This paper introduces the robust internal-loop compensator based sliding mode control (SMRIC) scheme for multiple-input multiple-output (MIMO) nonlinear systems subjected to mismatched uncertainties, which are time-varying and non-vanishing with non-constant steady-state values. The proposed approach extends an application area of the robust internal-loop compensator (RIC), as well as a class of mismatched uncertainties that could be imposed on the system. The developed SMRIC technique allows substantial alleviation of the chattering phenomenon in the presence of disturbances while retaining the nominal performance of the system in the absence of disturbances. The stability analysis of the closed-loop system is performed using the Lyapunov-based approach. The proposed SMRIC method guarantees the finite-time convergence of the system trajectories to the sliding surface and provides asymptotic stability of the equilibrium. The simulation results of the numerical example and both simulation and experimental results of the application example show that the proposed SMRIC technique exhibits, in comparison with the concurrent algorithms, excellent tracking performance and robustness properties in the presence of modeling uncertainties, parameter variations, external disturbances, and mismatched uncertainties.

Objectives: To determine the epidemiological features of patients and animals after bites/scratches from rabies-suspected animals in Zenica-Doboj Canton, Bosnia and Herzegovina. Methods: Data from all patients (and the causative animals) admitted to the Antirabies Service of the Institute for Health and Food Safety Zenica in the 2009-2017 period were analyzed, including age, sex, anatomical site of the bite/scratch, animal type (stray/owned/wildlife), veterinary observations of the animal, and whether antirabies post-exposure prophylaxis (PEP) was indicated and/or administered. Results: In total, 1716 patients were admitted. Bites/scratches were most frequently recorded during April and May (n=181, 10.5% and n=163, 9.5%, respectively). The persons admitted were mostly from the Zenica municipality (n=1278, 74.5%; incidence: 11.55/ 1000), which is 66.6% urbanized. Males were more frequently represented (n=1089, 63.6%). The patients were mostly 50-64 and 25-49 years of age (n=425, 24.7% and n=390, 22.7%, respectively). Dog bites were the most common cause (n=1634, 95.1%, of which n=1258, 77.0% were caused by stray dogs). PEP was indicated for 997 (58.1%) patients. Only 340 (19.9%) animals underwent veterinary observations (3.1% of stray and 76.1% of owned animals). The largest number of injuries were presented at lower extremities, 1044 (60.8%) cases. Conclusions: Zenica-Doboj Canton is a rabies-free region. Due to the high rate of stray animals not undergoing veterinary observations, the non-existence of a unique dog registry, and the consequent lack of information about stray animals in terms of number, vaccination, neutering, and euthanasia, there is an urgent need for improving the prevention and control of rabies within the One Health framework.

Lentigo maligna (LM) is a melanoma in situ and the incidence is still rising in The Netherlands. LM is mostly located in the face, therefore radical surgical removal, which is the first choice of treatment, can be challenging in this delicate anatomical region. Staged excision is considered a useful alternative. The initial diagnosis of clinically suspicious LM is usually based on just one or a few biopsies, which may lead to reclassification into lentigo maligna melanoma (LMM) based on histological evaluation of the excision specimen. This article is protected by copyright. All rights reserved.

Genome-wide association studies (GWAS) have identified more than 170 breast cancer susceptibility loci. Here we hypothesize that some risk-associated variants might act in non-breast tissues, specifically adipose tissue and immune cells from blood and spleen. Using expression quantitative trait loci (eQTL) reported in these tissues, we identify 26 previously unreported, likely target genes of overall breast cancer risk variants, and 17 for estrogen receptor (ER)-negative breast cancer, several with a known immune function. We determine the directional effect of gene expression on disease risk measured based on single and multiple eQTL. In addition, using a gene-based test of association that considers eQTL from multiple tissues, we identify seven (and four) regions with variants associated with overall (and ER-negative) breast cancer risk, which were not reported in previous GWAS. Further investigation of the function of the implicated genes in breast and immune cells may provide insights into the etiology of breast cancer. Over 170 susceptibility loci have been identified by genome-wide association studies in breast cancer. Here, the authors interrogated the role of risk-associated variants from non-breast tissue, and using expression quantitative trait loci, identify potential target genes of known breast cancer susceptibility variants, as well as 11 regions not previously known to be associated with breast cancer risk.

Tractography is a family of algorithms that use diffusion-weighted magnetic resonance imaging data to reconstruct the white matter pathways of the brain. Although it has been proven to be particularly effective for studying non-invasively the neuronal architecture of the brain, recent studies have highlighted that the large incidence of false positive connections retrieved by these techniques can significantly bias any connectivity analysis. Some solutions have been proposed to overcome this issue and the ones relying on convex optimization framework showed a significant improvement. Here we propose an evolution of the Convex Optimization Modeling for Microstructure Informed Tractography (COMMIT) framework, that combines basic prior knowledge about brain anatomy with group-sparsity regularization into the optimization problem. We show that the new formulation dramatically reduces the incidence of false positives in synthetic DW-MRI data.

[This corrects the article DOI: 10.1155/2018/3078031.].