Modelling rates of gasification of a char particle in chemical looping combustion

Rates of gasification of lignite char were compared when gasification with CO2 was undertaken in a fluidised bed of either (i) an active Fe-based oxygen carrier used for chemical looping or (ii) inert sand. The kinetics of the gasification were found to be significantly faster in the presence of the oxygen carrier, especially at temperatures above 1123 K. An analytical solution assuming pseudo-binary diffusion of species was developed to account for external and internal mass transfer and for the effect of the looping agent. The model also included the effects of the evolution of the pore structure at different conversions. The results are compared with a full numerical model using the Stefan-Maxwell equations. Excellent agreement was observed between the rates predicted by the two models and those observed experimentally at T ≤ 1123 K. At 1173 K, the pseudo-binary model predicted slightly higher rates than the full numerical solution. It was found that a significant share of the error of the predicted rates with the analytical solution was caused by an underestimation of intraparticle diffusional resistance rather than by assuming a pseudo-binary system external to the particle. Both models suggested that the presence of Fe2O3 led to an increase in the rate of gasification because of the rapid oxidation of CO by the oxygen carrier to CO2. This resulted in the removal of CO and maintained a higher mole fraction of CO2 in the mixture of gas around the particle of char, i.e. within the mass transfer boundary layer surrounding the particle. This effect was most prominent at ~20% conversion when (i) the surface area for reaction was a maximum and (ii) because of the accompanying increase in porosity, intraparticle resistance to gas mass transfer within the particle of char had fallen, compared with that in the initial particle.EPSRCThis is the author accepted manuscript. The final version is now available at http://www.sciencedirect.com/science/article/pii/S1540748914003150

Targeting the Redox Landscape in Cancer Therapy

Reactive oxygen species (ROS) are produced predominantly by the mitochondrial electron transport chain and by NADPH oxidases in peroxisomes and in the endoplasmic reticulum. The antioxidative defense counters overproduction of ROS with detoxifying enzymes and molecular scavengers, for instance, superoxide dismutase and glutathione, in order to restore redox homeostasis. Mutations in the redox landscape can induce carcinogenesis, whereas increased ROS production can perpetuate cancer development. Moreover, cancer cells can increase production of antioxidants, leading to resistance against chemo- or radiotherapy. Research has been developing pharmaceuticals to target the redox landscape in cancer. For instance, inhibition of key players in the redox landscape aims to modulate ROS production in order to prevent tumor development or to sensitize cancer cells in radiotherapy. Besides the redox landscape of a single cell, alternative strategies take aim at the multi-cellular level. Extracellular vesicles, such as exosomes, are crucial for the development of the hypoxic tumor microenvironment, and hence are explored as target and as drug delivery systems in cancer therapy. This review summarizes the current pharmaceutical and experimental interventions of the cancer redox landscape

Initial Characterization of WDR5B Reveals a Role in the Proliferation of Retinal Pigment Epithelial Cells.

The chromatin-associated protein WDR5 has been widely studied due to its role in histone modification and its potential as a pharmacological target for the treatment of cancer. In humans, the protein with highest sequence homology to WDR5 is encoded by the retrogene WDR5B, which remains unexplored. Here, we used CRISPR-Cas9 genome editing to generate WDR5B knockout and WDR5B-FLAG knock-in cell lines for further characterization. In contrast to WDR5, WDR5B exhibits low expression in pluripotent cells and is upregulated upon neural differentiation. Loss or shRNA depletion of WDR5B impairs cell growth and increases the fraction of non-viable cells in proliferating retinal pigment epithelial (RPE) cultures. CUT&RUN chromatin profiling in RPE and neural progenitors indicates minimal WDR5B enrichment at established WDR5 binding sites. These results suggest that WDR5 and WDR5B exhibit several divergent biological properties despite sharing a high degree of sequence homology

Learning Motivation: Strategies to Increase Students' Engagement in Online Learning at San Sebastian College-Recoletos, Manila

The objective of this study is to be able to find ways or the best strategies in teaching that will motivate students to exert effort in their studies, considering the present conditions in this pandemic period. A quantitative method was used to define the study's objective, where two sections of Psychology students who took up Science 101 and Science 104 were chosen as respondents to answer the survey questionnaire through google forms. The purposive sampling technique was also employed since these students can appropriately answer the queries sent to them. The Likert scale method was used to measure the students' level of agreement, with the 5-point range, where the results were collated and analyzed.  The research result finds several strategic activities such as report enhancement, online debates, virtual experiments, discussion and updating of recent findings, and the creation of infomercials that truly captured their interest and attention. This study made use of several references and tables in order to support the results obtained. The researcher recommends that there should be effective and efficient motivational activities to sustain student engagement. The researchers, who are also educators, have agreed to continuously upgrade the newfound motivational activities to encourage more students to study well even in an online setting, thus giving more opportunities for better achievement in education

Sensitivity of chemical-looping combustion to particle reaction kinetics

A simple simulation for chemical-looping combustion (CLC) is discussed: two, coupled fluidised reactors with steady circulation of particles of oxygen carrier between them. In particular, the sensitivity of CLC to different particle kinetics is investigated. The results show that the system is relatively insensitive to different kinetics when the mean residence time of particles in each reactor is greater than the time taken for them to react completely.This is the final published version. It first appeared at http://www.sciencedirect.com/science/article/pii/S0009250916302779

Counterfactual Fairness for Predictions using Generative Adversarial Networks

Fairness in predictions is of direct importance in practice due to legal, ethical, and societal reasons. It is often achieved through counterfactual fairness, which ensures that the prediction for an individual is the same as that in a counterfactual world under a different sensitive attribute. However, achieving counterfactual fairness is challenging as counterfactuals are unobservable. In this paper, we develop a novel deep neural network called Generative Counterfactual Fairness Network (GCFN) for making predictions under counterfactual fairness. Specifically, we leverage a tailored generative adversarial network to directly learn the counterfactual distribution of the descendants of the sensitive attribute, which we then use to enforce fair predictions through a novel counterfactual mediator regularization. If the counterfactual distribution is learned sufficiently well, our method is mathematically guaranteed to ensure the notion of counterfactual fairness. Thereby, our GCFN addresses key shortcomings of existing baselines that are based on inferring latent variables, yet which (a) are potentially correlated with the sensitive attributes and thus lead to bias, and (b) have weak capability in constructing latent representations and thus low prediction performance. Across various experiments, our method achieves state-of-the-art performance. Using a real-world case study from recidivism prediction, we further demonstrate that our method makes meaningful predictions in practice

Multifactor Models and Their Consistency with the APT

We examine the consistency of several prominent multifactor models from the empirical asset pricing literature with the arbitrage pricing theory (APT) framework. We follow the APT-related literature and estimate the common factor structure from a rich cross-section (associated with 42 major CAPM anomalies) by employing the asymptotic principal components method. Our benchmark model contains six statistical factors and clearly dominates, in both economic and statistical terms, most of the empirical multifactor models proposed in the literature by a good margin. These results represent a critical challenge to the current workhorse models in terms of explaining large-scale equity risk premiums

Exploiting Cancer Cell Mitochondria as a Therapeutic Strategy: Structure Activity Relationship Analysis of Synthetic Analogues of Pancratistatin

Distinct characteristics, including decreased dependence on mitochondrial respiration and high levels of oxygen radicals, provide opportunities for cancer targeting. We have shown the compound pancratistatin (PST) to selectively induce apoptosis in cancers by mitochondrial targeting. However, its low availability in nature was limiting its preclinical development. Various PST analogues were synthesized to circumvent this limitation. In this dissertation, these analogues were screened and several had comparable or greater anti-cancer activity compared to PST. The analogue, SVTH-7, demonstrated the most potent anti-cancer activity, followed by SVTH-6 and -5 in vitro and in vivo. These compounds had greater efficacy than PST, 7-deoxyPST analogues, and multiple standard chemotherapeutics, and were found to induce apoptosis in cancer cells by acting on cancer cell mitochondria. Furthermore, the anti-cancer effects of PST analogues were enhanced when used with agents known to target cancer cell mitochondria and oxidative vulnerabilities, including tamoxifen, curcumin, and piperlongumine. Interestingly, functional complex II and III of the electron transport chain were required for SVTH-7 to inflict its pro-apoptotic effects on cancer cells, suggesting exploitation of a mitochondrial vulnerability by SVTH-7. Therefore, these findings demonstrate a novel approach to treat cancer by exploiting cancer cell mitochondria with PST analogues alone or in combination with other compounds. These PST analogues have high therapeutic potential and this work will lay the groundwork for the identification and characterization of distinct mitochondrial features of cancer cells