Jaw Functional Orthopedics and Cranoficial Growth
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Investigation of dynamic response characteristics of light fixed-wing aircraft
No full textIn order to ensure the stability of light fixed-wing aircraft during flight missions, considering the effects of relative airflow velocity and angle of attack, the distribution characteristics of velocity and pressure fields under different conditions, as well as the law of change of dynamic parameters, were derived by using aerodynamic methods. In the free modal condition, the modal truncation method was used to simulate and analyze the low-order modal shapes. Based on the modal analysis results, the sweep frequency range was set to 3-50 Hz, with a step size of 1.6 Hz, for a total of 30 substeps. A harmonic load of 1500 N was applied to the fuselage, and the displacement-frequency response curves and stress-frequency response curves of the fuselage structure and wing structure were extracted after the calculation. The results shows that the maximum lift-drag ratio occurs when the angle of attack is 6°, and the peak displacement deformation of the aircraft occurred around 24 Hz
Improving piano music signal recognition through enhanced frequency domain analysis
No full textFeature extraction is a crucial component in the analysis of piano music signals. This article introduced three methods for feature extraction based on frequency domain analysis, namely short-time Fourier transform (STFT), linear predictive cepstral coefficient (LPCC), and Mel-frequency cepstral coefficient (MFCC). An improvement was then made to the MFCC. The inverse MFCC (IMFCC) was combined with mid-frequency MFCC (MidMFCC). The Fisher criterion was used to select the 12-order parameters with the maximum Fisher ratio, which were combined into the F-MFCC feature for recognizing 88 single piano notes through a support vector machine. The results indicated that when compared with the STFT and LPCC, the MFCC exhibited superior performance in recognizing piano music signals, with an accuracy rate of 78.03 % and an F1 value of 85.92 %. Nevertheless, the proposed F-MFCC achieved a remarkable accuracy rate of 90.91 %, representing a substantial improvement by 12.88 % over the MFCC alone. These findings provide evidence for the effectiveness of the designed F-MFCC feature for piano music signal recognition as well as its potential application in practical music signal analysis
Effect of aging process on precipitated phase and properties of mechanical extruded aluminum alloy
No full textAs the industrial sector develops, the performance requirements for aluminum alloys are also constantly improving. The study explores how aging and rolling treatment affect aluminum alloys' precipitates and mechanical properties by controlling the parameters of aging process and rolling deformation variables. 7N01 aluminum alloy was selected as the experimental object, and the samples were treated with non-aging, natural aging, artificial aging, and rolling deformation. How aging processes and rolling deforming affected alloys’ mechanical properties was evaluated through performance testing (mechanical and tensile testing) and material fiber characterization methods (advanced electronic instruments). These results confirmed that the combination of three aging pre-treatments + R20 % + 120 °C re-aging could significantly improve the hardness of aluminum alloys and maintain high ductility. As the deformation decreased, the time for the sample to reach the hardness peak was shorter and the hardness was higher. The 20 % deformation sample’s strength was better than the 80 % deformation sample’s. This confirmed that appropriate aging process and deformation combinations could improve the strength and hardness of aluminum alloys. These results have certain guiding significance for optimizing the aging process of mechanical extruded aluminum alloys and provide reference for the study of related alloy properties
Advances of 3D printing in oral oncology: personalized technologies for patients – a narrative review
No full textThis study presents a narrative review of the literature that focuses on the substantial relevance and practical application of additive manufacturing and 3D printing in the context of oncology patients in the dental field. To address innovative technologies for diagnosis and treatment, this review underscores the progressive role of 3D printing in the creation of customized models for rehabilitation, surgical planning, prosthetics, examinations, and even tissue engineering. We analyzed five articles focused on the following categories: applications, benefits, and challenges associated with additive manufacturing; 3D printing; head and neck cancer; as well as assistive technology in the context of improving the effectiveness of treatments for people with this type of neoplasm. Oropharyngeal squamous cell carcinoma stood out as the most cited neoplasm for the use of 3D printing. 3D printing has played a significant role in transforming oral cancer treatment by providing customized solutions and enhancing outcomes: custom implants and prosthetics, patient-specific radiotherapy accessories, dose modulation devices, and improved preoperative planning. Additionally, 3D printing enables the production of complex medical devices in a single process, reducing steps and potentially costs. This also opens doors to creating more affordable solutions and extends the reach of personalized treatment to a greater number of patients. Continuous advancements in research and development of additive manufacturing and 3D printing technologies demonstrate significant potential for optimizing treatments and improving outcomes for patients with head and neck cancer
Transforming data with the arcsine distribution for random walks
No full textThis article delves into a pioneering methodology for optimizing the analysis of random walk data by implementing the arcsine distribution. The application of the arcsine distribution serves as an imperceptible yet potent solution, mitigating asymmetry and introducing bounds while effectively modeling the nuanced characteristics intrinsic to random walk patterns. Through a meticulous exploration of the mathematical foundations and practical applications of this distribution, this study discreetly advances statistical methodologies for handling random walk data. The article illuminates the theoretical underpinnings, subtle advantages, and pragmatic implications of arcsine distribution utilization, showcasing its imperceptible yet impactful role in capturing and reshaping random walk dynamics. Through a meticulous exploration of the mathematical foundations and practical applications of this distribution, this study discreetly advances statistical methodologies for handling random walk data, particularly in the context of financial modeling
Research on citrus segmentation algorithm based on complex environment
No full textAiming to address the low efficiency of current deep learning algorithms for segmenting citrus in complex environments, this paper proposes a study on citrus segmentation algorithms based on a multi-scale attention mechanism. The DeepLab V3+ network model was utilized as the primary framework and enhanced to suit the characteristics of the citrus dataset. In this paper, we will introduce a more sophisticated multi-scale attention mechanism to enhance the neural network’s capacity to perceive information at different scales, thus improving the model’s performance in handling complex scenes and multi-scale objects. The DeepLab V3+ network addresses the challenges of low segmentation accuracy and inadequate refinement of segmentation edges when segmenting citrus in complex scenes, and the experimental results demonstrate that the improved algorithm in this paper achieves 96.8 % in the performance index of MioU and 98.4 % in the performance index of MPA, which improves the segmentation effectiveness to a significant degree
Integration of robotics and automation in supply chain: a comprehensive review
No full textRobotics and automation have developed as key technologies for supply chain management as a result of the increased demand for quicker and more effective supply chains. Robotics and automation improve supply chain management by lowering long-haul expenses, boosting work and usage strength, reducing errors, declining repetitive stock checks, updating orchestrating, taking care of times, and assembling induction to the problematic and hazardous places. Robotics aids in design, creation, etc. Automation helps to do tasks that are often done by people through the use of self-operating physical machines, computer software, and other technology. Despite being widely accepted as a tool to aid in decision-making, supply chain management (SCM) has very seldom used AI and ML. This article investigates several AI and ML sub-fields that are best suited for resolving real-world SCM-related issues in order to fully realize the potential benefits of AI and Ml for SCM. In doing so, this article examines the track record of successful AI and ML applications to supply chain management and highlights the most fruitful SCM domains to apply AI and ML. And also find out the how robotics and automations helps in warehouse management. The most recent developments in robotics and automation for supply chain management are thoroughly reviewed in this paper. We first give a general overview of the difficulties that supply chain management faces before going over the many ways that robotics and automation are used at various points along the supply chain. Additionally, we go over the advantages of robots and automation in supply chain management, including higher efficiency, accuracy, lower costs, and improved safety. Lastly, we discuss some of the present drawbacks and difficulties associated with robots and automation in supply chain management and suggest some possible directions for further investigation
Checking the manufacturing of Simões Network 10 – SN10 through surface electromyography (sEMG) – case report study
No full textUse of functional orthopedic appliances (FOA) in the treatment of malocclusion and Temporomandibular Disorders (TMD) has been proved to be effective but there is still questions to be answered like the muscular action of the referred appliances. The aim of this study is checking through a proven protocol of surface electromyography (sEMG) to study muscular action of FOA to check to check if it is correctly manufactured. The appliance studied is a Simões Network 10 – SN10 to treat Class II malocclusion of retrognathia. The sEMG was collected 1 patients with class II malocclusion with retrognathia who belong to a 164 volunteers with malocclusion, in two times T1 before installation of the FOA in mouth, T2 15 minutes after the FOA installation in the mouth. sEMG data of bilateral masseter, bilateral temporal and bilateral suprahyoid muscles using conditioner signals module from Lynx Electronics Ltda with 8 channels, model EMG1000; software AqDAnalysis 4,18 from Lynx Electronics Ltda.; Software Lynx BioInspector 1,8r; passive surface electrodes (Ag/AgCl) from Noraxon Dual Electrodes (USA); dischargeable reference electrodes Kendall Meditrace (Ag/AgCl) – Canada were used for the sEMG measurements. Frequency calibration was 2000 Hz, with 2048 sample by channel and time 1,024 seconds, and filters regulation was 20 Hz and 1000 Hz. With the FOA in the mouth all measurements improved with a more simetrical sEMG in T2 in rest and isometric contraction measurements. The protocol used to check the manufacturing of functional orthopedic appliances using surface EMG proved to be a valid tool in this case report study. Further investigations are needed to confirm this protocol and check if the same happens with other types of functional orthopedics appliances
Editor’s Letter. Malocclusion treatment tools evolution – electromagnetic synergism. What is the current status of knowledge? Part I
No full textStudy on vibration isolation design using elastomeric pads and its application
No full textThe vibration mechanism of railways and urban rail transit is highly intricate, particularly within the railway environment. This study employs a variety of vertical stiffness damping pads to develop an integrated damping system for a floating slab. Through optimization of damper stiffness and arrangement, the modal characteristics of the floating slab are analyzed, resulting in a reduction of the inherent frequency of the track structure and attenuation of vibration transmission. Subsequently, this damping system is implemented in an actual engineering project to assess its effectiveness. The findings indicate that lower stiffness in the vibration isolation pad corresponds to a smaller inherent frequency for the floating slab, thereby enhancing its damping efficacy. Utilizing elastic supports for vibration isolation pads within the track structure can mitigate upper structure vibrations induced by trains