Reinforcement learning movement path for multiple mobile sinks in wireless sensor networks

Mobile sink nodes play a very active role in wireless sensor network (WSN) routing. Because hiring these nodes can decrease the energy consumption of each node, end-to-end delay, and network latency significantly. Therefore, mobile sinks can soar the network lifetime dramatically. Generally, there are three movement paths for a mobile sink, which are as follows: (1) Random/stochastic, (2) controlled, and (3) fixed/ predictable/predefined paths. In this paper, a novel movement path is introduced as a fourth category of movement paths for mobile sinks. This path is based on deep learning, so a mobile sink node can go to the appropriate region that has more data at a suitable time. Thereupon, WSN routing can improve very much in terms of end-to-end delay, network latency, network lifetime, delivery ratio, and energy efficiency. The new proposed routing suggests a reinforcement learning movement path (RLMP) for multiple mobile sinks. The network in the proposed work consists of a couple of regions; each region can be employed for a special purpose, so this method is hired for any application and any size of the network. All simulations in this paper are done by network simulator 3 (NS-3). The experimental results clearly show that the RLMP overcomes other approaches by at least 32.48% in the network lifetime benchmark.     

The Growth‐Inhibiting Effects of Beef Fatty Acids on MCF‐7 Cells Are Influenced Mostly by the Depot Location and Inconsistently by the Biohydrogenation Intermediate Content

Biohydrogenation intermediates (BHI) including conjugated linoleic acid (CLA) isomers are formed during ruminal biohydrogenation of polyunsaturated fatty acids (PUFA) in ruminants. Although many studies have examined the anticarcinogenic effects of CLA, few studies have reported the anticarcinogenic properties of BHI in their natural form found in dairy and beef fats. The present study compared the growth‐inhibitory effects of fatty acids from beef perirenal fat (PRF) or subcutaneous fat (SCF) with low or high levels of BHI in MCF‐7 human breast cancer cells. Cells were exposed for 72 h to media containing increasing doses (50 to 400 μM) of different beef fat treatments. Fatty‐acid analysis showed that BHI were readily incorporated into cell phospholipids (PL) in a treatment‐dependent manner, but higher BHI in PL did not consistently inhibit growth. Culturing with low‐BHI PRF or high‐BHI PRF did not lead to growth inhibition, but low‐BHI SCF inhibited growth, and inhibition was further increased by high‐BHI SCF. Other classes of fatty acids may, therefore, be interacting with BHI resulting in differential effects on growth inhibition in human breast cancer cells.     

Crystallization kinetics study of dynamically vulcanized PA6/NBR/HNTs nanocomposites by nonisothermal differential scanning calorimetry

Investigation of crystallization behavior and kinetics of thermoplastic elastomer nanocomposites was the subject of limited works because of complexities associated with semiexperimental modeling of such phenomenon in a system containing components having completely different behavior in the molten state. Nonisothermal crystallization kinetics of dynamically vulcanized PA6/NBR/HNTs thermoplastic elastomer nanocomposites was mathematically modeled applying well‐known Avrami, Ozawa, and Mo theoretical models to the differential scanning calorimetry data gathered at various cooling rates. It was found that HNTs contribute as nucleating agents to the crystallization kinetics and cause acceleration of crystallization. Activation energy of the crystallization was calculated by correlating the crystallization peak temperature with the cooling rate using Kissinger model. It was found that Mo equation could properly describe nonisothermal crystallization kinetics of the PA6/NBR/HNTs thermoplastic elastomer nanocomposites. This was recognized from the obtained parameters of Mo equation in terms of HNTs loading level, which suggested a higher rate for dynamic crystallization. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2018 , 135, 46488.     

Compaction of LiBH4-LiAlH4 nanoconfined in activated carbon nanofibers: Dehydrogenation kinetics,reversibility, and mechanical stability during cycling

To enhance volumetric hydrogen capacity for on-board fuel cells, compaction of LiAlH₄-LiBH₄ nanoconfined in activated carbon nanofibers (ACNF) is for the first time proposed. Loose powders of milled and nanoconfined LiAlH₄-LiBH₄ samples are compacted under 976 MPa to obtain the pellet samples with thickness and diameter of ～1.20–1.30 and 8.0 mm, respectively. Dehydrogenation temperature of milled LiAlH₄-LiBH₄ increases from 415 to 434 °C due to compaction, while those of both compacted and loose powder samples of nanoconfined LiAlH₄-LiBH₄ are lower at comparable temperature of 330–335 °C. Hydrogen content liberated from milled LiAlH₄-LiBH₄ pellet is 65% of theoretical capacity in the temperature range of 80–475 °C, while that of nanoconfined LiAlH₄-LiBH₄ pellet is up to 80% at lower temperature of 100–400 °C. Besides, nanoconfined LiAlH₄-LiBH₄ pellet shows significant reduction of activation energy (ΔE_A up to 69 kJ/mol H₂) as compared with milled sample. Significant enhancement of volumetric hydrogen storage capacity up to 64% (from 32.5 to 53.3 gH₂/L) is obtained from nanoconfined LiAlH₄-LiBH₄ pellet. Hydrogen content released and reproduced of nanoconfined LiAlH₄-LiBH₄ pellet are 67 and 50% of theoretical capacity, respectively, while those of milled LiAlH₄-LiBH₄ pellet are only 30 and 10%, respectively. Moreover, upon four hydrogen release and uptake cycles, nanoconfined LiAlH₄-LiBH₄ pellet can preserve its shape with slight cracks, suggesting good mechanical stability during cycling. Curvatures and fibrous structure woven on one another of ACNF in nanoconfined LiAlH₄-LiBH₄ pellet not only favor hydrogen permeability through pellet sample during de/rehydrogenation, resulting fast kinetics, but also reinforce the pellet shape during cycling under high temperature and pressure condition.     

Catalytic fast pyrolysis of sugarcane bagasse pith with HZSM-5 catalyst using tandem micro-reactor-GC-MS

Fast pyrolysis of biomass is praised as an efficient and feasible process to selectively convert lignocellulosic biomass into bio-fuels and bio-chemicals. Pith of sugarcane bagasse could be an attractive lignocellulosic waste from depithing process from pulp and paper mill, which can utilize for production of biofuel and added value products. In this study, we employed a tandem micro-reactor coupled with gas chromatography-mass spectroscopy to investigate the products distribution from pith of sugarcane bagasse via catalytic fast pyrolysis. In the operating conditions, pyrolysis temperature and HZSM-5 catalyst had significant effect on products and distributions. An increase in the pyrolysis temperature from 400°C to 550°C led to an increase in the yield of phenolic compounds (6.3%, w/w%), followed decrease at higher temperature. The maximum carboxylic acids (10.6%) and furfural (3.5%) were obtained at lower temperature. At presence of HZSM-5 catalyst, the selectivity of aromatics such as benzene, toluene, indene, and naphthalene were improved.     

Zwitterionic poly(carboxybetaine) microgels for enzyme (chymotrypsin) covalent immobilization with extended stability and activity

There is emerging evidence that biocompatible zwitterionic materials can prevent nonspecific interactions within protein systems and increase protein stability. Here, a zwitterionic microgel was synthesized from poly (carboxybetaine methyl methacrylate) (pCB) using an inverse emulsion, free radical polymerization reaction technique. The microgel was loaded with a model enzyme, α-chymotrypsin (ChT), using a post-fabrication loading technique. A reaction scheme was developed and studied for covalent immobilization of ChT within the microgel. Confocal laser microscopy studies showed that immobilized ChT (i-ChT) was distributed within the hydrogel. The enzyme-immobilized microgels showed excellent reusability (72% of its initial activity after 10 uses) and could undergo several freezing/drying/rehydration cycles while retaining enzymatic activity. The i-ChT activity, half-life, and conformational stability were studied at varying pH and temperatures with results compared to free ChT in buffer. ChT immobilized within pCB hydrogel showed increased enzymatic stability as observed by a 13°C increase in the temperature at which i-ChT loses activity compared to free ChT. Furthermore, enzyme half-life increased up to seven-fold for the pCB immobilized ChT, and the increased stability resulted in higher activity at elevated pH. The i-ChT was most active at pH of 8.5 and was partially active up to the pH of 10.2.     

Beef Fat Enriched with Polyunsaturated Fatty Acid Biohydrogenation Products Improves Insulin Sensitivity Without Altering Dyslipidemia in Insulin Resistant JCR:LA-cp Rats

The main dietary sources of trans fatty acids are partially hydrogenated vegetable oils (PHVO), and products derived from polyunsaturated fatty acid biohydrogenation (PUFA‐BHP) in ruminants. Trans fatty acid intake has historically been associated with negative effects on health, generating an anti‐trans fat campaign to reduce their consumption. The profiles and effects on health of PHVO and PUFA‐BHP can, however, be quite different. Dairy products naturally enriched with vaccenic and rumenic acids have many purported health benefits, but the putative benefits of beef fat naturally enriched with PUFA‐BHP have not been investigated. The objective of the present experiment was to determine the effects of beef peri‐renal fat (PRF) with differing enrichments of PUFA‐BHP on lipid and insulin metabolism in a rodent model of dyslipidemia and insulin resistance (JCR:LA‐cp rat). The results showed that 6 weeks of diet supplementation with beef PRF naturally enriched due to flaxseed (FS‐PRF) or sunflower‐seed (SS‐PRF) feeding to cattle significantly improved plasma fasting insulin levels and insulin sensitivity, postprandial insulin levels (only in the FS‐PRF) without altering dyslipidemia. Moreover, FS‐PRF but not SS‐PRF attenuated adipose tissue accumulation. Therefore, enhancing levels of PUFA‐BHP in beef PRF with FS feeding may be a useful approach to maximize the health‐conferring value of beef‐derived fats.     

Developing GEP tree-based,neuro-swarm,and whale optimization models for evaluation of bearing capacity of concrete-filled steel tube columns

The type of materials used in designing and constructing structures significantly affects the way the structures behave. The performance of concrete and steel, which are used as a composite in columns, has a considerable effect upon the structure behavior under different loading conditions. In this paper, several advanced methods were applied and developed to predict the bearing capacity of the concrete-filled steel tube (CFST) columns in two phases of prediction and optimization. In the prediction phase, bearing capacity values of CFST columns were estimated through developing gene expression programming (GEP)-based tree equation; then, the results were compared with the results obtained from a hybrid model of artificial neural network (ANN) and particle swarm optimization (PSO). In the modeling process, the outer diameter, concrete compressive strength, tensile yield stress of the steel column, thickness of steel cover, and the length of the samples were considered as the model inputs. After a series of analyses, the best predictive models were selected based on the coefficient of determination (R²) results. R² values of 0.928 and 0.939 for training and testing datasets of the selected GEP-based tree equation, respectively, demonstrated that GEP was able to provide higher performance capacity compared to PSO–ANN model with R² values of 0.910 and 0.904 and ANN with R² values of 0.895 and 0.881. In the optimization phase, whale optimization algorithm (WOA), which has not yet been applied in structural engineering, was selected and developed to maximize the results of the bearing capacity. Based on the obtained results, WOA, by increasing bearing capacity to 23436.63 kN, was able to maximize significantly the bearing capacity of CFST columns.

     

Design of a Compact 1:2 and 1:4 Power Divider with Harmonic Suppression Using Resonator

Wireless Personal Communications - A new design of a 1:2 and 1:4 microstrip power divider is proposed using finite defected ground structure (FDGS), in this paper. In order to design the presented...     

An analytical investigation on the effect of porous conductive cellulose acetate composite morphology on the detection of organic compounds

A smart porous conductive polymer composite (CPC) consisting of cellulose acetate as matrix and multiwalled carbon nanotubes as conductive filler was prepared to detect a set of lung cancer biomarkers. The solvent evaporation-induced phase separation was used to introduce porosity into the conductive composite. The prepared sensitive layers exhibited high response intensity, low response time, and good recovery behavior toward the mentioned analytes. A thorough investigation was conducted on the morphology, response behavior, sensitivity, and selectivity of the prepared CPC transducer. The selectivity of responses was considered based on the thermodynamic and kinetic characteristics of polymer and analytes such as Hansen solubility parameters, Flory-Huggins interaction parameter, and diffusion coefficient of analytes into the polymer membrane. Moreover, the microstructure of porous layers was characterized by using SEM, contact angle, and BET. The volume porosity and specific surface area of the sensitive layers were increased by the introduction of porosity into the polymer composite, causing the improvement of sensing parameters. The obtained responses further confirmed the promising potential of the prepared porous CPC structure, for the detection of lung cancer biomarkers, from exhaled breath as an inexpensive, repeatable, accurate, and noninvasive method.