Advancing solar energy forecasting with modified ANN and light GBM learning algorithms

In the evolving field of solar energy, precise forecasting of Solar Irradiance (SI) stands as a pivotal challenge for the optimization of photovoltaic (PV) systems. Addressing the inadequacies in current forecasting techniques, we introduced advanced machine learning models, namely the Rectified Linear Unit Activation with Adaptive Moment Estimation Neural Network (RELAD-ANN) and the Linear Support Vector Machine with Individual Parameter Features (LSIPF). These models broke new ground by striking an unprecedented balance between computational efficiency and predictive accuracy, specifically engineered to overcome common pitfalls such as overfitting and data inconsistency. The RELAD-ANN model, with its multi-layer architecture, sets a new standard in detecting the nuanced dynamics between SI and meteorological variables. By integrating sophisticated regression methods like Support Vector Regression (SVR) and Lightweight Gradient Boosting Machines (Light GBM), our results illuminated the intricate relationship between SI and its influencing factors, marking a novel contribution to the domain of solar energy forecasting. With an R2 of 0.935, MAE of 8.20, and MAPE of 3.48%, the model outshone other models, signifying its potential for accurate and reliable SI forecasting, when compared with existing models like Multi-Layer Perceptron, Long Short-Term Memory (LSTM), Multilayer-LSTM, Gated Recurrent Unit, and 1-dimensional Convolutional Neural Network, while the LSIPF model showed limitations in its predictive ability. Light GBM emerged as a robust approach in evaluating environmental influences on SI, outperforming the SVR model. Our findings contributed significantly to the optimization of solar energy systems and could be applied globally, offering a promising direction for renewable energy management and real-time forecasting

AI-Driven precision in solar forecasting: Breakthroughs in machine learning and deep learning

The need for accurate solar energy forecasting is paramount as the global push towards renewable energy intensifies. We aimed to provide a comprehensive analysis of the latest advancements in solar energy forecasting, focusing on Machine Learning (ML) and Deep Learning (DL) techniques. The novelty of this review lies in its detailed examination of ML and DL models, highlighting their ability to handle complex and nonlinear patterns in Solar Irradiance (SI) data. We systematically explored the evolution from traditional empirical, including machine learning (ML), and physical approaches to these advanced models, and delved into their real-world applications, discussing economic and policy implications. Additionally, we covered a variety of forecasting models, including empirical, image-based, statistical, ML, DL, foundation, and hybrid models. Our analysis revealed that ML and DL models significantly enhance forecasting accuracy, operational efficiency, and grid reliability, contributing to economic benefits and supporting sustainable energy policies. By addressing challenges related to data quality and model interpretability, this review underscores the importance of continuous innovation in solar forecasting techniques to fully realize their potential. The findings suggest that integrating these advanced models with traditional approaches offers the most promising path forward for improving solar energy forecasting

Differential modulatory effects of GSK-3β and HDM2 on sorafenib-induced AIF nuclear translocation (programmed necrosis) in melanoma

<p>Abstract</p> <p>Background</p> <p>GSK-3β phosphorylates numerous substrates that govern cell survival. It phosphorylates p53, for example, and induces its nuclear export, HDM2-dependent ubiquitination, and proteasomal degradation. GSK-3β can either enhance or inhibit programmed cell death, depending on the nature of the pro-apoptotic stimulus. We previously showed that the multikinase inhibitor sorafenib activated GSK-3β and that this activation attenuated the cytotoxic effects of the drug in various BRAF-mutant melanoma cell lines. In this report, we describe the results of studies exploring the effects of GSK-3β on the cytotoxicity and antitumor activity of sorafenib combined with the HDM2 antagonist MI-319.</p> <p>Results</p> <p>MI-319 alone increased p53 levels and p53-dependent gene expression in melanoma cells but did not induce programmed cell death. Its cytotoxicity, however, was augmented in some melanoma cell lines by the addition of sorafenib. In responsive cell lines, the MI-319/sorafenib combination induced the disappearance of p53 from the nucleus, the down modulation of Bcl-2 and Bcl-x_L, the translocation of p53 to the mitochondria and that of AIF to the nuclei. These events were all GSK-3β-dependent in that they were blocked with a GSK-3β shRNA and facilitated in otherwise unresponsive melanoma cell lines by the introduction of a constitutively active form of the kinase (GSK-3β-S9A). These modulatory effects of GSK-3β on the activities of the sorafenib/MI-319 combination were the exact reverse of its effects on the activities of sorafenib alone, which induced the down modulation of Bcl-2 and Bcl-x_Land the nuclear translocation of AIF only in cells in which GSK-3β activity was either down modulated or constitutively low. In A375 xenografts, the antitumor effects of sorafenib and MI-319 were additive and associated with the down modulation of Bcl-2 and Bcl-x_L, the nuclear translocation of AIF, and increased suppression of tumor angiogenesis.</p> <p>Conclusions</p> <p>Our data demonstrate a complex partnership between GSK-3β and HDM2 in the regulation of p53 function in the nucleus and mitochondria. The data suggest that the ability of sorafenib to activate GSK-3β and alter the intracellular distribution of p53 may be exploitable as an adjunct to agents that prevent the HDM2-dependent degradation of p53 in the treatment of melanoma.</p

Worldwide trends in the burden of asthma symptoms in school-aged children: Global Asthma Network Phase I cross-sectional study

Background: Asthma is the most common chronic disease in children globally. The Global Asthma Network (GAN) Phase I study aimed to determine if the worldwide burden of asthma symptoms is changing. Methods: This updated cross-sectional study used the same methods as the International study of Asthma and Allergies in Childhood (ISAAC) Phase III. Asthma symptoms were assessed from centres that completed GAN Phase I and ISAAC Phase I (1993–95), ISAAC Phase III (2001–03), or both. We included individuals from two age groups (children aged 6–7 years and adolescents aged 13–14 years) who self-completed written questionnaires at school. We estimated the 10-year rate of change in prevalence of current wheeze, severe asthma symptoms, ever having asthma, exercise wheeze, and night cough (defined by core questions in the questionnaire) for each centre, and we estimated trends across world regions and income levels using mixed-effects linear regression models with region and country income level as confounders. Findings: Overall, 119 795 participants from 27 centres in 14 countries were included: 74 361 adolescents (response rate 90%) and 45 434 children (response rate 79%). About one in ten individuals of both age groups had wheeze in the preceding year, of whom almost half had severe symptoms. Most centres showed a change in prevalence of 2 SE or more between ISAAC Phase III to GAN Phase I. Over the 27-year period (1993–2020), adolescents showed a significant decrease in percentage point prevalence per decade in severe asthma symptoms (–0·37, 95% CI –0·69 to –0·04) and an increase in ever having asthma (1·25, 0·67 to 1·83) and night cough (4·25, 3·06 to 5·44), which was also found in children (3·21, 1·80 to 4·62). The prevalence of current wheeze decreased in low-income countries (–1·37, –2·47 to –0·27], in children and –1·67, –2·70 to –0·64, in adolescents) and increased in lower-middle-income countries (1·99, 0·33 to 3·66, in children and 1·69, 0·13 to 3·25, in adolescents), but it was stable in upper-middle-income and high-income countries. Interpretation: Trends in prevalence and severity of asthma symptoms over the past three decades varied by age group, country income, region, and centre. The high worldwide burden of severe asthma symptoms would be mitigated by enabling access to effective therapies for asthma. Funding: International Union Against Tuberculosis and Lung Disease, Boehringer Ingelheim New Zealand, AstraZeneca Educational Grant, National Institute for Health Research, UK Medical Research Council, European Research Council, and Instituto de Salud Carlos III

Co-circulation of three camel coronavirus species and recombination of MERS-CoVs in Saudi Arabia

Outbreaks of Middle East respiratory syndrome (MERS) raise questions about the prevalence and evolution of the MERS coronavirus (CoV) in its animal reservoir. Our surveillance in Saudi Arabia in 2014 and 2015 showed that viruses of the MERS-CoV species and a human CoV 229E-related lineage co-circulated at high prevalence, with frequent co-infections in the upper respiratory tract of dromedary camels. viruses of the betacoronavirus 1 species, we found that dromedary camels share three CoV species with humans. Several MERS-CoV lineages were present in camels, including a recombinant lineage that has been dominant since December 2014 and that subsequently led to the human outbreaks in 2015. Camels therefore serve as an important reservoir for the maintenance and diversification of the MERS-CoVs and are the source of human infections with this virus

A novel thiol-reductase activity of Arabidopsis YUC6 confers drought tolerance independently of auxin biosynthesis

AbstractYUCCA (YUC) proteins constitute a family of flavin monooxygenases (FMOs), with an important role in auxin (IAA) biosynthesis. Here we report that Arabidopsis plants overexpressing YUC6 display enhanced IAA-related phenotypes and exhibit improved drought stress tolerance, low rate of water loss and controlled ROS accumulation under drought and oxidative stresses. Co-overexpression of an IAA-conjugating enzyme reduces IAA levels but drought stress tolerance is unaffected, indicating that the stress-related phenotype is not based on IAA overproduction. YUC6 contains a previously unrecognized FAD- and NADPH-dependent thiol-reductase activity (TR) that overlaps with the FMO domain involved in IAA biosynthesis. Mutation of a conserved cysteine residue (Cys-85) preserves FMO but suppresses TR activity and stress tolerance, whereas mutating the FAD- and NADPH-binding sites, that are common to TR and FMO domains, abolishes all outputs. We provide a paradigm for a single protein playing a dual role, regulating plant development and conveying stress defence responses.</jats:p