Investigation of wood pellets self-heating kinetics and thermal runaway phenomena using lab scale experiments

The phenomena of spontaneous combustion and thermal runaway in wood pellets storage were investigated using lab-scale experiments in the temperature range of 100–200 °C. The critical temperatures were determined for four sizes of reactors. The kinetic parameters of the self-heating were determined using three methods, the Frank-Kamenetskii's method, crossing point method, and numerical curve fitting method. Mean values of activation energy (E) of 78.7 ±0.8 kJ/mol and self-heating rate constant (∆ _rhA) of (4.22 ±2.5) × 10 ⁶ kJ/(kg s) were obtained for four type of wood pellets (made from whitewood) samples from different pellet producers in British Columbia. Finally, a two-dimensional numerical model was developed to predict the temperature development during self-heating and the critical temperature for known sizes of reactors.     

Transforming Hand Drawn Wireframes into Front-End Code with Deep Learning

The way towards generating a website front end involves a designer settling on an idea for what kind of layout they want the website to have, then proceeding to plan and implement each aspect one by one until they have converted what they initially laid out into its Html front end form, this process can take a considerable time, especially considering the first draft of the design is traditionally never the final one. This process can take up a large amount of resource real estate, and as we have laid out in this paper, by using a Model consisting of various Neural Networks trained on a custom dataset. It can be automated into assisting designers, allowing them to focus on the other more complicated parts of the system they are designing by quickly generating what would rather be straightforward busywork. Over the past 20 years, the boom in how much the internet is used and the sheer volume of pages on it demands a high level of work and time to create them. For the efficiency of the process, we proposed a multi-model-based architecture on image captioning, consisting of Convolutional neural network (CNN) and Long short-term memory (LSTM) models. Our proposed approach trained on our custom-made database can be automated into assisting designers, allowing them to focus on the other more complicated part of the system. We trained our model in several batches over a custom-made dataset consisting of over 6300 files and were finally able to achieve a Bilingual Evaluation Understudy (BLEU) score for a batch of 50 hand-drawn images at 87.86%     

Salinomycin nanoparticles interfere with tumor cell growth and the tumor microenvironment in an orthotopic model of pancreatic cancer

Aims: Recently, salinomycin (SAL) has been reported to inhibit proliferation and induce apoptosis in various tumors. The aim of this study was to deliver SAL to orthotopic model of pancreatic cancer by the aid of poly(lactic-co-glycolic acid) (PLGA) nanoparticles (NPs).

Methods: The NPs were physico-chemically characterized and evaluated for cytotoxicity on luciferase-transduced AsPC-1 cells in vitro as well as implanted orthotopically into the pancreas of nude mice.

Results: SAL (3.5 mg/kg every other day) blocked tumor growth by 52% compared to the control group after 3 weeks of therapy. Western blotting of tumor protein extracts indicated that SAL treatment leads to up-regulation of E-cadherin, β-catenin, and transforming growth factor beta receptor (TGFβR) expressions in AsPC-1 orthotopic tumor. Noteworthy, immunofluorescence staining of adjacent tumor sections showed that treatment with SAL NPs cause significant apoptosis in the tumor cells rather than the stroma. Further investigations also revealed that TGFβR2 over-expression was induced in stroma cells after treatment with SAL NPs.

Conclusion: These results highlight SAL-loaded PLGA NPs as a promising system for pancreatic cancer treatment, while the mechanistic questions need to be subsequently tested.     

Traffic Queuing Management in the Internet of Things: An Optimized RED Algorithm Based Approach

Congestion control is one of the main obstacles in cyberspace traffic. Overcrowding in internet traffic may cause several problems; such as high packet hold-up, high packet dropping, and low packet output. In the course of data transmission for various applications in the Internet of things, such problems are usually generated relative to the input. To tackle such problems, this paper presents an analytical model using an optimized Random Early Detection (RED) algorithm-based approach for internet traffic management. The validity of the proposed model is checked through extensive simulation-based experiments. An analysis is observed for different functions on internet traffic. Four performance metrics are taken into consideration, namely, the possibility of packet loss, throughput, mean queue length and mean queue delay. Three sets of experiments are observed with varying simulation results. The experiments are thoroughly analyzed and the best packet dropping operation with minimum packet loss is identified using the proposed model.     

Fe3O4@FeSO4-MCM-41 Nanoparticles and Reusable Catalyst for the Synthesis of Quinoxalines in Solvent-free Conditions

Silicon - The direct condensation of diketones and 1,2-phenylenediamines was accomplished in the presence of magnetic MCM-41 supported ferrous sulfate (Fe3O4@FeSO4-MCM-41) as a nanosized solid acid...     

Enhancing liquid micromixing using low‐frequency rotating nanoparticles

Magnetic nanofluid actuation by rotating magnetic fields was proposed as a high‐performance tool for liquid mixing with enhanced micromixing features. A comparative study was conducted to evaluate the mixing index in T‐type mixers of magnetic and nonmagnetic fluids subject to static (SMF), oscillating (OMF), and rotating (RMF) magnetic fields. RMF excitation unveiled superior mixing indices with strong dependences to magnetic field frequency and content of magnetic nanoparticles. The impact of magnetic field types on micromixing was further examined at low and moderate Re numbers using the Villermaux–Dushman reaction and IEM micromixing model. The IEM‐inferred micromixing times were remarkably shorter by nearly four orders of magnitude in comparison with OMF and SMF excitations, and without magnetic field. The proposed mixing strategy is foreseen to complement innovative microfluidic devices with valuable mixing tools and methods for the diagnosis of the coupling between transport and intrinsic kinetics. © 2016 American Institute of Chemical Engineers AIChE J, 63: 337–346, 2017     

Synthesis of novel optically active poly(ester‐imide)s with benzophenone linkages by microwave‐assisted polycondensation

A new simple and rapid polycondensation reaction of 4,4′‐carbonyl‐bis(phthaloyl‐L ‐alanine)diacid chloride [N,N ′‐(4,4′‐carbonyldiphthaloyl)]bisalanine diacid chloride with several diphenols, such as bisphenol‐A, phenolphthalein, 1,8‐dihydroxyanthraquinone, 4,4′‐dihydroxybiphenyl, 1,5‐dihydroxynaphthalene and hydroquinone, in the presence of a small amount of a polar organic medium such as o‐cresol was performed using a domestic microwave oven. The polycondensation reaction proceeded rapidly and was almost complete within 12 min to give a series of poly(ester‐imide)s with inherent viscosities of about 0.35–0.58 dl g⁻¹. The resulting poly(ester‐imide)s were obtained in high yield and are optically active and thermally stable. All the above compounds have been fully characterized by IR spectroscopy, elemental analysis, inherent viscosity (η_inh), solubility test and specific rotation. Thermal properties of the poly(ester‐imide)s have been investigated using thermal gravimetric analysis (TGA). © 2000 Society of Chemical Industry     

Radiation dose to neonates undergoing X-ray imaging in special care baby units in Iran

Radiographic imaging has a significant role in the timely diagnosis of the diseases of neonates in intensive care units. The estimation of the dose received by the infants undergoing radiographic examination is of great importance, due to greater more radiosensitivity and longer life expectancy of the neonates and premature babies. In this study, the values of entrance skin dose (ESD), dose area products (DAPs), energy imparted (EI), whole-body dose, effective dose and risk of childhood cancer were estimated using three methods including direct method [using thermoluminescence dosimetry (TLD) chips], indirect method (using tube output) and Monte Carlo (MC) method (using MCNP4C code). In the first step, the ESD of the neonates was directly measured using TLD-100 chips. Fifty neonates, mostly premature, with different weights and gestational ages in five hospitals mostly suffering from respiratory distress syndrome and pneumonia were involved in this study. In the second step, the values of ESD to neonates were indirectly obtained from the tube output in different imaging techniques. The imaging room, incubator, neonates and other components were then simulated in order to obtain the ESD values using the MCNP4C code. Finally, the values of ESD assessed by the three methods were used for calculation of DAP, EI, whole-body dose, effective dose and risk of childhood cancer. The results indicate that the mean ESD per radiograph estimated by the direct, indirect and MC methods are 56.6±4.1, 50.1±3.1 and 54.5±3.3 μGy, respectively. The mean risk of childhood cancer estimated in this study varied between 4.21×10(-7) and 2.72×10(-6).     

Porosity and permeability prediction from well logs using an adaptive neuro-fuzzy inference system in a naturally fractured gas-condensate reservoir

Interpretation of petrophysical log is one of the most useful and important tools in petroleum geology. Well logs help determine the physical characteristics of a reservoir, such as lithology, porosity, permeability, producer regions and their depth and thickness, and also differentiating between oil and gas and water in a reservoir and defining hydrocarbon reserve. A continual record of the physical characteristics of rocks in various depths is called well logs. Petrophysical logs usually include gamma ray, spontaneous potential, resistance, density, neutron, nuclear magnetic resonance, and sonic. The purpose of this study is to determine those characteristics of the reservoir that cannot be specified directly through present measuring well logs, using an intelligent problem-solving system of neuro-fuzzy. In this study, porosity and permeability are determined as two of the most important reservoir characteristics having much influence on reservoir understanding, reservoir reserve, and capability of reservoir production. The system of determining reservoir characteristics (neuro-fuzzy) was tested on collected well log data from oil and gas fields in the south of Iran. The most important result obtained in this study is that if all data influencing one of the reservoir characteristics are presented to the neuro-fuzzy system, then this system will be an excellent model with low error for determining all of the complex characteristics of the reservoir. These produced intelligent systems predict porosity and permeability completely on training and testing data and the correlation coefficient is near 1 and normalized mean square error is near to zero. Engineers and researchers can predict the reservoir characteristics with very good precision by these intelligent systems. The results of this study prove that a neuro-fuzzy intelligent system is a very powerful tool for determining permeability and porosity at the wells of a naturally fractured gas condensate reservoir. It is the first time to predict porosity and permeability from well logs using adaptive neuro-fuzzy inference system in a naturally fractured gas-condensate reservoir in Khuff Formation (Kangan and Upper Dalan Formation), which is a heterogeneous formation with a wide range of permeability and porosity in the Middle East; this method predicts permeability and porosity precisely in this heterogeneous formation. The other novelty of this study is the choice of appropriate input parameters to determine porosity and permeability precisely. Because of the heterogeneous condition of naturally fractured gas-condensate reservoirs in Khuff Formation, the appropriate input parameters cause the system to train optimally and thus increase the system ability to estimate the output in various conditions precisely.     

Dynamic mechanical study of epoxy,epoxy/glass,and glass/epoxy/wood hybrid composites aged in various media

It was proposed and subsequently established that wrapping of red oak wood crossties with epoxy impregnated glass fiber composites will impart longer service life and better stiffness and strength characteristics to these hybrid ties than conventional ones and will help them better withstand environmental extremes. The objective was to understand the degrading effects of aqueous (distilled water), saline (NaCl), acidic (HCl), and alkaline (NaOH) solutions, as well as accelerated aging and freeze/thaw cycling environments on the dynamic and static mechanical properties of these hybrid materials (i.e., wood, wrapped with fiber reinforced resin) and their components. Also micrographs of composite samples, obtained through scanning electron microscopy (SEM), were studied to determine the failure mechanism of composite specimens aged in different environments. Results showed that immersion in aging media lowered the glass transition temperature (T_g) and enhanced apparent phase separation in the samples because of polymer plasticization. In water immersion, the T_g and the stiffness increased with time owing to continued resin curing. At ambient temperature, sustained load had little effect on the mechanical behavior of the aged samples. The extent of degradation was the least for samples aged in salt solution. Soaking in room‐temperature acid solution was most damaging to pure red oak wood samples. Six‐cycle aging did not damage the neat resin or the hybrid samples, whereas it damaged pure wood specimens. Therefore, the composite wrapping around the wood core of the hybrid sample protected it sufficiently, thereby preventing damage to the hybrid specimen during the aging process. POLYM. COMPOS., 2009. © 2008 Society of Plastics Engineers