The inclusive production of the $η_c(1S)$, $η_c(2S)$ and $χ_{c}$ charmonium states in $b$-hadron decays is studied with LHCb Run~2 data, corresponding to an integrated luminosity of $5.9~\text{fb}^{-1}$, using charmonia decays to $ϕϕ$ pairs. The production branching fractions of the $χ_{c}(1P)$ states in $b$-hadron decays are measured, using $b \to η_c(1S) (\to ϕϕ) X$ as a normalisation channel, with $X$ indicating any additional particles. The results are \begin{align*} &{\cal{B}} (b \to χ_{c0} X) = (1.34 \pm 0.13 \pm 0.06 \pm 0.37) \times 10^{-3}, &{\cal{B}} (b \to χ_{c1} X) = (1.58 \pm 0.12 \pm 0.09 \pm 0.44) \times 10^{-3}, &{\cal{B}} (b \to χ_{c2} X) = (0.55 \pm 0.08 \pm 0.05 \pm 0.15) \times 10^{-3}, \end{align*} where the first uncertainty is statistical, the second systematic and the last is due to the limited knowledge of externally measured branching fractions. The production branching fraction of $η_c(2S)$ times the branching fraction of its decay into $ϕϕ$ is measured as ${\cal{B}} (b \to η_c(2S) X) \times {\cal{B}} (η_c(2S) \to ϕϕ) = (4.0 \pm 0.6 \pm 0.6 \pm 1.1) \times 10^{-7}$. Furthermore, the mass of the $η_c(1S)$ state is measured to be $M_{η_c(1S)} = 2984.1 \pm 0.5 \pm 0.5$ MeV with the best precision to date.

Residual stresses (RS) are a critical challenge in metal additive manufacturing (AM). This challenge is especially significant in directed energy deposition (DED), where larger part sizes and melt pools, together with heat accumulation and repeated thermal cycling, promote substantial stress accumulation. Control of RS is further complicated by the many tunable process parameters. Existing reviews either isolate individual parameters or cover RS in AM generally, and rarely address how parameters interact to shape the final stress state. This review addresses that gap with a framework that breaks RS formation into sequential steps: process parameters, intermediate variables, thermal drivers, and RS mechanisms. Using this framework, it analyses how changes in individual parameters propagate through the process to the resulting RS, focusing on experimental studies in DED. It then examines energy density as a unifying metric that captures the combined effect of interacting parameters, collecting published data to correlate calculated energy densities with reported RS levels. Normalised enthalpy is also evaluated as a complementary metric that accounts for intrinsic material properties. Beyond parameter optimisation, the review evaluates the effectiveness of in-situ and post-process mitigation strategies. This work consolidates current knowledge and provides a structured foundation for reducing RS in DED-fabricated parts.

A precision measurement of the 𝑊 -boson production cross section is performed using the 𝑊 →𝜇⁢𝜈 decay channel, based on a sample of proton-proton collision data collected by the LHCb experiment at √𝑠 =13  TeV and corresponding to an integrated luminosity of 5.1  fb−1 . The cross section is measured for muons with transverse momentum between 25 and 55 GeV and pseudorapidity between 2.0 and 4.5. The total production cross sections of 𝑊 bosons are measured to be 𝜎𝑊+→𝜇+⁢𝜈=1754.2±1.5±11.8±35.1  pb 𝜎𝑊−→𝜇−⁢ ¯ 𝜈 =1178.1±1.3±9.7±23.6  pb where uncertainties are statistical, systematic, and due to the luminosity determination, respectively. Differential distributions d⁢𝜎𝑊±→𝜇±⁢𝜈/d⁢𝜂𝜇± are also presented. The total and differential cross sections are in good agreement with theoretical predictions at next-to-next-to-leading order in perturbative quantum chromodynamics. This measurement is significantly more precise than previous results in this kinematic regime.

In the mammalian central nervous system (CNS), the ability to regenerate after injury drops sharply in the first weeks after birth, but how this change is reflected in cell morphology and organization is still not fully understood. Here we cultivated cortical cell cultures from the gray short-tailed opossum (Monodelphis domestica) and compared cells derived from early postnatal pups (postnatal day 3-6, "Pyoung") with those from older pups (postnatal day 16-18, "Pold"), which differ in their capacity to regenerate after injury. For each culture, we assessed marker-defined cellular composition using fluorescently labeled markers for neurons, glia, and immature/progenitor cells, and characterized their nanoscale-resolved three-dimensional morphology using label-free scanning ion conductance microscopy (SICM). Pyoung cultures exhibited active change in shape over time, contained a higher proportion of immature SOX2⁺ cells, and grew more neurites (TUJ1⁺) into the lesion site after injury. Moreover, Pold cultures showed more stable soma size (e.g., thickness, area, volume), a larger astroglial (SOX9⁺) population early in culture, and a glia-dominated lesion response. These early astroglia included more immature or reactive (vimentin⁺) astrocytes. SICM further revealed cellular bridges across the lesion, ridges left in the substrate by the injury, and aligned neurite outgrowth. Across all measurements, changes in molecular markers were associated with corresponding changes in cell morphology. This multimodal combination of fluorescence labeling and SICM therefore relates marker-defined cellular composition to physical organization across micro- and nanoscale features during and after postnatal in vitro development.

Microfluidic devices control fluid flow and the cellular microenvironment, and their fabrication usually relies on photolithography in a clean room. For devices with features of hundreds of micrometers to millimeters, this route is slow and costly, especially during prototyping, when the design changes after each test. Here, we describe and benchmark a workflow to fabricate polydimethylsiloxane (PDMS) devices from laser-cut master molds, with equipment accessible to most biology laboratories. We cut three inexpensive materials, poly(methyl methacrylate) (PMMA), polystyrene and polyvinyl chloride (PVC) tape, over a grid of laser power and speed and measured each cut by scanning electron microscopy. Cut depth and width increased line-arly with the laser energy delivered per unit length, which gives a simple rule to choose the settings for each material. We then bonded the PDMS replicas to glass without a plasma cleaner, by stopping curing early, once the replica could be demolded, and completing it in contact with the glass. Without any surface treatment, these devices held up to about 400 mbar; activating the glass with a handheld corona device raised this to about 900 mbar, enough for perfusion. The master material set the surface of the device: PMMA gave smooth replicas, whereas PVC tape gave rough walls. A three-channel device molded on PMMA held two cell-laden gels in place with phase guides and supported the co-culture of cancer cells and fibroblasts under perfusion. Further analysis of flow laminarity and different mixer designs confirmed the robustness of this method. This workflow takes a digital design to a working de-vice within a day and lets biology laboratories adapt microfluidic devices to their experiments without the need of a clean room.

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.

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 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.

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.

Barrel cortex has a characteristic somatotopic map, where each whisker maps to a single barrel. Each cortical column therefore has a known principal whisker input, so a functional response can be studied against structure identified in advance. Individual barrels are visible in the CCFv3 average template, but the parcellation stops at area and layer. Anatomically detailed modelling of the full region had been done in rat, and no model of mouse barrel cortex reached this level of detail. In this thesis, I identified the features that distinguish barrel cortex, and supplied them to a model built in atlas space with the barrel columns annotated.

Firstly, I segmented 33 barrels in CCFv3, and used an area-preserving flatmap to annotate the barrel columns representing the posteromedial barrel subfield. The resulting columns follow the curvature of the cortex, span full depth and never overlap. The annotations are released with the flatmap as a tool for data integration and analysis.

Then, I used this enhanced atlas space and a pipeline validated in rat non-barrel somatosensory cortex to build a detailed model. The model contains 33 barrel columns, approximately 230,000 neurons and around 357 million synapses, drawn from 60 morphological and 15 electrical types. Every inhibitory neuron additionally carries a molecular class, so the model can be compared against mouse measurements directly. The connectome is built from anatomy alone, with no rule imposing how likely one cell type is to connect to another. I extended the pipeline with morphological synthesis, generalised electrical models and a new set of thalamocortical projections, with VPM confined to individual barrels and POm spread across the field.

In barrel cortex, layer 4 dendritic trees grow preferentially towards, and remain within, the barrel that carries their principal whisker input. Dendritic polarity has been described in individual cell types, but not measured across them. To address this, I curated dendritic reconstructions from mouse barrel cortex and applied the same descriptors to every cell, so classes can be ranked against one another. Polarity is class-dependent and concentrated in layer 4, in spiny stellate cells, non-Martinotti somatostatin neurons and parvalbumin neurons. I used the result to build two models differing in a single property of basal dendritic synthesis: one polarised, one symmetric. Finally, I ran in silico experiments on a 3x3 grid of barrel columns and the associated septum, with C2 as the principal column throughout. I simulated three experimental contexts: the quiet and whisking brain states, and active touch of the C2 whisker. Membrane potential and spikes were recorded from every neuron, with the afferent connectivity of each known. The model reproduces patterns reported in mouse: the laminar sequence of the touch response, the recruitment order of the molecular classes, and their dependence on brain state.

We decomposed the spiking response using cyclicity analysis and retained two components. The two modes have distinct spatial profiles: the first is focused on the principal column, while the second crosses the septum and the neighbouring barrels. The same decomposition applied across the two circuits divides the signal into a common and a contrast plane. The contrast plane isolates the unique response contributions of each circuit. Layer 4 dendritic polarisation sharpens the touch response in space and advances it in time.