Investigation into the effect of carboxylic acid monomer on particle nucleation and growth in emulsifier-free emulsion copolymerization of styrene-butadiene-acrylic acid

Latexes of carboxylated styrene-butadiene rubber were prepared via batch emulsion copolymerization with different amounts of acrylic acid in the absence of emulsifier. The effect of acid monomer was investigated in the particle formation and growth. It was observed that the amount of acrylic acid strongly affected the particle formation. The number of particles and thus polymerization rate increased with increasing of the acid content. There was no significant difference in the polymerization rate per particle in all experiments. The results show that in this case particle growth process is less dependent on the acrylic acid amount in comparison with its influence on nucleation stage and then particle number. Several parameters such as polymerization rate and number of latex particle per unit volume of the aqueous phase were calculated. Attempt was made to evaluate the average number of growing chain per particle. Also average particle diameter of the above carboxylated SBR latexes was obtained through some calculations from the direct measurement of average particle diameter in the swollen state by light scattering technique for the first time.     

Relating Sediment Yield Estimations to the Wet Front Term Using Rainfall Simulator Field Experiments

Water Resources Management - Depth to wet front is generally considered as the amount of water that penetrates into soil and wets the internal soil layer. This is an important variable especially...     

Knowledge Diffusion of the Internet of Things (IoT): A Main Path Analysis

Wireless Personal Communications - The Internet of Things (IoT) is a concept that has attracted significant attention since the emergence of wireless technology. The knowledge diffusion of IoT...     

Modeling industrial thickener using computational fluid dynamics (CFD), a case study: Tailing thickener in the Sarcheshmeh copper mine

Separation of particles from liquid in the large gravitational tanks is widely used in mining and industrial wastewater treatment process. Thickener is key unit in the operational processes of hydrometallurgy and is used to separate solid from liquid. In this study, population balance models were combined with computational fluid dynamics (CFD) for modeling the tailing thickener. Parameters such as feed flow rate, flocculant dosage, inlet solid percent and feedwell were investigated. CFD was used to simulate the industrial tailing thickener with settled bed of 120 m diameter which is located in the Sarcheshmeh copper mine. Important factor of drag force that defines the rake torque of rotating paddles on the bed was also determined. Two phases turbulence model of Eulerian/Eulerian in accordance with turbulence model of k-ε was used in the steady-state. Also population balance model consists of 15 groups of particle sizes with Luo and Lehr kernel was used for aggregation/breakage kernel. The simulation results showed good agreement with the operational data.     

Effect of galvanic contact on the flotability of galena in the presence and absence of a collector

In this paper, the effect of various electrochemical environments in the galena flotation is investigated. The electrochemical environments consisted of a ball mill for grinding of galena ore and a Denver flotation cell for flotation of galena in the laboratory scale. In order to achieve the maximum recovery with sodium hyposulfite, the concentrations of 0.06 and 0.12 M of air and nitrogen gases have been used to control the pulp potential in the Denver flotation cell. The galena sample was from the “Era mine” which is located in the Kiyasar area, north of Iran. This mine contains: Galena (PbS) at least 22%, Fluorite (CaF₂) 73.37%, Quartz (SiO₂) 2.54% and other minerals such as Cerussite (PbCO₃) and Kaolinite (Al₂Si₂O₅(OH)₄). Flotation of Galena was conducted in a 0.12 M of sodium hyposulfite solution. It was found that the amount of recovery by this process was 85% and 63% in the presence and absence of potassium amyl xanthate (KAX) and at an estimated potential of 280 to 350 mV respectively while the recovery was 70% and 52% at an approximate potential of 175 to 210 mV in water in the presence and absence of collector (KAX).     

Stable identification of nonlinear systems using neural networks: theory and experiments

This paper presents an approach for stable identification of multivariable nonlinear system dynamics using a multilayer feedforward neural network. Unlike most of the previous neural network identifiers, the proposed identifier is based on a nonlinear-in-parameters neural network (NLPNN). Therefore, it is applicable to systems with higher degrees of nonlinearities. Both parallel and series-parallel models are used with no a priori knowledge about the system dynamics. The method can be considered both as an online identifier that can be used as a basis for designing a neural network controller as well as an offline learning scheme for monitoring the system states. A novel approach is proposed for the weight updating mechanism based on the modification of the backpropagation (BP) algorithm. The stability of the overall system is shown using Lyapunov's direct method. To demonstrate the performance of the proposed algorithm, an experimental setup consisting of a three-link macro-micro manipulator (M/sup 3/) is considered. The proposed approach is applied to identify the dynamics of the experimental robot. Experimental and simulation results are given to show the effectiveness of the proposed learning scheme.     

Association between antiinflammatory cytokine,IL‐10, and sleep quality in patients on maintenance hemodialysis

Elevated proinflammatory cytokines have been attributed to poor sleep quality in patients receiving hemodialysis. This is the first investigation about the relationship between sleep quality and circulating levels of antiinflammatory markers in these patients. A total of 72 patients who were receiving maintenance hemodialysis were enrolled in this cross‐sectional study. The Pittsburgh Sleep Quality Index (PSQI) was used to measure sleep quality. Patients were divided into two groups: good sleepers (PSQI score < 5) and poor sleepers (PSQI score ≥ 5). Assessments were made for serum biochemical parameters (albumin, parathyroid hormone), inflammatory (interleukin [IL]‐6, tumor necrosis factor‐alpha [TNF‐α], and high‐sensitivity c‐reactive protein [hs‐CRP] ) and antiinflammatory (IL‐10) markers. Fifty‐four patients (75%) were classified as poor sleepers. Poor sleepers showed significantly lower levels of serum IL‐10 and higher serum triglyceride and parathyroid hormone concentrations. These patients were more likely to have more comorbidities. The global PSQI score was significantly correlated with serum IL‐10 (p = 0.03) and triglyceride levels (p = 0.01). Multivariate logistic regression analysis showed a direct correlation between PSQI and having comorbidities (p = 0.011, odds ratio [OR] = 3.918; confidence interval 95% [CI] = 2.742–19.031), between PSQI and serum triglyceride (p = 0.027, OR = 1.027 [95% CI = 1.007–1.048] ), and an inverse correlation between PSQI and serum IL‐10 level (p = 0.021, OR = 0.424 [95% CI = 0.195–0.922]). Reduced circulating levels of the antiinflammatory cytokine IL‐10 were significantly associated with poor sleep quality in hemodialysis patients. Factors including serum IL‐10 and triglyceride concentrations and having comorbidities may predict patients prone to poor sleep quality.     

A high-performance and scalable multi-core aware software solution for network monitoring

In recent years, the need for high-performance network monitoring tools, which can cope with rapidly increasing network bandwidth, has become vital. A possible solution is to utilize the processing power of multi-core processors that nowadays are available as commercial-off-the-shelf (COTS) hardware. In this paper, we introduce a software solution for wire-speed packet capturing and transmission for TCP/IP networks under Linux operating system, called DashCap. The results of our experimental evaluations show that the proposed solution causes more than two times performance boost for packet capturing in comparison to the existing software solutions under Linux. We have proposed a scalable software architecture for network monitoring tools called DashNMon, which is based on DashCap. Multi-core awareness is a distinguished property of this architecture. Comparing to the existing cluster-based solutions, DashNMon can be used with COTS multi-core processors. In order to evaluate the proposed solutions, we have developed several prototype tools. The results of the experiments carried out using these tools show the scalability and high performance of the network monitoring tools that are based on the proposed architecture. Using the proposed architecture, it is possible to design and implement high-performance multi-threaded network intrusion detection systems (NIDSs) or application-layer firewalls, completely in the user space and with better utilization of the computational resources of multi-processor/multi-core systems.     

Nurr1 Is Not an Essential Regulator of BDNF in Mouse Cortical Neurons

Nurr1 and brain-derived neurotrophic factor (BDNF) play major roles in cognition. Nurr1 regulates BDNF in midbrain dopaminergic neurons and cerebellar granule cells. Nurr1 and BDNF are also highly expressed in the cerebral cortex, a brain area important in cognition. Due to Nurr1 and BDNF tissue specificity, the regulatory effect of Nurr1 on BDNF in different brain areas cannot be generalized. The relationship between Nurr1 and BDNF in the cortex has not been investigated previously. Therefore, we examined Nurr1-mediated BDNF regulation in cortical neurons in activity-dependent and activity-independent states. Mouse primary cortical neurons were treated with the Nurr1 agonist, amodiaquine (AQ). Membrane depolarization was induced by KCl or veratridine and reversed by nimodipine. AQ and membrane depolarization significantly increased Nurr1 (p < 0.001) and BDNF (p_AQ < 0.001, p_KCl < 0.01) as assessed by real-time qRT-PCR. However, Nurr1 knockdown did not affect BDNF gene expression in resting or depolarized neurons. Accordingly, the positive correlation between Nurr1 and BDNF expression in AQ and membrane depolarization experiments does not imply co-regulation because Nurr1 knockdown did not affect BDNF gene expression in resting or depolarized cortical neurons. Therefore, in contrast to midbrain dopaminergic neurons and cerebellar granule cells, Nurr1 does not regulate BDNF in cortical neurons.     

Thermo-mechanical vibration analysis of rotating nonlocal nanoplates applying generalized differential quadrature method

In this study, thermal and small-scale effects on the flapwise bending vibrations of a rotating nanoplate, which can be the basis of nano-turbine design, have been analyzed. The nano-turbine is made of an orthotropic nanoplate with a setting angle that is modeled based on the classical plate theory (CPT) with cantilever boundary conditions. The axial forces are also included in the model as the true spatial variation due to the rotation and temperature change. The governing equations and boundary conditions are derived according to Hamilton's principle and the governing equations are solved with the aid of the generalized differential quadrature method. The effects of small-scale parameter, nondimensional angular velocity, temperature change, and setting angles in the first four nondimensional frequencies are discussed. Due to the consideration of the rotating effects, results of this study are applicable in nano-machines, such as nano-motors, nano-rotor, and other rotating nano-structures. Also, by considering the effect of thermal loading on rotation of a nanoplate, the results are useful in the design of nano-turbines.