A large-NcN_c PNJL model with explicit ZNc_{N_c} symmetry

A PNJL model is built, in which the Polyakov-loop potential is explicitly Z$_{N_c}$-symmetric in order to mimic a Yang-Mills theory with gauge group SU($N_c$). The physically expected large-$N_c$ and large-$T$ behaviours of the thermodynamic observables computed from the Polyakov-loop potential are used to constrain its free parameters. The effective potential is eventually U(1)-symmetric when $N_c$ is infinite. Light quark flavours are added by using a Nambu-Jona-Lasinio (NJL) model coupled to the Polyakov loop (the PNJL model), and the different phases of the resulting PNJL model are discussed in 't Hooft's large-$N_c$ limit. Three phases are found, in agreement with previous large-$N_c$ studies. When the temperature $T$ is larger than some deconfinement temperature $T_d$, the system is in a deconfined, chirally symmetric, phase for any quark chemical potential $\mu$. When $T<T_d$ however, the system is in a confined phase in which chiral symmetry is either broken or not. The critical line $T_\chi(\mu)$, signalling the restoration of chiral symmetry, has the same qualitative features than what can be obtained within a standard $N_c=3$ PNJL model.Comment: To appear in Phys Rev

Neutron Stars as a Probe for Dense Matter

We study different stages of the neutron star cooling by computing neutron star properties at various temperatures and entropies using an effective chiral model including hadronic and quark degrees of freedom. Macroscopic properties of the star such as mass and radius are calculated and compared with observations. It can be seen that the effects of chiral restoration and deconfinement to quark matter in the core of the neutron star at different stages of the evolution can be significant for the evolution of the star and allow insight into the behaviour of matter at extreme densities.Comment: To appear in the proceedings of the International Conference on Particles And Nuclei (PANIC08), Eilat, Israel, 9-14 Nov 200

The problem of repulsive quark interactions - Lattice versus mean field models

We calculate the 2nd and 4th order quark number susceptibilities at zero baryochemical potential, using a PNJL approach and an approach which includes, in a single model, quark and hadronic degrees of freedom. We observe that the susceptibilities are very sensitive to possible quark-quark vector interactions. Compared to lattice data our results suggest that above $T_c$ any mean field type of repulsive vector interaction can be excluded from model calculations. Below $T_c$ our results show only very weak sensitivity on the strength of the quark and hadronic vector interaction. The best description of lattice data around $T_c$ is obtained for a case of coexistence of hadronic and quark degrees of freedom.Comment: 5 pages, 4 figure, version accepted by PL

QGP Susceptibilities from PNJL Model

An improved version of the PNJL model is used to calculate various thermodynamical quantities, {\it viz.}, quark number susceptibility, isospin susceptibility, specific heat, speed of sound and conformal measure. Comparison with Lattice data is found to be encouraging.Comment: 4 pages, 2 figures, poster presented at Quark Matter'0

The metabolic environment of the developing embryo: A multidisciplinary approach on oilseed rapeseed

Brassicaceae seeds consist of three genetically distinct structures: the embryo, endosperm and seed coat, all of which are involved in assimilate allocation during seed development. The complexity of their metabolic interrelations remains unresolved to date. In the present study, we apply state-of-the-art imaging and analytical approaches to assess the metabolic environment of the Brassica napus embryo. Nuclear magnetic resonance imaging (MRI) provided volumetric data on the living embryo and endosperm, revealing how the endosperm envelops the embryo, determining endosperm's priority in assimilate uptake from the seed coat during early development. MRI analysis showed higher levels of sugars in the peripheral endosperm facing the seed coat, but a lower sugar content within the central vacuole and the region surrounding the embryo. Feeding intact siliques with 13C-labeled sucrose allowed tracing of the post-phloem route of sucrose transfer within the seed at the heart stage of embryogenesis, by means of mass spectrometry imaging. Quantification of over 70 organic and inorganic compounds in the endosperm revealed shifts in their abundance over different stages of development, while sugars and potassium were the main determinants of osmolality throughout these stages. Our multidisciplinary approach allows access to the hidden aspects of endosperm metabolism, a task which remains unattainable for the small-seeded model plant Arabidopsis thaliana

Racial Equity Considerations In Safe To Sleep Messaging: Learning From The Community

Black infants are dying at a rate of over twice that of White infants. We know that infants in unsafe sleep positions are more likely to die from Sudden Unexpected Infant Death (SUID). Safe to Sleep® education has led to a dramatic decrease in mortality among white infants, but over 60% of Black families do not follow the Safe to Sleep® parameters. Safe to Sleep® education is given to pregnant women during the prenatal period and prior to hospital discharge, but what is the best way to share this message with Black families

Application of SAR time-series and deep learning for estimating landslide occurence time

The time series of normalized difference vegetation index (NDVI) and interferometric coherence extracted from optical and Synthetic Aperture Radar (SAR) images, respectively, have strong responses to sudden landslide failures in vegetated regions, which is expressed by a sudden increase or decrease in the values of NDVI and coherence. Compared with optical sensors, SAR sensors are not affected by cloud and daylight conditions and can detect the occurrence time of failure in near real-time. The purpose of this paper is to automatically determine the time of failure occurrence using time series coherence values. We propose, based on some existing anomaly detection algorithms, a deep neural network-based anomaly detection strategy that combines supervised and unsupervised learning without a priori knowledge about failure time. Our experiment using July 21, 2020 Shaziba landslide in China shows that in comparison to widely used unsupervised methodology, the use of our algorithm leads to a more accurate detection of the timing of the landslide failure

Comprehensive systematic review summary: Treatment of tics in people with Tourette syndrome and chronic tic disorders

Objective To systematically evaluate the efficacy of treatments for tics and the risks associated with their use. Methods This project followed the methodologies outlined in the 2011 edition of the American Academy of Neurology\u27s guideline development process manual. We included systematic reviews and randomized controlled trials on the treatment of tics that included at least 20 participants (10 participants if a crossover trial), except for neurostimulation trials, for which no minimum sample size was required. To obtain additional information on drug safety, we included cohort studies or case series that specifically evaluated adverse drug effects in individuals with tics. Results There was high confidence that the Comprehensive Behavioral Intervention for Tics was more likely than psychoeducation and supportive therapy to reduce tics. There was moderate confidence that haloperidol, risperidone, aripiprazole, tiapride, clonidine, onabotulinumtoxinA injections, 5-ling granule, Ningdong granule, and deep brain stimulation of the globus pallidus were probably more likely than placebo to reduce tics. There was low confidence that pimozide, ziprasidone, metoclopramide, guanfacine, topiramate, and tetrahydrocannabinol were possibly more likely than placebo to reduce tics. Evidence of harm associated with various treatments was also demonstrated, including weight gain, drug-induced movement disorders, elevated prolactin levels, sedation, and effects on heart rate, blood pressure, and ECGs. Conclusions There is evidence to support the efficacy of various medical, behavioral, and neurostimulation interventions for the treatment of tics. Both the efficacy and harms associated with interventions must be considered in making treatment recommendations

Practice Guideline Recommendations Summary: Treatment of Tics in People with Tourette Syndrome and Chronic Tic Disorders

Objective To make recommendations on the assessment and management of tics in people with Tourette syndrome and chronic tic disorders. Methods A multidisciplinary panel consisting of 9 physicians, 2 psychologists, and 2 patient representatives developed practice recommendations, integrating findings from a systematic review and following an Institute of Medicine–compliant process to ensure transparency and patient engagement. Recommendations were supported by structured rationales, integrating evidence from the systematic review, related evidence, principles of care, and inferences from evidence. Results Forty-six recommendations were made regarding the assessment and management of tics in individuals with Tourette syndrome and chronic tic disorders. These include counseling recommendations on the natural history of tic disorders, psychoeducation for teachers and peers, assessment for comorbid disorders, and periodic reassessment of the need for ongoing therapy. Treatment options should be individualized, and the choice should be the result of a collaborative decision among patient, caregiver, and clinician, during which the benefits and harms of individual treatments as well as the presence of comorbid disorders are considered. Treatment options include watchful waiting, the Comprehensive Behavioral Intervention for Tics, and medication; recommendations are provided on how to offer and monitor these therapies. Recommendations on the assessment for and use of deep brain stimulation in adults with severe, treatment-refractory tics are provided as well as suggestions for future research

Metabolic profiling of diabetic cats in remission

Background: The majority of diabetic cats in remission have abnormal glucose tolerance, and approximately one third relapse within 1 year. Greater understanding of the metabolic characteristics of diabetic cats in remission, and predictors of relapse is required to effectively monitor and manage these cats. Objectives: To identify and compare differences in plasma metabolites between diabetic cats in remission and healthy control cats using a metabolomics approach. Secondly, to assess whether identified metabolites are predictors of diabetic relapse. Animals: Twenty cats in diabetic remission for a median of 101 days, and 22 healthy matched control cats. Methods: Cats were admitted to a clinic, and casual blood glucose was recorded. After a 24 h fast, blood glucose concentration was measured, then a blood sample was taken for metabolomic (GCMS and LCMS) analyses. Three hours later, a simplified intravenous glucose tolerance test (1 g glucose/kg) was performed. Cats were monitored for diabetes relapse for at least 9 months (270 days) after baseline testing. Results: Most cats in remission continued to display impaired glucose tolerance. Concentrations of 16 identified metabolites differed (P ≤ 0.05) between remission and control cats: 10 amino acids and stearic acid (all lower in remission cats), and glucose, glycine, xylitol, urea and carnitine (all higher in remission cats). Moderately close correlations were found between these 16 metabolites and variables assessing glycaemic responses (most |r| = 0.31 to 0.69). Five cats in remission relapsed during the study period. No metabolite was identified as a predictor of relapse. Conclusion and clinical importance: This study shows that cats in diabetic remission have abnormal metabolism