Large-scale linear regression: Development of high-performance routines

In statistics, series of ordinary least squares problems (OLS) are used to study the linear correlation among sets of variables of interest; in many studies, the number of such variables is at least in the millions, and the corresponding datasets occupy terabytes of disk space. As the availability of large-scale datasets increases regularly, so does the challenge in dealing with them. Indeed, traditional solvers---which rely on the use of black-box" routines optimized for one single OLS---are highly inefficient and fail to provide a viable solution for big-data analyses. As a case study, in this paper we consider a linear regression consisting of two-dimensional grids of related OLS problems that arise in the context of genome-wide association analyses, and give a careful walkthrough for the development of {\sc ols-grid}, a high-performance routine for shared-memory architectures; analogous steps are relevant for tailoring OLS solvers to other applications. In particular, we first illustrate the design of efficient algorithms that exploit the structure of the OLS problems and eliminate redundant computations; then, we show how to effectively deal with datasets that do not fit in main memory; finally, we discuss how to cast the computation in terms of efficient kernels and how to achieve scalability. Importantly, each design decision along the way is justified by simple performance models. {\sc ols-grid} enables the solution of $10^{11}$ correlated OLS problems operating on terabytes of data in a matter of hours

Catching Cheats: Detecting Strategic Manipulation in Distributed Optimisation of Electric Vehicle Aggregators

Given the rapid rise of electric vehicles (EVs) worldwide, and the ambitious targets set for the near future, the management of large EV fleets must be seen as a priority. Specifically, we study a scenario where EV charging is managed through self-interested EV aggregators who compete in the day-ahead market in order to purchase the electricity needed to meet their clients' requirements. With the aim of reducing electricity costs and lowering the impact on electricity markets, a centralised bidding coordination framework has been proposed in the literature employing a coordinator. In order to improve privacy and limit the need for the coordinator, we propose a reformulation of the coordination framework as a decentralised algorithm, employing the Alternating Direction Method of Multipliers (ADMM). However, given the self-interested nature of the aggregators, they can deviate from the algorithm in order to reduce their energy costs. Hence, we study the strategic manipulation of the ADMM algorithm and, in doing so, describe and analyse different possible attack vectors and propose a mathematical framework to quantify and detect manipulation. Importantly, this detection framework is not limited the considered EV scenario and can be applied to general ADMM algorithms. Finally, we test the proposed decentralised coordination and manipulation detection algorithms in realistic scenarios using real market and driver data from Spain. Our empirical results show that the decentralised algorithm's convergence to the optimal solution can be effectively disrupted by manipulative attacks achieving convergence to a different non-optimal solution which benefits the attacker. With respect to the detection algorithm, results indicate that it achieves very high accuracies and significantly outperforms a naive benchmark

Microfluidic polymerase chain reaction

We implement microfluidic technology to miniaturize a thermal cycling system for amplifying DNA fragments. By using a microfluidic thermal heat exchanger to cool a Peltier junction, we have demonstrated rapid heating and cooling of small volumes of solution. We use a miniature K-type thermocouple to provide a means for in situ sensing of the temperature inside the microrefrigeration system. By combining the thermocouple, two power supplies controlled by a relay system, and computer automation, we reproduce the function of a commercial polymerase chain reaction thermal cycler and demonstrate amplification of a DNA sample of about 1000 base pairs

Consulting project - Recidar

En cuanto al proyecto de consultoría que se ha llevado a cabo para Recidar, encierra un enfoque innovador para garantizar un futuro viable a su compromiso social de abogar por procesos de economía circular en Lima. La iniciativa recomendada se construye a través de la colaboración con diferentes actores clave que permitirán optimizar el alcance y la profundidad de la nueva Recidar. La asociación con actores locales clave es la clave para que Recidar desarrolle una mejor vía para su visión a largo plazo. Dado que Recidar está actualmente atascada con el alto nivel de actividad que se le exige a diario, el trabajo externo propuesto le dará una nueva visión para construir adecuadamente su negocio de modo que pueda resistir a las importantes fluctuaciones del entorno externo en el que opera.The following consultancy project analyzes the status of Recidar's strategic plan and recommends a greater emphasis on a long-term vision. The preliminary work has been based on the search for relevant academic articles covering the different dimensions of the circular economy. In addition, the literature review covers the different management practices that a social enterprise should foster to ensure a viable long-term vision for its operations. To successfully develop a comprehensive recommendation, an industry analysis (Porter's 5 forces), external analysis (PESTEL), internal analysis (AMOFHIT) and a detailed analysis of the problem at hand have been carried out. In terms of concrete recommendations, it highlights collaboration with universities, an engagement with a professional with inside knowledge of Gamarra, initiatives within the Gamarra ecosystem and the development of an e-commerce platform. These initiatives aim to improve brand recognition, promote a circular economy, create diverse revenue streams, and most importantly, respond to Recidar's request to build a long-term strategy for the future of its social mission

Forces driving the three-dimensional folding of eukaryotic genomes

The last decade has radically renewed our understanding of higher order chromatin folding in the eukaryotic nucleus. As a result, most current models are in support of a mostly hierarchical and relatively stable folding of chromosomes dividing chromosomal territories into A- (active) and B- (inactive) compartments, which are then further partitioned into topologically associating domains (TADs), each of which is made up from multiple loops stabilized mainly by the CTCF and cohesin chromatin-binding complexes. Nonetheless, the structure-to-function relationship of eukaryotic genomes is still not well understood. Here, we focus on recent work highlighting the biophysical and regulatory forces that contribute to the spatial organization of genomes, and we propose that the various conformations that chromatin assumes are not so much the result of a linear hierarchy, but rather of both converging and conflicting dynamic forces that act on it

Probing the local dielectric function of WS2 on an Au substrate by near field optical microscopy operating in the visible spectral range

The optoelectronic properties of nanoscale systems such as carbon nanotubes (CNTs), graphene nanoribbons and transition metal dichalcogenides (TMDCs) are determined by their dielectric function. This complex, frequency dependent function is affected by excitonic resonances, charge transfer effects, doping, sample stress and strain, and surface roughness. Knowledge of the dielectric function grants access to a material’s transmissive and absorptive characteristics. Here we use the dual scanning near field optical microscope (dual s-SNOM) for imaging local dielectric variations and extracting dielectric function values using a pre-established mathematical inversion method. To demonstrate our approach, we studied a monolayer of WS2 on bulk Au and identified two areas with differing levels of charge transfer. The experiments highlight a further advantage of the technique: the dielectric function of contaminated samples can be measured, as dirty areas can be easily identified and excluded for the calculation, being important especially for exfoliated 2D materials (Rodriguez et al., 2021). Our measurements are corroborated by atomic force microscopy (AFM), Kelvin force probe microscopy (KPFM), photoluminescence (PL) intensity mapping, and tip enhanced photoluminescence (TEPL). We extracted local dielectric variations from s-SNOM images and confirmed the reliability of the obtained values with spectroscopic imaging ellipsometry (SIE) measurements

Mechanical frequency control in inductively coupled electromechanical systems

Nano-electromechanical systems implement the opto-mechanical interaction combining electromagnetic circuits and mechanical elements. We investigate an inductively coupled nano-electromechanical system, where a superconducting quantum interference device (SQUID) realizes the coupling. We show that the resonance frequency of the mechanically compliant string embedded into the SQUID loop can be controlled in two different ways: (i) the bias magnetic flux applied perpendicular to the SQUID loop, (ii) the magnitude of the in-plane bias magnetic field contributing to the nano-electromechanical coupling. These findings are quantitatively explained by the inductive interaction contributing to the effective spring constant of the mechanical resonator. In addition, we observe a residual field dependent shift of the mechanical resonance frequency, which we attribute to the finite flux pinning of vortices trapped in the magnetic field biased nanostring.Comment: 5 pages, 3 figure