Atomic decoration for improving the efficiency of field electron emission of carbon nanotubes

The field electron emission from the single-walled carbon nanotubes with their open ends terminated by -BH, -NH, and -O has been simulated. The apex-vacuum barrier and the emission current have been calculated. It has been found that -BH and -NH suppress the apex-vacuum barrier significantly and lead to higher emission current in contrast to the -O terminated structure in the same applied field. The calculated binding energy implies that the carbon nanotubes terminated with -BH and -NH are more stable than those saturated by oxygen atoms or by hydrogen atoms.Comment: 8 pages, 9 figures, LaTeX; content changed, typos corrected, references adde

Measuring Firm Size in Empirical Corporate Finance

In empirical corporate finance, firm size is commonly used as an important, fundamental firm characteristic. However, no research comprehensively assesses the sensitivity of empirical results in corporate finance to different measures of firm size. This paper fills this hole by providing empirical evidence for a “measurement effect” in the “size effect”. In particular, we examine the influences of employing different proxies (total assets, total sales, and market capitalization) of firm size in 20 prominent areas in empirical corporate finance research. We highlight several empirical implications. First, in most areas of corporate finance the coefficients of firm size measures are robust in sign and statistical significance. Second, the coefficients on regressors other than firm size often change sign and significance when different size measures are used. Unfortunately, this suggests that some previous studies are not robust to different firm size proxies. Third, the goodness of fit measured by R-squared also varies with different size measures, suggesting that some measures are more relevant than others in different situations. Fourth, different proxies capture different aspects of “firm size”, and thus have different implications in corporate finance. Therefore, the choice of size measures needs both theoretical and empirical justification. Finally, our empirical assessment provides guidance to empirical corporate finance researchers who must use firm size measures in their work

A Method for Assessing the Efficiency in Two-Stage Production Systems in the Presence of Dual-Role Factors

Due to the existence of dual-role factors, it is difficult to evaluate the production efficiency of two-stage systems. Unlike single-stage systems, two-stage systems involve intermediate products that serve as both inputs and outputs. Hence, to overcome existing obstacles, we propose a novel approach called the two-stage enhanced Russell model with dual-role factors (T-ERM-D) to assess the overall efficiency of two-stage production systems. Furthermore, divisional models are developed to evaluate the efficiency of each individual stage. The 0-1 programming is applied to deal with dual-role factors. To handle the non-linearity of these models, the Charnes-Cooper transformation is employed to convert them into linear ones. Using the proposed models, we evaluate efficiency scores of 10 supply chains involving suppliers and producers. By comparing the results obtained from new models with those obtained from models that do not consider dual-role factors, we validate the advantages of the proposed approach

Exploring OCR Capabilities of GPT-4V(ision) : A Quantitative and In-depth Evaluation

This paper presents a comprehensive evaluation of the Optical Character Recognition (OCR) capabilities of the recently released GPT-4V(ision), a Large Multimodal Model (LMM). We assess the model's performance across a range of OCR tasks, including scene text recognition, handwritten text recognition, handwritten mathematical expression recognition, table structure recognition, and information extraction from visually-rich document. The evaluation reveals that GPT-4V performs well in recognizing and understanding Latin contents, but struggles with multilingual scenarios and complex tasks. Specifically, it showed limitations when dealing with non-Latin languages and complex tasks such as handwriting mathematical expression recognition, table structure recognition, and end-to-end semantic entity recognition and pair extraction from document image. Based on these observations, we affirm the necessity and continued research value of specialized OCR models. In general, despite its versatility in handling diverse OCR tasks, GPT-4V does not outperform existing state-of-the-art OCR models. How to fully utilize pre-trained general-purpose LMMs such as GPT-4V for OCR downstream tasks remains an open problem. The study offers a critical reference for future research in OCR with LMMs. Evaluation pipeline and results are available at https://github.com/SCUT-DLVCLab/GPT-4V_OCR

A brief exploration of the physical properties of single living cells under dynamic loading conditions

Introduction:Single living cells exhibit both active biological functions and material-like mechanical behaviors. While extensive research has focused on static or quasi-static loading, the purely mechanical properties under high-rate impact remain underexplored. Investigating cell responses to dynamic loading can isolate rapid deformation characteristics, potentially clarifying how life activities modulate mechanical behavior.Methods:We developed a custom dynamic loading system to expose single adherent macrophage cells to transient compression–shear stresses in a controlled fluid environment. A Polymethyl Methacrylate chamber housed the cells, and impact pressures (156.48–3603.85 kPa) were measured in real time using a high-frequency sensor. High-speed imaging (up to 2×105 fps) captured cellular area changes, providing insight into global deformation. In total, 198 valid experiments were performed, and statistical tests confirmed that initial perimeter and area followed normal-like distributions suitable for theoretical analysis.Results:Cells demonstrated a two-stage expansion under shock loading. At lower pressures, cytoplasmic regions rapidly spread into the focal plane, producing significant increases in projected area. As pressure rose further, deformation rate decreased, reflecting the constraining influence of the nucleus. By analyzing the final-to-initial area ratios across various pressures and initial cell sizes, we derived an incomplete state equation akin to Tait-like or Birch–Murnaghan models, indicating an inflection point of maximum deformation rate.Discussion:These findings highlight that fast impact loading effectively minimizes confounding biological processes, revealing intrinsic mechanical responses. The proposed state equation captures cell behavior within milliseconds, offering a path to integrate dynamic results with slower, life-activity-driven adaptations, and laying groundwork for more comprehensive biomechanical models of living cells