We study some Gaussian models for anomalous diffusion, which include the time-rescaled Brownian motion, two types of fractional Brownian motion, and models associated with fractional Brownian motion based on the generalized Langevin equation. Gaussian processes associated with these models satisfy the anomalous diffusion relation which requires the mean-square displacement to vary with t(alpha), 0

We introduce an Lq(Lp)-theory for the quasi-linear fractional equations of the typeHere, α ∈ (0, 2), p, q > 1, and ∂ α t is the Caupto fractional derivative of order α. Uniqueness, existence, and Lq(Lp)-estimates of solutions are obtained. The leading coefficients a ij (t, x) are assumed to be piecewise continuous in t and uniformly continuous in x. In particular a ij (t, x) are allowed to be discontinuous with respect to the time variable. Our approach is based on classical tools in PDE theories such as the Marcinkiewicz interpolation theorem, the Calderon-Zygmund theorem, and perturbation arguments.2010 Mathematics Subject Classification. 45D05, 45K05, 45N05, 35B65, 26A33.

No abstract

No abstract

The Health Promotion Board (HPB) has developed the Clinical Practice Guidelines (CPG) on Obesity to provide health professionals in Singapore with recommendations for evidence-based interventions for obesity. This article summarises the introduction, epidemiology and executive summary of the key recommendations from the HPB-MOH CPG on Obesity for the information of SMJ readers. The chapters and page numbers mentioned in the reproduced extract refer to the full text of the guidelines, which are available from the Health Promotion Board website: http://www.hpb.gov.sg/cpg-obesity. The recommendations should be used with reference to the full text of the guidelines. Following this article are multiple choice questions based on the full text of the guidelines.

Cytokines of the interleukin-1 (IL-1) family, such as IL-1α/β and IL-18, have pleiotropic activities in innate and adaptive immune responses in host defense and diseases. Insight into their biological functions helped develop novel therapeutic approaches to treat human inflammatory diseases. IL-33 is an important member of the IL-1 family of cytokines and is a ligand of the ST2 receptor, a member of the IL-1 receptor family. However, the role of the IL-33/ST2 axis in tumor growth and metastasis of breast cancer remains unclear. Here, we demonstrate that IL-33 is a critical tumor promoter during epithelial cell proliferation and tumorigenesis in the breast. IL-33 dose- and time-dependently increased Cancer Osaka Thyroid (COT) phosphorylation via ST2-COT interaction in normal epithelial and breast cancer cells. The IL-33/ST2/COT cascade induced the activation of the MEK-ERK (MEK-extracellular signal-regulated kinase), JNK-cJun (cJun N-terminal kinase-cJun) and STAT3 (signal transducer and activator of transcription 3) signaling pathways, followed by increased AP-1 and stat3 transcriptional activity. When small interfering RNAs of ST2 and COT were introduced into cells, IL-33-induced AP-1 and stat3 activity were significantly decreased, unlike that in the control cells. The inhibition of COT activity resulted in decreased IL-33-induced epithelial cell transformation, and knockdown of IL-33, ST2 and COT in breast cancer cells attenuated tumorigenicity of breast cancer cells. Consistent with these observations, ST2 levels were positively correlated with COT expression in human breast cancer. These findings provide a novel perspective on the role of the IL-33/ST2/COT signaling pathway in supporting cancer-associated inflammation in the tumor microenvironment. Therapeutic approaches that target this pathway may, therefore, effectively inhibit carcinogenesis in the breast.

In this paper, we propose an uncertainty-aware learning from demonstration method by presenting a novel uncertainty estimation method utilizing a mixture density network appropriate for modeling complex and noisy human behaviors. The proposed uncertainty acquisition can be done with a single forward path without Monte Carlo sampling and is suitable for real-time robotics applications. Then, we show that it can be can be decomposed into explained variance and unexplained variance where the connections between aleatoric and epistemic uncertainties are addressed. The properties of the proposed uncertainty measure are analyzed through three different synthetic examples, absence of data, heavy measurement noise, and composition of functions scenarios. We show that each case can be distinguished using the proposed uncertainty measure and presented an uncertainty-aware learning from demonstration method of an autonomous driving using this property. The proposed uncertainty-aware learning from demonstration method outperforms other compared methods in terms of safety using a complex real-world driving dataset.

This study describes Chromobacterium violaceum's use of extracellular membrane vesicles (MVs) to both solubilize and transport violacein to other microorganisms. Violacein is a hydrophobic bisindole with known antibiotic activities against other microorganisms. Characterization of the MVs found they carried more violacein than protein (1.37 AE 0.19-fold), suggesting they may act as a reservoir for this compound. However, MVs are not produced in response to violaceina ΔvioA isogenic mutant, which is incapable of making violacein, actually produced significantly more MVs (3.2-fold) than the wild-type strain. Although violacein is insoluble in water (Log P octanol: water = 3.34), 79.5% remained in the aqueous phase when it was present within the C. violaceum MVs, an increase in solubility of 1740-fold. Moreover, tests with a strain of Staphylococcus aureus showed MVassociated violacein is bactericidal, with 3.