Agency Rules with the Force of Law: The Original Convention

The Supreme Court recently held in United States v. Mead Corp. that agency interpretations should receive Chevron deference only when Congress has delegated power to the agency to make rules with the force of law and the agency has rendered its interpretation in the exercise of that power. The first step of this inquiry is difficult to apply to interpretations adopted through rulemaking, because often rulemaking grants authorize the agency to make such rules and regulations as are necessary to carry out the provisions of this chapter or words to that effect, without specifying whether rules and regulations encompasses rules that have the force of law, or includes only procedural and interpretive rules. Mead therefore requires that courts decipher the meaning of facially ambiguous rulemaking grants. This Article argues that throughout most of the Progressive and New Deal eras, Congress followed a convention for signaling when an otherwise ambiguous rulemaking grant was intended to confer delegated authority to make rules with the force of law. Under this convention, rulemaking grants coupled with a statutory provision imposing sanctions on those who violate the rules were understood to authorize rules with the force of law; rulemaking grants not coupled with any provision for sanctions were understood to authorize only interpretive and procedural rules. Although this understanding can be detected in the Administrative Procedure Act of 1946 (APA), the Supreme Court\u27s decisions construing rulemaking grants after the adoption of the APA betray no awareness of the convention. In the 1970s and early 1980s, the D.C. Circuit and Second Circuit, in an effort to encourage greater use of rulemaking, adopted in place of the convention a presumption that facially ambiguous rulemaking grants always authorize rules with the force of law. As a result, courts held that some agencies, such as the FTC, FDA, and NLRB, had legislative rulemaking powers that Congress almost certainly had not intended. Because the Supreme Court has never endorsed the presumption of the D.C. and Second Circuits, it is not constrained in the aftermath of Mead from drawing upon the original convention in discerning whether Congress intended to delegate power to make rules with the force of law. Strong arguments exist in favor of adopting the convention as a general canon for interpreting facially ambiguous rulemaking grants. Compared to the current approach that treats all rulemaking grants as presumptively authorizing legislative rules, the convention is generally more faithful to congressional intent and to constitutional values associated with the nondelegation doctrine. These advantages, however, must be weighed against the fact that adopting such a canon at this late date would almost certainly upset reliance interests, most prominently in the FDA context

Information Flow and Staff Contact: A Quick Evaluation of Financial Aid

The authors examine the relationship between financial aid staff and students and attempt to analyze how the experience at one institution might provide some insight. The problem is viewed from the client perspective based upon day to day contact with various services provided to students by the financial aid office

Efficient amplitude encoding of polynomial functions into quantum computers

Loading functions into quantum computers represents an essential step in several quantum algorithms, such as in the resolution of partial derivative equations. Therefore, the inefficiency of this process leads to a major bottleneck for the application of these algorithms. Here, we present and compare two efficient methods for the amplitude encoding of real polynomial functions. The first one relies on the matrix product state representation, where we study and benchmark the approximations of the target state when the bond dimension is assumed to be small. The second algorithm combines two subroutines, initially we encode the linear function into the quantum registers with a swallow sequence of multi-controlled gates that loads its Hadamard-Walsh series expansion, followed by the inverse discrete Hadamard-Walsh transform. Then, we use this construction as a building block to achieve a $\mathcal{O}(n)$ block encoding of the amplitudes corresponding to the linear function and apply the quantum singular value transformation that implements the corresponding polynomial transformation to the block encoding of the amplitudes. Additionally, we explore how truncating the Hadamard-Walsh series of the linear function affects the final fidelity of the target state, reporting high fidelities with small resources

Root density distribution and biomass allocation of co-occurring woody plants on contrasting soils in a subtropical savanna parkland

Background and aims: Root niche partitioning among trees/shrubs and grasses facilitates their coexistence in savannas, but little is known regarding root distribution patterns of co-occurring woody plants, and how they might differ on contrasting soils. Methods: We quantified root distributions of co-occurring shrubs to 2m on argillic and non-argillic soils. Results: Root biomass in the two shrub communities was 3- to 5- fold greater than that in the grassland community. Prosopis glandulosa, the dominant overstory species was deep-rooted, while the dominant understory shrub, Zanthoxylum fagara, was shallow-rooted (47% vs. 25% of root density at depths >0.4m). Shrubs on argillic soils had less aboveground and greater belowground mass than those on non-argillic soils. Root biomass and density on argillic soils was elevated at shallow (0.4m. Root density decreased exponentially with increasing distance from woody patch perimeters. Conclusions: Belowground biomass (carbon) pools increased markedly with grassland-to-shrubland state change. The presence/absence of a restrictive barrier had substantial effects on root distributions and above- vs. belowground biomass allocation. Differences in root distribution patterns of co-occurring woody species would facilitate their co-existence.NSF [BSR-9109240]; NASA [NAGW-2662]; NSF Doctoral Dissertation Improvement Grant [DEB/DDIG-1600790]; USDA/NIFA Hatch Project [1003961]; Sid Kyle Graduate Merit Assistantship from the Department of Ecosystem Science and Management; Tom Slick Graduate Research Fellowship from the College of Agriculture and Life Sciences, Texas AM University; Office of Graduate and Professional Studies at Texas AM University12 month embargo; first online: 11 March 2019This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Preferential Myosin Heavy Chain Isoform B Expression May Contribute to the Faster Velocity of Contraction in Veins versus Arteries

Smooth muscle myosin heavy chains occur in 2 isoforms, SMA (slow) and SMB (fast). We hypothesized that the SMB isoform is predominant in the faster-contracting rat vena cava compared to thoracic aorta. We compared the time to half maximal contraction in response to a maximal concentration of endothelin-1 (ET-1; 100 nM), potassium chloride (KCl; 100 mM) and norepinephrine (NE; 10 µM). The time to half maximal contraction was shorter in the vena cava compared to aorta (aorta: ET-1 = 235.8 ± 13.8 s, KCl = 140.0 ± 33.3 s, NE = 19.8 ± 2.7 s; vena cava: ET-1 = 121.8 ± 15.6 s, KCl = 49.5 ± 6.7 s, NE = 9.0 ± 3.3 s). Reverse-transcription polymerase chain reaction supported the greater expression of SMB in the vena cava compared to aorta. SMB was expressed to a greater extent than SMA in the vessel wall of the vena cava. Western analysis determined that expression of SMB, relative to total smooth muscle myosin heavy chains, was 12.5 ± 4.9-fold higher in the vena cava compared to aorta, while SMA was 4.9 ± 1.2-fold higher in the aorta than vena cava. Thus, the SMB isoform is the predominant form expressed in rat veins, providing one possible mechanism for the faster response of veins to vasoconstrictors

Quantum Variational Solving of Nonlinear and Multi-Dimensional Partial Differential Equations

A variational quantum algorithm for numerically solving partial differential equations (PDEs) on a quantum computer was proposed by Lubasch et al. In this paper, we generalize the method introduced by Lubasch et al. to cover a broader class of nonlinear PDEs as well as multidimensional PDEs, and study the performance of the variational quantum algorithm on several example equations. Specifically, we show via numerical simulations that the algorithm can solve instances of the Single-Asset Black-Scholes equation with a nontrivial nonlinear volatility model, the Double-Asset Black-Scholes equation, the Buckmaster equation, and the deterministic Kardar-Parisi-Zhang equation. Our simulations used up to $n=12$ ansatz qubits, computing PDE solutions with $2^n$ grid points. We also performed proof-of-concept experiments with a trapped-ion quantum processor from IonQ, showing accurate computation of two representative expectation values needed for the calculation of a single timestep of the nonlinear Black--Scholes equation. Through our classical simulations and experiments on quantum hardware, we have identified -- and we discuss -- several open challenges for using quantum variational methods to solve PDEs in a regime with a large number ($\gg 2^{20}$) of grid points, but also a practical number of gates per circuit and circuit shots.Comment: 16 pages, 10 figures (main text

Linear-depth quantum circuits for loading Fourier approximations of arbitrary functions

The ability to efficiently load functions on quantum computers with high fidelity is essential for many quantum algorithms. We introduce the Fourier Series Loader (FSL) method for preparing quantum states that exactly encode multi-dimensional Fourier series using linear-depth quantum circuits. The FSL method prepares a ($Dn$)-qubit state encoding the $2^{Dn}$-point uniform discretization of a $D$-dimensional function specified by a $D$-dimensional Fourier series. A free parameter $m < n$ determines the number of Fourier coefficients, $2^{D(m+1)}$, used to represent the function. The FSL method uses a quantum circuit of depth at most $2(n-2)+\lceil \log_{2}(n-m) \rceil + 2^{D(m+1)+2} -2D(m+1)$, which is linear in the number of Fourier coefficients, and linear in the number of qubits ($Dn$) despite the fact that the loaded function's discretization is over exponentially many ($2^{Dn}$) points. We present a classical compilation algorithm with runtime $O(2^{3D(m+1)})$ to determine the FSL circuit for a given Fourier series. The FSL method allows for the highly accurate loading of complex-valued functions that are well-approximated by a Fourier series with finitely many terms. We report results from noiseless quantum circuit simulations, illustrating the capability of the FSL method to load various continuous 1D functions, and a discontinuous 1D function, on 20 qubits with infidelities of less than $10^{-6}$ and $10^{-3}$, respectively. We also demonstrate the practicality of the FSL method for near-term quantum computers by presenting experiments performed on the Quantinuum H$1$-$1$ and H$1$-$2$ trapped-ion quantum computers: we loaded a complex-valued function on 3 qubits with a fidelity of over $95\%$, as well as various 1D real-valued functions on up to 6 qubits with classical fidelities $\approx 99\%$, and a 2D function on 10 qubits with a classical fidelity $\approx 94\%$.Comment: V2: published versio

Ursinus College Bulletin Vol. 10, No. 1, October 1893

A digitized copy of the October 1893 Ursinus College Bulletin.https://digitalcommons.ursinus.edu/ucbulletin/1088/thumbnail.jp