Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses

Very few genetic variants have been associated with depression and neuroticism, likely because of limitations on sample size in previous studies. Subjective well-being, a phenotype that is genetically correlated with both of these traits, has not yet been studied with genome-wide data. We conducted genome-wide association studies of three phenotypes: subjective well-being (n = 298,420), depressive symptoms (n = 161,460), and neuroticism (n = 170,911). We identify 3 variants associated with subjective well-being, 2 variants associated with depressive symptoms, and 11 variants associated with neuroticism, including 2 inversion polymorphisms. The two loci associated with depressive symptoms replicate in an independent depression sample. Joint analyses that exploit the high genetic correlations between the phenotypes (|ρ^| ≈ 0.8) strengthen the overall credibility of the findings and allow us to identify additional variants. Across our phenotypes, loci regulating expression in central nervous system and adrenal or pancreas tissues are strongly enriched for association.</p

Low cost printed, flexible, and energy autonomous Van-Atta and carbon-nanotubes-based mm-wave RFID gas sensors for ultra-long-range ubiquitous IoT and 5g implementations

Has the concept of "smart wall" or "smart surface" ever come through your mind? That is unlikely. Indeed, our interactions with the digital world—the universe predominantly stored and crated by data centers, connected through the internet—is generally mediated by discrete, dedicated, and recognizable components: your phone, your laptop, your smartwatch, or even your TV. This state is not the product of a lack of interest, need, or imagination. Indeed, the concept of "digital twin"—the virtual alter ego of a physical object—has started to make its way into Internet-of-Things-powered products and services. Rather, it is the consequence of hardware's inability to keep up with the exponentially-increasing demands and capabilities of software. The work presented in this thesis presents significant hardware developments, on the path leading towards the ubiquitous presence of intelligence, and the permeation of the physical into the digital. More specifically, the work reported in this document describes the creation of an approach that enables the addition of intelligence unto any surface, for the low-cost, real-time, and ubiquitous sensing of chemical agents. This outcome is the product of reported advances enabling the design and demonstration of fully-printed skin-like devices that can be precisely located and can fully-autonomously sense and transmit, at long range, in real time, part of the make-up of their chemical environments. These results were achieved through the combination of additive-manufacturing tools and technologies, nanomaterials-based sensing, and ultra-low-power mm-wave (24 to 28 GHz) retrodirective communications schemes and signal processing. Notably, the work describes (to our knowledge), the longest-ranging chipless RFIDs and unamplified monostatic backscatter RFIDs—at the time of their publication—and the first ever fully-inkjet-printed organophosphorus nerve agent in the literature.Ph.D

Wirelessly powered large-area electronics for the Internet of Things

Powering the increasing number of sensor nodes used in the Internet of Things creates a technological challenge. The economic and sustainability issues of battery-powered devices mean that wirelessly powered operation—combined with environmentally friendly circuit technologies—will be needed. Large-area electronics—which can be based on organic semiconductors, amorphous metal oxide semiconductors, semiconducting carbon nanotubes and two-dimensional semiconductors—could provide a solution. Here we examine the potential of large-area electronics technology in the development of sustainable, wirelessly powered Internet of Things sensor nodes. We provide a system-level analysis of wirelessly powered sensor nodes, identifying the constraints faced by such devices and highlighting promising architectures and design approaches. We then explore the use of large-area electronics technology in wirelessly powered Internet of Things sensor nodes, with a focus on low-power transistor circuits for digital processing and signal amplification, as well as high-speed diodes and printed antennas for data communication and radiofrequency energy harvesting

Corrigendum: Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses

In the version of this article initially published, one of the affiliations listed for author Maciej Trzaskowski, to the Department of Public Health, Faculty of Medicine, University of Split, Split, Croatia, was included in error. The correct affiliation for this author is the Queensland Brain Institute, University of Queensland, Brisbane, Queensland, Australia. The error has been corrected in the HTML and PDF versions of the article