Optimal Conditions of Paint Wastewater Coagulation With Gastropod Shell Conchiolin Using Response Surface Design and Artificial Neural Network-Genetic Algorithm

The potential of gastropod shell conchiolin (GSC) (a waste product of the deprotenization stage of chitosan production) as one of the alternatives to chemical coagulants has been explored for treatment of paint industrial wastewater (PW). The accuracy of response surface design (RSD) and the precision of artificial intelligence (AI) in predicting and optimizing the process conditions were harnessed in raising experimental design matrix and response optimization, respectively for the bench scale jar test coagulation experiment. PW was characterized using American public health association (APHA) standard methods. Extraction of conchiolin was done via alkaline extraction method. PW contains 2098mg/l total suspended solid (TSS) above discharge limit (1905mg/l). Fourier transform infrared (FTIR) spectrum of GSC revealed a broad N–H wagging band at 750 – 650 cm−1 indicating the presence of secondary amine linked to the presence of protein. Turbidity removal from PW via one factor at a time (OFAT) was found to be a function of pH, GSC dosage, temperature and time. Artificial neural network (ANN) response prediction shows 92% correlation with the response surface design (RSD) experimental result. The optimal conditions obtained via genetic algorithm (GA) for the response optimization at the best pH of 4 indicate optimal turbidity removal of 98% at GSC dosage, time and temperature of 4 g, 20 min and 45oC, respectively.

Structural patterns of a coastal hermit crab-gastropod shell interaction network: new insights from a unique relationship

Hermit crabs are ideal organisms for assessing how species that share resources can coexist, as these crustacean species have an intimate relationship with gastropod shells and therefore compete for this particular resource. There is compelling evidence that hermit crabs do not interact with gastropod shells randomly, but few studies have investigated the community-level interactions between hermit crabs and shells. Here we used network analyses to present the first community-level assessment of the structure of a hermit crab-shell interaction network in a coastal region in southeastern Brazil in order to identify mechanisms that underlie hermit crab coexistence. Our results show that the hermit crab-gastropod shell interaction network was non-nested, specialized, and modular. The modular network structure revealed differences in resource use among hermit crab species. The network structure departs from those of free-living species in which the lack of interaction intimacy between species leads to a nested pattern. Thus, the morphological specialization of hermit crabs in relation to their host shells appears to play an important role in structuring the community-level interaction network. Future studies should evaluate the relative importance of abundance and functional traits in the structure of this unique interaction network.

A developmentally descriptive method for quantifying shape in gastropod shells

The growth of snail shells can be described by simple mathematical rules. Variation in a few parameters can explain much of the diversity of shell shapes seen in nature. However, empirical studies of gastropod shell shape variation typically use geometric morphometric approaches, which do not capture this growth pattern. We have developed a way to infer a set of developmentally descriptive shape parameters based on three-dimensional logarithmic helicospiral growth and using landmarks from two-dimensional shell images as input. We demonstrate the utility of this approach, and compare it to the geometric morphometric approach, using a large set of Littorina saxatilis shells in which locally adapted populations differ in shape. Our method can be modified easily to make it applicable to a wide range of shell forms, which would allow for investigations of the similarities and differences between and within many different species of gastropods.