This paper proposes a real-time distributed operational architecture to coordinate integrated transmission and distribution systems (ITD). At the distribution system level, the distribution system operator (DSO) calculates the aggregated flexibility of all controllable devices by power-energy envelopes and provides them to the transmission system operator (TSO). At the transmission system level, a distributed nonlinear model predictive control (nmpc) approach is proposed to coordinate the economic dispatch of multiple TSOs, considering the aggregated flexibility of all distribution systems. The subproblems of the proposed approach are associated with different TSOs and individual time periods. In addition, the aggregated flexibility of controllable devices in distribution networks is encapsulated, re-calculated, and communicated through the power-energy envelopes, facilitating a reduction in computational complexity and eliminating redundant information exchanges between TSOs and DSOs, thereby enhancing privacy and security. The framework's effectiveness and applicability in real-world scenarios are validated through simulated operational scenarios on a summer day in Germany, highlighting its robustness in the face of significant prediction mismatches due to severe weather conditions.

Background: Arthrodesis of the first metatarsophalangeal joint is an effective treatment of advanced hallux rigidus. Numerous options have been described for performing this intervention. The aim of this study was to evaluate the outcomes following a consistent surgical technique of joint preparation with hand tools and fixation with 2 crossed screws and a dorsal compression plate. Methods: Thirteen patients (16 feet) who underwent primary isolated arthrodesis of the first metatarsophalangeal joint between March 2019 and June 2021 were available for clinical, radiologic, and pedobarographic evaluation at a minimum of 12 months after surgery. American Orthopaedic Foot & Ankle Society scores, numerical pain rating scale, the radiologic hallux valgus and intermetatarsal 1-2 angles as well as the distribution of plantar pressure during gait were compared between the pre- and postoperative conditions. Results: After an average follow-up period of 26 months, union was achieved in all cases and the mean AOFAS score raised significantly by 39 points. All the patients were satisfied with the result. Only 1 patient complained of mild residual pain at walk. Hardware removal was performed in 2 cases. The mean hallux valgus angle dropped from 12.3 to 6.3 degrees. The mean postoperative dorsiflexion angle was 21.6 degrees. After the procedure, peak pressure was significantly higher beneath the first metatarsal head and heel, whereas pressure-time integral was significantly lower beneath the hallux and medial lesser toes. Conclusion: Arthrodesis of the first metatarsophalangeal joint with 2 crossed screws and a dorsal compression plate is a safe and effective treatment of advanced hallux rigidus. This procedure provides adequate pain relief and functional improvement of gait. Level of Evidence: Level IV, therapeutic, retrospective case series.

In recent years organic–inorganic hybrid halide perovskites nanocrystals have made a remarkable impact in display color converting layer application. However, lead toxicity and stability issues always pose arduous challenges. In this regard, the incorporation of a suitable metal ion to reduce toxicity and enhance stability is a widely tested method. In this study, we used a simple ligand-assisted reprecipitation (LARP) technique to simultaneously introduce metal ion and halide ion substitution by synthesizing MAPb1-xZnxBr3-2xCl2x nanocrystals (NCs). Being eco-friendly with a smaller ionic radius than lead ion, zinc metal ion was chosen as a substitute. With the variation of Zn2+ concentration, the highest quantum yield of 95 % was recorded with an emission width of 21 nm. Temperature-dependent photoluminescence (PL) studies revealed the higher optical phonon-exciton interaction after Zn2+ incorporation leading to radiative transition in NCs. Variation of PL peak energy with temperature revealed the reduced thermal chromaticity of Zn2+ incorporated NCs making them suitable for display application. Further, these NCs maintained a stable cubic structure and luminescence up to 150 °C, indicating higher thermal stability. The MAPb0.9Zn0.1Br2.8Cl0.2 (x = 0.1 or 10 mol%) NCs embedded in PMMA (poly (methyl methacrylate) polymer matrix coated LED emits narrow width, green light with color coordinate (0.15, 0.79), which is closer to green coordinate (0.17, 0.79) in Rec.2020. This helps to reproduce close to 97 % color gamut of Rec.2020. This research paves the way for finding less toxic and stable green light-emitting materials instead of cadmium-based molecules.

The identification of red, apparently massive galaxies at z > 7 in early James Webb Space Telescope (JWST) photometry suggests a strongly accelerated time line compared to standard models of galaxy growth. A major uncertainty in the interpretation is whether the red colors are caused by evolved stellar populations, dust, or other effects such as emission lines or active galactic nuclei (AGNs). Here we show that three of the massive galaxy candidates at z = 6.7–8.4 have prominent Balmer breaks in JWST/NIRSpec spectroscopy from the RUBIES program. The Balmer breaks demonstrate unambiguously that stellar emission dominates at λ rest = 0.4 μm and require formation histories extending hundreds of millions of years into the past in galaxies only 600–800 Myr after the big bang. Two of the three galaxies also show broad Balmer lines, with Hβ FWHM > 2500 km s−1, suggesting that dust-reddened AGNs contribute to, or even dominate, the spectral energy distributions of these galaxies at λ rest ≳ 0.6 μm. All three galaxies have relatively narrow [O iii] lines, seemingly ruling out a high-mass interpretation if the lines arise in dynamically relaxed, inclined disks. Yet the inferred masses also remain highly uncertain. We model the high-quality spectra using Prospector to decompose the continuum into stellar and AGN components and explore limiting cases in stellar/AGN contribution. This produces a wide range of possible stellar masses, spanning M ⋆ ∼ 109−1011 M ⊙. Nevertheless, all fits suggest a very early and rapid formation, most of which follow with a truncation in star formation. Potential origins and evolutionary tracks for these objects are discussed, from the cores of massive galaxies to low-mass galaxies with overmassive black holes. Intriguingly, we find all of these explanations to be incomplete; deeper and redder data are needed to understand the physics of these systems.

Polynomial commitments schemes are a powerful tool that enables one party to commit to a polynomialpof degreed, and prove that the committed function evaluates to a certain valuezat a specified pointu, i.e.$p(u) = z$, without revealing any additional information about the polynomial. Recently, polynomial commitments have been extensively used as a cryptographic building block to transform polynomial interactive oracle proofs (PIOPs) into efficient succinct arguments. In this paper, we propose a lattice-based polynomial commitment that achieves succinct proof size and verification time in the degreedof the polynomial. Extractability of our scheme holds in the random oracle model under a natural ring version of the BASIS assumption introduced by Wee and Wu (EUROCRYPT 2023). Unlike recent constructions of polynomial commitments by Albrecht et al. (CRYPTO 2022), and by Wee and Wu, we do not require any expensive preprocessing steps, which makes our scheme particularly attractive as an ingredient of a PIOP compiler for succinct arguments. We further instantiate our polynomial commitment, together with the PIOP (EUROCRYPT 2020), to obtain a publicly-verifiable trusted-setup succinct argument for Rank-1 Constraint System (R1CS). Performance-wise, we achieve$17$MB proof size for$2^{20}$constraints, which is$15$X smaller than currently the only publicly-verifiable lattice-based SNARK proposed by Albrecht et al.

As it reveals the increasing complexity of the contemporary world, the socio-ecological transition demands a renewal of our gaze. By observing to imagine and drawing to narrate, architects and urbanists shape space through its representations and narratives, accompanying societies in their quest to find their place in the world. In this regard, cartography is an essential project tool for spatial designers, allowing them to sketch out possibilities. However, maps have long promoted a conception of inhabitability closely linked to technical control of the environment, embodying a parametric and anthropocentric gaze designed for a single subject: the human being. Today, socio-ecological challenges highlight the presence of other subjects who, also involved in the transformation of cities and territories, prove our relationships of coinhabitations. This paradigm shift therefore calls for a re-invention of our urban and territorial imaginaries, a re-writing of our narratives of inhabiting, and a re-thinking of our cartographic practices and gazes, in order to finally read the geo-eco-sociological realities of the Earth. By proposing a new narrative based on coexistence, the research supports the urgent need to re-present the conditions of our being-in-the-world in order to understand the dual nature - social and ecological - of the contemporary crisis.

Through what processes of re-presentation can the narrative of inhabitability evolve into a narrative of co-inhabitability?

To address this question, the research proposes a series of cartographic narratives to help interpret and conceptualize territories in transition, according to their potential conditions of coinhabitability. These conceptual and methodological explorations - guided by the research hypothesis that reconsiders the concept of territory as Territory-Subject - reveal the dynamic and evolving nature of territories both in space and time. The Atlas thus emerges as an obvious methodological choice. By combining approaches and diversifying themes, it brings together heterogeneous materials in dialogue. As a practical tool, the Atlas enables us to sketch out a new territorial narrative of coinhabitability, supported by the production of hybrid cartographies. The narrative and cartographic explorations re-present two territories, Geneva and Paris, which constitute both practical terrains and supports for analysis. Integrated into the research, these exercises contribute to the development of the new gaze required by the socio-ecological transition. They also offer a critical lever for de-constructing and re-interpreting existing cartographic practices, thus paving the way for an Atlas of the new gaze.

The urban landscape is in flux. Traffic congestion, environmental concerns, and a growing desire for flexible transportation options are pushing cities to rethink mobility. Mobility-on-Demand (MoD) systems, such as Uber and Lyft, offer a promising opportunity by linking passenger requests with available vehicles through smartphone applications. However, the growth of these services raises concerns regarding congestion and emissions, necessitating advanced operational strategies. This dissertation investigates the integration of automated vehicles (AVs) within MoD systems to enhance fleet coordination and overall service efficiency. It addresses two key challenges: empty vehicle repositioning and ride-pooling route planning. The research focuses on innovative methods to capture the complex relationship between passenger demand and vehicle supply in dynamic mobility systems, proposing advanced control algorithms to optimize fleet operations.

This dissertation includes two main parts. In Part I, a novel distributed coverage control scheme is introduced to guide idle vehicles to high-demand areas. Initially formulated in continuous space and further extended to a graph-based representation which better captures the nature of urban road networks, the method treats the repositioning challenge as an area coverage problem, aligning vehicle distribution with passenger demand. Further, a hierarchical framework is developed to coordinate vehicle repositioning at both macroscopic and microscopic scales. At the higher level, a data-driven predictive control algorithm is mainly described to manage inter-regional vehicle transfers, while the lower level leverages node-level position guidance to control individual vehicle movements. This framework effectively coordinates between the actions of the high-level controllers, which manage aggregated traffic components, and the self-governance of individual vehicles at the lower level. Part II extends the study to ride-pooling systems, where vehicles serve multiple passengers via one pooled trip. A theoretical and numerical study validates the potential benefits of detouring partially-occupied vehicles, which enhances their likelihood of matching with additional passengers. The pool-match probability between passengers and one partially occupied vehicle is modeled. Building on this foundation, a Mixed Integer Linear Programming (MILP) algorithm is developed to construct optimal detour paths by evaluating candidate road segments. It can adapt to fluctuating demand and traffic conditions. To evaluate the proposed methods, an operational, agent-based Mobility-on-Demand simulator is implemented, enabling analysis under diverse experimental scenarios. Simulation results demonstrate significant improvements, including a higher request answer rate, reduced waiting times, minimized empty travel distances, and enhanced profitabilityâ achieving a win-win-win outcome for customers, service providers, and the environment.

Catalytic hydrogenation stands out as a powerful tool for the atom-economical transformation of unsaturated systems. Nitrogen heterocycles are widespread in organic chemistry, they are found in many natural products and exhibit notable biological activities. Among them, piperidine is the most commonly encountered saturated heterocycle in alkaloids and drug discovery. Its high sp3 carbon-content contributes to higher drug-success rate and enables access to broader chemical space, escaping from traditionally flat sp2-rich drug molecules. Piperidines are notoriously difficult to access scaffolds and there does not seem to be a single strategy that would enable their streamlined synthesis. In contrast, pyridines are very easy to access and represent a highly modulable core, thus hydrogenation provides a simple way to access complex piperidines from readily available pyridines. However, the hydrogenation of pyridines remains underexplored compared to other heterocycles and most reports rely on a three-step strategy involving activation, hydrogenation and deprotection to access piperidines. Our first objective focused on the development of a catalytic system that would enable pyridine hydrogenation without the need for prefunctionalization. We found that, using an air and moisture stable C,N-cyclometalated iridium complex with a strong acid enabled the hydrogenation of a broad scope of (highly) substituted pyridines. Our method tolerates a large range of functional groups delivering unique and sometimes unprecedented functional group combinations on the piperidine ring, allowing fast access to new chemical space. We then imagined a new design of chiral catalysts that showed good promises in the enantioselective hydrogenation of pyridines. A library of chiral iridium complexes was synthesized and tested to assess what substitution could improve the catalyst performance. Further ligand design will need to be investigated in order to improve the catalyst efficiency and enantio-induction. The hydrogenation of complex nitrogen-containing-heterocycles was then investigated using the previously established methodology. This allowed us to access many piperazines under mild conditions and to explore the hydrogenation of pyridazines to piperidazines, without hydrogenation of the sensitive N-N bond. Several bicyclic systems were also readily hydrogenated, giving access to tetrahydronaphthyridines, tetrahydroazaindoles or tetrahydropyrrolo[1,2-b]pyridazines.

Clonal hematopoiesis of indeterminate potential (CHIP) and myelodysplastic syndromes (MDS) are disorders associated with clonal expansion within the hematopoietic system that can result in cytopenias, increased risk of cardiovascular and autoimmune disease and progression to acute myeloid leukemia (AML). Multiple recent investigations into hematopoietic malignancies such as multiple myeloma (MM) and AML leveraging single-cell transcriptomics to investigate the tissue at cellular resolution have highlighted the importance of the bone marrow microenvironment in creating favorable conditions for mutant cells and promoting disease progression and relapse. However a detailed understanding of how various bone marrow niches are perturbed in CHIP and MDS is missing. An ancillary, but important technical question related to single-cell profiling of cancer tissues is accurate discrimination of mutant cells from their non-malignant counterparts. This is not always straightforward, particularly in the context of blood cancers, because of a lack of definitive features between the two on the level of RNA expression or cell surface markers. The aim of this thesis is to provide a detailed characterization of how the bone marrow niche is affected in CHIP and MDS and how these alterations might contribute to pathogenesis of these conditions. We first describe SpliceUp, a novel computational method for identifying cells with mutations in splicing factor genes, which is a common feature of various blood cancers, including MDS, in single-cell transcriptomic data. Next we provide a detailed bone marrow niche characterization of healthy controls, CHIP and MDS patients using a combination of bulk and single-cell transcriptomics, proteomics, cell sorting and imaging techniques. We highlight several important features associated with inflammatory changes in the bone marrow in CHIP and MDS, such as alteration in stromal and T cell composition and emergence of inflammatory MSCs (iMSCs) and IFN-response T cells restricted to the disease conditions. Our findings indicate a set of common inflammatory changes in the niche partially overlapping with existing findings in AML and MM, as well as certain unique features like residual expression of HSPC-support genes in iMSC specific to our MDS samples. This work provides a general characterization of the bone marrow microenvironment in CHIP and MDS and puts it in the context of existing knowledge about other hematological malignancies. It highlights the importance of the bone marrow niche in these disorders and provides a reference for future studies targeting the individual components of this niche.

Non-regular or irregular statistical problems are those that do not satisfy a set of standard regularity conditions that allow useful theoretical properties of inferential procedures to be proven. Non-regular problems are prevalent; a classical example is the Gaussian mixture model, while more recently, the advent of machine learning has introduced models that are highly non-regular as well as black-box. In this thesis, we make some contributions to non-regular statistical inference. Our framework is likelihood-based; we give an overview of likelihood theory in Chapter 1.

In Chapter 2, we study universal inference, a method proposed by~\citet{Wasserman16880} that can construct finite-sample level $\alpha$ tests with minimal regularity conditions. We identify three sources of the resulting loss of power in the normal case, as a trade-off to this great generality. We show that universal inference becomes catastrophically conservative as the number of nuisance parameters grows, and propose a correction factor to mitigate this conservativeness while maintaining finite-sample level $\alpha$ error control. We demonstrate the viability of the correction factor on the non-regular problem of testing for the number of components in a two-component Gaussian mixture model. We also study the $K$-fold variant of universal inference and caution against using certain splits that lead to degenerate statistics.

In Chapter 3, we apply universal inference to construct model confidence sets with finite-sample coverage guarantees, which we dub universal model confidence sets (UMCS). We study the asymptotic properties of UMCS and establish its ability to include true and correct models and exclude wrong ones. We examine the application of the quasi-reverse information projection (qRIPR) to mitigate the conservativeness of UMCS, and study some cases where the application of qRIPR maintains the e-value property of the universal inference statistics, a property central to its error-controlling feature. We test the performance of UMCS to pick out signal covariates on a high-dimensional gene example.

In Chapter 4 we study discrete profiling, an extension of profile likelihood through the introduction of discrete nuisance parameters that index different functional forms modelling uncertainty. We extend the phenomenon of an observed bias in mis-specified normal linear models to a general one using asymptotic theory, and examine the ability of the discrete profiling algorithm to asymptotically detect mis-specified and slightly mis-specified models. We derive an expanded form for the discrete profile likelihood statistic and study its asymptotic properties under different cases of mis-specification. We corroborate our theory on the task of finding the best Student's $t$ density to model a normal density.

We conclude in Chapter 5 and discuss directions for future work.