Novel resistance training-specific rating of perceived exertion scale measuring repetitions in reserve

The primary aim of this study was to compare rating of perceived exertion (RPE) values measuring repetitions in reserve (RIR) at particular intensities of 1 repetition maximum (RM) in experienced (ES) and novice squatters (NS). Furthermore, this investigation compared average velocity between ES and NS at the same intensities. Twenty-nine individuals (24.0 ± 3.4 years) performed a 1RM squat followed by a single repetition with loads corresponding to 60, 75, and 90% of 1RM and an 8-repetition set at 70% 1RM. Average velocity was recorded at 60, 75, and 90% 1RM and on the first and last repetitions of the 8-repetition set. Subjects reported an RPE value that corresponded to an RIR value (RPE-10 = 0-RIR, RPE-9 = 1-RIR, and so forth). Subjects were assigned to one of the 2 groups: (a) ES (n = 15, training age: 5.2 ± 3.5 years) and (b) NS (n = 14, training age: 0.4 ± 0.6 years). The mean of the average velocities for ES was slower (p ≤ 0.05) than NS at 100% and 90% 1RM. However, there were no differences (p > 0.05) between groups at 60, 75%, or for the first and eighth repetitions at 70% 1RM. In addition, ES recorded greater RPE at 1RM than NS (p = 0.023). In ES, there was a strong inverse relationship between average velocity and RPE at all percentages (r = −0.88, p < 0.001), and a strong inverse correlation in NS between average velocity and RPE at all intensities (r = −0.77, p = 0.001). Our findings demonstrate an inverse relationship between average velocity and RPE/RIR. Experienced squatter group exhibited slower average velocity and higher RPE at 1RM than NS, signaling greater efficiency at high intensities. The RIR-based RPE scale is a practical method to regulate daily training load and provide feedback during a 1RM test.

Modeling chemistry in massive star forming regions with internal PDRs

Over the past decades star formation has been a very attractive field because knowledge of star formation leads to a better understanding of the formation of planets and thus of our solar system but also of the evolution of galaxies. Conditions leading to the formation of high-mass stars are still under investigation but an evolutionary scenario has been proposed: As a cold pre-stellar core collapses under gravitational force, the medium warms up until it reaches a temperature of 100 K and enters the hot molecular core (HMC) phase. The forming central proto-star accretes materials, increasing its mass and luminosity and eventually it becomes sufficiently evolved to emit UV photons which irradiate the surrounding environment forming a hyper compact (HC) and then a ultracompact (UC) HII region. At this stage, a very dense and very thin internal photon-dominated region (PDR) forms between the HII region and the molecular core. Information on the chemistry allows to trace the physical processes occurring in these different phases of star formation. Formation and destruction routes of molecules are influenced by the environment as reaction rates depend on the temperature and radiation field. Therefore, chemistry also allows the determination of the evolutionary stage of astrophysical objects through the use of chemical models including the time evolution of the temperature and radiation field. Because HMCs host a very rich chemistry with high abundances of complex organic molecules (COMs), several astrochemical models have been developed to study the gas phase chemistry as well as grain chemistry in these regions. In addition to HMCs models, models of PDRs have also been developed to study in particular photo-chemistry. So far, few studies have investigated internal PDRs and only in the presence of outflows cavities. Thus, these unique regions around HC/UCHII regions remain to be examined thoroughly. My PhD thesis focuses on the spatio-temporal chemical evolution in HC/UC HII regions with internal PDRs as well as in HMCs. The purpose of this study is first to understand the impact and effects of the radiation field, usually very strong in these regions, on the chemistry. Secondly, the goal is to study the emission of various tracers of HC/UCHII regions and compare it with HMCs models, where the UV radiation field does not impact the region as it is immediately attenuated by the medium. Ultimately we want to determine the age of a given region using chemistry in combination with radiative transfer.

STAR Modeling of Pulmonary Tuberculosis Delay-Time in Diagnosis

Understanding what characterizes patients who suffer great delays in diagnosis of pulmonary tuberculosis is of great importance when establishing screening strategies to better control TB. Greater delays in diagnosis imply a higher chance for susceptible individuals to become infected by a bacilliferous patient. A Structured Additive Regression model is attempted in this study in order to potentially contribute to a better characterization of bacilliferous prevalence in Portugal. The main findings suggest the existence of significant regional differences in Portugal, with the fact of being female and/or alcohol dependent contributing to an increased delay-time in diagnosis, while being dependent on intravenous drugs and/or being diagnosed with HIV are factors that increase the chance of an earlier diagnosis of pulmonary TB. A decrease in 2010 to 77% on treatment success in Portugal underlines the importance of conducting more research aimed at better TB control strategies.

A double chance to investigate populist influence: The Five Star Movement.

In the last decade, new kinds of European populist parties and movements characterized by a left wing, right wing or “eclectic” attitude have succeeded in entering in governments where they could exert a direct populist influence on their coalition partners or, conversely, become victims themselves of the influence of the institutional background. Such a scenario brought this research to formulate two questions: (i) “To what extent did populist parties succeed in influencing their government coalition partners, leading them to adopt populist rhetoric and change their policy positions?” and (ii) “Have populist parties been able to retain their populist “outside mainstream politics” identity, or have they been assimilated to mainstream parties?”. As a case study this project chose the Italian Five Star Movement. Since 2018 this eclectic populist actor has experienced three different governments first with the radical right wing populist League (2018-2019) and then with the mainstream center left Democratic Party (2019-2021). In addition to this, currently the Five Star Movement is a coalition partner of the ongoing Draghi’s government. Theoretically based on the ideological definition of populism (Mudde, 2004), on a new “revised” model of the inclusionary - exclusionary framework to classify populist parties and on a novel definition of “populist influence”,this research made use of both quantitative (bidimensional and text analysis) and qualitative methods (semi-structured interviews) and mainly focuses on the years 2017- 2020.The importance of this study is threefold. First it contributes to the study of populist influence in government in relation to the ideological attachment of the political actors involved. Second, it contributes to understand if populists in power necessarily need to tone down their anti-system character in order to survive. Third, this study introduces conceptual and methodological novelties within the study of populism and populist influence in government.

A Unified Model for XVA, including Interest Rates and Rating

We start in Chapter 2 to investigate linear matrix-valued SDEs and the Itô-stochastic Magnus expansion. The Itô-stochastic Magnus expansion provides an efficient numerical scheme to solve matrix-valued SDEs. We show convergence of the expansion up to a stopping time τ and provide an asymptotic estimate of the cumulative distribution function of τ. Moreover, we show how to apply it to solve SPDEs with one and two spatial dimensions by combining it with the method of lines with high accuracy. We will see that the Magnus expansion allows us to use GPU techniques leading to major performance improvements compared to a standard Euler-Maruyama scheme. In Chapter 3, we study a short-rate model in a Cox-Ingersoll-Ross (CIR) framework for negative interest rates. We define the short rate as the difference of two independent CIR processes and add a deterministic shift to guarantee a perfect fit to the market term structure. We show how to use the Gram-Charlier expansion to efficiently calibrate the model to the market swaption surface and price Bermudan swaptions with good accuracy. We are taking two different perspectives for rating transition modelling. In Section 4.4, we study inhomogeneous continuous-time Markov chains (ICTMC) as a candidate for a rating model with deterministic rating transitions. We extend this model by taking a Lie group perspective in Section 4.5, to allow for stochastic rating transitions. In both cases, we will compare the most popular choices for a change of measure technique and show how to efficiently calibrate both models to the available historical rating data and market default probabilities. At the very end, we apply the techniques shown in this thesis to minimize the collateral-inclusive Credit/ Debit Valuation Adjustments under the constraint of small collateral postings by using a collateral account dependent on rating trigger.

New indicators of star cluster dynamical evolution

This thesis presents a study of globular clusters (GCs), based on analysis of Monte Carlo simulations of globular clusters (GCs) with the aim to define new empirical parameters measurable from observations and able to trace the different phases of their dynamical evolution history. During their long term dynamical evolution, due to mass segregation and and dynamical friction, massive stars transfer kinetic energy to lower-mass objects, causing them to sink toward the cluster center. This continuous transfer of kinetic energy from the core to the outskirts triggers the runaway contraction of the core, known as "core collapse" (CC), followed by episodes of expansion and contraction called gravothermal oscillations. Clearly, such an internal dynamical evolution corresponds to significant variations also of the structure of the system. Determining the dynamical age of a cluster can be challenging as it depends on various internal and external properties. The traditional classification of GCs as CC or post-CC systems relies on detecting a steep power-law cusp in the central density profile, which may not always be reliable due to post-CC oscillations or other processes. In this thesis, based on the normalized cumulative radial distribution (nCRD) within a fraction of the half-mass radius is analyzed, and three diagnostics (A5, P5, and S2.5) are defined. These diagnostics show sensitivity to dynamical evolution and can distinguish pre-CC clusters from post-CC clusters.The analysis performed using multiple simulations with different initial conditions, including varying binary fractions and the presence of dark remnants showed the time variations of the diagnostics follow distinct patterns depending on the binary fraction and the retention or ejection of black holes. This analysis is extended to a larger set of simulations matching the observed properties of Galactic GCs, and the parameters show a potential to distinguish the dynamical stages of the observed clusters as well.

Obscured AGN in deep fields: tracing accretion and star-formation up to z ∼ 5

The discovery of scaling relations between the mass of the SMBH and some key physical properties of the host galaxy suggests that the growth of the SMBH and that of the galaxy are coupled, with the AGN activity and the star-formation (SF) processes influencing each other. Although the mechanism of this co-evolution are still a matter of debate, all scenarios agree that a key phase of the co-evolution is represented by the obscured accretion phase. This phase is of the co-evolution is the least studied, mostly due to the challenge in detecting and recognizing such obscured AGN. My thesis aims at investigating the AGN-galaxy co-evolution paradigm by identifying and studying AGN in the obscured accretion phase. The study of obscured AGN is key for our understanding of the feedback processes and of the mutual influence of the SF and the AGN activity. Moreover, these obscured and elusive AGN are needed to explain the X-ray background spectrum and to reconcile the measurements and the theoretical prediction of the BH accretion rate density. In this thesis, we firstly investigate the synergies between IR and X-ray missions in detecting and characterizing AGN, with a particular focus on the most obscured ones. We exploited UV/optical emission lines to select high-redshift obscured AGN at the cosmic noon, where the highest SFR density and BH accretion rate density are expected. We provide X-ray spectral analysis and UV-to-far-IR SED-fitting. We show that our samples host a significant fraction of very obscured sources; many of these are highly accreting. Finally, we performe a thoughtful investigation of a galaxy at z~5 with unusual and peculiar features, that lead us to identify a second extremely young population of stars and hidden AGN activity.

tecniche di machine learning per la predizione del rating delle applicazioni all’interno di un play store

Il mio progetto di tesi ha come obiettivo quello di creare un modello in grado di predire il rating delle applicazioni presenti all’interno del Play Store, uno dei più grandi servizi di distribuzione digitale Android. A tale scopo ho utilizzato il linguaggio Python, che grazie alle sue librerie, alla sua semplicità e alla sua versatilità è certamen- te uno dei linguaggi più usati nel campo dell’intelligenza artificiale. Il punto di partenza del mio studio è stato il Dataset (Insieme di dati strutturati in forma relazionale) “Google Play Store Apps” reperibile su Kaggle al seguente indirizzo: https://www.kaggle.com/datasets/lava18/google-play-store-apps, contenente 10841 osservazioni e 13 attributi. Dopo una prima parte relativa al caricamen- to, alla visualizzazione e alla preparazione dei dati su cui lavorare, ho applica- to quattro di↵erenti tecniche di Machine Learning per la stima del rating delle applicazioni. In particolare, sono state utilizzate:https://www.kaggle.com/datasets/lava18/google-play-store-apps, contenente 10841 osservazioni e 13 attributi. Dopo una prima parte relativa al caricamento, alla visualizzazione e alla preparazione dei dati su cui lavorare, ho applicato quattro differenti tecniche di Machine Learning per la stima del rating delle applicazioni: Ridje, Regressione Lineare, Random Forest e SVR. Tali algoritmi sono stati applicati attuando due tipi diversi di trasformazioni (Label Encoding e One Hot Encoding) sulla variabile ‘Category’, con lo scopo di analizzare come le suddette trasformazioni riescano a influire sulla bontà del modello. Ho confrontato poi l’errore quadratico medio (MSE), l’errore medio as- soluto (MAE) e l’errore mediano assoluto (MdAE) con il fine di capire quale sia l’algoritmo più efficiente.

The molecular gas content of star-forming galaxies in the ALPINE fields.

In this thesis, I aim to study the evolution with redshift of the gas mass fraction of a sample of 53 sources (from z ∼ 0.5 to z > 5) serendipitously detected in ALMA band 7 as part of the ALMA Large Program to INvestigate C II at Early Times (ALPINE). First, I used SED-fitting software CIGALE, which is able to implement energy balancing between the optical and the far infrared part, to produce a best-fit template of my sources and to have an estimate of some physical properties, such as the star formation rate (SFR), the total infrared luminosity and the total stellar mass. Then, using the tight correlation found by Scoville et al. (2014) between the ISM molecular gas mass and the rest-frame 850 μm luminosity, I used the latter, extrapolating it from the best-fit template using a code that I wrote in Python, as a tracer for the molecular gas. For my sample, I then derived the most important physical properties, such as molecular gas mass, gas mass fractions, specific star formation rate and depletion timescales, which allowed me to better categorize them and find them a place within the evolutionary history of the Universe. I also fitted our sources, via another code I wrote again in Python, with a general modified blackbody (MBB) model taken from the literature (Gilli et al. (2014), D’Amato et al. (2020)) to have a direct method of comparison with similar galaxies. What is evident at the end of the paper is that the methods used to derive the physical quantities of the sources are consistent with each other, and these in turn are in good agreement with what is found in the literature.

Beam-energy Dependence Of The Directed Flow Of Protons, Antiprotons, And Pions In Au+au Collisions.

Rapidity-odd directed flow (v1) measurements for charged pions, protons, and antiprotons near midrapidity (y=0) are reported in sNN=7.7, 11.5, 19.6, 27, 39, 62.4, and 200 GeV Au+Au collisions as recorded by the STAR detector at the Relativistic Heavy Ion Collider. At intermediate impact parameters, the proton and net-proton slope parameter dv1/dy|y=0 shows a minimum between 11.5 and 19.6 GeV. In addition, the net-proton dv1/dy|y=0 changes sign twice between 7.7 and 39 GeV. The proton and net-proton results qualitatively resemble predictions of a hydrodynamic model with a first-order phase transition from hadronic matter to deconfined matter, and differ from hadronic transport calculations.

Neurodevelopment Of Small-for-gestational Age Infants: Behavioral Aspects In First Year.

The purpose of this study was to compare the behavior of full-term small-for-gestational age (SGA) with full-term appropriate-for gestational age (AGA) infants in the first year of life. We prospectively evaluated 68 infants in the 2nd month, 67 in the 6th month and 69 in the 12th month. The Bayley Scales of Infant Development-II were used, with emphasis on the Behavior Rating Scale (BRS). The groups were similar concerning the item interest in test materials and stimuli; there was a trend toward differences in the items negative affect, hypersensitivity to test materials and adaptation to change in test materials. The mean of Raw Score was significantly lower for the SGA group in the items predominant state, liability of state of arousal, positive affect, soothability when upset, energy, exploration of objects and surroundings, orientation toward examiner. A lower BRS score was associated with the SGA group in the 2nd month.

Dielectron Mass Spectra From Au+au Collisions At √[s(nn)]=200 gev.

We report the STAR measurements of dielectron (e(+)e(-)) production at midrapidity (|y(ee)|<1) in Au+Au collisions at √[s(NN)]=200  GeV. The measurements are evaluated in different invariant mass regions with a focus on 0.30-0.76 (ρ-like), 0.76-0.80 (ω-like), and 0.98-1.05 (ϕ-like)   GeV/c(2). The spectrum in the ω-like and ϕ-like regions can be well described by the hadronic cocktail simulation. In the ρ-like region, however, the vacuum ρ spectral function cannot describe the shape of the dielectron excess. In this range, an enhancement of 1.77±0.11(stat)±0.24(syst)±0.33(cocktail) is determined with respect to the hadronic cocktail simulation that excludes the ρ meson. The excess yield in the ρ-like region increases with the number of collision participants faster than the ω and ϕ yields. Theoretical models with broadened ρ contributions through interactions with constituents in the hot QCD medium provide a consistent description of the dilepton mass spectra for the measurement presented here and the earlier data at the Super Proton Synchrotron energies.

Beam-energy Dependence Of Charge Separation Along The Magnetic Field In Au+au Collisions At Rhic.

Local parity-odd domains are theorized to form inside a quark-gluon plasma which has been produced in high-energy heavy-ion collisions. The local parity-odd domains manifest themselves as charge separation along the magnetic field axis via the chiral magnetic effect. The experimental observation of charge separation has previously been reported for heavy-ion collisions at the top RHIC energies. In this Letter, we present the results of the beam-energy dependence of the charge correlations in Au+Au collisions at midrapidity for center-of-mass energies of 7.7, 11.5, 19.6, 27, 39, and 62.4 GeV from the STAR experiment. After background subtraction, the signal gradually reduces with decreased beam energy and tends to vanish by 7.7 GeV. This implies the dominance of hadronic interactions over partonic ones at lower collision energies.

Measurement Of Longitudinal Spin Asymmetries For Weak Boson Production In Polarized Proton-proton Collisions At Rhic.

We report measurements of single- and double-spin asymmetries for W^{±} and Z/γ^{*} boson production in longitudinally polarized p+p collisions at sqrt[s]=510  GeV by the STAR experiment at RHIC. The asymmetries for W^{±} were measured as a function of the decay lepton pseudorapidity, which provides a theoretically clean probe of the proton's polarized quark distributions at the scale of the W mass. The results are compared to theoretical predictions, constrained by polarized deep inelastic scattering measurements, and show a preference for a sizable, positive up antiquark polarization in the range 0.05