A Multi-Criteria Route Selection Method for Vehicles Using Genetic Algorithms Based on Driver’s Preference

Wireless Personal Communications - Finding the best path between a given source and a destination in a road network is an important problem. It has its applications in various map services and...     

Let There be Light: Polymeric Micelles with Upper Critical Solution Temperature as Light‐Triggered Heat Nanogenerators for Combating Drug‐Resistant Cancer

Complete drug release and efficient drug retention are two critical factors in reversing drug resistance in cancer therapy. In this regard, polymeric micelles with an upper critical solution temperature (UCST) are designed as a new exploration to reverse drug resistance. The amphiphilic UCST‐type block copolymers are used to encapsulate photothermal agent IR780 and doxorubicin (DOX) simultaneously. The integrated UCST‐type drug nanocarriers show light‐triggered multiple synergistic effects to reverse drug resistance and are expected to kill three birds with one stone: First, owing to the photothermal effect of IR780, the nanocarriers will be dissociated upon exposure to laser irradiation, leading to complete drug release. Second, the photothermal effect‐induced hyperthermia is expected to avoid the efflux of DOX and realize efficient drug retention. Last but not least, photothermal ablation of cancer cells can be achieved after laser irradiation. Therefore, the UCST‐type drug nanocarriers provide a new strategy in reversing drug resistance in cancer therapy.     

Accuracy vs Efficiency Trade-offs in Optical Flow Algorithms

There have been two thrusts in the development of optical flow algorithms. One has emphasized higher accuracy; the other faster implementation. These two thrusts, however, have been independently pursued, without addressing the accuracy vs efficiency trade-offs. Although the accuracy–efficiency characteristic is algorithm dependent, an understanding of a general pattern is crucial in evaluating an algorithm as far as real-world tasks are concerned, which often pose various performance requirements. This paper addresses many implementation issues that have often been neglected in previous research, including temporal filtering of the output stream, algorithms' flexibility, and robustness to noise, subsampling, etc. Their impacts on accuracy and/or efficiency are emphasized. We present a survey of different approaches toward the goal of higher performance and present experimental studies on accuracy vs efficiency trade-offs. A detailed analysis of how this trade-off affects algorithm design is manifested in a case study involving two state-of-the-art optical flow algorithms: a gradient and a correlation-based method. The goal of this paper is to bridge the gap between the accuracy- and the efficiency-oriented approaches.     

Unsteady development of a deformable bubble rising in a quiescent liquid

An accurate finite-volume based numerical method for the simulation of an isothermal two-phase flow, consisting of a rising deformable bubble translating in a quiescent, unbounded liquid, is presented. This direct simulation method is built on a sharp interface concept and developed on an Eulerian, Cartesian fixed-grid with a cut-cell scheme and marker points to track the moving interface. The unsteady Navier–Stokes equations in both liquid and gas phases are solved separately. The mass continuity and momentum flux conditions are explicitly matched at the true surface phase boundary to determine the evolving interface shape and movement of the bubble. The highlights of this method are that it utilizes a combined Eulerian–Lagrangian approach, and is capable of treating the interface as a sharp discontinuity. A fixed underlying grid is used to represent the control volume. The interface, however, is denoted by a separate set of marker particles which move along with the interface. A quadratic curve fitting algorithm with marker points is used to yield smooth and accurate information of the interface curvatures. This numerical scheme can handle a wide range of density and viscosity ratios. The bubble is assumed to be spherical and at rest initially, but deforms as it rises through the liquid pool due to buoyancy. Additionally, the flow is assumed to be axisymmetric and incompressible. The bubble deformation and dynamic motion are characterized by the Reynolds number, the Weber number, the density ratio and the viscosity ratio. The effects of these parameters on the translational bubble dynamics and shape are given and the physical mechanisms are explained and discussed. Results for the shape, velocity profile and various forces acting on the bubble are presented here as a function of time until the bubble reaches terminal velocity. The range of Reynolds numbers investigated is 1 < Re < 100, and that of Weber number is 1 < We < 10.     

Aligned texture map creation for pose invariant face recognition

In last years, Face recognition based on 3D techniques is an emergent technology which has demonstrated better results than conventional 2D approaches. Using texture (180° multi-view image) and depth maps is supposed to increase the robustness towards the two main challenges in Face Recognition: Pose and illumination. Nevertheless, 3D data should be acquired under highly controlled conditions and in most cases depends on the collaboration of the subject to be recognized. Thus, in applications such as surveillance or control access points, this kind of 3D data may not be available during the recognition process. This leads to a new paradigm using some mixed 2D-3D face recognition systems where 3D data is used in the training but either 2D or 3D information can be used in the recognition depending on the scenario. Following this concept, where only part of the information (partial concept) is used in the recognition, a novel method is presented in this work. This has been called Partial Principal Component Analysis (P²CA) since they fuse the Partial concept with the fundamentals of the well known PCA algorithm. This strategy has been proven to be very robust in pose variation scenarios showing that the 3D training process retains all the spatial information of the face while the 2D picture effectively recovers the face information from the available data. Furthermore, in this work, a novel approach for the automatic creation of 180° aligned cylindrical projected face images using nine different views is presented. These face images are created by using a cylindrical approximation for the real object surface. The alignment is done by applying first a global 2D affine transformation of the image, and afterward a local transformation of the desired face features using a triangle mesh. This local alignment allows a closer look to the feature properties and not the differences. Finally, these aligned face images are used for training a pose invariant face recognition approach (P²CA).     

ILP-assisted de novo drug design

The accurate and early detection of epileptic seizures in continuous electroencephalographic (EEG) data has a growing role in the management of patients with epilepsy. Early detection allows for therapy to be delivered at the start of seizures and for caregivers to be notified promptly about potentially debilitating events. The challenge to detecting epileptic seizures, however, is that seizure morphologies exhibit considerable inter-patient and intra-patient variability. While recent work has looked at addressing the issue of variations across different patients (inter-patient variability) and described patient-specific methodologies for seizure detection, there are no examples of systems that can simultaneously address the challenges of inter-patient and intra-patient variations in seizure morphology. In our study, we address this complete goal and describe a multi-task learning approach that trains a classifier to perform well across many kinds of seizures rather than potentially overfitting to the most common seizure types. Our approach increases the generalizability of seizure detection systems and improves the tradeoff between latency and sensitivity versus false positive rates. When compared against the standard approach on the CHB–MIT multi-channel scalp EEG data, our proposed method improved discrimination between seizure and non-seizure EEG for almost 83 % of the patients while reducing false positives on nearly 70 % of the patients studied.     

On the formation of the diamond grain configuration during high temperature creep and fatigue

A study has been made of the influence of test variables on the formation of the diamond grain configuration during high temperature creep and fatigue deformation of a wide variety of metals. The proposed mechanisms for the formation of this interesting grain morphology are reviewed. It is concluded that the diamond grain configuration arises from a balance between grain-boundary sliding, grain-boundary mobility, intragranular deformation and defect imbalance across the grain boundaries and that it tends to be stabilized by intergranular cavitation. While the phenomenon occurs during high temperature fatigue in a variety of metals irrespective of their crystal structure, during creep it has been observed only in to h c p metals. It is surmised that the occurrence of the diamond array of grain boundaries during creep deformation in h c p metals is aided by the limited number of slip systems which leads to high defect imbalances in adjacent grains and consequently high driving forces for grain-boundary migration. On the basis of quantitative metallography involving measurements of the number of edges per grain section, the number of grains meeting at vertices, angular distribution histograms and grain-boundary lengths in different angular orientations with respect to the stress axis in "annealed" and "diamond" microstructures, it is concluded that the shape of the "diamond" grain is essentially the same as that of the "annealed" grain but in a distorted form.