Recurrence statistics for the space of Interval Exchange maps and the Teichm\"uller flow on the space of translation surfaces

In this note we show that the transfer operator of a Rauzy-Veech-Zorich renormalization map acting on a space of quasi-H\"older functions is quasicompact and derive certain statistical recurrence properties for this map and its associated Teichm\"uller flow. We establish Borel-Cantelli lemmas, Extreme Value statistics and return time statistics for the map and flow. Previous results have established quasicompactness in H\"older or analytic function spaces, for example the work of M. Pollicott and T. Morita. The quasi-H\"older function space is particularly useful for investigating return time statistics. In particular we establish the shrinking target property for nested balls in the setting of Teichm\"uller flow. Our point of view, approach and terminology derives from the work of M. Pollicott augmented by that of M. Viana

Nitrogen sorption as a tool for the characterisation of polysaccharide aerogels

Supercritically dried aerogels of several polysaccharides (chitin, chitosan, alginate, alginic acid, k- carrageenan, and agar) have been characterised by physisorption ofN2. Surface areas as high as 570m2 g−1 have been measured. The nature of the functional groups of the polysaccharide significantly influences the adsorption of N2 on the surface of the aerogel. The net enthalpy of adsorption increases with the polarity of the surface groups of the polymer, in the order chitin < agar≤chitosan < carrageenan < alginic acid∼alginate. The surface area and the mesopore distribution of the aerogels depend both on the dispersion of the parent hydrogel and on the behaviour of each polymer in the drying treatment. Aerogels which retain the dispersion of the parent hydrogel are mainly macroporous (pores larger than 50 nm) while materials liable to shrink upon solvent exchange form mesoporous structures

The Science Case for the Planet Formation Imager (PFI)

Among the most fascinating and hotly-debated areas in contemporary astrophysics are the means by which planetary systems are assembled from the large rotating disks of gas and dust which attend a stellar birth. Although important work has already been, and is still being done both in theory and observation, a full understanding of the physics of planet formation can only be achieved by opening observational windows able to directly witness the process in action. The key requirement is then to probe planet-forming systems at the natural spatial scales over which material is being assembled. By definition, this is the so-called Hill Sphere which delineates the region of influence of a gravitating body within its surrounding environment. The Planet Formation Imager project (PFI) has crystallized around this challenging goal: to deliver resolved images of Hill-Sphere-sized structures within candidate planet-hosting disks in the nearest star-forming regions. In this contribution we outline the primary science case of PFI. For this purpose, we briefly review our knowledge about the planet-formation process and discuss recent observational results that have been obtained on the class of transition disks. Spectro-photometric and multi-wavelength interferometric studies of these systems revealed the presence of extended gaps and complex density inhomogeneities that might be triggered by orbiting planets. We present detailed 3-D radiation-hydrodynamic simulations of disks with single and multiple embedded planets, from which we compute synthetic images at near-infrared, mid-infrared, far-infrared, and sub-millimeter wavelengths, enabling a direct comparison of the signatures that are detectable with PFI and complementary facilities such as ALMA. From these simulations, we derive some preliminary specifications that will guide the array design and technology roadmap of the facility.Comment: SPIE Astronomical Telescopes and Instrumentation conference, June 2014, Paper ID 9146-120, 13 pages, 3 Figure

Use of traditional and complementary medicine by ethnic Indian women living with polycystic ovary syndrome: a global survey

Background: Traditional, complementary, and integrative medicine (TCIM) is commonly used by those living with Polycystic Ovary Syndrome (PCOS) but little is known about the use of TCIM such as yoga and Ayurveda in ethnic Indian women with PCOS living worldwide. This survey aimed to explore the prevalence and types of TCIM used and in particular the pattern of use of yoga and Ayurveda including reasons for not using and future interest in using them among non-users. Method: An online, international cross-sectional survey was conducted using a pre-designed survey tool. Participants were ethnic Indian women of reproductive age who reported that they were medically diagnosed with PCOS. Descriptive analysis was used to identify the proportion of TCIM users, while a multivariable binary logistic regression was used to analyze their characteristics. Results: Data from 3130 respondents were analysed. The prevalence of TCIM use was 80% (2515/3130). Yoga and Ayurveda were the most frequently practised TCIM modalities with a prevalence of 57% and 37% respectively. We found a high future interest in using yoga (81%) and Ayurveda (70%) among the non-users. The motivation for most Ayurveda use was a recommendation from family/friends (66%), rather than personal choice (38%) or the internet (19%). Most women used Ayurveda because it has natural ingredients (64%) and it is safe (60%) and cited its use to be safe and somewhat helpful. The majority of women were currently practising yoga (73%) up to four times a week (54%) at home (93%). Yoga was primarily used to improve overall health (67%), manage weight (64%), stress (54%) hormonal imbalance (49%) and emotional well-being (48%). Barriers to practising yoga were common among the current users and non-users and included lack of motivation (59% and 59%), time constraints (48% and 39%), and non-availability of yoga teachers specialised in PCOS (31% and 23%). Most women found yoga to be helpful and preferred individual one-on-one (52%) yoga sessions specifically tailored for PCOS (58%). Conclusion: This is the first international study that discovered the prevalence and pattern of TCIM use among ethnic Indian women with PCOS living worldwide. We support the urgent need for more research, education, and regulation of different TCIM modalities to promote safe and effective practices globally

A potassium tert-butoxide and hydrosilane system for ultra-deep desulfurization of fuels

Hydrodesulfurization (HDS) is the process by which sulfur-containing impurities are removed from petroleum streams, typically using a heterogeneous, sulfided transition metal catalyst under high H_2 pressures and temperatures. Although generally effective, a major obstacle that remains is the desulfurization of highly refractory sulfur-containing heterocycles, such as 4,6-dimethyldibenzothiophene (4,6-Me_2DBT), which are naturally occurring in fossil fuels. Homogeneous HDS strategies using well-defined molecular catalysts have been designed to target these recalcitrant S-heterocycles; however, the formation of stable transition metal sulfide complexes following C–S bond activation has largely prevented catalytic turnover. Here we show that a robust potassium (K) alkoxide (O)/hydrosilane (Si)-based (‘KOSi’) system efficiently desulfurizes refractory sulfur heterocycles. Subjecting sulfur-rich diesel (that is, [S] ∼ 10,000 ppm) to KOSi conditions results in a fuel with [S] ∼ 2 ppm, surpassing ambitious future governmental regulatory goals set for fuel sulfur content in all countries. Fossil fuels contain naturally occurring organosulfur impurities, with quantities varying depending on the type of feedstock. These sulfur-containing organic small molecules poison catalytic converters and generate polluting sulfur dioxides when combusted. Hydrodesulfurization (HDS) is the industrial process by which sulfur impurities are removed from petroleum fractions prior to their use as fuels. Currently, HDS is performed by treating petroleum with H_2 at high pressures and temperatures (that is, 150–2,250 psi and 400 °C) over heterogeneous catalysts such as cobalt-doped molybdenum sulfide supported on alumina (that is, CoMoS_x∕γ-Al_2O_3; Fig. 1a). However, certain organosulfur species, in particular dibenzothiophenes alkylated at positions 4 and 6, are not efficiently removed. Homogeneous strategies employing sophisticated, well-defined transition metal complexes—including those based on platinum, nickel, tungsten, molybdenum, palladium, ruthenium, rhodium, iron, cobalt, and others—have been extensively investigated. While these studies have provided valuable mechanistic insights, several fundamental issues, such as the formation of stable organometallic S–M species upon C–S bond activation by the metal centre (Fig. 1b), generally restrict industrial implementation of such methods. Rare examples of desulfurization of dibenzothiophenes alkylated at the 4 and 6 positions by homogeneous transition metal catalysis utilized either Ni compounds in combination with superstoichiometric alkyl Grignard reagents or Ni or Co phosphoranimide complexes in the presence of superstoichiometric KH. These issues pose a formidable challenge for the development of new HDS methods. Moreover, increasingly strict governmental regulations require limiting the sulfur content in diesel fuel and gasoline (in the US: typically <15 and <30 ppm, respectively) as well as other fuels, rendering the development of new powerful HDS methods a primary global concern. In 2013, Grubbs and co-workers reported the KO^tBu mediated cleavage of aryl C–O bonds in lignin models in the absence of transition metals using hydrosilanes. Careful inductively coupled plasma mass spectrometry (ICP-MS) analyses of the reagents and reaction mixtures ruled out catalysis with transition metals. We thus became interested in extending this method to sulfur heterocycles of relevance in oil and gas refining applications. Herein, we report that the robust KOtBu/silane-based (that is, KOSi) system is a powerful and effective homogeneous HDS method, which desulfurizes HDS-resistant dibenzothiophenes in good yield and reduces the sulfur content in diesel fuel to remarkably low levels (Fig. 1c)

The rise and fall of the ancient northern pike master sex-determining gene

The understanding of the evolution of variable sex determination mechanisms across taxa requires comparative studies among closely related species. Following the fate of a known master sex-determining gene, we traced the evolution of sex determination in an entire teleost order (Esociformes). We discovered that the northern pike (Esox lucius) master sex-determining gene originated from a 65 to 90 million-year-old gene duplication event and that it remained sex linked on undifferentiated sex chromosomes for at least 56 million years in multiple species. We identified several independent species- or population-specific sex determination transitions, including a recent loss of a Y chromosome. These findings highlight the diversity of evolutionary fates of master sex-determining genes and the importance of population demographic history in sex determination studies. We hypothesize that occasional sex reversals and genetic bottlenecks provide a non-adaptive explanation for sex determination transitions

DeepBacs for multi-task bacterial image analysis using open-source deep learning approaches

This work demonstrates and guides how to use a range of state-of-the-art artificial neural-networks to analyse bacterial microscopy images using the recently developed ZeroCostDL4Mic platform. We generated a database of image datasets used to train networks for various image analysis tasks and present strategies for data acquisition and curation, as well as model training. We showcase different deep learning (DL) approaches for segmenting bright field and fluorescence images of different bacterial species, use object detection to classify different growth stages in time-lapse imaging data, and carry out DL-assisted phenotypic profiling of antibiotic-treated cells. To also demonstrate the ability of DL to enhance low-phototoxicity live-cell microscopy, we showcase how image denoising can allow researchers to attain high-fidelity data in faster and longer imaging. Finally, artificial labelling of cell membranes and predictions of super-resolution images allow for accurate mapping of cell shape and intracellular targets. Our purposefully-built database of training and testing data aids in novice users’ training, enabling them to quickly explore how to analyse their data through DL. We hope this lays a fertile ground for the efficient application of DL in microbiology and fosters the creation of tools for bacterial cell biology and antibiotic research

DeepBacs for multi-task bacterial image analysis using open-source deep learning approaches

This work demonstrates and guides how to use a range of state-of-the-art artificial neural-networks to analyse bacterial microscopy images using the recently developed ZeroCostDL4Mic platform. We generated a database of image datasets used to train networks for various image analysis tasks and present strategies for data acquisition and curation, as well as model training. We showcase different deep learning (DL) approaches for segmenting bright field and fluorescence images of different bacterial species, use object detection to classify different growth stages in time-lapse imaging data, and carry out DL-assisted phenotypic profiling of antibiotic-treated cells. To also demonstrate the ability of DL to enhance low-phototoxicity live-cell microscopy, we showcase how image denoising can allow researchers to attain high-fidelity data in faster and longer imaging. Finally, artificial labelling of cell membranes and predictions of super-resolution images allow for accurate mapping of cell shape and intracellular targets. Our purposefully-built database of training and testing data aids in novice users' training, enabling them to quickly explore how to analyse their data through DL. We hope this lays a fertile ground for the efficient application of DL in microbiology and fosters the creation of tools for bacterial cell biology and antibiotic research.DeepBacs guides users without expertise in machine learning methods to leverage state-of-the-art artificial neural networks to analyse bacterial microscopy images

The EMSO Generic Instrument Module (EGIM): standardized and interoperable instrumentation for ocean observation

The oceans are a fundamental source for climate balance, sustainability of resources and life on Earth, therefore society has a strong and pressing interest in maintaining and, where possible, restoring the health of the marine ecosystems. Effective, integrated ocean observation is key to suggesting actions to reduce anthropogenic impact from coastal to deep-sea environments and address the main challenges of the 21st century, which are summarized in the UN Sustainable Development Goals and Blue Growth strategies. The European Multidisciplinary Seafloor and water column Observatory (EMSO), is a European Research Infrastructure Consortium (ERIC), with the aim of providing long-term observations via fixed-point ocean observatories in key environmental locations across European seas from the Arctic to the Black Sea. These may be supported by ship-based observations and autonomous systems such as gliders. In this paper, we present the EMSO Generic Instrument Module (EGIM), a deployment ready multi-sensor instrumentation module, designed to measure physical, biogeochemical, biological and ecosystem variables consistently, in a range of marine environments, over long periods of time. Here, we describe the system, features, configuration, operation and data management. We demonstrate, through a series of coastal and oceanic pilot experiments that the EGIM is a valuable standard ocean observation module, which can significantly improve the capacity of existing ocean observatories and provides the basis for new observatories. The diverse examples of use included the monitoring of fish activity response upon oceanographic variability, hydrothermal vent fluids and particle dispersion, passive acoustic monitoring of marine mammals and time series of environmental variation in the water column. With the EGIM available to all the EMSO Regional Facilities, EMSO will be reaching a milestone in standardization and interoperability, marking a key capability advancement in addressing issues of sustainability in resource and habitat management of the oceans.This work was funded by the project EMSODEV (Grant agreement No 676555) supported by DG Research and Innovation of the European Commission under the Research Infrastructures Programme of the H2020. EMSO-link EC project (Grant agreement No 731036) provided additional funding. Other projects which supported the work include Plan Estatal de Investigación Científica y Técnica y de Innovación 2017–2020, project BITER-LANDER PID2020- 114732RB-C32, iFADO (Innovation in the Framework of the Atlantic Deep Ocean, 2017–2021) EAPA_165/2016. The Spanish Government contributed through the “Severo Ochoa Centre Excellence” accreditation to ICM-CSIC (CEX2019-000928-S) and the Research Unit Tecnoterra (ICM-CSIC/UPC). UK colleagues were supported by Climate Linked Atlantic Sector Science (CLASS) project supported by NERC National Capability funding (NE/R015953/1).Peer ReviewedArticle signat per 33 autors/es: Nadine Lantéri; Henry A. Ruh; Andrew Gates; Enoc Martínez; Joaquin del Rio Fernandez; Jacopo Aguzzi; Mathilde Cannat; Eric Delory; Davide Embriaco; Robert Huber; Marjolaine Matabos;George Petihakis; Kieran Reilly; Jean-François Rolin; Mike van der Schaar; Michel André; Jérôme Blandin; Andrés Cianca; Marco Francescangeli; Oscar Garcia; Susan Hartman; Jean-Romain Lagadec; Julien Legrand; Paris Pagonis; Jaume Piera; Xabier Remirez; Daniel M. Toma; Giuditta Marinaro; Bertrand Moreau; Raul Santana; Hannah Wright; Juan José Dañobeitia; Paolo FavaliPostprint (published version