A study of selected visual materials to improve instruction at the primary grade level

Call number: LD2668 .R4 1967 H5

Environmental Social Activism in the San Diego-Tijuana Transborder Region

This paper examines the obstacles and opportunities social activists face when attempting to fight environmental injustices in the San Diego-Tijuana transborder region. The study undertakes a case study of the Environmental Health Coalition (EHC) - the leading environmental justice organization in the region, which operates on both sides of the US-Mexico Border. The analyses conclude that despite a strong rhetoric of binationalism employed throughout border activists’ campaigns, the strategies that are utilized on the ground have been vastly local and short-term in focus. While activist organizations like the EHC demonstrate a keen awareness of the binational implications of environmental injustices and tout the benefits of a binational approach to addressing these problems, discrepancies are present due to obstacles that are economic, political and perceptual in nature. Ultimately, perceptions about the existence of environmental injustices as well as their character affect whether communities engage in local, short-term strategies to address immediate health concerns, or binational, long-term strategies that address the paradigmatic structures that underlie and perpetuate injustices. Key variables that shape community members’ and activists’ perceptions of environmental injustice include the economic situation that dictates individuals’ priorities and their ability to affect political decisions, as well as jurisdictional inconsistencies caused by the physical and political nature of the border. These findings contribute to a relatively sparse body of literature on the dynamics of transborder environmental justice activism by demonstrating the strategic shortcomings that perpetuate a true lack of binational collaboration in the San Diego-Tijuana region

Gradient-based adaptive HMC

Hamiltonian Monte Carlo (HMC) is a popular Markov Chain Monte Carlo (MCMC) algorithm to sample from an unnormalized probability distribution. A leapfrog integrator is commonly used to implement HMC in practice, but its performance can be sensitive to the choice of mass matrix used therein. We develop a gradient-based algorithm that allows for the adaptation of the mass matrix by encouraging the leapfrog integrator to have high acceptance rates while also exploring all dimensions jointly. In contrast to previous work that adapt the hyperparameters of HMC using some form of expected squared jumping distance, the adaptation strategy suggested here aims to increase sampling efficiency by maximizing an approximation of the proposal entropy. We illustrate that using multiple gradients in the HMC proposal can be beneficial compared to a single gradientstep in Metropolis-adjusted Langevin proposals. Empirical evidence suggests that the adaptation method can outperform different versions of HMC schemes by adjusting the mass matrix to the geometry of the target distribution and by providing some control on the integration time

A method for the separation of paramagnetic, ferrimagnetic and haematite magnetic subfabrics using high-field torque magnetometry

In this study, the contribution of the paramagnetic, ferrimagnetic and haematite components to the magnetic anisotropy is separated by means of high-field torque magnetometry. Torque measurements at different fields, which are high enough to saturate the ferrimagnetic minerals, however, still low enough that the torque resulting from the haematite is linear with field, allow for the separation of the three magnetic anisotropy components. The method has been applied to haematite single crystals in which no paramagnetic or ferrimagnetic components have been found contribute to the torque signal. The mean direction of the poles to the crystallographic basal plane in the haematite single crystals is subparallel to the minimum-susceptibility direction measured in low-field. The separation analysis has also been applied to highly deformed red beds from the Lower Glarus nappe complex (Switzerland). No ferrimagnetic phases are present in the rocks and, therefore, they cannot contribute to the anisotropy of magnetic susceptibility. The magnetic fabric arises from a paramagnetic subfabric carried by the phyllosilicate minerals and haematite, in which the basal planes of both phases are in the cleavage plane. The measured magnetic lineation seen in low-field anisotropy of magnetic susceptibility appears to be an apparent lineation that arises from a weak girdling of haematite and the paramagnetic minerals conforming the roc

Evidence for weak ferromagnetic moment within the basal plane of hematite natural crystals at low temperature

Lowerature magnetization of hematite within the basal plane has been studied in a collection of natural crystals by means of torque magnetometry. Comparison between the torque curves at room temperature and at 77 K allows identification of a weak ferromagnetic moment constrained within the basal plane at temperatures well below the Morin transition. Annealing the samples produces the expected reduction of the weak ferromagnetic moment, but there is also a relationship between the ferromagnetic moment before and after annealing. Lowerature measurements after the annealing experiment reveal the presence of a weak ferromagnetic moment that survives the annealing. This observation suggests the magnetic structure of natural hematite crystals below the Morin transition can still be a carrier of magnetization. Key Points A weak ferromagnetic (WFM) moment is detected below the Morin transition The WFM lies within the basal plane Natural Hematite is not a pure AF below TM ©2013. American Geophysical Union. All Rights Reserved.Peer Reviewe

Give My Regards To Broadway

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Entropy-based adaptive Hamiltonian Monte Carlo

Hamiltonian Monte Carlo (HMC) is a popular Markov Chain Monte Carlo (MCMC) algorithm to sample from an unnormalized probability distribution. A leapfrog integrator is commonly used to implement HMC in practice, but its performance can be sensitive to the choice of mass matrix used therein. We develop a gradient-based algorithm that allows for the adaptation of the mass matrix by encouraging the leapfrog integrator to have high acceptance rates while also exploring all dimensions jointly. In contrast to previous work that adapt the hyperparameters of HMC using some form of expected squared jumping distance, the adaptation strategy suggested here aims to increase sampling efficiency by maximizing an approximation of the proposal entropy. We illustrate that using multiple gradients in the HMC proposal can be beneficial compared to a single gradient-step in Metropolis-adjusted Langevin proposals. Empirical evidence suggests that the adaptation method can outperform different versions of HMC schemes by adjusting the mass matrix to the geometry of the target distribution and by providing some control on the integration time

Entropy-based adaptive Hamiltonian Monte Carlo

Hamiltonian Monte Carlo (HMC) is a popular Markov Chain Monte Carlo (MCMC) algorithm to sample from an unnormalized probability distribution. A leapfrog integrator is commonly used to implement HMC in practice, but its performance can be sensitive to the choice of mass matrix used therein. We develop a gradient-based algorithm that allows for the adaptation of the mass matrix by encouraging the leapfrog integrator to have high acceptance rates while also exploring all dimensions jointly. In contrast to previous work that adapt the hyperparameters of HMC using some form of expected squared jumping distance, the adaptation strategy suggested here aims to increase sampling efficiency by maximizing an approximation of the proposal entropy. We illustrate that using multiple gradients in the HMC proposal can be beneficial compared to a single gradient-step in Metropolis-adjusted Langevin proposals. Empirical evidence suggests that the adaptation method can outperform different versions of HMC schemes by adjusting the mass matrix to the geometry of the target distribution and by providing some control on the integration time

A refined biomonitoring study of airborne particulate matter pollution in Rome, with magnetic measurements on Quercus Ilex tree leaves

Elevated levels of airborne particulate matter (PM) are a current problem for air quality in many major metropolitan areas. Many European cities have tightened the PM limits in the air, due to advances in monitoring PM levels. In order to establish guidelines for monitoring and curbing anthropogenic PM output, a better understanding of its origin, composition and diffusion is required. Biomonitoring of magnetic properties of tree leaves has been suggested previously to be a good approach to measure pollution levels in cities both in space and time. We report on a magnetic biomonitoring study of PM in the city of Rome, conducted from 2005 October to December. We collected approximately 180 different sample sets of tree leaves of Quercus ilex, an evergreen oak widely distributed in Rome, at 112 different locations. Specific magnetic susceptibility χ of the leaf is used as a fast, easy and cost-effective proxy to assess levels of primary anthropogenic airborne PM pollution. Highly polluted areas correlate with high traffic areas, with an average susceptibility value of χ = 3.2 × 10−7 m3 kg−1. Low traffic zones are characterized by values more than an order of magnitude lower at χ = 1.4 × 10−8 m3 kg−1, and the background magnetic susceptibility is around χ = 2.6 × 10−9 m3 kg−1. The data show that distance dependence from the source is the most significant factor for the concentration of magnetic PM, and that pollution levels and sources can be reliably delineated by measuring magnetic susceptibility values on tree leaf samples of Q. ilex. A new protocol for magnetic susceptibility measurements is proposed, in order to account for changes due to water evaporation in the leaves as a function of time after collection of the samples. Additional magnetic analyses, such as acquisition of artificial remanences and hysteresis properties, were used to characterize the mineralogy and grain size of the magnetic PM. The results indicate that the population of ferrimagnetic phases have a homogenous composition and grain size throughout the investigated are