Barkhausen noise in the Random Field Ising Magnet Nd2_2Fe14_{14}B

With sintered needles aligned and a magnetic field applied transverse to its easy axis, the rare-earth ferromagnet Nd$_2$Fe$_{14}$B becomes a room-temperature realization of the Random Field Ising Model. The transverse field tunes the pinning potential of the magnetic domains in a continuous fashion. We study the magnetic domain reversal and avalanche dynamics between liquid helium and room temperatures at a series of transverse fields using a Barkhausen noise technique. The avalanche size and energy distributions follow power-law behavior with a cutoff dependent on the pinning strength dialed in by the transverse field, consistent with theoretical predictions for Barkhausen avalanches in disordered materials. A scaling analysis reveals two regimes of behavior: one at low temperature and high transverse field, where the dynamics are governed by the randomness, and the second at high temperature and low transverse field where thermal fluctuations dominate the dynamics.Comment: 16 pages, 7 figures. Under review at Phys. Rev.

Stronger instruments via integer programming in an observational study of late preterm birth outcomes

In an optimal nonbipartite match, a single population is divided into matched pairs to minimize a total distance within matched pairs. Nonbipartite matching has been used to strengthen instrumental variables in observational studies of treatment effects, essentially by forming pairs that are similar in terms of covariates but very different in the strength of encouragement to accept the treatment. Optimal nonbipartite matching is typically done using network optimization techniques that can be quick, running in polynomial time, but these techniques limit the tools available for matching. Instead, we use integer programming techniques, thereby obtaining a wealth of new tools not previously available for nonbipartite matching, including fine and near-fine balance for several nominal variables, forced near balance on means and optimal subsetting. We illustrate the methods in our on-going study of outcomes of late-preterm births in California, that is, births of 34 to 36 weeks of gestation. Would lengthening the time in the hospital for such births reduce the frequency of rapid readmissions? A straightforward comparison of babies who stay for a shorter or longer time would be severely biased, because the principal reason for a long stay is some serious health problem. We need an instrument, something inconsequential and haphazard that encourages a shorter or a longer stay in the hospital. It turns out that babies born at certain times of day tend to stay overnight once with a shorter length of stay, whereas babies born at other times of day tend to stay overnight twice with a longer length of stay, and there is nothing particularly special about a baby who is born at 11:00 pm.Comment: Published in at http://dx.doi.org/10.1214/12-AOAS582 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Interactions between glyphosate, Fusarium infection of waterhemp, and soil microorganisms

In recent years, an increasing number of weed populations have been characterized with resistance to the herbicide glyphosate. In particular, waterhemp has evolved glyphosate resistance (GR) across numerous soybean fields in Missouri. Therefore research is needed to determine best management practices for GR weed biotypes. The objectives of these experiments were to determine the frequency and distribution of GR waterhemp in Missouri and identify any in-field parameters which could serve as indicators of GR in future crop production systems; determine the effects of various pre-emergence (PRE) and post-emergence (POST) herbicide programs on palmer amaranth and waterhemp control, soybean yield, and net income in conventional, glyphosate-resistant, and glufosinate-resistant soybean production systems; determine the effects of soil microbial and phytopathogen populations on GR and susceptible (GS) waterhemp survival and Fusarium infection; and determine the soil microbial abundance and diversity in soils collected from soybean fields with differences in waterhemp biotypes and herbicide and crop rotation histories. Results from these experiments indicate herbicide programs that contain PRE herbicide treatments provide the best opportunity for season-long control of waterhemp and palmer amaranth, highest grain yields, and highest net returns in the soybean systems evaluated. GR was confirmed in 69% of the total waterhemp populations sampled in Missouri. Additionally, the in-field parameters evaluated suggest that soybean fields containing GR waterhemp were more likely to be free of other weed species, occur where soybeans were continuously cropped, occur where glyphosate was the only herbicide applied for several seasons consecutively, and where waterhemp exhibited signs of surviving herbicide treatment compared to fields characterized with GS waterhemp. Results of the soil study indicate plants are more sensitive to glyphosate in soils with microbial populations compared to those without and that glyphosate may predispose plants to soilborne phytopathogens. The results also suggest continuous use of glyphosate does not significantly affect soil microbial abundance or diversity

The use of prognostic scores for causal inference with general treatment regimes

In nonrandomised studies, inferring causal effects requires appropriate methods for addressing confounding bias. Although it is common to adopt propensity score analysis to this purpose, prognostic score analysis has recently been proposed as an alternative strategy. While both approaches were originally introduced to estimate causal effects for binary interventions, the theory of propensity score has since been extended to the case of general treatment regimes. Indeed, many treatments are not assigned in a binary fashion and require a certain extent of dosing. Hence, researchers may often be interested in estimating treatment effects across multiple exposures. To the best of our knowledge, the prognostic score analysis has not been yet generalised to this case. In this article, we describe the theory of prognostic scores for causal inference with general treatment regimes. Our methods can be applied to compare multiple treatments using nonrandomised data, a topic of great relevance in contemporary evaluations of clinical interventions. We propose estimators for the average treatment effects in different populations of interest, the validity of which is assessed through a series of simulations. Finally, we present an illustrative case in which we estimate the effect of the delay to Aspirin administration on a composite outcome of death or dependence at 6 months in stroke patients

Baby-Step Giant-Step Algorithms for the Symmetric Group

We study discrete logarithms in the setting of group actions. Suppose that $G$ is a group that acts on a set $S$. When $r,s \in S$, a solution $g \in G$ to $r^g = s$ can be thought of as a kind of logarithm. In this paper, we study the case where $G = S_n$, and develop analogs to the Shanks baby-step / giant-step procedure for ordinary discrete logarithms. Specifically, we compute two sets $A, B \subseteq S_n$ such that every permutation of $S_n$ can be written as a product $ab$ of elements $a \in A$ and $b \in B$. Our deterministic procedure is optimal up to constant factors, in the sense that $A$ and $B$ can be computed in optimal asymptotic complexity, and $|A|$ and $|B|$ are a small constant from $\sqrt{n!}$ in size. We also analyze randomized "collision" algorithms for the same problem

Percolating through networks of random thresholds: Finite temperature electron tunneling in metal nanocrystal arrays

We investigate how temperature affects transport through large networks of nonlinear conductances with distributed thresholds. In monolayers of weakly-coupled gold nanocrystals, quenched charge disorder produces a range of local thresholds for the onset of electron tunneling. Our measurements delineate two regimes separated by a cross-over temperature $T^*$. Up to $T^*$ the nonlinear zero-temperature shape of the current-voltage curves survives, but with a threshold voltage for conduction that decreases linearly with temperature. Above $T^*$ the threshold vanishes and the low-bias conductance increases rapidly with temperature. We develop a model that accounts for these findings and predicts $T^*$.Comment: 5 pages including 3 figures; replaced 3/30/04: minor changes; final versio

Critical Behavior of the Conductivity of Si:P at the Metal-Insulator Transition under Uniaxial Stress

We report new measurements of the electrical conductivity sigma of the canonical three-dimensional metal-insulator system Si:P under uniaxial stress S. The zero-temperature extrapolation of sigma(S,T -> 0) ~\S - S_c\^mu shows an unprecidentedly sharp onset of finite conductivity at S_c with an exponent mu = 1. The value of mu differs significantly from that of earlier stress-tuning results. Our data show dynamical sigma(S,T) scaling on both metallic and insulating sides, viz. sigma(S,T) = sigma_c(T) F(\S - S_cT^y) where sigma_c(T) is the conductivity at the critical stress S_c. We find y = 1/znu = 0.34 where nu is the correlation-length exponent and z the dynamic critical exponent.Comment: 5 pages, 4 figure