Vícios construtivos e a controvérsia envolvendo a eventual responsabilidade civil solidária do agente financeiro

- Disponível também na Revista Jurídica, São Paulo, v. 67, n. 494, p. 77-100, dez. 2018.- Disponível também na Revista Síntese: Direito Imobiliário, São Paulo, v. 8, n. 47, p. 51-72, set./out. 2018

Unfolding spinor wavefunctions and expectation values of general operators: Introducing the unfolding-density operator

We show that the spectral weights $W_{m\vec K}(\vec k)$ used for the unfolding of two-component spinor eigenstates $| {\psi_{m\vec K}^\mathrm{SC}} > = | \alpha > | {\psi_{m\vec{K}}^\mathrm{SC, \alpha}} > + | \beta > | {\psi_{m\vec{K}}^\mathrm{SC, \beta}} >$ can be decomposed as the sum of the partial spectral weights $W_{m\vec{K}}^{\mu}(\vec k)$ calculated for each component $\mu = \alpha, \beta$ independently, effortlessly turning a possibly complicated problem involving two coupled quantities into two independent problems of easy solution. Furthermore, we define the unfolding-density operator $\hat{\rho}_{\vec{K}}(\vec{k}_{i}; \, \varepsilon)$, which unfolds the primitive cell expectation values $\varphi^{pc}(\vec{k}; \varepsilon)$ of any arbitrary operator $\mathbf{\hat\varphi}$ according to $\varphi^{pc}(\vec{k}_{i}; \varepsilon) = \mathit{Tr}(\hat{\rho}_{\vec{K}}(\vec{k}_{i}; \, \varepsilon)\,\,\hat{\varphi})$. As a proof of concept, we apply the method to obtain the unfolded band structures, as well as the expectation values of the Pauli spin matrices, for prototypical physical systems described by two-component spinor eigenfunctions

Distributed drone base station positioning for emergency cellular networks using reinforcement learning

Due to the unpredictability of natural disasters, whenever a catastrophe happens, it is vital that not only emergency rescue teams are prepared, but also that there is a functional communication network infrastructure. Hence, in order to prevent additional losses of human lives, it is crucial that network operators are able to deploy an emergency infrastructure as fast as possible. In this sense, the deployment of an intelligent, mobile, and adaptable network, through the usage of drones—unmanned aerial vehicles—is being considered as one possible alternative for emergency situations. In this paper, an intelligent solution based on reinforcement learning is proposed in order to find the best position of multiple drone small cells (DSCs) in an emergency scenario. The proposed solution’s main goal is to maximize the amount of users covered by the system, while drones are limited by both backhaul and radio access network constraints. Results show that the proposed Q-learning solution largely outperforms all other approaches with respect to all metrics considered. Hence, intelligent DSCs are considered a good alternative in order to enable the rapid and efficient deployment of an emergency communication network

Alterações no processamento de recursos

- Disponível também na Revista dos Tribunais: RT, São Paulo, v. 88, n. 764, p. 75-87, jun. 1999.Comenta as alterações ocorridas na Lei n° 9.756, de 17 de dezembro de 1998, referente ao processamento de recursos no âmbito dos tribunais. Enfoca a análise da efetividade do novo sistema recursal

São Paulo, v.30

ABSTRACT: Usually the classical approach to make inference in linear regressio

Releitura da Súmula 54 do STJ

Disponível também na Revista Jurídica, São Paulo, v. 71, n. 530, p. 9-38, dez. 2021.Disponível também na Revista dos Tribunais: RT, São Paulo, v. 111, n. 1037, p. 215-238, mar. 2022