Ionic liquids (ILs)-as environmentally friendly "green" solvents-have been progressively used in various reactions as reagents, solvents and co-solvents including lipase-catalysed reactions. In fact, lipase-catalysed reactions in ILs are considered as a "green"-reaction and are more advantageous than chemical methods owing to the easy recovery of the product and the mild conditions of the reactions. The use of lipase in ILs provides many technological advantages compared to conventionally used solvents, such as selectivity enhancement, enzyme stability improvement, higher conversion rate, and better recyclability and recovery system. Nevertheless, in some cases, especially in hydrophilic ILs, lipase exhibits activity reduction when compared with organic solvents. Currently, various attempts have been made to enhance the performance of lipases in ILs. The main objective of this review is to demonstrate recent developments in the technology of using ILs as reaction media for lipase. It is expected that this review might be an inspiration in ILs assisted lipase-catalysed reactions to produce value-added materials including biofuels as well as biodiesel.

The two-fold threats of the crisis of petrochemical industry-based plastics and serious environmental pollution have triggered the valorization of naturally occurring biopolymers to produce nanocellulose (NC). Nanocellulose has been used extensively in a variety of demanding applications due to its excellent features including biocompatibility, light weight, tunable surface properties, and improved environmental footprint. However, the sustainable production of NC is still confronted with bottlenecks to realize commercial feasibility due to poor solubility and hard processability of biopolymers using conventional hazardous solvents and reagents including concentrated sulfuric acid. The key might rest on the use of ionic liquids (ILs) that have induced a great deal of interest in recent years as powerful “green” solvents for biopolymer processing. ILs can be used as a catalyst and/or reaction medium and/or swelling agent for NC production with an eminent yield of high-quality NC under mild operating conditions coupled with proficient recoverability and recyclability. This review presents the recent technological developments of ILs-assisted proper valorization strategies of numerous bioresources for NC isolation and modification. The impact of IL cation/anion on structural changes of NC is also covered. The major advances in exploring ILs for NC surface modification reactions such as esterification, silylation, and surface plasticization as well as the microscopic insights of NC interaction with ILs are also reviewed. In view of the dominance of green chemistry principles for high purity of the recovered nanocellulose, close R&D endeavors for cheap and biodegradable ILs conjoined with emerging recycling techniques might boost sustainable commercialization.

The effects of medium components affecting lipase production by Aspergillus niger AS-02 using sheanut cake (SNC) were studied based on the one-factor-at-a-time (OFAT) method and the face-centred central composite design (FCCCD). Of the six medium components analysed by OFAT, three (Tween-80, (NH 4) 2 SO 4 and Na 2 HPO 4) were subjected to FCCCD. Under optimized conditions, the obtained lipase production showed good agreement between the experimental (49.37 U/g) and predicted (48.81 U/g) yields, with a coefficient of determination (R 2) of 0.96. The optimum medium components were 1.0% (v/w) Tween-80, 0.35% (w/w) (NH 4) 2 SO 4 and 0.40% (w/w) Na 2 HPO 4. The findings in this study showed that, in addition to lipase production, the fermented SNC had reduced tannin and saponin contents, which are the major components that limit the use of SNC in feed formulations.

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BackgroundMalaria, being a mosquito-borne infectious disease, is still one of the most devastating global health issues. The malaria vector Anopheles vagus is widely distributed in Asia and a dominant vector in Bandarban, Bangladesh. However, despite its wide distribution, no agent based model (ABM) of An. vagus has yet been developed. Additionally, its response to combined vector control interventions has not been examined.MethodsA spatial ABM, denoted as ABM, was designed and implemented based on the biological attributes of An. vagus by modifying an established, existing ABM of Anopheles gambiae. Environmental factors such as temperature and rainfall were incorporated into ABM using daily weather profiles. Real-life field data of Bandarban were used to generate landscapes which were used in the simulations. ABM was verified and validated using several standard techniques and against real-life field data. Using artificial landscapes, the individual and combined efficacies of existing vector control interventions are modeled, applied, and examined.ResultsSimulated female abundance curves generated by ABM closely follow the patterns observed in the field. Due to the use of daily temperature and rainfall data, ABM was able to generate seasonal patterns for a particular area. When two interventions were applied with parameters set to mid-ranges, ITNs/LLINs with IRS produced better results compared to the other cases. Moreover, any intervention combined with ITNs/LLINs yielded better results. Not surprisingly, three interventions applied in combination generate best results compared to any two interventions applied in combination.ConclusionsOutput of ABM showed high sensitivity to real-life field data of the environmental factors and the landscape of a particular area. Hence, it is recommended to use the model for a given area in connection to its local field data. For applying combined interventions, three interventions altogether are highly recommended whenever possible. It is also suggested that ITNs/LLINs with IRS can be applied when three interventions are not available.Electronic supplementary materialThe online version of this article (doi:10.1186/s12936-017-2075-6) contains supplementary material, which is available to authorized users.

Solid state bioconversion (SSB) of lignocellulosic material oil palm biomass (OPB) generated from palm oil industries as waste was conducted by evaluating the enzyme production through filamentous fungus in lab-scale experiment. OPB in the form of empty fruit bunches (EFB) was used as the solid substrate and treated with the fungus Trichoderma harzianum to produce cellulase. The results presented in this study revealed that the higher cellulase activity of 0.0413 unit was achieved at the day 3 of fermentation. While the optimum study indicated the enzyme production of 0.0433 unit with moisture content of 50%, 0.0413 unit with 5% v/w of inoculum size and 0.0413 unit with co-substrate concentration of 2% (w/w) at days 9, 9 and 12 of fungal treatment, respectively. The parameters glucosamine and reducing sugar were observed to evaluate the growth and substrate utilization in the experiment

The main motive of this study is to investigate the use of ARCH model for forecasting volatility of the DSE20 and DSE general indices by using the daily data. GARCH, EGARCH, PARCH, and TARCH models are used as benchmark models for the study purpose. This study covers from December 1, 2001 to August 14, 2008 and from August 18, 2008 to September 10, 2011 as in-sample and out-of-sample set sets respectively. The study finds the past volatility of both the DSE20 and DSE general indices returns series are significantly, influenced current volatility. Based on in-sample statistical performance, both the ARCH and PARCH models are considered as the best performing model jointly for DSE20 index returns, whereas for DSE general index returns series, ARCH model outperforms other models. According to the out – of- sample statistical performance, all models except GARCH and TARCH models are regarded as the best model jointly for DSE20 index returns series, while for DSE general index returns series, no model is nominated as the best model individually. Based on the in-sample trading performance, all models except GARCH are considered as the best model jointly for DSE20 index returns series, while ARCH model is selected as the best model for DSE general index returns series. A per outputs of out-of-sample trading performance, the EGARCH model is the best performing model for DSE20 index returns series, whereas the GARCH and ARCH models are considered as the best performing model jointly for DSE general index returns series