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X-ray Transient Absorption Spectroscopy (XTAS) is a powerful probe for ultrafast molecular dynamics. The evolution of XTAS signal is controlled by the shapes of potential energy surfaces of the associated core-excited states, which are difficult to directly measure. Here, we study the vibrational dynamics of Raman activated CCl4 with XTAS targeting the C 1s and Cl 2p electrons. The totally symmetric stretching mode leads to concerted elongation or contraction in bond lengths, which in turn induce an experimentally measurable red or blue shift in the X-ray absorption energies associated with inner-shell electron excitations to the valence antibonding levels. The ratios between slopes of different core-excited potential energy surfaces (CEPESs) thereby extracted agree very well with Restricted Open-Shell Kohn-Sham calculations. The other, asymmetric, modes do not measurably contribute to the XTAS signal. The results highlight the ability of XTAS to reveal coherent nuclear dynamics involving  < 0.01 Å atomic displacements and also provide direct measurement of forces on CEPESs.

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PURPOSE: To characterize the dose-response, energy dependence, postexposure changes, orientation dependence, and spatial capabilities of LD-V1, a new low-dose Gafchromic film for low-energy x-ray dosimetry. METHODS: A single sheet of LD-V1 Gafchromic film was cut into 15 × 20 mm2 rectangles with a notch to track orientation. Eight different doses between 5 and 320 mGy were delivered by an MXR-160/22 x-ray tube using x-ray beams of 90, 100, and 120 kVp filtered with 3 mm of Al and 2 mm of Ti. The 120 kVp films were scanned at 1, 1.5, 2, 3, 12, 24, 48, 72, and 168 h postexposure in portrait orientation and additionally scanned in landscape orientation at 24 h. The 90 and 100 kVp films were scanned at 24 h postexposure in portrait orientation. Lastly, a 20 × 200 mm2 strip of film was irradiated using a thin-slit imaging collimator and scanned 24 h postexposure to test the film performance in an x-ray imaging application. RESULTS: Of the three color channels, the red channel was found to produce a dose-response curve with a large range of net optical density (netOD) values across the considered dose range. A prominent energy dependence was discovered, resulting in dose discrepancies on the scale of 17 mGy between 90 and 120 kVp for a dose of 80 mGy. The measured postexposure changes suggest that the calibration irradiation-to-scan time should be longer than 12 h with a ± 4 h scanning time window for dose errors of <0.5%. An average dose difference of 3.4% was found between the two scanning orientations. Lastly, noise of 4% was measured in the thin slit collimator film for a dose of 30 mGy. CONCLUSIONS: We have characterized the LD-V1 film for low-energy, low-dose x-ray dosimetry. Energy, scan-time, and orientation dependencies should be considered when using this film.

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Background: Lung cancer is one of the most common types of cancer in the United Kingdom. It is often diagnosed late. The 5-year survival rate for lung cancer is below 10%. Early diagnosis may improve survival. Software that has an artificial intelligence-developed algorithm might be useful in assisting with the identification of suspected lung cancer. Objectives: This review sought to identify evidence on adjunct artificial intelligence software for analysing chest X-rays for suspected lung cancer, and to develop a conceptual cost-effectiveness model to inform discussion of what would be required to develop a fully executable cost-effectiveness model for future economic evaluation. Data sources: The data sources were MEDLINE All, EMBASE, Cochrane Database of Systematic Reviews, Cochrane CENTRAL, Epistemonikos, ACM Digital Library, World Health Organization International Clinical Trials Registry Platform, clinical experts, Tufts Cost-Effectiveness Analysis Registry, company submissions and clinical experts. Searches were conducted from 25 November 2022 to 18 January 2023. Methods: Rapid evidence synthesis methods were employed. Data from companies were scrutinised. The eligibility criteria were (1) primary care populations referred for chest X-ray due to symptoms suggestive of lung cancer or reasons unrelated to lung cancer; (2) study designs that compared radiology specialist assessing chest X-ray with adjunct artificial intelligence software versus radiology specialists alone and (3) outcomes relating to test accuracy, practical implications of using artificial intelligence software and patient-related outcomes. A conceptual decision-analytic model was developed to inform a potential full cost-effectiveness evaluation of adjunct artificial intelligence software for analysing chest X-ray images to identify suspected lung cancer. Results: None of the studies identified in the searches or submitted by the companies met the inclusion criteria of the review. Contextual information from six studies that did not meet the inclusion criteria provided some evidence that sensitivity for lung cancer detection (but not nodule detection) might be higher when chest X-rays are interpreted by radiology specialists in combination with artificial intelligence software than when they are interpreted by radiology specialists alone. No significant differences were observed for specificity, positive predictive value or number of cancers detected. None of the six studies provided evidence on the clinical effectiveness of adjunct artificial intelligence software. The conceptual model highlighted a paucity of input data along the course of the diagnostic pathway and identified key assumptions required for evidence linkage. Limitations: This review employed rapid evidence synthesis methods. This included only one reviewer conducting all elements of the review, and targeted searches that were conducted in English only. No eligible studies were identified. Conclusions: There is currently no evidence applicable to this review on the use of adjunct artificial intelligence software for the detection of suspected lung cancer on chest X-ray in either people referred from primary care with symptoms of lung cancer or people referred from primary care for other reasons. Future work: Future research is required to understand the accuracy of adjunct artificial intelligence software to detect lung nodules and cancers, as well as its impact on clinical decision-making and patient outcomes. Research generating key input parameters for the conceptual model will enable refinement of the model structure, and conversion to a full working model, to analyse the cost-effectiveness of artificial intelligence software for this indication. Study registration: This study is registered as PROSPERO CRD42023384164. Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Evidence Synthesis programme (NIHR award ref: NIHR135755) and is published in full in Health Technology Assessment; Vol. 28, No. 50. See the NIHR Funding and Awards website for further award information.

Lung cancer is one of the most common types of cancer in the United Kingdom. Early diagnosis may improve survival, as lung cancer is often diagnosed late. Chest X-rays can be used to identify features of lung cancer. There can be delays in getting X-rays, and sometimes features of lung cancer are not seen on them. Artificial intelligence software may help by finding features of cancer on chest X-rays and highlighting them. A radiologist will look at the X-rays and information from the software. There is a lack of information about how lung cancer diagnosis could change if artificial intelligence software is used and what the costs may be to the National Health Service. This project looked at the use of artificial intelligence software in the detection of lung cancer in people referred from primary care. Software companies were invited to provide evidence. There were no studies that looked at this topic among people from primary care. We summarised the closest evidence we could find instead. All of this had flaws, so we could not tell if the results were accurate or helpful to this review. It was not clear if artificial intelligence helped to find cancers or improve people's health. We made a theoretical model to discuss the best way to assess if artificial intelligence software might be cost-effective in detecting lung cancer and what evidence would be needed to do this in a fully working model. Costs and alternative pricing models provided by five companies were used to calculate the cost of adding artificial intelligence software to review chest X-rays in people referred from their general practitioner, for the first 5 years, based on one National Health Service trust. Future studies are needed to identify the impact of adjunct artificial intelligence on test accuracy, clinical decision-making and patient outcomes (e.g. mortality and morbidity).

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Metal halide perovskites have emerged as promising materials for X-ray detection due to their high X-ray attenuation coefficients, defect tolerance, and suitability for large-area, low-temperature fabrication. However, the intrinsic high ion conductivity of these materials presents challenges, such as high dark current density and current drift, which impair the stability and sensitivity of perovskite X-ray detectors. This study introduces an approach to mitigating these issues by incorporating 2,2,3,3,3-pentafluoropropylamine hydrochloride (PFH) into polycrystalline MAPbI3-xClx films using a one-step blade-coating method. PFH aggregates at grain boundaries, raising local vacuum energy levels and passivating surface defects, thereby reducing ion conductivity without affecting electron conductivity. As a result, this approach significantly reduces the dark current and enhances sensitivity, achieving a low detection limit of 14.7 nGyair/s. Additionally, it improves signal stability, consistency, and response speed of the detector. These findings suggest that PFH is a promising additive for advancing the performance and practical application of polycrystalline metal halide perovskite-based X-ray detectors.

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BACKGROUND AND OBJECTIVES: Ambiguity in diagnosing acute heart failure (AHF) leads to inappropriate treatment and potential side effects of rescue medications. To address this issue, this study aimed to use multimodality deep learning models combining chest X-ray (CXR) and electronic health record (EHR) data to screen patients with abnormal N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels in emergency departments. METHODS: Using the open-source dataset MIMIC-IV and MIMICCXR, the study population consisted of 1,432 patients and 1,833 pairs of CXRs and EHRs. We processed the CXRs, extracted relevant features through lung-heart masks, and combined these with the vital signs at triage to predict corresponding NT-proBNP levels. RESULTS: The proposed method achieved a 0.89 area under the receiver operating characteristic curve by fusing predictions from single-modality models of heart size ratio, radiomic features, CXR, and the region of interest in the CXR. The model can accurately predict dyspneic patients with abnormal NT-proBNP concentrations, allowing physicians to reduce the risks associated with inappropriate treatment. CONCLUSION: The study provided new image features related to AHF and offered insights into future research directions. Overall, these models have great potential to improve patient outcomes and reduce risks in emergency departments.

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The design and optimization of laser-Compton x-ray systems based on compact distributed charge accelerator structures can enable micron-scale imaging of disease and the concomitant production of beams of Very High Energy Electrons (VHEEs) capable of producing FLASH-relevant dose rates. The physics of laser-Compton x-ray scattering ensures that the scattered x-rays follow exactly the trajectory of the incident electrons, thus providing a route to image-guided, VHEE FLASH radiotherapy. The keys to a compact architecture capable of producing both laser-Compton x-rays and VHEEs are the use of X-band RF accelerator structures which have been demonstrated to operate with over 100 MeV/m acceleration gradients. The operation of these structures in a distributed charge mode in which each radiofrequency (RF) cycle of the drive RF pulse is filled with a low-charge, high-brightness electron bunch is enabled by the illumination of a high-brightness photogun with a train of UV laser pulses synchronized to the frequency of the underlying accelerator system. The UV pulse trains are created by a patented pulse synthesis approach which utilizes the RF clock of the accelerator to phase and amplitude modulate a narrow band continuous wave (CW) seed laser. In this way it is possible to produce up to 10 µA of average beam current from the accelerator. Such high current from a compact accelerator enables production of sufficient x-rays via laser-Compton scattering for clinical imaging and does so from a machine of "clinical" footprint. At the same time, the production of 1000 or greater individual micro-bunches per RF pulse enables > 10 nC of charge to be produced in a macrobunch of < 100 ns. The design, construction, and test of the 100-MeV class prototype system in Irvine, CA is also presented.

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The ability to freely control the polarization of X-rays enables measurement techniques relying on circular or linear dichroism, which have become indispensable tools for characterizing the properties of chiral molecules or magnetic structures. Therefore, the demand for polarization control in X-ray free-electron lasers is increasing to enable polarization-sensitive dynamical studies on ultrafast time scales. The soft X-ray branch Athos of SwissFEL was designed with the aim of providing freely adjustable and arbitrary polarization by building its undulator solely from modules of the novel Apple X type. In this paper, the magnetic model of the linear inclined and circular Apple X polarization schemes are studied. The polarization is characterized by measuring the angular electron emission distributions of helium for various polarizations using cold target recoil ion momentum spectroscopy. The generation of fully linear polarized light of arbitrary angle, as well as elliptical polarizations of varying degree, are demonstrated.

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Visual perception of X-radiation is a well-documented, but poorly understood phenomenon. Scotopic rod cells and rhodopsin have been implicated in visual responses to X-rays, however, some evidence suggests that X-rays excite the retina via a different mechanism than visible light. While rhodopsin's role in X-ray perception is unclear, the possibility that it could function as an X-ray receptor has led to speculation that it could act as a transgenically expressed X-ray receptor. If so, it could be used to transduce transcranial X-ray signals and control the activity of genetically targeted populations of neurons in a less invasive version of optogenetics, X-genetics. Here we investigate whether human rhodopsin (hRho) is capable of transducing X-ray signals when expressed outside of the retinal environment. We use a live-cell cAMP GloSensor luminescence assay to measure cAMP decreases in hRho-expressing HEK293 cells in response to visible light and X-ray stimulation. We show that cAMP GloSensor luminescence decreases are not observed in hRho-expressing HEK293 cells in response to X-ray stimulation, despite the presence of robust responses to visible light. Additionally, irradiation had no significant effect on cAMP GloSensor responses to subsequent visible light stimulation. These results suggest that ectopically expressed rhodopsin does not function as an X-ray receptor and is not capable of transducing transcranial X-ray signals into neural activity for X-ray mediated, genetically targeted neuromodulation.

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Ollier Disease (OD) and Maffucci syndrome (MS) is a rare bone disorder that affects the growth and development of the bones, with an estimated prevalence of 1 in 100,000 people. It is associated with somatic mosaicism of isocitrate dehydrogenase-1 (IDH1) or 2 (IDH2) pathogenic variants. Ivosidenib is indicated for the treatment of acute myeloid leukemia and locally advanced or metastatic cholangiocarcinoma and is currently investigated in low-grade glioma with a susceptible isocitrate dehydrogenase-1 (IDH1) pathogenic variant, but its effects in patients with OD or MS are unknown. We here report the first case of a patient with MS who was treated with Ivosidenib for recurrent IDH-1 mutated glioma. Besides the stabilization of the tumor size, the patient observed significant improvement in his enchondromas that became stiffer, with reduced pain, and significant modification of the mineralization of the enchondromas observed on X-rays. This first case report provides hope for the medical management of patients suffering because of OD or MS. Future clinical research is urgently needed to evaluate long-term benefit risk profile of IDH inhibitors in these rare diseases.

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This research focused on the determination of scatter radiation levels in x-ray rooms during chest radiography. 108 patients were examined. Four x-ray machines (A, B, C, and D) were used during the research from three centers. Three positions were considered in this study; position Q just beside the (Bucky stand), position R, which is 150 cm from the left of the Bucky stand towards the door and position T, 200 cm from the Bucky stand to the radiographer's protective screen respectively. Two machines (A and B) from center 1 and one machine from center 2 (C) and one machine from center 3 (D). The body mass index (BMI) of the participants ranged from 20 to 25 kgm-2 with mean value of 23.97 kgm-2. The background radiation level was read using Radalert 100 m before any exposure, and the mean background level was 0.298 mR/h. The mean of the scatter radiation doses obtained from positions Q with respect to the four machines A, B, C, and D, were 0.109, 0.201, 0.204, 0.200 mR/h (9.166, 16.903, 17.156, 16.819 mSv/yr) and their standard deviations were ±0.052, ±0.053, ±0.064, and ±0.081 respectively. The results were comparable with previous studies. The study recommends staff education and training in determination of radiation levels for enhanced work safety.

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With the emergence of ultrafast X-ray sources, interest in following fast processes in small molecules and macromolecules has increased. Most of the current research into ultrafast structural dynamics of macromolecules uses X-ray free-electron lasers. In parallel, small-scale laboratory-based laser-driven ultrafast X-ray sources are emerging. Continuous development of these sources is underway, and as a result many exciting applications are being reported. However, because of their low flux, such sources are not commonly used to study the structural dynamics of macromolecules. This article examines the feasibility of time-resolved powder diffraction of macromolecular microcrystals using a laboratory-scale laser-driven ultrafast X-ray source.

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BACKGROUND: Phase-contrast computed tomography (CT) using high-brilliance, synchrotron-generated x-rays enable three-dimensional (3D) visualization of microanatomical structures within biological specimens, offering exceptionally high-contrast images of soft tissues. Traditional methods for phase-contrast CT; however, necessitate a gap between the subject and the x-ray camera, compromising spatial resolution due to penumbral blurring. Our newly developed technique, Superimposed Wavefront Imaging of Diffraction-enhanced x-rays (SWIDeX), leverages a Laue-case Si angle analyzer affixed to a scintillator to convert x-rays to visible light, capturing second-order differential phase contrast images and effectively eliminating the distance to the x-ray camera. This innovation achieves superior spatial resolution over conventional methods. PURPOSE: In this paper, the imaging principle and CT reconstruction algorithm based on SWIDeX are presented in detail and compared with conventional analyzer-based imaging (ABI). It also shows the physical setup of SWIDeX that provides the resolution preserving second-order differential images for reconstruction. We compare the spatial resolution and the sensitivity of SWIDeX to conventional ABI. METHODS: To demonstrate high-spatial resolution achievable by SWIDeX, the internal structures of four human tissues-ductal carcinoma in situ, normal stomach, normal pancreas, and intraductal papillary mucinous neoplasm of the pancreas-were visualized using an imaging system configured at the Photon Factory's BL14B beamline under the High Energy Accelerator Research Organization (KEK). Each tissue was thinly sliced after imaging, stained with hematoxylin and eosin (H&E) for conventional microscope-based pathology. RESULTS: A comparison of SWIDeX-CT and pathological images visually demonstrates the effectiveness of SWIDeX-CT for biological tissue imaging. SWIDeX could generate clearer 3D images than existing analyzer-based phase-contrast methods and accurately delineate tissue structures, as validated against histopathological images. CONCLUSIONS: SWIDeX can visualize important 3D structures in biological soft tissue with high spatial resolution and can be an important tool for providing information between the disparate scales of clinical and pathological imaging.

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BACKGROUND: This study aimed to examine whether the non-weight-bearing tunnel view X-ray is effective for short-term evaluation of medial meniscus posterior root tear (MMPRT) by assessing the X-ray characteristics at the initial and follow-up visits. METHODS: This was a retrospective longitudinal study of 26 enrolled knees diagnosed with MMPRT on magnetic resonance imaging. The distance between the medial tibial eminence and medial femoral condyle (MTE-MFC distance) and medial tibiofemoral joint (MTFJ) width were measured by obtaining non-weight-bearing tunnel view and frontal view X-ray radiographs. The initial and follow-up values at a median interval of 17 days were compared. Additionally, the correlations between the MTE-MFC distance increase rate and body mass index (BMI), age, femorotibial angle (FTA), and posterior tibial slope (PTS) were evaluated using linear regression analysis. RESULTS: The tunnel view images of the initial and follow-up X-rays showed a significant increase in the MTE-MFC distance and a significant decrease in the MTFJ width. Furthermore, a moderate correlation was observed between the change in the MTE-MFC distance and the time interval between X-rays. However, no substantial correlation was observed for the change in the MTFJ width over time. Moreover, no significant correlation was observed between the change in the MTE-MFC distance in the non-weight-bearing tunnel view and BMI, age, FTA, and PTS. CONCLUSIONS: The non-weight-bearing tunnel view is highly beneficial for evaluating MMPRT progression in the short term.

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BACKGROUND: There is compelling evidence that AXRs have limited clinical value in the acute setting. Despite this, they are frequently used in many EDs. This quality improvement project (QIP) aimed to reduce unnecessary AXR use in a single-centre ED. METHOD: All consecutive AXRs conducted on patients aged 16 years and above in a District General Hospital ED in England between 2 August 2021 and 5 June 2022 were included. This period of time was divided into a pre-intervention and intervention period, during which iterative plan-do-study-act cycles were undertaken to implement a wide range of educational and system level interventions. RESULTS: 501 AXRs were performed during the QIP. The average number of AXRs per fortnight fell from 27.5 during the preintervention period to 17.6 during the intervention period and met criteria for special cause variation. No special cause variation in CT usage was observed, with an average number of 70.7 and 74 CT abdomen-pelvis scans during the preintervention and intervention periods, respectively. 119 (23.8%) AXRs showed acute and clinically significant findings, and of this group 118/119 (99.2%) underwent further imaging. In contrast, 382 (76.2%) AXRs had no acute or clinically significant findings, and of this group 344/382 (90.1%) proceeded to further imaging. CONCLUSION: In this single-centre QIP, coordinated multidisciplinary interventions were effective in reducing unnecessary AXR usage without resulting in excess CTs. The methods and interventions described are easily reproducible at minimal expense and may be of interest to other departments undertaking quality improvement work in this area.

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OBJECTIVE: Evidence-based radiographic guidelines are used to justify the need for radiographs and prevent their overuse. This study aimed to assess whether 4th-year chiropractic interns at the International Medical University plan to use x-ray imaging in their future private practice in line with the principles taught throughout their chiropractic program and the evidence-based imaging guidelines. METHODS: A survey questionnaire was distributed to 74 final year chiropractic interns, with 62 completed responses. The questionnaire consisted of 8 case scenarios representing potential chiropractic patients. The interns were asked to decide whether to x-ray the patient or not, and which x-ray views to request if they chose to x-ray the patient. RESULTS: Results were compared with the gold standard using percentage agreement. The findings revealed that the chiropractic students adhered to the gold standard answers for 6 out of 8 cases. However, they did not perform well in selecting the correct x-ray views for the 3 cases where radiography was indicated by the gold standard. CONCLUSION: Results suggest that while the interns have a good understanding of when radiography is necessary, they may need additional training in selecting the appropriate x-ray views for each case.

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Purpose: The use of artificial intelligence (AI) for chest X-ray (CXR) analysis is becoming increasingly prevalent in medical environments. This study aimed to determine whether AI in CXR can unexpectedly detect lung nodule detection and influence patient diagnosis and management in non-respiratory outpatient clinics. Methods: In this retrospective study, patients over 18 years of age, who underwent CXR at Yongin Severance Hospital outpatient clinics between March 2021 and January 2023 and were identified to have lung nodules through AI software, were included. Commercially available AI-based lesion detection software (Lunit INSIGHT CXR) was used to detect lung nodules. Results: Out Of 56,802 radiographic procedures, 40,191 were from non-respiratory departments, with AI detecting lung nodules in 1,754 cases (4.4%). Excluding 139 patients with known lung lesions, 1,615 patients were included in the final analysis. Out of these, 30.7% (495/1,615) underwent respiratory consultation and 31.7% underwent chest CT scans (512/1,615). As a result of the CT scans, 71.5% (366 cases) were found to have true nodules. Among these, the final diagnoses included 36 lung cancers (7.0%, 36/512), 141 lung nodules requiring follow-up (27.5%, 141/512), 114 active pulmonary infections (22.3%, 114/512), and 75 old inflammatory sequelae (14.6%, 75/512). The mean AI nodule score for lung cancer was significantly higher than that for other nodules (56.72 vs. 33.44, p < 0.001). Additionally, active pulmonary infection had a higher consolidation score, and old inflammatory sequelae had the highest fibrosis score, demonstrating differences in the AI analysis among the final diagnosis groups. Conclusion: This study indicates that AI-detected incidental nodule abnormalities on CXR in non-respiratory outpatient clinics result in a substantial number of clinically significant diagnoses, emphasizing AI's role in detecting lung nodules and need for further evaluation and specialist consultation for proper diagnosis and management.

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INTRODUCTION: Deep neural networks (DNNs) have made significant contributions to diagnosing pneumonia from chest X-ray imaging. However, certain aspects of diagnosis and planning can be further enhanced through the implementation of a quantum deep neural network (QDNN). Therefore, we introduced a technique that integrates neural networks with quantum algorithms named the ZFNet-quantum neural network for detecting pneumonia using 5863 X-ray scans with binary cases. METHODS: The hybrid model efficiently pre-processes complex and high-dimensional data by extracting significant features from the ZFNet model. These significant features are given to the quantum circuit algorithm and further embedded into a quantum device. The parameterized quantum circuit algorithm using qubits, superposition theorem, and entanglement phenomena generates 4 features from 4098 features extracted from images via a deep transfer learning model. Moreover, to validate the outcome measures of the proposed technique, we used various PennyLane quantum devices to detect pneumonia and normal control images. By using the Adam optimizer, which exploits an adaptive learning rate that is fixed to 10-6 and six layers of a quantum circuit composed of quantum gates, the proposed model achieves an accuracy of 96.5%, corresponding to 25 epochs. RESULTS: The integrated ZFNet-quantum learning network outperforms the deep transfer learning network in terms of testing accuracy, as the accuracy gained by the convolutional neural network (CNN) is 94%. Therefore, we use a hybrid classical-quantum model to detect pneumonia in which a variational quantum algorithm enhances the outcomes of a ZFNet transfer learning method. CONCLUSION: This approach is an efficient and automated method for detecting pneumonia and could significantly enhance outcome measures related to the speed and accuracy of the network in the clinical and healthcare sectors.

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Osteocytes are the major actors in bone mechanobiology. Within bone matrix, they are trapped close together in a submicrometric interconnected network: the lacunocanalicular network (LCN). The interstitial fluid circulating within the LCN transmits the mechanical information to the osteocytes that convert it into a biochemical signal. Understanding the interstitial fluid dynamics is necessary to better understand the bone mechanobiology. Due to the submicrometric dimensions of the LCN, making it difficult to experimentally investigate fluid dynamics, numerical models appear as a relevant tool for such investigation. To develop such models, there is a need for geometrical and morphological data on the human LCN. This study aims at providing morphological data on the human LCN from measurement of 27 human femoral diaphysis bone samples using synchrotron radiation nano-computed tomography with an isotropic voxel size of 100 nm. Except from the canalicular diameter, the canalicular morphological parameters presented a high variability within one sample. Some differences in terms of both lacunar and canalicular morphology were observed between the male and female populations. But it has to be highlighted that all the canaliculi cannot be detected with a voxel size of 100 nm. Hence, in the current study, only a specific population of large canaliculi that could be characterize. Still, to the authors knowledge, this is the first time such a data set was introduced to the community. Further processing will be achieved in order to provide new insight on the LCN permeability.

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The Biomedical Imaging and Therapy facility of the Canadian Light Source comprises two beamlines, which together cover a wide X-ray energy range from 13 keV up to 140 keV. The beamlines were designed with a focus on synchrotron applications in preclinical imaging and veterinary science as well as microbeam radiation therapy. While these remain a major part of the activities of both beamlines, a number of recent upgrades have enhanced the versatility and performance of the beamlines, particularly for high-resolution microtomography experiments. As a result, the user community has been quickly expanding to include researchers in advanced materials, batteries, fuel cells, agriculture, and environmental studies. This article summarizes the beam properties, describes the endstations together with the detector pool, and presents several application cases of the various X-ray imaging techniques available to users.

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The Pohang Accelerator Laboratory X-ray Free-Electron Laser (PAL-XFEL) operates hard X-ray and soft X-ray beamlines for conducting scientific experiments providing intense ultrashort X-ray pulses based on the self-amplified spontaneous emission (SASE) process. The X-ray free-electron laser is characterized by strong pulse-to-pulse fluctuations resulting from the SASE process. Therefore, online photon diagnostics are very important for rigorous measurements. The concept of photo-absorption and emission using solid materials is seldom considered in soft X-ray beamline diagnostics. Instead, gas monitoring detectors, which utilize the photo-ionization of noble gas, are employed for monitoring the beam intensity. To track the beam position at the soft X-ray beamline in addition to those intensity monitors, an X-ray ionization beam position monitor (XIBPM) has been developed and characterized at the soft X-ray beamline of PAL-XFEL. The XIBPM utilizes ionization of either the residual gas in an ultra-high-vacuum environment or injected krypton gas, along with a microchannel plate with phosphor. The XIBPM was tested separately for monitoring horizontal and vertical beam positions, confirming the feasibility of tracking relative changes in beam position both on average and down to single-shot measurements. This paper presents the basic structure and test results of the newly developed non-invasive XIBPM.