Direct data-driven control synthesizes controllers from a single measured trajectory without first identifying a model. It offers deterministic robustness guarantees whenever a known disturbance bound holds. However, existing multiplier-based formulations for robust H2 control typically restrict attention to conservative subclasses of valid certificates. It has remained unclear whether collecting more data drives their certified performance toward the true optimum, or whether a persistent gap remains regardless of trajectory length. This paper answers this question for a discrete-time linear system subject to pointwisebounded disturbances. We first show that the widely used matrix S-lemma formulation suffers from a fundamental limitation. Under a bounded state trajectory, its certified performance remains bounded away from the optimum by a gap that does not vanish as the trajectory length grows. Motivated by this finding, we construct a semidefinite-representable family of multipliers that combines nonnegative sample weights with an auxiliary symmetric matrix. This family contains both the matrix S-lemma family and an existing Frobenius-bound family, and it adds only marginal computational overhead per sample. We then derive deterministic trajectory conditions under which this enlarged family yields a certificate close to the optimal performance. We show that these conditions hold with high probability under mild excitation assumptions on the disturbance and the stateinput trajectory. This yields a non-asymptotic bound on the number of samples needed for a prescribed accuracy. It establishes that the certified performance converges to the true optimum even though the disturbance bound stays fixed rather than vanishing. For disturbances uniform over a Euclidean ball, the relative certificate gap decreases at a rate proportional to the inverse square root of the trajectory length, up to logarithmic factors. Numerical experiments corroborate both the persistent conservatism of the matrix S-lemma approach and the predicted convergence rate of the proposed method.

Over the last two decades, significant progress has been made in multi-robot systems (MRS) and human-robot interaction (HRI). In architectural applications, however, robots have mainly served as fabrication tools rather than design collaborators. Integrating robots into design and fabrication processes can yield numerous advantages, including enhanced adaptability at dynamic construction sites and more efficient and creative construction processes. This paper showcases how robots can cooperate with humans through visual computing to design and build X-module and T3-prism tensegrity structures. Instead of following predefined blueprints, the human-robot team relies on generalized procedures and spontaneous decisions, resulting in greater flexibility and an expanded design space. The experiments include: 1) Employing stigmergic mechanisms and visual servoing for robots to adapt to structural changes and human interventions during the fabrication of an X-module tensegrity structure. 2) Incorporating so-called robot design preferences to influence the final form of a T3-prism tensegrity structure. Audio feedback and direct human-robot interactions, such as material handling, make the robotic fabrication process more user-friendly and intuitive for human designers. The presented prototypes illustrate how robots can autonomously adjust during fabrication, promoting collective decision-making between robots and humans in the design process. The paper’s contributions encompass four key aspects: 1) a novel robotic end effector design for manipulating X-module and T3-prism tensegrity modules; 2) a computationally inexpensive visual servoing method for robotic arms to track and interact with building elements; 3) human-in-the-loop improvisational workflows for the design and fabrication of tensegrity structures; 4) proof-of-concept prototypes.

Galaxy mergers play a crucial role in shaping the morphology, the star formation, and the mass growth of galaxies across cosmic time. While mergers have been extensively investigated in the local Universe, the evolution of their frequency and physical properties in the early Universe has yet to be fully understood. In this work, we investigate the role of mergers in a large spectroscopic sample of 1233 galaxies in the range 5 < z < 14 with good detection (S∕Npixel > 3) in the JWST/F444W band, covering six different extragalactic fields (COSMOS, UDS, GOODS-South, GOODS-North, EGS, and Abell2744). We identified mergers from rest-frame optical disturbances in F444W, using a combination of Gini, M20, and asymmetry morphological parameters, which trace more advanced mergers (including also minor mergers) with shorter observability timescales compared to the close photometric pair selection. The observed morphological merger fraction, fm, does not strongly evolve with redshift from z = 0 to z ∼ 8. We find an average merger fraction of fm ∼ 5% for our golden merger condition (Gini+0.14×M20 > 0.33, A> 0.35) tracing major mergers with τobs,golden 30-10 Myr at z = 5-10. This fraction increases to ∼8% for asymmetry mergers (A > 0.35) owing a longer observability timescale, and reaches ∼13% when considering Gini-M20 mergers (Gini+0.14×M20 > 0.33), which trace major+minor mergers. After accounting for the different merger observability timescales, and considering the shorter merger duration in the early Universe, we find that the merger rate is strongly increasing from z = 1 to z = 7 by more than one order of magnitude, averaging ∼2 merger/galaxy/Gyr at redshifts of 5 < z < 10 for major mergers (in agreement with photometric pair studies), and a factor of ∼3 higher for minor+major mergers. We finally performed spectral energy distribution modeling using available HST+JWST photometry to infer stellar masses and star formation rates (SFRs) averaged over multiple timescales, using a nonparametric star formation history. We find that mergers at this cosmic epoch have a significant impact (although significantly lower than at z = 1) on the SFR of galaxies, with an average enhancement by a factor of ∼1.8 compared to isolated galaxies in the same mass and redshift range. This enhancement is higher in the last 10 Myr and for shorter merger timescale indicators, suggesting that mergers trigger star formation through short-lived powerful bursty episodes. Despite this, mergers contribute only by 5–10% to the mass buildup of galaxies in the redshift range explored, suggesting that in situ star formation is the dominant process in galaxy growth at all cosmic epochs.

Rising outdoor temperatures and the increasing frequency of heatwaves raise pressing challenges to the resilience of building cooling systems, particularly in tropical regions where cooling demand is continuous, and dehumidification is essential. This study investigates the impact of future climate scenarios, including typical meteorological years and heatwave years provided by the International Energy Agency’s Annex 80, on the seasonal performance of conventional vapor-compression cooling systems: unitary systems, represented by split units. Numerical simulations were carried out using EnergyPlus to assess the Seasonal Coefficient of Performance (SCOP). Results indicate that split systems performance and optimal sizing strategies are sensitive to climate change, with SCOP degradation between 5% and 10% by the end of the century and up to 12% during severe heatwaves. In contrast, centralized chilled-water systems exhibit greater adaptability through temperature regime optimization. Raising the chilled-water supply temperature by several degrees reduces the refrigerant lift and distribution thermal losses, improving chiller SCOP by up to 5%. However, these benefits come at the expense of reduced dehumidification capacity, highlighting a fundamental balance between energy efficiency and hygrometric comfort. Overall, the results highlight the importance of considering future climate conditions when assessing air-conditioning performance and suggest that elevated chilled-water temperature regimes can improve system efficiency while remaining compatible with thermal and hygrometric comfort within a case-specific operating range. For the simulated chilled-water configuration, higher supply temperatures improved energy performance while maintaining acceptable indoor conditions up to system- and comfort-dependent limits.

Spinodal and binodal decomposition were used here to drive the formation of self-assembled bulk Bi2Se3/CdSe (i.e. topological insulator / trivial semiconductor) heterojunctions. As a first step, we determined the formation conditions of the stable layered compound, whose stoichiometry was quantified to be Bi2.4Cd0.8Se4.4, and we investigated its crystalline, surface chemical and electronic properties. After this, a systematic study allowed us to establish the thermodynamic and kinetic conditions necessary to achieve phase separation of Bi2.4Cd0.8Se4.4 in the spinodal and binodal regimes. In the spinodal bulk heterojunction material the widths of the CdSe and Bi2Se3 lamellar structures were ~25 to 100 nm and ~80 to 130 nm, respectively. In the binodal bulk heterojunction material, we observed drop-like CdSe crystallites ranging in size from ~ 20 nm to 1 m within the Bi2Se3 matrix. Moreover, the junction between Bi2Se3 and CdSe, was found to be atomically abrupt for both spinodal and binodal patterns. This approach offers a facile self-driven one-step alternative procedure to the complex and expensive multi-step artificial growth methods typically used to produce nanostructured all-inorganic bulk heterojunction materials for future applications in the field of solar energy.

This thesis explores the role of carbon in climate-neutral energy systems. Climate mitigation is often framed as the decarbonization of the energy system, but in reality, in a climate-neutral system, carbon would still be present and circulate through remaining fossil fuels, biomass, CO2, synthetic fuels, chemicals, and negative emission technologies. The interactions between these components lead to complex mechanisms, calling for a systemic vision of carbon flows in the energy system.

To address this challenge, this work develops the Energy-Carbon Cycle Framework, which formalises the coupling between carbon sources and sinks under a neutrality constraint. It shows that residual fossil use is a possible system choice only with sufficient availability of carbon sinks. This concept is then translated into practice within the EnergyScope TD energy system model through a method that tracks the carbon flows between the different energy system technologies.

The proposed method is applied to the French energy system under climate neutrality constraints. This future climate-neutral energy system is compared with the national French strategy and other reference prospective documents. The results propose a clear merit order of lignocellulosic biomass use, in which sacrificing biomass to store carbon to reach climate neutrality is prioritised.

Building on this foundation, the thesis explores the specific case of the aviation sector. It is shown that e-bio-fuels are the most optimal pathway to produce sustainable aviation fuels (SAF), although this optimality is subject to uncertainty, which can favour the e-fuel pathway. The production cost of SAF, the total system cost, and the energy required for their production all depend strongly on the selectivity of the Fischer-Tropsch process towards jet fuel.

This work highlights that domestic production of SAF can reduce the need for flexible gas-based electricity production. These results are evaluated for different uncertainties surrounding the energy system, but the impact of interconnection and the recent downward trend in renewable energy CAPEX significantly reduce the initial values, bringing them to almost no effect.

Energy and carbon exchange between countries forces the expansion of the scope of this work to a European energy system, via the EnergyScope Multi-Cells model. To reduce the computational load of such an expansion, spatial and temporal aggregation methods are proposed and validated, leading to a reduction of the model's solve time by approximately 98 % without major change in energy system behaviour.

This new version of the model allows for uncertainty analysis of the European energy system. The robust decision-making method is used to identify carbon management strategies that are robust to uncertainties across multiple metrics, including total cost and life cycle impact assessment. This method particularly underlines that achieving European climate neutrality requires 339â 1018 MtCO2/yr of geological sequestration.

Overall, this work demonstrates that carbon remains a central component of climate-neutral energy systems. Rather than being eliminated, carbon resources must be understood from a systemic perspective, balancing two main roles: fulfilling the demand for carbonaceous sustainable fuels and enabling the system to reach climate neutrality by offsetting carbon sources with carbon sinks.

Understanding turbulence in magnetically confined fusion plasmas is a major element in the reliable design and operation of fusion power plants. Turbulence produces interacting fluctuations ranging from the Larmor radius to the size of the machine, which are notoriously difficult to model. In particular, despite recent advances, the interaction of microturbulence, i.e. turbulence on the scale of the Larmor radius, with macroturbulence, on the scale of the machine size, is not well understood. In order to describe the microturbulence, usually a gyrokinetic ordering is imposed, where the amplitude of the turbulent fluctuations is assumed to be small and separated from the background ($\delta$-f approach). On the other hand, in order to describe the macroturbulence, a drift-kinetic ordering is usually imposed, where the turbulent fluctuations are assumed to have a large spatial extent and large amplitude, with no separation between equilibrium and fluctuating quantities (full-f approach). In this thesis, we combine both orderings and self-consistently derive a comprehensive full-f drift-kinetic and $\delta$-f gyrokinetic model. The standard two-fluid drift-reduced Braginskii model and the $\delta$-f gyrokinetic model are retrieved in the appropriate limits. Then, we use an orthogonal Hermite-Laguerre basis expansion to efficiently include collisions and obtain a numerically efficient model.

Simulations are carried out, first, for a higher-order drift-kinetic model in a linear plasma device showing clear limitations of this model. Simulations using the comprehensive full-f drift-kinetic and $\delta$-f gyrokinetic model are then carried out in the same geometry. A hybrid spectral and finite difference numerical scheme is implemented and the simulations show that the limitations seen in the extended drift-kinetic model are removed. Microturbulence is not present at the large ion-ion collision frequency, however, when collisions are suppressed, the gyrokinetic fields are seen to affect the turbulence.

Stepping up in complexity, we carry out simulations of the comprehensive full-f drift-kinetic and $\delta$-f gyrokinetic model in a tokamak geometry. We use two different levels of resistivity corresponding to increasing the input power. At low power, the simulations share several similarities with the simulations in the linear plasma device. At high power, the formation of a transport barrier at the plasma edge through an increase in the radial electric field is observed while the gyrokinetic fields are dominating the turbulence in the core of the device through universal modes.

Finally, we focus on the boundary conditions of the model. In the vicinity of solid walls, a Debye sheath forms where the quasi-neutrality assumption is violated. Therefore, any global simulation must impose boundary conditions at the sheath entrance. We consistently derive sheath boundary conditions in the case of perpendicular incidence of the magnetic field with the wall. Simulations with these boundary conditions are carried out in a linear plasma device geometry. The sheath boundary conditions are shown to have an impact on the particle balance and equilibrium state of the plasma.

Low-density lipoproteins (LDL) are naturally occurring, monodisperse nanoparticles composed of proteins and lipids with an average diameter in the range of 20 nm. Their biological functions such as cholesterol trafficking and their roles in various diseases have been extensively studied. However, their properties as nanoparticles are seldom discussed. In this thesis, we investigate the formation of a protein corona on LDL, establish methods for its characterization, and explore the use of LDL-protein complex in cancer detection, biomarker discovery and disease monitoring. First, we show that LDL isolated from human serum or plasma carry a protein corona. Polyethylene glycol (PEG)-based precipitation followed by size-exclusion chromatography (SEC) preserves exchangeable proteins associated with LDL, while density-gradient ultracentrifugation largely removes the soft corona and yields LDL whose protein composition is dominated by ApoB-100. The two isolation strategies produce particles with distinct hydrodynamic size, homogeneity, and protein composition. Furthermore, incubation studies with purified proteins show negligible interaction of LDL with human serum albumin and apotransferrin, while immunoglobulin G exhibits only weak association, indicating that corona formation is selective rather than a consequence of indiscriminate adsorption of abundant plasma proteins. Building on this discovery, we focus on the study of LDL together with their protein corona, that we call protein-rich lipoproteins (ProLips), specifically on their potential in cancer detection. The tool we use is a proteomic comparison between samples from cancer patients and sample from healthy donors. Compared with whole-serum proteomics, ProLips proteomics consistently reveals substantially more differentially expressed proteins and provides clearer separation between healthy individuals and patients with melanoma, colon carcinoma, and liver cancer. The reduced contribution of highly abundant plasma proteins improves the detection of disease-associated proteins. Finally, six proteins as a melanoma-associated biomarker set are identified and validated. At last, we evaluate whether ProLips proteomics can monitor disease progression and treatment response. In a melanoma rat model, ProLips protein profiles distinguish different stages of tumor development. We show that in colorectal cancer patients sampled before, during, and after surgery, temporal changes in ProLips composition reflect surgery-associated remodeling, while persistent deviations after surgery are associated with clinical relapse. In liver cancer patients receiving immunotherapy, ProLips proteomics captures individualized treatment-associated changes, and both TMT- and DIA-based analyses reveal consistent biological trends despite differences in individual proteins identified.

The emerging technology of wearable robots is gradually transforming our daily life. Up to 2026, many commericallized exoskeleton products have flourished, including those from companies ReWalk, HAL, ULS Robotics, Kenqing Technologies, ready on market to improve wearer's mobility and endurance. Nearly all the market-available exoskeletons are motor-driven, based on bulky external components, rigid transmission elements, or complex control architectures, which decreases wearing willingness. Developing soft wearable robots can well address some of the challenges of hard exoskeletons, improving wearing comfort, unobtrusiveness, and social ac-ceptance. However, to realize soft wearable robots critically depends on soft, thin, compact, and lightweight actuators to deliver sufficient torque (10 ~ 100 Nm) and displacement (5 ~ 30 cm) while maintaining energy-efficiency and reliability. This thesis investigates soft actuators in textile format (textile actuators) to enable unobtrusive actuation on body. This thesis explores the design, modeling, fabrication, experimental characterization, and application scenarios of fabric actuators based on shape memory alloys (SMAs) and electrostatic clutches (ESClutches). This thesis has three contributions to soft wearable robotics. Firstly, by encapsulating ESClutches and commercially available SMA springs into woven fabrics, we developed an energy-efficient fabric actuator (weighing 55 grams) that can lift 40 N mass and consumes milliwatts power for statically holding the mass. Secondly, using mechanics-informed principles, we developed X-Crossing architecture to enable SMA fabrics of 4.5 grams lifting 1 kg mass with 50% contraction, outperforming published SMA fabrics, including knitted and knotted SMA fabric actuators. Thirdly, we developed variable-stiffness mechanics model for X-Crossing SMA fabric actuator. This model predicts the actuator performances and add understandings to the actuator characteristics, including the peak in its performance curves and fundamental limits on actuator contraction. In this thesis, we also demonstrate the applications of developed fabric actuators. The clutchable fabric actuator mounted on the upper limb of a mannequin lifted 2.6 kilograms of mass, reducing 70 % energy consumption by using ESClutches compared to that without using ESClutches. Using this actuator, we demonstrate a waistband with controllable tightness as exoskeleton anchoring for force transmission to body, and using the ESClutches reduces 80% of energy consumption in defined tasks. We also demonstrate the X-Crossing architectured SMA fabric actuator can be well controlled to bend a mannequin elbow to target angles, and this fabric actuator can be fabricated as wrist sleeve to generate compression up to 13 kPa, and then maintain a residual compression pressure of 5 kPa with zero energy cost.

This thesis concerns the blow-up analysis, and more precisely, the asymptotic decomposition into profiles of solutions to nonlinear partial differential equations. In Chapter 1, we present a unifying framework for finding profile decompositions in Hilbert spaces. The next chapters are then devoted to my publications.

In the second chapter, based on my first publication, we construct solutions to the focusing, energy-critical, nonlinear wave equation in dimension 4 and 5, exhibiting finite-time Type II blow-up precisely at the origin with a single profile and a prescribed polynomial blow-up rate of order -1-v, where v > 1 in 4D and v > 3 in 5D. Such solutions have been constructed by Krieger-Schlag-Tataru in 3D and by Jendrej in 5D. The major difference between dimension 4 and 5 consists in the renormalization procedure. In 4D, we essentially follow the Krieger-Schlag-Tataru scheme developed for the 3-dimensional equation. This scheme has been applied with success for other equations such as the 3D-critical NLS, Schrödinger maps or wave maps. In all of these cases, the polynomial structure of the nonlinearity permits the use of simple algebraic manipulations to control error terms. By contrast, the 5D case requires a modified setup due to the lower regularity of the nonlinearity, which complicates the treatment of nonlinear error terms.

The remaining chapters are based on my second publication. We first provide, in Chapter 3, a modern presentation of classical Lp and Schauder estimates for parabolic equations. Then, in Chapter 4, we consider finite-time and k-equivariant solutions to the harmonic map heat flow from a disk to a sphere. Under general time-dependent, k-equivariant and smooth boundary data, we prove that the profile decomposition at the singular time contains only one bubble. The method relies on the maximum and comparison principle. We also prove a global existence criterion and exhibit solutions blowing up in infinite time for any degree of equivariance. Finally, the appendix presents the profile decomposition for the harmonic map heat flow proved by Struwe and Qing using energy arguments and the Palais-Smale condition.