73 research outputs found
Homeostasis by Design: Harmony, Friction, Cue A Neuroergonomic Framework for Systems as Extensions of Human Being
No full textThis position paper introduces Harmony Friction Cue, a neuroergonomic design framework proposing that systems should function as extensions of human being rather than separate entities to manage. Grounded in cognitive neuroscience and direct operational observation, the framework applies to any system — digital or physical — that exists in relationship with a human pursuing a purpose. Author: Rajasekaran Thulasidoss, March 2026
Fig. 1 in An overview on the role of plant-derived tannins for the treatment of lung cancer
No full textFig. 1. Molecular targets modulated by tannins in lung cancer. Tannins Abbreviations: CASU - casuarinin; EGCG - epigallocatechin-3-gallate; FPTF - fructus phyllanthi tannin fraction; GA – gallic acid; GERA - geraniin; GRA – granatin A; GRB – granatin B; GSPs - grape seed proanthocyanidins; GSPC - grape seed procyanidins; OEB - oenothein B; PAC – proanthocyanidin rich cranberry fraction; PARE – procyanidin rich extract from sorghum bran; PBOG - prodelphinidin B-2 3′-Ogallate; PCC – procyanidins from cinnamomi cortex; PCCC – procyanidin C1 from cinnamomi cortex; PRFR – proanthocyanidin rich fraction from red rice; TA - tannic acid; TT – total tannins. Abbreviations for molecules: AP-1 - Activator protein 1; Apaf-1 - Apoptotic protease activating factor 1; BAX - BCL2 Associated X; BCL2 - Bcell lymphoma 2; BCL-XL - B-cell lymphoma-extra large; CD31 - cluster of differentiation 31; CDK - cyclin dependent kinase; CDKN1A - cyclin-dependent kinase inhibitor; c-FLIP - FLICE-like inhibitory protein; Cip1/p21 - cyclin-dependent kinase inhibitor 1; COX-2 – cyclooxygenase-2; Cyt C - cytochrome C; E-Cad – E-cadherin; EMT – epithelial-to-mesenchymal transition; Fas - apoptosis antigen 1; FasL - Fas ligand; FN - fibronectin; GR – glutathione reductase; GSH – reduced glutathione; GST - glutathione S-transferase; 15-HETE - 15-hydroxyeicosatetraenoic acid; IGFBP-3 - insulin like factor binding protein 3; IGF-2R - insulin-like growth factor 2 receptor; Kip1/p27 - cyclin-dependent kinase inhibitor 1B; MAPK - mitogen-activated protein kinase; MDM2 - mouse double minute 2 homolog; mFasL - membrane-bound FasL; miR – microRNA; NANOG - transcriptional factor; N-cad - N-cadherin; NOX - NADPH oxidase; NF-kB - nuclear factor kappa-light-chainenhancer of activated B cells; NRF2 - nuclear factor erythroid 2 (NFE2)-related factor 2; NQO1 - NAD(P)H:quinone oxidoreductase; OCT-4 - octamer-binding transcription factor 4; PARP - poly-ADP ribose polymerase; PCNA - proliferating cell nuclear antigen; PGE2 - prostaglandin E2; 6-keto-PGF1α - 6-keto-prostaglandin F1α; PTEN - phosphatase and tensin homolog; PTGIS - prostacyclin synthase; pMDM2 – phospho mouse double minute 2 homolog; pAKT – phosphorylated protein kinase B; pERK1/2 – phosphorylated extracellular signal-regulated kinase 1/2; pJNK1/2 – phosphorylated c-Jun N-terminal kinase 1/2; pNF-kB - phosphorylated nuclear factor kappa-light-chain-enhancer of activated B cells; pPI3K – phosphorylated phosphatidylinositol 3-kinase; α-SMA – alpha-smooth muscle actin; pSmad2 – phosphorylated SMAD family member 2; pSmad3 – phosphorylated SMAD family member 3; p21/WAF1 - cyclin-dependent kinase inhibitor 1; p22phox - human neutrophil cytochrome b light chain; p47phox – neutrophil cytosol factor 1; pp38 – phosphorylated p38; Rb - retinoblastoma protein; sFasL - soluble FasL; Smac/ DIABLO - Second mitochondria-derived activator of caspase/direct inhibitor of apoptosis-binding protein with low pI; SNAIL1 - Zinc finger protein SNAI1; SOX2 - SRY (sex determining region Y)-box 2; pEGFR – phosphorylated epidermal growth factor receptor; TGF-βR1 - transforming growth factor beta receptor; UGT - uridine diphosphate glucuronosyl transferase; VIM - vimentin; VEGF - vascular endothelial growth factor; XIAP - X-linked inhibitor of apoptosis protein; ZO1 - Zonula occludens1. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)Published as part of Rajasekar, Nandhine, Sivanantham, Ayyanar, Ravikumar, Vilwanathan & Rajasekaran, Subbiah, 2021, An overview on the role of plant-derived tannins for the treatment of lung cancer, pp. 1-12 in Phytochemistry (112799) 188 on page 5, DOI: 10.1016/j.phytochem.2021.112799, http://zenodo.org/record/825915
The impact of environmental and occupational exposures of manganese on pulmonary, hepatic, and renal functions
No full text
Anterior Procedures in the Management of Tuberculosis of Thoracic, Thoracolumbar and Lumbar Spine
No full textTowards Active Power Control of Waked Wind Farms: A study in SOWFA simulation environment
No full textThe power generated from wind is not synchronized to the electrical frequency of the power grid. Grid balancing services must be assured when the output from a wind farm is integrated into the electrical grid to avoid the risk of blackouts. Active Power Control (APC) methods are employed to provide grid balancing ancillary services such as frequency control. One objective of APC is to have the total power generated from a wind farm, track the power demand requirements obtained from the utility grid. To achieve this objective, the wind farm should be able to operate below their maximum power production capacity i.e, in derating mode. This implies that the turbines in the wind farm should also be derated. The presence of wakes in the wind farm results in the downstream turbines to experience reduced wind speed and increased turbulence. The earlier works on APC for wind farms revealed the need for a closed-loop wind farm control strategy to combat the effect of wake turbulence. The presence of wakes posed several challenges on obtaining the estimate of the available power at every turbine on a time scale of seconds. Yet, some model-free algorithms were dependent on the estimation of available power at every turbine in the wind farm. This, leads us to the question, “Can a wind farm controller be developed to provide APC for waked wind farms, where the setpoint selection and distribution are made without estimating the available power at each turbine?” To explore the answer to this question, a single wind turbine power tracking control algorithm is developed as the first step. This tracking algorithm does not depend on the estimation of available power. The proposed algorithm makes the turbine operate on two different operating modes namely, the perfect tracking mode and greedy/boosting mode. The algorithms were developed in a way that they can be integrated with the existing torque and pitch controllers of the turbine. Following this, a closed-loop wind farm control strategy has been developed. The closed-loop wind farm controller takes the total power generated from the wind farm as the feedback signal. Based on the operating mode of the individual turbines, the wind farm controller coordinates and distributes the total power reference signal as individual power set-points to the respective wind turbines. The performance of the closed loop wind farm controller was evaluated for a 9-turbine case in SOWFA simulation for four different scenarios. The scenarios differed from each other based on the way the turbines in the wind farm are derated and the individual set points to the turbines are distributed by the wind farm controller. Simulation results showed that the scenario in which the upstream turbines are derated more than the downstream turbines, the tracking performance was better compared to the other scenarios. The damage equivalent loads experienced by the tower base of the individual turbines were also calculated and each of the scenario resulted in different loading patterns. Recommendations are also provided to extend this work and perform further research.Mechanical Engineering | Systems and Contro
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