Gaussian-like Distribution Research Articles

Corrosion resistance and biocompatibility of carbon ion implanted AZ31B magnesium alloy

The poor corrosion resistance of magnesium limits its clinical applications. Accordingly, in the present study, carbon ions were incorporated into a AZ31b magnesium alloy surface via carbon plasma immersion ion-implantation to improve its corrosion resistance and biocompatibility. The surface morphology and properties of the modified alloy were evaluated by field-emission scanning electron microscopy, water contact angle measurement, Raman scattering, X-ray photoelectron spectroscopy, and energy dispersive X-ray spectroscopy. Furthermore, compositional depth profiles were obtained by glow discharge optical emission spectroscopy, revealing a Gaussian-like distribution of carbon concentration. Electrochemical and hydrogen-evolution analysis demonstrated the successfully improved corrosion resistance of the AZ31b Mg alloy, while its biocompatibility was demonstrated by MTT and cell-adherence assays.

A Fast 3D Range-Modulator Delivery Approach: Validation of the FLUKA Model on a Varian ProBeam System Including a Robustness Analysis

A 3D range-modulator (RM), optimized for a single energy and a specific target shape, is a promising and viable solution for the ultra-fast dose delivery in particle therapy. The aim of this work was to investigate the impact of potential beam and modulator misalignments on the dose distribution. Moreover, the FLUKA Monte Carlo model, capable of simulating 3D RMs, was adjusted and validated for the 250 MeV single-energy proton irradiation from a Varian ProBeam system. A 3D RM was designed for a cube target shape rotated 45° around two axes using a Varian-internal research version of the Eclipse treatment planning software, and the resulting dose distribution was simulated in a water phantom. Deviations from the ideal alignment were introduced, and the dose distributions from the modified simulations were compared to the original unmodified one. Finally, the FLUKA model and the workflow were validated with base-line data measurements and dose measurements of the manufactured modulator prototype at the HollandPTC facility in Delft. The adjusted FLUKA model, optimized particularly in the scope of a single-energy FLASH irradiation with a PMMA pre-absorber, demonstrated very good agreement with the measured dose distribution resulting from the 3D RM. Dose deviations resulting from modulator-beam axis misalignments depend on the specific 3D RM and its shape, pin aspect ratio, rotation angle, rotation point, etc. A minor modulator shift was found to be more relevant for the distal dose distribution than for the spread-out Bragg Peak (SOBP) homogeneity. On the other hand, a modulator tilt (rotation away from the beam axis) substantially affected not only the depth dose profile, transforming a flat SOBP into a broad, Gaussian-like distribution with increasing rotation angle, but also shifted the lateral dose distribution considerably. This work strives to increase awareness and highlight potential pitfalls as the 3D RM method progresses from a purely research concept to pre-clinical studies and human trials. Ensuring that gantry rotation and the combined weight of RM, PMMA, and aperture do not introduce alignment issues is critical. Given all the other range and positioning uncertainties, etc., not related to the modulator, the RM must be aligned with an accuracy below 1° in order to preserve a clinically acceptable total uncertainty budget. Careful consideration of critical parameters like the pin aspect ratio and possibly a novel robust modulator geometry optimization are potential additional strategies to mitigate the impact of positioning on the resulting dose. Finally, even the rotated cube 3D modulator with high aspect ratio pin structures (~80 mm height to 3 mm pin base width) was found to be relatively robust against a slight misalignment of 0.5° rotation or a 1.5 mm shift in one dimension perpendicular to the beam axis. Given a reliable positioning and QA concept, the additional uncertainties introduced by the 3D RM can be successfully managed adopting the concept into the clinical routine.

A convolutional neural networks method for tropospheric ozone vertical distribution retrieval from Multi-AXis Differential Optical Absorption Spectroscopy measurements

The vertical distribution of tropospheric ozone (O3) is crucial for understanding atmospheric physicochemical processes. A Convolutional Neural Networks (CNN) method for the retrieval of tropospheric O3 vertical distribution from ground-based Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) measurements to tackle the issue of stratospheric O3 absorption interference faced by MAX-DOAS in obtaining tropospheric O3 profiles. Firstly, a hybrid model, named PCA-F_Regression-SVR, is developed to screen features sensitive to O3 inversion based on the MAX-DOAS spectra and EAC4 reanalysis O3 profiles, which incorporates Principal Component Analysis (PCA), F_Regression function, and Support Vector Regression (SVR) algorithm. Thus, these screened features for ancillary inversion include the profiles of temperature, specific humidity, fraction of cloud coverage, eastward and northward wind, the profiles of SO2, NO2, and HCHO, as well as season and time features to serve as sensitive factors. Secondly, the preprocessed MAX-DOAS spectra dataset and the sensitive factor dataset are utilized as input, while the O3 profiles of the EAC4 reanalysis dataset incorporating the surface O3 concentrations are employed as output for constructing the CNN model. The Mean Absolute Percentage Error (MAPE) decreases from 26 % to approximately 19 %. Finally, the CNN model is applied for inversion and comparison of tropospheric O3 profiles using independent input data. The CNN model effectively reproduces the O3 profiles of the EAC4 dataset, showing a Gaussian-like spatial distribution with peaks primarily around 950 hPa (550 m). Since the reanalysis data used for model training has been smoothed, the CNN model is insensitive to extreme values. This behavior can be attributed to the MAPE loss function, which evaluates Absolute Percentage Errors (APEs) of O₃ concentration at all altitudes, resulting in varying retrieval accuracy across different altitudes while maintaining overall MAPE control. Temporally, the CNN model tends to overestimate surface O3 in summer by around 20 μg/m3, primarily due to the influence of the temperature feature in the sensitivity factor dataset. In conclusion, leveraging MAX-DOAS spectra enables the retrieval of tropospheric O3 vertical distribution through the established CNN model.

Complex dynamics of partially freezable confined water revealed by combined experimental and computational studies

We investigate water dynamics in mesoporous silica across partial crystallization by combining broadband dielectric spectroscopy (BDS), nuclear magnetic resonance (NMR), and molecular dynamics simulations (MDS). Exploiting the fact that not only BDS but also NMR field-cycling relaxometry and stimulated-echo experiments provide access to dynamical susceptibilities in broad frequency and temperature ranges, we study both the fully liquid state above the melting point Tm and the dynamics of coexisting water and ice phases below this temperature. It is found that partial crystallization leads to a change in the temperature dependence of rotational correlation times τ, which occurs in addition to previously reported dynamical crossovers of confined water and depends on the pore diameter. Furthermore, we observe that dynamical susceptibilities of water are strongly asymmetric in the fully liquid state, whereas they are much broader and nearly symmetric in the partially frozen state. Finally, water in the nonfreezable interfacial layer below Tm does not exhibit a much debated dynamical crossover at ∼220 K. We argue that its dynamics is governed by a static energy landscape, which results from the interaction with the bordering silica and ice surfaces and features a Gaussian-like barrier distribution. Consistently, our MDS analysis of the motional mechanism reveals a hopping motion of water in thin interfacial layers. The rotational correlation times of the confined ice phases follow Arrhenius laws. While the values of τ depend on the pore diameter, freezable water in various types of confinements and mixtures shows similar activation energies of Ea ≈ 0.43 eV.

Reverse engineering and analysis of microstructure polymer fiber via artificial neural networks: simplifying the design approach

Abstract Microstructure polymer fibers have been extensively researched for their applications in various fields. The design and simulation of these fibers have utilized time-consuming techniques like the finite-difference time-domain and finite element method to facilitate the process. This study proposes an optimal artificial neural network (ANN) for predicting the structural design required to achieve desired optical properties. The ANN model takes various optical properties, including confinement loss, effective index, effective mode area, and wavelengths, as inputs to predict fiber design parameters such as diameter and pitch. To address the challenge of skewed distributions, a data set with a Gaussian-like distribution for confinement loss was generated using a logarithmic transformation method, enabling effective training of machine learning models. Furthermore, the ANN model demonstrates its capability to rapidly predict unknown geometric parameters using only the core mode properties of a polymer fiber, achieving results in a significantly shorter time (3 ms) compared to the trial-and-error approach of finite element method simulation (15 s). The reverse engineering model achieves a mean square error of 3.4877 × 10−06 with five hidden layers. The ANN model not only offers ultrafast calculation speed but also delivers high prediction accuracy, thereby accelerating the design process of optical devices. The differentiation among the prediction result, target, and calculation result provides compelling evidence that the proposed approach is an effective methodology for designing microstructure polymer fibers.

The Jarzynski binding free energy can effectively rank ligand-protein affinities in inadequate samplings

The use of the Jarzynski equality for estimating ligand–protein binding free energies are illustrated for cases of inadequate samplings. Data obtained from a large amount (104) of work are thus converged to an incorrect value, due to creation of a distorted Gaussian-like distribution. However, even in such cases, the Jarzynski equality can effectively rank binding affinities in the early stage of rational drug design. A combination of steered molecular dynamics calculations, Jarzynski relation and block averaging can provide such relative binding free energies having significantly better correlations in the cases of the thrombin and HIV-1 complexes examined.

Investigation of the interface state characteristics of the Al/Al2O3/Ge/p-Si heterostructure over a wide frequency range by capacitance and conductance measurements

In this work, Al/Al2O3/Ge/p-Si heterostructures were fabricated by e-beam thermal evaporation. The EDX (energy dispersive X-ray spectroscopy) map visually obtained the basic distribution information in a two-dimensional graph. Three-dimensional atomic Force Microscope (AFM) analysis of the roughness of the Al/Al2O3/Ge/p-Si heterostructure shows that the Al2O3 particle has approximately 4.35 nm. Quantitative analysis via histogram plots for Al2O3 interlayer grown on p-Si shows a Gaussian-like distribution, and it has a sharp profile between 0 and 2 nm on silicon, located around 1.2 nm. The current-voltage (I–V) and capacitance-conductance-voltage (C-G/ω-V) measurements were used to investigate the electrical properties of the structure at room temperature. The I–V measurements revealed two distinct linear regions, attributed to barrier inhomogeneity and distribution of interfacial state/trap densities (Dit). For this reason, we obtained Dit distributions by considering the voltage dependence of the ideality factor n(V) in two regions. Diode parameters acquired through different methods are comparatively presented with a brief literature review. Then, the C-G/ω-V measurements were conducted across a broad frequency range (from 0.3 kHz to 3 MHz), and these measurements revealed notable alterations in the electrical parameters with regard to frequency. In order to probe interface states/traps, we employed the conductance/admittance method, which provided satisfactory information about trap lifetime, following the low-high frequency (LF-HF) and Hill-Coleman methods. The effects of these states/traps on the measurements according to voltage, frequency, and energy level (Eit-Ev) are discussed in detail.

Measurements of proton beam flux and energy of APEP using foil activation technique

The activation method of metallic foils is an important technique to measure the flux and energy of proton beams. In this paper, the method was used to measure the CSNS APEP proton flux at seven nominal proton energies ranging from 10 MeV to 70 MeV for beam spot sizes of the 20 mm × 20 mm and 50 mm × 50 mm. The reactions of natTi(p, x)48V, natNi(p, x)57Ni, natCu(p, x)58Co, and 27Al(p, x)24Na were employed to measure the proton beam flux with a range of 107-109 p/cm2/s. Furthermore, we also proposed a method using the activity ratio with a stacked-foil target to determine the energy spread of a Gaussian-like distribution for different nominal proton energies. The optimal combinations of Al, Cu, Ti, Ni, Mo, Fe, Nb, and In foils were adopted for the proton energies. The measured energy spreads for degraded beams of 30 MeV–70 MeV were found to be smaller than 10.00%.

In-depth three-component assessment of wind turbine wake using stereo PIV under low tip speed ratio conditions

The behavior of wind turbine wake is unique and has a distinct pattern that often carries crucial information on the nature of wake propagation. This information plays a vital role in dictating the wind turbine wake model and subsequently in the design and placement of multirotor system. In most cases, either analytical or numerical, the representation of wind turbine wake is expressed as a streamwise flow deficit at different downstream locations. Though the result provides valuable information, the representation often lacks three-dimensional characterization, thus ignoring several influential factors that could potentially define the extent of propagation. In this aspect, an in-depth flow field mapping and assessment have been carried out behind a model horizontal-axis wind turbine using stereo particle image velocimetry (SPIV) under low tip speed ratio conditions. The three-component mapping using the time-resolved SPIV data helped to understand the notion of the wake's helical behavior and its relationship with the velocity deficit. Apart from the Gaussian-like (skew) distribution of the streamwise velocity component, the stereo assessment reveals the formation of two opposite crests supporting the helical analogy. Toward the end, a comparative assessment with the existing analytical models have been carried out.

Thermal fluid dynamics of the effect of filler wire on deposition rate and bead formation intending plasma arc-based DED

The influence of filler wire configuration, such as size and geometry, on the deposition rate (DR) and bead formation, has been studied in wire arc-based directed energy deposition (WADED), but the fundamental physics underlying its effect on wire melting and melt pool dynamics remains unclear. In this paper, a series of plasma arc-based DED (plasma-DED) experiments were conducted to investigate the impact of five different filler wire configurations on DR and bead dimensions. The coupling behaviours of wire melting, metal transfer and melt pool dynamics under the five filler wire configurations were also simulated numerically using the authors' recently developed wire-feeding model. The calculated wire melting and bead cross-sections are consistent with the experimental images and measurements. The results demonstrate that the filler wire significantly affects the highest DR by altering wire melting and metal transfer behaviours through changes in arc energy absorption. The filler wire with a rhombus geometry which is closer to a Gaussian-like arc distribution than the flat wire was shown to get higher DR and more stable metal transfer. Furthermore, different filler wire configurations lead to distinct melt pool behaviours, including temperature distribution and flow velocity, due to various metal transfer behaviours and arc shading effects. This study sheds light on the fundamental physics underlying the impact of filler wire on wire melting and bead formation for the first time. The methods and findings can guide improving DR and controlling bead shape in the plasma-DED process.

An analytical approach to predict post-cracking behavior of steel fiber reinforced concrete considering the fibers orientation

The presence of steel fiber in plain concrete improves significantly the stiffness as well as the ductility of the material. However, themechanical behavior in the post-cracking stage of steel fiber-reinforced concrete depends on many factors. Among them, the orientation of the fibers is an important factor that is difficult to quantify. This paper presents a theoretical study that describes the fiber bridging mechanism under tensile stress using a closed-form analytical function. This proposed analytical model allows estimating the stress at a crack openingwhere the fiber orientation is represented by a Gaussian-like periodic distribution function. The relevance of the proposed model is validated through several numerical analyses with both pre-defined values of different material properties and geometrical parameters of the fibers and the experimental parameters of the two directtensile tests reported in the literature. The model shows an overall reasonable estimation and presents a lot ofpotential for further development.

Transmission Characteristics and Spatial Coherence of Partially Coherent Light-Emitting Diode Array in the Ocean

Underwater LED light sources are commonly implemented in array configurations with a wide-angle field of view, primarily catering to high-speed communication within a few meters. To increase transmission distance and mitigate oceanic turbulence effects, this paper focuses on the spatial coherence analysis of narrow-beam partially coherent light-emitting diode (PCLED) arrays, examining their average light intensity distribution, beam width, and spatial coherence during oceanic transmission. Based on the extended Huygens–Fresnel integral, the optical field models and spatial characteristics of the radial PCLED array are derived under oceanic conditions, considering parameters such as water attenuation coefficient, kinetic energy dissipation rate, temperature dissipation rate, temperature-to-salinity ratio, as well as the radial filling factor and the sub-beam spatial coherence length of the light source at different transmission distances. The simulations show that, as the spatial coherence length of the sub-beam decreases from hundreds to a few micrometers, the combining distance of the beam arrays also decreases. This reduction in coherence results in the average light intensity distribution degrading into a Gaussian-like distribution, with a significant five-fold decrease in peak intensity. Furthermore, the width of the array spreads, starting from distances of 7 m and 0 m, respectively. The radial PCLED beam array, with its sub-beam spatial coherence length inside micrometers, possesses inherent characteristics that suppress turbulence effects and has future extensive possibilities in the ocean.

W-AMA: Weight-aware Approximate Multiplication Architecture for neural processing

This paper presents the Weight-aware Approximate Multiplication Architecture (W-AMA) for Deep Neural Networks (DNNs). Considering the Gaussian-like weight distribution, it deploys an accuracy-configurable computing component to improve the computational efficiency. Two techniques for effectively integrating the W-AMA into DNN accelerator are presented: (1) A Cartesian Genetic Programming (CGP) based approximate multiplier is designed and selectable to compute the Least Significant Bit (LSB) for a higher accuracy mode. The Reward–Penalty-Coefficient (RPC) is proposed to achieve the internal-compensation. (2) The Hessian-Aware-Approximation (HAA) method is utilized for hybrid approximate modes cross-layer mapping. Based on the W-AMA, an energy-efficient DNN accelerator is proposed and evaluated on 28 nm technology. It can achieve the energy efficiency of 9.6 TOPS/W, and the computational energy efficiency can be improved by 1.5× compared with the standard units, with an 0.52% accuracy loss on CIFAR-10 using ResNet-18.

WPE: Weighted prototype estimation for few-shot learning

Few-shot learning (FSL) is a challenging task that aims to transfer a model trained on base classes with adequate labeled data to accommodate novel classes with only a few training examples. In this paper, we propose a simple but effective weighted prototype estimation (WPE) method to improve FSL. We assume that similar classes have similar distributions in the feature space so that the prototypes of novel classes can be estimated by transferring information from their similar base classes. Specifically, the proposed method learns the Gaussian-like feature distributions of similar base classes with sufficient samples and then transfers the learned distributions to calibrate the prototype of the novel class, which is weighted by its similarities. With the estimated prototype, more robust samples can be generated to improve the FSL task. Comparative experiments are conducted to evaluate the effectiveness of our proposed algorithm on three benchmark FSL datasets. The results show that our proposed method can generate more robust samples and significantly improve FSL, outperforming the state-of-the-art methods on these datasets.

Study on CO migration characteristics and hazard potential function under ventilation after roof cutting blasting

Multiple toxic gases, such as carbon monoxide (CO), are generated by roof-cutting blasting (RCB) in the automatically formed roadway without coal pillars (AFRCP). To eliminate potential hazards in time, a ventilation model was established based on field data from Dianping Coal Mine. The spatial and temporal evolution characteristics of CO under different conditions after roof-cutting by shaped-charge blasting (SCB) and shaped-charge hydraulic blasting (SCHB), respectively, were investigated by using the Computational Fluid Dynamics (CFD) method. The results demonstrate that the CO gas cloud presents the coupling effect of movement and dilution under ventilation. The charge mainly affects the peak value of CO concentration (PVC). The air velocity affects the PVC and the CO gas cloud's over-limit time (OLT) and migration velocity. Roadway cross-sectional area and corner structure affect the PVC by influencing local air velocity. The CO hazard potential functions of the roadway after RCB were established, indicating a Gaussian-like distribution. The maximum hazard potential of SCHB was found to be 60% lower than that of SCB, and the re-entry time for personnel reduced by 36%. This study can serve as a guide for optimizing the ventilation design of roadways after RCB and contribute to the promotion of AFRCP.

Orbital Angular Momentum Mode-Multiplexed Amplification and Transmission Based on a Ring-Core Erbium-Doped Fiber

Recently, orbital angular momentum (OAM) multiplexing has attracted much attention for providing an exponential growth in optical fiber capacity. As an irreplaceable component to promote long-haul OAM mode fiber transmission system, the on-line OAM mode-multiplexed fiber amplifier need to be developed. In this paper, we propose a Gaussian-like erbium doping distribution design method for ring-core erbium doped fiber (RC-EDF) to optimize the differential modal gain (DMG), which can reduce the fabrication complexity of the fiber preform. With a good match with original design, the fabricated RC-EDF was characterized by all the supporting four OAM modes ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\vert l \vert$</tex-math></inline-formula> = 1, 2, 3, 4) multiplexed amplification, which achieves an ultra-low DMG less than 0.3 dB at 1550 nm. The gain is above 15 dB and DMG is less than 1.2 dB for four OAM modes across the C-band under a 500 mW pump power. As a proof for transmission, 32 channels (8 wavelengths × 4 OAM modes) carrying 32-Gbaud quadrature phase-shift keying (QPSK) OAM modes multiplexed-WDM transmission over the OAM-EDFA is demonstrated. The proposed OAM-EDFA with the average OSNR penalties of 0.34 dB may promote the practical implementation for the long-haul OAM modes fiber transmission system.

A smooth transition towards a Tracy–Widom distribution for the largest eigenvalue of interacting k-body fermionic embedded Gaussian ensembles

In spite of its simplicity, the central limit theorem captures one of the most outstanding phenomena in mathematical physics, that of universality. While this classical result is well understood, it is still not very clear what happens to this universal behavior when the random variables become correlated. A fruitful mathematically laboratory to investigate the rising of new universal properties is offered by the set of eigenvalues of random matrices. In this regard, a lot of work has been done using the standard random matrix ensembles and focusing on the distribution of extreme eigenvalues. In this case, the distribution of the largest or smallest eigenvalue departs from the Fisher–Tippett–Gnedenko theorem yielding the celebrated Tracy–Widom distribution. One may wonder, yet again, how robust this new universal behavior captured by the Tracy–Widom distribution is when the correlation among eigenvalues changes. Few answers have been provided to this poignant question, and our intention in the present work is to contribute to this interesting unexplored territory. Thus, we study numerically the probability distribution for the normalized largest eigenvalue of the interacting k-body fermionic orthogonal and unitary embedded Gaussian ensembles in the diluted limit. We find a smooth transition from a slightly asymmetric Gaussian-like distribution, for small , to the Tracy–Widom distribution as , where k is the rank of the interaction and m is the number of fermions. Correlations at the edge of the spectrum are stronger for small values of and are independent of the number of particles considered. Our results indicate that subtle correlations toward the edge of the spectrum distinguish the statistical properties of the spectrum of interacting many-body systems in the dilute limit, from those expected for the standard random matrix ensembles.

A phase correlation based peak detection method for accurate shape from focus measurements

Estimating a 3D shape from 2D images is a classic computer vision problem. Shape from focus is a commonly used method for this purpose. With shape from focus, 3D depth is estimated using a so-called focus measure operator. Pixel focus follows a Gaussian-like distribution in which the location of the peak is an indicator of the 3D depth. Locating the peak in this distribution is complicated due to noise coming from various sources. We investigate the accuracy of some existing algorithms and introduce a new algorithm based on phase correlation. Phase correlation is a powerful method for finding correlations between signals, especially in a noisy environment. The accuracy and robustness to noise of the proposed method are tested and proven by applying it to synthetic data as well as measurements of a calibration target. The proposed method is over 30% more accurate than comparable methods, yet requires more computational effort.

Open flow cytometer with the combination of 3D hydrodynamic single cell focusing and confocal laser-induced fluorescence detection

Flow cytometry is among the most powerful tools for single-cell analysis, while the high cost and mechanical complexity of the commercial instrumentation limit the applications in personalized single-cell analysis. For this issue, we hereby construct an open and low-cost flow cytometer. It is highly compact to integrate the functions of (1) single cell aligning by a lab-made modularized 3D hydrodynamic focusing device, and (2) fluorescence detection of the single cells by a confocal laser-induced fluorescence (LIF) detector. The ceiling cost of the entire hardware for the LIF detection unit and 3D focusing device is $ 3200 and $ 400 respectively. A sheath flow velocity of 150 μL/min produces a focused sample stream of 17.6 μm × 14.6 μm at sample flow of 2 μL/min, based on the LIF response frequency and the laser beam spot diameter. The assay performance of the flow cytometer was evaluated by characterizing fluorescent microparticles and acridine orange (AO) stained HepG2 cells, producing throughputs of 40.5/s and 6.2/s respectively. Favorable assay precision and accuracy were demonstrated by the agreement of frequency histogram with imaging analysis, and good Gaussian-like distributions of fluorescent microparticles and AO-stained HepG2 cells. Practically, the flow cytometer was successfully applied for the evaluation of ROS generation in single HepG2 cells.

Development of a compact linear accelerator to generate ultrahigh dose rate high-energy X-rays for FLASH radiotherapy applications.

In recent years, the FLASH effect, in which ultrahigh dose rate (UHDR) radiotherapy (RT) can significantly reduce toxicity to normal tissue while maintaining antitumor efficacy, has been verified in many studies and even applied in human clinical cases. This work evaluates whether a room-temperature radio-frequency (RF) linear accelerator (linac) system can produce UHDR high-energy X-rays exceeding a dose rate of 40Gy/s at a clinical source-surface distance (SSD), exploring the possibility of a compact and economical clinical FLASH RT machine suitable for most hospital treatmentrooms. A 1.65m long S-band backward-traveling-wave (BTW) electron linac was developed to generate high-current electron beams, supplied by a commercial klystron-based power source. A tungsten-copper electron-to-photon conversion target for UHDR X-rays was designed and optimized with Monte Carlo (MC) simulations using Geant4 and thermal finite element analysis (FEA) simulations using ANSYS. EBT3 and EBT-XD radiochromic films, which were calibrated with a clinical machine Varian VitalBeam, were used for absolute dose measurements. A PTW ionization chamber detector was used to measure the relative total dose and a plane-parallel ionization chamber detector was used to measure the relative normalized dose of each pulse. The BTW linac generated 300-mA-pulse-current 11 MeV electron beams with 29kW mean beam power, and the conversion target could sustain this high beam power within a maximum irradiation duration of 0.75 s. The mean energy of the produced X-rays was 1.66 MeV in the MC simulation. The measured flat-filter-free (FFF) maximum mean dose rate of the room-temperature linac exceeded 80Gy/s at an SSD of 50cm and 45Gy/s at an SSD of 67.9cm, both at a 2.1cm depth of the water phantom. The FFF radiation fields at 50cm and 67.9cm SSD at a 2.1cm depth of the water phantom showed Gaussian-like distributions with 14.3 and 20cm full-width at half-maximum (FWHM) values, respectively. This work demonstrated the feasibility of UHDR X-rays produced by a room-temperature RF linac, and explored the further optimization of system stability. It shows that a simple and compact UHDR X-ray solution can be facilitated for both FLASH-RT scientific research and clinical applications.