Telomeres cluster de novo before the initiation of synapsis: a three-dimensional spatial analysis of telomere positions before and during meiotic prophase.

We have analyzed the progressive changes in the spatial distribution of telomeres during meiosis using three-dimensional, high resolution fluorescence microscopy. Fixed meiotic cells of maize (Zea mays L.) were subjected to in situ hybridization under conditions that preserved chromosome structure, allowing identification of stage-dependent changes in telomere arrangements. We found that nuclei at the last somatic prophase before meiosis exhibit a nonrandom, polarized chromosome organization resulting in a loose grouping of telomeres. Quantitative measurements on the spatial arrangements of telomeres revealed that, as cells passed through premeiotic interphase and into leptotene, there was an increase in the frequency of large telomere-to-telomere distances and a decrease in the bias toward peripheral localization of telomeres. By leptotene, there was no obvious evidence of telomere grouping, and the large, singular nucleolus was internally located, nearly concentric with the nucleus. At the end of leptotene, telomeres clustered de novo at the nuclear periphery, coincident with a displacement of the nucleolus to one side. The telomere cluster persisted throughout zygotene and into early pachytene. The nucleolus was adjacent to the cluster at zygotene. At the pachytene stage, telomeres rearranged again by dispersing throughout the nuclear periphery. The stage-dependent changes in telomere arrangements are suggestive of specific, active telomere-associated motility processes with meiotic functions. Thus, the formation of the cluster itself is an early event in the nuclear reorganizations associated with meiosis and may reflect a control point in the initiation of synapsis or crossing over

Stationary distributions for diffusions with inert drift

Consider reflecting Brownian motion in a bounded domain in $${\mathbb R^d}$$ that acquires drift in proportion to the amount of local time spent on the boundary of the domain. We show that the stationary distribution for the joint law of the position of the reflecting Brownian motion and the value of the drift vector has a product form. Moreover, the first component is uniformly distributed on the domain, and the second component has a Gaussian distribution. We also consider more general reflecting diffusions with inert drift as well as processes where the drift is given in terms of the gradient of a potential

Levy distribution and long correlation times in supermarket sales

Sales data in a commodity market (supermarket sales to consumers) has been analysed by studying the fluctuation spectrum and noise correlations. Three related products (ketchup, mayonnaise and curry sauce) have been analysed. Most noise in sales is caused by promotions, but here we focus on the fluctuations in baseline sales. These characterise the dynamics of the market. Four hitherto unnoticed effects have been found that are difficult to explain from simple econometric models. These effects are: (1) the noise level in baseline sales is much higher than can be expected for uncorrelated sales events; (2) weekly baseline sales differences are distributed according to a broad non-Gaussian function with fat tails; (3) these fluctuations follow a Levy distribution of exponent alpha = 1.4, similar to financial exchange markets and in stock markets; and (4) this noise is correlated over a period of 10 to 11 weeks, or shows an apparent power law spectrum. The similarity to stock markets suggests that models developed to describe these markets may be applied to describe the collective behaviour of consumers.Comment: 19 pages, 7 figures, accepted for publication in Physica

The Stochastic Reach-Avoid Problem and Set Characterization for Diffusions

In this article we approach a class of stochastic reachability problems with state constraints from an optimal control perspective. Preceding approaches to solving these reachability problems are either confined to the deterministic setting or address almost-sure stochastic requirements. In contrast, we propose a methodology to tackle problems with less stringent requirements than almost sure. To this end, we first establish a connection between two distinct stochastic reach-avoid problems and three classes of stochastic optimal control problems involving discontinuous payoff functions. Subsequently, we focus on solutions of one of the classes of stochastic optimal control problems---the exit-time problem, which solves both the two reach-avoid problems mentioned above. We then derive a weak version of a dynamic programming principle (DPP) for the corresponding value function; in this direction our contribution compared to the existing literature is to develop techniques that admit discontinuous payoff functions. Moreover, based on our DPP, we provide an alternative characterization of the value function as a solution of a partial differential equation in the sense of discontinuous viscosity solutions, along with boundary conditions both in Dirichlet and viscosity senses. Theoretical justifications are also discussed to pave the way for deployment of off-the-shelf PDE solvers for numerical computations. Finally, we validate the performance of the proposed framework on the stochastic Zermelo navigation problem

Marine heatwaves and decreased light availability interact to erode the ecophysiological performance of habitat-forming kelp species

Coastal marine ecosystems are threatened by a range of anthropogenic stressors, operating at global, local, and temporal scales. We investigated the impact of marine heatwaves (MHWs) combined with decreased light availability over two seasons on the ecophysiological responses of three kelp species (Laminaria digitata, L. hyperborea, and L. ochroleuca). These species function as important habitat-forming foundation organisms in the northeast Atlantic and have distinct but overlapping latitudinal distributions and thermal niches. Under low-light conditions, summertime MHWs induced significant declines in biomass, blade surface area, and Fv/Fm values (a measure of photosynthetic efficiency) in the cool-water kelps L. digitata and L. hyperborea, albeit to varying degrees. Under high-light conditions, all species were largely resistant to simulated MHW activity. In springtime, MHWs had minimal impacts and in some cases promoted kelp performance, while reduced light availability resulted in lower growth rates. While some species were negatively affected by summer MHWs under low-light conditions (particularly L. digitata), they were generally resilient to MHWs under high-light conditions. As such, maintaining good environmental quality and water clarity may increase resilience of populations to summertime MHWs. Our study informs predictions of how habitat-forming foundation kelp species will be affected by interacting, concurrent stressors, typical of compound events that are intensifying under anthropogenic climate change

Winning or not winning: the influence on coach-athlete relationships and goal achievement

This study analyses the relation between sports success and athletes’ perception of coaches’ leadership, athletes’ satisfaction with coaches’ leadership, coach-athlete compatibility, and goal achievement. Sixty-six athletes who qualified for the final Division I play-offs of a professional volleyball championship were grouped into winning (n = 21) and non-winning teams (n = 45). Leadership styles, satisfaction with leadership, coach-athlete compatibility, and goal achievement were evaluated. Analysis of variance with repeated-measures revealed that the winning teams evaluated their coaches’ vision, inspiration, technical instruction, positive feedback, and active management more positively than non-winning teams and that their satisfaction with coaches’ strategies increased over time. A multivariate analysis of variance (MANOVA) indicated that the winning teams’ perceived achievement of personal and team goals was greater than that of the non-winning teams. Sports success was associated with athletes’ positive evaluation of coaches’ leadership, satisfaction with coaches’ strategy, and higher perceived goal attainment

ICAM: Interpretable Classification via Disentangled Representations and Feature Attribution Mapping

Feature attribution (FA), or the assignment of class-relevance to different locations in an image, is important for many classification problems but is particularly crucial within the neuroscience domain, where accurate mechanistic models of behaviours, or disease, require knowledge of all features discriminative of a trait. At the same time, predicting class relevance from brain images is challenging as phenotypes are typically heterogeneous, and changes occur against a background of significant natural variation. Here, we present a novel framework for creating class specific FA maps through image-to-image translation. We propose the use of a VAE-GAN to explicitly disentangle class relevance from background features for improved interpretability properties, which results in meaningful FA maps. We validate our method on 2D and 3D brain image datasets of dementia (ADNI dataset), ageing (UK Biobank), and (simulated) lesion detection. We show that FA maps generated by our method outperform baseline FA methods when validated against ground truth. More significantly, our approach is the first to use latent space sampling to support exploration of phenotype variation. Our code will be available online at https://github.com/CherBass/ICAM.Comment: Submitted to NeurIPS 2020: Neural Information Processing Systems. Keywords: interpretable, classification, feature attribution, domain translation, variational autoencoder, generative adversarial network, neuroimagin

Wideband THz time domain spectroscopy based on optical rectification and electro-optic sampling

We present an analytical model describing the full electromagnetic propagation in a THz time-domain spectroscopy (THz-TDS) system, from the THz pulses via Optical Rectification to the detection via Electro Optic-Sampling. While several investigations deal singularly with the many elements that constitute a THz-TDS, in our work we pay particular attention to the modelling of the time-frequency behaviour of all the stages which compose the experimental set-up. Therefore, our model considers the following main aspects: (i) pump beam focusing into the generation crystal; (ii) phase-matching inside both the generation and detection crystals; (iii) chromatic dispersion and absorption inside the crystals; (iv) Fabry-Perot effect; (v) diffraction outside, i.e. along the propagation, (vi) focalization and overlapping between THz and probe beams, (vii) electro-optic sampling. In order to validate our model, we report on the comparison between the simulations and the experimental data obtained from the same set-up, showing their good agreement

ICAM-reg: Interpretable Classification and Regression with Feature Attribution for Mapping Neurological Phenotypes in Individual Scans

Feature attribution (FA), or the assignment of class-relevance to different locations in an image, is important for many classification and regression problems but is particularly crucial within the neuroscience domain, where accurate mechanistic models of behaviours, or disease, require knowledge of all features discriminative of a trait. At the same time, predicting class relevance from brain images is challenging as phenotypes are typically heterogeneous, and changes occur against a background of significant natural variation. Here, we present an extension of the ICAM framework for creating prediction specific FA maps through image-to-image translation