Solar Flare Prediction and Feature Selection using Light Gradient Boosting Machine Algorithm

Solar flares are among the most severe space weather phenomena, and they have the capacity to generate radiation storms and radio disruptions on Earth. The accurate prediction of solar flare events remains a significant challenge, requiring continuous monitoring and identification of specific features that can aid in forecasting this phenomenon, particularly for different classes of solar flares. In this study, we aim to forecast C and M class solar flares utilising a machine-learning algorithm, namely the Light Gradient Boosting Machine. We have utilised a dataset spanning 9 years, obtained from the Space-weather Helioseismic and Magnetic Imager Active Region Patches (SHARP), with a temporal resolution of 1 hour. A total of 37 flare features were considered in our analysis, comprising of 25 active region parameters and 12 flare history features. To address the issue of class imbalance in solar flare data, we employed the Synthetic Minority Oversampling Technique (SMOTE). We used two labeling approaches in our study: a fixed 24-hour window label and a varying window that considers the changing nature of solar activity. Then, the developed machine learning algorithm was trained and tested using forecast verification metrics, with an emphasis on evaluating the true skill statistic (TSS). Furthermore, we implemented a feature selection algorithm to determine the most significant features from the pool of 37 features that could distinguish between flaring and non-flaring active regions. We found that utilising a limited set of useful features resulted in improved prediction performance. For the 24-hour prediction window, we achieved a TSS of 0.63 (0.69) and accuracy of 0.90 (0.97) for $\geq$C ($\geq$M) class solar flares.Comment: Accepted for publication in Solar Physics journa

Sequence and de novo assembly of the genome of the Indian oil sardine, Sardinella longiceps

The Indian oil sardine, Sardinella longiceps, is a widely distributed and commercially important small pelagic fish of the Northern Indian Ocean. The genome of the Indian oil sardine has been characterized using Illumina and Nanopore platforms. The assembly is 1.077 Gb (31.86 Mb Scaffold N50) in size with a repeat content of 23.24%. The BUSCO (Benchmarking Universal Single Copy Orthologues) completeness of the assembly is 93.5% when compared with Actinopterygii (ray finned fishes) data set. A total of 46316 protein coding genes were predicted. Sardinella longiceps is nutritionally rich with high levels of omega-3 polyunsaturated fatty acids (PUFA). The core genes for omega-3 PUFA biosynthesis, such as Elovl 1a and 1b,Elovl 2, Elovl 4a and 4b,Elovl 8a and 8b,and Fads 2, were observed in Sardinella longiceps. The presence of these genes may indicate the PUFA biosynthetic capability of Indian oil sardine, which needs to be confirmed functionally

Chromosome level genome assembly of the Asian green mussel, Perna viridis

The Asian green mussel, Perna viridis is an important aquaculture species in the family Mytilidae contributing substantially to molluscan aquaculture. We generated a high-quality chromosome level assembly of this species by combining PacBio single molecule sequencing technique (SMRT), Illumina paired-end sequencing, high-throughput chromosome conformation capture technique (Hi-C) and Bionano mapping. The final assembly resulted in a genome of 723.49 Mb in size with a scaffold N50 of 49.74 Mb with 99% anchored into 15 chromosomes. A total of 49654 protein-coding genes were predicted from the genome. The presence of 634 genes associated with the cancer pathway and 408 genes associated with viral carcinogenesis indicates the potential of this species to be used as a model for cancer studies. The chromosome-level assembly of this species is also a valuable resource for further genomic selection and selective breeding for improving economically important aquaculture traits and augmenting aquaculture productivity

Mendeley Readership Characteristics of Library and Information Science Articles: An Altmetric Exploration

The present study assesses the occupation, discipline and location-wise Mendeley readership characteristics of LIS articles. Besides, the study analyzed the association between citations and Mendeley readership. Data for the analysis were collected from the WoS database by searching the keyword "Information science and Library science" through the advanced search feature. To extract the Mendeley readership of the articles, Webometric Analyst 4.1 was used. It was found that out of 16796 articles, 8370 (44.12%) articles have a readership. Nine user categories were reported to read LIS papers, and PhD/doctoral students were the most readers with 147217 readers, followed by postgraduate/master's students with 112597 readers. Readers from the Computer Science discipline were found to be the most intake of the LIS articles with 99001 reads, followed by readers from Engineering (88210). Geographically, the highest readership was recorded in the United States with 8442 readers, Malaysia with 1809 readers and Brazil with 1720 readers. A low positive correlation was reported between the citations and Mendeley readership for the articles, and the association did not become strong in the longer term. The study's findings offer a hint for scientometricians to use Mendeley metrics for measuring the early impact of LIS articles along with the traditional citation metrics

Evaluation of CERES-Rice model for the selected rice varieties of Kerala

A field experiment was conducted at Thrissur during kharif seasons of 2013 and 2014 using two rice varieties (Jyothi and Kanchana) and five dates of planting (June 5th, June 20th, July 5th, July 20th and August 5th). CERES-Rice model of DSSAT v 4.6 was used to simulate the phenology and grain yield of rice. Calibration of genetic coefficients was done with 6000 iterations and then the model was validated. The model could simulate the phenology of both the rice varieties with RMSE ranging between 0.89 to 1.92 for physiological maturity.The model overestimated the grain yield of rice cultivars which need further refinement.

Demonstration of Synergistic Catalysis in Au@Ni Bimetallic Core–Shell Nanostructures

Core–shell bimetallic nanoparticles comprised of gold core and varying nickel shell have been synthesized, and their synergistic effect in catalysis is explored through catalytic hydrogenation of <i>p</i>-nitrophenol and <i>p</i>-nitrothiophenol. A clear evidence for synergism in Au@Ni core–shell nanoparticles having an ultrathin Ni shell (1–2 nm) around a Au core (6–10 nm) resulting in enhanced catalytic activity is observed. The rates observed from a thin nickel shell are higher than monometallic Au or Ni nanoparticles of similar size or with a thicker Ni shell of 6–8 nm

Synthesis of Au@Ni bimetallic core shell nanoparticle and nanochains in soyabean oil and their catalytic hydrogenation reactions

Synthesis of Au@Ni bimetallic core shell nanostructures using commercially available soya bean oil as the solvent through a sequential reduction strategy is reported. The energy efficiency and economic viability comes from the much milder temperatures and replacement of expensive and environmentally hazardous solvents like long chain organic amines and acids previously reported for synthesis. Thus, core shell nanoparticles having size regime of 10‐15 nm with an excellent control over the nickel shell thickness (2 nm) over the gold core (8‐10 nm) and Au@Ni nanochains is achieved. The synthesized materials are demonstrated to synergistically catalyze hydrogenation of nitro and C‐C multiple bonds with much better efficiency as compared to individual nanoparticle counterparts

Refolding and characterization of a diabody against Pfs25, a vaccine candidate of Plasmodium falciparum

Pfs25, a vaccine candidate, expressed on the surface of the malarial parasite, plays an important role in the development of Plasmodium falciparum. 1269, a monoclonal antibody targeting the epidermal growth factor-like domain 1 and epidermal growth factor-like domain 3 of Pfs25, blocks the transmission of parasites in mosquitoes. In this study, we refolded 1269-Db, a dimeric antibody fragment referred as diabody, designed from 1269, with a yield of 3 mg/litre of bacterial culture. Structural integrity of the protein was validated with thermal stability, disulphide bond analysis and glutaraldehyde crosslinking experiments. To evaluate the functionality of 1269-Db, recombinant monomeric MBP-Pfs25 was produced from bacteria. Qualitative binding assays demonstrated that 1269-Db recognized the epitopes on Pfs25 in its native, but not the denatured state. An apparent KD of 2.6 nM was determined for 1269-Db with monomeric MBP-Pfs25, using isothermal titration calorimetry. 1269-Db recognized the periphery of zygotes/ookinetes, demonstrating recognition of Pfs25, expressed on the surface of the parasite. As the established refolding method resulted in a functional diabody, the optimized method pipeline for 1269-Db can potentially facilitate engineering of antibody fragments with desired properties