X-ray Data Research Articles

Characterization and the physical properties of nano-sized Bi2O3/polymer for energy and high-refractive index applications

The present work focuses on developing nanocomposites for optoelectronics and energy storage devices leveraging the unique physicochemical features of bismuth (III) oxide (Bi2O3) using a polyvinyl pyrrolidone/polyvinyl alcohol matrix (PV(A/P)). Bi2O3 nanofillers (NF) and Bi2O3/PV(A/P) nanocomposite (NC) films were prepared by facile chemical solution approaches. The X-ray (XRD) data and a transmission electron image revealed that the NF exhibits a monoclinic phase, resembling slightly deformed agglomerated spheres. In the FTIR spectrum, different stretching vibrations of Bi-O-Bi bonds were found, along with their complexation and interaction with the reactive groups in the matrix. The SEM revealed a uniform distribution of Bi2O3 NF loading up to 1.5 wt% on the sample’s surface. Thermal analyses (TGA and DSC thermograms) were used to study the thermal stability, melting, and decomposition temperatures of the NC films. The dielectric features were studied under frequencies between 2 × 103 and 8 × 106 Hz and heating from 293 to 393 K. The dielectric constant and energy density were increased with Bi2O3 NF content. This implies that we can utilize the prepared NC for the fabrication of energy storage devices. The influences of the Bi2O3 NF doping level on the transmittance, band gap, Urbach energy, refractive index, conductivity, and other physical parameters were discussed. The modifications induced in the dielectric/optical parameters make the prepared NC films the best candidates for applications requiring a high refractive index, such as optical coatings and integrated photonic devices.

Crystal structure and in vitro biological studies of a Pt(II) complex based on gallic acid and triphenylphosphine

Gallic acid is a natural polyphenol found in a variety of fruits, plants and nuts that has several biological properties, such as anti-oxidant, anti-inflammatory, and antitumor, among other activities. Some studies have proven that metal complexation could be an interesting strategy to enhance its pharmacological activities. Taking that into account, we report here the synthesis, spectral characterization (FTIR, 1H, 13C{1H}, 31P{1H} and 195Pt{1H} NMR), structural analysis, and biological activities of a new platinum(II) complex bearing gallic acid (ga) and triphenylphosphine (PPh3) as ligands. Spectral data suggest that a gallic acid molecule chelates the metal via two deprotonated phenolic oxygen atoms and two monodentate triphenylphosphines complete the coordination sphere. Furthermore, X-ray data support that the platinum(II) ion adopts a slightly distorted square-planar coordination environment. Time-dependent 1H NMR spectra at room temperature suggest that the complex is very stable in DMSO for at least 48 h. Subsequently, the cytotoxic activity of the platinum(II) complex was assessed against chronic myelogenous leukemia cells (k562) and in a non-cancerous cell line (LLCMK2). The complex was more active than gallic acid, cisplatin and carboplatin against the K562 cell line, exhibiting outstanding activity (IC50 = 0.75 μM). When tested against Mycobacterium tuberculosis, the complex showed good activity with a MIC value of 3.75 μg/mL. The results reported here reinforce the antitumor and antimycobacterial potential of metal complexes containing gallic acid and derivatives.

Toward robust and high-throughput detection of seed defects in X-ray images via deep learning

BackgroundThe detection of internal defects in seeds via non-destructive imaging techniques is a topic of high interest to optimize the quality of seed lots. In this context, X-ray imaging is especially suited. Recent studies have shown the feasibility of defect detection via deep learning models in 3D tomography images. We demonstrate the possibility of performing such deep learning-based analysis on 2D X-ray radiography for a faster yet robust method via the X-Robustifier pipeline proposed in this article.Results2D X-ray images of both defective and defect-free seeds were acquired. A deep learning model based on state-of-the-art object detection neural networks is proposed. Specific data augmentation techniques are introduced to compensate for the low ratio of defects and increase the robustness to variation of the physical parameters of the X-ray imaging systems. The seed defects were accurately detected (F1-score >90%), surpassing human performance in computation time and error rates. The robustness of these models against the principal distortions commonly found in actual agro-industrial conditions is demonstrated, in particular, the robustness to physical noise, dimensionality reduction and the presence of seed coating.ConclusionThis work provides a full pipeline to automatically detect common defects in seeds via 2D X-ray imaging. The method is illustrated on sugar beet and faba bean and could be efficiently extended to other species via the proposed generic X-ray data processing approach (X-Robustifier). Beyond a simple proof of feasibility, this constitutes important results toward the effective use in the routine of deep learning-based automatic detection of seed defects.

Automated Porosity Characterization for Aluminum Die Casting Materials Using X-ray Radiography, Synthetic X-ray Data Augmentation by Simulation, and Machine Learning.

Detection and characterization of hidden defects, impurities, and damages in homogeneous materials like aluminum die casting materials, as well as composite materials like Fiber-Metal Laminates (FML), is still a challenge. This work discusses methods and challenges in data-driven modeling of automated damage and defect detectors using measured X-ray single- and multi-projection images. Three main issues are identified: Data and feature variance, data feature labeling (for supervised machine learning), and the missing ground truth. It will be shown that simulation of synthetic measuring data can deliver a ground truth dataset and accurate labeling for data-driven modeling, but it cannot be used directly to predict defects in manufacturing processes. Noise has a significant impact on the feature detection and will be discussed. Data-driven feature detectors are implemented with semantic pixel Convolutional Neural Networks. Experimental data are measured with different devices: A low-quality and low-cost (Low-Q) X-ray radiography, a typical industrial mid-quality X-ray radiography and Computed Tomography (CT) system, and a state-of-the-art high-quality μ-CT device. The goals of this work are the training of robust and generalized data-driven ML feature detectors with synthetic data only and the transition from CT to single-projection radiography imaging and analysis. Although, as the title implies, the primary task is pore characterization in aluminum high-pressure die-cast materials, but the methods and results are not limited to this use case.

Bulk Properties of PSR J0030+0451 Inferred with the Compactness Measurement of NICER

In 2019, the Neutron star Interior Composition ExploreR (NICER) mission released its findings on the mass and radius of the isolated neutron star (INS) PSR J0030+0451, revealing a mass of approximately 1.4 solar masses (M ⊙) and a radius near 13 km. However, the recent reanalysis by the NICER collaboration suggests that the available data primarily yield a precise inference of the compactness for this source while the resulting mass and radius are strongly model-dependent and diverse (the 68.3% credible regions just overlap slightly for the ST+PDT and PDT-U models). By integrating this compactness data with the equation of state (EOS) refined by our latest investigations, we have deduced the mass and radius for PSR J0030+0451, delivering estimates of M=1.48−0.10+0.09M⊙ and R=12.38−0.70+0.51km for the compactness found in the ST+PDT model, alongside M=1.47−0.20+0.14M⊙ and R=12.37−0.69+0.50km for the compactness in the PDT-U model. These two groups of results are well consistent with each other and the direct X-ray data inference within the ST+PDT model seems to be favored. Additionally, we have calculated the tidal deformability, moment of inertia, and gravitational binding energy for this neutron star. Furthermore, employing these refined EOS models, we have updated mass–radius estimates for three INSs with established gravitational redshifts.

Plutonium oxide melt structure and covalency.

Advances in nuclear power reactors include the use of mixed oxide fuel, containing uranium and plutonium oxides. The high-temperature behaviour and structure of PuO2-x above 1,800 K remain largely unexplored, and these conditions must be considered for reactor design and planning for the mitigation of severe accidents. Here, we measure the atomic structure of PuO2-x through the melting transition up to 3,000 ± 50 K using X-ray scattering of aerodynamically levitated and laser-beam-heated samples, with O/Pu ranging from 1.57 to 1.76. Liquid structural models consistent with the X-ray data are developed using machine-learned interatomic potentials and density functional theory. Molten PuO1.76 contains some degree of covalent Pu-O bonding, signalled by the degeneracy of Pu 5f and O 2p orbitals. The liquid is isomorphous with molten CeO1.75, demonstrating the latter as a non-radioactive, non-toxic, structural surrogate when differences in the oxidation potentials of Pu and Ce are accounted for. These characterizations provide essential constraints for modelling pertinent to reactor safety design.

Histology and chronological magnetic resonance images of congenital spinal deformity: An experimental study in mice model

BackgroundThe natural history of the congenital spinal deformity and its clinical magnitude vary widely in human species. However, we previously reported that the spinal deformities of congenital scoliosis mice did not progress throughout our observational period according to soft X-ray and MRI data. In this study, congenital vertebral and intervertebral malformations in mice were assessed via magnetic resonance (MR) and histological images.MethodsCongenital spinal anomalies were chronologically assessed via soft X-ray and 7 T MR imaging. MR images were compared to the histological images to validate the findings around the malformations.ResultsSoft X-ray images showed the gross alignment of the spine and the contour of the malformed vertebrae, with the growth plate and cortical bone visible as higher density lines, but could not be used to distinguish the existence of intervertebral structures. In contrast, MR images could be used to distinguish each structure, including the cortical bone, growth plate, cartilaginous end plate, and nucleus pulposus, by combining the signal changes on T1-weighted imaging (T1WI) and T2-weighted imaging (T2WI). The intervertebral structure adjacent to the malformed vertebrae also exhibited various abnormalities, such as growth plate and cartilaginous end plate irregularities, nucleus pulposus defects, and bone marrow formation. In the chronological observation, the thickness and shape of the malformed structures on T1WI did not change.ConclusionsSpinal malformations in mice were chronologically observed via 7 T MRI and histology. MR images could be used to distinguish the histological structures of normal and malformed mouse spines. Malformed vertebrae were accompanied by adjacent intervertebral structures that corresponded to the fully segmented structures observed in human congenital scoliosis, but the intervertebral conditions varied. This study suggested the importance of MRI and histological examinations of human congenital scoliosis patients with patterns other than nonsegmenting patterns, which may be used to predict the prognosis of patients with spinal deformities associated with malformed vertebrae.

AB Dor: Coronal Imaging and Activity Cycles

Using long-term X-ray observations, we present short-term and long-term X-ray variability analysis of the ultrafast rotating active star AB Dor. Flaring events are common in X-ray observations of AB Dor and occupy a substantial portion of the total observation time, averaging at around 57% ± 23%. The flare-free X-ray light curves show rotational modulation, indicating the presence of highly active regions in the star's corona. We have developed a light-curve inversion code to image the corona of active fast rotating stars. The results of coronal imaging reveal the presence of two active regions of different brightness that are separated by ∼180° in longitude. These active regions are also found to migrate along the longitude and also show variation in their brightness. Our analysis of long-term X-ray data spanning from 1979 to 2022 shows multiple periodicities. The existence of a ∼19.2 yr cycle and its first harmonic indicates the presence of a solar-like, long-term pattern. In comparison, the periodicities of ∼3.6 and ∼5.4 yr are possibly due to the presence of a flip-flop cycle in the X-rays, which is also supported by findings for similar periods from the optical data in earlier studies. Further confirmation of the existence of the X-ray flip-flop cycle requires long-term observations at regular intervals in the quiescent state.

Redetermination of germacrone type II based on single-crystal X-ray data.

The extraction and purification procedures, crystallization and crystal structure refinement (single-crystal X-ray data) of germacrone type II, C15H22O, are presented. The structural results are compared with a previous powder X-ray synchrotron study [Kaduk et al. (2022 ▸). Powder Diffr. 37, 98-104], revealing significant improvements in terms of accuracy and precision. Hirshfeld atom refinement (HAR), as well as Hirshfeld surface analysis, give insight into the inter-molecular inter-actions of germacrone type II.

KINNTREX: a neural network to unveil protein mechanisms from time-resolved X-ray crystallography.

Here, a machine-learning method based on a kinetically informed neural network (NN) is introduced. The proposed method is designed to analyze a time series of difference electron-density maps from a time-resolved X-ray crystallographic experiment. The method is named KINNTREX (kinetics-informed NN for time-resolved X-ray crystallography). To validate KINNTREX, multiple realistic scenarios were simulated with increasing levels of complexity. For the simulations, time-resolved X-ray data were generated that mimic data collected from the photocycle of the photoactive yellow protein. KINNTREX only requires the number of intermediates and approximate relaxation times (both obtained from a singular valued decomposition) and does not require an assumption of a candidate mechanism. It successfully predicts a consistent chemical kinetic mechanism, together with difference electron-density maps of the intermediates that appear during the reaction. These features make KINNTREX attractive for tackling a wide range of biomolecular questions. In addition, the versatility of KINNTREX can inspire more NN-based applications to time-resolved data from biological macromolecules obtained by other methods.

A comprehensive X-ray analysis of the massive O-type binary HD 93250 over two decades

Massive star winds are known to be responsible for X-ray emission arising from wind plasma heated by the strong shocks up to temperatures of 10$^6$--10$^7$ K in the case of colliding wind binaries. The investigation of X-ray emission from massive stars thus constitutes a valuable tool for identifying binaries, which is otherwise a difficult task using classical techniques. We investigated thermal and nonthermal X-ray emission from the massive O-type star HD\,93250 to unveil its binary orbital parameters independently. To meet our goal, we analyzed X-ray data obtained with European Photon Imaging Camera on board XMM-Newton spanning over sim 19 years. Additionally, we analyzed NuSTAR observations of HD\,93250 taken at various epochs. We determine the variability timescale of the X-ray emission to be 193.8pm 1.3\,d, in full agreement with the 194.3pm 0.4\,d period derived from the astrometric orbit. The X-ray spectrum of HD\,93250 is well explained by a three-temperature thermal plasma emission model with temperatures of 0.26, 1.0, and 3.3 keV. The resulting X-ray flux varies in compliance with the typical colliding wind emission from eccentric massive binaries where it enhances near periastron passage and decreases gradually close to apastron in proportion to the inverse of the binary separation. The periastron-to-apastron X-ray emission ratio points to an eccentricity range of 0.20-0.25, once again in agreement with the previously determined astrometric orbit. Finally, we do not detect any hard X-ray emission attributable to nonthermal emission above 10 keV. Given the derived plasma temperature, the strong phase-locked variability, and the significant over-luminosity in X-rays, we establish that the X-ray emission from HD\,93250 is dominated by the colliding-wind region. Our results lend support to the idea that X-ray time analysis of massive stars constitutes a relevant tool for investigating their multiplicity and for extracting relevant information on their basic orbital parameters ---such as period and eccentricity--- independently of any orbital solution derived from classical techniques.

Hydrazine metal complexes as a single source in the mechanochemical preparation of metallic magnetic nanoparticles and investigation of their magnetic hyperthermia properties

Ferromagnetic metallic cobalt and nickel nanoparticles were synthesized by intramolecular metal-hydrazine ligand oxidation reduction reaction in basic media and the solid state. Nickel nanoparticles Ni1 and Ni2 are obtained from two complexes, Ni(N2H4)2(C2O4) and Ni(N2H4)2(HCO2)2, respectively. X-ray powder diffraction (XRD) and energy-dispersive X-ray (EDX) data show pure fcc crystal structures of nanoparticles. Scanning electron microscopy (SEM) images revealed both Ni1 and Ni2 nanoparticles have agglomerated sphere morphologies. The crystallite size estimated by using the Scherer method for Ni1 and Ni2 were 18.7 and 6.2 nm. Vibrating sample magnetometer (VSM) data show the coercivity of metallic nickel samples Ni1 and Ni2 are 50 and 153 Oe, respectively. Both nanoparticles cause an increase in the temperature of water under applied alternative magnetic field and showed specific loss power (SLP) of 70 W/g and 104.8 W/g, respectively. The same method is used in preparation of cobalt nanoparticles from two complexes, Co(N2H4)2(C2O4) and Co(N2H4)2(HCO2)2. XRD analysis data show both nanoparticles have hcp crystal structure. SEM images show nanosheet structure with sheet thickness of 10 to 30 nm. Coercivity of Co1 and Co2 nanoparticles obtained by VSM and Hc are 182 and 171 Oe, respectively. In spite of high coercivity in both Co1 and Co2 nanoparticles, the magnetic hyperthermia heating effects are not observed in practice and specific loss power (SLP) is zero.

Morphological and radiographic studies on the Manus region in the Arabian one-humped camel (Camelus dromedaries).

The study aims to analyse the normal anatomical and radiographical features of the Manus of the southern Aswanian-adapted Arabian one-humped camel, providing crucial data for diagnosing and treating various ailments. Our study was applied to 10 cadaver forelimbs of adult male one-humped camels (4-5 years old) for an explanation of the gross anatomy of the bones of the Manus region from under the carpal bones by using traditional techniques, including the gross anatomical, radiographic and x-ray (at the dorsopalmar and lateral planes) of the preparation of Manus bones. Our results showed that the large fused (third and fourth) metacarpal bones, in which the fusion extended along the entire length of the bone except at the distal end, diverged to form separate articulations with cross-ponding digits. As described in all ruminant species, especially the camel, there were two digits, and each digit consisted of three phalanges and two proximal sesamoid bones. Our radiographic x-ray data revealed that the complete radiopaque septum that completely divided the medullary cavity into two separate parts was clear from the dorsopalmar view, while the lateral view showed the proximal sesamoid bones that were placed over each other and located palmar to the head of the large metacarpal bone. In conclusion, our study reveals the adaptations of the Arabian one-humped camel to Egyptian conditions, aiding in the early diagnosis of lameness and digit problems and enabling veterinarians and camel owners to better address these issues, thereby improving the overall health and well-being of these animals.

Comprehensive Experimental and Computational Analysis of the Structural and HSA Binding Properties of Newly Synthesized Coumarin-Trimethoxybenzohydrazide Derivative

Polycyclic aromatic compounds encompass a diverse array of molecules that exhibit remarkable chemical activity and play pivotal roles across various scientific domains. Coumarins represent a diverse class of heterocyclic compounds, which exhibit a wide range of significant biological and pharmacological activities, while containing at least two aromatic rings in their structure. Because chemical, biological, as well as pharmacological properties and activities are highly dependent on the structural characteristics of the molecule, in this paper a detailed structural investigation of the monocrystal structure of newly synthesized (E)-N′-(1-(2,4-dioxochroman-3-ylidene)ethyl)-3,4,5-trimethoxybenzohydrazide was performed. The DFT model that is best suited for describing the structural parameters of coumarin-benzohydrazides was determined. Out of three tested models which were previously proven to be excellent in describing structures of organic compounds, B3LYP-D3BJ was found to be the best in describing the structure of investigated coumarin derivative in regard to the obtained X-ray and spectroscopic data. Determination of the best theoretical model allows for better structural characterization of the coumarin-benzohydrazides for which monocrystals and consequently X-ray structure cannot be obtained. Finally, both experimental and computational analysis indicated (with high mutual correlation) that investigated compound showed excellent binding potential toward the albumin, indicating good distribution through the organism.

Elemental Abundances in the Diffuse Interstellar Medium from Joint Far-ultraviolet and X-Ray Spectroscopy: Iron, Oxygen, Carbon, and Sulfur

In this study, we investigate interstellar absorption lines along the line of sight toward the galactic low-mass X-ray binary Cygnus X-2. We combine absorption line data obtained from high-resolution X-ray spectra collected with the Chandra and XMM-Newton satellites, along with far-UV absorption lines observed by the Hubble Space Telescope’s (HST) Cosmic Origins Spectrograph (COS) instrument. Our primary objective is to understand the abundance and depletion of oxygen, iron, sulfur, and carbon. To achieve this, we have developed an analysis pipeline that simultaneously fits both the UV and X-ray data sets. This novel approach takes into account the line-spread function of HST/COS, enhancing the precision of our results. We examine the absorption lines of Fe ii, S ii, C ii, and C i present in the far-UV spectrum of Cygnus X-2, revealing the presence of at least two distinct absorbers characterized by different velocities. Additionally, we employ Cloudy simulations to compare our findings concerning the ionic ratios for the studied elements. We find that gaseous iron and sulfur exist in their singly ionized forms, Fe ii and S ii, respectively, while the abundances of C ii and C i do not agree with the Cloudy simulations of the neutral ISM. Finally, we explore discrepancies in the X-ray atomic data of iron and discuss their impact on the overall abundance and depletion of iron.

SUSHI: An algorithm for source separation of hyperspectralimages with non-stationary spectral variation. Semi-blind Unmixing with Sparsity for Hyperspectral Images

Hyperspectral images are data cubes with two spatial dimensions and a third spectral dimension, providing a spectrum for each pixel, and thus allowing the mapping of extended sources' physical properties. In this article, we present the Semi-blind Unmixing with Sparsity for Hyperspectral Images (SUSHI), an algorithm for non-stationary unmixing of hyperspectral images with spatial regularization of spectral parameters. The method allows for the disentangling of physical components without the assumption of a unique spectrum for each component. Thus, unlike most source separation methods used in astrophysics, all physical components obtained by SUSHI vary in spectral shape and in amplitude across the data cube. Non-stationary source separation is an ill-posed inverse problem that needs to be constrained. We achieve this by training a spectral model and applying a spatial regularization constraint on its parameters. For the spectral model, we used an Interpolatory Auto-Encoder, a generative model that can be trained with limited samples. For spatial regularization, we applied a sparsity constraint on the wavelet transform of the model parameter maps. We applied SUSHI to a toy model meant to resemble supernova remnants in X-ray astrophysics, though the method may be used on any extended source with any hyperspectral instrument. We compared this result to the one obtained by a classic 1D fit on each individual pixel. We find that SUSHI obtains more accurate results, particularly when it comes to reconstructing physical parameters. We then applied SUSHI to real X-ray data from the supernova remnant Cassiopeia A and to the Crab Nebula. The results obtained are realistic and in accordance with past findings but have a much better spatial resolution. Thanks to spatial regularization, SUSHI can obtain reliable physical parameters at fine scales that are out of reach for pixel-by-pixel methods.

Finding Space-Time Boundaries with Deformable Hypersurfaces

AbstractDynamic 3D imaging is increasingly used to study evolving objects. We address the problem of detecting and tracking simple objects that merge or split in time. Common solutions involve detecting topological changes. Instead, we solve the problem in 4D by exploiting the observation that if objects only merge or only split, they appear as a single component in 4D. This allows us to initiate a topologically simple 3D hypersurface and deform it to fit the surface of all objects at all times. This gives an extremely compact representation of the objects’ evolution. We test our method on artificial 4D images and compare it to other segmentation methods. We also apply our method to a 4D X-ray data set to quantify evolving topology. Our method performs comparably to existing methods with better resource use and improved robustness.

Optical identification and follow-up observations of SRGA J213151.5+491400

Context. The paper is comprised of optical identification and multiwavelength studies of a new X-ray source discovered by the Spectrum Roentgen-Gamma (SRG) observatory during the ART-XC survey and its follow-up optical and X-ray observations. Aims. We aim to identify SRGA J213151.5+491400 in the optical wavelengths. We determine spectra and light curves in the optical high and low states to find periodicities in the light curves and resolve emission lines in the system using optical ground-based data. We intend to study the spectral and temporal X-ray characteristics of the new source using the SRG surveys in the high and low states and NICER data in the low state. Methods. We present optical data from telescopes in Türkiye (RTT-150 and T100 at the TÜBİTAK National Observatory) and in Russia (6-m and 1-m at SAO RAS), together with the X-ray data obtained with ART-XC and eROSITA telescopes aboard SRG and the NICER observatory. Using the optical data, we performed astrometry, photometry, spectroscopy, and power spectral analysis of the optical time series. We present optical Doppler tomography along with X-ray data analysis producing light curves and spectra. Results. We detected SRGA J213151.5+491400 in a high state in 2020 (17.9 mag) that decreased by about 3 mag into a low state (21 mag) in 2021. We find only one significant period using optical photometric time series analysis, which reveals the white dwarf spin (orbital) period to be 0.059710(1) days (85.982 min). The long slit spectroscopy in the high state yields a power-law continuum increasing towards the blue with a prominent He II line along with the Balmer line emissions with no cyclotron humps, which is consistent with a magnetic cataclysmic variable (MCV) nature. Doppler Tomography confirms the polar nature revealing ballistic stream accretion along with magnetic stream during the high state. These characteristics show that the new source is a polar-type MCV source. ART-XC detections yield an X-ray flux of (4.0−7.0) × 10−12 erg s−1 cm−2 in the high state. eROSITA detects a dominating hot plasma component (kTmax > 21 keV in the high state) declining to (4.0−6.0) × 10−13 erg s−1 cm−2 in 2021 (low state). The NICER data obtained in the low state reveal a two-pole accretor showing a soft X-ray component at (6−7)σ significance with a blackbody temperature of 15−18 eV. A soft X-ray component has never been detected for a polar in the low state before.

DP-GAN+B: A lightweight generative adversarial network based on depthwise separable convolutions for generating CT volumes

X-rays, commonly used in clinical settings, offer advantages such as low radiation and cost-efficiency. However, their limitation lies in the inability to distinctly visualize overlapping organs. In contrast, Computed Tomography (CT) scans provide a three-dimensional view, overcoming this drawback but at the expense of higher radiation doses and increased costs. Hence, from both the patient's and hospital's standpoints, there is substantial medical and practical value in attempting the reconstruction from two-dimensional X-ray images to three-dimensional CT images. In this paper, we introduce DP-GAN+B as a pioneering approach for transforming two-dimensional frontal and lateral lung X-rays into three-dimensional lung CT volumes. Our method innovatively employs depthwise separable convolutions instead of traditional convolutions and introduces vector and fusion loss for superior performance. Compared to prior models, DP-GAN+B significantly reduces the generator network parameters by 21.104 M and the discriminator network parameters by 10.82 M, resulting in a total reduction of 31.924 M (44.17%). Experimental results demonstrate that our network can effectively generate clinically relevant, high-quality CT images from X-ray data, presenting a promising solution for enhancing diagnostic imaging while mitigating cost and radiation concerns.

Anticancer, antimicrobial and photocatalytic activities of a new pyrazole containing thiosemicarbazone ligand and its Co(III) and Ni(II) complexes: Synthesis, spectroscopic characterization and X-ray crystallography

A new pyrazole based thiosemicarbazone ligand, 5-methyl-3-formylpyrazole-N(4)-isopropylthiosemicarbazone, (HMPzNHPri) (compound I), and its cobalt(III) and nickel(II) complexes, [Co(MPzNHPri)2]Cl (compound II) and [Ni(HMPzNHPri)2]Br2 (compound III), respectively, have been synthesized and characterized through various physico-chemical and spectroscopic studies. Both the reported Co(III) and Ni(II) complexes are cationic in nature and behave as 1:1 and 1:2 electrolytes in MeOH, respectively. Electronic spectral features of the complexes have classified them as distorted octahedral ones. IR spectral data (4000–450 cm−1) have suggested a monoprotic tridentate (NNS) function of compound I coordinating to the Co(III) ion via the pyrazolyl (tertiary) ring nitrogen, azomethine nitrogen and thiolato sulphur atom; while for compound III, compound I has been found to act as neutral NNS tridentate one, coordinating to Ni(II) via the pyrazolyl iminic nitrogen, azomethine nitrogen and thioketo sulphur. Structural features of all the compounds are confirmed by the single crystal X-ray data. All the compounds reported here have been found to exhibit significant photocatalytic activity towards degradation of Methylene Blue (MB) under UV radiation. Anticancer activity of all the three compounds against cancer cell lines (HeLa and A549) and a normal cell line (HEK293) have been investigated. Compound II has been found to be more efficient against the human cervical cancer cell (HeLa) and the lung cancer cell (A549) than compounds I and III. The ligand and both the complexes display potential activities against both gram-positive (Bacillus subtilis MTCC 7193) and gram-negative bacteria (E. coli MTCC 1610).