Numerical detection of the Gardner transition in a mean-field glass former.

Recent theoretical advances predict the existence, deep into the glass phase, of a novel phase transition, the so-called Gardner transition. This transition is associated with the emergence of a complex free energy landscape composed of many marginally stable sub-basins within a glass metabasin. In this study, we explore several methods to detect numerically the Gardner transition in a simple structural glass former, the infinite-range Mari-Kurchan model. The transition point is robustly located from three independent approaches: (i) the divergence of the characteristic relaxation time, (ii) the divergence of the caging susceptibility, and (iii) the abnormal tail in the probability distribution function of cage order parameters. We show that the numerical results are fully consistent with the theoretical expectation. The methods we propose may also be generalized to more realistic numerical models as well as to experimental systems.

Universal Non-Debye Scaling in the Density of States of Amorphous Solids.

At the jamming transition, amorphous packings are known to display anomalous vibrational modes with a density of states (DOS) that remains constant at low frequency. The scaling of the DOS at higher packing fractions remains, however, unclear. One might expect to find a simple Debye scaling, but recent results from effective medium theory and the exact solution of mean-field models both predict an anomalous, non-Debye scaling. Being mean-field in nature, however, these solutions are only strictly valid in the limit of infinite spatial dimension, and it is unclear what value they have for finite-dimensional systems. Here, we study packings of soft spheres in dimensions 3 through 7 and find, away from jamming, a universal non-Debye scaling of the DOS that is consistent with the mean-field predictions. We also consider how the soft mode participation ratio evolves as dimension increases.

Decoding Spontaneous Emotional States in the Human Brain.

Pattern classification of human brain activity provides unique insight into the neural underpinnings of diverse mental states. These multivariate tools have recently been used within the field of affective neuroscience to classify distributed patterns of brain activation evoked during emotion induction procedures. Here we assess whether neural models developed to discriminate among distinct emotion categories exhibit predictive validity in the absence of exteroceptive emotional stimulation. In two experiments, we show that spontaneous fluctuations in human resting-state brain activity can be decoded into categories of experience delineating unique emotional states that exhibit spatiotemporal coherence, covary with individual differences in mood and personality traits, and predict on-line, self-reported feelings. These findings validate objective, brain-based models of emotion and show how emotional states dynamically emerge from the activity of separable neural systems.

A field agronomic evaluation of Typha grass in Tomas dam Kano State Nigeria

The study was carried out by measuring plant height, length of leaves, width of the leaves, length of inflorescent, length of inflorescent tip were also measured with a measuring tape. Number of tillers per plants was counted. Soil auger was used to take soil samples randomly from ten different locations in Tomas Dam Kano states Nigeria. At the depths of 0-5cm, 5cm 13 10cm, 10cm 13 15cm. The soil samples were put into polyethylene bags and labelled according to their depth for mineral analyses. In the two season calcium, nitrogen and phosphorus constitute the highest concentration of the minerals at 0 155 cm depth. There is no significant differences in terms of mineral composition between wet season and dry season. (P<0.005).There is significance differences between plant Length of inflorescent and length of inflorescent tip when the two season are compared. KEYWORDS: Typha grass, field, agronomic evaluation,

COACHES, CLIMATES, “FIELD” GOALS, AND EFFICACY: A “DE-CONSTRUCTION” OF THE MASTERY-APPROACH TO COACHING AND EXAMINATION OF RELATIONSHIPS TO PSYCHOSOCIAL OUTCOMES IN A YOUTH FOOTBALL PLAYER DEVELOPMENT PROGRAM.

In support of the achievement goal theory (AGT), empirical research has demonstrated psychosocial benefits of the mastery-oriented learning climate. In this study, we examined the effects of perceived coaching behaviors on various indicators of psychosocial well-being (competitive anxiety, self-esteem, perceived competence, enjoyment, and future intentions for participation), as mediated by perceptions of the coach-initiated motivational climate, achievement goal orientations and perceptions of sport-specific skills efficacy. Using a pre-post test design, 1,464 boys, ages 10-15 (M = 12.84 years, SD = 1.44), who participated in a series of 12 football skills clinics were surveyed from various locations across the United States. Using structural equation modeling (SEM) path analysis and hierarchical regression analysis, the cumulative direct and indirect effects of the perceived coaching behaviors on the psychosocial variables at post-test were parsed out to determine what types of coaching behaviors are more conducive to the positive psychosocial development of youth athletes. The study demonstrated that how coaching behaviors are perceived impacts the athletes’ perceptions of the motivational climate and achievement goal orientations, as well as self-efficacy beliefs. These effects in turn affect the athletes’ self-esteem, general competence, sport-specific competence, competitive anxiety, enjoyment, and intentions to remain involved in the sport. The findings also clarify how young boys internalize and interpret coaches’ messages through modification of achievement goal orientations and sport-specific efficacy beliefs.

Lifetime and distribution of ozone and related pollutants in the eastern United States

Most major cities in the eastern United States have air quality deemed unhealthy by the EPA under a set of regulations known as the National Ambient Air Quality Standards (NAAQS). The worst air quality in Maryland is measured in Edgewood, MD, a small community located along the Chesapeake Bay and generally downwind of Baltimore during hot, summertime days. Direct measurements and numerical simulations were used to investigate how meteorology and chemistry conspire to create adverse levels of photochemical smog especially at this coastal location. Ozone (O3) and oxidized reactive nitrogen (NOy), a family of ozone precursors, were measured over the Chesapeake Bay during a ten day experiment in July 2011 to better understand the formation of ozone over the Bay and its impact on coastal communities such as Edgewood. Ozone over the Bay during the afternoon was 10% to 20% higher than the closest upwind ground sites. A combination of complex boundary layer dynamics, deposition rates, and unaccounted marine emissions play an integral role in the regional maximum of ozone over the Bay. The CAMx regional air quality model was assessed and enhanced through comparison with data from NASA’s 2011 DISCOVER-AQ field campaign. Comparisons show a model overestimate of NOy by +86.2% and a model underestimate of formaldehyde (HCHO) by –28.3%. I present a revised model framework that better captures these observations and the response of ozone to reductions of precursor emissions. Incremental controls on electricity generating stations will produce greater benefits for surface ozone while additional controls on mobile sources may yield less benefit because cars emit less pollution than expected. Model results also indicate that as ozone concentrations improve with decreasing anthropogenic emissions, the photochemical lifetime of tropospheric ozone increases. The lifetime of ozone lengthens because the two primary gas-phase sinks for odd oxygen (Ox ≈ NO2 + O3) – attack by hydroperoxyl radicals (HO2) on ozone and formation of nitrate – weaken with decreasing pollutant emissions. This unintended consequence of air quality regulation causes pollutants to persist longer in the atmosphere, and indicates that pollutant transport between states and countries will likely play a greater role in the future.

Long distance coupling of a quantum mechanical oscillator to the internal states of an atomic ensemble

We propose and investigate a hybrid optomechanical system consisting of a micro-mechanical oscillator coupled to the internal states of a distant ensemble of atoms. The interaction between the systems is mediated by a light field which allows the coupling of the two systems in a modular way over long distances. Coupling to internal degrees of freedom of atoms opens up the possibility to employ high-frequency mechanical resonators in the MHz to GHz regime, such as optomechanical crystal structures, and to benefit from the rich toolbox of quantum control over internal atomic states. Previous schemes involving atomic motional states are rather limited in both of these aspects. We derive a full quantum model for the effective coupling including the main sources of decoherence. As an application we show that sympathetic ground-state cooling and strong coupling between the two systems is possible.

Crop Insurance For Maryland Field Crops And Livestock

Multi-peril crop insurance is a valuable risk management tool which allows you to insure against losses on your farm due to adverse weather conditions, price fluctuations, and unavoidable pests and diseases. It shifts unavoidable production risks to an insurance company for the payment of a fixed amount of premium per acre. This publication assists readers in understanding the basics of the federal crop insurance program.

Whole-cell-analysis of live cardiomyocytes using wide-field interferometric phase microscopy.

We apply wide-field interferometric microscopy techniques to acquire quantitative phase profiles of ventricular cardiomyocytes in vitro during their rapid contraction with high temporal and spatial resolution. The whole-cell phase profiles are analyzed to yield valuable quantitative parameters characterizing the cell dynamics, without the need to decouple thickness from refractive index differences. Our experimental results verify that these new parameters can be used with wide field interferometric microscopy to discriminate the modulation of cardiomyocyte contraction dynamics due to temperature variation. To demonstrate the necessity of the proposed numerical analysis for cardiomyocytes, we present confocal dual-fluorescence-channel microscopy results which show that the rapid motion of the cell organelles during contraction preclude assuming a homogenous refractive index over the entire cell contents, or using multiple-exposure or scanning microscopy.

APPLICATION OF AN IMPUTATION METHOD FOR GEOSPATIAL INVENTORY OF FOREST STRUCTURAL ATTRIBUTES ACROSS MULTIPLE SPATIAL SCALES IN THE LAKE STATES, U.S.A.

Credible spatial information characterizing the structure and site quality of forests is critical to sustainable forest management and planning, especially given the increasing demands and threats to forest products and services. Forest managers and planners are required to evaluate forest conditions over a broad range of scales, contingent on operational or reporting requirements. Traditionally, forest inventory estimates are generated via a design-based approach that involves generalizing sample plot measurements to characterize an unknown population across a larger area of interest. However, field plot measurements are costly and as a consequence spatial coverage is limited. Remote sensing technologies have shown remarkable success in augmenting limited sample plot data to generate stand- and landscape-level spatial predictions of forest inventory attributes. Further enhancement of forest inventory approaches that couple field measurements with cutting edge remotely sensed and geospatial datasets are essential to sustainable forest management. We evaluated a novel Random Forest based k Nearest Neighbors (RF-kNN) imputation approach to couple remote sensing and geospatial data with field inventory collected by different sampling methods to generate forest inventory information across large spatial extents. The forest inventory data collected by the FIA program of US Forest Service was integrated with optical remote sensing and other geospatial datasets to produce biomass distribution maps for a part of the Lake States and species-specific site index maps for the entire Lake State. Targeting small-area application of the state-of-art remote sensing, LiDAR (light detection and ranging) data was integrated with the field data collected by an inexpensive method, called variable plot sampling, in the Ford Forest of Michigan Tech to derive standing volume map in a cost-effective way. The outputs of the RF-kNN imputation were compared with independent validation datasets and extant map products based on different sampling and modeling strategies. The RF-kNN modeling approach was found to be very effective, especially for large-area estimation, and produced results statistically equivalent to the field observations or the estimates derived from secondary data sources. The models are useful to resource managers for operational and strategic purposes.

Sustainable Energy Production in the United States: Life Cycle Assessment of Biofuels and Bioenergy

The United States of America is making great efforts to transform the renewable and abundant biomass resources into cost-competitive, high-performance biofuels, bioproducts, and biopower. This is the key to increase domestic production of transportation fuels and renewable energy, and reduce greenhouse gas and other pollutant emissions. This dissertation focuses specifically on assessing the life cycle environmental impacts of biofuels and bioenergy produced from renewable feedstocks, such as lignocellulosic biomass, renewable oils and fats. The first part of the dissertation presents the life cycle greenhouse gas (GHG) emissions and energy demands of renewable diesel (RD) and hydroprocessed jet fuels (HRJ). The feedstocks include soybean, camelina, field pennycress, jatropha, algae, tallow and etc. Results show that RD and HRJ produced from these feedstocks reduce GHG emissions by over 50% compared to comparably performing petroleum fuels. Fossil energy requirements are also significantly reduced. The second part of this dissertation discusses the life cycle GHG emissions, energy demands and other environmental aspects of pyrolysis oil as well as pyrolysis oil derived biofuels and bioenergy. The feedstocks include waste materials such as sawmill residues, logging residues, sugarcane bagasse and corn stover, and short rotation forestry feedstocks such as hybrid poplar and willow. These LCA results show that as much as 98% GHG emission savings is possible relative to a petroleum heavy fuel oil. Life cycle GHG savings of 77 to 99% were estimated for power generation from pyrolysis oil combustion relative to fossil fuels combustion for electricity, depending on the biomass feedstock and combustion technologies used. Transportation fuels hydroprocessed from pyrolysis oil show over 60% of GHG reductions compared to petroleum gasoline and diesel. The energy required to produce pyrolysis oil and pyrolysis oil derived biofuels and bioelectricity are mainly from renewable biomass, as opposed to fossil energy. Other environmental benefits include human health, ecosystem quality and fossil resources. The third part of the dissertation addresses the direct land use change (dLUC) impact of forest based biofuels and bioenergy. An intensive harvest of aspen in Michigan is investigated to understand the GHG mitigation with biofuels and bioenergy production. The study shows that the intensive harvest of aspen in MI compared to business as usual (BAU) harvesting can produce 18.5 billion gallons of ethanol to blend with gasoline for the transport sector over the next 250 years, or 32.2 billion gallons of bio-oil by the fast pyrolysis process, which can be combusted to generate electricity or upgraded to gasoline and diesel. Intensive harvesting of these forests can result in carbon loss initially in the aspen forest, but eventually accumulates more carbon in the ecosystem, which translates to a CO2 credit from the dLUC impact. Time required for the forest-based biofuels to reach carbon neutrality is approximately 60 years. The last part of the dissertation describes the use of depolymerization model as a tool to understand the kinetic behavior of hemicellulose hydrolysis under dilute acid conditions. Experiments are carried out to measure the concentrations of xylose and xylooligomers during dilute acid hydrolysis of aspen. The experiment data are used to fine tune the parameters of the depolymerization model. The results show that the depolymerization model successfully predicts the xylose monomer profile in the reaction, however, it overestimates the concentrations of xylooligomers.

Potential mitigation of midwest grass-finished beef production emissions with soil carbon sequestration in the United States of America

Beef production can be environmentally detrimental due in large part to associated enteric methane (CH4) production, which contributes to climate change. However, beef production in well-managed grazing systems can aid in soil carbon sequestration (SCS), which is often ignored when assessing beef production impacts on climate change. To estimate the carbon footprint and climate change mitigation potential of upper Midwest grass-finished beef production systems, we conducted a partial life cycle assessment (LCA) comparing two grazing management strategies: 1) a non-irrigated, lightly-stocked (1.0 AU/ha), high-density (100,000 kg LW/ha) system (MOB) and 2) an irrigated, heavily-stocked (2.5 AU/ha), low-density (30,000 kg LW/ha) system (IRG). In each system, April-born steers were weaned in November, winter-backgrounded for 6 months and grazed until their endpoint the following November, with average slaughter age of 19 months and a 295 kg hot carcass weight. As the basis for the LCA, we used two years of data from Lake City Research Center, Lake City, MI. We included greenhouse gas (GHG) emissions associated with enteric CH4, soil N2O and CH4 fluxes, alfalfa and mineral supplementation, and farm energy use. We also generated results from the LCA using the enteric emissions equations of the Intergovernmental Panel on Climate Change (IPCC). We evaluated a range of potential rates of soil carbon (C) loss or gain of up to 3 Mg C ha-1 yr-1. Enteric CH4 had the largest impact on total emissions, but this varied by grazing system. Enteric CH4 composed 62 and 66% of emissions for IRG and MOB, respectively, on a land basis. Both MOB and IRG were net GHG sources when SCS was not considered. Our partial LCA indicated that when SCS potential was included, each grazing strategy could be an overall sink. Sensitivity analyses indicated that soil in the MOB and IRG systems would need to sequester 1 and 2 Mg C ha-1 yr-1 for a net zero GHG footprint, respectively. IPCC model estimates for enteric CH4 were similar to field estimates for the MOB system, but were higher for the IRG system, suggesting that 0.62 Mg C ha-1 yr-1 greater SCS would be needed to offset the animal emissions in this case.

Iberian and Latin American Music Scholarship on the Ascent: Reflections from the United States

In the early twentieth century, musicology was established as an academic discipline in the United States. Nonetheless, with the exception of Iberian medieval and Renaissance repertories, U.S. scholars largely overlooked the music of the Spanish- and Portuguese- speaking world. Why should this have been the case, especially in light of Spain’s strong historical presence in the United States? This autobiographical essay examines this question by tracing the career of an individual musicologist, the Hispanist musicologist Carol A. Hess. Evaluated here are disciplinary shifts in U.S. musicology —methodological, philosophical, and ideological— over the past thirty years. These transformations have combined to make this repertory a viable field of study today. Musicologists in the United States can now make their careers by specializing in Iberian and Latin American music, as well as the music of the Hispanic diaspora. They research topics ranging from the avant-garde composer Llorenç Barber to the rapper Nach Scratch or the popular bandleader Xavier Cugat and his U.S. audiences of the 1940s, while others also pursue the time-tested areas of medieval and Renaissance music. Iberian and Latin American music is regularly offered in postsecondary institutions while instructors now have a variety of textbooks and other pedagogical resources from which to choose. All add up to a disciplinary freedom that would have been unthinkable only a few decades ago.