Landsliding and its multiscale influence on mountainscapes

Landsliding is a complex process that modifies mountainscapes worldwide. Its severe and sometimes long-lasting negative effects contrast with the less-documented positive effects on ecosystems, raising numerous questions about the dual role of landsliding, the feedbacks between biotic and geomorphic processes, and, ultimately, the ecological and evolutionary responses of organisms. We present a conceptual model in which feedbacks between biotic and geomorphic processes, landslides, and ecosystem attributes are hypothesized to drive the dynamics of mountain ecosystems at multiple scales. This model is used to integrate and synthesize a rich, but fragmented, body of literature generated in different disciplines, and to highlight the need for profitable collaborations between biologists and geoscientists. Such efforts should help identify attributes that contribute to the resilience of mountain ecosystems, and also should help in conservation, restoration, and hazard assessment. Given the sensitivity of mountains to land-use and global climate change, these endeavors are both relevant and timel

Impacts of Colombia's current irrigation management transfer program

Privatization / Irrigation management / Irrigated farming / Policy / Costs / Economic aspects / Operations / Maintenance / Agricultural production

Inhibition causes ceaseless dynamics in networks of excitable nodes

The collective dynamics of a network of excitable nodes changes dramatically when inhibitory nodes are introduced. We consider inhibitory nodes which may be activated just like excitatory nodes but, upon activating, decrease the probability of activation of network neighbors. We show that, although the direct effect of inhibitory nodes is to decrease activity, the collective dynamics becomes self-sustaining. We explain this counterintuitive result by defining and analyzing a "branching function" which may be thought of as an activity-dependent branching ratio. The shape of the branching function implies that for a range of global coupling parameters dynamics are self-sustaining. Within the self-sustaining region of parameter space lies a critical line along which dynamics take the form of avalanches with universal scaling of size and duration, embedded in ceaseless timeseries of activity. Our analyses, confirmed by numerical simulation, suggest that inhibition may play a counterintuitive role in excitable networks.Comment: 11 pages, 6 figure

Estimating the NAIRU for Chile

The purpose of this paper is to obtain a set of estimates of the non-accelerating-inflation rate of unemployment (NAIRU) for Chile. Measuring the NAIRU permits building the unemployment gap, which is a complementary measure of activity and output gap, which is used on a regular basis by central banks as another indicator helping in inflation forecasts and policy decision making. Initially, an estimate is obtained based on a purely statistical method (unobserved components) Later, estimates are conducted for both constant and variable NAIRU based on Phillips curve equations. The different estimates yield similar results, indicating that the most likely point estimate for the current NAIRU stands between 7.4% and 8.3%. However, these figures are contained in a confidence interval ranging from 6.5% to 9.7%, reflecting great uncertainty regarding the exact value of NAIRU.

Robust entropy requires strong and balanced excitatory and inhibitory synapses

It is widely appreciated that well-balanced excitation and inhibition are necessary for proper function in neural networks. However, in principle, such balance could be achieved by many possible configurations of excitatory and inhibitory strengths, and relative numbers of excitatory and inhibitory neurons. For instance, a given level of excitation could be balanced by either numerous inhibitory neurons with weak synapses, or few inhibitory neurons with strong synapses. Among the continuum of different but balanced configurations, why should any particular configuration be favored? Here we address this question in the context of the entropy of network dynamics by studying an analytically tractable network of binary neurons. We find that entropy is highest at the boundary between excitation-dominant and inhibition-dominant regimes. Entropy also varies along this boundary with a trade-off between high and robust entropy: weak synapse strengths yield high network entropy which is fragile to parameter variations, while strong synapse strengths yield a lower, but more robust, network entropy. In the case where inhibitory and excitatory synapses are constrained to have similar strength, we find that a small, but non-zero fraction of inhibitory neurons, like that seen in mammalian cortex, results in robust and relatively high entropy

Effects of network topology, transmission delays, and refractoriness on the response of coupled excitable systems to a stochastic stimulus

We study the effects of network topology on the response of networks of coupled discrete excitable systems to an external stochastic stimulus. We extend recent results that characterize the response in terms of spectral properties of the adjacency matrix by allowing distributions in the transmission delays and in the number of refractory states, and by developing a nonperturbative approximation to the steady state network response. We confirm our theoretical results with numerical simulations. We find that the steady state response amplitude is inversely proportional to the duration of refractoriness, which reduces the maximum attainable dynamic range. We also find that transmission delays alter the time required to reach steady state. Importantly, neither delays nor refractoriness impact the general prediction that criticality and maximum dynamic range occur when the largest eigenvalue of the adjacency matrix is unity

High School Influences on the Selection of Athletic Training as a Career

Context: Research suggests internships, mentorship, and specialized school programs positively influence career selection; however, little data exists specific to athletic training. Objective: We identified high school (HS) experiences influencing career choice in college athletic training students (ATS). Design: Our survey included 35 Likert-type close-ended questions, which were reviewed by a panel of faculty and peers to establish content and construct validity. Setting: Participants completed an online questionnaire at their convenience. Participants: 217 college ATS (153 female, 64 male) from a random selection of accredited programs on the east coast. We excluded minors, freshmen, and undecided majors from the study. Informed consent was implied by proceeding to the questionnaire. Data Collection and Analysis: We used descriptive statistics to analyze the data collected via a secure website. Results: Mentors were most influential in the decision of career path (62.4%;n=131/210) with 85.2% (n=138/162) reporting mentors were readily available to answer questions regarding career options and 53.1% (n=86/162) counseled them regarding HS electives. Of participants involved in an internship (41.0%;n=86/210), most developed such opportunities independently (66.3%;n=57/86). Respondents who attended traditional HS suggested providing diverse electives (71.9%;n=133/185), additional internship (53.5%;n=99/185), and mentorship (33.0%;n=61/185) opportunities to effectively educate students regarding career options. Conclusions: College ATS that gained internship experience during HS report the opportunity positively influenced their career selection. Mentors support HS students by offering insight and expertise in guiding students’ career choices. Participants suggested HS afford diverse electives with internship and mentorship opportunities to positively influence interested students towards pursuing a career in athletic training

Dynamics and Pattern Formation in Large Systems of Spatially-Coupled Oscillators with Finite Response Times

We consider systems of many spatially distributed phase oscillators that interact with their neighbors. Each oscillator is allowed to have a different natural frequency, as well as a different response time to the signals it receives from other oscillators in its neighborhood. Using the ansatz of Ott and Antonsen (Ref. \cite{OA1}) and adopting a strategy similar to that employed in the recent work of Laing (Ref. \cite{Laing2}), we reduce the microscopic dynamics of these systems to a macroscopic partial-differential-equation description. Using this macroscopic formulation, we numerically find that finite oscillator response time leads to interesting spatio-temporal dynamical behaviors including propagating fronts, spots, target patterns, chimerae, spiral waves, etc., and we study interactions and evolutionary behaviors of these spatio-temporal patterns