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This document presents a dataset on various stoichiometric Niobium nitrides compounds under different pressures, which have been identified by first-principles calculations in combination with an evolutionary algorithm methodology implemented in the USPEX code in its variable-composition mode. The feature of this methodology is to find the ground state or metastable structures with only the knowledge of chemical composition at given pressure conditions and predict through all possible structures, not relying on any prior known structural information. We have successfully predicted the crystal structures and phase transitions of NbN at pressures up to 100 GPa. Because the Niobium nitrides represent a rich family of phases where the stability and microstructures are still not completely understood, it is exciting to find news structures of NbxNy under high pressure.This study used a statistical approach to measure how urban citizens in certain provinces of Indonesia handle their waste. It illustrates how the desirable habits related to environmental consciousness differ across urban citizens among different regions and economic classes. A wide disparity was found in people's understanding of a healthy and clean environment across provinces and cities. Waste management ignorance was also found to be prevalent. Inculcating personal awareness of the local environment was found to be a good start toward keeping the environment clean. The observed positive correlation between the overall living conditions and littering behavior indicates that households that exhibit littering behavior also tend to score higher on living conditions. This significant positive correlation is indicative of self-interest and ignorance. Birinapant The study also suggests that a higher level of household economic prosperity correlates with a more desirable behavior toward maintaining a clean and healthy environment; such behaviors are also adopted by citizens living in clean neighborhoods. Furthermore, a clean and healthy lifestyle is also supported by environmental consciousness in conjunction with hygienic environmental conditions.This article presents raw data from a survey conducted to identify the selection criteria of breeders raising either of four strains of Beetal goats, namely Beetal Faisalabadi, Beetal Makhi-Cheeni, Beetal Nuqri, and Beetal Rahim Yar Khan. After a pre-survey, a questionnaire was developed and a survey was conducted at four sites of the Punjab province of Pakistan Faisalabad/Sahiwal, Bahawalpur/Bahawalnagar, Rajanpur, and Rahim Yar Khan. Each of these sites was the home tract of one strain. During the survey breeders (n = 162) were asked to rank the traits of their selection criteria based on the relative importance of those traits. Furthermore, the prevailing production system was also characterized by the breeders. For the interpretation of the results of this survey the readers are referred to Ref. [1]. The raw data set provided in this article can be extended in the future to include more strains of Beetal goats as well as other goat breeds. The selection criteria of breeders can change over time. This data set can also be used in future studies to investigate the temporal changes in the relative importance of different traits for the breeders. The factors potentially influencing those changes can also be investigated. This data set can further be utilized to design community based breeding plans tailored to the needs of the goat farming community.To elucidate the regularities of adaptation of the representatives of class Mollicutes to antimicrobials and to identify the promising targets for eradication of mycoplasma infections and contaminations the comparative analysis of the molecular basis of bacterial resistance to antibiotics of different classes is needed. Previously, we presented the data on the whole-genome sequences of Acholeplasma laidlawii strains with different susceptibility to ciprofloxacin (GenBank LXYB00000000.1), tetracycline (GenBank NELO00000000.2) and melittin (GenBank NELN00000000.2) as well as the data on cell and extracellular vesicle proteomes of melittin-resistant A. laidlawii strain [1]. The lists of extracellular vesicle proteins secreted by A. laidlawii strains with the increased resistance to ciprofloxacin (PG8R10) and tetracycline (PG8RTet) are presented here. The vesicle proteome profiles were obtained by 1D SDS-PAGE and liquid chromatography-mass spectrometry.Spectral libraries generated by data dependent acquisition (DDA) are a useful tool for the analysis of data created by data independent acquisition (DIA) in mass spectrometry. The quality of DIA analysis is dependent on the quality of the spectral library. We used cerebrospinal fluid (CSF) of patients with Parkinson's disease and healthy controls to create a spectral library of human CSF proteome. To this date, there is no validated CSF biomarker for Parkinson's disease. This data set may therefore be valuable for the future analysis of CSF proteins. Part of the samples consisted of fractions that were separated by gel electrophoresis. After tryptic digestion, all samples were spiked with indexed retention time (iRT) peptides and were measured using a DDA mass spectrometry approach. The here provided data set can be used as a CSF-specific spectral library. Data files generated from the described workflow are hosted in the public repository ProteomeXchange under the identifier PXD013487.The term social bots refer to software-controlled accounts that actively participate in the social platforms to influence public opinion toward desired directions. To this extent, this data descriptor presents a Twitter dataset collected from October 4th to November 11th, 2019, within the context of the Spanish general election. Starting from 46 hashtags, the collection contains almost eight hundred thousand users involved in political discussions, with a total of 5.8 million tweets. The proposed data descriptor is related to the research article available at [1]. Its main objectives are i) to enable worldwide researchers to improve the data gathering, organization, and preprocessing phases; ii) to test machine-learning-powered proposals; and, finally, iii) to improve state-of-the-art solutions on social bots detection, analysis, and classification. Note that the data are anonymized to preserve the privacy of the users. Throughout our analysis, we enriched the collected data with meaningful features in addition to the ones provided by Twitter.
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