When heterogeneous congestion control protocols that react to different pricing signals share the same network, the resulting equilibrium may no longer be interpreted as a solution to the standard ...utility maximization problem. We prove the existence of equilibrium in general multiprotocol networks under mild assumptions. For almost all networks, the equilibria are locally unique, finite, and odd in number. They cannot all be locally stable unless there is a globally unique equilibrium. Finally, we show that if the price mapping functions, which map link prices to effective prices observed by the sources, are sufficiently similar, then global uniqueness is guaranteed.
Current stomach disease detection and diagnosis is challenged by data complexity and high dimensionality and requires effective deep learning algorithms to improve diagnostic accuracy. To address ...this challenge, in this paper, an improved strategy based on the Adam algorithm is proposed, which aims to alleviate the influence of local optimal solutions, overfitting, and slow convergence rates by controlling the restart strategy and the gradient norm joint clipping technique. This improved algorithm is abbreviated as the CG-Adam algorithm. The control restart strategy performs a restart operation by periodically checking the number of steps and once the number of steps reaches a preset restart period. After the restart is completed, the algorithm will restart the optimization process. It helps the algorithm avoid falling into the local optimum and maintain convergence stability. Meanwhile, gradient norm joint clipping combines both gradient clipping and norm clipping techniques, which can avoid gradient explosion and gradient vanishing problems and help accelerate the convergence of the optimization process by restricting the gradient and norm to a suitable range. In order to verify the effectiveness of the CG-Adam algorithm, experimental validation is carried out on the MNIST, CIFAR10, and Stomach datasets and compared with the Adam algorithm as well as the current popular optimization algorithms. The experimental results demonstrate that the improved algorithm proposed in this paper achieves an accuracy of 98.59%, 70.7%, and 73.2% on the MNIST, CIFAR10, and Stomach datasets, respectively, surpassing the Adam algorithm. The experimental results not only prove the significant effect of the CG-Adam algorithm in accelerating the model convergence and improving generalization performance but also demonstrate its wide potential and practical application value in the field of medical image recognition.
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Marfan syndrome, an autosomal dominant disorder of connective tissue, is primarily caused by mutations in the fibrillin-1 (FBN1) gene, which encodes the protein fibrillin-1. The protein is composed ...of epidermal growth factor-like (EGF-like) domains, transforming growth factor beta-binding protein-like (TB) domains, and hybrid (Hyb) domains and is an important component of elastin-related microfibrils in elastic fiber tissue. In this study, we report a cysteine to tyrosine substitution in two different domains of fibrillin-1, both of which cause Marfan syndrome with ocular abnormalities, in two families. Using protease degradation and liquid chromatography-tandem mass spectrometry analyses, we explored the different effects of substitution of cysteine by tyrosine in an EGF-like and a calcium-binding (cb) EGF-like domain on protein stability. The results showed that cysteine mutations in the EGF domain are more likely to result in altered proteolytic sensitivity and thermostability than those in the cbEGF domain. Furthermore, cysteine mutations can lead to new enzymatic sites exposure or hidden canonical cleavage sites. These results indicate the differential clinical phenotypes and molecular pathogenesis of Marfan syndrome caused by cysteine mutations in different fibrillin-1 domains. These results strongly suggest that failure to form disulfide bonds and abnormal proteolysis of fibrillin-1 caused by cysteine mutations may be an important factor underlying the pathogenesis of diseases caused by fibrillin-1 mutations, such as Marfan syndrome.
Top coal caving is an important way of thick coal seam mining. The current coal gangue identification technology is not mature, resulting in a low degree of automation of coal caving. The current ...numerical simulation pays little attention to the real shape of rocks. This paper aims to reveal the vibration response of the tail beam under the action of real shape coal gangue particles. First, the real shape rock and hydraulic support model are established, and the relationship between the Rock Mixed Ratio (RMR) and the vibration signal characteristics during the impact process are studied. The influence of falling velocity and coal strength on this relationship are analyzed. Finally, the influence of motion mode on this relationship is analyzed and discussed. The numerical results show that the increase of the RMR can significantly enhance the velocity and acceleration signals of the tail beam, and the signals caused by different RMR are still different under different velocities and strengths. The best recognition effect can be obtained when the coal gangue particles slip on the hydraulic support, and the effect is the the worst when the coal gangue particles impact upon and roll on the hydraulic support. The conclusion provides directions for further study of coal gangue identification based on vibration.
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The use of computer vision to estimate the Body Condition Score for cow has demonstrated to be feasible. However, most research has been limited to fixed camera positions, which restricts the ...technique's usefulness. This research acquired cow data at various distances and angles to investigate the impact of distance and different depth images restoration method on scoring accuracy. A U-Net neural network-based model was employed for background segmentation. The model proposed in this study performs best among SegNet, UNet, UNet++ and DeeplabV3, with significant performance improvement and superior overall segmentation accuracy, and has stronger foreground object identification capability. Additionally, we utilize the concept of human feature point localization to pinpoint the positions of cow feature points. The results show that compared to Hourglass, CPN, and Hrnet, the model in this study has significant advantages in three core indicators: accuracy, recall, and mAP. Moreover, we presented an unsupervised depth image reconstruction model based on the Denoising Diffusion Probabilistic Model and Unet++ Mode, facilitating the measurement and scoring of cow characteristics. Finally, the measurement results of cow body size using the Lerp model, autoregressive model, GAN model, and the depth image completion model proposed in this study were compared. The method proposed in this study was found to be effective and feasible for meeting actual production requirements at a camera distance of 1-2 m from the cow, achieving high accuracy with a coefficient of determination above 0.9. Additionally, the three models used were effective in handling small-scale depth deficits, with a high degree of agreement between machine and manual measurements. The DDPM-based depth image reconstruction model was found to produce the most accurate results when the camera distance from the cow was between 1-3m. Therefore, this research makes it possible to make flexible measurements in the near range using existing methods. Accurate measurements at longer ranges are influenced by depth image quality and feature point localization accuracy, which require more advanced techniques for further investigation.
This paper introduces an enhanced variant of the Adam optimizer—the BGE-Adam optimization algorithm—that integrates three innovative technologies to augment the adaptability, convergence, and ...robustness of the original algorithm under various training conditions. Firstly, the BGE-Adam algorithm incorporates a dynamic β parameter adjustment mechanism that utilizes the rate of gradient variations to dynamically adjust the exponential decay rates of the first and second moment estimates (β1 and β2), the adjustment of β1 and β2 is symmetrical, which means that the rules that the algorithm considers when adjusting β1 and β2 are the same. This design helps to maintain the consistency and balance of the algorithm, allowing the optimization algorithm to adaptively capture the trending movements of gradients. Secondly, it estimates the direction of future gradients by a simple gradient prediction model, combining historic gradient information with the current gradient. Lastly, entropy weighting is integrated into the gradient update step. This strategy enhances the model’s exploratory nature by introducing a certain amount of noise, thereby improving its adaptability to complex loss surfaces. Experimental results on classical datasets, MNIST and CIFAR10, and gastrointestinal disease medical datasets demonstrate that the BGE-Adam algorithm has improved convergence and generalization capabilities. In particular, on the specific medical image gastrointestinal disease test dataset, the BGE-Adam optimization algorithm achieved an accuracy of 69.36%, a significant improvement over the 67.66% accuracy attained using the standard Adam algorithm; on the CIFAR10 test dataset, the accuracy of the BGE-Adam algorithm reached 71.4%, which is higher than the 70.65% accuracy of the Adam optimization algorithm; and on the MNIST dataset, the BGE-Adam algorithm’s accuracy was 99.34%, surpassing the Adam optimization algorithm’s accuracy of 99.23%. The BGE-Adam optimization algorithm exhibits better convergence and robustness. This research not only demonstrates the effectiveness of the combination of these three technologies but also provides new perspectives for the future development of deep learning optimization algorithms.
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Perovskite solar cells (PSCs) via two‐step sequential method have received great attention in recent years due to their high reproducibility and low processing costs. However, the relatively high ...trap‐state density and poor charge carrier extraction efficiency pose challenges. Herein, highly efficient and stable PSCs via a two‐step sequential method are fabricated using organic—inorganic (OI) complexes as multifunctional interlayers. In addition to reduce the under‐coordinated Pb2+ ions related trap states by forming interactions with the functional groups, the complexes interlayer tends to form dipole moment which can enhance the built‐in electric field, thus facilitating charge carrier extraction. Consequently, with rational molecular design, the resulting devices with a vertical dipole moment that parallels with the built‐in electric field yield a champion efficiency of 23.55% with negligible hysteresis. More importantly, the hydrophobicity of the (OI) complexes contributes to an excellent ambient stability of the resulting device with 91% of initial efficiency maintained after 3000 h storage.
Highly efficient and stable perovskite solar cells (PSCs) via the two‐step sequential method are fabricated using organic–inorganic (OI) complexes as multifunctional interlayers. OIcomplexes not only passivate the metal ions related trap states but also introduce dipole moment which can enhance the built‐in electric field, thus facilitating charge carrier extraction. The resulting devices perform a champion efficiency of 23.55% with excellent long‐term air stability.
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Recently, sulfide-based solid-state electrolytes (SSEs) have attracted much attention owing to their high ionic conductivity and feasible mechanical features. The environmental stability of ...sulfide-based SSEs is one of the critical aspects due to the possible decomposition, and ionic conductivity change will affect the fabrication and electrochemical performance of the batteries. Thus, important efforts have been made to reveal and improve their environmental stability, and a timely summary of the progress is urgently needed. In this review, we first clarify the definition of environmental stability and its significance in the context of practical use. After indicating the degradation mechanisms of sulfide-based SSEs, we summarize several effective strategies to improve their stability and also highlight the related theoretical studies. The stability of organic solvents of sulfide SSEs is also summarized and discussed, which may help reliable sulfide SSEs in the battery system. The main target of this review is to gain insights and provide useful guidance to further improve the environmental stability of sulfide SSEs, which will finally promote the commercialization of sulfide-based all-solid-state batteries.
With the widespread application of Implantable Collamer Lens (ICL) implantation surgery in the field of myopia correction, a comprehensive understanding of its potential complications, especially ...those related to intraocular pressure (IOP), becomes crucial. This article systematically reviews various complications that may lead to IOP elevation after ICL surgery. Firstly, common complications after ICL surgery, including residual viscoelastic, steroid response, and excessive vault of the ICL, are detailed, emphasizing their potential impact on intraocular pressure. Regarding residual viscoelastic, we delve into its direct relationship with postoperative elevated IOP and possible preventive measures. For steroid response, we stress the importance of timely adjustment of steroid therapy and monitoring intraocular pressure. Additionally, excessive vault of the ICL is considered a significant potential issue, and we elaborate on its mechanism and possible management methods. In further discussion, we focus on relatively rare complications such as Toxic Anterior Segment Syndrome (TASS), Urrets-Zavalia Syndrome (UZS), Pigment Dispersion Syndrome (PDS), and malignant glaucoma. For these relatively rare complications, this review thoroughly explores their potential mechanisms, emphasizes the importance of prevention, and provides guidance for early diagnosis and treatment. This is a comprehensible review that aims to offer eye care professionals a comprehensive understanding and effective management guidance for complications of elevated IOP after ICL surgery, ultimately providing optimal care for patients' visual health.
Pre-charge as a key step in the battery manufacture processes, which has a great impact on the film-forming properties and electrochemical performances, especially the Li-rich system batteries. As a ...key influence factor, it is necessary to clarify the effect of pre-charge temperature on battery performance. In this paper, we mainly studied the influence of different pre-charge temperatures (25°C, 40°C, 60°C) on the gas production and electrochemical performance of the batteries. The results show that the increase of the pre-charge temperature will result in the increase of gas production, and the gas components are mainly CO
2
, H
2
. After the long-term cycle, the sample under 40°C maintains the highest capacity retention rate, and as the pre-charge temperature increases, the median voltage of the battery can be effectively increased. In addition, compared with room temperature pre-charge, high pre-charge temperature samples have more excellent rate performance.
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