It is time-consuming for acquiring complete data by fully phase encoding in two orthogonal directions along with one frequency encoding direction. Undersampling in the 3D k-space is promising in accelerating such 3D MRI process. Though 3D undersampling can be conducted according to predefined probability density, the density based method is not optimal. Because of the large amount of 3D data and computational cost, it is challenging to perform data-driven and learning-based 3D undersampling and subsequent 3D reconstruction. To tackle this challenge, this paper proposes a deep neural network called EEUR-Net, realized by optimizing specific undersampling patterns for the fully-sampled 3D k-space data. Innovatively, our undersampling algorithm employs an end-to-end deep learning approach to optimize phase encoding patterns and uses a 3D U-Net for image reconstruction of undersampled data. Through end-to-end training, we obtain an optimized 3D undersampling pattern, which significantly enhances the quality of the reconstructed image under the same acceleration factor. A series of experiments on a knee MRI dataset demonstrated that, in comparison to standard random uniform, radial, Poisson and equispaced Cartesian undersampling schemes, our end-to-end learned undersampling pattern considerably improves the reconstruction quality of undersampled MRI images.

Abstract: The pursuit of youth and attractiveness is a fundamental desire in contemporary society. For many individuals, the appearance of visible signs of aging, such as skin laxity, gravitational changes in facial and neck soft tissues, and loss of harmonious proportions, can be psychologically distressing. The choice of effective methods for addressing these changes depends on their specific characteristics, the patient's anatomical features, and the type of facial aging. The introduction of 3D imaging to determine the hyoid bone level, the volume of soft tissue structures in the cervico-mental area, ptosis of subplatysmal structures, and the volume of submandibular glands, in addition to ultrasound study of the submental projection at the preoperative stage, are key for taking the best decision regarding preoperative planning. This case report aims to illustrate how modern imaging techniques are a fundamental part of the preoperative assessment of the mid and lower third of the face to ensure the most favorable aesthetic outcomes for each patient. Key message: To attain harmonious results in surgical correction of age-related facial and neck changes, it is crucial to consider the patient's anatomical features and the extent of age-related alterations. A comprehensive facial analysis, taking into account the type of facial aging and employing a CT scan and ultrasound examination of the soft tissues in the chin region, facilitates the development of an individualized plan tailored to achieve the patient's desired outcome.

Backgrounds Linear association has widely been assumed for prediction of aging-related fractional anisotropy (FA) decline in white matter of the brain. While useful for testing significance of the aging effect, it fails to identify a threshold age before and after which the age-FA association changes. Identification of such a threshold is often of clinical interest for timely intervention. Methods We employed a sigmoidal growth function to test a threshold effect in age triggering onset of cerebral decline in 21 white matter tracts, and compared its fitting performance to those of linear, and power regression. The study sample was a normal healthy cohort of 106 participants with ages in mid-life ranging from 18 to 60 years. Results Of the 21 white matter tracts analyzed, the posterior thalamic radiation showed better fit with sigmoidal curve model, compared to a linear or power regression. The estimated threshold age in years (95% confidence interval) were 47.2 (44.1-48.4). Conclusion While available evidence regarding the presence of a specific age threshold for cerebral decline in mid-life based on FA was limited, the posterior thalamic radiation exhibited a threshold age of 47.2. Beyond this age point, we observed a significant change in the FA risk pattern.

Coronary angiography, long considered the gold standard for coronary imaging, faces limitations in assessing coronary vessel wall anatomy and guiding percutaneous coronary intervention (PCI). Despite its prevalence, studies have demonstrated that it is suboptimal in estimating the severity of coronary disease and physiologic significance of stenosis. Intracoronary imaging techniques, such as intravascular ultrasound (IVUS) and optical coherence tomography (OCT), offer promising alternatives to overcome these limitations. This review delves into the nuances of IVUS and OCT, highlighting their strengths and limitations as adjuncts to PCI. IVUS, utilizing ultrasound technology, and OCT, based on near-infrared light, each provide unique insights into coronary pathology. They differ in terms of temporal and spatial resolution, influencing their capabilities in plaque characterization and vessel assessment. The discussion navigates their historical evolution, technical specifications, and clinical utility. Meta-analyses and adjusted observational studies suggest that both IVUS and OCT-guided PCI correlate with reduced cardiovascular risks compared to angiographic guidance alone. While IVUS has demonstrated consistent benefits in terms of clinical outcomes, the evidence supporting OCT is less robust. However, the utilization of these imaging modalities remains variable across regions, with increasing adoption in recent years, particularly in IVUS-guided PCIs. Intravascular ultrasound's journey from early motion detection to current high-resolution mechanical systems is traced, including improvements in catheter size and compatibility. On the other hand, optical coherence tomography has advanced significantly, utilizing near infrared light to achieve unparalleled resolutions, albeit requiring temporary blood clearance for optimal imaging. In conclusion, IVUS and OCT offer valuable insights into coronary pathophysiology and guide interventions with improved precision compared to traditional angiography. While IVUS remains more extensively utilized, OCT's growing potential is underscored by advancements in technology, culminating in enhanced imaging capabilities. Both modalities demonstrate comparable clinical outcomes, emphasizing the need for tailored imaging choices based on individual clinical scenarios. The continued refinement and broader integration of intravascular imaging are expected to play a pivotal role in optimizing coronary interventions and patient outcomes.

Coded aperture 3D imaging techniques have been rapidly evolving in the recent years. The two main directions of evolution are in aperture engineering to generate the optimal optical field and in development of computational reconstruction to reconstruct the object’s image from the intensity distribution with a minimal noise. The goal is to find the ideal aperture-reconstruction method pair and if not, to optimize one to match the other for designing an imaging system with required 3D imaging characteristics. Lucy-Richardson-Rosen algorithm (LR²A), a recently developed computational reconstruction method was found to perform better than its predecessors such as matched filter, Weiner filter, phase-only filter, Lucy-Richardson algorithm and non-linear reconstruction (NLR) for certain apertures when the point spread function (PSF) is a real and symmetric function. For other cases of PSF, NLR performed better than the rest of the methods. In this tutorial, LR²A has been presented as a generalized approach for any optical field along with MATLAB codes for reconstruction of any image when the PSF is known. The common problems and pitfalls in using LR²A has been discussed. Simulation and experimental studies for common optical fields such as spherical, Bessel, vortex beams and exotic optical fields such as Airy, scattered and self-rotating beams have been presented. From this study, it can be seen that it is possible to transfer the 3D imaging characteristics from non-imaging type exotic fields to indirect imaging systems faithfully using LR²A. The application of LR²A to medical images such as colonoscopy images and cone beam computed tomography images with synthetic PSF has been demonstrated. We believe that the tutorial will provide a deeper understanding of computational reconstruction using LR²A.

Drones equipped with thermal cameras have recently become readily available, broadening the possibilities for monitoring wildlife. The European hare (Lepus europaeus) is a nocturnal mammal that is closely monitored in Denmark due to populations declining since the mid-1900s. The limitations of current population assessment methods, such as spotlight counts and hunting game statistics, could be overcome by relying on drone surveys with thermal imaging for population counts. The aim of this study was to investigate the use of a DJI Mavic 2 Enterprise Advanced drone with thermal imaging as a tool for monitoring the Danish hare population. Multiple test flights were conducted over agricultural areas in Denmark in spring 2022, testing various flight altitudes, camera settings, and recording methods. The test flights were used to suggest a method for identifying and counting hare. The applied use of this methodology was then evaluated through a case survey that had the aim of identifying and counting hare over an agricultural area of 242 ha. Hare could be detected with thermal imaging at flight altitudes up to 80 m and it was possible to fly as low as 40 m without observing direct behavior changes. Thermal images taken at these altitudes also provided enough detail to differentiate between species and animal body size proved to be a good species indicator. The case study confirmed the use of thermal imaging based drone surveys to identify hare and conduct population counts, thus, indicating the suggested methodology as a viable alternative to traditional counting methods.

Background: As coronavirus (COVID-19) continues to pose a threat to the entire world, it is critical to developing strategies for containing its spread. The purpose of this study was to assess the demographic characteristics, brain tomography characteristics, and diffusion magnetic resonance findings of COVID-19 positive individuals. Material and Method: Between January 1 and December 31, 2021, 317 patients over the age of 18 were admitted to the emergency department with symptoms consistent with COVID-19. Three groups were formed based on clinical findings in patients, divided into light, medium, and severe, and four groups were formed based on radiological imaging findings. Results: The mean age of the 317 patients included in the study was 67.28±12.06 years, with a range of 28-91 years. The clinical classification of the patients was based on laboratory parameters and radiological imaging, not on their age or gender. Mild cases were classified as CO-RADS 0-4; moderate and severe cases were classified as CO-RADS 5-6 (p=0.001). While 60 (18.9%) of patients were followed outpatient, 144 (45.4%) were admitted to the hospital, 73 (23%) were admitted to the intensive care unit, and 40 (12.7%) died (p=0.001). Direct radiographs revealed bilateral involvement in 224 (70.7%) cases, peripheral involvement in 259 (81.7%) cases, and mid-lower lobe lung involvement in 194 (61.2%) cases (p=0.001). Brain tomography revealed infarction in 42 (13.2%) of the patients who were followed and hospitalized and hemorrhage in 22 (6.9%) of the patients. Magnetic resonance imaging revealed diffusion involvement in 68 (21.5%) of the cases (p=0.001). Conclusion: A standardized reporting system for COVID-19 data is required, and it must be simple to use, quick to understand, and focused on determining the risk of pneumonia. Additionally, the diagnostic role of radiological imaging, prognosis prediction, and severity scoring of lung involvement should be included.

In clinical diagnostics and longitudinal studies, the reproducibility of MRI assessments is of high importance in order to detect pathological changes, but developments in MRI hard- and software often outrun extended periods of data acquisition and analysis. This could potentially introduce artefactual changes or mask pathological alterations. However, if and how changes of MRI hardware, scanning protocols or preprocessing software affect complex neuroimaging outcomes from e.g. diffusion weighted imaging (DWI) remains largely understudied. We therefore compared DWI outcomes and artefact severity of 121 healthy participants (age range 19-54 years) who underwent two matched DWI protocols (Siemens product and Center for Magnetic Resonance Research sequence) at two sites (Siemens 3T Magnetom Verio and Skyra^fit). After different preprocessing steps, fractional anisotropy (FA) and mean diffusivity (MD) maps,obtained by tensor fitting, were processed with tract-based spatial statistics (TBSS). Inter-scanner and inter-sequence variability of skeletonised FA values reached up to 5% and differed largely in magnitude and direction across the brain. Skeletonised MD values differed up to 14% between scanners. We here demonstrate that DTI outcome measures strongly depend on imaging site and software, and that these biases vary between brain regions. These regionally inhomogeneous biases may exceed and considerably confound physiological effects such as ageing, highlighting the need to harmonise data acquisition and analysis. Future studies thus need to implement novel strategies to augment neuroimaging data reliability and replicability.

Background: Molecular nuclear medicine, due to hybrid imaging camera systems and new tailored radiopharmaceuticals, has been gained a clinical relevance for diagnosis, therapy and follow-up of solid tumors. Despite numerous literature studies, many new radiopharmaceuticals for imaging tumor microenvironment, have not yet been used, routinely, in oncological clinical practice to monitor treatments. This is due to poor comparability of published studies, due to poor design and methodology, heterogeneous population and prevalence of preclinical studies. Methods: In this systematic review, we described the use of radiopharmaceuticals for evaluation of tumor treatment response by targeting microenvironment. We reviewed studies published from 2000 to 2020, to provide an updated status of research in this topic. Results: There is a growing role of radiopharmaceuticals and nuclear medicine imaging techniques in the management of cancer treatments, especially immunotherapy. Of the 24 papers included, 16 were preclinical studies. Conclusions: New radiopharmaceuticals could have an excellent impact in molecular imaging, leading to better diagnosis and important clinical information for therapy decision making and follow-up of cancer treatments in different solid tumors. Recently developed radiopharmaceuticals may provide great advantage to improve personalized medicine for patients with a great cost-effectiveness ratio.

Ultrasonic imaging & NDE applications can greatly improve their signal-to-noise ratios (SNR) by driving each transducer (composing piezoelectric arrays) with a spike giving pulsed power of k-Watts, repetitively at a PRF = 5000 spikes/s, by using a HV capacitive-discharge generator. However very-high levels, of pulsed intensities (3-10 A) and voltages (300-700 V) must be considered for a rigorous spike modeling. Even though the consumed "average" power will be small, the intensity through each transducer achieves several amperes, so the pulsed powers delivered by each HV generator can attain levels higher than in CW high-power ultrasonic applications: e.g., up to 5 kW / spike. This is concluded here from a transient modeling of the loaded generator. Then, unforeseen phenomena rise: intense brief pulses of driving power & emitted force in transducers, and non-linearities in driver semiconductors, because their characteristic curves only include linear ranges. But fortunately, piezoelectric devices working in this intense regime do not show serious heating problems, because the average power remains being moderate. Intensity, power and voltage, driving a broadband transducer from a HV capacitive pulser, are calculated to drastically improve (in ≅ 40 dB) the ultrasonic net dynamic range available, with emitted forces ≅ 250 Newtons pp and E/R received pulses of 70 V pp.

The main objective of this study is to develop a Hapke photometric model that is suited for Chang’E-1 (CE-1) Interference Imaging Spectrometer (IIM) data. We first divided the moon into three areas including ‘maria’, ‘new highland’ and old ‘highland’ with similar photometry characteristic based on the Hapke parameters of the moon derived from Lunar Reconnaissance Orbiter Camera (LROC) Wide Angle Camera (WAC) multispectral data. Then, we selected the sample data in the ‘maria’ area and obtained a new set of Hapke model’s parameters that can best fit these data. Result shows that photometric correction using Hapke model with these new derived parameters can eliminate the effect of variations in viewing and luminating geometry, especially ‘opposition surge’, more efficiently than the empirical model. The corrected mosaic shows no significant artifacts along the tile boundaries, and more detailed information of the image can be exhibited due to a better correction of ‘opposition surge’ at small phase angle (g <15°).

Late onset Pompe disease is a recessive lysosomal storage disease. Clinical features include skeletal muscles deficiency and diaphragm weakness. Clinical management relies on supportive treatment and mechanical ventilation in patents with chronic respiratory failure. M mode ultrasound and tissue Doppler imaging can be used to assess and to follow up diaphragm function.

Computation of Common Middle Point seismic sections and their subsequent time migration and diffraction imaging provides very important knowledge about the internal structure of 3D heterogeneous geological media and are key elements for successive geological interpretation. Full-scale numerical simulation, that computes all single shot seismograms, provides a full understanding of how the features of the image reflect the properties of the subsurface prototype. Unfortunately, this kind of simulations of 3D seismic surveys for realistic geological media needs huge computer resources, especially for simulation of seismic waves’ propagation through multiscale media like cavernous fractured reservoirs. In order to significantly reduce the query of computer resources we propose to model these 3D seismic cubes directly rather than the shot-by-shot simulation with subsequent CMP stacking. To do that we modify the well known "exploding reflectors principle" for 3D heterogeneous multiscale media by use of the finite-difference technique on the base of grids locally refined in time and space. To be able to simulate realistic models and acquisition we develop scalable parallel software, which needs reasonable computational costs. Numerical results for simulation of Common Middle Points sections and their time migration are presented and discussed.

Among extensive studies on click chemistry the inverse electron-demand Diels-Alder reaction between 1,2,4,5-tetrazine (Tz) and trans-cyclooct-2-en (TCO) has gained increasing attraction due to its exceptionally fast reaction kinetics and high selectivity for in vivo pretargeting applications including PET imaging. The facile two-step approach utilizing TCO-modified antibodies as targeting structures has not made it into clinic though as the increase in blood volume from mice to human seems to be the major limitation. This study aimed to show if the design of multimeric Tz-ligands by chelator scaffolding can improve the binding capacity and may lead to enhanced PET imaging with gallium-68. For this purpose we utilized the macrocyclic siderophore Fusarinine C (FSC) which allows to conjugate up to three Tz-residues due to three primary amines available for site specific modification. The resulting mono- di- and trimeric conjugates were radiolabelled with gallium-68 and characterized in vitro (logD, protein binding, stability, binding towards TCO modified rituximab (RTX)) and in vivo (biodistribution- and imaging studies in normal BALB/c mice using a simplified RTX-TCO tumour surrogate). The 68Ga-labelled FSC-based Tz-ligands showed suitable hydrophilicity, high stability, high targeting specificity and the binding capacity to RTX-TCO was increased by the grade of multimerization. Corresponding in vivo studies showed a multimerization typical profile but generally suitable pharmacokinetics with low accumulation in non-targeted tissue. Imaging studies in RTX-TCO tumour surrogate bearing BALB/c mice confirmed this trend and revealed improved targeting by multimerization as increased accumulation in RTX-TCO positive tissue was observed.

Microbubbles and nanobubbles can be prepared using various shells, such as phospholipids, polymers, proteins, and surfactants. They are echogenic and can be used as contrast agents for ultrasonic and photoacoustic imaging. These bubbles can be engineered in various sizes as vehicles for gas and drug delivery applications with novel properties and flexible structures. Hypoxic areas in tumors develop owing to an imbalance of oxygen supply and demand. In tumors, hypoxic regions have shown more resistance to chemotherapy, radiotherapy, and photodynamic therapies. The efficacy of photodynamic therapy depends on the availability of oxygen in the tumor to generate reactive oxygen species. Micro/nanobubbles have been shown to reverse hypoxic conditions and increase tissue oxygen levels. This review summarizes the synthesis methods and shell compositions of micro/nanobubbles and methods deployed for oxygen delivery. In addition, the shortcomings and prospects of engineering micro/nanobubbles are discussed for their potential use in photodynamic therapy.

TVs and monitors are among the most widely used displays in various environments. However, they have limitations in their physical display conditions, such as a fixed size/position and a rigid/flat space. In this paper, we suggest a new "Display In the Wild" (DIW) concept to overcome the aforementioned problems. Our proposed DIW system allows us to display a flexibly large screen on dynamic non-planar surfaces at an arbitrary display position. To implement our DIW concept practically, we choose a projector as the hardware configuration in order to a generate screen anywhere with different sizes. However, distortion occurs when the projector displays content on a surface that is dynamic and/or non-planar. Therefore, we propose a distortion correction method for DIW to overcome the aforementioned surface-constraints. Since projectors are not capture devices, we propose using a depth camera to determine the distortions on the surfaces quickly. We also propose DIW-specific calibration and fast/precise correction methods. Our calibration method is constructed to easily and quickly detect the projection surface, and also allows our proposed system to accommodate the intrinsic parameters such as a display resolution and field of view. We accomplish a fast undistortion process of the projector by considering only surface boundary pixels, which enables our method to run in real time. In our comprehensive experiments, the proposed DIW system generates undistorted screens such as TVs and monitors on dynamic non-planar surfaces at an arbitrary display position with Unmanned Aerial Vehicles (UAVs) in a fast and accurate manner, demonstrating its usefullness in practical DIW scenarios.

The crack geometry and associated strain field around Berkovich and Vickers indents on silicon have been studied by X-ray diffraction imaging and micro-Raman spectroscopy scanning. The techniques are complementary, the Raman data coming from within a few micrometers of the indentation, whereas the X-ray image probes the strain field at a distance of typically tens of micrometers. For example, Raman data provides an explanation for the central contrast feature in the X-ray images of an indent. Strain relaxation from breakout and high temperature annealing are examined and it is demonstrated that millimeter length cracks, similar to those produced by mechanical damage from misaligned handling tools, can be generated in a controlled fashion by indentation within 75 micrometers of the bevel edge of 200mm diameter wafers.

Based on research data from the renovation of old residential areas in Chengdu, China, this study provides empirical evidence regarding the causal relationship between urban renewal and the transformation of residents' pro-environmental behaviors. The research findings demonstrate a significant enhancement in residents' engagement in pro-environmental behaviors due to the renovation of old residential areas. Robustness tests based on replacement samples and two-stage difference-in-difference models also confirm the reliability of the conclusions. The preliminary mechanism test indicates that the mechanism of the impact of renovation of old residential areas on the transformation of residents' pro-environmental behaviors can be attributed to two main factors. Firstly, the improvement of environmental infrastructure provides residents with better conditions for participating in pro-environmental activities. Secondly, there is an elevation in residents' environmental protection awareness, prompting a more voluntary engagement in pro-environmental behavior. This study suggests that decision-makers should fully recognize that urban renewal activities nationwide are not only a process of improving urban hardware and functionality, but also a realistic and vivid "environmental education" course for the whole nation. Taking urban renewal as an opportunity to enhance citizens' awareness of environmental protection will effectively promote the transformation of pro-environmental behaviors among residents.

This study introduces a robust methodology utilizing Multi-Criteria Decision Analysis (MCDA) combined with the Analytic Hierarchy Process (AHP) to repurpose abandoned hydrocarbon fields for energy storage, supporting the transition to renewable energy sources. We use a geostatistical approach integrated with Python scripting to analyze reservoir parameters—including porosity, permeability, thickness, lithology, temperature, heat capacity, and thermal conductivity—from a decommissioned hydrocarbon field in Southeast Hungary. Our workflow leverages stochastic simulation data to identify potential zones for energy storage, categorizing them into high, moderate, and low suitability scenarios. This innovative approach provides rapid and precise analysis, enabling effective decision-making for energy storage implementation in depleted fields.

The effect of the melt cooling rate on the atomic ordering of austenite and, as a consequence, on the martensitic transformation of a nonstoichiometric alloy of the Ni-Mn-In system has been studied. In-situ TEM observations revealed differences in the mechanism of phase transformations of the alloy subjected to different cooling conditions. It is shown that during quenching a high density of antiphase boundaries (APB) is formed and the alloy is in the austenite-martensitic (10M and 14M) state up to a temperature of 120K. In a slowly cooled alloy, a lower APB density is observed, and a two-stage transformation L21/B2 → 10M → 14M occurs in the range of 150–120 K.

Improvement of agronomic traits in crops through gene editing (GE) relies on efficient trans-formation protocols for delivering the CRISPR/Cas9-coded transgenes. Recently, a few embryo-genesis-related genes have been described, the co-delivery of which significantly increases the transformation efficiency with reduced genotype dependency. Here we characterized the trans-genic and GE events in wheat (cv. Fielder) when transformed with the GROWTH-REGULATING FACTOR 4 (GRF4) and its cofactor GRF-INTERACTING FACTOR 1 (GIF1) chimeric gene. Trans-formation efficiency in our experiments ranged from 22% to 68%, and the editing events were faithfully propagated into the following generation. Both low and high copy number integration events were recovered in the T0 population with the various level of integrity of the left and right T-DNA borders. We also generated a population of wheat plants with ten different gRNAs targeting 30 loci in the genome. Comparison of the epigenetic profiles at the target sites and editing efficiency revealed a significant positive correlation between chromatin accessibility and muta-genesis rate. Overall, preliminary screening of the transgene quality and GE events in the T0 population of plants regenerated through the co-delivery of GRF-GIF can allow for the propagation of the best candidates for further phenotypic analysis.

In the first wave of COVID-19, up to 20% of patients had skin lesions with variable characteristics. There is no clear evidence of the involvement of the SARS-CoV-2 virus in all the cases; some of these lesions may be secondary to drug hypersensitivity. To analyze the possible cause of the skin lesions, we performed a complete allergology study on 11 patients. One year after recovery from COVID-19, we performed a lymphocyte transformation test (LTT) and Th1/Th2 cytokine secretion assays of PBMC. We included 5 nonallergic patients treated with the same drugs without lesions. Except for one patient who had an immediate reaction to azithromycin, all patients had a positive LTT to at least one of the drugs tested (azithromycin, clavulanic acid, hydroxychloroquine, lopinavir, and ritonavir). None of the nonallergic patients had a positive LTT. We found mixed Th1/Th2 cytokine secretion (IL-4, IL-5, IL-13, and IFN-γ) in patients with skin lesions corresponding to mixed drug hypersensitivity type IVa and IVb. In all cases, we identified a candidate drug as the culprit for skin lesions during SARS-CoV-2 infection, although only three patients had a positive drug challenge. Therefore, it would be reasonable to recommend avoiding the drug in question in all cases.

The coastal zone, situated at the sensitive interface between land and sea, serves as a pivotal area of extensive human economic activities. As one of China's economic special zones, Xiamen exemplifies the comprehensive trajectory of coastal governance in China. This research adopts an interdisciplinary approach grounded in historical geography and political ecology, employing data collection methods encompassing historical literature, field surveys, and interviews. The research findings indicate that:(1) The year 1994 witnessed the pivotal role played by the United Nations Convention on the Law of the Sea (UNCLOS) in connecting Jimei Peninsula from a local context to the international arena, thus signifying a momentous turning point in the process of scale reconstruction. However, the subsequent implementation of the Coastal Exclusion Policy in 2002 had detrimental consequences, leading to the disintegration of the local scale, the erosion of maritime culture, and the disregard for the livelihood security of displaced coastal populations.(2)The Coastal Exclusion Policy serves as an instrumental tool for implementing scale politics, while its functional realignment has had profound implications for the coastal zone, encompassing economic transformation, ecological degradation, and the marginalization of the socio-cultural fabric that intertwines humans and the coastal environment.

Heusler Ni-Mn-Ga alloys with martensitic transformation being multiferroic materials are touted for magneto- and multi-caloric effect (MCE) and moreover, they exhibit magnetic shape memory (MSM) phenomena. MCE benefits from high saturation magnetization and also large variability and sensitivity of transformation temperatures on alloying. In contrast, MSM phenomena are limited by low temperatures of both ferromagnetic and ferroelastic transformations. In an attempt to increase the transformation temperatures and to understand the physical fundamentals beyond transformation variations and magnetic ordering, we experimentally investigate the magnetic and transformation properties in Ni2MnGa alloyed with transitional elements spanning from Cr to Cu. These elements are consecutively substituted on Ni, Mn, and Ga sites, to establish the effect of positional substitution and elemental evolution. The elemental dependence of saturation magnetization, magnetocrystalline anisotropy, Curie temperature, and martensitic transformation temperatures are compared with (non-)stoichiometric Ni-Mn-Ga Heusler compounds. The observed behavior is complex and there are no clear trends of transformation temperatures as a function of the number of valence (non-bonding) electrons per atom, however, the saturation magnetization at 10K and Curie temperature seems to follow the Pauli-Slater curve. Obtained results can serve as useful rectification for the theoretical prediction of new Ni-Mn-Ga-X Heusler alloys.

Cancer stem cells remain a challenge to isolate and characterize because of their plastic phenotype. Using a microfluidic lab-on-a-chip based on ultra-high frequency dielectophoresis, we measured the electromagnetic signature of colorectal cancer cells and demonstrated that cancer stem cells show a distinct and lower electromagnetic signature than differentiated cells. The release of extracellular vesicles from tumor cells can drive tumor progression and metastasis development. As extracellular vesicles from cancer stem cells carry more aggressive content, we treated colorectal cancer cells with these vesicles to test whether the lab-on-a-chip can detect a change in phenotype. The electromagnetic signature of treated cells is modified in comparison to untreated cells and sometimes even when no biological change is observed. The lab-on-a-chip provides rapid and relevant result without prior labeling compared to conventional biological approaches. It could be useful in the clinic for early detection of cancer stem cells in the tumor mass and for monitoring the aggressive potential of extracellular vesicles in the bloodstream in order to adapt therapeutic management and prevent relapse.

Mine waste rock and drainage pose lasting environmental, social, and economic threats to the mining industry, regulatory agencies, and society as a whole. Mine drainage can be alkaline, neutral, moderately or extremely acidic and contains significant levels of sulfate, dissolved iron, and frequently a variety of heavy metals and metalloids, such as cadmium, lead, arsenic, and selenium. In acid neutralization by carbonate and silicate minerals, a range of secondary minerals can form and possibly scavenge these potentially harmful elements. Apart from the extensively-studied microbial-facilitated sulfide oxidation, the diverse microbial communities present in mine rock and drainage may also participate in the formation, dissolution, and transformation of secondary minerals influencing the mobilization of these metals and metalloids. This article reviews major microbial-mediated geochemical processes occurring in mine rock piles that affect drainage chemistry, with a focus on the role of microorganisms in the formation, dissolution and transformation of secondary minerals. Understanding this is crucial for developing biologically-based measures to deal with contaminant release at the source, i.e., source control.

ABSTRACT Education is the most important instrument in human life because education can increase human dignity. In addition, education can also be a benchmark for human quality and an example of the progress of a nation. The history of education in Indonesia has evolved from the colonial era to the digital era. These developments have influenced government policies in every era. In the 21st century, the development of education in Indonesia is starting to show progress. This is because it is supported by the rapid growth of information and technology. This research article aims to analyze the educational policies carried out by the government from the colonial era to the digital era to be used as evaluation material at this time so that in the future education in Indonesia is even better. To achieve this goal, this research focuses on the question of how is the transformation of education in Indonesia from the colonial era to the digital era? and what is the paradigm of education in Indonesia when viewed from a historical perspective?. The research method used is the Literature Review method from 27 sources in journal articles, websites, and data reports for 2019-2021. The results of this study found that changes in the Indonesian education system from time to time have a positive influence on the progress of the Indonesian nation. The development of education in Indonesia also has an impact on increasing the Human Development Index (HDI). This shows that the quality of Indonesian society is increasing. Based on the results obtained, it is hoped that it can provide information about the transformation of education in Indonesia from the colonial era to the digital era from a historical perspective. This article is suitable as a reference source for education observers in Indonesia to know the history of education and its policies from the colonial era to the digital era and useful for academics to know the history of education in Indonesia. This research has limitations, namely this research is only limited to the development of education in Indonesia from the colonial era to the digital era and the paradigm of education development in Indonesia from a historical perspective.

In this paper, the deformation and phase transformation of disorder α phase at (α + γ) two phase region in as-forged Ti-44Al-8Nb-(W, B, Y) alloy are investigated by hot compression and hot packed rolling. Detailed microstructural evolution demonstrates that the as-deformed microstructure is significantly affected by deformation conditions. The mircrostructure differences are mainly due to temperature drop and strain rate. The evolution of α lamelae into α grains is detailed descripted. Moreover, the disorder α lamellae can also be decomposed into some new α grains by the assisted decomposition mechanism of γ grains. Microstructure evolution model of current TiAl alloy at 1250 °C during hot rolling is built.

Digital transformation, organizational resilience, and agility are now becoming one of the keys to meeting the competitive challenges of modern organizations. It is no surprise that digital transformation and digital technologies have also begun to significantly impact the energy industry, moving towards improving the sector's profitability and efficiency. However, to navigate through the difficult process of digital transformation in today's turbulent environment, organizations, including those in the energy sector, need to build organizational resilience. Nevertheless, the nature of the relationship between digital transformation and organizational resilience has not yet been sufficiently clarified. Focusing on the level of digital transformation, and more precisely within the two dimensions of digital maturity, i.e. digital intensity and transformation management intensity, as well as based on the perspective of dynamic capabilities, this study developed a configurational framework and proposed a theoretical model to study the equifinal paths through which digital transformation and dynamic capabilities influence organizational resilience in energy sector companies. Based on a fuzzy set qualitative comparative analysis (fs/QCA) conducted on selected companies in the energy sector, i.e. Polish CHP plants, the relationship between digital transformation, dynamic capabilities and organizational resilience was investigated. The results show that a high level of organizational resilience can be achieved through two main paths based on the dominance of dynamic capabilities and the dominance of digital maturity. The study found that digital maturity can significantly influence CHP resilience. Moreover, the transformation management intensity is strongly related to high organizational resilience. The paper concludes by describing theoretical and practical implications, as well as research limitations and prospects for future research.

One of the most concerning global environmental issues is the pollution of agricultural soils by heavy metals (HMs), especially cadmium (Cd), which not only affects human health by taking Cd-containing foods but also impacts the quality of rice. The soil's nitrification and denitrification processes, coupled with the release of volatile organic compounds by plants, raise substantial concerns. The understanding of three aspects of paddy soil under conditions of heavy-metal pollution and water management is currently limited. In this review, we summarized recent literature related to the deleterious effects of Cd on both soil processes related to the N cycle and rice quality, particularly aroma, in different water management practices. Under both continuous flooding (CF) and alternate wetting and drying (AWD) conditions, cadmium (Cd) has been observed to reduce both nitrification and denitrification processes. The adverse effects are more pronounced in continuous flooding (CF) compared to alternate wetting and drying (AWD). Similarly, the alteration in rice aroma is more significant in AWD than in CF. The precise modulation of volatile organic compounds (VOCs) by Cd, remains unclear based on the available literature. Nevertheless, HM accumulation is higher in AWD conditions compared to CF, leading to a detrimental impact on volatile organic compounds (VOCs). The literature concluded that AWD practices should be avoided in Cd contaminated fields to decrease accumulation and maintain the quality of rice. In the future, rhizospheric engineering and plant biotechnology can be used to decrease the transport of HMs from the soil to the plant’s edible parts.

This article illuminates the reception and transformation of Ippen一遍(1234-1289)’s religious tenets and practices by Enju Kato加藤円住 (1919-2021) and his temple Shōjōkō-ji清浄光寺. While Enju Kato asserts that his life has been dedicated to adhering and enacting Ippen's concept of "renunci-ation," he has reinterpreted this concept based on his personal experiences and comprehension. Second, Enju Kato and Shōjōkō-ji have inherited some of Ippen's religious practices yet adapted these to align with contemporary settings. This article presents a case study discussing the ac-ceptance and transformation of doctrines and practices of jishū時宗 in contemporary era, which has been overlooked by academia thus far.

The allocation of funding for higher education typically focuses on competition in neoliberal mechanisms. Surprisingly, much less attention has been paid to considering the effect of fund locations for sustainable development through public goods purposes in neoliberal contexts. This study aims to examine specific funding schemes and determine the influential factors impacting funding for teaching, research, and public goods transformation. Taking Taiwan's Higher Education Sprout Project (HESP) as an example, we explored the effect of policy initiatives on public goods transformation towards sustainable development. The data were collected from the Ministry of Education and Scopus databases. First, a regression analysis was conducted to determine which factors influence the effect of funding allocations in academic institutes. Second, we used logistic regression to detect the effects of the system and the sector. Third, we used partial least square structural equation modeling (PLS-SEM) to explore the causal effects among the selected impact variables on expected outcomes. Finally, we used the bootstrap method to demonstrate the model’s robustness. Our study found that only diversity was shown in private technology groups receiving less HESP funding. At the same time, it did not widen the differences in the sector and system in the transformation process. Our findings suggest that funding allocations will not affect teaching and research based on sectors and systems. In contrast, this study demonstrates that transforming public goods through special funding can play a critical role in leading sustainable development in higher education.

In the next decade, further digitalisation of the entire wind energy project lifecycle is expected to be a major driver for reducing project costs and risks. In this paper, a literature review on the challenges related to implementation of digitalisation in the wind energy industry is first carried out, showing that there is a strong need for new solutions that enable co-innovation within and between organisations. Therefore, a new collaboration method called the WeDoWind Ecosystem is developed and demonstrated. The method is centred around specific "challenges", which are defined by "challenge providers" within a topical "space" and made available to participants via a digital platform. The data required in order to solve a particular "challenge" is provided by the "challenge providers" under the confidentiality conditions they specify. The method is demonstrated via a case study, the EDP Wind Turbine Fault Detection Challenge. Six submitted solutions using diverse approaches are evaluated. Two of the methods perform significantly better than EDP’s existing method in terms of Total Prediction Costs (saving up to €120,000). The WeDoWind Ecosystem is found to be a promising solution for enabling co-innovation in wind energy, providing a number of tangible benefits for both challenge and solution providers.

Based on electromagnetic heat transfer and metal phase transformation co-simulations, we modeled an AISI 1045 specimen under high-frequency heat treatment. Hardening zone predictions were confirmed through cooling and metal phase transformation simulations after obtaining the results from electromagnetic heat transfer simulations. The cooling process was modeled by applying the cooling coefficient of the cooling water in the same way as the actual heat-treatment process. To obtain the current flowing through the coil during high-frequency induction heating, the voltage was measured and applied using the resistance–inductance–capacitance circuit calculation method. Experimental and simulated results of the heating temperature and curing depth of an AISI 1045 specimen with a carbon content of 0.45% were compared; the comparison indicated good agreement between the two. Using the simulation results, we established a method for obtaining the current flowing through the induction coil for predicting the extent and depth of the hardening zone during high-frequency induction heat treatment.

Efficient oxygen evolution reaction (OER) electrocatalysts are highly desired in the field of water electrolysis and rechargeable metal-air batteries. In this study, a chelate polymer, composed of copper (II) and dithiooxamide, was used to derive an efficient catalytic system for OER. Upon potential sweep in 1M KOH, copper (II) centers of the chelate polymer were transformed to CuO and Cu(OH)2. The carbon-dispersed CuO nanostructures formed a nanocomposite which exhibits an enhanced catalytic activity for OER in alkaline media. The nanocomposite catalyst has overpotential of 280 mV (at 1 mA/cm2) and a Tafel slope of 81 mV/dec in 1M KOH solution. It has a seven-fold higher current than IrO2/C electrode, per metal loading. A catalytic cycle is proposed, in which, CuO undergoes electrooxidation to Cu2O3 that further decomposes to CuO with releasing oxygen. This work reveals a new method to produce an active nanocomposite catalyst for OER in alkaline media using a non-noble metal chelate polymer and a porous carbon. This method can be applied to the synthesis of transition metal oxide nanoparticles used in the preparation of composite electrodes for water electrolyzers and can be used to derive cathode materials for aqueous-type metal-air batteries.

Background and Objective: To examine the effect of ordered subset expectation maximization (OSEM) parameters on the quantitative image quality of cardiac SPECT images in two different frequently used SPECT cameras and determine the optimal settings for producing images of best diagnostic quality. Another objective was to assess if different cameras produced a significant change in optimal parameters and levels of detectability. Methods: The optimization of OSEM iterative reconstruction algorithm was carried out by comparing image quality metrics, namely, contrast-to-noise ratio (CNR) and defect contrast across 12 OSEM subset-iteration combinations to find the best choice for cardiac perfusion SPECT images. Eight frames were reconstructed using the SIMIND Monte Carlo Simulation package. An activity of 370 MBq (10mCi) and projection acquisition interval of 20 seconds per projection were used. Attenuation (AC) and scatter corrections (SC) were performed in this study for all images. Results: The 16-2 subset-iteration combination yielded the highest CNR and defect contrast values for both cameras. The difference between CNR values for two cameras was found to be around 5% only. Conclusions: Monte Carlo simulations can be useful to investigate how quantitative image quality behaves with respect to reconstruction parameters and correction algorithms in a controlled environment. The found optimum is similar to values reported in previous findings. In this study, the use of different camera brands did not affect the optimum. The quantitative detectability measures were also very similar.

Abstract: Imaging of low (LGG) to high (HGG) grade gliomas is conventionally performed with MRI, which is the non-invasive gold-standard imaging modality to derive data. Gliomas (Grade 1,2,3,4) are lethal and demonstate poor outcomes despite novel therapies. Integrins compose of heterodimeric parasympathetic nervous system; the aVb3 (RGD i.e. Galacto-Arginine-Glycine-Aspartic acid) have been displayed as a potential biomarker that can be imaged via PET in order to trace the angiogenetic pathway. Gliomas are common primary central nervous system (CNS) tumours which are often pose a diagnostic challenge, even to stage and manage because of their heterogeneity in molecular aberrations. Several core mutational core hallmarks of gliomas are inducing/accessing vasculature, tumour promoting inflamation, polymorphic microbes and avoiding/resisting cell death; these ultimately lead to poor prognosis. In 2007, the classification of diffuse gliomas was based on the histopathology and subtype e.g. Pilocytic astrocytoma and low cell proliferation, in 2016, the classification of diffuse gliomas was based on the IDH status, 1p/19q codeletion, subtype and grade; then in 2021, the IDH status (wild-type or mutant), molecular profile, subtype and grade were added in order to improve the classification of diffuse gliomas. Imaging (MRI) techniques progress stalled despite the imperfections in MRI e.g distinguishing RN (radionecrosis) and PsP (Pseudoprogression) hence the exploration of PET probes that detect important hallmarks of gliomas e.g. techniques such as [68Ga]68Ga-RGD positron emission tomography (PET) to be utilised to assess vasculature. This case report aimed to determine the potential clinical utility of molecular imaging with 68Ga-RGD PET used in complementary to traditional MRI techniques.

Mitral regurgitation (MR) is a broadly diffuse valvular heart disease (VHD) with a significant impact on healthcare system and patient’s prognosis. Transcatheter mitral valve interventions (TMVI) are now well-established techniques included in the therapeutic armamentarium for managing patients with mitral regurgitation, either primary or functional MR. Even if guidelines give indications regarding the correct management of this VHD, the wide heterogeneity of patient’s clinical background, valvular and heart’s anatomy make each patient a unique case, in which the appropriate device’s selection requires a multimodality imaging evaluation and a multidisciplinary discussion. Proper pre-procedural evaluation plays a pivotal role to judge the feasibility of TMVI, as well as a cooperative works between imagers and interventionalist is crucial for procedural success. This manuscript aims to provide an exhaustive overview of the main parameters that need to be evaluated for appropriate device selection, pre-procedural planning, intraprocedural guidance and post-operative assessment in the setting of TMVI. In addition, it tries to give some insights about next perspective of structural cardiovascular imaging.

Background: Online survey-based observational cross-sectional study aimed at elucidating experience and attitudes of unstructured population regarding diagnostic imaging. Methods: Invitations to participate were distributed using mixed-mode design to deidentified residents aged 18 years and older. Main outcome measures included morbidity structure and incidence of diagnostic imaging administrations. Results: Respondents (n = 1069) aged 44.3 ± 14.4 years; 32.8% suffered from cardiovascular diseases (CVD); 9.5% had chronic respiratory pathology; 28.9% considered themselves healthy. Respondents with COVID-19 history (49.7%) reported higher rates of computed tomography (CT) (p &lt; .0001), magnetic resonance imaging (MRI) (p &lt; .001), and ultrasound (p &lt; .05). COVID-19 history in CVD respondents shifted imaging administrations towards CT and MRI (p &lt; .05). Every tenth respondent received MRI, CT, and ultrasound on paid basis; 29.0% could not pay for diagnostic procedures; 13.1% reported unavailable MRI. Professional status significantly affected the pattern of diagnostic modalities (p &lt; .05). MRI and CT availability differed between respondents in urban and rural areas (p &lt; .0001). History of technogenic events predisposed responders to overestimate diagnostic value of fluorography (p &lt; .05). Conclusions: Preparedness to future pandemics requires development of community-based outreach programs focusing on people's awareness regarding medical imaging safety and diagnostic value.

Introduction: Contrast-enhanced spectral mammography (CESM) is a novel technique employed in breast cancer screening and detection. In this systematic review, we aim to compare the diagnostic performance of CESM with magnetic resonance imaging (MRI) in the context of breast cancer diagnosis. Material and Method: We have searched for paper in Pubmed and Scopus from July 2023 to February 2024, finding 256 suitable papers according to our selection criteria (perspective or retrospective studies, women diagnosed with breast cancer, comparison of Contrast-enhanced Spectral Mammography and Magnetic Resonance Imaging, sensitivity and specificity metrics provided). Every paper was then checked for quality using the QUADAS 2 assesement score. Sensibility, specificity, Positive Predictive Value (PPV), Negative Predictive Value (NPV) and accuracy were recorded. Results: 15 studies were selected for analysis. CESM demonstrated comparable sensitivity to MRI, with values ranging from 36.4% to 100% for CESM and 0% to 100% for MRI. Specificity varied between the modalities, with CESM showing specificity ranges of 17% to 100% compared to 23% to 92.31% for MRI. Discussion and Conclusion: CESM has comparable diagnostic validity to MRI, and is a valuable tool in detecting breast cancer.

The orbitofrontal cortex (OFC) area plays a critical role in human brain functions. However, susceptibility differences between paranasal sinuses and nasal cavity tissues often cause local field variations in the OFC during MRI, resulting in image distortions and signal loss. In this paper, we introduce a subject-friendly neck passive shim solution aimed at enhancing field homogeneity in the brain, specifically in the OFC region. Utilizing 3D gradient-echo pulse sequences, main magnetic field (B0) maps of four subjects’ brains were acquired at 4T MRI. Subsequently, these maps were decomposed into spherical harmonic coefficients and averaged. Optimal positions for placing shim elements on a semi-cylindrical surface, positioned slightly above the neck and below the chin, were computed. The findings indicate a substantial enhancement in B0 homogeneity, particularly within the OFC region, through the integration of this semi-cylindrical passive shim system in conjunction with first and second-order active shimming.

Pyridoxine is a versatile molecule that forms part of the family of B vitamins. It is used to treat and prevent vitamin B6 deficiency and certain type of metabolic disorders. Besides, pyridoxine molecule has been investigated as a suitable ligand toward metal ions. Nevertheless, the study of the magnetic properties of metal complexes containing lanthanide(III) ions and this biomolecule has been unexplored. We have synthesized and characterized a novel pyridoxine-based GdIII complex of formula [Gd(III)(pyr)2(H2O)4]Cl3 • 2 H2O (1) [pyr = pyridoxine]. 1 crystallizes in the triclinic system with space group Pī. In its crystal packing, the cationic [Gd(pyr)2(H2O)4]3+ entities are linked each other through H-bonding interactions involving non-coordinating water molecules and chloride anions. In addition, Hirshfeld surfaces of 1 were calculated to further investigate their intermolecular interactions in the crystal lattice. The study of the magnetic properties of 1 through ac magnetic susceptibility measurements reveals the occurrence of slow relaxation of magnetization in this mononuclear Gd(III) complex, this fact indicating an unusual single-ion magnet (SIM) behavior. We have also studied the relaxometric properties of 1, as a potential contrast agent for high-field MR imaging, from solutions of 1 prepared in physiological serum (0.0 - 3.2 mM range) and measured at 3 T on a clinical MR scanner. The relaxivity values obtained for 1 are larger than those of some commercial MR imaging contrast agents based on mononuclear Gd(III) systems

We are currently investigating the ultrasound imaging of a sensor consisting of a randomized encoding mask attached to a single lead zirconate titanate (PZT) oscillator for use in a puncture microscope. The proposed model was performed using a finite element method (FEM) simulator. To increase the number of measurements required by a single element system, the transducer was rotated at different angles. The image was constructed by solving a linear equation of the image model. In a previous study, the image resolution was improved by extracting phase information. In this study, we propose a strategy by integrating the weighted frequency subbands compound and a super resolution method (SCM) to improve the resolution in range and lateral resolution. We also evaluated the image performance by applying different methods to improve the image quality. The results show that better image resolution and speckle suppression were obtained by applying the proposed method.

Background: Appendicitis is a common cause of emergency department visits and appendectomies in the US, with 250,000 appendectomies performed annually. Current diagnostic methods, such as clinical findings, lead to inaccuracies and missed diagnoses, increasing morbidity and mortality. The only solution is surgery, but current hematological tests are not reliable and may lead to unnecessary surgery if the underlying etiology is self-limiting or requires medical treatment. This study explores the role of MRI as a diagnostic modality that can replace US/CT and supplement traditional clinical diagnostic signs while avoiding ionizing radiation and intravenous contrast medium. The purpose of this meta-analysis is to determine the accuracy of MRI as a diagnostic modality in diagnosing appendicitis, addressing concerns about diagnostic modalities and their adverse effects, and addressing the necessity and success of relevant interventions. Methods: Medical literature was comprehensively searched and reviewed without restrictions to particular study designs, or publication dates using PubMed, Cochrane Library, and Google Scholar databases for all relevant literature formulated in English. The extraction of necessary data proceeded after specific inclusion and exclusion criteria were applied. Meta Analysis was performed for 5206 patients, with 35 RCTs being selected. Analysis was done using the QualSyst tool, wherein two writers independently assessed the caliber of each study as well as the use of the Cochrane tool for bias risk apprehension. The statistical software packages RevMan (Review Manager, version 5.3), SPSS (Statistical Package for the Social Sciences, version 20), and Excel in Stata 14 were used to perform the statistical analyses along with other analytical software. Results: MRI had an overall sensitivity of over 95%, an overall specificity of 94.2% with a PPV of 0.875 in comparison to CT scan in the diagnosis and intervention regarding appendicitis. Conclusion: These findings strongly suggest that MRI is a reasonable alternative to CT for the diagnosis of appendicitis in hospitals with appropriate access to this technology for reasons about accuracy, reliability, and reproducibility as well as addressing safety concerns.

Inflammation involves the activation of innate immune cells and is believed to play an important role in the development and progression of both infectious and non-infectious diseases such as neurodegeneration, rheumatoid arthritis or cancer. Inflammation in the brain is marked by the upregulation of the translocator protein (TSPO) in microglia. Moreover, high TSPO levels are found, for example in macrophages during rheumatoid arthritis and in malignant tumor cells compared to its relatively low physiological expression. The same applies for cycloxygenase-2 (COX-2), which is constitutively expressed in the kidney, brain, thymus and gastrointestinal tract, but induced in microglia, macrophages and synoviocytes during inflammation. This puts TSPO and COX-2 in the spotlight as important targets for the diagnosis of inflammation. Imaging modalities, such as positron emission tomography and single-photon emission tomography, can be used to localize inflammatory processes and to track their progression over time. They could also enable to monitor the efficacy of therapy and predict its outcome. This review focuses on the current development of PET and SPECT tracers not only for the detection of neuroinflammation, but also for emerging diagnostic measures in infectious and other non-infectious diseases like rheumatic arthritis, cancer, cardiac inflammation and in lung diseases.

Backround Cochlear implant is the first approved cranial nerve stimulator that works by directly stimulating the cochlear nerve. Various attempts have been made to evaluate the dimensions of the cochlea related to cochlear implantationThe preoperative computed tomographic examination is essential in assessing the anatomical aspect of the cochlea, but also in determining its dimensions, in order to choose an appropriate electrode, in order to obtain the best possible audiological performance. Method In the present paper, we aimed to carry out an observational study, regarding the role of cochlear measurements in the preoperative evaluation of patients proposed for cochlear implant. The purpose of the study was to measure the cochlea and to establish the existence of a correlation between the size of the cochlea and the age and gender of the patients. Results From the group of 35 examined patients, 54% (n= 19) were male and 46% (n=16) female. The average length of the cochlea in the age group 0-4 years is 7.82 mm in the left ear and 7.86 in the right ear, in the age group 4-7 years it is 7.82 mm and 7.94 mm respectively, for the age group 7-14 years the dimensions increase to 8.48 and 8.77 mm respectively, and after 14 years these dimensions reach 9.12, respectively 9.18 mm. Comparative measurements of the length of the cochlea by age groups show an increase in length with the patient's age, but this increase does not exceed 1.5 mm for both the right and left ears. The measurements of the width of the cochlea, by age group, start from 6.84 mm left ear and 6.81 mm right ear at 0-4 years, 6.94 mm and respective 6.97 mm at the group 4-7 years, 7.71 mm and respective 7.55 mm at 7-14 years , and reaching 8.19 mmm and 8.12 mm at the age of over 14 years. Conclusions From the study carried out it can be concluded that the evaluation of the dimensions of the cochlea is important for cochlear implantation, the size variables, although small, are still an element to be considered in correlation with the age of the patient and the implanted ear. This increase is statistically insignificant, but it still exists, even if from a theoretical point of view, it is considered that the dimensions of the cochlea remain constant.

The Atlantic puffin is a medium-sized seabird with black and white plumage and orange feet. It is distributed mainly along the northern Atlantic Ocean and due, among other reasons, to human activities, it is in a threatened situation and classified as a vulnerable species according to the International Union of Conservation of Nature (IUCN). In this study, we used a total of 20 carcasses of juvenile Atlantic puffins to perform anatomical cross sections and magnetic resonance images. Thus, an adequate description of the head was made, providing valuable information that could be helpful as a diagnostic tool for veterinary clinicians, who increasingly treat these birds in zoos, rehabilitation centers and even in the wild.

Hypoxic-ischemic encephalopathy (HIE) secondary to perinatal asphyxia occurs when the brain does not receive enough oxygen and blood. A surrogate marker for ‘intact survival’ is necessary for the successful management of HIE. The severity of HIE can be classified based on clinical presentation, including presence of seizures, using a clinical classification scale called Sarnat staging; however, Sarnat staging is subjective and the score changes over time. Furthermore, seizures are difficult to detect clinically and are associated with a poor prognosis. Therefore, a tool for continuous monitoring on the cot side is necessary, for example, electroencephalogram (EEG) that non-invasively measures the electrical activity of the brain from the scalp. Then, multimodal brain imaging, when combined with functional near-infrared spectroscopy (fNIRS), can capture the neurovascular coupling (NVC) status. In this study, we first tested the feasibility of a low-cost EEG-fNIRS imaging system to differentiate between normal, hypoxic, and ictal states in a perinatal ovine hypoxia model. Here, the objective was to evaluate a portable cot side device and autoregressive (ARX) modelling to capture the perinatal ovine brain states during a simulated HIE injury. So, ARX parameters were tested with a linear classifier using a single differential channel EEG, with varying states of tissue oxygenation detected using fNIRS, to label simulated HIE states in a perinatal ovine hypoxia model. Then, we showed the technical feasibility of the low-cost EEG-fNIRS device and ARX modeling with support vector machine classification for a human HIE case series with and without sepsis. The classifier trained with the ovine hypoxia data labelled ten severe HIE human cases (with and without sepsis) as “hypoxia” group and the four moderate HIE human cases as the “control” group. Furthermore, we showed the feasibility of experimental modal analysis (EMA) based on the ARX model to investigate the NVC dynamics using EEG-fNIRS joint-imaging data that differentiated six severe HIE human cases without sepsis from four severe HIE human cases with sepsis. In conclusion, our study showed the technical feasibility of EEG-fNIRS imaging, ARX modeling of NVC for HIE classification, and EMA that may provide a biomarker to detect sepsis effects on the NVC in HIE.

Insulator defect detection is of great significance to compromise the stability of the power transmission line. The state-of-the-art network of object detection, YOLOv5, has been widely used on insulator and defect detection. However, YOLOv5 network has some limitations like poor detection rate and high computational loads in detecting small insulator defects. To solve these problems, we proposed a light-weight network for insulator and defect detection. In this network, we introduced Ghost module into YOLOv5 backbone and neck to reduce the parameters and model size to enhance the performance in unmanned aerial vehicles (UAVs). Besides, we added small object detection anchors and layers for small defect detection. In addition, we optimized the backbone of YOLOv5 by applying convolutional block attention module (CBAM) to focus on critical information for insulator and defect detection and suppress uncritical information. The experiment result shows the mean average precision (mAP) 0.5 and the mAP0.5:0.95 of our model can reach 99.4% and 91.7%, the parameters and model weight are reduced to 3807372 and 8.79M, which can easily deploy to embedded devices like UAVs. And the speed of detection can reach 10.9ms/image, which can meet the real-time detection requirement.

Breast cancer is among the most common and fatal diseases for women, and no permanent treatment has been discovered. Thus, early detection is a crucial step to control and cure breast cancer that can save the lives of millions of women. For example, in 2020, more than 65% of breast cancer patients were diagnosed in early-stage of cancer, from whom all survived cancer. Although early detection is the most effective approach for cancer treatment, breast cancer screening conducted by radiologists is very expensive and time-consuming. More importantly, conventional methods of analyzing breast cancer images suffer from high false detection rates. Different breast cancer imaging modalities are used to extract and analyze the key features affecting diagnosis and treatment of breast cancer. These imaging modalities can be divided into subgroups such as mammograms, ultrasound, magnetic resonance imaging, histopathological images, or any combination of them. Radiologists or pathologists analyze images produced by these methods manually that leads to increase the risk of wrong decisions for cancer detection. Thus, utilization of new automatic methods to analyze all kinds of breast screening images to assist radiologists to interpret images is required. Recently, artificial intelligence (AI) has been widely utilized to automatically improve the early detection and treatment of different types of cancer, specifically breast cancer, thereby enhancing the survival chance of patients. Advances in AI algorithms, such as deep learning, and availability of datasets obtained from various imaging modalities have opened an opportunity to surpass limitations of current breast cancer analysis methods. In this article, we first review breast cancer imaging modalities, and their strengths and limitations. Then, we explore and summarize the most recent studies that employed AI in breast cancer detection using various breast imaging modalities. In addition, we report available datasets on the breast cancer imaging modalities which are important in developing AI-based algorithms and training deep learning models. In conclusion, this review paper tries to provide a comprehensive resource to help researchers working in breast cancer imaging analysis.

In this paper, we present a method for detecting and quantifying pathogens in water samples. The method proposes a portable dark field imaging and analysis system for quantifying E. coli concentrations in water after being labeled with magnetic particles. The system utilizes the tracking of moving micro/nano objects close to or below the optical resolution limit confined in small sample volumes (~ 10 µl). In particular, the system analyzes the effect of volumetric changes due to bacteria conjugation to magnetic microparticles (MP) on their Brownian motion while being suspended in liquid buffer solution. The method allows for a simple inexpensive implementation and the possibility to be used as point-of-need testing system. Indeed, a work-ing prototype is demonstrated with the capacity of quantifying E. coli colony forming units (CFU) at a range of 1x10³ - 6x10³ CFU/mL.

The paramagnetic gadolinium(III) ion is used as contrast agent in magnetic resonance (MR) imaging to improve the lesion detection and characterization. It generates a signal by changing the relaxivity of protons from associated water molecules and creates a clearer physical distinction between the molecule and the surrounding tissues. New gadolinium-based contrast agents displaying larger relaxivity values and specifically targeted might provide higher resolution and better functional images. We have synthesized the gadolinium(III) complex of formula [Gd(thy)2(H2O)6](ClO4)3·2H2O (1) [thy = 5-methyl-1H-pyrimidine-2,4-dione or thymine], which is the first reported compound based on gadolinium and thymine nucleobase. 1 has been characterized through vis-IR, SEM-EDAX and single-crystal X-ray diffraction techniques, and its magnetic and relaxometric properties have been investigated by means of SQUID magnetometer and MR imaging phantom studies, respectively. On the basis of its high relaxivity values, this gadolinium(III) complex can be considered a suitable candidate for contrast enhanced magnetic resonance imaging.

Lanthanide-doped upconversion nanoparticles (UCNPs) are promising bioimaging nanoprobes due to their excellent photostability. As one of the most commonly-used lanthanide activators, Tm3+ ions have perfect ladder-type electron configuration and can be directly excited by bio-friendly near-infrared-II (NIR-II) wavelengths. Here, the emission characteristics of Tm3+-doped nanoparticles under laser excitations of different near-infrared-II wavelengths were systematically investigated. The 1064 nm, 1150 nm and 1208 nm lasers are proposed to be three excitation strategies with different response spectra of Tm3+ ions. Particularly we found that 1150 nm laser excitation enables intense three-photon 475 nm emission, which is nearly 100 times stronger than that excited by 1064 nm excitation. We further optimized the luminescence brightness after investigating the luminescence quenching mechanism of bare NaYF4:Tm (1.75%) core. After growing inert shell, ten-fold increase of emission intensity was achieved. Combining the advantages of NIR-II wavelength and the higher-order nonlinear excitation, a promising facile excitation strategy was developed for the application of thulium-doped upconversion nanoparticles in single nanoparticle imaging and cancer cell microscopic imaging.

Atrophy quantification is fundamental for understanding brain development and diagnosing and monitoring brain diseases. FSL-SIENA is a well-known fully-automated method that has been widely used in brain magnetic resonance imaging studies. However, intensity variations arising during image acquisition that may compromise evaluation, analysis and even diagnosis. In this work, we study whether intensity standardisation can improve longitudinal atrophy quantification. We considered seven methods comprising z-score, fuzzy c-means, Gaussian mixture model, kernel density, histogram matching, white stripe, and removal of artificial voxel effects by linear regression (RAVEL). We used a total of 330 scans from two publicly-available datasets, ADNI and OASIS. In scan-rescan assessments, that measures robustness to subtle imaging variations, intensity standardisation did not compromise the robustness of FSL-SIENA significantly (p>0.1). In power analysis assessments, that measures the ability to discern between two groups of subjects, three methods led to consistent improvements in both datasets with respect to the original: fuzzy c-means, Gaussian mixture model, and kernel density estimation. Reduction in sample size using these three methods ranged from 17% to 95%. The performance of the other four methods was affected by spatial normalisation, skull stripping errors, presence of periventricular white matter hyperintensities, or tissue proportion variations over time. Our work evinces the relevance of appropriate intensity standardisation in longitudinal cerebral atrophy assessments using FSL-SIENA.

Background: The liver is involved in disseminated tuberculosis in more than 80% of the cases while primary liver involvement is rare, representing < 1% of all cases. Hepatic tuberculosis (TB) can be treated by conventional anti-TB therapy, however, diagnosing this disease still remains a challenge. The diagnosis might be particularly difficult in patients with a single liver lesion that could be misdiagnosed as a tumor or other focal liver lesions. While computed tomography and magnetic resonance imaging findings have been described, there is a paucity of literature on contrast-enhanced ultrasound (CEUS) features of hepatic TB. Case Summary: herein, we describe a case of a patient with tuberculous lymphadenopathy and chronic HCV-related liver disease who developed a single macronodular hepatic TB lesion. Due to the finding of a hepatocellular carcinoma (HCC) highly suggestive CEUS pattern, specifically a LR5 category according to the Liver Imaging Reporting and Data System (LI-RADS), and a good response to antitubercular therapy, a non-invasive diagnosis of HCC was made, and the patient underwent liver resection. We also review the published literature on imaging features of hepatic TB and discuss the diagnostic challenge represented by hepatic TB when occurs as a single focal liver lesion. Conclusions: this report shows for the first time that CEUS pattern of hepatic TB might be misinterpreted as HCC and specific imaging features are lacking. Personal history and epidemiological data are mandatory in interpreting CEUS findings of a focal liver lesion even when the imaging pattern is highly suggestive of HCC.

People counting applications have been used in diverse applications. The ability and accuracy of thermal imaging over conventional image cameras has led to the implementation of thermal cameras in people counting applications. This paper present a thermal people counting smart glass windows. The people counting application would be remotely monitored from a single centralized PC station as it’s connected to a multiplex of mass monitoring of 20 thermal camera, all embedded into different glass windows. The thermal cameras would then be able to detect body temperatures of all individuals who pass through any of the camera range and also count the numbers of people who passed through the camera range. The data gotten can then be further utilized in various ways, example is in the control of air conditioning and lightening.

Electron Channeling Contrast Imaging (ECCI) is becoming a powerful tool in Materials Science for characterizing deformation defects. Dislocations observed by ECCI in Scanning Electron Microscope, exhibit several features depending on the crystal orientation relative to the incident beam (white/black line on a dark/bright background). In order to bring new insights concerning these contrasts, we report an original theoretical approach based on the dynamical diffraction theory. Our calculations led, for the first time, to an explicit formulation of the backscattered intensity as a function of various physical and practical parameters governing the experiment. Intensity profiles are modeled for dislocations parallel to the sample surface for different channeling conditions. All theoretical predictions are consistent with experimental results.

Electron Beam Melting (EBM) is an increasingly used Additive Manufacturing (AM) technique employed by many industrial sectors, including the medical device and aerospace industries. The application of this technology is, however, challenged by the lack of process monitoring and control system that underpins process repeatability and part quality reproducibility. An electronic imaging system prototype has been developed to serve as an EBM monitoring technique, the capabilities of which have been verified at room temperature and at 320+10°C. Nevertheless, in order to fully assess the applicability of this technique, the image quality needs to be investigated at a range of elevated temperatures to fully understand the influence of thermal noise due to heat. In this paper, electronic imaging pilot trials at elevated temperatures, ranging from room temperature to , were carried out. Image quality measure Q of the digital electron images was evaluated, and the influence of temperature was investigated. In this study, raw electronic images generated at higher temperatures had greater Q values, i.e. better global image quality. It has been demonstrated that, for temperatures between , the influence of temperature on electronic image quality was not adversely affecting the visual clarity of image features. It is envisaged that the prototype has significant potential to contribute to in-process EBM monitoring in many manufacturing sectors.

This paper reports on the production and mechanical properties of Ti6Al4V micro-lattice structures, with strut thickness nearing the single-track width of the laser-based powder bed fusion (LPBF) system used. Besides providing new information on the mechanical properties and manufacturability of such thin-strut lattices, this paper also reports on the in-situ deformation imaging of micro-lattice structures with 6 unit cells in every direction. LPBF lattices are of interest for medical implants, due to the possibility of creating structures with an elastic modulus close to that of the bones and small pore sizes which allow effective osseointegration. In this work four different cubes were produced by laser powder bed fusion and subsequently analyzed using microCT, compression testing and one selected lattice was subjected to in-situ microCT imaging during compression. The in-situ imaging was performed at 4 steps during yielding. The results indicate that mechanical performance (elastic modulus and strength) correlate well with actual density and that this performance is remarkably good, despite the high roughness and irregularity of the struts at this scale. In-situ yielding is visually illustrated.

Here, we present a staged approach for an innovative repurposing of a portable infant humidicrib into a live cell growth, observation, and imaging system. Furthmore, humidicrib can support different variations of “umbilical” bioreactors, and can be used to conduct electrophysiology experiments and in situ immunohistochemistry. Modifications incorporate a closed loop carbon dioxide (CO₂) concentration control system with umbilical CO₂ and heating support for tailored bioreactors. The repurposing cost is inexpensive and allows for the continued observation and imaging of cells. This prototype unit has been used to continuously observe and image live primary neurons for up to 21 days. This demonstrates the repurposed units’ suitability for use in tissue culture based research, particularly where modifications to microscopes are required or where sensitive manipulation outside of a standard incubator is needed.

Digital infrastructure is the basic guarantee for digital transformation, it is of practical significance to discuss how to effectively use digital infrastructure construction to promote the digital transformation of tourism enterprises. This paper examines the impact of digital infrastructure construction on tourism enterprises based on the "Broadband China" policy as a quasi-natural experiment. A-share tourism listed enterprises from 2010 to 2021 are studied using the double difference method. Findings indicate that digital infrastructure construction positively and significantly influences the digital transformation of tourism enterprises, driven by digital leadership and innovation capabilities. State-owned, small-scale, and high-growth tourism enterprises benefit more from this transformation. The results suggested that the state should develop differentiated digital infrastructure plans based on the specific conditions of different tourism enterprises. Additionally, tourism enterprises should enhance digital leadership and innovation capabilities through strategic changes and digital applications to amplify the impact of digital infrastructure on their transformation.

Ostreococcus tauri is a simple unicellular green alga representing an ecologically important group of phytoplankton in oceans worldwide. Modern molecular techniques must be developed in order to understand the mechanisms that permit adaptation of microalgae to their environment. We present for the first time in O. tauri a detailed characterization of individual genomic integration events of foreign DNA of plasmid origin after PEG-mediated transformation. Vector integration appears to be random, occurring mainly at a single locus, and thus confirming the utility of this technique for insertional mutagenesis. While the mechanism of double-stranded DNA repair in the O. tauri model remains to be elucidated, we clearly demonstrate by genome resequencing that the integration of the vector leads to frequent structural variations (deletions/insertions and duplications) and some chromosomal rearrangements in the genome at the insertion loci, and often within the vector sequence itself. From these observations, we speculate that a non-homologous end joining-like mechanism is required during random insertion events, as described in plants and other freshwater algal models. PEG-mediated transformation is therefore a promising molecular biology tool, not only for functional genomic studies, but also for biotechnological research in ecologically important marine algae.

In order to study the crystallinity of different density polyethylenes, the experimental study on the transformation of the conductance mechanism under high electric field was carried out. The X-ray Diffraction(XRD), Different Scanning Calorimeter(DSC), Direct Current(DC) breakdown of Low-density polyethylene(LDPE), Linear low density polyethylene(LLDPE), Medium density polyethylene(MDPE) and High-density polyethylene(HDPE) and the electric field of 5-200kV/mm were tested. Conductivity characteristics experiments, in addition, using the mathematical formula of a variety of conductance mechanisms, the electric field-current density curves of the four kinds of polyethylene were fitted to analyze the conductance transition of the above four kinds of polyethylene in non-ohmic regions under different high field strengths. mechanism. The experimental results show that as the density of polyethylene increases, the crystallinity increases continuously, and the continuous increase of crystallinity causes the electric conduction flow under the same field strength to decrease significantly. The field strength corresponding to the two turning points in the conductance characteristic curve increases simultaneously. Large, the breakdown field strength increases; through analysis, it is found that in the high field, as the electric field increases, the conductance mechanism develops from the ohmic conductance of the low field strength region to the bulk effect of the high field strength region (Poole-Frenkel). Then the electrode effect to the high field strength (Schottky), and the threshold field strength of this conductance mechanism transition increases with the increase of crystallinity.

In strawberry cultivation, precise disease management is crucial for maximizing yields and reducing unnecessary fungicide use. Traditional methods for measuring Leaf Wetness Duration (LWD), a critical factor in assessing the risk of fungal diseases such as botrytis fruit rot and anthracnose, have been reliant on sensors with known limitations in accuracy and reliability and difficulties with calibrating. To overcome these limitations, this study introduced an innovative algorithm for leaf wetness detection systems employing high-resolution imaging and deep learning technologies, including convolutional neural networks (CNNs). Implemented at the University of Florida's Plant Science Research and Education Unit (PSREU) in Citra, Florida, USA and expanded to three additional locations across Florida, USA, the system captured and analyzed images of a reference plate to accurately determine the wetness and, consequently, the LWD. The comparison of system outputs with manual observations across diverse environmental conditions demonstrated the enhanced accuracy and reliability of the artificial intelligence-driven approach. By integrating this system into the Strawberry Advisory System (SAS), this study provided an efficient solution to improve disease risk assessment and fungicide application strategies, promising significant economic benefits and sustainability advances in strawberry production.

In this multicenter, retrospective study we evaluated the added value of magnetic resonance dispersion imaging (MRDI) to standard multiparametric MRI (mpMRI) for PCa detection. The study included 76 patients - 51 with clinically significant prostate cancer (csPCa), who underwent radical prostatectomy and had an mpMRI including dynamic contrast enhanced-MRI. Two radiologists performed three separate randomized scorings based on mpMRI, MRDI and mpMRI+MRDI. Radical prostatectomy histopathology was used as the reference standard. Imaging and histopathology were both scored according to the Prostate Imaging-Reporting and Data System V2.0 sector map. Sensitivity and specificity for PCa detection were evaluated for mpMRI, MRDI and mpMRI+MRDI. Inter- and intra-observer variability for both radiologists were evaluated using Cohen’s Kappa. On a per patient level, sensitivity for csPCa for radiologist 1 (R1) for mpMRI, MRDI and mpMRI+MRDI were 0.94, 0.82 and 0.94, respectively. For the second radiologist (R2) these were 0.78, 0.94 and 0.96. R1 detected 4% additional csPCa cases using MRDI compared to mpMRI and R2 detected 20% extra csPCa cases using MRDI. Inter-observer agreement was significant only for MRDI (Cohen’s kappa = 0.4250, p=0.004). The results of this study show the potential of MRDI to improve interobserver variability and the detection of csPCa.

Hyperspectral imaging, a rapidly evolving technique, furnishes exhaustive information on Earth's surface reflectance over an extensive spectrum of wavelengths. We have developed a more precise method for analyzing spectral data by meticulously selecting plant leaf pixels and employing a relative reference approach. This enhanced technique correlates camera pixel values with light intensity, bypassing the need for complex equations and thereby providing clearer insights into vegetation vitality. The findings of this study not only enhance the precision of hyperspectral imaging but also bolster our capability for ecological monitoring and understanding environmental health. A novel algorithm based on the red-edge slope was established to classify images, exploiting the spectral reflectance data gleaned from the hyperspectral Liquid Crystal Tunable Filter (LCTF) camera. Compared with conventional SVM and K-means algorithms, our novel algorithm demonstrated commendable performance, achieving an overall accuracy of 90% with a Kappa Coefficient of 0.86. This comparison highlights the novel algorithm's relative strength and potential for large-scale satellite and drone imagery analysis applications. The advancements facilitated by this research are instrumental in ecological assessments, conservation efforts, and resource management strategies, signaling a leap forward in the era of environmental monitoring and analysis.

This study introduces a compact Raman spectrometer with a 1064 nm excitation laser coupled with a fiber probe and an inexpensive motorized stage, offering a promising alternative to widely used Raman imaging instruments with 785 nm excitation lasers. The benefits of 1064 nm excitation for biomedical applications include further suppression of fluorescence background and deeper tissue penetration. The performance of the 1064 nm instrument in detecting cancer in human bladder resectates is demonstrated. Raman images with 1064 nm excitation were collected ex vivo from 10 human tumor and non-tumor bladder specimens and the results are compared to previously published Raman images with 785 nm excitation. K-Means cluster (KMC) analysis is used after pre-processing to identify Raman signatures of control, tumor, necrosis, and lipid-rich tissues. Hierarchical cluster analysis (HCA) groups the KMC centroids of all specimens as input. The tools for data processing and hyperspectral analysis were compiled in an open source Python library called SpectraMap (SpMap). In conclusion, the 1064 nm Raman system can differentiate between tumor and non-tumor bladder tissues in a similar way to 785 nm Raman spectroscopy. These findings hold promise for future clinical hyperspectral imaging.

To assess the impact of a deep learning (DL) denoising reconstruction algorithm applied to identical patient scans acquired with two different voxel dimensions, representing distinct spatial resolutions. This IRB approved prospective study was conducted at a tertiary pediatric center in compliance with the Health Insurance Portability and Accountability Act. We used a General Electric Signa Premier unit (GE Medical Systems, Milwaukee, WI) to acquire two DTI sequences of the left knee on each child at 3T: an in-plane 2.0 x 2.0 mm2 with section thickness of 3.0 mm and a 2 mm3 isovolumetric voxel, neither had an inter-section gap. We used a multi-band DTI acquisi-tion with fat-suppressed single-shot spin-echo echo-planar sequence (20 non-collinear directions; b-values of 0 and 600 sec/mm2). The MR vendor-provided a commercially available DL model applied with 75% noise reduction settings to same subject DTI sequences at different spatial res-olutions. We compared DTI tract metrics from both DL-reconstructed scans and non-denoised scans for femur and tibia, at each spatial resolution. Differences were evaluated using Wilcox-on-signed ranked test and Bland-Altman plots. When comparing DL versus non-denoised diffu-sion metrics in femur and tibia using the 2 mm x 2mm x 3 mm voxel dimension there were no significant differences between tract count (p = 0.1, p =0.14) tract volume (p = 0.14, p = 0.29), or tibial tract length (p=0.16); femur tract length exhibited a significant difference (p

Background: Thyroid nodules are common, affecting nearly 65% of the general population. While they are widespread, it's crucial to recognize that the majority of these nodules are not cancerous and can be effectively managed through careful monitoring. Thyroid ultrasound is commonly used to evaluate thyroid nodules owing to its low cost, wide availability and technical ease of application. In sonography, it's crucial to assess characteristics and vascular flow. Yet, conventional color and power Doppler ultrasound may not always effectively capture small vessels and low velocities due to their limitations. Superior Microvascular Imaging can display the blood flow of small vessels and low-velocity blood flow, which is difficult to visualize with conventional Doppler ultrasound. Meanwhile other thyroid scans, that utilize either [99mTc] pertechnetate or (18)F-fluorodeoxyglucose, can categorize nodules as hyperactive ('hot'), exhibiting normal activity ('warm'), or having reduced/no activity ('cold'). Thus, the main goal of screening and tracking thyroid nodules is to improve the management of potentially worrisome thyroid malignancies. Methodology: The study was conducted within the structural framework of a network meta-analysis, with the index tests being - SMI, Radionuclide Scanning and Color Doppler, and the general link between them being the reference gold standard. The data collection involved searching for all pertinent literature using PubMed, Google Scholar, and the Cochrane Library databases. The essential data was extracted following the application of specific inclusion and exclusion criteria.This meta-analysis included 7 RCTs with 1,152 patients for Radionuclide Scanning, 10 RCTs with 1,847 patients for SMI and 8 RCTs with 4,480 patients for Color Doppler. They were analyzed using the QualSyst tool and the risk of bias was evaluated by using QUADAS-2 analysis.The statistical software packages MetaDiSc 1.4, RevMan (Review Manager, version 5.3), SPSS (Statistical Package for the Social Sciences, version 20) and Excel in Stata 14 were used to perform the statistical analyses. Result: According to the findings, the sensitivity for Radionuclide Scanning is calculated as 0.79 (range: 0.76 to 0.81) and specificity as 0.55 (range: 0.50 to 0.60) with a 95% confidence interval. The overall diagnostic odds ratio (DOR) for Radionuclide Scanning Is 10.54.Additionally, with a 95% confidence interval, SMI exhibits a sensitivity of 0.82 (with a range of 0.79 to 0.84) and a specificity of 0.86 (with a range of 0.84 to 0.88), while the overall DOR is approximately 25.73. Color Doppler demonstrates a calculated sensitivity of 0.71 (ranging from 0.69 to 0.74) and specificity of 0.81 (ranging from 0.79 to 0.83) with a 95% confidence interval, while its DOR is 13.48.Conclusion: As evidenced by this meta-analysis, blood flow dependent imaging techniques are superior in their abilities to be used as diagnostic tests, especially in conjunction with their use in detecting thyroid nodules. This study offers a starting point for delving deeper into the utilization of Radionuclide Imaging, Superior Microvascular Imaging and Color Doppler in diagnosing thyroid nodules in a clinical setting. Key Words: - Thyroid Nodule, Radionuclide Scanning, Superior Microvascular Imaging, Color Doppler Diagnosis, Sensitivity, Specificity, Diagnostic imaging

The small-molecule iododiflunisal (IDIF) is a transthyretin (TTR) tetramer stabilizer and acts as a chaperone of the TTR-Amyloid beta interaction. Oral administration of IDIF improves Alzheimer’s Disease (AD)-like pathology in mice, although mechanism of action and pharmacokinetics remain unknown. Radiolabeling IDIF with positron or gamma emitters may aid in the in vivo evaluation of IDIF using non-invasive nuclear imaging techniques. In this work, we report isotopic exchange reaction to obtain IDIF radiolabeled with 18F. [19F/ 18F]exchange reaction over IDIF in dimethylsulfoxide at 160 °C resulted in the formation of [18F]IDIF in 7±3% radiochemical yield in a 20 minutes reaction time, with a final radiochemical purity of >99%. Biodistribution studies after intravenous administration of [18F]IDIF in wild-type mice using positron emission tomography (PET) imaging showed capacity to cross the blood-brain barrier (ca. 1% of injected dose per gram of tissue in the brain at t&gt;10 min post administration), rapid accumulation in the liver, long circulation time and progressive elimination via urine. Our results open opportunities for future studies in larger animal species or human subjects.

(1) Background: The imaging energy range of a typical Compton camera is limited due to the fact that scattered gamma photons are seldom fully absorbed when the incident energies are above 3 MeV. Further improving the upper energy limit of gamma-ray imaging has important application significance in active interrogation of special nuclear materials and chemical warfare agents, as well as range verification of proton therapy; (2) Methods: To realize gamma-ray imag-ing in a wide energy range of 0.3~7 MeV, a principle prototype, named a portable three-layer Compton camera, was developed using the scintillation detector that consist of an silicon photo-multiplier array coupled with a Gd3Al2Ga3O12:Ce pixelated scintillator array. Implemented in a list-mode maximum likelihood expectation maximization algorithm, a far-field energy-domain imaging method based on two-interaction and three-interaction events was applied to estimate the initial energy and spatial distribution of gamma-ray sources. The simulation model of detec-tors was established based on Monte Carlo simulation toolkit Geant4. The reconstructed images of a 133Ba, a 137Cs and a 60Co point-like sources were successfully obtained with our prototype in laboratory tests and compared with simulation studies; (3) Results: The proportion of effective imaging events accounted for about 2%, which made our prototype realize reconstructing the distribution of a 0.05 μSv/h 137Cs source in 10 seconds. The angular resolution for resolving two 137Cs point-like sources was 15°. Additional simulated imaging of the 6.13 MeV gamma-rays from 14.1 MeV neutron scattering with water preliminarily demonstrated the imaging capability for high incident energy; (4) Conclusions: We concluded that the prototype had good imaging per-formance in a wide energy range (0.3~7 MeV), which showed potential in several MeV gam-ma-ray imaging applications.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) often causes severe viral pneumonia, especially among older individuals and those with underlying health conditions. The C57BL/6 mouse is widely used to develop mouse models of obesity, diabetes, hypertension, and immune disorders, conditions that are associated with increased risk of severe COVID-19. Although many studies using these mouse models have examined the pathogenicity of SARS-CoV-2, COVID-19 pathogenesis remains poorly understood. In vivo imaging analysis using two-photon excitation microscopy is useful for elucidating the pathology of COVID-19, providing pathological insights that are not available from conventional histological analysis. However, there is no reporter SARS-CoV-2 that demonstrates pathogenicity in C57BL/6 mice and emits sufficient light intensity for two-photon in vivo imaging. Here, we generated SARS-CoV-2 expressing the fluorescent protein Venus to facilitate in vivo pathological studies using C57BL/6 mouse models. We generated a mouse-adapted strain of SARS-CoV-2, by performing sequential lung-to-lung passages in BALB/c mice, followed by in C57BL/6 mice. We observed that the C57BL/6-adapted SARS-CoV-2 (named MASCV2-p25) replicated efficiently in the lungs of C57BL/6 mice, causing fatal pneumonia. Histopathologic analysis revealed severe inflammation and infiltration of immune cells in the lungs of MASCV2-p25-infected C57BL/6J mice, not unlike that observed in COVID-19 patients with severe pneumonia. Subsequently, we generated a mouse-adapted reporter SARS-CoV-2 (named MASCV-Venus-p9) by inserting the fluorescent gene Venus into MASCV2-p25, and sequential lung-to-lung passages in C57BL/6 mice. C57BL/6 mice infected with MASCV2-Venus-p9 exhibited severe pneumonia similar to that induced by MASCV2-p25. In addition, two-photon excitation microscopy of the lungs of the infected C57BL/6J mice showed that the infected cells emitted sufficient levels of fluorescence for easy observation. These findings suggest that MASCV2-Venus-p9 will be useful for two photon in vivo imaging studies of the pathogenesis of severe COVID-19 and for the development of therapeutic agents for severe pneumonia.

This paper presents a novel sensor for the detection and characterization of regions of air turbulence that would be of use to improve UAV stability in bad weather. It consists of a combined Schlieren imager and a Radar Acoustic Sounding System (RASS) to produce dual modality “images” of air movement within the measurement volume. The ultrasound modulated Schlieren imager consists of a strobed point light source, parabolic mirror, light-block and camera which are controlled by two laptops. It provides a fine scale projection of the acoustic pulse modulated air turbulence through the measurement volume. The narrow beam 40 kHz/ 17 GHz RASS produces spectra based on Bragg enhanced Doppler radar reflections from the acoustic pulse as it travels. Tests using artificially generated air vortices showed some disruption of the Schlieren image and of the RASS spectrogram. This should allow the higher resolution Schlieren images to identify the turbulence mechanisms that are disrupting the RASS spectra.

Video capsule endoscopy (VCE) is increasingly used to decrease the discomfort among patients owing to its small size. However, VCE has a major drawback of not having narrow band imaging (NBI) functionality. The current VCE has the traditional white light imaging (WLI) only, which has poor performance in the computer-aided detection (CAD) of different types of cancer compared with NBI. Specific cancers, such as esophageal cancer (EC), do not exhibit any early biomarkers, making their early detection difficult. In most cases, the symptoms are unnoticeable, and EC is diagnosed only in later stages, making its 5-year survival rate below 20% on an average. NBI filters provide particular wavelengths that increase the contrast and enhance certain features of the mucosa, thereby enabling early identification of EC. However, VCE does not have a slot for NBI functionality because its size cannot be increased. Hence, NBI image conversion from WLI can be achieved only in post-processing at present. In this study, a complete arithmetic assessment of the decorrelated color space was conducted to generate NBI images from WLI images for VCE of the esophagus. Three parameters, namely, structural similarity index metric (SSIM), entropy, and peak-signal-to-noise ratio (PSNR), were used to asses the simulated NBI images. Results show the good performance of the NBI image reproduction method, with SSIM, entropy difference, and PSNR values of 93.215%, 4.360, and 28.064 dB, respectively.

MAD is the gold standard therapy for mild/moderate OSA and is a second-choice treatment in patients with severe OSA not responding to CPAP. The aim of this study was to analyze the upper airway characteristics of OSA patients and the morphological changes in the upper airway, inducted by four different types of mandibular advancement devices, using CBCT 3D imaging. Twenty-two patients were recruited after OSA diagnosis with polysomnography. Four different customized and titratable MAD were used and an initial CBCT scan was obtained for each patient. After 6 months to the end of the MAD titration phase, all the subjects showed an AHI of &lt; 5 or a decrease of 50% in AHI with MAD when compared with initial AHI and a second CBCT scan with MAD in situ was performed. An important improvement of the airway was observed (+33.76%) and a significant difference in the enlargement ratio between the posterior soft palate (+32.41%) and the posterior tongue (+36.96%) region was also found. The greatest increase in airway volume was achieved in patients treated with the MAD Forward and TAP (respectively +42.77% and + 41.63%). MAD therapy is effective to treat mild/severe OSA with increased upper airway volume. The design of the MAD can influence the effectiveness of the treatment.

In a context of exponential demographic growth, the imbalance between human resources and public health problems is impelling us to envision other solutions to the difficulties faced in the diagnosis, prevention and large-scale management of the most common diseases. Cardiovascular diseases represent the leading cause of morbidity and mortality worldwide. A large-scale screening program would make it possible to promptly identify patients with high cardiovascular risk in order to manage them adequately. Optical coherence tomography-angiography (OCT-A), as a window into the state of the cardiovascular system, is a rapid, reliable, and reproducible imaging examination that enables prompt identification of at-risk patients through the use of automated classification models. One challenge that limits the development of computer-aided diagnostic programs is the small number of open-source OCT-A acquisitions available. To facilitate the development of such models, we have assembled a set of images of the retinal microvascular system from 499 patients. It consists of 814 angiocubes as well as 2005 en face images. Angiocubes were captured with a swept-source OCT-A device of patients with varying overall cardiovascular risk. To the best of our knowledge, our dataset, RASTA, is the only publicly available dataset comprising such a variety of images from healthy and at-risk patients. This dataset will enable the development of generalizable models for screening of cardiovascular diseases from OCT-A retinal images.

A reliable and practical renal-lipid quantification and imaging method is needed. Here, the feasibility of an accelerated MRSI method to map renal fat fractions (FF) at 3T and its repeatability were investigated. A 2D density-weighted concentric-ring-trajectory MRSI was used to accelerate acquiring 48×48 voxels (each of 0.25 ml spatial-resolution) without respiratory navigation implementations. The data was collected over 512 complex-FID timepoints with a 1250 Hz spectral bandwidth. The MRSI sequence was designed with a metabolite-cycling technique for lipid-water separation. The in vivo repeatability performance of the sequence was assessed by conducting a test-reposition-retest study within healthy subjects. The coefficient of variation (CV) in the estimated FF from the test-retest measurements showed a high degree of repeatability of the MRSI-FF (CV= 4.3 ±2.5%). Additionally, the matching level of spectral signature within the same anatomical region was also investigated, and their intrasubject repeatability was also high, with a small standard deviation (8.1 ±6.4%). The MRSI acquisition duration was ~3 minutes only. The proposed MRSI technique can be a reliable technique to quantify and map renal metabolites within a clinically acceptable scan time at 3T that supports the future application of this technique for the non-invasive characterization of heterogeneous renal diseases and tumors.

Development of supervised AI algorithms requires a large amount of labeled images. Image labelling is both time-consuming and expensive. Therefore, we explored the value of e-learning derived annotations for AI algorithm development in medical imaging. Methods We have developed an e-learning platform that involves image-based single click labelling as part of the educational learning process. Ten radiology residents, as part of their residency training, trained the recognition of pneumothorax on 1161 chest X-rays in posterior-anterior projection. Using this data, multiple AI algorithms for detecting pneumothorax were developed. Classification and localization performance of the models was tested on an independent internal testing dataset and on the public NIH ChestX-ray14 dataset. Results The AI models F1 scores on the internal and the NIH dataset were 0.87 and 0.44, respectively. Sensitivity was 0.85 and 0.80 for classification and specificity 0.96 and 0.48 for classification. F1 scores were 0.72 and 0.66, sensitivity 0.72 and 0.72. False positive rate was 0.36 and 0.32 for localisation. Conclusion Our results demonstrated that e-learning derived annotations are a valuable data source for algorithm development. Further work is needed to include additional parameters such as user performance, consensus of diagnosis, and quality control in the development pipeline.

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%.

: Increased glucose and choline uptake are hallmarks of cancer. We investigated if the uptake and conversion of [2H9]choline alone and together with that of [6,6’ 2H2]glucose can be assessed in subcutaneous tumors by deuterium metabolic imaging (DMI) after bolus administration of these compounds. Therefore tumors with human renal carcinoma cells were grown subcutaneously in mice up to ~0.5 cm3. Mice were anesthetized with isoflurane and IV infused in the MR magnet for ~20 sec with ~0.2 ml solutions containing either [2H9]choline (0.05g/kg) alone or together with [6,6’ 2H2]glucose (1.3g/kg). 2H MR was performed on a 11.7T MR system with a home-built 2H/1H coil using a 900 excitation pulse and 400ms repetition time. 3D DMI was recorded at high resolution (2x2x2mm) in 37 min or at low resolution (3.7x3.7x3.7mm) in 2:24 min. Absolute tissue concentrations were calculate assuming initial [HOD]=13.7mM. Within 5 minutes after [2H9]choline infusion its signal appeared in tumor spectra representing concentration increasing up to 0.3–1.2 mM and then slowly decreased or remained constant over 100 minutes. In plasma [2H9]choline disappeared within 15 minutes post-infusion implying that its tumor signal arises from tissue and not blood. After infusing a mixture of [2H9]choline and [6,6’ 2H2]glucose their signals were observed separately in tumor 2H spectra. Over time the [2H9]choline signal broadened, possibly due to conversion to other choline compounds, [[6,6’ 2H2]glucose] declined, [HOD] increased and a lactate signal appeared, reflecting glycolysis. Metabolic maps of all 2H compounds were reconstructed from high resolution DMIs. As choline infusion and glucose DMI is feasible in patients, their simultaneous detection has clinical potential for tumor characterization.

Objectives: To explore the potential of Radiomics alone and in combination with diffusion-weighted derived quantitative parameter namely apparent diffusion co-efficient (ADC) using supervised classification algorithms in predicting outcomes and prognosis. Materials and Methods: Retrospective evaluation of the imaging was done for a study cohort of uterine cervical cancer, candidates for radical treatment with chemo radiation. ADC values were calculated from the darkest part of the tumor, both before (labeled preADC) and post treatment (labeled postADC) with chemo radiation. Post extraction of 851 Radiomics features and feature selection by taking the union of the features which had Pearson correlation >0.35 for recurrence, >0.49 for lymph node and >0.40 for metastasis, analysis was done to predict clinical outcomes. Results: The study enrolled 52 patients who presented with variable FIGO stages and age range 28–79 (Median = 53 years) with median follow-up of 26.5 months (range, 7–76 months). Disease recurrence occurred in 12 patients (23%). Metastasis occurred in 15 patients (28%). A model generated with 24 radiomics features and preADC using a monotone multi-layer perceptron neural network to predict the recurrence yields AUC of 0.80 and kappa value as 0.55 and shows that addition of radiomics features on ADC values improves the statistical metrics by 40% approximately for AUC and 223% approximately for Kappa. Similarly, neural network model for prediction of metastasis re-turns AUC of 0.84 and kappa value as 0.65 over performs by 25% for AUC and 140% for Kappa approximately. There was a significant input of GLSZM features (SALGLE and LGLZE) and GLDM features (SDLGLE and DE) correlation with clinical outcomes of recurrence and metastasis. Conclusions: The study is an effort to bridge the unmet need of translational predictive biomarkers in stratification of uterine cervical cancer patients based on prognosis.

Tumor vasculature proliferates rapidly, generally lacks pericyte coverage, and is uniquely frag-ile making it an attractive therapeutic target. A subset of small-molecule tubulin binding agents cause disaggregation of the endothelial cytoskeleton leading to enhanced vascular permeability generating increased interstitial pressure. The resulting vascular collapse and ischemia cause downstream hypoxia, ultimately leading to cell death and necrosis. Thus, local damage gener-ates massive amplification and tumor destruction. The tumor vasculature is readily accessed and potentially a common target irrespective of disease site in the body. Development of a therapeutic approach and particularly next generation agents benefits from effective non-invasive assays. Imaging technologies offer varying degrees of sophistication and ease of implementation. This review considers technological strengths and weaknesses with examples from our own laboratory. Methods reveal vascular extent and patency, as well as insights into tissue viability, proliferation and necrosis. Spatiotemporal resolution ranges from cellular mi-croscopy to single slice tomography and full three-dimensional views of whole tumors and measurements can be sufficiently rapid to reveal acute changes or long-term outcomes. Since imaging is non-invasive, each tumor may serve as its own control making investigations par-ticularly efficient and rigorous. The concept of tumor vascular disruption was proposed over 30 years ago and it remains an active area of research.

The Chang’e-4 (CE-4) lunar rover, equipped with The Visible and Near-IR Imaging Spectrometer(VNIS) which based on acousto-optic tunable filter spectroscopy, was launched to the far side of the moon on December 8, 2018. The detection band of VNIS ranges from 0.45 to 2.4μm. Because of the weak reflection of infrared radiation from the lunar surface, a static electronic phase-locked acquisition method is adopted in the infrared channel for signal amplification. In this paper, full-link simulations and modeling are conducted of the infrared channel information flow of the instrument. The signal/noise characteristics of VNIS are analyzed in depth, and the signal-to-noise(SNR) ratio prediction and laboratory verification are presented. On January 4, 2019, the VNIS started working successfully and acquired high-resolution spectrum data of the far side of the moon for the first time. Through analysis, the SNR ratio is in line with predictions, and the data obtained by VNIS in orbit are consistent with the information model proposed in this paper.

Although the most common forms of brain injury in preterm infants have been associated with adverse neurodevelopmental outcomes, existing MRI scoring systems lack specificity, do not incorporate clinical factors, and are technically challenging to perform. The objective of this study was to develop a web-based, clinically-focused prediction system which differentiates severe from normal-moderate neurodevelopmental outcomes at two years. Infants were retrospectively identified as those who were born ≤30 weeks gestation, had MR imaging at term-equivalent age, and neurodevelopmental testing at 18-24 months. Each MRI was scored on injury in three domains (intraventricular hemorrhage, white matter injury, and cerebellar hemorrhage) and clinical factors strongly predictive of outcome were investigated. A binary logistic regression model was then generated from the composite of clinical and imaging components. A total of 154 infants were included (mean GA = 26.1±1.8 weeks, BW = 889.1±226.2 grams). The final model (imaging score + ventilator days + delivery mode + antenatal steroids + ROP requiring surgery) had strong discriminatory power for severe disability (AUC=0.850), with a PPV of 76% and NPV of 90%. Available as a web-based tool, it can be useful for prognostication and targeting early intervention services to infants who may benefit most from such services.

The superharmonic imaging of tissue has the potential for high spatial and contrast resolutions, compared to the fundamental and second harmonic imaging. For this technique, the spectral bandwidth of an ultrasound transducer is divided for transmission of ultrasound and reception of its superharmonics (i.e., higher than the second harmonic). Due to the spectral division for the transmission and reception, transmitted ultrasound energy is not sufficient to induce superharmonics in media without using contrast agents, and it is difficult that a transducer has a -6-dB fractional bandwidth of higher than 100%. For the superharmonic imaging of tissue, thus, multi-frequency array transducers are the best choice if available; transmit and receive elements are separate and have different center frequencies. However, the construction of a multi-frequency transducer for intravascular ultrasound (IVUS) imaging is particularly demanding because of its small size of less than 1 mm. Here, we report a recently developed dual-element focused IVUS transducer for the third harmonic imaging of tissue, which consists of a 35-MHz element for ultrasound transmission and a 105-MHz element for third harmonic reception. For high quality third harmonic imaging, both elements were fabricated to have the same focus at 2.5 mm. The results of tissue mimicking phantom tests demonstrated that the third harmonic images produced by the developed transducer had higher spatial resolution and deeper imaging depth than the fundamental images.

Increasing of the imaging rate of conventional atomic force microscopy (AFM) is almost impossible without impairing of the imaging quality, since the probe tip tends to lose contact with the sample. We propose to apply the additional nonlinear force on the upper surface of a cantilever, which will help to keep the tip and surface in contact. In practice this force can be produced by the precisely regulated airflow. Such an improvement affects the AFM system dynamics, which were evaluated using a mathematical model presented in this paper. The model defines the relationships between the additional nonlinear force, the pressure of the applied air stream and the initial air gap between the upper surface of the cantilever and the end of the air duct. It was found that the nonlinear force created by the stream of compressed air (aerodynamic force) prevents the contact loss caused by the high scanning speed or higher surface roughness, and at the same time has minimal influence on the interaction force, thus maintaining stable contact between the probe and the surface. This improvement allows to effectively increase the scanning speed by at least 10 times using a soft (spring constant of 0.2 N/m) cantilever by applying the air pressure of 40 Pa. If a stiff cantilever (spring constant of 40 N/m) is used, the potential of accuracy improvement reaches 92 times. This method is suitable for use with different types of AFM sensors and can be implemented practically without essential changes in AFM sensor design.

Older adults with obesity have an increased risk for cognitive decline and subsequent Alzheimer’s disease. Previous research has focused on the impact of individual nutrients and overall dietary patterns to improve cognitive function. The Brain and Body Health (BB-Health) study aims to demonstrate the feasibility of a multicomponent nutritional supplement (MCNS) and weight loss (WL) intervention for individuals with overweight and obesity who are not consuming a healthy diet. BB-Health is a parallel-group randomized placebo-controlled 2x2 factorial pilot trial comparing the MCNS, WL, and MCNS+WL with a Control group. Eligible participants are 55 to 85 years of age with a body mass index 27.0 to 39.9 kg/m2. Major exclusion criteria include type 2 diabetes, moderate or severe cognitive impairment, and self-reported healthy dietary pattern. The BB-Health feasibility trial is registered as NCT05542199 at clinicaltrials.gov. The BB-Health objectives are to report: 1) recruitment and enrollment, including pace and descriptive statistics of the study sample; 2) adherence to the administered interventions; 3) successful data collection and performance of outcome assessments, including evaluation of change in key outcomes over time that are powered for this pilot study; and 4) summary statistics on outcomes for use in planning a subsequent, larger trial. The outcomes of interest are age-sensitive cognitive assessments, cerebral hemodynamics, and related health parameters. All measurements are collected at baseline, 3-, 6-, and 12-month visits. If the BB-Health protocol demonstrates feasibility, the novel MCNS with and without a parallel WL intervention has potential to be administered in a confirmatory randomized trial to evaluate ability to prevent age-related cognitive decline and improve brain health. The BB-Health Feasibility Study could significantly contribute to our understanding of the influence of diet and weight management on cognitive health

Good health and well-being is one of the essential SDGs that ensure healthy lives and promote well-being for all ages and further entails providing substantial medical services to the public at low cost and with minimal adverse effects on the environment. Information and communication technologies (ICTs) have taken on an increasingly important function as significant facilitators of healthcare reform, with the goals of enhancing access to health services, the quality of treatment provided, and the overall productivity of the healthcare system. However, the integration of ever-increasing ICT technologies into the healthcare systems, also referred to as digital transformation, is not a straightforward process, but it comes with different types of challenges from integration level to application design level and security level. Although several studies have been proposed to address the integration of ICT technologies into healthcare systems, there is still a need for a comprehensive research study on the integration and design challenges, security and privacy challenges, application areas, and possible positive and negative impacts. Therefore, this paper contributes as the research literature study covering an important SDG, "Good health and well-being," and its digital transformation, along with summarising our research findings in a detailed and taxonomical way. To start with, firstly, we present a detailed comparison of existing studies on healthcare and well-being, mainly focusing on integrating ICT technologies in healthcare in terms of sustainable aspects, security and privacy challenges, design and integration challenges, E-health-related applications, and future directions. We also present an overview and the need for digital transformation in healthcare, discuss its significant components, highlight E-health's importance and benefits, explore its integration and design challenges, and categorise the security and privacy challenges. Next, we present an in-depth discussion on the role of Blockchain technology as today's leading technology in E-health, discussing Blockchain technology and its characteristics, highlighting its benefits, and describing the possible types of Blockchain-based E-health use cases. Furthermore, we discuss the positive and negative impact of ICT integration along with identifying open issues and challenges of integrating ICT technologies into the healthcare systems and discuss future research directions, which provide the strength for researchers to address the issues in future solutions.

Since the 21st century, China's urbanization process has been rapid development, the concept and function of urban public space in the city has been gradually paid attention to. In order to guarantee life and water, most urban construction relies on rivers, and Bridges are the most important way to communicate between urban areas. The main functional part of the bridge is the span structure, that is, the bearing structure of the bridge, and the lower part of the "gray" space formed by the bridge structure. Considering the social level, with the economic growth and urbanization development, people have brought a better living environment and quality of life, and also improved the requirements for urban public environment. In the increasingly tense urban space, how to use and transform the space under the bridge is a problem that needs to be considered and solved. In view of this problem, in this study, we try to solve the micro-transformation of space under Bridges in cities through public art from the perspective of "regional culture" and "art for all". This paper analyzes the micro-transformation of space art under Bridges in two large cities of Shanghai and Foshan, namely, the space under Bridges under Songhong Road in Shanghai, the space under Bridges under Central Of Suzhou River and the space under Bridges under Pingsheng Bridge in Foshan. This paper discusses the cultural intervention of "regional culture" in the micro-transformation of the space under the bridge, and the influence and effect of "art for all" on the public art space under the bridge after the transformation to the community and the public.

This study investigated the speciation, transformation and availability of P during indigenous vegetable production by employing a combination of chemical and spectroscopic techniques. The study focused upon sites in two ecozones of SSA, the Dry Savanna (lna, Benin Republic) and Rainforest (Ilesha, Nigeria). Both sites were cultivated with two indigenous vegetable species; local amaranth (Amaranthus cruentus (AV)) and African eggplant (Solanum macrocarpon (SM)). The soils were treated with 5 t/ha poultry manure and urea fertilizer at the rate of 0, 20, 40, 60 and 80 kg N/ha. Soil samples were collected before planting and after harvest. Phosphorus K-edge X-ray absorption near-edge structure (XANES) spectroscopy was used to determine P speciation in these soils. Quantitative analysis showed that adsorbed and organic P were the two dominant P species in the manure amended Dry Savanna (DS) soils before planting and after harvest in soils cultivated with both AV and SM, with the addition of urea (40 kg N/ha) causing an increase in the organic P form in Dry Savanna soils cultivated with AV. Soils of the Rainforest (RF) cultivated with AV initially had large amounts of apatite P in the manure amended soils prior to planting which was transformed to adsorbed and organic P after harvest. Urea addition to the Rainforest soils shifted the dominant P species from organic P to adsorbed and apatite P, which is likely to limit P availability. Soils cultivated with SM had similar proportions of both organic and adsorbed P forms, with 40 kg N/ha addition slightly increased the proportion of adsorbed P.

Gliomas are common primary central nervous system (CNS) tumours which are often very difficult to diagnose, stage and manage because of their heterogeneity and molecular aberrations. The notable hallmark of gliomas is integrated genome mutations and methylome that correlates with distinctive patterns of transcription that potentiates glioma heterogeneity, angiogenesis and ultimately poor prognosis. The World Health Organization (WHO) has decided to reclassify gliomas based on molecular markers rather than the traditional anatomical basis; use of Nuclear Medicine techniques e.g. SPECT/PET and Magnetic Resonance Imaging (MRI) techniques based on molecular markers is set to become the future gold standards. This has led to the investigations on potential for the use of non-invasive imaging techniques such as [68Ga]68Ga-RGD positron emission tomography (PET) to be utilised routinely in clinical practice based on angiogenic markers and also the potential to add information that may assist in drug-design and therapeutic decision making. This review aims to provide an overview of the basis of recent advances in glioma imaging using molecular targeting with positron emission tomography and SPECT imaging, as well as the role in patient management i.e. diagnosis, staging, recurrence detection etc.

Cardiomyopathies (CMPs) are a group of myocardial disorders that are characterized by structural and functional abnormalities of the heart muscle. These abnormalities occur in the absence of coronary artery disease (CAD), hypertension, valvular disease, and congenital heart disease. CMPs are an increasingly important topic in the field of cardiovascular diseases due to the complexity of their diagnosis and management. In 2023, the ESC guidelines on cardiomyopathies were first published, marking significant progress in the field. The growth of techniques such as cardiac magnetic resonance imaging (CMR) and genetics has been fueled by the development of multimodal imaging approaches. For the diagnosis of CMPs, a multimodal imaging approach, including CMR, is recommended. CMR has become the standard for non-invasive analysis of cardiac morphology and myocardial function. This document provides an overview of the role of CMR in CMPs, with a focus on tissue mapping. CMR enables the characterization of myocardial tissues and the assessment of cardiac functions. CMR sequences and techniques, such as late gadolinium enhancement (LGE) and parametric mapping, provide detailed information on tissue composition, fibrosis, edema, and myocardial perfusion. These techniques offer valuable insights for early diagnosis, prognostic evaluation, and therapeutic guidance of CMPs. The use of quantitative CMR markers enables personalized treatment plans, improving overall patient outcomes. This review aims to serve as a guide for the use of these new tools in clinical practice.

Spatial-structured longitudinal light beams are optical fields sculpted in three-dimensional (3D) space by diffractive optical elements. These beams have been recently suggested for use in im-proving several imaging capabilities, such as 3D imaging, enhancing image resolution, engineering the depth of field, and sectioning 3D scenes. All these imaging tasks are performed using coded aperture correlation holography systems. Each system designed for a specific application is characterized by a point spread function of a different spatial-structured longitudinal light beam. This article reviews the topic of applying certain structured light beams for optical imaging.

Hallux valgus deformity (HVD) involves subluxation of the first metatarsophalangeal joint. While HVD is primarily considered a forefoot condition, midfoot instability may play a significant role in its development and severity. Therefore, this review had a particular focus on understanding midfoot instability based upon weightbearing imaging assessments of the TMT joint. This review followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and searched five databases for studies on midfoot instability in HVD patients. Severity of HVD was defined by hallux valgus angle (HVA) and distal metatarsal articular angle (DMAA). Data was extracted, and articles were graded using the Methodological Index for Non-Randomized Studies (MINORS). Of 547 initially retrieved articles, 23 met inclusion criteria. Patients with HVD showed higher HVA and DMAA on weight-bearing radiographs (WBRG) and weight-bearing computed tomography (WBCT) compared to healthy individuals. Midfoot instability was assessed through intermetatarsal angle (IMA) and tarsometatarsal angle (TMT angle). Patients with HVD exhibited greater IMA and TMT angles on both WBRG and WBCT. This review highlights the importance of weight-bearing imaging assessments for midfoot instability in HVD. IMA and TMT angles can differentiate between healthy individuals and HVD patients, emphasizing the significance of midfoot assessment in understanding HVD pathology.

The bionic polarization imaging navigation sensor (BPINS) is a navigation sensor that provides absolute heading, and it is of practical engineering significance to model the measurement error of BPINS. The existing BPINSs are still modeled using photodiode-based measurements rather than imaging measurements and are not modeled systematically enough. This paper proposes a measurement model of BPINS that takes into account the geometric and polarization errors of the optical system. Firstly, the key error factors affecting the measurement accuracy of BPINS are systematically investigated and the Stokes vector-based measurement error model of BPINS is established. Secondly, based on its measurement error model, the effect of the error source on the measurement performance of BPINS is quantitatively analyzed by using Rayleigh scattering to generate scattered sunlight as a known incident light source. The experimental results show that the coordinate deviation of the principal point has a greater impact, followed by grayscale response inconsistency of CMOS and integration angle error of micro-polarization array, and finally lens attenuation. This finding can guide the subsequent calibration of BPINS, and the quantitative results provide an important reference for its optimal design.

Concrete-filled steel tube (CFST) members have been widely used in the field of civil engineering due to their advanced superior mechanical properties. However, internal defects such as concrete core voids and interface debonding are likely to weaken the load-carrying capacity and stiffness of these members, which affects safety and serviceability of CFST structures. Visualizing the inner defects of concrete core in CFST members have been a critical need in civil engineering construction, a travel time tomography (TTT) is introduced to quantitatively identify and visualize the sizes and positions of CFST members in this paper. Moreover, a parameter analysis is performed to investigate the relationship between TTT imaging qualities and influence factors, e.g. inversion parameters, defect sizes and positions. The effectiveness and accuracy of the TTT algorithm are verified by several numerical examples and the results demonstrate that TTT can identify the sizes and positions of concrete core void defects in CFST members efficiently and several inversion parameters including model weighting matrix and inversion grid size really pose a significant impact on the imaging results of CFST members. In addition, several optimum parameters are recommended to benefit the future study of the promising TTT approach for CFST members.

Atherosclerosis is a chronic systemic inflammatory condition of the vasculature and a leading cause of stroke. Luminal stenosis severity is an important factor in determining vascular risk. Conventional imaging modalities, such as angiography or duplex ultrasonography, are used to quantify stenosis severity and inform clinical care but provide limited information on plaque biology. Inflammatory processes are central to atherosclerotic plaque progression and destabilization. 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) is a validated technique for quantifying plaque inflammation. In this review, we discuss the evolution of FDG-PET as an imaging modality to quantify plaque vulnerability, challenges to standardization of image acquisition and analysis, its potential application to routine clinical care after stroke, and the possible role it will play in future drug discovery.

In neuroendocrine neoplasms (NENs), the use of new radiopharmaceuticals has improved the accuracy of diagnosis and staging, refined surveillance approaches, and introduced specific and personalized radiation therapies. Nuclear medicine has therefore acquired a crucial role in the management of NENs patients by improving their risk stratification and personalized therapies. Artificial intelligence (AI) and radiomics can enable physicians to further improve the overall efficiency and accuracy of the use of these tools in both di-agnostic and therapeutic settings by improving the prediction of tumor grade, differential diagnosis from other malignancies, assessment of tumor behavior and aggressiveness, and prediction of treatment response. This systematic review aims to describe the state-of-the-art on AI and radiomics applications in molecular imaging of NENs.

Melanoma is a type of highly malignant and metastatic skin cancer. In situ molecular imaging of endogenous levels of the melanoma biomarker tyrosinase (TYR) may decrease the likelihood of mortality. In this study we proposed the weakly fluorescent probe 1-(4-(2-(4-(dicyanomethylene)-4H-chromen-2-yl)vinyl)phenyl)-3-(4-hydroxybenzyl)urea (DCM-HBU), which releases a strong red-shifted fluorescent signal after a TYR-mediated oxidation followed by hydrolysis of the urea linkage. The large Stokes shift of the dye is owed to the recovery of the intramolecular charge transfer (ICT) effect. The resulting probe derivate shows a highly ratiometric fluorescence output. Furthermore, the simultaneous excitation by two near-infrared (NIR) photons of the released DCM-NH2 fluorophore could avoid the usual drawbacks, such as cellular absorption, autofluorescence and light scattering, due to an usually short wavelength of the excitation light on biological systems, resulting in images with deeper tissue penetration. In addition, the probe is useful for the quantitative sensing of TYR activity in vivo, as demonstrated in zebrafish larvae. This new ratiometric two photon NIR fluorescent probe is expected to be useful for the accurate detection of TYR in complex biosystems at greater depths than other one-photon excited fluorescent probes.

Artificial intelligence is dramatically transforming medical imaging. We assessed the levels of artificial intelligence use among radiology trainees and explored their perceived impact of artifi-cial intelligence on the radiology workflow and radiology profession, in correlation with the perceived ease of use and behavioral intention to use artificial intelligence. This cross-sectional study enrolled radiology trainees from Saudi Arabia, and an online 5-part-structured question-naire was disseminated via online networks to trainee in July 2021. We included 98 participants (51 male; age 27.59±2.02 years). Level of use was low; few used it in routine practice (7%). The impact of artificial intelligence on the radiology workflow was positively perceived in all radi-ology workflow steps (3.64–3.97 out of 5). A positive impact on the radiology profession was more frequently perceived for technical and performance aspects (81%–85%) compared with prestige and legal aspects (64%–71%). Perceived ease of use and behavioral intention to use arti-ficial intelligence was associated with the current professional activity, level of use artificial in-telligence use, and perceived impact on the profession as well as on radiology workflow (p<0.05). Levels of artificial intelligence use in radiology are very low. The perceived positive impact of ar-tificial intelligence on radiology workflow and profession is correlated with an increase in be-havioral intention to use artificial intelligence. Thus, increasing awareness about the favorable impact can improve the behavioral use.