Multivariate synthetic streamflow generation using a hybrid model based on artificial neural networks

A model for multivariate streamflow generation is presented, based on a multilayer feedforward neural network. The structure of the model results from two components, the neural network (NN) deterministic component and a random component which is assumed to be normally distributed. It is from this second component that the model achieves the ability to incorporate effectively the uncertainty associated with hydrological processes, making it valuable as a practical tool for synthetic generation of streamflow series. The NN topology and the corresponding analytical explicit formulation of the model are described in detail. The model is calibrated with a series of monthly inflows to two reservoir sites located in the Tagus River basin (Spain), while validation is performed through estimation of a set of statistics that is relevant for water resources systems planning and management. Among others, drought and storage statistics are computed and compared for both the synthetic and historical series. The performance of the NN-based model was compared to that of a standard autoregressive AR(2) model. Results show that NN represents a promising modelling alternative for simulation purposes, with interesting potential in the context of water resources systems management and optimisation.</p> <p style='line-height: 20px;'><b>Keywords: </b>neural networks, perceptron multilayer, error backpropagation, hydrological scenario generation, multivariate time-series.</p>

Commensurate-Incommensurate Magnetic Phase Transition in Magnetoelectric Single Crystal LiNiPO4_4

Neutron scattering studies of single-crystal LiNiPO$_4$ reveal a spontaneous first-order commensurate-incommensurate magnetic phase transition. Short- and long-range incommensurate phases are intermediate between the high temperature paramagnetic and the low temperature antiferromagnetic phases. The modulated structure has a predominant antiferromagnetic component, giving rise to satellite peaks in the vicinity of the fundamental antiferromagnetic Bragg reflection, and a ferromagnetic component giving rise to peaks at small momentum-transfers around the origin at $(0,\pm Q,0)$. The wavelength of the modulated magnetic structure varies continuously with temperature. It is argued that the incommensurate short- and long-range phases are due to spin-dimensionality crossover from a continuous to the discrete Ising state. These observations explain the anomalous first-order transition seen in the magnetoelectric effect of this system

Formal Visual Modeling of Real-Time Systems in e-Motions: Two Case Studies

e-Motions is an Eclipse-based visual timed model transformation framework with a Real-Time Maude semantics that supports the usual Maude formal analysis methods, including simulation, reachability analysis, and LTL model checking. e-Motions is characterized by a novel and powerful set of constructs for expressing timed behaviors. In this paper we illustrate the use of these constructs --- and thereby implicitly investigate their suitability to define real-time systems in an intuitive way --- to define and formally analyze two prototypical and very different real-time systems: (i) a simple round trip time protocol for computing the time it takes a message to travel from one node to another, and back; and (ii) the EDF scheduling algorithm.Comment: In Proceedings AMMSE 2011, arXiv:1106.596

Coasting cosmologies with time dependent cosmological constant

The effect of a time dependent cosmological constant is considered in a family of scalar tensor theories. Friedmann-Robertson-Walker cosmological models for vacumm and perfect fluid matter are found. They have a linear expansion factor, the so called coasting cosmology, the gravitational "constant" decreace inversely with time; this model satisfy the Dirac hipotesis. The cosmological "constant" decreace inversely with the square of time, therefore we can have a very small value for it at present time.Comment: 7 pages, latex file (ijmpal macro), accepted for publication in Int. Mod. Phys.

Impact of noise on a dynamical system: prediction and uncertainties from a swarm-optimized neural network

In this study, an artificial neural network (ANN) based on particle swarm optimization (PSO) was developed for the time series prediction. The hybrid ANN+PSO algorithm was applied on Mackey--Glass chaotic time series in the short-term $x(t+6)$. The performance prediction was evaluated and compared with another studies available in the literature. Also, we presented properties of the dynamical system via the study of chaotic behaviour obtained from the predicted time series. Next, the hybrid ANN+PSO algorithm was complemented with a Gaussian stochastic procedure (called {\it stochastic} hybrid ANN+PSO) in order to obtain a new estimator of the predictions, which also allowed us to compute uncertainties of predictions for noisy Mackey--Glass chaotic time series. Thus, we studied the impact of noise for several cases with a white noise level ($\sigma_{N}$) from 0.01 to 0.1.Comment: 11 pages, 8 figure

New Community Sponsorships for Humanitarian Immigrants: Guidance on Washington’s Practice of Law and Immigration Services Fraud Prevention Rules

Every state, including Washington, has enacted laws to protect the public from the harm caused when an unqualified person provides legal services. Each state defines the practice of law and generally limits that practice to members of the state bar association. In Washington, a complex collage of case law, statutes, and a Supreme Court rule attempt to define the practice of law, identify when the practice of law by a nonlawyer is unauthorized, and determine when public policy considerations allow such nonlawyer practice. Protecting immigrants from unauthorized practice of immigration law is a particular concern. People who claim to be qualified to help immigrants routinely victimize newcomers; others may assist in good faith. Either way, unauthorized legal representation can cause an immigrant to miss viable opportunities for protection, to be unnecessarily detained or deported, to incur penalties for filing false claims, and often to be tricked into spending thousands of dollars for such “assistance.” The Washington legislature has attempted to prevent such harms through its Immigration Services Fraud Prevention Act. The line between authorized and unauthorized practice of law, especially in the immigration context, can be thick and blurry. New federal programs that allow community financial sponsorship of immigrants fleeing war and state collapse are unintentionally contributing to this grey area. The Biden administration has recently authorized Ukrainians and others to come to the United States temporarily, but only when supported by a U.S.-based financial sponsor. A U.S.-based individual initiates the process by applying to become a financial sponsor. Like all immigration documents, this sponsorship application form can be unclear, particularly for noncitizens. Submission of the form affects an applicant’s legal rights and its completion involves the exercise of legal discretion. Individuals seeking to become financial sponsors are turning to friends and other non-lawyers for help in completing these applications. This article sheds light on the concern that a layperson’s help in completing a financial sponsor application form may represent the unauthorized practice of law in Washington, including the unauthorized provision of immigration-related services. An understanding of this issue is critical, as the Biden administration has expanded community financial sponsorship programs exponentially within the first nine months of their existence. We conclude that a layperson who assists another in completing a financial sponsorship application form is engaged in the practice of law in Washington. A layperson’s assistance that goes beyond entering objective data or language translation likely triggers a violation of Washington’s civil and criminal unauthorized practice rules, as well as its Immigration Services Fraud Prevention Act