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A wearable sensing system that can reconstruct dynamic 3D human body models for virtual cloth fitting is highly important in the era of information and metaverse. However, few research has been conducted regarding conformal sensors for accurately measuring the human body circumferences for dynamic 3D human body reshaping. Here, we develop a stretchable spring‐sheathed yarn sensor (SSYS) as a smart ruler, for precisely measuring the circumference of human bodies and long‐term tracking the movement for the dynamic 3D body reconstruction. The SSYS has a robust property, high resilience, high stability (>18 000), and ultrafast response (12 ms) to external deformation. It is also washable, wearable, tailorable, and durable for long‐time wearing. Moreover, geometric, and mechanical behaviors of the SSYS are systematically investigated both theoretically and experimentally. In addition, a transfer learning algorithm that bridges the discrepancy of real and virtual sensing performance is developed, enabling a small body circumference measurement error of 1.79%, noticeably lower than that of traditional learning algorithm. Furtherly, 3D human bodies that are numerically consistent with the actual bodies are reconstructed. The 3D dynamic human body reconstruction based on the wearing sensing system and transfer learning algorithm enables excellent virtual fitting and shirt customization in a smart and highly efficient manner. This wearable sensing technology shows great potential in human‐computer interaction, intelligent fitting, specialized protection, sports activities, and human physiological health tracking. [ABSTRACT FROM AUTHOR]

In a recent perspective (Diversity and Distributions, 29, 39–50), '10 variables' were proposed to measure vegetation structure from airborne laser scanning (ALS) for assessing species distributions and habitat suitability. We worry about this list because the variables predominantly represent variation in vegetation height, the vertical variability of vegetation biomass is insufficiently captured, and variables of vegetation cover are ill‐defined or not ecosystem agnostic. We urge for a better defined, more comprehensive and more balanced list, and for assessing which information from ALS point clouds is truly essential to measure the major dimensions of 3D vegetation structure within and across ecosystems and animal habitats. We think that the currently proposed 'list of 10 ALS metrics' is premature and that researchers and stakeholders should be cautious in adopting this list. [ABSTRACT FROM AUTHOR]

Natural materials have irreplaceable advantages in the preparation of in vivo/vitro electronic devices. However, most current fabrication techniques for flexible electronics are not compatible with natural materials due to mechanical and chemical stability issues. In this work, an ink‐jet printing and electrodeposition coupling technique is introduced to fabricate pattern electrodes on silk fibroin and polyurethane (SF‐PU) composite films. The addition of PU can improve the chemical properties of SF film while maintaining its considerable permeability and biocompatibility. Owing to such composite film, different pattern electrodes are successfully printed by ink‐jet printing technology. Subsequently, a layer of nickel (Ni) is electrodeposited on printed electrodes to protect and further enhance the conductivity the electrodes (<0.01 Ω cm−1). Based on these double‐layer pattern electrodes, an integrated protein‐based electronic skin (PPES) is developed for pressure distribution monitoring. This ink‐jet and electrodeposition (IJ‐ED) coupling technique is particularly beneficial to the manufacture of next‐generation in vivo/vitro bioelectronic devices. [ABSTRACT FROM AUTHOR]

Virtual research environments (VREs) provide user‐centric support in the lifecycle of research activities, for example, discovering and accessing research assets or composing and executing application workflows. A typical VRE is often implemented as an integrated environment, including a catalog of research assets, a workflow management system, a data management framework, and tools for enabling user collaboration. In contrast, notebook environments like Jupyter allow researchers to rapidly prototype scientific code and share their experiments as online accessible notebooks. Jupyter can support several popular languages used by data scientists, such as Python, R, and Julia. However, such notebook environments do not have seamless support for running heavy computations on remote infrastructure or finding and accessing collaborative software code inside notebooks. This article investigates the gap between a notebook environment and a VRE and proposes an embedded VRE solution for the Jupyter environment called Notebook‐as‐a‐VRE (NaaVRE). The NaaVRE solution provides functional components via a component marketplace and allows users to create a customized VRE on top of the Jupyter environment. From the VRE, a user can search research assets (data, software, and algorithms), compose workflows, manage the lifecycle of an experiment, and share the results among users in the community. We demonstrate how such a solution can enhance a legacy workflow that uses Light Detection and Ranging (LiDAR) data from country‐wide airborne laser scanning surveys for deriving geospatial data products of ecosystem structure at high resolution over broad spatial extents. This enables users to scale out the processing of multi‐terabyte LiDAR point clouds for ecological applications to more data sources in a distributed cloud environment. Similar applications could be developed for workflows producing other essential biodiversity variables. [ABSTRACT FROM AUTHOR]

The cover image is based on the Research Article I Notebook-as-a-VRE (NaaVRE): From private notebooks to a collaborative cloud virtual research environment i by Zhiming Zhao et al., https://doi.org/10.1002/spe.3098. [Extracted from the article]