A Non-Linear Procurement Model with Quantity Discounts

This paper presents a procurement model for a multinational oil company with affiliate plants located worldwide. The proposed model uses a quantity discount relationship to reduce the total procurement cost. We use a non-linear programming method to solve the model and make comparisons with the current approach used by the oil company. The proposed approach has several distinct advantages: assured minimum cost, ease of data management, flexibility in design, and accuracy in results.     

Improving Prediction of Neural Networks: A Study of Two Financial Prediction Tasks

Neural networks are excellent mapping tools for complex financial data. Their mapping capabilities however do not always result in good generalizability for financial prediction models. Increasing the number of nodes and hidden layers in a neural network model produces better mapping of the data since the number of parameters available to the model increases. This is detrimental to generalizability of the model since the model memorizes idiosyncratic patterns in the data. A neural network model can be expected to be more generalizable if the model architecture is made less complex by using fewer input nodes. In this study we simplify the neural network by eliminating input nodes that have the least contribution to the prediction of a desired outcome. We also provide a theoretical relationship of the sensitivity of output variables to the input variables under certain conditions. This research initiates an effort in identifying methods that would improve the generalizability of neural networks in financial prediction tasks by using mergers and bankruptcy models. The result indicates that incorporating more variables that appear relevant in a model does not necessarily improve prediction performance.     

Highly selective and sensitive monohydrogen phosphate membrane sensor based on molybdenum acetylacetonate

In this work, a highly selective and sensitive monohydrogen phosphate membrane sensor based on a molybdenum bis(2-hydroxyanil) acetylacetonate complex (MAA) is reported. The sensor shows a linear dynamic range between 1.0 × 10⁻¹ and 1.0 × 10⁻⁷ M, with a nice Nernstian behavior (−29.5 ± 0.3 mV decade⁻¹) in pH of 8.2. The detection limit of the electrode is 6.0 × 10⁻⁸ M (∼6 ppb). The best performance was obtained with a membrane composition of 32% poly(vinyl chloride), 58% benzyl acetate, 2% hexadecyltrimethylammonium bromide and 8% MAA. The sensor possesses the advantages of short response time, low detection limit and especially, very good selectivity towards a large number of organic and inorganic anions including salicylate, citrate, tartarate, acetate, oxalate, fluoride, chloride, bromide, iodide, sulfite, sulfate, nitrate, nitrite, cyanide, thiocyanate, perchlorate, metavanadate, and bicarbonate ions. The electrode can be used for at least 10 weeks without any considerable divergence in its slope and detection limit. It was used as an indicator electrode in potentiometric titration of monohydrogenphosphate ion with barium chloride. The proposed sensor was successfully applied to direct determination of monohydrogenphosphate in two fertilizer samples (NPK).     

Synthesis, characterization and catalytic oxidation of cyclohexene with molecular oxygen over host (zeolite-Y)/guest (nickel(II) complexes of R2[12]1,3-dieneN2O2 and R2[13]1,4-dieneN2O2; R = H, Me, Ph) nanocatalyst (HGN)

12- and 13-Membered diaza dioxa Schiff-base nickel(II) complexes were successfully prepared in a nanoscale microreactor by the template condensation of (1,8-diamino-3,6-dioxaoctane)nickel(II) complex with bifunctional diketones within the nanodimensional pores of zeolite Y. The host–guest nanocatalyst (HGN); ([Ni((R₂[12]1,3-dieneN₂O₂)]²⁺-NaY, [Ni(R₂[13]1,4-dieneN₂O₂)]²⁺-NaY; R = H, Me and Ph) is catalytically very efficient as compared to other neat complexes for oxidation of cyclohexene with molecular oxygen as oxidant in the absence of solvent at 70 °C, affording 2-cyclohexene-1-ol and 2-cyclohexene-1-one.     

Equilibrium and kinetic study of novel methyltrimethoxysilane magnetic titanium dioxide nanocomposite for methylene blue adsorption from aqueous media

Novel magnetic titanium dioxide nanoparticles decorated with methyltrimethoxysilane (Fe₃O₄@TiO₂‐MTMOS) were successfully fabricated via a sol–gel method at room temperature. The synthesized material was characterized using Fourier transform infrared spectroscopy, X‐ray diffraction, scanning electron microscopy, energy‐dispersive X‐ray spectroscopy, thermogravimetric analysis and vibrating sample magnetometry. The removal efficiency of the adsorbent was evaluated through the adsorption of methylene blue (MB) dye from water samples. The adsorption isotherm and kinetics were evaluated using various models. The Langmuir model indicated a high adsorption capacity (11.5 mg g^?1) of Fe₃O₄@TiO₂‐MTMOS. The nanocomposite exhibited high removal efficiency (96%) and good regeneration (10 times) compared to Fe₃O₄ and Fe₃O₄@TiO₂ at pH = 9.0. Based on the adsorption mechanism, electrostatic interaction plays a main role in adsorption since MB dye is cationic in nature at pH = 9, whereas the adsorbent acquired an anionic nature. The newly synthesized Fe₃O₄@TiO₂‐MTMOS can be used as a promising material for efficient removal of MB dye from aqueous media.     

The investigation of structural,electronic, elastic and thermodynamic properties of Gd1−xYxAuPb alloys: A first principle study

First principle calculations have been employed to investigate the effects of Y concentration, pressure and temperature on various properties of ${\mathrm{Gd}}_{1?x}{\mathrm{Y}}_x\mathrm{AuPb}$ ($x=0,0.25,0.5,0.75,1$) alloys using density functional theory (DFT). The full potential linearized augmented plane wave (FP-LAPW) method within a framework of the generalized gradient approximation (GGA) is used to perform the calculated results of this paper. Phase stability of ${\mathrm{Gd}}_{1?x}{\mathrm{Y}}_x\mathrm{AuPb}$ alloys is studied using the total energy versus unit cell volume calculations. The equilibrium lattice parameters of these alloys are in good agreement with the available experimental results. The mechanical stability of ${\mathrm{Gd}}_{1?x}{\mathrm{Y}}_x\mathrm{AuPb}$ alloys is proved using elastic constants calculations. Also, the influence of Y concentration on elastic properties of ${\mathrm{Gd}}_{1?x}{\mathrm{Y}}_x\mathrm{AuPb}$ alloys such as Young's modulus, shear modulus, Poisson's ratio and anisotropy factor are investigated and analyzed. By considering both Pugh's ratio and Poisson's ratio, the ductility and brittleness of these alloys are studied. In addition, the total density of states and orbital's hybridizations of different atoms are investigated and discussed. Moreover, the effect of pressure and temperature on some important thermodynamic properties is investigated.     

Design,synthesis, biological evaluation,and docking study of new acridine-9-carboxamide linked to 1,2,3-triazole derivatives as antidiabetic agents targeting α-glucosidase

A new series of acridine-9-carboxamide-1,2,3-triazole derivatives 7a-m were designed, synthesized, and evaluated as novel α-glucosidase inhibitors. Acridine-9-carboxamide-1,2,3-triazole scaffold has been designed by combination of effective moieties from potent α-glucosidase inhibitors. Most of the synthesized compounds were more potent than standard inhibitor acarbose. Among the title compounds, the most potent compounds were compounds 7j , 7k , and 7a with IC₅₀ values of 120.2 ± 1.0, 151.1 ± 1.4, and 157.6 ± 1.6 μM, respectively (IC₅₀ value of acarbose = 750.0 ± 10.0 μM). Docking study of the most potent compounds demonstrated that these compounds formed stable complexes with α-glucosidase active site. Anti-α-amylase assay of compounds 7j , 7k , and 7a was performed and no activity was observed. in vitro cytotoxicity assay of the latter compounds revealed that these compounds were not cytotoxic toward human normal (HDF) and cancer (MCF-7) cell lines. ADME and toxicity prediction of compounds 7j , 7k , and 7a were also performed.