Augmented Lagrangian Pattern Search Based Multi‐Agent Model Predictive Control of Rhine‐Meuse Delta

In Large Scale Systems the concept of centrality fails due to the lack of centralized computing capability. The control of such systems has to be performed using multiple control agents. In this case, the matter of interactions among neighboring subsystems needs to be considered. In this paper, a water control system in the Netherlands is studied as a real large scale system. A multi‐agent scheme is applied to control the flow through the system which is decomposed into two interconnected subsystems. Each agent employs a model‐based predictive control (MPC) technique. The model of this large scale system is nonlinear and nonconvex. Therefore, an augmented Lagrangian pattern search optimization algorithm is used to implement multi‐agent MPC for this system. This proposed algorithm is applied by each control agent to solve its own interconnected optimization problem, at each subsystem of whole the water system. Simulation results show the effectiveness of the proposed approach.     

Current status and future forecasting of biofuels technology development

Over the last few decades, the significant increase in energy demand followed by increasing fossil fuels depletion convinced countries authority to choose renewable energy to satisfy demand. Therefore, global enthusiasm in renewable energy such as bioenergy technology is increased. Is biofuels technology ready to address the global demand for energy? Investigating in technology development can answer. In this paper, the current statuses of biofuel technologies are determined. Regarding patent codes, seven technologies are identified, which are CHP turbines for biofeed, gas turbine for biofeed, biodiesel, grain bioethanol, bio‐pyrolysis, torrefaction of biomass, and cellulosic bioethanol. The results of patent investigating show that the biodiesel technology is in the mature status and its technology trend is going to go downward. The others six technologies are in the growth stage. Analysis of 57 619 patents in biofuel technologies for technology forecasting has been done by technology life cycle. The torrefication of biomass technology has started its growth stages and will become mature in 2061. In this research, the S‐curves of all biofuel groups are plotted and maturity phases are forecasted.     

A multi‐predictor model to estimate solar and wind energy generations

Recent technological developments in renewable energy systems and significant growth of solar and wind energy have made these 2 renewable sources potential viable alternatives for conventional energy sources. However, due to intermittent nature, their reliability and availability are not similar to traditional sources. Hence, it is crucial to estimate the solar and wind availability and contribution more accurately. There are various factors affecting the generation capacity of renewable sources. There has been a vast research on the impact of factors related to climate condition such as wind speed, air temperature, and humidity on renewable energy generation. However, there are several other factors with indirect impact on renewable capacity and generation mostly overshadowed by the climate factors. In this study, a multi‐predictor regression model is developed and presented for solar and wind energy generation capacity across the USA. Our study of 50 states shows how the generation capacity can be affected by several indexes including human development index. Variables with the more significant impacts have been chosen using a regression analysis. A recommendation on the best transformation of the response variables and sensitivity analysis of the results has also been presented. The results provide a model to estimate the generation capacity using significant predictors. For instance, the impact of population growth on the wind turbine generation can be explored using these models.     

Physically crosslinked polyvinyl alcohol/chitosan/gum tragacanth hydrogels loaded with vitamin E for wound healing applications

For the healing process, in this study, an innovative polymeric hydrogel network including polyvinyl alcohol (PVA)/chitosan (CS)/gum tragacanth (GT) loaded with vitamin E (VE) was produced by the freeze–thaw approach. In order to investigate the characteristics of the prepared samples, Fourier transform infrared spectroscopy (FTIR) and scanning electron microscope (SEM) analyzes were performed. Also, water vapor transmission rate (WVTR), swelling ratio, gel fraction and mechanical properties were measured. Then, to observe their cytocompatibility, MTT assay and cell adhesion studies were assessed. The results of FTIR confirmed the presence of PVA, CS, GT, and VE in hydrogel films. As well as, the SEM images showed the effect of the freezing and thawing method in creating a smooth surface with small and regular pores. It was found with adding the CS and GT to PVA improves swelling ratio, gel fraction, WVTR and elongation of hydrogel films. Further, in examining the adhesion and cytotoxicity of the samples, the non-toxic quiddity of the PVA/CS/GT hydrogel films was corroborated. In the end, the antibacterial properties revealed that the film containing GT and CS had the greatest antibacterial activity. According to the observed results, PVA/CS/GT hydrogel films loaded with VE can be good for wound healing applications.     

Modeling the release of food bioactive ingredients from carriers/nanocarriers by the empirical,semiempirical, and mechanistic models

The encapsulation process has been utilized in the field of food technology to enhance the technofunctional properties of food products and the delivery of nutraceutical ingredients via food into the human body. The latter application is very similar to drug delivery systems. The inherent sophisticated nature of release mechanisms requires the utilization of mathematical equations and statistics to predict the release behavior during the time. The science of mathematical modeling of controlled release has gained a tremendous advancement in drug delivery in recent years. Many of these modeling methods could be transferred to food. In order to develop and design enhanced food controlled/targeted bioactive release systems, understanding of the underlying physiological and chemical processes, mechanisms, and principles of release and applying the knowledge gained in the pharmaceutical field to food products is a big challenge. Ideally, by using an appropriate mathematical model, the formulation parameters could be predicted to achieve a specific release behavior. So, designing new products could be optimized. Many papers are dealing with encapsulation approaches and evaluation of the impact of process and the utilized system on release characteristics of encapsulated food bioactives, but still, there is no deep insight into the mathematical release modeling of encapsulated food materials. In this study, information gained from the pharmaceutical field is collected and discussed to investigate the probable application in the food industry.     

Comparison of practical methods for an efficient FPGA implementation of STAP

In this paper, practical methods for an efficient field programmable gate array (FPGA) implementation of space-time adaptive processing (STAP) are investigated and compared. The most important part for calculating the STAP weights is QR decomposition (QRD) which can be implemented using the modified Gram–Schmidt algorithm. Investigations show the method that uses QRD with less computational burden and leads to more effective implementation. Its structure parameterised with vector size to create a trade-off between hardware and performance factors. For this purpose, the modifications on QRD-MGS are performed in order to speed increasing. Then, the calculation of STAP weight vector was implemented. The implementation results show that decreasing vector size decreases the resources utilisation, computational burden and consumption power. However, computation time increases slightly, but the update rate of the STAP weights is maintained. For example, weights in the system with 6 antenna arrays, 10 received pulses and 200 range samples computed in 262 µs by vector size of 17 on the Arria10 FPGA the maximum of which is 155 µs are related to QRD-MGS and 107 µs is related to other parts. Therefore, QRD-MGS is the most important part in calculation of the STAP weight vector and its simplifying led to an efficient implementation.

Abbreviations: Computation time, Field programmable gate array, QR decomposition, Space time adaptive processing     

Estrogen Receptor Subtypes Elicit a Distinct Gene Expression Profile of Endothelial-Derived Factors Implicated in Atherosclerotic Plaque Vulnerability

In the presence of established atherosclerosis, estrogens are potentially harmful. MMP-2 and MMP-9, their inhibitors (TIMP-2 and TIMP-1), RANK, RANKL, OPG, MCP-1, lysyl oxidase (LOX), PDGF-β, and ADAMTS-4 play critical roles in plaque instability/rupture. We aimed to investigate (i) the effect of estradiol on the expression of the abovementioned molecules in endothelial cells, (ii) which type(s) of estrogen receptors mediate these effects, and (iii) the role of p21 in the estrogen-mediated regulation of the aforementioned factors. Human aortic endothelial cells (HAECs) were cultured with estradiol in the presence or absence of TNF-α. The expression of the aforementioned molecules was assessed by qRT-PCR and ELISA. Zymography was also performed. The experiments were repeated in either ERα- or ERβ-transfected HAECs and after silencing p21. HAECs expressed only the GPR-30 estrogen receptor. Estradiol, at low concentrations, decreased MMP-2 activity by 15-fold, increased LOX expression by 2-fold via GPR-30, and reduced MCP-1 expression by 3.5-fold via ERβ. The overexpression of ERα increased MCP-1 mRNA expression by 2.5-fold. In a low-grade inflammation state, lower concentrations of estradiol induced the mRNA expression of MCP-1 (3.4-fold) and MMP-9 (7.5-fold) and increased the activity of MMP-2 (1.7-fold) via GPR-30. Moreover, p21 silencing resulted in equivocal effects on the expression of the abovementioned molecules. Estradiol induced different effects regarding atherogenic plaque instability through different ERs. The balance of the expression of the various ER subtypes may play an important role in the paradoxical characterization of estrogens as both beneficial and harmful.     

Property investigation of polypropylene/multiwall carbon nanotube nanocomposites prepared via in situ polymerization

In this study, polypropylene/carbon nanotube nanocomposites were prepared via in situ polymerization using a bi‐supported Ziegler ? Natta catalytic system. In this system, magnesium ethoxide and multiwall carbon nanotubes (MWCNTs) are jointly used as catalyst supports. SEM images reveal the distribution and quite good dispersion of MWCNTs throughout the polypropylene (PP) matrix. The thermal properties of the samples were examined using DSC and TGA tests. The results show that the crystallization temperature of the nanocomposites significantly increases while the melting point is not markedly affected. In addition, the thermal stability is improved. The melt rheological properties of PP/MWCNT nanocomposites in the linear and nonlinear viscoelastic response regions were studied. An increment of the complex viscosity (η^*), storage modulus (G′) and loss modulus (G′′) and a decrement of the loss factor (tan δ) compared with neat PP are observed. Steady shear flow experiments show an increase in shear viscosity with increasing the MWCNT content. © 2013 Society of Chemical Industry     

PRMT5 Selective Inhibitor Enhances Therapeutic Efficacy of Cisplatin in Lung Cancer Cells

As a therapeutic approach, epigenetic modifiers have the potential to enhance the efficacy of chemotherapeutic agents. Protein arginine methyltransferase 5 (PRMT5), highly expressed in lung adenocarcinoma, was identified to be involved in tumorigenesis. In the current study, we examined the potential antineoplastic activity of PRMT5 inhibitor, arginine methyltransferase inhibitor 1 (AMI-1), and cisplatin on lung adenocarcinoma. Bioinformatic analyses identified apoptosis, DNA damage, and cell cycle progression as the main PRMT5-associated functional pathways, and survival analysis linked the increased PRMT5 gene expression to worse overall survival in lung adenocarcinoma. Combined AMI-1 and cisplatin treatment significantly reduced cell viability and induced apoptosis. Cell cycle arrest in A549 and DMS 53 cells was evident after AMI-1, and was reinforced after combination treatment. Western blot analysis showed a reduction in demethylation histone 4, a PRMT5- downstream target, after treatment with AMI-1 alone or in combination with cisplatin. While the combination approach tackled lung cancer cell survival, it exhibited cytoprotective abilities on HBEpC (normal epithelial cells). The survival of normal bronchial epithelial cells was not affected by using AMI-1. This study highlights evidence of novel selective antitumor activity of AMI-1 in combination with cisplatin in lung adenocarcinoma cells.