ARM Climate Research Facility Quarterly Value-Added Product Report Third Quarter: April 01?June 30, 2011

The purpose of this report is to provide a concise status update for value-added products (VAP) implemented by the Atmospheric Radiation Measurement Climate Research Facility. The report is divided into the following sections: (1) new VAPs for which development has begun, (2) progress on existing VAPs, (3) future VAPs that have been recently approved, (4) other work that leads to a VAP, and (5) top requested VAPs from the archiv

Bacterial citrate lyase

Bacterial citrate lyase, the key enzyme in fermentation of citrate, has interesting structural features. The enzyme is a complex assembled from three non-identical subunits, two having distinct enzymatic activities and one functioning as an acyl-carrier protein. Bacterial citrate lyase, si-citrate synthase and ATP-citrate lyase have similar stereospecificities and show cofactor cross-reactions. On account of these common features, the citrate enzymes are promising markers in the study of evolutionary biology. The occurrence, function, regulation and structure of bacterial citrate lyase are reviewed in this article

A Conformational Switch in the Active Site of BT_2972, a Methyltransferase from an Antibiotic Resistant Pathogen B. thetaiotaomicron

Methylation is one of the most common biochemical reactions involved in cellular and metabolic functions and is catalysed by the action of methyltransferases. Bacteroides thetaiotaomicron is an antibiotic-resistant bacterium that confers resistance through methylation, and as yet, there is no report on the structure of methyltransferases from this bacterium. Here, we report the crystal structure of an AdoMet-dependent methyltransferase, BT_2972 and its complex with AdoMet and AdoHcy for B. thetaiotaomicron VPI-5482 strain along with isothermal titration calorimetric assessment of the binding affinities. Comparison of the apo and complexed BT_2972 structures reveals a significant conformational change between open and closed forms of the active site that presumably regulates the association with cofactors and may aid interaction with substrate. Together, our analysis suggests that BT_2972 is a small molecule methyltransferase and might catalyze two O-methylation reaction steps involved in the ubiquinone biosynthesis pathway

Domain Adaptation under Missingness Shift

Rates of missing data often depend on record-keeping policies and thus may change across times and locations, even when the underlying features are comparatively stable. In this paper, we introduce the problem of Domain Adaptation under Missingness Shift (DAMS). Here, (labeled) source data and (unlabeled) target data would be exchangeable but for different missing data mechanisms. We show that when missing data indicators are available, DAMS can reduce to covariate shift. Focusing on the setting where missing data indicators are absent, we establish the following theoretical results for underreporting completely at random: (i) covariate shift is violated (adaptation is required); (ii) the optimal source predictor can perform worse on the target domain than a constant one; (iii) the optimal target predictor can be identified, even when the missingness rates themselves are not; and (iv) for linear models, a simple analytic adjustment yields consistent estimates of the optimal target parameters. In experiments on synthetic and semi-synthetic data, we demonstrate the promise of our methods when assumptions hold. Finally, we discuss a rich family of future extensions

Enabling Future Sustainability Transitions: An Urban Metabolism Approach to Los Angeles Pincetl et al. Enabling Future Sustainability Transitions

Summary: This synthesis article presents an overview of an urban metabolism (UM) approach using mixed methods and multiple sources of data for Los Angeles, California. We examine electric energy use in buildings and greenhouse gas emissions from electricity, and calculate embedded infrastructure life cycle effects, water use and solid waste streams in an attempt to better understand the urban flows and sinks in the Los Angeles region (city and county). This quantification is being conducted to help policy-makers better target energy conservation and efficiency programs, pinpoint best locations for distributed solar generation, and support the development of policies for greater environmental sustainability. It provides a framework to which many more UM flows can be added to create greater understanding of the study area's resource dependencies. Going forward, together with policy analysis, UM can help untangle the complex intertwined resource dependencies that cities must address as they attempt to increase their environmental sustainability

Selective Harmonic Elimination of The Multilevel Inverter Using Artificial Neural Network

The multilevel inverter is a powerful electronic device widely used for high power utility applications. The main purpose of the multilevel inverter is to provide sinusoidal waveforms with low level harmonic content to reduce distortion. Improving the inverter performance means improving the quality of the output voltage. Here we made an attempt of eliminating the desired harmonics in the output voltage waveform by solving the system of non-linear transcendental equations for getting the solution vector for different modulation index, here the solution of this system of equations was obtained using the method of least-squares (numerical method). After getting the solutions we have chosen the feed-foreword structure of ANN (artificial neural network). The ANN was made to learn by using the error-backpropagation algorithm. And finally we have obtained the weights to the corresponding neural network. The multilevel inverter chosen was three level cascaded inverter, which was simulated in the Matlab for different modulation indexe

Photometry of the solar corona of March 7, 1970

Isophotes obtained by equidensitometry techniques from four exposures of the March 7, 1970 corona are used for derivation of intensity distributions along the equator, poles, streamers and dark 'gaps' in the visible corona. The distributions differ from the van de Hulst curves for a maximum corona. The Kodaikanal measures agree well with the NRL measures of the outer corona made from a rocket coronagraph and together provide data from 1.2R⊙ to 8.0R⊙ along the solar equator. Radial intensity gradients for different position angles and the Ludendorff parameters obtained, characterize this corona as typical of the solar maximum

RLSbench: Domain Adaptation Under Relaxed Label Shift

Despite the emergence of principled methods for domain adaptation under label shift, their sensitivity to shifts in class conditional distributions is precariously under explored. Meanwhile, popular deep domain adaptation heuristics tend to falter when faced with label proportions shifts. While several papers modify these heuristics in attempts to handle label proportions shifts, inconsistencies in evaluation standards, datasets, and baselines make it difficult to gauge the current best practices. In this paper, we introduce RLSbench, a large-scale benchmark for relaxed label shift, consisting of $>$500 distribution shift pairs spanning vision, tabular, and language modalities, with varying label proportions. Unlike existing benchmarks, which primarily focus on shifts in class-conditional $p(x|y)$, our benchmark also focuses on label marginal shifts. First, we assess 13 popular domain adaptation methods, demonstrating more widespread failures under label proportion shifts than were previously known. Next, we develop an effective two-step meta-algorithm that is compatible with most domain adaptation heuristics: (i) pseudo-balance the data at each epoch; and (ii) adjust the final classifier with target label distribution estimate. The meta-algorithm improves existing domain adaptation heuristics under large label proportion shifts, often by 2--10\% accuracy points, while conferring minimal effect ($<$0.5\%) when label proportions do not shift. We hope that these findings and the availability of RLSbench will encourage researchers to rigorously evaluate proposed methods in relaxed label shift settings. Code is publicly available at https://github.com/acmi-lab/RLSbench.Comment: Accepted at ICML 2023. Paper website: https://sites.google.com/view/rlsbench

Cloud Condensation Nuclei Profile Value-Added Product

The cloud condensation nuclei (CCN) concentration at cloud base is the most relevant measure of the aerosol that influences droplet formation in clouds. Since the CCN concentration depends on supersaturation, a more general measure of the CCN concentration is the CCN spectrum (values at multiple supersaturations). The CCN spectrum is now measured at the surface at several fixed ARM sites and by the ARM Mobile Facility (AMF), but is not measured at the cloud base. Rather than rely on expensive aircraft measurements for all studies of aerosol effects on clouds, a way to project CCN measurements at the surface to cloud base is needed. Remote sensing of aerosol extinction provides information about the vertical profile of the aerosol, but cannot be directly related to the CCN concentration because the aerosol extinction is strongly influenced by humidification, particularly near cloud base. Ghan and Collins (2004) and Ghan et al. (2006) propose a method to remove the influence of humidification from the extinction profiles and tie the “dry extinction” retrieval to the surface CCN concentration, thus estimating the CCN profile. This methodology has been implemented as the CCN Profile (CCNPROF) value-added product (VAP)

Raman Lidar Profiles?Temperature (RLPROFTEMP) Value-Added Product

The purpose of this document is to describe the Raman Lidar Profiles–Temperature (RLPROFTEMP) value-added product (VAP) and the procedures used to derive atmospheric temperature profiles from the raw RL measurements. Sections 2 and 4 describe the input and output variables, respectively. Section 3 discusses the theory behind the measurement and the details of the algorithm, including calibration and overlap correction