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To evaluate the measurement accuracy of horizontal and vertical remote emission sensing (RES) equipment, a real-world dynamic test was carried out in Chengdu by using electric vehicles equipped with various concentrations of standard gases. In addition, a new Image-based Spectral Processing Algorithm (ISPA) for vertical remote sensing spectral data was developed to improve the measurement capability. The results showed that the ISPA provided a greater percentage of valid data and lower relative errors; thus, our new algorithm could more effectively analyze the spectral data to measure vehicle emission levels. The percentages of valid horizontal and vertical RES data were 71% and 84%, respectively. The mean relative errors of CO2, CO, HC and NO measured by the vertical RES were about 5%, 20%, 20% and 40%, respectively, and those of CO2, CO and NO measured by the horizontal RES were 3%, 13% and 15%, respectively. For the common vehicle emission concentration, the percentage of valid data for the two RES types increased with increasing gas concentration. As the vehicle speed increased, the relative errors of the horizontal RES equipment showed an increasing trend for the same concentration of gas. Furthermore, for the same speed segment, the relative errors of the horizontal RES equipment increased as the simulated emission concentration decreased. The vertical RES equipment did not exhibit a consistent trend in terms of changes. This study provides a data quality reference for further RES applications.

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This study evaluates the performance of five satellite precipitation products (GPM IMERG, TRMM 3B42, ERA5, PERSIANN, and CHIRPS) compared to monthly observations from two weather stations (Laayoune and Essmara) over 2001-2017 using statistical metrics including correlation coefficient (CC) and mean square error (MSE). The results reveal notable differences between products. On a monthly timescale, GPM IMERG shows the best overall accuracy with a MSE of 16.8 mm/month. However, TRMM 3B42 exhibits higher temporal correlations with a CC around 0.83. The analysis provides insights into product capabilities and limitations for hydrological monitoring in data-sparse regions. Key findings include the superior performance of latest generation datasets like GPM alongside biases requiring localized calibration. The study delivers an assessment framework to guide integration of multiple satellite estimates for enhanced precipitation quantification and hydroclimatic modeling in water-stressed environments.

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NASA has released the latest Moderate Resolution Imaging Spectroradiometer (MODIS) Multi-Angle Implementation of Atmospheric Correction (MAIAC) Collection 6 (C6) and Collection 6.1 (C6.1) aerosol optical depth (AOD) products with 1 km spatial resolution. This study validated and compared C6 and C6.1 MAIAC AOD products with AERONET observations in terms of accuracy and stability, and analyzed the spatiotemporal characteristics of AOD at different scales in China. The results show that the overall accuracy of MAIAC products is good, with correlation coefficient (R) > 0.9, mean bias (BIAS) < 0.015, and the fraction within the expected error (EE) > 68 %. However, after the algorithm update, the accuracy of Terra MAIAC aerosol products C6.1 has significantly decreased. The accuracy of the products varies with the region. The accuracy of C6.1 in North China, Central East China, and West China, is comparable to or even exceeds that of C6, but performs poorly in South China. In addition, the stability of the updated C6.1 MAIAC aerosol products has not seen significantly improvement. The metrics of no product can all meet the stability goals of the Global Climate Observing System (GCOS, 0.02 per decade) in China. C6.1 improves the retrieval frequency in many regions and temporarily solves the problem of AOD discontinuity at the boundaries of different aerosol models in C6, but there are some fixed climatological AOD blocks (AOD = 0.014) in the eastern Tibetan Plateau region. Both C6 and C6.1 can capture similar annual variation characteristics of AOD to those observed at the AERONET sites. The study provides possible references for improving the MAIAC algorithm and building long-term stable aerosol records.

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Ground experimentation is an important method to verify the performance and quality of spacecraft structures. How to simulate the force and heat fields that a spacecraft may be subjected to during flight is a challenge for experiment design. In this paper, the static strength experimental method of spacecraft in the combined force and heat fields is studied. Furthermore, the coupling cases of the spacecraft during the flight process are simulated using an airbag and a resistive heater. Finally, it can be concluded that the accuracy of the proposed experimental method as well as the structural strength of the spacecraft can meet technical requirements during flight.

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Wetlands play an important role in ecological health and sustainable development, and dynamic monitoring of their spatial distribution is crucial for developing management and conservation measures. The types of coastal wetlands are complex and diverse, natural and artificial wetlands are easily confused, making precise classification more difficult. The coastal wetland of Chongming Island in China, which has diverse types and unique and complex ecological and hydrological characteristics, was deliberately chosen as a challenging case study. The objective of this study was to research effective method of fine classification of coastal wetlands, by constructing feature variables and proposing strategies for multi-level selection and fusion of feature variables. Sentinel-2 data with rich spectral information and high spatial resolution was be used. In this study, firstly, the classification effect of characteristic variables such as vegetation index, water body index, red edge index, and texture index were evaluated. Focusing on the "different objects with same spectra" of the humid planning land and farm growing ponds, the spectral characteristics of them were analyzed and a "water-rich soil index (WRSI)" was established. Subsequently, correlation analysis and J-M distance method were used to multi-level selection for the feature variables and four sets of features combination schemes were established. Finally, random forest (RF) was applied to classify coastal wetlands using different feature combination schemes, and the accuracy of different schemes was compared and verified. The results show the following: 1)Texture features have a promoting effect on improving classification accuracy. The constructed "water rich soil index"(WRSI) has the effectively contribution to identification and classification of farm growing ponds and humid planned land, improving the overall classification accuracy by 6.52%. 2)By multi-level selecting and fusion of feature variable sets, both accuracy and efficiency for classification are improved. For different features combination schemes, the classification accuracy is up to 90.03% by integrating spectral features, spectral index, texture index, and WRSI. This study evaluates the potential of Sentinel-2 data in coastal wetland classification, constructs effective feature parameters, and provides a new idea for wetland information extraction. The resulting classification map can be used for sustainable management, ecological assessment and conservation of the coastal wetland.

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A high-quality dataset is a basic requirement to ensure the training quality and prediction accuracy of a deep learning network model (DLNM). To explore the influence of label image accuracy on the performance of a concrete crack segmentation network model in a semantic segmentation dataset, this study uses three labelling strategies, namely pixel-level fine labelling, outer contour widening labelling and topological structure widening labelling, respectively, to generate crack label images and construct three sets of crack semantic segmentation datasets with different accuracy. Four semantic segmentation network models (SSNMs), U-Net, High-Resolution Net (HRNet)V2, Pyramid Scene Parsing Network (PSPNet) and DeepLabV3+, were used for learning and training. The results show that the datasets constructed from the crack label images with pix-el-level fine labelling are more conducive to improving the accuracy of the network model for crack image segmentation. The U-Net had the best performance among the four SSNMs. The Mean Intersection over Union (MIoU), Mean Pixel Accuracy (MPA) and Accuracy reached 85.47%, 90.86% and 98.66%, respectively. The average difference between the quantized width of the crack image segmentation obtained by U-Net and the real crack width was 0.734 pixels, the maximum difference was 1.997 pixels, and the minimum difference was 0.141 pixels. Therefore, to improve the segmentation accuracy of crack images, the pixel-level fine labelling strategy and U-Net are the best choices.

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The variation of dynamic accuracy for press systems is the nonlinear phenomenon that results from the consideration of contact and impact on the deformation of transmission mechanism, usually revolute joint and translation joint. The influence is especially obvious in the ultra-precision mechanism, which can cause the vibration and unstabitily of position and machining accuracy would be failure. As usual, the dynamic accuracy is used to evaluate the ability of press systems, which is also the important design object. Due to the stronger nonlinear of dynamic accuracy, especially for the effect of coupling factors, the mathematical analysis method plays an important role in the study of dynamic behavior for press systems. This work proposes the new approach to conduct the simplified dynamic accuracy analysis based on the orthogonal design method, which optimize the reasonability of sample collection. The proposed method is compared with the traditional approach, which illustrates the advantage and efficiency for the dynamic accuracy analysis of press systems.•Developed dynamic accuracy analysis is observed to be effective for the stability evaluation of press systems.•The simplified model of coupling effect analysis is established based on orthogonal design method.•No need to collect a large amount of data for comparison and the reliable nonlinear analysis is conducted with simplified model.

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OBJECTIVE: Current application of mixed reality as a navigation aid in the field of spinal navigation points to the potential of this technology in spine surgery. Crucial factors for acceptance include intuitive workflow, system stability, reliability, and accuracy of the method. The authors therefore aimed to investigate the accuracy of the system in visualization of anatomical structures using mixed reality in the example of pedicles of the thoracic spine in a human cadaveric study. Potential difficulties and limitations are discussed. METHODS: CT scans of a human cadaveric spinal column specimen were performed. After segmentation and import into the advanced HoloLens 2 software, the vertebrae were exposed. The vertebral arches were preserved on one side for a landmark-based surface registration, whereas pedicles were exposed on the other side in order to measure and evaluate deviation of the overlay holographs with regard to the exact anatomical structure. Accuracy was measured and statistically evaluated. RESULTS: In this work it was demonstrated that the overlay of the virtual 3D model pedicles with the real anatomical structures with anatomical landmark registration was within an acceptable surgical accuracy with the mean value of 2.1 mm (maximum 3.8 mm, minimum 1.2 mm). The highest accuracy was registered at the medial and lateral pedicle wall, and the measurement results were best in the region of the middle thoracic spine. CONCLUSIONS: The accuracy analysis for mixed reality (i.e., between the virtual and real anatomical situation of the thoracic spine) showed a very good agreement when focus was on the pedicles. This work is thus a rare proof of the precision of segmentation to the potential surgical area. The results encourage researchers to open up mixed reality technology in its development and application for spinal navigation.

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BACKGROUND: Machine learning (ML)-based clinical decision support tools (CDSTs) make personalized predictions for different treatments; by comparing predictions of multiple treatments, these tools can be used to optimize decision making for a particular patient. However, CDST prediction accuracy varies for different patients and also for different treatment options. If these differences are sufficiently large and consistent for a particular subcohort of patients, then that bias may result in those patients not receiving a particular treatment. Such level of bias would deem the CDST "unfair." The purpose of this study is to evaluate the "fairness" of ML CDST-based clinical outcomes predictions after anatomic (aTSA) and reverse total shoulder arthroplasty (rTSA) for patients of different demographic attributes. METHODS: Clinical data from 8280 shoulder arthroplasty patients with 19,249 postoperative visits was used to evaluate the prediction fairness and accuracy associated with the following patient demographic attributes: ethnicity, sex, and age at the time of surgery. Performance of clinical outcome and range of motion regression predictions were quantified by the mean absolute error (MAE) and performance of minimal clinically important difference (MCID) and substantial clinical benefit classification predictions were quantified by accuracy, sensitivity, and the F1 score. Fairness of classification predictions leveraged the "four-fifths" legal guideline from the US Equal Employment Opportunity Commission and fairness of regression predictions leveraged established MCID thresholds associated with each outcome measure. RESULTS: For both aTSA and rTSA clinical outcome predictions, only minor differences in MAE were observed between patients of different ethnicity, sex, and age. Evaluation of prediction fairness demonstrated that 0 of 486 MCID (0%) and only 3 of 486 substantial clinical benefit (0.6%) classification predictions were outside the 20% fairness boundary and only 14 of 972 (1.4%) regression predictions were outside of the MCID fairness boundary. Hispanic and Black patients were more likely to have ML predictions out of fairness tolerance for aTSA and rTSA. Additionally, patients <60 years old were more likely to have ML predictions out of fairness tolerance for rTSA. No disparate predictions were identified for sex and no disparate regression predictions were observed for forward elevation, internal rotation score, American Shoulder and Elbow Surgeons Standardized Shoulder Assessment Form score, or global shoulder function. CONCLUSION: The ML algorithms analyzed in this study accurately predict clinical outcomes after aTSA and rTSA for patients of different ethnicity, sex, and age, where only 1.4% of regression predictions and only 0.3% of classification predictions were out of fairness tolerance using the proposed fairness evaluation method and acceptance criteria. Future work is required to externally validate these ML algorithms to ensure they are equally accurate for all legally protected patient groups.

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Objective:To retrospectively evaluate the clinical outcomes of autonomous dental implant robot(ADIR)assisted implant surgery in 1-year follow-up.Methods:20 patients with tooth missing underwent implantation surgery by ADIR were incuded.The plat-form deviation,apex deviation and angular deviation of the implants were analyzed.The marginal bone height and peri-implant soft tis-sue health were measured and observed immediately,6 months and 12 months after the restoration.Results:The platform deviation,apex deviation and angular deviation of 20 implants at the 3 follow-up examinations were(0.34±0.11)mm,(0.34±0.15)mm and(0.82°±0.38°),respectively.There was no significant difference in the accuracy of different implant diameter and length(P＞0.05).During the follow-up period,all implants had successful osseointegration,stable marginal bone height,and acceptable peri-implant soft tissue condition.Conclusion:The 1-year follow-up indicates that ADIR can achieve promising clinical performance.Long-term follow-up studies are still necessary for verification.

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This study used oleogels to resolve unsolidified white chocolate in 3D printing. Because white chocolate cannot be shaped during 3D printing, the oleogel system is used to solve this problem. The printing parameters and accuracy in a 3D printing system were investigated by using different oleogels added to white chocolate as a material to enhance chocolate extrusion solidification, monoglycerides (MAG), sucrose fatty acid ester (SE) and hydroxypropyl methylcellulose (HPMC), and their effects on rheological characterization, bridging experiments, and optimal print parameters (material formulation, nozzle height, layer height and print speed) were compared. In the rheological analysis, the viscosity recovery was more than 80% for the HPMC group and less than 80% for the MAG and SE groups. In the bridging experiment, when MAG and SE were added at more than 2%, the white chocolate could be effectively extruded and solidified, and the bridging distance could be stretched to 10 mm. The suitable printing parameters are a nozzle height of 3 mm, a layer height of 3 mm, and a printing speed of 10 mm/s. This study provides a future solution to solve the problem of extruded unsolidified chocolate.

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Laparoscopy is employed in conventional minimally invasive surgery to inspect internal cavities by viewing two-dimensional images on a monitor. This method has a limited field of view and provides insufficient information for surgeons, increasing surgical complexity. Utilizing simultaneous localization and mapping (SLAM) technology to reconstruct laparoscopic scenes can offer more comprehensive and intuitive visual feedback. Moreover, the precision of the reconstructed models is a crucial factor for further applications of surgical assistance systems. However, challenges such as data scarcity and scale uncertainty hinder effective assessment of the accuracy of endoscopic monocular SLAM reconstructions. Therefore, this paper proposes a technique that incorporates existing knowledge from calibration objects to supplement metric information and resolve scale ambiguity issues, and it quantifies the endoscopic reconstruction accuracy based on local alignment metrics. The experimental results demonstrate that the reconstructed models restore realistic scales and enable error analysis for laparoscopic SLAM reconstruction systems. This suggests that for the evaluation of monocular SLAM three-dimensional (3D) reconstruction accuracy in minimally invasive surgery scenarios, our proposed scheme for recovering scale factors is viable, and our evaluation outcomes can serve as criteria for measuring reconstruction precision.

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In the wide scenario of heritage documentation and conservation, the multi-scale nature of digital models is able to twin the real object, as well as to store information and record investigation results, in order to detect and analyse deformation and materials deterioration, especially from a structural point of view. The contribution proposes an integrated approach for the generation of an n-D enriched model, also called a digital twin, able to support the interdisciplinary investigation process conducted on the site and following the processing of the collected data. Particularly for 20th Century concrete heritage, an integrated approach is required in order to adapt the more consolidated approaches to a new conception of the spaces, where structure and architecture are often coincident. The research plans to present the documentation process for the halls of Torino Esposizioni (Turin, Italy), built in the mid-twentieth century and designed by Pier Luigi Nervi. The HBIM paradigm is explored and expanded in order to fulfil the multi-source data requirements and adapt the consolidated reverse modelling processes based on scan-to-BIM solutions. The most relevant contributions of the research reside in the study of the chances of using and adapting the characteristics of the IFC (Industry Foundation Classes) standard to the archiving needs of the diagnostic investigations results so that the digital twin model can meet the requirements of replicability in the context of the architectural heritage and interoperability with respect to the subsequent intervention phases envisaged by the conservation plan. Another crucial innovation is a proposal of a scan-to-BIM process improved by an automated approach performed by VPL (Visual Programming Languages) contribution. Finally, an online visualisation tool enables the HBIM cognitive system to be accessible and shareable by stakeholders involved in the general conservation process.

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IntroductionIn craniofacial surgery, magnetic navigation systems can effectively extend the doctor's limited visual range, improve their surgical precision, shorten the operation time, and reduce the incidence of surgical complications. Owing to the ease of magnetic navigation, the accuracy of the magnetic navigation system is affected by various equipment in the operating room. Therefore, its large-scale application is lacking because the navigation accuracy requirement can be extremely high during craniofacial surgery. Therefore, the accuracy of magnetic navigation systems is crucial. Various surgical instruments have been evaluated to effectively reduce the interference of magnetic navigation systems with surgical instruments. In craniofacial surgery, magnetic navigation systems can effectively extend the doctor's limited visual range, improve their surgical precision, shorten the operation time, and reduce the incidence of surgical complications. Owing to the ease of magnetic navigation, the accuracy of the magnetic navigation system is affected by various equipment in the operating room. Therefore, its large-scale application is lacking because the navigation accuracy requirement can be extremely high during craniofacial surgery. Therefore, the accuracy of magnetic navigation systems is crucial. Various surgical instruments have been evaluated to effectively reduce the interference of magnetic navigation systems with surgical instruments. In the surgical environment, the use of surgical instruments during mandibular surgery was simulated by selecting several conventional surgical instruments to record errors in the magnetic navigation system. The fluctuation values of the magnetic navigation errors were subsequently estimated and changes in its accuracy measured. MATLAB was used to calculate and analyze the fluctuations of the magnetic navigation errors. As results, the high-frequency electrosurgical system caused the greatest interference with the magnetic navigation system during surgery while powered on, with a maximum fluctuation error value of 1.8120 mm, and the maximum fluctuation error values of the stitch scissors, teeth forceps, and a needle holder were 1.3662, 1.3781, and 0.3912 mm, respectively. The closer the instrument is to the magnetic field generator or navigation target, the greater its impact. In conclusion, stitch scissors, teeth forceps, a needle holder, and the high-frequency electrosurgical system all affect magnetic navigation system accuracy. Therefore, it is necessary to avoid magnetic navigation system use and surgical instrument disturbances during surgery or select surgical instruments that do not interfere with the system. Surgical instruments must be evaluated for electromagnetic interference before they can be used in surgery with a magnetic navigation system.

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The Qilian Mountains are a climate-sensitive area in northwest China, and extreme precipitation events have an important impact on its ecological environment. Therefore, considering the global warming scenario, it is highly important to project the extreme precipitation indices over the Qilian Mountains in the future. This study is based on three CMIP6 models (CESM2, EC-Earth3, and KACE-1-0-G). A bias correction algorithm (QDM) was used to correct the precipitation outputs of the models. The eight extreme precipitation indices over the Qilian Mountains during the historical period and in the future were calculated using meteorological software (ClimPACT2), and the performance of the CMIP6 models to simulate the extreme precipitation indices of the Qilian Mountains in the historical period was evaluated. Results revealed that: (1) The corrected CMIP6 models could simulate the changes in extreme precipitation indices over the Qilian Mountains in the historical period relatively well, and the corrected CESM2 displayed better simulation as compared to the other two CMIP6 models. The CMIP6 models performed well while simulating R10mm (CC is higher than 0.71) and PRCPTOT (CC is higher than 0.84). (2) The changes in the eight extreme precipitation indices were greater with the enhancement of the SSP scenario. The growth rate of precipitation in the Qilian Mountains during the 21st century under SSP585 is significantly higher than the other two SSP scenarios. The increment of precipitation in the Qilian Mountains mainly comes from the increase in heavy precipitation. (3) The Qilian Mountains will become wetter in the 21st century, especially in the central and eastern regions. The largest increase in precipitation intensity will be observed in the western Qilian Mountains. Additionally, total precipitation will also increase in the middle and end of the 21st century under SSP585. Furthermore, the precipitation increment of the Qilian Mountains will increase with the altitude in the middle and end of the 21st century. This study aims to provide a reference for the changes in extreme precipitation events, glacier mass balance, and water resources in the Qilian Mountains during the 21st century.

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PURPOSE: This study proposes a method for improving the accuracy of three-dimensional (3D) models generated through cone-beam computed tomography (CBCT). METHODS: A 3D cuboid model fitted with a »-scale dentition on its top surface was constructed to simulate an alveolar bone with teeth. A physical specimen of the model was printed and the distance between its opposite sides was measured using a vernier caliper. The physical model was light-scanned, and the surface data of the generated 3D model were corrected by calibrating the distance between opposite sides against the vernier caliper measurements. The physical model was also scanned using CBCT to reconstruct a second 3D model. The overall deviation between the two models and the distance deviation in each direction of the cuboid and dentition were quantified and statistically analyzed. RESULTS: The overall deviation between the reconstructed CBCT model and the calibrated structured light-scanned model was 0.098 ± 0.001 mm. Following calibration, the overall deviation was 0.010 ± 0.006 mm. A one-way variance analysis suggested that the overall deviations' differences were not statistically significant (P < 0.05). CONCLUSION: This study lays a solid foundation for accurate dental implantation.

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PURPOSE: Thermal ablation of large tumors may benefit from simultaneous placement of multiple needles, but accurate placement becomes challenging as the number of needles increases. The aim of this work was to evaluate use of personalized needle guidance grid templates based on intraprocedural CT and fabricated at the point of care to implement ablation treatment plans with multiple needles in vivo. METHODS: A plastic frame was designed to hold two parallel plastic guide plates in a rigid relationship, fixed over the abdomen by a mounting arm. Steel ball targets (1.5 mm) were implanted under ultrasound in the livers of two domestic swine under general anesthesia. Following breath-hold CT of the subject and frame, the targets and frame were identified using customized 3D Slicer-based planning software. Multiple needle trajectories targeting the balls were planned, including complex off-plane trajectories. A machining program for drilling the hole pattern corresponding to the planned needle trajectories was generated. The pattern was drilled in the two plates with a numerical-controlled milling machine in the suite. The plates were attached to the frame and needles passed through the paired holes to the calculated depth. Placement accuracy was defined as needle tip-to-target distance on post-placement CT. RESULTS: The planning process and manufacturing required approximately 6 and 15 min, respectively. Needles were rapidly inserted (n = 11) to the target points without complications or traversing nontarget anatomy. The mean needle tip-to-target distance error was 3.4 ± 2.2, range 0-7 mm. CONCLUSION: Rapid and accurate needle placement was feasible using a subject-specific, custom-drilled, needle guidance grid template fabricated intraprocedurally. Targeting accuracy and performance were similar to more complex and expensive tracking systems which may enable accurate intraprocedural implementation of treatment plans in the liver or other organs. This may be of value in complex ablation cases or in areas where more advanced guidance systems are not available.

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BACKGROUND: A large variety of electronic hand hygiene monitoring systems (EHHMS) are being developed and applied in health care settings. Monitoring hand hygiene (HH) opportunity at bed-level has been the key technical challenge. Accuracy evaluation needs more attention as the prerequisite upon widespread acceptance and adoption. METHODS: For the first time, we explored, debugged and upgraded an EHHMS based on ultra-wide bandwidth (UWB) which can obtain HH opportunities at bed-level. The real-time positioning and electronic fence of UWB technology was applied for EHHMS. The accuracy of EHHMS was compared with the simultaneous manual direct observations in real-world clinical setting. Sensitivity and specificity were calculated for EHHMS capturing HH action and opportunity. RESULTS: Two generations of EHHMS were constructed. For the first generation, the system properly recorded 84% and 78% of the pre-identified HH actions and opportunities performed by experimenters. For the second generation, sensitivity and specificity of the system capturing HH action were 89% (84.83-92.36) and 100% (98.26-100.00), respectively. For capturing HH opportunity, the system showed the sensitivity and specificity of 86.52% (82.52-89.89) and 88.10% (84.14-91.36)), respectively. CONCLUSION: The EHHMS based on UWB could accurately identify HH action and opportunity with equivalent accuracy compared with simultaneous direct observation.

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Background: Robotic-based guidance systems are becoming increasingly capable of assisting in needle placement during interventional procedures. Despite these technical advances, less sophisticated low-cost guidance devices promise to enhance puncture accuracy compared with the traditional freehand technique. Purpose: To compare the in vitro accuracy and feasibility of two different aiming devices for computed-tomography (CT)-guided punctures. Methods: A total of 560 CT-guided punctures were performed by using either a robotic (Perfint Healthcare: Maxio) or a novel low-cost patient-mounted system (Medical Templates AG: Puncture Cube System [PCS]) for the placement of Kirschner wires in a plexiglass phantom with different slice thicknesses. Needle placement accuracy as well as procedural time were assessed. The Euclidean (ED) and normal distances (ND) were calculated at the entry and target point. Results: Using the robotic device, the ND at the target for 1.25 mm, 2.5 mm, 3.75 mm and 5 mm slice thickness were 1.28 mm (SD ± 0.79), 1.25 mm (SD ± 0.81), 1.35 mm (SD ± 1.00) and 1.35 mm (SD ± 1.03). Using the PCS, the ND at the target for 1 mm, 3 mm and 5 mm slices were 3.84 mm (SD ± 1.75), 4.41 mm (SD ± 2.31) and 4.41 mm (SD ± 2.11), respectively. With all comparable slice thicknesses, the robotic device was significantly more accurate compared to the low-cost device (p < 0.001). Needle placement with the PCS resulted in lower intervention time (mean, 158.83 s [SD ± 23.38] vs. 225.67 s [SD ± 17.2]). Conclusion: Although the robotic device provided more accurate results, both guidance systems showed acceptable results and may be helpful for interventions in difficult anatomical regions and for those requiring complex multi-angle trajectories.

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The rehabilitation of the skull's bones is a difficult process that poses a challenge to the surgical team. Due to the range of design methods and the availability of materials, the main concerns are the implant design and material selection. Mirror-image reconstruction is one of the widely used implant reconstruction techniques, but it is not a feasible option in asymmetrical regions. The ideal design approach and material should result in an implant outcome that is compact, easy to fit, resilient, and provides the perfect aesthetic and functional outcomes irrespective of the location. The design technique for the making of the personalized implant must be easy to use and independent of the defect's position on the skull. As a result, this article proposes a hybrid system that incorporates computer tomography acquisition, an adaptive design (or modeling) scheme, computational analysis, and accuracy assessment. The newly developed hybrid approach aims to obtain ideal cranial implants that are unique to each patient and defect. Polyetheretherketone (PEEK) is chosen to fabricate the implant because it is a viable alternative to titanium implants for personalized implants, and because it is simpler to use, lighter, and sturdy enough to shield the brain. The aesthetic result or the fitting accuracy is adequate, with a maximum deviation of 0.59 mm in the outside direction. The results of the biomechanical analysis demonstrate that the maximum Von Mises stress (8.15 MPa), Von Mises strain (0.002), and deformation (0.18 mm) are all extremely low, and the factor of safety is reasonably high, highlighting the implant's load resistance potential and safety under high loading. Moreover, the time it takes to develop an implant model for any cranial defect using the proposed modeling scheme is very fast, at around one hour. This study illustrates that the utilized 3D reconstruction method and PEEK material would minimize time-consuming alterations while also improving the implant's fit, stability, and strength.