Search Results (18,585)

Abstract: Background/Objectives: Three-dimensional (3D) analysis of maxillofacial structures in dysmorphic patients offers clinical advantages over 2D analysis due to its high accuracy and precision in measuring many morphological parameters. Currently, no reliable gold standard exists for calculating 3D volumetric measurements of maxillofacial structures when captured by 3D surface imaging techniques. The aim of this scoping review is to provide an overview of the scientific literature related to 3D surface imaging methods used for volumetric analysis of the dysmorphic maxillofacial structures of patients affected by CL/P or other syndromes and to provide an update on the existing protocols, methods, and, when available, reference data. Methods: A total of 17 papers selected according to strict inclusion and exclusion criteria were reviewed for the qualitative analysis out of more than 4500 articles published between 2002 and 2024 that were retrieved from the main electronic scientific databases according to the PRISMA-ScR guidelines. A qualitative synthesis of the protocols used for the selection of the anatomical areas of interest and details on the methods used for the calculation of their volume was completed. Results: The results suggest a great degree of heterogeneity between the reviewed studies in all the aspects analysed (patient population, anatomical structure, area selection, and volume calculation), which prevents any chance of direct comparison between the reported volumetric data. Conclusion: Our qualitative analysis revealed dissimilarities in the procedures specified in the studies, highlighting the need to develop uniform methods and protocols and the need for comparative studies to verify the validity of methods in order to achieve high levels of scientific evidence, homogeneity of volumetric data, and clinical consensus on the methods to use for 3D volumetric surface-based analysis. Full article

The maximal vertical distance (MVD) recursive algorithm, a novel approach for the optimal discretization of stress–strain material curves, is proposed. The algorithm simplifies the process of defining multilinear curves from material stress–strain curves when conducting a finite element analysis (FEA) of components. By directly selecting points on the material curve, the MVD algorithm eliminates the requirement for initial discretization, thereby minimizing information loss. As the measure of goodness of fit of the simplified polyline to the original curve, the percentage of stress deviation (SD) is proposed. The algorithm can generate multiple multilinear curves while keeping the stress deviation of each curve within a predefined limit. This feature is particularly beneficial during the finite element analysis of components exhibiting complex and position-dependent material properties, such as surface-hardened components, ensuring consistent modelling accuracy of material properties across the components’ geometry. Consistent accuracy also proves advantageous when exploring multiple differing material states of quenched and tempered steel, ensuring fair and reliable comparisons. The MVD algorithm was compared with existing algorithms from the literature, consistently maintaining the accuracy of the multilinear curves within predetermined limits using the fewest possible points. Full article

Mass spectrometry (MS) is a widely used analytical technique including medical diagnostics, forensic toxicology, food and water analysis. The gold standard for quantifying compounds involves using stable isotope-labeled internal standards (SIL-IS). However, when these standards are not commercially available, are prohibitively expensive, or are extremely difficult to synthesize, alternative external quantification techniques are employed. We hereby present a novel, convenient and cheap quantification approach—quantification via post column infusion (PCI). As a proof of concept, we demonstrated PCI quantification for the immunosuppressant tacrolimus in whole blood using liquid chromatography–tandem mass spectrometry (LC-MS/MS). The validation results met the criteria according to the guideline on bioanalytical method validation of the European Medicine Agency (EMA), achieving imprecisions and inaccuracies with coefficient of variation and relative bias below 15%. Anonymized and leftover whole blood samples from immunosuppressed patients receiving tacrolimus were used for method comparison (PCI quantification vs. conventional internal standard (IS) quantification). Both methods showed strong agreement with a Pearson correlation coefficient of r = 0.9532. This novel PCI quantification technique (using the target analyte itself) expands the quantification options available in MS, providing reliable results, particularly when internal standards are unavailable or unaffordable. With the current paper, we aim to demonstrate that our innovative PCI technique has great potential to overcome practical issues in quantification and to provide guidance on how to incorporate PCI in existing or new LC-MS methods. Moreover, this study demonstrated a more convenient method for correcting matrix effects in comparison to alternative PCI techniques. Full article

Scapular dyskinesia, glenohumeral internal rotation deficit, upper posterior labral anterior tears, and rotator cuff injuries are common in athletes who play “overhead” sports due to their repetitive excessive movements. The aims of this study are to propose a new protocol with kinematic analysis coupled with sEMG and to objectively analyze the effect of a specific prevention exercise protocol. Thirty-two subjects (age: 22 ± 4 years, height: 183 ± 3.2 cm, BMI: 23 ± 0.96 kg/m²), including sixteen healthy subjects (Group A) and sixteen male water polo athletes (Group B), underwent a three-dimensional motion analysis based on optoelectronic and sEMG systems. A functional evaluation was performed on Group A and Group B to assess the reliability of the operator-dependent tasks and collect a series of normative data, before starting the prevention protocol (T0) and after 8 weeks (T1). The athletes performed a specific exercise protocol to prevent shoulder injuries. In Group B, the movements of abduction (T0: 111° ± 24°; T1: 140° ± 13°) and extension (T0: 72°± 10°; T1: 84° ± 2.8°) of the glenohumeral joint and the scapulothoracic joint (T0: 33° ± 8.36°; T1: 40.5° ± 10.6°) significantly improved. A significant reduction (in %) in the maximum voluntary contraction (MCV) at T1 of the upper trapezius, teres minor, and pectoralis major was observed. This protocol provides objective data in a simple and reliable way for the functional assessment of the shoulder in water polo players during the sport season. Full article

Structural damage identification has been one of the key applications in the field of Structural Health Monitoring (SHM). With the development of technology and the growth of demand, the method of identifying damage anomalies in plate structures is increasingly being developed in pursuit of accuracy and high efficiency. Principal Component Analysis (PCA) has always been effective in damage identification in SHM, but because of its sensitivity to outliers and low robustness, it does not work well for complex damage or data. The effect is not satisfactory. This paper introduces the Robust Principal Component Analysis (RPCA) model framework for the characteristics of PCA that are too sensitive to the outliers or noise in the data and combines it with Lamb to achieve the damage recognition of wavefield images, which greatly improves the robustness and reliability. To further improve the real-time monitoring efficiency and reduce the error, this paper proposes a non-convex approximate RPCA (NCA-RPCA) algorithm model. The algorithm uses a non-convex rank approximation function to approximate the rank of the matrix, a non-convex penalty function to approximate the norm to ensure the uniqueness of the sparse solution, and an alternating direction multiplier method to solve the problem, which is more efficient. Comparison and analysis with various algorithms through simulation and experiments show that the algorithm in this paper improves the real-time monitoring efficiency by about ten times, the error is also greatly reduced, and it can restore the original data at a lower rank level to achieve more effective damage identification in the field of SHM. Full article

Accurate rock mass quality classification is crucial for the design and construction of underground projects. Traditional methods often rely on expert experience, introducing subjectivity, and struggle with complex geological conditions. Machine learning algorithms have improved this issue, but obtaining complete rock mass quality datasets is often difficult due to high cost and complex procedures. This study proposed a hybrid XGBoost model for predicting rock mass quality using incomplete datasets. The zebra optimization algorithm (ZOA) and Bayesian optimization (BO) were used to optimize the hyperparameters of the model. Data from various regions and types of underground engineering projects were utilized. Adaptive synthetic (ADASYN) oversampling addressed class imbalance. The model was evaluated using metrics including accuracy, Kappa, precision, recall, and F1-score. The ZOA-XGBoost model achieved an accuracy of 0.923 on the test set, demonstrating the best overall performance. Feature importance analysis and individual conditional expectation (ICE) plots highlighted the roles of RQD and UCS in predicting rock mass quality. The model’s robustness with incomplete data was verified by comparing its performance with other machine learning models on a dataset with missing values. The ZOA-XGBoost model outperformed other models, proving its reliability and effectiveness. This study provides an efficient and objective method for rock mass quality classification, offering significant value for engineering applications. Full article

Tourism eco-efficiency has played a significantly essential role in the sustainable development of tourism destinations and tourism industries, providing ideal inputs and outputs amidst the deepening environmental crisis. This study evaluates the development level of tourism eco-efficiency using the Super-SBM model with undesirable outputs, employing the Malmquist-Luenberger (ML) index to analyse the internal optimisation forces of tourism eco-efficiency. Furthermore, human capital is assessed through both horizontal and vertical education levels, followed by a panel Tobit econometric analysis to explore the external impact mechanisms on tourism eco-efficiency. The results show that (1) Technological advancement is the core intrinsic driver for optimising tourism eco-efficiency. (2) In the analysis of influencing mechanisms, Human capital significantly contributes to enhancing tourism eco-efficiency, a conclusion upheld even after conducting robustness tests. (3) Analysis of mediating mechanisms indicates that tourism industry agglomeration is a critical pathway through which human capital enhances tourism eco-efficiency. This correlation has been proven reliable by regional regression analysis. (4) Results of the threshold model test suggest a law of “increasing marginal effect” concerning the positive impact of human capital on tourism eco-efficiency within the regulation of tourism industry agglomeration. Consequently, regions should actively promote the roles of human capital and tourism industry agglomeration in advancing tourism eco-efficiency, improving resource utilization efficiency, and tourism industry specialization to foster sustainable tourism development. Full article

With the emergence and development of application requirements such as data analysis and publishing, it is particularly important to use differential privacy protection technology to provide more reliable, secure, and compliant datasets for research in the field of children’s health. This paper focuses on the differential privacy protection of the ultrasound examination health dataset of adolescents in southern Texas from three aspects: differential privacy protection with output perturbation on basic statistics, publication of differential privacy marginal histogram and synthesized data, and a machine learning differential privacy learning algorithm. Firstly, differential privacy protection results with output perturbation show that Laplace and Gaussian mechanisms for numerical data, as well as the exponential mechanism for non-numerical data, can achieve the goal of protecting privacy. The exponential mechanism provides higher privacy protection. Secondly, a differential privacy marginal histogram with four attributes can be obtained with an appropriate privacy budget that approximates the marginal histogram of the original data. In order to publish synthetic data, we construct a synthetic query to obtain the corresponding differential privacy histogram for two attributes. Further, a synthetic dataset can be constructed by following the data distribution of the original dataset and the quality of the synthetic data publication can also be evaluated by the mean square error and error rate. Finally, consider a differential privacy logistic regression model under machine learning to predict whether children have fatty liver in binary classification tasks. The experimental results show that the model combined with quadratic perturbation has better accuracy and privacy protection. This paper can provide differential privacy protection models under different demands, which provides important data release and analysis options for data managers and research organizations, in addition to enriching the research on child health data releasing and mining. Full article

Probability of detection (POD) is an acknowledged mean of evaluation for many investigations aiming at detecting some specific property of a subject of interest. For instance, it has had many applications for Non-Destructive Evaluation (NDE), aimed at identifying defects within structural architectures, and can easily be used for structural health monitoring (SHM) systems, meant as a compact and more integrated evolution of the former technology. In this paper, a probability of detection analysis is performed to estimate the reliability of an SHM system, applied to a wing box composite spar for bonding line quality assessment. Such a system is based on distributed fiber optics deployed on the reference component at specific locations for detecting strains; the attained data are then processed by a proprietary algorithm whose capability was already tested and reported in previous works, even at full-scale level. A finite element (FE) model, previously validated by experimental results, is used to simulate the presence of damage areas, whose effect is to modify strain transfer between adjacent parts. Numerical data are used to verify the capability of the SHM system in revealing the presence of the modeled physical discontinuities with respect to a specific set of loads, running along the beam up to cover its complete extension. The POD is then estimated through the analysis of the collected data sets, wide enough to assess the global SHM system performance. The results of this study eventually aim at improving the current strategies adopted for SHM for bonding analysis by identifying the intimate behavior of the system assessed at the date. The activities herein reported have been carried out within the RESUME project. Full article

Background/Objectives: To better understand the impact of different oral conditions on children, several instruments are available to measure oral health-related quality of life (OHRQoL). To adapt and validate cross-culturally the Child Oral Health Impact Profile—Short Form 19 (COHIP-SF19) questionnaire to the Portuguese language. Methods: The COHIP SF-19 was translated and back-translated, and tested for its reliability and for psychometric properties in children who were aged between 8 and 17 years old. The COHIP-19-PT was tested for its internal consistency, construct validity, content validity, and test–retest reliability. Results: The COHIP-19-PT revealed good internal consistency (Cronbach’s alpha = 0.88) and test–retest reliability (interclass correlation = 0.78). The CFA analysis confirmed the structure of COHIP-19-PT. The first-order model showed an adequate fit: GFI = 0.878; CFI = 0.812; RMSEA = 0.083 (90% CI: 0.077–0.090). No invariance was found for the gender-based groups. The correlation between the sub-scales was also assessed, confirming significant correlations between all subdomains. Conclusions: The COHIP-19-PT is a valid and reliable scale for measuring children’s oral health-related quality of life. Full article

The method of measuring temperature using luminescence by analyzing the emission spectra of Pr³⁺-doped YF₃ using principal component analysis is presented. The Pr³⁺-doped YF₃ is synthesized using a solid-state technique, and its single-phase orthorhombic crystal structure is confirmed using X-ray diffraction. The emission spectra measured within the 93–473 K temperature range displays characteristic Pr³⁺ f-f electronic transitions. The red emission from the ³P_0,1→³H₆,³F₂ electronic transition mostly dominates the spectra. However, at low temperatures, the intensity of the green emissions from the ³P_0,1→³H₅, deep-red ³P_0,1→³F₄, and the deep-red emissions from the ³P_0,1→³F₄ transitions are considerably lower compared to the intensity of the red emissions. Temperature variations directly impact the photoluminescent spectra, causing a notable increase in the green and deep-red emissions from the ³P₁ excited state. We utilized the entire spectrum as an input for principal component analysis, considering each temperature as an independent group of data. The first principal component explained 99.3% of the variance in emission spectra caused by temperature and we further used it as a reliable temperature indicator for luminescence thermometry. The approach has a maximum absolute sensitivity of around 0.012 K⁻¹. The average accuracy and precision values are 0.7 K and 0.5 K, respectively. Full article

Background: Ehlers–Danlos syndrome (EDS), Marfan syndrome (MFS), and Loeys–Dietz syndrome (LDS) are connective tissue disorders frequently associated with vascular aneurysm formation, dissections, and subsequent major complications. Regular imaging surveillance is recommended for these conditions. However, no guidelines currently exist regarding imaging modality or surveillance intervals. Methods: This retrospective single-center observational study analyzed clinical and imaging data of patients attending an outpatient clinic for vascular connective tissue disorders between August 2008 and January 2024. Imaging (1424 data points in total) and clinical data were extracted from electronic health records. Analysis primarily included a comparison of vessel diameter progression across imaging modalities, with an additional review of the clinical history of vascular events. Results: In total, 19 patients with vascular connective tissue disorders (vCTDs) underwent consultations at our outpatient clinic. Nine (47.4%) patients experienced vascular events, while two (10.5%) passed away during the study period. Multimodal imaging surveillance revealed a tendency towards arterial diameter increase. Consistent ultrasound monitoring provided more reliable diameter progression data for the same arterial segment than a combination of imaging modalities. Temporal analysis indicated a tendency for the continuous growth of the abdominal aorta, the common and internal carotid artery, and the common femoral and popliteal artery. Conclusion: The study highlights the importance of standardized, modality-specific imaging protocols in monitoring patients with vCTDs. The variability in disease progression among these patients further complicates surveillance strategies, contemplating the need for individualized approaches. Further research and prospective multicenter studies are required to refine and improve monitoring protocols. Full article

Background and objectives: Automated drug dispensing systems (ADDs) have been introduced to improve the efficiency of dispensing and patient safety. The available questionnaires measure patient satisfaction with particular aspects of ADDs. Also, the level of patient satisfaction with ADDs is not widely established. This study aimed to develop and validate a novel questionnaire to assess patient satisfaction with ADDs. Methods: Content and construct validity procedures were used to validate the 20-item questionnaire with four domains, including pharmacy administration, dispensing practice, patient education, and the dispensing system. Two hundred consenting participants took part in this study, from those who visited the outpatient pharmacy in a government hospital. Results: The internal consistency of all four scale items shows acceptable reliability (>0.7). In the exploratory factor analysis, three items were removed due to poor factor loading and cross-loading. In the confirmatory factor analysis, the model has acceptable fit indices, including the comparative fit index (0.937), Tucker–Lewis’s index (0.924), standardized root mean square residual (0.051), root mean square error of approximation (0.057), and χ²/df (1.67). The convergent and discriminant validity were established, since the average variance extracted (AVE) was ≥0.5 and the squared correlation (SC) values of one construct with other constructs were less than the AVE of the specific construct. Conclusion: This study offered a reliable and valid 17-item questionnaire incorporating a multi-dimensional four-factor model to evaluate patient satisfaction with ADDs. The validated questionnaire can be utilized to explore patients’ perspectives on ADDs. Full article

Existing cleaning devices for edible sunflower have a low cleaning efficiency, high cleaning loss rate, and high impurity rate; therefore, a wind-sieve-type cleaning device for edible sunflower harvesting was designed. According to the characteristics of dislodged objects, a vibrating screen for the device was designed, and the dislodged edible sunflower objects in the device were used for a mechanical analysis of the force conditions to determine the displacement of the different edible sunflower objects dislodged by the action of airflow. Using FLUENT-DEM gas–solid coupling simulation technology, the velocity of the flow field, the velocity vector, and the trajectory of the dislodged objects inside the cleaning device were analyzed, and the law of motion applied to the airflow and the dislodged objects inside the device was clarified. According to the results of the coupled simulation analysis, the key factors affecting the operation of the cleaning device were wind speed, vibration frequency, and amplitude. Based on the key factors of wind speed, vibration frequency, and amplitude, an orthogonal rotary combination test was carried out with the loss rate and impurity rate of cleaned grains as the evaluation indexes, and the test parameters were optimized to obtain the optimal combination of operating parameters of the device, which were as follows: wind speed: 30 m·s⁻¹; vibration frequency: 8.44 Hz; and amplitude: 41.35 mm. With this combination of parameters, the seed loss rate and impurity rate reached 3.47% and 6.17%, respectively. Based on the optimal combination of operating parameters, a validation test was performed, and the results of this test were compared with the results of the test bench using this combination of parameters. The results show that the relative errors of the loss rate and impurity rate between the bench test and the simulation test were 3.45% and 3.07%, respectively, which are less than 5%, proving the reliability of the simulation analysis and the reasonableness of the design of the test bench. Full article

This study investigates active filling friction stir repair (AF-FSR) and passive filling friction stir repair (PF-FSR) for repairing AISI 304 stainless steel sheets, focusing on addressing the challenges posed by high melting point metals. The research involved repairing overlapping 2 mm thick sheets with pre-drilled holes of 2, 4, and 6 mm diameters, simulating broken components. Various process parameters, including rotational speed, dwell time, and the use of metal fillers, were tested to evaluate their impact on repair quality. The results demonstrated that PF-FSR provided superior mechanical strength to AF-FSR, particularly for larger pre-hole diameters. PF-FSR achieved higher shear tension strength due to better defect filling and reduced void formation, with shear tension strengths exceeding 25 kN for larger pre-holes and lower variability in strength measurements. AF-FSR was less effective for larger pre-holes, resulting in significant voids and reduced strength. Microstructural analysis revealed that PF-FSR facilitated more efficient material mixing and filling, minimizing unrepaired regions. However, excessive rotational speeds and dwell times in PF-FSR led to deformation and flash formation, highlighting the need for optimal parameter selection. Although further studies are needed, this study confirms the feasibility of FSR techniques for repairing small defects in AISI 304 steels, offering valuable insights for sustainable manufacturing practices in industries such as automotive and aerospace, where efficient and reliable repair methods are critical. Full article