Production of high molecular weight organic compounds on the surfaces of amorphous iron silicate catalysts: Implications for organic synthesis in the solar nebula

The high molecular weight organic products of Fischer-Tropsch/Haber-Bosch syntheses on the surfaces of Fe-silicate catalysts have been studied by GCMS

The hydration state of HO−^-(aq)

The HO$^-$(aq) ion participates in myriad aqueous phase chemical processes of biological and chemical interest. A molecularly valid description of its hydration state, currently poorly understood, is a natural prerequisite to modeling chemical transformations involving HO$^-$(aq). Here it is shown that the statistical mechanical quasi-chemical theory of solutions predicts that $\mathrm{HO\cdot[H_2O]_3{}^-}$ is the dominant inner shell coordination structure for HO$^-$(aq) under standard conditions. Experimental observations and other theoretical calculations are adduced to support this conclusion. Hydration free energies of neutral combinations of simple cations with HO$^-$(aq) are evaluated and agree well with experimental values.Comment: 10 pages, 1 figur

Static And Dynamic Properties Of Fibonacci Multilayers

We theoretically investigate static and dynamic properties of quasiperiodic magnetic multilayers. We considered identical ferromagnetic layers separated by non-magnetic spacers with two different thicknesses chosen based on the Fibonacci sequence. Using parameters for Fe/Cr, the minimum energy was determined and the equilibrium magnetization directions found were used to calculate magnetoresistance curves. Regarding dynamic behavior, ferromagnetic resonance (FMR) curves were calculated using an approximation known from the literature. Our numerical results illustrate the effects of quasiperiodicity on the static and dynamic properties of these structures. © 2013 American Institute of Physics.11317Grünberg, P., Schreiber, R., Pang, Y., Brodsky, M.B., Sowers, H., (1986) Phys. Rev. Lett., 57, p. 2442. , 10.1103/PhysRevLett.57.2442Baibich, M.N., Broto, J.M., Fert, A., Nguyen Van Dau, F., Petroff, F., Etienne, P., Creuzet, G., Chazelas, J., (1988) Phys. Rev. Lett., 61, p. 2472. , 10.1103/PhysRevLett.61.2472Binasch, G., Grünberg, P., Saurenbach, F., Zinn, W., (1989) Phys. Rev. B, 39, p. 4828. , 10.1103/PhysRevB.39.4828Prinz, G.A., (1998) Science, 282, p. 1660. , 10.1126/science.282.5394.1660Kools, J.C.S., (1996) IEEE Trans. Magn., 32, p. 3165. , 10.1109/20.508381Stiles, M.D., Zangwill, A., (2002) Phys. Rev. B, 66, p. 014407. , 10.1103/PhysRevB.66.014407Lakys, Y., Zhao, W.S., Devolder, T., Zhang, Y., Klein, J.O., Ravelosona, D., Chappert, C., (2012) IEEE Trans. Magn., 48, p. 2403. , 10.1109/TMAG.2012.2194790Chaves, R.C., Cardoso, S., Ferreira, R., Freitas, P.P., (2011) J. Appl. Phys, 109, pp. 07E506. , 10.1063/1.3537926Vedyayev, A., Dieny, B., Ryzhanova, N., Genin, J.B., Cowache, C., (1994) Europhys. Lett., 25, p. 465. , 10.1209/0295-5075/25/6/012Albuquerque, E.L., Cottam, M.G., (2004) Polaritons in Periodic and Quasiperiodic Structures, , (Elsevier, Amsterdam)Bezerra, C.G., Albuquerque, E.L., (1997) Physica A, 245, p. 379. , 10.1016/S0378-4371(97)00309-9Bezerra, C.G., De Araujo, J.M., Chesman, C., Albuquerque, E.L., (1999) Phys. Rev. B, 60, p. 9264. , 10.1103/PhysRevB.60.9264Bezerra, C.G., De Araujo, J.M., Chesman, C., Albuquerque, E.L., (2001) J. Appl. Phys., 89, p. 2286. , 10.1063/1.1340600Bezerra, C.G., Cottam, M.G., (2002) J. Magn. Magn. Mater., 240, p. 529. , 10.1016/S0304-8853(01)00838-1Bezerra, C.G., Cottam, M.G., (2002) Phys. Rev. B, 65, p. 054412. , 10.1103/PhysRevB.65.054412Mauriz, P.W., Albuquerque, E.L., Bezerra, C.G., (2002) J. Phys.: Condens. Matter, 14, p. 1785. , 10.1088/0953-8984/14/8/308Fullerton, E.E., Conover, M.J., Mattson, J.E., Sowers, C.H., Bader, S.D., (1993) Phys. Rev. B, 48, p. 15755. , 10.1103/PhysRevB.48.15755Machado, L.D., Bezerra, C.G., Correa, M.A., Chesman, C., Pearson, J.E., Hoffmann, A., (2012) Phys. Rev. B, 85, p. 224416. , 10.1103/PhysRevB.85.22441

Nonparametric nonlinear model predictive control

Model Predictive Control (MPC) has recently found wide acceptance in industrial applications, but its potential has been much impeded by linear models due to the lack of a similarly accepted nonlinear modeling or databased technique. Aimed at solving this problem, the paper addresses three issues: (i) extending second-order Volterra nonlinear MPC (NMPC) to higher-order for improved prediction and control; (ii) formulating NMPC directly with plant data without needing for parametric modeling, which has hindered the progress of NMPC; and (iii) incorporating an error estimator directly in the formulation and hence eliminating the need for a nonlinear state observer. Following analysis of NMPC objectives and existing solutions, nonparametric NMPC is derived in discrete-time using multidimensional convolution between plant data and Volterra kernel measurements. This approach is validated against the benchmark van de Vusse nonlinear process control problem and is applied to an industrial polymerization process by using Volterra kernels of up to the third order. Results show that the nonparametric approach is very efficient and effective and considerably outperforms existing methods, while retaining the original data-based spirit and characteristics of linear MPC

Building Social Capital Through Rhetoric and Public Relations

When the focus is on meaning making, language, rhetorical argument, and persuasion, there is enormous potential to see how public relations theory and practice in external organizational rhetoric can serve community interests—or not. Rhetoric (as the discourse) and public relations (as the enactment of that discourse) are essential to building and sustaining a society as a good place to live because they create various types of social capital. This article describes the various relationships among international and indigenous NGOs, business organizations, and community activists in facilitating (and, at times, frustrating) dialogue in Jordan. It offers an example of how social capital may be created when rhetors using public relations advocate in ways that enhance the capacity of local governance and make their community a better place to live.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

Synthetic Nitrogen Fertiliser in South Asia: Production, Import, Export, and Use for Crops, South Asia Nitrogen Hub (SANH) Policy Brief

This policy brief is produced by the UKRI GCRF South Asian Nitrogen Hub (SANH). It provides an overview of the patterns and trends in synthetic nitrogen (N) fertiliser use in crop production, import, export and emission in the South Asian Region (SAR) and its member countries; Afghanistan, Bangladesh, Bhutan, Nepal, India, Maldives, Pakistan, and Sri Lanka. In summary, reactive nitrogen (Nr) in fertilisers is essential for meeting global food and animal feed demands, but Nr pollution has become a major environmental issue across all scales. For SAR, inefficient use of synthetic N fertiliser is a key factor contributing to water pollution, air pollution, climate change, biodiversity loss and soil degradation. Further insights are provided on major fertiliser products, as well as in crop production, import and export. These data are essential for informing and promoting sustainable nitrogen management. Evidence based policy is more important than ever. The SANH is supported by UK Research and Innovation (UKRI) through its Global Challenge Research Fund (GCRF) to gather evidence on nitrogen issues to support countries in the South Asian Region (SAR) comprising eight countries (Nepal, Bangladesh, Pakistan, India, Bhutan, Sri Lanka, Afghanistan, and Maldives) to identify solutions and reduce nitrogen waste. SANH is pioneering a UK-SAR research partnership to catalyse transformational change in SAR to tackle the nitrogen challenge, benefi ting the economy, people’s health and the environment. SANH brings together 32 leading research organisations with governments and other partners. This policy brief provides key insights into national fertiliser trends for all eight SAR countries

Synthetic Nitrogen Fertiliser in South Asia: Production, Import, Export, and Use for Crops, South Asia Nitrogen Hub (SANH) Policy Brief

This policy brief is produced by the UKRI GCRF South Asian Nitrogen Hub (SANH). It provides an overview of the patterns and trends in synthetic nitrogen (N) fertiliser use in crop production, import, export and emission in the South Asian Region (SAR) and its member countries; Afghanistan, Bangladesh, Bhutan, Nepal, India, Maldives, Pakistan, and Sri Lanka. In summary, reactive nitrogen (Nr) in fertilisers is essential for meeting global food and animal feed demands, but Nr pollution has become a major environmental issue across all scales. For SAR, inefficient use of synthetic N fertiliser is a key factor contributing to water pollution, air pollution, climate change, biodiversity loss and soil degradation. Further insights are provided on major fertiliser products, as well as in crop production, import and export. These data are essential for informing and promoting sustainable nitrogen management. Evidence based policy is more important than ever. The SANH is supported by UK Research and Innovation (UKRI) through its Global Challenge Research Fund (GCRF) to gather evidence on nitrogen issues to support countries in the South Asian Region (SAR) comprising eight countries (Nepal, Bangladesh, Pakistan, India, Bhutan, Sri Lanka, Afghanistan, and Maldives) to identify solutions and reduce nitrogen waste. SANH is pioneering a UK-SAR research partnership to catalyse transformational change in SAR to tackle the nitrogen challenge, benefi ting the economy, people’s health and the environment. SANH brings together 32 leading research organisations with governments and other partners. This policy brief provides key insights into national fertiliser trends for all eight SAR countries

Optimum electrode configurations for fast ion separation in microfabricated surface ion traps

For many quantum information implementations with trapped ions, effective shuttling operations are important. Here we discuss the efficient separation and recombination of ions in surface ion trap geometries. The maximum speed of separation and recombination of trapped ions for adiabatic shuttling operations depends on the secular frequencies the trapped ion experiences in the process. Higher secular frequencies during the transportation processes can be achieved by optimising trap geometries. We show how two different arrangements of segmented static potential electrodes in surface ion traps can be optimised for fast ion separation or recombination processes. We also solve the equations of motion for the ion dynamics during the separation process and illustrate important considerations that need to be taken into account to make the process adiabatic

Comparison of some Reduced Representation Approximations

In the field of numerical approximation, specialists considering highly complex problems have recently proposed various ways to simplify their underlying problems. In this field, depending on the problem they were tackling and the community that are at work, different approaches have been developed with some success and have even gained some maturity, the applications can now be applied to information analysis or for numerical simulation of PDE's. At this point, a crossed analysis and effort for understanding the similarities and the differences between these approaches that found their starting points in different backgrounds is of interest. It is the purpose of this paper to contribute to this effort by comparing some constructive reduced representations of complex functions. We present here in full details the Adaptive Cross Approximation (ACA) and the Empirical Interpolation Method (EIM) together with other approaches that enter in the same category

Multimodal Representation Learning for Place Recognition Using Deep Hebbian Predictive Coding

Recognising familiar places is a competence required in many engineering applications that interact with the real world such as robot navigation. Combining information from different sensory sources promotes robustness and accuracy of place recognition. However, mismatch in data registration, dimensionality, and timing between modalities remain challenging problems in multisensory place recognition. Spurious data generated by sensor drop-out in multisensory environments is particularly problematic and often resolved through adhoc and brittle solutions. An effective approach to these problems is demonstrated by animals as they gracefully move through the world. Therefore, we take a neuro-ethological approach by adopting self-supervised representation learning based on a neuroscientific model of visual cortex known as predictive coding. We demonstrate how this parsimonious network algorithm which is trained using a local learning rule can be extended to combine visual and tactile sensory cues from a biomimetic robot as it naturally explores a visually aliased environment. The place recognition performance obtained using joint latent representations generated by the network is significantly better than contemporary representation learning techniques. Further, we see evidence of improved robustness at place recognition in face of unimodal sensor drop-out. The proposed multimodal deep predictive coding algorithm presented is also linearly extensible to accommodate more than two sensory modalities, thereby providing an intriguing example of the value of neuro-biologically plausible representation learning for multimodal navigation