Superconductivity in nearly single-phase Bi-Pb-Sr-Ca-Cu-O samples with different nominal compositions

The preparation conditions, phase composition, and superconducting properties of Bi-Pb-Sr-Ca-Cu oxide materials from different nominal compositions have been investigated. Nearly single-phase samples from Bi₂Pb_0.4Sr₂Ca₃Cu₄O _y , as well as from the proposed compositions Bi_1.8Pb_0.4Sr₂Ca₃Cu₄O _y and Bi_1.8Pb_0.4Sr₂Ca_2.5Cu_3.5O _y were obtained by a solid-state reaction in air. Samples with the third nominal composition showed the best superconducting properties (T _on=111 K and zero resistance atT ₀=103 K). A possible mechanism for the 2223 phase formation in the three investigated compositions has been discussed.     

Al-Cu-Fe QUASICRYSTALLINE PHASE FORMATION BY MECHANICAL ALLOYING

Al-Cu-Fe alloys were prepared from elemental powders in a high-energy planetary ball mill. A sequence of solid state reactions resulting in quasicrystal (QC) phase formation takes place during heating of the as-milled powder. These reactions were studied by both differential scanning calorimetry and x-ray diffraction methods. Mechanically alloyed powders were consolidated by cold and hot pressing, as well as by explosive compaction. After annealing at sufficiently high temperatures, the consolidated samples are single-phase QC, except the ones consolidated by explosion. The high reactivity of the as-milled alloys causes the appearance of high porosity of the consolidated samples after the annealing.     

硫脲型整合树脂在分析上的应用 Ⅰ.岩样中微量银的中子活化分析

前言银和其他贵金属元素一样,在地壳中比较稀少,按其自然丰度为第67号元素,平均含量仅0.07 ppm。由于地质样品成分非常复杂,为测定其微量银,必须进行严格的化学分离。但是迄今文献中报道的许多分离分法,步骤都相当冗长,一般采用氯化银反     

Are Samples in Randomized Controlled Trials of Psychotherapy Representative of Community Outpatients? A New Methodology and Initial Findings.

To determine the extent to which published randomized controlled trials (RCTs) of psychotherapy can be generalized to a sample of community outpatients, the authors used a method of matching information obtained from outpatient charts to inclusion and exclusion criteria from published RCT studies. They found that 80% of the patients in their sample who had diagnoses represented in the RCT literature were judged eligible for at least 1 published RCT; however, 58% of the patients had primary diagnoses such as adjustment disorder or dysthymia, which were not represented in the existing psychotherapy outcome literature. The most common reasons that patients in their sample did not match with published RCTs for psychotherapy are listed, and the implications of these findings for research and practice are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Microplastic and other anthropogenic microparticles in water and sediments of Lake Simcoe

Microplastics (plastic particles <5 mm in size) have been reported in ecosystems worldwide and have been shown to cause adverse negative impacts on organisms. This study provides the first report of microplastics and other anthropogenic microparticles in the surface waters and sediments of Lake Simcoe in Ontario, Canada, a popular recreational and fishing lake. Surface waters (low volume grabs and manta trawls) and sediments were sampled from eight sites to determine microparticle abundances and character (size, morphology, material identity). Concentrations ranged from 0 to 0.7 particles/L in surface water grab samples, 0.4–1.3 particles/m³ in manta trawl samples, and 8.3–1070 particles/kg in sediment samples. Spectroscopic analysis confirmed that 72% of particles were anthropogenic, with 64% unambiguously identified as microplastics. However, confirmed microplastic concentrations were approximately 6–7 times lower than unadjusted counts in sediments, demonstrating the importance of verifying and adjusting reported values. Fibers were only quantified and characterized in surface water grab samples and sediments, and were the most common morphology, accounting for 82% and 89% of anthropogenic particles, respectively. Fragments were most common in manta trawl samples (75%, excluding fibers) and consisted predominantly of polyethylene (41%) and polypropylene (22%). The influence of proximity to urban centers and prevailing winds on the distribution of microplastics was apparent in surface water manta trawls. Microplastics and other anthropogenic microparticles are present in Lake Simcoe but at lower abundances than at locations impacted by larger population centers in other large freshwater lakes such as Lakes Ontario and Erie of the Great Lakes.     

Speech Enhancement via Residual Dense Generative Adversarial Network

Generative adversarial networks (GANs) are paid more attention to dealing with the end-to-end speech enhancement in recent years. Various GAN-based enhancement methods are presented to improve the quality of reconstructed speech. However, the performance of these GAN-based methods is worse than those of masking-based methods. To tackle this problem, we propose speech enhancement method with a residual dense generative adversarial network (RDGAN) contributing to map the log-power spectrum (LPS) of degraded speech to the clean one. In detail, a residual dense block (RDB) architecture is designed to better estimate the LPS of clean speech, which can extract rich local features of LPS through densely connected convolution layers. Meanwhile, sequential RDB connections are incorporated on various scales of LPS. It significantly increases the feature learning flexibility and robustness in the time-frequency domain. Simulations show that the proposed method achieves attractive speech enhancement performance in various acoustic environments. Specifically, in the untrained acoustic test with limited priors, e.g., unmatched signal-to-noise ratio (SNR) and unmatched noise category, RDGAN can still outperform the existing GAN-based methods and masking-based method in the measures of PESQ and other evaluation indexes. It indicates that our method is more generalized in untrained conditions.     

Semisupervised Encrypted Traffic Identification Based on Auxiliary Classification Generative Adversarial Network

The rapidly increasing popularity of mobile devices has changed the methods with which people access various network services and increased network traffic markedly. Over the past few decades, network traffic identification has been a research hotspot in the field of network management and security monitoring. However, as more network services use encryption technology, network traffic identification faces many challenges. Although classic machine learning methods can solve many problems that cannot be solved by port- and payload-based methods, manually extract features that are frequently updated is time-consuming and labor-intensive. Deep learning has good automatic feature learning capabilities and is an ideal method for network traffic identification, particularly encrypted traffic identification; Existing recognition methods based on deep learning primarily use supervised learning methods and rely on many labeled samples. However, in real scenarios, labeled samples are often difficult to obtain. This paper adjusts the structure of the auxiliary classification generation adversarial network (ACGAN) so that it can use unlabeled samples for training, and use the wasserstein distance instead of the original cross entropy as the loss function to achieve semisupervised learning. Experimental results show that the identification accuracy of ISCX and USTC data sets using the proposed method yields markedly better performance when the number of labeled samples is small compared to that of convolutional neural network (CNN) based classifier.     

An economic and sensitive method for extracting chromium speciation in airborne inhalable dust,using a green sample treatment coupled with electrothermal atomic absorption

ABSTRACT

A new approach of cloud point extraction CPE procedure is optimized for hexavalent chromium determination in airborne dusts. Triton X-114 is used as a surfactant and 1-(2-pyridylazo)-2-naphthol as a specific complexing agent for the trivalent chromium’s removal from the aqueous phase to isolate hexavalent chromium compounds. The parameters influencing the extraction protocol (pH, surfactant concentration, and temperature are optimized. The obtained detection and quantification limits are 0.1 and 0.4 μg/L, respectively. The linearity is verified, with a regression coefficient close to 0.999 and the extraction recovery exceeds 99%. The method was successfully applied to analyze airborne samples collected from workplaces.     

缺失数据下m相依样本的大样本性质

讨论了缺失数据在随机补充方式下均值的估计,证明了估计的相合性和渐进正态性,并给出了经验似然比统计量的渐进分布．     

定数截尾数据缺失场合下k/N(G)系统可靠性指标的Bayes估计

在定数截尾缺失数据样本下,研究了不可修k/N(G)系统的可靠性指标评估问题。将经典估计方法和Bayes方法相结合得到了部件的平均寿命、系统可靠度及平均寿命等可靠性指标的Bayes估计。最后利用随机模拟例子说明了本研究方法的正确性和可行性。