Longevity Risk Management and Shareholder Value for a Life Annuity Business

The life annuity business is heavily exposed to longevity risk. Risk transfer solutions are not yet fully developed, and when available they are expensive. A significant part of the risk must therefore be retained by the life insurer. So far, most of the research work on longevity risk has been mainly concerned with capital requirements and specific risk transfer solutions. However, the impact of longevity risk on shareholder value also deserves attention. While it is commonly accepted that a market-consistent valuation should be performed in this respect, the definition of a fair shareholder value for a life insurance business is not trivial. In this paper we develop a multi-period market-consistent shareholder value model for a life annuity business. The model allows for systematic and idiosyncratic longevity risk and includes the most significant variables affecting shareholder value: the cost of capital (which in a market-consistent setting must be quantified in terms of frictional and agency costs, net of the value of the limited liability put option), policyholder demand elasticity and the cost of alternative longevity risk management solutions, namely indemnity-based and index-based solutions. We show how the model can be used for assessing the impact of different longevity risk management strategies on life insurer shareholder value and solvency

FGF-2/FGFR1 neurotrophic system expression level and its basal activation do not account for the age-dependent decline of precursor cell proliferation in the subventricular zone of rat brain.

It is largely accepted that neurogenesis in the adult brain decreases with age and reduced levels of local neurotrophic support is speculated to be a contributing factor. Among neurotrophic factors involved on neurogenesis, we focused our attention on the neurotrophic system fibroblast growth factor-2 (FGF-2) and its receptor FGFR1, a potent modulator of precursor cell proliferation. In the present work, we aimed to analyse if potential age-dependent changes of the FGF-2/FGFR1 neurotrophic system may give account for the age-dependent decline of precursor cell proliferation in the neurogenic region of the subventricular zone (SVZ) in the rat brain. Using in situ hybridization and western blotting procedures we examined FGF-2 and FGFR1 expression levels in the SVZ of 20-month-old rats as compared to young adult 3-month-old rats. The results showed that during aging the FGF-2 and its receptor expression levels, both as mRNA and protein, were unchanged in the SVZ. The levels of phosphorylated FGFR1 form did not show significant variations suggesting that also the level of receptor activation does not change during aging. No changes were also observed in the phosphorylation of two FGFR1 related proteins involved in intracellular signaling, the canonical extracellular signal-regulated kinase Erk1/2 and the phospholipase-C\u3b31. Additionally, we could show that also the proliferation rate of stem cells does not change during aging. Taken together, our results show that FGF-2/FGFR1 neurotrophic system expression level and its basal activation do not account for the age-dependent decline of precursor cell proliferation in the rat brain

Background suppression in massive TeO2_2 bolometers with Neganov-Luke amplified light detectors

Bolometric detectors are excellent devices for the investigation of neutrinoless double-beta decay (0$\nu\beta\beta$). The observation of such decay would demonstrate the violation of lepton number, and at the same time it would necessarily imply that neutrinos have a Majorana character. The sensitivity of cryogenic detectors based on TeO$_2$ is strongly limited by the alpha background in the region of interest for the 0$\nu\beta\beta$ of $^{130}$Te. It has been demonstrated that particle discrimination in TeO$_2$ bolometers is possible measuring the Cherenkov light produced by particle interactions. However an event-by-event discrimination with NTD-based light detectors has to be demonstrated. We will discuss the performance of a highly-sensitive light detector exploiting the Neganov-Luke effect for signal amplification. The detector, being operated with NTD-thermistor and coupled to a 750 g TeO$_2$ crystal, shows the ability for an event-by-event identification of electron/gamma and alpha particles. The extremely low detector baseline noise, RMS 19 eV, demonstrates the possibility to enhance the sensitivity of TeO$_2$-based 0$\nu\beta\beta$ experiment to an unprecedented level

Emission-aware Energy Storage Scheduling for a Greener Grid

Reducing our reliance on carbon-intensive energy sources is vital for reducing the carbon footprint of the electric grid. Although the grid is seeing increasing deployments of clean, renewable sources of energy, a significant portion of the grid demand is still met using traditional carbon-intensive energy sources. In this paper, we study the problem of using energy storage deployed in the grid to reduce the grid's carbon emissions. While energy storage has previously been used for grid optimizations such as peak shaving and smoothing intermittent sources, our insight is to use distributed storage to enable utilities to reduce their reliance on their less efficient and most carbon-intensive power plants and thereby reduce their overall emission footprint. We formulate the problem of emission-aware scheduling of distributed energy storage as an optimization problem, and use a robust optimization approach that is well-suited for handling the uncertainty in load predictions, especially in the presence of intermittent renewables such as solar and wind. We evaluate our approach using a state of the art neural network load forecasting technique and real load traces from a distribution grid with 1,341 homes. Our results show a reduction of >0.5 million kg in annual carbon emissions -- equivalent to a drop of 23.3% in our electric grid emissions.Comment: 11 pages, 7 figure, This paper will appear in the Proceedings of the ACM International Conference on Future Energy Systems (e-Energy 20) June 2020, Australi

Critical droplets in Metastable States of Probabilistic Cellular Automata

We consider the problem of metastability in a probabilistic cellular automaton (PCA) with a parallel updating rule which is reversible with respect to a Gibbs measure. The dynamical rules contain two parameters $\beta$ and $h$ which resemble, but are not identical to, the inverse temperature and external magnetic field in a ferromagnetic Ising model; in particular, the phase diagram of the system has two stable phases when $\beta$ is large enough and $h$ is zero, and a unique phase when $h$ is nonzero. When the system evolves, at small positive values of $h$, from an initial state with all spins down, the PCA dynamics give rise to a transition from a metastable to a stable phase when a droplet of the favored $+$ phase inside the metastable $-$ phase reaches a critical size. We give heuristic arguments to estimate the critical size in the limit of zero ``temperature'' ($\beta\to\infty$), as well as estimates of the time required for the formation of such a droplet in a finite system. Monte Carlo simulations give results in good agreement with the theoretical predictions.Comment: 5 LaTeX picture

Population history from the Neolithic to present on the Mediterranean island of Sardinia: an ancient DNA perspective

Recent ancient DNA studies of western Eurasia have revealed a dynamic history of admixture, with evidence for major migrations during the Neolithic and Bronze Age. The population of the Mediterranean island of Sardinia has been notable in these studies –} Neolithic individuals from mainland Europe cluster more closely with Sardinian individuals than with all other present-day Europeans. The current model to explain this result is that Sardinia received an initial influx of Neolithic ancestry and then remained relatively isolated from expansions in the later Neolithic and Bronze Age that took place in continental Europe. To test this model, we generated genome-wide capture data (approximately 1.2 million variants) for 43 ancient Sardinian individuals spanning the Neolithic through the Bronze Age, including individuals from Sardinia{’}s Nuragic culture, which is known for the construction of numerous large stone towers throughout the island. We analyze these new samples in the context of previously generated genome-wide ancient DNA data from 972 ancient individuals across western Eurasia and whole-genome sequence data from approximately 1,500 modern individuals from Sardinia. The ancient Sardinian individuals show a strong affinity to western Mediterranean Neolithic populations and we infer a high degree of genetic continuity on the island from the Neolithic (around fifth millennium BCE) through the Nuragic period (second millennium BCE). In particular, during the Bronze Age in Sardinia, we do not find significant levels of the {“}Steppe{” ancestry that was spreading in many other parts of Europe at that time. We also characterize subsequent genetic influx between the Nuragic period and the present. We detect novel, modest signals of admixture between 1,000 BCE and present-day, from ancestry sources in the eastern and northern Mediterranean. Within Sardinia, we confirm that populations from the more geographically isolated mountainous provinces have experienced elevated levels of genetic drift and that northern and southwestern regions of the island received more gene flow from outside Sardinia. Overall, our genetic analysis sheds new light on the origin of Neolithic settlement on Sardinia, reinforces models of genetic continuity on the island, and provides enhanced power to detect post-Bronze-Age gene flow. Together, these findings offer a refined demographic model for future medical genetic studies in Sardinia

Dark blood late enhancement imaging.

Background Bright blood late gadolinium enhancement (LGE) imaging typically achieves excellent contrast between infarcted and normal myocardium. However, the contrast between the myocardial infarction (MI) and the blood pool is frequently suboptimal. A large fraction of infarctions caused by coronary artery disease are sub-endocardial and thus adjacent to the blood pool. It is not infrequent that sub-endocardial MIs are difficult to detect or clearly delineate. Methods In this present work, an inversion recovery (IR) T2 preparation was combined with single shot steady state free precession imaging and respiratory motion corrected averaging to achieve dark blood LGE images with good signal to noise ratio while maintaining the desired spatial and temporal resolution. In this manner, imaging was conducted free-breathing, which has benefits for image quality, patient comfort, and clinical workflow in both adults and children. Furthermore, by using a phase sensitive inversion recovery reconstruction the blood signal may be made darker than the myocardium (i.e., negative signal values) thereby providing contrast between the blood and both the MI and remote myocardium. In the proposed approach, a single T1-map scout was used to measure the myocardial and blood T1 using a MOdified Look-Locker Inversion recovery (MOLLI) protocol and all protocol parameters were automatically calculated from these values within the sequence thereby simplifying the user interface. Results The contrast to noise ratio (CNR) between MI and remote myocardium was measured in n = 30 subjects with subendocardial MI using both bright blood and dark blood protocols. The CNR for the dark blood protocol had a 13 % loss compared to the bright blood protocol. The CNR between the MI and blood pool was positive for all dark blood cases, and was negative in 63 % of the bright blood cases. The conspicuity of subendocardial fibrosis and MI was greatly improved by dark blood (DB) PSIR as well as the delineation of the subendocardial border. Conclusions Free-breathing, dark blood PSIR LGE imaging was demonstrated to improve the visualization of subendocardial MI and fibrosis in cases with low contrast with adjacent blood pool. The proposed method also improves visualization of thin walled fibrous structures such as atrial walls and valves, as well as papillary muscles

Setting the photoelectron clock through molecular alignment

The interaction of strong laser fields with matter intrinsically provides a powerful tool for imaging transient dynamics with an extremely high spatiotemporal resolution. Here, we study strong-field ionisation of laser-aligned molecules, and show a full real-time picture of the photoelectron dynamics in the combined action of the laser field and the molecular interaction. We demonstrate that the molecule has a dramatic impact on the overall strong-field dynamics: it sets the clock for the emission of electrons with a given rescattering kinetic energy. This result represents a benchmark for the seminal statements of molecular-frame strong-field physics and has strong impact on the interpretation of self-diffraction experiments. Furthermore, the resulting encoding of the time-energy relation in molecular-frame photoelectron momentum distributions shows the way of probing the molecular potential in real-time, and accessing a deeper understanding of electron transport during strong-field interactions

Random-cluster representation of the Blume-Capel model

The so-called diluted-random-cluster model may be viewed as a random-cluster representation of the Blume--Capel model. It has three parameters, a vertex parameter $a$, an edge parameter $p$, and a cluster weighting factor $q$. Stochastic comparisons of measures are developed for the `vertex marginal' when $q\in[1,2]$, and the `edge marginal' when q\in[1,\oo). Taken in conjunction with arguments used earlier for the random-cluster model, these permit a rigorous study of part of the phase diagram of the Blume--Capel model