Fabrication of calix[4]pyrrole nanofilms at the glassy carbon surface and their characterization by spectroscopic, optic and electrochemical methods

meso-Octamethylcalix[4]pyrrole (CP) and meso-heptaethylcalix[4]pyrrole-meso-4-aminophenyl (4APCP) modified glassy carbon (GC) electrodes were prepared by the electrochemical oxidation in acetonitrile solution. Binding of the calix[4]pyrroles with the glassy carbon surface was investigated that it is through the etheric linkage revealed from the reflection-absorption infrared spectroscopy (RAIRS). Surface films of CP and 4APCP were investigated by cyclic voltammetry (CV), ellipsometry, X-ray photoelectron spectroscopy, RAIRS and the contact angle measurements. The thicknesses of the films were determined by ellipsometry which confirmed that the film was multilayer and homogeneous over the surface. Ellipsometric measurements also provided that the CP and 4APCP film thicknesses were 2.49 nm and 4.58 nm for 6 CV cycle modification, corresponding to 66 μF/cm² and 106 μF/cm² capacitances obtained by CV. The wetting behavior was examined by contact angle measurements and found that the hydrophobicity of the GC-4APCP surface was higher than that of GC-CP, probably due to the aromatic meso substituent present in the former.     

Ab initio and DFT study on 1,4-dinitroglycoluril configurational isomers: cis-DINGU and trans-DINGU

cis-1,4-Dinitroglycoluril (1,4-dinitrotetrahydroimidazo[4,5-d]imidazole-2,5-(1H,3H)-dione, C(4)H(4)N(6)O(6), known as DINGU in the literature) is an important explosive regarded as one of the potential ingredients for LOVA (low vulnerability ammunition) applications. However, there is no study concerning trans-DINGU, to the best of our knowledge. Thus, in the present study the structural and electronic properties of the configurational isomers of DINGU (cis- and trans-isomers) have been investigated by performing density functional theory (DFT) calculations at B3LYP/6-31G(d,p), UB3LYP/6-31G(d,p) levels and also ab initio calculations at RHF/6-31G(d,p) and UHF/6-31G(d,p) levels. The optimized geometries, vibrational frequencies, electronic structures, and some thermodynamical values for the presently considered DINGU isomers have been obtained in their ground states. Comparing the calculated energy data (total electronic energy, heat of formation values and homolytic bond dissociation values of N-NO(2)) and the calculated bond lengths, cis-DINGU was found to be a more stable molecule than the trans-isomer.     

PETROLEUM AT THE ROOF OF THE WORLD: The geological evolution of the Tibet (Qinghai-Xizang) Plateau Part II

Abundant field data collected within the past twelve years or so show that all published explanations for the origin of this 2.4MM sq. km region violates some of these data. Among them, one fact is of paramount importance. This is the discovery that none of the great east-west fracture zones is a boundary between different, but coeval, lithofacies. Instead, several major facies boundaries (in rocks of various ages) form a zigzag pattern across the various blocks of the region. This fact, in turn, means that most published tectonic interpretations, including those of plate tectonics, are incorrect.
In Part 2 of this paper, the Authors now point out that the recently-proposed surge-tectonics hypothesis explains all field data. If the surge-tectonics hypothesis is correct, most of the Tibetan Plateau, including its Cambrian-through-Tertiary section, is prospective. They conclude, therefore, that Tibet could eventually become a major petroleum-producing province of the world.     

Evaluation of cross-track illumination in EO-1 Hyperion imagery for lithological mapping

Hyperspectral remote sensing data is a powerful tool for discriminating lithological units and for the preparation of mineral maps for alteration studies. The spaceborne hyperspectral Hyperion sensor, despite its narrow swath width (～7.5 km), possesses great potential with its 196 channels within the wavelength range 426.82–2395.50 nm. Although it has many advantages such as low cost and on-demand coverage, much uncertainty exists in the utility of its applications. For example, poor signal-to-noise ratio, the presence of sensor-specific defects and thicker atmospheric column due to its spaceborne platform makes certain environmental and geological applications difficult or impossible. In this article we demonstrate these calibration-related uncertainties, which are manifest from the preprocessing stage to the classification stage. In addition, the intimate mixing of minerals within specific targets, for example within individual outcropping lithological units or endmembers, adds uncertainty to our spectral discrimination results. The aim of this study was to develop and evaluate an approach for geological mapping of outcrops with Earth Observing-1 (EO-1) Hyperion data. Atmospheric corrections and correction for cross-track illumination (CTI) variations (smile) were determined at different wavelength regions: the visible–near-infrared (VNIR; 420–1000 nm) and shortwave infrared (SWIR; 1000–2400 nm) regions. Our methodology was tested in a selected site at Central Anatolia, Turkey containing minimal vegetation cover. The results obtained from the image analyses were then compared and assessed with field observations and spectral measurements.     

Model selection in omnivariate decision trees using Structural Risk Minimization

As opposed to trees that use a single type of decision node, an omnivariate decision tree contains nodes of different types. We propose to use Structural Risk Minimization (SRM) to choose between node types in omnivariate decision tree construction to match the complexity of a node to the complexity of the data reaching that node. In order to apply SRM for model selection, one needs the VC-dimension of the candidate models. In this paper, we first derive the VC-dimension of the univariate model, and estimate the VC-dimension of all three models (univariate, linear multivariate or quadratic multivariate) experimentally. Second, we compare SRM with other model selection techniques including Akaike’s Information Criterion (AIC), Bayesian Information Criterion (BIC) and cross-validation (CV) on standard datasets from the UCI and Delve repositories. We see that SRM induces omnivariate trees that have a small percentage of multivariate nodes close to the root and they generalize more or at least as accurately as those constructed using other model selection techniques.     

Endogenous Effects of Hubbing on Flow Intensities

Location of hub facilities and the allocation decisions in transport networks endogenously affect both the flow intensities and the transportation costs. Since the introduction of the hub location problem to the operations research literature in mid-1980s, many researchers investigated different ways of modelling the effects of hub facilities on the transportation costs. On the other hand, there has been very limited research on their effect on the flow intensities. This study proposes a new approach, inspired by the Bass diffusion model, to forecast the change in the demand patterns generated at different locations as a result of the placement of new hubs. This new model is used in the context of the uncapacitated single allocation p-hub median problem to investigate the effects of endogenous attraction, caused by the spatial interaction of present hubs, on future hub location decisions. Computational results indicate that the location and allocation decisions may be greatly affected when these forecasts are taken into account in the selection of future hub locations.     

A new approach to the manufacturing of elemental boron from boron oxide by carbon monoxide

Elemental boron is one of the most valuable high-tech boron products and it has highest energy density 14 kcal/g in the world for this type of product. With the rapid advancements in technology in recent years, a demand has grown for a light materials with functionality and excellent properties such as high hardness, high melting point, high strength, high chemical resistance and nuclear characteristics that can be used in the fields of aerospace, aviation, automotive and solar cells. In this study boron oxide was reduced using carbon monoxide via a batch system to produce elemental boron. To determine the most suitable conditions for the reduction reaction different temperatures and different CO/B₂O₃ mol ratio parameters were studied. As a result of thermodynamic calculations for the most efficient parameters for reaction temperature was 140–210 °C and the CO/B₂O₃ mol ratio being studied was 3/1 and 2/1 for the batch system. Boron oxide reduction was performed by carbon monoxide gas with the pressure set at 10 bar. Characterization of the product was carried out by using X-Ray Diffractometer (XRD), Fourier Transform Infrared Spectroscopy (FT-IR) and Scanning Electron Microscopy (SEM) at optimum temperature and mol ratio (140 °C and 3/1). Boron phase was seen in both XRD and FT-IR analysis. Also, SEM analysis was performed in order to observe morphological structure of elemental boron.     

In-plane face orientation estimation in still images

This paper addresses a fine in-plane (roll) face orientation estimation for a perspective face analysis algorithm that requires normalized frontal faces. As most of the face analysers (e.g., gender, expression, and recognition) need frontal up-right faces, there is a clear need for the precise roll estimation, as precise face normalization has an important role in classification methods. The in-plane orientation estimation algorithm is constructed on top of regular Viola-Jones frontal face detector. When a face is detected for the first time, it is rotated with respect to the face origin to find the boundaries of the detection. Mean value of these angles is said to be the measurement of the in-plane rotation of the face. Since we only need a face detection algorithm, the proposed method can work effectively on very small sized faces where traditional landmark (eye, mouth) or planar detection based estimations fail. Experiments on controlled and unconstrained large-scale datasets (CMU Rotated, YouTube, Boston University Face Tracking, Caltech, FG-NET Aging, BioID and Manchester Talking-Face) showed that the proposed method is robust to various settings for in-plane face orientation estimation in terms of RMSE and MAE. We achieved less than ±3.5 ^° mean absolute error for roll estimation which proves that the accuracy of the proposed method is comparable to that of the state-of-the-art tracking based approaches for the roll estimation.     

Software defect prediction using Bayesian networks

There are lots of different software metrics discovered and used for defect prediction in the literature. Instead of dealing with so many metrics, it would be practical and easy if we could determine the set of metrics that are most important and focus on them more to predict defectiveness. We use Bayesian networks to determine the probabilistic influential relationships among software metrics and defect proneness. In addition to the metrics used in Promise data repository, we define two more metrics, i.e. NOD for the number of developers and LOCQ for the source code quality. We extract these metrics by inspecting the source code repositories of the selected Promise data repository data sets. At the end of our modeling, we learn the marginal defect proneness probability of the whole software system, the set of most effective metrics, and the influential relationships among metrics and defectiveness. Our experiments on nine open source Promise data repository data sets show that response for class (RFC), lines of code (LOC), and lack of coding quality (LOCQ) are the most effective metrics whereas coupling between objects (CBO), weighted method per class (WMC), and lack of cohesion of methods (LCOM) are less effective metrics on defect proneness. Furthermore, number of children (NOC) and depth of inheritance tree (DIT) have very limited effect and are untrustworthy. On the other hand, based on the experiments on Poi, Tomcat, and Xalan data sets, we observe that there is a positive correlation between the number of developers (NOD) and the level of defectiveness. However, further investigation involving a greater number of projects is needed to confirm our findings.     

Synthesis,Characterization, and Thermal Degradation of Oligo-2-[(4-Chlorophenyl) Imino Methylene] Phenol and Its Oligomer-Metal Complexes

The oxidative polycondensation reaction conditions of 2-[(4-chlorophenyl) imino methylene] phenol (CPIMP) were studied by air O₂ and NaOCl oxidants at various temperatures and times. Optimum reaction conditions of air O₂ and NaOCl were determined for CPIMP. Oligo-2-[(4-chlorophenyl) imino methylene] phenol (OCPIMP) was synthesized from the oxidative polycondensation of CPIMP with air O₂ and NaOCl in alkaline medium between 50 and 90°C. The number-average molecular weight (M_n) weight-average molecular weight (M_w) and polydispersity index (PDI) values of OCPIMP were found to be 470 g mol^?1, 895 g mol^?1, and 1.90, using NaOCl, and 455 g mol^?1, 765 g mol^?1, and 1.68, using air O₂, respectively. At the optimum reaction conditions, the yield of OCPIMP was found to be 62.80% (for air O₂ oxidant) and 87.50% (for NaOCl oxidant). The OCPIMP was characterized by ¹H-NMR, FT-IR, UV-Vis and elemental analysis. The thermogravimetric (TGA)-DTA analyses were shown to be stable of OCPIMP and its oligomer metal complexes (such as Co⁺², Ni⁺², and Cu⁺²) against thermo-oxidative decomposition. The weight loss of OCPIMP and its oligomer metal complexes (such as Co⁺², Ni⁺², and Cu⁺²) were found to be 98%, 85%, 80%, and 82%, respectively, at 1000°C.