Earth orbiting satellites come in a wide range of shapes and sizes to meet a diverse variety of uses and applications. Large satellites with masses over 1000 kg support high-resolution remote sensing ...of the Earth, high bandwidth communications services, and world-class scientific studies but take lengthy developments and are costly to build and launch. The advent of commercially available, high-volume, and hence low-cost microelectronics has enabled a different approach through miniaturization. This results in physically far smaller satellites that dramatically reduce timescales and costs and that are able to provide operational and commercially viable services. This paper charts the evolution and rise of small satellites from being an early curiosity with limited utility through to the present where small satellites are a key element of modern space capabilities.
Considerable evidence suggests that the steroid hormone testosterone mediates major life-history trade-offs in vertebrates, promoting mating effort at the expense of parenting effort or survival. ...Observations from a range of wild primates support the “Challenge Hypothesis,” which posits that variation in male testosterone is more closely associated with aggressive mating competition than with reproductive physiology. In both seasonally and non-seasonally breeding species, males increase testosterone production primarily when competing for fecund females. In species where males compete to maintain long-term access to females, testosterone increases when males are threatened with losing access to females, rather than during mating periods. And when male status is linked to mating success, and dependent on aggression, high-ranking males normally maintain higher testosterone levels than subordinates, particularly when dominance hierarchies are unstable. Trade-offs between parenting effort and mating effort appear to be weak in most primates, because direct investment in the form of infant transport and provisioning is rare. Instead, infant protection is the primary form of paternal investment in the order. Testosterone does not inhibit this form of investment, which relies on male aggression. Testosterone has a wide range of effects in primates that plausibly function to support male competitive behavior. These include psychological effects related to dominance striving, analgesic effects, and effects on the development and maintenance of the armaments and adornments that males employ in mating competition.
•Testosterone promotes mating effort in primates, at the expense of survival.•In primates testosterone primarily facilitates aggression in reproductive contexts.•Trade-offs between parenting effort and mating effort are weak in most primates.•Testosterone's psychological and physiological effects promote male competition.
Multivariate decoding methods were developed originally as tools to enable accurate predictions in real-world applications. The realization that these methods can also be employed to study brain ...function has led to their widespread adoption in the neurosciences. However, prior to the rise of multivariate decoding, the study of brain function was firmly embedded in a statistical philosophy grounded on univariate methods of data analysis. In this way, multivariate decoding for brain interpretation grew out of two established frameworks: multivariate decoding for predictions in real-world applications, and classical univariate analysis based on the study and interpretation of brain activation. We argue that this led to two confusions, one reflecting a mixture of multivariate decoding for prediction or interpretation, and the other a mixture of the conceptual and statistical philosophies underlying multivariate decoding and classical univariate analysis. Here we attempt to systematically disambiguate multivariate decoding for the study of brain function from the frameworks it grew out of. After elaborating these confusions and their consequences, we describe six, often unappreciated, differences between classical univariate analysis and multivariate decoding. We then focus on how the common interpretation of what is signal and noise changes in multivariate decoding. Finally, we use four examples to illustrate where these confusions may impact the interpretation of neuroimaging data. We conclude with a discussion of potential strategies to help resolve these confusions in interpreting multivariate decoding results, including the potential departure from multivariate decoding methods for the study of brain function.
•We highlight two sources of confusion that affect the interpretation of multivariate decoding results.•Confusion 1: The dual use of multivariate decoding for real-world predictions and interpretation in terms of brain function.•Confusion 2: A mixture of statistical and conceptual frameworks of classical univariate analysis and multivariate decoding.•We show six differences between univariate analysis and multivariate decoding and a different meaning of signal and noise.•We use four illustrative examples to reveal these confusions and the assumptions of multivariate decoding for interpretation.
Adolescents spend an increasing amount of time using digital media, but gender differences in their use and in associations with psychological well-being are unclear.
We drew from three large, ...representative surveys of 13- to 18-year-old adolescents in the U.S. and UK (total N = 221,096) examining digital media use in hours per day and several measures of psychological well-being separately in each of the three datasets.
Adolescent girls spent more time on smartphones, social media, texting, general computer use, and online, and boys spent more time gaming and on electronic devices in general. Associations between moderate or heavy digital media use and low psychological well-being/mental health issues were generally larger for girls than for boys. Light users of digital media were slightly higher in well-being than non-users, with larger differences among boys. Among both genders, heavy users of digital media were often twice as likely as low users to be low in well-being or have mental health issues, including risk factors for suicide.
Associations between heavy digital media use and low psychological well-being are larger for adolescent girls than boys.
In nationally representative yearly surveys of United States 8th, 10th, and 12th graders 1991-2016 (N = 1.1 million), psychological well-being (measured by self-esteem, life satisfaction, and ...happiness) suddenly decreased after 2012. Adolescents who spent more time on electronic communication and screens (e.g., social media, the Internet, texting, gaming) and less time on nonscreen activities (e.g., in-person social interaction, sports/exercise, homework, attending religious services) had lower psychological well-being. Adolescents spending a small amount of time on electronic communication were the happiest. Psychological well-being was lower in years when adolescents spent more time on screens and higher in years when they spent more time on nonscreen activities, with changes in activities generally preceding declines in well-being. Cyclical economic indicators such as unemployment were not significantly correlated with well-being, suggesting that the Great Recession was not the cause of the decrease in psychological well-being, which may instead be at least partially due to the rapid adoption of smartphones and the subsequent shift in adolescents' time use.
In recent years, the use of a large number of object concepts and naturalistic object images has been growing strongly in cognitive neuroscience research. Classical databases of object concepts are ...based mostly on a manually curated set of concepts. Further, databases of naturalistic object images typically consist of single images of objects cropped from their background, or a large number of naturalistic images of varying quality, requiring elaborate manual image curation. Here we provide a set of 1,854 diverse object concepts sampled systematically from concrete picturable and nameable nouns in the American English language. Using these object concepts, we conducted a large-scale web image search to compile a database of 26,107 high-quality naturalistic images of those objects, with 12 or more object images per concept and all images cropped to square size. Using crowdsourcing, we provide higher-level category membership for the 27 most common categories and validate them by relating them to representations in a semantic embedding derived from large text corpora. Finally, by feeding images through a deep convolutional neural network, we demonstrate that they exhibit high selectivity for different object concepts, while at the same time preserving variability of different object images within each concept. Together, the THINGS database provides a rich resource of object concepts and object images and offers a tool for both systematic and large-scale naturalistic research in the fields of psychology, neuroscience, and computer science.
Representational Similarity Analysis (RSA) has emerged as a popular method for relating representational spaces from human brain activity, behavioral data, and computational models. RSA is based on ...the comparison of representational (dis-)similarity matrices (RDMs or RSMs), which characterize the pairwise (dis-)similarities of all conditions across all features (e.g. fMRI voxels or units of a model). However, classical RSA treats each feature as equally important. This ‘equal weights’ assumption contrasts with the flexibility of multivariate decoding, which reweights individual features for predicting a target variable. As a consequence, classical RSA may lead researchers to underestimate the correspondence between a model and a brain region and, in case of model comparison, may lead them to select an inferior model. The aim of this work is twofold: First, we sought to broadly test feature-reweighted RSA (FR-RSA) applied to computational models and reveal the extent to which reweighting model features improves RSM correspondence and affects model selection. Previous work suggested that reweighting can improve model selection in RSA but it has remained unclear to what extent these results generalize across datasets and data modalities. To draw more general conclusions, we utilized a range of publicly available datasets and three popular deep neural networks (DNNs). Second, we propose voxel-reweighted RSA, a novel use case of FR-RSA that reweights fMRI voxels, mirroring the rationale of multivariate decoding of optimally combining voxel activity patterns. We found that reweighting individual model units markedly improved the fit between model RSMs and target RSMs derived from several fMRI and behavioral datasets and affected model selection, highlighting the importance of considering FR-RSA. For voxel-reweighted RSA, improvements in RSM correspondence were even more pronounced, demonstrating the utility of this novel approach. We additionally show that classical noise ceilings can be exceeded when FR-RSA is applied and propose an updated approach for their computation. Taken together, our results broadly validate the use of FR-RSA for improving the fit between computational models, brain, and behavioral data, allowing us to better adjudicate between competing computational models. Further, our results suggest that FR-RSA applied to brain measurement channels could become an important new method to assess the correspondence between representational spaces.
There is increasing interest in the study of Life Cycle Assessment (LCA) of buildings, which entails an estimate of the potential environmental impacts and resource use of buildings. This is driven ...by increasing awareness of the environmental impact of buildings, as well as the emergence of enabling tools for their assessment. There are review articles on building LCA (see Table 1) but none focuses on the challenges of building LCA, ongoing studies and potential solutions to address the challenges. The aim of this paper is to provide an up-to-date systematic review of life cycle assessment of buildings, and to discuss the major challenges in building LCA, ongoing studies and potential solutions to resolve the identified issues. The methodology involves a detailed literature review to provide an overview of existing studies in building LCA, and a systematic selection and study of review articles/books to investigate the benefits and challenges of building LCA. A summary of the research outputs and recommended further studies on building LCA are outlined in the conclusion section. The major challenges in building LCA were identified as data intensity and quality, subjectivity in environmental impact characterization and valuation, inadequate definition of functional units, assumptions for building life span and service life, lack of procedure for system boundaries, lack of uncertainty analysis, and limitation as a decision-making tool. In addition to discussing ongoing studies to address the issues, this study also proposes research trajectories to resolve the major challenges identified in building LCA.
•Provides an up-to-date statistic of the patterns of growth of interest in building LCA using a bibliometric approach.•Presents a review of current research on building LCA to highlight the trends and opportunities in the topic.•Discusses top issues in building LCA and proposes research trajectories to resolve the identified issues.•Provides a summary of existing review studies on LCA of buildings and their individual goals to enable easy references.•Uses a systematic approach to provide an up-to-date review of life cycle assessment of buildings.
Nonribosomal peptide synthetases (NRPSs) are very large proteins that produce small peptide molecules with wide-ranging biological activities, including environmentally friendly chemicals and many ...widely used therapeutics. NRPSs are macromolecular machines, with modular assembly-line logic, a complex catalytic cycle, moving parts and many active sites. In addition to the core domains required to link the substrates, they often include specialized tailoring domains, which introduce chemical modifications and allow the product to access a large expanse of chemical space. It is still unknown how the NRPS tailoring domains are structurally accommodated into megaenzymes or how they have adapted to function in nonribosomal peptide synthesis. Here we present a series of crystal structures of the initiation module of an antibiotic-producing NRPS, linear gramicidin synthetase. This module includes the specialized tailoring formylation domain, and states are captured that represent every major step of the assembly-line synthesis in the initiation module. The transitions between conformations are large in scale, with both the peptidyl carrier protein domain and the adenylation subdomain undergoing huge movements to transport substrate between distal active sites. The structures highlight the great versatility of NRPSs, as small domains repurpose and recycle their limited interfaces to interact with their various binding partners. Understanding tailoring domains is important if NRPSs are to be utilized in the production of novel therapeutics.
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