Enhanced flare prediction by advanced feature extraction from solar images : developing automated imaging and machine learning techniques for processing solar images and extracting features from active regions to enable the efficient prediction of solar flares.

Space weather has become an international issue due to the catastrophic impact it can have on modern societies. Solar flares are one of the major solar activities that drive space weather and yet their occurrence is not fully understood. Research is required to yield a better understanding of flare occurrence and enable the development of an accurate flare prediction system, which can warn industries most at risk to take preventative measures to mitigate or avoid the effects of space weather. This thesis introduces novel technologies developed by combining advances in statistical physics, image processing, machine learning, and feature selection algorithms, with advances in solar physics in order to extract valuable knowledge from historical solar data, related to active regions and flares. The aim of this thesis is to achieve the followings: i) The design of a new measurement, inspired by the physical Ising model, to estimate the magnetic complexity in active regions using solar images and an investigation of this measurement in relation to flare occurrence. The proposed name of the measurement is the Ising Magnetic Complexity (IMC). ii) Determination of the flare prediction capability of active region properties generated by the new active region detection system SMART (Solar Monitor Active Region Tracking) to enable the design of a new flare prediction system. iii) Determination of the active region properties that are most related to flare occurrence in order to enhance understanding of the underlying physics behind flare occurrence. The achieved results can be summarised as follows: i) The new active region measurement (IMC) appears to be related to flare occurrence and it has a potential use in predicting flare occurrence and location. ii) Combining machine learning with SMART¿s active region properties has the potential to provide more accurate flare predictions than the current flare prediction systems i.e. ASAP (Automated Solar Activity Prediction). iii) Reduced set of 6 active region properties seems to be the most significant properties related to flare occurrence and they can achieve similar degree of flare prediction accuracy as the full 21 SMART active region properties. The developed technologies and the findings achieved in this thesis will work as a corner stone to enhance the accuracy of flare prediction; develop efficient flare prediction systems; and enhance our understanding of flare occurrence. The algorithms, implementation, results, and future work are explained in this thesis

Hydrogenolysis of Glycerol over γ-Al2O3-Supported Iridium Catalyst

In recent years, much attention has been focused on the hydrogenolysis of biodiesel derived glycerol to other high value products for the sustainable development and efficient valorization strategies. In the present work, alumina-supported Ir catalyst was prepared by the incipient wetness impregnation method and tested in the glycerol hydrogenolysis reaction. The synthesized catalyst was characterized by neutron activation analysis, N2 physisorption, and H2 chemisorption techniques. The experiments standard conditions were 150 mL feed volume, 0.3 g catalyst, 1500 rpm stirring speed, and 5 wt% glycerol aqueous solution for 4 h. The effects of catalyst amount, temperature, hydrogen pressure, stirring speed, and solution pH on glycerol conversion and selectivity of the principal products obtained were also investigated. The glycerol conversion and the 1,2-propanediol selectivity varied from 4.9% to 22% and from 23.8% to 70.3%, respectively. It was found that the selectivity of 1,2-propanediol increased significantly with the increased alkalinity of the reaction medium

Effect of Cr2O3, ZrO2 and LiF on nucleation and crystallization of nepheline syenite-dolomite glass-ceramic compositions

Inexpensive nepheline-pyroxene glass-ceramics of superior mechanical, and thermal properties could be easily prepared from nepheline syenite and dolomite rock mixture by using the conventional glass preparation and heat treatment methods. The parent glass composition, to yield ≈35 % nepheline ss (solid solution) and 65 % diopside ss, was formulated by a modified chemico-mineralogical calculation method after CIPW norm. The effect of the nucleating agents Cr2O3, ZrO2 and LiF on the mechanisms of nucleation and crystallization of these phases were determined by DTA, XRD, as well as optical and electron microscopy. In the absence of these nueleators, crystallization was difficult and semi-crystalline coarse microstructure of diopsidic ss was obtained. LiF showed maximum effect on crystal growth rates, while sufficient nucleation density for glass-ceramic of good quality was achieved by adding Cr2O3 even in the amount as small as 0.5 wt%. Both Cr2O3- and ZrO2-containing samples hindered the crystallization of nepheline but greatly stimulated the epitactic formation of diopside ss of holocrystalline microstructures. LiF-containing samples stimulated the crystallization of the framework silicates, nepheline ss and carnegieite, which progressively increased with the LiF concentration. The thermal expansion coefficient and Vickers hardness of the obtained glass-ceramic reached values of 9.0 × 10^-6 K-1 (20 to 300 °C) and (950 × 10^7 ± 25) N/m2, respectively

p62/SQSTM1 Accumulation in Squamous Cell Carcinoma of Head and Neck Predicts Sensitivity to Phosphatidylinositol 3-Kinase Pathway Inhibitors

The phosphoinositol-3 kinase (PI3K) pathway is highly dysregulated in squamous cell carcinoma of the head and neck (SCCHN). While inhibitors of the PI3K/AKT pathway are being developed in cancer, their efficacy does not appear to be related to the presence of mutations or amplification in pathway genes. The PI3K pathway is a major regulator of macro-autophagy, an evolutionarily conserved catabolic process that degrades cellular materials to promote cellular homeostasis and survival under stress. Employing a panel of SCCHN cell lines, we observed a significant correlation between the activity of PI3K/AKT inhibitors and their ability to induce autophagy. More specifically, resistance to these inhibitors was associated with accumulation of p62/SQSTM1, a pleotropic protein that is consumed during autophagy, while loss of autophagy was, for the first time, found to be due to silencing of an essential autophagy gene, ATG7. Moreover, modulating ATG7 and p62/SQSTM1 could regulate sensitivity to PI3K/AKT inhibitors, underscoring a mechanistic link between autophagy and drug sensitivity. Analysis of human tissues revealed progressive accumulation of p62/SQSTM1 in a significant proportion of cancer samples compared to normal tissue, suggesting that defective autophagy has relevance to SCCHN. These findings are further validated by analysis of TCGA data confirming homozygous deletion and mRNA down-regulation of ATG7 in 10.0% of SCCHN samples. Taken together, these data indicate that p62/SQSTM1 levels modulate sensitivity to PI3K/AKT inhibitors; cancers vary in their capacity to undergo autophagy through epigenetic modification and, when deficient, accumulate p62/SQSTM1; and expression of autophagy-related proteins may serve as markers for resistance to PI3K/AKT inhibitors in SCCHN.</p

Meta-analysis of published cerebrospinal fluid proteomics data identifies and validates metabolic enzyme panel as Alzheimer's disease biomarkers

To develop therapies for Alzheimer's disease, we need accurate in vivo diagnostics. Multiple proteomic studies mapping biomarker candidates in cerebrospinal fluid (CSF) resulted in little overlap. To overcome this shortcoming, we apply the rarely used concept of proteomics meta-analysis to identify an effective biomarker panel. We combine ten independent datasets for biomarker identification: seven datasets from 150 patients/controls for discovery, one dataset with 20 patients/controls for down-selection, and two datasets with 494 patients/controls for validation. The discovery results in 21 biomarker candidates and down-selection in three, to be validated in the two additional large-scale proteomics datasets with 228 diseased and 266 control samples. This resulting 3-protein biomarker panel differentiates Alzheimer's disease (AD) from controls in the two validation cohorts with areas under the receiver operating characteristic curve (AUROCs) of 0.83 and 0.87, respectively. This study highlights the value of systematically re-analyzing previously published proteomics data and the need for more stringent data deposition

Application of the ANOVA method in the optimization of a thermoelectric cooler-based dehumidification system

© 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).In recent studies, Thermo-Electric Coolers (TEC) have been utilized for dehumidification purposes, which is mainly based on the extraction of moisture from humid atmospheric air. The reviewed literature showed that the rate of water collection from the TEC-based system can be affected by various parameters such as the module’s input voltage, the heat sink orientation, and tilt angles. In this research, the analysis of variance (ANOVA) was used to examine the significance of these factors and their interaction within the system on the TEC-based dehumidification system. Four levels were investigated for both, the Peltier’s input voltage and the rotation angle, and three levels for the tilt angle. This study indicated the significance of the studied factors and their interactions within the dehumidification system along with performing an overall numerical optimization. The experiments were conducted under the same working conditions in an enclosed environment to minimize errors. According to the overall numerical optimization, which was validated experimentally, the optimum system performance was predicted to be obtained at approximately 6.8V Peltier input volt, 65° rotation angle, and 90° tilt angles, with predicted optimum productivities of 0.32278 L/kWh and 13.03 mL/hr. For the same set of parameters, the variation between the experiment and the numerical optimization was less than 4%. The experiments show that when optimizing water collection rates for thermoelectric cooling heat sinks​ under high humidity conditions, the orientation of the heat sink should be considered.Peer reviewe

Thermohydraulic analysis of covalent and noncovalent functionalized graphene nanoplatelets in circular tube fitted with turbulators

© The Author(s) 2022. This article is licensed under a Creative Commons Attribution 4.0 International. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.Covalent and non-covalent nanofluids were tested inside a circular tube fitted with twisted tape inserts with 45° and 90° helix angles. Reynolds number was 7000 ≤ Re ≤ 17,000, and thermophysical properties were assessed at 308 K. The physical model was solved numerically via a two-equation eddy-viscosity model (SST k-omega turbulence). GNPs-SDBS@DW and GNPs-COOH@DW nanofluids with concentrations (0.025 wt.%, 0.05 wt.% and 0.1 wt.%) were considered in this study. The twisted pipes' walls were heated under a constant temperature of 330 K. The current study considered six parameters: outlet temperature, heat transfer coefficient, average Nusselt number, friction factor, pressure loss, and performance evaluation criterion. In both cases (45° and 90° helix angles), GNPs-SDBS@DW nanofluids presented higher thermohydraulic performance than GNPs-COOH@DW and increased by increasing the mass fractions such as 1.17 for 0.025 wt.%, 1.19 for 0.05 wt.% and 1.26 for 0.1 wt.%. Meanwhile, in both cases (45° and 90° helix angles), the value of thermohydraulic performance using GNPs-COOH@DW was 1.02 for 0.025 wt.%, 1.05 for 0.05 wt.% and 1.02 for 0.1 wt.%.Peer reviewe

Effect of BN dimers on the stability, electronic, and thermal properties of monolayer graphene

Publisher's version (útgefin grein)We theoretically investigate structural stability, electronic and thermal characteristic of boron and nitrogen codoped monolayer graphene using density functional theory and Boltzmann transport equation. Three types of BN dimers, ortho, meta, and para dimers, are identified at different concentration ratios of B and N atoms. Our DFT calculations suggest that the BN ortho dimers are structurally favorable configurations due to the lowest required formation energy. At low doping ratio, large bandgap for BN para dimer is predicted leading to high Seebeck coefficient and figure of merit. In addition, a large deviation in the Wiedemann–Franz ratio is also seen, and a maximum value of the Lorenz number is thus found. In contrast, at high doping ratio, high Seebeck coefficient and figure of merit are found for BN ortho dimer and a low Seebeck coefficient for BN para dimer is noticed. Furthermore, a small deviation in Lorenz number is found for high doping ratio where the distance between BN pair is large.This work was financially supported by the University of Sulaimani and the Research center of Komar University of Science and Technology. The computations were performed on resources provided by the Division of Computational Nanoscience at the University of Sulaimani.Peer Reviewe

Next-generation ion torrent sequencing of drug resistance mutations in Mycobacterium tuberculosis strains

A novel protocol for full-length Mycobacterium tuberculosis gene analysis of first- and second-line drug resistance was developed using the Ion Torrent Personal Genome Machine (PGM). Five genes—rpoB (rifampin), katG (isoniazid), pncA (pyrazinamide), gyrA (ofloxacin/fluoroquinolone), and rrs (aminoglycosides)—were amplified and sequenced, and results were compared to those obtained by genotypic Hain line probe assay (LPA) and phenotypic Bactec MGIT 960 analysis using 26 geographically diverse South African clinical isolates collected between July and November 2011. Ion Torrent sequencing exhibited 100% (26/26) concordance to phenotypic resistance obtained by MGIT 960 culture and genotypic rpoB and katG results by LPA. In several rifampin- resistant isolates, Ion Torrent sequencing revealed uncommon substitutions (H526R and D516G) that did not have a defined mutation by LPA. Importantly, previously uncharacterized mutations in rpoB (V194I), rrs (G878A), and pncA (Q122Stop) genes were observed. Ion Torrent sequencing may facilitate tracking and monitoring geographically diverse multidrug- resistant and extensively drug-resistant strains and could potentially be integrated into selected regional and reference settings throughout Africa, India, and China.http://jcm.asm.org/am201