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Delivery drones are a disruptive technology that is spurring logistics system change, such as the adoption of urban micro-fulfilment centres (MFCs). In this paper, we develop and implement a two-stage continuum approximation (CA) model of this disruptive system in a geographic information system. The model includes common CA techniques at a local level to minimise cost, and then these local solutions are used in a second stage regional location-allocation multiple knapsack problem. We then compare the drone MFC system to a traditional delivery-by-van system and investigate potential cost or emissions savings by adjusting time-window demand, logistical sprawl, electric van alternatives, and MFC emissions. Furthermore, we conduct a sensitivity analysis to show that uncertainty in demand and effective storage density both significantly influence the number of MFCs selected and benchmark our model against commercial solvers. This methodology may also be further developed and applied to other new delivery vehicle modes.

Abstract Mid- to late-Miocene continental arc volcanism on the North Island of New Zealand is found in the Coromandel Peninsula, the Kiwitahi volcanic chain and the Taranaki Basin (Kora Volcano) offshore the western margin of the North Island. Coeval oceanic arc volcanism is also found along the offshore Colville Ridge/Kermadec Ridge north of New Zealand. This Pb–Sr–Nd–Hf isotopic study aims to evaluate mantle sources and potential crustal contaminants along these sections of the Miocene arc system. The Colville/Kermadec Ridge and Kora lavas have the lowest Sr (0.7029–0.7045) and highest Nd (0.51305–0.51292) ratios; the Coromandel and Kiwitahi lavas overlap (Sr = 0.704–0.706; Nd = 0.51268–0.51296). The Colville/Kermadec Ridge, Kora, and Coromandel/Kiwitahi rocks form three distinct arrays on Pb–Pb plots, all above the Northern Hemisphere Reference Line, but none trend towards local Mesozoic basement greywackes. Isotopic and trace element ratio variations suggest that subducted sediments are a component in Coromandel/Kiwitahi mafic lava sources. The younger, southern Kiwitahi lavas have a more depleted mantle source than that for the older, northern Kiwitahi chain. Evolved lavas commonly have interacted with Waipapa basement rocks. Kora rocks have compositions similar to those of back-arc lavas and have been emplaced as sills in a rift environment above a distinct subduction-modified mantle.

This study investigates the factors influencing university student’s living arrangement choice, the distance between home and the university, and mode choice. A closed-form probabilistic choice modelling formulation is developed to model three choices jointly: student’s living arrangement choice, the distance between home and the university, and student’s typical commuting mode choice to campus. The proposed joint model harnesses the power of both Random Utility Maximisation (RUM) and Cobb–Douglas direct utility maximisation principle. This study identifies the nature and extent of various systematic and random factors influencing university student’s residence and mode choice behaviour to provide evidence for the planners and policymakers to act upon. Walk and cycling accessibility appear to be the most influential factor in the distance between home and the university. The results suggest that affordable housing choices by university campuses can significantly increase the number of active mode users among the student population in Toronto.

The ability to obtain accurate precipitation data from various geographic locations is crucial for many applications. Various global products have been released in recent decades for estimating precipitation spatially and temporally. Nevertheless, it is extremely important to provide reliable and accurate products for estimating precipitation in a variety of environments. This is due to the complexity of topographic, climatic, and other factors. This study proposes a multi-product information combination for improving precipitation data accuracy based on a generalized regression neural network model using global and local optimization strategies. Firstly, the accuracy of ten global precipitation products from four different categories (satellite-based, gauge-corrected satellites, gauge-based, and reanalysis) was assessed using monthly precipitation data collected from 1896 gauge stations in Iran during 2003–2021. Secondly, to enhance the accuracy of the modeled precipitation products, the importance score of effective and auxiliary variables—such as elevation, the Enhanced Vegetation Index (EVI), the Land Surface Temperature (LST), the Soil Water Index (SWI), and interpolated precipitation maps—was assessed. Finally, a generalized regression neural network (GRNN) model with global and local optimization strategies was used to combine precipitation information from several products and auxiliary characteristics to produce precipitation data with high accuracy. Global precipitation products scored higher than interpolated precipitation products and surface characteristics. Furthermore, the importance score of the interpolated precipitation products was considerably higher than that of the surface characteristics. SWI, elevation, EVI, and LST scored 53%, 20%, 15%, and 12%, respectively, in terms of importance. The lowest RMSE values were associated with IMERGFinal, TRMM3B43, PERSIANN-CDR, ERA5, and GSMaP-Gauge. For precipitation estimation, these products had Kling–Gupta efficiency (KGE) values of 0.89, 0.86, 0.77, 0.78, and 0.60, respectively. The proposed GRNN-based precipitation product with a global (local) strategy showed RMSE and KGE values of 9.6 (8.5 mm/mo) and 0.92 (0.94), respectively, indicating higher accuracy. Generally, the accuracy of global precipitation products varies depending on climatic conditions. It was found that the proposed GRNN-derived precipitation product is more efficient under different climatic conditions than global precipitation products. Moreover, the local optimization strategy based on climatic classes outperformed the global optimization strategy.

Data S1. Results of HMM-motif search for KN-A, KN-B, and PBL-Red domains. Data S2. Alignment of the KN-A, KN-B, and PBL-Red domains. (PDF 66 kb)

Table S1. Genomic resources used in this study. Table S2. Archaeplastidal homeobox collection of TALE protein analyzed in this study. Table S3. KNOX domain homology among KNOX classes. Table S4. Primers used in this study. Table S5. Yeast-two-hybrid constructs used in this study. Table S6. Homeobox profile in Trebouxiophyceae. (XLSX 370 kb)

Additional file 1 : Fig. S1. A-C – Syssomonas multiformis sucks out the cytoplasm of the prey; D – three cells of Syssomonas (s) suck out the cytoplasm of the same prey cell together, other Syssomonas cells (arrows) become attracted and swim to the same prey cell; E – unusual flagellated cell of Syssomonas containing vesicular structures; F – cells of Syssomonas with engulfed starch granules swim to the starch crystals druse and hide within the starch crystals. Fig. S2. Rice grain destruction in Petri dish with Pratt medium and presence of the cells of Parabodo caudatus (prey) only (A) and Syssomonas multiformis (B) after 9 days of incubation.

Note S1. Lack of TALE TFs in Trebouxiophyceae. Note S2. Horizontal transfer may explain the presence of Rhodophyta TALE heterodimers in Picocystis and Klebsormidium of Viridiplantae. (PDF 55 kb)