High temperature protective coatings for refractory metals progress report no. 1, oct. 23, 1964 - jan. 23, 1965

Iridium as high temperature protective coating for unalloyed niobium and tantalu

Grain Sorghum and Soybean Variety Tests on Reconstructed Prime Land - 1985

Prime farmland disturbed by surface mining must by law be returned to a productivity level equal to that before mining. The coal operator has several test crops that can be selected to determine whether these production standards have been met before final bond release will be made. Grain sorghum and soybeans are two of the crops that may be used. The purposes of this research are (1) to determine the crop yield potential of restored prime farmland from surface mined areas, (2) to determine varietal adaptation on restored prime farmland as compared to non-mined prime farmland, and (3) to provide crop yield data to Kentucky farmers on grain sorghum and soybeans from restored prime farmland

Influence of Time of Application of Nitrogen Fertilizer on Corn Yields

Soil moisture conditions can have a large effect on crop responses to nitrogen fertilization. Kentucky\u27s usual climatic pattern of periods of heavy rainfall and relatively warm temperatures during the winter and spring seasons influences expected yield responses of corn to applied nitrogen. If nitrogen fertilizer is applied in late winter or early spring, some of it may be lost before the plants have made sufficient growth to take up appreciable quantities. The amount of loss that might be expected will be influenced by the amount of rainfall, temperature, amount of organic matter and drainage of the soil

Experimental Evidence for the Incorporation of Two Metals at Equivalent Lattice Positions in Mixed-Metal Metal–Organic Frameworks

Metal–organic frameworks containing multiple metals distributed over crystallographically equivalent framework positions (mixed‐metal MOFs) represent an interesting class of materials, since the close vicinity of isolated metal centers often gives rise to synergistic effects. However, appropriate characterization techniques for detailed investigations of these mixed‐metal metal–organic framework materials, particularly addressing the distribution of metals within the lattice, are rarely available. The synthesis of mixed‐metal FeCuBTC materials in direct syntheses proved to be difficult and only a thorough characterization using various techniques, like powder X‐ray diffraction, X‐ray absorption spectroscopy and electron paramagnetic resonance spectroscopy, unambiguously evidenced the formation of a mixed‐metal FeCuBTC material with HKUST‐1 structure, which contained bimetallic Fe−Cu paddlewheels as well as monometallic Cu−Cu and Fe−Fe units under optimized synthesis conditions. The in‐depth characterization showed that other synthetic procedures led to impurities, which contained the majority of the applied iron and were impossible or difficult to identify using solely standard characterization techniques. Therefore, this study shows the necessity to characterize mixed‐metal MOFs extensively to unambiguously prove the incorporation of both metals at the desired positions. The controlled positioning of metal centers in mixed‐metal metal–organic framework materials and the thorough characterization thereof is particularly important to derive structure–property or structure–activity correlations

REPLAB: A Study in Scientific Inquiry Using the PLATO System

Coordinated Science Laboratory was formerly known as Control Systems LaboratoryJoint Services Electronics Programs / DA 28 043 AMC 00073(E)Advanced Research Projects Agency through the Office of Naval Research / Nonr-3985(08

A type VII-secreted lipase toxin with reverse domain arrangement

Funding: This study was supported by the Wellcome Trust (through Investigator Awards 10183/Z/15/Z and 224151/Z/21/Z to TP), the Intramural Research Program of the NIH, NCI, Center for Cancer Research (awarded to SML), the German Centre of Infection Research (DZIF) to SH (TTU 08.708). NM holds a Walter Benjamin Fellowship (M2871/1-1), funded by the DFG (German Research Foundation). Additionally, we acknowledge infrastructural funding by the DFG in the frame of Germany's Excellence Strategy—EXC 2124—390838134 (SH). SG is funded by the Newcastle-Liverpool-Durham BBSRC DTP2 Training Grant, project reference number BB/M011186/1 and YY by the China Scholarship Council.The type VII protein secretion system (T7SS) is found in many Gram-positive bacteria and in pathogenic mycobacteria. All T7SS substrate proteins described to date share a common helical domain architecture at the N-terminus that typically interacts with other helical partner proteins, forming a composite signal sequence for targeting to the T7SS. The C-terminal domains are functionally diverse and in Gram-positive bacteria such as Staphylococcus aureus often specify toxic anti-bacterial activity. Here we describe the first example of a class of T7 substrate, TslA, that has a reverse domain organisation. TslA is widely found across Bacillota including Staphylococcus, Enterococcus and Listeria. We show that the S. aureus TslA N-terminal domain is a phospholipase A with anti-staphylococcal activity that is neutralised by the immunity lipoprotein TilA. Two small helical partner proteins, TlaA1 and TlaA2 are essential for T7-dependent secretion of TslA and at least one of these interacts with the TslA C-terminal domain to form a helical stack. Cryo-EM analysis of purified TslA complexes indicate that they share structural similarity with canonical T7 substrates. Our findings suggest that the T7SS has the capacity to recognise a secretion signal present at either end of a substrate.Publisher PDFPeer reviewe

Attenuated and Protease-Profile Modified Sendai Virus Vectors as a New Tool for Virotherapy of Solid Tumors

Peer reviewe

The Secret to Successful User Communities: An Analysis of Computer Associates’ User Groups

This paper provides the first large scale study that examines the impact of both individual- and group-specific factors on the benefits users obtain from their user communities. By empirically analysing 924 survey responses from individuals in 161 Computer Associates' user groups, this paper aims to identify the determinants of successful user communities. To measure success, the amount of time individual members save through having access to their user networks is used. As firms can significantly profit from successful user communities, this study proposes four key implications of the empirical results for the management of user communities

Recognizing recurrent neural networks (rRNN): Bayesian inference for recurrent neural networks

Recurrent neural networks (RNNs) are widely used in computational neuroscience and machine learning applications. In an RNN, each neuron computes its output as a nonlinear function of its integrated input. While the importance of RNNs, especially as models of brain processing, is undisputed, it is also widely acknowledged that the computations in standard RNN models may be an over-simplification of what real neuronal networks compute. Here, we suggest that the RNN approach may be made both neurobiologically more plausible and computationally more powerful by its fusion with Bayesian inference techniques for nonlinear dynamical systems. In this scheme, we use an RNN as a generative model of dynamic input caused by the environment, e.g. of speech or kinematics. Given this generative RNN model, we derive Bayesian update equations that can decode its output. Critically, these updates define a 'recognizing RNN' (rRNN), in which neurons compute and exchange prediction and prediction error messages. The rRNN has several desirable features that a conventional RNN does not have, for example, fast decoding of dynamic stimuli and robustness to initial conditions and noise. Furthermore, it implements a predictive coding scheme for dynamic inputs. We suggest that the Bayesian inversion of recurrent neural networks may be useful both as a model of brain function and as a machine learning tool. We illustrate the use of the rRNN by an application to the online decoding (i.e. recognition) of human kinematics