Reconstruction and rehabilitation of short-range, high-velocity gunshot injury to the lower face: a case report

BACKGROUND: Germ cell tumors (GCTs) and their metastases may be found in numerous sites that are accessible to cytologic sampling, and many are responsive to chemotherapy. METHODS: The authors reviewed 20 examples of GCT cytology from 16 males and 3 females ranging in age from 1.5 to 61 years (median, 34 years). With two exceptions, one benign cystic ovarian teratoma in which intraoperative cytology was used to diagnose an associated adult-type carcinoma and one undescended testis in which seminoma presented as an abdominal mass, the material reviewed included no examples of primary gonadal GCT. RESULTS: The authors studied 7 primary and 13 metastatic GCTs; these studies were based on 13 in vivo aspirations, 4 intraoperative preparations, and 3 samples of body cavity fluids. All samples were correctly interpreted as malignant, and only one was incorrectly classified as a non-GCT malignancy. CONCLUSIONS: Clinical and cytologic findings are useful in the diagnosis of GCTs and their metastases. Incorrect interpretation of these neoplasms as poorly differentiated malignancies of other types may deprive the patient of effective chemotherapy. Air-dried, Romanowsky-stained smear material and cell block sections may contribute to the resolution of diagnostic dilemmas.     

A Wavelet-ANFIS Hybrid Model for Groundwater Level Forecasting for Different Prediction Periods

Artificial neural network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) have an extensive range of applications in water resources management. Wavelet transformation as a preprocessing approach can improve the ability of a forecasting model by capturing useful information on various resolution levels. The objective of this research is to compare several data-driven models for forecasting groundwater level for different prediction periods. In this study, a number of model structures for Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS), Wavelet-ANN and Wavelet-ANFIS models have been compared to evaluate their performances to forecast groundwater level with 1, 2, 3 and 4 months ahead under two case studies in two sub-basins. It was demonstrated that wavelet transform can improve accuracy of groundwater level forecasting. It has been also shown that the forecasts made by Wavelet-ANFIS models are more accurate than those by ANN, ANFIS and Wavelet-ANN models. This study confirms that the optimum number of neurons in the hidden layer cannot be always determined by using a specific formula but trial-and-error method. The decomposition level in wavelet transform should be determined according to the periodicity and seasonality of data series. The prediction of these models is more accurate for 1 and 2 months ahead (for example RMSE?=?0.12, E?=?0.93 and R ²?=?0.99 for wavelet-ANFIS model for 1 month ahead) than for 3 and 4 months ahead (for example RMSE?=?2.07, E?=?0.63 and R ²?=?0.91 for wavelet-ANFIS model for 4 months ahead).     

Landslide susceptibility mapping of the Sea to Sky transportation corridor, British Columbia, Canada: comparison of two methods

The Sea to Sky corridor stretches over a distance of 135?km into British Columbia’s Coast Mountains. The corridor has witnessed hundreds of historical and pre-historic landslides. In the last 154?years, 155 landslide events have been reported. The most common types of landslides are rockfalls and debris flows, which are small in volume, but can be quite damaging. These are more abundant in the southern part of the corridor where infrastructure is built close to steep slopes. Two different methods were adapted to create debris flow and rockfall/rock slide susceptibility maps. Both qualitative heuristic and fuzzy logic susceptibility maps showed a similar distribution of susceptibility zones, especially high susceptibility. Correlation of high susceptibility zones with occurrence of historical and mapped geological landslide events was very good. Success rate curves were calculated for extrapolated zones of initiation for debris flow and rockfall/rock slide deposits. Success rate curves were better for debris flow than rockfall/rockslide maps.     

Piperazine and methyldiethanolamine interrelationships in CO2 absorption by aqueous amine mixtures. Part II—Saturation rates of mixed reagent solutions

This work is a companion to a previous article, Part I, published in The Canadian Journal of Chemical Engineering, dealing with CO₂ absorption in aqueous solutions containing a single aminic reagent (specifically methyldiethanolamine (MDEA) or piperazine (PZ)). In this second part, different PZ/MDEA mixtures are experimentally studied and their performances are compared with that of the single reagents. It is indeed well known that small quantities of PZ added to MDEA aqueous solutions are sufficient to obtain a significant improvement in the kinetics of the process. PZ is considered an activator or promoter for MDEA, but the mechanism of this synergy has still not been clearly demonstrated. The aim of this study is an attempt to understand how PZ and MDEA can interact by experimentally analyzing this beneficial mutual effect and by explaining it with the help of a suitable yet not complex model. We believe that the involved chemistry is not more complex than that reported in Part I for the single reagents. According to our findings, it is MDEA that enhances the action of PZ, as opposed to what many authors claim. Moreover, our results seem to rule out the existence of any PZ shuttle effect.     

Boundary layer instability of the natural convection flow on a uniformly heated vertical plate

Direct numerical simulation is employed to investigate the two-dimensional boundary layer instability of a natural convection flow on a uniformly heated vertical plate submerged in a homogeneous quiescent environment. A Boussinesq fluid with Prandtl numbers of Pr = 0.733 (air) and 6.7 (water), in the local Rayleigh number range 0 ? Ra_x ? 2.4 × 10¹⁰, is studied. Controlled low amplitude numerical disturbances introduced into the base flow excite unstable travelling waves, with the resulting waves tracked and analyzed as they travel up the boundary layer. The numerical simulation readily reproduced what is predicted by the parallel linear stability theory for the two dimensional mode relatively short wave spectrum, but not for some parts of the long wave spectrum. Critical Rayleigh numbers have been obtained separately for both the temperature and velocity signals using the numerical results, and shown to be in good agreement with each other provided the data is renormalized using the boundary layer scalings of Sparrow and Greg [1]. It has been shown that the disturbance behavior depends on the Prandtl and Rayleigh numbers, the excitation frequency and to a lesser extent the prescribed thermal coupling at the plate.     

Merger of Energetic Affinity and Optimal Geometry Provides New Class of Boron Nitride Based Sorbents with Unprecedented Hydrogen Storage Capacity

Hydrogen is an ideal synthetic fuel because it is lightweight, abundant and its oxidation product (water) is environmentally benign. However, its utilization is impeded by the lack of an efficient storage device. A new building block approach is proposed for an exhaustive search of optimal hydrogen uptakes in a series of low density boron nitride (BN) nanoarchitectures via extensive 3868 ab initio‐based multiscale simulations. By probing various geometries, temperatures, pressures, and doping ratios, these results demonstrate a maximum uptake of 8.65 wt% at 300 K, the highest hydrogen uptake on sorbents at room temperature without doping. Li⁺ doping of the nanoarchitectures offers a set of optimal combinations of gravimetric and volumetric uptakes, surpassing the US Department of Energy targets. These findings suggest that the merger of energetic affinity and optimal geometry in BN building blocks overcomes the intrinsic limitations of sorbent materials, putting hybrid BN nanoarchitectures on equal footing with hydrides while demonstrating a superior capacity‐kinetics–thermodynamics relationship.     

Membrane heat exchanger in HVAC energy recovery systems, systems energy analysis

The thermal performance of an enthalpy/membrane heat exchanger is experimentally investigated. The heat exchanger utilizes a 60gsm Kraft paper as the heat and moisture transfer surface for HVAC energy recovery. The heat exchanger sensible, latent and total effectiveness have been determined through temperature and moisture content measurements. The annual energy consumption of an air conditioner coupled with an enthalpy/membrane heat exchanger is also studied and compared with a conventional air conditioning cycle using in-house modified HPRate software. The heat exchanger effectiveness are used as thermal performance indicators and incorporated in the modified software. Energy analysis showed that an air conditioning system coupled with a membrane heat exchanger consumes less energy than a conventional air conditioning system in hot and humid climates where the latent load is high. It has been shown that in humid climate a saving of up to 8% in annual energy consumption can be achieved when membrane heat exchanger is used instead of a conventional HVAC system.     

Optimization of electromagnetic phased-arrays for hyperthermia via magnetic resonance temperature estimation

A technique for the optimization of electromagnetic annular phased arrays (APAs) for therapeutic hyperthermia has been developed and implemented. The controllable inputs are the amplitudes and phases of the driving signals of each element of the array. Magnetic resonance imaging (MRI) is used to estimate noninvasively the temperature distribution based on the temperature dependence of the proton resonance frequency (PRF). A parametric model of the dynamics that couple the control inputs to the resultant temperature elevations is developed based on physical considerations. The unknown parameters of this model are estimated during a pretreatment identification phase and can be continuously updated as new measurement data become available. Based on the parametric model, a controller automatically chooses optimal phases and amplitudes of the driving signals of the APA. An advantage of this approach to optimizing the APA is that no a priori information is required, eliminating the need for patient-specific computational modeling and optimization. Additionally, this approach represents a first step toward employing temperature feedback to make the optimization of the APA robust with respect to modeling errors and physiological changes. The ability of the controller to choose therapeutically beneficial driving amplitudes and phases is demonstrated via simulation. Experimental results are presented which demonstrate the ability of the controller to choose optimal phases for the APA using only information from magnetic resonance thermometry (MRT).     

A comparison of classification algorithms using Landsat-7 and Landsat-8 data for mapping lithology in Canada’s Arctic

To map Arctic lithology in central Victoria Island, Canada, the relative performance of advanced classifiers (Neural Network (NN), Support Vector Machine (SVM), and Random Forest (RF)) were compared to Maximum Likelihood Classifier (MLC) results using Landsat-7 and Landsat-8 imagery. A ten-repetition cross-validation classification approach was applied. Classification performance was evaluated visually and statistically using the global classification accuracy, producer’s and user’s accuracies for each individual lithological/spectral class, and cross-comparison agreement. The advanced classifiers outperformed MLC, especially when training data were not normally distributed. The Landsat-8 classification results were comparable to Landsat-7 using the advanced classifiers but differences were more pronounced when using MLC. Rescaling the Landsat-8 data from 16 bit to 8 bit substantially increased classification accuracy when MLC was applied but had little impact on results from the advanced classifiers.     

First-Principles Study of Elastic Constants and Interlayer Interactions of Complex Hydrated Oxides: Case Study of Tobermorite and Jennite

It is a common perception that layered materials are soft in the interlayer direction. Herein, we present results of first-principles calculations of the structure and elastic constants of a class for hydrated oxides, tobermorite, and jennite, which illustrate that this is not the case, if (1) the interlayer distance is such that coulombic interlayer interactions become comparable to the iono-covalent intralayer interactions and (2) the existence of interlayer ions and water molecules do not shield the coulombic interlayer interactions. In this case, the mechanically softest directions are two inclined regions that form a hinge mechanism. The investigated class of materials and results are relevant to chemically complex hydrated oxides such as layered calcium–silicate–hydrates (C–S–H), the binding phase of all concrete materials, and the principle source of their strength and stiffness. In addition, the first-principles results may serve as a benchmark for validating empirical force fields required for the analysis of complex calcio–silicate oxides.