Evapotranspiration Modeling Using Different Tree Based Ensembled Machine Learning Algorithm

Water Resources Management - The present study investigates and evaluate the scope and potential of modern computing tools and techniques such as ensembled machine learning methods in estimating...     

Multi-item inventory model of breakable items with stock-dependent demand under stock and time dependent breakability rate

Items made of glass, ceramic, etc. are normally stored in stacks and get damaged during the storage due to the accumulated stress of heaped stock. These items are known as breakable items. Here a multi-item inventory model of breakable items is developed, where demands of the items are stock dependent, breakability rates increase linearly with stock and nonlinearly with time. Due to non-linearity and complexity of the problem, the model is solved numerically and final decisions are made using Genetic Algorithm (GA). In a particular case, model is solved analytically as well as numerically and results are compared. Models are developed with both crisp and uncertain inventory costs. For uncertain inventory costs both fuzzy and stochastic parameters are considered. A chance constrained approach is followed to deal with simultaneous presence of stochastic and fuzzy parameters. Different numerical examples are used to illustrate the problem for different cases.     

A multi-item transportation problem with fuzzy tolerance

This paper presents the recently introduced modified subgradient method for optimization and its effectiveness in a fuzzy transportation model. Here a multi-item balanced transportation problem (MIBTP) is formulated where unit transportation costs are imprecise. Also available spaces and budgets at destinations are limited but imprecise. The objective is to find a shipment schedule for the items that minimizes the total cost subjected to imprecise warehouse and budget constraints at destinations. The proposed model is reduced to a multi-objective optimization problem using tolerances, then to a crisp single-objective one using fuzzy non-linear programming (FNLP) technique and Zimmermann's method. The above fuzzy MIBTP is also reduced to another form of deterministic one using modified sub-gradient method (MSM). These two crisp optimization problems are solved by Genetic Algorithm (GA). As an extension, fuzzy multi-item balanced solid transportation problems (STPs) with and without restrictions on some routes and items are formulated and reduced to deterministic ones following FNLP and Zimmermann's methods. These models are also solved by GA. Models are illustrated numerically, optimum results of fuzzy MIBTP from two deductions are compared. Results are also presented for different GA parameters.     

Enhancement of properties of recycled coarse aggregate concrete using bacteria

Due to rapid construction, necessity for raw materials of concrete, especially coarse aggregate, tends to increase the danger of early exhaustion of the natural resources. An alternative source of raw materials would perhaps delay the advent of this early exhaustion. Recycled coarse aggregate (RCA) plays a great role as an alternative raw material that can replace the natural coarse aggregate (NCA) for concrete. Previous studies show that the properties of RCA concrete are inferior in quality compared to NCA concrete. This article attempts to study the improvement of properties of RCA concrete with the addition of bacteria named as Bacillus subtilis. The experimental investigation was carried out to evaluate the improvement of the compressive strength, capillary water absorption, and drying shrinkage of RCA concrete incorporating bacteria. The compressive strength of RCA concrete is found to be increased by about 20% when the cell concentration of B. subtilis is 10⁶ cells/ml. The capillary water absorption as well as drying shrinkage of RCA are reduced when bacteria is incorporated. The improvement of RCA concrete is confirmed to be due to the calcium carbonate precipitation as observed from the microstructure studies carried out on it such as EDX, SEM, and XRD.     

Nitroarenes as Antitubercular Agents: Stereoelectronic Modulation to Mitigate Mutagenicity

Nitroarenes are less preferred in drug discovery due to their potential to be mutagenic. However, several nitroarenes were shown to be promising antitubercular agents with specific modes of action, namely, nitroimidazoles and benzothiazinones. The nitro group in these compounds is activated through different mechanisms, both enzymatic and non‐enzymatic, in mycobacteria prior to binding to the target of interest. From a whole‐cell screening program, we identified a novel lead nitrobenzothiazole (BT) series that acts by inhibition of decaprenylphosphoryl‐β‐d ‐ribose 2′‐epimerase (DprE1) of Mycobacterium tuberculosis (Mtb). The lead was found to be mutagenic to start with. Our efforts to mitigate mutagenicity resulted in the identification of 6‐methyl‐7‐nitro‐5‐(trifluoromethyl)‐1,3‐benzothiazoles (cBTs), a novel class of antitubercular agents that are non‐mutagenic and exhibit an improved safety profile. The methyl group ortho to the nitro group decreases the electron affinity of the series, and is hence responsible for the non‐mutagenic nature of these compounds. Additionally, the co‐crystal structure of cBT in complex with Mtb DprE1 established the mode of binding. This investigation led to a new non‐mutagenic antitubercular agent and demonstrates that the mutagenic nature of nitroarenes can be solved by modulation of stereoelectronic properties.     

Mechanistic origins of multi-scale reinforcements in segmented polyurethane-clay nanocomposites

The objective of the present work is to get insights into the mechanistic origin of the reinforcement effects of nanoclay on a segmented polybutadiene polyurethane-urea system. To this end, a convergent analysis of the hard domain morphology and conformational state of soft segment in the nanocomposites was carried out by using a combination of complementary characterization techniques, namely, Fourier transform infrared spectroscopy, small angle neutron scattering, transmission electron microscopy, modulated differential scanning calorimetry and dynamic mechanical analysis. Analysis of small angle neutron scattering data by a combination of Percus–Yevick hard sphere and Zernike-Ornstein model coupled with direct visualization of the dispersed hard domain morphology from transmission electron microscopy provided insight on clay induced changes in the hard domain morphology. A monotonic decrease in the domain size as well as the average interdomain distance was observed with increasing nanoclay content in the polymer matrix. Analysis of the carbonyl stretching region from FTIR showed increased degree of hydrogen bonding for the urethane carbonyl groups of the nanocomposites compared to the neat matrix. A combination of calorimetric and dynamic mechanical analysis revealed the existence of a constrained amorphous region; quantified to be ≈ 16% at the highest clay content experimented. The manifestation of these morphological and conformational changes on the nano-, micro- and macro scale reinforcements in the nanocomposites was investigated by mechanical properties at these length scales using nanoindentation, DMA and tensile testing, respectively.     

A production-recycling-inventory model with learning effect

This paper develops an integrated production-recycling system over a finite time horizon. Here, the dynamic demand is satisfied by production and recycling. The used units are bought back and then either recycled or disposed of which are not repairable. The used units are collected continuously from the customers. Recycling products can be used as new products which are sold again. The rate of production and disposal are assumed to be function of time. The setup cost is reduced over time due to “Learning curve” effect. The optimum results are presented both in tabular form and graphically.     

Computer-aided design of chiral ligands. Part I. Database search methods to identify chiral ligand types for asymmetric reactions

The utility of database searching to identify chiral ligand motifs is outlined. The key elements of three known chiral ligands have been described as bond vectors. The CAVEAT program was then used to screen the Cambridge Structural Database (CSD), portions of the Chemical Abstracts Services three-dimensional database (CAS-3D), and the TRIAD tricyclic structure database for scaffolds containing these elements. Scaffolds corresponding to the known starting points were identified indicating that this method can be used to identify chiral ligand structural motifs. In addition, alternate structural motifs were found that suggested alternative possible ligands.     

Second generation waste package design and storage concept for the Yucca Mountain Repository

The reference waste package design and operating mode to be used in the Yucca Mountain Repository is reviewed. An alternate (second generation) operating concept and waste package design is proposed to reduce the risk of localized corrosion of waste packages and to reduce repository costs. The second generation waste package design and storage concept is proposed for implementation after the initial licensing and operation of the reference repository design. Implementation of the second generation concept at Yucca Mountain would follow regulatory processes analogous to those used successfully to extend the design life and uprate the power of commercial light water nuclear reactors in the United States. The second generation concept utilizes the benefits of hot dry storage to minimize the potential for localized corrosion of the waste package by liquid electrolytes. The second generation concept permits major reductions in repository costs by increasing the number of fuel assemblies stored in each waste package, by eliminating the need for titanium drip shields and by fabricating the outer container from corrosion resistant low alloy carbon steel.