Stock Valuation- Incorporating New Measures into the Traditional Methods

This study investigate the specific factors which impact on corporate stock performance which is measured by stock return in the US companies from 2009 to 2012, aims to examine the relationship between firms` environmental performance and stock performance and discuss the way to incorporate environmental performance into stock valuation process. The results report the dividend yield and overall green score have negative impact on stock performance, and return on invested capital, environmental impact score, the green policies score and the reputation have positive impact on stock performance in the model of this study, and the P/E ratio, return on equity and cash flow/sales ratio have no relationship with stock performance. The result implies that environmental performance do impact on stock performance which is in line with the expectation. Finally this paper provide a analysis about how the environmental affect the stock performance which include short-term and long-term period and discuss the way to take corporate environmental performance into account while valuing a stock, provide a more comprehensive and reliable way for stock valuation process

Stock Valuation- Incorporating New Measures into the Traditional Methods

This study investigate the specific factors which impact on corporate stock performance which is measured by stock return in the US companies from 2009 to 2012, aims to examine the relationship between firms` environmental performance and stock performance and discuss the way to incorporate environmental performance into stock valuation process. The results report the dividend yield and overall green score have negative impact on stock performance, and return on invested capital, environmental impact score, the green policies score and the reputation have positive impact on stock performance in the model of this study, and the P/E ratio, return on equity and cash flow/sales ratio have no relationship with stock performance. The result implies that environmental performance do impact on stock performance which is in line with the expectation. Finally this paper provide a analysis about how the environmental affect the stock performance which include short-term and long-term period and discuss the way to take corporate environmental performance into account while valuing a stock, provide a more comprehensive and reliable way for stock valuation process

The thermal and electrical properties of the promising semiconductor MXene Hf2CO2

In this work, we investigate the thermal and electrical properties of oxygen-functionalized M2CO2 (M = Ti, Zr, Hf) MXenes using first-principles calculations. Hf2CO2 is found to exhibit a thermal conductivity better than MoS2 and phosphorene. The room temperature thermal conductivity along the armchair direction is determined to be 86.25-131.2 Wm-1K-1 with a flake length of 5-100 um, and the corresponding value in the zigzag direction is approximately 42% of that in the armchair direction. Other important thermal properties of M2CO2 are also considered, including their specific heat and thermal expansion coefficients. The theoretical room temperature thermal expansion coefficient of Hf2CO2 is 6.094x10-6 K-1, which is lower than that of most metals. Moreover, Hf2CO2 is determined to be a semiconductor with a band gap of 1.657 eV and to have high and anisotropic carrier mobility. At room temperature, the Hf2CO2 hole mobility in the armchair direction (in the zigzag direction) is determined to be as high as 13.5x103 cm2V-1s-1 (17.6x103 cm2V-1s-1), which is comparable to that of phosphorene. Broader utilization of Hf2CO2 as a material for nanoelectronics is likely because of its moderate band gap, satisfactory thermal conductivity, low thermal expansion coefficient, and excellent carrier mobility. The corresponding thermal and electrical properties of Ti2CO2 and Zr2CO2 are also provided here for comparison. Notably, Ti2CO2 presents relatively low thermal conductivity and much higher carrier mobility than Hf2CO2, which is an indication that Ti2CO2 may be used as an efficient thermoelectric material.Comment: 26 pages, 5 figures, 2 table

Distributed AC Optimal Power Flow for Generic Integrated Transmission-Distribution Systems

Coordination of transmission and distribution power systems is increasingly critical in the context of the ongoing energy transition. However, traditional centralized energy management faces challenges related to privacy and/or sovereignty concerns, leading to growing research interests in distributed approaches. Nevertheless, solving distributed AC optimal power flow (OPF) problems encounters difficulties due to their nonlinearity and nonconvexity, making it challenging for state-of-the-art distributed approaches. To solve this issue, the present paper focuses on investigating the distributed AC OPF problem of generic integrated transmission-distribution (ITD) systems, considering complex grid topology, by employing a new variant of the Augmented Lagrangian based Alternating Direction Inexact Newton method (ALADIN). In contrast to the standard ALADIN, we introduce a second-order correction into ALADIN to enhance its numerical robustness and properly convexify distribution subproblems within the ALADIN framework for computing efficiency. Moreover, a rigorous proof shows that the locally quadratic convergence rate can be preserved for solving the resulting distributed nonconvex problems. Extensive numerical simulations with varying problem sizes and grid topologies demonstrate the effectiveness of the proposed algorithm, outperforming state-of-the-art approaches in terms of numerical robustness, convergence speed, and scalability

Biomedical Entity Recognition by Detection and Matching

Biomedical named entity recognition (BNER) serves as the foundation for numerous biomedical text mining tasks. Unlike general NER, BNER require a comprehensive grasp of the domain, and incorporating external knowledge beyond training data poses a significant challenge. In this study, we propose a novel BNER framework called DMNER. By leveraging existing entity representation models SAPBERT, we tackle BNER as a two-step process: entity boundary detection and biomedical entity matching. DMNER exhibits applicability across multiple NER scenarios: 1) In supervised NER, we observe that DMNER effectively rectifies the output of baseline NER models, thereby further enhancing performance. 2) In distantly supervised NER, combining MRC and AutoNER as span boundary detectors enables DMNER to achieve satisfactory results. 3) For training NER by merging multiple datasets, we adopt a framework similar to DS-NER but additionally leverage ChatGPT to obtain high-quality phrases in the training. Through extensive experiments conducted on 10 benchmark datasets, we demonstrate the versatility and effectiveness of DMNER.Comment: 9 pages content, 2 pages appendi

Magnetostrictive and magnetoelectric behavior of Fe–20 at. % Ga/Pb(Zr,Ti)O3 laminates

The magnetostrictive and magnetoelectric (ME) properties of laminate composites of Fe–20 at. % Ga and Pb(Zr,Ti)O3 (PZT) have been studied for laminates of different geometries. The results show that (i) a long-type magnetostrictive Fe–20 at. % Ga crystal plate oriented along 〈001〉c and magnetized in its longitudinal (or length) direction has higher magnetostriction than a disk-type one; and consequently (ii) a long-type Fe–20 at. % Ga/PZT laminate has a giant ME effect, and is sensitive to low-level magnetic fields

“What should be computed” for supporting post-pandemic recovery policymaking?:A life-oriented perspective

The COVID-19 pandemic has caused various impacts on people’s lives, while changes in people’s lives have shown mixed effects on mitigating the spread of the SARS-CoV-2 virus. Understanding how to capture such two-way interactions is crucial, not only to control the pandemic but also to support post-pandemic urban recovery policies. As suggested by the life-oriented approach, the above interactions exist with respect to a variety of life domains, which form a complex behavior system. Through a review of the literature, this paper first points out inconsistent evidence about behavioral factors affecting the spread of COVID-19, and then argues that existing studies on the impacts of COVID-19 on people’s lives have ignored behavioral co-changes in multiple life domains. Furthermore, selected uncertain trends of people’s lives for the post-pandemic recovery are described. Finally, this paper concludes with a summary about “what should be computed?” in Computational Urban Science with respect to how to catch up with delays in the SDGs caused by the COVID-19 pandemic, how to address digital divides and dilemmas of e-society, how to capture behavioral co-changes during the post-pandemic recovery process, and how to better manage post-pandemic recovery policymaking processes.</p

Fe–Ga/Pb(Mg1/3Nb2/3)O3–PbTiO3 magnetoelectric laminate composites

We have found large magnetoelectric (ME) effects in long-type laminate composites of Fe–20%Ga magnetostrictive alloys and piezoelectric Pb(Mg1/3Nb2/3)O3–PbTiO3 single crystals. At lower frequencies, the ME voltage coefficient of a laminate with longitudinally magnetized and longitudinally polarized (i.e., L-L mode) layers was 1.41 V/Oe (or1.01 V/cm Oe). Near the natural resonant frequency ( ∼ 91 kHz) of the laminate, the ME voltage coefficients were found to be dramatically increased to 50.7 V/Oe (36.2 V/cm Oe)for the L-L mode. In addition, the laminate can detect a minute magnetic field as low as ∼ 2×10−12 T at resonance frequency, and ∼ 1×10−10 T at lower frequencies