The impact of metallic coagulants on the removal of organic compounds from oil sands process-affected water

Coagulation/flocculation (CF) by use of alum and cationic polymer polyDADMAC, was performed as a pretreatment for remediation of oil sands process-affected water (OSPW). Various factors were investigated and the process was optimized to improve efficiency of removal of organic carbon and turbidity. Destabilization of the particles occurred through charge neutralization by adsorption of hydroxide precipitates. Scanning electron microscope images revealed that the resultant flocs were compact. The CF process significantly reduced concentrations of naphthenic acids (NAs) and oxidized NAs by 37 and 86%, respectively, demonstrating the applicability of CF pretreatment to remove a persistent and toxic organic fraction from OSPW. Concentrations of vanadium and barium were decreased by 67-78% and 42-63%, respectively. Analysis of surface functional groups on flocs also confirmed the removal of the NAs compounds. Flocculation with cationic polymer compared to alum, caused toxicity toward the benthic invertebrate, Chironoums dilutus, thus application of the polymer should be limited.     

Electronic and structural properties of TiB2: Bulk, surface, and nanoscale effects

Titanium diboride (TiB₂), is a widely used hard material that comprises graphene-like layers of B and intercalated Ti atoms. Here we report the results of extensive first-principles calculations on key properties of bulk TiB₂, TiB₂ surfaces, and TiB₂ nanocrystals (NCs). The computational approach is first validated based on the agreement between calculated structural and electronic properties of bulk TiB₂ and available experimental and theoretical data. We then obtain the formation energies for several surface cuts and use these values to construct TiB₂ NCs based on the Wulff theorem. Finally, we demonstrate by studying the adsorption of small molecules that hydrogen and oxygen adatoms can be attached through strongly exothermic chemisorption reactions on TiB₂ surfaces. Likewise, water molecules bind on various TiB₂ surfaces and NC facets, with an energetic preference for the latter. The results are relevant to applications that depend on reactivity-related TiB₂ properties, for example resistance to corrosion and interactions with water-based solutions.     

A pattern recognition methodology for evaluation of load profiles and typical days of large electricity customers

This paper describes a pattern recognition methodology for the classification of the daily chronological load curves of each large electricity customer, in order to estimate his typical days and his respective representative daily load profiles. It is based on pattern recognition methods, such as k-means, self-organized maps (SOM), fuzzy k-means and hierarchical clustering, which are theoretically described and properly adapted. The parameters of each clustering method are properly selected by an optimization process, which is separately applied for each one of six adequacy measures. The results can be used for the short-term and mid-term load forecasting of each consumer, for the choice of the proper tariffs and the feasibility studies of demand side management programs. This methodology is analytically applied for one medium voltage industrial customer and synoptically for a set of medium voltage customers of the Greek power system. The results of the clustering methods are presented and discussed.     

An Adaptive Policy-Based Framework for Network Services Management

This paper presents a framework for specifying policies for the management of network services. Although policy-based management has been the subject of considerable research, proposed solutions are often restricted to condition-action rules, where conditions are matched against incoming traffic flows. This results in static policy configurations where manual intervention is required to cater for configuration changes and to enable policy deployment. The framework presented in this paper supports automated policy deployment and flexible event triggers to permit dynamic policy configuration. While current research focuses mostly on rules for low-level device configuration, significant challenges remain to be addressed in order to:a) provide policy specification and adaptation across different abstraction layers; and, b) provide tools and services for the engineering of policy-driven systems. In particular, this paper focuses on solutions for dynamic adaptation of policies in response to changes within the managed environment. Policy adaptation includes both dynamically changing policy parameters and reconfiguring the policy objects. Access control for network services is also discussed.     

Global Intrinsic Symmetries of Shapes

Although considerable attention in recent years has been given to the problem of symmetry detection in general shapes, few methods have been developed that aim to detect and quantify the intrinsic symmetry of a shape rather than its extrinsic, or pose‐dependent symmetry. In this paper, we present a novel approach for efficiently computing symmetries of a shape which are invariant up to isometry preserving transformations. We show that the intrinsic symmetries of a shape are transformed into the Euclidean symmetries in the signature space defined by the eigenfunctions of the Laplace‐Beltrami operator. Based on this observation, we devise an algorithm which detects and computes the isometric mappings from the shape onto itself. We show that our approach is both computationally efficient and robust with respect to small non‐isometric deformations, even if they include topological changes.     

As‐Killing‐As‐Possible Vector Fields for Planar Deformation

Cartoon animation, image warping, and several other tasks in two‐dimensional computer graphics reduce to the formulation of a reasonable model for planar deformation. A deformation is a map from a given shape to a new one, and its quality is determined by the type of distortion it introduces. In many applications, a desirable map is as isometric as possible. Finding such deformations, however, is a nonlinear problem, and most of the existing solutions approach it by minimizing a nonlinear energy. Such methods are not guaranteed to converge to a global optimum and often suffer from robustness issues. We propose a new approach based on approximate Killing vector fields (AKVFs), first introduced in shape processing. AKVFs generate near‐isometric deformations, which can be motivated as direction fields minimizing an “as‐rigid‐as‐possible” (ARAP) energy to first order. We first solve for an AKVF on the domain given user constraints via a linear optimization problem and then use this AKVF as the initial velocity field of the deformation. In this way, we transfer the inherent nonlinearity of the deformation problem to finding trajectories for each point of the domain having the given initial velocities. We show that a specific class of trajectories — the set of logarithmic spirals — is especially suited for this task both in practice and through its relationship to linear holomorphic vector fields. We demonstrate the effectiveness of our method for planar deformation by comparing it with existing state‐of‐the‐art deformation methods.