4 Contributo in atti di convegno (Proceedings)

4 Contributo in atti di convegno (Proceedings): [28968] Home page macrotipologia

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4.1a Atto convegno Rivista 2639
4.1b Atto convegno Volume 21959
4.2 Abstract in Atti di Convegno 3429
4.3 Poster 846
4.4 Intervento a convegno non pubblicato 95

Prodotti recenti

Reduction of the asymptotic prefactors for an optimally bounded quantum state preparation algorithm

The preparation of arbitrary n-qubit quantum states is a cross-cutting subroutine for many quantum algorithms, and the effort to reduce its circuit complexity is a significant challenge. In the literature, the quantum state preparation algorithm by Sun et al. is known to be optimally bounded, defining the asymptotically optimal width-depth trade-off bounds with and without ancillary qubits. In this work, a simpler algebraic decomposition is proposed to separate the preparation of the real par...

Exact Quantum State Preparation with the Standard Recursive Block Basis

Variational approaches to Quantum State Preparation (QSP) allow for low-depth and structured circuit ansatz, at the cost of non-convex optimization landscapes and barren plateaus that severely limit scalability. In contrast, exact synthesis methods typically involve exponential growth in the number of independent parameters, leading to a rapid increase in circuit depth. In this work, it is shown that the algebraic properties of the Standard Recursive Block Basis (SRBB) can partially overcome ...

Structure-Guided Discovery of Selective Indolizine-Based HDAC6 Inhibitors

Histone deacetylase 6 (HDAC6) is a cytoplasmic zinc-dependent epigenetic enzyme that mainly deacetylates non-histone proteins, which emerged as a novel molecular target to treat neuroinflammation. HDAC inhibitors have a general pharmacophoric architecture comprising a cap group (CAP), a linker region, and a zinc-binding group (ZBG), which corresponds to a hydroxamic acid for most ligands. However, all the approved inhibitors lack isoform selectivity and are therefore linked to off-target e...

Improved Embedded Structural Health Monitoring via High-Resolution Spectral Analysis Using a MEMCF-based Algorithm

Structural Health Monitoring (SHM) systems based on modal parameters often suffer from sensitivity to environmental and operational variability, limiting their ability in detecting structural alterations. Recently, the Modal Electro-Mechanical Coupling Factor (MEMCF), obtained from piezoelectric sensors operated under different electrical boundary conditions, has been recognized as a more robust damage-sensitive feature. This work investigates the effectiveness of the application of an enhanc...

Machine Learning enhanced e-tongue for the characterization of a new paracetamol-based formulation for pediatric delivery

The development of palatable pediatric formulations of paracetamol remains a major pharmaceutical challenge due to its intrinsic bitter taste and the limited availability of well accepted solid dosage forms for children. This work presents a machine learning enhanced electronic tongue platform for the characterization of two newly developed dextrin based granulated formulations designed for pediatric delivery. A portable and wireless dual channel potentiostat was employed to acquire different...

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