渐增大的趋势,CDOM的芳香性逐渐增强并在沉积物间隙水中达到最大;海带区和外海区沉积物间隙水中的SUVA_(254)显著高于其他各区。研究表明,海带区的规模化养殖活动向养殖海区及邻近海域贡献了较多的惰性溶解有机物,暗示着海带养殖活动有较强的碳汇效应,并通过海流作用向外海输送。本研究对桑沟湾海域不同养殖区域的CDOM的吸收特性和空间分布特征进行研究,可为全面了解海水养殖的碳源汇效应提供基础数据。

氧化物中存在O2p空穴的典型实验结果和磁性氧化物的O2p巡游电子模型

负二价氧离子具有满壳层价电子结构(2s^(2)2p^(6)).负一价氧离子的价电子结构为2s^(2)2p^(5),相当于存在1个O2p空穴.传统的凝聚态物理和材料化学研究中都假设氧化物中的氧离子全部为负二价离子,在迄今为止的绝大多数研究氧化物磁性和电输运性质的报道中,采用关于磁有序的超交换和双交换作用模型,都没有考虑O2p空穴的影响.然而,许多价电子状态实验证明,在氧化物中存在不可忽略的O2p空穴,即存在不可忽略的负一价氧离子,其占比可达30%或更多.基于这些实验结果,对传统磁有序模型进行改进,英美学者首先进行了探讨,笔者所在课题组与中国科学院物理研究所磁学国家重点实验室合作进行了系统的研究.介绍了相关的典型实验结果和理论模型.

不同光谱对东亚小花蝽捕食西花蓟马的影响

设施补光可能会影响天敌昆虫的应用效率,为探索提升天敌应用效果的补光光谱,促进补光与天敌释放技术的有机结合,本研究在相同光强和光周期的条件下,比较了红(R)、蓝(B)、红蓝组合(RB)和白(W,对照)光处理下东亚小花蝽对西花蓟马捕食能力的差异。结果表明,相比于W光,B光显著降低东亚小花蝽雌成虫的存活率,R和RB光未影响其雌成虫的存活。R和RB光显著增加东亚小花蝽在高密度猎物下对西花蓟马的捕食量。不同光谱处理下东亚小花蝽雌成虫对西花蓟马雌成虫的捕食能力均符合HollingⅡ型功能反应模型,且搜寻效应随猎物密度增加逐渐降低。RB光处理下,东亚小花蝽捕食西花蓟马的效果最好,理论日最大捕食量最高,为43.10头/d,单头猎物处理时间最短,为0.0232d;B光的理论日最大捕食量也较高,为42.90头/d,单头猎物处理时间为0.0233d;R光下东亚小花蝽捕食西花蓟马的瞬时攻击率最高为1.0837。东亚小花蝽对西花蓟马的搜寻效率最高的是RB光处理,其次是R或B光,最低的是W光。以上结果表明,相比于W光,R、B和RB光均增加东亚小花蝽对西花蓟马的捕食能力和搜寻效率,但B光会降低东亚小花蝽的存活率。因此,与设施补充R和RB光相结合,可潜在提升东亚小花蝽对西花蓟马的捕食效果。本文基于捕食功能差异评价了三种常用补光光谱对东亚小花蝽捕食西花蓟马的影响,为设施补光兼顾天敌应用提供了基础数据。