ESIDE: A computationally intelligent method to identify earthworm species (E. fetida) from digital images: Application in taxonomy.

Earthworms (Crassiclitellata) being ecosystem engineers significantly affect the physical, chemical, and biological properties of the soil by recycling organic material, increasing nutrient availability, and improving soil structure. The efficiency of earthworms in ecology varies along with species. Therefore, the role of taxonomy in earthworm study is significant. The taxonomy of earthworms cannot reliably be established through morphological characteristics because the small and simple body plan of the earthworm does not have anatomical complex and highly specialized structures. Recently, molecular techniques have been adopted to accurately classify the earthworm species but these techniques are time-consuming and costly. To combat this issue, in this study, we propose a machine learning-based earthworm species identification model that uses digital images of earthworms. We performed a stringent performance evaluation not only through 10-fold cross-validation and on an external validation dataset but also in real settings by involving an experienced taxonomist. In all the evaluation settings, our proposed model has given state-of-the-art performance and justified its use to aid earthworm taxonomy studies. We made this model openly accessible through a cloud-based webserver and python code available at https://sites.google.com/view/wajidarshad/software and https://github.com/wajidarshad/ESIDE.

High-performance graphene/sulphur electrodes for flexible Li-ion batteries using the low-temperature spraying method.

Elementary sulphur (S) has been shown to be an excellent cathode material in energy storage devices such as Li-S batteries owing to its very high capacity. The major challenges associated with the sulphur cathodes are structural degradation, poor cycling performance and instability of the solid-electrolyte interphase caused by the dissolution of polysulfides during cycling. Tremendous efforts made by others have demonstrated that encapsulation of S materials improves their cycling performance. To make this approach practical for large scale applications, the use of low-cost technology and materials has become a crucial and new focus of S-based Li-ion batteries. Herein, we propose to use a low temperature spraying process to fabricate graphene/S electrode material, where the ink is composed of graphene flakes and the micron-sized S particles prepared by grinding of low-cost S powders. The S particles are found to be well hosted by highly conductive graphene flakes and consequently superior cyclability (∼70% capacity retention after 250 cycles), good coulombic efficiency (∼98%) and high capacity (∼1500 mA h g(-1)) are obtained. The proposed approach does not require high temperature annealing or baking; hence, another great advantage is to make flexible Li-ion batteries. We have also demonstrated two types of flexible batteries using sprayed graphene/S electrodes.