Market Integration: Case Studies of Structural Change

The grain/oilseed industry is undergoing considerable structural change through mergers and new value-added businesses, which raises price-related questions. We analyze the level of price integration prior to and following a merger between two grain firms and the start-up of a producer-owned ethanol facility. This research utilizes error correction vector autoregression analysis to compute market integration structural change effects. We find evidence that market integration initially increases with the merger, but deteriorates with time following the merger. We find no significant localized change in the level of price integration for the case of a new value-added business.consolidation, structural change, price integration, Agribusiness, Industrial Organization,

Tracking the distance to criticality in systems with unknown noise

Many real-world systems undergo abrupt changes in dynamics as they move across critical points, often with dramatic and irreversible consequences. Much of the existing theory on identifying the time-series signatures of nearby critical points -- such as increased signal variance and slower timescales -- is derived from analytically tractable systems, typically considering the case of fixed, low-amplitude noise. However, real-world systems are often corrupted by unknown levels of noise which can obscure these temporal signatures. Here we aimed to develop noise-robust indicators of the distance to criticality (DTC) for systems affected by dynamical noise in two cases: when the noise amplitude is either fixed, or is unknown and variable across recordings. We present a highly comparative approach to tackling this problem that compares the ability of over 7000 candidate time-series features to track the DTC in the vicinity of a supercritical Hopf bifurcation. Our method recapitulates existing theory in the fixed-noise case, highlighting conventional time-series features that accurately track the DTC. But in the variable-noise setting, where these conventional indicators perform poorly, we highlight new types of high-performing time-series features and show that their success is underpinned by an ability to capture the shape of the invariant density (which depends on both the DTC and the noise amplitude) relative to the spread of fast fluctuations (which depends on the noise amplitude). We introduce a new high-performing time-series statistic, termed the Rescaled Auto-Density (RAD), that distils these two algorithmic components. Our results demonstrate that large-scale algorithmic comparison can yield theoretical insights and motivate new algorithms for solving important practical problems.Comment: The main paper comprises 18 pages, with 5 figures (.pdf). The supplemental material comprises a single 4-page document with 1 figure (.pdf), as well as 3 spreadsheet files (.xls

Spacings of Quarkonium Levels with the Same Principal Quantum Number

The spacings between bound-state levels of the Schr\"odinger equation with the same principal quantum number $N$ but orbital angular momenta $\ell$ differing by unity are found to be nearly equal for a wide range of power potentials $V = \lambda r^\nu$, with $E_{N \ell} \approx F(\nu, N) - G(\nu,N) \ell$. Semiclassical approximations are in accord with this behavior. The result is applied to estimates of masses for quarkonium levels which have not yet been observed, including the 2P $c \bar c$ states and the 1D $b \bar b$ states.Comment: 20 pages, latex, 3 uuencoded figures submitted separately (process using psfig.sty

Fine structure splittings of excited P and D states in charmonium

It is shown that the fine structure splittings of the $2 ^3P_J$ and $3 ^3P_J$ excited states in charmonium are as large as those of the $1^3P_J$ state if the same $\alpha_s(\mu)\approx 0.36$ is used. The predicted mass $M(2 ^3P_0)=3.84$ GeV appears to be 120 MeV lower that the center of gravity of the $2 ^3P_J$ multiplet and lies below the $D\bar D^*$ threshold. Our value of $M(2 ^3P_0)$ is approximately 80 MeV lower than that from the paper by Godfrey and Isgur while the differences in the other masses are \la 20 MeV. Relativistic kinematics plays an important role in our analysis.Comment: 12 page

Climate and pest interactions pose a cross-landscape management challenge to soil and water conservation

Climate change and biological invasions by plant pests (weeds), agriculture and forest insect pests (insects), and microbial pests (plant pathogens) are complex interactive components of global environmental change. The influence of pest distribution and prevalence across landscapes are challenging the conservation and sustainability of natural resources, agricultural production, native biological diversity, and the valuable ecosystem services they provide (Huenneke 1997; Vitousek 1997; Juroszek and von Tiedemann 2013; Ziska and Dukes 2014). Since 2000, numerous scientific studies indicate accelerating climate change is posing substantial risks to natural and managed systems in North America (IPPC 2022). Intensified droughts, largescale wildfires, and increased demands for limited surface and groundwater water supplies in arid regions are threatening the sustainability of irrigated agriculture and contributing to economic losses (Stewart et al. 2020), while extreme rainfall events are contributing to severe riverine and urban flooding across the United States. Climate change affects crops, rangelands, forests, and natural areas directly through the immediate effects of temperature, precipitation, and atmospheric carbon dioxide (CO2) levels and thereby impacts production and management systems. These effects are amplified by climatedriven increases in weed, insect, and plant pathogen problems that further complicate related factors such as water, nutrient, and pest management (Walthall et al. 2013). Changing climates also alter physiological, ecological, and evolutionary processes that can support increased establishment, invasiveness, local spread, and geographic range changes of weeds, insects, and plant pathogens (Chidawanyika et al. 2019; Gallego-Tevár et al. 2019; Ziska et al. 2019) that have cascading effects on soil and water quality, and human livelihoods. Joshua W. Campbell is a research ecologist studying basic insect and pollinator behavior in managed and wild ecosystems at the USDA Agricultural Research Service (ARS) Pest Management Research Unit in Sidney, Montana. Michael R. Fulcher is a research plant pathologist conducting research to identify pathogenic biocontrol agents at the USDA ARS Foreign Disease-Weed Science Research Unit in Fort Detrick, Maryland. Brenda J. Grewell is a research plant ecologist focusing on understanding the biogeography of invasive plant species and the ecology of invaded systems at the USDA ARS Invasive Species and Pollinator Health Research Unit in Davis, California. Stephen L. Young is a national program leader in weeds and invasive pests at the USDA ARS Office of National Programs in Beltsville, Maryland. Received October 25, 2022. Thus, a need exists for cross-habitat and landscape/watershed-scale perspectives to improve understanding of mechanisms underlying pest fitness and impacts within and across integrated systems

The charmonium and bottomonium mass spectroscopy with a simple approximaton of the kinetic term

In this paper we propose a particular description of meson spectroscopy, with emphasis in heavy bound states like charmonia and bottomonia, after working on the main aspects of the construction of an effective potential model. We use the prerogatives from ``soft QCD'' to determine the effective potential terms, establishing the asymptotic Coulomb term from one gluon exchange approximation. At the same time, a linear confinement term is introduced in agreement with QCD and phenomenological prescription. The main aspect of this work is the simplification in the calculation, consequence of a precise and simplified description of the kinetic term of the Hamiltonian. With this proposition we perform the calculations of mass spectroscopy for charmonium and bottomonium mesons and we discuss the real physical possibilities of developing a generalized potential model, its possible advantages relative to experimental parameterization and complexity in numerical calculations