Angle Profiles Research Articles

Anthropometric and Angular Measurements in Healthy Persian Females in Comparison to the Golden Ratio.

Anthropology is the scientific exploration of the human body morphology. The present study aims to establish the anthropometric norms among young Persian ethnic women and compare them with golden proportion, a mathematical formula in facial esthetics. This cross-sectional study was performed on Persian women between July 2020 and January 2021. Persian women were randomly selected based on the inclusion criteria of the study. Two standard photos were taken of each participant in profile and frontal angle, and then the anthropometric ratios were extracted and compared in different groups. Two hundred twenty-five Persian women aged 20-50 years with an average age of 32.4 ± 7.09 were included. The golden ratio in Fars ethnicity was 1.79 ± 0.24. Forehead height I significantly increased with age (p value = 0.03). Philtrum length also showed a significant age-related increase (p value = 0.001). Lower and upper lip heights increased with age (p value = 0.002). Our results revealed statistically significant differences in the mean labial fissure width among the three age groups (p value = 0.009). Lower vermilion height significantly decreased with increasing age (p value = 0.028). The mentolabial and nasal dorsum angles exhibited significant differences among the age groups (p value = 0.002). Furthermore, the jaw and chin angles were notably lower in the younger age groups (p value = 0.047 and 0.001, respectively). When comparing different ethnicities, the Turk ethnicity stood out as having a significantly higher chin angle. In conclusion, the present study challenges the universality of the golden ratio, with Persian females demonstrating a closer adherence to a ratio of 1.75 and recommending a modified golden ratio for Middle Eastern. Our findings also highlight the importance of considering age-related changes in cosmetic interventions, particularly lip and forehead dimensions.

MATHEMATICAL MODEL AND OPTIMIZATION ALGORITHM ACCORDING TO THE CRITERIA OF MINIMUM CONTACT STRESS FOR INVOLUTE SPUR GEARS WITH INCREASED CONTACT RATIO

Reducing the mass and dimensions of involute spur gears is an actual task of modern mechanical engineering. One of the perspective ways to solve it is the use of gearing with an increased working tooth depth and profile contact ratio εα ≥ 2. The study is devoted to the development of optimal design methods for such gears. Optimality criteria is formulated as follows: the contact stresses in the pitch point must take a minimum value when all constructive, geometric, kinematic, and technological constraints are met, first, when the profile contact ratio εα ≥ 2 is ensured. Variables planning are defined. These are addendum coefficients of the basic racks tooth for pinion and wheel h*a1, h*a2; profile angle of the basic rack α; addendum modification coefficient of the pinion x1. Formed a system of constraints for the variables planning: the main functional constraint of the minimum value of the profile contact ratio: εα ≥ 2; constraint for the addendum coefficients of the basic racks tooth for pinion and wheel h*a1, h*a2; constraint for profile angle of the basic rack α; constraint for addendum modification coefficients x1, x2; absence of the cutter interference for tooth dedendum; absence of the sharpening for tooth addendum; absence of the mesh interference; ensuring the bending strength of pinion and wheel teeth. A method for solving the problem of optimal design is chosen. The method of probing the space of design parameters was chosen from all the variety. The points of the LPτ-sequence are used as test points. The method allows you to operate with a significant number of parameters – up to 51, provides a sufficiently large number of evenly distributed test points – up to 220. The algorithm for optimal design of gear has been developed. The main stages of the algorithm are as follows: setting input data (numerical constraints on design variables, gear parameters and its load); generation of LPτ-sequence for variables planning with simultaneous consideration of their numerical constraints; checking of functional constraints; additional verification calculations (if necessary) of the gearing contact strength; formation of an array of possible solutions; searching of the best solution variant (the test point corresponding to the minimum value of the objective function) by sorting the array.

2D and 3D Nonlinear Finite Element Sensitivity Analysis of the Static and Dynamic Behavior of the Adobe Pyramid of Huaca de la Luna, Trujillo, Perú

ABSTRACT Huaca de la Luna is a monumental earthen complex near Trujillo, Peru built by the Moche civilization from 200 to 850 C.E. Its principal structure, a stepped pyramid constructed with millions of adobe bricks on sloping bedrock and sandy soil, presents severe structural damage at the northwest corner. A sensitivity study of the static and dynamic response of the pyramid is conducted in Abaqus/CAE Explicit using 2D and 3D nonlinear finite element models derived from archaeological, material, and geotechnical data. Concrete damaged plasticity and Mohr-Coulomb formulations are adopted to represent adobe and sandy soil, respectively. Models undergo quasi-static gravitational loading followed by dynamic application of lateral ground accelerations. Lateral capacity is defined as the applied acceleration that produces collapse and is identified from the time-evolution of elastic strain and plastic dissipation energies. Initial 2D sensitivity analysis investigates the effect on lateral capacity of adobe tensile strength, bedrock/soil configuration, west façade profile, eastward architecture, and plastic dilation angle. Critical configurations identified from 2D analysis are expanded into 3D models. All results show stability under gravitational load. At dynamically induced failure, damage corresponds closely to the extant collapse of the northwest corner of the pyramid, suggesting that present damage is due to seismic activity.

Study of a tilted thin accretion disk around a Kerr-Taub-NUT black hole

The accreting collapsed object GRO J1655-40 could contain the gravitomagnetic monopole (GMM), and it was shown to be better described by the Kerr-Taub-NUT (KTN) spacetime instead of the Kerr spacetime. The warped accretion disk has also been observed for the same collapsed object. Motivated by these, we study a tilted thin inner accretion disk around a KTN black hole. Such a tilting could have a significant effect on the X-ray spectral and timing features via the Lense-Thirring effect. Taking into account the contribution from the inner accretion disk for the KTN black hole, here we calculate the radial profile of a tilt angle. Depending on the numerical values of the viscosity of the accreting material and Kerr parameter, GMM tends the angular momentum of the disk to align along the black hole's spin axis, or to make it more tilted. Our solution for the radial profile of the tilted disk around a KTN black hole could be useful to probe the strong gravity regime, and could also give indirect evidence for the existence of GMM in nature.

Optimal design of off-grid hybrid system using a new zebra optimization and stochastic load profile

Renewable energy systems are becoming more and more popular and used these days as a result of environmental, technical, and economic concerns. The reliable and optimal economic size of the system is the primary issue with the renewable energy-based power supply system for rural electrification. A new Zebra optimization algorithm (ZOA) is used for the optimal design and to perform the techno-economic performance analysis of the renewable energy-based off-grid power supply system with the stochastic load profile of Ethiopian rural communities. The components of the power supply system are modeled, the objective function is formulated, and optimization and techno-economic analysis are performed to get the minimum total annual cost of the hybrid system with the consideration of loss of power supply probability (LPSP), stochastic load profile and solar module optimal tilt angle. Three off-grid power supply systems, such as PV-BAT, PV-WT-BAT, and WT-BAT, are proposed to evaluate the optimal configuration for the study site at various LPSP. The study’s findings showed that the photovoltaic-battery (PV-BAT) system, with an optimal size of 3483.161 kW of PV, 3668 units of storage batteries (11,444.160 kWh), and 2082 kW of converter at 0.044030% LPSP, is the best configuration for electrifying the rural communities of the study site with the minimum annual total cost of 621,736.056 USD and 0.227063 $/kWh COE. It results in a 3.3% annual total cost reduction and a 1.3% unmet load (kWh/year) improvement as compared to the PV-WT-BAT system. The performance of the proposed ZOA in obtaining the optimal size of the renewable energy-based power supply system for rural communities is evaluated by comparing it with the previous studies, gray wolf optimization (GWO) and HOMER Pro software, and it was found that the proposed algorithm is best at finding the optimal size of the power supply system at the minimum annual cost. The standard deviation for ZOA and GWO, respectively, in determining the optimal configuration value for 25 runs is 14.295 and 36.360 for the PV-BAT configuration, indicating that ZOA is more reliable than GWO in determining the optimal size. Furthermore, ZOA yields a 16.76% reduction in the total net present cost when compared to the HOMER software results.

A transmission line tower tilt detection method based on BeiDou positioning signals and UAV inspection images

Owing to the angle deviation of UAV patrol inspection image acquisition, the current detection method of transmission line tower tilt lacks positioning constraints, which leads to the need for repeated judgment of the transmission line tilt. To solve this problem, a method for detecting the inclination of transmission line towers based on the Beidou positioning signal and UAV inspection images is proposed. Constructing a transmission line tower tilt detection framework, the acquisition unit uses the Beidou measurement antenna installed on the tower to obtain its position information and the corresponding tower-monitoring image. After pre-processing by the monitoring unit, the collected information is transmitted to the data center through the communication network. The positioning module uses RTK positioning technology to solve the tower position in real time. The tilt detection module uses the YOLOv4 network to identify the tower target in the monitoring image, and regards it as the area of interest. The LSD algorithm is used to extract the central axis and calculate the tilt angle of the tower profile. Combined with the processing results of the positioning module, the tower tilt angle is monitored. The detection results are presented through the monitoring terminal, and safety warnings are provided. The experimental results show that this method can achieve precise positioning of tower positions, and the positioning results are very close to the actual situation. After 100 training sessions, the network loss can be reduced to 0.06, enabling tower tilt detection and determination of its inclination.

Studies of beam ion confinement to enhance plasma performance on EAST

A key physics issue for achieving steady-state high-performance plasmas on EAST tokamak is to decrease beam-ion losses to improve plasma confinement during neutral beam injections (NBIs). To decrease the beam losses, previous counter-I p NBI injections are upgraded to co-I p injections. Analysis shows that due to the reversed direction of drift across the flux surfaces caused by the pitch angle, the beam prompt loss fraction decreases from about 49% to 3% after the upgrade. Moreover, because of the change of entire beam path, beam shine-through (ST) loss fraction for counter-I p tangential and counter-I p perpendicular injections is reversed to co-I p tangential and co-I p perpendicular injections, respectively. Due to the change in the initial trapped-confined beam ion fraction caused by the peaked pitch profiles, the losses induced by toroidal ripple field are also reversed after the upgrade. To further improve the beam-ion confinement under the present NBI layout, the amplitudes of toroidal field are increased from 1.75 to 2.20 T. Result shows that, due to the smaller orbit width and peaked pitch angle profile, the beam prompt loss power is lower with higher toroidal field. Due to the synergy of higher initial trapped-confined beam ion fraction and narrower Goldston-White-Boozer (GWB) boundary, the loss induced by ripple diffusion is higher with higher toroidal field. The combined effect of beam ST loss, prompt loss and ripple loss, contributes to the increase in beam ion density. The decrease in beam loss power enhances beam heating efficiency, especially the fraction of beam heating ions. Finally, comparison between simulation and measurement by 235U fission chamber (FC) indicates that the increase in neutron rate is mainly contributed by improvement of beam-ion confinement. This study can provide potential support for beam operation and high-T i experiment on EAST tokamak.

Forming a database to study reversed magnetic shear from the National Spherical Torus eXperiment using machine learning

Achieving a long-lived reversed magnetic shear (RMS) target plasma in the National Spherical Torus eXperiment Upgrade will require developing various sustainment scenarios. To help with the ongoing plasma control efforts, the development of a new analysis for the motional Stark effect (MSE) diagnostic using a machine learning algorithm, namely, MSE-ML, is described. MSE-ML will be used to identify patterns during RMS discharges, some of which suffer magnetohydrodynamic (MHD) events resulting in current redistribution and monotonic q-profiles. A database consisting of q and magnetic shear profiles is being constructed primarily based on the existing National Spherical Torus eXperiment data with equilibrium reconstructions constrained by the magnetic field pitch angle profile measured using the multi-channel MSE diagnostic. An unsupervised k-means clustering of the data is developed to study the RMS formation as a function of time. The initial clustering from the q-profiles shows significant differences in both amplitude and the duration of the RMS period. As a goal, the clustering results that detect and distinguish shots with substantial and sustained RMS are to be used as a preprocessing step in a supervised algorithm to identify the underlying conditions that lead to long-lasting improved confinement with RMS. Another aim of the MSE-ML study is to identify precursors of RMS-destroying MHD events in either derived data such as the q-profile or directly measured data such as the magnetic field pitch angle profile.

2D Facial Analysis Performed by a Human Operator Versus an Artificial Intelligence Software.

Artificial intelligence (AI) has been a contribution in recent years to the development of new tools for dental, surgical, and esthetic treatment. In the case of image diagnosis, AI allows automated analysis of some facial parameters. The aim of this study was to evaluate the precision and reproducibility of these IA analyses compared with a human operator. Thirty subjects were selected, and frontal and profile photographs were taken of each. The photographs were previously calibrated and then analyzed by a human operator and an AI for vertical, horizontal, symmetry parameters, and facial profile angles. Statistically significant differences were found in at least 1 vertical, horizontal, symmetry, and facial profile measurement. The 2D facial analysis performed on photographs using AI is an interesting and constantly evolving tool. However, there are still many differences with the analysis performed by the human operator, so it should be used carefully. Further studies using metric measurements should be performed to contrast the values obtained by human operators and AI and to analyze the accuracy of point selection in facial soft tissues.

Investigation of contact ratio and dynamic characteristics of non-circular planetary gear train in hydraulic motor

As a basic component of the non-circular gear hydraulic motor (NGHM), the non-circular planetary gear train (NPGT) offers a number of advantages, including low velocity, high output torque and compact design. Two different types of NPGT pitch curves have been designed using the 4–6 type of NGHM as an example. Aiming at two kinds of pitch curves, the contact ratio solution methods for the planetary gear meshing respectively with the sun gear and the inner gear ring are proposed. A comparative analysis of an integrated pitch curve design and a segmented pitch curve design is conducted to evaluate the effects of varying addendum coefficient (AC) and tool tooth profile angle (TTPA) on the contact ratio. Furthermore, the influence of load, velocity, and contact ratio on the dynamic characteristics (DC) of the NPGT with a segmented pitch curve is investigated through dynamic simulation. The results show that AC and TTPA significantly affect the contact ratio, with an increase in contact ratio observed as TTPA decreases and AC increases. Additionally, the load has a notable impact on the dynamic meshing force and its fluctuation. A higher contact ratio is associated with greater transmission stability in the gear train. This study provides a theoretical foundation for the design and optimization of NGHMs, and expands the potential application of contact ratio effects on NPGTs in this field.

Assessment of Nasal Morphology within various Sagittal Skeletal Growth Patterns—A Cross-sectional Cephalometric Study

ABSTRACT Aim: The present research aims to assess the nasal morphology within various Sagittal skeletal growth patterns like Classes I, II and III. Material and Method: The present research assesses various nasal parameters within equally distributed 150 lateral cephalograms having Skeletal Classes I, II, and III by manual tracing. The study identified differences in nasal morphology across different skeletal classes. Result: Naso-facial angle and Profile angle were greater in Class II cases, whereas Naso-mental angle was greater in Class III cases. Conclusion: Nasal morphology must be considered for accurate diagnosis, treatment planning, and facial reconstruction.

Experimental optimization of the FSW parameters to weld the dissimilar Al- and Cu-alloys by using additives at their joints

Friction stir welding (FSW) stands as a promising technique for joining materials, offering advantages over conventional methods. This study investigates the influence of tool tilt angle, rotational speed and profile on welded joint characteristics using a design of experiment (DOE) approach. The research objective aims to determine optimal parameter combinations for improved mechanical properties. Methodology entails the systematic variation of tilt angle, rotational speed and tool profile in a DOE setup, with subsequent FSW of samples. Mechanical testing, including tensile, bend and hardness tests, is conducted on 24 samples, with scanning electron microscope (SEM) and microstructure analysis on two specimens. Results reveal that higher tilt angles, rotational speeds and threaded profiles yield increased tensile strength but decreased ductility. Similarly, bend tests show higher fracture loads but reduced deflection before fracture under these conditions. Hardness tests indicate elevated hardness in welded areas, with variations based on input parameters. Main findings highlight the importance of parameter optimization for desired mechanical properties. Lower tilt angles and rotational speeds promote smoother material flow and uniform heating, resulting in consistent microstructure and hardness distribution. In conclusion, this study provides valuable insights for optimizing FSW parameters to achieve desired mechanical properties in welded joints. The combination of a 2° tilt angle, threaded tool profile and 1500 rpm rotational speed demonstrated the highest tensile strength, while a 1° tilt angle, cylindrical tool profile and 1000 rpm rotational speed yielded highest ductility.

Artificial neural network-based control of powered knee exoskeletons for lifting tasks: design and experimental validation

AbstractThis study introduces a hybrid model that utilizes a model-based optimization method to generate training data and an artificial neural network (ANN)-based learning method to offer real-time exoskeleton support in lifting activities. For the model-based optimization method, the torque of the knee exoskeleton and the optimal lifting motion are predicted utilizing a two-dimensional (2D) human–exoskeleton model. The control points for exoskeleton motor current profiles and human joint angle profiles from cubic B-spline interpolation represent the design variables. Minimizing the square of the normalized human joint torque is considered as the cost function. Subsequently, the lifting optimization problem is tackled using a sequential quadratic programming (SQP) algorithm in sparse nonlinear optimizer (SNOPT). For the learning-based approach, the learning-based control model is trained using the general regression neural network (GRNN). The anthropometric parameters of the human subjects and lifting boundary postures are used as input parameters, while the control points for exoskeleton torque are treated as output parameters. Once trained, the learning-based control model can provide exoskeleton assistive torque in real time for lifting tasks. Two test subjects’ joint angles and ground reaction forces (GRFs) comparisons are presented between the experimental and simulation results. Furthermore, the utilization of exoskeletons significantly reduces activations of the four knee extensor and flexor muscles compared to lifting without the exoskeletons for both subjects. Overall, the learning-based control method can generate assistive torque profiles in real time and faster than the model-based optimal control approach.

Surrogate-Based Multidisciplinary Optimization for the Takeoff Trajectory Design of Electric Drones

Electric vertical takeoff and landing (eVTOL) aircraft attract attention due to their unique characteristics of reduced noise, moderate pollutant emission, and lowered operating cost. However, the benefits of electric vehicles, including eVTOL aircraft, are critically challenged by the energy density of batteries, which prohibit long-distance tasks and broader applications. Since the takeoff process of eVTOL aircraft demands excessive energy and couples multiple subsystems (such as aerodynamics and propulsion), multidisciplinary analysis and optimization (MDAO) become essential. Conventional MDAO, however, iteratively evaluates high-fidelity simulation models, making the whole process computationally intensive. Surrogates, in lieu of simulation models, empower efficient MDAO with the premise of sufficient accuracy, but naive surrogate modeling could result in an enormous training cost. Thus, this work develops a twin-generator generative adversarial network (twinGAN) model to intelligently parameterize takeoff power and wing angle profiles of an eVTOL aircraft. The twinGAN-enabled surrogate-based takeoff trajectory design framework was demonstrated on the Airbus A3 Vahana aircraft. The twinGAN provisioned two-fold dimensionality reductions. First, twinGAN generated only realistic trajectory profiles of power and wing angle, which implicitly reduced the design space. Second, twinGAN with three variables represented the takeoff trajectory profiles originally parameterized using 40 B-spline control points, which explicitly reduced the design space while maintaining sufficient variability, as verified by fitting optimization. Moreover, surrogate modeling with respect to the three twinGAN variables, total takeoff time, mass, and power efficiency, reached around 99% accuracy for all the quantities of interest (such as vertical displacement). Surrogate-based, derivative-free optimizations obtained over 95% accuracy and reduced the required computational time by around 26 times compared with simulation-based, gradient-based optimization. Thus, the novelty of this work lies in the fact that the twinGAN model intelligently parameterized trajectory designs, which achieved implicit and explicit dimensionality reductions. Additionally, twinGAN-enabled surrogate modeling enabled the efficient takeoff trajectory design with high accuracy and computational cost reduction.

First Results of Airborne GNSS Radio Occultation Sounding From Airbus Commercial Aircraft

AbstractThe lack of high vertical resolution atmospheric thermodynamic structure observations inside or near major weather events impedes our understanding of physical processes and their predictability in numerical weather prediction (NWP) models. Airborne Global Navigation Satellite System (GNSS) radio occultation (airborne radio occultation [ARO]) has proven to be a viable remote sensing option to offer dense soundings near flight tracks. The global fleet of commercial aircraft already equipped with GNSS receivers could be leveraged to produce an unprecedented number of ARO soundings along global flight paths. Eleven cases of atmospheric bending angle and refractivity profiles were successfully retrieved and compared with the colocated European Center for Medium‐Range Weather Forecasting global reanalysis data. Good quality measurements are obtained with median refractivity differences less than 1% in the middle and upper troposphere, between 5.5 and 11.5 km. Given the use of aircraft data (e.g., Aircraft Meteorological DAta Relay) for data assimilation, incorporating ARO profiles would be a valuable addition, further enhancing the accuracy of aviation and weather forecasts.

Perancangan Mesin Pengupas Singkong dengan Metodologi NIDA-QFD untuk Industri Keripik Singkong ABC Banyuwangi

Banyuwangi produces potential cassava chips. However, due to slow manual stripping, production capacity is low, market demand is high, and product quality decreases. This study develops an optimized peeling machine using NIDA-QFD to meet user needs and increase innovation. Experimental design model and 5 alternative actions of cassava peeling machine. ABC Banyuwangi Industry with 10 respondents, including owners and employees, was given intervention in the action decision. NIDA-QFD developed a cassava peeling machine design that is efficient and minimizes risk. Alternative 3 was chosen, with user body dimensions (height 110-180 cm), using sturdy materials (steel angle profile, stainless steel plate), and having 5 peeling rolls (diameter 80 mm, length 910 mm) for an effective and efficient stripping process. The 220 volt 1/2 PK AC drive system ensures the roll rotates with optimal speed and torque. The cassava skin remover is made of stainless steel which is rust-resistant and easy to clean, so it is feasible to overcome the problem of manual peeling of cassava and opportunities for progress in the cassava chips industry.

Study on the internal waves induced by a submerged body moving in a continuously stratified fluid

This paper studies the characteristics of internal waves induced by the motion of a submerged body through a combination of experimental and numerical methods. First, by deploying an array of conductivity probes in an experiment, the temporal evolution of the internal wave at the plane of the conductivity probe array is obtained and compared with numerical simulation results based on the Navier–Stokes equations, thereby validating the accuracy of the Computational Fluid Dynamics (CFD) model. Subsequently, utilizing CFD calculations, further exploration is conducted on the spatiotemporal distribution characteristics of the internal wave, encompassing its generation and evolution, velocity field distribution, wake angle, and wave profile features. Finally, the variation of the internal wave with the Froude number (Fr) is investigated, revealing that it varies apparently with Fr, including the wave component, wave mode, wake length, wake angle, wave amplitude, and so on. It is found that when Fr is large, the internal wave converges toward the centerline behind the body, until forming a line. The wave magnitude changes with Fr in four stages, i.e., increasing with Fr from zero in the first stage, reaching a peak and decreasing thereafter in the second stage, then changing little in the third stage, and finally increasing approximately linearly in the fourth stage.

Implementation of a real-time MSE system.

Motional Stark effect polarimetry is a key diagnostic for plasma fusion research since its usage on PBX-M. The MSE diagnostic measures the radial magnetic pitch angle profile in a plasma from a neutral beam by observation of Stark split D-alpha emission from atoms excited by collision with ions and electrons in the plasma. The pitch angle measurement is used with equilibrium reconstruction codes to determine the q-profile for studies of plasma stability, confinement, and transport. Historically, the algorithm was used in a post-processing fashion. The goal of our work was to apply this method in real time and pass the results to the plasma control system computer for real-time equilibrium reconstruction and control.

Human-Exoskeleton Coupling Simulation for Lifting Tasks with Shoulder, Spine, and Knee-Joint Powered Exoskeletons.

In this study, we introduce a two-dimensional (2D) human skeletal model coupled with knee, spine, and shoulder exoskeletons. The primary purpose of this model is to predict the optimal lifting motion and provide torque support from the exoskeleton through the utilization of inverse dynamics optimization. The kinematics and dynamics of the human model are expressed using the Denavit-Hartenberg (DH) representation. The lifting optimization formulation integrates the electromechanical dynamics of the DC motors in the exoskeletons of the knee, spine, and shoulder. The design variables for this study include human joint angle profiles and exoskeleton motor current profiles. The optimization objective is to minimize the squared normalized human joint torques, subject to physical and task-specific lifting constraints. We solve this optimization problem using the gradient-based optimizer SNOPT. Our results include a comparison of predicted human joint angle profiles, joint torque profiles, and ground reaction force (GRF) profiles between lifting tasks with and without exoskeleton assistance. We also explore various combinations of exoskeletons for the knee, spine, and shoulder. By resolving the lifting optimization problems, we designed the optimal torques for the exoskeletons located at the knee, spine, and shoulder. It was found that the support from the exoskeletons substantially lowers the torque levels in human joints. Additionally, we conducted experiments only on the knee exoskeleton. Experimental data indicated that using the knee exoskeleton decreases the muscle activation peaks by 35.00%, 10.03%, 22.12%, 30.14%, 16.77%, and 25.71% for muscles of the erector spinae, latissimus dorsi, vastus medialis, vastus lateralis, rectus femoris, and biceps femoris, respectively.

Association of Peri-Implant Mucosa Dimensions With Emergence Profile Angles of the Implant Prosthesis.

The primary aim of this cross-sectional study was to investigate the association between prosthesis design and peri-implant mucosa dimensions and morphology. The secondary aim was to investigate associations between mucosal dimensions and the presence of mucositis. Forty-seven patients with 103 posterior bone level implants underwent clinical and radiographic examination, including cone beam computer tomography and intraoral optical scanning. Three-dimensional models for each implant and peri-implant mucosa were constructed. Vertical mucosa height (TH), horizontal mucosa width at implant platform (TW), and 1.5 mm coronal of the platform (TW1.5), as well as mucosal emergence angle (MEA),deep angle (DA), and total contour angle (TA) were measured at six sites for each implant. There was a consistent correlation between peri-implant mucosa width and height (β = 0.217, p < 0.001), with the width consistently surpassing height by a factor of 1.4-2.1. All three angles (MEA, DA, TA) were negatively associated with mucosa height (p < 0.001), while DA was negatively associated with mucosa width (TW1.5) (p < 0.001, β = -0.02, 95% CI: -0.03, -0.01). There was a significant negative association between bleeding on probing (BoP) and mucosa width at platform (OR 0.903, 95% CI: 0.818-0.997, p = 0.043) and 1.5 coronal (OR 0.877,95% CI: 0.778-0.989, p = 0.033). Implants with less than half sites positive for BoP (0-2/6) had significantly higher mucosa height (OR 3.51, 95% CI: 1.72-7.14,p = 0.001). Prosthesis design can influence the dimensions of the peri-implant mucosa, with wider emergence profile angles associated with reduced peri-implant mucosa height. In particular, a wider deep angle is associated with reduced mucosa width in posterior sites. Reduced peri-implant mucosa height and width are associated with more signs of inflammation. Registered in Thai Clinical Trials Registry: http://www.thaiclinicaltrials.org/show/TCTR20220204002.