Cost-efficient parallel programs based on set-distributions for polynomial interpolation

The paper presents parallel algorithms for Lagrange and Hermite interpolation methods formally derived from specifications, and using set-distributions. Set-distributions are based on set-valued mappings, and they assign a data object to more than one process. The derivation from specifications assures the correctness, and the set-distributions assure the efficiency of the programs. The obtained parallel algorithms have very good time complexities and speeds-up, and they are also cost-efficient. We consider the number of processes p to be a parameter of the algorithms, so, bounded parallelism is considered. The derivation of the algorithms is not ruled by any particular interconnection network. The possible mappings on different networks could be evaluated. The performance analysis is done considering a full-connected network, and other two interconnection networks: hypercube and multi-mesh hypercube, which preserve the cost-efficiency of the algorithms.     

Causal fault detection and isolation based on a set-membership approach

This paper presents a diagnostic methodology relying on a set-membership approach for fault detection and on a causal model for fault isolation. Set-membership methods are a promising approach to fault detection because they take into account a priori knowledge of model uncertainties and measurement errors. Every uncertain model parameter and/or measurement is represented by a bounded variable. In this paper, detection consists of verifying the membership of measurements to an interval. First order discrete time models are used and their output is explicitly computed with interval arithmetic. Fault isolation relies on a causal analysis and the exoneration principle, which allows focusing the consistency tests on simple local models. The isolation strategy consists of two steps: performing minimal tests found with the causal graph and determining on line additional relevant tests that reduce the final diagnosis. An application for a nuclear process is used in order to illustrate the method's efficiency.     

Computing non-fragile PI controllers for delay models of TCP/AQM networks

This article focuses on the stabilisation problem of fluid-flow delay models of transmission control protocol/active queue management (TCP/AQM) networks by using a proportional-integral (PI) controller as AQM strategy. More precisely, the complete set of PI controllers that exponentially stabilises the corresponding linear time-delay system is derived. Using the particular geometric properties of this set of the controller parameters, the issues of robustness to uncertainty in the network parameters and to perturbation in the controller coefficients are addressed. Then, a methodology to compute a non-fragile PI AQM controller is provided. Finally, exponential estimates for the closed-loop system solutions, allowing to evaluate the performance of the corresponding PI-controlled closed-loop system, are proposed by using a Lyapunov–Krasovskii functional approach. An illustrative example completes the presentation.     

Robust stabilization for uncertain time-delay systems containingsaturating actuators

A class of uncertain time-delay systems containing a saturating actuator is considered. These systems are characterized by delayed state equations (including a saturating actuator) with norm-bounded parameter uncertainty (possibly time varying) in the state and input matrices. The delay is assumed to be constant bounded but unknown. Using a Razumikhin approach for the stability of functional differential equations, upper bounds on the time delay are given such that the considered uncertain system is robustly stabilizable, in the case of constrained input, via memoryless state feedback control laws. These bounds are given in terms of solutions of appropriate finite dimensional Riccati equations     

On state-constrained porous-media systems with gradient-type multiplicative noise

The aim of the present paper is to provide necessary and sufficient conditions to maintain a stochastic coupled system with porous media components and gradient-type noise in a prescribed set of constraints by using internal controls. This work is a complementary contribution to the results obtained by the same authors, also on the viability problem associated to the porous media equation, but with Lipschitz noise. Second, the present paper provides a different framework in which the quasi-tangency condition can be obtained with optimal speed. In comparison with the aforementioned result, and from a technical point of view, here, we transform the stochastic system into a random-PDE one, via the rescaling approach, and then we study the viability of random sets. As an application, (stronger) conditions for the stabilization of the stochastic porous media equations are obtained. These are illustrated on a simple example.     

Supplementation of the diet with the functional fiber PolyGlycoplex? is well tolerated by healthy subjects in a clinical trial

Background  

The relationship of dietary fiber to overall health is of great importance, as beneficial effects have been demonstrated with the use of fiber from diverse sources, some traditional, other novel. PolyGlycopleX^? (PGX^?) is a unique proprietary product composed of three water-soluble polysaccharides, that when processed using novel technology give rise to a final product – a soluble, highly viscous functional fiber.     

The Roles of Imaging Biomarkers in the Management of Chronic Neuropathic Pain

Chronic neuropathic pain (CNP) affects around 10% of the general population and has a significant social, emotional, and economic impact. Current diagnosis techniques rely mainly on patient-reported outcomes and symptoms, which leads to significant diagnostic heterogeneity and subsequent challenges in management and assessment of outcomes. As such, it is necessary to review the approach to a pathology that occurs so frequently, with such burdensome and complex implications. Recent research has shown that imaging methods can detect subtle neuroplastic changes in the central and peripheral nervous system, which can be correlated with neuropathic symptoms and may serve as potential markers. The aim of this paper is to review available imaging methods used for diagnosing and assessing therapeutic efficacy in CNP for both the preclinical and clinical setting. Of course, further research is required to standardize and improve detection accuracy, but available data indicate that imaging is a valuable tool that can impact the management of CNP.     

Temporomandibular Joint Osteoarthritis: Pathogenic Mechanisms Involving the Cartilage and Subchondral Bone,and Potential Therapeutic Strategies for Joint Regeneration

The temporomandibular joint (TMJ) is a specialized synovial joint that is crucial for the movement and function of the jaw. TMJ osteoarthritis (TMJ OA) is the result of disc dislocation, trauma, functional overburden, and developmental anomalies. TMJ OA affects all joint structures, including the articular cartilage, synovium, subchondral bone, capsule, ligaments, periarticular muscles, and sensory nerves that innervate the tissues. The present review aimed to illustrate the main pathomechanisms involving cartilage and bone changes in TMJ OA and some therapeutic options that have shown potential restorative properties regarding these joint structures in vivo. Chondrocyte loss, extracellular matrix (ECM) degradation, and subchondral bone remodeling are important factors in TMJ OA. The subchondral bone actively participates in TMJ OA through an abnormal bone remodeling initially characterized by a loss of bone mass, followed by reparative mechanisms that lead to stiffness and thickening of the condylar osteochondral interface. In recent years, such therapies as intraarticular platelet-rich plasma (PRP), hyaluronic acid (HA), and mesenchymal stem cell-based treatment (MSCs) have shown promising results with respect to the regeneration of joint structures or the protection against further damage in TMJ OA. Nevertheless, PRP and MSCs are more frequently associated with cartilage and/or bone repair than HA. According to recent findings, the latter could enhance the restorative potential of other therapies (PRP, MSCs) when used in combination, rather than repair TMJ structures by itself. TMJ OA is a complex disease in which degenerative changes in the cartilage and bone develop through intricate mechanisms. The regenerative potential of such therapies as PRP, MSCs, and HA regarding the cartilage and subchondral bone (alone or in various combinations) in TMJ OA remains a matter of further research, with studies sometimes obtaining discrepant results.     

Mitochondrial DNA Together with miR-142-3p in Plasma Can Predict Unfavorable Outcomes in Patients after Acute Myocardial Infarction

Myocardial infarction is one of the leading causes of death worldwide, despite numerous efforts to find efficient prognostic biomarkers and treatment targets. In the present study, we aimed to assess the potential of six microRNAs known to be involved in cardiovascular diseases, cell-free DNA (cfDNA), and mitochondrial DNA (mtDNA) circulating in plasma to be used as prognostic tools for the occurrence of unfavorable outcomes such as major adverse cardiovascular events (MACE) after acute ST-segment elevation myocardial infarction (STEMI). Fifty STEMI patients were enrolled and monitored for 6 months for the occurrence of MACE. Plasma was collected at three time points: upon admission to hospital (T₀), at discharge from hospital (T₁), and 6 months post-STEMI (T₆). Plasma levels of miR-223-3p, miR-142-3p, miR-155-5p, miR-486-5p, miR-125a-5p, and miR-146a-5p, as well as of cfDNA and mtDNA, were measured by RT-qPCR. Results showed that the levels of all measured miRNAs, as well as of cfDNA and mtDNA, were the most increased at T₁, compared to the other two time points. In the plasma of STEMI patients with MACE compared to those without MACE, we determined increased levels of miRNAs, cfDNA, and mtDNA at T_1. Hence, we used the levels of all measured parameters at T₁ for further statistical analysis. Statistical analysis demonstrated that all six miRNAs and cfDNA plus mtDNA levels, respectively, were associated with MACE. The minimal statistical model that could predict MACE in STEMI patients was the combination of mtDNA and miR-142-3p levels, as evidenced by ROC analysis (AUC = 0.97, p < 0.001). In conclusion, the increased plasma levels of mtDNA, along with miR-142-3p, could be used to predict unfavorable outcomes in STEMI patients.     

Reactive Oxygen Species and Long Non-Coding RNAs,an Unexpected Crossroad in Cancer Cells

Long non-coding RNAs (lncRNA) have recently been identified as key regulators of oxidative stress in several malignancies. The level of reactive oxygen species (ROS) must be constantly regulated to maintain cancer cell proliferation and chemoresistance and to prevent apoptosis. This review will discuss how lncRNAs alter the ROS level in cancer cells. We will first describe the role of lncRNAs in the nuclear factor like 2 (Nrf-2) coordinated antioxidant response of cancer cells. Secondly, we show how lncRNAs can promote the Warburg effect in cancer cells, thus shifting the cancer cell’s “building blocks” towards molecules important in oxidative stress regulation. Lastly, we explain the role that lncRNAs play in ROS-induced cancer cell apoptosis and proliferation.