Kato square root problem with unbounded leading coefficients

We prove the Kato conjecture for elliptic operators, $L=-\nabla\cdot\left((\mathbf A+\mathbf D)\nabla\ \right)$, with $\mathbf A$ a complex measurable bounded coercive matrix and $\mathbf D$ a measurable real-valued skew-symmetric matrix in $\mathbb{R}^n$ with entries in $BMO(\mathbb{R}^n)$;\, i.e., the domain of $\sqrt{L}\,$ is the Sobolev space $\dot H^1(\mathbb{R}^n)$ in any dimension, with the estimate $\|\sqrt{L}\, f\|_2\lesssim \| \nabla f\|_2$

High spatial resolution and high contrast optical speckle imaging with FASTCAM at the ORM

In this paper, we present an original observational approach, which combines, for the first time, traditional speckle imaging with image post-processing to obtain in the optical domain diffraction-limited images with high contrast (1e-5) within 0.5 to 2 arcseconds around a bright star. The post-processing step is based on wavelet filtering an has analogy with edge enhancement and high-pass filtering. Our I-band on-sky results with the 2.5-m Nordic Telescope (NOT) and the lucky imaging instrument FASTCAM show that we are able to detect L-type brown dwarf companions around a solar-type star with a contrast DI~12 at 2" and with no use of any coronographic capability, which greatly simplifies the instrumental and hardware approach. This object has been detected from the ground in J and H bands so far only with AO-assisted 8-10 m class telescopes (Gemini, Keck), although more recently detected with small-class telescopes in the K band. Discussing the advantage and disadvantage of the optical regime for the detection of faint intrinsic fluxes close to bright stars, we develop some perspectives for other fields, including the study of dense cores in globular clusters. To the best of our knowledge this is the first time that high contrast considerations are included in optical speckle imaging approach.Comment: Proceedings of SPIE conference - Ground-based and Airborne Instrumentation for Astronomy III (Conference 7735), San Diego 201

Cerebellum Transcriptome of Mice Bred for High Voluntary Activity Offers Insights into Locomotor Control and Reward-Dependent Behaviors.

The role of the cerebellum in motivation and addictive behaviors is less understood than that in control and coordination of movements. High running can be a self-rewarding behavior exhibiting addictive properties. Changes in the cerebellum transcriptional networks of mice from a line selectively bred for High voluntary running (H) were profiled relative to an unselected Control (C) line. The environmental modulation of these changes was assessed both in activity environments corresponding to 7 days of Free (F) access to running wheel and to Blocked (B) access on day 7. Overall, 457 genes exhibited a significant (FDR-adjusted P-value < 0.05) genotype-by-environment interaction effect, indicating that activity genotype differences in gene expression depend on environmental access to running. Among these genes, network analysis highlighted 6 genes (Nrgn, Drd2, Rxrg, Gda, Adora2a, and Rab40b) connected by their products that displayed opposite expression patterns in the activity genotype contrast within the B and F environments. The comparison of network expression topologies suggests that selection for high voluntary running is linked to a predominant dysregulation of hub genes in the F environment that enables running whereas a dysregulation of ancillary genes is favored in the B environment that blocks running. Genes associated with locomotor regulation, signaling pathways, reward-processing, goal-focused, and reward-dependent behaviors exhibited significant genotype-by-environment interaction (e.g. Pak6, Adora2a, Drd2, and Arhgap8). Neuropeptide genes including Adcyap1, Cck, Sst, Vgf, Npy, Nts, Penk, and Tac2 and related receptor genes also exhibited significant genotype-by-environment interaction. The majority of the 183 differentially expressed genes between activity genotypes (e.g. Drd1) were under-expressed in C relative to H genotypes and were also under-expressed in B relative to F environments. Our findings indicate that the high voluntary running mouse line studied is a helpful model for understanding the molecular mechanisms in the cerebellum that influence locomotor control and reward-dependent behaviors

Analysis of a silvopastoral system with animals of the autochtonous swine breed Porco Celta in Galicia (NW Spain)

PosterPig traditional production systems in Galicia (NW Spain) are based on seasonal resources us like chestnut and pastures. The Breeders' Association of the autochthonous Celtic breed of pigs (ASOPORCEL) has developed a novel system within the traditional Galicia grazed forest areas in order to preserve landscape quality and biologic diversity, minimizing therefore the environmental impact of pig production. One of the main concerns of silvopastoral system implementation is the need of fencing. Fencing costs could be reduced if animals are rearing with infrastructures based on Pavlov animal condition reflex management in an extensive system. Therefore, cost reduction is obtained thanks to the clear reduction of personnel needs to feed animals, fencing costs and understorey clearance to reduce forest fires. In 2013 an experiment was carried out in Nebra (NW of Spain) in a young Pinus pinaster plantation. Pig stocking rate was around 3.85 pigs per ha (25 males and 25 females) in a total surface of 13 ha. Forest grazing program was initiated when animals were three months old in March 2013 and finished in December 2013. They were allowed access the whole plot. Concentrate was provided twice every day after sounding an alarm to attract pigs. All the animals adapted rapidly to the system. Two types o understory vegetation (Ulex and Pteridium) was sampled following a transect from close to far away feeding areas (three distances). Fern control was intense, being gorse less consumed. After nine months, average animal daily gain (ADG) obtained was 290 ± 4 gr. We can conclude that the used method is perfectly adaptable to the systems of exploitation suggested for the Celtic pig breed. This will be highly relevant to preserve this autochthonous breed and increase the number of extensive farms in the area while contributing to fix population dedicated to use silvopastoral systems

The Low Redshift survey at Calar Alto (LoRCA)

The Baryon Acoustic Oscillation (BAO) feature in the power spectrum of galaxies provides a standard ruler to measure the accelerated expansion of the Universe. To extract all available information about dark energy, it is necessary to measure a standard ruler in the local, z<0.2, universe where dark energy dominates most the energy density of the Universe. Though the volume available in the local universe is limited, it is just big enough to measure accurately the long 100 Mpc/h wave-mode of the BAO. Using cosmological N-body simulations and approximate methods based on Lagrangian perturbation theory, we construct a suite of a thousand light-cones to evaluate the precision at which one can measure the BAO standard ruler in the local universe. We find that using the most massive galaxies on the full sky (34,000 sq. deg.), i.e. a K(2MASS)<14 magnitude-limited sample, one can measure the BAO scale up to a precision of 4\% and 1.2\% using reconstruction). We also find that such a survey would help to detect the dynamics of dark energy.Therefore, we propose a 3-year long observational project, named the Low Redshift survey at Calar Alto (LoRCA), to observe spectroscopically about 200,000 galaxies in the northern sky to contribute to the construction of aforementioned galaxy sample. The suite of light-cones is made available to the public.Comment: 15 pages. Accepted in MNRAS. Please visit our website: http://lorca-survey.ft.uam.es

Predicting Isoform-Selective Carbonic Anhydrase Inhibitors via Machine Learning and Rationalizing Structural Features Important for Selectivity

Carbonic anhydrases (CAs) catalyze the physiological hydration of carbon dioxide and are among the most intensely studied pharmaceutical target enzymes. A hallmark of CA inhibition is the complexation of the catalytic zinc cation in the active site. Human (h) CA isoforms belonging to different families are implicated in a wide range of diseases and of very high interest for therapeutic intervention. Given the conserved catalytic mechanisms and high similarity of many hCA isoforms, a major challenge for CA-based therapy is achieving inhibitor selectivity for hCA isoforms that are associated with specific pathologies over other widely distributed isoforms such as hCA I or hCA II that are of critical relevance for the integrity of many physiological processes. To address this challenge, we have attempted to predict compounds that are selective for isoform hCA IX, which is a tumor-associated protein and implicated in metastasis, over hCA II on the basis of a carefully curated data set of selective and nonselective inhibitors. Machine learning achieved surprisingly high accuracy in predicting hCA IX-selective inhibitors. The results were further investigated, and compound features determining successful predictions were identified. These features were then studied on the basis of X-ray structures of hCA isoform-inhibitor complexes and found to include substructures that explain compound selectivity. Our findings lend credence to selectivity predictions and indicate that the machine learning models derived herein have considerable potential to aid in the identification of new hCA IX-selective compounds