Global standards of Constitutional law : epistemology and methodology

Just as it led the philosophy of science to gravitate around scientific practice, the abandonment of all foundationalist aspirations has already begun making political philosophy into an attentive observer of the new ways in which constitutional law is practiced. Yet paradoxically, lawyers and legal scholars are not those who understand this the most clearly. Beyond analyzing the jurisprudence that has emerged from the expansion of constitutional justice, and taking into account the development of international and regional law, the ongoing globalization of constitutional law requires comparing the constitutional laws of individual nations. Following Waldron, the product of this new legal science can be considered as ius gentium. This legal science is not as well established as one might like to think. But it can be developed on the grounds of the practice that consists in ascertaining standards. As abstract types of best “practices” (and especially norms) of constitutional law from around the world, these are only a source of law in a substantive, not a formal, sense. They thus belong to what I should like to call a “second order legal positivity.” In this article I will undertake, both at a methodological and an epistemological level, the development of a model for ascertaining global standards of constitutional law

In-Silico Hyperthermia Performance of a Near-Field Patch Antenna at Various Positions on a Human Body Model

A compact patch applicator designed to enhance targeted energy coupling at 434 MHz is a key enabler for sensitizing temperature increments in body regions containing superficial tumours. A detailed FDTD body model is used to explore simulated RF coupling and temperature increments for typical clinical conditions. The antenna impedance matching, specific absorption rate and thermal distribution parameters are evaluated to identify applied performance outcomes. The analysis reveals physiological-RF coupling patterns for an optimised closely-coupled single element applicator

Interaction of RF-hyperthermia Applicator with High Fidelity Human Body Model

A compact patch antenna working at the 434 MHz ISM frequency band is proposed as an RF-Hyperthermia applicator. The electromagnetic interaction in terms of S11, SAR and E-Field distribution of the antenna with a High Fidelity human body model is investigated. This analysis provides useful information for engineers and clinical staff to develop more efficient and smaller antennas for medical applications, in particular for RF-Hyperthermia cancer therapy, where the size of the antenna determines tumor accessibility

Driving Electrochemical Organic Hydrogenations on Metal Catalysts by Tailoring Hydrogen Surface Coverages

Electrochemical hydrogenation, powered by renewable electricity, represents a promising sustainable approach for organic synthesis and the valorization of biomass-derived chemicals. Traditional strategies often rely on alkaline conditions to mitigate the competing hydrogen evolution reaction, posing challenges in sourcing hydrogen atoms for hydrogenation, which can be addressed through localized water dissociation on the electrode surface. In this study, we present a computationally guided design of electrochemical hydrogenation catalysts by optimizing hydrogen coverage density and binding strength on the electrode. Our theoretical investigations identify Cu, Au, and Ag - metals with moderate hydrogen coverage - as promising catalysts for electrochemical hydrogenations in alkaline media. These predictions are experimentally validated using a model organic substrate (acetophenone), achieving yields and faradaic efficiencies of up to 90%. Additionally, Cu, a nonprecious metal, is demonstrated to selectively hydrogenate a wide range of unsaturated compounds, including C═O, C═C, C≡C, and C≡N bonds, at low potentials with moderate to excellent conversion rates and chemoselectivities. This work highlights the potential of tailoring hydrogen coverage on electrode surfaces to rationally design nonprecious metal electrocatalysts for efficient organic hydrogenations. The insights gained here are expected to inform the development of more effective catalysts for organic hydrogenations and other industrially relevant chemical transformations

Planar Antennas

This article reviews the state of the art in broadband antennas for emerging UWB applications and addresses the important issues of the broadband antenna design for UWB applications. First, a variety of planar monopoles with finite ground planes are reviewed. Next, the roll antennas with enhanced radiation performance are outlined. After that, the planar antennas printed on PCBs are described. A directional antipodal Vivaldi antenna is also presented for UWB applications. Last, a UWB antenna for wearable applications is exemplifie

Special Libraries, January 1930

Volume 21, Issue 1https://scholarworks.sjsu.edu/sla_sl_1930/1000/thumbnail.jp

AI-Powered Identification of Osteoporosis in Dental Panoramic Radiographs: Addressing Methodological Flaws in Current Research

Background: Osteoporosis, a systemic skeletal disorder, is expected to affect 60% of women over 50. While dual-energy X-ray absorptiometry (DXA) scans are the current gold standard for diagnosis, they are typically used only after fractures occur, highlighting the need for early detection tools. Initial studies have shown panoramic radiographs (PRs) to be a potential medium, but these have methodological flaws. This study aims to address these shortcomings by developing a robust AI application for accurate osteoporosis identification in PRs. Methods: A total of 348 PRs were used for development, 58 PRs for validation, and 51 PRs for hold-out testing. Initially, the YOLOv8 object detection model was employed to predict the regions of interest. Subsequently, the predicted regions of interest were extracted from the PRs and processed by the EfficientNet classification model. Results: The model for osteoporosis detection on a PR achieved an overall sensitivity of 0.83 and an F1-score of 0.53. The area under the curve (AUC) was 0.76. The lowest detection sensitivity was for the cropped angulus region (0.66), while the highest sensitivity was for the cropped mental foramen region (0.80). Conclusion: This research presents a proof-of-concept algorithm showing the potential of deep learning to identify osteoporosis in dental radiographs. Furthermore, our thorough evaluation of existing algorithms revealed that many optimistic outcomes lack credibility when subjected to rigorous methodological scrutiny