Spatially Resolved Heat Transfer Rates in an Impinging Circular Microscale Jet

An experimental study of a submerged 125-μm circular microscale jet impingement is presented. These jets flows are associated with low exit Reynolds number and a correspondingly high, subsonic Mach number. Detailed distributions of heated and adiabatic wall temperature, and local and average Nusselt number variations are presented for five laminar exit Reynolds numbers in the range of 690 to 1770 at three nozzle-to-surface spacings of 2, 4, and 6 times the nozzle diameter. The corresponding jet exit Mach numbers range between 0.26 and 0.63. An infrared radiometer is used in conjunction with a heated-thin-foil technique to measure detailed surface temperatures. Results indicate that the adiabatic surface temperature distribution is relatively insensitive to nozzle-to-surface spacing within the parameter range studied. With an increase in Reynolds number, the adiabatic surface temperature decreases significantly near the stagnation point. The average Nusselt numbers are higher compared to Martin's correlation [1] Martin, H. 1977. Heat and Mass Transfer between Impinging Gas Jets and Solid Surfaces. Advances in Heat Transfer, vol. 13: pp. 1–60.  [Google Scholar] for large Reynolds numbers. A similar observation has been reported previously in a numerical study on microscale jet impingement [5] Pence, D. V., Boeschoten, P. A. and Liburdy, J. A. 2003. Simulation of Compressible Micro-Scale Jet Impingement Heat Transfer. Journal of Heat Transfer, vol. 125(no. 3): pp. 447–453. [CROSSREF] [Google Scholar] and attributed to compressibility of the flow and the possible existence of a slip flow.     

Cobalt(II) Phthalocyanine‐Catalyzed Highly Chemoselective Reductive Amination of Carbonyl Compounds in a Green Solvent

Cobalt phthalocyanine has been employed for the highly chemoselective reductive amination of aldehydes and ketones in ethanol as a green solvent. A large range of functional groups such as nitro, acid, amide, ester, nitrile, halogen, lactone, methoxy, hydroxy, alkene, N‐benzyl, O‐benzyl and heterocyclic rings were well tolerated under the present reaction conditions.     

Exploring online virtual networks mapping with stochastic bandwidth demand in multi-datacenter

Network virtualization serves as a promising technique for providing a flexible and highly adaptable shared substrate network to satisfy the diversity of demands and overcoming the ossification of Internet infrastructure. As a key issue of constructing a virtual network (VN), various state-of-the-art algorithms have been proposed in many research works for addressing the VN mapping problem. However, these traditional works are efficient for mapping VN which with deterministic amount of network resources required, they even deal with the dynamic resource demand by using over-provisioning. These approaches are obviously not advisable, since the network resources are becoming more and more scarce. In this paper, we investigate the online stochastic VN mapping (StoVNM) problem, in which the VNs are generated as a Poisson process and each bandwidth demand x _i follows a normal distribution, i.e., x _i ~ N(μ _i , σ _i ²). Firstly, we formulate the model for StoVNM problem by mixed integer linear programming, which with objective including minimum-mapping-cost and load balance. Then, we devise a sliding window approach-based heuristic algorithm w-StoVNM for tackling this NP-hard StoVNM problem efficiently. The experimental results achieved from extensive simulation experiments demonstrate the effectiveness of the proposed approach and superiority than traditional solutions for VN mapping in terms of VN mapping cost, blocking ratio, and total net revenue in the long term.     

Optimal provisioning for virtual network request in cloud-based data centers

Today applications and services are migrating to a cloud-computing-based paradigm in which the users access the applications and services hosted in data centers, by using thin-clients on the user terminal device. These applications/services are typically hosted and run on virtual machines in interconnected data centers. Different applications from the same user may need to access and change shared data or information. Thus, we may abstract the applications from same user as a virtual network (VN). For better performance and efficiency, it is critical that the VN request be accommodated with optimal provisioning under the current resource state of data centers. In this paper, for addressing the issue of how to design an optimal provisioning scheme for the VN request such that the total revenue of is maximized, we first develop a framework for the optimal provisioning of VN request by using mixed integer programming. Since the optimal provisioning problem is NP-hard, we also propose a genetic algorithm?Cbased heuristic algorithm for addressing the problem of optimal provisioning for VN with unsplittable flow and optimal provisioning for VN with splittable flow problems. We demonstrate the effectiveness of our approach in improving the total revenue by conducting extensive simulations on different networks.     

Effects of rice harvest moisture on kernel damage and milled rice surface free fatty acid levels

ABSTRACT:  Surface free fatty acid (FFA) on milled rice is a key factor in determining rice quality and acceptability to the brewing industry. Rice FFA oxidizes, causing off-flavors and odors to develop, compromising the brewing quality of milled rice. The effect of harvest moisture (13%, 16%, and 20%), harvester type (1688 Case and 9500 John Deere), and rice variety (Cocodrie and Bengal) on harvest damaged rough rice and milled rice surface FFA after drying to 12% moisture and 6 mo rough rice storage was examined. The Case harvester produced more damaged kernels than the John Deere harvester, but this was not reflected in surface FFA development. There were no significant FFA differences in variety or harvester type. Rice harvested at a higher moisture content (20%) produced significantly greater FFA values, with a peak near 0.1%, than rice harvested at lower moisture contents (13% and 16%), which had FFA values near 0.08%. Retention of bran by damaged kernels at high harvest moisture probably was responsible for promoting surface FFA development, but if bran was lost at lower harvest moistures, surface FFA, development was limited. Harvest moisture affected milled rice FFA, although rough rice was dried to 12% immediately after harvesting.     

Nonionic polymeric surfactant template for mesoporous NiCo<Subscript>2</Subscript>O<Subscript>4</Subscript> formation

Mesostructured NiCo₂O₄ is synthesized in presence of nonionic glucose based polymeric surfactant, β-C₁₀Alkyl Poly Glucoside (β-C₁₀APG). Formed NiCo₂O₄ mesostructures have pore size in the range of 25–65 Å and surface area of 202.9 m²/g. Formed particles are rod shape with 2d hexagonal pattern and Fd3m space group point symmetry. The formation of mesostructure phase is explained by coordination bond formation between metal ions with surfactant head. β-C₁₀APG has the potential to be explored as green template for mesopore formation.     

Investigating surface roughness of parts produced by SLS process

Selective laser sintering (SLS) has been recognized as one of the best rapid prototyping (RP) technique for producing solid models, directly from computer-aided design data by fussing together different layers with the help of laser light. Further, RP has traditionally been used for producing a solid model for visualization purpose and assessing kinematic functionality. So, the model is required to have superior mechanical integrity and surface quality for handling and model testing. This study investigates surface roughness (SR) of parts produced by SLS process. The empirical models have been purposed to predict the feasibility of different process parameters viz., laser power, scan spacing, bed temperature, hatch length, and scan count on SR. Further, these parameters have been optimized using face-centered central composite design with response surface methodology. The optimized parameters have been verified by conducting confirmation experiments.     

Studies on the copolymerization of methyl methacrylate with N‐(o/m/p‐chlorophenyl) itaconimides

The article describes the synthesis and characterization of N‐aryl itaconimide monomers such as: N‐(p‐chlorophenyl) itaconimide (PI)/N‐(m‐chlorophenyl) itaconimide (MI)/N‐(o‐chlorophenyl) itaconimide (OI) and its copolymerization behavior with MMA. The homopolymers and copolymers of N‐aryl itaconimides and methyl methacrylate (MMA, M₂) were synthesized by varying the mol fraction of N‐aryl itaconimides in the initial feed from 0.1 to 0.5 using azobisisobutyronitrile (AIBN) as an initiator and tetrahydrofuran (THF) as the solvent. Copolymer composition was determined using ¹H‐NMR spectroscopy [by taking the ratio of intensities of signals due to ? OCH₃ of MMA (δ = 3.59 ppm) and the aromatic proton (δ = 7.2–7.5 ppm) of N‐aryl itaconimides] and percent nitrogen content. The reactivity ratios were found to be r₁ = 1.33 and r₂ = 0.36 (PI‐MMA) r₁ = 1.15 and r₂ = 0.32 (MI‐MMA) and r₁ = 0.81 and r₂ = 0.35 (OI‐MMA). Molecular weight as determined using high‐performance liquid chromatography decreased with increasing mol fraction of itaconimides in copolymers. All the polymers had a polydisperstivity index in the range of 1.5–2.6.Thermal characterization was done using differential scanning calorimetry and dynamic thermogravimetry in nitrogen atmosphere. Incorporation of these N‐aryl itaconimides in PMMA backbone resulted in an improvement in glass transition temperature (T_g) and thermal stability. Percent char increased with the increase of PI/MI/OI content in the copolymers. © 2001 John Wiley & Sons, Inc. J Appl Polym Sci 82: 2078–2086, 2001     

Gastric Tract Disease Recognition Using Optimized Deep Learning Features

Artificial intelligence aids for healthcare have received a great deal of attention. Approximately one million patients with gastrointestinal diseases have been diagnosed via wireless capsule endoscopy (WCE). Early diagnosis facilitates appropriate treatment and saves lives. Deep learning-based techniques have been used to identify gastrointestinal ulcers, bleeding sites, and polyps. However, small lesions may be misclassified. We developed a deep learning-based best-feature method to classify various stomach diseases evident in WCE images. Initially, we use hybrid contrast enhancement to distinguish diseased from normal regions. Then, a pretrained model is fine-tuned, and further training is done via transfer learning. Deep features are extracted from the last two layers and fused using a vector length-based approach. We improve the genetic algorithm using a fitness function and kurtosis to select optimal features that are graded by a classifier. We evaluate a database containing 24,000 WCE images of ulcers, bleeding sites, polyps, and healthy tissue. The cubic support vector machine classifier was optimal; the average accuracy was 99%.     

Sulfonated poly(ether ether ketone) reinforced with polystyrene sulfonic acid functionalized micelle templated mesoporous MCM-41 for direct methanol fuel cells

A composite membrane comprising sulfonated polyether ether ketone (sPEEK) and polystyrene sulfonic acid functionalized micelle templated MCM-41 (PSSA-f-MCM-41) is realized as a potential alternative to the Nafion membrane for direct methanol fuel cells (DMFC). PSSA-f-MCM-41 incorporation in sPEEK leads to improvement in the physio-chemical properties such as ionic conductivity, methanol permeability, tensile strength, water uptake and ion exchange capacity. The methanol permeability of the composite membrane i.e. PSSA-f-MCM-41 (1.5 wt %)-sPEEK is reduced by 60% in comparison to pristine sPEEK. Moreover, the electrochemical selectivity of the aforesaid composite membrane is four times higher than sPEEK. The DMFC performance shows the peak power density of 147 mW cm^?2 for the composite membrane which is higher than the pristine sPEEK and Nafion 117 membranes. Stability test for the composite membranes confirm less degradation in OCV in comparison to pristine sPEEK.