Improving Academic Performance Through the Enhancement of Teacher/Student Relationships: The Relationship Teaching Model

The authors present their case for the development of strong and appropriate relationships with students as a key for success in college teaching. The model of Relationship Teaching includes a wide and varied agenda of techniques and commitments with which to strengthen the interpersonal relationships present in the educational environment

Asp-120 Locates Zn2 for Optimal Metallo-β-lactamase Activity

Metallo-β-lactamases are zinc-dependent hydrolases that inactivate β-lactam antibiotics, rendering bacteria resistant to them. Asp-120 is fully conserved in all metallo-β-lactamases and is central to catalysis. Several roles have been proposed for Asp-120, but so far there is no agreed consensus. We generated four site-specifically substituted variants of the enzyme BcII from Bacillus cereus as follows: D120N, D120E, D120Q, and D120S. Replacement of Asp-120 by other residues with very different metal ligating capabilities severely impairs the lactamase activity without abolishing metal binding to the mutated site. A kinetic study of these mutants indicates that Asp-120 is not the proton donor, nor does it play an essential role in nucleophilic activation. Spectroscopic and crystallographic analysis of D120S BcII, the least active mutant bearing the weakest metal ligand in the series, reveals that this enzyme is able to accommodate a dinuclear center and that perturbations in the active site are limited to the Zn2 site. It is proposed that the role of Asp-120 is to act as a strong Zn2 ligand, locating this ion optimally for substrate binding, stabilization of the development of a partial negative charge in the β-lactam nitrogen, and protonation of this atom by a zinc-bound water molecule

From Random Matrices to Stochastic Operators

We propose that classical random matrix models are properly viewed as finite difference schemes for stochastic differential operators. Three particular stochastic operators commonly arise, each associated with a familiar class of local eigenvalue behavior. The stochastic Airy operator displays soft edge behavior, associated with the Airy kernel. The stochastic Bessel operator displays hard edge behavior, associated with the Bessel kernel. The article concludes with suggestions for a stochastic sine operator, which would display bulk behavior, associated with the sine kernel.Comment: 41 pages, 5 figures. Submitted to Journal of Statistical Physics. Changes in this revision: recomputed Monte Carlo simulations, added reference [19], fit into margins, performed minor editin

Prediction of the Aerothermodynamic Environment of the Huygens Probe

An investigation of the aerothermodynamic environment of the Huygens entry probe has been conducted. A Monte Carlo simulation of the trajectory of the probe during entry into Titan's atmosphere was performed to identify a worst-case heating rate trajectory. Flowfield and radiation transport computations were performed at points along this trajectory to obtain convective and radiative heat-transfer distributions on the probe's heat shield. This investigation identified important physical and numerical factors, including atmospheric CH4 concentration, transition to turbulence, numerical diffusion modeling, and radiation modeling, which strongly influenced the aerothermodynamic environment

Scenic: A Language for Scenario Specification and Scene Generation

We propose a new probabilistic programming language for the design and analysis of perception systems, especially those based on machine learning. Specifically, we consider the problems of training a perception system to handle rare events, testing its performance under different conditions, and debugging failures. We show how a probabilistic programming language can help address these problems by specifying distributions encoding interesting types of inputs and sampling these to generate specialized training and test sets. More generally, such languages can be used for cyber-physical systems and robotics to write environment models, an essential prerequisite to any formal analysis. In this paper, we focus on systems like autonomous cars and robots, whose environment is a "scene", a configuration of physical objects and agents. We design a domain-specific language, Scenic, for describing "scenarios" that are distributions over scenes. As a probabilistic programming language, Scenic allows assigning distributions to features of the scene, as well as declaratively imposing hard and soft constraints over the scene. We develop specialized techniques for sampling from the resulting distribution, taking advantage of the structure provided by Scenic's domain-specific syntax. Finally, we apply Scenic in a case study on a convolutional neural network designed to detect cars in road images, improving its performance beyond that achieved by state-of-the-art synthetic data generation methods.Comment: 41 pages, 36 figures. Full version of a PLDI 2019 paper (extending UC Berkeley EECS Department Tech Report No. UCB/EECS-2018-8

A “Rosetta Stone” for Metazoan Zooplankton: DNA Barcode Analysis of Species Diversity of the Sargasso Sea (Northwest Atlantic Ocean)

Species diversity of the metazoan holozooplankton assemblage of the Sargasso Sea, Northwest Atlantic Ocean, was examined through coordinated morphological taxonomic identification of species and DNA sequencing of a ∼650 base-pair region of mitochondrial cytochrome oxidase I (mtCOI) as a DNA barcode (i.e., short sequence for species recognition and discrimination). Zooplankton collections were made from the surface to 5,000 meters during April, 2006 on the R/V R.H. Brown. Samples were examined by a ship-board team of morphological taxonomists; DNA barcoding was carried out in both ship-board and land-based DNA sequencing laboratories. DNA barcodes were determined for a total of 297 individuals of 175 holozooplankton species in four phyla, including: Cnidaria (Hydromedusae, 4 species; Siphonophora, 47); Arthropoda (Amphipoda, 10; Copepoda, 34; Decapoda, 9; Euphausiacea, 10; Mysidacea, 1; Ostracoda, 27); and Mollusca (Cephalopoda, 8; Heteropoda, 6; Pteropoda, 15); and Chaetognatha (4). Thirty species of fish (Teleostei) were also barcoded. For all seven zooplankton groups for which sufficient data were available, Kimura-2-Parameter genetic distances were significantly lower between individuals of the same species (mean=0.0114; S.D. 0.0117) than between individuals of different species within the same group (mean=0.3166; S.D. 0.0378). This difference, known as the barcode gap, ensures that mtCOI sequences are reliable characters for species identification for the oceanic holozooplankton assemblage. In addition, DNA barcodes allow recognition of new or undescribed species, reveal cryptic species within known taxa, and inform phylogeographic and population genetic studies of geographic variation. The growing database of “gold standard” DNA barcodes serves as a Rosetta Stone for marine zooplankton, providing the key for decoding species diversity by linking species names, morphology, and DNA sequence variation. In light of the pivotal position of zooplankton in ocean food webs, their usefulness as rapid responders to environmental change, and the increasing scarcity of taxonomists, the use of DNA barcodes is an important and useful approach for rapid analysis of species diversity and distribution in the pelagic community

Leveraging Domain Adaptation for Accurate Machine Learning Predictions of New Halide Perovskites

We combine graph neural networks (GNN) with an inexpensive and reliable structure generation approach based on the bond-valence method (BVM) to train accurate machine learning models for screening 222,960 halide perovskites using statistical estimates of the DFT/PBE formation energy (Ef), and the PBE and HSE band gaps (Eg). The GNNs were fined tuned using domain adaptation (DA) from a source model, which yields a factor of 1.8 times improvement in Ef and 1.2 - 1.35 times improvement in HSE Eg compared to direct training (i.e., without DA). Using these two ML models, 48 compounds were identified out of 222,960 candidates as both stable and that have an HSE Eg that is relevant for photovoltaic applications. For this subset, only 8 have been reported to date, indicating that 40 compounds remain unexplored to the best of our knowledge and therefore offer opportunities for potential experimental examination

Progress in Interferometry for LISA at JPL

Recent advances at JPL in experimentation and design for LISA interferometry include the demonstration of Time Delay Interferometry using electronically separated end stations, a new arm-locking design with improved gain and stability, and progress in flight readiness of digital and analog electronics for phase measurements.Comment: 11 pages, 9 figures, LISA 8 Symposium, Stanford University, 201

Composition of dissolved organic matter within a lacustrine environment

Freshwater dissolved organic matter (DOM) is a complex mixture of chemical components that are central to many environmental processes, including carbon and nitrogen cycling. However, questions remain as to its chemical characteristics, sources and transformation mechanisms. Here, we employ 1- and 2-D nuclear magnetic resonance (NMR) spectroscopy to investigate the structural components of lacustrine DOM from Ireland, and how it varies within a lake system, as well as to assess potential sources. Major components found, such as carboxyl-rich alicyclic molecules (CRAM) are consistent with those recently identified in marine and freshwater DOM. Lignin-type markers and protein/peptides were identified and vary spatially. Phenylalanine was detected in lake areas influenced by agriculture, whereas it is not detectable where zebra mussels are prominent. The presence of peptidoglycan, lipoproteins, large polymeric carbo- hydrates and proteinaceous material supports the substantial contribution of material derived from microorganisms. Evidence is provided that peptidoglycan and silicate species may in part originate from soil microbes