Organizational, direct support, and general support maintenance repair parts and special tools list (including depot maintenance repair parts and special tools) for battery charger PP-6259B/U (NSN 6130-00-400-5258).

"1 September 1983."

Spatial variation of particle number concentration in school microscale environments and its impact on exposure assessment

It has not yet been established whether the spatial variation of particle number concentration (PNC) within a microscale environment can have an effect on exposure estimation results. In general, the degree of spatial variation within microscale environments remains unclear, since previous studies have only focused on spatial variation within macroscale environments. The aims of this study were to determine the spatial variation of PNC within microscale school environments, in order to assess the importance of the number of monitoring sites on exposure estimation. Furthermore, this paper aims to identify which parameters have the largest influence on spatial variation, as well as the relationship between those parameters and spatial variation. Air quality measurements were conducted for two consecutive weeks at each of the 25 schools across Brisbane, Australia. PNC was measured at three sites within the grounds of each school, along with the measurement of meteorological and several other air quality parameters. Traffic density was recorded for the busiest road adjacent to the school. Spatial variation at each school was quantified using coefficient of variation (CV). The portion of CV associated with instrument uncertainty was found to be 0.3 and therefore, CV was corrected so that only non-instrument uncertainty was analysed in the data. The median corrected CV (CVc) ranged from 0 to 0.35 across the schools, with 12 schools found to exhibit spatial variation. The study determined the number of required monitoring sites at schools with spatial variability and tested the deviation in exposure estimation arising from using only a single site. Nine schools required two measurement sites and three schools required three sites. Overall, the deviation in exposure estimation from using only one monitoring site was as much as one order of magnitude. The study also tested the association of spatial variation with wind speed/direction and traffic density, using partial correlation coefficients to identify sources of variation and non-parametric function estimation to quantify the level of variability. Traffic density and road to school wind direction were found to have a positive effect on CVc, and therefore, also on spatial variation. Wind speed was found to have a decreasing effect on spatial variation when it exceeded a threshold of 1.5 (m/s), while it had no effect below this threshold. Traffic density had a positive effect on spatial variation and its effect increased until it reached a density of 70 vehicles per five minutes, at which point its effect plateaued and did not increase further as a result of increasing traffic density.

One pot synthesis of polycyclic oxygen aromatics. Part III mechanism of formation

Reaction of 6-Image -butyl-1-bromomethyl-2-(2-tetrahydropyranyloxy)-naphthalene2c with tetrachlorocatechol (TCC) in acetone in presence of K2CO3 gave diastereomers 6c and 7c. A mechanism (Scheme-1) invoking the base induced cleavage of the pyranyl ether 2 to 1,2-naphthoquinone-1-methide 8 as the first step has been postulated. The cleavage of the pyranyl ether linkage in 2 to give dimers 4 and 5 of 1,2-naphthoquinone-1-methide has been demonstrated with different bases. 1,2-Naphthoquinone-1-methide 8, thus generated, undergoes Michael addition with TCC followed by elimination of chloride ions to give a diketone, which further undergoes aldolisation with acetone to give diastereomers 6 and 7. Michael reaction of 8, generated Image from pyranyl ethers 2a-c, with tetrabromocatechol (TBC) under similar-reaction conditions gave the expected monobromo compounds 6h, 6i, 6k, 7n, 7n and 7q. The last step in the proposed mechanism, Image ., aldolisation has also been demonstrated using different ketonic solvents. Thus, reaction of 2a-c with TCC/TBC in diethyl ketone/methyl ethyl ketone under similar reaction conditions gave the expected compounds 6 and 7.

Primary and rechargeable zinc-air batteries using ceramic and highly stable TiCN as an oxygen reduction reaction electrocatalyst

Primary and secondary zinc-air batteries based on ceramic, stable, one dimensional titanium carbonitride (TiCN) nanostructures are reported. The optimized titanium carbonitride composition by density functional theory reveals their good activity towards the oxygen reduction reaction (ORR). Electrochemical measurements show their superior performance for the ORR in alkaline media coupled with favourable kinetics. The nanostructured TiCN lends itself amenable to be used as an air cathode material in primary and rechargeable zinc-air batteries. The battery performance and cyclability are found to be good. Further, we have demonstrated a gel-based electrolyte for rechargeable zinc-air batteries based on a TiCN cathode under ambient, atmospheric conditions without any oxygen supply from a cylinder. The present cell can work at current densities of 10-20 mA cm(2) (app. 10 000 mA g(-1) of TiCN) for several hours (63 h in the case of 10 mA cm(-2)) with a charge retention of 98%. The low cost, noble metal-free, mechanically stable and corrosion resistant TiCN is a very good alternative to Pt for metal-air battery chemistry.

Naive asymptotic expansion of the water wave generated by a slowly moving body

It is pointed out that the naive asymptotic expansion does not satisfy all the body boundary condition. A nonhomogeneous body boundary condition is obtained from this expansion. It is this condition that the additional wave term must satisfy. Moreover, because of this condition, the wave term must appear. It is pointed out that the zeroth approximation in the naive asymptotic expansion has weak singularity and the singularities become still stronger in the subsequent approximations.

Description of sampling stations, methods of benthic sampling and biological water quality assessment; with some consideration of the influence of sample variation on the assessment values obtained

The first bilateral study of methods of biological sampling and biological methods of water quality assessment took place during June 1977 on selected sampling sites in the catchment of the River Trent (UK). The study was arranged in accordance with the protocol established by the joint working group responsible for the Anglo-Soviet Environmental Agreement. The main purpose of the bilateral study in Nottingham was for some of the methods of sampling and biological assessment used by UK biologists to be demonstrated to their Soviet counterparts and for the Soviet biologists to have the opportunity to test these methods at first hand in order to judge the potential of any of these methods for use within the Soviet Union. This paper is concerned with the nine river stations in the Trent catchment.

No coração da tempestade: uma reflexão sobre o insólito em Vinte e zinco, de Mia Couto

Em Vinte e zinco, o escritor moçambicano Mia Couto, recorrendo ao universo telúrico de seu país, tenta recuperar, ficcionalmente, um período cronológico que perpassa dias imediatamente anteriores e posteriores à Revolução dos Cravos em Portugal, quando se deu a queda do regime salazarista, no 25 de Abril de 1974, iniciando a narrativa em 19 de Abril e concluindo-a no dia 30. O escritor vale-se de recursos lúdicos inerentes à produção ficcional, somados às possibilidades estéticas oferecidas ao longo do processo de resgate sociocultural dos valores da terra. Assim, conta uma história em que elementos do maravilhoso são legíveis como comuns à realidade quotidiana. A narrativa apresenta a função da Casa dos Castro os integrantes da família e suas relações com África e das demais personagens que transitam ao seu redor seja na figura de negros, seja na de alguns brancos, estes, assimilados ao avesso ou não. Essas personagens juntas mesmo que estejam, em determinados momentos, em lados opostos caminham, como representação da dualidade colonial, em direção à apoteótica cena insólita em que se dão a ascensão do Napolo e a tempestade que cai ao final, manchando a terra às vésperas do 25 de Abril. Mia Couto, em um universo cercado de mitos, crenças e tradições, torna visível o invisível, espelhando, no plano da diegese, a realidade desse cenário, e recupera, pela via das trocas culturais ao longo dos séculos, estratégias de construção narrativa ficcional desenvolvidas nas literaturas latino-americanas a fim de representar Moçambique em sua obra. Assim, apropria-se dos preceitos do Real Maravilhoso, em sua vertente africana aqui chamada de Real Animismo miacoutiano para apresentar essa mestiçagem cultural com imagens plurivalentes do real

Active learning of model evidence using Bayesian quadrature

Numerical integration is a key component of many problems in scientific computing, statistical modelling, and machine learning. Bayesian Quadrature is a modelbased method for numerical integration which, relative to standard Monte Carlo methods, offers increased sample efficiency and a more robust estimate of the uncertainty in the estimated integral. We propose a novel Bayesian Quadrature approach for numerical integration when the integrand is non-negative, such as the case of computing the marginal likelihood, predictive distribution, or normalising constant of a probabilistic model. Our approach approximately marginalises the quadrature model's hyperparameters in closed form, and introduces an active learning scheme to optimally select function evaluations, as opposed to using Monte Carlo samples. We demonstrate our method on both a number of synthetic benchmarks and a real scientific problem from astronomy.

水质酸化和模拟酸雨对浮游动物影响的研究

在水质酸化和模拟酸雨试验中,共出现浮游动物17种,其中包括轮虫9种、枝角类6种和桡足类2种。在pH5.0—8.3各试验组出现种类数(10—13种)和个体数(223.0—334.5个·L~(-1))较多,而在pH3.0和4.5试验组出现种类数(5—9种)和个体数(16.8—182.0个·L~(-1))较少,表明pH5.0以下对浮游动物群落有明显的影响。从不同类群出现所占比例看,在pH5.5以下,随着pH的下降,存在着轮虫逐渐取代桡足类的趋势。

Gaussian process volatility model

The prediction of time-changing variances is an important task in the modeling of financial data. Standard econometric models are often limited as they assume rigid functional relationships for the evolution of the variance. Moreover, functional parameters are usually learned by maximum likelihood, which can lead to over-fitting. To address these problems we introduce GP-Vol, a novel non-parametric model for time-changing variances based on Gaussian Processes. This new model can capture highly flexible functional relationships for the variances. Furthermore, we introduce a new online algorithm for fast inference in GP-Vol. This method is much faster than current offline inference procedures and it avoids overfitting problems by following a fully Bayesian approach. Experiments with financial data show that GP-Vol performs significantly better than current standard alternatives.

Bayesian inference and learning in Gaussian process state-space models with Particle MCMC

State-space models are successfully used in many areas of science, engineering and economics to model time series and dynamical systems. We present a fully Bayesian approach to inference and learning (i.e. state estimation and system identification) in nonlinear nonparametric state-space models. We place a Gaussian process prior over the state transition dynamics, resulting in a flexible model able to capture complex dynamical phenomena. To enable efficient inference, we marginalize over the transition dynamics function and, instead, infer directly the joint smoothing distribution using specially tailored Particle Markov Chain Monte Carlo samplers. Once a sample from the smoothing distribution is computed, the state transition predictive distribution can be formulated analytically. Our approach preserves the full nonparametric expressivity of the model and can make use of sparse Gaussian processes to greatly reduce computational complexity.

Correlations strike back (again): The case of associative memory retrieval

It has long been recognised that statistical dependencies in neuronal activity need to be taken into account when decoding stimuli encoded in a neural population. Less studied, though equally pernicious, is the need to take account of dependencies between synaptic weights when decoding patterns previously encoded in an auto-associative memory. We show that activity-dependent learning generically produces such correlations, and failing to take them into account in the dynamics of memory retrieval leads to catastrophically poor recall. We derive optimal network dynamics for recall in the face of synaptic correlations caused by a range of synaptic plasticity rules. These dynamics involve well-studied circuit motifs, such as forms of feedback inhibition and experimentally observed dendritic nonlinearities. We therefore show how addressing the problem of synaptic correlations leads to a novel functional account of key biophysical features of the neural substrate.

Predictive entropy search for efficient global optimization of black-box functions

We propose a novel information-theoretic approach for Bayesian optimization called Predictive Entropy Search (PES). At each iteration, PES selects the next evaluation point that maximizes the expected information gained with respect to the global maximum. PES codifies this intractable acquisition function in terms of the expected reduction in the differential entropy of the predictive distribution. This reformulation allows PES to obtain approximations that are both more accurate and efficient than other alternatives such as Entropy Search (ES). Furthermore, PES can easily perform a fully Bayesian treatment of the model hyperparameters while ES cannot. We evaluate PES in both synthetic and real-world applications, including optimization problems in machine learning, finance, biotechnology, and robotics. We show that the increased accuracy of PES leads to significant gains in optimization performance.