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Major element compositions of minerals (Ol, Opx, Cpx and Spl), whole-rock major- trace- and Re-Os isotopic compositions of the Yunzhug ophiolitic peridotites
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The Quality of Nationality Index (QNI) Settlement Freedom dataset contains the settlement freedom of virtually all nationalities in the world over the last 10 years (2010–2019). Settlement freedom is defined as the freedom of the holder of a particular nationality to have “full access” (that is, being able to freely work and live) to other territories than the one with which the nationality is associated, without being subject to substantive immigration requirements. For measuring Settlement Freedom, settlement in a particular country is considered possible if an adult holder of a nationality is allowed to work there without having to obtain a visa or with a visa acquired on arrival. Permission to work in that country is either not required or virtually automatic. The following factors are not considered in determining the freedom to settle in another country: entitlement to public pension systems; entitlement to health care; entitlement to social security benefits; ability of family members to join the person in question; specific skill qualifications that are required to perform certain professions, particularly of a qualitative nature, such as bar qualifications to practice as a lawyer, medical qualifications to practice as a doctor, or construction-worker qualifications. We also do not take into account any settlement freedom that is based on factors other than nationality itself, such as being in possession of a higher education diploma. We distinguish between Diversity of Settlement Freedom and Weight of Settlement Freedom. Diversity and Weight of Settlement Freedom each account for 15% of the overall score of a nationality in the QNI General Ranking (see Kälin and Kochenov’s Quality of Nationality Index (D. Kochenov and J. Lindeboom eds., 2020)). Diversity of Settlement Freedom refers to the number of destinations to which the holder of a nationality has full access as defined above. Data is gathered through extensive research into the legal requirements for settlement throughout the world, complemented with expert consultation in all regions of the world. The more countries giving full-access settlement to the holder of a nationality, the higher that nationality’s score is on Diversity of Settlement Freedom. All data is converted and normalized on the 0–15 scale. Weight of Settlement Freedom refers to the aggregate value of the destinations to which the holder of a nationality has full access. This aggregate value is based on the sum of weighted scores of those destinations on the QNI’s “Human Development” and “Economic Strength” parameters (see in more detail, Kälin and Kochenov’s Quality of Nationality Index 2020, p. 52–67). Each parameter accounts for 50% of the “destination value” of each destination. The sum of all these destination values becomes the Weight of Settlement Freedom for a given nationality. This sum is normalized on a 0–15 scale. For the Quality of Nationality Index dataset, see 10.17632/53zr7cfyrs.1.
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this Data reveals all results founded in this research paper
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Results of reliability assessment of punching shear resistance models for flat slabs without shear reinforcement through three different reliability analysis techniques: Mean Value First Order Second Moment Method (MVFOSM), First Order Second Method (FOSM) and a Monte-Carlo Simulation with Importance Sampling (MC-IS).
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Dados para análise fatorial exploratória para a composição do modelo de dados.
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Band gaps and Total Density of States for calculated lead-free perovskites
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Palynomorph assemblages and palynofacies analysis have been performed on several core samples from the Devonian–Carboniferous deposits identified in five wells located in the eastern part of the Moesian Platform. The investigated sections include, in ascending stratigraphic order, the Ţăndărei, Smirna, Călăraşi and Vlaşin formations. Based on stratigraphic distribution of key taxa identified (miospores, chitinozoans, acritarchs), seven biozone intervals (four for Devonian and three for Carboniferous) have been recognized. The oldest samples were dated as being part of the micrornatus-newportense (MN) – lower part of breconensis-zavallatus (BZ) interval zones (early Devonian), while the younger ones are assigned to the kosankei-varioreticulatus (KV) – nobilis-junior (NJ) interval zones (late Carboniferous). Palynofacies observations suggest a more distal depositional environment during the period between Lochkovian and Pragian times, followed by some proximal/fluvio-deltaic conditions in Emsian–early Eifelian (the top of Ţăndărei Formation). The upper Tournaisian to Serpukhovian sedimentary rocks of the Călăraşi and lower part of Vlaşin formations were deposited in inner neritic environments. Mud-dominated dysoxic/anoxic conditions prevailed in the Bashkirian, which were quickly succeeded by a deltaic deposition and oxidizing environments which persisted up to Moscovian. The lower Devonian terrestrial palynoflora is dominated by trilete spores which belong to the lowland vegetation of a non-forest mire palaeoecological group. The Carboniferous deposits yielded only terrestrial palynomorphs of various types of arborescent and herbaceous lycopsids and ferns, suggesting different habitats such as non-flooded wetlands or swamps within coastal plain and continental interiors. These assemblages of Carboniferous miospores are an indication of the neutral-humid climatic conditions which existed at the time of deposition.
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Data for three experiments
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Selected companies in Russia investing in intellectual capital. Designed VAIC components for companies: CEE, HCE, SCE.
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The research question for this dataset was: How will climate change impact the growth of spring wheat in Fairbanks, Alaska? The DSSAT CERES-Wheat crop simulation model was used to answer this research question. Data consists of DSSAT V4.7.0.0 Files and Field Data. Data in the Field Data files were collected at the University of Alaska Fairbanks small grains variety trial plot in Fairbanks, AK. This field data was input into DSSAT. DSSAT Files were used to calibrate, validate, and apply the DSSAT CERES-Wheat crop simulation model for simulating spring wheat growth (cultivar Ingal) in projected climate change scenarios. These DSSAT files are ready for a modeler to use.
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