Influencer marketing has an unethical side that was important for us to talk about. Thisstudy’s objective was to understand how impactful it was regarding the consumer and how itcould be really bad for a company to use this type of marketing in an unethical way. Theresearch then permitted us to investigate, see and understand consumer’s point of view onthis topic, especially thanks to the interviews that were conducted. The findings were varied,but most of the people that were asked about it were positive about the fact that unethicalpromotions impacted their behavior towards the brands in a bad way. This is the reason whycompanies must choose wisely the influencers they chose to use to promote their brands onsocial media. Indeed, as their name suggests, they influence their followers. That is thereason why they must be ethically correct.

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Inspired by a planar partitioning problem involving multiple unbounded chambers, this thesis investigates using classical techniques what can be said of the existence, uniqueness, and regularity of minimizers in a certain free-endpoint isoperimetric problem. In two cases, a full existence-uniqueness-regularity result is proved using a convexity technique inspired by work of Talenti. The problem studied here can be interpreted physically as the identification of the equilibrium shape of a sessile liquid drop in half-space (in the absence of gravity). This is a well-studied variational problem whose full resolution requires the use of geometric measure theory, in particular the theory of sets of finite perimeter. A crash course on the theory required for the modern statement of the equilibrium shape theorem is presented in an appendix. / Thesis / Master of Science (MSc)

Les technologies récentes de séquençage de l’ARN de cellules uniques (scRNA-seq, pour single cell RNA-seq) ont permis de quantifier le niveau d’expression des gènes au niveau de la cellules, alors que les technologies standards de séquençage de l’ARN (RNA-seq, ou bulk RNA-seq) ne permettaient de quantifier que l’expression moyenne des gènes dans un échantillon de cellules. Cette résolution supérieure a permis des avancées majeures dans le domaine de la recherche biomédicale, mais a également posé de nouveaux défis, notamment computationnels. Les données qui découlent des technologies de scRNA-seq sont en effet complexes et plus bruitées que les données de bulk RNA-seq. En outre, les technologies sont nombreuses et leur nombre explose, nécessitant chacune un prétraitement plus ou moins différent. De plus en plus de méthodes sont ainsi développées, mais il n’existe pas encore de norme établie (gold standard) pour le prétraitement et l’analyse de ces données. Le laboratoire du Dr. Mader a récemment fait l’acquisition de la technologie Drop-Seq (une technologie haut débit de scRNA-seq), nécessitant une expertise nouvelle pour le traitement des données qui en découlent. Dans ce mémoire, différentes étapes du prétraitement des données issues de la technologie Drop-Seq sont donc passées en revue et le fonctionnement de certains outils dédiés à cet effet est étudié, permettant d’établir des lignes directrices pour de futures expériences au sein du laboratoire du Dr. Mader. Cette étude est menée sur les premiers jeux de données générés avec la technologie Drop-Seq du laboratoire, issus de lignées cellulaires du cancer du sein. Les méthodes d’analyses, moins spécifiques à la technologie, ne sont pas étudiées dans ce mémoire, mais une analyse exploratoire des jeux de données du laboratoire pose les bases pour une analyse plus poussée. / Recent single cell RNA sequencing technologies (scRNA-seq) have enabled the quantification of gene expression levels at the cellular level, while standard RNA sequencing technologies (RNA-seq, or bulk RNA-seq) have only been able to quantify the average gene expression in a sample of cells. This higher resolution has allowed major advances in biomedical research, but has also raised new challenges, in particular computational ones. The data derived from scRNA-seq technologies are indeed complex and noisier than bulk RNA-seq data. In addition, the number of scRNA-seq technologies is exploding, each of them requiring a rather different pre-processing. More and more methods are thus being developed, but there is still no gold standard for the preprocessing and analysis of these data. Dr. Mader’s laboratory has recently invested in the Drop-Seq technology (a high-throughput scRNAseq technology), requiring new expertise for the processing of the resulting data. In this thesis, different steps for the pre-processing of Drop-Seq data are reviewed and the behavior of some of the dedicated tools are studied, allowing to establish guidelines for future experiments in Dr. Mader’s laboratory. This study is conducted on the first data sets generated with the Drop-Seq technology of the laboratory, derived from breast cancer cell lines. Analytical methods, less specific to the technology, are not investigated in this thesis, but an exploratory analysis of the lab’s datasets lays the foundation for further analysis.

Analytical, closed-form solutions governing thermoelectric behavior are derived. An analytical model utilizing a thermal circuit is presented involving heat transfer into, through, out of, and around a thermoelectric device. A nondimensionalization of the model is presented. Linear heat transfer theory is applied to the model to obtain a series of closed form equations predicting net power output for the thermoelectric device. Fluid streams flowing through shrouded heat sinks with square pin fins are considered for the thermal pathways to and from the device. Heat transfer and pressure drop are characterized in a manner conducive to an analytical model using previously published experimental results. Experimental data is presented which validates and demonstrates the usefulness of the model in predicting power output for commercially available thermoelectric generators. A specific design for a thermoelectric power harvester is suggested consisting of a pattern of thermoelectric generators. An economic model for calculating payback time is developed. An optimization process is demonstrated that allows for the payback time of such a system to be minimized through optimization of the physical design of the system. It is shown that optimization of the thermal pathways dramatically reduces payback time. Optimized design of a system is discussed in light of theoretical cases with feasible payback times.