Influences of rennet and container types on proteolysis of traditional Kurdish cheese during the ripening

The effect of rennet and container types was evaluated on proteolysis of traditional Kurdish cheese during 60 days ripening. The enzymes involved were commercial chymosin and traditional rennet from lamb abomasum. Goat skin (traditional container) and plastic containers were used as storage containers. The trend of proteolysis was determined by measuring the content of nitrogen (N) in compounds soluble in water, 12% trichloroacetic acid and 5% phosphotungstic acid along with the urea–polyacrylamide gel electrophoresis method. The results showed that the nitrogen in compounds soluble in water, 12% trichloroacetic acid and 5% phosphotungstic acid was higher in ripened cheeses into plastic containers; however, the containers had no significant effect on the breakdown of α‐ and β‐caseins (P < 0.05). Using commercial rennet caused the breakdown of α‐ and β‐caseins and the level of nitrogen in compounds soluble in water to increase. Finally, however, the amount of α‐ and β‐caseins breakdown was trivial, and α‐casein was decreased more than β‐casein in all samples.     

Application of Chebyshev polynomials to predict phase behavior of fluids containing asphaltene and associating components using SAFT equation of state

In this work, a thermodynamic model based on statistical association fluid theory (SAFT) is developed to predict the phase behavior of mixtures containing asphaltene contents. The SAFT equation of state is a good candidate for closing that gap between statistical mechanic models and the classical models dominated by cubic equation of state. A robust, fast and accurate computational algorithm based on Chebyshev polynomial approximation is developed to calculate the density and hence fugacity using SAFT equation of state in order to perform phase equilibrium calculations. Application of Chebyshev polynomials to approximate pressure-density function leads to an interpolation error of degree 10⁻¹³. Application of the proposed algorithm to calculate density of binary systems composed of ethanol and toluene shows an average relative deviation of 0.143% in the temperature range 283.15-353.15 K and for pressures up to 45 MPa. The proposed model is developed to predict the precipitation behavior of petroleum fluids containing asphaltene. The effect of pressure, temperature and solvent concentration on the amount of asphaltene precipitation is investigated. A good agreement with an AAD of 2.593% is observed between experimental and predicted amount of asphaltene precipitate. The model is also tested to investigate the effect of temperature and solvent concentration on asphaltene onset pressures (upper and lower). Again, an excellent agreement is observed between experimental and predicted values of the asphaltene onset pressure at different temperatures and solvent concentrations with an average 0.705% relative error. The accuracy of the proposed model is compared with WinProp software using Peng-Robinson equation of state with average 53.132% and 8.657% relative errors for the amount of asphaltene precipitate and onset pressure, respectively.     

Regulating microwave absorption and energy bandgap using cauliflower-like polyaniline coated on La0.8Sr0.2FeO3 nanoparticles

In this research, La_0.8Sr_0.2FeO₃/cauliflower-like polyaniline (PANi) nanocomposite was architected based on a novel complementary method using dodecylbenzenesulfonic acid as a doping agent. The prepared nanocomposite was characterized using Fourier transform infrared, X-ray powder diffraction, field emission scanning electron microscopy, vibrating sample magnetometer diffuse reflection spectroscopy, and vector network analyzer analyses. All of the used analyses attested that the pure structure of materials has been synthesized. Polarizability, energy bandgap, magnetic property, and microwave absorbing features were tailored by loading the various mass fraction of PANi. Exclusive interactions between the nanoparticles with alkaline property and aniline monomers along the experimental route led to the preparation of nanocomposite with unique morphology. Inserting PANi augmented softness and isotropic magnetic property of the prepared nanocomposite, desirable for microwave absorption. Moreover, polyacrylonitrile (PAN) was applied as a novel microwave absorbing matrix. The maximum reflection loss (RL) of La_0.8Sr_0.2FeO₃/PANi_10%/PAN was ??69.24 dB at 12.62 GHz with an efficient bandwidth of 6.47 GHz (RL?<???10 dB) meanwhile the efficient bandwidth was enhanced to 6.97 GHz (RL?<???10 dB) for La_0.8Sr_0.2FeO₃/PANi_30%/PAN nanocomposite.

     

Optimizing reserve capacity of urban road networks in a discrete Network Design Problem

This paper addresses the problem of designing of street directions and lane additions in urban road networks, based on the concept of reserve capacity. Reserve capacity is identified by the largest multiplier applied to a given existing demand matrix, that can be allocated to a network without violating the arc capacities. Having a two-way streets base network and the allowable street lane additions, the problem is to find the optimum configuration of street directions and two-way street lane allocations, and the optimum selection of street lane addition projects, in a way that the reserve capacity of the network is maximized. The problem is considered in two variations; in the first variation no restriction is imposed on the symmetricity of lane allocations for two-way streets, and in the second variation, two-way street lane allocations are restricted to be symmetric. The proposed problems are modeled as mixed-integer bi-level mathematical problems. A hybrid genetic algorithm and an evolutionary simulated annealing algorithm are proposed to solve the models. Computational results for both problem variations are presented.     

The effect of concentration on gas sensor model based on graphene nanoribbon

Graphene nanoribbon (GNR), a superior material with two-dimensional structure and monolayer honeycomb of carbon, is noteworthy and important in all fields’ mainly electronic, chemistry, biology, physics and nanotechnology. Recently, observing about sensors demonstrates that for better accuracy, faster response time and enlarged sensitivity, it needs to be improved. Nowadays, carbon-based equipments as an exclusive substance are remarkable in the sensing technology. High conductivity as unique properties caused that graphene can be used in biological applications. Gas sensor based on graphene can be supposed to have great sensitivity for gas molecules detection. In this study, graphene-based carbon dioxide sensor analytically is modeled. In addition, new methods of gas sensor model based on the gradient of GNR conductance are provided. Also, a field effect transistor-based structure as a modeling platform is suggested. Ultimately, optimum model is evaluated by comparison study between analytical model and experimental performance.     

Not Waving,Drowning: Can Local Government Policies on Climate Change Adaptation and Disaster Resilience Make a Difference?

Climate change will increase the intensity, duration and/or frequency of some climate-related hazards. Responsibility for adapting to such impacts of climate change in Australia has, in the main, fallen on local governments which have paid varying degrees of attention to the issue. This paper takes an integrated approach to compare the climate adaptation and disaster resilience policies and plans of local governments of two low-lying coastal cities in Australia to understand whether (and how) local governments can make a difference. The findings indicate that local governments can significantly contribute to building resilience and adapting to climate-related hazards, however a number of factors such as the attitudes of local governments on climate change, environmental activism, and the recent experiences of climate-related disasters are instrumental for shaping a better local response. Local action also needs to be supported by a more integrated approach by all levels of government.     

Thermoplastic vulcanizate nanocomposites based on polyethylene/reclaimed rubber: A correlation between carbon nanotube dispersion state and electrical percolation threshold

A three-step melt blending process was utilized to produce linear low-density polyethylene (LLDPE)/reclaimed rubber (RR)/carbon nanotube (CNT) nanocomposites in the presence of maleic anhydride grafted polyethylene as a compatibilizer. The effect of LLDPE/RR ratio and CNT content on the morphological, thermal, mechanical, and rheological behavior of these dynamically vulcanized LLDPE/RR nanocomposites were investigated. The morphological study showed that the RR was dispersed in the LLDPE matrix, and CNT addition led to an improved morphology as smaller RR sizes inside LLDPE were observed. The mechanical results revealed that increasing the RR content decreased the hardness, modulus of elasticity, and elongation at break while CNT improved the tensile properties and other mechanical properties. The differential scanning calorimeter analysis showed that the CNT improved the LLDPE crystallization by acting as nucleation agents. Dynamic mechanical analysis showed higher storage modulus and lower loss factor as compared to the neat blend due to mobility restrictions of the polymer chains induced by the presence of CNT. For the conditions studied, the electrical percolation threshold was found to occur at a very low CNT concentration (about 1 wt %) compared to the literature because of the specific structure produced leading to CNT residing in the LLDPE matrix and at the interface between both polymeric phases. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47795.     

A machine-to-loop assignment and layout design methodology for tandem AGV systems with single-load vehicles

In this paper, we propose a method for design of tandem automated guided vehicle (AGV) systems with single-load vehicles. We consider the concurrent design of machines layout and AGV guide paths for a tandem system. Our goal is to devise a method that can achieve the following objectives: (1) maximise the workload balance between loops; (2) minimise the inter-loop flow; and (3) minimise the total flow distance. Our method solves the problem in four stages, considering the machines layout and the tandem paths at the same time. It assigns machines to loops, determines the layout of each loop, arranges loops on the floor, and finally designs a transportation centre to link the loops. We compare the performance of our method with a sequential design method that first determines the layout and then assigns the machines to loops. We solve a number of randomly generated problems for both methods. Results indicate that the proposed algorithm performs faster and achieves lower values of inter-loop flows and inter-loop flow distances.