Release Profile of Nitrogen during Thermal Treatment of Waste Wooden Packaging Materials

In this paper, the fast pyrolysis experiment of particle board was carried out on a fixed bed reactor and a Py-GC/MS equipment. The effects of temperature and gas phase residence time on the product yields and its components distribution were investigated. The effect of components of particle board on product yields and its components distribution was also investigated. The results showed that the temperature has a great influence on the yields of fast pyrolysis products, and the yield of pyrolysis oil reached the highest at 550°C. The urea-formaldehyde resin would prevent the pyrolysis of particle board. Compared with the bio-oil from fast pyrolysis of wood, the major components of the bio-oil from fast pyrolysis of particle board did not change much

Impact of Uniaxial Pressure on Structural and Magnetic Phase Transitions in Electron-Doped Iron Pnictides

We use neutron resonance spin echo and Larmor diffraction to study the effect of uniaxial pressure on the tetragonal-to-orthorhombic structural ($T_s$) and antiferromagnetic (AF) phase transitions in iron pnictides BaFe$_{2-x}$Ni$_{x}$As$_{2}$ ($x=0,0.03,0.12$), SrFe$_{1.97}$Ni$_{0.03}$As$_2$, and BaFe$_2$(As$_{0.7}$P$_{0.3}$)$_2$. In antiferromagnetically ordered BaFe$_{2-x}$Ni$_{x}$As$_{2}$ and SrFe$_{1.97}$Ni$_{0.03}$As$_2$ with $T_N$ and $T_s$ ($T_N\leq T_s$), a uniaxial pressure necessary to detwin the sample also increases $T_N$, smears out the structural transition, and induces an orthorhombic lattice distortion at all temperatures. By comparing temperature and doping dependence of the pressure induced lattice parameter changes with the elastoresistance and nematic susceptibility obtained from transport and ultrasonic measurements, we conclude that the in-plane resistivity anisotropy found in the paramagnetic state of electron underdoped iron pnictides depends sensitively on the nature of the magnetic phase transition and a strong coupling between the uniaxial pressure induced lattice distortion and electronic nematic susceptibility.Comment: 18 pages, 15 figure

Intelligent Gearbox Diagnosis Methods Based on SVM, Wavelet Lifting and RBR

Given the problems in intelligent gearbox diagnosis methods, it is difficult to obtain the desired information and a large enough sample size to study; therefore, we propose the application of various methods for gearbox fault diagnosis, including wavelet lifting, a support vector machine (SVM) and rule-based reasoning (RBR). In a complex field environment, it is less likely for machines to have the same fault; moreover, the fault features can also vary. Therefore, a SVM could be used for the initial diagnosis. First, gearbox vibration signals were processed with wavelet packet decomposition, and the signal energy coefficients of each frequency band were extracted and used as input feature vectors in SVM for normal and faulty pattern recognition. Second, precision analysis using wavelet lifting could successfully filter out the noisy signals while maintaining the impulse characteristics of the fault; thus effectively extracting the fault frequency of the machine. Lastly, the knowledge base was built based on the field rules summarized by experts to identify the detailed fault type. Results have shown that SVM is a powerful tool to accomplish gearbox fault pattern recognition when the sample size is small, whereas the wavelet lifting scheme can effectively extract fault features, and rule-based reasoning can be used to identify the detailed fault type. Therefore, a method that combines SVM, wavelet lifting and rule-based reasoning ensures effective gearbox fault diagnosis

New non-destructive method for testing the strength of cement mortar material based on vibration frequency of steel bar: Theory and experiment

Timely and accurately obtaining the strength of pouring material, e.g., concrete, cement mortar, is of great significance for engineering construction. In this paper, a non-destructive, economical and accurate strength detection method that suites for on-site using is proposed for the steel bar cement mortar material. The method based on the relationship between the vibration frequency of the steel bar and the properties of the mortar material, which is obtained by solving the Euler-Bernoulli beam problem. Both Particle Flow Code (PFC) software simulation (calibrated) and Split Hopkinson pressure Bar experiment on test samples of cement mortar and steel bar were performed to verify the theoretically obtained relationship. Studies on samples of various aggregate ratio further confirmed such correspondence. Results show that the dynamic stiffness of the cement mortar material dominates the calculation of the vibration frequency of steel bar, while the combined effect of the density, length, elastic modulus, inertia moment of the steel bar can be safely ignored. A single-valued mapping relation exists in between the dynamic stiffness coefficient and the Uniaxial Compressive Strength (UCS) of the cement mortar sample, i.e., increased dynamic stiffness coefficient with increasing UCS. Both experimental and predicted results showed a linear relationship between the vibration frequency of the steel bar and the strength of the mortar material. Fitted linear relations were proposed with coefficients depending on sample size and aggregate ratio and might serve as a good indicator for the strength of the mortar material. Further studies on the effect of internal defects of the mortar materials as well as on samples of more size and aggregate ratio are required to make the proposed method a practical too

Genomic Analyses Reveal Mutational Signatures and Frequently Altered Genes in Esophageal Squamous Cell Carcinoma

Esophageal squamous cell carcinoma (ESCC) is one of the most common cancers worldwide and the fourth most lethal cancer in China. However, although genomic studies have identified some mutations associated with ESCC, we know little of the mutational processes responsible. To identify genome-wide mutational signatures, we performed either whole-genome sequencing (WGS) or whole-exome sequencing (WES) on 104 ESCC individuals and combined our data with those of 88 previously reported samples. An APOBEC-mediated mutational signature in 47% of 192 tumors suggests that APOBEC-catalyzed deamination provides a source of DNA damage in ESCC. Moreover, PIK3CA hotspot mutations (c.1624G>A [p.Glu542Lys] and c.1633G>A [p.Glu545Lys]) were enriched in APOBEC-signature tumors, and no smoking-associated signature was observed in ESCC. In the samples analyzed by WGS, we identified focal (<100 kb) amplifications of CBX4 and CBX8. In our combined cohort, we identified frequent inactivating mutations in AJUBA, ZNF750, and PTCH1 and the chromatin-remodeling genes CREBBP and BAP1, in addition to known mutations. Functional analyses suggest roles for several genes (CBX4, CBX8, AJUBA, and ZNF750) in ESCC. Notably, high activity of hedgehog signaling and the PI3K pathway in approximately 60% of 104 ESCC tumors indicates that therapies targeting these pathways might be particularly promising strategies for ESCC. Collectively, our data provide comprehensive insights into the mutational signatures of ESCC and identify markers for early diagnosis and potential therapeutic targets