Ethical Concerns of Heroism Training

Heroism training programs originated in the mid-2000s with the goal to “Train everyday heroes” (Heroic Imagination Project, 2017). Most participants of these programs are students between the ages of 10 and 20. Anecdotal and empirical evidence suggests that these programs may create more courageous and prosocial people (Heiner, 2018; Kohen & Sólo, 2019), however there is very little discussion in the emerging academic field of heroism science about the potential ethical concerns of training minors to be heroes (Beggan, 2019; Franco & Zimbardo, 2016; Franco et al., 2017). With the growth of heroism science scholarship, it would be wise to examine and offer best practices for the ethical training of heroism with minors. Heroic action is inherently risky, and while training programs currently discuss mortality and risk assessment, minors have not developed the neural or cognitive capacity to assess risks as adults can. Furthermore, the content and goals of heroism training may go against schools’ and parents’ wishes. Heroism training programs also have the potential to make heroism seem glamorous, which could lead some participants to seek out, or create, situations requiring heroic action. The paper discusses these, and other, ethical concerns in training minors to be heroes. The paper concludes with a variety of best practice recommendations for heroism training programs working with minors including; obtaining parent consent for training, working to improve minors’ risk assessment abilities, domain specific training, and involving parents and other relevant stakeholders in the heroism training process

Backstreaming from oil diffusion pumps Final report, Dec. 1, 1963 - May 30, 1966

Backstreaming from oil diffusion and turbomolecular pump

CSM-423 - Evolutionary Solo Pong Players

An Internet Java Applet http://www.cs.essex.ac.uk/staff/poli/ SoloPong/ allows users anywhere to play the Solo Pong game. We compare people?s performance to a hand coded ?Optimal? player and programs automatically produced by artificial intelligence. The AI techniques are: genetic programming, including a hybrid of GP and a human designed algorithm, and a particle swarm optimiser. The AI approaches are not fine tuned. GP and PSO find good players. Evolutionary computation (EC) is able to beat both human designed code and human players

Uncovering the expression patterns of chimeric transcripts using surveys of affymetrix GeneChips.

BACKGROUND: A chimeric transcript is a single RNA sequence which results from the transcription of two adjacent genes. Recent studies estimate that at least 4% of tandem human gene pairs may form chimeric transcripts. Affymetrix GeneChip data are used to study the expression patterns of tens of thousands of genes and the probe sequences used in these microarrays can potentially map to exotic RNA sequences such as chimeras. RESULTS: We have studied human chimeras and investigated their expression patterns using large surveys of Affymetrix microarray data obtained from the Gene Expression Omnibus. We show that for six probe sets, a unique probe mapping to a transcript produced by one of the adjacent genes can be used to identify the expression patterns of readthrough transcripts. Furthermore, unique probes mapping to an intergenic exon present only in the MASK-BP3 chimera can be used directly to study the expression levels of this transcript. CONCLUSIONS: We have attempted to implement a new method for identifying tandem chimerism. In this analysis unambiguous probes are needed to measure run-off transcription and probes that map to intergenic exons are particularly valuable for identifying the expression of chimeras

Evolving better RNAfold structure prediction

Grow and graft genetic programming (GGGP) evolves more than 50000 parameters in a state-of-the-art C program to make functional source code changes which give more accurate predictions of how RNA molecules fold up. Genetic improvement updates 29% of the dynamic programming free energy model parameters. In most cases (50.3%) GI gives better results on 4655 known secondary structures from RNA_STRAND (29.0% are worse and 20.7% are unchanged). Indeed it also does better than parameters recommended by Andronescu, M., et al.: Bioinformatics 23(13) (2007) i19–i28

Finite element approximation of a sixth order nonlinear degenerate parabolic equation

We consider a finite element approximation of the sixth order nonlinear degenerate parabolic equation ut = ?.( b(u)? 2u), where generically b(u) := |u|? for any given ? ? (0,?). In addition to showing well-posedness of our approximation, we prove convergence in space dimensions d ? 3. Furthermore an iterative scheme for solving the resulting nonlinear discrete system is analysed. Finally some numerical experiments in one and two space dimensions are presented

NRF2 regulates HER1 signaling pathway to modulate the sensitivity of ovarian cancer cells to lapatinib and erlotinib

NF-E2-related factor 2 (NRF2) regulates the transcription of a battery of metabolic and cytoprotective genes. NRF2 and epidermal growth factor receptors (EGFRs/HERs) are regulators of cellular proliferation and determinants of cancer initiation and progression. NRF2 and HERs confer cancers with resistance to several therapeutic agents. Nevertheless, there is limited understanding of the regulation of HER expression and activation and the link between NRF2 and HER signalling pathways. We show that NRF2 regulates both basal and inducible expression of HER1, as treatment of ovarian cancer cells (PEO1, OVCAR3, and SKOV3) with NRF2 activator tBHQ inducing HER1, while inhibition of NRF2 by siRNA knockdown or with retinoid represses HER1. Furthermore, treatment of cells with tBHQ increased total and phosphorylated NRF2, HER1, and AKT levels and compromised the cytotoxic effect of lapatinib or erlotinib. Treatment with siRNA or retinoid antagonised the effect of tBHQ on NRF2 and HER1 levels and enhanced the sensitivity of ovarian cancer cells to lapatinib or erlotinib. Pharmacological or genetic inhibition of NRF2 and/or treatment with lapatinib or erlotinib elevated cellular ROS and depleted glutathione. This extends the understanding of NRF2 and its regulation of HER family receptors and opens a strategic target for improving cancer therapy