Boundedness of Pseudodifferential Operators on Banach Function Spaces

We show that if the Hardy-Littlewood maximal operator is bounded on a separable Banach function space $X(\mathbb{R}^n)$ and on its associate space $X'(\mathbb{R}^n)$, then a pseudodifferential operator $\operatorname{Op}(a)$ is bounded on $X(\mathbb{R}^n)$ whenever the symbol $a$ belongs to the H\"ormander class $S_{\rho,\delta}^{n(\rho-1)}$ with $0<\rho\le 1$, $0\le\delta<1$ or to the the Miyachi class $S_{\rho,\delta}^{n(\rho-1)}(\varkappa,n)$ with $0\le\delta\le\rho\le 1$, $0\le\delta0$. This result is applied to the case of variable Lebesgue spaces $L^{p(\cdot)}(\mathbb{R}^n)$.Comment: To appear in a special volume of Operator Theory: Advances and Applications dedicated to Ant\'onio Ferreira dos Santo

Lower plasma levels of selenium and glutathione in smear-positive tuberculosis patients in Malawi

No Abstract

Complexity and Inapproximability Results for Parallel Task Scheduling and Strip Packing

We study the Parallel Task Scheduling problem $Pm|size_j|C_{\max}$ with a constant number of machines. This problem is known to be strongly NP-complete for each $m \geq 5$, while it is solvable in pseudo-polynomial time for each $m \leq 3$. We give a positive answer to the long-standing open question whether this problem is strongly $NP$-complete for $m=4$. As a second result, we improve the lower bound of $\frac{12}{11}$ for approximating pseudo-polynomial Strip Packing to $\frac{5}{4}$. Since the best known approximation algorithm for this problem has a ratio of $\frac{4}{3} + \varepsilon$, this result narrows the gap between approximation ratio and inapproximability result by a significant step. Both results are proven by a reduction from the strongly $NP$-complete problem 3-Partition

An output-sensitive algorithm for the minimization of 2-dimensional String Covers

String covers are a powerful tool for analyzing the quasi-periodicity of 1-dimensional data and find applications in automata theory, computational biology, coding and the analysis of transactional data. A \emph{cover} of a string $T$ is a string $C$ for which every letter of $T$ lies within some occurrence of $C$. String covers have been generalized in many ways, leading to \emph{k-covers}, \emph{$\lambda$-covers}, \emph{approximate covers} and were studied in different contexts such as \emph{indeterminate strings}. In this paper we generalize string covers to the context of 2-dimensional data, such as images. We show how they can be used for the extraction of textures from images and identification of primitive cells in lattice data. This has interesting applications in image compression, procedural terrain generation and crystallography

L-Arginine promotes gut hormone release and reduces food intake in rodents

Aims: To investigate the anorectic effect of L‐arginine (L‐Arg) in rodents. Methods: We investigated the effects of L‐Arg on food intake, and the role of the anorectic gut hormones glucagon‐like peptide‐1 (GLP‐1) and peptide YY (PYY), the G‐protein‐coupled receptor family C group 6 member A (GPRC6A) and the vagus nerve in mediating these effects in rodents. Results: Oral gavage of L‐Arg reduced food intake in rodents, and chronically reduced cumulative food intake in diet‐induced obese mice. Lack of the GPRC6A in mice and subdiaphragmatic vagal deafferentation in rats did not influence these anorectic effects. L‐Arg stimulated GLP‐1 and PYY release in vitro and in vivo. Pharmacological blockade of GLP‐1 and PYY receptors did not influence the anorectic effect of L‐Arg. L‐Arg‐mediated PYY release modulated net ion transport across the gut mucosa. Intracerebroventricular (i.c.v.) and intraperitoneal (i.p.) administration of L‐Arg suppressed food intake in rats. Conclusions: L‐Arg reduced food intake and stimulated gut hormone release in rodents. The anorectic effect of L‐Arg is unlikely to be mediated by GLP‐1 and PYY, does not require GPRC6A signalling and is not mediated via the vagus. I.c.v. and i.p. administration of L‐Arg suppressed food intake in rats, suggesting that L‐Arg may act on the brain to influence food intake. Further work is required to determine the mechanisms by which L‐Arg suppresses food intake and its utility in the treatment of obesity

Dwarf Nova V1040 Centauri and Variable Stars in its Vicinity

We present the results of a photometric campaign of the dwarf nova V1040 Cen. The light curve shows two normal outbursts with recurrence time ~ 40 days and amplitude ~ 2.5 mag. Quiescence data show oscillations with periods in the range ~ 0.1 days (2.4 h) to ~ 0.5 days (12 h) of unknown origin. We measured the orbital period of V1040 Cen to be P_orb=0.060458(80) days (1.451+-0.002 h). Based on the M_v-P_orb relation we found the distance of V1040 Cen to be 137+-31 pc. In this paper we also report the detection of eleven new variable stars in the field of the monitored dwarf nova.Comment: 7 figures and 2 tables, accepted for publication in Acta Astronomic

A Goal-based Framework for Contextual Requirements Modeling and Analysis

Requirements Engineering (RE) research often ignores, or presumes a uniform nature of the context in which the system operates. This assumption is no longer valid in emerging computing paradigms, such as ambient, pervasive and ubiquitous computing, where it is essential to monitor and adapt to an inherently varying context. Besides influencing the software, context may influence stakeholders' goals and their choices to meet them. In this paper, we propose a goal-oriented RE modeling and reasoning framework for systems operating in varying contexts. We introduce contextual goal models to relate goals and contexts; context analysis to refine contexts and identify ways to verify them; reasoning techniques to derive requirements reflecting the context and users priorities at runtime; and finally, design time reasoning techniques to derive requirements for a system to be developed at minimum cost and valid in all considered contexts. We illustrate and evaluate our approach through a case study about a museum-guide mobile information system

Graphene-based photovoltaic cells for near-field thermal energy conversion

Thermophotovoltaic devices are energy-conversion systems generating an electric current from the thermal photons radiated by a hot body. In far field, the efficiency of these systems is limited by the thermodynamic Schockley-Queisser limit corresponding to the case where the source is a black body. On the other hand, in near field, the heat flux which can be transferred to a photovoltaic cell can be several orders of magnitude larger because of the contribution of evanescent photons. This is particularly true when the source supports surface polaritons. Unfortunately, in the infrared where these systems operate, the mismatch between the surface-mode frequency and the semiconductor gap reduces drastically the potential of this technology. Here we show that graphene-based hybrid photovoltaic cells can significantly enhance the generated power paving the way to a promising technology for an intensive production of electricity from waste heat.Comment: 5 pages, 4 figure

The JAK inhibitor tofacitinib suppresses synovial JAK1-STAT signalling in rheumatoid arthritis.

ObjectiveTofacitinib is an oral Janus kinase (JAK) inhibitor for the treatment of rheumatoid arthritis (RA). The pathways affected by tofacitinib and the effects on gene expression in situ are unknown. Therefore, tofacitinib effects on synovial pathobiology were investigated.MethodsA randomised, double-blind, phase II serial synovial biopsy study (A3921073; NCT00976599) in patients with RA with an inadequate methotrexate response. Patients on background methotrexate received tofacitinib 10 mg twice daily or placebo for 28 days. Synovial biopsies were performed on Days -7 and 28 and analysed by immunoassay or quantitative PCR. Clinical response was determined by disease activity score and European League Against Rheumatism (EULAR) response on Day 28 in A3921073, and at Month 3 in a long-term extension study (A3921024; NCT00413699).ResultsTofacitinib exposure led to EULAR moderate to good responses (11/14 patients), while placebo was ineffective (1/14 patients) on Day 28. Tofacitinib treatment significantly reduced synovial mRNA expression of matrix metalloproteinase (MMP)-1 and MMP-3 (p&lt;0.05) and chemokines CCL2, CXCL10 and CXCL13 (p&lt;0.05). No overall changes were observed in synovial inflammation score or the presence of T cells, B cells or macrophages. Changes in synovial phosphorylation of signal transducer and activator of transcription 1 (STAT1) and STAT3 strongly correlated with 4-month clinical responses (p&lt;0.002). Tofacitinib significantly decreased plasma CXCL10 (p&lt;0.005) at Day 28 compared with placebo.ConclusionsTofacitinib reduces metalloproteinase and interferon-regulated gene expression in rheumatoid synovium, and clinical improvement correlates with reductions in STAT1 and STAT3 phosphorylation. JAK1-mediated interferon and interleukin-6 signalling likely play a key role in the synovial response.Trial registration numberNCT00976599

Prediction of the Atomization Energy of Molecules Using Coulomb Matrix and Atomic Composition in a Bayesian Regularized Neural Networks

Exact calculation of electronic properties of molecules is a fundamental step for intelligent and rational compounds and materials design. The intrinsically graph-like and non-vectorial nature of molecular data generates a unique and challenging machine learning problem. In this paper we embrace a learning from scratch approach where the quantum mechanical electronic properties of molecules are predicted directly from the raw molecular geometry, similar to some recent works. But, unlike these previous endeavors, our study suggests a benefit from combining molecular geometry embedded in the Coulomb matrix with the atomic composition of molecules. Using the new combined features in a Bayesian regularized neural networks, our results improve well-known results from the literature on the QM7 dataset from a mean absolute error of 3.51 kcal/mol down to 3.0 kcal/mol.Comment: Under review ICANN 201