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We use an infrared dataset captured between 1984 and 2017 using several instruments and observatories to report five rare equatorial disturbances that completely altered the appearance of Jupiter's Equatorial Zone (EZ): the clearance of tropospheric clouds revealed a new 5-$\mu$m-bright band encircling the planet at the equator, accompanied by large 5-$\mu$m-bright filaments. Three events were observed in ground-based images in 1973, 1979 and 1992. We report and characterize for the first time the entire evolution of two new episodes of this unusual EZ state that presented their maximum 5-$\mu$m-brightness in December 1999 and February 2007, coinciding with a brown coloration south of the equator and with large bluish filaments and white plumes in the northern EZ at visible wavelengths. We characterize their typical infrared-bright lifetimes of 12-18 months, with possible periodicities of 6-8 or 13-14 years. We predict that a full-scale equatorial disturbance could occur in 2019-21.

Using images at multiple mid-infrared wavelengths, acquired in May 2018 using the VISIR instrument on ESO's Very Large Telescope (VLT), we study Jupiter's pole-to-pole thermal, chemical and aerosol structure in the troposphere and stratosphere. We confirm that the pattern of cool and cloudy anticyclonic zones and warm cloud-free cyclonic belts persists throughout the mid-latitudes, up to the polar boundaries, and evidence a strong correlation with the vertical maximum windshear and the locations of Jupiter's zonal jets. At high latitudes, VISIR images reveal a large region of mid-infrared cooling poleward $\sim$64$^{\circ}$N and $\sim$67$^{\circ}$S extending from the upper troposphere to the stratosphere, co-located with the reflective aerosols observed by JunoCam, and suggesting that aerosols play a key role in the radiative cooling at the poles. Comparison of zonal-mean thermal properties and high-resolution visible imaging from Juno allows us to study the variability of atmospheric properties as a function of altitude and jet boundaries, particularly in the cold southern polar vortex. However, the southern stratospheric polar vortex is partly masked by a warm mid-infrared signature of the aurora. Co-located with the southern main auroral oval, this warming results from the auroral precipitation and/or joule heating which heat the atmosphere and thus cause a significant stratospheric emission. This high emission results from a large enhancement of both ethane and acetylene in the polar region, reinforcing the evidence of enhanced ion-related chemistry in Jupiter's auroral regions.

While maximizing line-of-sight coverage of specific regions or agents in the environment is a well explored path planning objective, the converse problem of minimizing exposure to the entire environment during navigation is especially interesting in the context of minimizing detection risk. This work demonstrates that minimizing line-of-sight exposure to the environment is non-Markovian, which cannot be efficiently solved optimally with traditional path planning. The optimality gap of the graph-search algorithm A* and the trade-offs in optimality vs. computation time of several approximating heuristics is explored. Finally, the concept of equal-exposure corridors, which afford polynomial time determination of all paths that do not increase exposure, is presented., Comment: 7 pages, 8 figures. Submitted to 2024 IEEE 20th International Conference on Automation Science and Engineering

Soft, wireless physiological sensors that gently adhere to the skin are capable of continuous clinical-grade health monitoring in hospital and/or home settings, of particular value to critically ill infants and other vulnerable patients, but they present risks for injury upon thermal failure. This paper introduces an active materials approach that automatically minimizes such risks, to complement traditional schemes that rely on integrated sensors and electronic control circuits. The strategy exploits thin, flexible bladders that contain small volumes of liquid with boiling points a few degrees above body temperature. When the heat exceeds the safe range, vaporization rapidly forms highly effective, thermally insulating structures and delaminates the device from the skin, thereby eliminating any danger to the skin. Experimental and computational thermomechanical studies and demonstrations in a skin-interfaced mechano-acoustic sensor illustrate the effectiveness of this simple thermal safety system and suggest its applicability to nearly any class of skin-integrated device technology.

Vocal fatigue is a measurable form of performance fatigue resulting from overuse of the voice and is characterized by negative vocal adaptation. Vocal dose refers to cumulative exposure of the vocal fold tissue to vibration. Professionals with high vocal demands, such as singers and teachers, are especially prone to vocal fatigue. Failure to adjust habits can lead to compensatory lapses in vocal technique and an increased risk of vocal fold injury. Quantifying and recording vocal dose to inform individuals about potential overuse is an important step toward mitigating vocal fatigue. Previous work establishes vocal dosimetry methods, that is, processes to quantify vocal fold vibration dose but with bulky, wired devices that are not amenable to continuous use during natural daily activities; these previously reported systems also provide limited mechanisms for real-time user feedback. This study introduces a soft, wireless, skin-conformal technology that gently mounts on the upper chest to capture vibratory responses associated with vocalization in a manner that is immune to ambient noises. Pairing with a separate, wirelessly linked device supports haptic feedback to the user based on quantitative thresholds in vocal usage. A machine learning-based approach enables precise vocal dosimetry from the recorded data, to support personalized, real-time quantitation and feedback. These systems have strong potential to guide healthy behaviors in vocal use.

This dissertation explores how four critical teachers of color learn and develop through dialogue and reflection about their own educational and life histories as well as their work in ethnic studies classrooms. As K–12 schools in states like California integrate ethnic studies into their curricula, educators are looking to established ethnic studies programs and experienced ethnic studies teachers as models. The existing literature on K–12 ethnic studies primarily focuses on students’ educational experiences, though it offers limited examinations of the experiences of ethnic studies educators. This dissertation addresses this gap by examining the lives, experiences, and insights of four critical teachers of color who teach a ninth-grade ethnic studies program at an East Los Angeles high school. Through individual and focus group interviews, this study explores how these four teachers learned and developed their ethnic studies teaching practice. In particular, this study explores (1) the individual life and educational trajectories of these educators; (2) the ways in which they drew upon individual and shared experiences as a pedagogy-focused collective; and (3) the ways that these educators envision ethnic studies as an inclusive, healing-centered, and restorative justice teaching practice. The study yields two overarching understandings. First, ethnic studies teacher development is a process of becoming—a process that is recursive and reflexive as educators link their own lives with their praxis. Second, the professional learning that these educators engage in is instrumental to their praxis, to the extent that critical professional development (CPD) with an ethnic studies ethos is humanizing and transformative. This dissertation argues that this type of ethnic studies-centered CPD space offers three pedagogical interventions into mainstream K–12 professional development: first, CPD holds space for reflection, vulnerability, and collaboration that cultivate a huma

Factor graphs are a ubiquitous tool for multi-source inference in robotics and multi-sensor networks. They allow for heterogeneous measurements from many sources to be concurrently represented as factors in the state posterior distribution, so that inference can be conducted via sparse graphical methods. Adding measurements from many sources can supply robustness to state estimation, as seen in distributed pose graph optimization. However, adding excessive measurements to a factor graph can also quickly degrade their performance as more cycles are added to the graph. In both situations, the relevant quality is the redundancy of information. Drawing on recent work in information theory on partial information decomposition (PID), we articulate two potential definitions of redundancy in factor graphs, both within a common axiomatic framework for redundancy in factor graphs. This is the first application of PID to factor graphs, and only one of a few presenting quantitative measures of redundancy for them., Comment: 8 pages + 1 refs, 2 figures, FUSION 2023 submission

Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative efforts, scientific breakthroughs can be made sooner and capitalized for the betterment of humanity.

Optical bandpass-filter observations can be simply processed to determine similar horizontal ammonia distributions above the Jovian cloud tops as mid-infrared and microwave observations. Current understanding of this distribution and its relationship to aerosol opacity, cloud-top pressure, and circulation is provided by atmospheric retrieval models using observations from major ground-based facilities and spacecraft. These techniques recover high fidelity information on the ammonia distribution but are limited in spatial and temporal coverage. Part of this coverage gap - upper tropospheric abundance - can be bridged by using continuum-divided ammonia and methane absorption images as suggested by Combes and Encrenaz [1979]. In 2020-21, Jupiter was imaged in the 645 nm ammonia absorption band and adjacent continuum bands, demonstrating that the spatially-resolved optical depth in that band could be determined with a 0.28-m Schmidt-Cassegrain telescope (SCT). In 2022, a 620 nm filter was added to include methane absorption images in the same wavelength range. Methane abundance provides a constant reference against which to determine the ammonia abundance, specifically the column-averaged mole fraction above the clouds. VLT/MUSE results are compared to these SCT results and those from the TEXES mid-infrared spectrometer used on the IRTF and the Gemini telescopes. Meridional and longitudinal features are examined, including the Equatorial Zone (EZ) ammonia enhancement, the North Equatorial Belt (NEB) depletion, depletion above the Great Red Spot (GRS), and suggested enhancements over bright plumes in the northern EZ. This work demonstrates meaningful ammonia monitoring that can provide synoptic coverage and continuity between spacecraft or major ground-based facility campaigns., Comment: 23 pages, 8 figures

BackgroundIncreasing research suggests that gait abnormalities can be a risk factor for Alzheimer's Disease (AD). Notably, there is growing evidence highlighting this risk factor in individuals with amnestic Mild Cognitive Impairment (aMCI), however further studies are needed. The aim of this study is to analyze cognitive tests results and brain-related measures over time in aMCI and examine how the presence of gait abnormalities (neurological or orthopedic) or normal gait affects these trends. Additionally, we sought to assess the significance of gait and gait-related measures as prognostic indicators for the progression from aMCI to AD dementia, comparing those who converted to AD with those who remained with a stable aMCI diagnosis during the follow-up.MethodsFour hundred two individuals with aMCI from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database were included. Robust linear mixed-effects models were used to study the impact of gait abnormalities on a comprehensive neuropsychological battery over 36 months while controlling for relevant medical variables at baseline. The impact of gait on brain measures was also investigated. Lastly, the Cox proportional-hazards model was used to explore the prognostic relevance of abnormal gait and neuropsychological associated tests.ResultsWhile controlling for relevant covariates, we found that gait abnormalities led to a greater decline over time in attention (DSST) and global cognition (MMSE). Intriguingly, psychomotor speed (TMT-A) and divided attention (TMT-B) declined uniquely in the abnormal gait group. Conversely, specific AD global cognition tests (ADAS-13) and auditory-verbal memory (RAVLT immediate recall) declined over time independently of gait profile. All the other cognitive tests were not significantly affected by time or by gait profile. In addition, we found that ventricles size increased faster in the abnormal gait group compared to the normal gait group. In terms of prognosis, abnormal gai

The integration of micro- and nanoelectronics into or onto biomedical devices can facilitate advanced diagnostics and treatments of digestive disorders, cardiovascular diseases, and cancers. Recent developments in gastrointestinal endoscopy and balloon catheter technologies introduce promising paths for minimally invasive surgeries to treat these diseases. However, current therapeutic endoscopy systems fail to meet requirements in multifunctionality, biocompatibility, and safety, particularly when integrated with bioelectronic devices. Here, we report materials, device designs, and assembly schemes for transparent and stable cubic silicon carbide (3C-SiC)-based bioelectronic systems that facilitate tissue ablation, with the capability for integration onto the tips of endoscopes. The excellent optical transparency of SiC-on-glass (SoG) allows for direct observation of areas of interest, with superior electronic functionalities that enable multiple biological sensing and stimulation capabilities to assist in electrical-based ablation procedures. Experimental studies on phantom, vegetable, and animal tissues demonstrated relatively short treatment times and low electric field required for effective lesion removal using our SoG bioelectronic system. In vivo experiments on an animal model were conducted to explore the versatility of SoG electrodes for peripheral nerve stimulation, showing an exciting possibility for the therapy of neural disorders through electrical excitation. The multifunctional features of SoG integrated devices indicate their high potential for minimally invasive, cost-effective, and outcome-enhanced surgical tools, across a wide range of biomedical applications.

On May 31, 2020 a short-lived convective storm appeared in one of the small cyclones of Jupiter's South Temperate Belt (STB) at planetographic latitude 30.8S. The outbreak was captured by amateur astronomer Clyde Foster in methane-band images, became widely known as Clyde's Spot, and was imaged at very high resolution by the Junocam instrument on board the Juno mission 2.5 days later. Junocam images showed a white two-lobed cyclonic system with high clouds observed in the methane-band at 890 nm. The storm evolved over a few days to become a dark feature that showed turbulence for months, presented oscillations in its drift rate, and slowly expanded, first into a Folded Filamentary Region (FFR), and later into a turbulent segment of the STB over a timescale of one year. On August 7, 2021, a new storm strikingly similar to Clyde's Spot erupted in a cyclone of the STB. The new storm exhibited first a similar transformation into a turbulent dark feature, and later transformed into a dark cyclone fully formed by January 2022. We compare the evolution into a FFR of Clyde's Spot with the formation of a FFR observed by Voyager 2 in 1979 in the South South Temperate Belt (SSTB) after a convective outburst in a cyclone that also developed a two-lobed shape. We also discuss the contemporaneous evolution of an additional cyclone of the STB, which was similar to the one were Clyde's Spot developed. This cyclone did not exhibit visible internal convective activity, and transformed from pale white in 2019, with low contrast with the environment, to dark red in 2020, and thus, was very similar to the outcome of the second storm. This cyclone became bright again in 2021 after interacting with Oval BA. We present observations of these phenomena obtained by amateur astronomers, ground-based telescopes, Hubble Space Telescope and Junocam. This study reveals that short-lived small storms that are active for only a few days can produce complex longterm changes that extend over much large

This dissertation responds to a critical call to challenge the “over-theorizing” and the pathologizing of marginalized youth, a phenomenon plagued with voyeurism, epistemological and ontological violence, and gross miss-representation that further benefits those who “theorize.” Through “theorizing-back,” a critical research methodology that honors the humanity, knowledge, and power of those whose lives are grounded in struggles, this dissertation documents how The Homies—a community of marginalized and system impacted youth—interrogate the theories that have sought to explain those who leave, are pushed out, give up on, or resist school, i.e., “them.” Born out of the relationships and insights that arose from a space of praxis, this project took place over a 2-year span in a youth re-entry center in Los Angeles. The study generated two primary domains of findings. The first critically documents the normalized and naturalized silencing, violence, exploitation, and dispossession that marginalized young people have to deal with as part of “normal life.” Through architectures of entanglement, (a conceptual framework theorized by the youth), the Homies documented how carceral geographies change, migrate, and transfigure, both ideologically and materially, institutions that often operate under a guise of neutrality and benevolence—including schools. In direct response to those who frame “out-of-school youth” as a national emergency, the Homies declared, loud and clear, that the systems of whiteness, colonialism, and capitalism—all for which schools are a critical component—are the national emergency. The second major domain of findings focuses on theorizing back and chronicles the development of a “refuge”; a humanizing, transformative, counter-hegemonic, and healing community of praxis. In this community, the Homies not only ended up interrogating and deconstructing the questions and findings from prior research, but denounced the “self-serving truths” stubbornly reprodu

California Policy Options 2009: California forecast, California politics, California budget, California educational opportunity, University of California

A high-field winding can be fabricated from a cable of non-insulated REBCO tapes, stacked face-face without twisting. If the cable is oriented within each turn of a winding so that the tape face is closely parallel to the magnetic field at its location, the supercurrent capacity of that cable is enhanced ~3x greater than in a transverse or twisting orientation. This concept for a conformal winding was presented in a previous paper pertinent to the body winding of a high-field dipole. Strategies are presented and simulated for how the same orientation can be sustained in the flared ends of a dipole., Comment: accepted for publication in Proceedings of International Cryogenic Materials Conference, 2021

Recent progress in soft material chemistry and enabling methods of 3D and 4D fabrication—emerging programmable material designs and associated assembly methods for the construction of complex functional structures—is highlighted. The underlying advances in this science allow the creation of soft material architectures with properties and shapes that programmably vary with time. The ability to control composition from the molecular to the macroscale is highlighted—most notably through examples that focus on biomimetic and biologically compliant soft materials. Such advances, when coupled with the ability to program material structure and properties across multiple scales via microfabrication, 3D printing, or other assembly techniques, give rise to responsive (4D) architectures. The challenges and prospects for progress in this emerging field in terms of its capacities for integrating chemistry, form, and function are described in the context of exemplary soft material systems demonstrating important but heretofore difficult-to-realize biomimetic and biologically compliant behaviors., QC 20221125

A quantitative understanding of the coupled dynamics of flow and particles in aerosol and droplet transmission associated with speech remains elusive. Here, we summarize an effort that integrates insights into flow-particle dynamics induced by the production plosive sounds during speech with skin-integrated electronic systems for monitoring the production of these sounds. In particular, we uncover diffusive and ballistic regimes separated by a threshold particle size and characterize the Lagrangian acceleration and pair dispersion. Lagrangian dynamics of the particles in the diffusive regime exhibit features of isotropic turbulence. These fundamental findings highlight the value in skin-interfaced wireless sensors for continuously measuring critical speech patterns in clinical settings, work environments, and the home, based on unique neck biomechanics associated with the generation of plosive sounds. We introduce a wireless, soft device that captures these motions to enable detection of plosive sounds in multiple languages through a convolutional neural network approach. This work spans fundamental flow-particle physics to soft electronic technology, with implications in monitoring and studying critical speech patterns associated with aerosol and droplet transmissions relevant to the spread of infectious diseases.

Swallowing is a complex neuromuscular activity regulated by the autonomic nervous system. Millions of adults suffer from dysphagia (impaired or difficulty swallowing), including patients with neurological disorders, head and neck cancer, gastrointestinal diseases, and respiratory disorders. Therapeutic treatments for dysphagia include interventions by speech-language pathologists designed to improve the physiology of the swallowing mechanism by training patients to initiate swallows with sufficient frequency and during the expiratory phase of the breathing cycle. These therapeutic treatments require bulky, expensive equipment to synchronously record swallows and respirations, confined to use in clinical settings. This paper introduces a wireless, wearable technology that enables continuous, mechanoacoustic tracking of respiratory activities and swallows through movements and vibratory processes monitored at the skin surface. Validation studies in healthy adults (n = 67) and patients with dysphagia (n = 4) establish measurement equivalency to existing clinical standard equipment. Additional studies using a differential mode of operation reveal similar performance even during routine daily activities and vigorous exercise. A graphical user interface with real-time data analytics and a separate, optional wireless module support both visual and haptic forms of feedback to facilitate the treatment of patients with dysphagia.

Continuous health monitoring is essential for clinical care, especially for patients in neonatal and pediatric intensive care units. Monitoring currently requires wired biosensors affixed to the skin with strong adhesives that can cause irritation and iatrogenic injuries during removal. Emerging wireless alternatives are attractive, but requirements for skin adhesives remain. Here, we present a materials strategy enabling wirelessly triggered reductions in adhesive strength to eliminate the possibility for injury during removal. The materials involve silicone composites loaded with crystallizable oils with melting temperatures close to, but above, surface body temperature. This solid/liquid phase transition occurs upon heating, reducing the adhesion at the skin interface by more than 75%. Experimental and computational studies reveal insights into effects of oil mixed randomly and patterned deterministically into the composite. Demonstrations in skin-integrated sensors that include wirelessly controlled heating and adhesion reduction illustrate the broad utility of these ideas in clinical-grade health monitoring.

Temporary postoperative cardiac pacing requires devices with percutaneous leads and external wired power and control systems. This hardware introduces risks for infection, limitations on patient mobility, and requirements for surgical extraction procedures. Bioresorbable pacemakers mitigate some of these disadvantages, but they demand pairing with external, wired systems and secondary mechanisms for control. We present a transient closed-loop system that combines a time-synchronized, wireless network of skin-integrated devices with an advanced bioresorbable pacemaker to control cardiac rhythms, track cardiopulmonary status, provide multihaptic feedback, and enable transient operation with minimal patient burden. The result provides a range of autonomous, rate-adaptive cardiac pacing capabilities, as demonstrated in rat, canine, and human heart studies. This work establishes an engineering framework for closed-loop temporary electrotherapy using wirelessly linked, body-integrated bioelectronic devices.

Local electrical stimulation of peripheral nerves can block the propagation of action potentials, as an attractive alternative to pharmacological agents for the treatment of acute pain. Traditional hardware for such purposes, however, involves interfaces that can damage nerve tissue and, when used for temporary pain relief, that impose costs and risks due to requirements for surgical extraction after a period of need. Here, we introduce a bioresorbable nerve stimulator that enables electrical nerve block and associated pain mitigation without these drawbacks. This platform combines a collection of bioresorbable materials in architectures that support stable blocking with minimal adverse mechanical, electrical, or biochemical effects. Optimized designs ensure that the device disappears harmlessly in the body after a desired period of use. Studies in live animal models illustrate capabilities for complete nerve block and other key features of the technology. In certain clinically relevant scenarios, such approaches may reduce or eliminate the need for use of highly addictive drugs such as opioids.

When robots operate in real-world off-road environments with unstructured terrains, the ability to adapt their navigational policy is critical for effective and safe navigation. However, off-road terrains introduce several challenges to robot navigation, including dynamic obstacles and terrain uncertainty, leading to inefficient traversal or navigation failures. To address these challenges, we introduce a novel approach for adaptation by negotiation that enables a ground robot to adjust its navigational behaviors through a negotiation process. Our approach first learns prediction models for various navigational policies to function as a terrain-aware joint local controller and planner. Then, through a new negotiation process, our approach learns from various policies' interactions with the environment to agree on the optimal combination of policies in an online fashion to adapt robot navigation to unstructured off-road terrains on the fly. Additionally, we implement a new optimization algorithm that offers the optimal solution for robot negotiation in real-time during execution. Experimental results have validated that our method for adaptation by negotiation outperforms previous methods for robot navigation, especially over unseen and uncertain dynamic terrains., Comment: 10 pages : 8 pages main + 2 pages supplemental

Batteries represent the dominant means for storing electrical energy, but many battery chemistries create waste streams that are difficult to manage, and most possess toxic components that limit their use in biomedical applications. Batteries constructed from materials capable of complete, harmless resorption into the environment or into living organisms after a desired period of operation bypass these disadvantages. However, previously reported eco/bioresorbable batteries offer low operating voltages and modest energy densities. Here, we introduce a magnesium-iodine chemistry and dual (ionic liquid/aqueous) electrolyte to overcome these limitations, enabling significant improvements in voltage, areal capacity, areal energy, areal power, volumetric energy, and volumetric power densities over any alternative. Systematic studies reveal key materials and design considerations. Demonstrations of this technology include power supplies for cardiac pacemakers, wireless environmental monitors, and thermal sensors/actuators. These results suggest strong potential for applications where commercial battery alternatives pose risks to the environment or the human body.

We present a self-supervised approach for learning to predict traversable paths for wheeled mobile robots that require good traction to navigate. Our algorithm, termed WayFAST (Waypoint Free Autonomous Systems for Traversability), uses RGB and depth data, along with navigation experience, to autonomously generate traversable paths in outdoor unstructured environments. Our key inspiration is that traction can be estimated for rolling robots using kinodynamic models. Using traction estimates provided by an online receding horizon estimator, we are able to train a traversability prediction neural network in a self-supervised manner, without requiring heuristics utilized by previous methods. We demonstrate the effectiveness of WayFAST through extensive field testing in varying environments, ranging from sandy dry beaches to forest canopies and snow covered grass fields. Our results clearly demonstrate that WayFAST can learn to avoid geometric obstacles as well as untraversable terrain, such as snow, which would be difficult to avoid with sensors that provide only geometric data, such as LiDAR. Furthermore, we show that our training pipeline based on online traction estimates is more data-efficient than other heuristic-based methods., Comment: Project website with code and videos: https://mateusgasparino.com/wayfast-traversability-navigation/ Published in the IEEE Robotics and Automation Letters (RA-L, 2022) Accepted for presentation in the 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2022)

Reinforcement learning (RL) approaches can illuminate emergent behaviors that facilitate coordination across teams of agents as part of a multi-agent system (MAS), which can provide windows of opportunity in various military tasks. Technologically advancing adversaries pose substantial risks to a friendly nation's interests and resources. Superior resources alone are not enough to defeat adversaries in modern complex environments because adversaries create standoff in multiple domains against predictable military doctrine-based maneuvers. Therefore, as part of a defense strategy, friendly forces must use strategic maneuvers and disruption to gain superiority in complex multi-faceted domains such as multi-domain operations (MDO). One promising avenue for implementing strategic maneuver and disruption to gain superiority over adversaries is through coordination of MAS in future military operations. In this paper, we present overviews of prominent works in the RL domain with their strengths and weaknesses for overcoming the challenges associated with performing autonomous strategic maneuver and disruption in military contexts., Comment: 23 pages, 3 figures, 60 references, Review Paper

Imagery collected from outdoor visual environments is often degraded due to the presence of dense smoke or haze. A key challenge for research in scene understanding in these degraded visual environments (DVE) is the lack of representative benchmark datasets. These datasets are required to evaluate state-of-the-art vision algorithms (e.g., detection and tracking) in degraded settings. In this paper, we address some of these limitations by introducing the first realistic hazy image benchmark, from both aerial and ground view, with paired haze-free images, and in-situ haze density measurements. This dataset was produced in a controlled environment with professional smoke generating machines that covered the entire scene, and consists of images captured from the perspective of both an unmanned aerial vehicle (UAV) and an unmanned ground vehicle (UGV). We also evaluate a set of representative state-of-the-art dehazing approaches as well as object detectors on the dataset. The full dataset presented in this paper, including the ground truth object classification bounding boxes and haze density measurements, is provided for the community to evaluate their algorithms at: https://a2i2-archangel.vision. A subset of this dataset has been used for the ``Object Detection in Haze'' Track of CVPR UG2 2022 challenge at http://cvpr2022.ug2challenge.org/track1.html., Comment: This paper has been ACCEPTED for publication as a REGULAR paper in the IEEE Transactions on Image Processing (TIP)

California Policy Options 2009: California forecast, California politics, California budget, California educational opportunity, University of California

Globally, neonatal mortality remains unacceptability high. Physiological monitoring is foundational to the care of these vulnerable patients to assess neonatal cardiopulmonary status, guide medical intervention, and determine readiness for safe discharge. However, most existing physiological monitoring systems require multiple electrodes and sensors, which are linked to wires tethered to wall-mounted display units, to adhere to the skin. For neonates, these systems can cause skin injury, prevent kangaroo mother care, and complicate basic clinical care. Novel, wireless, and biointegrated sensors provide opportunities to enhance monitoring capabilities, reduce iatrogenic injuries, and promote family-centric care. Early validation data have shown performance equivalent to (and sometimes exceeding) standard-of-care monitoring systems in premature neonates cared for in high-income countries. The reusable nature of these sensors and compatibility with low-cost mobile phones have the future potential to enable substantially lower monitoring costs compared with existing systems. Deployment at scale, in low-income countries, holds the promise of substantial improvements in neonatal outcomes., ChemE/Product and Process Engineering

Radiolarians (holoplanktonic protozoa) preserved in marine sediments are commonly used as palaeoclimate proxies for reconstructing past Southern Ocean environments. Generating reconstructions of past climate based on microfossil abundances, such as radiolarians, requires a spatially and environmentally comprehensive reference dataset of modern census counts. The Southern Ocean Radiolarian (SO-RAD) dataset includes census counts for 238 radiolarian taxa from 228 surface sediment samples located in the Atlantic, Indian, and southwest Pacific sectors of the Southern Ocean. This compilation is the largest radiolarian census dataset derived from surface sediment samples in the Southern Ocean. The SO-RAD dataset may be used as a reference dataset for palaeoceanographic reconstructions, or for studying modern radiolarian biogeography and species diversity. As well as describing the data collection and collation, we include recommendations and guidelines for cleaning and subsetting the data for users unfamiliar with the procedures typically used by the radiolarian community. The SO-RAD dataset is available to download from https://doi.org/10.1594/PANGAEA.929903 (Lawler et al., 2021).

A cardinal obstacle to performing quantum-mechanical simulations of strongly correlated matter is that, with the theoretical tools presently available, sufficiently accurate computations are often too expensive to be ever feasible. Here we design a computational framework combining quantum-embedding (QE) methods with machine learning. This allows us to bypass altogether the most computationally expensive components of QE algorithms, making their overall cost comparable to bare density functional theory. We perform benchmark calculations of a series of actinide systems, where our method accurately describes the correlation effects, reducing by orders of magnitude the computational cost. We argue that, by producing a larger-scale set of training data, it will be possible to apply our method to systems with arbitrary stoichiometries and crystal structures, paving the way to virtually infinite applications in condensed matter physics, chemistry, and materials science.

Three-dimensional (3D), submillimeter-scale constructs of neural cells, known as cortical spheroids, are of rapidly growing importance in biological research because these systems reproduce complex features of the brain in vitro. Despite their great potential for studies of neurodevelopment and neurological disease modeling, 3D living objects cannot be studied easily using conventional approaches to neuromodulation, sensing, and manipulation. Here, we introduce classes of microfabricated 3D frameworks as compliant, multifunctional neural interfaces to spheroids and to assembloids. Electrical, optical, chemical, and thermal interfaces to cortical spheroids demonstrate some of the capabilities. Complex architectures and high-resolution features highlight the design versatility. Detailed studies of the spreading of coordinated bursting events across the surface of an isolated cortical spheroid and of the cascade of processes associated with formation and regrowth of bridging tissues across a pair of such spheroids represent two of the many opportunities in basic neuroscience research enabled by these platforms.

Capabilities for continuous monitoring of pressures and temperatures at critical skin interfaces can help to guide care strategies that minimize the potential for pressure injuries in hospitalized patients or in individuals confined to the bed. This paper introduces a soft, skin-mountable class of sensor system for this purpose. The design includes a pressure-responsive element based on membrane deflection and a battery-free, wireless mode of operation capable of multi-site measurements at strategic locations across the body. Such devices yield continuous, simultaneous readings of pressure and temperature in a sequential readout scheme from a pair of primary antennas mounted under the bedding and connected to a wireless reader and a multiplexer located at the bedside. Experimental evaluation of the sensor and the complete system includes benchtop measurements and numerical simulations of the key features. Clinical trials involving two hemiplegic patients and a tetraplegic patient demonstrate the feasibility, functionality and long-term stability of this technology in operating hospital settings.

Precise, quantitative measurements of the hydration status of skin can yield important insights into dermatological health and skin structure and function, with additional relevance to essential processes of thermoregulation and other features of basic physiology. Existing tools for determining skin water content exploit surrogate electrical assessments performed with bulky, rigid, and expensive instruments that are difficult to use in a repeatable manner. Recent alternatives exploit thermal measurements using soft wireless devices that adhere gently and noninvasively to the surface of the skin, but with limited operating range (∼1 cm) and high sensitivity to subtle environmental fluctuations. This paper introduces a set of ideas and technologies that overcome these drawbacks to enable high-speed, robust, long-range automated measurements of thermal transport properties via a miniaturized, multisensor module controlled by a long-range (∼10 m) Bluetooth Low Energy system on a chip, with a graphical user interface to standard smartphones. Soft contact to the surface of the skin, with almost zero user burden, yields recordings that can be quantitatively connected to hydration levels of both the epidermis and dermis, using computational modeling techniques, with high levels of repeatability and insensitivity to ambient fluctuations in temperature. Systematic studies of polymers in layered configurations similar to those of human skin, of porcine skin with known levels of hydration, and of human subjects with benchmarks against clinical devices validate the measurement approach and associated sensor hardware. The results support capabilities in characterizing skin barrier function, assessing severity of skin diseases, and evaluating cosmetic and medication efficacy, for use in the clinic or in the home.

Early identification of atypical infant movement behaviors consistent with underlying neuromotor pathologies can expedite timely enrollment in therapeutic interventions that exploit inherent neuroplasticity to promote recovery. Traditional neuromotor assessments rely on qualitative evaluations performed by specially trained personnel, mostly available in tertiary medical centers or specialized facilities. Such approaches are high in cost, require geographic proximity to advanced healthcare resources, and yield mostly qualitative insight. This paper introduces a simple, low-cost alternative in the form of a technology customized for quantitatively capturing continuous, full-body kinematics of infants during free living conditions at home or in clinical settings while simultaneously recording essential vital signs data. The system consists of a wireless network of small, flexible inertial sensors placed at strategic locations across the body and operated in a wide-bandwidth and time-synchronized fashion. The data serve as the basis for reconstructing three-dimensional motions in avatar form without the need for video recordings and associated privacy concerns, for remote visual assessments by experts. These quantitative measurements can also be presented in graphical format and analyzed with machine-learning techniques, with potential to automate and systematize traditional motor assessments. Clinical implementations with infants at low and at elevated risks for atypical neuromotor development illustrates application of this system in quantitative and semiquantitative assessments of patterns of gross motor skills, along with body temperature, heart rate, and respiratory rate, from long-term and follow-up measurements over a 3-mo period following birth. The engineering aspects are compatible for scaled deployment, with the potential to improve health outcomes for children worldwide via early, pragmatic detection methods.

Temporary cardiac pacemakers used in periods of need during surgical recovery involve percutaneous leads and externalized hardware that carry risks of infection, constrain patient mobility and may damage the heart during lead removal. Here we report a leadless, battery-free, fully implantable cardiac pacemaker for postoperative control of cardiac rate and rhythm that undergoes complete dissolution and clearance by natural biological processes after a defined operating timeframe. We show that these devices provide effective pacing of hearts of various sizes in mouse, rat, rabbit, canine and human cardiac models, with tailored geometries and operation timescales, powered by wireless energy transfer. This approach overcomes key disadvantages of traditional temporary pacing devices and may serve as the basis for the next generation of postoperative temporary pacing technology.

Recently developed methods for transforming 2D patterns of thin-film materials into 3D mesostructures create many interesting opportunities in microsystems design. A growing area of interest is in multifunctional thermal, electrical, chemical, and optical interfaces to biological tissues, particularly 3D multicellular, millimeter-scale constructs, such as spheroids, assembloids, and organoids. Herein, examples of 3D mechanical interfaces are presented, in which thin ribbons of parylene-C form the basis of transparent, highly compliant frameworks that can be reversibly opened and closed to capture, envelop, and mechanically restrain fragile 3D tissues in a gentle, nondestructive manner, for precise measurements of viscoelastic properties using techniques in nanoindentation. Finite element analysis serves as a design tool to guide selection of geometries and material parameters for shape-matching 3D architectures tailored to organoids of interest. These computational approaches also quantitate all aspects of deformations during the processes of opening and closing the structures and of forces imparted by them onto the surfaces of enclosed soft tissues. Studies of cerebral organoids by nanoindentation show effective Youngs moduli in the range from 1.5 to 2.5 kPa depending on the age of the organoid. This collection of results suggests broad utility of compliant 3D mesostructures in noninvasive mechanical measurements of millimeter-scale, soft biological tissues.

Itch is a common clinical symptom and major driver of disease-related morbidity across a wide range of medical conditions. A substantial unmet need is for objective, accurate measurements of itch. In this article, we present a noninvasive technology to objectively quantify scratching behavior via a soft, flexible, and wireless sensor that captures the acousto-mechanic signatures of scratching from the dorsum of the hand. A machine learning algorithm validated on data collected from healthy subjects (n = 10) indicates excellent performance relative to smartwatch-based approaches. Clinical validation in a cohort of predominately pediatric patients (n = 11) with moderate to severe atopic dermatitis included 46 sleep-nights totaling 378.4 hours. The data indicate an accuracy of 99.0% (84.3% sensitivity, 99.3% specificity) against visual observation. This work suggests broad capabilities relevant to applications ranging from assessing the efficacy of drugs for conditions that cause itch to monitoring disease severity and treatment response.

Vital signs monitoring is a fundamental component of ensuring the health and safety of women and newborns during pregnancy, labor, and childbirth. This monitoring is often the first step in early detection of pregnancy abnormalities, providing an opportunity for prompt, effective intervention to prevent maternal and neonatal morbidity and mortality. Contemporary pregnancy monitoring systems require numerous devices wired to large base units; at least five separate devices with distinct user interfaces are commonly used to detect uterine contractility, maternal blood oxygenation, temperature, heart rate, blood pressure, and fetal heart rate. Current monitoring technologies are expensive and complex with implementation challenges in low-resource settings where maternal morbidity and mortality is the greatest. We present an integrated monitoring platform leveraging advanced flexible electronics, wireless connectivity, and compatibility with a wide range of low-cost mobile devices. Three flexible, soft, and low-profile sensors offer comprehensive vital signs monitoring for both women and fetuses with time-synchronized operation, including advanced parameters such as continuous cuffless blood pressure, electrohysterography-derived uterine monitoring, and automated body position classification. Successful field trials of pregnant women between 25 and 41 wk of gestation in both high-resource settings (n = 91) and low-resource settings (n = 485) demonstrate the systems performance, usability, and safety.

Capabilities in continuous monitoring of key physiological parameters of disease have never been more important than in the context of the global COVID-19 pandemic. Soft, skin-mounted electronics that incorporate high-bandwidth, miniaturized motion sensors enable digital, wireless measurements of mechanoacoustic (MA) signatures of both core vital signs (heart rate, respiratory rate, and temperature) and underexplored biomarkers (coughing count) with high fidelity and immunity to ambient noises. This paper summarizes an effort that integrates such MA sensors with a cloud data infrastructure and a set of analytics approaches based on digital filtering and convolutional neural networks for monitoring of COVID-19 infections in sick and healthy individuals in the hospital and the home. Unique features are in quantitative measurements of coughing and other vocal events, as indicators of both disease and infectiousness. Systematic imaging studies demonstrate correlations between the time and intensity of coughing, speaking, and laughing and the total droplet production, as an approximate indicator of the probability for disease spread. The sensors, deployed on COVID-19 patients along with healthy controls in both inpatient and home settings, record coughing frequency and intensity continuously, along with a collection of other biometrics. The results indicate a decaying trend of coughing frequency and intensity through the course of disease recovery, but with wide variations across patient populations. The methodology creates opportunities to study patterns in biometrics across individuals and among different demographic groups.

Soft, skin-integrated electronic sensors can provide continuous measurements of diverse physiological parameters, with broad relevance to the future of human health care. Motion artifacts can, however, corrupt the recorded signals, particularly those associated with mechanical signatures of cardiopulmonary processes. Design strategies introduced here address this limitation through differential operation of a matched, time-synchronized pair of high-bandwidth accelerometers located on parts of the anatomy that exhibit strong spatial gradients in motion characteristics. When mounted at a location that spans the suprasternal notch and the sternal manubrium, these dual-sensing devices allow measurements of heart rate and sounds, respiratory activities, body temperature, body orientation, and activity level, along with swallowing, coughing, talking, and related processes, without sensitivity to ambient conditions during routine daily activities, vigorous exercises, intense manual labor, and even swimming. Deployments on patients with COVID-19 allow clinical-grade ambulatory monitoring of the key symptoms of the disease even during rehabilitation protocols.

Ground robots require the crucial capability of traversing unstructured and unprepared terrains and avoiding obstacles to complete tasks in real-world robotics applications such as disaster response. When a robot operates in off-road field environments such as forests, the robot's actual behaviors often do not match its expected or planned behaviors, due to changes in the characteristics of terrains and the robot itself. Therefore, the capability of robot adaptation for consistent behavior generation is essential for maneuverability on unstructured off-road terrains. In order to address the challenge, we propose a novel method of self-reflective terrain-aware adaptation for ground robots to generate consistent controls to navigate over unstructured off-road terrains, which enables robots to more accurately execute the expected behaviors through robot self-reflection while adapting to varying unstructured terrains. To evaluate our method's performance, we conduct extensive experiments using real ground robots with various functionality changes over diverse unstructured off-road terrains. The comprehensive experimental results have shown that our self-reflective terrain-aware adaptation method enables ground robots to generate consistent navigational behaviors and outperforms the compared previous and baseline techniques., Comment: 13 pages, 7 figures, IJRR21

© 2018 IOP Publishing Ltd. This roadmap outlines the role semiconductor-based materials play in understanding the complex biophysical dynamics at multiple length scales, as well as the design and implementation of next-generation electronic, optoelectronic, and mechanical devices for biointerfaces. The roadmap emphasizes the advantages of semiconductor building blocks in interfacing, monitoring, and manipulating the activity of biological components, and discusses the possibility of using active semiconductor-cell interfaces for discovering new signaling processes in the biological world.

Terrain adaptation is an essential capability for a ground robot to effectively traverse unstructured off-road terrain in real-world field environments such as forests. However, the expected robot behaviors generated by terrain adaptation methods cannot always be executed accurately due to setbacks such as wheel slip and reduced tire pressure. To address this problem, we propose a novel approach for consistent behavior generation that enables the ground robot's actual behaviors to more accurately match expected behaviors while adapting to a variety of unstructured off-road terrain. Our approach learns offset behaviors that are used to compensate for the inconsistency between the actual and expected behaviors without requiring the explicit modeling of various setbacks. Our approach is also able to estimate the importance of the multi-modal features to improve terrain representations for better adaptation. In addition, we develop an algorithmic solver for our formulated regularized optimization problem, which is guaranteed to converge to the global optimal solution. To evaluate the method, we perform extensive experiments using various unstructured off-road terrain in real-world field environments. Experimental results have validated that our approach enables robots to traverse complex unstructured off-road terrain with more navigational behavior consistency, and it outperforms previous methods, particularly so on challenging terrain., Comment: 6 pages, 6 figures, Submitted to ICRA21

Jupiter’s Great Red Spot (GRS), a giant anticyclone, is the largest and longest-lived of all the vortices observed in planetary atmospheres. During its history, the GRS has shrunk to half its size since 1879, and encountered many smaller anticyclones and other dynamical features that might tend to erode it. In 2018-2020, while having a historically small size, its structure and even its survival appeared to be threatened when a series of anticyclones moving in from the east tore off large fragments of the red area and distorted its shape. In this work we report observations of the dynamics of these interactions and show that as a result the GRS increased its internal rotation velocity, maintaining its vorticity but decreasing its visible area, and suffering a transient change in its otherwise steady 90-day oscillation in longitude. From a radiative transfer analysis and numerical simulations of the dynamics we show that the interactions affected the upper cloud tops of the GRS. We argue that the intense vorticity of the GRS, together with its larger size and depth compared to the interacting vortices, guarantees its long lifetime., This work has been supported by the Spanish project AYA2015-65041-P and PID2019-109467GB-I00 (MINECO/ FEDER, UE) and Grupos Gobierno Vasco IT1366-19. PI acknowledges a PhD scholarship from Gobierno Vasco. EGM is Serra Hunter Fellow at UPC. This work used data acquired from the NASA/ESA HST Space Telescope, asso- ciated with OPAL program (PI: Simon, GO13937), and archived by the Space Telescope Science Institute, which is operated by the Association of Universi- ties for Research in Astronomy, Inc., under NASA contract NAS 5–26,555. All maps are available at http://dx.doi. org/10.17909/T9G593. PlanetCam ob- servations were collected at the Centro Astronómico Hispánico en Andalucía (CAHA), operated jointly by the Insti- tuto de Astrofisica de Andalucia (CSIC) and the Andalusian Universities (Junta de Andalucía). EGM, MS, APG, MAC and ASL thankfully acknowledge the computer resources at Mare Nostrum and the technical support provided by Barcelona Supercomputing Center (AECT-2019-2-0006). This research has made use of the USGS Integrated Software for Imagers and Spectrometers (ISIS). We appreciate the contribution from all observers cited in TableS1 for his fundamental contribution to this study with Jupiter images obtained with high dedication and skill. GSO and TM were supported by NASA with funds distributed to the Jet Propulsion Laboratory, California Institute of Technology., Peer Reviewed, Postprint (author's final draft)

REBCO tape has remarkable performance for super-conducting technology, but it is extremely expensive and it is a strongly anisotropic superconductor. The design of a 3.5 T collider dipole is presented in which all turns of the body winding are oriented so that the all turns of REBCO tape operate with maximum current density. Each turn within the winding contains a stack of Cu-clad REBCO tapes; all tapes within the turn are compressed to provide low-resistance Cu-Cu contact, but the successive turns are electrically isolated. Each turn is oriented so that the local magnetic field at the tapes is closely parallel to the tape surface. Sextupole is controlled using a current-programmed turn to provide excellent homogeneity over a 20:1 dynamic range. Issues of current re-distribution during ramping, quench stability, AC losses, synchrotron radiation, and cryogenics have been considered, and appear to provide favorable properties for an ultimate-energy hadron collider.