Solar Power Prediction Using Machine Learning

This paper presents a machine learning-based approach for predicting solar power generation with high accuracy using a 99% AUC (Area Under the Curve) metric. The approach includes data collection, pre-processing, feature selection, model selection, training, evaluation, and deployment. High-quality data from multiple sources, including weather data, solar irradiance data, and historical solar power generation data, are collected and pre-processed to remove outliers, handle missing values, and normalize the data. Relevant features such as temperature, humidity, wind speed, and solar irradiance are selected for model training. Support Vector Machines (SVM), Random Forest, and Gradient Boosting are used as machine learning algorithms to produce accurate predictions. The models are trained on a large dataset of historical solar power generation data and other relevant features. The performance of the models is evaluated using AUC and other metrics such as precision, recall, and F1-score. The trained machine learning models are then deployed in a production environment, where they can be used to make real-time predictions about solar power generation. The results show that the proposed approach achieves a 99% AUC for solar power generation prediction, which can help energy companies better manage their solar power systems, reduce costs, and improve energy efficiency.Comment: 7 page

The role of JIP-1 in JNK signalling during stress and apoptosis

Recently, the JIP group of proteins was shown to organise the JNK pathway components into scaffolds. Transient transfection studies have shown that JIP-1 binds to JNK, MKK7, MLK3 and HPK1 and organises the JNK pathway in the form of a scaffold to selectively mediate JNK activation in response to stressful stimuli. An examination of the interaction of endogenous JIP-1 with JNK, MLK3 and HPK1 in vivo demonstrated that JIP-1 interacted with MLK3 and HPK1 in resting N1E-115 cells. In stressed N1E-115 cells, the activation of JNK coincided with the JIP-1-JNK1 interaction while the JIP-1-MLK3 interaction was lost. In the rat brain extracts JIP-1-JNK and MLK3-HPK1 interactions were detected. These data suggest that the JIP-1 scaffold complex is dynamic and the differential interaction of JIP-1 with the JNK pathway kinases may regulate JNK activity in vivo. The exchange of the JNK pathway components with the JIP-1 scaffold during stress and the ability of JIP-1 to oligomerise also suggests a possibility of signal amplification.;The presence of putative caspase-3 and -8 cleavage sites in JIP-1 led us to investigate whether JIP-1 was caspase substrate during apoptosis in vivo. The results showed that JIP-1 was cleaved by caspase-3 in vivo during both receptor- and chemical-induced apoptosis of HeLa cells. An analysis of caspase-3 cleavage-resistant JIP-1b mutants in vitro mapped the caspase-3 cleavage sites as being DLID98/A and DESD405/S.;An examination of JIP-1 cleavage and JNK activity in HeLa cells during apoptosis demonstrated that intact JIP-1 was associated with high levels of JNK activity and the cleavage of JIP-1 was coincident with a decrease in JNK activity. Furthermore, during TRAIL-induced apoptosis, the co-immunoprecipitation of JIP-1 and JJNK1 was coincident with JNK activation, whereas a decrease in JNK activity correlated with a reduced ability of JIP-1 to interact with JNK1. These results suggest that the interaction of JIP-1 with JNK may be required for JNK activation, and that the cleavage of JIP-1 may attenuate JNK signalling, in vivo during apoptosis.;Overall, the results suggests that the interaction of JIP-1 with the JNK pathway components may be necessary for JNK activation in vivo during stress and apoptosis

Transport and magnetic properties of laser ablated La<SUB>0.7</SUB>Ce<SUB>0.3</SUB>MnO<SUB>3</SUB> films on LaAlO<SUB>3</SUB>

La0.7Ce0.3MnO3 is a relatively new addition to the family of colossal magnetoresistive manganites, in which the cerium ion is believed to be in the Ce4+ state. In this article, we report the magnetotransport properties of laser ablated La0.7Ce0.3MnO3 films on LaAlO3, and the effect of varying the ambient oxygen pressure during growth and the film thickness. We observe that the transport and magnetic properties of the film depend on the oxygen pressure, surface morphology, film thickness, and epitaxial strain. The films were characterized by x-ray diffraction using a four-circle goniometer. We observe an increase in the metal-insulator transition temperature with decreasing oxygen pressure. This is in direct contrast to the oxygen pressure dependence of La0.7Ce0.3MnO3 films and suggests the electron doped nature of the La0.7Ce0.3MnO3 system. With decreasing film thickness we observe an increase in the metal-insulator transition temperature. This is associated with a compression of the unit cell in the a-b plane due to epitaxial strain. On codoping with 50% Ca at the Ce site, the system (La0.7Ca0.15Ce0.15MnO3) is driven into an insulating state suggesting that the electrons generated by Ce4+ are compensated by the holes generated by Ca2+, thus making the average valence at the rare-earth site 3+ as in the parent material LaMnO3

Genome-Wide Association Analysis of Radiation Resistance in <i>Drosophila melanogaster</i>

<div><p>Background</p><p>Ionizing radiation is genotoxic to cells. Healthy tissue toxicity in patients and radiation resistance in tumors present common clinical challenges in delivering effective radiation therapies. Radiation response is a complex, polygenic trait with unknown genetic determinants. The <i>Drosophila</i> Genetic Reference Panel (DGRP) provides a model to investigate the genetics of natural variation for sensitivity to radiation.</p><p>Methods and Findings</p><p>Radiation response was quantified in 154 inbred DGRP lines, among which 92 radiosensitive lines and 62 radioresistant lines were classified as controls and cases, respectively. A case-control genome-wide association screen for radioresistance was performed. There are 32 single nucleotide polymorphisms (SNPs) associated with radio resistance at a nominal <i>p</i><10⁻⁵; all had modest effect sizes and were common variants with the minor allele frequency >5%. All the genes implicated by those SNP hits were novel, many without a known role in radiation resistance and some with unknown function. Variants in known DNA damage and repair genes associated with radiation response were below the significance threshold of <i>p</i><10⁻⁵ and were not present among the significant hits. No SNP met the genome-wide significance threshold (<i>p</i> = 1.49×10⁻⁷), indicating a necessity for a larger sample size.</p><p>Conclusions</p><p>Several genes not previously associated with variation in radiation resistance were identified. These genes, especially the ones with human homologs, form the basis for exploring new pathways involved in radiation resistance in novel functional studies. An improved DGRP model with a sample size of at least 265 lines and ideally up to 793 lines is recommended for future studies of complex traits.</p></div

Odds ratio histogram of top 32 SNPs at p<10⁻⁵.

<p>Odds ratio histogram of top 32 SNPs at p<10⁻⁵.</p

DGRP radioresistance is heritable.

<p>Reciprocal crosses between a completely sensitive RAL-28 and a highly resistant RAL-69 lines were set up to generate F1, which were then selfed to produce F2. 50 males from F1 and F2 of each cross were scored for survival after 1382 Gy irradiation. The data shown represents the mean of two independent trials.</p

Association analyses of radiation resistance among 154 DGRP lines.

<p>(A) Quantile-quantile plot. The red line indicates the expected and the black line the observed <i>p</i> values. (B) Manhattan plot of <i>p</i> values. The red dashed line indicates <i>p</i><10⁻⁵.</p

Variants in DNA damage and repair genes are not among the top associated SNPs.

<p>A scatterplot of <i>p</i> values for all 10,916 SNPs representing a comprehensive set of 102 DNA damage and repair genes (dots), along with the <i>p</i> values of top 32 SNPs (crosses).</p