Enrichment of macaroni with cellulose-derivative protein complex from whey and corn steep liquor

Macaroni was prepared from semolina fortified with 3, 6 and 9% CMC-protein (CMC — carboxymethyl cellulose) or HEC-protein (HEC — hydroxyethyl cellulose) complexes from whey and corn steep liquor to increase the protein quality and quantity. Fortification increased the protein content up to 14.2% in DM (vs. 12.1% in control) for macaroni. Water absorption, dough weakening and mixing tolerance index were decreased, while dough development time and dough stability were increased when the amount of precipitated cellulose-protein complex from whey and corn steep liquor in the blends increased. Addition of both tested cellulose-protein complexes improved cooking quality by increasing the weight and volume of cooked macaroni, but cooking losses were greater. Sensory evaluation of the colour, flavour and appearance of macaroni were improved as a result of adding cellulose-protein complex from whey. Macaroni samples prepared from dough mixtures with 6 and 9% of cellulose-protein complex from corn steep liquor were less acceptable than those prepared from 100% semolina.     

Performance of biomimetic coating modified fiber incorporated styrene butadiene styrene modified asphalt

This study reports the effect of polydopamine bionic coating and γ-methacryloxypropyltrimethoxysilane (KH570) composite modified polyacrylonitrile (PAN) fiber as a secondary modifier on the performance of styrene-butadiene-styrene (SBS) modified asphalt. Dynamic shear rheometer test indicated the complex shear modulu, storage modulus, and loss modulus of modified PAN (KD-PAN) incorporated SBS modified asphalt was increased by 12.4, 20.5, and 11.2%, respectively compared with PAN/SBS modified asphalt. The master curve of G^* of fiber/SBS composite modified asphalt shows that the deformation resistance of KD-PAN/SBS modified asphalt is greater than that of PAN/SBS modified asphalt in the entire loading frequency range. The cone penetration test showed significantly enhanced shear strength of KD-PAN/SBS modified asphalt. The adhesion work test results and SEM images of interface between fiber and SBS modified asphalt revealed that the adhesion effect of KD-PAN and SBS modified asphalt is better than that of PAN and SBS modified asphalt. SEM and AFM images of fiber further showed that the fiber surface becomes rough after modification. The increased surface roughness of KD-PAN facilitated the adherence of SBS modified asphalt to it, which in turn led to the enhanced performance of KD-PAN/SBS composite modified asphalt at the same fiber content and temperature.     

A Cooperative Game Theoretical Technique for Joint Optimization of Energy Consumption and Response Time in Computational Grids

With the explosive growth in computers and the growing scarcity in electric supply, reduction of energy consumption in large-scale computing systems has become a research issue of paramount importance. In this paper, we study the problem of allocation of tasks onto a computational grid, with the aim to simultaneously minimize the energy consumption and the makespan subject to the constraints of deadlines and tasks' architectural requirements. We propose a solution from cooperative game theory based on the concept of Nash Bargaining Solution. In this cooperative game, machines collectively arrive at a decision that describes the task allocation that is collectively best for the system, ensuring that the allocations are both energy and makespan optimized. Through rigorous mathematical proofs we show that the proposed cooperative game in mere O(n mlog(m)) time (where n is the number of tasks and m is the number of machines in the system) produces a Nash Bargaining Solution that guarantees Pareto-optimally. The simulation results show that the proposed technique achieves superior performance compared to the Greedy and Linear Relaxation (LR) heuristics, and with competitive performance relative to the optimal solution implemented in LINDO for small-scale problems.     

Political Optimizer with Deep Learning-Enabled Tongue Color Image Analysis Model

Biomedical image processing is widely utilized for disease detection and classification of biomedical images. Tongue color image analysis is an effective and non-invasive tool for carrying out secondary detection at anytime and anywhere. For removing the qualitative aspect, tongue images are quantitatively inspected, proposing a novel disease classification model in an automated way is preferable. This article introduces a novel political optimizer with deep learning enabled tongue color image analysis (PODL-TCIA) technique. The presented PODL-TCIA model purposes to detect the occurrence of the disease by examining the color of the tongue. To attain this, the PODL-TCIA model initially performs image pre-processing to enhance medical image quality. Followed by, Inception with ResNet-v2 model is employed for feature extraction. Besides, political optimizer (PO) with twin support vector machine (TSVM) model is exploited for image classification process, shows the novelty of the work. The design of PO algorithm assists in the optimal parameter selection of the TSVM model. For ensuring the enhanced outcomes of the PODL-TCIA model, a wide-ranging experimental analysis was applied and the outcomes reported the betterment of the PODL-TCIA model over the recent approaches.     

Theoretical Investigation of Cubic BaVO<Subscript>3</Subscript> and LaVO<Subscript>3</Subscript> Perovskites via Tran–Blaha-Modified Becke–Johnson Exchange Potential Approach

The full potential linearized augmented plane wave method of density functional theory has been used to investigate the structural, electronic, magnetic and thermoelectric properties of cubic perovskites BaVO₃ and LaVO₃. The ferromagnetic ground state has been found to be stable by comparing the total energies of non-spin-polarized and spin-polarized calculations performed for optimized unit cells. For both compounds, the bond length and tolerance factor are also measured. From the band structures and density of states plots, it is found that both compounds are half-metallic. We found that the presence of V at the octahedral site of these perovskites develops exchange splitting through p-d hybridization, which results in a stable ferromagnetic state. The observed exchange splitting is further clarified from the magnetic moment, charge and spin of the anion and cations. Finally, we also presented the calculated thermoelectric properties of these materials, which show that half-metallic BaVO₃ and LaVO₃ materials are potential contenders for thermoelectric applications.     

DEMCMC-GPU: An Efficient Multi-Objective Optimization Method with GPU Acceleration on the Fermi Architecture

In this paper, we present an efficient method implemented on Graphics Processing Unit (GPU), DEMCMC-GPU, for multi-objective continuous optimization problems. The DEMCMC-GPU kernel is the DEMCMC algorithm, which combines the attractive features of Differential Evolution (DE) and Markov Chain Monte Carlo (MCMC) to evolve a population of Markov chains toward a diversified set of solutions at the Pareto optimal front in the multi-objective search space. With parallel evolution of a population of Markov chains, the DEMCMC algorithm is a natural fit for the GPU architecture. The implementation of DEMCMC-GPU on the pre-Fermi architecture can lead to a ^~25 speedup on a set of multi-objective benchmark function problems, compare to the CPU-only implementation of DEMCMC. By taking advantage of new cache mechanism in the emerging NVIDIA Fermi GPU architecture, efficient sorting algorithm on GPU, and efficient parallel pseudorandom number generators, the speedup of DEMCMC-GPU can be aggressively improved to ^~100.     

On exploiting task duplication in parallel program scheduling

One of the main obstacles in obtaining high performance from message-passing multicomputer systems is the inevitable communication overhead which is incurred when tasks executing on different processors exchange data. Given a task graph, duplication-based scheduling can mitigate this overhead by allocating some of the tasks redundantly on more than one processor. In this paper, we focus on the problem of using duplication in static scheduling of task graphs on parallel and distributed systems. We discuss five previously proposed algorithms and examine their merits and demerits. We describe some of the essential principles for exploiting duplication in a more useful manner and, based on these principles, propose an algorithm which outperforms the previous algorithms. The proposed algorithm generates optimal solutions for a number of task graphs. The algorithm assumes an unbounded number of processors. For scheduling on a bounded number of processors, we propose a second algorithm which controls the degree of duplication according to the number of available processors. The proposed algorithms are analytically and experimentally evaluated and are also compared with the previous algorithms     

Comparison of alteplase (tissue plasminogen activator) high‐dose vs. low‐dose protocol in restoring hemodialysis catheter function: The ALTE‐DOSE study

Hemodialysis catheter (HDC) dysfunction due to thrombosis is common, and dysfunction incidence can reach up to 50% within 1 year of use. Although administration of intraluminal alteplase (tissue plasminogen activator [tPA]) is the standard of practice to pharmacologically restore HDC function, there are no evidence‐based guidelines concerning the optimal tPA dose. The purpose of this study was to compare the efficacy of 1.0‐mg vs. 2.0‐mg tPA dwell protocols in restoring the HDC function in thrombotic dysfunctional catheters. A retrospective, single‐center study was conducted on two independent cohorts of patients; the first (n = 129) received 2.0 mg tPA/catheter lumen, while the second (n = 108) received 1.0 mg tPA/catheter lumen. Kaplan–Meier and Cox regression analyses were performed to compare the catheter survival time between patients who received 1.0 mg tPA and those who received 2.0 mg tPA. Catheter removal occurred in 25 (19.4%) of those catheters treated with 1.0 mg tPA compared with 11 (10.2%) of catheters treated with 2.0 mg tPA (P = 0.05). The hazard ratio (HR) for catheter removal was 2.75 (95% confidence interval [^95%CI] = 1.25–6.04) for the 1.0‐mg tPA cohort compared with the 2.0‐mg tPA cohort. Correction added on 3 December 2012, after first online publication: The tPA cohort values were changed. Female gender (HR = 2.51; ^95%CI = 1.20–5.27) and age (HR = 0.96; ^95%CI = 0.94–0.98) were also associated with catheter survival. Our findings suggest that treatment of dysfunctional HDC with 2.0‐mg tPA dwells is superior to 1.0‐mg tPA dwells.     

Microscopic details of asphaltenes aggregation onset during waterflooding

We report detailed microscopic studies of asphaltenes aggregation onset during waterflooding of petroleum reservoirs. To achieve this objective, a series of simulations are performed on asphaltenic-oil miscibilized with water at high pressure and temperature through molecular dynamics. Results of this simulation onset are applicable to asphaltenes behavior in real crude oils. Our simulation results illustrate that the aggregation onset in waterflooding generally follows three sequential steps: (i) Asphaltene-water interaction; (ii) Water bridging; (iii) Face-to-face stacking. Then, asphaltene-water and water-water hydrogen-bonding network surround every aggregate boosting the intensity of aggregation onset. We intend to utilize such understanding of these details in our predictive and preventive measures of arterial blockage in oil reservoirs during waterflooding.