2,284 research outputs found
Productivity shocks and labour market outcomes for top earners: evidence from Italian Serie A
How are top earners affected by productivity shocks? We address this question using a unique longitudinal data set on the universe of professional football players in the Italian Serie A, representing 20% of top earners in Italy. We use traumatic injuries and adopt an IV strategy to provide causal estimates of the impact of productivity shocks on several labour market outcomes. We find that a 30-day injury substantially affects the probability of contract renegotiation and reduces net wages by around 12%. We show that this large penalty is due to employer's precautionary motives rather than to shock-induced reduction in current player's performance
Data mining crystallization kinetics
The population balance model is a valuable modelling tool which facilitates the optimization and understanding of crystallization processes. However, in order to use this tool, it is necessary to have previous knowledge of the crystallization kinetics, specifically crystal growth and nucleation. The majority of approaches to achieve proper estimations of kinetic parameters require experimental data. Over time, a vast amount of literature on the estimation of kinetic parameters and population balances has been published. Considering the availability of data, in this work a database was built with information on solute, solvent, kinetic expression, parameters, crystallization method and seeding. Correlations were assessed and cluster structures identified by hierarchical cluster analysis. The final database contains 336 datapoints of kinetic parameters from 185 different sources. The data were analysed using kinetic parameters of the most common expressions. Subsequently, clusters were identified for each kinetic model. With these clusters, classification random forest models were made using solute descriptors, seeding, solvent, and crystallization methods as classifiers. Random forest models had an overall classification accuracy higher than 70% whereby they were useful for providing rough estimates of kinetic parameters, although these methods have some limitations
A novel integrated workflow for isolation solvent selection using prediction and modelling
A predictive tool was developed to aid process design and to rationally select optimal solvents for isolation of active pharmaceutical ingredients. The objective was to minimize the experimental work required to design a purification process by (i) starting from a rationally selected crystallization solvent based on maximizing yield and minimizing solvent consumption (with the constraint of maintaining a suspension density which allows crystal suspension); (ii) for the crystallization solvent identified from step 1, a list of potential isolation solvents (selected based on a series of constraints) is ranked, based on thermodynamic consideration of yield and predicted purity using a mass balance model; and (iii) the most promising of the predicted combinations is verified experimentally, and the process conditions are adjusted to maximize impurity removal and maximize yield, taking into account mass transport and kinetic considerations. Here, we present a solvent selection workflow based on logical solvent ranking supported by solubility predictions, coupled with digital tools to transfer material property information between operations to predict the optimal purification strategy. This approach addresses isolation, preserving the particle attributes generated during crystallization, taking account of the risks of product precipitation and particle dissolution during washing, and the selection of solvents, which are favorable for drying
Search for CP Violation in the Decay Z -> b (b bar) g
About three million hadronic decays of the Z collected by ALEPH in the years
1991-1994 are used to search for anomalous CP violation beyond the Standard
Model in the decay Z -> b \bar{b} g. The study is performed by analyzing
angular correlations between the two quarks and the gluon in three-jet events
and by measuring the differential two-jet rate. No signal of CP violation is
found. For the combinations of anomalous CP violating couplings, and , limits of \hat{h}_b < 0.59h^{\ast}_{b} < 3.02$ are given at 95\% CL.Comment: 8 pages, 1 postscript figure, uses here.sty, epsfig.st
Search for the glueball candidates f0(1500) and fJ(1710) in gamma gamma collisions
Data taken with the ALEPH detector at LEP1 have been used to search for gamma
gamma production of the glueball candidates f0(1500) and fJ(1710) via their
decay to pi+pi-. No signal is observed and upper limits to the product of gamma
gamma width and pi+pi- branching ratio of the f0(1500) and the fJ(1710) have
been measured to be Gamma_(gamma gamma -> f0(1500)). BR(f0(1500)->pi+pi-) <
0.31 keV and Gamma_(gamma gamma -> fJ(1710)). BR(fJ(1710)->pi+pi-) < 0.55 keV
at 95% confidence level.Comment: 10 pages, 3 figure
Single hadron response measurement and calorimeter jet energy scale uncertainty with the ATLAS detector at the LHC
The uncertainty on the calorimeter energy response to jets of particles is
derived for the ATLAS experiment at the Large Hadron Collider (LHC). First, the
calorimeter response to single isolated charged hadrons is measured and
compared to the Monte Carlo simulation using proton-proton collisions at
centre-of-mass energies of sqrt(s) = 900 GeV and 7 TeV collected during 2009
and 2010. Then, using the decay of K_s and Lambda particles, the calorimeter
response to specific types of particles (positively and negatively charged
pions, protons, and anti-protons) is measured and compared to the Monte Carlo
predictions. Finally, the jet energy scale uncertainty is determined by
propagating the response uncertainty for single charged and neutral particles
to jets. The response uncertainty is 2-5% for central isolated hadrons and 1-3%
for the final calorimeter jet energy scale.Comment: 24 pages plus author list (36 pages total), 23 figures, 1 table,
submitted to European Physical Journal
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