Numerical Analysis of Effect of Crack Location on the Crack Breathing Behavior

In this work, a three-dimensional finite element model was developed to investigate the crack breathing behavior at different crack locations considering the effect of unbalance force. A two-disk rotor with a crack is simulated using ABAQUS. The duration of each crack status (open, closed and partially open/closed) during a full shaft rotation was examined to analyse the crack breathing behavior. Unbalanced shaft crack breathing behavior was found to be different at different crack locations. The breathing behavior of crack along the shaft length is divided into different regions depending on the unbalance force and crack location. The simulated results in this work can be further utilised to obtain the time-varying stiffness matrix of the cracked shaft element under the influence of unbalance force

Design and analysis of three nonlinearly activated ZNN models for solving time-varying linear matrix inequalities in finite time

To obtain the superiority property of solving time-varying linear matrix inequalities (LMIs), three novel finite-time convergence zeroing neural network (FTCZNN) models are designed and analyzed in this paper. First, to make the Matlab toolbox calculation processing more conveniently, the matrix vectorization technique is used to transform matrix-valued FTCZNN models into vector-valued FTCZNN models. Then, considering the importance of nonlinear activation functions on the conventional zeroing neural network (ZNN), the sign-bi-power activation function (AF), the improved sign-bi-power AF and the tunable sign-bi-power AF are explored to establish the FTCZNN models. Theoretical analysis shows that the FTCZNN models not only can accelerate the convergence speed, but also can achieve finite-time convergence. Computer numerical results ulteriorly confirm the effectiveness and advantages of the FTCZNN models for finding the solution set of time-varying LMIs

SPHINX: The Joint Mixing of Weights, Tasks, and Visual Embeddings for Multi-modal Large Language Models

We present SPHINX, a versatile multi-modal large language model (MLLM) with a joint mixing of model weights, tuning tasks, and visual embeddings. First, for stronger vision-language alignment, we unfreeze the large language model (LLM) during pre-training, and introduce a weight mix strategy between LLMs trained by real-world and synthetic data. By directly integrating the weights from two domains, the mixed LLM can efficiently incorporate diverse semantics with favorable robustness. Then, to enable multi-purpose capabilities, we mix a variety of tasks for joint visual instruction tuning, and design task-specific instructions to avoid inter-task conflict. In addition to the basic visual question answering, we include more challenging tasks such as region-level understanding, caption grounding, document layout detection, and human pose estimation, contributing to mutual enhancement over different scenarios. Additionally, we propose to extract comprehensive visual embeddings from various network architectures, pre-training paradigms, and information granularity, providing language models with more robust image representations. Based on our proposed joint mixing, SPHINX exhibits superior multi-modal understanding capabilities on a wide range of applications. On top of this, we further propose an efficient strategy aiming to better capture fine-grained appearances of high-resolution images. With a mixing of different scales and high-resolution sub-images, SPHINX attains exceptional visual parsing and reasoning performance on existing evaluation benchmarks. We hope our work may cast a light on the exploration of joint mixing in future MLLM research. Code is released at https://github.com/Alpha-VLLM/LLaMA2-Accessory.Comment: Work in progress. Code and demos are released at https://github.com/Alpha-VLLM/LLaMA2-Accessor

Artificial intelligence : A powerful paradigm for scientific research

Y Artificial intelligence (AI) coupled with promising machine learning (ML) techniques well known from computer science is broadly affecting many aspects of various fields including science and technology, industry, and even our day-to-day life. The ML techniques have been developed to analyze high-throughput data with a view to obtaining useful insights, categorizing, predicting, and making evidence-based decisions in novel ways, which will promote the growth of novel applications and fuel the sustainable booming of AI. This paper undertakes a comprehensive survey on the development and application of AI in different aspects of fundamental sciences, including information science, mathematics, medical science, materials science, geoscience, life science, physics, and chemistry. The challenges that each discipline of science meets, and the potentials of AI techniques to handle these challenges, are discussed in detail. Moreover, we shed light on new research trends entailing the integration of AI into each scientific discipline. The aim of this paper is to provide a broad research guideline on fundamental sciences with potential infusion of AI, to help motivate researchers to deeply understand the state-of-the-art applications of AI-based fundamental sciences, and thereby to help promote the continuous development of these fundamental sciences.Peer reviewe

Prevalence and trend of hepatitis C virus infection among blood donors in Chinese mainland: a systematic review and meta-analysis

<p>Abstract</p> <p>Background</p> <p>Blood transfusion is one of the most common transmission pathways of hepatitis C virus (HCV). This paper aims to provide a comprehensive and reliable tabulation of available data on the epidemiological characteristics and risk factors for HCV infection among blood donors in Chinese mainland, so as to help make prevention strategies and guide further research.</p> <p>Methods</p> <p>A systematic review was constructed based on the computerized literature database. Infection rates and 95% confidence intervals (95% CI) were calculated using the approximate normal distribution model. Odds ratios and 95% CI were calculated by fixed or random effects models. Data manipulation and statistical analyses were performed using STATA 10.0 and ArcGIS 9.3 was used for map construction.</p> <p>Results</p> <p>Two hundred and sixty-five studies met our inclusion criteria. The pooled prevalence of HCV infection among blood donors in Chinese mainland was 8.68% (95% CI: 8.01%-9.39%), and the epidemic was severer in North and Central China, especially in Henan and Hebei. While a significant lower rate was found in Yunnan. Notably, before 1998 the pooled prevalence of HCV infection was 12.87% (95%CI: 11.25%-14.56%) among blood donors, but decreased to 1.71% (95%CI: 1.43%-1.99%) after 1998. No significant difference was found in HCV infection rates between male and female blood donors, or among different blood type donors. The prevalence of HCV infection was found to increase with age. During 1994-1995, the prevalence rate reached the highest with a percentage of 15.78% (95%CI: 12.21%-19.75%), and showed a decreasing trend in the following years. A significant difference was found among groups with different blood donation types, Plasma donors had a relatively higher prevalence than whole blood donors of HCV infection (33.95% <it>vs </it>7.9%).</p> <p>Conclusions</p> <p>The prevalence of HCV infection has rapidly decreased since 1998 and kept a low level in recent years, but some provinces showed relatively higher prevalence than the general population. It is urgent to make efficient measures to prevent HCV secondary transmission and control chronic progress, and the key to reduce the HCV incidence among blood donors is to encourage true voluntary blood donors, strictly implement blood donation law, and avoid cross-infection.</p

Fracture behaviour of rubber-modified epoxies and their carbon fibre-reinforced composites

A comprehensive experimental investigation of fracture toughness of rubbertoughened DGEBA epoxies and interlaminar fracture toughness of carbon fibre composite laminates was conducted

An experimental study of breathing mechanism for the transversely cracked shafts

Shaft fatigue crack is one of the most common defects in rotating equipment, due to its extensive operation with continuous heavy loads. Finding an efficient way to evaluate the true stiffness variation due to the crack rotation is the key step to develop both on-line and off-line crack diagnostic techniques. This study analyzed time-variant bending stiffness of elastic shafts with experimentally-induced fatigue, welding and wire cut transverse cracks. It was found that crack gap has a significant effect on the opening and closing behaviour of the transverse crack. As in the case of a cut crack, large crack gap could completely prevent the crack from closing during rotation. A fatigue crack without a clear gap shows a typical opening and closing behavior. Further, it remains fully closed within a small angular range and most of time it is partially closed. It was also observed that both switch and harmonic models cannot describe periodic stiffness variation well enough to represent the actual breathing function of the fatigue crack

Numerical and experimental studies on the\ud fracture behavior of rubber-toughened epoxy\ud in bulk specimen and laminated composites

To study the toughening mechanisms of liquid rubber (LR) and core-shell rubber (CSR) in\ud bulk epoxy and composite laminate, experimental and numerical investigations were\ud carried out on compact tension (CT) and double-cantilever-beam (DCB) specimens under\ud mode-I loading. The matrix materials were pure epoxy (DGEBA), 15% LR (CTBN) and 15%\ud CSR modified epoxies. Experimental results and numerical analyses showed that both\ud liquid rubber (LR) and core-shell rubber (CSR) could improve significantly the fracture\ud toughness of pure epoxy (DGEBA). However, the high toughness of these toughened\ud epoxies could not be completely transferred to the interlaminar fracture toughness of the\ud unidirectional carbon fibre reinforced laminate. The main toughening mechanism of CSR in\ud bulk epoxy was the extensive particle cavitation, which greatly released the crack-tip\ud triaxiality and promoted matrix shear plasticity. The poor toughness behavior of CSR in the\ud carbon fibre laminate was thought to be caused by the high constraint imposed by the stiff\ud fibre layers. No particle cavitation had been observed in LR modified epoxy and the main\ud toughening mechanism was merely the large plastic deformation near the crack-tip due to\ud the rubber domains in the matrix which results in a lower yield strength but a higher\ud elongation-to-break