Can FAO's measure of chronic undernourishment be strengthened?

In its Sixth World Food Survey released at the 1996 World Food Summit, the Food and Agriculture Organization of the United Nations (FAO) reported that 841 million people in developing countries are chronically undernourished. This number and its country- and regional-level disaggregations have proved tremendously useful to countless aid agencies and researchers. In the context of a recent wave of new nationally-representative household food consumption and expenditure data, this paper examines the estimation methodology underlying this food insecurity indicator, which relies on national aggregate measures of food availability and distribution. The paper finds that the measure is methodologically biased toward national food availability and does not fully account for the effects of poverty—the most widespread cause of food insecurity in developing countries. The implications of this bias for use of the indicator in cross-country comparisons of food insecurity and for tracking changes in it over time are drawn out. The paper concludes by arguing that the time has come to review the potential for employing the new household survey data for strengthening the empirical foundations of the FAO's measure of chronic undernourishment.Food security Measurement Methodology. ,Food consumption Statistics. ,

Poly Pelletizer: Recycled Pet Pellets From Water Bottles

Plastic water bottles comprise a large amount of waste worldwide. The goal of the Poly Pelletizer project is to create a system that will turn water bottles into polyethylene terephthalate (PET) pellets compatible with extruders to produce 3-D printer lament, along with other recycling applications.The system promotes a sustainable solution to plastic pollution by giving manufactures, particularly in developing nations, the means to produce their own bulk materials using waste plastic. Shrinking industrial recycling processes to a workbench scale gives individuals the ability to convert excess bottles into seemingly limitless products. The system works by using a dual heating and pressure system to both evenly mix and melt the plastic before pushing the resin through a die. The Poly Pelletizer successfully created pellets using various mixtures of virgin PET and shredded water bottles

Validation of CReSIS Synthetic Aperture Radar Processor and Optimal Processing Parameters

Sounding the ice sheets of Greenland and Antarctica is a vital component in determining the effect of global warming on sea level rise. Of particular importance are measurements of the bedrock topography of the outlet glaciers that transport ice from the ice sheet's interior to the margin where it calves into icebergs, contributing to sea level rise. These outlet glaciers are difficult to sound due to crevassing caused by the relatively fast movement of the ice in the glacial channel and higher signal attenuation caused by warmer ice. The Center for Remote Sensing of Ice Sheets (CReSIS) uses multi-channel airborne radars which employ methods for achieving better resolution and signal-to-noise ratio (SNR) to better sound outlet glaciers. Synthetic aperture radar (SAR) techniques are used in the along-track dimension, pulse compression in the range dimension, and an antenna array in the cross-track dimension. CReSIS has developed the CReSIS SAR processor (CSARP) to effectively and efficiently process the data collected by these radars in each dimension. To validate the performance of this processor a SAR simulator was developed with the functionality to test the implementation of the processing algorithms in CSARP. In addition to the implementation of this simulator for validation of processing the data in the along-track, cross-track and range dimensions, there are a number of data-dependent processing steps that can affect the quality of the final data product. CSARP was tested with an ideal simulated point target in white Gaussian noise. The SNR change achieved by range compression, azimuth compression, array combination with and without matched filtering, and lever arm application were all within .2 dB of the theoretical expectation. Channel equalization, when paired with noise-based matched filtering, provided 1-2 dB of gain on average but significantly less than the expected gain. Extending the SAR aperture length to sound bedrock will improve the along-track resolution, but at the expense of SNR. Increasing the taper of a window in the fast-time and slow-time will slightly improve the SNR of the data. Changing the relative permittivity used to process the data improved the resulting SNR by no more than 0.025 dB for the test dataset

Kondo insulators in the periodic Anderson model: a local moment approach

The symmetric periodic Anderson model is well known to capture the essential physics of Kondo insulator materials. Within the framework of dynamical mean-field theory, we develop a local moment approach to its single-particle dynamics in the paramagnetic phase. The approach is intrinsically non-perturbative, encompasses all energy scales and interaction strengths, and satisfies the low-energy dictates of Fermi liquid theory. It captures in particular the strong coupling behaviour and exponentially small quasiparticle scales characteristic of the Kondo lattice regime, as well as simple perturbative behaviour in weak coupling. Particular emphasis is naturally given to strong coupling dynamics, where the resultant clean separation of energy scales enables the scaling behaviour of single-particle spectra to be obtained.Comment: 15 pages, 10 postscript figures, accepted for publication in EPJ B; HyperTex disable

Recommending Learning Algorithms and Their Associated Hyperparameters

The success of machine learning on a given task dependson, among other things, which learning algorithm is selected and its associated hyperparameters. Selecting an appropriate learning algorithm and setting its hyperparameters for a given data set can be a challenging task, especially for users who are not experts in machine learning. Previous work has examined using meta-features to predict which learning algorithm and hyperparameters should be used. However, choosing a set of meta-features that are predictive of algorithm performance is difficult. Here, we propose to apply collaborative filtering techniques to learning algorithm and hyperparameter selection, and find that doing so avoids determining which meta-features to use and outperforms traditional meta-learning approaches in many cases.Comment: Short paper--2 pages, 2 table

Exploring Cycloaddition Reactions for the Synthesis of Novel Organic Compounds, Including Microwave Promotion

The work presented here focuses on using the Diels‐Alder reaction as the first step in “catch‐and‐release” strategies for isolating useful organic compounds, especially from natural product extracts. The purpose is to discover better isolation methods than those currently available. The proposed method uses a dienophile attached to a polymeric resin, allowing separation of the adduct from the filtrate by simply rinsing the polymer‐bound adduct with solvents to remove extraneous compounds. Different dienophiles were tested, including 4‐phenyl‐1,2,4‐triazoline‐3,5‐dione, dimethyl acetylenedicarboxylate, and diphenyl acetylene. These were reacted with the furan ring of salvinorin A, an extract obtained from a natural product, which acted as the diene. These were tested to find dienophiles that could either potentially be fixed to a polymeric resin or provide some insight as to what conditions salvinorin A might react under. These were reacted in a microwave instrument and characterized with thin layer chromatography and infrared spectrometry. Initial results suggest new Diels‐Alder adducts based on the salvinorin A skeleton, and one reaction that proceeds without heat. Finally, one polymer‐bound dienophile, diethy diazodicarboxylate, was reacted with salvinorin A to produce a polymer‐bound Diels‐Alder adduct

Exploring Cycloaddition Reactions for the Synthesis of Novel Organic Compounds, Including Microwave Promotion

The work presented here focuses on using the Diels‐Alder reaction as the first step in “catch‐and‐release” strategies for isolating useful organic compounds, especially from natural product extracts. The purpose is to discover better isolation methods than those currently available. The proposed method uses a dienophile attached to a polymeric resin, allowing separation of the adduct from the filtrate by simply rinsing the polymer‐bound adduct with solvents to remove extraneous compounds. Different dienophiles were tested, including 4‐phenyl‐1,2,4‐triazoline‐3,5‐dione, dimethyl acetylenedicarboxylate, and diphenyl acetylene. These were reacted with the furan ring of salvinorin A, an extract obtained from a natural product, which acted as the diene. These were tested to find dienophiles that could either potentially be fixed to a polymeric resin or provide some insight as to what conditions salvinorin A might react under. These were reacted in a microwave instrument and characterized with thin layer chromatography and infrared spectrometry. Initial results suggest new Diels‐Alder adducts based on the salvinorin A skeleton, and one reaction that proceeds without heat. Finally, one polymer‐bound dienophile, diethy diazodicarboxylate, was reacted with salvinorin A to produce a polymer‐bound Diels‐Alder adduct

A LOW-POWER APPROACH FOR FRONT END BIOLOGICAL SIGNAL CONDITIONING

In a lab-on-a-chip (LOC) application, the measurement of small analog signals such as local temperature variation often involves detection of very low-level signals in a noisy micro-scale environment. This is true for other biomedical monitoring systems as well. These systems observe various physiological parameters or electrochemical reactions that need to be tracked electrically. For temperature measurement pyroelectric transducers represent an efficient solution in terms of speed, sensitivity, and scale of integration, especially when prompt and accurate temperature monitoring is desired. The ability to perform laboratory operations on a small scale using miniaturized LOC devices is a promising biosensing technique. The advantages of using LOC include faster time of analysis, low reagent costs, and reduced amount of chemical wastes. The application of portable, easy-to-use, and highly sensitive LOC biosensors for real-time detection could offer significant advantages over the currently used analytical methods. This thesis presents design and analysis of a low frequency charge amplifier suited for biological sample applications, with a wide window for signal size and speed. The charge amp has been fabricated in a commercial 180nm CMOS process. The circuit has been tested for signals in 100Hz-100kHz range with a max charge of 250nC. This thesis begins with a study of the transducer that produces the charge for the charge amplifier. Next it moves into the design of low power charge sensitive amplifiers, along with an analysis of various components essential to the makeup of the design. The charge amplifier circuit is simulated using analytical model as well as numerical simulation tools. Finally, the test setup is presented and the measurement results are compared with those obtained from simulation

Power Output Modeling and Optimization for a Single Axis Tracking Solar Farm on Skewed Topography Causing Extensive Shading

Many utility-scale solar farms use horizontal single axis tracking to follow the sun throughout the day and produce more energy. Solar farms on skewed topography produce complex shading patterns that require precise modeling techniques to determine the energy output. To accomplish this, MATLAB was used in conjunction with NREL weather predictions to predict shading shapes and energy outputs. The MATLAB models effectively predicted the sun’s position in the sky, panel tilt angle throughout the day, irradiance, cell temperature, and shading size. The Cal Poly Gold Tree Solar Farm was used to validate these models for various lengths of time. First, the models predicted the shading and power output for a single point in time. Four points of time measurements were taken; resulting in 6 to 32 percent difference in shade height, 5 to 60 percent difference for shade length, and 29 to 59 percent difference for power output. This shows the difficulty of predicting a point in time and suggests the sensitivity of numerous variables like solar position, torque tube position, panel tilt, and time itself. When predicting the power over an entire day, the power output curves for a single inverter matched almost exactly except for in the middle of the day due to possible inaccurate cell temperature modeling or the lack of considering degradation and soiling. Since the backtracking region of the power curve is modeled accurately, the optimization routine could be used to reduce interrow shading and maximize the energy output for a single zone of the solar field. By assuming every day is sunny, the optimization routine adjusted the onset of backtracking to improve the energy output by 117,695 kilowatt hours for the year or 8.14 percent compared to the nominal settings. The actual solar farm will likely never see this increase in energy due to cloudy days but should improve by a similar percentage. Further optimization of other zones can be analyzed to optimize the entire solar field