Model predictive-based secondary frequency control considering heat pump water heaters

The extensive development of renewable energies in power systems causes several problems due to intermittent output power generation. To tackle the challenge, demand response contribution to ancillary service is currently well recognized under the smart grid infrastructure. The application of the heat pump water heater (HPWH) as a controllable load in primary frequency control is well presented in the literature; however, the motivation of this paper is to use HPWHs for secondary frequency control. To this end, a model predictive control (MPC) method for a two-area power system incorporating HPWHs to contribute to secondary frequency control is proposed in this paper. A detailed model of HPWH is employed as a controllable load to control the power consumption during water heating. The MPC method predicts the future control signals using a quadratic programming-based optimization. It uses the system model, past inputs and outputs, as well as system control signals to predict the next signals. The effective performance of the proposed method for the two-area power system with HPWH is demonstrated for different scenarios of load changes, intermittent renewable power generation and parameter variations as the sensitivity analysis

Coordination of heat pumps, electric vehicles and AGC for efficient LFC in a smart hybrid power system via SCA-based optimized FOPID controllers

© 2018 by the authors. Licensee MDPI, Basel, Switzerland. Due to the high price of fossil fuels, the increased carbon footprint in conventional generation units and the intermittent functionality of renewable units, alternative sources must contribute to the load frequency control (LFC) of the power system. To tackle the challenge, dealing with controllable loads, the ongoing study aims at efficient LFC in smart hybrid power systems. To achieve this goal, heat pumps (HPs) and electric vehicles (EVs) are selected as the most effective controllable loads to contribute to the LFC issue. In this regard, the EVs can be controlled in a bidirectional manner as known charging and discharging states under a smart structure. In addition, regarding the HPs, the power consumption is controllable. As the main task, this paper proposes a fractional order proportional integral differential (FOPID) controller for coordinated control of power consumption in HPs, the discharging state in EVs and automatic generation control (AGC). The parameters of the FOPID controllers are optimized simultaneously by the sine cosine algorithm (SCA), which is a new method for optimization problems. In the sequel, four scenarios, including step and random load changes, aggregated intermittent generated power from wind turbines, a random load change scenario and a sensitivity analysis scenario, are selected to demonstrate the efficiency of the proposed SCA-based FOPID controllers in a hybrid two-area power system

Re-Expression of Poly/Oligo-Sialylated Adhesion Molecules on the Surface of Tumor Cells Disrupts Their Interaction with Immune-Effector Cells and Contributes to Pathophysiological Immune Escape

Glycans linked to surface proteins are the most complex biological macromolecules that play an active role in various cellular mechanisms. This diversity is the basis of cell–cell interaction and communication, cell growth, cell migration, as well as co-stimulatory or inhibitory signaling. Our review describes the importance of neuraminic acid and its derivatives as recognition elements, which are located at the outermost positions of carbohydrate chains linked to specific glycoproteins or glycolipids. Tumor cells, especially from solid tumors, mask themselves by re-expression of hypersialylated neural cell adhesion molecule (NCAM), neuropilin-2 (NRP-2), or synaptic cell adhesion molecule 1 (SynCAM 1) in order to protect themselves against the cytotoxic attack of the also highly sialylated immune effector cells. More particularly, we focus on α-2,8-linked polysialic acid chains, which characterize carrier glycoproteins such as NCAM, NRP-2, or SynCam-1. This characteristic property correlates with an aggressive clinical phenotype and endows them with multiple roles in biological processes that underlie all steps of cancer progression, including regulation of cell–cell and/or cell–extracellular matrix interactions, as well as increased proliferation, migration, reduced apoptosis rate of tumor cells, angiogenesis, and metastasis. Specifically, re-expression of poly/oligo-sialylated adhesion molecules on the surface of tumor cells disrupts their interaction with immune-effector cells and contributes to pathophysiological immune escape. Further, sialylated glycoproteins induce immunoregulatory cytokines and growth factors through interactions with sialic acid-binding immunoglobulin-like lectins. We describe the processes, which modulate the interaction between sialylated carrier glycoproteins and their ligands and illustrate that sialic acids could be targets of novel therapeutic strategies for treatment of cancer and immune diseases.publishedVersio

Re-Expression of Poly/Oligo-Sialylated Adhesion Molecules on the Surface of Tumor Cells Disrupts Their Interaction with Immune-Effector Cells and Contributes to Pathophysiological Immune Escape

Glycans linked to surface proteins are the most complex biological macromolecules that play an active role in various cellular mechanisms. This diversity is the basis of cell–cell interaction and communication, cell growth, cell migration, as well as co-stimulatory or inhibitory signaling. Our review describes the importance of neuraminic acid and its derivatives as recognition elements, which are located at the outermost positions of carbohydrate chains linked to specific glycoproteins or glycolipids. Tumor cells, especially from solid tumors, mask themselves by re-expression of hypersialylated neural cell adhesion molecule (NCAM), neuropilin-2 (NRP-2), or synaptic cell adhesion molecule 1 (SynCAM 1) in order to protect themselves against the cytotoxic attack of the also highly sialylated immune effector cells. More particularly, we focus on α-2,8-linked polysialic acid chains, which characterize carrier glycoproteins such as NCAM, NRP-2, or SynCam-1. This characteristic property correlates with an aggressive clinical phenotype and endows them with multiple roles in biological processes that underlie all steps of cancer progression, including regulation of cell–cell and/or cell–extracellular matrix interactions, as well as increased proliferation, migration, reduced apoptosis rate of tumor cells, angiogenesis, and metastasis. Specifically, re-expression of poly/oligo-sialylated adhesion molecules on the surface of tumor cells disrupts their interaction with immune-effector cells and contributes to pathophysiological immune escape. Further, sialylated glycoproteins induce immunoregulatory cytokines and growth factors through interactions with sialic acid-binding immunoglobulin-like lectins. We describe the processes, which modulate the interaction between sialylated carrier glycoproteins and their ligands and illustrate that sialic acids could be targets of novel therapeutic strategies for treatment of cancer and immune diseases.publishedVersio

Measurement-induced state transitions in a superconducting qubit: Beyond the rotating wave approximation

Many superconducting qubit systems use the dispersive interaction between the qubit and a coupled harmonic resonator to perform quantum state measurement. Previous works have found that such measurements can induce state transitions in the qubit if the number of photons in the resonator is too high. We investigate these transitions and find that they can push the qubit out of the two-level subspace, and that they show resonant behavior as a function of photon number. We develop a theory for these observations based on level crossings within the Jaynes-Cummings ladder, with transitions mediated by terms in the Hamiltonian that are typically ignored by the rotating wave approximation. We find that the most important of these terms comes from an unexpected broken symmetry in the qubit potential. We confirm the theory by measuring the photon occupation of the resonator when transitions occur while varying the detuning between the qubit and resonator

Activating Natural Killer Cell Receptors, Selectins, and Inhibitory Siglecs Recognize Ebolavirus Glycoprotein

Expression of the extensively glycosylated Ebolavirus glycoprotein (EBOV-GP) induces physical alterations of surface molecules and plays a crucial role in viral pathogenicity. Here we investigate the interactions of EBOV-GP with host surface molecules using purified EBOV-GP, EBOV-GP-transfected cell lines, and EBOV-GP-pseudotyped lentiviral particles. Subsequently, we wanted to examine which receptors are involved in this recognition by binding studies to cells transfected with the EBOV-GP as well as to recombinant soluble EBOV-GP. As the viral components can also bind to inhibitory receptors of immune cells (e.g., Siglecs, TIM-1), they can even suppress the activity of immune effector cells. Our data show that natural killer (NK) cell receptors NKp44 and NKp46, selectins (CD62E/P/L), the host factors DC-SIGNR/DC-SIGN, and inhibitory Siglecs function as receptors for EBOV-GP. Our results show also moderate to strong avidity of homing receptors (P-, L-, and E-selectin) and DC-SIGNR/DC-SIGN to purified EBOV-GP, to cells transfected with EBOV-GP, as well as to the envelope of a pseudotyped lentiviral vector carrying the EBOV-GP. The concomitant activation and inhibition of the immune system exemplifies the evolutionary antagonism between the immune system and pathogens. Altogether these interactions with activating and inhibitory receptors result in a reduced NK cell-mediated lysis of EBOV-GP-expressing cells. Modulation of these interactions may provide new strategies for treating infections caused by this virus.publishedVersio

Application of Linear Discriminant Analysis in Dimensionality Reduction for Hand Motion Classification

The classification of upper-limb movements based on surface electromyography (EMG) signals is an important issue in the control of assistive devices and rehabilitation systems. Increasing the number of EMG channels and features in order to increase the number of control commands can yield a high dimensional feature vector. To cope with the accuracy and computation problems associated with high dimensionality, it is commonplace to apply a processing step that transforms the data to a space of significantly lower dimensions with only a limited loss of useful information. Linear discriminant analysis (LDA) has been successfully applied as an EMG feature projection method. Recently, a number of extended LDA-based algorithms have been proposed, which are more competitive in terms of both classification accuracy and computational costs/times with classical LDA. This paper presents the findings of a comparative study of classical LDA and five extended LDA methods. From a quantitative comparison based on seven multi-feature sets, three extended LDA-based algorithms, consisting of uncorrelated LDA, orthogonal LDA and orthogonal fuzzy neighborhood discriminant analysis, produce better class separability when compared with a baseline system (without feature projection), principle component analysis (PCA), and classical LDA. Based on a 7-dimension time domain and time-scale feature vectors, these methods achieved respectively 95.2% and 93.2% classification accuracy by using a linear discriminant classifier

Computational Fluid Dynamics Simulation of Gas-Solid Hydrodynamics in a Bubbling Fluidized-Bed Reactor: Effects of Air Distributor, Viscous and Drag Models

In this work, we employed a computational fluid dynamics (CFD)-based model with a Eulerian multiphase approach to simulate the fluidization hydrodynamics in biomass gasification processes. Air was used as the gasifying/fluidizing agent and entered the gasifier at the bottom which subsequently fluidized the solid particles inside the reactor column. The momentum exchange related to the gas-phase was simulated by considering various viscous models (i.e., laminar and turbulence models of the re-normalisation group (RNG), k-ε and k-ω). The pressure drop gradient obtained by employing each viscous model was plotted for different superficial velocities and compared with the experimental data for validation. The turbulent model of RNG k-Ɛ was found to best represent the actual process. We also studied the effect of air distributor plates with different pore diameters (2, 3 and 5 mm) on the momentum of the fluidizing fluid. The plate with 3-mm pores showed larger turbulent viscosities above the surface. The effects of drag models (Syamlal–O’Brien, Gidaspow and energy minimum multi-scale method (EMMS) on the bed’s pressure drop as well as on the volume fractions of the solid particles were investigated. The Syamlal–O’Brien model was found to forecast bed pressure drops most consistently, with the pressure drops recorded throughout the experimental process. The formation of bubbles and their motion along the gasifier height in the presence of the turbulent flow was seen to follow a different pattern from with the laminar flow.Ministry of Higher Education (MOHE) Malaysia; Engineering and Physical Sciences Research Counci

Does high-dose metformin cause lactic acidosis in type 2 diabetic patients after CABG surgery? A double blind randomized clinical trial

Metformin is a dimethyl biguanide oral anti-hyperglycemic agent. Lactic acidosis due to metformin is a fatal metabolic condition that limits its use in patients in poor clinical condition, consequently reducing the number of patients who benefit from this medication. In a double blind randomized clinical trial, we investigated 200 type 2 diabetic patients after coronary artery bypass surgery in the open heart ICU of the Mazandaran Heart Center, and randomly assigned them to equal intervention and control groups. The intervention group received regular insulin infusion along with 2 metformin 500 mg tablets every twelve hours, while the control group received only intravenous insulin with 2 placebo tablets every twelve hours. Lactate level, pH, base excess, blood glucose and serum creatinine were measured over five 12 h periods, with data averaged for each period. The primary outcome in this study was high lactate levels. Comparison between the 2 groups was made by independent Student’s t-test. To compare changes in multiple measures in each group and analysis of group interaction, a repeated measurement ANOVA test was used