Synthesis and characterizations of new organic molecules luminescent for applications in lighting and bioimaging

In recent years, devices based on thermally activated delayed fluorescence (TADF) emitters have proven to be the most promising and efficient approach to convert dark triplet states into emissive singlet states. TADF materials are characterized by a small energy gap between the excited singlet state (S1) and the excited triplet state (T1), this gap called ΔEST is generally less than 0.2 eV. As with phosphorescent emitters, purely organic TADF emitters can recruit excitons from both singlet and triplet states for light emission and thus allow to construct OLED devices reaching 100% internal quantum efficiencies (IQE). An important advantage of these emitters is related with their organic molecular skeleton, thus avoiding the problems associated with the use of heavy metal-based organometallic complexes. Thanks to their unique photophysical properties, organic TADF materials are being studied for a wide range of domains, such as in organic light emitting diodes (OLEDs), solar cells, photocatalysis, etc. Furthermore, TADF-based materials have a unique advantage in some imaging techniques due to their longer life than promptly fluorescent materials. These organic compounds are particularly promising in bioimaging applications due to their low cytotoxicity compared to traditional compounds such as lanthanide complexes. In the course of this thesis, the synthesis and photophysical characterization of new organic TADF molecules was carried out, specifically new coumarin and spiro structures, candidates for the construction of new OLED and as non-toxic biomarkers with efficient emissions in the blue-green spectral region

The Value of Integrative Risk Management for Insurance Products with Guarantees

Insurers increasingly offer policies that converge with the products of the capital markets, and they face a need for integrative asset and liability management strategies. In this paper we show that an integrative approach -- based on scenario optimization modeling -- adds value to the risk management process, when compared to traditional methods. Empirical analysis with products offered by the Italian insurance industry are presented. The results have implications for the design of competitive insurance policies, and some examples are analyzed.

Asset and Liability Modeling for Participating Policies with Guarantees

We study the problem of asset and liability management of participating insurance policies with guarantees. We develop a scenario optimization model for integrative asset and liability management, analyze the tradeoffs in structuring such policies, and study alternative choices in funding them. The nonlinearly constrained optimization model can be linearized through closed form solutions of the dynamic equations. Thus large-scale problems are solved with standard methods. We report on an empirical analysis of policies offered by Italian insurers. The optimized model results are in general agreement with current industry practices. However, some inefficiencies are identified and potential improvements are highlighted.

On the slip‐weakening behavior of rate‐ and state dependent constitutive laws

We study the dynamic traction behavior within the cohesive zone during the propagation of earthquake ruptures adopting rate‐ and state‐dependent constitutive relations. The resulting slip‐weakening curve displays an equivalent slip‐weakening distance (D0eq), which is different from the parameter L controlling the state variable evolution. The adopted constitutive parameters (a, b, L) control the slip‐weakening behavior and the absorbed fracture energy. The dimension of the nucleation patch scales with L and not with D0eq. We propose a scaling relation between these two lengthscale parameters which prescribes that D0eq/L ∼ 15

www.Personal_Asset_Allocation.

Today consumers demand delivery of financial services anytime and anywhere, and their needs and desires are evolving rapidly. The World Wide Web provides a rich channel for distributing customized services to a range of clients. An Internet-based system developed by Prometeia S.r.l. for Italian banks—both traditional and e-banks—supports consumers and financial advisors in planning personal finances. The system provides advice on allocating personal assets to fund consumers’ needs, such as paying for a house, children’s education, retirement, or other projects. State-of-the-art models of financial engineering—based on scenario optimization— develop plans that are consistent with clients’ goals, their attitudes towards risk, and the prevailing views on market performance. The system then helps clients to select off-the-shelf financial products, such as mutual funds, to create customized portfolios. Finally, it analyzes the risk of portfolios in terms that are intuitive for laypersons and monitors their performance in achieving the target goals. Four major banks use the system to support their networks of several thousand financial advisors and to reach tens of thousands of clients directly

Scenario Optimization Asset and Liability Modelling for Individual Investors

We develop a scenario optimization model for asset and liability management of individual investors. The individual has a given level of initial wealth and a target goal to be reached within some time horizon. The individual must determine an asset allocation strategy so that the portfolio growth rate will be sufficient to reach the target. A scenario optimization model is formulated which maximizes the upside potential of the portfolio, with limits on the downside risk. Both upside and downside are measured vis- `a-vis the goal. The stochastic behavior of asset returns is captured through bootstrap simulation, and the simulation is embedded in the model to determine the optimal portfolio. Post-optimality analysis using out-of-sample scenarios measures the probability of success of a given portfolio. It also allows us to estimate the required increase in the initial endowment so that the probability of success is improved

Mechanical behaviour and phase transition mechanisms of a shape memory alloy by means of a novel analytical model

The aim of the present paper is to examine both the fatigue behaviour and the phase transition mechanisms of an equiatomic pseudo-elastic NiTi Shape Memory Alloy through cyclic tests (up to 100 loading cycles). More precisely, miniaturised dog-bone specimens are tested by using a customised testing machine and the contents of both austenite and martensite phase are experimentally measured by means of X-Ray diffraction (XRD) analyses. On the basis of such experimental results in terms of martensite content, an analytical model is here formulated to correlate the stress-strain relationship to the phase transition mechanisms. Finally, a validation of the present model by means of experimental data pertaining the stress-strain relationship is performed

Remote Monitoring of Two-State Markov Sources via Random Access Channels: an Information Freshness vs. State Estimation Entropy Perspective

We study a system in which two-state Markov sources send status updates to a common receiver over a slotted ALOHA random access channel. We characterize the performance of the system in terms of state estimation entropy (SEE), which measures the uncertainty at the receiver about the sources' state. Two channel access strategies are considered, a reactive policy that depends on the source behavior and a random one that is independent of it. We prove that the considered policies can be studied using two different hidden Markov models (HMM) and show through density evolution (DE) analysis that the reactive strategy outperforms the random one in terms of SEE while the opposite is true for AoI. Furthermore, we characterize the probability of error in the state estimation at the receiver, considering a maximum a posteriori (MAP) estimator and a low-complexity (decode and hold) estimator. Our study provides useful insights on the design trade-offs that emerge when different performance metrics such as SEE, age or information (AoI) or state estimation error probability are adopted. Moreover, we show how the source statistics significantly impact the system performance