11,790,283 research outputs found
Introduzione
No full textAbstract
Giuseppe Capriotti e Francesca Coltrinari introducono e presentano i saggi pubblicati in " Periferie. Dinamiche economiche territoriali e produzione artistica".
Giuseppe Capriotti and Francesca Coltrinari present the papers published in " Peripheries. Territorial economic dynamics and artistic production"
Ricerca e diffusione del sapere: un’intervista a Chiara Frugoni
No full textChiara Frugoni, una delle massime medieviste italiane, risponde alle domande di Giuseppe Capriotti sull’importanza della comunicazione ad un vasto pubblico dei risultati della ricerca scientifica.
Chiara Frugoni, one of the greatest Italian expert of medieval history, answers to Giuseppe Capriotti’s questions about the importance of communicating the results of the scientific research to a wider audience
LHCb searches for the strong CP-violating decays η → ππ and η′ → ππ
No full textA search for the CP-violating strong decays η → π(+)π(−) and η′(958) → π(+)π(−) has been performed using approximately 2.5 × 10(7) events of each of the decays D(+) → π(+)π(+)π(−) and , recorded by the LHCb experiment. The data set corresponds to an integrated luminosity of 3.0 fb(−)(1) of pp collision data recorded during LHC Run 1 and 0.3 fb(−)(1) recorded in Run 2. No evidence is seen for with η (()(′)()) → π(+)π(−) and upper limits at 90% confidence level are set on the branching fractions, and . The limit for the η decay is comparable with the existing one, while that for the η′ is a factor of three smaller than the previous limit
Sibille Contra Judaeos. Una lettura antiebraica della Cappella Baglioni di Pintoricchio a Spello
No full textThe effect of mutations on protein stability changes: a three class pair residue discrimination study
No full textMotivation A basic question in protein structural studies is to which extent mutations affect protein folding stability. This can be
asked starting from protein sequence and/or from structure. In proteomics and genomics studies prediction of protein stability free
energy change (DDG) upon single point mutation may also help the annotation process. So far methods to address this problem are
based on to two different approaches: development of optimised and different energy functions (Gilis and Rooman, 1997; Guerois
et al., 2002; Zhou and Zhou, 2002) for proteins whose structure is known and implementations of machine learning approaches
when sequences and/or structures are available (Capriotti et al., 2004; Capriotti et al 2005a; Capriotti et al 2005b; Cheng et al.,
2006). On the other hand experimental DDG values are affected by uncertainty as measured by standard deviations. Most of the
DDG values are nearly zero (about 32% of the DDG data set ranges from -0.5 to 0.5 Kcal/mol); furthermore both the value and
sign of DDG may be either positive or negative for the same mutation blurring the relationship among mutations and expected
DDG value. In order to overcome this problem we describe a new predictor that discriminates between 3 mutation classes:
destabilizing mutations, stabilizing mutations and neutral mutations, being neutral mutations all those substitutions whose effect is
to promote a protein stability free energy change (DDG) ranging from -0.5 to 0.5 Kcal/mol. Methods In this paper a support vector
machine (SVM) starting from the protein sequence or structure discriminates between stabilizing, destabilizing and neutral
mutations. The machine learning method here presented was trained and tested considering experimental data selected from the
new release of the ProTherm Database (Kumar et al. 2006). We collect more than 1600 mutations and according to the criterion of
thermodynamic reversibility for each mutation, we double all the thermodynamic data. Finally, we end up with more than 3200
mutations to train our method with a cross-validation procedure. Following other previous works of ours (Capriotti et al 2005a;
Capriotti et al 2005b) two different SVM methods were developed depending on the provided information. If the predictions are
sequence-based an input vector of 42 elements is used. The input accounts for the residue mutation (encoded in the first 20
elements), the sequence environment (encoded in second 20 elements) and experimental conditions (temperature and pH reported
in the last two element). When the 3D structure of the mutated proteins is known is it also possible to perform the prediction with
the structure-based method that considers an input vector of 43 elements. The input vector is similar to that of the sequence-based
predictor: however the 20 element vector encoding for the sequence environment is replaced considering the structural
environment and adding also one element accounting for the relative solvent accessible area is added. Results We rank all the
possible substitutions according to a three class-classification system that aside prediction indicates also the rate of occurrence of
the mutations in the data base and the list of proteins where the mutation effect has been experimentally detected. We show that the
overall accuracy of our predictor is as high as 52% when performed starting from sequence information and 58% when the protein
structure is available with a mean value correlation coefficient of 0.30 and 0.39 respectively. These values are about 20 points per
cent higher than those of a random predictor; when selecting only the mutations with high effect on the protein stability
(|DDG|>0.5 Kcal) the prediction of the destabilizing and stabilizing mutations are well balanced and reaches the accuracy values of
71% and 76% with correlation coefficient of 0.43 and 0.52, respectively when sequence-based and structure-based predictions are
provided
"...con li coltelli delle nostre lingue". Immagini eloquenti come prediche nell'Osservanza francescana
No full text“E tu andrai tanto tosto che tu m’aspetterai!” L’iconografia dell’ebreo errante da Matthew Paris a Orazio Gentileschi
No full textAlgorithmic differentiation and the calculation of forces by quantum Monte Carlo
No full textWe describe an efficient algorithm to compute forces in quantum Monte Carlo using adjoint algorithmic differentiation. This allows us to apply the space warp coordinate transformation in differential form, and compute all the 3M force components of a system with M atoms with a computational effort comparable with the one to obtain the total energy. Few examples illustrating the method for an electronic system containing several water molecules are presented. With the present technique, the calculation of finite-temperature thermodynamic properties of materials with quantum Monte Carlo will be feasible in the near future
Spontaneous plaquette dimerization in the J(1)-J(2) Heisenberg model
No full textWe investigate the nonmagnetic phase of the spin-half frustrated Heisenberg antiferromagnet on the square lattice using exact diagonalization (up to 36 sites) and quantum Monte Carlo techniques (up to 144 sites). The spin gap and the susceptibilities for the most important crystal symmetry breaking operators are computed. A genuine and somehow unexpected "plaquette resonating valence bond," with spontaneously broken translation symmetry and no broken rotation symmetry, comes out from our numerical simulations as the most plausible ground state for J(2)/J(1) similar or equal to 0.5
In viaggio per lavoro. La decorazione delle cappelle dei Cavallari nei santuari mariani di Macereto e l'Ambro
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