570 research outputs found
Emergence of ambient temperature ferroelectricity in meso-tetrakis(1- methylpyridinium-4-yl)porphyrin chloride thin films
Here, we demonstrate that the meso-tetrakis(1-methylpyridinium-4-yl) porphyrin chloride, [H2TMPyP]4+Cl4, with a face-to-face orientation directed along a single direction displays ferroelectric properties at room temperature. This is attributed to its spontaneous polarization, due to an extensive hydrogen-bonded network. From C-V measurements, a remnant polarization of approximately 0.5 μC cm-2 was estimated for pristine porphyrin film, which increases linearly up to about 1.7 μC cm-2 after applying 2 V at the top electrode and further to 9.6 μC cm-2 after 5 V positive poling. This large - for practical utilization - level of remnant polarization of [H2TMPyP] 4+Cl4 makes it promising for future applications.</p
Environmental ethics: values in and duties to the natural world (summarized with commentary by Panagiotis Perros)
Summarized with commentary in Greek by Panagiotis Perros.Environmental ethics stands on a frontier, as radically theoretical as it is applied. Alone, it asks whether there can be nonhuman objects of duty. Animals, plants, endangered species, ecosystems, and even Earth are progressively unfamiliar as objects of duty, and puzzles arise both for theory and practice. Answers to such questions are as urgent as any humans face, and intimately related to the four principal issues on the world agenda: peace, population, development, and environment
Nanoparticles-Based Flash-Like Nonvolatile Memories: Cluster Beam Synthesis of Metallic Nanoparticles and Challenges for the Overlying Control Oxide Layer
Nanoparticles (NPs) are of great scientific interest as they are effectively a bridge between bulk materials and atomic or molecular structures. In this work the focus is to present results concerning the use of NPs deposited using a novel room temperature cluster beam technique and show their applications in an emerging non-volatile memory (NVM) technology which represents an evolution of the standard floating gate NVM (which is the building block of the Flash architecture) and consists in the replacement of the floating gate with a NP layer. This work, except presenting new results, provides also a review and in depth insight into the main results obtained by the authors in the last decade
R-CAUSTIC: Rippling CAUSTICs underwater Image dataset
<p><strong>Description</strong></p><p>Rippling caustics seem to be the main factor degrading the underwater RGB image quality and affecting the image- based 3D reconstruction process in very shallow waters. These effects are adversely affecting image matching algorithms by throwing off most of them, leading to less accurate matches and causing issues in the Simultaneous Localization and Mapping (SLAM) based navigation of the Remotely Operated Vehicles (ROV) and Autonomous Underwater Vehicles (AUV) on shallow waters. Also, they are the main cause for dissimilarities in the generated textures and orthoimages. In order to fill the gap in the literature regading underwater rippling caustics imagery with real ground truth and reference images, the first real-world underwater caustics benchmark dataset which contains 1465 underwater images is presented. Together with the RGB imagery, the corresponding generated ground truth images are delivered for facilitating the training and testing of machine learning and deep learning methods for image classification. R-CAUSTIC dataset also provides the necessary data to evaluate, at least to some extent, the performance of 3D reconstruction approaches. Data were acquired using a GoPro Hero 4 Black action camera with image dimensions of 4000 x 3000 pixels, focal length of 2.77mm and pixel size of 1.55μm and a tripod. Action cameras are widely used for underwater image acquisition. The dataset was captured in near-shore underwater sites at depths varying from 0.5 to 2m. No artificial light sources were used. Due to the wind, the turbulent surface of the water created dynamic rippling caustics on the seabed. In total 1465 RGB images were collected, separated in 7 different datasets; five of them containing stereo images, one of them tri-stereo images and one consists of multi-stereo imagery acquired in 7 different camera poses.</p><p> </p><p><strong>Publication</strong></p><p>The paper is availbale in Open Access here: https://ieeexplore.ieee.org/document/10172291</p><p><strong>If you use this dataset please cite it as R-CAUSTIC</strong> [Reference].<br>[Reference]: <strong>P. Agrafiotis, K. Karantzalos and A. Georgopoulos, "Seafloor-Invariant Caustics Removal From Underwater Imagery," in </strong><i><strong>IEEE Journal of Oceanic Engineering</strong></i><strong>, vol. 48, no. 4, pp. 1300-1321, Oct. 2023, doi: 10.1109/JOE.2023.3277168.</strong></p><p>BibTeX:</p><p>@ARTICLE{10172291,
author={Agrafiotis, Panagiotis and Karantzalos, Konstantinos and Georgopoulos, Andreas},
journal={IEEE Journal of Oceanic Engineering},
title={Seafloor-Invariant Caustics Removal From Underwater Imagery},
year={2023},
volume={48},
number={4},
pages={1300-1321},
doi={10.1109/JOE.2023.3277168}}</p><p> </p>
R-CAUSTIC: Rippling CAUSTICs underwater Image dataset
<p> </p>
<h3><strong>Version 2 available! Please make sure to download the latest version of the dataset! <br></strong></h3>
<p> </p>
<p><strong>Description</strong></p>
<p>Rippling caustics seem to be the main factor degrading the underwater RGB image quality and affecting the image- based 3D reconstruction process in very shallow waters. These effects are adversely affecting image matching algorithms by throwing off most of them, leading to less accurate matches and causing issues in the Simultaneous Localization and Mapping (SLAM) based navigation of the Remotely Operated Vehicles (ROV) and Autonomous Underwater Vehicles (AUV) on shallow waters. Also, they are the main cause for dissimilarities in the generated textures and orthoimages. In order to fill the gap in the literature regading underwater rippling caustics imagery with real ground truth and reference images, the first real-world underwater caustics benchmark dataset which contains 1465 underwater images is presented. Together with the RGB imagery, the corresponding generated ground truth images are delivered for facilitating the training and testing of machine learning and deep learning methods for image classification. R-CAUSTIC dataset also provides the necessary data to evaluate, at least to some extent, the performance of 3D reconstruction approaches. Data were acquired using a GoPro Hero 4 Black action camera with image dimensions of 4000 x 3000 pixels, focal length of 2.77mm and pixel size of 1.55μm and a tripod. Action cameras are widely used for underwater image acquisition. The dataset was captured in near-shore underwater sites at depths varying from 0.5 to 2m. No artificial light sources were used. Due to the wind, the turbulent surface of the water created dynamic rippling caustics on the seabed. In total 1465 RGB images were collected, separated in 7 different datasets; five of them containing stereo images, one of them tri-stereo images and one consists of multi-stereo imagery acquired in 7 different camera poses.</p>
<p> </p>
<p><strong>Publication</strong></p>
<p>The paper is availbale in Open Access here: https://ieeexplore.ieee.org/document/10172291</p>
<p><strong>If you use this dataset please cite it as R-CAUSTIC</strong> [Reference].<br>[Reference]: <strong>P. Agrafiotis, K. Karantzalos and A. Georgopoulos, "Seafloor-Invariant Caustics Removal From Underwater Imagery," in </strong><em><strong>IEEE Journal of Oceanic Engineering</strong></em><strong>, vol. 48, no. 4, pp. 1300-1321, Oct. 2023, doi: 10.1109/JOE.2023.3277168.</strong></p>
<p>BibTeX:</p>
<p>@ARTICLE{10172291, author={Agrafiotis, Panagiotis and Karantzalos, Konstantinos and Georgopoulos, Andreas}, journal={IEEE Journal of Oceanic Engineering}, title={Seafloor-Invariant Caustics Removal From Underwater Imagery}, year={2023}, volume={48}, number={4}, pages={1300-1321}, doi={10.1109/JOE.2023.3277168}}</p>
<p> </p>
Does genetic diversity on corporate boards lead to improved environmental performance?
Elsevier
Journal of International Financial Markets, Institutions and Money
Volume 84, April 2023, 101756
Journal of International Financial Markets, Institutions and Money
Does genetic diversity on corporate boards lead to improved environmental performance?
Author links open overlay panelRenatas Kizys a, Emmanuel C. Mamatzakis b, Panagiotis Tzouvanas c
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https://doi.org/10.1016/j.intfin.2023.101756
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Highlights
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We examine the effect of boards’ genetic diversity (GENETICD) on corporate ESG performance.
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ESG performance and disclosures are higher in more genetically diverse firms.
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The positive GENETICD effect on ESG performance is driven by the environmental pillar.
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Corporate carbon performance significantly improves with increases in GENETICD.
We study the effects of boards’ genetic diversity on corporate environmental performance. Using a multidimensional information set for 3690 US firms during the period from 2005 to 2019, and three different measures of genetic diversity, we find that, pursuant to the diversity theory, which posits that diversity improves the quality of management decisions and business ethics, genetic diversity leads to improved environmental performance. We also find that genetic diversity improves carbon and governance performance, and ESG disclosure. Particularly, a one percentage point increase in boards’ genetic diversity will increase the carbon performance, measured by the inverse of the carbon emissions to total assets ratio, and environmental performance by 3.54% and 5.57%, respectively. Our results remain robust to different model specifications, while also controlling for endogeneity. In terms of policy implications, results suggest that the key to tackling climate challenges is to promote boards’ genetic diversity
Dataset in support of the Southampton doctoral thesis 'The boatbuilding tradition of the Aegean during the Late Neolithic – Early Bronze Age periods. Typological classification, digital reconstruction and seakeeping assessment'
Dataset in support of the Southampton doctoral thesis 'The boatbuilding tradition of the Aegean during the Late Neolithic – Early Bronze Age periods. Typological classification, digital reconstruction and seakeeping assessment' Appendix D - Resistance data and Appendix C - Stability data.
This dataset is focused on two appendices:
Appendix D - Resistance data. D.1 Resistance data produced by the author via MAXSURF Resistance for this thesis.
Appendix C - Stability data
C1. Stability data – STIX and ISO criteria, produced by the author via MAXSURF Stability software for his thesis
This research was funded by Southampton Marine and Maritime Institute (SMMI), Vice-Chancellor's Scholarship, Greek Archaeological Committee UK (GACUK)
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The effect of external stimuli on the performance of memristive oxides
This book chapter provides a comprehensive overview of the interrelationship between memristors properties and their responses to external stimuli such as electrical field, magnetic field, temperature, strain, and radiation. The ability of a material to change properties in response to external stimuli is an attractive feature that is gaining attention across many different fields. This feature is especially desirable for metal oxides already in use in applications such as light-emitting diodes and photodetectors, chemical sensors, transistors, and nonvolatile memories. This book chapter introduces the concepts of stimuli-responsiveness for metal oxide-based memristors, including the fundamental materials properties required for designing and understanding the new generation of memristors under external stimuli. It provides the readers with a comprehensive scientific literature review on the principles and the developments of the stimuli-responsive memristor. It presents several concrete examples showing the effect of external stimuli on the materials’ properties
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