Average Shape Research Articles

Structural, Optical and Antimicrobial Properties of Carbohydrate-Capped Cadmium Sulfide Nanoparticles

Cadmium sulfidenanoparticles (CdSNPs) were prepared through the chemical precipitation process where sweet potato starch and glucose-functioned as capping agents. Ultraviolet-Visible (UV-Vis) spectroscopy, Fourier Transform Infrared (FTIR) spectroscopy and X-ray diffraction (XRD) techniques were applied for the analysis of prepared CdSNPs. The absorption peaks in the UV-Vis spectroscopy towards the lower wavelength region compared to the bulk CdS (512 nm) indicated the formation of CdS particles in the nanometer scale range. FTIR spectroscopy showed the characteristic absorption peaks of the CdSNPs along with the functional groups present in starch and glucose, suggesting the possible interaction between CdSNPs and capping agents. The XRD revealed crystallographic information such as the average crystallite size and shape of CdSNPs. Using the Scherrer equation, the average crystallite size of CdSNPs was determined to be 11.48 nm and 16.03 nm for starch-capped and glucose-capped CdSNPs (CdS-St andCdS-Gl)respectively. Antibacterial and antifungal activities of the prepared CdSNPs were found to be highly efficient for various pathogenic bacteria and fungi. Hence in the present study, the new synthetic route of CdSNPs was applied, and antimicrobial activities were performed

Digital light processing 4D printing multilayer polymers with tunable mechanical properties and shape memory behavior

Four-dimensional (4D) printing has currently been renowned as a world-changing technology which has recently gained significant attention amongst researchers. It enables 3D printed objects to alter its shape, properties and functions through the application of external stimuli. However, the development of 4D printing has been impeded by the overexposure effect, which has made it difficult for photocuring to print gradient structures. In this paper, we propose a novel photocuring 4D printing strategy of gradient structures with tunable properties. Multi-walled carbon nanotubes (MWCNTs) are added to the intermediate layer (Fast Layer, FL) of multilayer shape memory polymers (SMPs) to reduce curing degree and absorb overexposure. The mechanical properties and shape memory behavior of multilayer SMPs can be tuned by adjusting the layer ratio of FL with low curing degree. Outcome of microscopic images, interlayer bonding force, and shore hardness originating from this study indicates that the printed multilayer SMPs possessed excellent interlayer bonding properties as well as obvious modulus differences between each layer. The average shape recovery speed (Sa) of multilayer SMPs was almost linearly related to the slice layer number of FL. The strategy was successfully demonstrated in the fabrication of multilayer SMPs with sequential recovery and multiple deformation behavior. An electrically responsive shape memory effect was also achieved by using embedded graphite electrothermal layer to exhibit its application in time-delay devices. The proposed strategy enables the application of multilayer SMPs gradient structures in soft robotics and flexible electronics.

Riparian forest response to extreme drought is influenced by climatic context and canopy structure

Droughts significantly impact forest ecosystems, reducing forest health and productivity, compromising ecosystem functioning, and nature-based solutions for climate change. The response and resilience of riparian forests to drought are poorly understood despite their key role in the functioning of aquatic and terrestrial ecosystems. Here we investigate riparian forest drought responses and resilience to an extreme drought event at a regional scale. We also examine how drought event characteristics, average climate conditions, topography, soil, vegetation structure, and functional diversity shape the resilience of riparian forests to drought. We used a time series of the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) to calculate the resistance to and recovery after an extreme drought (2017–2018) in 49 sites across an Atlantic-Mediterranean climate gradient in North Portugal. We used generalized additive models and multi-model inference to understand which factors best explained drought responses. We found a trade-off between drought resistance and recovery (maximum r = −0.5) and contrasting strategies across the climatic gradient of the study area. Riparian forests in the Atlantic regions showed comparatively higher resistance, while Mediterranean forests recovered more. Canopy structure and climate context were the most relevant predictors of resistance and recovery. However, median NDVI and NDWI had not returned to pre-drought levels (RcNDWI mean = 1.21, RcNDVI mean = 1.01) three years after the event. Our study shows that riparian forests have contrasting drought response strategies and may be susceptible to extended legacy effects associated with extreme and/or recurring droughts, similarly to upland forests. This work highlights the drought vulnerability of riparian ecosystems and emphasises the need for further studies on long-term resilience to droughts.

Polarization-Dependent Sum-Frequency-Generation Spectroscopy for In Situ Tracking of Nanoparticle Morphology.

The surface structure of oxide-supported metal nanoparticles can be determined via characteristic vibrations of adsorbed probe molecules such as CO. Usually, spectroscopic studies focus on peak position and intensity, which are related to binding geometries and number of adsorption sites, respectively. Employing two differently prepared model catalysts, it is demonstrated that polarization-dependent sum-frequency-generation (SFG) spectroscopy reveals the average surface structure and shape of the nanoparticles. SFG results for different particle sizes and morphologies are compared to direct real-space structure analysis by TEM and STM. The described feature of SFG could be used to monitor particle restructuring in situ and may be a valuable tool for operando catalysis.

Impact of human body shape on forced convection heat transfer

Predicting human thermal comfort and safety requires quantitative knowledge of the convective heat transfer between the body and its surrounding. So far, convective heat transfer coefficient correlations have been based only upon measurements or simulations of the average body shape of an adult. To address this knowledge gap, here we quantify the impact of adult human body shape on forced convection. To do this, we generated fifty three-dimensional human body meshes covering 1st to 99th percentile variation in height and body mass index (BMI) of the USA adult population. We developed a coupled turbulent flow and convective heat transfer simulation and benchmarked it in the 0.5 to 2.5m·s-1 air speed range against prior literature. We computed the overall heat transfer coefficients, hoverall, for the manikins for representative airflow with 2m·s-1 uniform speed and 5% turbulence intensity. We found that hoverall varied only between 19.9 and 23.2 W·m-2K-1. Within this small range, the height of the manikins had negligible impact while an increase in the BMI led to a nearly linear decrease of the hoverall. Evaluation of the local coefficients revealed that those also nearly linearly decreased with BMI, which correlated to an inversely proportional local area (i.e., cross-sectional dimension) increase. Since even the most considerable difference that exists between 1st and 99th percentile BMI manikins is less than 15% of hoverall of the average manikin, it can be concluded that the impact of the human body shape on the convective heat transfer is minor.

3D printing a universal knee meniscus using a custom collagen ink

Tears of the meniscus are among the most commonly diagnosed knee injuries. Because most of the meniscus lacks the ability to self-heal due to its low vascularity, surgical intervention is needed in more than 85% of cases. Tissue-engineered meniscal implants may provide a treatment strategy that better supports healing and long-term health and mobility benefits. We used three-dimensional printing to develop a “universal” human meniscal tissue repair device that can be trimmed to match the corresponding area of damage debrided during the patient's surgical repair. Computer aided design software was used to design an adult meniscus of average shape based on published physical dimensions. To reproduce the natural fiber arrangement found in the meniscus, the tool path for 3D bioprinting was structured to use alternating layers of circumferential and radial extrusions. We also developed extrudable, shear thinning bioinks based on meniscus biochemical components, including collagen I methacrylate, collagen II, and chondroitin sulfate methacrylate. The combination of this tissue-specific bioink and the deposition pattern to build the meniscus are novel. Ink formulations were evaluated with rheology to assess the viscosity and post-gelling stiffness. Inks retained shape fidelity when thermally gelled after printing into a support bath, and the fabricated menisci maintained stable dimensions for up to 4 weeks post printing. Bioprinted menisci containing human mesenchymal stem cells were also dimensionally stable, and viable cells were present up to 4 weeks post printing. Increased glycosaminoglycan deposition was noted in the bioprinted meniscus over 21 days, and decorin and collagen type I gene expression increased. Compression testing demonstrated that Young's modulus approaches 100 kPa when molded as a solid object and 45 kPa when extruded into the meniscus shape. This 3D printed, anisotropic meniscus emulates the natural architecture and biochemical composition of the natural human meniscus and has potential to be developed into a device for use in treatment of meniscal injuries.

Shape Sensing of Flexible Robots Based on Deep Learning

In this article, a deep learning method for the shape sensing of continuum robots based on multicore fiber bragg grating (FBG) fiber is introduced. The proposed method, based on an artificial neural network (ANN), differs from traditional approaches, where accurate shape reconstruction requires a tedious characterization of many characteristic parameters. A further limitation of traditional approaches is that they require either multiple fibers, whose location relative to the centerline must be precisely known (calibrated), or a single multicore fiber whose position typically coincides with the neutral line. The proposed method addresses this limitation and, thus, allows shape sensing based on a single multicore fiber placed off-center. This helps in miniaturizing and leaves the central channel available for other purposes. The proposed approach was compared to a recent state-of-the-art model-based shape sensing approach. A two-degree-of-freedom benchtop fluidics-driven catheter system was built to validate the proposed ANN. The proposed ANN-based shape sensing approach was evaluated on a 40-mm-long steerable continuum robot in both 3-D free-space and 2-D constrained environments, yielding an average shape sensing error of 0.24 and 0.49 mm, respectively. With these results, the superiority of the proposed approach compared to the recent model-based shape sensing method was demonstrated.

Nocturnal pollination is equally important as, and complementary to, diurnal pollination for strawberry fruit production

Declining insect populations and their associated pollination services to crops raise concerns for global food security. While most studies focus on the contribution of diurnal pollinators to crop yields, nocturnal pollination receives little attention. In this study, we used a randomised block design (n = 6) in the open ground to determine the relative contribution of nocturnal and diurnal pollination to strawberry yield. We found that, on average, there was no effect of insect pollination (nocturnal, diurnal, or both) on total number of fruits and total weight of fruits harvested per plant. However, when plants produced many fruits, night-pollinated and open-pollinated plants increased total fruit weight per plant, compared to plants that received no pollinators. Furthermore, compared to the no-pollinators treatment, individual fruit weight (g) was significantly higher in night-pollinated plants (27% higher) and open-pollinated plants (46% higher), whereas the day-pollinated treatment (17% higher) did not significantly differ from no-pollinators and night-pollinated plants. Fruit diameter (mm) followed a similar pattern. Fruit sweetness (%total soluble solids) was highest in the no-pollinated treatment, and other treatments did not differ from each other. The average fruit shape was of significantly poorer quality in the no-pollinators treatment than any of the other treatments, which did not significantly differ from each other, but did show a trend of fewer poorly shaped fruits. Overall, nocturnal pollination was at least equally important as, and highly complementary to diurnal pollination for determining strawberry fruit quality. However, we do not know the identity of the nocturnal pollinators. Nevertheless, nocturnal pollination seems to be an important, but overlooked part of the contribution to insect pollination to crop yield.

集束超音波中での気泡クラウド形成に関するマルチスケールシミュレーション

This study deals with a numerical simulation of the growth of bubble nuclei and the corresponding bubble cloud formation in a pressure field given by high intensity focused ultrasound (HIFU) backscattered from a laser-induced bubble interface. In the present paper, using a multiscale numerical method (Tamura et al., Japanese J. Multiphase Flow, 2022) in which the ghost fluid method is coupled with bubble dynamics, the growth of the bubble cloud which consists of multiple bubble layers is simulated continuously as observed in the experiments. It is shown that the distance between the first cavitation inception point and a laser-induced bubble interface is about 0.27λwhere λ is the wavelength of HIFU; the distance between bubble layers in the cloud is also about 0.35λ these distances in the simulation are in good agreement with the experiments. The influence of the configuration of bubble nuclei on the final form of a cone-shaped bubble cloud is investigated. It is also shown that the shape of each bubble layer, which depends on the initial configuration of bubble nuclei, affects the final formation of bubble clouds. This is because that the negative pressure due to the backscattering of HIFU is dependent on the shape of each bubble layer. The results also show that the averaged final shape of bubble clouds quantitively matches the results as observed in the experiment by Horiba et al. (J. Acoust. Soc. Am., 2020).

Machine Learning-Based Shape Error Estimation Using the Servomotor Current Generated During Micro-Milling of a Micro-Lens Mold

The demand for the mass production of micro-lens arrays (MLAs) is increasing. An MLA is fabricated through an injection molding process, and its mold is manufactured by a five-axis high-precision machine tool using a small diameter endmill. A visual examination is not available to judge the quality of the mold while machining. Therefore, an effective process monitoring technology must be developed. A promising approach is to apply a servomotor current to in-process monitoring because as long as the servomotor works well, no external sensors, capital investment, or maintenance processes are required. From this perspective, a machine learning-based shape error estimation method using only the servomotor current is proposed. To explore the relationship between the motor current generated during micro-milling and the shape error of the mold, the servomotor current in X-, Y-, and Z-axes was recorded, and the corresponding shape error of the MLA mold was measured after machining. Input data were prepared by converting time-domain servomotor current data to frequency-domain data using short-time Fourier transform and reducing the dimensions of the data via principal component analysis. In terms of a meaningful label for the output data, the average shape error in the machined area corresponding to each window was provided. The input/output relationships were used to train five different machine learning models, and the accuracy of shape error estimation using each model was evaluated. In addition, the estimation accuracies using the X-, Y-, and Z-axes were compared to find the axis that senses the shape error with the highest accuracy. The results show that the non-linear method using the X-axis servomotor current information closest to the machining point achieved the highest shape error estimation accuracy.

Scaling of Average Avalanche Shapes for Acoustic Emission during Jerky Motion of Single Twin Boundary in Single-Crystalline Ni2MnGa

Temporal average shapes of crackling noise avalanches, U(t) (U is the detected parameter proportional to the interface velocity), have self-similar behavior, and it is expected that by appropriate normalization, they can be scaled together according to a universal scaling function. There are also universal scaling relations between the avalanche parameters (amplitude, A, energy, E, size (area), S, and duration, T), which in the mean field theory (MFT) have the form E∝A3, S∝A2, S∝T2. Recently, it turned out that normalizing the theoretically predicted average U(t) function at a fixed size, U(t)=atexp-bt2 (a and b are non-universal, material-dependent constants) by A and the rising time, R, a universal function can be obtained for acoustic emission (AE) avalanches emitted during interface motions in martensitic transformations, using the relation R~A1-φ too, where φ is a mechanism-dependent constant. It was shown that φ also appears in the scaling relations E~A3-φ and S~A2-φ, in accordance with the enigma for AE, that the above exponents are close to 2 and 1, respectively (in the MFT limit, i.e., with φ= 0, they are 3 and 2, respectively). In this paper, we analyze these properties for acoustic emission measurements carried out during the jerky motion of a single twin boundary in a Ni50Mn28.5Ga21.5 single crystal during slow compression. We show that calculating from the above-mentioned relations and normalizing the time axis of the average avalanche shapes with A1-φ, and the voltage axis with A, the averaged avalanche shapes for the fixed area are well scaled together for different size ranges. These have similar universal shapes as those obtained for the intermittent motion of austenite/martensite interfaces in two different shape memory alloys. The averaged shapes for a fixed duration, although they could be acceptably scaled together, showed a strong positive asymmetry (the avalanches decelerate much slower than they accelerate) and thus did not show a shape reminiscent of an inverted parabola, predicted by the MFT. For comparison, the above scaling exponents were also calculated from simultaneously measured magnetic emission data. It was obtained that the φ values are in accordance with theoretical predictions going beyond the MFT, but the AE results for φ are characteristically different from these, supporting that the well-known enigma for AE is related to this deviation.

Instabilities of a droplet on a liquid substrate heated from below under the action of vibration

The action of vibration on Marangoni flows in a droplet on a liquid substrate heated from below is investigated. The analysis has been carried out using a closed system of strongly nonlinear equations. The problem is studied numerically in the framework of longwave amplitude equations and the precursor model. It is shown that vibrations slightly affect the average (inkpot) shape of the droplet.

Preparation and characterization of foamed ceramics from coal bottom ash for construction insulation materials

Foamed ceramic is a novel lightweight wall material combining high strength, low density, and excellent thermal insulation. This study used coal bottom ash (CBA) to fabricate microporous foamed ceramics by the high-temperature foaming method. The CBA content and heating rate effects on the bulk density, compressive strength, pore structure, and phase components of foamed ceramics were systematically investigated. The results demonstrate that using CBA in foamed ceramics can effectively improve the green body foaming capacity. With the increased CBA content, the bulk density of foamed ceramics dropped, while the average pore size and shape factor increased, jointly reducing the compressive strength. Meanwhile, the quartz phase content decreased, and the mullite phase appeared gradually. The transition of the main crystalline phase from MgAl2O4 to Mg0.7Fe0.23Al1.97O4 with the increased CBA content gave rise to a change in the color of the foamed ceramic. The elevation in the heating rate can improve the foaming ability of the green body, contributing to increased porosity. However, the rapid heating rate of 10 °C/min results in an uneven pore size distribution in the foamed ceramics containing more than 70 wt % CBA. It increases the temperature difference in the sample, promoting a stratified distribution of pore size in samples with a CBA content of less than 30 wt %.

Evaluation of Composites Reinforced by Processed and Unprocessed Coconut Husk Powder

Engineering activities aim to satisfy the demands of society. Not only should the economic and technological aspects be considered, but also the socio-environmental impact. In this sense, the development of composites with the incorporation of waste has been highlighted, aiming not only for better and/or cheaper materials, but also optimizing the use of natural resources. To obtain better results using industrial agro waste, we need to treat this waste to incorporate engineered composites and obtain the optimal results for each application desired. The objective of this work is to compare the effect of processing coconut husk particulates on the mechanical and thermal behavior of epoxy matrix composites, since we will need a smooth composite in the near future to be applied by brushes and sprayers with a high quality surface finish. This processing was carried out in a ball mill for 24 h. The matrix was a Bisphenol A diglycidyl ether (DGEBA)/triethylenetetramine (TETA) epoxy system. The tests that were performed were resistance to impact and compression, as well as the linear expansion test. Through this work, it can be observed that the processing of coconut husk powder was beneficial, allowing not only positive improvements to the properties of the composite, but also a better workability and wettability of the particulates, which was attributed to the change in the average size and shape of particulates. That means that the composites with processed coconut husk powders have improved impact strength (46 up to 51%) and compressive strength (88 up to 334%), in comparison with unprocessed particles.

A continuous constraint satisfaction problem for the rigidity transition in confluent tissues

Models of confluent tissues are built out of tessellations of the space (both in two and three dimensions) in which the cost function is constructed in such a way that individual cells try to optimize their volume and surface in order to reach a target shape. At zero temperature, many of these models exhibit a rigidity transition that separates two phases: a liquid phase and a solid (glassy) phase. This phenomenology is now well established but the theoretical understanding is still not complete. In this work we consider an exactly soluble mean field model for the rigidity transition which is based on an abstract mapping. We replace volume and surface functions by random non-linear functions of a large number of degrees of freedom forced to be on a compact phase space. We then seek for a configuration of the degrees of freedom such that these random non-linear functions all attain the same value. This target value is a control parameter and plays the role of the target cell shape in biological tissue models. Therefore we map the microscopic models of cells to a random continuous constraint satisfaction problem with equality constraints. We argue that at zero temperature, the rigidity transition corresponds to the satisfiability transition of the problem. We also characterize both the satisfiable (SAT) and unsatisfiable (UNSAT) phase. In the SAT phase, before reaching the rigidity transition, the zero temperature SAT landscape undergoes an replica symmetry breaking (RSB)/ergodicity breaking transition of the same type as the Gardner transition in amorphous solids. By solving the RSB equations we compute the SAT/UNSAT threshold and the critical behavior around it. In the UNSAT phase we also compute the average shape index as a function of the target one and we compare the thermodynamical solution of the model with the results of the numerical greedy minimization of the corresponding cost function.

Inhomogeneous Superconductivity Onset in FeSe Studied by Transport Properties

Heterogeneous superconductivity onset is a common phenomenon in high-Tc superconductors of both the cuprate and iron-based families. It is manifested by a fairly wide transition from the metallic to zero-resistance states. Usually, in these strongly anisotropic materials, superconductivity (SC) first appears as isolated domains. This leads to anisotropic excess conductivity above Tc, and the transport measurements provide valuable information about the SC domain structure deep within the sample. In bulk samples, this anisotropic SC onset gives an approximate average shape of SC grains, while in thin samples, it also indicates the average size of SC grains. In this work, both interlayer and intralayer resistivity were measured as a function of temperature in FeSe samples of various thicknesses. To measure the interlayer resistivity, FeSe mesa structures oriented across the layers were fabricated using FIB. As the sample thickness decreases, a significant increase in superconducting transition temperature Tc is observed: Tc raises from 8 K in bulk material to 12 K in microbridges of thickness ∼40 nm. We applied analytical and numerical calculations to analyze these and earlier data and find the aspect ratio and size of the SC domains in FeSe consistent with our resistivity and diamagnetic response measurements. We propose a simple and fairly accurate method for estimating the aspect ratio of SC domains from Tc anisotropy in samples of various small thicknesses. The relationship between nematic and superconducting domains in FeSe is discussed. We also generalize the analytical formulas for conductivity in heterogeneous anisotropic superconductors to the case of elongated SC domains of two perpendicular orientations with equal volume fractions, corresponding to the nematic domain structure in various Fe-based superconductors.

Assessment of SWAN and WAVEWATCH-III models regarding the directional wave spectra estimates based on Eastern Black Sea measurements

The spectral wave models are often calibrated or validated based on bulk wave data derived from spectral information such as the significant wave height (Hs) and mean period (Tm). However, the precision in the hindcasted spectral data was not evaluated in many seas, such as the Black Sea, due to the lack of spectral wave measurements. As part of this study, a spectral wave measuring buoy was installed near the cape Small Utrish to collect the spectral measurement data. The study objective is to assess the SWAN and WAVEWATCH-III (WWIII) models regarding the directional wave spectra estimates based on measurements conducted in the eastern Black Sea. For this purpose, the estimated spectral density distribution and spectral mean direction in terms of spectral frequency bins are assessed for both SWAN and WWIII outputs. The biases in variance densities are firstly calculated for both models at each frequency based on 14 710 spectral measurements, as well as the biases in the annual and seasonal averages. In addition, the correlation coefficients and root mean squared errors at each frequency are calculated and discussed. The accuracies in the mean direction at each spectral shape over the whole measurement period are secondly evaluated. Thirdly, the annual and seasonal averaged two-dimensional wave spectrums are discussed compared to measurements. The performances of both models are lastly verified based on bulk data measured at 8 locations on different coasts of the Black Sea. The results show that SWAN output fits better the average variance density shape at all frequency ranges f > 0.08Hz. However, it slightly overestimates the variance density in the 0.13–0.17 Hz range. In contrast to the SWAN model, WWIII data show only better correspondence in the 0.13–0.17 Hz frequency range but underestimate the lower frequency energies and overestimate higher frequency ranges. The SWAN model is therefore recommended for the spectral density estimate at seasonal and annual scales.

Finite driving rate effects in the nonequilibrium athermal random field Ising model of thin systems

Thin disordered ferromagnetic systems driven by varying magnetic field represent a challenge from theoretical, experimental and technological perspective. Understanding their temporal evolution under the mutual influence of finite driving rate with which the external magnetic field changes, geometry of the sample, and the amount of disorder is a complex task. It is studied here within the framework of the nonequilibrium athermal random field Ising model which has a dynamical behavior suitable for this kind of analysis both in statistical physics and physics of magnetism. Our results, obtained by means of numerical simulations performed at a discrete time scale of the model in a wide range of driving rates and domains of disorder, unveil the rate sensitivity exhibited by the response signal and the underlying avalanche distributions, correlation functions of spin-flip events, average avalanche shapes and the values of coercive field. Due to the rate-imposed spreading of multiple avalanches during the same/partially shared intervals of time, the pertaining effective exponents turn out to be rate-dependent as well. Our findings provide new insights on some features of field driven nonequilateral systems that could be applicable for investigations of a variety of thin systems driven at finite driving rates.

Persistent Opacification of the Woven EndoBridge Device: A Conebeam CT Analysis of the Bicêtre Occlusion Scale Score 1 Phenomenon.

Some Woven EndoBridge devices present a persistent intradevice opacification at imaging follow-up, described as the Bicêtre Occlusion Scale Score 1 (BOSS 1) phenomenon. The clinical implications remain unknown. We aimed here to analyze the factors influencing this occurrence and to precisely describe the evolution of BOSS 1 with time using conebeam CT. We retrospectively analyzed a prospectively maintained Woven EndoBridge database at our tertiary center and included all patients with isolated BOSS 1 and BOSS 1 associated with small neck remnant (BOSS 1 + 2). Two hundred sixty-seven aneurysms were treated with a Woven EndoBridge device between July 2012 and December 2021. Follow-up with DSA was available for 220 aneurysms (median, 5 months), among which BOSS 1 and 1 + 2 were found in 9.1% (20/220) (95% CI, 5.5%-12.7%). A second DSA follow-up (median, 17 months) was performed in 15 of these 20 aneurysms, which revealed that 40% had evolved to complete Woven EndoBridge occlusion, 33% showed a decreased persistent opacification, and 27% remained stable. BOSS 1 was significantly associated with postoperative antiplatelet medication, a lower aneurysm aspect ratio, and the use of the Woven EndoBridge 17 (P < .05). The average Woven EndoBridge shape modification was less pronounced in the BOSS 1 population (P < .02). None of the BOSS 1 or 1 + 2 aneurysms required retreatment or were associated with hemorrhage occurrence. Isolated persistent flow inside the Woven EndoBridge device at follow-up is rare and notably associated with antiplatelet prescription. It seems to present a benign course in most cases.

Detect Orientation of Symmetric Objects from Monocular Camera to Enhance Landmark Estimations in Object SLAM

Object simultaneous localization and mapping (SLAM) introduces object-level landmarks to the map and helps robots to further perceive their surroundings. As one of the most preferred landmark representations, ellipsoid has a dense mathematical expression and can represent the occupied space of objects with high accuracy. However, the orientations of ellipsoid approximations often fail to coincide with the orientation of objects. To further improve the performance of object SLAM systems with ellipsoid landmarks, we innovatively propose a strategy that first extracts the orientations of those symmetric human-made objects in a single frame and then implements the results of the orientation as a back-end constraint factor of the ellipsoid landmarks. Experimental results obtained show that, compared with the baseline, the proposed orientation detection method can reduce the orientation error by more than 46.5% in most tested datasets and improves the accuracy of mapping. The average translation, rotation and shape error improved by 63.4%, 61.7% and 42.4%, respectively, compared with quadric-SLAM. With only 9 ms additional time cost of each frame, the object SLAM system integrated with our proposed method can still run in real time.