Computation of the lambert W function in photovoltaic modeling

Recently, the Lambert W function has emerged as a valuable mathematical tool in photovoltaic (PV) modeling and other scientific fields. This increasing interest is because it can be used to reformulate the implicit equations of the single-diode PV model into explicit form. However, the computation of the Lambert W function itself is still not clear in the literature; some studies use the iterative built-in functions in MATLAB or other computational platforms, while others adopt their own approximation formulae. This paper takes a deeper look at the ways the Lambert W function is evaluated in PV models and carries out a comparative study to assess the most commonly used methods in terms of accuracy, computational cost, and application range. These alternatives are implemented in a modern computer and a typical microcontroller to evaluate their performance in both simulations and embedded applications. The analysis concludes that some series expansions are good options for PV modeling applications, requiring less execution time than the built-in MATLAB lambertw function and exhibiting negligible approximation error

Montage: An Astronomical Image Mosaic Service for the NVO

Montage is a software system for generating astronomical image mosaics according to user-specified size, rotation, WCS-compliant projection and coordinate system, with background modeling and rectification capabilities. Its architecture has been described in the proceedings of ADASS XII and XIII (Berriman et al. 2003, 2004). It has been designed as a toolkit, with independent modules for image reprojection, background rectification and co-addition, and will run on workstations, clusters and grids. The primary limitation of Montage thus far has been in the projection algorithm. It uses a spherical trigonometry approach that is general at the expense of speed. The reprojection algorithm has now been made 30 times faster for commonly used tangent plane to tangent plane reprojections that cover up to several square degrees, through modification of a custom algorithm first derived for the Spitzer Space Telescope. This focus session will describe this algorithm, demonstrate the generation of mosaics in real time, and describe applications of the software. In particular, we will highlight one case study which shows how Montage is supporting the generation of science-grade mosaics of images measured with the Infrared Array Camera aboard the Spitzer Space Telescope

Towards a Generic Architecture from Symbiotic Simulation System-based Digital Twin

Digital twin (DT)—one of the most prominent technologies in the Industry 4.0 era—has the ability to integrate the physical and virtual worlds, such that the data exchanged between them could be used to support decision-making and improve operations. DT could benefit from advancement in symbiotic simulation system (SSS), which has been used for so many years, prior to the advent of Industry 4.0, to interact with physical systems and support decision-making using the data from their interaction. Therefore, this paper will propose an SSS-based generic architecture for DT that satisfies DT requirements

When data sharing gets close to 100%. What human paleogenetics can teach the open science movement

This study analyzes data sharing regarding mitochondrial, Y chromosomal and autosomal polymorphisms in a total of 162 papers on ancient human DNA published between 1988 and 2013. The estimated sharing rate was not far from totality (97.6% ± 2.1%) and substantially higher than observed in other fields of genetic research (evolutionary, medical and forensic genetics). Both a questionnaire-based survey and the examination of Journals’ editorial policies suggest that this high sharing rate cannot be simply explained by the need to comply with stakeholders requests. Most data were made available through body text, but the use of primary databases increased in coincidence with the introduction of complete mitochondrial and next-generation sequencing methods. Our study highlights three important aspects. First, our results imply that researchers’ awareness of the importance of openness and transparency for scientific progress may complement stakeholders’ policies in achieving very high sharing rates. Second, widespread data sharing does not necessarily coincide with a prevalent use of practices which maximize data findability, accessibility, useability and preservation. A detailed look at the different ways in which data are released can be very useful to detect failures to adopt the best sharing modalities and understand how to correct them. Third and finally, the case of human paleogenetics tells us that a widespread awareness of the importance of Open Science may be important to build reliable scientific practices even in the presence of complex experimental challenges

Detection of Fake Generated Scientific Abstracts

The widespread adoption of Large Language Models and publicly available ChatGPT has marked a significant turning point in the integration of Artificial Intelligence into people's everyday lives. The academic community has taken notice of these technological advancements and has expressed concerns regarding the difficulty of discriminating between what is real and what is artificially generated. Thus, researchers have been working on developing effective systems to identify machine-generated text. In this study, we utilize the GPT-3 model to generate scientific paper abstracts through Artificial Intelligence and explore various text representation methods when combined with Machine Learning models with the aim of identifying machine-written text. We analyze the models' performance and address several research questions that rise during the analysis of the results. By conducting this research, we shed light on the capabilities and limitations of Artificial Intelligence generated text

Dissolved organic matter cycling in eastern Mediterranean rivers experiencing multiple pressures. The case of the trans-boundary Evros River

The objective of our study was to provide a comprehensive evaluation on C, N, P cycling in medium sized Mediterranean rivers, such as the Evros, experiencing multiple pressures (intensive agriculture, industrial activities, population density). Our work aims also to contribute to the development of integrated management policies. Dissolved organic matter (DOM) cycling were investigated, during a one-year study. It was shown that the organic component of N and P was comparable to those of large Mediterranean rivers (Rhone, Po). In the lower parts of the river where all point and non-point inputs converge, the high inorganic N input favour elevated assimilation rates by phytoplankton and result in increased chl-a concentrations and autochthonous dissolved organic matter (DOM) production during the dry season with limited water flow. Moreover, carbohydrate distribution revealed that there is a constant background of soil derived mono-saccharides on top of which are superimposed impulses of poly-saccharides during blooms. During the dry season, inorganic nutrients and DOM are trapped in the lower parts of the river, whereas during high flow conditions DOM is flushed towards the sea and organic nitrogen forms can become an important TDN constituent (at least 40%) transported to shelf waters. The co-existence of terrigenous material with autochthonous and some anthropogenic is supported by the relatively low DOC:DON and DOC:DOP ratios, the positive correlation of DOC vs chl-a and the decoupling between DOC and DON. Overall, this study showed that in medium size Mediterranean rivers, such as the Evros, intensive agriculture and pollution sources in combination with water management practices and climatic variability are important factors determining C, N, P dynamics and export to coastal seas. Also, it highlights the importance of the organic fraction of N and P when considering management practices