Convex regions in the plane and their domes

We make a detailed study of the relation of a euclidean convex region $\Omega \subset \mathbb C$ to $\mathrm{Dome} (\Omega)$. The dome is the relative boundary, in the upper halfspace model of hyperbolic space, of the hyperbolic convex hull of the complement of $\Omega$. The first result is to prove that the nearest point retraction $r: \Omega \to \mathrm{Dome} (\Omega)$ is 2-quasiconformal. The second is to establish precise estimates of the distortion of $r$ near $\partial \Omega$

Variation of Milk Yield and Milk Composition of Pivska Pramenka Sheep Breed Through Lactation

The aim of this paper is to present the research results on the milk traits and variation of milk composition during lactation of Pivska pramenka breed, as one of the most important autochthonous sheep breeds in Montenegro. Investigation was conducted on the family sheep farm located in the municipality of Žabljak, a typical rearing area of Pivska pramenka breed. The following milk traits were studied: length of lactation, milk yield (daily milk yield – DMY and total milk yield - TMY) and milk composition (Fat, Protein, Lactose, Solid non-fat - SNF and Somatic cells count - SCC). Based on the data of 68 completed lactations, average length of lactation was 178.5 days and average milk yield 94.1 kg. On the basis of 289 milk samples analysed in 5 consecutive milk recordings, average daily milk yield was 0.549 litres, with 5.71% of fat, 5.75% of protein, 4.47% of lactose, 11.04 % of solid non-fat and 600x103 SCC on average. Differences in averages for milk composition among test days (days of milk recording) during lactation were significant (P0.01). The largest variation was for milk fat, from 2.95% in the first control to 9.42% in the fifth control, while variation of protein was between 4.5% in the first and 7.4 in the fifth control. The content of lactose exposed decreasing trend during lactation (from 4.7% in first to 3.1% in fifth control)

Corticotropin-releasing hormone interacts with interleukin-1 to regulate prostaglandin H synthase-2 expression in human myometrium during pregnancy and labor

Context: The onset of labor appears to involve the activation of myometrial inflammatory pathways, and transcription factors such as nuclear factor-κB (NF-κB) control expression of the contraction-associated proteins required to induce a procontractile phenotype. These responses might involve CRH, which integrates immune and neuroendocrine systems. Objectives: In human myometrium we investigated cyclooxygenase 2 (PGHS2) expression and regulation by CRH and the proinflammatory cytokine IL-1β before and after labor. Design: Myometrial tissues obtained from pregnant women at term before (n = 12) or during labor (n = 10) and pathological cases of choriamnionitis-associated term labor (n = 5) were used to isolate primary myocytes and investigate in vitro, CRH effects on basal and IL-1β regulated p65 activation and PGHS2 expression. Results: In nonlaboring myometrial cells, CRH was unable to induce NF-κB nuclear translocation; however, it altered the temporal dynamics of IL-1β-driven NF-κB nuclear entry by initially delaying entry and subsequently prolonging retention. These CRH-R1-driven effects were associated with a modest inhibitory action in the early phase (within 2 hours) of IL-1β stimulated PGHS2 mRNA expression, whereas prolonged stimulation for 6–18 hours augmented the IL-1β effects. The early-phase effect required intact protein kinase A activity and was diminished after the onset of labor. The presence of chorioamnionitis led to exaggerated PGHS2 mRNA responses to IL-1β but diminished effects of CRH. Conclusions: CRH is involved in the inflammatory regulation of PGHS2 expression before and during labor; these actions might be important in priming and preparing the myometrium for labor and cellular adaptive responses to inflammatory mediator

Insecticidal Activity of Sage (Salvia Officinalis) Essential Oil to Varroa Destructor (Acari: Varroidae) and Apis Mellifera (Hymenoptera: Apidae)

The need to find alternative systems of the fight against Varroa mite without application of chemicals and provide healthy bee products resulted in investigation of application of different plant essences to arthropod control. In order to perceive the sage essential oil (Salvia officinalis) bioactivity, contact residual toxicity of mites and bees was examined in the laboratory conditions. The chemical composition of essential oil was determined by standard GC and GC/MS methods. Different doses of the sage essential oil dissolved in acetone (0.1–10 μl/Petri dish) were applied in Petri dishes and left to dry for 20 minute at a room temperature. Following this period of time, ten honey bees and five adult female mites were added in each Petri dish and they were all maintained in controlled conditions (T = 30°C, Relative humidity = 60%). Survival of examined honey bees and Varroa mites was recorded two times, after 24 h and 48 h. The most prominent toxic effect on the examined Varroa mites was observed after 24 h and 48 h, with application of 10 μl of sage oil (the average values for dead mite individuals were 3.25 and 3.50, respectively). Recorded biological activities of the oil tested in different doses on both honey bee and Varroa mite revealed opportunity to proceed with further investigation by selecting the most appropriate variants and combinations of the most prominent individual components of the examined sage oil

Assessing non-linear models for galaxy clustering I: unbiased growth forecasts from multipole expansion

We assess the performance of the Taruya, Nishimichi and Saito (TNS) model for the halo redshift space power spectrum, focusing on utilising mildly non-linear scales to constrain the growth rate of structure f. Using simulations with volume and number density typical of forthcoming Stage IV galaxy surveys, we determine ranges of validity for the model at redshifts z = 0.5 and z = 1. We proceed to perform a Bayesian MCMC analysis utilising the monopole, quadrupole, and hexadecapole spectra, followed by an exploratory Fisher matrix analysis. As previously noted in other forecasts as well as in real data analyses, we find that including the hexadecapole can significantly improve the constraints. However, a restricted range of scales is required for the hexadecapole in order for the growth parameter estimation to remain unbiased, limiting the improvement. We consistently quantify these effects by employing the multipole expansion formalism in both our Fisher and MCMC forecasts.Comment: 12 pages, 7 figures, 2 tables, accepted in OJ

Vertex routing models

A class of models describing the flow of information within networks via routing processes is proposed and investigated, concentrating on the effects of memory traces on the global properties. The long-term flow of information is governed by cyclic attractors, allowing to define a measure for the information centrality of a vertex given by the number of attractors passing through this vertex. We find the number of vertices having a non-zero information centrality to be extensive/sub-extensive for models with/without a memory trace in the thermodynamic limit. We evaluate the distribution of the number of cycles, of the cycle length and of the maximal basins of attraction, finding a complete scaling collapse in the thermodynamic limit for the latter. Possible implications of our results on the information flow in social networks are discussed.Comment: 12 pages, 6 figure

QCSP on reflexive tournaments

We give a complexity dichotomy for the Quantified Constraint Satisfaction Problem QCSP(H) when H is a reflexive tournament. It is well known that reflexive tournaments can be split into a sequence of strongly connected components H1,…,Hn so that there exists an edge from every vertex of Hi to every vertex of Hj if and only if

The corticotrophin-releasing factor/urocortin system regulates white fat browning in mice through paracrine mechanisms

Objectives: The corticotrophin-releasing factor (CRF)/urocortin system is expressed in the adipose tissue of mammals, but its functional role in this tissue remains unknown. Methods: Pharmacological manipulation of the activity of CRF receptors, CRF1 and CRF2, was performed in 3T3L1 white pre-adipocytes and T37i brown pre-adipocytes during in vitro differentiation. The expression of genes of the CRF/urocortin system and of markers of white and brown adipocytes was evaluated along with mitochondrial biogenesis and cellular oxygen consumption. Metabolic evaluation of corticosterone-deficient or supplemented Crhr1-null (Crhr1−/−) mice and their wild-type controls was performed along with gene expression analysis carried out in white (WAT) and brown (BAT) adipose tissues. Results: Peptides of the CRF/urocortin system and their cognate receptors were expressed in both pre-adipocyte cell lines. In vitro pharmacological studies showed an inhibition of the expression of the CRF2 pathway by the constitutive activity of the CRF1 pathway. Pharmacological activation of CRF2 and, to a lesser extent, inhibition of CRF1 signaling induced molecular and functional changes indicating transdifferentiation of white pre-adipocytes and differentiation of brown pre-adipocytes. Crhr1−/− mice showed increased expression of CRF2 and its agonist Urocortin 2 in adipocytes that was associated to brown conversion of WAT and activation of BAT. Crhr1−/− mice were resistant to diet-induced obesity and glucose intolerance. Restoring physiological circulating corticosterone levels abrogated molecular changes in adipocytes and the favorable phenotype of Crhr1−/− mice. Conclusions: Our findings suggest the importance of the CRF2 pathway in the control of adipocyte plasticity. Increased CRF2 activity in adipocytes induces browning of WAT, differentiation of BAT and is associated with a favorable metabolic phenotype in mice lacking CRF1. Circulating corticosterone represses CRF2 activity in adipocytes and may thus regulate adipocyte physiology through the modulation of the local CRF/urocortin system. Targeting CRF receptor signaling specifically in the adipose tissue may represent a novel approach to tackle obesity

Development of an early-warning system for high-risk patients for suicide attempt using deep learning and electronic health records

Suicide is the tenth leading cause of death in the United States (US). An early-warning system (EWS) for suicide attempt could prove valuable for identifying those at risk of suicide attempts, and analyzing the contribution of repeated attempts to the risk of eventual death by suicide. In this study we sought to develop an EWS for high-risk suicide attempt patients through the development of a population-based risk stratification surveillance system. Advanced machine-learning algorithms and deep neural networks were utilized to build models with the data from electronic health records (EHRs). A final risk score was calculated for each individual and calibrated to indicate the probability of a suicide attempt in the following 1-year time period. Risk scores were subjected to individual-level analysis in order to aid in the interpretation of the results for health-care providers managing the at-risk cohorts. The 1-year suicide attempt risk model attained an area under the curve (AUC ROC) of 0.792 and 0.769 in the retrospective and prospective cohorts, respectively. The suicide attempt rate in the very high risk category was 60 times greater than the population baseline when tested in the prospective cohorts. Mental health disorders including depression, bipolar disorders and anxiety, along with substance abuse, impulse control disorders, clinical utilization indicators, and socioeconomic determinants were recognized as significant features associated with incident suicide attempt