A penalty approach for nonlinear optimization with discrete design variables

Introduced here is a simple approach to minimization problems with discrete design variables by modifying the penaly function approach of converting the constrained problems into sequential unconstrained minimization technique (SUMT) problems. It was discovered, during the course of the present work, that a similar idea was suggested by Marcal and Gellatly. However, no further work has been encountered. A brief description of the SUMT is presented. The form of the penalty function for the discrete-valued design variables and strategy used for the implementation of the procedure is discussed next. Finally, several design examples are used to demonstrate the procedure, and results are compared with the ones available in the literature

Approaching the adiabatic timescale with machine-learning

The control and manipulation of quantum systems without excitation is challenging, due to the complexities in fully modeling such systems accurately and the difficulties in controlling these inherently fragile systems experimentally. For example, while protocols to decompress Bose-Einstein condensates (BEC) faster than the adiabatic timescale (without excitation or loss) have been well developed theoretically, experimental implementations of these protocols have yet to reach speeds faster than the adiabatic timescale. In this work, we experimentally demonstrate an alternative approach based on a machine learning algorithm which makes progress towards this goal. The algorithm is given control of the coupled decompression and transport of a metastable helium condensate, with its performance determined after each experimental iteration by measuring the excitations of the resultant BEC. After each iteration the algorithm adjusts its internal model of the system to create an improved control output for the next iteration. Given sufficient control over the decompression, the algorithm converges to a novel solution that sets the current speed record in relation to the adiabatic timescale, beating out other experimental realizations based on theoretical approaches. This method presents a feasible approach for implementing fast state preparations or transformations in other quantum systems, without requiring a solution to a theoretical model of the system. Implications for fundamental physics and cooling are discussed.Comment: 7 pages main text, 2 pages supporting informatio

Prediction of Neighbor-Dependent Microbial Interactions From Limited Population Data

Modulation of interspecies interactions by the presence of neighbor species is a key ecological factor that governs dynamics and function of microbial communities, yet the development of theoretical frameworks explicit for understanding context-dependent interactions are still nascent. In a recent study, we proposed a novel rule-based inference method termed the Minimal Interspecies Interaction Adjustment (MIIA) that predicts the reorganization of interaction networks in response to the addition of new species such that the modulation in interaction coefficients caused by additional members is minimal. While the theoretical basis of MIIA was established through the previous work by assuming the full availability of species abundance data in axenic, binary, and complex communities, its extension to actual microbial ecology can be highly constrained in cases that species have not been cultured axenically (e.g., due to their inability to grow in the absence of specific partnerships) because binary interaction coefficients – basic parameters required for implementing the MIIA – are inestimable without axenic and binary population data. Thus, here we present an alternative formulation based on the following two central ideas. First, in the case where only data from axenic cultures are unavailable, we remove axenic populations from governing equations through appropriate scaling. This allows us to predict neighbor-dependent interactions in a relative sense (i.e., fractional change of interactions between with versus without neighbors). Second, in the case where both axenic and binary populations are missing, we parameterize binary interaction coefficients to determine their values through a sensitivity analysis. Through the case study of two microbial communities with distinct characteristics and complexity (i.e., a three-member community where all members can grow independently, and a four-member community that contains member species whose growth is dependent on other species), we demonstrated that despite data limitation, the proposed new formulation was able to successfully predict interspecies interactions that are consistent with experimentally derived results. Therefore, this technical advancement enhances our ability to predict context-dependent interspecies interactions in a broad range of microbial systems without being limited to specific growth conditions as a pre-requisite

Minimal Interspecies Interaction Adjustment (MIIA): Inference of Neighbor-Dependent Interactions in Microbial Communities

An intriguing aspect in microbial communities is that pairwise interactions can be influenced by neighboring species. This creates context dependencies for microbial interactions that are based on the functional composition of the community. Context dependent interactions are ecologically important and clearly present in nature, yet firmly established theoretical methods are lacking from many modern computational investigations. Here, we propose a novel network inference method that enables predictions for interspecies interactions affected by shifts in community composition and species populations. Our approach first identifies interspecies interactions in binary communities, which is subsequently used as a basis to infer modulation in more complex multi-species communities based on the assumption that microbes minimize adjustments of pairwise interactions in response to neighbor species. We termed this rule-based inference minimal interspecies interaction adjustment (MIIA). Our critical assessment of MIIA has produced reliable predictions of shifting interspecies interactions that are dependent on the functional role of neighbor organisms. We also show how MIIA has been applied to a microbial community composed of competing soil bacteria to elucidate a new finding that – in many cases – adding fewer competitors could impose more significant impact on binary interactions. The ability to predict membership-dependent community behavior is expected to help deepen our understanding of how microbiomes are organized in nature and how they may be designed and/or controlled in the future

Strong enhancement of ultraviolet emission from ZnO films by V implantation

ZnOfilms were prepared on Si(100) wafers by rf sputtering and subsequently implanted with V ions to fluences of (1,2.5,5,10)×10¹⁵ cm¯². The room-temperature ultraviolet photoluminescence(PL) intensity of the implantedfilms is shown to increase with increasing fluence up to 2.5×1015 cm−2, becoming ∼37 times more intense than the emission from the unimplanted ZnOfilm, before decreasing at higher fluences. The increase in PL intensity is correlated with improved crystallinity of ZnO, accompanied by a reduction in the concentration of deep-level native defects by V incorporation into the ZnO lattice, as verified by x-ray diffraction, x-ray photoelectron spectroscopy, and low-temperature PL. The subsequent reduction in PL intensity at fluences higher than 2.5×10¹⁵ cm¯² is shown to result from the deterioration of the crystal quality and the precipitation of V secondary phase possibly introducing defects in the films

Effect of (O, As) dual implantation on p-type doping of ZnO films

Optical and electrical characteristics of ZnOfilms co-implanted with O and As ions have been investigated by photoluminescence(PL), Hall-effect, and current-voltage (I-V) measurements. 100-nm-thick ZnOfilms grown on n-type Si (100) wafers by RF sputtering have been implanted with various fluences of 30 keV O and 100 keV As ions at room temperature, and subsequently annealed at 800 °C for 20 min in a N2 ambient. The dually-implanted ZnOfilms show stable p-type characteristics for particular implant combinations, consistent with the observation of dominant PL peaks at 3.328 and 3.357 eV that are associated with the acceptor levels. For these dually-implanted p-type ZnO films/n-type Si diodes, the I-V curves show rectifying p-n junction behavior. Other singly (As)- or dually-implanted samples show n-type or indeterminable doping characteristics. These results suggest that O implantation plays a key role in forming p-type ZnOfilms by reducing the oxygen vacancy concentration and facilitating the formation of As-related acceptors in ZnO.This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (No. 2011-0017373)

Homer 2 tunes G protein–coupled receptors stimulus intensity by regulating RGS proteins and PLCβ GAP activities

Homers are scaffolding proteins that bind G protein–coupled receptors (GPCRs), inositol 1,4,5-triphosphate (IP3) receptors (IP3Rs), ryanodine receptors, and TRP channels. However, their role in Ca2+ signaling in vivo is not known. Characterization of Ca2+ signaling in pancreatic acinar cells from Homer2−/− and Homer3−/− mice showed that Homer 3 has no discernible role in Ca2+ signaling in these cells. In contrast, we found that Homer 2 tunes intensity of Ca2+ signaling by GPCRs to regulate the frequency of [Ca2+]i oscillations. Thus, deletion of Homer 2 increased stimulus intensity by increasing the potency for agonists acting on various GPCRs to activate PLCβ and evoke Ca2+ release and oscillations. This was not due to aberrant localization of IP3Rs in cellular microdomains or IP3R channel activity. Rather, deletion of Homer 2 reduced the effectiveness of exogenous regulators of G proteins signaling proteins (RGS) to inhibit Ca2+ signaling in vivo. Moreover, Homer 2 preferentially bound to PLCβ in pancreatic acini and brain extracts and stimulated GAP activity of RGS4 and of PLCβ in an in vitro reconstitution system, with minimal effect on PLCβ-mediated PIP2 hydrolysis. These findings describe a novel, unexpected function of Homer proteins, demonstrate that RGS proteins and PLCβ GAP activities are regulated functions, and provide a molecular mechanism for tuning signal intensity generated by GPCRs and, thus, the characteristics of [Ca2+]i oscillations

On the question of universality in \RPn and \On Lattice Sigma Models

We argue that there is no essential violation of universality in the continuum limit of mixed \RPn and \On lattice sigma models in 2 dimensions, contrary to opposite claims in the literature.Comment: 16 pages (latex) + 3 figures (Postscript), uuencode

Minimal Interspecies Interaction Adjustment (MIIA): Inference of Neighbor-Dependent Interactions in Microbial Communities

An intriguing aspect in microbial communities is that pairwise interactions can be influenced by neighboring species. This creates context dependencies for microbial interactions that are based on the functional composition of the community. Context dependent interactions are ecologically important and clearly present in nature, yet firmly established theoretical methods are lacking from many modern computational investigations. Here, we propose a novel network inference method that enables predictions for interspecies interactions affected by shifts in community composition and species populations. Our approach first identifies interspecies interactions in binary communities, which is subsequently used as a basis to infer modulation in more complex multi-species communities based on the assumption that microbes minimize adjustments of pairwise interactions in response to neighbor species. We termed this rule-based inference minimal interspecies interaction adjustment (MIIA). Our critical assessment of MIIA has produced reliable predictions of shifting interspecies interactions that are dependent on the functional role of neighbor organisms. We also show how MIIA has been applied to a microbial community composed of competing soil bacteria to elucidate a new finding that – in many cases – adding fewer competitors could impose more significant impact on binary interactions. The ability to predict membership-dependent community behavior is expected to help deepen our understanding of how microbiomes are organized in nature and how they may be designed and/or controlled in the future

KMT-2018-BLG-1292: A Super-Jovian Microlens Planet in the Galactic Plane

We report the discovery of KMT-2018-BLG-1292Lb, a super-Jovian $M_{\rm planet} = 4.5\pm 1.3\,M_J$ planet orbiting an F or G dwarf $M_{\rm host} = 1.5\pm 0.4\,M_\odot$, which lies physically within {\cal O}(10\,\pc) of the Galactic plane. The source star is a heavily extincted $A_I\sim 5.2$ luminous giant that has the lowest Galactic latitude, $b=-0.28^\circ$, of any planetary microlensing event. The relatively blue blended light is almost certainly either the host or its binary companion, with the first explanation being substantially more likely. This blend dominates the light at $I$ band and completely dominates at $R$ and $V$ bands. Hence, the lens system can be probed by follow-up observations immediately, i.e., long before the lens system and the source separate due to their relative proper motion. The system is well characterized despite the low cadence $\Gamma=0.15$--$0.20\,{\rm hr^{-1}}$ of observations and short viewing windows near the end of the bulge season. This suggests that optical microlensing planet searches can be extended to the Galactic plane at relatively modest cost.Comment: 35 pages, 3 Tables, 8 figure