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Abstract Contrast-free ultrasound quantitative microvasculature imaging shows promise in several applications, including the assessment of benign and malignant lesions. However, motion represents one of the major challenges in imaging tumor microvessels in organs that are prone to physiological motions. This study aims at addressing potential microvessel image degradation in in vivo human thyroid due to its proximity to carotid artery. The pulsation of the carotid artery induces inter-frame motion that significantly degrades microvasculature images, resulting in diagnostic errors. The main objective of this study is to reduce inter-frame motion artifacts in high-frame-rate ultrasound imaging to achieve a more accurate visualization of tumor microvessel features. We propose a low-complex deep learning network comprising depth-wise separable convolutional layers and hybrid adaptive and squeeze-and-excite attention mechanisms to correct inter-frame motion in high-frame-rate images. Rigorous validation using phantom and in-vivo data with simulated inter-frame motion indicates average improvements of 35% in Pearson correlation coefficients (PCCs) between motion corrected and reference data with respect to that of motion corrupted data. Further, reconstruction of microvasculature images using motion-corrected frames demonstrates PCC improvement from 31 to 35%. Another thorough validation using in-vivo thyroid data with physiological inter-frame motion demonstrates average improvement of 20% in PCC and 40% in mean inter-frame correlation. Finally, comparison with the conventional image registration method indicates the suitability of proposed network for real-time inter-frame motion correction with 5000 times reduction in motion corrected frame prediction latency.

The curing behavior of an epoxy/phenolic-based system containing graphene oxide (GO), and rubber powder as a toughening agent has been studied using differential scanning calorimetry (DSC) under non-isothermal conditions at a temperature from 0 to 200 °C. So, to better dispersion of GO nanoplates in the resin media, the surface of the GOs was modified by 1,12-diaminododecane and subsequently aforementioned reaction was confirmed by Fourier transform infrared spectroscopy (FT-IR) and thermogravimetric techniques (TGA). DSC results show that rubber powders despite toughening properties prohibited resin-curing reactions. On the other hand, modified GO led to the promotion of curing reactions. The results of differential and integral isoconversional approaches indicated low activation energy for nanocomposite containing modified GO. Furthermore, thermal stability results reveal that the maximum decomposition temperature and char yield values of samples were increased gradually by the addition of GO and rubber powder to the system.

Hepatocellular Carcinoma (HCC), the most common primary liver cancer, is a significant contributor to worldwide cancer-related deaths. Various medical imaging techniques, including computed tomography, magnetic resonance imaging, and ultrasound, play a crucial role in accurately evaluating HCC and formulating effective treatment plans. Artificial Intelligence (AI) technologies have demonstrated potential in supporting physicians by providing more accurate and consistent medical diagnoses. Recent advancements have led to the development of AI-based multi-modal prediction systems. These systems integrate medical imaging with other modalities, such as electronic health record reports and clinical parameters, to enhance the accuracy of predicting biological characteristics and prognosis, including those associated with HCC. These multi-modal prediction systems pave the way for predicting the response to transarterial chemoembolization and microvascular invasion treatments and can assist clinicians in identifying the optimal patients with HCC who could benefit from interventional therapy. This paper provides an overview of the latest AI-based medical imaging models developed for diagnosing and predicting HCC. It also explores the challenges and potential future directions related to the clinical application of AI techniques.

Abstract Background Transgingival probing is conventionally used for gingival thickness (GT) measurement. However, invasiveness is a major drawback of transgingival probing. Thus, researchers have been in search of alternative methods for measurement of GT. This study compared the clinical efficacy of intraoral ultrasonography and transgingival probing for measurement of GT in different biotypes. Materials and methods This clinical trial was conducted on 34 patients requiring crown lengthening surgery. GT was measured at 40 points with 2- and 4-mm distances from the free gingival margin (FGM) of anterior and premolar teeth of both jaws in each patient by an intraoral ultrasound probe. For measurement of GT by the transgingival probing method, infiltration anesthesia was induced, and a #25 finger spreader (25 mm) was vertically inserted into the soft tissue until contacting bone. The inserted length was measured by a digital caliper with 0.01 mm accuracy. All measurements were made by an operator with high reliability under the supervision of a radiologist. Data were analyzed by t-test, Power and Effect Size formula, and intraclass correlation coefficient (ICC). Results The two methods were significantly different in measurement of GT in both thick and thin biotypes at 2- and 4-mm distances (P

Purpose: Instagram pages of public libraries were a suitable platform to establish and maintain communication with users and provide services and information they needed, especially during the epidemic of diseases such as COVID-19. The aim of the present study is to identify the factors affecting the willingness of users to continue using the Instagram pages of public libraries in West Azerbaijan province during the COVID-19 pandemic. Method: The current research is applied in terms of purpose and descriptive-survey of correlation type in terms of the data collection method. The research was carried out in 1399-1400. The data collection tool was a researcher-made questionnaire, whose face validity was confirmed by experts in this field, and its reliability was calculated using Cronbach’s alpha coefficient at 72%. The statistical population of the research included all the followers of the Instagram pages of public libraries in West Azerbaijan province during the COVID-19 pandemic, from which 20 active pages were selected, and the questionnaire was provided to them privately by the managers of the pages, and finally 212 questionnaires were returned. Descriptive statistics were used to determine frequency, frequency percentage, standard deviation and mean in SPSS software, and the structural equation modeling by partial least squares method in SmartPLS software was used to investigate the relationships between variables and test hypotheses. Findings: The findings of the analysis of path coefficients showed that there is a positive and significant relationship between perceived usefulness, responsiveness, social benefits and satisfaction with the desire to continuously use Instagram pages of public libraries in West Azerbaijan province. Satisfaction with the path coefficient (0.446) was the strongest factor in predicting the continued use of Instagram pages of public libraries in West Azerbaijan province during the COVID-19 pandemic. After satisfaction, responsiveness, usefulness, and social benefits, respectively, had the greatest impact on the desire to continuously use these pages. Interestingly, no significant relationship was observed between the variables of ease of use, expectations, perceived enjoyment, type of post uploaded, post upload time, content, social influence, and correlation with the tendency to continuously use Instagram pages of public libraries. The results related to the path coefficients of the factors of type of uploaded post, time of uploading post, ease of use and content on the perceived usefulness of users from the Instagram pages of public libraries in West Azerbaijan province showed that there is a positive and significant relationship and the type of uploaded post with the path coefficient (0/290) was the strongest predictor of perceived usefulness. Furthermore, the analysis of path coefficients showed that the relationship between perceived enjoyment and perceived usefulness on user satisfaction is not significant, but the coefficients of the effect of ease of use and expectations on user satisfaction from Instagram pages of public libraries in West Azerbaijan Province is positive and significant. In general, the value of the goodness of fit was 0/641, which indicates the appropriateness of the overall fit of the model. Originality/value: Considering that the desire and intention to continue using social media sites is an act after their admission and so far, few studies have identified the factors influencing the desire to continue using social media, especially Instagram pages in public libraries, the results of this study can have valuable scientific and practical implications for managers and policy makers in this field.

Mg and its alloys have been introduced as promising biodegradable materials for biomedical implant applications due to their excellent biocompatibility, mechanical behavior, and biodegradability. However, their susceptibility to rapid corrosion within the body poses a significant challenge and restricts their applications. To overcome this issue, various surface modification techniques have been developed to enhance the corrosion resistance and bioactivity of Mg-based implants. PEO is a potent technique for producing an oxide film on a surface that significantly minimizes the tendency to corrode. However, the inevitable defects due to discharges and poor biological activity during the coating process remain a concern. Therefore, adding suitable particles during the coating process is a suitable solution. Hydroxyapatite (HAp) has attracted much attention in the development of biomedical applications in the scientific community. HAp shows excellent biocompatibility due to its similarity in chemical composition to the mineral portion of bone. Therefore, its combination with Mg-based implants through PEO has shown significant improvements in their corrosion resistance and bioactivity. This review paper provides a comprehensive overview of the recent advances in the preparation, characterization, corrosion behavior and bioactivity applications of HAp particles on Mg-based implants by PEO.

Introduction: Fungal aerosols from landfill sites can play a fundamental role in environmental pollution and health. The present study aimed to assess the dispersion of fungal aerosols from municipal solid waste disposal site. Materials and Methods: In this cross-sectional study, the concentration of fungal aerosols was determined in four geographical directions at distances of 250, 500, 750, and 1000 m around landfill site. Relative humidity and temperature were also measured. Moreover the concentration and type of the fungal taxa isolated from landfill site under different environmental and metrological conditions were evaluated. Results: The results showed that the maximum and minimum concentrations of fungal aerosol in the landfill site were 256.18 ± 59.7 CFU/m3 and 76.56 ± 23.2 CFU/m3, respectively. The most frequent fungi detected from municipal landfill site included Penicillium (43.67%), Cladosporium (33.54%), Yeast (7.60%), Aspergillus (5.91%), Curvularia (3.62%), Chrysosporium (1.57%), Alternaria (1.54%), Scopulariopsis (0.84%), and Ulocladium (0.60%) taxa. The maximum identified fungal aerosol concentration in the area around the solid waste landfill was 350 CFU/m3. Furthermore, the concentration of fungal aerosols in the environment was significantly related to relative humidity, wind direction, and temperature in spring and winter (P < 0.05). Conclusion: Municipal solid waste disposal site can be a potential source for fungal aerosol dispersion. Moreover, fungal aerosols concentration is correlated with wind direction and speed, relative humidity, and temperature.

To adapt to the changes in nature, living systems adjust their structure and function according to the environmental conditions. Scientists are inspired by nature and try to create materials that can change their behavior depending on the situation, just like living organisms do to survive. The idea of intelligent materials comes from natural biological systems, which follow a mechanism of sensing, reacting, and learning. Smart polymers, also known as stimuli-responsive, are a group of materials that possess the ability to respond to specific stimuli by undergoing reversible changes in their properties. Smart polymers have amazing features that come from their flexibility and responsiveness. They can change their molecular structure and function to suit different external stimuli or environmental changes. These materials are like living systems that adapt to their surroundings. Smart polymers have unique and highly desirable properties that make them attractive for a wide range of applications in medicine. This article reviews provides a comprehensive review of the recent advances in smart functional polymers, exploring their responses to various stimuli, be it physical, chemical, or biological. It also discusses some of the most advanced medical applications of these polymers, showcasing their transformative potential as materials that dynamically adjust to their environment.

Abstract While being a relatively prevalent condition particularly among aging patients, peripheral arterial disease (PAD) of lower extremities commonly goes undetected or misdiagnosed due to its symptoms being nonspecific. Additionally, progression of PAD in the absence of timely intervention can lead to dire consequences. Therefore, development of non-invasive and affordable diagnostic approaches can be highly beneficial in detection and treatment planning for PAD patients. In this study, we present a contrast-free ultrasound-based quantitative blood flow imaging technique for PAD diagnosis. The method involves monitoring the variations of blood flow in the calf muscle in response to thigh-pressure-cuff-induced occlusion. Four quantitative metrics are introduced for analysis of these variations. These metrics include post-occlusion to baseline flow intensity variation (PBFIV), total response region (TRR), Lag0 response region (L0RR), and Lag4 (and more) response region (L4 + RR). We examine the feasibility of this method through an in vivo study consisting of 14 PAD patients with abnormal ankle-brachial index (ABI) and 8 healthy volunteers. Ultrasound data acquired from 13 legs in the patient group and 13 legs in the healthy group are analyzed. Out of the four utilized metrics, three exhibited significantly different distributions between the two groups (p-value

Abstract Purpose Changes in microcirculation of axillary lymph nodes (ALNs) may indicate metastasis. Reliable noninvasive imaging technique to quantify such variations is lacking. We aim to develop and investigate a contrast-free ultrasound quantitative microvasculature imaging technique for detection of metastatic ALN in vivo. Experimental design The proposed ultrasound-based technique, high-definition microvasculature imaging (HDMI) provides superb images of tumor microvasculature at sub-millimeter size scales and enables quantitative analysis of microvessels structures. We evaluated the new HDMI technique on 68 breast cancer patients with ultrasound-identified suspicious ipsilateral axillary lymph nodes recommended for fine needle aspiration biopsy (FNAB). HDMI was conducted before the FNAB and vessel morphological features were extracted, analyzed, and the results were correlated with the histopathology. Results Out of 15 evaluated quantitative HDMI biomarkers, 11 were significantly different in metastatic and reactive ALNs (10 with P <

The Arvand River forms the border between Iran and Iraq and is the only permanent river discharging into the Persian Gulf(PG). It is a tidal river adversely affected by sedimentation,which is more likely resulted from tidal asymmetry. The tidal barrier(TB) has remarkable effects on the tidal regime. To assess these effects on the tidal waves asymmetry,it is critical to study the two main factors of closure percentage(CP) and closure duration(CD). This manuscript aims to investigate the tidal barrier effect on the asymmetry of the tidal waves propagating through the estuary. To evaluate tidal asymmetry,Tidal Asymmetry Index(TAI) is introduced based on the relative phase angle of the M2 and M4 components through the river. A two-dimensional Delft3D hydrodynamic model is utilized. The tidal wave is flood dominant, and its relative phase angle increased slightly, from 90 to 135 degrees in Km 40 and then decreased to just under 90 degrees near the Abadan(65km) and constant along the Abadan to Khorramshahr. The tidal barrier has changed the tidal regime in the river which leads to relatively constant tidal asymmetry during the 45km upward. To reach the highest TAI, a closure percentage and duration of 55% and 180 minutes are estimated. The tidal barrier operation also adversely affects the amplitude of the M2 and M4 components. M4 component amplitude increases before reaching the TB and then decreases. The decrease is more elaborated from kilometer 45 onward. Increasing the closure percentage amplifies the changes described above,but it has little effect on the general trends.

Abstract Background There is a strong correlation between the morphological features of new tumor vessels and malignancy. However, angiogenic heterogeneity necessitates 3D microvascular data of tumor microvessels for more reliable quantification. To provide more accurate information regarding vessel morphological features and improve breast lesion characterization, we introduced a quantitative 3D high-definition microvasculature imaging (q3D-HDMI) as a new easily applicable and robust tool to morphologically characterize microvasculature networks in breast tumors using a contrast-free ultrasound-based imaging approach. Methods In this prospective study, from January 2020 through December 2021, a newly developed q3D-HDMI technique was evaluated on participants with ultrasound-identified suspicious breast lesions recommended for core needle biopsy. The morphological features of breast tumor microvessels were extracted from the q3D-HDMI. Leave-one-out cross-validation (LOOCV) was applied to test the combined diagnostic performance of multiple morphological parameters of breast tumor microvessels. Receiver operating characteristic (ROC) curves were used to evaluate the prediction performance of the generated pooled model. Results Ninety-three participants (mean age 52 ± 17 years, 91 women) with 93 breast lesions were studied. The area under the ROC curve (AUC) generated with q3D-HDMI was 95.8% (95% CI 0.901–1.000), yielding a sensitivity of 91.7% and a specificity of 98.2%, that was significantly higher than the AUC generated with the q2D-HDMI (p = 0.02). When compared to q2D-HDMI, the tumor microvessel morphological parameters obtained from q3D-HDMI provides distinctive information that increases accuracy in differentiating breast tumors. Conclusions The proposed quantitative volumetric imaging technique augments conventional breast ultrasound evaluation by increasing specificity in differentiating malignant from benign breast masses.

Ruddlesden‐Popper (RP) oxides have emerged as a promising alternative to Ni cermet electrodes for high‐temperature steam electrolysis due to their superior oxide ion mobility and conductivity. Combining RP with perovskite (P) can provide superior electrocatalytic activity toward hydroxide oxidation and reduction reaction, driving higher efficiency in solid oxide cells (SOC). This work provides a novel approach to enhancing SOC performance by employing A‐site Ce‐substituted Sr0.6Pr0.4‐xCexMnO3 (x = 0.1‐0.3) electrodes, investigating their phase evolution, crystal properties, and cation oxidation states under oxidizing and reducing atmospheres. X‐ray diffraction analysis of heat‐treated powder in a reducing atmosphere revealed forming mixed P and RP structures at 600–800 °C for x = 0.1 and 0.2, which provides excellent conductivity and electrocatalytic activity. Consequently, outstanding cell performance is achieved, with low polarization resistances of 0.053 ± 0.004 Ω cm2 at 800 °C. The voltage response at different current densities in an electrolyte‐supported cell revealed a high power density of 1.084 W cm−2 in fuel cell operation and a current density of 1.00 A cm−2 at the thermoneutral voltage at 850 °C in steam electrolysis. Moreover, a low overpotential degradation rate of 45 mV kh−1 demonstrated the remarkable potential of the SPCM electrode as a promising Ni‐free candidate for SOC application. [ABSTRACT FROM AUTHOR]

Abstract Background Low specificity in current breast imaging modalities leads to increased unnecessary follow-ups and biopsies. The purpose of this study is to evaluate the efficacy of combining the quantitative parameters of high-definition microvasculature imaging (HDMI) and 2D shear wave elastography (SWE) with clinical factors (lesion depth and age) for improving breast lesion differentiation. Methods In this prospective study, from June 2016 through April 2021, patients with breast lesions identified on diagnostic ultrasound and recommended for core needle biopsy were recruited. HDMI and SWE were conducted prior to biopsies. Two new HDMI parameters, Murray’s deviation and bifurcation angle, and a new SWE parameter, mass characteristic frequency, were included for quantitative analysis. Lesion malignancy prediction models based on HDMI only, SWE only, the combination of HDMI and SWE, and the combination of HDMI, SWE and clinical factors were trained via elastic net logistic regression with 70% (360/514) randomly selected data and validated with the remaining 30% (154/514) data. Prediction performances in the validation test set were compared across models with respect to area under the ROC curve as well as sensitivity and specificity based on optimized threshold selection. Results A total of 508 participants (mean age, 54 years ± 15), including 507 female participants and 1 male participant, with 514 suspicious breast lesions (range, 4–72 mm, median size, 13 mm) were included. Of the lesions, 204 were malignant. The SWE-HDMI prediction model, combining quantitative parameters from SWE and HDMI, with AUC of 0.973 (95% CI 0.95–0.99), was significantly higher than the result predicted with the SWE model or HDMI model alone. With an optimal cutoff of 0.25 for the malignancy probability, the sensitivity and specificity were 95.5% and 89.7%, respectively. The specificity was further improved with the addition of clinical factors. The corresponding model defined as the SWE-HDMI-C prediction model had an AUC of 0.981 (95% CI 0.96–1.00). Conclusions The SWE-HDMI-C detection model, a combination of SWE estimates, HDMI quantitative biomarkers and clinical factors, greatly improved the accuracy in breast lesion characterization.

IntroductionA contrast-free ultrasound microvasculature imaging technique was evaluated in this study to determine whether extracting morphological features of the vascular networks in hepatic lesions can be beneficial in differentiating benign and malignant tumors (hepatocellular carcinoma (HCC) in particular).MethodsA total of 29 lesions from 22 patients were included in this work. A post-processing algorithm consisting of clutter filtering, denoising, and vessel enhancement steps was implemented on ultrasound data to visualize microvessel structures. These structures were then further characterized and quantified through additional image processing. A total of nine morphological metrics were examined to compare different groups of lesions. A two-sided Wilcoxon rank sum test was used for statistical analysis.ResultsIn the malignant versus benign comparison, six of the metrics manifested statistical significance. Comparing only HCC cases with the benign, only three of the metrics were significantly different. No statistically significant distinction was observed between different malignancies (HCC versus cholangiocarcinoma and metastatic adenocarcinoma) for any of the metrics.DiscussionObtained results suggest that designing predictive models based on such morphological characteristics on a larger sample size may prove helpful in differentiating benign from malignant liver masses.

Background: Atherosclerosis is the primary cause of the cardiovascular disease (CVD). Several risk factors lead to atherosclerosis, and altered nutrition is one among those. Nutrition has been ignored quite often in the process of CVD risk assessment. Altered nutrition along with carotid ultrasound imaging-driven atherosclerotic plaque features can help in understanding and banishing the problems associated with the late diagnosis of CVD. Artificial intelligence (AI) is another promisingly adopted technology for CVD risk assessment and management. Therefore, we hypothesize that the risk of atherosclerotic CVD can be accurately monitored using carotid ultrasound imaging, predicted using AI-based algorithms, and reduced with the help of proper nutrition. Layout: The review presents a pathophysiological link between nutrition and atherosclerosis by gaining a deep insight into the processes involved at each stage of plaque development. After targeting the causes and finding out results by low-cost, user-friendly, ultrasound-based arterial imaging, it is important to (i) stratify the risks and (ii) monitor them by measuring plaque burden and computing risk score as part of the preventive framework. Artificial intelligence (AI)-based strategies are used to provide efficient CVD risk assessments. Finally, the review presents the role of AI for CVD risk assessment during COVID-19. Conclusions: By studying the mechanism of low-density lipoprotein formation, saturated and trans fat, and other dietary components that lead to plaque formation, we demonstrate the use of CVD risk assessment due to nutrition and atherosclerosis disease formation during normal and COVID times. Further, nutrition if included, as a part of the associated risk factors can benefit from atherosclerotic disease progression and its management using AI-based CVD risk assessment.