Planet Trial and Error: A Student\u27s Guide to Film Preproduction

This article highlights the importance of preproduction to the filmmaking process and provides a series of steps and guidelines meant to aid student filmmakers in the preproduction phase of their own films. The research was gathered from various filmmaking textbooks of note and from the personal experiences of the author during the making of his capstone film project

Optimization of Stroboscopic Electron Deflection Systems

Highly corrected electron-beam blanking systems (EBBS) are required for analyzing fast periodic processes at submicron spatial resolutions by stroboscopic methods. The deleterious degradation of the probe during the blanking operation can be avoided by a new straight-vision deflection system. Chopping of the beam is performed within this system by deflecting it across a knife edge. Calculations demonstrate that this system should be able to generate almost rectangular beam pulses with rise times of a few picoseconds and spot sizes smaller than 0.5 µm. The proposed EBBS consists of two wedge-shaped plate capacitors located symmetrically about the midplane of a rotationally symmetric double lens. Time-of-flight effects are largely compensated by driving the two capacitors as a traveling-wave structure to yield resonance deflection

Biological Upgrading of Hemicellulose Derived Xylose

As changing climates, resource scarcity, and policy drivers force society toward a future based on renewable resources, technical efforts must be made to achieve the best possible use of all resources. The highest value use for lignocellulosic biomass is achieved through a biorefinery where lignocellulosic biomass is broken into its substituents. While the cellulose and lignin portions (roughly 50% and 25% dry wt. respectively) of biomass have well defined end uses, a high value or high demand use for hemicelluloses (25% dry wt.) derived from lignocellulosic biomass in a biorefinery has yet to be found. These hemicelluloses could be biologically upgraded to lipids by microalgae and subsequently converted to biodiesel. Recent work has shown that many species of microalgae, such as Chlorella protothecoides, can produce lipids at very high yield and that some species can grow heterotrophically on xylose (a five carbon sugar derived from the hemicellulosic fraction of lignocellulosic biomass). Near infrared (NIR) absorbance will be used to monitor sugar concentrations in growth media while Nile red fluorometry will be used to monitor lipid concentrations. By tracking the lipid productivity and growth rate of heterotrophic Chlorella protothecoides in a variety of nitrogen and xylose conditions, this work will identify the optimal conditions under which hydrolyzed hemicelluloses (xylose) could be biologically upgraded to lipids and eventually biodiesel

Nonparametric Estimation of Conditional Incremental Effects

Conditional effect estimation has great scientific and policy importance because interventions may impact subjects differently depending on their characteristics. Most research has focused on estimating the conditional average treatment effect (CATE). However, identification of the CATE requires all subjects have a non-zero probability of receiving treatment, or positivity, which may be unrealistic in practice. Instead, we propose conditional effects based on incremental propensity score interventions, which are stochastic interventions where the odds of treatment are multiplied by some factor. These effects do not require positivity for identification and can be better suited for modeling scenarios in which people cannot be forced into treatment. We develop a projection estimator and a flexible nonparametric estimator that can each estimate all the conditional effects we propose and derive model-agnostic error guarantees showing both estimators satisfy a form of double robustness. Further, we propose a summary of treatment effect heterogeneity and a test for any effect heterogeneity based on the variance of a conditional derivative effect and derive a nonparametric estimator that also satisfies a form of double robustness. Finally, we demonstrate our estimators by analyzing the effect of intensive care unit admission on mortality using a dataset from the (SPOT)light study

Lifted Regression/Reconstruction Networks

In this work we propose lifted regression/reconstruction networks(LRRNs), which combine lifted neural networks with a guaranteed Lipschitz continuity property for the output layer. Lifted neural networks explicitly optimize an energy model to infer the unit activations and therefore—in contrast to standard feed-forward neural networks—allow bidirectional feedback between layers. So far lifted neural networks have been modelled around standard feed-forward architectures. We propose to take further advantage of the feedback property by letting the layers simultaneously perform regression and reconstruction. The resulting lifted network architecture allows to control the desired amount of Lipschitz continuity, which is an important feature to obtain adversarially robust regression and classification methods. We analyse and numerically demonstrate applications for unsupervised and supervised learnin

Heterogeneous interventional indirect effects with multiple mediators: non-parametric and semi-parametric approaches

We propose semi- and non-parametric methods to estimate conditional interventional effects in the setting of two discrete mediators whose causal ordering is unknown. Average interventional indirect effects have been shown to decompose an average treatment effect into a direct effect and interventional indirect effects that quantify effects of hypothetical interventions on mediator distributions. Yet these effects may be heterogeneous across the covariate distribution. We consider the problem of estimating these effects at particular points. We propose an influence-function based estimator of the projection of the conditional effects onto a working model, and show under some conditions that we can achieve root-n consistent and asymptotically normal estimates. Second, we propose a fully non-parametric approach to estimation and show the conditions where this approach can achieve oracle rates of convergence. Finally, we propose a sensitivity analysis for the conditional effects in the presence of mediator-outcome confounding. We propose estimating bounds on the conditional effects using these same methods, and show that these results easily extend to allow for influence-function based estimates of the bounds on the average effects. We conclude examining heterogeneous effects with respect to the effect of COVID-19 vaccinations on depression during February 2021

On the energy momentum dispersion in the lattice regularization

For a free scalar boson field and for U(1) gauge theory finite volume (infrared) and other corrections to the energy-momentum dispersion in the lattice regularization are investigated calculating energy eigenstates from the fall off behavior of two-point correlation functions. For small lattices the squared dispersion energy defined by $E_{\rm dis}^2=E_{\vec{k}}^2-E_0^2-4\sum_{i=1}^{d-1}\sin(k_i/2)^2$ is in both cases negative ($d$ is the Euclidean space-time dimension and $E_{\vec{k}}$ the energy of momentum $\vec{k}$ eigenstates). Observation of $E_{\rm dis}^2=0$ has been an accepted method to demonstrate the existence of a massless photon ($E_0=0$) in 4D lattice gauge theory, which we supplement here by a study of its finite size corrections. A surprise from the lattice regularization of the free field is that infrared corrections do {\it not} eliminate a difference between the groundstate energy $E_0$ and the mass parameter $M$ of the free scalar lattice action. Instead, the relation $E_0=\cosh^{-1} (1+M^2/2)$ is derived independently of the spatial lattice size.Comment: 9 pages, 2 figures. Parts of the paper have been rewritten and expanded to clarify the result

Detection of Intestinal Pathogens in River, Shore, and Drinking Water in Lima, Peru

Water quality management is an ongoing struggle for many locations worldwide. Current testing of water supplies can be time-consuming, expensive, and lack sensitivity. This study describes an alternative, easy-to-use, and inexpensive method to water sampling and testing at remote locations. This method was employed to detect a number of intestinal pathogens in various locations of Lima, Peru. A total of 34 PCR primer pairs were tested for specificity and high-yield amplification for 12 different pathogens using known DNA templates. Select primers for each pathogen were then tested for minimum detection limits of DNA. Water samples were collected from 22 locations. PCR was used to detect the presence of a pathogen, virulence factors, or differentiate between pathogenic species. In 22 water samples, cholera toxin gene was detected in 4.5% of samples, C. perfringens DNA was detected in 50% of samples, E. histolytica DNA was detected in 54.5% of samples, Giardia intestinalis DNA was detected in 4.5% of samples, Leptospira spp. DNA was detected in 29% of samples, and T. gondii DNA was detected in 31.8% of samples. DNA from three pathogens, C. perfringens, E. histolytica, and T. gondii, were found in residential samples, which accounted for 10 out of 22 samples

Detection of Intestinal Pathogens in River, Shore, and Drinking Water in Lima, Peru

Water quality management is an ongoing struggle for many locations worldwide. Current testing of water supplies can be time-consuming, expensive, and lack sensitivity. This study describes an alternative, easy-to-use, and inexpensive method to water sampling and testing at remote locations. This method was employed to detect a number of intestinal pathogens in various locations of Lima, Peru. A total of 34 PCR primer pairs were tested for specificity and high-yield amplification for 12 different pathogens using known DNA templates. Select primers for each pathogen were then tested for minimum detection limits of DNA. Water samples were collected from 22 locations. PCR was used to detect the presence of a pathogen, virulence factors, or differentiate between pathogenic species. In 22 water samples, cholera toxin gene was detected in 4.5% of samples, C. perfringens DNA was detected in 50% of samples, E. histolytica DNA was detected in 54.5% of samples, Giardia intestinalis DNA was detected in 4.5% of samples, Leptospira spp. DNA was detected in 29% of samples, and T. gondii DNA was detected in 31.8% of samples. DNA from three pathogens, C. perfringens, E. histolytica, and T. gondii, were found in residential samples, which accounted for 10 out of 22 samples

Do Juvenile Nearctic River Otters (Lontra canadensis) Contribute to Fall Scent Marking?

We present photographic evidence in support of the hypothesis that juvenile Nearctic River Otters (Lontra canadensis) contribute to the observed fall peak in scent marking