Supplementary material

  title={Supplementary material},
  author={Yunbo Zhang and Wenhao Yu and Greg Turk and A. Hyperparameters},
A pair of enantiomeric 4-oxabicyclic[4.3.0]lactam derivatives, (+)- and (−)-penicilactam A ( 1 ), and one new polyketide derivative penicitrinone F ( 2 ) were isolated from the marine-derived fungus Penicillium griseofulvum GT-10. Their structures and absolute configurations were elucidated through extensive spectroscopic analyses combined with the calculated ECD spectra. Penicitrinone F ( 2 ) had moderate inhibitory activity towards Bacillus subtilis with a MIC value of 6.3 μ M. 

Figures and Tables from this paper

Benzimidazole derivatives as potential dual inhibitors for PARP-1 and DHODH.

N-Myristoyltransferase Is a Cell Wall Target in Aspergillus fumigatus

It is shown that the filamentous fungal pathogen Aspergillus fumigatus possesses an active NMT enzyme that is essential for survival and evidence of NMT being a potential drug target in A. fmigatus is provided.

A UV/Vis Spectroscopy-Based Assay for Monitoring of Transformations Between Nucleosides and Nucleobases

A UV/Vis spectroscopy-based assay employing an algorithm for spectral unmixing in a 96-well plate format that enables data collection in a high-throughput fashion and reduces costs compared to state-of-the-art HPLC analyses by approximately 5-fold while being 20-fold faster and offering comparable precision.

Inland Concentrations of Cl2 and ClNO2 in Southeast Texas Suggest Chlorine Chemistry Significantly Contributes to Atmospheric Reactivity

Measurements of molecular chlorine (Cl2), nitryl chloride (ClNO2), and dinitrogen pentoxide (N2O5) were taken as part of the DISCOVER-AQ Texas 2013 campaign with a High Resolution Time-of-Flight

Raman Imaging and Chemometrics Evaluation of Natural and Synthetic Beeswaxes as Matrices for Nanostructured Lipid Carriers Development

Cite: Mitsutake, H.; da Silva, G. H. R.; Ribeiro, L. N. M.; de Paula, E.; Poppi, R. J.; Rutledge, D. N.; Breitkreitz, M. C. Raman Imaging and Chemometrics Evaluation of Natural and Synthetic

Multi-charge transfer from photodoped ITO nanocrystals

Evidence for multi-electron transfer processes from photodoped Sn’: In2O3 nanocrystals to a widely employed organic electron acceptor (F4TCNQ) is provided, via oxidative titration and optical spectroscopy, and the potential of photodoping electrons to drive chemical reactions involving more than one electron is disclosed.

Genotyping of Leptospira interrogans isolates from Mexican patients

Clinical isolates identified as L. interrogans serovar POM have a clonal reproduction type, suggesting that this clone is distributed in different regions of Mexico.

Abundance of hard-hexagon crystals in the quantum pyrochlore antiferromagnet

We propose a simple family of valence-bond crystals as potential ground states of the S = 1 / 2 and S = 1 Heisenberg antiferromagnet on the pyrochlore lattice. Exponentially numerous in the linear

Interplay between Adsorbates and Polarons: CO on Rutile TiO_{2}(110).

The results show that polarons are of primary importance for understanding the performance of polar semiconductors and transition metal oxides in catalysis and energy-related applications.



Super Learner

A fast algorithm for constructing a super learner in prediction which uses V-fold cross-validation to select weights to combine an initial set of candidate learners.

High-Dimensional Continuous Control Using Generalized Advantage Estimation

This work addresses the large number of samples typically required and the difficulty of obtaining stable and steady improvement despite the nonstationarity of the incoming data by using value functions to substantially reduce the variance of policy gradient estimates at the cost of some bias.

Learning Efficient Convolutional Networks through Network Slimming

The approach is called network slimming, which takes wide and large networks as input models, but during training insignificant channels are automatically identified and pruned afterwards, yielding thin and compact models with comparable accuracy.

Learning both Weights and Connections for Efficient Neural Network

A method to reduce the storage and computation required by neural networks by an order of magnitude without affecting their accuracy by learning only the important connections, and prunes redundant connections using a three-step method.

A new family of power transformations to improve normality or symmetry

SUMMARY We introduce a new power transformation family which is well defined on the whole real line and which is appropriate for reducing skewness and to approximate normality. It has properties

Caltech-UCSD Birds 200

Caltech-UCSD Birds 200 (CUB-200) is a challenging image dataset annotated with 200 bird species. It was created to enable the study of subordinate categorization, which is not possible with other

ltmle: An R Package Implementing Targeted Minimum Loss-Based Estimation for Longitudinal Data

The ltmle package provides methods to estimate intervention-specific means and measures of association including the average treatment effect, causal odds ratio and causal risk ratio and parameters of a longitudinal working marginal structural model.

Pruning Convolutional Neural Networks for Resource Efficient Transfer Learning

A new criterion based on an efficient first-order Taylor expansion to approximate the absolute change in training cost induced by pruning a network component is proposed, demonstrating superior performance compared to other criteria, such as the norm of kernel weights or average feature map activation.

Learning Deep Features for Discriminative Localization

In this work, we revisit the global average pooling layer proposed in [13], and shed light on how it explicitly enables the convolutional neural network (CNN) to have remarkable localization ability

Dense-Captioning Events in Videos

This work proposes a new model that is able to identify all events in a single pass of the video while simultaneously describing the detected events with natural language, and introduces a new captioning module that uses contextual information from past and future events to jointly describe all events.