Numerical study of vapor bubble effect on flow and heat transfer in microchannel

Flow boiling in a microchannel is characterized by nucleation and dynamic behavior of vapor bubbles in the channel. In the present study, the effect of vapor bubble on fluid flow and heat transfer in a microchannel is investigated via lattice Boltzmann (LB) modeling. With respect to boiling flow in a single microchannel, the bubble nucleation, growth, and departure are simulated by using an improved hybrid LB model. Relating bubble behavior with fluid flow and boiling heat transfer provides some insight into the relevant fundamental physics on flow boiling in the microchannel. It is found that the bubble growth before its departure from the wall induces an obvious resistance to the fluid flow. The processes of nucleation and motion of different bubbles interact, leading to an alternate, either enhanced or weakened, effect of bubble behavior on the flow boiling. (C) 2011 Elsevier Masson SAS. All rights reserved.</p

Improving effectiveness of online learning for higher education students during the COVID-19 pandemic

During the COVID-19 pandemic, online learning has become one of the important ways of higher education because it is not confined by time and place. How to ensure the effectiveness of online learning has become the focus of education research, and the role of the “online learning community” cannot be ignored. In the context of the Internet of Things (IoT), we try to build up a new online learning community model: (1) First, we introduce the Kolb learning style theory to identify different online learning styles; (2) Second, we use a clustering algorithm to identify the nature of different learning style groups; and (3) Third, we introduce the group dynamics theory to design the dimensions of the questionnaire and combine the Analytic Hierarchy Process (AHP) method to identify the key influencing factors of the online learning community. We take business administration majors and students in universities as an example. The results show that (1) as a machine learning method, the clustering algorithm method is superior to the random construction method in identifying different learning style groups, and (2) our method can well judge the importance of each factor based on hierarchical analysis and clarify the different roles of factors in the process of knowledge transfer. This study can provide a useful reference for the sustainable development of online learning in higher education

Constructing a Ternary FCSR with a Given Connection Integer

FCSRs have been proposed as an alternative to LFSRs for the design of stream ciphers. In 2009, a new ring representation of FCSRs was presented. This new representation preserves the statistical properties and circumvents the weaknesses of the Fibonacci and the Galois FCSRs. Moreover an extension of the ring FCSRs called ternary FCSRs has been proposed. They are suitable for hardware and software implementations of FCSRs. In this paper, we show a method of constructing a ternary FCSR with a given connection integer for hardware implementation. The construction is simple and convenient. And the ternary FCSRs we get are able to meet the hardware criteria

Impact of Cross-Axis Structural Dynamics on Validation of Linear Models for Space Launch System

A feasibility study was performed to examine the advisability of incorporating a set of Programmed Test Inputs (PTIs) during the Space Launch System (SLS) vehicle flight. The intent of these inputs is to provide validation to the preflight models for control system stability margins, aerodynamics, and structural dynamics. During October 2009, Ares I-X program was successful in carrying out a series of PTI maneuvers which provided a significant amount of valuable data for post-flight analysis. The resulting data comparisons showed excellent agreement with the preflight linear models across the frequency spectrum of interest. However unlike Ares I-X, the structural dynamics associated with the SLS boost phase configuration are far more complex and highly coupled in all three axes. This presents a challenge when implementing this similar system identification technique to SLS. Preliminary simulation results show noticeable mismatches between PTI validation and analytical linear models in the frequency range of the structural dynamics. An alternate approach was examined which demonstrates the potential for better overall characterization of the system frequency response as well as robustness of the control design

Physical cue influences children’s empathy for pain: The role of attention allocation

Empathy for pain is evolutionally important and context-dependent. The current study explored the effect of physical cue on 4- to 5-year-old children’s empathy for pain with two experiments. Experiment 1 investigated the effect of valid and invalid physical cue as compared to baseline (without cue) in pain evaluation task (evaluating the pain intensity of a facial expression, N = 28). Experiment 2 employed eye-tracking to investigate the attentional process in valid and baseline conditions (evaluating the pain intensity of a body image with an apparently injured arm or leg, N = 65). We found the evaluation of pain intensity was the highest in the valid condition, and higher in baseline condition than invalid. As for eye-tracking results, children fixated more quickly, had more fixations and longer total fixation duration in valid-cue condition. Of attention allocation, compared with baseline condition, children fixated on arm/leg more quickly, more frequently and for longer time in valid condition. Additionally, eye-tracking results were significantly related to their evaluation of pain intensity

Gut-immunity-joint axis: a new therapeutic target for gouty arthritis

Gouty arthritis (GA) is an inflammatory disease characterized by pain. The primary goal of current treatment strategies during GA flares remains the reduction of inflammation and pain. Research suggests that the gut microbiota and microbial metabolites contribute to the modulation of the inflammatory mechanism associated with GA, particularly through their effect on macrophage polarization. The increasing understanding of the gut-joint axis emphasizes the importance of this interaction. The primary objective of this review is to summarize existing research on the gut-immune-joint axis in GA, aiming to enhance understanding of the intricate processes and pathogenic pathways associated with pain and inflammation in GA, as documented in the published literature. The refined comprehension of the gut-joint axis may potentially contribute to the future development of analgesic drugs targeting gut microbes for GA

Can GPT models be Financial Analysts? An Evaluation of ChatGPT and GPT-4 on mock CFA Exams

Large Language Models (LLMs) have demonstrated remarkable performance on a wide range of Natural Language Processing (NLP) tasks, often matching or even beating state-of-the-art task-specific models. This study aims at assessing the financial reasoning capabilities of LLMs. We leverage mock exam questions of the Chartered Financial Analyst (CFA) Program to conduct a comprehensive evaluation of ChatGPT and GPT-4 in financial analysis, considering Zero-Shot (ZS), Chain-of-Thought (CoT), and Few-Shot (FS) scenarios. We present an in-depth analysis of the models' performance and limitations, and estimate whether they would have a chance at passing the CFA exams. Finally, we outline insights into potential strategies and improvements to enhance the applicability of LLMs in finance. In this perspective, we hope this work paves the way for future studies to continue enhancing LLMs for financial reasoning through rigorous evaluation

MicroRNA miR-326 regulates TH-17 differentiation and is associated with the pathogenesis of multiple sclerosis

MicroRNA miR-326 regulates TH-17 differentiation and is associated with the pathogenesis of multiple sclerosis Changsheng Du1,5, Chang Liu1,5, Jiuhong Kang1,2, Guixian Zhao3, Zhiqiang Ye4, Shichao Huang1, Zhenxin Li3, Zhiying Wu3 & Gang Pei1,2 Interleukin 17 (IL-17)-producing T helper cells (TH-17 cells) are increasingly recognized as key participants in various autoimmune diseases, including multiple sclerosis. Although sets of transcription factors and cytokines are known to regulate TH-17 differentiation, the role of noncoding RNA is poorly understood. Here we identify a TH-17 cell–associated microRNA, miR-326, whose expression was highly correlated with disease severity in patients with multiple sclerosis and mice with experimental autoimmune encephalomyelitis (EAE). In vivo silencing of miR-326 resulted in fewer TH-17 cells and mild EAE, and its overexpression led to more TH-17 cells and severe EAE. We also found that miR-326 promoted TH-17 differentiation by targeting Ets-1, a negative regulator of TH-17 differentiation. Our data show a critical role for microRNA in TH-17 differentiation and the pathogenesis of multiple sclerosis

DocLLM: A layout-aware generative language model for multimodal document understanding

Enterprise documents such as forms, invoices, receipts, reports, contracts, and other similar records, often carry rich semantics at the intersection of textual and spatial modalities. The visual cues offered by their complex layouts play a crucial role in comprehending these documents effectively. In this paper, we present DocLLM, a lightweight extension to traditional large language models (LLMs) for reasoning over visual documents, taking into account both textual semantics and spatial layout. Our model differs from existing multimodal LLMs by avoiding expensive image encoders and focuses exclusively on bounding box information to incorporate the spatial layout structure. Specifically, the cross-alignment between text and spatial modalities is captured by decomposing the attention mechanism in classical transformers to a set of disentangled matrices. Furthermore, we devise a pre-training objective that learns to infill text segments. This approach allows us to address irregular layouts and heterogeneous content frequently encountered in visual documents. The pre-trained model is fine-tuned using a large-scale instruction dataset, covering four core document intelligence tasks. We demonstrate that our solution outperforms SotA LLMs on 14 out of 16 datasets across all tasks, and generalizes well to 4 out of 5 previously unseen datasets.Comment: 16 pages, 4 figure

Toll-like receptor agonists Porphyromonas gingivalis LPS and CpG differentially regulate IL-10 competency and frequencies of mouse B10 cells

IL-10 expressing regulatory B cells (B10) play a key role in immune system balance by limiting excessive inflammatory responses. Effects of toll-like receptor signaling and co-stimulatory molecules on B10 activity during innate and adaptive immune responses are not fully understood. Objective This study is to determine the effects of P. gingivalis LPS and CpG on B10 cell expansion and IL-10 competency in vitro. Material and Methods Spleen B cells were isolated from C57BL/6J mice with or without formalin-fixed P. gingivalis immunization. B cells were cultured for 48 hours under the following conditions: CD40L, CD40L+LPS, CD40L+CpG, and CD40L+LPS+CpG in the presence or absence of fixed P. gingivalis. Percentages of CD1dhiCD5+ B cells were measured by flow cytometry. IL-10 mRNA expression and secreted IL-10 were measured by real-time quantitative PCR and by ELISA respectively. Results P. gingivalis LPS plus CD40L significantly increased CD1dhiCD5+ B cell percentages and secreted IL-10 levels in both immunized and non-immunized mice B cells in the presence or absence of P. gingivalis, compared with control group. Secreted IL-10 levels were significantly increased in CD40L+LPS treated group compared with CD40L treatment group in the absence of P. gingivalis. CpG plus CD40L significantly decreased CD1dhiCD5+ B cell percentages, but greatly elevated secreted IL-10 levels in immunized and non-immunized mice B cells in the absence of P. gingivalis, compared with CD40L treatment group. Conclusions P. gingivalis LPS and CpG differentially enhance IL-10 secretion and expansion of mouse B10 cells during innate and adaptive immune responses