A new texture and shape based technique for improving meningioma classification

Over the past decade, computer‐aided diagnosis is rapidly growing due to the availability of patient data, sophisticated image acquisition tools and advancement in image processing and machine learning algorithms. Meningiomas are the tumors of brain and spinal cord. They account for 20% of all the brain tumors. Meningioma subtype classification involves the classification of benign meningioma into four major subtypes: meningothelial, fibroblastic, transitional, and psammomatous. Under the microscope, the histology images of these four subtypes show a variety of textural and structural characteristics. High intraclass and low interclass variabilities in meningioma subtypes make it an extremely complex classification problem. A number of techniques have been proposed for meningioma subtype classification with varying performances on different subtypes. Most of these techniques employed wavelet packet transforms for textural features extraction and analysis of meningioma histology images. In this article, a hybrid classification technique based on texture and shape characteristics is proposed for the classification of meningioma subtypes. Meningothelial and fibroblastic subtypes are classified on the basis of nuclei shapes while grey‐level co‐occurrence matrix textural features are used to train a multilayer perceptron for the classification of transitional and psammomatous subtypes. On the whole, average classification accuracy of 92.50% is achieved through the proposed hybrid classifier; which to the best of our knowledge is the highest. Microsc. Res. Tech. 77:862–873, 2014. © 2014 Wiley Periodicals, Inc.     

Effect of high temperature and the role of sulfate on adsorption behavior and effectiveness of AMPS®‐based cement fluid loss polymers

The fluid loss control performance of 2‐acrylamido‐2‐methylpropane sulfonic acid (AMPS®)‐based copolymers added to cement slurries was studied at 27 and 100°C, respectively. It was found that effectiveness of these fluid loss additives solely relies on achievement of a high adsorbed amount on the surface of cement. At elevated temperature (100°C), CaAMPS®‐N,N‐dimethyl acrylamide copolymer (CaAMPS®‐co‐NNDMA) exhibits reduced adsorption and hence decreased fluid loss control of the cement slurry. The reason behind this behavior is poor calcium binding capability of the sulfonate anchor groups, which coordinate with calcium atoms present on the mineral surface. Whereas, an increase in the sulfate concentration present in cement pore solution instigates partial coiling of CaAMPS®‐co‐NNDMA and causes only a slight influence on the performance of this copolymer. The elevated sulfate content results from thermal degradation of ettringite, a cement hydrate mineral produced during the early stages of cement hydration. Incorporation of minor amounts (～ 1.3 mol %) of maleic anhydride into this copolymer produces a terpolymer, which exhibits higher and more stable adsorption, even at high temperature. This effect is owed to the presence of homopolymer blocks of polycarboxylates distributed along the polymer trunk. On mineral surfaces, they present much stronger anchor groups than sulfonate functionalities, as evidenced by their higher calcium binding capability. Consequently, fluid loss performance of CaAMPS®‐co‐NNDMA‐co‐MA is little affected by temperature. Understanding the influence of temperature on the physicochemical interactions occurring between additives and the mineral surface can help to design more effective admixtures suitable for high temperature applications. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2011     

Polyelectrolyte complexes from polyethylene imine/acetone formaldehyde sulfite polycondensates: A novel reagent for effective fluid loss control of oil well cement slurries

When used by itself, polyethylene imine (PEI) does not perform well as cement fluid loss additive. Its combination with acetone formaldehyde sulfite (AFS) polycondensate, however, exhibits excellent filtration control. The mechanism underlying this synergistic effect was studied and the conditions producing best results were determined. For optimum performance, PEI and AFS must be reacted with each other to yield a polyelectrolyte complex (PEC) (d ～ 5–10 μm), which effectively plugs the pores of the cement filter cake. Composition, size, and effectiveness of the PEC are strongly influenced by the anionic charge amount of the AFS dispersant. Ionic interactions between cationic imine functionalities of PEI and anionic sulfonate groups existing in AFS were confirmed by conductivity, infrared, zeta potential, and particle size measurements. For AFS samples possessing different degrees of sulfonation, the largest particle size and hence best fluid loss performance of the PEC was found to occur at a PEI:AFS molar ratio, which corresponds to neutral charge. Occurrence of large PEC particles (d ～ 5 μm) within the cement filter cake pores was visualized by scanning electron microscopy, and their stability in highly alkaline cement pore solution was confirmed by particle size measurement. Other anionic polyelectrolytes may be used to yield such PECs with PEI to provide effective fluid loss control for cement slurries. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2011     

Intergenerational family predictors of the Black–White achievement gap.

The authors examined intergenerational family predictors of the Black–White achievement gap among 4,406 adolescents from the National Longitudinal Survey of Youth. An intergenerational model of the process by which family factors contribute to the achievement gap was also tested. The results showed that the ethnic gaps in socioeconomic status (SES) and achievement had significantly reduced over the past few generations. Moreover, measures of grandparent SES, mothers’ achievement, parent SES, and a comprehensive set of reliable parenting practices explained all of the ethnic differences in achievement scores. Parenting practices such as creating a school-oriented home environment, allowing adolescents to make decisions, and not burdening them with too many chores had particularly important effects on the achievement gap. The authors conclude that adjusting for these differences would eliminate the ethnic achievement gap. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Ligand‐Free Synthesis of Aluminum‐Doped Zinc Oxide Nanocrystals and their Use as Optical Spacers in Color‐Tuned Highly Efficient Organic Solar Cells

The color of polymer solar cells using an opaque electrode is given by the reflected light, which depends on the composition and thickness of each layer of the device. Metal‐oxide‐based optical spacers are intensively studied in polymer solar cells aiming to optimize the light absorption. However, the low conductivity of materials such as ZnO and TiO₂ limits the thickness of such optical spacers to tenths of nanometers. A novel synthesis route of cluster‐free Al‐doped ZnO (AZO) nanocrystals (NCs) is presented for solution processing of highly conductive layers without the need of temperature annealing, including thick optical spacers on top of polymer blends. The processing of 80 nm thick optical spacers based on AZO nanocrystal solutions on top of 200 nm thick polymer blend layer is demonstrated leading to improved photocurrent density of 17% compared to solar cells using standard active layers of 90 nm in combination with thin ZnO‐based optical spacers. These AZO NCs also open new opportunities for the processing of high‐efficiency color tuned solar cells. For the first time, it is shown that applying solution‐processed thick optical spacer with polymer blends of different thicknesses can process solar cells of similar efficiency over 7% but of different colors.     

Single‐Step Deposition of Au‐ and Pt‐Nanoparticle‐Functionalized Tungsten Oxide Nanoneedles Synthesized Via Aerosol‐Assisted CVD,and Used for Fabrication of Selective Gas Microsensor Arrays

Tungsten oxide nanostructures functionalized with gold or platinum NPs are synthesized and integrated, using a single‐step method via aerosol‐assisted chemical vapour deposition, onto micro‐electromechanical system (MEMS)‐based gas‐sensor platforms. This co‐deposition method is demonstrated to be an effective route to incorporate metal nanoparticles (NP) or combinations of metal NPs into nanostructured materials, resulting in an attractive way of tuning functionality in metal oxides (MOX). The results show variations in electronic and sensing properties of tungsten oxide according to the metal NPs introduced, which are used to discriminate effectively analytes (C₂H₅OH, H₂, and CO) that are present in proton‐exchange fuel cells. Improved sensing characteristics, in particular to H₂, are observed at 250 °C with Pt‐functionalized tungsten oxide films, whereas non‐functionalized tungsten oxide films show responses to low concentrations of CO at low temperatures. Differences in the sensing characteristics of these films are attributed to the different reactivities of metal NPs (Au and Pt), and to the degree of electronic interaction at the MOX/metal NP interface. The method presented in this work has advantages over other methods of integrating nanomaterials and devices, of having fewer processing steps, relatively low processing temperature, and no requirement for substrate pre‐treatment.     

Autonomous Parking-Lots Detection with Multi-Sensor Data Fusion Using Machine Deep Learning Techniques

The rapid development and progress in deep machine-learning techniques have become a key factor in solving the future challenges of humanity. Vision-based target detection and object classification have been improved due to the development of deep learning algorithms. Data fusion in autonomous driving is a fact and a prerequisite task of data preprocessing from multi-sensors that provide a precise, well-engineered, and complete detection of objects, scene or events. The target of the current study is to develop an in-vehicle information system to prevent or at least mitigate traffic issues related to parking detection and traffic congestion detection. In this study we examined to solve these problems described by (1) extracting region-of-interest in the images (2) vehicle detection based on instance segmentation, and (3) building deep learning model based on the key features obtained from input parking images. We build a deep machine learning algorithm that enables collecting real video-camera feeds from vision sensors and predicting free parking spaces. Image augmentation techniques were performed using edge detection, cropping, refined by rotating, thresholding, resizing, or color augment to predict the region of bounding boxes. A deep convolutional neural network F-MTCNN model is proposed that simultaneously capable for compiling, training, validating and testing on parking video frames through video-camera. The results of proposed model employing on publicly available PK-Lot parking dataset and the optimized model achieved a relatively higher accuracy 97.6% than previous reported methodologies. Moreover, this article presents mathematical and simulation results using state-of-the-art deep learning technologies for smart parking space detection. The results are verified using Python, TensorFlow, OpenCV computer simulation frameworks.     

Exposure of Mice to Thirdhand Smoke Modulates In Vitro and In Vivo Platelet Responses

Smoking is a risk factor for a variety of deleterious conditions, such as cancer, respiratory disease and cardiovascular disease. Thrombosis is an important and common aspect of several cardiovascular disease states, whose risk is known to be increased by both first- and secondhand smoke. More recently, the residual cigarette smoke that persists after someone has smoked (referred to as thirdhand smoke or THS) has been gaining more attention, since it has been shown that it also negatively affects health. Indeed, we have previously shown that 6-month exposure to THS increases the risk of thrombogenesis. However, neither the time-dependence of THS-induced thrombus formation, nor its sex dependence have been investigated. Thus, in the present study, we investigated these issues in the context of a shorter exposure to THS, specifically 3 months, in male and female mice. We show that the platelets from 3-month THS-exposed mice exhibited enhanced activation by agonists. Moreover, we also show that mice of both sexes exposed to THS have decreased tail bleeding as well as decreased thrombus occlusion time. In terms of the role of sex, intersex disparities in thrombus development and hemostasis as well as in platelet aggregation were, interestingly, observed. Together, our findings show that exposing mice to THS for 3 months is sufficient to predispose them to thrombosis; which seems to be driven, at least in part, by an increased activity in platelets, and that it does not manifest equally in both sexes.