Movements and Behavior of Pheasants During the Breeding Cycle as Determined by Radio-Tracking

Behavior and movement studies were carried out on the Rifle-Calahan Study area, Sanborn County, South Dakota, in 1965 and 1966. Objectives of the study were to evaluate radio telemetry techniques, determine the territorial area and home range of the hen and cock, study the behavior pattern of hen and cock in the harem makeup, determine the distance traveled by the hen when attracted to the harem, determine if the hen nests in the immediate area of the crowing territory, and study the behavior of the hen while nesting and caring for the brood. Twenty adult pheasants (16 hens and 4 cocks) were monitored with radio telemetry equipment designed by Sidney Markusen of Cloquet, Minnesota. The home range of the hen averaged 28.5 acres and did not appear to be strongly tied to the crowing territory of the cock. It encompassed all movements while feeding, mating, nesting, and caring for the young. The activity center of the hen covered 5-10 acres surrounding the nest. Activity centers of the two cocks marked in 1966 covered 4 and 8 acres, respectively, in the home range where crowing occurred. The oestrus cycle of the hen pheasant in South Dakota lasts about two weeks during early nesting attempts, and 9-10 days during re-nesting attempts. Egg laying occurred after mid-day with the hen spending an increasing amount of time on the nest as the incubation period approached. Rest periods during incubation occurred most commonly in the afternoon around 5:00 p.m. Hens cared for their broods in the near vicinity of the nest until the chicks were about three weeks old. Re-nesting interval for instrumented hens was about 10 days. Second clutches were smaller than first clutches. Instrumented cocks tended to select knolls relatively free of tall vegetation as their crowing sites and ceased crowing about July 1

Simultaneous Coherent Structure Coloring facilitates interpretable clustering of scientific data by amplifying dissimilarity

The clustering of data into physically meaningful subsets often requires assumptions regarding the number, size, or shape of the subgroups. Here, we present a new method, simultaneous coherent structure coloring (sCSC), which accomplishes the task of unsupervised clustering without a priori guidance regarding the underlying structure of the data. sCSC performs a sequence of binary splittings on the dataset such that the most dissimilar data points are required to be in separate clusters. To achieve this, we obtain a set of orthogonal coordinates along which dissimilarity in the dataset is maximized from a generalized eigenvalue problem based on the pairwise dissimilarity between the data points to be clustered. This sequence of bifurcations produces a binary tree representation of the system, from which the number of clusters in the data and their interrelationships naturally emerge. To illustrate the effectiveness of the method in the absence of a priori assumptions, we apply it to three exemplary problems in fluid dynamics. Then, we illustrate its capacity for interpretability using a high-dimensional protein folding simulation dataset. While we restrict our examples to dynamical physical systems in this work, we anticipate straightforward translation to other fields where existing analysis tools require ad hoc assumptions on the data structure, lack the interpretability of the present method, or in which the underlying processes are less accessible, such as genomics and neuroscience

Model parameter estimation using coherent structure colouring

Lagrangian data assimilation is a complex problem in oceanic and atmospheric modelling. Tracking drifters in large-scale geophysical flows can involve uncertainty in drifter location, complex inertial effects and other factors which make comparing them to simulated Lagrangian trajectories from numerical models extremely challenging. Temporal and spatial discretisation, factors necessary in modelling large scale flows, also contribute to separation between real and simulated drifter trajectories. The chaotic advection inherent in these turbulent flows tends to separate even closely spaced tracer particles, making error metrics based solely on drifter displacements unsuitable for estimating model parameters. We propose to instead use error in the coherent structure colouring (CSC) field to assess model skill. The CSC field provides a spatial representation of the underlying coherent patterns in the flow, and we show that it is a more robust metric for assessing model accuracy. Through the use of two test cases, one considering spatial uncertainty in particle initialisation, and one examining the influence of stochastic error along a trajectory and temporal discretisation, we show that error in the coherent structure colouring field can be used to accurately determine single or multiple simultaneously unknown model parameters, whereas a conventional error metric based on error in drifter displacement fails. Because the CSC field enhances the difference in error between correct and incorrect model parameters, error minima in model parameter sweeps become more distinct. The effectiveness and robustness of this method for single and multi-parameter estimation in analytical flows suggest that Lagrangian data assimilation for real oceanic and atmospheric models would benefit from a similar approach

Coherent structure colouring: identification of coherent structures from sparse data using graph theory

We present a frame-invariant method for detecting coherent structures from Lagrangian flow trajectories that can be sparse in number, as is the case in many fluid mechanics applications of practical interest. The method, based on principles used in graph colouring and spectral graph drawing algorithms, examines a measure of the kinematic dissimilarity of all pairs of fluid trajectories, measured either experimentally, e.g. using particle tracking velocimetry, or numerically, by advecting fluid particles in the Eulerian velocity field. Coherence is assigned to groups of particles whose kinematics remain similar throughout the time interval for which trajectory data are available, regardless of their physical proximity to one another. Through the use of several analytical and experimental validation cases, this algorithm is shown to robustly detect coherent structures using significantly less flow data than are required by existing spectral graph theory methods

Identification of individual coherent sets associated with flow trajectories using coherent structure coloring

We present a method for identifying the coherent structures associated with individual Lagrangian flow trajectories even where only sparse particle trajectory data are available. The method, based on techniques in spectral graph theory, uses the Coherent Structure Coloring vector and associated eigenvectors to analyze the distance in higher-dimensional eigenspace between a selected reference trajectory and other tracer trajectories in the flow. By analyzing this distance metric in a hierarchical clustering, the coherent structure of which the reference particle is a member can be identified. This algorithm is proven successful in identifying coherent structures of varying complexities in canonical unsteady flows. Additionally, the method is able to assess the relative coherence of the associated structure in comparison to the surrounding flow. Although the method is demonstrated here in the context of fluid flow kinematics, the generality of the approach allows for its potential application to other unsupervised clustering problems in dynamical systems such as neuronal activity, gene expression, or social networks. In recent years, there has been a proliferation of techniques that aim to characterize fluid flow kinematics on the basis of Lagrangian trajectories of collections of tracer particles. Most of these techniques depend on the presence of tracer particles that are initially closely spaced, in order to compute local gradients of their trajectories. In many applications, the requirement of close tracer spacing cannot be satisfied, especially when the tracers are naturally occurring and their distribution is dictated by the underlying flow. Moreover, current methods often focus on determination of the boundaries of coherent sets, whereas in practice it is often valuable to identify the complete set of trajectories that are coherent with an individual trajectory of interest. We extend the concept of Coherent Structure Coloring, an approach based on spectral graph theory, to achieve identification of the coherent set associated with individual Lagrangian trajectories. The method does not require a priori determination of the number of coherent structures in the flow, nor does it require heuristics regarding the eigenvalue spectrum corresponding to the generalized eigenvalue problem. Importantly, although the method is demonstrated here in the context of fluid flow kinematics, the generality of the approach allows for its potential application to other unsupervised clustering problems in dynamical systems such as neuronal activity, gene expression, or social networks

Age-related alterations in efferent medial olivocochlear-outer hair cell and primary auditory ribbon synapses in CBA/J mice

Copyright \ua9 2024 D\uf6rje, Shvachiy, K\ufcck, Outeiro, Strenzke, Beutner and Setz.Introduction: Hearing decline stands as the most prevalent single sensory deficit associated with the aging process. Giving compelling evidence suggesting a protective effect associated with the efferent auditory system, the goal of our study was to characterize the age-related changes in the number of efferent medial olivocochlear (MOC) synapses regulating outer hair cell (OHC) activity compared with the number of afferent inner hair cell ribbon synapses in CBA/J mice over their lifespan. Methods: Organs of Corti of 3-month-old CBA/J mice were compared with mice aged between 10 and 20 months, grouped at 2-month intervals. For each animal, one ear was used to characterize the synapses between the efferent MOC fibers and the outer hair cells (OHCs), while the contralateral ear was used to analyze the ribbon synapses between inner hair cells (IHCs) and type I afferent nerve fibers of spiral ganglion neurons (SGNs). Each cochlea was separated in apical, middle, and basal turns, respectively. Results: The first significant age-related decline in afferent IHC-SGN ribbon synapses was observed in the basal cochlear turn at 14 months, the middle turn at 16 months, and the apical turn at 18 months of age. In contrast, efferent MOC-OHC synapses in CBA/J mice exhibited a less pronounced loss due to aging which only became significant in the basal and middle turns of the cochlea by 20 months of age. Discussion: This study illustrates an age-related reduction on efferent MOC innervation of OHCs in CBA/J mice starting at 20 months of age. Our findings indicate that the morphological decline of efferent MOC-OHC synapses due to aging occurs notably later than the decline observed in afferent IHC-SGN ribbon synapses

Contact force sensing in ablation of ventricular arrhythmias using a 56-hole open-irrigation catheter: a propensity-matched analysis.

PURPOSE: The effect of adding contact force (CF) sensing to 56-hole tip irrigation in ventricular arrhythmia (VA) ablation has not been previously studied. We aimed to compare outcomes with and without CF sensing in VA ablation using a 56-hole radiofrequency (RF) catheter. METHODS: A total of 164 patients who underwent first-time VA ablation using Thermocool SmartTouch Surround Flow (TC-STSF) catheter (Biosense-Webster, Diamond Bar, CA, USA) were propensity-matched in a 1:1 fashion to 164 patients who had first-time ablation using Thermocool Surround Flow (TC-SF) catheter. Patients were matched for age, gender, cardiac aetiology, ejection fraction and approach. Acute success, complications and long-term follow-up were compared. RESULTS: There was no difference between procedures utilising either TC-SF or TC-STSF in acute success (TC-SF: 134/164 (82%), TC-STSF: 141/164 (86%), p = 0.3), complications (TC-SF: 11/164 (6.7%), TC-STSF: 11/164 (6.7%), p = 1.0) or VA-free survival (TC-SF: mean arrhythmia-free survival time = 5.9 years, 95% CI = 5.4-6.4, TC-STSF: mean = 3.2 years, 95% CI = 3-3.5, log-rank p = 0.74). Fluoroscopy time was longer in normal hearts with TC-SF (19 min, IQR: 14-30) than TC-STSF (14 min, IQR: 8-25; p = 0.04). CONCLUSION: Both TC-SF and TC-STSF catheters are safe and effective in treating VAs. The use of CF sensing catheters did not improve safety or acute and long-term outcomes, but reduced fluoroscopy time in normal heart VA