The significance of land cover as an environmental variable has made land use change an important subject in global environmental change and sustainable development. Modeling land use change has attracted considerable attention. Currently, empirical estimation models using statistical techniques are one of mostly used spatial models to simulate land use pattern and its changes. Empirical estima...

Evaluating agricultural land management practices requires knowledge of soil spatial variability and understanding their relationships. Spatial distributions for fourteen soil physical and chemical properties were examined in a wheat field in Sorkhankalateh district, in Golestan province, Iran. 101 soil samples at the distances of 5m, 10m and 20m as nested grid were collected at the depth of 0-...

We study the detection of continuous-variable entanglement, for which most existing methods designed so far require a full specification devices, and we present protocols entanglement in scenario where measurement devices are completely uncharacterized. first generalize, to continuous variable regime, seminal results by Buscemi [Phys. Rev. Lett. 108, 200401 (2012)] Branciard et al. 110, 060405 ...

Continuous-variable measurement-based quantum computation on cluster states has in recent years shown great potential for scalable, universal, and fault-tolerant when combined with the Gottesman-Kitaev-Preskill (GKP) code error correction. However, no complete architecture exists that includes everything from cluster-state generation finite squeezing to gate implementations realistic noise In t...

Latent variable models are common in the social sciences to measure ideal points of U.S. Senators, countries’ “level of democracy” or the relationships between latent attitudes and values across countries, for instance. Because differences in measurement parameters can be confounded with substantively interesting differences, measurement invariance or “equivalence” is a prerequisite for cross-g...