Range Of Distances Research Articles

UNDULATING POTENTIALS OF RYDBERG Σ+-STATES OF ME-RG MOLECULES: NON-EMPIRICAL TREATMENT OF NA-HE EXCIPLEX

The multi-reference con guration interaction method based on single and double excitations (MR-CISD), l-independent core polarization potential (CPP) and diffuse function-saturated cc-pVQZ and aug-cc-pV5Z basis sets for Na and He atoms, respectively, have been used to perform non-relativistic calculations of potential energy curves and permanent dipole moment functions for the ground and excited electronic states of the exciplex Na-He molecule up to the Na(62S) state. The ab initio results obtained in a wide range of internuclear distances R [1.7, 20.0] (Å) have quantitatively claimed the undulating behavior of interatomic potentials, predicted within the framework of the inelastic scattering theory. It has been established that at large R the interatomic potentials and dipole moments of highly excited (3,6,10)2Σ+ states, converging to Na (n = 4, 5, 62S)+He(22S) atomic limits, are modulated by the nodal structure of the radial Rydberg wave function (n > 3) s-electron of Na atom during its scattering on the remote He atom.

Use of acoustic signals in Cape fur seal mother-pup reunions: individual signature, signal propagation and pup home range.

The Cape fur seal (Arctocephalus pusillus pusillus) is one of the most colonial mammals, with colonies of up to hundreds of thousands of individuals during the breeding season. During the lactation period, mothers and pups are regularly separated as females undertake multi-day foraging trips at sea. Mothers and pups use a mutual vocal recognition system to reunite after separation. Such communication is highly constrained by both high background noise and risk of individual confusion owing to the density of seals. This study aimed to experimentally assess the acoustic features relevant for mother-pup vocal identification and the propagation properties of their calls. Playback experiments revealed that mother and pup individual vocal signatures rely on both temporal and frequency parameters: amplitude and frequency modulations, timbre and fundamental frequency (f0). This is more parameters than in any colonial species studied so far. The combinational use of acoustic features reinforces the concept that both environmental and social constraints may have acted as selective pressures on the individual vocal recognition systems. Theoretical propagation distances of mother and pup vocalisations were estimated to be below the range of distances at which mother-pup reunions can occur. This suggests that Cape fur seals may have strong abilities to extract vocal signals from the background noise, as previously demonstrated in the highly colonial king penguin. Investigating the transmission of information throughout the propagation of the signal as well as the ability of the receiving individual to decipher vocal signatures is crucial to understanding vocal recognition systems in the wild.

Utilizing indicator functions with computational data to confirm nature of overlap in normal turbulent stresses: Logarithmic or quarter-power

Indicator functions of the streamwise normal-stress profiles (NSP), based on careful differentiation of some of the best direct numerical simulations (DNS) data from channel and pipe flows, over the range 550<Reτ<16 000, are examined to establish the existence and range in wall distances of either a logarithmic-trend segment or a 1/4-power region. For nine out of 15 cases of DNS data we examined where Reτ<2000, the NSP did not contain either of the proposed trends. As Reτ exceeds around 2000 a 1/4-power, reflecting the “bounded-dissipation” predictions of Chen and Sreenivasan [“Law of bounded dissipation and its consequences in turbulent wall flows,” J. Fluid Mech. 933, A20 (2022); “Reynolds number asymptotics of wall-turbulence fluctuations,” J. Fluid Mech. 976, A21 (2023)] and data analysis of Monkewitz [“Reynolds number scaling and inner-outer overlap of stream-wise Reynoldss stress in wall turbulence,” arXiv:2307.00612 (2023)], develops near y+=1000 and expands with Reynolds numbers extending to 1000<y+<10 000 for Reτ around 15 000. This range of 1/4-power NSP corresponds to a range of outer-scaled Y between around 0.3 and 0.7. The computational database examined did not include the zero-pressure-gradient boundary layer experiments at higher Reynolds numbers where the logarithmic trend in the NSP has been previously reported around y+ of 1000 by Marusic et al. [“Attached eddy model of wall turbulence,” Annu. Rev. Fluid Mech. 51, 49–74 (2019); “The logarithmic variance of streamwise velocity and conundrum in wall turbulence,” J. Fluid Mech. 933, A8 (2022)] according to a “wall-scaled eddy model.”

Energy absorption characteristics of expansion tube subjected to the coupled loading in near-field explosion

Expansion tube structures (ETSs) are extensively employed as energy-absorbing components in protective structures, yet their dynamic response under near-filed explosion remains inadequately understood, which limits their applications in anti-explosion devices. This paper investigates the response of ETS through explosion experiments, testing both the overpressure history of blast loading and the propagation process of detonation products. Following experimental verification, finite element models are established to obtain the characteristics of explosive loading and the response of ETS. The findings demonstrate that as the velocity of slider increases, the embedding displacement of ETS exceeding its limit induces a local buckling transformation in thin-wall tubes from one end buckling to simultaneous buckling at both ends. In the scaled distance range of 0.4–0.5 m/kg1/3, the energy absorption (EA) of ETS under different explosive masses exhibits distinct trends as the scaled distance increases, despite the decrease in peak pressure of blast loading. This is due to the coupling effect between blast shock waves and detonation products, resulting in diverse alterations in specific impulse with increasing scaled distance for varying explosive masses. In the case of oblique impact of blast loading, the percentage decrease in EA within the near-field range (Z < 0.8 m/kg1/3) is higher than that at mid-to-far range due to the uneven and random ejection of detonation products. The study elucidates the dynamic response of ETS under the coupled loading of blast wave and blast products, and provides valuable insights for optimizing designs of ETS utilized in near-field blast-resistant structures.

Analyzing Cooling Island Effect of Urban Parks in Zhengzhou City: A Study on Spatial Maximum and Spatial Accumulation Perspectives

As a result of urbanization, cities worldwide are experiencing urban heat island (UHI) challenges. Urban parks, which are essential components of urban blue and green landscapes, typically have lower temperatures in providing outdoor comfort than their surroundings with impervious surfaces. This phenomenon, known as the park cooling island effect (PCIE), has been recognized as an effective approach to mitigate the negative effects of the UHI in the context of sustainable development of urban environment. To cope with the serious UHI challenge and to guide urban park planning and design for Zhengzhou City, which is one of the China’s new first-tier cities, 35 urban parks in the city were analyzed in this study. Remotely sensed land surface temperature (LST) and reflectance images by Landsat 9 and Sentinel-2 were selected as data sources. A cubic polynomial model that depicts the relationship between the LST and the distance from the park edge was first built for each park. Based on this model, the spatial maximum perspective metrics (including the park cooling area (PCA) and park cooling efficiency (PCE)) and the spatial accumulation perspective metrics (including park cooling intensity (PCI) and park cooling gradient (PCG)) were calculated to quantify the PCIE of each park. The 35 parks were divided into three groups using the hierarchical clustering method for further analysis. For each group, the metrics of the PCIE were statistically analyzed, and the main factors influencing the PCIE were identified by the Spearman correlation coefficient. The results indicate the following: (1) The 35 urban parks exhibit an obvious PCIE. The maximum cooling distance is 133.95 ± 41.93 m. The mean LST of the park is 3.01 ± 1.23 °C lower than that within the maximum cooling distance range. (2) The PCIE varies among different types of parks. Parks with large areas and covered by certain water bodies generally exhibit higher PCA, PCI, and PCG values. However, parks with small areas and mainly covered by vegetation show higher PCE values, which makes them more economical in exerting the PCIE. (3) Park area and landscape shape index (LSI) were positively correlated with PCA, PCI, and PCG. However, there is a threshold in the relationship between the park area and the PCI. A park area of approximately 19 ha can produce a higher PCI than a smaller one. In central urban areas with limited space, parks with small areas, complex shapes, and predominant vegetation coverage can be designed to achieve higher cooling efficiency.

A Video App for Screening Osgood-Schlatter Disease Using Soccer Instep Kicking Motion Analysis.

Osgood-Schlatter disease (OSD) is a type of osteochondrosis and traction apophysitis that results from repeated contractions of the quadriceps femoris muscle on the tibial tuberosity. Its prevention, early diagnosis, and treatment are crucial because it causes chronic knee pain and surgical approaches are required if left untreated. Three-dimensional motion analysis is a useful approach for elucidating the pathological factors of OSD; however, it requires advanced cameras, sophisticated facilities, and expensive software. Conversely, the advent of technology has provided affordable video recording devices, and smartphone/tablet-based applications have enabled two-dimensional (2D) motion analysis. This emerging tool and artificial intelligence technology were used to analyze the pivot leg from videos recorded on a tablet device during the instep kicks of adolescent soccer players. Therefore, in this study, we aimed to determine whether the pathological factors for OSD occurring in the pivot foot can be identified through a simple 2D motion analysis using a tablet device. In total, 94 knees of 47 soccer players (aged 14.1±0.8 years, all male) who belong to a single soccer club were evaluated. OSD was diagnosed using ultrasonography and physical examination (a positive bone fragment on ultrasonography or tenderness at the tibial tuberosity). Lower limb muscle tightness was evaluated using the finger-floor distance, straight leg raising test, heel-buttock distance, Thomas test, and ankle range of motion using a goniometer. We then performed motion analysis, and the instep kicking motion was recorded using a video camera on a tablet device. The joint angles of the hip, knee, and ankle were measured using a real-time human-pose detection system. Data were compared between the OSD and non-OSD groups. Overall, six of the 47 players (12.8%) were diagnosed with OSD. No correlation was found between lower limb tightness and the occurrence of OSD in all indices. However, the 2D motion analysis revealed that the knee flexion angle at the time of plantar placement during the instep kick movement was significantly larger in the OSD group than in the non-OSD group (OSD group: 42.0±7.2˚, non-OSD group: 33.5±6.6˚, *p=0.013). A video motion analysis revealed that the knee flexion angle during the instep kicking motion was significantly greater in athletes with OSD of the supporting foot.

Object–Environment Fusion of Visual System for Automatic Pear Picking

A visual system is a key tool for automatic fruit harvesting. It faces the challenges of varied occlusion and illumination in the field, resulting in difficulties in fruit recognition and picking. At present, there are many studies that lack a comprehensive analysis of the impact of the environment on harvesting. This study proposes an object–environment fusion visual system. It comprises modules for object perception, environment perception, and picking pose estimation. The object perception module aims to identify and locate pears. The environment perception module is deployed to analyze the three-dimensional (3D) information of objects and obstacles. Finally, the picking pose estimation module fuses the information of the objects and environment to calculate the collision-free picking position and orientation. Additionally, specific implementations are employed for each module. It compares three networks to identify pears for object perception. Voxel-based representation is used to simplify point clouds for environmental perception. A sampler and evaluator are applied for picking pose estimation. The S1 and S2 datasets were acquired in a laboratory pear tree model and the orchard of Zhejiang Academy of Agricultural Sciences, respectively, to evaluate the proposed method. In the S2 dataset, the success rate for picking pose estimation reached 87.11% within the distance range of 30∼50 cm. All of the results demonstrate that the proposed method can be applied to visual perception for automatic pear harvesting.

The percolation inception of the CNT-polymer nanocomposites with the magneto-electric field effects on the CNT subbands

The percolation inception of CNT-polymer nanocomposites is studied considering the magneto-electric field effects on CNT subbands. The analytical model predicts the electrical conductivity where CNTs are modeled as slender rods with their geometric orientations as randomly distributed or aligned to transfer electrons at tunneling distance range. The tunneling effect takes into account the electron transmission between every linked pair of CNTs when evaluating electrical resistance. The subsequent CNT displacement computation and the resistance change comprise the other phase of the modeling approach. Piezoresistivity results of the analyses agree well with the experimental data when considering tunneling behavior in the percolation transition zone. The magnetic field enhances the field affected subbands and increases the electrical conductivity by enhancing the mobility of the charges. The results reveal that the efficiency of CNT network in transmitting charges is increased with higher aspect ratio CNTs that scaled the sensitivity to lower values.

Collapse of a giant iceberg in a dynamic Southern Ocean marine ecosystem: In situ observations of A-68A at South Georgia

Large icebergs (>20 km long) are responsible for most of the freshwater discharged into the Southern Ocean. We report on in situ and satellite observations made during the break-up phase around South Georgia of the giant tabular iceberg A-68A. The in situ measurements were obtained during a 4-day visit by a research vessel in February 2021, where physical, chemical and biological measurements were made at a range of distances away from the main and subsidiary icebergs. These results were compared to a far-field station 133 km away. Upstream of the iceberg field, water column structure was similar to ambient water although there was evidence of iceberg-associated phytoplankton as a likely remnant of the passage of the icebergs. Nevertheless, enhancement of primary productivity along the path of the icebergs was not resolved in either in situ or monthly mean satellite observations. There was a considerable brash-ice field moving ahead of the icebergs which limited the number of downstream sampling stations. One downstream station within 2 km of iceberg A-68P showed several ice-melt influenced features that distinguished it from most other stations. Firstly, there was a strong stratified meltwater influenced layer that reached to around 120 m. This had the effect of deepening underlying water masses, with the core of the temperature minimum layer around 50 m deeper than elsewhere. Secondly, there was evidence of rapid downward displacement of both particulate material and certain phytoplankton taxa that may be a further result of this water mass deepening. Thirdly, macronutrient profiles were altered, with concentrations of nitrate, silicic acid and phosphate characteristic of deeper layers being found closer to the surface and a dilution of the ambient nutrient pool just above the iceberg draft that we ascribe to meltwater released from basal melting. Meanwhile, nutrient recycling processes associated with organic matter remineralisation were also modified by the physical restructuring of the water column and biotic components. Finally, the ice-associated phytoplankton taxa Pseudo-nitszchia/Nitszchia, found in both upstream and downstream locations, were abundant at this < 2 km-distant station through melting out from the iceberg and subsequent rapid growth. Overall, we resolved alterations to water column structure, nutrient profiles and phytoplankton community composition at fine to medium scales around the iceberg field. Nevertheless, although there may have been longer term and larger scale impacts, the dynamic oceanographic environment, including the presence of a strong oceanographic front and shelf-edge processes, dominated during the collapse of A-68A.

Detection of open cluster members inside and beyond tidal radius by machine learning methods based on Gaia DR3

ABSTRACT In our previous work, we introduced a method that combines two unsupervised algorithms: Density-based spatial clustering of applications with noise (DBSCAN) and Gaussian mixture model (GMM). We applied this method to 12 open clusters based on Gaia Early Data Release 3 (EDR3) data, demonstrating its effectiveness in identifying reliable cluster members within the tidal radius. However, for studying cluster morphology, we need a method capable of detecting members both inside and outside the tidal radius. By incorporating a supervised algorithm into our approach, we successfully identified members beyond the tidal radius. In our current work, we initially applied DBSCAN and GMM to identify reliable members of cluster stars. Subsequently, we trained the random forest algorithm using DBSCAN- and GMM-selected data. Leveraging the random forest, we can identify cluster members outside the tidal radius and observe cluster morphology across a wide field of view. Our method was then applied to 15 open clusters based on Gaia DR3, which exhibit a wide range of metallicity, distances, members, and ages. Additionally, we calculated the tidal radius for each of the 15 clusters using the King profile and detected stars both inside and outside this radius. Finally, we investigated mass segregation and luminosity distribution within the clusters. Overall, our approach significantly improved the estimation of the tidal radius and detection of mass segregation compared to the previous work. We found that in Collinder 463, low-mass stars do not segregate in comparison to high-mass and intermediate-mass stars. Additionally, we detected a peak of luminosity in the clusters, some of which were located far from the centre, beyond the tidal radius.

Inhibition of Extracellular Signal-Regulated Kinase Activity Improves Cognitive Function in Mice Subjected to Myocardial Infarction.

Cognitive impairment is a commonly observed complication following myocardial infarction; however, the underlying mechanisms are still not well understood. The most recent research suggests that extracellular signal-regulated kinase (ERK) plays a critical role in the development and occurrence of cognitive dysfunction-related diseases. This study aims to explore whether the ERK inhibitor U0126 targets the ERK/Signal Transducer and Activator of Transcription 1 (STAT1) pathway to ameliorate cognitive impairment after myocardial infarction. To establish a mouse model of myocardial infarction, we utilized various techniques including Echocardiography, Hematoxylin-eosin (HE) staining, Elisa, Open field test, Elevated plus maze test, and Western blot analysis to assess mouse cardiac function, cognitive function, and signal transduction pathways. For further investigation into the mechanisms of cognitive function and signal transduction, we administered the ERK inhibitor U0126 via intraperitoneal injection. Reduced total distance and activity range were observed in mice subjected to myocardial infarction during the open field test, along with decreased exploration of the open arms in the elevated plus maze test. However, U0126 treatment exhibited a significant improvement in cognitive decline, indicating a protective effect through the inhibition of the ERK/STAT1 signaling pathway. Hence, this study highlights the involvement of the ERK/STAT1 pathway in regulating cognitive dysfunction following myocardial infarction and establishes U0126 as a promising therapeutic target.

Shear viscosity of a near-critical binary system analyzed with variable-temperature atomic force microscopy

Variation in shear viscous drag in a near-critical binary mixture was measured between a hydrophilic probe sphere and a hydrophilic substrate down to a distance range comparable to or smaller than the correlation length ξ using a magnetic excitation method of atomic force microscopy at temperatures T=Tc−∆T with ∆T varying from 0.1 to 0.7 K. As the temperature approached the Tc, the increase in the drag coefficient toward the zero distance was observed to be less pronounced in the distance range below ca. 100 nm. The data was discussed as arising from suppression in a concentration gradient in the intersurface region due to the overlap of the affected layers on similar surfaces.

Cannabis as a shareable commodity in a social discounting task.

Cannabis use and cannabis use disorder diagnoses continue to increase in United States college-aged students as more states legalize recreational cannabis. Previous studies have attempted to associate cannabis use with delay discount rates, which involves participants making choices for smaller sooner versus larger later hypothetical rewards. More smaller sooner choices result in higher discount rates and suggest increased impulsivity. Delay discounting studies have shown a significant, but small effect size with people who use cannabis more likely to choose the smaller sooner rewards, relative to people who do not use cannabis. The present study tested whether students with different experience using cannabis (people who currently use cannabis, people who formerly used cannabis, or people who never used cannabis) would be sensitive to sharing a proportion of hypothetical marijuana with another individual at a given social distance, as a putative measure for cannabis value. Results from two separate data sets showed that students classified as current cannabis users were significantly less likely to share a proportion of hypothetical marijuana across a range of social distances, relative to students that self-reported never using cannabis. Students classified as either former or current users were not statistically different. These results were consistent with previous delay discounting results and showed a medium effect size (η² ≥ 0.10) for each data set, both separately and when combined. These results indicate that social distance is a meaningful variable that can be used in a modified discounting task to assess differential cannabis value in a student population who are increasingly susceptible to cannabis use disorder. These results may have future clinical implications. Social discount rates for cannabis may be able to differentiate individuals who will continue recreational use versus individuals that may develop cannabis dependence problems. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Model‐driven neural network based for HPO‐MIMO channel estimation

AbstractIntegrated Sensing and Communications (ISAC) need to process data streams in high‐speed sensor data acquisition or high‐speed wireless communications. To process the data can require more computing and communication resources, resulting in higher power consumption. Halved‐Phase Only Multiple Input Multiple Output (HPO‐MIMO) communication technology can solve this problem by using low‐power nonlinear detection devices. In ISAC, Channel Estimation (CE) technology can provide key channel characteristics and state information for sensing and collaborative work of perception and communication tasks. However, HPO‐MIMO system cannot realize CE using traditional receiver schemes because of the missing amplitude. In order to solve this problem, two HPO‐MIMO CE schemes based on model‐driven deep learning are proposed in this paper. The proposed schemes include a Densely Residual Network (DRN) and a Inception‐Resnet (IR), which is suitable for the case of sufficient data and insufficient data, respectively. The simulation results show that the performance of DRN based scheme is better than that of IR based scheme when the data amount is sufficient, and the performance of IR based scheme is better when the dataset is small. In addition, the proposed CE schemes work well with a range of antenna sizes and distances.

Can subsea shuttles be a cost-competitive solution for [formula omitted] transport?

Considering the role that offshore CO2 storage is expected to play in deploying carbon capture and storage, enabling cost-efficient and flexible solutions for transporting CO2 to relevant storage locations will be crucial. While pipeline and ship-based approaches have long been considered the most relevant options, transport via subsea shuttles is a new concept that has also been proposed in the past couple of years. The present study seeks to understand if this new approach could be cost-efficient compared to current and upcoming ship-based transport concepts.The result shows that the shuttle concept could be cost-competitive with currently mature 15 barg-based shipping, especially if the subsea shuttle connects to a CO2 pipeline infrastructure rather than to the reservoir directly, although cost-competitiveness is achieved only for a limited range of volumes and distances. However, it is unlikely that this concept would be cost-attractive compared to the upcoming 7 barg-based shipping, and sensitivity analyses highlight that the subsea shuttle investment cost would need to fall to unlikely low levels to reverse this trend. Thus, this study concludes that the subsea shuttle concept is unlikely to become a significant solution for transporting CO2 to offshore storage.

Evidence for an Imbricated Lower Crust and Its Role in Accommodating Crustal Shortening in Sikkim Himalaya

AbstractGeometrical heterogeneity of the subducting Indian continental crust along the Himalaya‐Tibet collision zone remains enigmatic. Mass budget estimates describing shortening across the orogen are partly derived from observations made from seismic imaging of the deep earth. Here, using data from 38 broadband seismic stations covering Sikkim Himalaya, we produce high resolution seismic images in order to fill crucial gaps in our understanding of the evolution of Himalayan collision zone. We used 12,288 high quality receiver functions computed using waveforms of earthquakes having magnitude &gt;5.5 in the distance range of 30°–100°. Our results reveal a highly imbricated and heterogeneous crust beneath Sikkim Himalaya. The Main Himalayan Thrust (MHT) responsible for large scale earthquakes in the Himalayan collision zone is not so distinct in the migrated images, but intermittent. A dominant cluster of earthquakes at shallower depths is associated with the MHT, marked by negative amplitude arrivals. The Moho is found to be gently dipping, reaching depths of ∼60 km beneath the Higher Himalaya compared to ∼40 km in the Himalayan foredeep. Interestingly, the Moho in this part of Himalaya has offsets and overlapping segments, indicating crustal imbrication in response to active shortening. Clusters of lower crustal earthquakes coincide with the junction of offsets in the Moho.

Experimental investigation of thermal characteristics of slot synthetic jet impingement on a circular cylinder: Free and constrained environment

The present study aimed to comprehensively investigate the thermal behavior of a slot synthetic jet (SJ) interacting with a circular cylinder in both free and constrained environments through experimental analysis. By traversing the cylinder along the jet centerline across a range of non-dimensional distances (H/w = 5-50), spanning from the near-field to the fully developed region, the research aimed to elucidate the factors governing heat transfer performance. Key parameters such as Reynolds number, jet-cylinder separation distance, and excitation frequency were scrutinized to understand their influence on thermal performance. The SJ was found to perform better in the constrained environment, attributed to relatively higher flow fluctuations developed by the complex interaction of the vortex with the sidewall boundary layer and the cylinder. Almost 12% higher average heat transfer was observed in the case of the constrained environment over the range of parameters employed in the current work. Moreover, a strong dependence of heat transfer on the jet cylinder separation distance was also found. In contrast to the SJ impinging on flat target surfaces where the maximum heat transfer was attained in the intermediate field, at H/w = 14 to 18, for SJ impingement on the circular cylinder, however, this was consistently achieved in the near field, i.e., H/w = 5. Also, the thermal performance as a function of the flow Reynolds number was comparable to the uniform flow case when the Reynolds number was based on the approach flow velocity (i.e., local velocity based on the cylinder location) instead of the velocity at the slot exit.

Recent Advances on the Chemistry of Transition Metal Complexes with Monoanionic Bidentate Silyl Ligands.

The chemistry of transition-metal (TM) complexes with monoanionic bidentate (κ2-L,Si) silyl ligands has considerably grown in recent years. This work summarizes the advances in the chemistry of TM-(κ2-L,Si) complexes (L=N-heterocycle, phosphine, N-heterocyclic carbene, thioether, ester, silylether or tetrylene). The most common synthetic method has been the oxidative addition of the Si-H bond to the metal center assisted by the coordination of L. The metal silicon bond distances in TM-(κ2-L,Si) complexes are in the range of metal-silyl bond distances. TM-(κ2-L,Si) complexes have proven to be effective catalysts for hydrosilylation and/or hydrogenation of unsaturated molecules among other processes.

A computational modelling tool for prediction of head reshaping following endoscopic strip craniectomy and helmet therapy for the treatment of scaphocephaly

BackgroundEndoscopic strip craniectomy followed by helmet therapy (ESCH) is a minimally invasive approach for correcting sagittal craniosynostosis. The treatment involves a patient-specific helmet designed to facilitate lateral growth while constraining sagittal expansion. In this study, finite element modelling was used to predict post-treatment head reshaping, improving our comprehension of the necessary helmet therapy duration. MethodSix patients (aged 11 weeks to 9 months) who underwent ESCH at Connecticut Children's Hospital were enrolled in this study. Day-1 post-operative 3D scans were used to create skin, skull, and intracranial volume models. Patient-specific helmet models, incorporating areas for growth, were designed based on post-operative imaging. Brain growth was simulated through thermal expansion, and treatments were modelled according to post-operative Imaging available. Mechanical testing and finite element modelling were combined to determine patient-specific mechanical properties from bone samples collected from surgery.Validation compared simulated end-of-treatment skin surfaces with optical scans in terms of shape matching and cranial index estimation. ResultsComparison between the simulated post-treatment head shape and optical scans showed that on average 97.3 ± 2.1 % of surface data points were within a distance range of −3 to 3 mm. The cranial index was also accurately predicted (r = 0.91). ConclusionsIn conclusion, finite element models effectively predicted the ESCH cranial remodeling outcomes up to 8 months postoperatively. This computational tool offers valuable insights to guide and refine helmet treatment duration. This study also incorporated patient-specific material properties, enhancing the accuracy of the modeling approach.

Image-Based Bolt-Loosening Detection Using a Checkerboard Perspective Correction Method.

In this paper, a new image-correction method for flange joint bolts is proposed. A checkerboard is arranged on the side of a flange node bolt, and the homography matrix can be estimated using more than four feature points, which include the checkerboard corner points. Then, the perspective distortion of the captured image and the deviation of the camera position angle are corrected using the estimated homography matrix. Due to the use of more feature points, the stability of homography matrix identification is effectively improved. Simultaneously, the influence of the number of feature points, camera lens distance, and light intensities are analyzed. Finally, based on a bolt image taken using an iPhone 12, the prototype structure of the flange joint in the laboratory is verified. The results show that the proposed method can effectively correct image distortion and camera position angle deviation. The use of more than four correction points not only effectively improves the stability of bolt image correction but also improves the stability and accuracy of bolt-loosening detection. The analysis of influencing factors shows that the proposed method is still effective when the number of checkerboard correction points is reduced to nine, and the average error of the bolt-loosening detection result is less than 1.5 degrees. Moreover, the recommended camera shooting distance range is 20 cm to 60 cm, and the method exhibits low sensitivity to light intensity.