Eva Hoffman considers the current preoccupation with memory - as opposed to its referents (history, experience) - and particularly with memory of the Holocaust. She proposes that the intense absorption with memory has largely emerged from the "second generation," i.e., from those for whom the Holocaust (or other disturbing pasts) has been a crucially formative event, yet one which they themselves did not experience.

This study endorses the main findings of a PhD thesis (Hoffmann 2020) and the manuscripts included intend to advance the success of protected areas in biodiversity conservation mediated through effective and efficient protected area management. The manuscripts provide missing scientific evaluations that modern conservation planning over large geographical extents requires: the comprehensive quantification of species diversity within and between protected areas; the development and application of efficient and effective in-situ monitoring and remote sensing of species diversity; and the assessment of anthropogenic climate change threats to protected areas. Moreover, the manuscripts aim at spreading conservation-minded data and knowledge by means of publishing open-access papers, open-source software and open data. This thesis synopsis is to stimulate a growing scientific and public debate on the effectiveness of protected areas and nature conservation under anthropogenic threats, which is necessary to stop nature’s decline and thus guarantee a sustainable future for the welfare of generations to come.

The effectiveness of immune responses depends on the precision of stimulus- responsive gene expression programs. Cells specify which genes to express by activating stimulus-specific combinations of stimulus-induced transcription factors (TFs). Their activities are decoded by a gene regulatory strategy (GRS) associated with each response gene. Here, we examined whether the GRSs of target genes may be inferred from stimulus-response (input-output) datasets, which remains an unresolved model-identifiability challenge. We developed a mechanistic modeling framework and computational workflow to determine the identifiability of all possible combinations of synergistic (AND) or non-synergistic (OR) GRSs involving three transcription factors. Considering different sets of perturbations for stimulus-response studies, we found that two thirds of GRSs are easily distinguishable but that substantially more quantitative data is required to distinguish the remaining third. To enhance the accuracy of the inference with timecourse experimental data, we developed an advanced error model that avoids error overestimates by distinguishing between value and temporal error. Incorporating this error model into a Bayesian framework, we show that GRS models can be identified for individual genes by considering multiple datasets. Our analysis rationalizes the allocation of experimental resources by identifying most informative TF stimulation conditions. Applying this computational workflow to experimental data of immune response genes in macrophages, we found that a much greater fraction of genes are combinatorially controlled than previously reported by considering compensation among transcription factors. Specifically, we revealed that a group of known NFκB target genes may also be regulated by IRF3, which is supported by chromatin immuno-precipitation analysis. Our study provides a computational workflow for designing and interpreting stimulus-response gene expression studies to identify underlying gene regulatory strategies and further a mechanistic understanding.

Despite attempts to discourage the use of machine translation (MT), we have observed that students continue to rely on it. Are teachers powerless? We believe not! Consistent with a range of solutions proposed in previous publications, we hypothesized that a “hands-on” approach would be effective in helping students raise awareness of the benefits and limitations of machine translation. This approach strives to reframe machine translation from an object of interdiction to an object of critical reflection. Hence, we created, implemented, and evaluated a 50-minute online lesson during Fall 2020. Our aim was to guide students toward a critical awareness of various machine translation tools [Google Translate (GT), WordReference.com (WR), French dictionaries] by choosing carefully crafted machine translation examples and asking students to correct them in class (“post-editing”). We also tried to track any potential change in the students’ representations via a confidential pre- and a post-survey, and an audio-record of the interactions in class. One of our main results is that a majority of the students had already built complex representations and clever usages of machine translation before the class, much more than what we had expected. This allows us to reflect on what kind of impacts can or cannot be expected from such a class and to discuss the benefits and limits of such an approach to better integrate translation tools into second language teaching.