An Insight View on Synthetic Protocol,Surface Activity,and Biological Aspects of Novel Biocompatible Quaternary Ammonium Cationic Gemini Surfactants

In this study, we prepared a novel series of diester-functionalized cationic gemini surfactants (C_m-E2O2-C_m) containing ethylene oxide as a spacer with varying alkyl chain lengths and characterized by ¹H NMR, FT-IR, elemental analysis, and ESI-MS. The physicochemical properties of the geminis were explored by tensiometry, fluorescence, dye solubilization, and Krafft point. These geminis acquire superior surface activity than the conventional surfactants. Fluorescence spectroscopy analysis affirmed that the micropolarity and aggregation number of micelles diminished with increase in the alkyl chain length. These geminis represent a new group of amphiphiles of considerably high biodegradability, better cleavability, and low toxicity as assessed by BOD test, FT-IR analysis, and HC₅₀ analysis, respectively. They also showed significant level of antimicrobial activity toward some specified bacterial strains of Gram-positive and Gram-negative by using agar well diffusion method. Furthermore, the thermogravimetric analysis provided information regarding thermal stabilities of the newly synthesized gemini surfactants.     

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.     

Light weight model for intra mode selection in HEVC

Multimedia Tools and Applications - The High Efficiency Video Coding (HEVC) efficiently reduces the size of the multimedia contents, but at the cost of high computation complexity. In order to make...     

Synthesis and characterization of eugenol-based silicone modified waterborne polyurethane with excellent properties

A eugenol-based silicone-containing monomer 4,4′-(1,1,3,3-tetramethyldisiloxane-1,3-dipropyl)bis-2-methoxyphenol(EUSi) was synthesized from eugenol and 1,1,3,3-tetramethyldisiloxane via the hydrosilylation reaction. And waterborne polyurethane (WPU) with excellent properties was obtained by using EUSi as a type of diol chain extender. The unique combination of rigidity and flexibility in the chemical structure of EUSi greatly facilitated the mechanical properties, thermal properties, and water resistance of WPU. With only a 3% dosage of EUSi, the maximum tensile strength was increased from 6.2 to 22.4 MPa, while the water absorption was decreased from 31.3% to a surprisingly 7.6%. Our work provides a new convenient strategy for the preparation of organosilicon-modified WPU with improved performance.     

Adaptive infill sampling criterion for multi-fidelity optimization based on Gappy-POD

This paper presents a reformulation of the “Gappy Proper Orthogonal Decomposition” (Gappy-POD) multi-fidelity modeling approach and proposes an enrichment criterion associated with an adaptive infill algorithm. The latter is here applied to the study of the flight domain of the RAE-2822 transonic airfoil at two different levels of accuracy to demonstrate its ability to detect areas in a two-dimensional design space where the surrogate model needs improvement to better drive the optimization process.     

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...     

Evaluating Six Sigma failure rate for inverse Gaussian cycle times

Six Sigma is a quality philosophy and methodology that aims to achieve operational excellence and delighted customers. The cost of poor quality depends on the sigma quality level and its corresponding failure rate. Six Sigma provides a well-defined target of 3.4 defects per million. This failure rate is commonly evaluated under the assumption that the process is normally distributed and its specifications are two-sided. However, these assumptions may lead to implementation of quality-improvement strategies that are based on inaccurate evaluations of quality costs and profits. This paper defines the relationship between failure rate and sigma quality level for inverse Gaussian processes. The inverse Gaussian distribution has considerable applications in describing cycle times, product life, employee service times, and so on. We show that for these processes attaining Six Sigma target failure rate requires higher quality efforts than for normal processes. A generic model is presented to characterise cycle times in manufacturing systems. In this model, the asymptotic production is described by a drifted Brownian motion, and the cycle time is evaluated by using the first passage time theory of a Wiener process to a boundary. The proposed method estimates the right efforts required to reach Six Sigma goals.