Mapping Coastal Wetland Change Based on Lake Level Fluctuation on Lake Ontario

Using an integrated digital elevation and bathymetry model of Lake Ontario and historic lake level data from 1860 to present, coastal areas of periodic inundation were identified to generate, by association, an estimate of coastal wetland change due to lake level control. Pre and post Robert Morris Dam models were constructed to help determine the reduction of lake surface area when the dam started to control the extreme highs and lows. The model creates annual high and low lake surface coverages. The goal of this study is to create a baseline analysis and methodology for future studies on wetland change on Lake Ontario. Results of this study indicate an average change in lake surface area of 123 square kilometers between pre and post dam periods, based on 148 annual calculations of the high and low water levels for each year. Lake levels are generally stabilized after the dam installation, with considerably less fluctuation at the lowest lake levels, compared to pre dam fluctuations. Spatial results were limited by the currently available 3-second (90m) per pixel resolution of the combined bathymetry and elevation data, which renders general results that mask shoreline details and seem to over estimate inundation. As higher resolution data become available in the next few years, such as LiDAR and SONAR, the methodology of the model should be adaptable, resulting in more accurate models for predicting areas of inundation, exposure, and potential wetland change due to alterations of historic lake level variability

Understanding School Counselors' Perceptions of Esports and Igaming as a Career Choice

Over the past 20 years, there has been a steady increase in the popularity of online gaming in the United States culture. There are many factors that have contributed to this spike in popularity, but the most significant are advancements in technology, televised competitions, social media, lucrative cash prizes, product endorsements, and scholarships (Morgan & Cole, 2023). From electronic sports (esports) to internet gaming (igaming), many of today's children, adolescents, and young adults perceive the virtual world of game play as both psychologically and financially rewarding. This has resulted in many young people pursuing professional gaming as a viable career choice. Undoubtedly, as more young people pursue esports and igaming as potential careers, high school counselors will find themselves interacting more with these students and providing them guidance into the world of professional esports and igaming. These studies examined the high school counselors’ perceptions of esports and igaming as potential career choices for their students. The first study examined how high school counselors experience the phenomenon of esports as a career choice. The second study examined how high school counselors experience igaming as a career choice. Interpretative phenomenological analysis (IPA) was chosen as the qualitative design for both studies. IPA is a hermeneutic circle of research where the researcher is involved in making sense of the experience while the participant reflects on the experience (Smith & Osborn, 2003). Participants were recruited from message board posts on high school counseling social media pages (e.g. Instagram, Facebook, and Twitter), personal emails, and through the following professional counseling and gaming organizations’ websites: American School Counselor Association (ASCA), the National Career Development Association (NCDA), and National Association of Collegiate Esports (NACE). Six participants met the criteria of the study and were interviewed utilizing online video conferencing software (i.e. Zoom). Semi-structured interviews were conducted lasting between 45 and 80 minutes. Upon conclusion, the interviews were transcribed verbatim and the transcripts analyzed identifying major themes, along with similarities and differences in the experiences of the six participants. Following step-by-step analysis presented by Smith, Flowers, and Larkin (2009), a master table was created of the discovered themes. Additionally, strategies were used to increase trustworthiness, including peer debriefing, research positionality reflection, and member checking (Morrow, 2005). The first manuscript examined how the participants (N=6) experienced esports as a career choice. The following five themes emerged from the data: (a) sense of limited job-specific knowledge, (b) marginalization of students due to stigma, (c) being guided by one’s professional identity and values of career counseling, (d) sense of determination to validate esports as a career choice, and (e) addressing feelings associated with navigating the professional relationship with students. The second manuscript examined how the high school counselors (N=6) experienced igaming as a career choice. The following five themes emerged from the data: (a) underlying absence of knowledge about igaming as a career, (b) anticipatory navigation of student marginalization based on school counselors’ biases, (c) countering personal bias with professional values and identity as they ponder working with students, (d) struggling to see igaming as a viable career and emerging realization of igaming career awareness, and (e) anticipating a professional relationship with students pursuing igaming as a career choice. The findings of both studies identified the need for more education, information and understanding of opportunities associated with esports and igaming as a career choice. The findings have multiple implications for research that are directed at the overall growth of knowledge in the experience of high school counselors working with students pursuing careers in these two phenomen

Lake-size dependency of wind shear and convection as controls on gas exchange

High-frequency physical observations from 40 temperate lakes were used to examine the relative contributions of wind shear (u*) and convection (w*) to turbulence in the surface mixed layer. Seasonal patterns of u* and w* were dissimilar; u* was often highest in the spring, while w * increased throughout the summer to a maximum in early fall. Convection was a larger mixed-layer turbulence source than wind shear (u */w*-1 for lakes* and w* differ in temporal pattern and magnitude across lakes, both convection and wind shear should be considered in future formulations of lake-air gas exchange, especially for small lakes. © 2012 by the American Geophysical Union.Jordan S. Read, David P. Hamilton, Ankur R. Desai, Kevin C. Rose, Sally MacIntyre, John D. Lenters, Robyn L. Smyth, Paul C. Hanson, Jonathan J. Cole, Peter A. Staehr, James A. Rusak, Donald C. Pierson, Justin D. Brookes, Alo Laas, and Chin H. W

Scaling and universality in coupled driven diffusive models

Inspired by the physics of magnetohydrodynamics (MHD) a simplified coupled Burgers-like model in one dimension (1d), a generalization of the Burgers model to coupled degrees of freedom, is proposed to describe 1dMHD. In addition to MHD, this model serves as a 1d reduced model for driven binary fluid mixtures. Here we have performed a comprehensive study of the universal properties of the generalized d-dimensional version of the reduced model. We employ both analytical and numerical approaches. In particular, we determine the scaling exponents and the amplitude-ratios of the relevant two-point time-dependent correlation functions in the model. We demonstrate that these quantities vary continuously with the amplitude of the noise cross-correlation. Further our numerical studies corroborate the continuous dependence of long wavelength and long time-scale physics of the model on the amplitude of the noise cross-correlations, as found in our analytical studies. We construct and simulate lattice-gas models of coupled degrees of freedom in 1d, belonging to the universality class of our coupled Burgers-like model, which display similar behavior. We use a variety of numerical (Monte-Carlo and Pseudospectral methods) and analytical (Dynamic Renormalization Group, Self-Consistent Mode-Coupling Theory and Functional Renormalization Group) approaches for our work. The results from our different approaches complement one another. Possible realizations of our results in various nonequilibrium models are discussed.Comment: To appear in JSTAT (2009); 52 pages in JSTAT format. Some figure files have been replace

A Global lake ecological observatory network (GLEON) for synthesising high-frequency sensor data for validation of deterministic ecological models

A Global Lake Ecological Observatory Network (GLEON; www.gleon.org) has formed to provide a coordinated response to the need for scientific understanding of lake processes, utilising technological advances available from autonomous sensors. The organisation embraces a grassroots approach to engage researchers from varying disciplines, sites spanning geographic and ecological gradients, and novel sensor and cyberinfrastructure to synthesise high-frequency lake data at scales ranging from local to global. The high-frequency data provide a platform to rigorously validate processbased ecological models because model simulation time steps are better aligned with sensor measurements than with lower-frequency, manual samples. Two case studies from Trout Bog, Wisconsin, USA, and Lake Rotoehu, North Island, New Zealand, are presented to demonstrate that in the past, ecological model outputs (e.g., temperature, chlorophyll) have been relatively poorly validated based on a limited number of directly comparable measurements, both in time and space. The case studies demonstrate some of the difficulties of mapping sensor measurements directly to model state variable outputs as well as the opportunities to use deviations between sensor measurements and model simulations to better inform process understanding. Well-validated ecological models provide a mechanism to extrapolate high-frequency sensor data in space and time, thereby potentially creating a fully 3-dimensional simulation of key variables of interest

Quasi-linear regime and rare-event tails of decaying Burgers turbulence

We study the decaying Burgers dynamics in $d$ dimensions for random Gaussian initial conditions. We focus on power-law initial energy spectra, such that the system shows a self-similar evolution. This is the case of interest for the "adhesion model" in cosmology and a standard framework for "decaying Burgers turbulence". We briefly describe how the system can be studied through perturbative expansions at early time or large scale (quasi-linear regime). Next, we develop a saddle-point method, based on spherical instantons, that allows to obtain the asymptotic probability distributions \cP(\eta_r) and \cP(\ctheta_r), of the density and velocity increment over spherical cells, reached in the quasi-linear regime. Finally, we show how this approach can be extended to take into account the formation of shocks and we derive the rare-event tails of these probability distributions, at any finite time and scale. This also gives the high-mass tail of the mass function of point-like singularities (shocks in the one dimensional case).Comment: 32 page

Canonical phase space approach to the noisy Burgers equation: Probability distributions

We present a canonical phase space approach to stochastic systems described by Langevin equations driven by white noise. Mapping the associated Fokker-Planck equation to a Hamilton-Jacobi equation in the nonperturbative weak noise limit we invoke a {\em principle of least action} for the determination of the probability distributions. We apply the scheme to the noisy Burgers and KPZ equations and discuss the time-dependent and stationary probability distributions. In one dimension we derive the long-time skew distribution approaching the symmetric stationary Gaussian distribution. In the short-time region we discuss heuristically the nonlinear soliton contributions and derive an expression for the distribution in accordance with the directed polymer-replica and asymmetric exclusion model results. We also comment on the distribution in higher dimensions.Comment: 18 pages Revtex file, including 8 eps-figures, submitted to Phys. Rev.

Soliton approach to the noisy Burgers equation: Steepest descent method

The noisy Burgers equation in one spatial dimension is analyzed by means of the Martin-Siggia-Rose technique in functional form. In a canonical formulation the morphology and scaling behavior are accessed by mean of a principle of least action in the asymptotic non-perturbative weak noise limit. The ensuing coupled saddle point field equations for the local slope and noise fields, replacing the noisy Burgers equation, are solved yielding nonlinear localized soliton solutions and extended linear diffusive mode solutions, describing the morphology of a growing interface. The canonical formalism and the principle of least action also associate momentum, energy, and action with a soliton-diffusive mode configuration and thus provides a selection criterion for the noise-induced fluctuations. In a ``quantum mechanical'' representation of the path integral the noise fluctuations, corresponding to different paths in the path integral, are interpreted as ``quantum fluctuations'' and the growth morphology represented by a Landau-type quasi-particle gas of ``quantum solitons'' with gapless dispersion and ``quantum diffusive modes'' with a gap in the spectrum. Finally, the scaling properties are dicussed from a heuristic point of view in terms of a``quantum spectral representation'' for the slope correlations. The dynamic eponent z=3/2 is given by the gapless soliton dispersion law, whereas the roughness exponent zeta =1/2 follows from a regularity property of the form factor in the spectral representation. A heuristic expression for the scaling function is given by spectral representation and has a form similar to the probability distribution for Levy flights with index $z$.Comment: 30 pages, Revtex file, 14 figures, to be submitted to Phys. Rev.

Event-related alpha suppression in response to facial motion

This article has been made available through the Brunel Open Access Publishing Fund.While biological motion refers to both face and body movements, little is known about the visual perception of facial motion. We therefore examined alpha wave suppression as a reduction in power is thought to reflect visual activity, in addition to attentional reorienting and memory processes. Nineteen neurologically healthy adults were tested on their ability to discriminate between successive facial motion captures. These animations exhibited both rigid and non-rigid facial motion, as well as speech expressions. The structural and surface appearance of these facial animations did not differ, thus participants decisions were based solely on differences in facial movements. Upright, orientation-inverted and luminance-inverted facial stimuli were compared. At occipital and parieto-occipital regions, upright facial motion evoked a transient increase in alpha which was then followed by a significant reduction. This finding is discussed in terms of neural efficiency, gating mechanisms and neural synchronization. Moreover, there was no difference in the amount of alpha suppression evoked by each facial stimulus at occipital regions, suggesting early visual processing remains unaffected by manipulation paradigms. However, upright facial motion evoked greater suppression at parieto-occipital sites, and did so in the shortest latency. Increased activity within this region may reflect higher attentional reorienting to natural facial motion but also involvement of areas associated with the visual control of body effectors. © 2014 Girges et al

Waymax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Research

Simulation is an essential tool to develop and benchmark autonomous vehicle planning software in a safe and cost-effective manner. However, realistic simulation requires accurate modeling of nuanced and complex multi-agent interactive behaviors. To address these challenges, we introduce Waymax, a new data-driven simulator for autonomous driving in multi-agent scenes, designed for large-scale simulation and testing. Waymax uses publicly-released, real-world driving data (e.g., the Waymo Open Motion Dataset) to initialize or play back a diverse set of multi-agent simulated scenarios. It runs entirely on hardware accelerators such as TPUs/GPUs and supports in-graph simulation for training, making it suitable for modern large-scale, distributed machine learning workflows. To support online training and evaluation, Waymax includes several learned and hard-coded behavior models that allow for realistic interaction within simulation. To supplement Waymax, we benchmark a suite of popular imitation and reinforcement learning algorithms with ablation studies on different design decisions, where we highlight the effectiveness of routes as guidance for planning agents and the ability of RL to overfit against simulated agents