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An improved understanding of the human lung necessitates advanced systems models informed by an ever-increasing repertoire of molecular omics, cellular, imaging, and pathological datasets. To centralize and standardize information across broad lung research efforts we expanded the LungMAP.net website into a new gateway portal. This portal connects a broad spectrum of research networks, bulk and single-cell multi-omics data and a diverse collection of image data that span mammalian lung development, and disease. The data are standardized across species and technologies using harmonized data and metadata models that leverage recent advances including those from the Human Cell Atlas, diverse ontologies, and the LungMAP CellCards initiative. To cultivate future discoveries, we have aggregated a diverse collection of single-cell atlases for multiple species (human, rhesus, mouse), to enable consistent queries across technologies, cohorts, age, disease, and drug treatment. These atlases are provided as independent and integrated queryable datasets, with an emphasis on dynamic visualization, figure generation, re-analysis, cell-type curation, and automated reference-based classification of user-provided single-cell genomics datasets (Azimuth). As this resource grows, we intend to increase the breadth of available interactive interfaces, supported data types, data portals and datasets from LungMAP and external research efforts.

What challenges arise when deploying a novel technology at increasing scale? This case study details our experience developing and deploying technologies to monitor power outages and voltage fluctuations at high temporal and geographic frequency. After a small initial pilot, our deployment grew over time and eventually exceeded 450 sensors and 3500 mobile app downloads with households and firms across Accra, Ghana. Our first lesson is that ad hoc solutions to deployment challenges may not scale, as larger scales bring unique challenges requiring unique and progressively more complex solutions. Second, challenges that arise with scale span distinct domains – not only technological but also cultural, organizational, and operational. Finally, we stress the importance of adaptability of operational structure, and of frequently updating operational strategy based on new learnings.

The human lung plays vital roles in respiration, host defense and basic physiology. Recent technological advancements such as single-cell RNA sequencing and genetic lineage tracing have revealed novel cell types and enriched functional properties of existing cell types in lung. The time has come to take a new census. Initiated from members of the NHLBI-funded LungMAP Consortium and aided by experts in the lung biology community, we synthesized current data into a comprehensive and practical cellular census of the lung. Identities of cell types in the normal lung are captured in individual cell cards with delineation of function, markers, developmental lineages, heterogeneity, regenerative potential, disease links and key experimental tools. This publication will serve as the starting point of a live, up-to-date guide for lung research at https://lungmap.net/cell-cards-browser/. We hope that this Lung CellCards will promote the community-wide effort to establish, maintain and restore respiratory health.

In this meta-analysis, we examined the quantitative relation between meat consumption or avoidance, depression, and anxiety. In June 2020, we searched five online databases for primary studies examining differences in depression and anxiety between meat abstainers and meat consumers that offered a clear (dichotomous) distinction between these groups. Twenty studies met the selection criteria representing 171,802 participants with 157,778 meat consumers and 13,259 meat abstainers. We calculated the magnitude of the effect between meat consumers and meat abstainers with bias correction (Hedges's

The world's population is flocking to city centers at an increasing rate, testing the ability of urban planners and local governments to address new problems in transportation, waste disposal, urban health, and public safety. While one could imagine solutions enabled by an emerging class of smart sensors, current attempts at such systems are difficult to deploy and single purpose in their design. If we expect researchers and citizen-scientists to participate in the data-driven rejuvenation of our urban spaces (and we should, since they are the ones experiencing the day-to-day problems), we must lower the bar to deploying sensors and accessing smart-city data. Towards this goal, we present Signpost, an infrastructurefree sensing platform that aims to enable easy, multi-use sensor deployments for citizens, and researchers who have little expertise in building smart and connected sensors.[1]

In much of the world, electricity grids are not instrumented at the customer level, limiting insights into the power quality experienced by utility customers. Moreover, to understand grid performance, regulators and investors must depend on utilities to self-report reliability data. To address these challenges, we introduce PowerWatch, an agile methodology to directly measure customer experience and aggregated grid performance without relying on the utility for deployment or management. PowerWatch employs a system of distributed sensors coupled with cloud-based analytics. We evaluate the PowerWatch methodology by deploying 462 sensors in homes and businesses in Accra, Ghana for over a year, yielding the largest open-source data set on electricity reliability at the customer-level in the region. We describe the architecture, design, and performance of PowerWatch, as well as the data that are collected, explaining how we determine the accuracy and coverage of our methodology without ground truth. Finally, we report on grid performance issues, finding nearly twice as many outages as the utility observed, suggesting a need for better grid performance monitoring.

Objective: To examine the relation between the consumption or avoidance of meat and psychological health and well-being.Methods: A systematic search of online databases (PubMed, PsycINFO, CINAHL Pl...

Lithium sulfide (Li2S) is one of the most attractive cathode materials for high energy density lithium batteries as it has a high theoretical capacity of 1166 mA h g-1. However, Li2S suffers from poor rate performance and short cycle life due to its insulating nature and polysulfide shuttle during cycling. In this work, we report a facile and viable approach to address these issues. We propose a method to synthesize a Li2S based nanocomposite cathode material by dissolving Li2S as the active material, polyvinylpyrrolidone (PVP) as the carbon precursor, and graphene oxide (GO) as a matrix to enhance the conductivity, followed by a co-precipitation and high-temperature carbonization process. The Li2S/rGO cathode yields an exceptionally high initial capacity of 817 mAh g-1 based on Li2S mass at C/20 rate and also shows a good cycling performance. The carbon-coated Li2S/rGO cathode demonstrates the capability of robust core-shell nanostructures for different rates and improved capacity retention, revealing carbon coated Li2S/rGO composites as an outstanding system for high-performance lithium-sulfur batteries.

Low-power wide-area networks (LPWANs) are a compelling answer to the networking challenges faced by many Internet of Things devices. Their combination of low power, long range, and deployment ease has motivated a flurry of research, including exciting results on backscatter and interference cancellation that further lower power budgets and increase capacity. But despite the interest, we argue that unlicensed LPWAN technologies can only serve a narrow class of Internet of Things applications due to two principal challenges: capacity and coexistence. We propose a metric, bit flux, to describe networks and applications in terms of throughput over a coverage area. Using bit flux, we find that the combination of low bit rate and long range restricts the use case of LPWANs to sparse sensing applications. Furthermore, this lack of capacity leads networks to use as much available bandwidth as possible, and a lack of coexistence mechanisms causes poor performance in the presence of multiple, independently-administered networks. We discuss a variety of techniques and approaches that could be used to address these two challenges and enable LPWANs to achieve the promise of ubiquitous connectivity.

The vision of sensor systems that collect critical and previously ungathered information about the world is often only realized when sensors, students, and subjects move outside the academic laboratory. However, deployments at even the smallest scales introduce complexities and risks that can be difficult for a research team to anticipate. Over the past year, our interdisciplinary team of engineers and economists has been designing, deploying, and operating a large sensor network in Accra, Ghana that measures power outages and quality at households and firms. This network consists of 457 custom sensors, over 3,000 mobile app instances, thousands of participant surveys, and custom user incentive and deployment management systems. In part, this deployment supports an evaluation of the impacts of investments in the grid on reliability and the subsequent effects of improvements in reliability on socioeconomic well-being. We report our experiences as we move from performing small pilot deployments to our current scale, attempting to identify the pain points at each stage of the deployment. Finally, we extract high-level observations and lessons learned from our deployment activities, which we wish we had originally known when forecasting budgets, human resources, and project timelines. These insights will be critical as we look toward scaling our deployment to the entire city of Accra and beyond, and we hope that they will encourage and support other researchers looking to measure highly granular information about our world's critical systems.

Today, most energy harvesting sensors rely on capacitors to buffer small amounts of energy as they intermittently work through a sensing task. While the utilization of capacitors for energy storage affords these systems indefinite lifetimes, their low energy capacity necessitates complex intermittent programming models for state retention and energy management. Recent advances in battery technology lead us to reevaluate the impact that increased energy storage capacity may have on the necessity of these programming models and the reliability and lifetime of energy harvesting sensors. Permamote, presented at IPSN 2019, is designed to explore the benefits of larger capacity energy harvesting Instead of a capacitor, Permamote utilizes a small lithium battery to store harvested energy. The inclusion and size of this battery was determined based on device reliability and lifetime modelling using real indoor solar irradiance traces. Permamote additionally includes a backup, non-rechargeable battery that allows continuous operation even for long periods of no available harvestable energy. In this demo, we present Permamote performing continuous and reliable sensing over a Thread (6LoWPAN 802.15.4) mesh network. Additionally, we show the end-to-end cloud infrastructure supporting connected Permamotes, with the intention of showing that energy harvesting with higher capacity enables more capable sensing.

Today, most sensors that harvest energy from indoor solar, ambient RF, or thermal gradients buffer small amounts of energy in capacitors as they intermittently work through a sensing task. While the utilization of capacitors for energy storage affords these systems indefinite lifetimes, their low energy capacity necessitates complex intermittent programming models for state retention and energy management. However, recent advances in battery technology lead us to reevaluate the impact that increased energy storage capacity may have on the necessity of these programming models and the reliability of energy harvesting sensors. In this paper, we propose a capacity-based framework to help structure energy harvesting sensor design, analyze the impact of capacity on key reliability metrics using a data-driven simulation, and consider how backup energy storage alters the design space. We find that for many designs that utilize solar energy harvesting, increasing energy storage capacity to 1-10 mWh can obviate the need for intermittent programming techniques, augment the total harvested energy by 1.4-2.3x, and improve the availability of a sensor by 1.3-2.6x. We also show that a hybrid design using energy harvesting with a secondary-cell battery and a backup primary-cell battery can achieve 2-4x the lifetime of primary-cell only designs while eliminating the failure modes present in energy harvesting systems. Finally, we implement an indoor, solar energy harvesting sensor based on our analysis and find that its behavior aligns with our simulation's predictions.

One of the largest impediments to pervasive sensing is ensuring equally pervasive network access. While we can create wireless sensors that last for years without human intervention, the network infrastructure to support their deployment requires planning, power, and maintenance. The potential for a crowd-based solution to this problem is ripe---ever pervasive smart phones have the hardware and connectivity to serve as ubiquitous mobile gateways---however the fragmentation of low power wireless protocols combined with the lack of incentive for users to sacrifice their own resources transporting others' data has made this approach untenable. Through an "off label'' use of Google's Physical Web and Nearby Notifications, it was possible to ignore these problems and exploit nearly the entire global population of Android phones to slowly transport sensor data to an arbitrary web server. This mechanism was enabled by default and transparent to the phone's user. On one hand, it served as an exciting opportunity to explore infrastructure-free wireless networking. In a one week deployment of five devices transmitting at 1\,Hz, we were able to successfully transport 326\,kB of data with an average data rate of 0.1--2.6\,bps. This is slow, but sufficient for many applications such as environmental monitoring and sensor status reporting. On the other hand, a mobile operating system probably should not have enabled exfiltration of arbitrary data without a user's knowledge or consent. While Nearby Notifications has now been decommissioned, we examine security policy requirements for future systems that interact with nearby devices, and we envision a similar, intentional mechanism to allow data hitchhiking for the Internet of Things.

For the past decade, the status-quo for energy harvesting sensors has been to buffer small amounts of energy in capacitors to intermittently work through a sensing task. While using capacitors for storage offers these systems indefinite lifetime, it comes at a cost - they must tolerate the decreased availability, lower energy utilization, and more complex programming models inherent to a volatile, intermittent design. We argue that many of these problems stem from insufficient energy storage and could be eliminated with the use of batteries. Recent advances in rechargeable battery technology weaken the historical arguments against their use. We believe that using batteries in energy harvesting sensors will push us closer to a class of reliable, general purpose devices that can better serve human-centric sensing applications than their capacitor-based counterparts at the cost of having a finite, but long, lifetime.

City-scale sensing holds the promise of enabling deeper insight into how our urban environments function. Applications such as observing air quality and measuring traffic flows can have powerful impacts, allowing city planners and citizen scientists alike to understand and improve their world. However, the path from conceiving applications to implementing them is fraught with difficulty. A successful city-scale deployment requires physical installation, power management, and communications---all challenging tasks standing between a good idea and a realized one.The Signpost platform, presented at IPSN 2018, has been created to address these challenges. Signpost enables easy deployment by relying on harvested, solar energy and wireless networking rather than their wired counterparts. To further lower the bar to deploying applications, the platform provides the key resources necessary to support its pluggable sensor modules in their distributed sensing tasks. In this demo, we present the Signpost hardware and several applications running on a deployment of Signposts on UC Berkeley's campus, including distributed, energy-adaptive traffic monitoring and fine grained weather reporting. Additionally we show the cloud infrastructure supporting the Signpost deployment, specifically the ability to push new applications and parameters down to existing sensors, with the goal of demonstrating that the existing deployment can serve as a future testbed.

City-scale sensing holds the promise of enabling a deeper understanding of our urban environments. However, a city-scale deployment requires physical installation, power management, and communications---all challenging tasks standing between a good idea and a realized one. This indicates the need for a platform that enables easy deployment and experimentation for applications operating at city scale. To address these challenges, we present Signpost, a modular, energy-harvesting platform for city-scale sensing. Signpost simplifies deployment by eliminating the need for connection to wired infrastructure and instead harvesting energy from an integrated solar panel. The platform furnishes the key resources necessary to support multiple, pluggable sensor modules while providing fair, safe, and reliable sharing in the face of dynamic energy constraints. We deploy Signpost with several sensor modules, showing the viability of an energy-harvesting, multi-tenant, sensing system, and evaluate its ability to support sensing applications. We believe Signpost reduces the difficulty inherent in city-scale deployments, enables new experimentation, and provides improved insights into urban health., Published in the proceedings of the 17th ACM/IEEE Conference on Information Processing in Sensor Networks (IPSN'18)

Embedded systems have long been synonymous with special purpose, single stakeholder computing. However, as these systems have become more capable and the demands placed on them have become more varied and variable, embedded software is beginning to embrace multi-tenancy. While the general problem of supporting multiple users and processes on a computing platform has been well explored in computer science, the challenges of supporting multiple users with competing desires on a highly energy-variable system remain unexplored. On an energy-harvesting platform, incoming energy needs to be distributed between stakeholders, and users accessing shared platform resources should be charged for the energy use of those resources. Furthermore, with system designers and application creators being increasingly removed from each other, the software environments of energy-harvesting platforms must provide primitives that enable applications to adapt to system variability. We explore several initial techniques for solving these problems and demonstrate them using Signpost---a modular, energy-harvesting platform for city-scale sensing.

We present Monoxalyze, a keychain-sized, Bluetooth-based, carbon monoxide breathalyzer that aims to enable mobile, scalable smoking cessation intervention programs. These intervention programs have been shown to greatly increase the rate of a quit attempt, which in turn decreases the rate of smoking, a major public health problem that still affects over one billion people around the world. Currently, intervention programs verify cessation compliance by requiring program participants to periodically visit clinics and exhale through large, expensive carbon monoxide breathalyzers---a practice that cannot scale to one billion smokers. Monoxalyze enables mobile cessation verification by working with a user's smartphone to establish a ring of spatio-temporal transitive trust between the Monoxalyze device, the user, and the smartphone, a concept that can be applied to many third-party monitoring applications. In Monoxalyze, the links of this trust are represented by simultaneous exhalation verification, facial recognition, and device-to-phone visible light authentication. In our evaluation, we show that Monoxalyze lasts over 80 days between charges, and has the ability to verify a Monoxalyze user. With a small user study we show that Monoxalyze determines smoking cessation with 92% accuracy, a level comparable with commercial CO breathalyzers. Further contributions describe the design decisions behind creating a low-power BLE device.

The era of city-scale sensing is dawning. Supported by new sensing capabilities, the capability to detect and measure phenomena throughout a large area will allow deeper insight and understanding into how cities work. The challenge of city-scale sensing is not limited to developing new sensing applications, however. A sensor must be installed in a location. It must be provided power, storage, and communications. All these tasks stand aside from the desired sensing effort, but are necessary nevertheless.In this demo, we introduce an initial prototype for a modular, city-scale sensing platform---the signpost network. The platform, designed to be physically attached to sign posts throughout a city, reduces the burden for sensor and application developers by providing the necessary resources to modules attached to it. Power is provided by harvesting from solar panels with battery storage, with each module allocated a certain subset of the system energy. The signpost platform also provides data storage, long-range communication, data processing, module isolation, and an installation point for connected modules. The signpost acts as a modular base station for researchers, citizen scientists, and other interested parties to deploy custom sensors for applications such as pedestrian counting, air quality monitoring, and RF spectrum sensing at a city-wide scale.

We are becoming increasingly surrounded by smart and connected devices, popularly known as the Internet of Things. The emerging user interface paradigm for many such things eschews physical buttons, knobs, and displays in favor of virtual interfaces that are downloaded from the web and rendered on remote platforms---like smartphones. However, such smartphone app-based interfaces often require tedious discovery and installation, as well as device discovery, pairing, and configuration before a user can interact with a nearby device. Requiring an explicit app install for each new device type scales poorly with device growth, and particularly hinders casual interactions with ambient devices. Instead of the high-friction, walled-garden approach now taking root, we propose name, a physical web browser that provides a seamless, scalable approach to browsing and interacting with nearby things. name leverages multiple network patterns and modern web technologies to provide users with rich device interfaces, even for devices under network or power constraints. We argue that this approach scales better and that it provides more intuitive and natural functionality for both users and developers. This demo presents the basic concept, allows others to experience our preliminary implementation, and raises several open research questions.

We demonstrate PolyPoint, a high-fidelity RF-based indoor localization system that achieves 28~cm accuracy indoors and tracks a fast-moving quadcopter with only 56~cm average error. PolyPoint uses ultra-wideband signals to achieve high precision RF time-of-flight estimates between nodes. To further improve accuracy, PolyPoint exploits two forms of diversity: frequency diversity, which leverages several ultra-wideband channels to improve channel response, and antenna diversity, which adds three antennas at 120 degree offsets to mitigate the effects of antenna polarization and nulls. PolyPoint introduces an efficient, novel ranging protocol that maximizes these diversity sources with a minimal number of packets.Additionally, this work introduces a new hardware platform that provides ranging and localization as a service. The minimal TriPoint module integrates an ultra-wideband transceiver and microcontroller with firmware that implements the protocol. The TriTag carrier board adds Bluetooth and batteries to create a complete mobile tag, and the TriBase anchor platform integrates a TriPoint with an Intel Edison to act as anchors for the system.

Building connected, pervasive, human-facing, and responsive applications that incorporate local sensors, smartphone interactions, device actuation, and cloud-based learning--the promised features of the Internet of Things (IoT)---requires a complete suite of tools spanning both hardware and software. We present a set of these pieces, including a gateway, four hardware building blocks, multiple sensor platforms, an indoor localization system, and software for connecting users and devices. Each piece plays an integral role towards enabling applications, from facilitating rapid development of wireless smart devices to composing data streams and services from a diverse set of components. By providing layered interoperable systems, our toolkit offers cohesive support for moving beyond single-device, cloud-centric applications---typical in today's IoT landscape--and towards richer applications that incorporate multiple data streams, human interaction, cloud processing, location awareness, multiple communication protocols, historical data, access control, and on-demand user interfaces. To show how the pieces in the toolkit cooperate, we demonstrate a location-based access control application where a user's smartphone can control a room's lighting, but only from within the room. Further, data streams from the phone and nearby sensors are used to provide a constant lighting service which attempts to maintain a user-set brightness under variable external lighting conditions.

The emergence of the Internet of Things will cause the density of wirelessly networked devices to increase significantly. As the industry and density continue to grow, enabling and managing networks of these devices in a scalable manner without constant user interaction becomes essential. Noting that information about physical context can guide interactions between devices, we introduce the desktop area network and Ving, a vibratory ping architecture that enables it. Ving is based on the wireless vibratory communications channel between a vibratory motor on one device and an accelerometer on another. Because vibratory communications is a physically-coupled, surface-constrained communications domain, Ving allows devices to bootstrap networks within their physical context, creating a literal desktop area network. Such context establishment and network creation enables a new class of applications for smartphones and embedded devices. We present several of these applications, discuss our preliminary implementation of Ving, compare Ving to alternate methods of context establishment, and suggest potential research challenges stemming from the widespread use of Ving.

The vision of an Internet of Things (IoT) has captured the imagination of the world and raised billions of dollars, all before we stopped to deeply consider how all these Things should connect to the Internet. The current state-of-the-art requires application-layer gateways both in software and hardware that provide application-specific connectivity to IoT devices. In much the same way that it would be difficult to imagine requiring a new web browser for each website, it is hard to imagine our current approach to IoT connectivity scaling to support the IoT vision. The IoT gateway problem exists in part because today's gateways conflate network connectivity, in-network processing, and user interface functions. We believe that disentangling these functions would improve the connectivity potential for IoT devices. To realize the broader vision, we propose an architecture that leverages the increasingly ubiquitous presence of Bluetooth Low Energy radios to connect IoT peripherals to the Internet. In much the same way that WiFi access points revolutionized laptop utility, we envision that a worldwide deployment of IoT gateways could revolutionize application-agnostic connectivity, thus breaking free from the stove-piped architectures now taking hold. In this paper, we present our proposed architecture, show example applications enabled by it, and explore research challenges in its implementation and deployment.