AGRICULTURAL CONSERVATION POLICY AT A CROSSROADS

U.S. agricultural conservation policy has focused on a range of potential policy instruments centered on voluntary approaches tied into Depression-era commodity programs. Entering the twenty-first century, conservation policy is at a crossroads between more coercive regulatory policies, more costly voluntary programs, and more facilitative market-oriented policies. What are the pitfalls, advantages, disadvantages, and tradeoffs along these paths?Agricultural and Food Policy,

Catalytic wet peroxide oxidation of formic acid in wastewater with naturally-occurring iron ore

The catalytic wet oxidation of formic acid, using hydrogen peroxide as the oxidizing agent over naturally-occurring iron ore, was explored. Firstly, the decomposition of hydrogen peroxide to its hydroxyl radicals (HO• and HOO•) over naturally-occurring iron ore was investigated. The reaction was monitored by ATR FTIR by following the disappearance of the O-H peak of H2O2 at 2 860 cm-1. Decomposition occurred according to the Fenton mechanism and resulted in observed first-order rate constants one order of magnitude faster than that without the catalyst. Turnover frequencies (TOF) of 1.97–8.85 x 10-9 s-1 were obtained for the decomposition of H2O2. The wet oxidation of formic acid using hydrogen peroxide as the oxidizing agent over naturally-occurring iron ore reaction was also monitored by ATR FTIR, following the disappearance of the carbonyl stretching frequency of formic acid at 1 727 cm-1. Experiments were performed at different hydrogen peroxide (2, 4, 6 and 8M) and formic acid (1.26, 2.52, 6.3 and 12.6 M) concentrations as well as with varying amounts of naturally-occurring iron ore catalyst, at pH = 2. Elevated hydrogen peroxide and formic acid concentrations led to increased observed first-order kinetics, as high as kobs = 21.75 x 10-4 min-1 with a TOF = 1.73 x 10-8 – 1.12 x 10-6 s-1.Keywords: iron ore, catalytic wet oxidation, formic acid, Fenton, hydrogen peroxid

Controlling the magnetic state of the proximate quantum spin liquid α-RuCl₃ with an optical cavity

Harnessing the enhanced light-matter coupling and quantum vacuum fluctuations resulting from mode volume compression in optical cavities is a promising route towards functionalizing quantum materials and realizing exotic states of matter. Here, we extend cavity quantum electrodynamical materials engineering to correlated magnetic systems, by demonstrating that a Fabry-Pérot cavity can be used to control the magnetic state of the proximate quantum spin liquid α-RuCl3. Depending on specific cavity properties such as the mode frequency, photon occupation, and strength of the light-matter coupling, any of the magnetic phases supported by the extended Kitaev model can be stabilized. In particular, in the THz regime, we show that the cavity vacuum fluctuations alone are sufficient to bring α-RuCl3 from a zigzag antiferromagnetic to a ferromagnetic state. By external pumping of the cavity in the few photon limit, it is further possible to push the system into the antiferromagnetic Kitaev quantum spin liquid state

Effects of biogenic amines and formamidine insecticides on the central production of flight by Manduca sexta

Call number: LD2668 .T4 1985 C52Master of Scienc

ac Losses in a Finite Z Stack Using an Anisotropic Homogeneous-Medium Approximation

A finite stack of thin superconducting tapes, all carrying a fixed current I, can be approximated by an anisotropic superconducting bar with critical current density Jc=Ic/2aD, where Ic is the critical current of each tape, 2a is the tape width, and D is the tape-to-tape periodicity. The current density J must obey the constraint \int J dx = I/D, where the tapes lie parallel to the x axis and are stacked along the z axis. We suppose that Jc is independent of field (Bean approximation) and look for a solution to the critical state for arbitrary height 2b of the stack. For c<|x|<a we have J=Jc, and for |x|<c the critical state requires that Bz=0. We show that this implies \partial J/\partial x=0 in the central region. Setting c as a constant (independent of z) results in field profiles remarkably close to the desired one (Bz=0 for |x|<c) as long as the aspect ratio b/a is not too small. We evaluate various criteria for choosing c, and we show that the calculated hysteretic losses depend only weakly on how c is chosen. We argue that for small D/a the anisotropic homogeneous-medium approximation gives a reasonably accurate estimate of the ac losses in a finite Z stack. The results for a Z stack can be used to calculate the transport losses in a pancake coil wound with superconducting tape.Comment: 21 pages, 17 figures, accepted by Supercond. Sci. Techno

Native roadside perennial grasses persist a decade after planting in the Sacramento Valley

Restoring native grassland along roadsides can provide a relatively low-maintenance, drought-tolerant and stable perennial vegetative cover with reduced weed growth, as opposed to the high-maintenance invasive annual cover (requiring intensive mowing and herbicide treatments) that dominates most Sacramento Valley roadsides. A survey of long-established roadside native-grass plantings in Yolo County showed that once established and protected from disturbance, such plantings can persist with minimal maintenance for more than a decade, retaining a high proportion of native species. The survey also showed that each species of native perennial grass displays a microhabitat preference for particular roadside topographic positions, and that native perennial grass cover is negatively affected by disturbance

Causal Shapley Values: Exploiting Causal Knowledge to Explain Individual Predictions of Complex Models

Shapley values underlie one of the most popular model-agnostic methods within explainable artificial intelligence. These values are designed to attribute the difference between a model's prediction and an average baseline to the different features used as input to the model. Being based on solid game-theoretic principles, Shapley values uniquely satisfy several desirable properties, which is why they are increasingly used to explain the predictions of possibly complex and highly non-linear machine learning models. Shapley values are well calibrated to a user's intuition when features are independent, but may lead to undesirable, counterintuitive explanations when the independence assumption is violated. In this paper, we propose a novel framework for computing Shapley values that generalizes recent work that aims to circumvent the independence assumption. By employing Pearl's do-calculus, we show how these 'causal' Shapley values can be derived for general causal graphs without sacrificing any of their desirable properties. Moreover, causal Shapley values enable us to separate the contribution of direct and indirect effects. We provide a practical implementation for computing causal Shapley values based on causal chain graphs when only partial information is available and illustrate their utility on a real-world example.Comment: Accepted at 34th Conference on Neural Information Processing Systems (NeurIPS 2020