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排序方式： 共有392条查询结果，搜索用时 15 毫秒
131.
Bharathipriya Rajasekaran Avtar Singh Soottawat Benjakul 《Journal of food science》2022,87(7):2879-2893
132.
Narayanan Murugan Padmakumar Amrishkumar Golok Behari Nando Nikhil Kumar Singha 《应用聚合物科学杂志》2020,137(27):48900
EMA–NBR has been explored to be a potential thermoplastic elastomer blend having good thermal stability as well as oil resistance property. The present investigation reports the optimization of process parameters for the novel polymer blends based on poly(ethylene-co-methyl acrylate) (EMA) and poly(acrylonitrile-co-butadiene) rubber (NBR) with criteria based on the statistical design of experiment (Taguchi L9 orthogonal array). In this case, the polymer blends were prepared by changing the polymer blending conditions such as mixing temperature, mixing time and rotor speed as per Taguchi's L9 orthogonal array. Optimization of the process parameters was carried out based on the physicomechanical properties such as tensile strength, elongation at break, hardness, and tensile impact strength of the resulting EMA/NBR blend. Each processing parameter has been optimized from the experimental data, which are converted into signal-to-noise ratio. The standard statistical technique of analysis of variance result was used to evaluate the proportional role of the different control variables. It has been found that the mixing temperature play very significant role trailed by rotor speed and mixing time in controlling droplet matrix morphology of the EMA/NBR blends. Predominantly, these factors affect the size of the NBR domain and its distribution in the EMA matrix, which in turn have a notable contribution to the physicomechanical properties of the blends. By the optimization of processing conditions, the NBR matrix domain size greatly decreases, leading to significant improvement in physicomechanical properties of the EMA/NBR blends. © 2020 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2020 , 137, 48900. 相似文献
133.
134.
Baiju Karun;T. Arun Prasath;M. Pallikonda Rajasekaran;Rakhee Makreri; 《International journal of imaging systems and technology》2024,34(1):e22937
MRI is a popular imaging method for examining brain tumours. The ability to precisely segment tumours from MRI is absolutely essential for medical diagnostics and surgical planning. Manual tumour segmentation might be unrealistic for more comprehensive studies. Deep learning is the most widely used technique in medical diagnosis. For effective tumour dissection from brain MRI, this paper proposed a novel combination of FLAME and EHO Algorithm. FLAME is a type of clustering method that groups the most similar pixels in to a single cluster. EHO algorithm is one of the nature-inspired metaheuristic optimization algorithms based on the social herding behaviour of elephants and swimming search methods. The proposed methodology's efficiency is validated through testing on various BraTS challenge datasets. The average computational time, mean squared error, peak signal to noise ratio, tanimoto coefficient, and dice score - obtained are 23.3775 s, 0.213, 54.9669 dB, 54.6148%, and 84.053%, respectively. 相似文献
135.
Charuvaka Muvva Natarajan Arul Murugan Venkatesan Subramanian 《International journal of molecular sciences》2021,22(6)
A wide variety of neurodegenerative diseases are characterized by the accumulation of protein aggregates in intraneuronal or extraneuronal brain regions. In Alzheimer’s disease (AD), the extracellular aggregates originate from amyloid-β proteins, while the intracellular aggregates are formed from microtubule-binding tau proteins. The amyloid forming peptide sequences in the amyloid-β peptides and tau proteins are responsible for aggregate formation. Experimental studies have until the date reported many of such amyloid forming peptide sequences in different proteins, however, there is still limited molecular level understanding about their tendency to form aggregates. In this study, we employed umbrella sampling simulations and subsequent electronic structure theory calculations in order to estimate the energy profiles for interconversion of the helix to β-sheet like secondary structures of sequences from amyloid-β protein (KLVFFA) and tau protein (QVEVKSEKLD and VQIVYKPVD). The study also included a poly-alanine sequence as a reference system. The calculated force-field based free energy profiles predicted a flat minimum for monomers of sequences from amyloid and tau proteins corresponding to an α-helix like secondary structure. For the parallel and anti-parallel dimer of KLVFFA, double well potentials were obtained with the minima corresponding to α-helix and β-sheet like secondary structures. A similar double well-like potential has been found for dimeric forms for the sequences from tau fibril. Complementary semi-empirical and density functional theory calculations displayed similar trends, validating the force-field based free energy profiles obtained for these systems. 相似文献
136.
The objective of this work is to fabricate aluminium alloy AA6061 reinforced with ZrB2 particles (10 wt-%) by the in situ reaction of K2ZrF6 and KBF4 salts with molten aluminium. The microstructure, tensile strength, wear resistance and corrosion rate of the fabricated composite were compared with those of matrix alloy. The in situ formed ZrB2 particles were uniformly dispersed in the aluminium matrix predominantly concentrated in inter granular regions and refined the microstructure of the matrix alloy. The incorporation of in situ formed ZrB2 particles into the aluminium matrix improved tensile strength and wear resistance but reduced ductility and corrosion resistance. 相似文献
137.
Four different soluble phase transfer catalysts (PTCs) containing single, di, tri, and tetra active sites have been prepared and proved by FT-IR, 1H NMR, 13C NMR, mass, elemental analysis, and conductivity measurement. The presence of the number of active sites in each catalyst was also been confirmed by determining their rate of polymerization of methyl methacrylate (MMA) using potassium peroxydisulfate (PDS) as a water soluble initiator in biphase medium. The comparative study reveals that the Rp of MMA determined in the presence of PTC combined with ultrasound has shown twofold enhancement in the activity than PTC alone. The observed order of activity was found to be of single-site < di-site < tri-site < tetra-site. Further, the thorough kinetic study of free radical polymerization of MMA has been investigated using superior tetra site viz., HBTAMPDTC and by varying the experimental parameters such as [MMA], [K2S2O8], [MPTC], and the temperature. Based on the observed kinetic results and activation parameters, a suitable mechanism was proposed. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2012 相似文献
138.
Poly(ethylene glycol)‐octafunctionalized polyhedral oligomeric silsesquioxane (POSS) (Mn = 5576.6 g/mol) alloying agent stabilized amphiphilic silica@silver metalloid nanocomposite blended with a triblock copolymer poly(p‐dioxanone‐co‐caprolactone)‐block‐poly(ethylene oxide)‐block‐poly(p‐dioxanone‐co‐caprolactone) (POSS‐SiO2@Ag/PPDO‐co‐PCL‐b‐PEG‐b‐PPDO‐co‐PCL) has been synthesized in both water and in organic medium utilizing ultrasonochemical reaction. The POSS stabilized pre‐made metalloid was successfully dispersed in amphiphilic PPDO‐co‐PCL‐b‐PEG‐b‐PPDO‐co‐PCL (ABA) triblock copolymer matrix of molecular weight 45.9 × 104 g/mol. The mechanism of synthesis of high concentration of SiO2@Ag nanocomposite from TEOS/AgNO3 (in the presence of NH4OH as catalyst/NaBH4 as reductant) nonmetal/metal precursors and the successful EISA of POSS‐SiO2@Ag/ABA nanocomposite into films has been discussed. The successful synthesis of metalloid nanocomposite was morphologically accessed by field emission‐scanning electron microscopy, transmission electron microscopy and atomic force microscopy. Surface plasmon resonance was ensured from UV–visible spectral analysis. Identity and the crystallinity of as prepared nanocomposite were studied by X‐ray diffractometer. Structural and luminescence properties of the nanocomposite were examined by Fourier transform infrared spectroscopy and photoluminescence. Thermogravimetric analysis was carried out to study the thermal stability of the resulting hybrid nanocomposite. The resultant inorganic–organic nanocomposite can be easily suspended in water and would be useful in variety of applications. POLYM. COMPOS., 31:1620–1627, 2010. © 2009 Society of Plastics Engineers 相似文献
139.
The aim of the present study is to develop a Fe-based metal matrix composite (MMC) coating using high velocity oxy-fuel spraying (HVOF) process. A ledeburitic high alloyed cold work tool steel (X220CrVMo13-4) and NbC with an average size of 2 µm at different volume fractions have been considered as metal matrix and hard particles respectively. MMC coatings were deposited on austenitic stainless substrates and the coatings were subsequently densified by hot isostatic pressing (HIP) with and without encapsulation. Microstructural analysis of the as-sprayed and HIPed coatings were characterized by SEM and XRD methods. Results showed that the feedstock preparation involving fine NbC was an influencing factor on the coating deposition. A relatively homogeneous dispersion of fine NbC up to 30 vol.% in cold work tool steel matrix was possible using optimized HVOF spraying. Besides, HVOF spraying and its subsequent HIP treatment induced significant microstructural and phase changes in the MMC coatings. The study showed the potential of HVOF spraying for the development of steel based MMC coatings and its subsequent densification can be achieved by HIP process with and without encapsulation. 相似文献
140.
Priyanka Nallusamy Sapna Saravanen Murugan Krishnan 《International Journal of Network Management》2021,31(4):e2141
The software-defined networking is used extensively in data centers that provide centralized control for the widely deployed networking resources. The traffic is shaped by rules created by the controller dynamically without modifying the individual switch. The key component that stores rules which are used to process the flows is the flow table which resides in the ternary content addressable memory. The current commercial OpenFlow appliances accommodate limited entries up to 8000 due to its high cost and high power consumption. There are two issues to be considered, where (1) flow table's inability to provide rules during flow table overflow leads to dropping of incoming packets and (2) the significant amount of rule replacement occurs when the traffic in data centers increases which creates massive route requests to controller creating overhead. The proposed scheme prevents flow table overflow using the robust machine learning algorithm called decision tree (Iterative Dichotomiser 3) that allows the flow table to learn its high prioritized fine-grained entries by means of multiple matching attributes. The entries are classified, and the usual eviction process is replaced by pushing the low important entries into counting bloom filter which acts as a cache to prevent flow entry miss. The simulations were carried out using real-time network traffic datasets, and the comparisons with the various existing schemes prove that the proposed approach reduces 99.99% of the controller's overhead and the entries are minimized to 99% providing extra space for new flows. 相似文献