Search Results (72)

Background: The COVID-19 pandemic progressed unevenly across the 417 municipalities of Bahia, Brazil. Pinpointing where and when risk peaked is vital for preparing for future emergencies. Methods: We performed an ecological, spatiotemporal study using COVID-19-confirmed cases in Bahia, Brazil, from January 2020 to December 2022. A discrete Poisson space–time scan in SaTScan-identified clusters. For each cluster, we calculated relative risk (RR) and Log Likelihood Ratio, considering p < 0.05 as significant. Results: A total of 33 clusters were detected; 25 statistically significant. The largest cluster (164 municipalities; May 2020–June 2021) comprised 702,720 observed versus 338,822 expected cases (RR = 2.8). Two overlapping large clusters (185 and 136 municipalities) during January–February 2022—coinciding with Omicron circulation—showed RR > 2.0. Localized clusters reached RR > 3.0. Spatially, risk concentrated in the south, southwest, and east of the state, with isolated countryside outbreaks. Conclusions: The heterogeneous spatiotemporal dynamics of COVID-19 in Bahia underscore the value of cluster detection for targeted surveillance and resource allocation. We recommend employing statistical techniques for early detection and control, as well as conducting further studies on socioeconomic and behavioral factors. Full article

Laser-induced periodic surface structures (LIPSSs) produced via ultrafast laser-induced oxidation offer a promising route for high-quality nanostructuring, with reduced thermal damage compared to conventional ablation-based methods. However, the influence of laser repetition frequency on the formation and morphology of oxidized LIPSSs remains insufficiently explored. In this study, we systematically investigate the effects of varying the femtosecond laser repetition frequency from 1 kHz to 100 kHz while keeping the total pulse number constant on the oxidation-induced LIPSSs formed on amorphous silicon films. Scanning electron microscopy and Fourier analysis reveal a transition between two morphological regimes with increasing repetition frequency: at low frequencies, the long inter-pulse intervals result in irregular, disordered oxidation patterns; at high frequencies, closely spaced pulses promote the formation of highly ordered, periodic surface structures. Statistical measurements show that the laser-modified area decreases with frequency, while the LIPSS period remains relatively stable and the ridge width exhibits a peak at 10 kHz. Finite-difference time-domain (FDTD) and finite-element simulations suggest that the observed patterns result from a dynamic balance between light-field modulation and oxidation kinetics, rather than thermal accumulation. These findings advance the understanding of oxidation-driven LIPSS formation dynamics and provide guidance for optimizing femtosecond laser parameters for precise surface nanopatterning. Full article

Platinum wires, known for their excellent electrical conductivity and durability, are widely used in high-precision industries, such as aerospace and automotive. These wires are typically coated with polyamide for protection; however, specific manufacturing processes require the coating to be selectively removed. Although traditional chemical stripping methods are effective, they are associated with high costs, safety concerns, and long processing times. As a result, laser ablation has emerged as a more efficient, precise, and cleaner alternative, especially at the microscale. In this study, ultraviolet nanosecond laser ablation was applied to remove polyamide coatings from ultra-thin platinum wires in a water-assisted environment. The presence of water enhances the process by promoting thermal management and minimizing debris. Key processing parameters, including the scanning speed, overlap percentage, and line distance, were evaluated. The optimal result was achieved at a scanning speed of 1200 mm/s, line distance of 1 µm, and single loop in water-ambient, where coating removal was complete, surface roughness remained low, and wire tensile strength was preserved. This performance is attributed to the effective energy distribution across the wire surface and reduced thermal damage due to the heat dissipation role of water, along with controlled overlap that ensured full coverage without overexposure. A thin, well-maintained water layer confined above the apex of the wire played a crucial role in regulating the thermal flow during ablation. This setup helped shield the delicate platinum substrate from overheating, thereby maintaining its mechanical integrity and preventing substrate damage throughout the process. This study primarily focused on analyzing the main effects and two-factor interactions of these parameters using Analysis of Variance (ANOVA). Interactions such as Speed × Overlap and Speed × Line Distance were statistically examined to identify the influence of combined factors on tensile strength and surface roughness. In the second phase of experimentation, the parameter space was further expanded by increasing the line distance and number of loops to reduce the overlap in the X-direction. This allowed for a more comprehensive process evaluation. Again, conditions around 1200 mm/s and 1500 mm/s with 2 µm line distance and two loops offered favorable outcomes, although 1200 mm/s was selected as the optimal speed due to better consistency. These findings contribute to the development of a robust, high-precision laser processing method for ultra-thin wire applications. The statistical insights gained through ANOVA offer a data-driven framework for optimizing future laser ablation processes. Full article

Background/Objectives: The removal of a fiber post (FP) during endodontic retreatment can be the source of significant complications. This study evaluated two commonly used techniques in removing a fiber post from an endodontically treated tooth by investigating three metrics: volume of dentin removed, efficiency, and temperature increase. Methods: Thirty extracted, single-rooted teeth were decoronated at the CEJ, then underwent endodontic treatment and post-space preparation. Fiber posts were bonded within the canal space. Teeth were pair-matched and randomly assigned to undergo post removal via Munce bur (MB) or diamond-coated ultrasonic tip (US). Teeth were scanned with micro-CT prior to post placement and after post removal. Results: The volume of dentin removal was not statistically significant between groups (p > 0.05), but the Munce bur resulted in eccentric removal patterns. There was a statistically significant difference in the time required to remove the fiber post between MB and US (p < 0.05). Removal of a fiber post with a Munce bur took an average of 58 s. Removal of a fiber post with an ultrasonic tip took an average of 502 s. There was no statistically significant difference in maximum temperature generated during post removal between MB and US (p > 0.05). Conclusions: Removal of a FP with a Munce bur requires significantly less time when compared to using an ultrasonic tip, with reduced risk of generating excessive heat for either technique with adequate coolant. US can stay more centered in the canal during FP removal when compared to Munce burs, potentially reducing unfavorable outcomes. Full article

Spatial, temporal, and space–time scan statistics can be used for geographical surveillance, identifying temporal and spatial patterns, and detecting outliers. While statistical cluster analysis is a valuable tool for identifying patterns, optimizing resource allocation, and supporting decision-making, accurately predicting future spatial clusters remains a significant challenge. Given the known relative risks of spatial clusters over the past k time intervals, the main objective of the present study is to predict the relative risks for the subsequent interval, $k+1$. Building on our prior research, we propose a predictive Markov chain model with an embedded corrector component. This corrector utilizes either multiple linear regression or an exponential smoothing method, selecting the one that minimizes the relative distance between the observed and predicted values in the k-th interval. To test the proposed method, we first calculated the relative risks of statistically significant spatial clusters of COVID-19 mortality in the U.S. over seven time intervals from May 2020 to March 2023. Then, for each time interval, we selected the top 25 clusters with the highest relative risks and iteratively predicted the relative risks of clusters from intervals three to seven. The predictive accuracies ranged from moderate to high, indicating the potential applicability of this method for predictive disease analytic and future pandemic preparedness. Full article

Background and Objectives: The present study aims to assess and compare the accuracy of post-space impressions captured by three different intraoral scanners (IOS) using various canal diameters. Methods: Three extracted natural maxillary central incisors were selected and prepared for a 1 mm wide margin and a 3 mm ferrule. All steps required for the endodontic procedure were performed, and the post space was prepared using post drills. The post length was kept constant at 12 mm, whereas the width was varied (Group 1: 1.4 mm, Group 2: 1.6 mm, and Group 3: 1.8 mm). Three IOSs (Trios3, iTero2, and Medit i700) were used to acquire a digital impression of the prepared post space. Each tooth was scanned 10 times by each scanner. So, in the end, 90 digital images were recorded, and the STL files were stored. GC Pattern resin was used to fabricate resin post and core patterns, which were scanned using an extraoral scanner (EOS). The STL file obtained was used as the reference file. To evaluate the trueness of the tested IOSs, each three-dimensional scan from an IOS was superimposed on the reference scan with the help of the Medit Design software 2.1.4. The software generates color plots and gives numerical values as deviations in the Root mean square (RMS) for the variance between the two superimposed scans. The data collected was tabulated for statistical analysis. One Way ANOVA was used to test the significance difference between three different IOSs, followed by Bonferroni Post-hoc test pairwise test to identify the differences between every two different IOS. Statistical significance was set at p < 0.05. Results: The mean deviation for trueness in post space impression values recorded by the Medit i700 was highest among groups 1, 2, and 3 [0.825 (±0.071), 0.673 (±0.042) and 0.516 (±0.039), respectively], followed by iTero2 [0.738 (±0.081), 0.569 (±0.043) and 0.470 (±0.037), respectively] and Trios3 [0.714 (±0.062), 0.530 (±0.040) and 0.418 (±0.024), respectively]. Significant differences were found between the groups for all three IOSs (Trios3: p-value < 0.0001; iTero2: p-value < 0.0001; Medit i700: p-value < 0.0001). Conclusions: Within the limitations of this study, it can be concluded that Trios3 IOS has higher accuracy (as it exhibited minimal deviation for trueness) in recording post space, followed by iTero2 and Mediti700 IOS. As the diameter of the post space is increased, the accuracy of recording by IOS increases. For all the tested IOSs (except for Trios3 and iTero2, when used to record post space with 1.8 mm canal diameter), the deviations in trueness were higher than the clinically acceptable limits. Thus, IOSs should be used cautiously when recording impressions of post spaces. Full article

Background: Diffusion-weighted imaging (DWI), a pivotal component of multiparametric magnetic resonance imaging (mpMRI), plays a pivotal role in the detection, diagnosis, and evaluation of gastric cancer. Despite its potential, DWI is often marred by substantial anatomical distortions and sensitivity artifacts, which can hinder its practical utility. Presently, enhancing DWI’s image quality necessitates reliance on cutting-edge hardware and extended scanning durations. The development of a rapid technique that optimally balances shortened acquisition time with improved image quality would have substantial clinical relevance. Objectives: This study aims to construct and evaluate the unsupervised learning framework called attention dual contrast vision transformer cyclegan (ADCVCGAN) for enhancing image quality and reducing scanning time in gastric DWI. Methods: The ADCVCGAN framework, proposed in this study, employs high b-value DWI (b = 1200 ${\mathrm{s}/\mathrm{mm}}^2$) as a reference for generating synthetic b-value DWI (s-DWI) from acquired lower b-value DWI (a-DWI, b = 800 ${\mathrm{s}/\mathrm{mm}}^2$). Specifically, ADCVCGAN incorporates an attention mechanism CBAM module into the CycleGAN generator to enhance feature extraction from the input a-DWI in both the channel and spatial dimensions. Subsequently, a vision transformer module, based on the U-net framework, is introduced to refine detailed features, aiming to produce s-DWI with image quality comparable to that of b-DWI. Finally, images from the source domain are added as negative samples to the discriminator, encouraging the discriminator to steer the generator towards synthesizing images distant from the source domain in the latent space, with the goal of generating more realistic s-DWI. The image quality of the s-DWI is quantitatively assessed using metrics such as the peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), feature similarity index (FSIM), mean squared error (MSE), weighted peak signal-to-noise ratio (WPSNR), and weighted mean squared error (WMSE). Subjective evaluations of different DWI images were conducted using the Wilcoxon signed-rank test. The reproducibility and consistency of b-ADC and s-ADC, calculated from b-DWI and s-DWI, respectively, were assessed using the intraclass correlation coefficient (ICC). A statistical significance level of p < 0.05 was considered. Results: The s-DWI generated by the unsupervised learning framework ADCVCGAN scored significantly higher than a-DWI in quantitative metrics such as PSNR, SSIM, FSIM, MSE, WPSNR, and WMSE, with statistical significance (p < 0.001). This performance is comparable to the optimal level achieved by the latest synthetic algorithms. Subjective scores for lesion visibility, image anatomical details, image distortion, and overall image quality were significantly higher for s-DWI and b-DWI compared to a-DWI (p < 0.001). At the same time, there was no significant difference between the scores of s-DWI and b-DWI (p > 0.05). The consistency of b-ADC and s-ADC readings was comparable among different readers (ICC: b-ADC 0.87–0.90; s-ADC 0.88–0.89, respectively). The repeatability of b-ADC and s-ADC readings by the same reader was also comparable (Reader1 ICC: b-ADC 0.85–0.86, s-ADC 0.85–0.93; Reader2 ICC: b-ADC 0.86–0.87, s-ADC 0.89–0.92, respectively). Conclusions: ADCVCGAN shows excellent promise in generating gastric cancer DWI images. It effectively reduces scanning time, improves image quality, and ensures the authenticity of s-DWI images and their s-ADC values, thus providing a basis for assisting clinical decision making. Full article

Arboviruses pose a significant global public health threat, with Ross River virus (RRV), Barmah Forest virus (BFV), and dengue virus (DENV) being among the most common and clinically significant in Australia. Some arboviruses, including those prevalent in Australia, have been reported to cause transfusion-transmitted infections. This study examined the spatiotemporal variation of these arboviruses and their potential impact on blood donation numbers across Australia. Using data from the Australian Department of Health on eight arboviruses from 2002 to 2017, we retrospectively assessed the distribution and clustering of incidence rates in space and time using Geographic Information System mapping and space–time scan statistics. Regression models were used to investigate how weather variables, their lag months, space, and time affect case and blood donation counts. The predictors’ importance varied with the spatial scale of analysis. Key predictors were average rainfall, minimum temperature, daily temperature variation, and relative humidity. Blood donation number was significantly associated with the incidence rate of all viruses and its interaction with local transmission of DENV, overall. This study, the first to cover eight clinically relevant arboviruses at a fine geographical level in Australia, identifies regions at risk for transmission and provides valuable insights for public health intervention. Full article

The integration of three-dimensional (3D) cameras into clinical practice for pre-operative planning and post-operative monitoring of rhinoplasties remains controversial. However, this technology offers the advantage of capturing the 3D surface without exposing patients to potentially harmful radiation. Continuous assessment allows the follow-up of swelling patterns, cartilage alignment, and bone remodeling. The primary objective of our study was to quantify changes in nasal structure before and after rhinoplasty by using 3D photography. Our study cohort consisted of 29 patients who underwent open structural rhinoplasty. We used the Artec Space Spider camera to acquire a total of 103 3D images. We collected pre-operative and at least two or three post-operative follow-up scans, which were taken one, three, and six months after surgery. We evaluated paired scans that included various time intervals to improve our understanding of swelling behavior and to ensure an objective analysis of changes. Eleven specific anatomical landmarks were identified for measurement. Two independent raters determined the distances between these landmarks over time. The calculation of intraclass correlation coefficients showed low inter-rater variability. Statistically significant changes over time (p < 0.05) were observed for various anatomical landmarks, including soft tissue nasion, soft tissue orbitale right, soft tissue maxillofrontale left, soft tissue maxillofrontale right, nasal bridge, and nasal break point. Conversely, no significant changes (p > 0.05) were observed in the measurements of soft tissue orbitale left, pronasale, subnasale, alare right, or alare left. A visual assessment was conducted using surface distance maps. The results indicate that the complete decrease in swelling takes at least 6 months or even longer. Additionally, 3D photography can provide an objectively comparable analysis of the face and external contours. Furthermore, it allows for a comparison of external contours and therefore pre- and post-operative differences. Full article

Global neural dynamics emerge from multi-scale brain structures, with nodes dynamically communicating to form transient ensembles that may represent neural information. Neural activity can be measured empirically at scales spanning proteins and subcellular domains to neuronal assemblies or whole-brain networks connected through tracts, but it has remained challenging to bridge knowledge between empirically tractable scales. Multi-scale models of brain function have begun to directly link the emergence of global brain dynamics in conscious and unconscious brain states with microscopic changes at the level of cells. In particular, adaptive exponential integrate-and-fire (AdEx) mean-field models representing statistical properties of local populations of neurons have been connected following human tractography data to represent multi-scale neural phenomena in simulations using The Virtual Brain (TVB). While mean-field models can be run on personal computers for short simulations, or in parallel on high-performance computing (HPC) architectures for longer simulations and parameter scans, the computational burden remains red heavy and vast areas of the parameter space remain unexplored. In this work, we report that our HPC framework, a modular set of methods used here to implement the TVB-AdEx model for the graphics processing unit (GPU) and analyze emergent dynamics, notably accelerates simulations and substantially reduces computational resource requirements. The framework preserves the stability and robustness of the TVB-AdEx model, thus facilitating a finer-resolution exploration of vast parameter spaces as well as longer simulations that were previously near impossible to perform. Comparing our GPU implementations of the TVB-AdEx framework with previous implementations using central processing units (CPUs), we first show correspondence of the resulting simulated time-series data from GPU and CPU instantiations. Next, the similarity of parameter combinations, giving rise to patterns of functional connectivity, between brain regions is demonstrated. By varying global coupling together with spike-frequency adaptation, we next replicate previous results indicating inter-dependence of these parameters in inducing transitions between dynamics associated with conscious and unconscious brain states. Upon further exploring parameter space, we report a nonlinear interplay between the spike-frequency adaptation and subthreshold adaptation, as well as previously unappreciated interactions between the global coupling, adaptation, and propagation velocity of action potentials along the human connectome. Given that simulation and analysis toolkits are made public as open-source packages, this framework serves as a template onto which other models can be easily scripted. Further, personalized data-sets can be used for for the creation of red virtual brain twins toward facilitating more precise approaches to the study of epilepsy, sleep, anesthesia, and disorders of consciousness. These results thus represent potentially impactful, publicly available methods for simulating and analyzing human brain states. Full article

Measuring human body dimensions is critical for many engineering and product design domains. Nonetheless, acquiring body dimension data for populations using typical anthropometric methods poses challenges due to the time-consuming nature of manual methods. The measurement process for three-dimensional (3D) whole-body scanning can be much faster, but 3D scanning typically requires subjects to change into tight-fitting clothing, which increases time and cost and introduces privacy concerns. To address these and other issues in current anthropometry techniques, a measurement system was developed based on portable, low-cost depth cameras. Point-cloud data from the sensors are fit using a model-based method, Inscribed Fitting, which finds the most likely body shape in the statistical body shape space and providing accurate estimates of body characteristics. To evaluate the system, 144 young adults were measured manually and with two levels of military ensembles using the system. The results showed that the prediction accuracy for the clothed scans remained at a similar level to the accuracy for the minimally clad scans. This approach will enable rapid measurement of clothed populations with reduced time compared to manual and typical scan-based methods. Full article

The aim of the study was to assess the impact of the COVID-19 pandemic on the notification of new VL cases in Brazil in 2020. It is an ecological and time-series study (2015–2020) with spatial analysis techniques, whose units of analysis were the 5570 Brazilian municipalities. The study population consisted of all new cases of VL recorded between 2015 and 2020. The P-score was calculated to estimate the percentage variation in new VL cases. Global and local univariate Moran’s Indices and retrospective space–time scan statistics were used in spatial and space–time analyses, respectively. It was expected that there would be 3627 new cases of VL in Brazil in 2020, but 1932 cases were reported (−46.73%). All Brazilian regions presented a negative percentage variation in the registration of new VL cases, with the Southeast (−54.70%), North (−49.97%), and Northeast (−44.22%) standing out. There was spatial dependence of the disease nationwide in both periods, before and during the first year of the COVID-19 pandemic. There was a significant reduction in the incidence of new VL cases in Brazil during the first year of the COVID-19 pandemic. These findings reinforce the need for better preparedness of the health system, especially in situations of new epidemics. Full article

In this paper, electroless nickel plating is explored for the protection of binder-jetting-based additively manufactured (AM) composite materials. Electroless nickel plating was attempted on binder-jetted composites composed of stainless steel and bronze, resulting in differences in the physicochemical properties. We investigated the impact of surface finishing, plating solution chemistry, and plating parameters to attain a wide range of surface morphologies and roughness levels. We employed the Keyence microscope to quantitatively evaluate dramatically different surface properties before and after the coating of AM composites. Scanning electron microscopy revealed a wide range of microstructural properties in relation to each combination of surface finishing and coating parameters. We studied chempolishing, plasma cleaning, and organic cleaning as the surface preparation methods prior to coating. We found that surface preparation dictated the surface roughness. Taguchi statistical analysis was performed to investigate the relative strength of experimental factors and interconnectedness among process parameters to attain optimum coating qualities. The quantitative impacts of phosphorous level, temperature, surface preparation, and time factor on the roughness of the nickel-plated surface were 17.95%, 8.2%, 50.02%, and 13.21%, respectively. On the other hand, the quantitative impacts of phosphorous level, temperature, surface preparation, and time factor on the thickness of nickel plating were 35.12%, 41.40%, 3.87%, and 18.24%, respectively. The optimum combination of the factors’ level projected the lowest roughness of Ra at 7.76 µm. The optimum combination of the factors’ level projected the maximum achievable thickness of ~149 µm. This paper provides insights into coating process for overcoming the sensitivity of AM composites in hazardous application spaces via robust coating. Full article

A method was previously developed to identify participant-specific parameters in a model of trabecular bone adaptation from longitudinal computed tomography (CT) imaging. In this study, we use these numerical methods to estimate changes in astronaut bone health during the distinct phases of spaceflight and recovery on Earth. Astronauts (N = 16) received high-resolution peripheral quantitative CT (HR-pQCT) scans of their distal tibia prior to launch (L), upon their return from an approximately six-month stay on the international space station (R+0), and after six (R+6) and 12 (R+12) months of recovery. To model trabecular bone adaptation, we determined participant-specific parameters at each time interval and estimated their bone structure at R+0, R+6, and R+12. To assess the fit of our model to this population, we compared static and dynamic bone morphometry as well as the Dice coefficient and symmetric distance at each measurement. In general, modeled and observed static morphometry were highly correlated (R²> 0.94) and statistically different (p < 0.0001) but with errors close to HR-pQCT precision limits. Dynamic morphometry, which captures rates of bone adaptation, was poorly estimated by our model (p < 0.0001). The Dice coefficient and symmetric distance indicated a reasonable local fit between observed and predicted bone volumes. This work applies a general and versatile computational framework to test bone adaptation models. Future work can explore and test increasingly sophisticated models (e.g., those including load or physiological factors) on a participant-specific basis. Full article

To address the problem of slow speed and low accuracy for recognizing and locating the explosive source in complex shallow underground blind spaces, this paper proposes an energy-focusing-based scanning and localization method. First, the three-dimensional (3D) energy field formed by the source explosion is reconstructed using the energy-focusing properties of the steered response power (SRP) localization model, and the velocity field is calculated based on a multilayered stochastic medium model by considering the random statistical characteristics of the medium. Then, a power function factor is introduced to quantum particle swarm optimization (QPSO) to search for and solve the above energy field and to approach the real location of the energy focus point. Additionally, the initial population is constructed based on the logistic chaos model to realize global traversal. Finally, extensive simulation results based on the real-world dataset show that compared to the baseline algorithm, the focusing accuracy of the energy field of the proposed scheme is improved by 117.20%, the root mean square error (RMSE) is less than 0.0551 m, the triaxial relative error (RE) is within 0.2595%, and the average time cost is reduced by 98.40%. It has strong advantages in global search capability and fast convergence, as well as robustness and generalization. Full article