Book Review: Theorising Interpreting Studies

status: publishe

The Stefan problem for the Fisher-KPP equation with unbounded initial range

We consider the nonlinear Stefan problem \left \{ \begin{array} {ll} -d \Delta u=a u-b u^2 \;\; & \mbox{for } x \in \Omega (t), \; t>0, \\ u=0 \mbox{ and } u_t=\mu|\nabla_x u |^2 \;\;&\mbox{for } x \in \partial\Omega (t), \; t>0, \\ u(0,x)=u_0 (x) \;\; & \mbox{for } x \in \Omega_0, \end{array}\right. where $\Omega(0)=\Omega_0$ is an unbounded smooth domain in $\mathbb R^N$, $u_0>0$ in $\Omega_0$ and $u_0$ vanishes on $\partial\Omega_0$. When $\Omega_0$ is bounded, the long-time behavior of this problem has been rather well-understood by \cite{DG1,DG2,DLZ, DMW}. Here we reveal some interesting different behavior for certain unbounded $\Omega_0$. We also give a unified approach for a weak solution theory to this kind of free boundary problems with bounded or unbounded $\Omega_0$

High-efficiency capacitance performance from foam-like MnO2/polyaniline/carbon nanotube film hybrids

Flexible supercapacitor electrode materials based on carbon nanotube film have been successfully fabricated. Honeylike M nO2/polyaniline/Carbon nanotube fi lm hybrids (MnO2/PANI/CNTF) were manufactured via chemical oxidation polymerization and solution chemical reduction method. All electrochemical tests were carried out in a 1 M Na2SO4 electrolyte at a window voltage of -0.2- 0.8 V. The structures and morphology of the hybrids are characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM). Raman spectroscopy and X-ray photoelectron spectrometer (XPS). The electrochemical performance was examined by cyclic voltammetry (CV) and galvanostatic charge/discharge (GCD). MnO2/PANI/CNTF hybrids exhibit a specifi c capacitance of 186 F/g at a current density of 1 A/g, which is much higher than of pure CNTF (20 F/g). After 1000 cycles, the capacitance was reduced by only 9 % compare to 15 % for PANI/CNTF hybrids and 19% for MnO2 /CNTF

Modeling Volatile Organic Sulfur Compounds In Anaerobic Digestion

Anaerobic digestion is a common process for treatment of wastewater sludge from municipal sewage systems. Volatile sulfur compounds, including volatile organic sulfur compounds (VOSCs) and hydrogen sulfide, have been reported as the most odorous compounds in digestion emissions and impurities which can damage facilities for generation, transportation, storage, and utilization of biogas. There has been no comprehensive study on biological generation and degradation kinetics of VOSC or modeling VOSC behaviors through anaerobic sludge digestion. The goal of the present study was to establish a model for VOSC conversions in anaerobic sludge digestion which could facilitate quantitative analysis of VOSC emissions in anaerobic digestion. VOSCs and methionine were employed in dosed batch tests. VOSC conversion processes in anaerobic methionine digestion have been identified. The kinetics for the identified VOSC degradation and conversion processes were determined at 35 and 55 °C respectively. Mixed-second order kinetics were found to best fit the conversion processes. A model was established based on the identified processes and estimated kinetic constants. To extend the model to VOSC release in anaerobic sludge digestion, mesophilic and thermophilic incubations were conducted with four different sludge samples. The effects of temperature and sludge source on VOSC release patterns were assessed. It was found that an unidentified DMS generation mechanism was triggered in the mesophilic incubation of activated sludge in which iron was dosed. To apply the model which was established based on methionine degradation in sludge digestion, hydrolysis of particulate materials was incorporated. The model simulations for VOSC behavior in thermophilic batch incubation were able to represent the observed VOSC releases. However, the simulations could not well fit the observed VOSC release at 35 ° because the model did not include the unidentified DMS generation mechanism. Application of the model to bench-scale digesters was lack-of-fit. It may have been due to imprecise estimation of the degradable sulfur in the feed sludge. In addition, in the batch tests and digester operation the ratios of the raw and digested sludge were different. This might have resulted in different concentrations of the microorganisms which mediated biotransformations and hence resulted in different kinetic constants

Matrix Completion with Noise via Leveraged Sampling

Many matrix completion methods assume that the data follows the uniform distribution. To address the limitation of this assumption, Chen et al. \cite{Chen20152999} propose to recover the matrix where the data follows the specific biased distribution. Unfortunately, in most real-world applications, the recovery of a data matrix appears to be incomplete, and perhaps even corrupted information. This paper considers the recovery of a low-rank matrix, where some observed entries are sampled in a \emph{biased distribution} suitably dependent on \emph{leverage scores} of a matrix, and some observed entries are uniformly corrupted. Our theoretical findings show that we can provably recover an unknown $n\times n$ matrix of rank $r$ from just about $O(nr\log^2 n)$ entries even when the few observed entries are corrupted with a small amount of noisy information. Empirical studies verify our theoretical results

Development of a Respirable Dust Mitigation System for a High Longwall Face at Sihe Colliery in China â a Case Study

Dust is a major hazard in underground coal mines that threatens the work health and safety of coal miners. The dust issue becomes increasingly significant with the development of highly mechanized coal mining. This issue is particularly serious at the high longwall faces of the Sihe colliery in China as the concentration of dust, in particular respirable dust, at these faces far exceeds the regulatory dust limits. Field testing and computational fluid dynamics (CFD) simulations were conducted to understand the sources of dust generation and its dynamic movement in the #5301 longwall face of high-cutting height at the colliery. The investigation results showed that shearer generated dust was minimal during the coal cutting operation; that face spalling and chock movement were the main dust generating sources, causing significant contamination to the walkway; and that the majority of dust particles from the face (regardless of source) eventually disperse into the main gate, where the dust concentration was greater than 500 mg/m3. These findings were used to develop an effective coal dust mitigation system involving the installation of dust scrubbers, curtains, and venture and crescent sprays. The results of CFD modeling indicate that the dust concentration could be significantly reduced by adopting the new dust mitigation system

A Dual-view Attention Neural Network for Assigning Industrial Categories to Academic Patents

Industrial technology matching events are held by governmental institutions worldwide to promote patent transfer from universities to industries. When collecting academic patents for the matching events, governmental institutions lack professional knowledge for identifying academic patents suitable for various industries. Therefore, previous studies adopted International Patent Classification (IPC) codes assigned by patent examiners to represent patents and mined the industry-related cues through the mapping link between IPC codes and industry categories. However, IPC codes are too general to specifically represent the complex patents, leading to inaccurate tagging. The view of patent inventors (e.g., patent titles and abstracts) contains rich industry-related cues that benefit assigning industrial categories to academic patents. Therefore, we propose a dual-view attention neural network that learns low-dimensional patent representations from the views of patent examiners and inventors and merges the representations for classifying academic patents into suitable industrial categories. Experiments show that the proposed method outperforms benchmark methods

Modélisation du mécanisme de coalescence des grains de polymère

Dans le procédé du rotomoulage, le phénomène physique majeur lors de l’écoulement des poudres est la coalescence et densification des grains. La coalescence est la formation d’une seule particule elliptique à partir de deux particules sous l’effet de la température et des forces de tension surfacique. Nous intéressons dans cette étude en particulier au mécanisme de coalescence des grains de poudre de PVDF. Les résultats de cette étude permettent de déterminer des paramètres tel que la vitesse de la coalescence pour l’optimisation du procédé