The radiation-induced rotation of cosmic dust particles: A feasibility study

A crossed beam, horizontal optical trap, used to achieve laser levitation of particles in an effort to determine how solar radiation produces high spin rate in interplanetary dust particles, is described. It is suggested that random variations in albedo and geometry give rise to a nonzero effective torque when the influence of a unidrectional source of radiaton (due to the Sun) over the surface of a interplanetary dust particle is averaged. This resultant nonzero torque is characterized by an asymmetry factor which is the ratio of the effective moment arm to the maximum linear dimension of the body and is estimated to be 5 X 10 to the minus four power. It is hoped that this symmetry factor, which stabilizes the nonstatistical response of the particle, can be measured in a future Spacelab experiment

The time-of-propagation counter for Belle II

The Belle II detector operating at the future upgrade to the KEKB accelerator will perform high-statistics precision investigations into the flavor sector of the Standard Model. As charged hadron identification is a vital element of the experiment's success, the time-of-propagation (TOP) counter has been chosen as the primary particle identification device in the barrel region of Belle II. The TOP counter is a compact variant of the detection of internally reflected Cherenkov light (DIRC) technique and relies heavily on exquisite single photon timing resolution with micro-channel plate photomultiplier tubes. We discuss the general principles of TOP operation and optimization of the Belle II TOP configuration, which is expected to provide 4 sigma or better separation of kaons and pions up to momenta of approximately 4 GeV/c.Comment: 5 pages, 5 figures, 2 tables; Submitted to special edition of NIMA, Proceedings of RICH201

Evolution of the bulk properties, structure, magnetic order, and superconductivity with Ni doping in CaFe2-xNixAs2

Magnetization, susceptibility, specific heat, resistivity, neutron and x-ray diffraction have been used to characterize the properties of single crystalline CaFe2-xNixAs2 as a function of Ni doping for x varying from 0 to 0.1. The combined first-order structural and magnetic phase transitions occur together in the undoped system at 172 K, with a small decrease in the area of the a-b plane along with an abrupt increase in the length of the c-axis in the orthorhombic phase. With increasing x the ordered moment and transition temperature decrease, but the transition remains sharp at modest doping while the area of the a-b plane quickly decreases and then saturates. Warming and cooling data in the resistivity and neutron diffraction indicate hysteresis of ~2 K. At larger doping the transition is more rounded, and decreases to zero for x=0.06. The susceptibility is anisotropic for all values of x. Electrical resistivity for x = 0.053 and 0.06 shows a superconducting transition with an onset of nearly 15 K which is further corroborated by substantial diamagnetic susceptibility. For the fully superconducting sample there is no long range magnetic order and the structure remains tetragonal at all temperature, but there is an anomalous increase in the area of the a-b plane in going to low T. Heat capacity data show that the density of states at the Fermi level increases for x > 0.053 as inferred from the value of Sommerfeld coefficient. The regime of superconductivity is quite restrictive, with a maximum TC of 15 K and an upper critical field Hc2=14 T. Superconductivity disappears in the overdoped region.Comment: 14 pages, 12 figures. Submitted to Phys. Rev.

Molecular diagnosis of medical viruses.

The diagnosis of infectious diseases has been revolutionized by the development of molecular techniques, foremost with the applications of the polymerase chain reaction (PCR). The achievable high sensitivity and ease with which the method can be used to detect any known genetic sequence have led to its wide application in the life sciences. More recently, real-time PCR assays have provided additional major contributions, with the inclusion of an additional fluorescent probe detection system resulting in an increase in sensitivity over conventional PCR, the ability to confirm the amplification product and to quantitate the target concentration. Further, nucleotide sequence analysis of the amplification products has facilitated epidemiological studies of infectious disease outbreaks, and the monitoring of treatment outcomes for infections, in particular with viruses which mutate at high frequency. This review discusses the applications of qualitative and quantitative real-time PCR, nested PCR, multiplex PCR, nucleotide sequence analysis of amplified products and quality assurance with nucleic acid testing (NAT) in diagnostic laboratories

HoloDetect: Few-Shot Learning for Error Detection

We introduce a few-shot learning framework for error detection. We show that data augmentation (a form of weak supervision) is key to training high-quality, ML-based error detection models that require minimal human involvement. Our framework consists of two parts: (1) an expressive model to learn rich representations that capture the inherent syntactic and semantic heterogeneity of errors; and (2) a data augmentation model that, given a small seed of clean records, uses dataset-specific transformations to automatically generate additional training data. Our key insight is to learn data augmentation policies from the noisy input dataset in a weakly supervised manner. We show that our framework detects errors with an average precision of ~94% and an average recall of ~93% across a diverse array of datasets that exhibit different types and amounts of errors. We compare our approach to a comprehensive collection of error detection methods, ranging from traditional rule-based methods to ensemble-based and active learning approaches. We show that data augmentation yields an average improvement of 20 F1 points while it requires access to 3x fewer labeled examples compared to other ML approaches.Comment: 18 pages

Closed-form approximations of first-passage distributions for a stochastic decision making model

In free response choice tasks, decision making is often modeled as a first-passage problem for a stochastic differential equation. In particular, drift-diffusion processes with constant or time-varying drift rates and noise can reproduce behavioral data (accuracy and response-time distributions) and neuronal firing rates. However, no exact solutions are known for the first-passage problem with time-varying data. Recognizing the importance of simple closed-form expressions for modeling and inference, we show that an interrogation or cued-response protocol, appropriately interpreted, can yield approximate first-passage (response time) distributions for a specific class of time-varying processes used to model evidence accumulation. We test these against exact expressions for the constant drift case and compare them with data from a class of sigmoidal functions. We find that both the direct interrogation approximation and an error-minimizing interrogation approximation can capture a variety of distribution shapes and mode numbers but that the direct approximation, in particular, is systematically biased away from the correct free response distribution