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The Electron Ion Collider (EIC) under construction at Brookhaven National Laboratory is a high luminosity collider as the next major research facility for the nuclear physics community. Among the numerous RF subsystems in the EIC, the electron storage ring (ESR) fundamental RF cavities system is one of the most challenging. This system will handle a high beam current of up to 2.5 A and replenish up to 10 MW of beam power losses from synchrotron radiation and HOM. Variable coupling is required in the cavities due to the wide range of required total RF voltage and beam current combinations. In this paper, we will present the status of the design and future plans., Proceedings of the 13th International Particle Accelerator Conference, IPAC2022, Bangkok, Thailand

The vibration of the vertical system of a cold rolling mill is a major concern for factory production. In factory production, it is found that the thickness control system with dynamic stiffness compensation of the rolling mill has a significant impact on the rolling mill vibration. In this work, a mechanical hydraulic coupling vibration model of a cold rolling mill with a thickness control system with dynamic stiffness compensation was established. MATLAB/Simulink was used to simulate and analyze the vibration response characteristics of the mechanical structure of the rolling mill and mechanical hydraulic coupling system considering the dynamic stiffness compensation control mode and position control mode of the upper cylinder. We found that the control system changed the vibration response of the mechanical structure, and different control modes have different effects on the vibration response curve. When the rolling mill works in the vibration area, the thickness difference at the strip steel outlet would be larger. Considering the rolling mill vibration and strip surface quality, the excitation of the strip inlet thickness can be achieved by adjusting the dynamic stiffness compensation system and changing the rolling speed reasonably to achieve good vibration suppression and control effects.

Reliability analysis of complex multi-state system has uncertainty, which is caused by complex structures, limited test samples, and insufficient reliability data. By introducing fuzzy mathematics and grey system theory into the Bayesian network, the model of the grey fuzzy Bayesian network is built, and the reliability analysis method of complex uncertainty multi-state system with the non-deterministic membership function and the interval characteristic quantity is proposed in this paper. Using the trapezoidal membership function with fuzzy support radius variable to describe the fault state of the component, it can effectively avoid the influence of human subjective factors on the selection of the membership function and solve the problem that the fault states of the system and its components are difficult to define accurately. And the conditional probability table containing interval grey numbers is constructed to effectively express the uncertain fault logic relationship between the system and its components. Moreover, a parameter planning model of the system reliability characteristic quantities is constructed, and the system reliability characteristic quantities are expressed as the form of interval values. Finally, two sets of numerical experiments are conducted and discussed, and the results show that the proposed method is an effective and a promising approach to reliability analysis for complex uncertainty multi-state systems.

Additional file 1: Table S1. Characteristics of the baseline sample included and excluded due to losses to follow-up.

Infrared image recognition in substation is always a difficult problem. In order to solve the problem of recognition of knife gate, insulator and other components in infrared image, the target location technology of deep learning is proposed to realize the detection and recognition of typical components in infrared image, and the multi-target detection algorithm YOLO is selected to locate and identify the defects. Firstly, the image preprocessing technology is used to process the collected image, so as to filter the interference of background and other factors on the equipment identification. Then, the infrared image is detected by the YOLO target detection model based on multi feature fusion, so as to locate the position of inspection equipment in the infrared image. Then, the type of equipment is identified by the trained equipment classification model. Finally, the algorithm is tested with a large number of pictures in the substation scene.

The stationary multi-pinhole (MPH) SPECT has the potential to achieve dynamic human myocardial perfusion imaging (MPI) with high sensitivity and high resolution. In this work, the sensitivity of MPH SPECT is 0.06%, four-fold higher than conventional SPECT (typically 0.015%), the dual-head SPECT was set up 77.6 degree. Acquisition time of stationary MPH SPECT was about 5 minutes, and Siemens Symbia T16 took approximately 15 minutes. For stationary MPH SPECT system, dedicated image reconstruction algorithm was developed. System calibration is necessary to ensure installation accuracy and obtain mechanical information for generating system transfer matrix, which will be employed to iterative reconstruction. Projection data were reconstructed using a Pixel-based Ordered Subset-expectation Maximization (POSEM) reconstruction algorithm with prior information. Reconstructed results showed that the image resolution obtained with stationary MPH is significantly better than Siemens Symbia T16, the image quality is also greatly improved compared to rotational LEHR SPECT. Meanwhile, the short acquisition time of MPH can reduce the possibility of artifacts due to patient movement. So it is potentially capable of dynamic 3D acquisition, and further more clinical trials for evaluating the system performances will be conducted.

Cooling of hadron beams is critically important in the next generation of hadron storage rings for delivery of unprecedented performance. One such application is the electron-ion collider presently under development in the US. The desire to develop electron coolers for operation at much higher energies than previously achieved necessitates the use of radio-frequency (RF) fields for acceleration as opposed to the conventional, electrostatic approach. While electron cooling is a mature technology at low energy utilizing a DC beam, RF acceleration requires the cooling beam to be bunched, thus extending the parameter space to an unexplored territory. It is important to experimentally demonstrate the feasibility of cooling with electron bunches and further investigate how the relative time structure of the two beams affects the cooling properties; thus, a set of four pulsed-beam cooling experiments was carried out by a collaboration of Jefferson Lab and Institute of Modern Physics (IMP). The experiments have successfully demonstrated cooling with a beam of electron bunches in both the longitudinal and transverse directions for the first time. We have measured the effect of the electron bunch length and longitudinal ion focusing strength on the temporal evolution of the longitudinal and transverse ion beam profile and demonstrate that if the synchronization can be accurately maintained, the dynamics are not adversely affected by the change in time structure., Comment: 13 pages, 19 figures. Submitted to Physical Review Accelerators and Beams

In the complex marine environment, with the continuous enrichment and development of target detection methods, massive target track data is stored and accumulated in the database, which contains a large amount of information and knowledge. It is possible to analyze and predict the behavior and intention of the target by means of target behavior law mining. Most of the existing target behavior law mining methods are based on the idea of clustering. When working in the complex environment of the sea battlefield, the working steps are complicated and the effect is poor. Therefore, in combination with situation analysis requirements and based on the idea of similar duplicate record detection, this paper proposes a mining method of maritime target behavior law by defining multi-dimensional record matching similarity (MDRS). The experimental analysis is carried out on the simulated military scene. The results show that the proposed method can accurately and effectively mine the behavior of the target.

The determination of alendronate (ALE) in biofluids using a low-cost instrument is potentially useful in preclinical pharmacokinetic studies. This study developed and validated a high-performance liquid chromatography with ultraviolet method for ALE determination in rat plasma using precolumn derivatization with phenyl isothiocyanate (PITC). Inhibiting compounds in the samples were first eliminated using solid-phase extraction. ALE in the sample was subsequently allowed to react with PITC to form a phenylthiocarbamoyl derivative for further analysis. The assay was linear within the concentration range of 0.29–25.0 µg/mL. The precision and accuracy were less than 3.9% and 98.0 ± 3.9%, respectively. The limits of detection and quantification were 0.08 and 0.20 µg/mL, respectively. The method was successfully used to evaluate the pharmacokinetic parameters of ALE in rats following a single oral administration (30.0 mg/kg). The results show that the peak plasma ALE concentration is 0.69 ± 0.18 µg/mL. ...

This paper presents a 2.57GHz All-Digital Phase-Locked Loop(ADPLL) Based on the digital controlled Ring Oscillator, which uses a frequency and phase detector controller architecture with high resolution and wide locking range. In order to speed up the phase locking, reduce the instantaneous phase locked differential, this dissertation adopts a forward prediction method. The DCO uses 3-stage ring oscillator, the oscillator frequency is controlled by the coarse tune words(CTW) and the fine tune words(FTW), the CTW to control the output frequency fast approaching the target frequency and the FTW to control the final target frequency, in addition, in order to make the DCO work in a linear zone, a normal open oscillation circuit is designed. The layout of the ADPLL circuit is completed by 0.18um CMOS process, which area is 0.3416 mm2 (including pad). The post simulation results show that the maximum output clock frequency is over 2.57GHZ.

A novel technology of multi-pinhole (MPH) SPECT for human myocardial perfusion imaging (MPI) by increasing angular sampling. In this study, the efficiency of MPH SPECT is 0.06%, four-fold higher than Dual-detector LEHR SPECT (typically 0.015%), we acquired projection data of patient MPI for rest and exercise with 12-pinhole collimator and Siemens Symbia T16. There are two cases for MPH SPECT scan in V mode: one view from -170°of main turning device, two views from -170°and -135°. Acquisition time of MPH SPECT was 5 minutes for single and dual angles, and the acquisition of Siemens was 15 minutes. MPH calibration is essential to generate system transfer matrix, which will be employed to iterative reconstruction. Projection data were reconstructed with a Pixel-based Ordered Subset-expectation Maximization (POSEM) reconstruction algorithm. Reconstructed results showed that dual-angle imaging results have better uniformity than single-angle imaging, and MPH SPECT has higher spatial resolution than Siemens Symbia T16 with reduced acquisition time. The short acquisition time of MPH can increase SPECT throughput and reduces the possibility of artifacts due to patient movement. More clinical trial for MPH dual angular sampling performance evaluation will be carried out.

Android based smartphone users’ privacy has been a hot issue recently in public concerns due to various instances of security attacks and privacy leakage on Android platform. Android existing security has been built upon a permission based mechanism which restricts critical resources accesses of third-party Android applications. This permission based security system is widely assessed for its major control of application permissions and critical management of permissions by developers, marketers, and endusers. Considering the critical management of permissions some previous research papers proposed automatic permission management tools. But those automatic tools never assessed end user’s expectation about permissions perfectly. This paper presents a tool, SDroid (Secured anDroid) that assesses the best permissions management based on end users opinion. SDroid evaluates requested permissions and allow users selectively grant permissions considering his/her knowledge level depending on the opinion.

In order to improve the performance of the magnetic navigation system used by substation inspection robot, the kinematic characteristics is analyzed based on a simplified magnetic guiding system model, and then the simulation process is executed to verify the reasonability of the whole analysis procedure. Finally, some suggestions are extracted out, which will be helpful to guide the design of the inspection robot system in the future.

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Distributed analysis of target kinematics captured by a large network of sensors has received significant attention lately. Tracking moving targets in nonlinear systems is one of the most fundamental tasks in this regard and information-type consensus filters (ICFs) have been applied to this problem. To improve the estimate performance, a squared-root cubature information filter which can avoid numerically sensitive matrix operations such as matrix square-rooting and inversion has been developed firstly. And then, based on this filter, a decentralised information filtering algorithm is proposed in an improved consensus framework. Specifically, consensus update at each time-cycle in the modified consensus scheme is computed in two steps, first towards the predicted value and then towards the final information estimate update, which can improve average estimation accuracy and speed the average consensus. Besides the basic merits of the traditional ICFs, the resulting algorithm is more scalable and robust. Simulation results clearly show the advantage of the proposed algorithm compared with existing ICFs in the considered application scenario.

Track-to-Track correlation (or association) is an ongoing area of interest in the field of distributed multisensory information fusion. In order to perform accurately identifying tracks with common origin and get fast convergence, this study presents independent and dependent Bi-threshold Track Correlation Algorithms (called BTCAs), which are described in detail and the track correlation mass and multivalency processing methods are discussed as well. Then, Based on BTCAs, two modified Bi-threshold Track Correlation Algorithms with average Test Statistic (called BTCA-TSs) are proposed. Finally, simulations are designed to compare the correlation performance of these algorithms with that of Singer’s and Bar-Shalom’s algorithms. The simulation results show that the performance of these algorithms proposed in this study is much better than that of the classical methods under the environments of dense targets, interfering, noise and track cross and so on.

Node self-localization is one of the supporting technologies in Wireless Sensor Networks (WSNs). In this study, a distributed hybrid localization algorithm based on divide-and-conquer and refinement method is proposed. Firstly, the effect of ranging error in the Received Signal Strength (RSS) model on node localization is analyzed and the topology relations of anchors and unknown nodes are derived when the least localization error is achieved and then, the localization-union scheme is designed and refinement method is presented to improve the estimate accuracy. Finally, the simulation results prove that our proposed algorithm has the merits of superior performance, simple design and less overhead. Especially, it can use sparse anchors to achieve high localization accuracy.

This study studies are error registration algorithm for the maneuvering radar network, which is one of the difficult problems of multi-sensor registration. Wh en the maneuvering radar has no orientation bias, measurement equations of both attitude bias and mea surement bias can be established by using the commo n targets observed by different radars. Based on the equations, the real-time estimation of both attitud e bias and measurement bias can be obtained with the twofold unscented Kalman filter. The results show that t he method has a fast convergence rate. When the distan ce of the sensors is very long, both the absolute registration and the relative registration of attit ude bias and measurement bias can be implemented.

Due to the huge computation complexity of Dezert-Smarandache Theory, its applications especially for multi-sources complex fusion problems have been limited.

Aiming to solve the track refined correlation problem of the group targets with systematic errors, based on the characteristics of the group tracks, an algorithm of track refined correlation with in group targets based on systematic error compensation is proposed with the error estimation technique and the track correlation technique. In this algorithm, the groups are identified with the tracks of the sensors based on the circulatory threshold model firstly. Secondly, the preparatory correlation groups with the nearest resolving state are searched or established based on group track state identification model. Thirdly, the final systematic errors are estimated with group track systematic error estimation model and error validation model. What is more, the error compensation is completed. Finally, group track refined correlation is done with the traditional track correlation algorithms. The analysis results of the simulation data show that the general performance of this algorithm, which can meet the engineering requirement of the track refined correlation of the group targets with systematic errors very well, is better than that of fuzzy track alignment-correlation algorithm based on target topological information, track alignment-correlation algorithm based on iterative closest track and modified weighted track correlation algorithm.

Aiming to solve the track refined tracking problem of the formation targets with the multi-sensor detections, intensive analysis on target echo characteristics of the formation targets, the centralized multi-sensor particle filter algorithm of formation targets are advanced. The algorithm set up a shape vector, which can represent the graph of each target in formation using shape and azimuth descriptor, then based on the measurement set to fall within the formation each target door of the waves, that associated to all graphics within each target formation might be associated measurement configuration for the object, through establish similarity model through space and shape similarity measurement step with the target state prediction value distance, at the same time, using the idea of selecting the master station to remove redundant images. Finally, achieve each formation target status updating, which based on particle filter using measurement set and the corresponding weight set. The analysis results of the simulation data show, this algorithm has obvious advantages in tracking accuracy, real-time performance and effective tracking rate three aspects, which can meet the engineering requirement of the track refined tracking of the formation targets with multi-sensor detections very well, is better than the algorithm based on data compression centralized multi-sensor multi-algorithm hypothesis which has superior performance in the traditional multi-sensor multi-target tracking algorithm.

Phase lock to an SRF cavity by using injection signal through output waveguide of a magnetron has been demonstrated [1, 3]. Amplitude control using magnetic field trimming and anode voltage modulation has been studied using MATLAB/Simulink simulations [2]. Based on these, we are planning to use an FPGA based digital LLRF system, which allows applying various types of control algorithms in order to achieve the required accelerating field stability. Since the 1497 MHz magnetron is still in the design stage, the proof of principle measurements of a commercial 2450 MHz magnetron are carried out to characterize the anode I-V curve, output power (the tube electronic efficiency), frequency dependence on the anode current (frequency pushing) and the Rieke diagram (frequency pulling by the reactive load). Based on early Simulink simulation, experimental data and extension of the Adler equation governing injection phase stability by Chen's model, the specification of the new LLRF control chassis for both 2450 and 1497MHz systems are presented in this paper., Proceedings of the 7th Int. Particle Accelerator Conf., IPAC2016, Busan, Korea

Thermophysical properties of undercooled liquid monotectic alloys are usually difficult to be determined because of the great difficulty in achieving large undercoolings. We measure the surface tension of liquid Fe77.5Cu13Mo9.5 monotectic alloy by an electromagnetic oscillating drop method over a wide temperature range from 1577 to 1784 K, including both superheated and undercooled states. A good linear relationship exists between the surface tension and temperature. The surface tension value is 1.588 N/m at the monotectic temperature of 1703 K, and its temperature coefficient is −3.7×10−4 Nm−1K−1. Based on the Butler equation, the surface tension is also calculated theoretically. The experimental and calculated results indicate that the effect of the enriched element on droplet surface is much more conspicuous than the other elements to decrease the surface tension.

d-Glucaric acid (GA) derivatives exhibit anti-cancerogenic properties in vivo in apples, but quantitative information about these derivatives is limited. Hydrophilic interaction-based HPLC with ultraviolet detection or mass spectrometry was developed to quantify GA and/or D-glucaro-1,4-lacton (1,4-GL) in apples. Although the formation of 1,4-GL from GA could be the prerequisite to exert biological effects in vivo, only a small portion of GA (

The dendritic growth characteristics of undercooled liquid Ni-5%Cu-5%Mo-5%Ge quaternary alloy were investigated by electromagnetic levitation method. The measured dendritic growth velocity of α-Ni phase increases with undercooling according to a power law relation, which attains a value of 28 m/s at the maximum undercooling of 321 K (0.19TL). The microstructure morphology appears as coarse dendrites at small undercoolings, while it is refined into equiaxed grains at substantial undercoolings. Furthermore, all the solute elements Cu, Mo and Ge exhibit a significant solute trapping effect during rapid dendritic growth. Keywords-dendritic growth; high undercooling; solute trapping.

This paper discusses an application of the IPM (inverse perspective mapping) geometrical transform on the inspection power robot (SmartGuard). The SmartGuard is an autonomous robotic system for inspection substation equipment instead of people. Based on the stereo vision system, we proposed a Vision base road edge and obstacle detection system. Firstly, we construct the IPM( Inverse perspective mapping) structure from the vision system structure and the road plane in the substation. Secondly, make the monocular image transform of IPM, and get the edge of the road based on the line detection. Thirdly, do the stereo images IPM, based the transformed images, detect the different of the stereo remapping images to get the probable obstacle. Continues, we give a hypothesis testing obstacle detection approach to make the obstacle information more exactly. At last, we make the 2D map both the road edge and obstacle which could provide enough information for the robot navigation in the substation.

Aimed at the deficiency of the magnetic guide and RFID parking system used by substation inspection robot now, a laser navigation method is introduced, and a prototype laser navigation system is designed based on NAV200. The whole structure of the navigation system is presented; the data processing and navigation control algorithm are also described in detail. In order to verify the repetitive precision of the system, an experimental test has been carried out in a 500KV outdoor substation. Experimental results show that the laser navigation system works well, and the repetitive precision of navigation control is precise enough to help the robot fulfill inspection tasks.

For the state estimation of nonlinear systems, especially high-dimensional systems, using existing nonlinear Gaussian filters it is hard to seek a balance between accuracy and efficiency. This paper proposes a novel Sparse-grid Quadrature Kalman Filter (SGQKF), an algorithm that utilizes the Kronrod-Patterson rule to determine the univariate quadrature point sets with a range of accuracy levels, which then are extended for the multi-dimensional point sets using the Sparse-grid technique. The Sparse-grid point sets generated by the Kronrod-Patterson rule, compared to those generated by the Gauss-Hermite rule and the Moment Matching method, not only has high precision, but also nested properties, which remarkably improve the estimation accuracy and efficiency of the new algorithm. Compared with conventional point-based algorithms like Quadrature Kalman Filter (QKF), the SGQKF can achieve close, even higher, accuracy with significantly less number of quadrature points, which effectively alleviate the “curse of dimensionality” for high-dimensional problems. Finally, the performance of this filter is demonstrated by a satellite orbit estimation problem. The simulation results verify the merits of the new algorithm.

Aim to solve the problem that the memory of the centralized multi-sensor system is easy to be saturated, this paper has proposed a new algorithm named centralized multi-sensor general association algorithm based on data compress technique against a background, which has a relative demand of real-time and tracking precision. In this algorithm, the measurement sets associated with the same target from each sensor are obtained and compressed into equivalents. A lot of association hypotheses are built with the equivalents, the remainder measurements and the track of each target. The score of every hypothesis could be obtained with the formula of the score function in multi-sensor general association algorithm, and the state estimation of the fusion center is gained finally. The simulation results show that this algorithm could track the targets effectively with the high density clutter and the general performance of this algorithm is better than that of sequential centralized multi-sensor joint probabilistic data association algorithm and parallel centralized multi-sensor general association algorithm.

To investigate the effect of nicorandil on the chronic air embolism-induced pulmonary hypertension and pulmonary vascular remodeling in rabbits. A total of 36 rabbits were randomly divided into control group, air embolic group, and air embolic + nicorandil treated group with 12 rabbits 0f each

This paper has researched on the problem of centralized multi-sensor multi-target tracking against a background, which has a high demand of real-time and a relative demand of tracking precision, and analyzed the advantages and disadvantages of the existent classical algorithms theoretically in this environment. Based on the research and the analysis, general association algorithm has been extended into multi-senor system through the parallel structure and a new algorithm named parallel centralized multi-sensor general association algorithm has been proposed. In this algorithm, a lot of hypotheses are built with the measurements of each sensor and the track of each target, the score of every hypothesis could be obtained with the formula of the score function in multi-sensor general association algorithm, and the state estimation of the fusion center is gained finally. The simulation results show that this algorithm could track the targets effectively with the high density clutter and the general performance of this algorithm is better than that of sequential centralized multi-sensor joint probabilistic data association algorithm and parallel centralized multi-sensor probabilistic nearest neighbor standard function.

As multimedia contents are becoming widely used in ubiquitous computing environments among many application fields, e.g., education, entertainment, and live surveillance, the demand of personalized access to these contents has increased dramatically. The provisioning of ubiquitous personalized multimedia services (UPMSs) is a challenging task, which involves a lot of heterogeneous entities ranging from objects, devices to software. In this work, we propose a three-layer software platform, called UPmP to support efficient development and deployment of UPMSs. It fulfills the core functionalities for ubiquitous personalized multimedia provisioning including service management, multimedia recommendation, adaptation, and delivery. We adopt service-oriented approach in building the platform. The enabling technologies such as component representation, service lifecycle management, platform configuration, and service composition are described in detail. The experimental results show that the UPmP is flexible to be configured under different settings.

This report describes the development of a new discrete-time multirate LQG (hereafter called MRLQG) controller. The project involves the design and simulation of a MRLQG controller for a DC Motor Speed Control System with the aim to improve tracking responses. Master of Science (Computer Control and Automation)

We report the electrostatic levitation of various kinds of seeds and flower buds. Coral berry and pepper near a spherical shape show a stable levitation state. The prolate ellipsoid soybean and flower buds are always "standing" in the free space with satisfactory levitation stability. For the irregular mushroom and wheat grain, the levitation state is characterized as a "top-heavy" posture. These special stable equilibrium states are proved by the analysis of surface charge distribution. The obtained saturation polarization charge of samples presents a good accordance with experimental data. The levitation ability is weighed by the factor m(r+2)/(rD2).

The Medium-energy Electron Ion Collider (MEIC) at JLab is designed to provide high luminosity and high polarization needed to reach new frontiers in the exploration of nuclear structure. The luminosity, exceeding 1033 cm⁻²s^{−1} in a broad range of the center-of-mass (CM) energy and maximum luminosity above 1034 cm⁻²s^{−1}, is achieved by high-rate collisions of short small-emittance low-charge bunches made possible by high-energy electron cooling of the ion beam and synchrotron radiation damping of the electron beam. The polarization of light ion species (p, d, 3He) can be easily preserved and manipulated due to the unique figure-8 shape of the collider rings. A fully consistent set of parameters have been developed considering the balance of machine performance, required technical development and cost. This paper reports recent progress on the MEIC accelerator design including electron and ion complexes, integrated interaction region design, figure-8-ring-based electron and ion polarization schemes, RF/SRF systems and ERL-based high-energy electron cooling. Luminosity performance is also presented for the MEIC baseline design., Proceedings of the 6th Int. Particle Accelerator Conf., IPAC2015, Richmond, VA, USA

The use of an injection locked CW magnetron to drive a 2.45 GHz superconducting RF cavity has been successfully demonstrated. With a locking power less than -27 dB with respect to the output and with a phase control system acting on the locking signal, cavity phase was accurately controlled for hours at a time without loss of lock whilst suppressing microphonics. The phase control accuracy achieved was 0.8o r.m.s. The main contributing disturbance limiting ultimate phase control was power supply ripple from the low specification switch mode power supply used for the experiment., Proceedings of the 1st International Particle Accelerator Conference, IPAC2010, Kyoto, Japan

X-ray photoelectron spectra have been obtained under the same experimental conditions for synthetic α-NiS and natural β-NiS in order to establish any difference in S electronic environment, and to test the proposition that S core electron binding energies increase measurably with coordination number when the same metal is in different sulfide structures or lattice sites. The Ni and S electronic environments in the two NiS structures have been further probed by near-edge X-ray absorption fine structure (NEXAFS) spectroscopy, and the NEXAFS spectra interpreted by reference to spectra simulated by ab initio calculations. The photoelectron and NEXAFS spectra for freshly prepared surfaces of α-NiS and β-NiS were found to be similar, with only subtle differences in electronic environment evident in the experimental and simulated NEXAFS spectra. The measured and calculated core electron binding energies did not support the previously postulated relationship between S coordination number and electron binding energies.