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opencc-by-4.0Jun 2024View details →

Crosswalks IUCLID 6 v9 EU PPP Active substance application (product) to KCA&KCP

This Excel file provides detailed crosswalks from the <a href="https://esubmission.croplifeeurope.eu/registration-for-download/">EU Table of Contents (SANCO/10181/2013)</a> for plant protection product (PPP) dossiers to <a href="https://iuclid6.echa.europa.eu/it/home">IUCLID 6 v9</a>. It includes two spreadsheets, containing the mappings for active substance (as laid out in Commission Regulation (EU) No 283/2013) and representative product (Commission Regulation (EU) No 284/2013): <ul> <li>EU_PPP_ActiveSubstance: mapping between the "KCA" ToC and IUCLID 6 v9 working context "EU PPP Active substance information"</li> <li>EU_PPP_Product: mapping between the "KCP" ToC and IUCLID 6 v9 working context "EU PPP Active substance application (product)"</li> </ul> The spreadsheets map each section of the original EU ToC to: <ul> <li>IUCLID section: name of the section in IUCLID where to input the corresponding data/information</li> <li>Endpoint study record: name of the document template used to report individual studies of the section (if exists). These usually correspond to <a href="https://www.oecd.org/en/topics/sub-issues/assessment-of-chemicals/harmonised-templates.html">OECD Harmonised Templates (OHT)</a>.</li> <li>Endpoint summary: name of the document template used to report the summary information of the studies presented in the section (if available)</li> <li>Other IUCLID document: name of any other document template in IUCLID used to report information of the section (if available)</li> <li>OHT: name/id of the OECD Harmonised Template used for the endpoint study record document (if available)</li> <li>Additional context: fulI IUCLID paths indicating the section of the respective document where information needs to be provided and/or specific values to be indicated. If more than one path is provided, these are separated by ";". Operators "=" and "!=" are used to indicate values to be used and to be avoided, respectively. When more than one value is possible, "IN" and "NOT IN" operators are used, followed by the exhaustive list of possible values. This nomenclature was defined with the aim of making contents machine-readable.</li> </ul> Version 6 includes changes in the table of contents of IUCLID 6 v9.

opencc-by-4.0Aug 2024View details →

Supplemental Figures for: "The SDSS-V Black Hole Mapper Reverberation Mapping Project: Multi-Line Dynamical Modeling of a Highly Variable Active Galactic Nucleus with Decade-long Light Curves"

Additional figures for the paper The SDSS-V Black Hole Mapper Reverberation Mapping Project: Multi-Line Dynamical Modeling of a Highly Variable Active Galactic Nucleus with Decade-long Light Curves.  <h2> </h2> <h2>Interactive Figure Data</h2> Data files used to create the intreactive version of Figure 5 in the publication. There is a version of each file for each line species in the plot (i.e., Hα, Hβ, and MgII). clouds_{line_name}.csv: A CSV file containing the cloud positions, line-of-sight velocities, and weights. The columns of the file are x [light-day], y [light-day], z [light-day], velocity [km/s], and weight. transfer_function_velocity_{line_name}.csv: A CSV file containing x-axis of the transfer function panels, the rest-frame velocity. transfer_function_tau_{line_name}.csv: A CSV file containing the y-axis of the transfer function panels, the rest-frame time delay τ in days. transfer_function_{line_name}.csv: A CSV file containing the transfer function Ψ.   <h2>Model-Related Figures</h2> fitplot_low.pdf: Same as Figure 4 in the publication, but for the low state. fitplot_high.pdf: Same as Figure 4 in the publication, but for the high state. geoplot_low.pdf: Same as Figure 5 in the publication, but for the low state. geoplot_high.pdf: Same as Figure 5 in the publication, but for the high state. lagplot_low.pdf: Same as Figure 6 in the publication, but for the low state. lagplot_high.pdf: Same as Figure 6 in the publication, but for the high state.    <h2>Spectral Reduction Method Comparison</h2> spec_decomp_pyqsofit.pdf: A figure showing the spectral decomposition performed in PyQSOFit for the processed line profiles for Hβ, Hα, and MgII for an example epoch. The total spectrum is shown in black, and each of the decomposed elements are shown, color-coded using the legend above the three panels. input_method_comp.pdf: A figure showing the processed multi-epoch line profiles for each spectral reduction method (PyQSOFit and PrepSpec). Each column corresponds to a given line (labeled above), and each row corresponds to a given spectral reduction method (labeled on the right). Note that the scales for each panel are different.   <h2>Published Value Comparison</h2> pubval_table.pdf: A table comparing the values obtained for certain physically relevant parameters obtained from our BRAINS modeling to those obtained in Shen et al. (2024).    <h2>Joint Posterior Analysis</h2> joint_line_posterior_table.pdf: A table containing the median values (and their uncertainties) extracted from the joint posteriors for a few key model parameters. These joint posteriors are produced for a given state, across all line species.    <h2>Virial Factor Analysis</h2> fcomp.pdf: A comparison of the virial factor values obtained by using the line dispersion (σ) and FWHM of each of the lines in each of the states. fcorr_table.pdf: A table showing the correlations between the virial factor and model parameters (i.e., the slopes obtained using <a href="https://github.com/jmeyers314/linmix">LinMix</a> assuming a linear relationship, and the correlation coefficients). Values are given for virial factors obtained using both the line dispersion (σ) and FWHM.

opencc-by-4.0Oct 2023View details →

Comparison of Leaves and Stem Aqueous Extract of Tridax Procumbens for Antimicrobial Activity

In present study, aq. extracts of leaves and stem part of Tridax Procumbens were compared for antimicrobial activity. Firstly, all organoleptic and physicochemical properties of leaves and stem powder were evaluated and it shows that drug is pure and having required constituents sufficiently. Aq. extract of leaves powder and stem powder was prepared separately using Soxhlet extraction technique. Both the extracts were evaluated for physiochemical screening using standard procedures. Aq. extract of leaves shows presence of tannis, saponins, anthocyanin, coumarins, alkaloids, proteins, amino acids, diterpenes, phytosterol, cardial glycosides, phlobatannins and flavonoids. Aq. extract of stem shows presence of tannins, coumarins, phenol, cardial glycosides and flavonoids. Both extracts were primarily evaluated for antimicrobial activity against E.coli and S. aureus by selecting dose of 500 mg. Finally, antimicrobial assay was performed for both extracts (500mg) against E.coli and S. aureus by well diffusion method using Amoxicillin and Amikacin as standards respectively. Antimicrobial assay shows that aq. extract of stem part is more effective against S. aureus than E.coli; leaves aq. extract also shows antimicrobial activity against S .aureus and E.coli. From present studies we can conclude that aq. extract of stem and leaves of Tridax Procumbens having antimicrobial activity and stem extract is more effective against S. aureus as compared to leaf extract.

opencc-by-nc-3.0Apr 2022View details →

Catalyst sites and active species in the early stages of MTO conversion over cobalt AlPO-18 followed by IR spectroscopy

Supplementary material:  Ex-situ DR-UV-visible spectroscopy, Ex-situ FT-IR Spectroscopy. In-situ FT-IR Spectroscopy, In continuo FT-IR Spectroscopy, Brønsted acidity of SAPO-18

opencc-by-4.0Sep 2023View details →

Inhibition of Parkinson's Disease-related LRRK2 by type-I and type-II kinase inhibitors: activity and structures

Mutations in Leucine Rich Repeat Kinase 2 (LRRK2) are a common cause of familial Parkinson’s Disease (PD), and a risk factor for the sporadic form. Increased kinase activity has been shown in both familial and sporadic PD patients. This has made LRRK2 kinase inhibitors a major focus of drug development efforts in PD. Although significant progress has been made in understanding the structural biology of LRRK2, there are no available structures of LRRK2 inhibitor complexes. To this end, we solved cryo-EM structures of LRRK2, wild-type and PD-linked mutants, bound to the LRRK2-specific type-I inhibitor MLi-2 and the broad-spectrum type-II inhibitor GZD-824. Our structures revealed LRRK2’s kinase in the active-like state, stabilized by type-I inhibitor interactions, and an inactive DYG-out type-II inhibitor complex. The structures also showed how inhibitor-induced conformational changes are affected by the N-terminal half of LRRK2. The structural models provide a template for the rational development of LRRK2 kinase inhibitors covering both canonical inhibitor binding modes.

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Data from: Artificial intelligence enabled multi-purpose smart detection in active-matrix digital microfluidics

Active-matrix digital microfluidics (AM-DMF), integrated with hundreds of thousands of active electrodes, can simultaneously realize multiple on-chip bio-chemical reactions at the single-cell level. An intelligent detection system is critical for fully automating manipulations of thousands of digitalized bio-samples and programming the subsequent experiments in real time. In this work, we developed a series of deep learning algorithms based on an AM-DMF system for sample detections. We used the U-net model to quantitatively evaluate different splitting methods on sample droplet generation uniformity. The results revealed that droplets generated using the "one-to-two" strategy exhibits optimal uniformity. We used the YOLOv5 model to monitor the droplet splitting success rates over 18 different AM-DMF chips, and a 97.7% splitting success rate was observed. The results indicated that the model precision was 99.980% and the model recall was 99.976% through manual verification. In addition, we used an improved YOLOv8 model to detect single cells in nanoliter droplets effectively. In comparison with manual verification, the results showed that the model achieved a precision of 99.260% and a recall of 99.193%. By leveraging an artificial intelligence enabled smart detection system, AM-DMF has shown great potential as a ubiquitous platform for true lab-on-a-chip.

opencc-zeroOct 2023View details →

Fig. 5 in Habitat Preferences And Activity Patterns Of The Larger Mammal Community In Phnom Prich Wildlife Sanctuary, Cambodia

Fig. 5. Mean Relative Abundance Indice (± SEM) for 12 most frequently encountered mammal species in PPWS at camera trap locations closer (black bars) and further (open bars) than 11-km from nearest village. RM red muntjac; EWP Eurasian wild pig; B banteng; E Asian elephant; LIC large Indian civet; EAP east Asian porcupine; L leopard; CPC common palm civet; D dhole; LC leopard cat; G gaur; and PTM pig-tailed macaque.

Fig. 4 in Habitat Preferences And Activity Patterns Of The Larger Mammal Community In Phnom Prich Wildlife Sanctuary, Cambodia

Fig. 4. Mean Relative Abundance Indices (± SEM) for 12 most frequently encountered mammal species in PPWS at camera trap locations in DDF (black bars) and SEGF (open bars). RM red muntjac; EWP Eurasian wild pig; B banteng; E Asian elephant; LIC large Indian civet; EAP east Asian porcupine; L leopard; CPC common palm civet; D dhole; LC leopard cat; G gaur; and PTM pig-tailed macaque.

Fig.6 in Habitat Preferences And Activity Patterns Of The Larger Mammal Community In Phnom Prich Wildlife Sanctuary, Cambodia

Fig.6. Activity patterns, % of all encounters within each hour, of red muntjacs and Eurasian wild pigs from camera-traps in PPWS.

Fig. 2 in Habitat Preferences And Activity Patterns Of The Larger Mammal Community In Phnom Prich Wildlife Sanctuary, Cambodia

Fig. 2. Increase in species richness (species recorded) with total cumulative number of camera trap nights within Phnom Prich Wildlife Sanctuary (Dec 08–Aug 09).

Fig. 2 in Diurnal activity, temperature responses and endothermy in three South American cicadas (Homoptera: Cicadidae: Dorisiana bonaerensis, Quesada gigas and Fidicina mannifera)

Fig. 2. Tb of Dorisiana bonaerensis during a light rain under a heavy overcast on the 21st December 1986. These animals were not exposed to direct solar radiation before the Tb was recorded. Closed circles, represent body temperatures of singing D. bonaerensis; open circles, represent body temperatures of D. bonaerensis engaged in other activities (including no activity). Details as in Fig. 1.

Fig. 3 in Diurnal activity, temperature responses and endothermy in three South American cicadas (Homoptera: Cicadidae: Dorisiana bonaerensis, Quesada gigas and Fidicina mannifera)

Fig. 3. Distribution of Dorisiana bonaerensis Tb as a function of Ta. The slope of the linear regression for "active" animals (closed circles) is significantly different from one, suggesting thermoregulation. The slope of the linear regression for "inactive" animals (open circles) is not significantly different from one, suggesting no thermoregulation is occurring.

Fig. 4 in Diurnal activity, temperature responses and endothermy in three South American cicadas (Homoptera: Cicadidae: Dorisiana bonaerensis, Quesada gigas and Fidicina mannifera)

Fig. 4. Distribution of Tb of as a function of Ta when Dorisiana bonaerensis were not exposed to solar radiation. The slope of the linear regression for " active " animals (closed circles) is significantly different from one, suggesting thermoregulation is occurring with endogenous heat. The slope of the linear regression for " inactive " animals (open circles) is not significantly different from one, suggesting no thermoregulation is occurring when the animals do not generate heat for activity.

Fig. 1 in Diurnal activity, temperature responses and endothermy in three South American cicadas (Homoptera: Cicadidae: Dorisiana bonaerensis, Quesada gigas and Fidicina mannifera)

Fig. 1. Diurnal distribution of Tb of Dorisiana bonaerensis and Quesada gigas on the 13th December 1986. A rainstorm from 07.00 to 08.00 h followed by a misting rain until 09.45 h delayed the start of activity approx. 2 h. Body temperatures are below ambient temperature before activity begins. Body temperatures are elevated at the start of activity (10.00 h) and regulated throughout the day. Body temperatures of quiescent animals decrease with ambient temperature after sunset (20.10 h). Animals participating in the evening chorus have body temperatures in or near the body temperature range measured during the day. Closed circles, Tb of singing D. bonaerensis; open circles, Tb of D. bonaerensis engaged in other activities (including no activity); closed triangles, Tb of singing Q. gigas; open triangles, Tb of Q. gigas performing other activities; solid line, ambient air temperature.

FIG. 2 in Biological activity of some Romanian and Turkish Trichoderma Pers. strains

FIG. 2. — Trichoderma Pers. hyperparasitic development on various plant pathogens: Alt., Alternaria sp. Nees; B.c., Botrytis cinerea Pers.; F.c., Fusarium culmorum (Wm.G.Sm.) Sacc.; F.g., F. graminearum Schwabe; F.o., F.oxysporum Schltdl.; F.p., F. proliferatum (Matsush.) Nirenberg ex Gerlach & Nirenberg; M.p., Macrophomina phaseolina (Tassi) Goid.; S.s., Sclerotinia sclerotiorum (Lib.) de Bary.

FIG. 1 in Biological activity of some Romanian and Turkish Trichoderma Pers. strains

FIG. 1. — In vitro antifungal activity of tested Trichoderma strains Ș4 (2), Td-Exp1 (3) and Td-Exp2 (4) against various plant pathogens (1), such as Fusarium culmorum (Wm.G.Sm.) Sacc. (A), F. oxysporum Schltdl. (B), Macrophomina phaseolina (Tassi) Goid. (C) and Sclerotinia sclerotiorum (Lib.) de Bary (D). Scale bars: 1 cm.

FIG. 3 in Biological activity of some Romanian and Turkish Trichoderma Pers. strains

FIG. 3. — Mycoparasitic activity of Trichoderma Td-Exp1 strains against plant pathogens:A, Botrytis cinerea Pers.; B, Fusarium graminearum Schwabe;C, Sclerotinia sclerotiorum (Lib.) de Bary. Scale bars: 1 cm.

FIG. 5 in Biological activity of some Romanian and Turkish Trichoderma Pers. strains

FIG. 5. — Metabolic activity in biofilm and antibiofilm effect of Trichoderma spp. against human pathogenic bacterial strains. Symbols: ns, no significant; *, p <0.05; **, p <0.01; ***, p <0.001; ****, p <0.0001.

opencc-by-4.0Nov 2023View details →

Daily Activity Schedule Tel Aviv 2040 from SimMobility MIT Preday

This database countain the activities conducted in the Tel Aviv metropolis on a typical day in 2040. The information is derived from the outcomes of the Simobility demand simulator, which operates on synthetic population and land-use inputs specific to the Tel Aviv metropolis predictions.