Evaluation efficiency of large-scale data set with negative data:an artificial neural network approach

Data envelopment analysis (DEA) is the most widely used methods for measuring the efficiency and productivity of decision-making units (DMUs). The need for huge computer resources in terms of memory and CPU time in DEA is inevitable for a large-scale data set, especially with negative measures. In recent years, wide ranges of studies have been conducted in the area of artificial neural network and DEA combined methods. In this study, a supervised feed-forward neural network is proposed to evaluate the efficiency and productivity of large-scale data sets with negative values in contrast to the corresponding DEA method. Results indicate that the proposed network has some computational advantages over the corresponding DEA models; therefore, it can be considered as a useful tool for measuring the efficiency of DMUs with (large-scale) negative data.

A pragmatic approach for engineering porous mannitol and mechanistic evaluation of particle performance

The importance of mannitol has increased recently as an emerging diluent for orodispersible dosage forms. The study aims to prepare spray dried mannitol retaining high porosity and mechanical strength for the development of orally disintegrating tablets (ODTs). Aqueous feed of d-mannitol (10% w/v) comprising ammonium bicarbonate, NH4HCO3 (5% w/v) as pore former was spray dried at inlet temperature of 110-170°C. Compacts were prepared at 151MPa and characterized for porosity, hardness and disintegration time. Particle morphology and drying mechanisms were studied using thermal (HSM, DSC and TGA) and polymorphic (XRD) methods. Tablet porosity increased from 0.20±0.002 for pure mannitol to 0.53±0.03 using fabricated porous mannitol. Disintegration time dropped by 50-77% from 135±5.29s for pure mannitol to 75.33±2.52-31.67±1.53s for mannitol 110-170°C. Hardness increased by 150% at 110°C (258.67±28.89N) and 30% at 150°C (152.70±10.58N) compared to pure mannitol tablets (104.17±1.70N). Increasing inlet temperature resulted in reducing tablet hardness due to generation of 'micro-sponge'-like particles exhibiting significant elastic recovery. Impact of mannitol polymorphism on plasticity/elasticity cannot be ruled out as a mixture of α and β polymorphs formed upon spray drying.

Performance evaluation of reverse osmosis (RO) pre-treatment technologies for in-land brackish water treatment

Integration of renewable energy with desalination technologies has emerged as an attractive solution to augment fresh water supply sustainably. Fouling and scaling are still considered as limiting factors in membrane desalination processes. For brackish water treatment, pre-treatment of reverse osmosis (RO) feed water is a key step in designing RO plants avoiding membrane fouling. This study aims to compare at pilot scale the rejection efficiency of RO membranes with multiple pre-treatment options at different water recoveries (30, 35, 40, 45 and 50%) and TDS concentrations (3500, 4000, and 4500mg/L). Synthetic brackish water was prepared and performance evaluation were carried out using brackish water reverse osmosis (BWRO) membranes (Filmtec LC-LE-4040 and Hydranautics CPA5-LD-4040) preceded by 5 and 1μm cartridge filters, 0.02μm ultra-filtration (UF) membrane, and forward osmosis (FO) membrane using 0.25M NaCl and MgCl2 as draw solutions (DS). It was revealed that FO membrane with 0.25M MgCl2 used as a draw solution (DS) and Ultra-filtration (UF) membrane followed by Filmtec membrane gave overall 98% rejection but UF facing high fouling potential due to high applied pressure. Use of 5 and 1μm cartridge filter prior to Filmtec membrane also showed effective results with 95% salt rejection.