Kinetics of oxygen absorption in aqueous sodium dithionite solutions

The absorption and reaction of oxygen in aqueous alkaline solutions of sodium dithionite has been experimentally investigated in a novel gas-liquid contactor. The novel gas-lift bubble column contactor was used to study the kinetics over wide ranges of reactant concentrations, temperature, and pH. The oxygen-sodium dithionite reaction was found to be first-order with respect to dithionite in the range of dithionite concentration < 0.1 M, and second-order in the range of dithionite concentration > 0.1 M. The reaction with respect to oxygen was found to be zero-order for all dithionite concentrations. These results and experimental investigations of the effect of solution alkalinity and temperature on the reaction rate are consistent with previous findings obtained in different gas-liquid contactors. The results thus confirm the feasibility of using the gas-lift bubble column for the kinetics of gas-liquid reactions.     

Correction to: Bismuth Yttrium Oxide (Bi3YO6), A New Electrode Material For Asymmetric Aqueous Supercapacitors

Journal of Inorganic and Organometallic Polymers and Materials - The original version of this article unfortunately contained mistakes. In line 9 of the abstract, 5% should read as 2%. The...     

A multi-echelon production–inventory system with supply disruption

The article investigates an integrated multi-layer supply chain model consisting of supplier, manufacturer and retailer while supply disruption, machine breakdown, safety stock, maintenance breakdown occur simultaneously. At beginning of the production, manufacturer keeps some raw materials in stock received from second supplier at high price, as safety stock due to supply disruption of first supplier. Corrective maintenance is done immediately to restore its normal stage when machine breakdown occurs. Stock out situations at manufacturer and retailer are considered due to disruption of production for machine breakdown. The integrated expected costs of the chain in centralized (collaborating) and decentralized (Stakelberg approach) system are compared. A numerical example and its sensitivity analysis are provided to test feasibility of the model.     

Towards Sustainable Agricultural Systems: A Lightweight Deep Learning Model for Plant Disease Detection

A country’s economy heavily depends on agricultural development. However, due to several plant diseases, crop growth rate and quality are highly suffered. Accurate identification of these diseases via a manual procedure is very challenging and time-consuming because of the deficiency of domain experts and low-contrast information. Therefore, the agricultural management system is searching for an automatic early disease detection technique. To this end, an efficient and lightweight Deep Learning (DL)-based framework (E-GreenNet) is proposed to overcome these problems and precisely classify the various diseases. In the end-to-end architecture, a MobileNetV3Small model is utilized as a backbone that generates refined, discriminative, and prominent features. Moreover, the proposed model is trained over the PlantVillage (PV), Data Repository of Leaf Images (DRLI), and a new Plant Composite (PC) dataset individually, and later on test samples, its actual performance is evaluated. After extensive experimental analysis, the proposed model obtained 1.00%, 0.96% and 0.99% accuracies on all three included datasets. Moreover, the proposed method achieves better inference speed when compared with other State-Of-The-Art (SOTA) approaches. In addition, a comparative analysis is conducted where the proposed strategy shows tremendous discriminative scores as compared to the various pre-trained models and other Machine Learning (ML) and DL methods.     

Investigations on mode-division multiplexed free-space optical transmission for inter-satellite communication link

Wireless Networks - Inter-satellite data transmission links are very crucial for providing global inter-connectivity. We report designing and investigations on high date rate inter-satellite...     

An imperfect production process for time varying demand with inflation and time value of money – An EMQ model

The paper deals with an economic manufacturing quantity (EMQ) model for time-dependent (quadratic) demand pattern. Every manufacturing sector wants to produce perfect quality items. But in long run process, there may arise different types of difficulties like labor problem, machinery capabilities problems, etc., due to that the machinery systems shift from in-control state to out-of-control state as a result the manufacturing systems produce imperfect quality items. The imperfect items are reworked at a cost to become the perfect one. The rework cost may be reduced by improvements in product reliability i.e., the production process depend on time and also the reliability parameter. We want to determine the optimal product reliability and production rate that achieves the biggest total integrated profit for an imperfect manufacturing process using Euler–Lagrange theory to build up the necessary and sufficient conditions for optimality of the dynamic variables. Finally, a numerical example is discussed to test the model which is illustrated graphically also.     

Applying Dynamic Training‐Subset Selection Methods Using Genetic Programming for Forecasting Implied Volatility

Volatility is a key variable in option pricing, trading, and hedging strategies. The purpose of this article is to improve the accuracy of forecasting implied volatility using an extension of genetic programming (GP) by means of dynamic training‐subset selection methods. These methods manipulate the training data in order to improve the out‐of‐sample patterns fitting. When applied with the static subset selection method using a single training data sample, GP could generate forecasting models, which are not adapted to some out‐of‐sample fitness cases. In order to improve the predictive accuracy of generated GP patterns, dynamic subset selection methods are introduced to the GP algorithm allowing a regular change of the training sample during evolution. Four dynamic training‐subset selection methods are proposed based on random, sequential, or adaptive subset selection. The latest approach uses an adaptive subset weight measuring the sample difficulty according to the fitness cases' errors. Using real data from S&P500 index options, these techniques are compared with the static subset selection method. Based on mean squared error total and percentage of non‐fitted observations, results show that the dynamic approach improves the forecasting performance of the generated GP models, especially those obtained from the adaptive‐random training‐subset selection method applied to the whole set of training samples.     

Two‐echelon manufacturer–retailer supply chain strategies with price,quality, and promotional effort sensitive demand

This study deals with the two‐layer supply chain model of one manufacturer and one retailer for a single commodity where market demand is assumed to be dependent on selling price, quality of the products, and promotional effort of the retailer. We investigate the behavior of the supply chain under centralized, manufacturer Stackelberg, conditional manufacturer Stackelberg, retailer Stackelberg, conditional retailer Stackelberg, and vertical Nash model structure. The nature of the above models provides great insights to a firm's manager for achieving optimal strategy in a competitive marketing system. Quite often, not all items produced in a firm are of perfect quality; some are perfect (conforming) quality and others are imperfect (nonconforming) quality. The nonconforming products are sold in a secondary shop or by other retailers. The procurement cost of finished products depends on the quality of the products due to more investment in advanced technology, better raw materials, and skilled labor, etc. The warranty policy for the products is also imposed to attract the customers to buy more. Here, both members (manufacturer and retailer) jointly share the cost of the warranty policy. The objective of this paper is to determine the optimal selling price and promotional effort of the retailer, while the optimal wholesale price and quality of the products are determined by the manufacturer so that the above strategies are maximized. Finally, numerical examples with sensitivity analysis of the key parameters are illustrated to investigate the proposed model.     

Sulfated Hyaluronan Binds to Heparanase and Blocks Its Enzymatic and Cellular Actions in Carcinoma Cells

We examined whether sulfated hyaluronan exerts inhibitory effects on enzymatic and biological actions of heparanase, a sole endo-beta-glucuronidase implicated in cancer malignancy and inflammation. Degradation of heparan sulfate by human and mouse heparanase was inhibited by sulfated hyaluronan. In particular, high-sulfated hyaluronan modified with approximately 2.5 sulfate groups per disaccharide unit effectively inhibited the enzymatic activity at a lower concentration than heparin. Human and mouse heparanase bound to immobilized sulfated hyaluronan. Invasion of heparanase-positive colon-26 cells and 4T1 cells under 3D culture conditions was significantly suppressed in the presence of high-sulfated hyaluronan. Heparanase-induced release of CCL2 from colon-26 cells was suppressed in the presence of sulfated hyaluronan via blocking of cell surface binding and subsequent intracellular NF-κB-dependent signaling. The inhibitory effect of sulfated hyaluronan is likely due to competitive binding to the heparanase molecule, which antagonizes the heparanase-substrate interaction. Fragment molecular orbital calculation revealed a strong binding of sulfated hyaluronan tetrasaccharide to the heparanase molecule based on electrostatic interactions, particularly characterized by interactions of (−1)- and (−2)-positioned sulfated sugar residues with basic amino acid residues composing the heparin-binding domain-1 of heparanase. These results propose a relevance for sulfated hyaluronan in the blocking of heparanase-mediated enzymatic and cellular actions.