Trace residue analysis of dicyandiamide, cyromazine, and melamine in animal tissue foods by ultra-performance liquid chromatography

AbstractAn effective sample preparation procedure using an accelerated solvent extraction (ASE) procedure, followed by cleaning with melamine molecularly imprinted polymers solid-phase extraction (MISPE) was developed. A novel and highly sensitive ASE–MISPE–ultra-performance liquid chromatography (UPLC) method was developed for effective separation and simultaneous determination of dicyandiamide (DCD), cyromazine (CYR), and melamine (MEL) in complex animal tissue foods. Under optimized conditions, good linearity was achieved with a correlation coefficient (r) of 0.9999 in the range of at least two orders of magnitude. The limit of quantification of the method was 1.7 μg/kg, 5.0 μg/kg, and 3.2 μg/kg for DCD, MEL, and CYR, which was three orders of magnitude smaller than the maximum residue limits (MRLs). The intra- and inter-day precisions (in terms of the relative standard deviation, RSD) of the three analytes were in the range of 1.7–3.1% and 3.1–6.3%, respectively. The average recoveries of analytes from blank chicken, beef, mutton, pork, and pig liver samples spiked with the three levels varied from 91.2% to 107% with RSD of 1.7–8.3% for DCD, 89.0–104% with RSD of 2.1–6.1% for CYR, and 94.8–105% with RSD of 1.1–6.6% for MEL. The proposed method has the characteristics of speed, sensitivity, and accuracy, and can be used for the routine determination of DCD, CYR, and MEL at the μg/kg level in complex animal tissue foods

New Interpretations of Normalization Methods in Deep Learning

In recent years, a variety of normalization methods have been proposed to help train neural networks, such as batch normalization (BN), layer normalization (LN), weight normalization (WN), group normalization (GN), etc. However, mathematical tools to analyze all these normalization methods are lacking. In this paper, we first propose a lemma to define some necessary tools. Then, we use these tools to make a deep analysis on popular normalization methods and obtain the following conclusions: 1) Most of the normalization methods can be interpreted in a unified framework, namely normalizing pre-activations or weights onto a sphere; 2) Since most of the existing normalization methods are scaling invariant, we can conduct optimization on a sphere with scaling symmetry removed, which can help stabilize the training of network; 3) We prove that training with these normalization methods can make the norm of weights increase, which could cause adversarial vulnerability as it amplifies the attack. Finally, a series of experiments are conducted to verify these claims.Comment: Accepted by AAAI 202

NP-Hardness of Tensor Network Contraction Ordering

We study the optimal order (or sequence) of contracting a tensor network with a minimal computational cost. We conclude 2 different versions of this optimal sequence: that minimize the operation number (OMS) and that minimize the time complexity (CMS). Existing results only shows that OMS is NP-hard, but no conclusion on CMS problem. In this work, we firstly reduce CMS to CMS-0, which is a sub-problem of CMS with no free indices. Then we prove that CMS is easier than OMS, both in general and in tree cases. Last but not least, we prove that CMS is still NP-hard. Based on our results, we have built up relationships of hardness of different tensor network contraction problems.Comment: Jianyu Xu and Hanwen Zhang are equal contributors. 10 pages (reference and appendix excluded), 20 pages in total, 6 figure

Study of the Vibration-Energy Properties of the CRTS-III Track Based on the Power Flow Method

The vibration induced by the high-speed railway (HSR) system has been a severe problem during the construction and operation period. To investigate the vibration-energy properties of the China Railways Track System (CRTS)-III track, a vehicle-track-subgrade coupling model is developed, in which the distribution of the tangent force is symmetrical according to the FASTSIM theory, and the power flow method is utilized. What’s more, the corresponding evaluation indexes of the power flow are proposed to analyze the vibration energy of the track structure. The results reveal that the vibration energy decreases from top to bottom of the track structure among the frequency considered, and the decreasing trend is obvious. The vibration energy of the track structure is sensitive to the stiffness of fasteners. Differently, the vibration energy of the composite slab and the base slab is more sensitive to the stiffness of rubber damping pads than that of the rail. To sum up, this paper can provide a new perspective and method to study the vibration-energy properties and select the reasonable stiffness of the fasteners and the rubber damping pads of the CRTS-III track, and the proposed values of the stiffness of the fasteners and the rubber damping pads for the case under this study are 40 kN/mm and 400 MPa/m, respectively

Supported cobalt catalysts by one-pot aqueous combustion synthesis for catalytic phenol degradation

Cobalt oxides (Co) and Al2O3-, SiO2-, and TiO2-supported cobalt oxide catalysts were prepared by anaqueous combustion method using urea and glycine as fuels. Their catalytic performance in activationof OXONE for phenol degradation in aqueous solution was investigated. It was found that unsupported Co oxide and supported Co oxide presented different mechanisms in activation of OXONE for phenol degradation. The supported Co catalysts presented higher activity in activation of OXONE for phenol degradation due to higher dispersion of Co3O4 on the supports and Co(II) coordination sites. The major oxidizing radicals were identified to be SO4- by competitive radical reactions. The Co oxides synthesized from urea or glycine showed a similar activity; however, the supported Co catalysts prepared by glycine fuel exhibited better activity than those prepared by urea. For Al2O3-, SiO2-, and TiO2-supported Co catalysts, Co/TiO2 presented a higher activity in phenol degradation compared with Co/SiO2 and Co/Al2O3. But, Co/SiO2 showed the best stability among the catalysts. Total organic carbon could be reduced by 80%, 72%, and 45% on Co/TiO2, Co/SiO2, and Co/Al2O3, respectively, at 30 ppm phenol. Phenol degradation was found to follow the zero-order kinetics. The causes of deactivation were investigated, and the regeneration methods were proposed