This article aims to detect lung cavitations using lung ultrasound (LUS) in a cohort of patients with pulmonary tuberculosis (TB) and correlate the findings with chest computed tomography (CT) and chest x-ray (CXR) to obtain LUS diagnostic sensitivity. Patients with suspected TB were enrolled after being evaluated with CXR and chest CT. A blinded radiologist performed LUS within 3 days after the admission at the Infectious Diseases Department. Finally, 82 patients were enrolled in the study. BAL confirmed TB in 58/82 (71%). Chest CT showed pulmonary cavitations in 38/82 (43.6%; 32 TB patients and 6 non-TB ones), LUS in 15/82 (18.3%; 11 TB patients and 4 non-TB ones) and CXR in 27/82 (33%; 23 TB patients and 4 non-TB ones). Patients with multiple cavitations were 12 detected at CT and only 1 at LUS. LUS sensitivity was 39.5%, specificity 100%, PPV 100%, NPV 65.7%. CXR sensitivity was 68.4% and specificity 97.8%. No false positive cases were found. LUS sensitivity is rather low as many cavitated consolidations do not reach the pleural surface. Aerated cavitations could be detected with LUS with relative confidence, highlighting a thin air-crescent sign towards the pleural surface within a hypoechoic area of consolidation, easily distinguishable from dynamic or static air-bronchogram.

Active-case finding (ACF) using chest X-ray is an essential method of finding and diagnosing TB cases that may be missed in Indonesia's routine TB case finding. This study compares active and passive TB case-finding strategies. A retrospective study of TB case notification was conducted. Data between January 1 and December 31, 2021, was used. The population in this study were TB cases notified from Kulon Progo District health facilities, including those found through routine activities or active-case finding. A total of 255 TB cases were diagnosed in Kulon Progo in 2021, and 106 (41.6%) were bacteriologically confirmed. The TB patients' mean age was 46.3 (SD 21.4, range 0-85 years). The majority of cases were male (58.8%) and mostly among people aged 16-60 years old (63.5%). ACF diagnosed 91 TB cases (35.7% total cases, 91/255). The proportion of clinical TB cases (n=68, 74.7%) among those found through ACF was higher than found through passive-case finding. Use of chest X-ray in ACF likely contributed to the detection of a higher proportion of clinical TB than bacteriologically confirmed.

Coronavirus disease since December 2019 has significantly affected millions of people. Given the effect this disease has on the pulmonary systems of humans, there is a need for chest radiographic imaging (CXR) for monitoring the disease and preventing further deaths. Several studies have been shown that Deep Learning models can achieve promising results for COVID-19 diagnosis towards the CXR perspective. However, this research field is at an initial stage since there is a limited number of large CXR repositories regarding COVID-19. In this study, five deep learning models were analyzed and evaluated with the aim of identifying COVID-19 from chest X-Ray images. More specifically, we utilized the ResNet50, ResNet101, DenseNet121, DenseNet169 and InceptionV3 using Transfer Learning. All models were trained and validated on the largest publicly available repository for COVID-19 CXR images. Furthermore, they were evaluated on unknown data as well, that was not used for training or validation, authenticating their performance, and clarifying their usage in a medical scenario. All models achieved satisfactory performance where ResNet101 was the superior model achieving 96% in Precision, Recall, and Accuracy. Our outcomes show the potential of deep learning models on COVID-19 medical offering a promising way for the deeper understanding of COVID-19.

This research addresses the respiratory distress syndrome (RDS) in preterm newborns, caused by insufficient surfactant synthesis, which can lead to serious complications, including pneumothorax, pulmonary hypertension, and pulmonary hemorrhage, increasing the risk of a fatal outcome. By analyzing chest radiographs and blood gases, we specifically focus on the significant contributions of these parameters to the diagnosis and analysis of the recovery of patients with RDS. The study involved 32 preterm newborns, and the analysis of gas parameters before and after the administration of surfactants and inhalation corticosteroid therapy revealed statistically significant changes in values of parameters such as FiO2, pH, pCO2, HCO3 and BE (Sig.<0.05), ehile the pO2 parameter showed a potential change (Sig.=0.061). Parallel to this, the research emphasizes the development of a lung segmentation algorithm implemented in the MATLAB programming environment. The key steps of the algorithm include preprocessing, segmentation, and visualization for a more detailed understanding of the recovery dynamics after RDS. These algorithms have achieved promising results, with a global accuracy of 0.93±0.06, precision 0.81±0.16 and an F-score of 0.82±0.14. These results highlight the potential application of algorithms in the analysis and monitoring of recovery in newborns with RDS, also underscoring the need for further development of software solutions in medicine, particularly in neonatology, to enhance the diagnosis and treatment of preterm newborns with respiratory distress syndrome.

Corona virus disease (COVID-19) has infected over more than 10 million people around the globe and killed at least 500K worldwide by the end of June 2020. As this disease continues to evolve and scientists and researchers around the world now trying to find out the way to combat this disease in most effective way. Chest X-rays are widely available modality for immediate care in diagnosing COVID-19. Precise detection and diagnosis of COVID-19 from these chest X-rays would be practical for the current situation. This paper proposes one shot cluster based approach for the accurate detection of COVID-19 chest x-rays. The main objective of one shot learning (OSL) is to mimic the way humans learn in order to make classification or prediction on a wide range of similar but novel problems. The core constraint of this type of task is that the algorithm should decide on the class of a test instance after seeing just one test example. For this purpose we have experimented with widely known Generalized Regression and Probabilistic Neural Networks. Experiments conducted with publicly available chest x-ray images demonstrate that the method can detect COVID-19 accurately with high precision. The obtained results have outperformed many of the convolutional neural network based existing methods proposed in the literature.

Purpose: We assessed if a CXR AI algorithm can detect missed or mislabeled chest radiographs (CXRs) findings in radiology reports. Methods: We queried multi-institutional radiology reports search database of 13-million reports to identify all CXRs reports with addendums from 1999-2021. Of the 3469 CXR reports with an addendum, a thoracic radiologist excluded reports where addendum was created for typographic errors, wrong report template, missing sections, or uninterpreted signoffs. The remaining reports with addendum (279 patients) with errors related to side-discrepancy or missed findings such as pulmonary nodules, consolidation, pleural effusions, pneumothorax, and rib fractures. All CXRs were processed with an AI algorithm. Descriptive statistics were performed to determine the sensitivity, specificity, and accuracy of AI to detect missed or mislabeled findings. Results: AI had high sensitivity (96%), specificity (100%), and accuracy (96%) for detecting all missed and mislabeled CXR findings. The corresponding finding-specific statistics for AI were nodules (96%, 100%, 96%), pneumothorax (84%, 100%, 85%), pleural effusion (100%, 17%, 67%), consolidation (98%, 100%, 98%), and rib fractures (87%, 100%, 94%). Conclusion: The CXR AI could accurately detect mislabeled and missed findings. Clinical Relevance: The CXR AI can reduce the frequency of errors in detection and side-labeling of radiographic findings.

The stellar winds of the central stars of planetary nebulae play an essential role in planetary nebulae shaping. In the interacting stellar winds model, the fast stellar wind injects energy and momentum which are transfered to the nebular envelope through an X-ray-emitting hot bubble. Together with other physical processes, such as the ionization of the nebular envelope, the asymmetrical mass-loss in the AGB, and the action of collimated outflows and magnetic fields, the presurized hot gas determines the expansion and evolution of planetary nebulae. \emph{Chandra} and \emph{XMM-Newton} have provided us with detailed information of this hot gas. Here in this talk I will review our current understanding of the effects of the fast stellar wind in the shaping and evolution of planetary nebulae and give some hints of the promissing future of this research.

Astronomical X-ray polarimetry was first explored in the end of the 60's by pioneering rocket instruments. The craze arising from the first discoveries on stellar and supernova remnant X-ray polarization led to the addition of X-ray polarimeters on-board of early satellites. Unfortunately, the inadequacy of the diffraction and scattering technologies required to measure polarization with respect to the constraints driven by X-ray mirrors and detectors, coupled to long integration times, slowed down the field for almost 40 years. Thanks to the development of new, highly sensitive, compact X-ray polarimeters in the beginning of the 2000's, the possibility to observe astronomical X-ray polarization is rising again and scientists are now ready to explore the high energy sky thanks to modern X-ray polarimeters. In the forthcoming years, several X-ray missions (both rockets, balloons and satellites) will open a new observational windows. A wind of renewal blows over the area of X-ray polarimetry and this paper presents for the first time a quantitative assessment, all based on scientific literature, of the growth of interest for astronomical X-ray polarimetry.

The archival Rossi X-ray Timing Explorer (RXTE) Proportional Counter Array (PCA) observations of HZ Her/Her X-1 are analyzed here. The time periods for Anomalous Low States are refined. The 35-day X-ray lightcurve of Her X-1 is produced using 35-day phases determined with RXTE All-Sky Monitor (ASM) and Swift Burst Altert Telescope (BAT) data, with adjustments based on the RXTE/PCA data. The result is the highest sensitivity 35-day lightcurve of Her X-1. The RXTE/PCA data were separated into 8 differents states of the 35-day cycle: Main High (MH) turn-on, MH, MH decline, Low State (LS) 1, Short High (SH) turn-on, SH, SH decline, and LS2. Orbital lightcurves were created for each state, and the different states are compared. Eclipse data was extracted for each state to determine the changes of eclipse shape with 35-day phase. A scattering corona model was fit to the eclipses for the different 35-day states: this shows that the corona is present at all 35-day phases with similar intensity. We carried out a search for previously-reported dips with no absorption, but did not find any.

The aging mechanism of 10% and 30% nickel substituted manganese hexacyanoferrate cathode material in aqueous zinc-ion batteries has been explored through the advanced synchrotron-based two-dimensional x-ray fluorescence technique. Thanks to the two-dimension modality, not only the metal concentration dynamics throughout the entire electrodes was followed during the aging process, but their spatial distribution was also revealed, suggesting the route of the material transformation. The dissolution of Mn and Ni, and the penetration of Zn inside the framework, alongside the Mn aggregations outside the hexacyanoferrate framework were detected. Additionally, the possibility of conducting x-ray absorption spectroscopy measurements on the regions of interest made it possible to explore the chemical state of each metal, and furthermore, synchrotron-based powder x-ray diffraction demonstrated the gradual structural modification in 30% Ni-containing sample series, in terms of the different phase formation.

Osteoporosis is a common problem in orthopedic medicine, and it has become an important medical issue in orthopedics as Taiwan is gradually becoming an aging society. In the diagnosis of osteoporosis, the bone mineral density (BMD) derived from dual-energy X-ray absorptiometry (DXA) is the main criterion for orthopedic diagnosis of osteoporosis, but due to the high cost of this equipment and the lower penetration rate of the equipment compared to the X-ray images, the problem of osteoporosis has not been effectively solved for many people who suffer from osteoporosis, however, at present, in clinical diagnosis, doctors are not yet able to accurately interpret X-ray images for osteoporosis manually, and must rely on the data obtained from DXA. In recent years, with the continuous development of artificial intelligence, especially in machine learning and deep learning, significant progress has been made in image recognition. Therefore, it is worthwhile to revisit whether it is possible to use a convolutional neural network model to read a hip X-ray image and then predict the patient's BMD. In this study, we proposed a hip X-ray image segmentation model and a hip X-ray image recognition classification model. First, we used the U-Net model as a framework to segment the femoral neck, greater trochanter, wards triangle, and the total hip in the hip X-ray images. We then performed image matting and data augmentation. Finally, we constructed a predictive model for osteoporosis using deep learning algorithms. In the segmentation experiments, we used intersection over union (IoU) as the evaluation metric for image segmentation, and both the U-Net and U-Net++ models achieved segmentation results greater than or equal to 0.5. In the classification experiments, using the T-score as the classification basis, the total hip using the DenseNet121 model has the highest accuracy of 74%.

Data sets for medical images are generally imbalanced and limited in sample size because of high data collection costs, time-consuming annotations, and patient privacy concerns. The training of deep neural network classification models on these data sets to improve the generalization ability does not produce the desired results for classifying the medical condition accurately and often overfit the data on the majority of class samples. To address the issue, we propose a framework for improving the classification performance metrics of deep neural network classification models using transfer learning: pre-trained models, such as Xception, InceptionResNet, DenseNet along with the Generative Adversarial Network (GAN) – based data augmentation. Then, we trained the network by combining traditional data augmentation techniques, such as randomly flipping the image left to right and GAN-based data augmentation, and then fine-tuned the hyper-parameters of the transfer learning models, such as the learning rate, batch size, and the number of epochs. With these configurations, the Xception model outperformed all other pre-trained models achieving a test accuracy of 98.7%, the precision of 99%, recall of 99.3%, f1-score of 99.1%, receiver operating characteristic (ROC) - area under the curve (AUC) of 98.2%.

Scattering of ultrashort X-ray pulses (USP) is an important component of the diffraction analysis of matter using modern USP sources. Usually, the specific scattering of such USPs is not taken into account to determine the structure of a substance. Taking into account the specifics of scattering on complex structures will give more accurate results when deciphering complex structures. In this work, it is shown that when X-ray USPs are scattered on diamond with NV centers, it is necessary to take into account the pulse duration. The results obtained can be very different from the widely used theory of diffraction analysis, which confirms the need to take into account the specifics of USP scattering when diagnosing complex structures. It is also shown that scattering spectra are quite sensitive to the concentration of NV centres in the diamond structure and this can be used in diffraction analysis.

Diamond powders with inclusions of europium atoms were synthesized at high pressure (7.7 GPa) and temperature (1800oC) from a mixture of pentaerythritol, C(CH2OH)4, and pyrolyzate of diphthalocyanine (C64H32N16Eu) served as a special precursor. In prepared diamonds by X-ray fluorescence spectroscopy, we have found the concentration of Eu atoms of 51±5 ppm that is by two orders of magnitude greater than that in known natural and synthetic diamonds. X-ray diffraction, SEM, X-ray exited optical luminescence, Raman and IR spectroscopy have confirmed the formation of diamond monocrystals of high quality with em-bedded Eu atoms and a nitrogen content of ~500 ppm. Numerical simulation has allowed us de-termine the energy cost of 5.8 eV needed for the incorporation of a single Eu atom with adjacent vacancy into growing diamond crystal (528 carbons).

At INFN-LNS, and in collaboration with the ATOMKI laboratories, an innovative multi-diagnostic system with advanced analytical methods has been designed and implemented. This is based on several detectors and techniques (Optical Emission Spectroscopy, RF systems, Interfero-polarimetry, X-ray detectors) and here we focus on high resolution spatially-resolved X-ray spectroscopy, performed by means of a X-ray pin-hole camera setup operating in the 0.5−20 keV energy domain. The diagnostic system was installed at a 14 GHz Electron Cyclotron Resonance (ECR) ion source (ATOMKI, Debrecen), enabling high precision X-ray spectrally-resolved imaging of ECR plasmas heated by hundreds of Watts. The achieved spatial and energy resolution were 0.5 mm and 300 eV at 8 keV, respectively. We here present the innovative analysis algorithm that we properly developed for obtaining Single Photon-Counted (SPhC) images providing the local plasma emitted spectrum in a High-Dynamic-Range (HDR) mode, by distinguishing fluorescence lines of the materials of the plasma chamber (Ti, Ta) from plasma (Ar). This method allows a quantitative characterization of warm electrons population in the plasma (and its 2D distribution) which are the most important for ionization, and also to estimate local plasma density and spectral temperatures. The developed post-processing analysis is also able to remove the readout noise, that is often observable at very low exposure times (msec). The setup is now under update including fast shutters and trigger systems in order to allow simultaneously space and time-resolved plasma spectroscopy during transients, stable and turbulent regimes.

Different contact materials along with optimization of the deposition techniques expand the possibilities to obtain high performance room temperature CdTe-based X/γ-ray detectors. The heterostructures with ohmic (MoOx) and Schottky (MoOx, TiOx, TiN, and In) contacts, created by DC reactive magnetron sputtering and vacuum thermal evaporation, as well as In/CdTe/Au diodes with a p-n junction, formed by laser-induced doping, were developed and investigated. Depending on the pre-treatment of the surface of semi-insulating p-CdTe crystals, deposition of a MoOx film formed an ohmic or Schottky contact. Based on the calculations and IV characteristics of the fabricated Mo-MoOx/р-CdTe/MoOx-Mo, In/CdTe/MoOx-Mo, Ti-TiOx/р-CdTe/MoOx-Mo, and Ti-TiN/р-CdTe/MoOx-Mo Schottky-diode detectors, the current transport processes were described in the models of the carrier generation-recombination within the space-charge region (SCR) at low bias voltages, and space-charge limited current at higher voltages, respectively. The energies of generation–recombination centers, density of trapping centers, and carrier lifetimes were determined. A sharp increase in the reverse current in the Mo-MoOx/р-CdTe/MoOx-Mo, Ti-TiOx/р-CdTe/MoOx-Mo, and Ti-TiN/р-CdTe/MoOx-Mo heterostructures at high bias was discussed in frames of the Poole–Frenkel emission model. Nanosecond laser irradiation of the In electrode, pre-deposited on the p-CdTe crystals, resulted in an increase in the voltage range, corresponding to the carrier generation-recombination in the SCR, in the IV characteristics of the In/CdTe/Au diodes. Such In/CdTe/Au p-n junction diodes demonstrated high energy resolutions (7%@59.5 keV, 4%@122 keV, and 1.6%@662 keV).

Agricultural crops productivity is heavily influenced by the strength of their seeds. Current methods for testing seed vigor, such as the germination rate and tetrazolium test, rely on time-consuming human visual inspections. Computer Vision, a crucial technology in smart production processes, offers an automated alternative and is increasingly applied in digital agriculture processes. Here we propose a method that combines YOLOv8 and morphological analysis of seeds using X-ray images to aid seed quality analysts in classifying seed lots based on their physiological potential. We examined the internal morphology of three seed lots and generated X-ray images to train a YOLOv8-based model with a post-segmentation module. This model assessed various parameters such as the total seed area, area filled by the embryo and endosperm, length, width, and calculated the percentage occupied by the embryo and endosperm in relation to the total seed area. Subsequently, seeds were classified into four categories based on the internal area occupied by the endosperm and embryo. Our findings reveal the robust performance of the YOLOv8 model in segmenting and classifying despite the challenges posed by a relatively small dataset. Notably, the proposed model achieved an impressive accuracy of up to 95.6% in identifying and segmenting the endosperm over 1,500 epochs with just 15 training images. The endosperm/seed area ratio, particularly within the 50-60% range covering over 50% of the samples, emerged as a significant metric for evaluating the viability of seed batches.

The development of novel coherent and brilliant sources, such as soft X-ray Free Electron Laser (FEL) and High Harmonic Generation (HHG) enables new ultrafast analysis of the electronic and structural dynamics of a wide variety of materials. Soft X-ray FEL delivers high brilliance beams with short pulse duration, high spatial coherence and photon energy tunability. In com-parison with FELs, HHG X-ray sources are characterized by a wide spectral bandwidth and few to sub-femtosecond pulses. The approach will lead to time-resolved reconstruction of molecular dynamics, shedding light on different photochemical pathways. The high peak brilliance of soft X-ray FELs facilitates investigations in nonlinear regime, while the broader spectral bandwidth of the HHG sources may provide the simultaneous probing of multiple components. Significant technical breakthroughs in these novel sources are under way to improve brilliance, pulse dura-tion, and to control spectral bandwidth, spot size, and energy resolution. Therefore, in the next few years, the new generation of soft X-ray sources combined with novel experimental tech-niques, new detectors, and computing capabilities will allow the study of several extremely-fast dynamics, such as vibronic dynamics. In the present review, we shortly discuss recent devel-opments in experiments, performed with soft X-ray FELs and HHG sources, operating near car-bon K-absorption edge, being a key atomic component in biosystems and soft materials. Differ-ent spectroscopy methods such as time-resolved pump-probe techniques, nonlinear spectrosco-pies and photoelectron spectroscopy studies have been addressed in an attempt of a better un-derstanding of fundamental physico-chemical processes

Ferroelectric materials are crucial for today’s technological society, and nanostructured ferroelectric materials are important for downscaling of devices. Controlled and reproducible synthesis of these materials are therefore of immense importance. Hydrothermal synthesis is a well-established synthesis route, with a large parameter space for optimization, but a better understanding of nucleation and growth mechanisms is needed for full utilization and control. Here we use in situ X-ray diffraction to follow the nucleation and growth of BaTiO₃ formed by hydrothermal synthesis using two different titanium precursors, an amorphous titania precipitate slurry and a Ti-citric acid complex solution. Sequential Rietveld refinement was used to extract the time dependency of lattice parameters, crystallite size, strain and atomic displacement parameters. Phase pure BaTiO₃ nanoparticles 10 - 15 nm in size were successfully synthesized at different temperatures (100, 125, and 150 °C) from both precursors after reaction times ranging from a few seconds, to several hours. The two precursors resulted in phase pure BaTiO₃ with similar final crystallite size. Finally, two different growth mechanisms were revealed, where the effect of surfactants present during hydrothermal synthesis is discussed as one of the key parameters.

To make low-cost catalytic materials that mimic the activity of tyrosinase enzymes (Catechol oxidase) is an exciting challenge of biochemical technology. Herein, we report the synthesis of a series of acylhydrazone-pyrazoles based biomolecule materials (L1-L7) with superior catecholase activity. These biomolecules were synthesized by a one pot chemical condensation between 5-methyl-1H-pyrazole-3-carbohydrazide and benzaldehyde derivatives. The X-ray single crystal diffraction (XRD) for two ligands L1 and L2 have been studied and the molecular structures were optimized and confirmed using the density functional theory (DFT/B3LYP) method. Copper (II) complexes of the biomolecules (L1-L7), generated in-situ, and were studied for their catalytic activities towards the oxidation reaction of catechol to ortho-quinone according to two parameters: the nature of the ligand and the nature of counter anion. The L7-CuSO4 was found to have an excellent catalytic activity (105.42 μmol·L−1·min−1) among the catalysts recently reported in the existing literature.

The three-point bending behavior of a single Au nanowire deformed with an atomic force microscope was monitored by coherent X-ray diffraction using a sub-micrometer sized hard X-ray beam. While three-dimensional reciprocal-space maps were recorded before and after deformation by standard rocking curves, they were measured by scanning the energy of the incident X-ray beam during deformation at different loading stages. The mechanical behavior of the nanowire is visualized in reciprocal space and a complex deformation mechanism is described. In addition to the expected bending of the nanowire, torsion is detected. Bending and torsion angles are quantified from the high resolution diffraction data.

Abstract: Comparing outcrop data to laboratory results is important to verify and validate experiments of analogue and reservoir materials especially regarding conditions for deformation experiments. This is important better understand highly complex carbonate reservoir strata and their response to changes in subsurface conditions, reducing subsurface uncertainty. This study develops methods to allow for a more straightforward comparison of outcrop data (m-scale) with experimentally created fracture arrays developed in cylindrical samples (cm-scale). The main objective is to assess usefulness of experimentally-produced fracture networks as analogues for subsurface structures, typically at the meter and above scale by developing new techniques to use the lab deformation. It analyses key characteristics of laboratory-induced fracture networks by adapting scanline methods to use with x-ray tomography (XRT) images to allow for comparison with outcrop and field data. To test and verify these new methods two low permeability carbonate samples were used for deformation testing and analysis. Applying the different scanline methods we show that they can be used to analyse lab induced fractures (mm to cm-scale) identified in XRT images for comparison with outcrop data (m-scale). In addition, these methods also allow for quantification of fracture network attributes e.g. fracture spacing, fracture apertures, orientation. This new data bridges the gap between micro-scanlines using thin sections and outcrop scanlines.

Industrial radiography is a pivotal non-destructive testing (NDT) method that ensures quality and safety in a wide range of industrial sectors. Conventional human-based approaches, however, are prone to challenges in defect detection accuracy and efficiency, primarily due to the high inspection demand from manufacturing industries with high production throughput. To solve this challenge, numerous computer-based alternatives have been developed, including Auto-mated Defect Recognition (ADR) using deep learning algorithms. At the core of training, these algorithms demand large volumes of data that should be representative of real-world cases. However, the availability of digital X-ray radiography data for open research is limited by non-disclosure contractual terms in the industry. This study presents a pipeline that is capable of modeling synthetic images based on statistical information acquired from X-ray intensity distribution from real digital X-ray radiography images. Through meticulous analysis of the intensity distribution in digital X-ray images, the unique statistical patterns associated with the exposure conditions used during image acquisition, type of component, thickness variations, beam divergence, anode heel effect, etc., are extracted. The realized synthetic images were utilized to train deep learning models, yielding an impressive model performance with mean intersection over union (IoU) of 0.93, and mean dice coefficient of 0.96, on real unseen digital X-ray radiography images. This methodology is scalable and adaptable, making it suitable for diverse industrial applications.

The COVID-19 pandemic situation has created even more difficulties in the quick identification and screening of the COVID-19 patients for the medical specialists. Therefore, a significant study is necessary for detecting COVID-19 cases using an automated diagnosis method, which can aid in controlling the spreading of the virus. In this paper, the study suggests a Deep Convolutional Neural Network-based multi-classification approach (COV-MCNet) using eight different pre-trained architectures such as VGG16, VGG19, ResNet50V2, DenseNet201, InceptionV3, MobileNet, InceptionResNetV2, Xception which are trained and tested on the X-ray images of COVID-19, Normal, Viral Pneumonia, and Bacterial Pneumonia. The results from 3-class (Normal vs. COVID-19 vs. Viral Pneumonia) showed that only the ResNet50V2 model provides the highest classification performance (accuracy: 95.83%, precision: 96.12%, recall: 96.11%, F1-score: 96.11%, specificity: 97.84%) compared to rest of the models. The results from 4-class (Normal vs. COVID-19 vs. Viral Pneumonia vs. Bacterial Pneumonia) demonstrated that the pre-trained model DenseNet201 provides the highest classification performance (accuracy: 92.54%, precision: 93.05%, recall: 92.81%, F1-score: 92.83%, specificity: 97.47%). Notably, the ResNet50V2 (3-class) and DenseNet201 (4-class) models in the proposed COV-MCNet framework showed higher accuracy compared to the rest six models. This indicates that the designed system can produce promising results to detect the COVID-19 cases on the availability of more data. The proposed multi-classification network (COV-MCNet) significantly speeds up the existing radiology-based method, which will be helpful to the medical community and clinical specialists for early diagnosis of the COVID-19 cases during this pandemic.

Setting A high proportion of notified tuberculosis cases in the Philippines are clinically diagnosed (63%) as opposed to bacteriologically confirmed. Better understanding of this phenomenon is required to improve tuberculosis control. Objectives To determine the percentage of Smear Negative Presumptive Tuberculosis patients that would be diagnosed by GeneXpert; compare clinical characteristics of patients diagnosed as tuberculosis cases; and review the impact that the current single government physician and a reconstituted Tuberculosis Diagnostic committee (Expert Panel) may have on tuberculosis over-diagnosis. Design This is a cross-sectional study of 152 patients 15-85 years old with two negative Direct Sputum Smear Microscopy results, with abnormal chest X-ray who underwent GeneXpert testing and review by an Expert Panel. Results 31% (48/152) of the sample were Xpert positive. 93% (97/104) of GeneXpert negatives were clinically diagnosed by a Single Physician. Typical symptoms and X-ray findings were higher in bacteriologically confirmed tuberculosis. When compared to GeneXpert results, the Expert panel’s sensitivity for active tuberculosis was high (97.5%, 39/40) but specificity was low (40.2%, 35/87). Conclusion Using the GeneXpert would increase the level of bacteriologically confirmed tuberculosis substantially among presumptive Tuberculosis. An Expert panel will greatly reduce over-diagnosis usually seen when a decision is made by a Single Physician.

Optimum design and accurate control of the internal structure of the laser target materials remain an important goal for various laser physics experiments, especially for generating high flux photon and neutron beams. The low-density material is considered to be one of the most difficult for X-ray study due to its high transparency and imperceptible contrast. To produce clear visualization of foam containing sparse structures we used a high-quality monochromatic X-ray beam of synchrotron radiation source PETRA-III at DESY. The X-ray beam parameters allow tomographic scanning with application of phase contrast retrieval algorithms. A series of 3D images of foam-suspended glass microsphere inside the plastic cylinder were obtained with the quality high enough to observe the internal structure and to visualize uniformity, displacement and surface roughness on both sides of the microsphere. The main object under investigation was a CH-plastic capillary including 10 mg/cc CHO-foam with the centered glass microsphere. The results of this work demonstrate that tomographic visualization based on a high quality X-ray radiation and phase contrast analysis is an effective and useful technique for development of new laser targets containing structured low density materials.

In recent years, semiconductor survey meters have been developed and are in increasing demand worldwide. This study aimed to investigate whether it is possible to calculate the time constant of the semiconductor survey meter using the X-ray equipment installed in each medical facility and whether it is possible to calibrate the semiconductor survey meter. Attach an additional filter to the medical X-ray system to satisfy the standards of N-60 to N-120, add more copper plates from there, and calculate the first and second half-value layers to compare with N-60 to N-120 values. Next, we will measure the leakage dose using a medical X-ray system and calculate the time constant of the survey meter. The survey meter is then calibrated and compared with the calibration factors in industrial X-ray system. Per experimental results, it is possible to reproduce the N-60 to N-120 radiation quality using a medical X-ray system and to calculate the time constant from the measured results assuming actual leakage dosimetry using that radiation quality. We also found that the calibration factor was equivalent to that of an industrial X-ray device. It was revealed that semiconductor survey meters can be calibrated using a medical X-ray system.

Magnesium-silver alloys are of high interest for the use as temporary bone implants due to their antibacterial properties in addition to biocompatibility and biodegradability. Thin wires in particular can be used for scaffolding, but the determination of their degradation rate and homogeneity using traditional methods is difficult. Therefore, we have employed 3D imaging using X-ray near-field holotomography with sub-micrometer resolution to study the degradation of thin (250 μm diameter) Mg-2Ag and Mg-6Ag wires. The wires were studied in two states, recrystallized and solution annealed to assess the influence of Ag content and precipitates on the degradation. Imaging was employed after degradation in Dulbecco’s modified Eagle’s medium and 10% fetal bovine serum after 1 to 7 days. At 3 days of immersion the degradation rates of both alloys in both states were similar, but at 7 days higher silver content and solution annealing lead to decreased degradation rates. The opposite was observed for the pitting factor. Overall, the standard deviation of the determined parameters was high, owing to the relatively small field of view during imaging and high degradation inhomogeneity of the samples. Nevertheless, Mg-6Ag in the solution annealed state emerges as a potential material for thin wire manufacturing for implants.

Cold gas-dynamic spray (cold spray) is an evolving coating deposition and restoration technology in which particles are deposited above the sonic speed. This paper presents the non-destructive three-dimensional characterization of cold sprayed stainless steel coating. The visualization of coating morphology and volumetric porosity, and the analyses of porosity size and spatial distributions confirmed that dense stainless steel coating with non-connected, micron-sized gradient porosity is successfully produced by cold spray. The suitability of X-ray tomography for characterizing cold sprayed coatings is assessed.

Chest trauma is a critical medical condition that encompasses a range of injuries and can result from various causes. Prompt and accurate diagnosis is crucial in managing chest trauma patients and radiology plays a pivotal role in this aspect. Imaging modalities in chest trauma aid in precise diagnosis and treatment planning. Especially, X-rays remain the initial imaging modality of choice due to their accessibility, speed, and ability to detect acute life-threatening conditions. Computed Tomography (CT) Scan offers detailed cross-sectional images allowing for comprehensive evaluation of chest trauma and surgical planning when necessary. Ultrasound (US) is increasingly valuable tool due to its portability and real-time imaging capabilities, aiding in rapid assessment at the bedside. Magnetic Resonance Imaging (MRI) is less commonly used due to time constraints and limited availability. Radiological imaging serves various purposes in the diagnosis and management of chest trauma such as early detection and triage, characterization and severity assessment, surgical planning, follow-up and monitoring of chest trauma. Reduction of radiation exposure, advancements in imaging technology (dual-energy CT, contrast-enhanced imaging) and Artificial Intelligence (AI) algorithms are crucial challenges and deserve attention. A multidisciplinary approach integrating radiological expertise remains fundamental in ensuring optimal outcomes for patients with chest trauma.

We have recently introduced the possibility of performing operando small-angle X-ray scattering measurements using a novel industrially relevant injection moulding system for plastics. We show that useful time-resolving measurements can be performed with a time-cycle of 1s and we highlight the possible steps to reduce this to 0.5s. We show how we can use the transmission measurements to provide a time-marker when plastic first enters the mould cavity in the region probed by the incident X-ray beam. We show the opportunities provided by this experimental stage mounted on the NCD-SWEET beamline at ALBA to probe the reproducibility of the injection moulding system on different scales. The design of the equipment allows the development of the structure and the morphology to be evaluated in different parts of mould cavity and we evaluate any differences in a rectangular mould cavity. We identify future prospects for this equipment in terms of novel mould heating and cooling systems and the opportunities for quantitatively evaluating radical approaches to injection moulding technology.

The pulse duration in short-pulse schemes for Self-Amplified Spontaneous Emission Free Electron Lasers (SASE FELs) is limited by the FEL coherence time. A recently proposed concept allows to overcome the coherence time barrier and to get much shorter pulses. When the lasing part of an electron bunch is much shorter than the coherence time, one can suppress the radiation in the long main undulator while preserving microbunching within that short lasing slice. Then a short radiation pulse is produced in a relatively short radiator. A possible suppression method, an excessive reverse undulator taper, is discussed and illustrated numerically in this paper. We also performed first experimental tests of this method at the soft X-ray FEL user facility FLASH. The measured pulse duration approaches 1 fs (FWHM) at the wavelength of 5 nm.

The aim of this study was to clarify degradation characteristics in each tissue of the knee complex of a medial meniscectomy (MMx)-induced knee osteoarthritis (KOA) animal model using classical methods and a new comprehensive evaluation method called contrast-enhanced X-ray micro-computed tomography (CEX-μCT), which was developed in the study. Surgical MMx was performed in the right knee joints of five male Wistar rats to induce KOA. At 4 wk post-surgery, the synovitis was evaluated using qPCR. Degradations of the articular cartilage of the tibial plateau were evaluated using classical methods and CEX-μCT. Evaluation of the synovitis demonstrated significantly increased expression levels of inflammation-associated marker genes in MMx-treated knees compared to that in sham-treated knees. Evaluation of the articular cartilage using classical methods showed that MMx fully induced degradation of the cartilage. Evaluation using CEX-μCT showed that local areas of the medial cartilage of the tibial plateau were significantly reduced in MMx-treated knees compared to that in sham-treated knees. On the other hand, total cartilage volumes were significantly increased in MMx-treated knees. Based on the findings of this study, the researchers in KOA research could be helped to select an optimal KOA model to discover new drugs.

The chelating aluminum complex [2-(Me2NCH2)C2B10H10]AlX2 (X = Br 3, CH3 4) was synthesized using 2-dimethylaminomethyl-o-carboranyl lithium (2) with aluminum tribromide or dimethylaluminum bromide, resulting in a modest yield. Compound 4 was obtained by reacting compound 3 with CH3Li in toluene. All compounds were characterized by infrared (IR) spectroscopy, 1H, 11B, 13C nuclear magnetic resonance (NMR) spectroscopy, and X-ray crystallography. X-ray structural studies of CabNAlBr2 (3) and CabNAlMe2 (4) indicated that the Al atom was located at the center of a distorted tetrahedron. Crystal structures of the CabNAlBr2 (3) [a = 8.9360(3) Å, b = 12.0358(9) Å, c = 14.7730(4) Å, α = β = γ = 90°] and the CabNAlMe2 (4) [a = 8.9551(3) Å, b = 11.9126(9) Å, c = 14.7711(4) Å, α = β = γ = 90°] were obtained. The reactivity of aluminum complexes 3 and 4 with Lewis bases, such as H2O, pyridine, alkylamines, and arylamines, confirmed their rapid decomposition.

It is well known that the basis of diffraction analysis of matter is scattering, including scattering of ultrashort laser pulses. In the theory of scattering of ultrashort pulses the pulse duration parameter is usually not taken into account, which leads to some error. This error may be more significant than the considered effects in the scattering of the pulse on the studied structure. In this paper it is shown that the pulse duration parameter should be taken into account when scattering X-ray pulses on oriented diamonds with NV-centers. It is shown that the scattering spectra can be used to judge the orientation of NV centers in the diamond structure. The obtained results may be very different from the widely used theory of diffraction analysis, which confirms the necessity of taking into account the pulse duration parameter in the diagnosis of complex structures.

High-throughput research on bimetallic nanoparticles brought a vast overview of their characteristics and catalytic activities.¹ However, traditional bimetallic nano-allloy quantification methods serving catalyst preparations are not suitable for the fast and robust data output of high-throughput experiments. Hence, this work designed and validated a more fast, more neat, and reliable quantitative analysis using X-ray fluorescence spectroscopy for bimetallic nanoparticles synthesized by high-throughput setups. The results demonstrated this method to be accurate with high precision. Furthermore, the agreement to qualitative results from an energy-dispersive X-ray spectrometer equiped on a scanning electron microscope provided an option to quantify a bimetallic nano-alloy by just analyzing one of the two composing elements. Thus, this method is proved to be highly compatible with high-throughput experiments.

The XChem facility at Diamond Light Source offers fragment screening by X-ray crystallography as a general access user program. The main advantage of X-ray crystallography as a primary fragment screen is that it yields directly the location and pose of the fragment hits, whether within pockets of interest or merely on surface sites: this is the key information for structure-based design and for enabling synthesis of follow-up molecules. Extensive streamlining of the screening experiment at XChem has engendered a very active user programme that is generating large amounts of data: in 2017, 36 academic and industry groups generated 35,000 datasets of uniquely soaked crystals. It has also generated a large number of learnings concerning the main remaining bottleneck, namely obtaining a suitable crystal system that will support a successful fragment screen. Here we discuss the practicalities of generating screen-ready crystals that have useful electron density maps, and how to ensure they will be successfully reproduced and usable at a facility outside the home lab.

The impact of the cell community on its individual components in the prokaryotic realm is often overlooked. However, in the case of intracellular pathogens, where each infected cell can be considered as a single community, understanding how a population adapts to its environment to evolve and successfully propagate is key. Chlamydia infections are characterised by a silent propagation of the bacteria within individual hosts and the wider population. Chlamydia are strict intracellular pathogens residing within a specialised membrane-bound compartment called the inclusion. The life cycle of Chlamydia involves altering between the invasive elementary bodies (EBs) and replicative reticulate bodies (RBs). We have used cryo-soft X-ray tomography to observe individual inclusions, combining excellent resolution (40 nm) and large volume imaging (up to 16 µm). Combined with a semi-automated segmentation pipeline, we were able to consider each inclusion as an individual bacterial niche. Within the inclusion, we identified and classified different forms of the bacteria and confirmed the recent finding that RBs have a variety of volumes (small, large and abnormal). Moreover, we demonstrate that the proportions of these different RB forms depend on the bacterial concentration in the cell demonstrating the impact of the group on its individual component. We conclude that each inclusion operates as an autonomous community which regulates the characteristics of individual bacteria within the inclusion

Accurate treatment planning in radiotherapy essentially decreases secondary damage to healthy tissue surrounding the tumor. Due to plans to use a direct, highly collimated, narrow beam with high intensity to treat small area tumors, researchers have studied microbeam radiation therapy extensively. Using a synchrotron beam as the radiation source may help to limit secondary damage, but treatment planning using computerized simulations and dosimetry is still necessary to achieve optimal results. For this purpose, PDA-gel dosimeters were developed and their sensitivity around a 150 keV induced synchrotron X-ray radiation beam was examined via Monte Carlo simulations using the EGS5 code system. The microbeam development is now at the animal study stage. In this study, we simulate the irradiation of a rat's brain. The simulation results obtained spectra for two types of PDA-gel dosimeters that were compared with the spectrum obtained in a modelized brain tumor of a rat. Additionally, percentage depth dose curves were calculated for the brain tissue and the two gels. Correction equations for the dosimeters were obtained from the dose-difference plots. For further references, these equations can be used to calculate the actual dose in a brain tumor in a rat. The Monte Carlo simulations demonstrate that PDA-gel dosimeters can be used as a reference technique in planning treatment using synchrotron irradiations and in other medical treatment planning methods.

This paper presents a two-stage ADC based on pseudo-differential operational transconductance amplifier (OTA), which is designed for the readout circuit of X-ray linear array sensor. This hybrid ADC employs an incremental sigma-delta ADC and a cyclic ADC, achieving a good trade-off between accuracy and conversion speed. The two stages share the same hardware to reduce power consumption and die area. A common-mood feedback module is used to suppress the influence of charge injection, and the effectiveness is demonstrated by detailed theoretical analysis. A test chip of 14-bit ADC is fabricated in 0.35μm CMOS technology. The measured root mean square (RMS) value of DNL is 0.254 LSB, and the maximum value of INL is -0.776/+1.56 LSB. The measured effective number of bits (ENOB) is 13.43 bits.

The radiation stability of polymer test objects fabricated by direct laser writing is studied. The two groups of 6 cubes (50×50×50 μm3) were printed on a common silicon substrate. 6 cubes were irradiated with X-rays in the synchrotron radiation beam (12 keV, 1010 photons/mm2/s), the other 6 kept non-irradiated for the reference. In each group, the fabrication parameters (laser power and slicing step) were uniformly varied from cube to cube. Each irradiated cube was exposed with the dose of 1013 X-ray photons. The calibration of this dose in the radiological units (Gy) was carried out using the tissue-equivalent thermoluminescent detectors (TLD-800). The corresponding exposition dose was estimated as 30 kGy for each cube. The radiation effects were evaluated by Raman spectroscopy and by morphological changes observed with the raster electron microscope. The primary radiation effect appears in the essential increase of the polymerization degree with consuming carbon-carbon double bonds in favor of the polymer cross-linking. Only one cube of 6 has changed the size and shape due to this effect, while the others retained the initial shape. Morphological changes are connected with the improper fabrication parameters (laser power and slicing step). Properly fabricated objects withstand the X-rays of the synchrotron radiation beam.

Contrast agents developed for X-ray computed tomography (CT) offer extremely valuable tools and techniques in diagnostics via contrast enhancements. Heavy metal-based nanoparticles (NPs) can provide high contrast in CT images. These result from a high density of heavy metal atoms with high X-ray attenuation coefficients that exceed that of iodine (I), which is currently used in hydrophilic organic CT contrast agents. Nontoxicity and colloidal stability are vital characteristics in designing heavy metal-based NPs as CT contrast agents. In addition, the particle size must be small for in vivo renal excretion. In vitro phantom imaging studies can provide X-ray attenuation efficiency, which is a critical parameter for CT contrast agents, and the imaging performance of CT contrast agents can be demonstrated via in vivo experiments. This review focuses on in vitro and in vivo studies of various heavy metal-based NPs (metal: Au, Pt, Pd, Ag, Ce, Gd, Dy, Ho, Yb, Ta, W, and Bi) and provides an outlook on their use as high-performance CT contrast agents.

We describe the design and fabrication of an industrial injection moulding system which can be mounted and used on the NCD-SWEET Small-angle X-Ray Scattering Beamline at ALBA. We show how highly useful time-resolved data can be obtained using this system. We are able to evaluate the fraction of material in the mould cavity and identify the first material to solidify and how this varies with the injection tem-perature. The design follows current industrial practice and provides opportunities to collect time-resolved data at several points within the mould cavity so we can build up a 4D perspective of the morphology and its temporal development. The quantitative data obtained will prove invaluable for the optimisation of the next generation of in-jection moulding techniques. This preliminary work used results from the injection moulding of a general purpose isotactic polypropylene.

In the current manuscript we assess to what extent X-ray photoelectron spectroscopy is a suitable tool for probing the dipoles formed at interfaces between self-assembled monolayers and metal substrates. To that aim, we perform dispersion-corrected, slab-type band-structure calculations on a number of biphenyl-based systems bonded to a Au(111) surface via different docking groups. In addition to changing the docking chemistry (and the associated interface dipoles), also the impacts of polar tail-group substituents and varying dipole densities are investigated. We find that for densely-packed monolayers the shifts of the peak positions of the simulated XP-spectra are a direct measure for the interface dipoles. In the absence of polar tail-group substituents they also directly correlate with adsorption-induced work-function changes. At reduced dipole-densities this correlation deteriorates, as work function measurements probe the difference between the Fermi-level of the substrate and the electrostatic energy far above the interface, while core level shifts are determined by the local electrostatic energy in the region of the atom from which the photoelectron is excited.

Recently, considerable work has been directed at development of a ultra-compact X-ray free-electron laser based on emerging techniques in high field cryogenic acceleration, with attendant dramatic improvements in electron beam brightness, and state-of-the-art concepts in beam dynamics, magnetic undulators, and X-ray optics. A full conceptual design of a 1 nm XFEL with a length and cost over an order of magnitude below current XFELs has resulted from this effort. This instrument has been developed with an emphasis on permitting exploratory scientific research in a wide variety of fields in a university setting. Concurrently, compact FELs are being urgently developed for use as an instrument to enable next generation chip manufacturing through use as a high flux, few-nm lithography source. This new role suggests consideration of XFELs to addressed urgently emerging demands in this sector, as identified by recent national need studies, for new radiation sources aimed at chip manufacturing: a coherent hard X-ray source which enables frontier metrology methods. Indeed, it has been shown that one may use coherent X-rays to perform 10 nm-class resolution surveys of macroscopic, cm-scale structures such as chips, using ptychographic laminography. As the XFEL is a very promising candidate for realizing such methods, we present here an analysis of the issues and likely solutions associated with extending the UCXFEL to harder X-rays (above 7 keV), much higher fluxes and levels of coherence, and methods of applying such a source for ptychographic laminography to micro-electronic device measurements. We discuss the development path to move the concept to rapid realization of a transformative FEL-based application, outlining FEL and metrology system challenges.

In this article, we analyse the computer aid screening method of COVID19 using Xray and CT scan images. The main objective is to set an analytical closure about the computer aid screening of COVID19 among the X-ray image and CT scan image. The computer aid screening method includes deep feature extraction, transfer learning and traditional machine learning image classification approach. The deep feature extraction and transfer learning method considered 13 pre-trained CNN model. The machine learning approach includes three sets of features and three classifiers. The pre-trained CNN models are alexnet, googlenet, vgg16, vgg19, densenet201, resnet18, resnet50, resnet101, inceptionv3, inceptionresnetv2, xception, mobilenetv2 and shufflenet. The features and classifiers in machine learning approaches are GLCM, LBP, HOG and KNN, SVM, Naive bay’s respectively. In addition, we also analyse the different paradigms of classifiers. In total, the comparative analysis is carried out in 65 classification models, i.e. 13 in deep feature extraction, 13 in transfer learning and 39 in machine learning approaches. Finally, all the classification models perform better in X-ray image set compare to CT scan image set.

The Human immunodeficiency virus-1 (HIV-1) matrix (MA) domain is involved in the highly regulated assembly process of the virus particles that occur at the host cell’s plasma membrane. High-resolution structures of the MA domain determined using cryo X-ray crystallography have provided initial insights into the possible steps in the viral assembly process. However, these structural studies have relied on large and frozen crystals in order to reduce radiation damage caused by the intense X-rays. Here, we report the first XFEL study of the HIV-1 MA domain’s interaction with inositol hexaphosphate (IP6), a phospholipid headgroup mimic. We also describe the purification, characterization and microcrystallization of two MA crystal forms obtained in the presence of IP6. In addition, we describe the capabilities of serial femtosecond X-ray crystallography (SFX) using X-ray free-electron laser (XFEL) to elucidate the diffraction data of MA-IP6 complex microcrystals in liquid suspension at ambient temperature. Two different microcrystal forms of MA-IP6 complex both diffracted to beyond 3.5 Å resolution, demonstrating the feasibility of using SFX to study the complexes of MA domain of HIV-1 Gag polyprotein with IP6 at near-physiological temperatures. Further optimization of the experimental and data analysis procedures will lead to better understanding of the MA domain of HIV-1 Gag and IP6 interaction at high resolution and provide basis for optimization of the lead compounds for efficient inhibition of the Gag protein recruitment to the plasma membrane prior to virion formation.

The spectra and global distributions of the X-ray emissions generated by the solar wind charge-exchange (SWCX) process in the terrestrial magnetosheath are investigated based on a global hybrid model and a global geocoronal hydrogen model. The solar wind O6+ ions which are the primary charge state for oxygen ions in solar wind are considered. The line emissivity of the charge-exchange born O5+ ions are calculated by Spectral Analysis System for Astrophysical and Lab oratory (SASAL). It is found that the emission lines from the O5+ ranges from 105.607 to 118.291 eV with the strong line at 107.047 eV. We then simulated the magnetosheath X-ray emission intensity distributions with a virtual camera at two positions of north pole and dusk at six stages during the passing of a perpendicular interplanetary shock combined with a tangential discontinuity structure through the Earth’s magnetosphere. During this process, the X-ray emission intensity increases with time, and the maximum value is 27.11 keV cm-2 s-1 sr-1 on the dayside, which is 4.5 times that before the solar wind structure reaches the Earth. A clear shock structure can be seen in the magnetosheath and moves earthward. The maximum emission intensity seen at dusk is always higher than that seen at north pole.

Air filtration mechanisms in the composite filter media used in practical applications are important and challenging to understand because the component fibers could have various size scales and morphologies. In this work, a three-dimensional digital model of nanofiber-based filter media was reconstructed for the first time based on the X-ray tomography data for the cellulose substrate and the Focused Ion Beam-Scanning Electron Microscope (FIB-SEM) image analysis for the several microns thick (3.82-7.90 μm) electrospun polyvinylidene fluoride (PVDF) nanofiber membrane. Besides the high-resolution model where the details of the fibrous structures were fully resolved, another low-resolution model with approximated unresolved structures was also established. Filtration simulations utilizing these models were conducted considering the drag force, Brownian diffusion and aerodynamic slip. The simulated filtration efficiencies agreed well with the experiments for particles of 70-400 nm, including the most penetrating particle size (MPPS, 100-200 nm). Moreover, the structure-resolved models had higher accuracy but higher computational costs, while the unresolved simulations saved much running time but over-predicted the filtration efficiency, especially for smaller particles (<100 nm). Our study presents a comprehensive strategy for investigating the composite filter media with multiscale complex structures using a combination of advanced characterization technologies and modular simulation models.

One of the critical tools for early detection and subsequent evaluation of the incidence of lung diseases is chest radiography. At a time when the speed and reliability of results, especially for COVID-19 positive patients, is important, the development of applications that would facilitate the work of untrained staff involved in the evaluation is also crucial. Our model takes the form of a simple and intuitive application, into which you only need to upload X-rays: tens or hundreds at once. In just a few seconds, the physician will determine the patient's diagnosis, including the percentage accuracy of the estimate. While the original idea was a mere binary classifier that could tell if a patient was suffering from pneumonia or not, in this paper we present a model that distinguishes between a bacterial disease, a viral infection, or a finding caused by COVID-19. The aim of this research is to demonstrate whether pneumonia can be detected or even spatially localized using a uniform, supervised classification.

The development of new cultivars is important for the profitability of the floriculture industry. There are a limited number of cultivars of Zantedeschia aethiopica, an iconic ornamental cut flower, garden plant, and potted plant, due to the incompatibility of interspecific crossings within the genus. Most present-day varieties are the result of spontaneous mutations or classical breeding within the species, followed by a long selection process. Breeders are very interested in the development of a time- and cost-effective method for producing new Z. aethiopica cultivars with novel characteristics. Here, Z. aethiopica mutants were generated by treating seeds with 100 Gy of X-ray radiation. The resulting putative mutants were selected based on particular flowering parameters and compared to non-irradiated, control plants. Over two growing seasons, characteristics such as early flowering, flower size and shape, yield and response to soft-rot disease were monitored and considerable variation was observed among the mutated lines. Out of 319 mutants, 20 lines were selected based on their phenotypes and then propagated and further analyzed. Within this group, only two phenotypes displayed at least five improved flowering properties under natural, Mediterranean conditions. The rest displayed two to four desired combinations of flowering traits, some with great commercial potential.

The purpose of this work was to achieve non-destructive detection of the internal defects of in-shell walnuts using X-ray radiography technology based on improved Faster R-CNN network model. First, the FPN structure was added to the feature extraction layer to extract richer image information. Then ROI Align was used to instead of ROI Pooling for eliminating the localization bias problem caused by quantization operation. Finally, the Softer-NMS module was introduced to the final regression layer with the predicted bounding box for improving the localization accuracy of the candidate boxes. The results indicated that the internal defects in intact walnuts with shells could be identified effectively using the proposed improved network model in this study. Specifically, the discrimination accuracy of the in-shell sound, shriveled and empty-shell walnuts were 96.14%, 91.72% and 94.80% respectively, and the highest overall accuracy can reach 94.22 %. Contrasted with original Faster R-CNN network model, the mAP and F1-value of the improved Faster R-CNN model increased by 5.86% and 5.65%, respectively. Consequently, the proposed method can be applied for the in-shell walnuts with shriveled and empty-shell defects.

For many decades, X-ray diffraction (XRD) has been used for material characterization. With the recent development in material science understanding and technology, various new materials are being developed, which requires upgrading the existing analytical techniques such that intricate problems can be solved. Although, XRD is a well-established non-destructive technique, it still requires further improvements in its characterization capabilities, especially when dealing with complex mineral structures. The present review conducts comprehensive discussions on atomic crystal structure, XRD principle, its applications, uncertainty during XRD analysis, and required safety precautions, all in one place. It further discusses the future research directions, especially the use of artificial intelligence and machine learning tools for improving the effectiveness and accuracy of XRD technique for mineral characterization. It has been focused that how XRD patterns can be utilized for a thorough understanding of the crystalline structure, size, and orientation, dislocation density, phase identification, quantification, and transformation, information about lattice parameters, residual stress, and strain, and thermal expansion coefficient of materials. All these important discussions on XRD for mineral characterization are compiled in this short yet comprehensive review that would benefit specialists and engineers in the chemical, mining, iron, metallurgy, and steel industries.

Panoramic and periapical radiograph tools help dentists diagnose the most common dental diseases. Generally, dentists identify dental caries manually by inspecting X-ray images. However, due to their heavy workload, or poor image quality, dentists may sometimes overlook some unnoticeable dental caries, which may ultimately hinder the patient treatment. The purpose of this study was to develop an algorithm that classifies the teeth X-Ray images into three categories of “Normal”, “Caries”, and “Filled”. Our study used a dataset of 116 patients and 3712 single teeth images for training, validation and testing. Images were pre-processed using a sharpening filter and an intensity color map. We used a pre-trained transfer learning model, the NASNetMobile, which served as the feature extractor and the Convolutional Neural Network (CNN) model served as the classifier. The training dataset had a “Recall” of 0.92, 0.90 and 0.91 for “Normal”, “Caries” and “Filled” respectively and the test dataset had a “Recall” of 0.86, 0.81 and 0.85 for “Normal”, “Caries” and “Filled” respectively. The classification of the teeth X-Rays was successful and can be valuable for dentist as the artificial intelligence algorithm can serve as a decision support tool to aid dentists when they need to diagnose dental treatment.

Candida boidinii NAD+-dependent formate dehydrogenase (CbFDH) has gained significant attention for its potential applications in the production of biofuels and various industrial chemicals from inorganic carbon dioxide. In this study, we present an atomic X-ray crystal structure of the apo CbFDH to 1.4 Å resolution determined at cryogenic temperature at the Turkish Light Source, “Turkish DeLight”. This structure offers a comprehensive view of the apo enzyme's dynamics, filling the gaps in our understanding from previous studies. Also, comparison of our high-resolution apo and previously available holo enzyme structures reveals major conformational changes of this dynamic enzyme in the absence and presence of the coenzyme and substrate/inhibitor complexes. Collectively all these information may provide invaluable insights into future protein engineering efforts that could enhance enzymatic activity and stability, potentially increasing its efficiency and effectiveness of CbFDH in industrial processes.

We put forward a co-axial pump(optical)-probe(X-rays) experimental concept and show performance of the optical component. A Bessel beam generator with a central 100 micrometers-diameter hole (on the optical axis) was fabricated using femtosecond (fs) laser structuring inside a silica plate. This flat-axicon optical element produces a needle-like axial intensity distribution which can be used for the optical pump pulse. The fs-X-ray free electron laser (X-FEL) beam of sub-1 micrometer diameter can be introduced through the central hole along the optical axis onto a target as a probe. Different realisations of optical pump are discussed. Such optical elements facilitate alignment of ultra-short fs-pulses in space and time and can be used in light-matter interaction experiments at extreme energy densities on the surface and in the volume of targets. Full advantage of ultra-short 10 fs X-FEL probe pulses with fs-pump(optical) opens an unexplored temporal dimension of phase transitions and the fastest laser-induced rates of material heating and quenching. A wider field of applications of fs-laser-enabled structuring of materials and design of specific optical elements for astrophotonics is presented.

Maghemite (γ-Fe2O3) is a mineral formed from magnetite oxidation at low temperatures, an intermediate metastable term of the magnetite to hematite oxidation and could be mixed with both. It has magnetic susceptibility similar to magnetite, crystal structure close to magnetite with which it forms a solid solution, while compositionally it equals hematite. Maghemite is thus easily misidentified as magnetite by X-ray diffraction and/or as hematite by spot chemical analysis in iron ore characterization routines. Nonstoichiometric magnetite could be quantified in samples of Brazilian soils and iron ores by the Rietveld method using a constrained refinement of the X-ray patterns. The results were confirmed by reflected light microscopy and Raman spectroscopy, thus qualitatively validating the method. X-ray diffraction with the refinement of the isomorphic substitution of Fe2+ by Fe3+ along the magnetite-maghemite solid solution could help to suitably characterize maghemite in iron ores, allowing for the evaluation of its ultimate influence on mineral processing, by affecting its surface and breakage properties.

A quantitative analysis of X-ray emission from an electron cyclotron resonance (ECR) plasma was performed to probe the spatial properties of electrons having energy for effective ionisation. A series of measurements were taken by INFN-LNS and ATOMKI, capturing spatially and spectrally resolved X-ray maps as well as volumetric emissions from argon plasma. Comparing the former with model generated maps (involving space-resolved phenomenological electron energy distribution function and geometrical efficiency calculated using ray-tracing MC routine) furnished information on structural aspects of the plasma. Similarly, fitting a model composed of bremsstrahlung and fluorescence to the volumetric X-ray spectrum provided valuable insight into the density and temperature of confined and lost electrons. The latter can be fed back to existing electron kinetics models for simulating more relevant energies, consequently improving theoretical X-ray maps and establishing the method as an excellent indirect diagnostic tool for warm electrons, required for both fundamental and applied research in ECR plasmas.

The X-ray induced spin crossover transition of an Fe(II) molecular thin film in the presence and absence of a magnetic field has been investigated. The thermal activation energy barrier in the soft X-ray activation of the spin crossover transition for [Fe{H2B(pz)2}2(bipy)] molecular thin films is reduced in the presence of an applied magnetic field, as measured through X-ray absorption spectroscopy at various temperatures. The influence of a 1.8 T magnetic field is sufficient to cause deviations from the expected exponential spin state transition behavior that is measured in the field free case. We find that orbital moment diminishes with increasing temperature, relative to the spin moment in the vicinity of room temperature.

(1) Background: In the year of 2020 Covid-19 was declared epidemic by WHO. From that time millions of people were affected and died by this disease. The main detection process for this epidemic is RT-PCR test or reverse polymerase transcription chain reaction test. One of the reason of spreading of this disease so much is lack of efficiency in RT-PCR test. Sampling error and low viral load were two main reasons for what the testing process faced such problems. Lung infection is a very common symptom for covid-19 patients, so, CT scan and chest X-ray imaging technique can be applied to detect patient at a very early stage of infection. Which will be very effective and also can be a better option to RT-PCR test; (2) Methods: We searched data in Scopus for articles published between 2020 and 2023. The initial set of articles was 189, from which 21 articles will eventually be selected by exclusion criteria; (3) Results: A total of thirteen (61.90%) articles were found working on detecting Covid-19 by extracting the X-ray and CT scan data individually. Three (14.28%) of those articles focused on a hybrid model of CT scan and X-ray Image Data. Another four articles made a comparison between Covid-19, pneumonia and a normal person to identify a Covid-19 patient. Where others have worked on unsupervised learning methods or SVM to detect Covid-19.; (4) Conclusions: We have conducted a systematic review of the studies that have been published up to this time, with the purpose to present a summary of the evidence about the detection of COVID-19. In this article, we have summarized and critically reviewed literatures which worked on development or application or both of different AI or ML technique from chest CT and X-ray images to find a solution to detect covid-19.

Material identification based on R_value (transparency natural logarithm ratio of low-energy to high-energy) of line-scan dual-energy X-ray transmission (DE-XRT) has a good prospect for industrial application. Unfortunately, the DE-XRT signals before attenuation cannot be directly measured, whereas their precision is very important to R_value. Therefore, a context-based signal synthesis method which takes the filtered signals that remove high-frequency noises and retain low-frequency actual fluctuations as the reference value, and takes into account the vertical (forward/column) direction and horizontal (scanning/row) direction anisotropy of line-scan images was proposed. The vertical is a time series with continuity of signal trend; the horizontal is a spatial characteristic with the fluctuation synchronization within the same row signals. The special synthesis evaluations of curve synthesis difference and surface synthesis difference were also proposed. Experimental results show that the tow evaluations are both only about 0.0007, and it only takes 35 ms to complete the surface synthesis of 119×119 pixels on the CPU with 3.4 GHz main frequency. The presented method can achieve high signal synthesis precision and calculation real-time, so as to facilitate DE-XRT material identification. It can be extended to improve the precision of numerical synthesis in other line-scan uncomplete signals.

Prolonged high-intensity grinding can modify the crystal structure of solid substances and/or induce chemical reaction, which is referred to as mechanochemical reaction. Such reactions can exert positive influences on hydrometallurgical processes, therefore, many researchers have applied mechanochemical reactions for metals dissolution from minerals. The mechanism of mechanochemical reaction has been investigated using solid analyses and simulations. Structural changes caused by mechanochemical reaction are not yet sufficiently clarified because the ground samples are amorphous. The objective of this study was to analyze structural changes of cerianite in weathered residual rare earth ore by mechanochemical reduction. Structural change was analyzed by x-ray absorption near-edge structure and extended x-ray absorption fine structure analysis at the cerium L_III- and K-edges. These analyses revealed that the structural change of cerianite in this ore induced by mechanochemical reduction involved oxygen vacancy production. The process of the oxygen vacancy formation was closely coupled with the quantum effect of localization–delocalization of the 4f electron of cerium.

X-ray fluorescence is largely employed in the measurement of the thickness of coatings. Despite of its diffusion, the task is not straightforward because of the complex physics involved that results in high dependence on matrix effects. Thickness quantification is in practice accomplished using the Fundamental Parameters approach, adjusted with empirical measurements of standards with known composition and thickness. This approach has two major drawbacks: i) there are no standards for any possible coating and coating architecture and ii) even relying on standards, the quantification of unknown samples requires the precise knowledge of the matrix nature (e.g., in case of multilayer coatings the thickness and the composition of each underlayer). In this work, we describe a semiquantitative approach to coatings thickness measurement based on the construction of calibration curves through simulated XRF spectra built with Monte Carlo simulations. Simulations have been performed with the freeware software XMI-MSIM. We have assessed the accuracy of the methods by comparing the results with those obtained by i) XRF thickness determination with standards and ii) FIB-SEM cross-sectioning. Then we evaluated which parameters are critical in this kind of indirect thickness measurements.

In response to the growing inspection demand exerted by process automation in component manufacturing, Non-destructive testing (NDT) continues to explore automated approaches that utilize deep learning algorithms for defect identification, including within digital X-ray radiography images. This necessitates a thorough understanding of the implication of image quality parameters on the performance of these deep learning models. This study investigates the influence of two image quality parameters, namely Signal-to-Noise Ratio (SNR) and Contrast-to-Noise Ratio (CNR), on the performance of U-net deep learning segmentation model. Input images were acquired with varying combinations of exposure factors such as kilovoltage, milli-ampere, and exposure time, which altered the resultant quality. The data was sorted into 5 different datasets according to their measured SNR and CNR values. The deep learning model was trained 5 distinct times, utilizing a unique dataset for each training session. Training the model with high CNR values yielded an intersection over Union (IoU) metric of 0.9594 on test data of the same category but drops to 0.5875 when tested on lower CNR test data. The result in this study emphasizes the importance of achieving a balance in training dataset according to the investigated quality parameters, to enhance the performance of deep learning segmentation models in NDT radiography applications.

Classical k-ratio models, e.g. ZAF and phi(rho z), used in electron probe microanalysis (EPMA) assume a homogeneous or multi-layered material structure, which essentially limits the spatial resolution of EPMA to the size of the interaction volume where characteristic x-rays are produced. We present a new model for characteristic x-ray emission that avoids assumptions on the material structure to not restrict the resolution of EPMA a-priori. Our model bases on the spherical harmonic (PN) approximation of the Boltzmann equation for electron transport in continuous slowing down approximation. PN models have a simple structure, are hierarchical in accuracy and well-suited for efficient adjoint-based gradient computation, which makes our model a promising alternative to classical models in terms of improving the resolution of EPMA in the future. We present results of various test cases including a comparison of the PN model to a minimum entropy moment model as well as Monte-Carlo (MC) trajectory sampling, a comparison of PN-based k-ratios to k-ratios obtained with MC, a comparison with experimental data of electron backscattering yields as well as a comparison of PN and Monte-Carlo based on characteristic X-ray generation in a three-dimensional material probe with fine structures.

A hydrothermal technique with microwave heating (200 °C, 2 hours, 2 magnetrons, 2.45 GHz) was modified to obtain UV-C luminescent LaPO4: Pr3+ colloidal nanorods for the potential use in X-ray cancer theranostics. For further possible biofunctionalization, a compound of tartaric acid formed under basic conditions was used as a coating and stabilizing agent to provide colloidal properties to the surface of nanoparticles in basic to neutral aqueous media, which was confirmed by zeta potential measurements. In addition, the colloidal properties and clustering processes of synthesized LaPO4:Pr3+ nanorods in aqueous solutions with different pH values were studied in real time using a highly sensitive laser ultramicroscope operating according to the “light-sheet” scheme. A comparative analysis of the transmission electron microscopy, X-ray powder diffraction and high-energy spectroscopy showed the different effects of synthesis parameters on the morphological, crystalline and luminescent properties of the obtained nanorods. Through optimization of the synthesis parameters, stable aqueous solutions of m-LaPO4:Pr3+ nanorods with sizes less than 30 nm and an intensity of UV-C luminescence equal to 5-10% of the unmodified nanofibers were obtained.

An outbreak of novel coronavirus(2019-nCoV) that began in Wuhan, China, is rapidly spreading to all over China, and gradually to multiple countries. Regarding to put the epidemic prevention and spread under the control, early identification and diagnosis play a critical role. Patients with initially no or mild symptoms of Novel Coronavirus Pneumonia (2019-nCoV), namely “stealth” infection, often lack of typical clinical evidence to establish the diagnosis. Based on the clinical analysis of 4 cases in stealth infection, the results of this study highlight that early diagnosis requires a combination of epidemiological history, clinical manifestations, early chest CT examination, and 2019-nCoV RNA test (nucleic acid test), with particular emphasis on definite epidemiological history and early chest CT findings when positive nucleic acid tests lag behind.

Finding new, safe strategies to prevent and control rheumatoid arthritis is an urgent task. Of particular interest in this regard are bioactive peptides and peptide-rich protein hydrolyzates, which represent a new trend in the development of functional foods and nutraceuticals. The resulting tissue hydrolyzate of the chicken embryo (CETH) has been evaluated for acute toxicity and tested against chronic arthritis induced by Freund's full adjuvant in rats. The anti-arthritic effect of CETH was studied on the 28th day of the experiment after two weeks of oral administration of CETH at doses of 60 and 120 mg/kg body weight. Arthritis was evaluated on the last day of the experiment on the injected animal paw using X-ray computerized microtomography and histopathology analysis methods. The CETH effect was compared with the non-steroidal anti-inflammatory drug diclofenac sodium (5 mg/kg). Oral administration of CETH was accompanied by effective dose-dependent correction of morphological changes caused by the adjuvant injection. CETH had relatively high recovery effects in terms of parameters for reducing inflammatory edema, inhibition of osteolysis, prevention of osteophitosis, reduction of the inflammatory reaction of periarticular tissues, and cartilage degeneration. This study presents a potential theoretical strategy for the safe correction of this pathological process and, for the first time, shows that CETH may be a powerful potential nutraceutical agent or bioactive component of functional products in the treatment of rheumatoid arthritis.

Abstract: : 2,3-dihydro-5,6,7,8-tetranitro-1,4-benzodioxine (TNBD), molecular formula =C8H4N4O10 is a completely nitrated in aromatic ring 1,4-benzodioxane derivative. The con-venient method of TNBD synthesis was developed (yield=81 %). The detailed structure of this compound has been investigated by X-ray crystallography. The results of differential thermal analysis (DTA) obtained with twice re-crystallized material showed onset at 247 and isoterm at 288 0C, with further total degradation at 300 0C. The experimental density 1,85 g/cm3 of TNBD was determined by X-ray crystallography. The spectral properties of TNBD (NMR, FT-IR, Ra-man) were explored. The detonation properties of TNBD calculated by EXPLO 5 code was slightly superior in comparison to standard high energy material - tetryl (detonation velocity of TNBD - 7727 m/s; detonation pressure - 278 kbar; tetryl – 7570 m/s and 226.4 kbar at 1.614 g/cm3, or 260 kbar at higher density - 1.71 g/cm3. The obtained preliminary results might suggest TNBD can be a potential thermostable high energy and density material (HEDM).

This study aims to investigate the effects of chest mobilization and breathing exercises on respiratory function, trunk stability, and endurance in chronic stroke patients who have contracted coronavirus disease (COVID-19). Thirty inpatients of a tertiary hospital in South Korea, who had a history of COVID-19 and were diagnosed with stroke within the last 6 months were randomly assigned to either the Chest Mobilization Exercise with Breathing Exercise (CMEBE) or Conservative Physical Therapy with Breathing Exercise (CPTBE) groups. The respiratory function, trunk stability, and endurance were measured at baseline and 6 weeks after the interventions. Both CMEBE and CPTBE groups showed improvements in respiratory function, trunk stability, and endurance after the intervention (p<0.05). However, the CMEBE group showed significantly greater improvements in forced expiratory volume in 1 second (p<0.05), trunk stability (p<0.05), and endurance (p<0.05) than the CPTBE group. No significant intergroup difference was observed in forced vital capacity and peak expiratory flow. Conclusion: The combination of chest mobilization and breathing exercises improved respiratory muscle mobility and endurance, stabilized the trunk, and enhanced balance and transfer of weight. The findings suggest that this intervention could be beneficial in improving respiratory function and endurance in stroke patients.

This study aimed to evaluate the role of chest radiographs and electrocardiograms in predicting the hemodynamics of congenital heart disease (CHD). This retrospective study included 50 patients with a diagnosis of CHD who had undergone any form of cardiac intervention, either surgical or nonsurgical between September 2019 and September 2020. Chest radiographs and electrocardiograms were evaluated and compared with the diagnostic gold standard echocardiography. Chest radiographs had the highest sensitivity, specificity, and accuracy, with all being 100%, in detecting situs and cardiac position. There was a very good agreement between chest radiographs and echocardiography in the detection of both situs and cardiac position (κ = 1.00, p &lt; 0.001), while moderate agreement was observed for the detection of cardiomegaly, position of aortic knuckle, main pulmonary artery dilation, and right pulmonary artery dilation. Electrocardiograms had a high sensitivity (100.00%), but modest specificity and accuracy for the detection of left ventricle pressure overload. For the detection of left atrial enlargement and left ventricle volume overload, electrocardiograms had high specificity (94.12% and 94.29%, respectively) but low sensitivity and modest accuracy. There was a moderate agreement between electrocardiograms and echocardiography in the detection of right ventricle pressure overload (κ = 0.43, p = 0.002) and left ventricle volume overload (κ = 0.46, p &lt; 0.001). The study findings indicate that chest radiographs and electrocardiograms alone are not adequate for the assessment of hemodynamics of CHD and reinstates the recommendation that in addition to routine chest radiographs and electrocardiograms, echocardiography should be performed.

Shot peening has become a well-established technique for the introduction of beneficial compressive Residual Stresses (RS) into the near-surface layers of metallic materials for the purpose of preventing or suppressing fatigue crack nucleation and growth. Ti-alloys are widely used to fabricate compressor blades of aeroengines. Titanium blades that may be susceptible to different modes of damage under cyclic loading (high cycle fatigue, fretting fatigue) are often subjected to shot peening to extend their safe operating time. The control and monitoring of residual stresses in titanium blades is of great importance to assure the safety of aeroengines. The techniques for residual stress evaluation include mechanical methods (material removal) as well as physical methods such as X-ray diffraction. Perhaps the most common and practically accessible form of the latter is the method. Conventional laboratory X-ray diffractometers typically probe samples to the depths up to ~20 µm that correspond to 1x...5x the average grain size for typical metals and alloys. The limitations of the method have been identified and reviewed in the literature, motivating the use of other semi-destructive approaches to evaluate the residual stresses in deeper layers and at more sharply defined locations. In the present report we present a case study of the comparison between non-destructive and semi-destructive evaluation techniques, namely the X-ray diffraction method against the mechanical and FIB-DIC ring-core drilling applied to the samples of VT6 (Russian designation of Ti-6Al-4V) titanium alloy after shot peening with 1 mm steel balls. Mechanical drilling of circular holes of ~2 mm diameter with laser speckle interferometry monitoring of strains gives a rough spatial resolution of a few millimeters, while the Korsunsky FIB-DIC method of Ga-ion beam micro-ring core milling within FIB-SEM with Digital Image Correlation (DIC) deformation analysis delivers spatial resolution down to a few micrometers. Good agreement has been found between the X-ray and FIB-DIC estimates of RS variation profiles as a function of depth in shot peened titanium alloy samples. Some advances in the FIB-DIC method are presented and discussed in terms of the acceleration of data acquisition and interpretation.

Primary spontaneous pneumothorax (PSP) is a pleural disease that abruptly affects healthy adolescents and young adults, representing a common thoracic disorder in this age group. This study aimed to investigate the necessity of preoperative chest tube insertion in patients with PSP and to re-evaluate current clinical treatment approaches. A retrospective review of medical records was conducted for children and young adults aged 14–30 years, diagnosed with PSP and who underwent Video-assisted thoracoscopic surgery (VATS) between January 2016 and December 2022 at Wonju Severance Christian Hospital. Patients were retrospectively divided into two groups based on their initial treatment: chest tube insertion and non-chest tube insertion. Clinical data including demographics, treatment details, and outcomes were collected and compared. Total 128 cases of PSP were included in the study. The total length of hospital stay was significantly shorter in the non-chest tube group (p=0.000), which was attributed to the omission of pre-operative chest tube insertions. No significant differences were observed between the two groups in terms of postoperative complications or recurrence rates. In cases of young patients with PSP, omitting pre-operative chest tube insertion may be a viable option if the patient is scheduled for VATS.

The prediction of corticosteroid responses in coronavirus disease 2019 (COVID-19) patients is crucial in clinical practice, and exploring the role of artificial intelligence (AI)-assisted analysis of chest radiographs (CXR) is warranted. This retrospective case-control study involving hospitalized COVID-19 patients treated with corticosteroids was conducted from September 4th, 2021, to August 30th, 2022. The primary endpoint of the study was corticosteroid responsiveness, defined as the advancement of two or more of the eight-categories-ordinal scale. Serial abnormality scores for consolidation and pleural effusion on CXR were obtained using a commercial AI-based software based on days from onset of symptoms. Amongst the 258 participants included in the analysis, 147 (57%) were male. Multivariable logistic regression analysis revealed that high pleural effusion score at 6–9 days from onset of symptoms (adjusted odds ratio of [aOR]: 1.022, 95% confidence interval [CI]: 1.003-1.042, p=0.020) and consolidation scores up to 9 days from onset of symptoms (0-2 days: aOR: 1.025, 95% CI: 1.006-1.045, p=0.010; 3-5 days: aOR: 1.03 95% CI: 1.011-1.051, p=0.002; 6-9 days: aOR; 1.052, 95% CI: 1.015-1.089, p=0.005) were associated with an unfavorable corticosteroid response. AI-generated scores could help intervene in the use of corticosteroids in COVID-19 patients who would not benefit from them

The search for biological markers, which allow a relatively accurate assessment of the individual course of pulmonary sarcoidosis at the time of diagnosis remains one of the research priorities in this field of pulmonary medicine. The aim of our study was to investigate possible prognostic factors for pulmonary sarcoidosis with a special focus on cellular immune inflammation markers. 2 years follow-up of the study population after initial prospective and simultaneous analysis of lymphocyte activation markers expression in the blood, as well as bronchoalveolar lavage fluid (BALF), and lung biopsy tissue of patients with newly diagnosed pulmonary sarcoidosis, was done. We found that some blood and BAL fluid immunological markers and lung computed tomography (CT) patterns have been associated with a different course of sarcoidosis. We revealed five markers that had a significant negative association with the course of sarcoidosis (worsening pulmonary function tests and/or the chest CT changes) – blood CD4+CD31+ and CD4+CD44+ T lymphocytes, BALF CD8+CD31+ and CD8+CD103+ T lymphocytes and a number of lung nodules on chest CT at the time of the diagnosis. Cut-off values, sensitivity, specificity, and odds ratio for predictors of sarcoidosis progression were calculated. These markers may be reasonable predictors of sarcoidosis progression.

Annually, an estimated 13-26 million newborns need respiratory support and 2-3 million newborns need extensive resuscitation, defined as chest compression and 100% oxygen with or without epinephrine in the delivery room. Despite such care, there is a high incidence of mortality and short-term neurologic morbidity. The poor prognosis associated with receiving chest compression alone or with medications in the delivery room raises questions as to whether improved cardiopulmonary resuscitation methods specifically tailored to the newborn could improve outcomes. This review discusses the current recommendations, mode of action, different compression to ventilation ratio, continuous chest compression with asynchronous ventilations, chest compression and sustained inflation optimal depth, and oxygen concentration during cardiopulmonary resuscitation.

Structure-based design and synthesis of two biphenyl-N-acyl-β-D-glucopyranosylamine derivatives as well as their assessment as inhibitors of human liver glycogen phosphorylase (hlGPa, a pharmaceutical target for type 2 diabetes) is presented. X-ray crystallography revealed the importance of structural water molecules and that the inhibitory efficacy correlates with the degree of disturbance caused by the inhibitor binding to a loop crucial for the catalytic mechanism. The in silico derived models of the binding mode generated during the design process corresponded very well with the crystallographic data.

The COVID-19 pandemic caused an unprecedented effect on national radiological investigations. Since the World Health Organization officially declared the COVID-19 as a global pandemic, health policies have been rapidly organized to limit the spread of the virus and decrease the risk of exposure. These restrictions, in combination with home-stay arrangements and the onset of economic recession. As a result of public policies, financial difficulties and patient fear, many radiology departments have suffered a significant reduction in diagnostic examinations with important implications for their economic stability. The aim of this work is to evaluate the economic impact of the COVID-19 pandemic in the Radiology Department of an infectious disease hospital.

This study aimed to investigate the characteristics and outcomes of patients who underwent per-cutaneous coronary intervention (PCI) and visited an emergency department (ED) with chest pain in Saudi Arabia. A retrospective analysis of patient data was conducted, focusing on demographics, risk factors, pain assessment, triage, diagnostic testing, and management. The results revealed a young adult population (40-59 years old) at risk for coronary heart disease (CHD), highlighting the need for increased awareness and education. Gender differences in cardiovascular disease (CVD) presentation and underdiagnoses in women also require attention for effective prevention and treatment. Accurate pain assessment during triage was found to be essential to prevent mistriage and negative patient outcomes. Chest pain and shortness of breath were common symptoms, emphasizing the importance of recognizing acute myocardial infarction (AMI) symptoms for proper triage, diagnostic testing, and prompt treatment. The study identified modifiable CVD risk factors, including diabetes (51.1%), hypertension (43.8%), and smoking (25.9%), stressing the importance of lifestyle modifications to reduce CVD risk. Saudi Arabia faces significant challenges in addressing cardiovascular disorders, but efforts to improve healthcare access and establish specialized centers are promising. In conclusion, this study underscores the need for increased awareness of CHD among young adults, accurate pain assessment during triage, and lifestyle modifications to address modifiable CVD risk factors. Furthermore, healthcare teams must stay updated on new chest pain guidelines in the ED and prioritize early detection of implicated arteries and prompt reperfusion. Further research investigating chest pain patient triage and assessments across Saudi Arabia is recommended to identify areas of improvement and implement necessary changes in clinical practice.

COVID-19 generated a scenario for global health with multiple systemic impairments. This retrospective study evaluated the clinical, radiological, and pulmonary functional evolution in 302 post-COVID-19 patients. Regarding post-COVID-19 pulmonary symptoms, dry cough, dyspnea, and chest pain were the most frequent. Of the associated comorbidities, asthma was more frequent (23.5%). Chest Tomography (CT) initially showed a mean pulmonary involvement of 69.7%, and the evaluation in the subsequent months showed an improvement in the evolutionary image, and with less than six months post-pathology, there was a commitment of 37 .7%, from six to twelve months, 20% and after 12 months, 9.9%. And as for most of the sample, 50.3% of the patients presented CT normalization in less than six months after infection, 23% normalized between six and twelve months, and 5.2% normalized the images after twelve months, with one remaining. Percentage of 17.3% who maintained post-COVID-19 pulmonary residual sequelae. Regarding spirometry, in less than six months after the pathology, 59.3% of the patients already showed a regular exam; 12.3% normalized their function within six to twelve months, and 6.3% concluded a normal exam after twelve months of post-pathology evaluation. Only 3.6% of the patients still showed some alteration in this period.

Deep convolutional neural networks (CNN) are favored methods widely used in medical image processing due to their assured shown performance. Recently, the emergence of new lung diseases and the possibility of early detection of their symptoms has attracted many researchers to classify diseases by training deep CNNs on lung CT images. The trained networks are expected to distinguish between lung indications in different diseases, especially at the early stages of them. With the hope of achieving this purpose, we proposed an efficient deep CNN called AFEX-Net with adaptive feature extraction layers that successfully extract distinguishing features and classify chest CT images. The efficiency of the proposed network has two aspects: it is a lightweight network with low number of parameters and fast training and it has adaptive pooling layers and adaptive activation functions to increase its level of compatibility to the input data. The proposed network has been evaluated on a dataset with more than 10K chest CT slices, while an efficient pre-processing method is developed to remove any bias from the images. Additionally, we evaluated the performance of the proposed model on the public COVID-CTset dataset to prove the generalisability of our model. The obtained results confirm the competence of the proposed network in confronting medical images, where prompt and accurate learning is required.

Traumatic pneumothorax (PTX) occurs in up to 50% of patients with severe polytrauma and chest injuries. Patients with traumatic PTX with clinical signs of tension physiology and hemodynamic instability are typically treated with an urgent decompressive thoracostomy, tube thoracostomy, or needle decompression. There is recent evidence that non-breathless patients with hemodynamically stable traumatic PTX can be managed conservatively through observation or a percutaneous pigtail catheter. We present here a 52-year-old woman who presented to the emergency department with 55 mm traumatic PTX. Following aspiration of 1500 ml of air, clinical improvement was immediately observed, allowing the patient to be discharged shortly thereafter. In hemodynamically stable patients with posttraumatic PTX, without specific risk factors or oxygen desaturation, observation or simple needle aspiration can be a reasonable approach. We aimed in this article to review the available literature on needle aspiration and conservative treatment of traumatic pneumothorax. A total of 12 studies were selected out of 190 articles on traumatic PTX, where conservative treatment versus chest tube decompression was compared. Our case report demonstrated that even a large PTX in a hemodynamically stable patient without other risk conditions, can be successfully treated conservatively with simple needle aspiration to avoid tube thoracostomy complications.

Examining forbidden reflections provides valuable information on electronic states and the local environment of resonant atoms in crystals. Experimental studies of two forbidden reflections 002 and 100 in TeO₂ single crystals were performed at photon energies close to the L₁ tellurium absorption edge. It was found that the spectral form corresponding to these two reflections looks almost identical, which is completely unexpected for a highly anisotropic material. Theoretical consideration shows that only one component f_xy of the tensor describing dipole-dipole resonance scattering contributes to the 002 reflection, while two components f_xy and f_xz correspond to the 100 reflection. Numerical calculations show that the latter tensor component is comparable to the first one, but the combination of several geometric factors leads to the fact that its contribution to the spectrum is negligible. This explains the experimentally observed results. The finding shows a way for targeted investigation of single tensor components and makes it possible to compare different spectra and use them the study the physical phenomena in functional materials.

Background: COVID-19 pneumonia caused by SARS-Cov-2 virus induces alveolar collapse and hypoxia that may become severe. The aim of the study is to analyze the effects of chest physiotherapy using a threshold valve in patients with acute respiratory failure due to COVID-19 pneumonia. Methods; Retrospective observational study, in hospitalized patients from March to May 2020. Breathing exercises were performed with a threshold valve of 10 cmH2O. Fraction of inspired oxygen, oxygen saturation, heart rate, respiratory rate and dyspnea were collected before and after the first session and at the end of the 5th day of chest physiotherapy treatment. Results: The final sample included 125 patients. Significant differences (p&lt;0.01) were found in the pre-post intervention SpO2/FiO2 ratio (250±88.4 vs 275.6±97.5, p&lt;0.001), reaching 354.4±110.2 after 5 days of therapy (p&lt;0.001 with respect to baseline). Mean baseline respiratory, heart rate and level of dyspnea measure by the Borg scale did not change during the technique performance. In patient maneuvers with FiO2&gt;0.4, the SaO2/FiO2 ratio increase was higher than in patients with milder severity (46.85 ± 77.69, p&lt;0.01). Conclusions: Chest physiotherapy with a 10 cmH2O threshold valve is a safe and tolerated intervention with short-term improvement in oxygenation in patients with COVID-19 pneumonia.

Background We intend to examine whether the COVID-19 outbreak influences medical decision-making (MDM) among Non-COVID patients. Method We recruit 287 patients who admit to ER department due to cardiovascular complaints. Anxiety level was measured using three questionnaires (GAD-7, Beck Inventory, and the cardiac anxiety questionnaire). A fourth survey was designed to assess MDM considerations. Results 64% of patients were male (median age 54). Almost half of the patients were found to have moderate to severe levels of anxiety.79.3% of patients reported that the outbreak influenced their MDM. 44.5% of patients sought medical care 2-3 from the onset of symptoms. Coronary artery disease was found in only 26 patients (9.1%). Almost half of the patients stated that they would have gone earlier if not for the current pandemic. Conclusion Non-COVID patients seeking medical care had a high anxiety level that directly affected decision-making and put them at unnecessary risk.

The analysis of autosomal polymorphism (STR) or Y chromosome polymorphisms (Y-STR) are usually used for the study and deconvolution of mixed DNA profiles in forensic genetics, accompanying data interpretation with biostatistical evaluations (e.g. RMP, RMNE, LR). Sometimes, however, some mixed DNA profiles are so complex that the autosomal and Y markers do not allow a correct discrimination and identification. In this work is reported a robbery case in which the analysis of the polymorphic markers of the X chromosome was applied to the mixed profiles obtained from the traces, thus falling outside the classic relationship use of the X-STRs. The aim of the authors is, in fact, to encourage the classic use of X-STRs not only in parental relationships, but also in purely forensic cases for interpreting complex mixed DNA profiles. Their application in case resolution could be more decisive than STR/Y-STR.

INTRODUCTION: The purpose of the study was to determine (a) the overall preclinical character; (b) the cumulative cutoff values and the risk ratio, and (c) the factors associated with severity by a unidimensional and multidimensional analysis on 2173 Sars-Cov2 patients. METHODS: The machine learning study population consisted of 2173 patients (1587 mild and non symptoms patients, 377 moderate patients, 209 severe patients). The status of the patients was recorded from September 2021 to March 2022. RESULTS: The Covid19 Severity directly links with a significant correlation to Age, Score index of the chest X-ray, percentage and quantity of neutrophils, Albumin, C reactive protein, and ratio of Lymphocytes. Their important cut off values (from regression analysis) respectively are: 77.56 years old (the mild-moderate group), 5.53 (the mild-moderate group) and 10.51 (the moderate-severe group), 84.80% (the mild-moderate group) and 87.74%(the moderate-severe group), 11.77G/L (the moderate-severe group), 29.73g/L (the moderate-severe group), 7.46mg/dL (the mild-moderate group), 6.32% (the moderate-severe group). Their significant (p<0.0001) R score correlation with the severity of Covid19, are: 0.44, 0.52 and 0.52, 0.33 and 0.44, 0.42, -0.43, 0.40, -0.41. Their significant risk ratio (p<0.00001) from the meta-analysis, respectively are: 4.19 [3.58-4.95], 3.29 [2.76-3.92] and 3.03 [2.4023;3.8314], 3.18 [2.73-3.70] and 3.32 [2.6480;4.1529], 3.15 [2.6153;3.8025], 3.4[2.91-3.97], 0.46 [0.3650;0.5752] (p<0.00001), 0.34 [0.2743;0.4210]. The pair ALT – Leucocytes and Transferrin – Anion Chloride get the most important correlation shift. ALT – Leucocytes show the important negative link (R=-1, p<0.00001) in the mild group to the significant positive correlation in the moderate group (R=1, p<0.00001). Transferrin–anion Chloride has an important positive association (R=1, p<0.00001) in the mild group with a significant negative correlation in the moderate group (R=-0.59, p<0.00001). The network map and HCA show that in the mild-moderate group, the closest neighbors with the Covid19 severity are ferritins, Age. Then there is C-reactive protein, SI of X-ray, Albumin, and Lactate dehydrogenase, which are the next close neighbors of these three factors. In the moderate-severe group, the closest neighbors with the Covid19 severity are Ferritin, Fibrinogen, Albumin, the quantity of Lymphocytes, SI of X-ray, white blood cells count, Lactate dehydrogenase, and quantity of neutrophils. CONCLUSIONS: Complete multidimensional study in 2173 Covid19 patients in Vietnam shows the whole picture of all the preclinical factors, which may become the clinical reference marker for surveillance and diagnostic management

Many patients with Coronavirus disease 2019 (COVID-19) suffer from shortness of breath and severe chest pain. Here we report successful therapy of a patient with diagnosis of COVID-19, severe chest pain and significant shortness of breath, using radial extracorporeal shock wave therapy (rESWT). The latter started seven days after beginning of symptoms and drug therapy without success, and involved daily application of 15.000 to 20.000 radial extracorporeal shock waves over the intercostal muscles as well as the paravertebral muscles of the thoracic and lumbar spine, diaphragm and flanks. Immediately after the first rESWT session the patient experienced significant pain relief and improvement of breathing. Four days later the pain had completely subsided and breathing was largely normalized. This type of noninvasive, non-pharmacologic treatment could help many COVID-19 patients or patients who still suffer from breathing problems weeks after having been infected with SARS-CoV-2, giving them back quality of life.

Background: Early rehabilitation is an important strategy for the treatment of severe diseases. The study aimed to assess the efficacy of early rehabilitation of patients with mild-to-moderate COVID-19. Methods: The retrospective single-center study with propensity score matching. Results: 180 patients (54 (44 - 62.3) yo) divided into three equal groups: 1 - physical exercises; 2 - physical exercises and chest massage in an electrostatic field; 3 - no rehabilitation. The length of stay (LOS) in the hospital in group 1 was 14 (11-15) days, group 2 - 13 (11-15) days, group 3 - 15 (13-18) days, p=0.0026. Physical exercises for patients with CT-1 improved the quality of life, assessed by the EQ-5D questionnaire, by reducing the level of anxiety and depression. The Hazard Ratio (HR) for desaturation (<93%) was 2.34 (95% Confidence Interval (CI) 1.18-4.63) for group 2, p=0.001. The HR for C-reactive protein level above 50 mg/l in patients with CT-2 was 2.33 (95% CI 1.56-3.47), p=0.0001. Conclusions: Rehabilitation programs are safe for СOVID-19-patients; reduce hospital LOS; improve the quality of life. Continuous monitoring of a patient's condition during rehabilitation is essential. ClinicalTrials.gov ID: NCT0580836

Background: Natural environment inhalation topography provides useful information for toxicant exposure, risk assessment and cardiopulmonary performance. Commercially available Wearable Respiratory Monitors (WRM), which are currently used to measure a variety of physiological parameters such as heart rate and breathing frequency, can be leveraged to obtain inhalation topography, yet little work has been done. This paper assesses the feasibility of adapting these WRMs for measuring inhalation topography. Methods: Commercially available WRMs were compiled and assessed for the ability to report chest motion, data analysis software features, ambulatory observation capabilities, participant acceptability, purchasing constraints and affordability. Results: The following WRMs were found: LifeShirt, Equivital EQ02 LifeMonitor, Smartex WWS, Hexoskin Smart Garment, Zephyr BioHarness, Nox T3&amp;A1, BioRadio, SleepSense Inductance Band, and ezRIP &amp; zRIP Durabelt. None of the WRMs satisfied all six assessment criteria in a manner enabling them to be used for inhalation topography without modification and development. Conclusion: The results indicate that there are WRMs with core technologies and characteristics that can be built upon for ambulatory inhalation topography measurement in the NE.

It is well known that X-ray crystallography is based on X-ray diffraction (XRD) by atoms and molecules. The diffraction pattern arises as a result of scattering of incident radiation, which makes it possible to determine the structure of the scattering substance. With the advent of ultrashort radiation sources, the theory and interpretation of X-ray diffraction analysis remained the same. This work shows that when an attosecond laser pulse is scattered on a DNA molecule, including during its nicking and bending, the pulse duration is an important characteristic of the scattering. In this case, the diffraction pattern changes significantly compared to the previously known scattering theory. The results obtained must be used in XRD theory to study DNA structures, their mutations and damage, since the previously known theory can produce large errors and, therefore, the DNA structure can be “deciphered” incorrectly.

Heat stress affects the yield of medicinal plants and can reduce biomass and/or metabolite production. In order to evaluate the effect of heat-induced stress on the essential oil production in Mentha x piperita L. var. Mitcham (Mitcham mint) and Mentha x arvensis var. piperascens Malinv. ex L. H. Bailey (Japanese mint), we studied the chemical composition of the oils of the two mint species under different heat shock stress in growth chambers. The antibacterial activity of the essential oils was also evaluated; microscopic observation (fluorescence and electron transmission) was used to assess the effect of the tested samples on bacterial growth. The results obtained shed light on the mint essential oils composition and biological activity in relation to heat stress.

Detailed description of carbonate minerals different in magnesium content of Triassic dolomites were presented in this article. The tests were carried out to determine geochemical and miner-alogical features in the terms of their geoengineering properties. The following carbonate phas-es were identified: a low-Mg calcite, a high-Mg calcite, a proto-dolomite, an ordered dolomite and a huntite. The following research methods were used: microscopic analysis, X-Ray Diffrac-tion, X-Ray Fluorescence and Electron probe microanalysis. The samples were collected from the Tarnowice formation which is the lower part the profile of the Upper Muschelkalk. On the basis of the results the chemical formulas of carbonate phases were calculated. The ranges of Mg and Ca content were presented in formulas. The results indicate of Mg in low-Mg calcite ranges from 0.6 to 1.2%, in high-Mg calcite from 7.47 to 10.41%. In proto-dolomite it ranges from 10.96 to 11.78%. In ordered dolomite Mg content is stoichiometric value for dolomite – 13.18%. Due to the reduced Mg content in identified huntite (the value ranges from 13.62% to 17.76), this carbonate phase was named as de-huntite.

X-ray diffraction (XRD) analysis of complex poly-atomic systems, especially of biomolecules, using ultra-short laser pulses (USP), is currently one of the most important fields of modern physics. The basis for interpreting and "deciphering" experimental data is the well-known theory of X-ray scattering, where the main parameter of USPs - its duration - is not taken into account. In the present work it is shown that for scattering of attosecond USPs on DNA and RNA trinucleotides the pulse length is the most important scattering parameter. In this case the diffraction pattern significantly changes with respect to the previously known scattering theory. The results obtained are extremely important in XRD when using attosecond pulses to study trinucleotides of DNA and RNA because using the previously known scattering theory which does not take into account the duration of USPs one can not correctly interpret and therefore "decode" DNA and RNA structures.

Space-based Interferometric Synthetic Aperture Radar (InSAR) applications have been widely used to monitor the cryosphere over past decades. Because of temporal decorrelation, interferometric coherence often severely degrades on fast moving glaciers. In addition, higher sensitivity ambiguity occurs in large baseline configurations, which are needed for extracting topographic information over low relief areas such as the surface of a glacier. TerraSAR-X add-on for Digital Elevation Measurement (TanDEM-X) observations, which overcome the temporal decorrelation because of their simultaneous measurements by two satellite constellations, have used a short baseline sufficient for generation of excellent digital elevation models in most locations around the world. However, it remains difficult to estimate detailed topographic characteristics over low slope glacier surfaces because of the relatively less sensitive height ambiguity from the small baselines. In this study, we used the TanDEM-X pursuit monostatic mode with large baseline formation following a scientific phase timeline to develop highly sensitive topographic elevation models of the Petermann Glacier of Northwest Greenland. As expected, coherent interferometric phases (> 0.8) were well maintained over the glaciers despite their fast movement thanks to the nearly simultaneous TanDEM‐X measurements. The height ambiguity, which defined as the altitude difference correspondent to phase change of flattened interferogram, of the dataset was 10.63 m, which is favorable for extracting topography in a low relief region. We validated the TanDEM‐X derived glacial topography by comparing it to the SAR/Interferometric radar altimeter observations acquired by CryoSat‐2 and the IceBridge Airborne Topographic Mapper laser altimeter measurements. Both observations showed very good correlation within a few meters of the offsets (‐12.5 – ‐3.1 m) with respect to the derived glacial topography. Because of highly sensitive ambiguity, we could successfully extract detailed geomorphological features on the glaciers. Routine TanDEM-X observations will be very useful to better understand the dynamics of glacial movements and topographic change.

The cerebellum is an encephalic region classically known for its central role in the control of movement, although recent research has revealed its involvement in other cognitive and affective tasks. Several different pathologies are known to affect this structure, causing a wide range of behavioral and gait impairments. Intriguingly, although the neurodegenerative factors affect all Purkinje cells of the cerebellum uniformly, certain neurodegeneration patterns can be distinguished, in which some Purkinje cells persist longer than other cell types. Precisely, there is a cerebellar region, lobe X, which is more resistant to different types of neurodegeneration regardless of the injury. This work will review the main models of cerebellar degeneration, with special emphasis on this region, and aims to reveal a common origin for its resistance to neuronal death.

CD15 (Lewis X/Lex) is a fucosyl (3-fucosly-N-acetyl-lactosamine) moiety found on membrane proteins of various cancer cells. These include renal cancer, prostate and bladder cancers, acute leukemias, hepatocellular carcinoma, breast cancer and melanoma. The antigen plays an espe-cially significant role in renal cell carcinoma. Its high expression serves as a good prognostic marker for patients and high hopes are related to its use in the immunotherapy of the tumor. The biological role of CD15 is the interaction with E-, L- and P-selectins (adhesion molecules) and al-lowing for the adhesion with the endothelial cells. In this way, cancer cells start to interact with the endothelium of blood vessels and consequently move out from the blood flow to the sur-rounding tissues. The blockage of antigen’s function results in reduced metastatic potential. Moreover, the molecule may be a therapeutic target against cancer in monoclonal antibod-ies-based therapies. CD15s is a sialyl derivative of CD15, that possess its own unique characteris-tics. Unlike high expression of CD15, which is a prognostic factor in Hodgkin lymphoma, CD15s relate to poor prognosis for the patients. Due to the high abundance in cancer cells, CD15 is con-sidered as a marker of Cancer Stem Cells. This review presents a comprehensive description of the role of CD15 and CD15s in cancer development and metastasis and overviews the clinical appli-cations of the anti-CD15 therapy.

Tungsten oxides play a pivotal role in a variety of modern technologies e.g., switchable glasses, wastewater treatment, and modern gas sensors. Metallic tungsten is used as armor material, for e.g., gas turbines as well as future fusion power devices. In the first case, oxides are desired as functional materials, while in the second case, oxides can lead to catastrophic failures, so avoiding the oxidation of tungsten is desired. In both cases, it is crucial to understand the reactivity of tungsten oxides with other chemicals. In this study, the different reactivities of tungsten oxides with the highly-oxophilic beryllium are studied and compared. Tungsten-(IV)-oxide and tungsten-(VI)-oxide layers are prepared on a tungsten substrate. In the next step, a thin film of beryllium is evaporated on the samples. In consecutive steps, the sample is heated in steps of 100 K from r. t. to 1273 K. The chemical composition is investigated after each experimental step by high-resolution X-ray photoelectron spectroscopy (XPS) of all involved core levels as well as the valence band. A model is developed to analyze the chemical reactions after each step. In this study, we find that tungsten trioxide was already reduced by beryllium at r. t. and started to react to form the ternary compounds BeWO₃ and BeWO₄ at temperatures starting from 673 K. However, tungsten dioxide is resistant to reduction at temperatures of up to 1173 K. In conclusion, we find WO₂ to be much more chemically resistant to the reduction agent Be than WO₃.

Cardiopulmonary complications remain the major cause of mortality despite newer therapies and improvements in lifespan of patients with sickle cell disease (SCD). Inflammation has been identified as a major risk modifier in the pathogenesis of SCD associated cardiopulmonary complications in recent mechanistic and observational studies. In this review, we discuss recent cellular and molecular mechanisms of cardiopulmonary complications in SCD and summarize the most recent evidence from clinical and laboratory studies. We emphasize the role of inflammation in the onset and progression of these complications to better understand the underlying pathobiological processes. We also discuss future basic and translational research in addressing questions about the complex role of inflammation in the development of SCD cardiopulmonary complications, which may lead to promising therapies and reduce morbidity and mortality in this vulnerable population.

Nuclear receptors (NRs) constitute a superfamily of ligand-activated transcription factors with a paramount role in ubiquitous physiological functions such as metabolism, growth, and reproduction. Owing to their physiological role and druggability, NRs are deemed attractive and valid targets for medicinal chemists. Pentacyclic triterpenes (PTs) represent one of the most important phytochemical classes present in higher plants, where oleanolic acid (OA) is the most studied PTs representative owing to its multitude of biological activities against cancer, inflammation, diabetes, and liver injury. PTs possess a lipophilic skeleton that imitates the NRs endogenous ligands. Herein, we report a literature overview on the modulation of metabolic NRs by OA and its semi-synthetic derivatives, highlighting their health benefits and potential therapeutic applications. Indeed, OA exhibited varying pharmacological effects on FXR, PPAR, LXR, RXR, PXR, and ROR in a tissue-specific manner. Owing to those NRs modulation, OA exhibited prominent hepatoprotective properties comparable to ursodeoxycholic acid (UDCA) in a bile duct ligation mice model and antiatherosclerosis effect as simvastatin in a model of New Zealand white (NZW) rabbits. It also demonstrated a great promise in alleviating non-alcoholic steatohepatitis (NASH) and liver fibrosis, attenuated alpha-naphthol isothiocyanate (ANIT)-induced cholestatic liver injury, and controlled blood glucose levels, making it a key player in the therapy of metabolic diseases. We also compiled OA semi-synthetic derivatives and explored their synthetic pathways and pharmacological effects on NRs, showcasing their structure-activity relationship (SAR). To the best of our knowledge, this is the first review article to highlight OA activity in terms of NRs modulation.