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Application of remote sensing to selected problems within the state of California
Specific case studies undertaken to demonstrate the usefulness of remote sensing technology to resource managers in California are highlighted. Applications discussed include the mapping and quantization of wildland fire fuels in Mendocino and Shasta Counties as well as in the Central Valley; the development of a digital spectral/terrain data set for Colusa County; the Forsythe Planning Experiment to maximize the usefulness of inputs from LANDSAT and geographic information systems to county planning in Mendocino County; the development of a digital data bank for Big Basin State Park in Santa Cruz County; the detection of salinity related cotton canopy reflectance differences in the Central Valley; and the surveying of avocado acreage and that of other fruits and nut crops in Southern California. Special studies include the interpretability of high altitude, large format photography of forested areas for coordinated resource planning using U-2 photographs of the NASA Bucks Lake Forestry test site in the Plumas National Forest in the Sierra Nevada Mountains.
To See the Unseen: A History of Planetary Radar Astronomy
This book relates the history of planetary radar astronomy from its origins in radar to the present day and secondarily to bring to light that history as a case of 'Big Equipment but not Big Science'. Chapter One sketches the emergence of radar astronomy as an ongoing scientific activity at Jodrell Bank, where radar research revealed that meteors were part of the solar system. The chief Big Science driving early radar astronomy experiments was ionospheric research. Chapter Two links the Cold War and the Space Race to the first radar experiments attempted on planetary targets, while recounting the initial achievements of planetary radar, namely, the refinement of the astronomical unit and the rotational rate and direction of Venus. Chapter Three discusses early attempts to organize radar astronomy and the efforts at MIT's Lincoln Laboratory, in conjunction with Harvard radio astronomers, to acquire antenna time unfettered by military priorities. Here, the chief Big Science influencing the development of planetary radar astronomy was radio astronomy. Chapter Four spotlights the evolution of planetary radar astronomy at the Jet Propulsion Laboratory, a NASA facility, at Cornell University's Arecibo Observatory, and at Jodrell Bank. A congeries of funding from the military, the National Science Foundation, and finally NASA marked that evolution, which culminated in planetary radar astronomy finding a single Big Science patron, NASA. Chapter Five analyzes planetary radar astronomy as a science using the theoretical framework provided by philosopher of science Thomas Kuhn. Chapter Six explores the shift in planetary radar astronomy beginning in the 1970s that resulted from its financial and institutional relationship with NASA Big Science. Chapter Seven addresses the Magellan mission and its relation to the evolution of planetary radar astronomy from a ground-based to a space-based activity. Chapters Eight and Nine discuss the research carried out at ground-based facilities by this transformed planetary radar astronomy, as well as the upgrading of the Arecibo and Goldstone radars. A technical essay appended to this book provides an overview of planetary radar techniques, especially range-Doppler mapping.
Bulb Miser
The Bulb-Miser was developed during NASA's Apollo program to protect the Saturn launch vehicle from electrical current surge. It is now being produced for the commercial market by Bulb-Miser, Inc., Houston, Texas. Technically known as a "temperature compensating thermistor," the Bulb-Miser is a simple, inexpensive device which looks like a washer about the size of a quarter. It is slipped between bulb and socket and can be used with any incandescent bulb that screws into a standard socket. In addition to delaying burnout, the Bulb-Miser also offers some reduction of electrical energy. But the economy of the device goes beyond energy use or bulb cost; to big users of bulbs, it makes possible substantially lower maintenance labor costs. One field test involving an apartment complex showed that it took two men 30 man hours monthly to replace light bulbs; after Bulb-Miser installation only nine man hours a month were needed. Bulb-Misers are used not only in private homes but also by hospitals, schools, hotels and motels, restaurants, banks and firms providing contract maintenance for large outdoor electric signs. The broadest use is in industrial facilities; the list of big companies which have purchased the Bulb-Miser reads like a Who's Who of American industry.
Big-Data Analytics for Electric Grid and Demand-Side Management
This report describes research to characterize the status of, and trends in, big-data analytics for the electricity grid. The research focused on 1) identifying power-grid big-data sources, types, and characteristics; and 2) characterizing big-data architecture, analytic methods, technology applications, and challenges. The first part of this report describes the main sources and characteristics of big data for the smart grid and comprehensively reviews big-data architecture, technologies, and applications in the power sector. The second part of this report presents case studies of big data applications in the power industry: (1) a smart-meter data and predictive analytics method for demand response (DR), (2) synchrophasor data analytics for the distribution grid, and (3) utility data for peak-demand management. For the predictive analytics case study, smart-meter-data-driven and physical models were developed to predict the potential kilowatt (kW) capacity reduction from DR. The DR estimation framework that was developed works for both small and large-scale customers. The synchrophasor case study demonstrates use of an algorithm applied to time-series data to detect events that appear as significant changes, known as “edges,” in voltage magnitude measurements. The synchrophasor case study also introduces an approach for clustering sets of events to reveal unique features that distinguish them (e.g., distinguishing capacitor bank switching from transformer tap changes). The peak-demand management case study describes the use of the data analytics to enable DR programs to limit forecasted peak demand, resulting in cost savings to the utility. The findings from the research described in this report support identification of opportunities and technologies for big-data and analytics applications for demand-side management in the power sector as well as other approaches to modernizing the electricity grid.
Discretely Charged Dark Matter in Inflation Models Based on Holographic Space-Time
The holographic space-time (HST) model of inflation has a potential explanation for dark matter as tiny primordial black holes. Motivated by a recent paper of Barrau, we propose a version of this model where some of the inflationary black holes (IBHs), whose decay gives rise to the Hot Big Bang, carry the smallest value of a discrete symmetry charge. The fraction f of IBHs carrying this charge is difficult to estimate from first principles, but we determine it by requiring that the crossover between radiation and matter domination occurs at the correct temperature T eq ~ 1eV=10 –28 M P . The fraction is small, f ~ 2×10 –9 , so we believe this gives an extremely plausible model of dark matter.
Sensitivity of Next-Generation CMB Surveys to Neutrinos and Other Light Relics
Neutrinos and other light relics leave characteristic imprints in the cosmic microwave background anisotropies, making their observation a sensitive probe of the particle content and thermal history of the early universe. The energy density in these relativistic species is parameterized by their effective number $N_\mathrm{eff}$. Measuring this parameter at the percent level, which is a long-standing science goal of CMB-S4 and other experiments, would test a wide range of well-motivated physics within and beyond the Standard Model of particle physics. In this paper, we present Fisher-matrix forecasts of the projected sensitivity to $N_\mathrm{eff}$ of several CMB-S4 survey configurations considered during its extensive design phase. The conceptual design reaches $σ(N_\mathrm{eff}) < 0.03$ over its seven-year observing period, while the revised configuration achieves the same precision over a longer timescale. We complement these results with a cosmic-variance-limited survey over the same multipole range to quantify the room for improvement accessible with additional instrumental, observational, and theoretical efforts. Finally, we discuss the broad implications of precise $N_\mathrm{eff}$ measurements for the radiation sector, big bang nucleosynthesis, light thermal relics, and other early-universe physics. The forecasts presented in this work are performed with the publicly released DRAFT (Dark Radiation Anisotropy Flowdown Team) tool. It provides an end-to-end pipeline from simulated foreground maps and component separation to delensing and projected sensitivities for any cosmological parameter, and it can be directly applied to other cosmic microwave background survey designs.
Facility Cybersecurity Framework Best Practices
Federal facilities are increasingly adopting automation and connecting to the Internet creating an energy-internet-of-things environment that converges operational technology (OT) and information technology (IT). Today's buildings increasingly weave together networked sensors and cyber and physical systems that enable data to be collected, aggregated, exchanged, stored and monetized in new ways. Building technological advances have created new energy technology, services, markets and value creation opportunities (e.g. transactive energy, two-way grid communications, machine learning, and increased use of renewable and distributed energy resources). But as larger data sets are being exchanged at faster speeds between an increasing number of OT systems, it becomes more difficult to protect the security of the data lifecycle and the physical equipment it interacts with. These challenges are especially difficult to overcome because the economic and environmental gain (interoperability, big data, social networks and ubiquitous information sharing) are driving these prominent trends in the digital age. Often cybersecurity is an afterthought. The U.S. Department of Energy’s (DOE) Federal Energy Management Program (FEMP) funded the Pacific Northwest National Laboratory (PNNL) to develop various cybersecurity tools, trainings, and reports to aid federal facility managers – and other building owners and operators – in better applying frameworks and lessons learned from the National Institute of Standards and Technology (NIST) Cybersecurity Framework (CSF), risk management framework (RMF), DOE’s cybersecurity capability maturity model (C2M2), and a wide variety of industry best practices and guidance documents (i.e., NIST 800 series, Department of Defense United Facilities Criteria). This set of tools, collectively known as the FEMP Facility-Related Control System Cyber Toolkit (FRCS Cyber Toolkit)2, is focused on cybersecurity concerns from facility-related control systems and other operational technology (OT), such as industrial control systems (ICS). The FRCS Cyber Toolkit can be applied across six of the sixteen critical infrastructure sectors designated by the Department of Homeland Security, including government facilities, healthcare and public health, commercial facilities (e.g., public assembly, offices, lodging), financial services (e.g., banking and insurance), emergency services (e.g., fire and police stations), and information technology. With increasingly converged IT and OT systems, it is crucial to address OT cybersecurity considerations and assess how the seam of these two systems could impact the overall cybersecurity posture of a facility. The objective of this report is to provide an overview of the best possible method to use FRCS Cyber Toolkit (section 2.0) and distilled cybersecurity best practices for the federal facilities to address growing non-linear cyber threats (section 3.0). Recommendations in this document are aggregated from several NIST and other documents (see Appendix A for additional details).
Paleo-Environment and C-14 Dating: The Key to the Depositional Age of the Tha Chang and Related Sand Pits, Northeastern Thailand
Tha Chang sand pits, Nakhon Ratchasima Province and many other sand pits in the area adjacent to the Mun River are characterized by their fluviatile environment in association with mass wasting deposits, along the paleo-river channel and the flood plain of the Mun River. Sediments of these deposits are characterized by clasts of various rock types especially the resistant ones with frequent big tree trunks, logs and wood fragments in different sizes and various stages of transformation from moldering stage to lignification and petrification. Widespread pyritization of the lower horizon suggests strongly reducing environment during burial. The Tha Chang deposits have been received much attention from geoscientists especially paleontologist communities, as they contain fragments of some distinct vertebrate species such as Stegadon sp., hominoid primate, rhinoceros Aceratherium and others. Based on the associated mammal fauna and hominoid fossils, the late Miocene ( 9 - 6 Ma) was given for the time of deposition of this sand and gravel unit. Some other reports believed that sediments and materials of these sand and gravel quarries (pits) were deposited by high-energy flood pulses contemporaneous with the tektites forming event during mid-Pleistocene at c. 0.8 Ma. Interpretation from Palynostratigraphical study suggested that the lower horizon of Tha Chang sand pit was deposited during Pliocene/Pleistocene period and the upper horizons are Pleistoncene/Holocene. It is crystal clear that all the fluviatile sediments including tektites and almost all fossil fragments being deposited in these sand pits were, likely a multiple times reworked materials. Only some old bamboo trees, some old crowling trees and fossils grasses observed on the old river bank are considered in situ. C-14 dating of 5 old wood specimens from Tha Chang Sand Pits, 15 old wood specimens from Chumpuang Sand Pits and one sample of old pottery from a Chumpuang Sand Pit were carried out in the NSF- Arizona AMS Laboratory. Although, there is no sharp boundary between the unconsolidated sedimentary horizons in the pits, C-14 ages obtained from the Tha Chang vary from 34,340 BP at the middle horizon (approx 10 m below ground zero) to >49,900 BP at the lower horizon with unknown basal formation (highly pyritized zone approx 20 - 25 m below ground zero). The ages for the Chumpuang vary from 41,700 BP, >45,900 BP and >49,900 BP from the upper most to the lower most of a broad horizon (approx 8 m to approx 12 m below ground zero). The C-14 age of the pottery collected from layer approximately 5 m below ground zero is 2,514 BP. The nature of fluviatile together with occasional mass wasting characteristics of all sand pits studies suggest the relatively faster depositional rate of the lower horizon which involved more flooding and mass wasting deposits than those of the upper horizons. The apparent of some mixing of the wood ages may indicate reworking and lag deposits nature of the area. The depositional rate of the upper most sand and soil horizon (5 m thick) is approximately 1 m per 500 years which mean both erosion and deposition had played a significant role during that time period. In term of the true age of the formation, we argue that since most of the materials deposited are reworked materials, all ages obtained from fossil fragments could not be the age of sand and gravel formation. Furthermore, the maximum age of all the tektite bearing horizons cannot be older than 0.8 Ma. The oldest C-14 age of 49,900 BP is interpreted as the minimum age of the Tha Chang and related sand pits formation when geomorphology of the area was a lot more hilly and much higher gradient than that of the present day.
Searching for pulsars using image pattern recognition
In the modern era of big data, many fields of astronomy are generating huge volumes of data, the analysis of which can sometimes be the limiting factor in research. Fortunately, computer scientists have developed powerful data-mining techniques that can be applied to various fields. In this paper, we present a novel artificial intelligence (AI) program that identifies pulsars from recent surveys by using image pattern recognition with deep neural nets—the PICS (Pulsar Image-based Classification System) AI. The AI mimics human experts and distinguishes pulsars from noise and interference by looking for patterns from candidate plots. Different from other pulsar selection programs that search for expected patterns, the PICS AI is taught the salient features of different pulsars from a set of human-labeled candidates through machine learning. The training candidates are collected from the Pulsar Arecibo L-band Feed Array (PALFA) survey. The information from each pulsar candidate is synthesized in four diagnostic plots, which consist of image data with up to thousands of pixels. The AI takes these data from each candidate as its input and uses thousands of such candidates to train its ∼9000 neurons. The deep neural networks in this AI system grant it superior ability to recognize various types of pulsars as well as their harmonic signals. The trained AI's performance has been validated with a large set of candidates from a different pulsar survey, the Green Bank North Celestial Cap survey. In this completely independent test, the PICS ranked 264 out of 277 pulsar-related candidates, including all 56 previously known pulsars and 208 of their harmonics, in the top 961 (1%) of 90,008 test candidates, missing only 13 harmonics. The first non-pulsar candidate appears at rank 187, following 45 pulsars and 141 harmonics. In other words, 100% of the pulsars were ranked in the top 1% of all candidates, while 80% were ranked higher than any noise or interference. The performance of this system can be improved over time as more training data are accumulated. This AI system has been integrated into the PALFA survey pipeline and has discovered six new pulsars to date.
Dark Energy Survey: Implications for cosmological expansion models from the final DES baryon acoustic oscillation and supernova data
The Dark Energy Survey (DES) recently released the final results of its two principal probes of the expansion history: Type Ia supernovae (SNe) and baryonic acoustic oscillations (BAO). In this paper, we explore the cosmological implications of these data in combination with external cosmic microwave background (CMB), big bang nucleosynthesis (BBN), and age-of-the-Universe information. The BAO measurement, which is ∼ 2 σ away from Planck ’s Λ CDM predictions, pushes for low values of Ω m compared to Planck, in contrast to SN which prefers a higher value than Planck. We identify several tensions among datasets in the Λ CDM model that cannot be resolved by including either curvature ( k Λ CDM ) or a constant dark energy equation of state ( w CDM ). By combining BAO + SN + CMB despite these mild tensions, we obtain Ω k = - 5.5 - 4.2 + 4.6 × 10 - 3 in k Λ CDM , and w = - 0.94 8 - 0.027 + 0.028 in w CDM . In w CDM , BAO and SN push again in different directions of parameter space, favoring, respectively, w < - 1 and w > - 1 . If we open the parameter space to w 0 w a CDM [where the equation of state of dark energy varies as w ( a ) = w 0 + ( 1 - a ) w a ], all the datasets are mutually more compatible, and we find concordance in the [ w 0 > - 1 , w a < 0 ] quadrant, with BAO pushing for w a < 0 and SN for [ w 0 > - 1 , w a < 0 ] . For DES BAO and SN in combination with Planck -CMB, we find a 3.2 σ deviation from Λ CDM , with w 0 = - 0.67 3 - 0.097 + 0.098 , w a = - 1.3 7 - 0.50 + 0.51 , a Hubble constant of H 0 = 67.8 1 - 0.86 + 0.96 km s - 1 Mpc - 1 , and an abundance of matter of Ω m = 0.310 9 - 0.0099 + 0.0086 . For the combination of all the background cosmological probes considered (including CMB’s angular acoustic scale θ ⋆ ), we still find a deviation of 2.8 σ from Λ CDM in the w 0 - w a plane. Assuming a minimal neutrino mass, this work provides tentative evidence for non- Λ CDM physics, which is consistent with recent claims in support of evolving dark energy, or a source of unknown systematics.