Reliable regulation in centralized control systems

This paper addresses the design of a reliable control system for a linear, asymptotically stable plant. Specifically, the considered problem consists in finding a regulator which guarantees asymptotic stability, signal tracking and disturbance rejection when all the instrumentation is operational, and ensures that these properties are preserved, to the maximum possible extent, when an arbitrary number of sensors and/or actuators faults occur, that is, some of the feedback loops open. With reference to a centralized control structure and exogenous signals with multiple poles on the imaginary axis, the paper supplies a necessary and sufficient condition for the problem to admit a solution, and a possible least order regulator.     

Enhancing augmented reality with cognitive and knowledge perspectives: a case study in museum exhibitions

ABSTRACT

In this paper, we present our results related to the definition of a methodology that combines augmented reality (AR) with semantic techniques for the creation of digital stories associated with museum exhibitions. In contrast to traditional AR approaches, we augment real-world elements by supplementing contents of a museum exhibition with additional inputs that provide new and different meanings. In this way we augment a cultural resource with respect to both its presentation and meaning. The methodology is framed in the cultural re-mediation theory and is grounded on a set of ontologies aimed at modelling a cultural resource and correlating it with external multimedia objects and resources. To provide an easy tool for the creation of museum narratives, the methodology makes use of a set of recognised practices widely adopted by museum curators that have been formalised through inference rules. The defined methodology has been experimented in a scenario related to Flemish paintings to validate the augmentation of cultural objects with two different approaches, the first basing on similarities and the second on dissimilarities.     

Formulations for an inventory routing problem

In this paper, we present and compare formulations for the inventory routing problem (IRP) where the demand of customers has to be served, over a discrete time horizon, by capacitated vehicles starting and ending their routes at a depot. The objective of the IRP is the minimization of the sum of inventory and transportation costs. The formulations include known and new mathematical programming formulations. Valid inequalities are also presented. The formulations are tested on a large set of benchmark instances. One of the most significant conclusions is that the formulations that use vehicle‐indexed variables are superior to the more compact, aggregate formulations.     

BETaaS: A Platform for Development and Execution of Machine-to-Machine Applications in the Internet of Things

Wireless Personal Communications - The integration of everyday objects into the Internet represents the foundation of the forthcoming Internet of Things (IoT). Smart objects will be the building...     

Chronic Hyperkaliemia in Chronic Kidney Disease: An Old Concern with New Answers

Increasing potassium intake ameliorates blood pressure (BP) and cardiovascular (CV) prognoses in the general population; therefore the World Health Organization recommends a high-potassium diet (90–120 mEq/day). Hyperkalaemia is a rare condition in healthy individuals due to the ability of the kidneys to effectively excrete dietary potassium load in urine, while an increase in serum K⁺ is prevalent in patients with chronic kidney disease (CKD). Hyperkalaemia prevalence increases in more advanced CKD stages, and is associated with a poor prognosis. This scenario generates controversy on the correct nutritional approach to hyperkalaemia in CKD patients, considering the unproven link between potassium intake and serum K⁺ levels. Another concern is that drug-induced hyperkalaemia leads to the down-titration or withdrawal of renin-angiotensin system inhibitors (RASI) and mineralocorticoids receptors antagonists (MRA) in patients with CKD, depriving these patients of central therapeutic interventions aimed at delaying CKD progression and decreasing CV mortality. The new K⁺-binder drugs (Patiromer and Sodium-Zirconium Cyclosilicate) have proven to be adequate and safe therapeutic options to control serum K⁺ in CKD patients, enabling RASI and MRA therapy, and possibly, a more liberal intake of fruit and vegetables.     

Gas Sensing of NiO‐SCCNT Core–Shell Heterostructures: Optimization by Radial Modulation of the Hole‐Accumulation Layer

Hierarchical core–shell (C–S) heterostructures composed of a NiO shell deposited onto stacked‐cup carbon nanotubes (SCCNTs) are synthesized by atomic layer deposition (ALD). A film of NiO particles (0.80–21.8 nm in thickness) is uniformly deposited onto the inner and outer walls of the SCCNTs. The electrical resistance of the samples is found to increase of many orders of magnitude with the increasing of the NiO thickness. The response of NiO–SCCNT sensors toward low concentrations of acetone and ethanol at 200 °C is studied. The sensing mechanism is based on the modulation of the hole‐accumulation region in the NiO shell layer upon chemisorption of the reducing gas molecules. The electrical conduction mechanism is further studied by the incorporation of an Al₂O₃ dielectric layer at NiO and SCCNT interfaces. The investigations on NiO–Al₂O₃–SCCNT, Al₂O₃–SCCNT, and NiO–SCCNT coaxial heterostructures reveal that the sensing mechanism is strictly related to the NiO shell layer. The remarkable performance of the NiO–SCCNT sensors toward acetone and ethanol benefits from the conformal coating by ALD, large surface area of the SCCNTs, and the optimized p‐NiO shell layer thickness followed by the radial modulation of the space‐charge region.     

Oxidative Stress and Chemoradiation-Induced Oral Mucositis: A Scoping Review of In Vitro,In Vivo and Clinical Studies

Chemoradiation-induced mucositis is a debilitating condition of the gastrointestinal tract eventuating from antineoplastic treatment. It is believed to occur primarily due to oxidative stress mechanisms, which generate Reactive Oxygen Species (ROS). The aim of this scoping review was to assess the role of oxidative stress in the development of Oral Mucositis (OM). Studies from the literature, published in MEDLINE and SCOPUS, that evaluated the oxidative stress pathways or antioxidant interventions for OM, were retrieved to elucidate the current understanding of their relationship. Studies failing inclusion criteria were excluded, and those suitable underwent data extraction, using a predefined data extraction table. Eighty-nine articles fulfilled criteria, and these were sub-stratified into models of study (in vitro, in vivo, or clinical) for evaluation. Thirty-five clinical studies evaluated antioxidant interventions on OM’s severity, duration, and pain, amongst other attributes. A number of clinical studies sought to elucidate the protective or therapeutic effects of compounds that had been pre-determined to have antioxidant properties, without directly assessing oxidative stress parameters (these were deemed “indirect evidence”). Forty-seven in vivo studies assessed the capacity of various compounds to prevent OM. Findings were mostly consistent, reporting reduced OM severity associated with a reduction in ROS, malondialdehyde (MDA), myeloperoxidase (MPO), but higher glutathione (GSH) and superoxide dismutase (SOD) activity or expression. Twenty-one in vitro studies assessed potential OM therapeutic interventions. The majority demonstrated successful a reduction in ROS, and in select studies, secondary molecules were assessed to identify the mechanism. In summary, this review highlighted numerous oxidative stress pathways involved in OM pathogenesis, which may inform the development of novel therapeutic targets.     

Targeting CD10 on B-Cell Leukemia Using the Universal CAR T-Cell Platform (UniCAR)

Chimeric antigen receptor (CAR)-expressing T-cells are without a doubt a breakthrough therapy for hematological malignancies. Despite their success, clinical experience has revealed several challenges, which include relapse after targeting single antigens such as CD19 in the case of B-cell acute lymphoblastic leukemia (B-ALL), and the occurrence of side effects that could be severe in some cases. Therefore, it became clear that improved safety approaches, and targeting multiple antigens, should be considered to further improve CAR T-cell therapy for B-ALL. In this paper, we address both issues by investigating the use of CD10 as a therapeutic target for B-ALL with our switchable UniCAR system. The UniCAR platform is a modular platform that depends on the presence of two elements to function. These include UniCAR T-cells and the target modules (TMs), which cross-link the T-cells to their respective targets on tumor cells. The TMs function as keys that control the switchability of UniCAR T-cells. Here, we demonstrate that UniCAR T-cells, armed with anti-CD10 TM, can efficiently kill B-ALL cell lines, as well as patient-derived B-ALL blasts, thereby highlighting the exciting possibility for using CD10 as an emerging therapeutic target for B-cell malignancies.     

Probabilistic topic models for sequence data

Probabilistic topic models are widely used in different contexts to uncover the hidden structure in large text corpora. One of the main (and perhaps strong) assumption of these models is that generative process follows a bag-of-words assumption, i.e. each token is independent from the previous one. We extend the popular Latent Dirichlet Allocation model by exploiting three different conditional Markovian assumptions: (i) the token generation depends on the current topic and on the previous token; (ii) the topic associated with each observation depends on topic associated with the previous one; (iii) the token generation depends on the current and previous topic. For each of these modeling assumptions we present a Gibbs Sampling procedure for parameter estimation. Experimental evaluation over real-word data shows the performance advantages, in terms of recall and precision, of the sequence-modeling approaches.