Decentralised Coordination of Low-Power Embedded Devices Using the Max-Sum Algorithm

This paper considers the problem of performing decentralised coordination of low-power embedded devices (as is required within many environmental sensing and surveillance applications). Specifically, we address the generic problem of maximising social welfare within a group of interacting agents. We propose a novel representation of the problem, as a cyclic bipartite factor graph, composed of variable and function nodes (representing the agents’ states and utilities respectively). We show that such representation allows us to use an extension of the max-sum algorithm to generate approximate solutions to this global optimisation problem through local decentralised message passing. We empirically evaluate this approach on a canonical coordination problem (graph colouring), and benchmark it against state of the art approximate and complete algorithms (DSA and DPOP). We show that our approach is robust to lossy communication, that it generates solutions closer to those of DPOP than DSA is able to, and that it does so with a communication cost (in terms of total messages size) that scales very well with the number of agents in the system (compared to the exponential increase of DPOP). Finally, we describe a hardware implementation of our algorithm operating on low-power Chipcon CC2431 System-on-Chip sensor nodes

Test Plan for a Calibration Demonstration System for the Reflected Solar Instrument for the Climate Absolute Radiance and Refractivity Observatory

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission addresses the need to observe high-accuracy, long-term climate change trends and to use decadal change observations as the most critical method to determine the accuracy of climate change. One of the major objectives of CLARREO is to advance the accuracy of SI traceable absolute calibration at infrared and reflected solar wavelengths. This advance is required to reach the on-orbit absolute accuracy required to allow climate change observations to survive data gaps while remaining sufficiently accurate to observe climate change to within the uncertainty of the limit of natural variability. While these capabilities exist at NIST in the laboratory, there is a need to demonstrate that it can move successfully from NIST to NASA and/or instrument vendor capabilities for future spaceborne instruments. The current work describes the test plan for the Solar, Lunar for Absolute Reflectance Imaging Spectroradiometer (SOLARIS) which is the calibration demonstration system (CDS) for the reflected solar portion of CLARREO. The goal of the CDS is to allow the testing and evaluation of calibration approaches , alternate design and/or implementation approaches and components for the CLARREO mission. SOLARIS also provides a test-bed for detector technologies, non-linearity determination and uncertainties, and application of future technology developments and suggested spacecraft instrument design modifications. The end result of efforts with the SOLARIS CDS will be an SI-traceable error budget for reflectance retrieval using solar irradiance as a reference and methods for laboratory-based, absolute calibration suitable for climate-quality data collections. The CLARREO mission addresses the need to observe high-accuracy, long-term climate change trends and advance the accuracy of SI traceable absolute calibration. The current work describes the test plan for the SOLARIS which is the calibration demonstration system for the reflected solar portion of CLARREO. SOLARIS provides a test-bed for detector technologies, non-linearity determination and uncertainties, and application of future technology developments and suggested spacecraft instrument design modifications. The end result will be an SI-traceable error budget for reflectance retrieval using solar irradiance as a reference and methods for laboratory-based, absolute calibration suitable for climate-quality data collections

Orbital-scale climate variability in Arabia as a potential motor for human dispersals

The Arabian Peninsula is situated at an important crossroads for the movement of Pleistocene human populations out of, and into, Africa. Although the timings, routes and frequencies of such dispersals have not yet been confirmed by genetic, fossil or archaeological evidence, expansion into Arabia would have been facilitated by humid periods driven by incursions of monsoon rainfall, potentially from both Indian Ocean and African monsoon systems. Here we synthesise terrestrial and marine core palaeoclimatic data in order to establish the spatial and temporal variability of humid periods in Arabia between late Marine Isotope Stage (MIS) 7 and 3. Incursions of monsoon rainfall occurred during periods of insolation maxima at ca. 200–190, 170, 155, 130–120, 105–95, 85–75 and 60–55 ka, providing multiple ‘windows’ of favourable climatic conditions that could have facilitated demographic expansion through Arabia. Strong summer monsoons are generally associated with mid-high latitude interglacials, however, enhanced monsoon convection also brought rainfall into Arabia during global glacial phases, possibly due to a strengthened winter monsoon and a greater influence of southern hemispheric temperature changes. Key periods for dispersal into northern regions of Arabia correspond with the synchronous intensification of both eastern Mediterranean and monsoon rainfall systems at insolation maxima during MIS 7 and MIS 5, which may have facilitated demographic connectivity between the Levant and the Arabian interior. Environmental conditions throughout southern and southeast regions were also favourable to expansion during these times, although strong monsoons in these regions during MIS 6 and MIS 3 suggest further opportunities for demographic expansion and exchange. Terrestrial and marine evidence show that during early MIS 3 (ca. 60–50 ka), a strengthened monsoon led to the activation of interior drainage systems and increased productivity in coastal zones, indicating that favourable environmental conditions existed along both coastal and interior routes at that time

Aggressive pituitary adenomas occurring in young patients in a large Polynesian kindred with a germline R271W mutation in the AIP gene.

peer reviewedOBJECTIVE: Mutations in the aryl hydrocarbon receptor-interacting protein (AIP) were recently shown to confer a pituitary adenoma predisposition in patients with familial isolated pituitary adenomas (FIPA). We report a large Samoan FIPA kindred from Australia/New Zealand with an R271W mutation that was associated with aggressive pituitary tumors. DESIGN AND METHODS: Case series with germline screening of AIP and haplotype analyses among R271W families. RESULTS: This previously unreported kindred consisted of three affected individuals that either presented with or had first symptoms of a pituitary macroadenoma in late childhood or adolescence. The index case, a 15-year-old male with incipient gigantism and his maternal aunt, had somatotropinomas, and the maternal uncle of the index case had a prolactinoma. All tumors were large (15, 40, and 60 mm maximum diameter) and two required transcranial surgery and radiotherapy. All three affected subjects and ten other unaffected relatives were found to be positive for a germline R271W AIP mutation. Comparison of the single nucleotide polymorphism patterns among this family and two previously reported European FIPA families with the same R271W mutation demonstrated no common ancestry. CONCLUSIONS: This kindred exemplifies the aggressive features of pituitary adenomas associated with AIP mutations, while genetic analyses among three R271W FIPA families indicate that R271W represents a mutational hotspot that should be studied further in functional studies

Wind and trophic status explain within and among‐lake variability of algal biomass

Phytoplankton biomass and production regulates key aspects of freshwater ecosystems yet its variability and subsequent predictability is poorly understood. We estimated within‐lake variation in biomass using high‐frequency chlorophyll fluorescence data from 18 globally distributed lakes. We tested how variation in fluorescence at monthly, daily, and hourly scales was related to high‐frequency variability of wind, water temperature, and radiation within lakes as well as productivity and physical attributes among lakes. Within lakes, monthly variation dominated, but combined daily and hourly variation were equivalent to that expressed monthly. Among lakes, biomass variability increased with trophic status while, within‐lake biomass variation increased with increasing variability in wind speed. Our results highlight the benefits of high‐frequency chlorophyll monitoring and suggest that predicted changes associated with climate, as well as ongoing cultural eutrophication, are likely to substantially increase the temporal variability of algal biomass and thus the predictability of the services it provides

Silicon carbide absorption features: dust formation in the outflows of extreme carbon stars

Infrared carbon stars without visible counterparts are generally known as extreme carbon stars. We have selected a subset of these stars with absorption features in the 10-13 $\mu$m range, which has been tentatively attributed to silicon carbide (SiC). We add three new objects meeting these criterion to the seven previously known, bringing our total sample to ten sources. We also present the result of radiative transfer modeling for these stars, comparing these results to those of previous studies. In order to constrain model parameters, we use published mass-loss rates, expansion velocities and theoretical dust condensation models to determine the dust condensation temperature. These show that the inner dust temperatures of the dust shells for these sources are significantly higher than previously assumed. This also implies that the dominant dust species should be graphite instead of amorphous carbon. In combination with the higher condensation temperature we show that this results in a much higher acceleration of the dust grains than would be expected from previous work. Our model results suggest that the very optically thick stage of evolution does not coincide with the timescales for the superwind, but rather, that this is a very short-lived phase. Additionally, we compare model and observational parameters in an attempt to find any correlations. Finally, we show that the spectrum of one source, IRAS 17534$-$3030, strongly implies that the 10-13 $\mu$m feature is due to a solid state rather than a molecular species.Comment: 13 Figure

Instrumentation and First Results of the Reflected Solar Demonstration System for the Climate Absolute Radiance and Refractivity Observatory

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission key goals include enabling observation of high accuracy long-term climate change trends, use of these observations to test and improve climate forecasts, and calibration of operational and research sensors. The spaceborne instrument suites include a reflected solar spectroradiometer, emitted infrared spectroradiometer, and radio occultation receivers. The requirement for the RS instrument is that derived reflectance must be traceable to Sl standards with an absolute uncertainty of <0.3% and the error budget that achieves this requirement is described in previo1L5 work. This work describes the Solar/Lunar Absolute Reflectance Imaging Spectroradiometer (SOLARIS), a calibration demonstration system for RS instrument, and presents initial calibration and characterization methods and results. SOLARIS is an Offner spectrometer with two separate focal planes each with its own entrance aperture and grating covering spectral ranges of 320-640, 600-2300 nm over a full field-of-view of 10 degrees with 0.27 milliradian sampling. Results from laboratory measurements including use of integrating spheres, transfer radiometers and spectral standards combined with field-based solar and lunar acquisitions are presented. These results will be used to assess the accuracy and repeatability of the radiometric and spectral characteristics of SOLARIS, which will be presented against the sensor-level requirements addressed in the CLARREO RS instrument error budget

The Future of Fundamental Science Led by Generative Closed-Loop Artificial Intelligence

Recent advances in machine learning and AI, including Generative AI and LLMs, are disrupting technological innovation, product development, and society as a whole. AI's contribution to technology can come from multiple approaches that require access to large training data sets and clear performance evaluation criteria, ranging from pattern recognition and classification to generative models. Yet, AI has contributed less to fundamental science in part because large data sets of high-quality data for scientific practice and model discovery are more difficult to access. Generative AI, in general, and Large Language Models in particular, may represent an opportunity to augment and accelerate the scientific discovery of fundamental deep science with quantitative models. Here we explore and investigate aspects of an AI-driven, automated, closed-loop approach to scientific discovery, including self-driven hypothesis generation and open-ended autonomous exploration of the hypothesis space. Integrating AI-driven automation into the practice of science would mitigate current problems, including the replication of findings, systematic production of data, and ultimately democratisation of the scientific process. Realising these possibilities requires a vision for augmented AI coupled with a diversity of AI approaches able to deal with fundamental aspects of causality analysis and model discovery while enabling unbiased search across the space of putative explanations. These advances hold the promise to unleash AI's potential for searching and discovering the fundamental structure of our world beyond what human scientists have been able to achieve. Such a vision would push the boundaries of new fundamental science rather than automatize current workflows and instead open doors for technological innovation to tackle some of the greatest challenges facing humanity today.Comment: 35 pages, first draft of the final report from the Alan Turing Institute on AI for Scientific Discover

Wind and trophic status explain within and among-lake variability of algal biomass

Phytoplankton biomass and production regulates key aspects of freshwater ecosystems yet its variability and subsequent predictability is poorly understood. We estimated within-lake variation in biomass using high-frequency chlorophyll fluorescence data from 18 globally distributed lakes. We tested how variation in fluorescence at monthly, daily, and hourly scales was related to high-frequency variability of wind, water temperature, and radiation within lakes as well as productivity and physical attributes among lakes. Within lakes, monthly variation dominated, but combined daily and hourly variation were equivalent to that expressed monthly. Among lakes, biomass variability increased with trophic status while, within-lake biomass variation increased with increasing variability in wind speed. Our results highlight the benefits of high-frequency chlorophyll monitoring and suggest that predicted changes associated with climate, as well as ongoing cultural eutrophication, are likely to substantially increase the temporal variability of algal biomass and thus the predictability of the services it provides.Peer reviewe