296 research outputs found
Modelling and Testing Behavior in Applications to Climate Change.
ROSSELLA BARGIACCHI starts her concluding chapter as follows. It has been our choice in this work to investigate from an economic perspective the question of the optimal extent of climate change prevention. We have therefore chosen an abstract approach to analyze the problem of giving proper ¿rational¿ foundation to the choice of abatement targets, taking into account relevant cognitive and cooperative issues that characterize the climate change problem. The definition of ¿optimal¿ abatement targets involves two conceptually different kinds of economic issues: determining the value of prevention on one side; and implementing international environmental agreements on the other hand. These two issues are deeply correlated: in the case of climate change, the perceived value of prevention for one policy actor depends among other things also on the degree of coordination expected at the international level; similarly, the attractiveness of cooperation depends crucially on the perceived costs and benefits from prevention. Methodologically, however, determining the value of prevention involves the use of very different instruments and concepts than the discussion on international cooperation. For this reason the content of the dissertation can be divided into two parts. Part one is made up by chapters 1 to 3 and it is dedicated to one-agent problems under uncertainty. Part two to is made up by chapters 4 and 5 and concentrates on multi-agents models useful for analyzing the issue of international cooperation.
Tensions with the flat CDM model from high-redshift cosmography
The longstanding search for the cosmological model that best describes the
Universe has been made more intriguing since the recent discovery of the Hubble
constant, , tension observed between the value of from the
Cosmic Microwave Background and from type Ia supernovae (SNe Ia). Hence, the
commonly trusted flat CDM model is under investigation. In this
scenario, cosmography is a very powerful technique to investigate the evolution
of the Universe without any cosmological assumption, thus revealing tensions
between observational data and predictions from cosmological models in a
completely model-independent way. We here employ a robust cosmographic
technique based on an orthogonal logarithmic polynomial expansion of the
luminosity distance to fit quasars (QSOs) alone and QSOs combined with
Gamma-Ray Bursts (GRBs), SNe Ia, and Baryon Acoustic Oscillations. To apply
QSOs and GRBs as probes we use, respectively, the Risaliti-Lusso relation
between ultraviolet and X-ray luminosities and the ``Dainotti GRB 3D relation"
among the rest-frame end time of the X-ray plateau emission, its corresponding
luminosity, and the peak prompt luminosity. We also correct QSOs and GRBs for
selection biases and redshift evolution and we employ both the traditional
Gaussian likelihood and the newly discovered best-fit likelihoods for each
probe investigated. This comprehensive analysis reveals a strong tension () between our data sets and the flat CDM model proving the
power of both the cosmographic approach and high-redshift sources, such as QSOs
and GRBs, which can probe the Universe at early epochs.Comment: 13 pages, 4 figures, 4 tables. Comments are welcome. Accepted for
publication in MNRA
energetic and exergetic analysis of an innovative plant for the production of electricity and substitute natural gas
Abstract The increasing penetration of intermittent and aleatory RES such as photovoltaics and wind power poses new challenges in terms of grid stabilization. Surplus electric energy needs to be stored, if not curtailed. From this point of view, chemical storage can pave the way for a long-term shift between demand and production, together with sector interconnection. Hydrogen as an energy vector has been deeply studied but it has difficulties in asserting itself due to its low energy density at environmental conditions and lack of infrastructure. In previous papers, an innovative plant for the conversion of biomass and fluctuating electric power into substitute natural gas and stable electricity has been designed and analysed in terms of its overall performances. The adoption of an electrolyser for hydrogen production allows to use part of the oxygen for the biomass gasification and the syngas oxy-combustion. The resulting combustion products have high carbon dioxide concentration, which avoids energy consuming separation equipment. This paper analyses in detail the plant performances in terms of energetic and exergetic efficiencies, components by components. The plant is simulated with the commercial software AspenONE® V9. Losses allocation and optimum operating conditions are identified. The proposed heat recovery strategies allow consistent energy savings, making this plant competitive with other energy storage conversion devices in terms of energy efficiency
Molecular Dissection of Breast Luminal Transcription Networks
During mammary development, cellular differentiation and lineage commitment to various epithelial and mesenchymal cell types are driven by hormonal and paracrine signaling mechanisms. Understanding mechanisms that govern differentiation into distinct cell populations is critically important for a complete understanding of development and breast tumorigenesis. Previous studies have shown that retroviral transduction of fibroblasts with four transcription factors can initiate the conversion of a somatic cell into an embryonic stem cell-like state with capabilities of differentiating into cell types of all three germ layers. The goal of my thesis work was to determine whether mammary specific transcription factors (TFs) could directly induce transdifferentiation to an ER+/luminal cell phenotype starting with mouse embryonic fibroblasts via an iPS-type approach. After screening 9 candidate TFs for their abilities to induce various epithelial-specific and breast-specific attributes, we focused subsequent efforts on ESR1, FOXA1, PGR, and GATA3. In human mammary epithelial cells, ectopic overexpression of these TFs had both unique and overlapping contributions toward inducing the expression of genes responsible for luminal differentiation. Combining these TFs in fibroblasts created combinations that produced a luminal progenitor phenotype as defined by gene expression histological markers for epithelial/breast development and functionality. Examination of the gene expression patterns induced by these combinations using a classifier of differentiation status identified several genes that drive a transition toward the luminal subtype. Since there are presently no cell lines or mouse models of luminal A/ER+ breast cancers, the creation of such of a line would be of tremendous value.Doctor of Philosoph
Gamma-Ray Bursts, Quasars, Baryonic Acoustic Oscillations, and Supernovae Ia: new statistical insights and cosmological constraints
The recent Hubble constant, , tension is observed
between the value of from the Cosmic Microwave Background (CMB) and
Type Ia Supernovae (SNe Ia). It is a decade since this tension is excruciating
the modern astrophysical community. To shed light on this problem is key to
consider probes at intermediate redshifts between SNe Ia and CMB and reduce the
uncertainty on . Toward these goals, we fill the redshift gap by employing
Gamma-Ray Bursts (GRBs) and Quasars (QSOs), reaching and ,
respectively, combined with Baryonic Acoustic Oscillations (BAO) and SNe Ia. To
this end, we employ the ``Dainotti GRB 3D relation" among the rest-frame end
time of the X-ray plateau emission, its corresponding luminosity, and the peak
prompt luminosity, and the ``Risaliti-Lusso" QSO relation between ultraviolet
and X-ray luminosities. We inquire the commonly adopted Gaussianity assumption
on GRBs, QSOs, and BAO. With the joint sample, we fit the flat Cold
Dark Matter model with both the Gaussian and the newly discovered likelihoods.
We also investigate the impact of the calibration assumed for \textit{Pantheon}
and \textit{Pantheon +} SNe Ia on this analysis. Remarkably, we show that only
GRBs fulfill the Gaussianity assumption. We achieve small uncertainties on the
matter density parameter and . We find values compatible
within 2 with the one from the Tip of the Red Giant Branch. Finally,
we show that the cosmological results are heavily biased against the arbitrary
calibration choice for SNe Ia.Comment: 17 pages, 6 figures, 1 table, accepted in MNRA
A bias-free cosmological analysis with quasars alleviating H tension
Cosmological models and their parameters are widely debated because of theoretical and observational mismatches of the standard cosmological model, especially the current discrepancy between the value of the Hubble constant, H, obtained by Type Ia supernovae (SNe Ia), and the cosmic microwave background radiation (CMB). Thus, considering high-redshift probes like quasars (QSOs), having intermediate redshifts between SNe Ia and CMB, is a necessary step. In this work, we use SNe Ia and the most updated QSO sample, reaching redshifts up to z ∼ 7.5, applying the Risaliti–Lusso QSO relation based on a nonlinear relation between ultraviolet and X-ray luminosities. We consider this relation both in its original form and corrected for selection biases and evolution in redshift through a reliable statistical method also accounting for the circularity problem. We also explore two approaches: with and without calibration on SNe Ia. We then investigate flat and nonflat standard cosmological models and a flat CDM model, with a constant dark energy equation-of-state parameter w. Remarkably, when correcting for the evolution as a function of cosmology, we obtain closed constraints on Ω using only noncalibrated QSOs. We find that considering noncalibrated QSOs combined with SNe Ia and accounting for the same correction, our results are compatible with a flat ΛCDM model with Ω = 0.3 and H = 70 km s Mpc. Intriguingly, the H values obtained are placed halfway between the one from SNe Ia and CMB, paving the way for new insights into the H tension
Reduced uncertainties up to 43\% on the Hubble constant and the matter density with the SNe Ia with a new statistical analysis
Type Ia Supernovae (SNe Ia) are considered the most reliable \textit{standard
candles} and they have played an invaluable role in cosmology since the
discovery of the Universe's accelerated expansion. During the last decades, the
SNe Ia samples have been improved in number, redshift coverage, calibration
methodology, and systematics treatment. These efforts led to the most recent
\textit{``Pantheon"} (2018) and \textit{``Pantheon +"} (2022) releases, which
enable to constrain cosmological parameters more precisely than previous
samples. In this era of precision cosmology, the community strives to find new
ways to reduce uncertainties on cosmological parameters. To this end, we start
our investigation even from the likelihood assumption of Gaussianity,
implicitly used in this domain. Indeed, the usual practise involves
constraining parameters through a Gaussian distance moduli likelihood. This
method relies on the implicit assumption that the difference between the
distance moduli measured and the ones expected from the cosmological model is
Gaussianly distributed. In this work, we test this hypothesis for both the
\textit{Pantheon} and \textit{Pantheon +} releases. We find that in both cases
this requirement is not fulfilled and the actual underlying distributions are a
logistic and a Student's t distribution for the \textit{Pantheon} and
\textit{Pantheon +} data, respectively. When we apply these new likelihoods
fitting a flat CDM model, we significantly reduce the uncertainties on
and of . This boosts the SNe Ia power in
constraining cosmological parameters, thus representing a huge step forward to
shed light on the current debated tensions in cosmology.Comment: 15 pages with 7 figures (with multiple panels), 1 table. This work
includes the suggestions of scientists from the community who reached out.
The paper is now under consideration in Ap
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