Physical properties of the Schur complement of local covariance matrices

General properties of global covariance matrices representing bipartite Gaussian states can be decomposed into properties of local covariance matrices and their Schur complements. We demonstrate that given a bipartite Gaussian state $\rho_{12}$ described by a $4\times 4$ covariance matrix \textbf{V}, the Schur complement of a local covariance submatrix $\textbf{V}_1$ of it can be interpreted as a new covariance matrix representing a Gaussian operator of party 1 conditioned to local parity measurements on party 2. The connection with a partial parity measurement over a bipartite quantum state and the determination of the reduced Wigner function is given and an operational process of parity measurement is developed. Generalization of this procedure to a $n$-partite Gaussian state is given and it is demonstrated that the $n-1$ system state conditioned to a partial parity projection is given by a covariance matrix such as its $2 \times 2$ block elements are Schur complements of special local matrices.Comment: 10 pages. Replaced with final published versio

Simulação de dados meteorológicos para avaliação de impactos de mudanças climáticas na agricultura.

Neste trabalho foi utilizado o simulador climático LARS-WG. Esse simulador é baseado em um modelo semiempírico, ou seja, para o processo há a utilização de parâmetros estatísticos em sua formulação e também a necessidade de calibrações para as devidas aplicações

Efficiency of distinct data mining algorithms for classifying stress level in piglets from their vocalization.

ABSTRACT: Among the challenges of pig farming in today's competitive market, there is factor of the product traceability that ensures, among many points, animal welfare. Vocalization is a valuable tool to identify situations of stress in pigs, and it can be used in welfare records for traceability. The objective of this work was to identify stress in piglets using vocalization, calling this stress on three levels: no stress, moderate stress, and acute stress. An experiment was conducted on a commercial farm in the municipality of Holambra, São Paulo State , where vocalizations of twenty piglets were recorded during the castration procedure, and separated into two groups: without anesthesia and local anesthesia with lidocaine base. For the recording of acoustic signals, a unidirectional microphone was connected to a digital recorder, in which signals were digitized at a frequency of 44,100 Hz. For evaluation of sound signals, Praat software was used, and different data mining algorithms were applied using Weka software. The selection of attributes improved model accuracy, and the best attribute selection was used by applying Wrapper method, while the best classification algorithms were the k-NN and Naive Bayes. According to the results, it was possible to classify the level of stress in pigs through their vocalization

MODELING AND ANALYSIS OF AN ELECTRIC VEHICLE USING PAMVEC

Electric vehicles are considered a key technology to reduce fossil fuel consumption, emissions and energy consumption. However, Electric Vehicles require larger battery packs to reach acceptable range levels. The development of new batteries with higher specific energy could reduce the mass and the cost of Electric Vehicles and increase their driving range. This work analyzes the influence of battery specific energy on battery pack mass, energy consumption and the cost per kilometer of a Tesla Model S Electric Vehicle. The energy consumption and the cost per kilometer calculated were 0.221 kWh/km (22.1 kWh/100 km) and 0.024 US$/km respectively