A new time-frequency method to reveal quantum dynamics of atomic hydrogen in intense laser pulses: Synchrosqueezing Transform

This study introduces a new adaptive time-frequency (TF) analysis technique, synchrosqueezing transform (SST), to explore the dynamics of a laser-driven hydrogen atom at an {\it ab initio} level, upon which we have demonstrated its versatility as a new viable venue for further exploring quantum dynamics. For a signal composed of oscillatory components which can be characterized by instantaneous frequency, the SST enables rendering the decomposed signal based on the phase information inherited in the linear TF representation with mathematical support. Compared with the classical type TF methods, the SST clearly depicts several intrinsic quantum dynamical processes such as selection rules, AC Stark effects, and high harmonic generation

A novel method, based on lithium sulfate precipitation for purification of chicken egg yolk immunoglobulin Y, applied to immunospecific antibodies against Sendai virus.

Egg-laying hens were immunized with Sendai virus (SV) that had been grown in chicken embryos. The  titres of immunospecific SV antibodies varied from log212 to log216 during the 5-month immunization  period and total immunoglobulin Y (IgY) concentrations varied from 1.6 to 4.0 mg per ml of egg yolk.  Two IgY purification methods based on salt precipitation using lithium sulfate or sodium citrate were  developed. These methods were compared with two other purification methods based on polyethylene glycol  (PEG) precipitation and chloroform extraction, respectively in terms of yield, total protein content, IgY  concentration and immunospecific anti Sendai IgY activity. The total protein and IgY contents when purified  by chloroform were 1.4-2.8 times and 1.3-2.3 times higher, respectively than in corresponding preparations  purified by the other methods. However, the proportion of nonsense proteins was approximately  10% higher in the IgY preparation purified by chloroform than in those purified by salt precipitation. The  immunospecific IgY activity recorded in the preparations from the new salting out methods was lower  compared with the PEG and chloroform purification methods. However, the purity analysis of IgY by sodium  dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) demonstrated that IgY purified with  lithium sulfate contained only two major components with molecular weights of 40 kDa and 66 kDa and  one minor protein component of 45 kDa. By contrast, IgY extracted with ammonium sulfate, which is a  classical method used to obtain purified IgY, contained two major protein of 40 kDa and 66 kDa and at  least three less intense protein bands corresponding to proteins of molecular weights 31.4 kDa, 33.5 kDa  and 45 kDa. The results indicate that the purification of IgY by lithium sulfate results in very pure IgY in  high quantities (94% +/- 5% of total egg yolk protein).

A High Flux Source of Cold Rubidium

We report the production of a continuous, slow, and cold beam of 87-Rb atoms with an unprecedented flux of 3.2 x 10^12 atoms/s and a temperature of a few milliKelvin. Hot atoms are emitted from a Rb candlestick atomic beam source and transversely cooled and collimated by a 20 cm long atomic collimator section, augmenting overall beam flux by a factor of 50. The atomic beam is then decelerated and longitudinally cooled by Zeeman slowing

Superconducting High Resolution Fast-Neutron Spectrometers

Superconducting high resolution fast-neutron calorimetric spectrometers based on {sup 6}LiF and TiB{sub 2} absorbers have been developed. These novel cryogenic spectrometers measure the temperature rise produced in exothermal (n, {alpha}) reactions with fast neutrons in {sup 6}Li and {sup 10}B-loaded materials with heat capacity C operating at temperatures T close to 0.1 K. Temperature variations on the order of 0.5 mK are measured with a Mo/Cu thin film multilayer operated in the transition region between its superconducting and its normal state. The advantage of calorimetry for high resolution spectroscopy is due to the small phonon excitation energies k{sub B}T on the order of {mu}eV that serve as signal carriers, resulting in an energy resolution {Delta}E {approx} (k{sub B}T{sup 2}C){sup 1/2}, which can be well below 10 keV. An energy resolution of 5.5 keV has been obtained with a Mo/Cu superconducting sensor and a TiB{sub 2} absorber using thermal neutrons from a {sup 252}Cf neutron source. This resolution is sufficient to observe the effect of recoil nuclei broadening in neutron spectra, which has been related to the lifetime of the first excited state in {sup 7}Li. Fast-neutron spectra obtained with a {sup 6}Li-enriched LiF absorber show an energy resolution of 16 keV FWHM, and a response in agreement with the {sup 6}Li(n, {alpha}){sup 3}H reaction cross section and Monte Carlo simulations for energies up to several MeV. The energy resolution of order of a few keV makes this novel instrument applicable to fast-neutron transmission spectroscopy based on the unique elemental signature provided by the neutron absorption and scattering resonances. The optimization of the energy resolution based on analytical and numerical models of the detector response is discussed in the context of these applications

Designing Network Design Strategies Through Gradient Path Analysis

Designing a high-efficiency and high-quality expressive network architecture has always been the most important research topic in the field of deep learning. Most of today's network design strategies focus on how to integrate features extracted from different layers, and how to design computing units to effectively extract these features, thereby enhancing the expressiveness of the network. This paper proposes a new network design strategy, i.e., to design the network architecture based on gradient path analysis. On the whole, most of today's mainstream network design strategies are based on feed forward path, that is, the network architecture is designed based on the data path. In this paper, we hope to enhance the expressive ability of the trained model by improving the network learning ability. Due to the mechanism driving the network parameter learning is the backward propagation algorithm, we design network design strategies based on back propagation path. We propose the gradient path design strategies for the layer-level, the stage-level, and the network-level, and the design strategies are proved to be superior and feasible from theoretical analysis and experiments.Comment: 12 pages, 9 figure