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BACKGROUND AND OBJECTIVE: The central organ of the human nervous system is the brain, which receives and sends stimuli to the various parts of the body to engage in daily activities. Uncontrolled growth of brain cells can result in tumors which affect the normal functions of healthy brain cells. An automatic reliable technique for detecting tumors is imperative to assist medical practitioners in the timely diagnosis of patients. Although machine learning models are being used, with minimal data availability to train, development of low-order based models integrated with machine learning are a tool for reliable detection. METHODS: In this study, we focus on comparing a low-order model such as proper orthogonal decomposition (POD) coupled with convolutional neural network (CNN) on 2D images from magnetic resonance imaging (MRI) scans to effectively identify brain tumors. The explainability of the coupled POD-CNN prediction output as well as the state-of-the-art pre-trained transfer learning models such as MobileNetV2, Inception-v3, ResNet101, and VGG-19 were explored. RESULTS: The results showed that CNN predicted tumors with an accuracy of 99.21% whereas POD-CNN performed better with about 1/3rd of computational time at an accuracy of 95.88%. Explainable AI with SHAP showed MobileNetV2 has better prediction in identifying the tumor boundaries. CONCLUSIONS: Integration of POD with CNN is carried for the first time to detect brain tumor detection with minimal MRI scan data. This study facilitates low-model approaches in machine learning to improve the accuracy and performance of tumor detection.

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Biofouling poses significant challenges for marine transportation due to increased skin drag, which results in increased fuel cost and associated [Formula: see text] emissions. Current antifouling methods involving polymer coating, biocides, and self-depleting layers harm marine ecosystems and contribute to marine pollution. Significant advancements have resulted in using bioinspired coatings to address this issue. However, prior investigations have predominantly focused on wettability and adhesion aspects, resulting in a limited understanding of the impact of flow regime on bioinspired structure patterns for antifouling. We conducted comprehensive experiments with two bioinspired coatings1 under laminar and turbulent flow regimes and compared them with a smooth surface. The two coatings are composed of regular arrangements of micropillars measuring 85 µm in height and spaced at 180 µm (pattern A) and 50 µm high micropillars spaced at 220 µm (pattern B). Theoretical arguments indicate that wall-normal velocity fluctuations near the micropillars' top significantly contribute to reducing the onset of biofouling under turbulence compared to the smooth surface. Pattern A coating can effectively decrease biofouling by 90% for fouling sizes exceeding 80 microns when compared to a smooth surface subjected to a turbulent flow regime. The coatings exhibited comparable anti-biofouling properties under a laminar flow. Also, the smooth surface experienced substantially higher biofouling under laminar flow compared to turbulent conditions. This underscores how the effectiveness of anti-biofouling approaches is critically influenced by the flow regime.

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BACKGROUND: In respiratory fluid dynamics research, it is typically assumed that the wall of the trachea is smooth. However, the trachea is structurally supported by a series of cartilaginous rings that create undulations on the wall surface, which introduce perturbations into the flow. Even though many studies use realistic Computer Tomography (CT) scan data to capture the complex geometry of the respiratory system, its limited spatial resolution does not resolve small features, including those introduced by the cartilaginous rings. RESULTS: Here we present an experimental comparison of two simplified trachea models with Grade II stenosis (70% blockage), one with smooth walls and second with cartilaginous rings. The use a unique refractive index-matching method provides unprecedented optical access and allowed us to perform non-intrusive velocity field measurements close to the wall (e.g., Particle Image Velocimetry (PIV)). Measurements were performed in a flow regime comparable to a resting breathing state (Reynolds number ReD = 3350). The cartilaginous rings induce velocity fluctuations in the downstream flow, enhancing the near-wall transport of momentum flux and thus reducing flow separation in the downstream flow. The maximum upstream velocity in the recirculation region is reduced by 38%, resulting in a much weaker recirculation zone- a direct consequence of the cartilaginous rings. CONCLUSIONS: These results highlight the importance of the cartilaginous rings in respiratory flow studies and the mechanism to reduce flow separation in trachea stenosis.

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The COVID-19 pandemic has caused a multi-scale impact on the world population that started from a nano-scale respiratory virus and led to the shutdown of macro-scale economies. Direct transmission of SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) and its variants through aerosolized droplets is a major contributor towards increasing cases of this infection. To curb the spread, one of the best engineered solutions is the use of face masks to prevent the passage of infectious saliva micro-droplets from an infected person to a healthy person. The commercially available masks are single use, passive face-piece filters. These become difficult to breathe in during strenuous activities. Also, they need to be disposed regularly due to accumulation of unwanted particulate and pathogens over time. Frequent disposal of these masks is unsustainable for the environment. In this study, we have proposed a novel design for a filter for enhanced virus filtration, better breathability, and virus inactivation over time. The filter is called Hy-Cu named after its (Hy) drophobic properties and another significant layer comprises of copper (Cu). The breathability (pressure drop across filter) of Hy-Cu is tested and compared with widely used surgical masks and KN95 masks, both experimentally and numerically. The results show that the Hy-Cu filter offers at least 10% less air resistance as compared to commercially available masks. The experimental results on virus filtration and inactivation tests using MS2 bacteriophage (a similar protein structure as SARS-CoV-2) show that the novel filter has 90% filtering efficiency and 99% virus inactivation over a period of 2 h. This makes the Hy-Cu filter reusable and a judicious substitute to the single use masks.

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The COVID-19 pandemic has resulted in high demand for disinfection technologies. However, the corresponding spray technologies are still not completely optimized for disinfection purposes. There are important problems, like the irregular coverage and dripping of disinfectant solutions on hard and vertical surfaces. In this study, we highlight two major points. Firstly, we discuss the effectiveness of the electrostatic spray deposition (ESD) of nanoparticle-based disinfectant solutions for systematic and long-lasting disinfection. Secondly, we show that, based on the type of material of the substrate, the effectiveness of ESD varies. Accordingly, 12 frequently touched surface materials were sprayed using a range of electrostatic spray system parameters, including ion generator voltage, nozzle spray size and distance of spray. It was observed that for most cases, the surfaces become completely covered with the nanoparticles within 10 s. Acrylic, Teflon, PVC, and polypropylene surfaces show a distinct effect of ESD and non-ESD sprays. The nanoparticles form a uniform layer with better surface coverage in case of electrostatic deposition. Quantitative variations and correlations show that 1.5 feet of working distance, an 80 µm spray nozzle diameter and an ion generator voltage of 3-7 kV ensures a DEF (differential electric field) that corresponds to an optimized charge-to-mass ratio, ensuring efficient coverage of nanoparticles.

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Coexisting with the current COVID-19 pandemic is a global reality that comes with unique challenges impacting daily interactions, business, and facility maintenance. A monumental challenge accompanied is continuous and effective disinfection of shared spaces, such as office/school buildings, elevators, classrooms, and cafeterias. Although ultraviolet light and chemical sprays are routines for indoor disinfection, they irritate humans, hence can only be used when the facility is unoccupied. Stationary air filtration systems, while being irritation-free and commonly available, fail to protect all occupants due to limitations in air circulation and diffusion. Hence, we present a novel collaborative robot (cobot) disinfection system equipped with a Bernoulli Air Filtration Module, with a design that minimizes disturbance to the surrounding airflow and maneuverability among occupants for maximum coverage. The influence of robotic air filtration on dosage at neighbors of a coughing source is analyzed with derivations from a Computational Fluid Dynamics (CFD) simulation. Based on the analysis, the novel occupant-centric online rerouting algorithm decides the path of the robot. The rerouting ensures effective air filtration that minimizes the risk of occupants under their detected layout. The proposed system was tested on a 2 × 3 seating grid (empty seats allowed) in a classroom, and the worst-case dosage for all occupants was chosen as the metric. The system reduced the worst-case dosage among all occupants by 26% and 19% compared to a stationary air filtration system with the same flow rate, and a robotic air filtration system that traverses all the seats but without occupant-centric planning of its path, respectively. Hence, we validated the effectiveness of the proposed robotic air filtration system.

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Mangrove swamps are extremely productive ecosystems providing many ecological services in coastal regions. The hydrodynamic interactions of mangrove roots and water flow have been proposed as a key element to mitigate erosion. Several studies reveal that precise prediction of the morphological evolution of coastal areas, in the face of global warming and the consequent sea-level rise, requires an understanding of interactions between root porosity (the fraction of the volume of void space over the total volume), water flows, and sediment transport. Water flows around the mangrove prop roots create a complex energetic process that mixes up sediments and generates a depositional region posterior to the roots. In this work, we investigated the boundary layer behind permeable arrays of cylinders (patch) that represent the mangrove roots to explore the impact of patch porosity on the onset of sediment transport. The flow measurements were performed in a vertical plane along the water depth downstream of the mangrove root models. A high-resolution Particle Image Velocimetry (PIV) was used in a flume to observe the impact of porosity on the mean flow, velocity derivatives, skin friction coefficient, and production of turbulent kinetic energy for Reynolds number of 2500 (based on patch diameter length-scale). Here, we proposed a predictive model for critical velocity for incipient motion that takes into account the mangrove roots porosity and the near-bed turbulence effect. It is found that the patch with the [Formula: see text] porosity, has the maximum critical velocity over which the sediment transport initiates. We found the optimum porosity has the minimum sediment erosion and creates negative vorticity sources near the bed that increases the critical velocity. This signifies an optimum porosity for the onset of sediment transport consistent with the porosity of mangroves in nature. The phenomenological model is elucidated based on an analysis of the vorticity evolution equation for viscous incompressible flows. For the optimum porous patch, a sink of vorticity was formed which yielded to lower the near-bed turbulence and vorticity. The minimum velocity fluctuations were sufficient to initiate the boundary layer transition, however, the viscous dissipation dominated the turbulence production to obstruct the sediment transport. This work identified the pivotal role of mangrove root porosity in sediment transport in terms of velocity and its derivatives in wall-bounded flows. Our work also provides insight into the sediment transport and erosion processes that govern the evolution of the shapes of shorelines.

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Objective: This study aimed to evaluate the knowledge of professional caregivers of dependent elderly. Methods: The study population consisted (n=24) and dependent elders (n=157) in a nursing home in Santa Maria, Brazil. Participants answered a questionnaire to determine if they have qualifications to perform their activities regarding oral hygiene, and to the elderly were carried out clinical tests to assess the IMP. Data were analyzed according to descriptive and inferential analysis using Saphiro-Wilk, Mann-Whitney, Wilcoxon and Kruskal-Wallis test (p≤ 0.05). Results: It was found that 79% of caregivers were qualified, and as respect to the elders, was found that 20% had a bad mucosal and plaque index (IMP), 26% unacceptable and 54% acceptable. Conclusion: Caregivers had a high percentage of qualification which did not reflect the conservation of the elderly's oral hygiene.

Objetivo ­ Avaliar o conhecimento dos profissionais cuidadores de idosos dependentes. Métodos ­ A população do estudo foi composta por cuidadores (n=24) e idosas dependentes (n=157) de um lar de idosos de Santa Maria/RS, Brasil. Os participantes responderam a um questionário para determinar se possuíam qualificação para realizar suas atividades com relação à higiene bucal. Com relação às idosas, foram realizados exames clínicos para avaliar o índice de mucosa e placa (IMP). Os dados foram avaliados de acordo com análise descritiva e inferencial, utilizando os testes de Saphiro-Wilk, Mann-Whitney, Wilcoxon e Kruskal-Wallis (p ≤ 0.05). Resultados ­ Os resultados mostraram que 79% dos profissionais avaliados eram qualificados; com relação às idosas, 20% possuíam índice IMP ruim, 26% não aceitável e 54% aceitável. Conclusão ­ Os cuidadores apresentaram um alto percentual de conhecimento e qualificação, o que não se refletiu na manutenção da higiene bucal das idosas.

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BACKGROUND: Despite the prevailing assumption of "smooth trachea walls" in respiratory fluid dynamics research, recent investigations have demonstrated that cartilaginous rings in the trachea and main bronchi have a significant effect on the flow behavior and in particle deposition. However, there is not enough detailed information about the underlying physics of the interaction between the cartilage rings and the flow. MATERIALS AND METHODS: This study presents an experimental observation of a simplified Weibel-based model of the human trachea and bronchi with cartilaginous rings. A transparent model and refractive index-matching methods were used to observe the flow, particularly near the wall. The flow was seeded with tracers to perform particle image velocimetry and particle tracking velocimetry to quantify the effect the rings have on the flow near the trachea and bronchi walls. The experiments were carried out with a flow rate comparable with a resting state (trachea-based Reynolds number of ReD = 2650). RESULTS: The results present a previously unknown phenomenon in the cavities between the cartilaginous rings: a small recirculation is observed in the upstream side of the cavities throughout the trachea. This recirculation is due to the adverse pressure gradient created by the expansion, which traps particles within the ring cavity, thus affecting the treatment of patients suffering from lung disease and other respiratory conditions. CONCLUSIONS: The detection of recirculation zones in the cartilage ring cavities sheds light on the particle deposition mechanism and helps explain results from previous studies that have observed an enhancement of particle deposition in models with cartilage rings. These results bring to light the importance of including cartilage rings in experimental, numerical, and theoretical models to better understand particle deposition in the trachea and bronchi. In addition, the results provide scientists and medical staff with new insights for improving drug delivery.

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Flow separation and vortex shedding are some of the most common phenomena experienced by bluff bodies under relative motion with the surrounding medium. They often result in a recirculation bubble in regions with adverse pressure gradient, which typically reduces efficiency in vehicles and increases loading on structures. Here, the ability of an engineered coating to manipulate the large-scale recirculation region was tested in a separated flow at moderate momentum thickness Reynolds number, [Formula: see text] We show that the coating, composed of uniformly distributed cylindrical pillars with diverging tips, successfully reduces the size of, and shifts downstream, the separation bubble. Despite the so-called roughness parameter, [Formula: see text], falling within the hydrodynamic smooth regime, the coating is able to modulate the large-scale recirculating motion. Remarkably, this modulation does not induce noticeable changes in the near-wall turbulence levels. Supported with experimental data and theoretical arguments based on the averaged equations of motion, we suggest that the inherent mechanism responsible for the bubble modulation is essentially unsteady suction and blowing controlled by the increasing cross-section of the tips. The coating can be easily fabricated and installed and works under dry and wet conditions, increasing its potential impact on a diverse range of applications.

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Understanding how fluid flow interacts with micro-textured surfaces is crucial for a broad range of key biological processes and engineering applications including particle dispersion, pathogenic infections, and drag manipulation by surface topology. We use high-speed digital holographic microscopy (DHM) in combination with a correlation based de-noising algorithm to overcome the optical interference generated by surface roughness and to capture a large number of 3D particle trajectories in a microfluidic channel with one surface patterned with micropillars. It allows us to obtain a 3D ensembled velocity field with an uncertainty of 0.06% and 2D wall shear stress distribution at the resolution of ~65 µPa. Contrary to laminar flow in most microfluidics, we find that the flow is three-dimensional and complex for the textured microchannel. While the micropillars affect the velocity flow field locally, their presence is felt globally in terms of wall shear stresses at the channel walls. These findings imply that micro-scale mixing and wall stress sensing/manipulation can be achieved through hydro-dynamically smooth but topologically rough micropillars.

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We present a comparison of the flow characteristics in an idealized smooth trachea model and a second model which has a roughness simulating cartilaginous rings. We use refractive index-matched particle image velocimetry (PIV) to measure the velocity field in a two-generation model of the trachea and main bronchi. The flow rate has a trachea-based Reynolds number Re=2800, which is comparable to a resting state. Our results show considerable differences between both cases, the most important of which is the size and magnitude of recirculation zones at the inlet of both bronchi. The smooth case shows a larger separation bubble at the bronchi entrance, which may retain aerosols and have different effects on particles of different sizes. Furthermore, the smooth case displays a higher vorticity along the bottom walls of the bronchi, while a higher vorticity is seen along the trachea walls in the ׳ringed׳ model. These findings suggest that modeling the trachea and main bronchi as smooth tubes may not be justified, since the flow conditions in lower generations will be affected by these differences.

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