Pulse shape discrimination based on the Tempotron: a powerful classifier on GPU

This study introduces the Tempotron, a powerful classifier based on a third-generation neural network model, for pulse shape discrimination. By eliminating the need for manual feature extraction, the Tempotron model can process pulse signals directly, generating discrimination results based on learned prior knowledge. The study performed experiments using GPU acceleration, resulting in over a 500 times speedup compared to the CPU-based model, and investigated the impact of noise augmentation on the Tempotron's performance. Experimental results showed that the Tempotron is a potent classifier capable of achieving high discrimination accuracy. Furthermore, analyzing the neural activity of Tempotron during training shed light on its learning characteristics and aided in selecting the Tempotron's hyperparameters. The dataset used in this study and the source code of the GPU-based Tempotron are publicly available on GitHub at https://github.com/HaoranLiu507/TempotronGPU.Comment: 14 pages,7 figure

A Sodium laser guide star coupling efficiency measurement method

Large telescope's adaptive optics (AO) system requires one or several bright artificial laser guide stars to improve its sky coverage. The recent advent of high power sodium laser is perfect for such application. However, besides the output power, other parameters of the laser also have significant impact on the brightness of the generated sodium laser guide star mostly in non-linear relationships. When tuning and optimizing these parameters it is necessary to tune based on a laser guide star generation performance metric. Although return photon flux is widely used, variability of atmosphere and sodium layer make it difficult to compare from site to site even within short time period for the same site. A new metric, coupling efficiency is adopted in our field tests. In this paper, we will introduce our method for measuring the coupling efficiency of a 20W class pulse sodium laser for AO application during field tests that were conducted during 2013-2015

Determinants of 14-3-3σ dimerization and function in drug and radiation resistance

Many proteins exist and function as homodimers. Understanding the detailed mechanism driving the homodimerization is important and will impact future studies targeting the “undruggable” oncogenic protein dimers. In this study, we used 14-3-3σ as a model homodimeric protein and performed a systematic investigation of the potential roles of amino acid residues in the interface for homodimerization. Unlike other members of the conserved 14-3-3 protein family, 14-3-3σ prefers to form a homodimer with two subareas in the dimeric interface that has 180° symmetry. We found that both subareas of the dimeric interface are required to maintain full dimerization activity. Although the interfacial hydrophobic core residues Leu12 and Tyr84 play important roles in 14-3-3σ dimerization, the non-core residue Phe25 appears to be more important in controlling 14-3-3σ dimerization activity. Interestingly, a similar non-core residue (Val81) is less important than Phe25 in contributing to 14-3-3σ dimerization. Furthermore, dissociating dimeric 14-3-3σ into monomers by mutating the Leu12, Phe25, or Tyr84 dimerization residue individually diminished the function of 14-3-3σ in resisting drug-induced apoptosis and in arresting cells at G2/M phase in response to DNA-damaging treatment. Thus, dimerization appears to be required for the function of 14-3-3σ

In Silico Syndrome Prediction for Coronary Artery Disease in Traditional Chinese Medicine

Coronary artery disease (CAD) is the leading causes of deaths in the world. The differentiation of syndrome (ZHENG) is the criterion of diagnosis and therapeutic in TCM. Therefore, syndrome prediction in silico can be improving the performance of treatment. In this paper, we present a Bayesian network framework to construct a high-confidence syndrome predictor based on the optimum subset, that is, collected by Support Vector Machine (SVM) feature selection. Syndrome of CAD can be divided into asthenia and sthenia syndromes. According to the hierarchical characteristics of syndrome, we firstly label every case three types of syndrome (asthenia, sthenia, or both) to solve several syndromes with some patients. On basis of the three syndromes' classes, we design SVM feature selection to achieve the optimum symptom subset and compare this subset with Markov blanket feature select using ROC. Using this subset, the six predictors of CAD's syndrome are constructed by the Bayesian network technique. We also design Naïve Bayes, C4.5 Logistic, Radial basis function (RBF) network compared with Bayesian network. In a conclusion, the Bayesian network method based on the optimum symptoms shows a practical method to predict six syndromes of CAD in TCM

Quantum LiDAR with Frequency Modulated Continuous Wave

The range and speed of a moving object can be ascertained using the sensing technique known as light detection and ranging (LiDAR). It has recently been suggested that quantum LiDAR, which uses entangled states of light, can enhance the capabilities of LiDAR. Entangled pulsed light is used in prior quantum LiDAR approaches to assess both range and velocity at the same time using the pulses' time of flight and Doppler shift. The entangled pulsed light generation and detection, which are crucial for pulsed quantum LiDAR, are often inefficient. Here, we study a quantum LiDAR that operates on a frequency-modulated continuous wave (FMCW), as opposed to pulses. We first outline the design of the quantum FMCW LiDAR using entangled frequency-modulated photons in a Mach-Zehnder interferometer, and we demonstrate how it can increase accuracy and resolution for range and velocity measurements by $\sqrt{n}$ and $n$, respectively, with $n$ entangled photons. We also demonstrate that quantum FMCW LiDAR may perform simultaneous measurements of the range and velocity without the need for quantum pulsed compression, which is necessary in pulsed quantum LiDAR. Since the generation of entangled photons is the only inefficient nonlinear optical process needed, the quantum FMCW LiDAR is better suited for practical implementations. Additionally, most measurements in the quantum FMCW LiDAR can be carried out electronically by down-converting optical signal to microwave region

Interface induced high temperature superconductivity in single unit-cell FeSe films on SrTiO3

Searching for superconducting materials with high transition temperature (TC) is one of the most exciting and challenging fields in physics and materials science. Although superconductivity has been discovered for more than 100 years, the copper oxides are so far the only materials with TC above 77 K, the liquid nitrogen boiling point. Here we report an interface engineering method for dramatically raising the TC of superconducting films. We find that one unit-cell (UC) thick films of FeSe grown on SrTiO3 (STO) substrates by molecular beam epitaxy (MBE) show signatures of superconducting transition above 50 K by transport measurement. A superconducting gap as large as 20 meV of the 1 UC films observed by scanning tunneling microcopy (STM) suggests that the superconductivity could occur above 77 K. The occurrence of superconductivity is further supported by the presence of superconducting vortices under magnetic field. Our work not only demonstrates a powerful way for finding new superconductors and for raising TC, but also provides a well-defined platform for systematic study of the mechanism of unconventional superconductivity by using different superconducting materials and substrates

Cancer-induced bone pain sequentially activates the ERK/MAPK pathway in different cell types in the rat spinal cord

<p>Abstract</p> <p>Background</p> <p>Previous studies have demonstrates that, after nerve injury, extracellular signal-regulated protein kinase (ERK) activation in the spinal cord-initially in neurons, then microglia, and finally astrocytes. In addition, phosphorylation of ERK (p-ERK) contributes to nociceptive responses following inflammation and/or nerve injury. However, the role of spinal cells and the ERK/MAPK pathway in cancer-induced bone pain (CIBP) remains poorly understood. The present study analyzed activation of spinal cells and the ERK/MAPK pathway in a rat model of bone cancer pain.</p> <p>Results</p> <p>A Sprague Dawley rat model of bone cancer pain was established and the model was evaluated by a series of tests. Moreover, fluorocitrate (reversible glial metabolic inhibitor) and U0126 (a MEK inhibitor) was administered intrathecally. Western blots and double immunofluorescence were used to detect the expression and location of phosphorylation of ERK (p-ERK). Our studies on pain behavior show that the time between day 6 and day 18 is a reasonable period ("time window" as the remaining stages) to investigate bone cancer pain mechanisms and to research analgesic drugs. Double-labeling immunofluorescence revealed that p-ERK was sequentially expressed in neurons, microglia, and astrocytes in the L4-5 superficial spinal cord following inoculation of Walker 256 cells. Phosphorylation of ERK (p-ERK) and the transcription factor cAMP response element-binding protein (p-CREB) increased in the spinal cord of CIBP rats, which was attenuated by intrathecal injection of fluorocitrate or U0126.</p> <p>Conclusions</p> <p>The ERK inhibitors could have a useful role in CIBP management, because the same target is expressed in various cells at different times.</p

Controlling Homogenous Spherulitic Crystallization for high-efficiency Planar Perovskite Solar Cells fabricated under ambient high-humidity conditions

The influence of precursor solution properties, fabrication environment, and antisolvent properties on the microstructural evolution of perovskite films is reported. First, the impact of fabrication environment on the morphology of methyl ammonium lead iodide (MAPbI3) perovskite films with various Lewis‐base additives is reported. Second, the influence of antisolvent properties on perovskite film microstructure is investigated using antisolvents ranging from nonpolar heptane to highly polar water. This study shows an ambient environment that accelerates crystal growth at the expense of nucleation and introduces anisotropies in crystal morphology. The use of antisolvents enhances nucleation but also influences ambient moisture interaction with the precursor solution, resulting in different crystal morphology (shape, size, dispersity) in different antisolvents. Crystal morphology, in turn, dictates film quality. A homogenous spherulitic crystallization results in pinhole‐free films with similar microstructure irrespective of processing environment. This study further demonstrates propyl acetate, an environmentally benign antisolvent, which can induce spherulitic crystallization under ambient environment (52% relative humidity, 25 °C). With this, planar perovskite solar cells with ≈17.78% stabilized power conversion efficiency are achieved. Finally, a simple precipitation test and in situ crystallization imaging under an optical microscope that can enable a facile a priori screening of antisolvents is shown

Coupling Efficiency Measurements for Long-pulsed Solid Sodium Laser Based on Measured Sodium Profile Data

In 2013, a serial sky test has been held on 1.8 meter telescope in Yunnan observation site after 2011-2012 Laser guide star photon return test. In this test, the long-pulsed sodium laser and the launch telescope have been upgraded, a smaller and brighter beacon has been observed. During the test, a sodium column density lidar and atmospheric coherence length measurement equipment were working at the same time. The coupling efficiency test result with the sky test layout, data processing, sodium beacon spot size analysis, sodium profile data will be presented in this paper