Maize-IAS: a maize image analysis software using deep learning for high-throughput plant phenotyping.

Background: Maize (Zea mays L.) is one of the most important food sources in the world and has been one of the main targets of plant genetics and phenotypic research for centuries. Observation and analysis of various morphological phenotypic traits during maize growth are essential for genetic and breeding study.

Fabrication of Fe-doped birnessite with tunable electron spin magnetic moments for the degradation of tetracycline under microwave irradiation.

Manganese oxides exhibit an excellent microwave absorption performance that could increase the degradation efficiency of organic pollutants in contaminated water. Incorporation of various transition metals into manganese oxides could bring about changes in their crystal structure and improve their physicochemical performance. In this work, a better microwave absorption material was obtained by adjusting and controlling the electron spin magnetic moments of Fe-doped birnessite.

Higher fungal diversity is correlated with lower CO2 emissions from dead wood in a natural forest.

Wood decomposition releases almost as much CO2 to the atmosphere as does fossil-fuel combustion, so the factors regulating wood decomposition can affect global carbon cycling. We used metabarcoding to estimate the fungal species diversities of naturally colonized decomposing wood in subtropical China and, for the first time, compared them to concurrent measures of CO2 emissions. Wood hosting more diverse fungal communities emitted less CO2, with Shannon diversity explaining 26 to 44% of emissions variation.

Plant diversity accurately predicts insect diversity in two tropical landscapes.

Plant diversity surely determines arthropod diversity, but only moderate correlations between arthropod and plant species richness had been observed until Basset et al. (Science, 338, 2012 and 1481) finally undertook an unprecedentedly comprehensive sampling of a tropical forest and demonstrated that plant species richness could indeed accurately predict arthropod species richness. We now require a high-throughput pipeline to operationalize this result so that we can (i) test competing explanations for tropical arthropod megadiversity, (ii) improve estimates of global eukaryotic species diversity, and (iii) use plant and arthropod communities as efficient proxies for each other, thus improving the efficiency of conservation planning and of detecting forest degradation and recovery.

High-throughput monitoring of wild bee diversity and abundance via mitogenomics.

Bee populations and other pollinators face multiple, synergistically acting threats, which have led to population declines, loss of local species richness and pollination services, and extinctions. However, our understanding of the degree, distribution and causes of declines is patchy, in part due to inadequate monitoring systems, with the challenge of taxonomic identification posing a major logistical barrier. Pollinator conservation would benefit from a high-throughput identification pipeline.

A mathematical model of cancer treatment by radiotherapy.

A periodic mathematical model of cancer treatment by radiotherapy is presented and studied in this paper. Conditions on the coexistence of the healthy and cancer cells are obtained. Furthermore, sufficient conditions on the existence and globally asymptotic stability of the positive periodic solution, the cancer eradication periodic solution, and the cancer win periodic solution are established.

Testing three pipelines for 18S rDNA-based metabarcoding of soil faunal diversity.

A number of basic and applied questions in ecology and environmental management require the characterization of soil and leaf litter faunal diversity. Recent advances in high-throughput sequencing of barcode-gene amplicons ('metabarcoding') have made it possible to survey biodiversity in a robust and efficient way. However, one obstacle to the widespread adoption of this technique is the need to choose amongst many candidates for bioinformatic processing of the raw sequencing data.