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opencc-by-4.0Jan 2023View details →

Steady states of Λ-type three-level systems excited by quantum light with various photon statistics in lossy cavities

Dataset of the publication "Steady states of Λ-type three-level systems excited by quantum light with various photon statistics in lossy cavities" H. Rose, O. V. Tikhonova, T. Meier, and P. R. Sharapova, New J. Phys. 24, 063020 (2022). ( https://doi.org/10.1088/1367-2630/ac74d8 ). The zip file includes the data on which the plots shown in figures 2,4,5,6,7, B1, and B2 are based.

opencc-by-4.0Jun 2023View details →

DOX_BDW: Incorporating Solvation and Desolvation Effects of Cavity Water into Nonfitting Protein–Ligand Binding Affinity Prediction

structures.zip:  including the coordinates of all optimized proteinligand complex structure obtained by DOX_BDW calculation. (compressed PDB file). These pdb files could also be  used as input for the binding energy calculation,as illustrated in SI section 8.  mdinput.zip: Including the input files,parameter files, topology files needed to run MD simulation for water mapping, as illustrated in SI section 8. Note that all of the parameter files and topology files would be automatically generated using the RUNMD program we uploaded with the example file.  example.zip: The programs and input files needed to run an example, as illustrated in SI section 9. And all the output files except MD trajectories are in there,too.

opencc-by-4.0Jul 2023View details →

Receptor cavity-based screening reveals potential allosteric modulators of gonadotropin receptors in carp (Cyprinus carpio)

The dataset include phase database consisting of prepared ligand used in screening of potential allosteric modulators for carp FSHR and LHR. the original dataset  were sourced from The compound libraries from <a href="https://enamine.net/compound-libraries">https://enamine.net/compound-libraries</a> and are free to access and downloaded and used as per the mentioned sites terms and conditions the Datasets given here are processed databases constructed using the Phase module (Phase, Schrödinger, LLC, New York, NY, 2021.).

opencc-by-4.0Jul 2023View details →

Research data for "Cavity-enhanced single-shot readout of a quantum dot spin within 3 nanoseconds"

The datasets presented here contain the underlying data used to create the figures for the publication "Cavity-enhanced single-shot readout of a quantum dot spin within 3 nanoseconds." The data is formatted in Matlab data (.mat) files, with the name indicating which figure the data corresponds to. The publication is available at the following address: https://www.nature.com/articles/s41467-023-39568-1 We note that for our spin readout experiments, the elapsed readout time is always defined relative to the start of the readout pulse.

opencc-by-4.0Dec 2022View details →

Salivary chemical barrier proteins in Oral Squamous Cell Carcinoma – Alterations in the defense mechanism of the oral cavity

Oral squamous cell carcinoma (OSCC) is one of the most frequent type of head and neck cancers. Despite the genetic and environmental risk factors, OSCC is also associated with microbial infections and/or dysbiosis. The secreted saliva serves as the chemical barrier of the oral cavity and since OSCC can alter the protein composition of saliva, our aim was to analyze the effect of OSCC on the salivary chemical barrier proteins. Publicly available datasets regarding the analysis of salivary proteins from patients with OSCC and controls were collected and examined in order to identify differentially expressed chemical barrier proteins. The network analysis and gene onthology (GO) classification of the differentially expressed chemical barrier proteins were performed, as well. 127 proteins showing different expression pattern between the OSCC and control groups were found. The protein-protein interaction network of up- and down-regulated proteins were constructed and analyzed. The main hub proteins (IL-6, IL-1B, IL-8, TNF, APOA1, APOA2, APOB, APOC3, APOE, and HP) were identified and the enriched GO terms were examined. Our study highlighted the importance of the chemical barrier of saliva in the development of OSCC.

Input files for the simulation of KcsA-K+-LAB-TEA, when LAB-TEA is placed in the cytoplasmic region with K+-ion in the channel cavity

Input files for the simulation of KcsA-K+-LAB-TEA, when LAB-TEA is placed in the cytoplasmic region with K+-ion in the channel cavity. The inputs include, 1. Input files for minimization (*min.in) 2. Input files for heating (*h1.in, *h2.in, and *h3.in) 3. Input files for equilibration (*eq*.in) and production runs (*prd*.in) 4. Input files for the first trajectories start with file name, 1-lab-tea-k-entra* 5. Input files for the remaining different trajectories start with file name, lab-tea-k-entra* 6. Input files for the  trajectories with restraint weight on K+-ion starting with file name, lab-tea-entra-k-restraint*

Input files for the simulation of KcsA-LAB-TEA, when LAB-TEA is placed in the channel cavity with no K+-ion

Input files for the simulation of KcsA-LAB-TEA, when LAB-TEA is placed in the channel cavity. The simulation is performed without K+-ion. The inputs include, 1. Input files for minimization (*min.in) 2. Input files for heating (*h1.in, *h2.in, and *h3.in) 3. Input files for equilibration (*eq*.in) and production runs (*prd*.in) 4. Input files for the first trajectories start with file name, 1-lab-tea* 5. Input files for the remaining different trajectories start with file name, lab-tea*

Input files for the simulation of KcsA-K+-LAB-TEA, when both LAB-TEA and K+-ion are placed inside the channel cavity.

Input files for the simulation of KcsA-K+-LAB-TEA, when both LAB-TEA and K+-ion are placed inside the channel cavity. The inputs include, 1. Input files for minimization (*min.in) 2. Input files for heating (*h1.in, *h2.in, and *h3.in) 3. Input files for equilibration (*eq*.in) and production runs (*prd*.in) 4. Input files for the first trajectories start with file name, 1-lab-tea-k+* 5. Input files for the remaining different trajectories start with the file name, lab-tea-k+*

Parameters for the solvated KcsA-LAB-TEA, when the LAB-TEA is placed inside the channel cavity without K+-ion

Parameters for the solvated KcsA-LAB-TEA. These KcsA-LAB-TEA systems were solvated by truncated octahedron TIP3PBOX, using the leap program in AMBER20. The LAB-TEA is placed inside the channel cavity. The simulation is performed without K+-ion.

Parameters for the solvated KcsA-K+-LAB-TEA, when both LAB-TEA and K+-ion placed inside the channel cavity

Parameters for the solvated KcsA-K+-LAB-TEA. These KcsA-K+-LAB-TEA systems were solvated by truncated octahedron TIP3PBOX, using the leap program in AMBER20. Both LAB-TEA and K+-ion are placed inside the channel cavity.

opencc-zeroAug 2023View details →

dryad32/100

Density and characteristics of tree cavities inside and outside Volcanoes National Park, Rwanda

Tree cavities, formed by animal excavation or processes of fungal decay and mechanical damage, may provide nesting, roosting, or resting opportunities to many invertebrate and vertebrate species. Although cavity availability has been linked to patterns of biodiversity and ecosystem functioning elsewhere, there have been few such studies in the Afrotropics. Here, we present a baseline survey of cavity availability inside the high elevation (2,200–3,714 m) Afromontane forest ecosystems of Volcanoes National Park (VNP), Rwanda. We aimed to provide such reference data in the form of summary statistics on cavity density and characteristics in a collection of 400 m2 plots that together cover 8.8 ha inside and 0.68 ha outside VNP. We also explored the relative importance of fungal decay vs. excavators in the formation of cavities, tested for the relative role of standing dead trees and living trees as cavity substrates, considered differences in diameter and height between cavity-bearing trees and trees without cavities, determined the orientation of cavity entrances, and tested whether cavity density varies across elevation. We found 109 cavities in 52 cavity-bearing trees (dominated by Hagenia abyssinica) inside VNP, for a density of 12.4 cavities and 5.9 cavity-bearing trees per hectare, and none outside the park. More cavities were decay-formed (n = 90) than excavated (n = 19) and though most cavities were found in living trees (n = 44) the number of cavities in dead trees (n = 8) was high relative to dead tree substrate availability. We also found that cavity-bearing trees were larger than those without cavities, that excavated cavities were predominantly oriented towards the southeast and decay-formed cavities to the northeast, and that cavity density peaked near ~3,000 m. Our results show that large and dead trees of particular species are important cavity substrates that need to be given attention in conservation and management as is clearly illustrated by the lack of cavities in the highly managed Eucalyptus stands outside VNP.

Data and processing for "Multitone Microwave Frequency Locking to a Noisy Cavity via Real-Time Feedback"

This folder contains all the code and data necessary to produce the figures of the paper titled "Multitone Microwave Frequency Locking to a Noisy Cavity via Real-Time Feedback" written by Jean-Paul van Soest, Clinton A. Potts, Sarwan Peiter, Adrián Sanz Mora and Gary A. Steele.

Fig. 2 in Phylogeography and species delimitation of the Asian cavity-nesting honeybees

Fig. 2. Bayes Factor species delimitation tests hypotheses of the number of species in a set of samples based on the multi-locus data. Blue lines show trace coalescence of SNPs, in which simultaneous coalescences to an ancestor node indicate a higher likelihood of speciation event. The best-supported model recognized A. nigrocincta and 6 species among populations currently placed within A. cerana.

Fig. 4 in Phylogeography and species delimitation of the Asian cavity-nesting honeybees

Fig. 4. RASP uses the localities of individuals and RADseq SNP data to reconstruct ancestral ranges for the major nodes. Above: Ultrametric tree; colors of the vertical blocks on the right indicate the single most likely reconstructed ancestral range for each of the major nodes.The 2 most likely ancestral ranges are shown by color-coded pie diagrams at the major nodes on the tree. Additional possible, but less likely, ancestral ranges at each node are indicated in black. Below: Event graph; X-axis shows time along the same scale as the ultrametric tree.Y-axis shows number of estimated events (dispersal, vicariance, extinction, and "standard̎, or corrected number of events considering the probabilities of all vicariance, dispersal, and extinction events).

Fig. 1 in Phylogeography and species delimitation of the Asian cavity-nesting honeybees

Fig. 1. (A) BEAST maximum clade credibility tree with 10 Apis clades indicated by colored bars, including: the dwarf honey bees Apis andreniformis and A. m. florea; the giant honey bees, A. dorsata; and the cavity-nesting species A. mellifera, A. koschevnikovi, A. nigrocincta, and A. cerana in the broad sense. Within A. cerana in the broad sense there are 5 clades associated with their geographic distribution: oceanic Philippine, India-yellow, Sundaland, Mainland, and Indiablack, which is nested within the Mainland clade.Terminals are individual bee samples, black, gray, and white circles indicate strength of support for nodes, and colored bars flanking nodes indicate the maximum credibility interval. Numbered nodes indicate the most recent common ancestors of clades discussed in the text. (B-F) STRUCTURE analyses support the hypothesis that populations currently placed in A. cerana can be divided into 4 lineages: oceanic Philippines, Indiayellow, Sundaland, and Mainland in the narrow sense.

Fig. 3 in Phylogeography and species delimitation of the Asian cavity-nesting honeybees

Fig. 3. Discriminant analysis of principle components (DAPC) indicates the number of isolated clusters among the individuals included in the analyses. Crosses represent the centroid of each group. Discriminant analyses were conducted using the first 20 principal component axes for cumulated variance (inset graphs in A and B show PCA eigenvalues; first 20 principal component axes are shaded black). (A) Apis mellifera and A. koschevnikovi are isolated from other cavitynesting Apis populations. Oceanic Philippine cavity-nesters and A. nigrocincta are shown as distinct groups very near the remaining populations. (B) This analysis shows 3 well-isolated groups among populations currently placed within A. cerana (excluding the Philippine cavity-nesters): Sundaland, India-yellow, and Mainland A. cerana.