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opencc-by-4.0Jul 2019View details →

Systematic screening of DMOF-1 with NH2, NO2, Br and azobenzene functionalities for elucidation of carbon dioxide and nitrogen separation properties

Publication: M. Xie. N. Prasetya and B. P. Ladewig, Systematic screening of DMOF-1 with NH2, NO2, Br and azobenzene functionalities for elucidation of carbon dioxide and nitrogen separation properties, Inorganic Chemistry Communications (2019). Preprint: M. Xie. N. Prasetya and B. P. Ladewig, Systematic screening of DMOF-1 with NH2, NO2, Br and azobenzene functionalities for elucidation of carbon dioxide and nitrogen separation properties, Inorganic Chemistry Communications (2019), <a href="https://doi.org/10.26434/chemrxiv.8862239.v1">https://doi.org/10.26434/chemrxiv.8862239.v1</a> Dataset supporting publication, including SEM images, optical microscope images, NMR spectra, data used in Figures, and full resolution figures as included in the manuscript. Abstract: In this study, dabco MOF-1 (DMOF-1) with four different functional groups (NH2, NO2, Br and azobenzene) has been successfully synthesized through systematic control of the synthesis condition of their parent framework. The functionalised DMOF-1 is characterized using various analytical techniques including PXRD, TGA and N2 sorption. The effect of the various functional groups on the performance of the MOFs for post-combustion CO2 capture is evaluated. DMOF-1s with polar functional groups are found to have better affinity with CO2 compared with the parent framework as indicated by higher CO2 heat of adsorption. However, imparting steric hindrance to the framework as in Azo-DMOF-1 enhances CO2/N2 selectivity, potentially as a result of lower N2 affinity for the framework.

opencc-by-4.0Sep 2019View details →

14-day smartphone ambulatory assessment of depression symptoms and mood dynamics in a general population sample: comparison with the PHQ-9 depression screening

This dataset contains 14 days of ambulatory assessment (AA) depression symptoms and mood ratings with timestamps, a retrospective Patient Health Questionnaire (PHQ-9) assessment and the demographic variables age and gender. The AA was conducted with users of the mobile mental health / depression screening app "Moodpath". ICD-10 depression symptoms were assessed with the following questions: ICD-10 symptom 1: "depressed mood" q1 = Are you feeling depressed? q2 = Are you feeling hopeless? ICD-10 symptom 2: "loss of interest and enjoyment" q3 = Do you feel like you are not interested in anything right now? q4 = Do you have less pleasure in doing things you usually enjoy? ICD-10 symptom 3: "increased fatigability" q5 = Do you currently have considerably less energy?  q6 = Are your everyday tasks making you very tired currently? ICD-10 symptom 4: "reduced concentration and attention" q11 = Is it hard for you to make decisions currently?  q12 = Is it hard for you to concentrate currently? ICD-10 symptom 5: "reduced self-esteem and self-confidence" q7 = Is your self-confidence clearly lower than usual? q8 = Are you feeling up to your tasks?   ICD-10 symptom 6: "ideas of guilt and unworthiness" q9 = Are you blaming yourself currently?  q10 = Do you think you are worth less than others right now? ICD-10 symptom 7: "bleak and pessimistic views of the future" q46 = Are you thinking that you will be doing well in the future?  q47 = Are you looking hopefully into the future? ICD-10 symptom 8: "ideas or acts of self-harm or suicide" q16 = Are you thinking about death more often than usual?  ICD-10 symptom 9: "disturbed sleep" q13 = Did you sleep badly last night?  ICD-10 symptom 10: "diminished appetite" q14 = Do you have less or no appetite today?

openapache2.0Aug 2024View details →

High-throughput Computational Screening of Hydrocarbon Molecules for Long-wavelength Infrared Imaging

This repository contains datasets associated with the paper titled "High-throughput Computational Screening of Hydrocarbon Molecules for Long-wavelength Infrared Imaging," accepted at ACS Materials Letters Journal. Contents: <ol> <li> Optimized XYZ Coordinates: The hydrocarbon molecules' XYZ coordinates, obtained using the B3LYP functional and the 6-31g(d,p) basis set in Gaussian 16 software, used to simulate the IR spectra (including transition energies and absorption intensities) of the molecules. </li> <li> Broadened Molar Absorptivity IR Spectra: The dataset's IR spectra, broadened using a Lorentzian band shape with a gamma (half-width at half-height) value of 5 cm⁻¹. Molecules with imaginary frequencies have been excluded. </li> <li> Related SMILES Strings: Contains SMILES strings for these hydrocarbons. </li> <li> NUMBERS_SMILES.csv: Provides the associated SMILES string for each numerated XYZ coordinate. </li> </ol> For any inquiries, please contact Dr. Maliheh Shaban Tameh at malihe.shaban<a rel="noreferrer">@gmail.com</a>

opencc-by-4.0Nov 2011View details →

Text-fig. 1. "Plant screen" scheme of complete results of the IPR-vegetation analysis derived from the database. in The Integrated Plant Record Vegetation Analysis: Internet Platform And Online Application

Text-fig. 1. "Plant screen" scheme of complete results of the IPR-vegetation analysis derived from the database.

opencc-by-4.0Dec 2020View details →

Fig. 4 in Molecular screening for rickettsial bacteria and piroplasms in ixodid ticks surveyed from white-tailed deer (Odocoileus virginianus) and nilgai antelope (Boselaphus tragocamelus) in southern Texas

Fig. 4. Phylogentic analysis of sca0 (rompA) sequences from putative Rickettsia sp. endosymbionts of Amblyomma maculatum and Ixodes scapularis ticks collected from white-tailed deer in southern Texas. This is a maximum-likelihood tree that is rooted at midpoint. Branch support was assessed with 10,000 replicates of UFBoot bootstrap replication, and bootstrap percentages are indicated at each branch point in the tree. Sequences from GenBank used in the comparative analysis were annotated as rickettsial endosymbionts. Accession numbers and tick species from which sequence was identified are included on the branch label.

opencc-by-4.0Dec 2020View details →

Fig. 3 in Molecular screening for rickettsial bacteria and piroplasms in ixodid ticks surveyed from white-tailed deer (Odocoileus virginianus) and nilgai antelope (Boselaphus tragocamelus) in southern Texas

Fig. 3. Phylogentic analysis of Theileria sp. fragments from Anocenter nitens ticks. Representative Type F, Type G, and 'divergent' Theileria sp. sequences were identified from individual A. nitens ticks collected from white-tailed deer and a single nilgai host (bold labels). A maximum-likelihood tree was constructed using Toxoplasma gondii as the outgroup, as it is from a different axpicomplexan class than Theileria. Branch support was assessed with 10,000 replicates of UFBoot bootstrap replication, and bootstrap percentages are indicated at each branch point in the tree. GenBank accession numbers and annotated identification for sequences used in the comparative analysis are indicated on the branch labels. Accession numbers in italics are those T. cervi sequences from white-tailed deer on the East Foundation's San Antonio Viejo Ranch in Starr and Jim Hogg Counties, Texas (Yu et al., 2020).

Fig. 2 in A rapid screening method for resistance to Anthonomus eugenii (Coleoptera: Curculionidae) in Capsicum (Solanaceae) spp. plants

Fig. 2. Visual scale of damaged leaf area by Anthonomus eugenii on pepper leaves: 1 = leaf with 0% of damaged area, 3 = leaf with approximate 25% of damaged area, 5 = leaf with approximate 50% of damaged area, 7 = leaf with approximate 75% of damaged area, and 9 = leaf with approximate 100% of damaged area.

Fig. 1 in A rapid screening method for resistance to Anthonomus eugenii (Coleoptera: Curculionidae) in Capsicum (Solanaceae) spp. plants

Fig. 1. Plastic micro-cages used for resistance experiments to Anthonomus eugenii on pepper leaves: (A) empty micro-cage, (B) micro-cage used as negative control where we placed only pepper leaves without insects, (C) micro-cage with adults of A. eugenii and pepper leaves, and (D) close up of 1 micro-cage with adults of A. eugenii and pepper leaves for resistance experiments.

Fig. 4 in A rapid screening method for resistance to Anthonomus eugenii (Coleoptera: Curculionidae) in Capsicum (Solanaceae) spp. plants

Fig. 4. Damage caused by Anthonomus eugenii: (A) susceptible control leaf of the Fascinato commercial cultivar with severe damage, and (B) Capsicum annuum plant considered resistant of the UTC17 wild pepper population collected from Tabasco, Mexico, infested with A. eugenii. Picture was taken 7 d afer infestation.

Fig. 3 in A rapid screening method for resistance to Anthonomus eugenii (Coleoptera: Curculionidae) in Capsicum (Solanaceae) spp. plants

Fig. 3. Mortality (%) of Anthonomus eugenii adults per micro-cage during 21 consecutive d afer infestation (DAI) in pepper leaves from wild and landrace populations and commercial cultivars. Bars are average percentage mortality. Comparisons made with Mann-Whitney test (P ≤ 0.05). Different letters in the columns indicate significant differences. Error bars indicate the standard error.

opencc-by-4.0Dec 2021View details →

Fig. 1 in Molecular screening of ticks of the genus Amblyomma (Acari: Ixodidae) infesting South African reptiles with comments on their potential to act as vectors for Hepatozoon fitzsimonsi (Dias, 1953) (Adeleorina: Hepatozoidae)

Fig. 1. Maximum likelihood analysis of Amblyomma tick species based on the 16S rRNA sequences. Bootstrap values at the major nodes are of percentage agreement among 1000 replicates. The branch scale represents substitutions per site.

opencc-by-4.0Dec 2021View details →

Fig. 2 in Molecular screening of ticks of the genus Amblyomma (Acari: Ixodidae) infesting South African reptiles with comments on their potential to act as vectors for Hepatozoon fitzsimonsi (Dias, 1953) (Adeleorina: Hepatozoidae)

Fig. 2. Maximum likelihood analysis of species of Hepatozoon based on the 18S rRNA sequences. Bootstrap values at the major nodes are of percentage agreement among 1000 replicates. The branch scale represents substitutions per site.

Fig. 3 in Eco-epidemiological screening of multi-host wild rodent communities in the UK reveals pathogen strains of zoonotic interest

Fig. 3. Bayesian phylogenetic tree of 18S ribosomal RNA sequences of Babesia microti isolates, indicating the position of the Munich strain-like isolate obtained from the tick Ixodes trianguliceps from a bank vole in Ceredigion, Wales. Sequences of the cogeneric species B. vulpes and B. rodhaini are used as outgroups.

Fig. 2 in Eco-epidemiological screening of multi-host wild rodent communities in the UK reveals pathogen strains of zoonotic interest

Fig. 2. Flea diversity. Percentage of flea genera collected during the two sampling seasons. *p <0.05.

Fig. 1 in Eco-epidemiological screening of multi-host wild rodent communities in the UK reveals pathogen strains of zoonotic interest

Fig. 1. Percentage of tick life stages across seasons collected from all rodent species. a) Total percentage of ticks found in the two study seasons. Light grey: larvae; dark grey: nymphs; black: adults. b) Percentage of tick life stages in each sampling season.

Fig. 3 in Molecular screening for Sarcocystidae in muscles of wild birds from Brazil suggests a plethora of intermediate hosts for Sarcocystis falcatula

Fig. 3. Phylogenetic tree of Sarcocystis spp. based on ITS1 sequences. The tree was constructed through the maximum likelihood method, using the best-fit model HKY + I. The final alignment contained 78 sequences and 661 aligned nucleotide positions. All positions containing gaps and missing data were eliminated (complete deletion option). Numbers on branches represent bootstrap values after 1000 replicates. The black dots identify the sequences obtained in this study.

Fig. 2. SAG1 in Molecular screening for Sarcocystidae in muscles of wild birds from Brazil suggests a plethora of intermediate hosts for Sarcocystis falcatula

Fig. 2. SAG1 (a), SAG2 (b) and SAG3 (c) haplotype networks for Sarcocystis falcatula and other closely related species obtained in this study. Perpendicular bars along the branches refer to mutation changes. The sizes of the circles are proportional to the numbers of haplotypes, and colors indicate the different orders of birds found. The numbers correspond to the sample IDs. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Fig. 1 in Molecular screening for Sarcocystidae in muscles of wild birds from Brazil suggests a plethora of intermediate hosts for Sarcocystis falcatula

Fig. 1. Phylogenetic tree of Sarcocystis spp. based on ITS1 sequences. The tree was constructed through the maximum likelihood method, using the best-fit model K2P + G. The final alignment contained 24 sequences and 389 aligned nucleotide positions. All positions containing gaps and missing data were eliminated (complete deletion option). Numbers on branches represent bootstrap values after 1000 replicates. The black dots identify the sequences obtained in this study.

opencc-by-4.0May 2017View details →

Fig 7 in An activity-integrated strategy of the identification, screening and determination of potential neuraminidase inhibitors from Radix Scutellariae

Fig 7. HCA dendrogram of 18 RS samples based on the NA inhibitory activity of compounds. Biennially cultivated RS (Group 1), perennially cultivated RS (Group 2), wild RS (Group 3) and plateau area RS (Group 4). https://doi.org/10.1371/journal.pone.0175751.g007