An integrated retail space allocation and lot sizing models under vendor managed inventory and consignment stock arrangements

In this paper, we develop integrated retail shelf space allocation and inventory models for a single item with a stock dependent demand. The integrated models are developed for a supply chain operating under vendor-managed inventory (VMI) and consignment stock (CS) agreement. More precisely, the supplier is responsible for initiating orders on behalf of the retailer and decides about the size of each order, the quantity to be displayed on the shelves, and the reorder point. In addition, the supplier owns the stock at the retailer’s premises until it is sold. We develop mathematical models to assess the benefits accrued by both parties as a result of the adoption of VMI–CS partnership. Results from the numerical experimental study show that such partnership is more attractive to all supply chain members when the retailer provides a flexible display capacity. Moreover, the supplier can use his/her selling price and the maximum allocated shelf space as negotiation means to benefit from the partnership.     

Reactive phase separation: Prediction of an occlusion morphology

Reaction-induced phase separation occurring by spinodal decomposition is simulated in this paper. A technique developed earlier [Alfarraj A, Nauman EB. Spinodal decomposition in ternary systems with significantly different component diffusivities. Macromolecular Theory and Simulations, 2007;16:627-31.] that allows component diffusivities to be dramatically different has been extended to reactive conditions. The example system is the formation of impact polystyrene. The final morphology is a continuous polystyrene phase and a discrete rubber phase where the rubber particles contain polystyrene occlusions. The morphology is modeled for an agitated batch reactor. Simulations of a quiescent batch polymerization also give a discrete rubber phase. This is contrary to reports in the early patent literature, the difference being attributed to cross-linking of the rubber that is not considered in the current model.     

Stability limits and NO emissions of premixed swirl ammonia-air flames enriched with hydrogen or methane at elevated pressures

This study reports measurements of stability limits and exhaust NO mole fractions of technically-premixed swirl ammonia-air flames enriched with either methane or hydrogen. Experiments were conducted at different pressures from atmospheric to 5 bar, representative of commercial micro gas turbines. The full range of ammonia fractions in the fuel blend, x_NH3, was considered, from 0 (pure methane or hydrogen) to 1 (pure ammonia), covering very lean (φ = 0.25) to rich (φ = 1.60) equivalence ratios. Results show that increasing pressure widens the range of stable equivalence ratios for pure ammonia-air flames. Regardless of pressure, there is a critical ammonia fraction above which the range of stable equivalence ratios suddenly widens. This is because flashback does not occur anymore when the equivalence ratio is progressively increased towards stoichiometric and rich blowout occurs instead. This critical ammonia fraction increases with pressure and is larger for ammonia-hydrogen than for ammonia-methane. Provided that enough hydrogen is blended with ammonia (x_NH3 < 0.9), flames with very lean equivalence ratios (φ < 0.7) can be stabilized and these yield competitively low NO emissions (<200 ppm), regardless of pressure. For this reason, very lean swirl ammonia-hydrogen-air flames are promising candidates for micro gas turbines. However, N₂O emissions have the potential to be unacceptably large for these operating conditions if heat loss is too large or residence time is too short. As a consequence, the post flame region must be considered carefully. Due to the lower reactivity of methane compared to that of hydrogen, very lean swirl ammonia-methane-air flames could not be stabilized and good NO performance is limited to rich equivalence ratios for ammonia-methane fuel blends. The equivalence ratio above which good NO performance depends on pressure and bulk velocity.     

Design and experimental validation of looped-tube thermoacoustic engine

The aim of this paper is to present the design and experimental validation process for a thermoacoustic looped-tube engine.The design procedure consists of numerical modelling of the system using DELTA EC tool,Design Environment for Low-amplitude ThermoAcoustic Energy Conversion,in particular the effects of mean pressure and regenerator configuration on the pressure amplitude and acoustic power generated.This is followed by the construction of a practical engine system equipped with a ceramic regenerator-a ...     

Towards Understanding the Decomposition/Isomerism Channels of Stratospheric Bromine Species: Ab Initio and Quantum Topology Study

The present study aims at a fundamental understanding of bonding characteristics of the C–Br and O–Br bonds. The target molecular systems are the isomeric CH₃OBr/BrCH₂OH system and their decomposition products. Calculations of geometries and frequencies at different density functional theory (DFT) and Hartree–Fock/Møller–Plesset (HF/MP2) levels have been performed. Results have been assessed and evaluated against those obtained at the coupled cluster single-double (Triplet) (CCSD(T)) level of theory. The characteristics of the C–Br and O–Br bonds have been identified via analysis of the electrostatic potential, natural bond orbital (NBO), and quantum theory of atoms in molecules (QTAIM). Analysis of the electrostatic potential (ESP) maps enabled the quantitative characterization of the Br σ-holes. Its magnitude seems very sensitive to the environment and the charge accumulated in the adjacent centers. Some quantum topological parameters, namely ∇²ρ, ellipticity at bond critical points and the Laplacian bond order, were computed and discussed. The potential energy function for internal rotation has been computed and Fourier transformed to characterize the conformational preferences and origin of the barriers. NBO energetic components for rotation about the C–Br and O–Br bonds as a function of torsion angle have been computed and displayed.     

A Novel Cultural Crowd Model Toward Cognitive Artificial Intelligence

Existing literature shows cultural crowd management has unforeseen issues due to four dynamic elements; time, capacity, speed, and culture. Cross-cultural variations are increasing the complexity level because each mass and event have different characteristics and challenges. However, no prior study has employed the six Hofstede Cultural Dimensions (HCD) for predicting crowd behaviors. This study aims to develop the Cultural Crowd-Artificial Neural Network (CC-ANN) learning model that considers crowd’s HCD to predict their physical (distance and speed) and social (collectivity and cohesion) characteristics. The model was developed towards a cognitive intelligent decision support tool where the predicted characteristics affect the estimated regulation plan’s time and capacity. We designed the experiments as four groups to analyze the proposed model’s outcomes and extract the interrelations between the HCD of crowd’s grouped individuals and their physical and social characteristics. Furthermore, the extracted interrelations were verified with the dataset’s statistical correlation analysis with a P-value < 0.05. Results demonstrate that the predicted crowd’s characteristics were positively/negatively affected by their considered cultural features. Similarly, analyzing outcomes identified the most influential HCD for predicting crowd behavior. The results also show that the CC-ANN model improves the prediction and learning performance for the crowd behavior because the achieved accepted level of accuracy does not exceed 10 to 20 epochs in most cases. Moreover, the performance improved by 90%, 93% respectively in some cases. Finally, all prediction best cases were related to one or more cultural features with a low error of 0.048, 0.117, 0.010, and 0.014 mean squared error, indicating a novel cultural learning model.     

A novel approach for measuring hyperspectral similarity

Hyperspectral measures are used to capture the degree of similarity between two spectra. Spectral angle mapper (SAM) is an example of such measures. SAM similarity values range from 0 to 1. These values do not indicate whether the two spectra are similar or not. A static similarity threshold is imposed to recognize similar and dissimilar spectra. Adjusting such threshold is a troublesome process. To overcome this problem, the proposed approach aims to develop learnable hyperspectral measures. This is done through using hyperspectral measures values as similarity patterns and employing a classifier. The classifier acts as an adaptive similarity threshold. The derived similarity patterns are flexible, as they are able to capture the specific notion of similarity that is appropriate for each spectral region. Two similarity patterns are proposed. The first pattern is the cosine similarity vector for the second spectral derivative pair. The second pattern is a composite vector of different similarity measures values. The proposed approach is applied on full hyperspectral space and subspaces. Experiments were conducted on a challenging benchmark dataset. Experimental results showed that, classifications based on second patterns were far better than first patterns. This is because first patterns were concerned only with the geometrical features of the spectral signatures, while second patterns combined various discriminatory features such as: orthogonal projections information, correlation coefficients, and probability distributions produced by the spectral signatures. The proposed approach results are statistically significant. This implies that using simple learnable measures outperforms complex and manually tuned techniques used in classification.     

Acidity of All-Silica MCM-41—Studied by Laser Spectroscopy of Adsorbed Fluorescent Probe Compounds

The polarity within the channel environment of all-silica MCM-41 and the surface acidity were probed by the adsorption of rhodamine-B lactone (RhB-L) and 1-naphthylamine (NA) respectively. The photochemical properties of these probe compounds were studied by laser-induced fluorescence spectroscopy and compared with their properties in solution. The environment within the channels was found to be as polar as methanol. The fluorescence wavelength and decay rate have shown that when adsorbed on all-silica MCM-41, the lactone ring in RhB-L was opened to form the zwitterion (RhB-Z). It was not possible to assess whether RhB-L was protonated by the surface of MCM-41 because the fluorescence of both the RhB-Z and the cationic form RhB-C are almost identical. NA was protonated at the ground state on the surface of all-silica MCM-41. The proton, however, was donated back to the surface upon excitation with laser. From the pKa of the conjugate acid of NA and the fluorescence decay time of the excited state of NA (NA*), the acidity of the surface of the all-silica MCM-41 was estimated to be equivalent to an aqueous perchloric acid with pH 1.8–2.5, depending on the level of loading of NA. The origin of the acid surface was concluded to be the silanol groups known to be present on the surface. The nature of these groups and the influence of the polarity and the solvation effect of the framework on the acidity were discussed.