Showing papers in "Highlights in Science, Engineering and Technology in 2022"
TL;DR: This paper finally verifies that the density-based clustering method has a good classification effect on the data with high complexity.
Abstract: With the rapid development and wide popularization of information technology, a large amount of data also follows. It is very important to use data mining tools to screen valuable information from complex data. As one of the widely used density clustering algorithms, density- based spatial clustering of application with noisy (DBSCAN) algorithm is an important data mining method. It can find the multi-dimensional relationship between data elements from the data set, complete the clustering of arbitrary shape and noisy data sets when the number of cluster classes is unknown, and support spatial database. Therefore, based on the example of judging the correctness of the relationship between the user's meter and the substation transformer, and supported by the clustering technology of DBSCAN, this paper finally verifies that the density-based clustering method has a good classification effect on the data with high complexity.
10 citations
TL;DR: In this article , the application of neural network algorithm in artificial intelligence recognition was analyzed, in order to provide some reference, and the results showed that the combination of NN algorithm and AI recognition is an important product of science and technology, greatly facilitate people's life and production.
Abstract: artificial intelligence technology is an important product of the development of science and technology, greatly facilitate people's life and production, in recent years, artificial intelligence technology without living and living artificial intelligence recognition technology is constantly improving, and the perfect process requires the organic combination of neural network algorithm and artificial intelligence recognition. Based on this, this paper analyzes the application of neural network algorithm in artificial intelligence recognition, in order to provide some reference.
4 citations
TL;DR: This review paper surveys several distinct deep learning techniques and provides a comprehensive review of automatic fake news detection classification tasks and the datasets and models used, demonstrating the performance evaluation on different approaches.
Abstract: One of the major concerns nowadays is the rapid spreading of fake news or unverified information on all kinds of social media. Misinformation and disinformation on the digital media of news distribution have brought significant negative impacts to our community, which the traditional techniques can no longer detect and deal with it effectively. It is urgent to squelch fake news immediately to limit its impact on the economy and society. As deep learning techniques continue developing in recent decades, scholars successfully deployed deep neural networks on fake news detection tasks. The first noticeable thing is to admit that the fake news detection task has made significant accomplishments as fast as we hoped. It is necessary to study further and broadly review the state-of-the-art fake news detection approaches. In this review paper, we survey several distinct deep learning techniques and provide a comprehensive review of automatic fake news detection classification tasks and the datasets and models used, demonstrating the performance evaluation on different approaches. We have also analyzed the potential challenge we encountered in fake news detection.
4 citations
TL;DR: In this article , the reliability evaluation method of the motorized spindle is proposed to avoid the problem that the traditional method cannot be analyzed when there is no failure data, and provides a new idea for the reliability performance evaluation of the spindle.
Abstract: Electric spindle is a key functional component of CNC machining equipment including CNC machine tools, and its reliability level is a key bottleneck factor restricting the reliability of high-end CNC equipment. So far, the research on the reliability evaluation method of electric spindle is still in its infancy, and there is a lack of Systematic and complete theoretical support. The motorized spindle is a typical high-reliability and long-life product, and it is difficult to fail or fail due to obvious performance degradation within a limited test time. Therefore, the traditional reliability evaluation method based on statistical theory is not effective. Therefore, it is of great significance to carry out the early reliability test of the motorized spindle and the reliability evaluation of the motorized spindle without failure data, which is of great significance to reasonably evaluate the reliability level of the motorized spindle. At present, when there is no failure data or very little failure data for the motorized spindle of the machine tool, only the point estimate of the parameter or the one-sided confidence interval of the parameter can be calculated, and it is extremely difficult to obtain the point estimate and the interval estimate at the same time, which will affect the reliability analysis results. Consistency. In order to solve this problem, this paper takes a certain type of CNC machine tool motorized spindle as the research object, and determines the monitoring points and monitoring information according to the failure analysis of similar motorized spindles; combines the test information to evaluate the reliability of the motorized spindle without failure data. The reliability evaluation method of the motorized spindle proposed in this paper can effectively avoid the problem that the traditional method cannot be analyzed when there is no failure data, and provides a new idea for the reliability evaluation of the motorized spindle.
3 citations
TL;DR: In this paper , an automatic mechanical workpiece measurement system based on machine vision is designed in order to solve the problem of automatic and intelligent measurement of mechanical workpieces in industrial production, and fast visual measurement is performed to judge whether the workpiece is qualified or not, which greatly improves the accuracy of workpiece detection.
Abstract: With the rapid development of modern industrial industry, the workpiece measurement system of many industrial products gradually exceeds the operating load, and the operating efficiency is not high, the cycle is too long, and the accuracy rate is low. In order to solve the problem of automatic and intelligent measurement of mechanical workpieces in industrial production, an automatic mechanical workpiece measurement system based on machine vision is designed in this paper. The digital division of the workpiece is carried out automatically, and fast visual measurement is performed to judge whether the workpiece is qualified or not, which greatly improves the accuracy of workpiece detection. On this basis, this paper optimizes the machine vision measurement system of the workpiece based on the picture and label recognition system to make its operation efficiency higher and operation accuracy better.
2 citations
TL;DR: In this article , Zhang et al. focused on finding a better model and modifications to BCCD example datasets containing 364 images of blood cells and used Faster RCNN and Yolo v5 as the basic two models for the dataset.
Abstract: Blood Cell Count and Detection (BCCD) has always been a popular topic in object detection and many researchers have applied and modified the two basic models: Faster RCNN and Yolo. However, it is still difficult to tell which model or modification would perform better on other BCCD datasets. Thus, this paper mainly focuses on finding a better model and modifications to BCCD example datasets containing 364 images of blood cells. Faster RCNN and Yolo v5 were used as the basic two models for the dataset. Through training and comparisons between the two models, the better model was chosen to make further modifications or adjustments to achieve a better maP result possible. The result shows that in this specific dataset, Yolo v5 performs better. The modified Yolo v5 model also has an improvement of 0.6 percent of map 0.5 and 0.5 percent of map 0.95 comparing to the original model, showing that modification of model configuration, model structures including head and backbone would efficiently improve the time taken for training and maP.
2 citations
TL;DR: In this paper , a brief introduction to photolithography as well as an outlook on the future development direction is provided, and the limitations of current lithography and forecast the future of lithography is examined.
Abstract: With the rapid development of industrial intelligent manufacturing and electronic information technology, the importance of integrated circuits has grown fast. Photolithography, as the core technology of integrated circuit industry, has become a key research target for researchers all over the world. In this paper, we provide a brief introduction to photolithography as well as an outlook on the future development direction. Firstly, the key metric of lithography system, which is resolution, and how it relates to lithographic performance is analyzed. Secondly, some exposure methods developed on UV and DUV light sources are discussed, which are commonly used in the industry nowadays. Subsequently, this paper presents the structure and performance of some representative lithography equipment. Then, some summarizations are completed about the most recent advances in EUV lithography and high NA lithography. Finally, we examine the limitations of current lithography and forecast the future of lithography. The goal of this paper is to provide a guide on lithography equipment, particularly the most advanced products available nowadays. Additionally, some potential challenges that photolithography may face in its future development are highlighted, and some perspectives on how photolithography will evolve over the next decade are provided. These results shed light on guiding the future development direction of lithography machine as well as ways to push Moore’s law even further.
2 citations
TL;DR: A review of the use of preservatives, pigments, and UV filters in cosmetics can be found in this article , where the mechanisms of toxicities of preservative, such as parabens, benzalkonium chloride, and chlorphenesin are illustrated.
Abstract: As additives, scents, preservatives, stabilizers, surfactants, stains, and shine, a variety of chemical substances have been added into the creation of cosmetic, beauty, and personal care products. Many of these compounds, on the other hand, are bioactive, ecologically persistent, and have the potential to bioaccumulate, posing a major hazard to the environment and human health. To genuinely address this issue, new techniques and approaches are necessary. This review summarizes the use of preservatives, pigments, and UV filters in cosmetics. The mechanisms of toxicities of preservative, such as parabens, benzalkonium chloride, and chlorphenesin are illustrated. Parabens have non-cutaneous adverse health effects, including infertility, spermatogenesis, adipogenesis, and perinatal exposure effects. Benzalkonium chloride in preservative decreased cell viability and caused apoptotic cell death in vitro. Pigment also played an important role in cosmetics and, some pigmentations in cosmetics are made by heavy metal or have heavy metal as ingredients. Cadmium and Chromium are two commonly used heavy metal in cosmetics. UV filters absorb UV energy and transform it chemically, which can lead to breakdown and the formation of photo-unstable reactive intermediates. Future research may focus on the safety assessment of specific substance in the application of cosmetics.
2 citations
TL;DR: In this paper , a particle swarm optimization (PSO) with Computational Fluid Dynamics (CFD) was used to get a better areodynmics performance in supersonic case.
Abstract: In order to adapt to the society demand of requiring faster aircraft, this thesis aims at combining Particle Swarm optimization (PSO) with Computational Fluid Dynamics (CFD) to get a optimized airfoil which possesses a better areodynmics performance in supersonic case. This paper adopts the method of using small disturbance equation to simulate the flow field, which is more effective and stable and easier to implement. Besides, this paper adopts traditional PSO. The results show that the magnitude of ratio of lift-drag has increased by 16.29% and the magnitude of lift has risen by 13.69%, while the magnitude of drag has decreased by 2.2% after the optimization, compared with the initial airfoil. Besides, the results also reveal that the front of the optimized airfoil is wider than that of the initial airfoil and the rear of the optimized airfoil is narrower than that of the initial airfoil, which can represent that the optimized airfoil effectively enlarge the magnitude of ratio of lift-drag and lift and suppresses the drag and influence generated by shock.
2 citations
TL;DR: The Key technologies of machine vision include image acquisition, image segmentation, and image recognition, which mainly include manufacturing dimensional measurement, part inspection, and object localization, are discussed.
Abstract: Machine vision technology has a rapid development rate in recent year especially in intelligent manufacturing. The field of intelligent manufacturing will undergo a revolution. Machine vision technology is currently developing and becoming more sophisticated. The related hardware and software items are continuously improved. They increasingly became significant in the industrial production process. Machine vision can replace some human labor in intelligent manufacturing, which effectively increases production efficiency and product quality. As a result, it might help businesses achieve full production automation, quality control standardization, automation, and automation. This paper discussed the key technologies of machine vision technology used in intelligent manufacturing industry, as well as the application of machine vision in intelligent manufacturing. The Key technologies of machine vision include image acquisition, image segmentation, and image recognition. The current application of machine vision in intelligent mainly include manufacturing dimensional measurement, part inspection, and object localization.
2 citations
TL;DR: The experimental results show that the digital plane pigment types of urban construction under visual communication are about 30 kinds higher than the pigment types in traditional graphic design on average, which verifies the effectiveness of the digital graphic design of architectural modelling underVisual communication.
Abstract: This article uses computer big data modelling technology to control urban construction. Use geometric model construction, texture feature extraction and real model construction to realize 3D modelling of virtual city environment scenes. At the same time, we use three-dimensional sound modelling to analyse and summarize the information data of the architectural graphic design, complete the construction of the building information model, and conduct a series of mining and management of the building information data. This describes its basic situation and attributes to optimize the data structure. The experimental results show that the digital plane pigment types of urban construction under visual communication are about 30 kinds higher than the pigment types of traditional graphic design on average. This verifies the effectiveness of the digital graphic design of architectural modelling under visual communication.
TL;DR: In this article , the authors provide a review on target detection in autonomous driving, and briefly summarize the difficulties faced by autonomous driving target detection, and then introduce five common current target detection algorithms.
Abstract: In recent years, with the rapid development of artificial intelligence technology, major technology companies around the world have strategically shifted their attention to the field of autonomous driving, momentarily pushing the research on autonomous driving to a climax. Target detection is one of the core technologies in the field of autonomous driving. For this reason, this paper provides a research review on driverless technology, deep learning target detection algorithms, and briefly summarizes the difficulties faced by autonomous driving target detection, and then introduces five common current target detection algorithms.
TL;DR: The development of BMD is critical during the growth period, which could contribute to less incidence of osteoporosis as people get old, and the DASH diet with low sodium intake positively affects bone mineral density to some extent.
Abstract: Bone health gets more and more attention in the younger population since the peak bone mass will be achieved during one’s childhood and adolescence. Bone mineral density (BMD), an important indicator, is commonly used to indicate overall bone health. The development of BMD is critical during the growth period, which could contribute to less incidence of osteoporosis as people get old. Osteoporosis is one of the most common bone diseases, which could lead to other health complications. In addition to other factors affecting bone health such as physical activity and hormones, nutrition is the most important factor of bone health. Calcium (Ca) and vitamin D (VD) act hand in hand. The absorption of dietary calcium is highly affected by VD. Different hormones regulate Ca homeostasis and balance in the body. Moreover, bone remodeling is tightly regulated to conserve bone integrity. The bone formation is tightly coupled to the resorption. Dietary intake of sodium (Na) cannot be ignored as well. High intake of Na is negatively associated with bone health. The DASH diet with low sodium intake positively affects bone mineral density to some extent.
TL;DR: In this article , the authors refits the stepping motor with the help of the characteristics of the magnetic encoder, so as to realize the closed-loop control of the step motor.
Abstract: Stepper motor is an actuator for converting electric pulse signal into angular displacement, which is characterized by no cumulative error, low mature price and good stability, which is widely used in various industrial environments. However, its disadvantage is also very obvious, that is, can only open loop control, the motor can only passively rotate according to the signal and cannot effectively feedback control.If closed-loop control is required, servo motors with higher price and larger volume are required. In order to solve this problem, this paper refits the stepping motor with the help of the characteristics of the magnetic encoder, so as to realize the closed-loop control of the stepping motor.
TL;DR: A comprehensive review of research focusing on transfer learning (TL) in brain tumor detection and three pre-trained models which are frequently used to attain a good performance are illustrated in detail.
Abstract: Detecting abnormalities in the human body with magnetic resonance imaging has long been a challenge in medical computer-aided diagnosis (CAD). This paper presents a comprehensive review of research focusing on transfer learning (TL) in brain tumor detection. Each work starts from collecting MR images and substantial strategies are applied when preprocessing data including data augmentation and image segmentation. Multiple pre-trained models from AlexNet to Hyb-DCNN-ResNet in the latest work are focused. And the results of binary and multiple class classification are compared chronologically. Three pre-trained models which are frequently used to attain a good performance in brain tumor detection are illustrated in detail. And these pre-trained models, GoogLeNet, VGG and ResNet, all are capable to help the proposed systems reach the accuracy of 99%. The challenges even after transferring apposite knowledge to the target domain still exist in pluralistic forms. But the essence of transfer learning can support interdisciplinary research to get better performance.
TL;DR: Wang et al. as discussed by the authors gave the mainstream structure model, advantages and disadvantages, time/space complexity, problems that may be encountered in the model training process and corresponding solutions used in image classification based on convolutional neural network.
Abstract: With the deep learning (DL) sweeping the world. Traditional image classification methods are difficult to process huge image data and cannot meet people's requirements for image classification accuracy and speed. The image classification method based on convolutional neural network (CNN) breaks through the bottle neck of traditional image classification methods and becomes the mainstream algorithm of image classification at present, how to effectively use convolutional neural network to classify images has become a hot research topic in the field of computer vision at home and abroad. Convolutional neural network (CNN) has performed well in image classification and segmentation, target detection and other applications, and its powerful feature learning and feature expression capabilities are increasingly respected by researchers. However, CNN still has a few problems, such as incomplete feature extraction and overfitting of sample training. In view of these problems, after in-depth research on the application of convolutional neural network in image processing, this paper gives the mainstream structure model, advantages and disadvantages, time/space complexity, problems that may be encountered in the model training process and corresponding solutions used in image classification based on convolutional neural network. Through the overview of the research status of CNN model in image classification, it provides suggestions for the further development and research direction of CNN.
TL;DR: In this article , the sound absorption coefficient of anechoic coating in infinite water area with steel plate as backing is calculated based on transfer function method and finite element method, anAd the solution results are compared with the analytical result of uniform layered medium to verify the correctness of the solution method.
Abstract: Aiming at the sound absorption problem of anechoic coating in water seepage state, firstly, the sound absorption coefficient of anechoic coating in infinite water area with steel plate as backing is calculated based on transfer function method and finite element method, anAd the solution results are compared with the analytical result of uniform layered medium to verify the correctness of the solution method. Secondly, the calculation model of cavity containing anechoic coating with different seepage proportion is established to analyze the influence of water seepage on the sound absorption performance of anechoic coating. The calculation results show that within the calculated frequency band, water seepage proportion has different influence characteristics on different frequency bands of anechoic coating, and with the aggravation of water seepage, the peak point of sound absorption moves to medium and low frequency, and the singular value point of sound absorption coefficient moves to high frequency; and the singularity of the valley value of the sound absorption coefficient is mainly due to the change of the cavity resonance mode. The results of this paper can provide some reference for the acoustic performance evaluation of abnormal state of anechoic coating.
TL;DR: This paper studies and analyzes the educational informatization technology system from the concept, the defects, the development trend, the characteristics, and the direction and measures for improvement so that the educational information technology system can be continuously improved and developed.
Abstract: The popularization of Internet and new media technology has promoted the upgrading of educational software and hardware, and promoted the continuous improvement of educational technology. This paper studies and analyzes the educational informatization technology system from the concept of the educational informatization technology system, the defects of the educational informatization technology system, and the development trend of the educational informatization technology system, and summarizes the characteristics of the educational informatization technology system. The direction and measures for improvement are set out, so that the educational information technology system can be continuously improved and developed.
TL;DR: This paper mainly introduces the step-by-step evolution of the existing methods in artificially designed neural networks and introduces the model compression based on AutoML and the automatic animation design based on NAS.
Abstract: There are currently two main schools of deep learning. One is academic. They pursue stronger performance through powerful, complex models. The other is the engineering school. Their purpose is to efficiently deploy models to various hardware platforms. Complex models have better performance. However, it also brings unavoidable consumption. With the increasing depth of convolutional neural networks, lightweighting has become a key research direction. There are currently four main methods for designing lightweight networks. This article will first introduce CNN model compression and basic convolution operations.This paper also introduces the model compression based on AutoML and the automatic animation design based on NAS. Finally, according to the above three points, this paper introduces the application of the above methods in artificially designed neural networks.This paper mainly introduces the step-by-step evolution of the existing methods. This paper analyzes aspects of current neural network improvements and emerging problems. The significance of this paper is to summarize and deepen the solved problems and key problems in the lightweight process through past experience.
TL;DR: In this paper , the authors analyze the use of mixed reality in engineering and non-engineering domains, discussing its benefits and drawbacks, and propose a solution for disaster management and prevention by conducting simulated drills and optimizing escape routines.
Abstract: Mixed reality, or MR, is a technology that incorporates information from real scenes in a virtual environment, allowing the actual and virtual worlds to be linked to enhance the realism of the user experience. With the rapid development of the 5G network and communication technology, MR technology has been used on a larger scale in every industry in the future. This study analyzes its use in engineering and non-engineering domains, discussing its benefits and drawbacks. MR can be used for data sharing and efficient communication, assisting workers in understanding and guiding their operation, and facilitating project management. However, its disadvantages include unreal images, delayed tracking, restricted condition for the environment, unsatisfactory user experience, and high costs. In non-engineering fields, MR is mainly applied to simulation, real-time interaction and so on in the military, medical science and education fields. The application of MR technology in engineering fields is mainly about construction, disaster management, and prevention. It enhances the work efficiency for construction by allowing 3D visualization of concealed or complex structure, and timely annotation. It eliminates risks for disaster management and prevention by conducting simulated drills, and optimizing escape routines.
TL;DR: In this article , the authors provide an overview of recent advances in nanofluids in cooling as well as summarize the controversies of the existing applications, and they aim to provide a deeper understanding of the thermophysical properties and applications and to understand the limitations and potential for future improvements.
Abstract: Nanofluids have been continuously investigated as innovative fluids in the last decades. The unique thermophysical properties exhibited by nanofluids have led to a variety of applications in modern energy-scarce environments. The purpose of this paper is to provide an overview of recent advances in nanofluids in cooling as well as to summarize the controversies of the existing applications. The development of electronic devices has heightened the need for an effective cooling system. Nanofluids in solar collector applications have greatly improved the thermal efficiency and solar energy utilization compared to conventional fluids, which can greatly alleviate today's energy problems. The cost of nanofluids in commercial applications may be too high, and long-term stability cannot be guaranteed due to the impacts of the thermal efficiency of nanofluids. More innovative approaches are needed to improve the cost and stability of nanofluids to cater to the commercial market. These results aim to provide a deeper understanding of the thermophysical properties and applications of nanofluids and to understand the limitations and potential for future improvements.
TL;DR: In this paper , the authors focus on the third-generation semiconductor materials and further study the most mature and widely used SiC and GaN, and introduce the mainstream methods for the preparation of SiCs and GaNs.
Abstract: The application and development of semiconductor technology has a very important role in the development of the world's science and technology. The third-generation semiconductors are broadband semiconductors with high thermal conductivity, high breakdown field strength, high saturation electron drift rate and high bonding energy, which are incomparable to the previous two generations of semiconductors. In this paper, we focus on the third-generation semiconductor materials and further study the most mature and widely used SiC and GaN, and introduce the mainstream methods for the preparation of SiC and GaN. The paper also introduces the applications of these two materials in energy, communication, and consumer electronics, taking into account the current development of the industry. Finally, the paper also considers the problems and challenges that still need to be solved in the next stage of the industry's development.
TL;DR: In this paper , a single channel Knock transducer was used to measure engine vibration caused by combustion pressure forces and knocking tendency, and the results reveal that the engine events derived from vibration signals are closely connected to the premixing fuel ratio, as expected.
Abstract: The measurement of engine vibrations components is used to identify combustion phases in a single-cylinder PCCI diesel engine in this work. A single channel Knock transducer was used to measure engine vibration caused by combustion pressure forces and knocking tendency. The transducer is used to obtain the engine's frequency spectrum in the temporal domain. Categorization discrete wavelet analysis is used to isolate the observed vibration data. Spectral analysis and filtration of fragmented sections of the source signal are used in this approach. Fast Fourier transforms (FFT) and short-time Fourier transform (STFT) are used to investigating the discrete parts of the observed signals (STFT). In order to study engine events, time is given in milliseconds in the time-frequency domain. The engine knocking is determined from the observed signal using time-frequency analysis. The outcomes reveal that the engine events derived from vibration signals are closely connected to the premixing fuel ratio, as expected.
TL;DR: In this article, the authors introduce the origin and development of long-span steel structure system, and focus on the characteristics and composition of grid structure, reticulated shell structure, pipe truss structure, chord supported structure, and cable structure.
Abstract: . This paper introduces the origin and development of long-span steel structure system, focuses on the characteristics and composition of grid structure system, reticulated shell structure system, pipe truss structure system, chord supported structure system, and cable structure, and analyzes and studies the typical cases of five basic structure systems of long-span steel structure, such as three center round coal shed, Tianjin Binhai station, Shenyang Olympic Sports Center, etc. The purpose is to provide beginners with introductory knowledge and reference cases and to provide references for structural personnel to choose the appropriate structural system.
TL;DR: Based on the instability and failure of garbage dump in large landfill, this article introduced the stability of landfill from theoretical research, numerical analysis, model test and laboratory test, and summarized the main influencing factors.
Abstract: Based on the instability and failure of garbage dump in large landfill, this paper introduces the stability of landfill from theoretical research, numerical analysis, model test and laboratory test. On the basis of summarizing the previous work and combining the latest research results, the stability analysis of garbage dump is discussed, and the main influencing factors of garbage dump stability are summarized. The main factors are the leachate level, the engineering properties of garbage soil and the shear slip of liner system.
TL;DR: In this paper , the physical parameters and components of the primary gas produced by the combustion of four propellants at a given pressure and temperature, and compares and analyzes them according to the propellant selection requirements, choose the appropriate propellant for the ATR engine.
Abstract: The propellant of the Air Turbo Rocket (ATR) engine is burned in the gas generator to produce primary gas. This paper uses the established ATR engine working fluid calculation model to calculate the physical parameters and components of the primary gas produced by the combustion of four propellants at a given pressure and temperature, and compares and analyzes them according to the propellant selection requirements, Choose the appropriate propellant for the ATR engine.
TL;DR: Results show that young and energetic men, as well as people who regularly participate in contact sports, are high-risk groups for this injury, and the treatment plan should be tailored to the individual's needs.
Abstract: Acromioclavicular (AC) joint separation is a frequent shoulder injury with increasing office working hours and sports. This research examines the classification of grades, as well as the causes, diagnostic procedures, and therapies associated with each grade. Results show that young and energetic men, as well as people who regularly participate in contact sports, are high-risk groups for this injury. X-rays, bone scans, positive compression, and horizontal adduction tests are among the diagnostic and examination methods available. The six-degree classification system developed by Rockwood is the most widely used classification system for AC joint injury. A minor sprain of the AC ligament is a Type I injury. Type II injuries are characterized by a torn AC ligament and sprained CC ligaments, and they typically result in more pain and swelling than Type I injuries. Types III-VI are the most serious injuries, with a burst AC ligament, CC ligament, and joint capsule in every case. The location of the damage, as well as the treatment choices, differ by type. Non-surgical treatments are indicated for Types I-III injuries. Surgical procedures are advised for Types IV-VI injuries. It should be mentioned that the treatment plan should be tailored to the individual's needs, with the negative effects taken into account.
TL;DR: In this paper , the chemical composition content of cultural relics before weathering is analyzed and the classification of glass relics is obtained using a regression model, statistical analysis, and a grey correlation matrix.
Abstract: To study the composition and identification of glass relics, the identification model is established using a regression model, statistical analysis, and a grey correlation matrix. Firstly, the chemical composition content of cultural relics before weathering is analyzed. Secondly, the classification of glass relics is obtained. Finally, the differences in the chemical composition of glass products are analyzed. The results show that: (1) there are more correlations among the chemical components in high potassium glass, and the correlation between potassium oxide, magnesium oxide, alumina, iron oxide, and copper oxide is closed. (2) Potassium oxide, magnesium oxide, alumina, and iron oxide in lead barium glass are more closely related to calcium oxide.
TL;DR: In this article , a digital transformation plan for the traditional parking that has high demand for such spaces is presented, which covers three main areas that include the inefficiency of traditional garage module, research of usable technologies and how these applications can be used to achieve digital transformation.
Abstract: This paper seeks to create a digital transformation plan for the traditional parking that has high demand for such spaces. It covers three main areas that include the inefficiency of traditional garage module, research of usable technologies and how these applications can be used to achieve digital transformation. It is set against the backdrop of the fact that traditional parking lots have low efficiency, high labor costs and occupy more space. Therefore, the system of the harbor and warehouse that the report comes up with uses a digital assist system backed by the relevant technologies. The paper also appreciates the fact that multiple technologies can be used to construct and improve the parking system, including technologies for locating vehicles and directing them to the desired destinations. After exploring the implementation for digital guidance system, it provides the concept that can be applied to achieve digital transformation. It applies a navigation app that easily assists the drivers to know the available parking lots and park within them. In addition, the digital transformation can be used to build, monitor and help in the navigation of vehicles to the parking lot based on the idea that a robust guidance system can enhance the efficiency of these parking lots. Eventually, conclusions are demonstrated that the employment of big digital platforms is key in creating an efficient parking system for drivers and their vehicles.
TL;DR: In this article , the authors showed that Doxorubicin causes oxidative stress due to increasing amount of Reactive oxygen species (ROS), and it promotes production of inflammatory cytokines.
Abstract: While exhibiting great value in treating multiple cancers, the chemotherapy drug, Doxorubicin, also manifests many side effects that significantly affect the post-chemotherapy life of patients. In the cardiac system, Doxorubicin causes oxidative stress due to increasing amount of Reactive oxygen species (ROS), and it promotes production of inflammatory cytokines. Oxidative stress and inflammatory cytokines then activate p38 mitogen-activated protein kinase (p38 MAPK), which can stimulate cardiomyocyte apoptosis. In the nervous system, Doxorubicin activates both extracellular signal-regulated kinase (ERK) and p38 MAPK. p38 MAPK predominately determines the result, leading to an overall reduction in Long-term Potentiation (LTP), or an analogous process of Long-term Facilitation (LTF). Moreover, neuroinflammatory effect achieved through the p38 MAPK pathway contributes to memory deficits by killing neurons excessively. Various inhibitors of p38 MAPK have shown promising results in lessening the effects of p38 MAPK, indicating future possibilities of using those inhibitors to ensure a safer application of Doxorubicin, while preserving the pharmacological values and properties of Doxorubicin.