Can small zooplankton mix lakes?

The idea that living organisms may contribute to turbulence and mixing in lakes and oceans (biomixing) dates to the 1960s, but has attracted increasing attention in recent years. Recent modeling and experimental studies suggest that marine organisms can enhance turbulence as much as winds and tides in oceans, with an impact on mixing. However, other studies show opposite and contradictory results, precluding definitive conclusions regarding the potential importance of biomixing. For lakes, only models and lab studies are available. These generally indicate that small zooplankton or passive bodies generate turbulence but different levels of mixing depending on their abundance. Nevertheless, biogenic mixing is a complex problem, which needs to be explored in the field, to overcome limitations arising from numerical models and lab studies, and without altering the behavior of the animals under study

The Conditional Lucas & Kanade Algorithm

The Lucas & Kanade (LK) algorithm is the method of choice for efficient dense image and object alignment. The approach is efficient as it attempts to model the connection between appearance and geometric displacement through a linear relationship that assumes independence across pixel coordinates. A drawback of the approach, however, is its generative nature. Specifically, its performance is tightly coupled with how well the linear model can synthesize appearance from geometric displacement, even though the alignment task itself is associated with the inverse problem. In this paper, we present a new approach, referred to as the Conditional LK algorithm, which: (i) directly learns linear models that predict geometric displacement as a function of appearance, and (ii) employs a novel strategy for ensuring that the generative pixel independence assumption can still be taken advantage of. We demonstrate that our approach exhibits superior performance to classical generative forms of the LK algorithm. Furthermore, we demonstrate its comparable performance to state-of-the-art methods such as the Supervised Descent Method with substantially less training examples, as well as the unique ability to "swap" geometric warp functions without having to retrain from scratch. Finally, from a theoretical perspective, our approach hints at possible redundancies that exist in current state-of-the-art methods for alignment that could be leveraged in vision systems of the future.Comment: 17 pages, 11 figure

Stretching and Heating Single DNA Molecules with Optically Trapped Gold-Silica Janus Particles

Self-propelled micro- and nanoscale motors are capable of autonomous motion typically by inducing local concentration gradients or thermal gradients in their surrounding medium. This is a result of the heterogeneous surface of the self-propelled structures that consist of materials with different chemical or physical properties. Here we present a self-thermophoretically driven Au–silica Janus particle that can simultaneously stretch and partially melt a single double-stranded DNA molecule. We show that the effective force acting on the DNA molecule is in the ∼pN range, well suited to probe the entropic stretching regime of DNA, and we demonstrate that the local temperature enhancement around the gold side of the particle produces partial DNA dehybridization

Synchronization in Complex Systems Following the Decision Based Queuing Process: The Rhythmic Applause as a Test Case

Living communities can be considered as complex systems, thus a fertile ground for studies related to their statistics and dynamics. In this study we revisit the case of the rhythmic applause by utilizing the model proposed by V\'azquez et al. [A. V\'azquez et al., Phys. Rev. E 73, 036127 (2006)] augmented with two contradicted {\it driving forces}, namely: {\it Individuality} and {\it Companionship}. To that extend, after performing computer simulations with a large number of oscillators we propose an explanation on the following open questions (a) why synchronization occurs suddenly, and b) why synchronization is observed when the clapping period ($T_c$) is $1.5 \cdot T_s < T_c < 2.0 \cdot T_s$ ($T_s$ is the mean self period of the spectators) and is lost after a time. Moreover, based on the model, a weak preferential attachment principle is proposed which can produce complex networks obeying power law in the distribution of number edges per node with exponent greater than 3.Comment: 16 pages, 5 figure

A New Global Ocean Climatology

A new global ocean temperature and salinity climatology is proposed for two time periods: a long time mean using multiple sensor data for the 1900–2017 period and a shorter time mean using only profiling float data for the 2003–2017 period. We use the historical database of World Ocean Database 2018. The estimation approach is novel as an additional quality control procedure is implemented, along with a new mapping algorithm based on Data Interpolating Variational Analysis. The new procedure, in addition to the traditional quality control approach, resulted in low sensitivity in terms of the first guess field choice. The roughness index and the root mean square of residuals are new indices applied to the selection of the free mapping parameters along with sensitivity experiments. Overall, the new estimates were consistent with previous climatologies, but several differences were found. The cause of these discrepancies is difficult to identify due to several differences in the procedures. To minimise these uncertainties, a multi-model ensemble mean is proposed as the least uncertain estimate of the global ocean temperature and salinity climatology

A point process framework for modeling electrical stimulation of the auditory nerve

Model-based studies of auditory nerve responses to electrical stimulation can provide insight into the functioning of cochlear implants. Ideally, these studies can identify limitations in sound processing strategies and lead to improved methods for providing sound information to cochlear implant users. To accomplish this, models must accurately describe auditory nerve spiking while avoiding excessive complexity that would preclude large-scale simulations of populations of auditory nerve fibers and obscure insight into the mechanisms that influence neural encoding of sound information. In this spirit, we develop a point process model of the auditory nerve that provides a compact and accurate description of neural responses to electric stimulation. Inspired by the framework of generalized linear models, the proposed model consists of a cascade of linear and nonlinear stages. We show how each of these stages can be associated with biophysical mechanisms and related to models of neuronal dynamics. Moreover, we derive a semi-analytical procedure that uniquely determines each parameter in the model on the basis of fundamental statistics from recordings of single fiber responses to electric stimulation, including threshold, relative spread, jitter, and chronaxie. The model also accounts for refractory and summation effects that influence the responses of auditory nerve fibers to high pulse rate stimulation. Throughout, we compare model predictions to published physiological data and explain differences in auditory nerve responses to high and low pulse rate stimulation. We close by performing an ideal observer analysis of simulated spike trains in response to sinusoidally amplitude modulated stimuli and find that carrier pulse rate does not affect modulation detection thresholds.Comment: 1 title page, 27 manuscript pages, 14 figures, 1 table, 1 appendi

Multi-color Molecular Visualization of Signaling Proteins Reveals How C-Terminal Src Kinase Nanoclusters Regulate T Cell Receptor Activation

Elucidating the mechanisms that controlled T cell activation requires visualization of the spatial organization of multiple proteins on the submicron scale. Here, we use stoichiometrically accurate, multiplexed, singlemolecule super-resolution microscopy (DNA-PAINT) to image the nanoscale spatial architecture of the primary inhibitor of the T cell signaling pathway, Csk, and two binding partners implicated in its membrane association, PAG and TRAF3. Combined with a newly developed co-clustering analysis framework, we find that Csk forms nanoscale clusters proximal to the plasma membrane that are lost post-stimulation and are re-recruited at later time points. Unexpectedly, these clusters do not co-localize with PAG at the membrane but instead provide a ready pool of monomers to downregulate signaling. By generating CRISPR-Cas9 knockout T cells, our data also identify that a major risk factor for autoimmune diseases, the protein tyrosine phosphatase non-receptor type 22 (PTPN22) locus, is essential for Csk nanocluster re-recruitment and for maintenance of the synaptic PAG population

Mediterranean Sea large-scale low-frequency ocean variability and water mass formation rates from 1987 to 2007: A retrospective analysis

We describe a synthesis of the Mediterranean Sea circulation structure and dynamics from a 23-year- long reanalysis of the ocean circulation carried out by Adani et al. (2011). This mesoscale permitting dynamical reconstruction of past ocean variability in the Mediterranean Sea allows the study of the time-mean circulation and its low frequency, decadal, components. It is found that the time-mean circu- lation is composed of boundary and open ocean intensified jets at the border of cyclonic and anticyclonic gyres. The large scale basin circulation is generally characterized in the northern regions by cyclonic gyres and in its southern parts by anticyclonic gyres and eddy-dominated flow fields, with the exception of the Tyrrhenian and the northern Ionian Sea. The time-mean Tyrrhenian Sea circulation is dominated by cyclonic gyres of different intensity and intermittency. The northern Ionian Sea circulation, however, reverses in sign in two ten-year periods, the first in 1987–1996 and the second in 1997–2006, which is here called the Northern Ionian reversal phenomenon. This reversal is provoked by the excursion of the Atlantic-Ionian Stream from the middle to the northern parts of the basin. The decadal variability of other parts of the basin is characterized by changes in strength of the basin scale structures. The water mass formation rates and variability are dominated by event-like periods where the intermediate and deep waters are formed for 2–3 years at higher rates. The largest deep water formation events of the past 23 years occurred separately in the western and eastern Mediterranean basin: the first coincided with the Eastern Mediterranean Transient (Roether et al., 1996) and the second with the western Mediterranean deep water formation event in 2005–2006 (Smith et al., 2008). A new schematic of the basin-scale circu- lation is formulated and commented.Published318-3324A. Oceanografia e climaJCR Journa

Optimal measurement of visual motion across spatial and temporal scales

Sensory systems use limited resources to mediate the perception of a great variety of objects and events. Here a normative framework is presented for exploring how the problem of efficient allocation of resources can be solved in visual perception. Starting with a basic property of every measurement, captured by Gabor's uncertainty relation about the location and frequency content of signals, prescriptions are developed for optimal allocation of sensors for reliable perception of visual motion. This study reveals that a large-scale characteristic of human vision (the spatiotemporal contrast sensitivity function) is similar to the optimal prescription, and it suggests that some previously puzzling phenomena of visual sensitivity, adaptation, and perceptual organization have simple principled explanations.Comment: 28 pages, 10 figures, 2 appendices; in press in Favorskaya MN and Jain LC (Eds), Computer Vision in Advanced Control Systems using Conventional and Intelligent Paradigms, Intelligent Systems Reference Library, Springer-Verlag, Berli