Review of Japanese work of the last ten years on identifiability in distributed parameter systems Two classes of wmputati0n.m described,. First heteroclinic o&its on the global attractor are computed; by using the viscous Cahn-Hilliard equation to perform a homotopy. these results show that the orbits, md hence the geometry of the atmctors, are remarkably insensitive to whether the Allen-Cahn or Cahn-Hilliard equation is studied. Second, initial-value computations are described; these computations emphasize three differing mechanisms by which interfaces in the equation propagate for the case of very small penalization of interfacial energy Furthermore, convergence to an appropriate free boundary problem is demonstrated numerically.

Generalized Procrustes Analysis (GPA) is the problem of bringing multiple shapes into a common reference by estimating transformations. GPA has been extensively studied for the Euclidean and affine transformations. We introduce GPA with deformable transformations, which forms a much wider and difficult problem. We specifically study a class of transformations called the Linear Basis Warps (LBWs), which contains the affine transformation and most of the usual deformation models, such as the Thin-Plate Spline (TPS). GPA with deformations is a nonconvex underconstrained problem. We resolve the fundamental ambiguities of deformable GPA using two shape constraints requiring the eigenvalues of the shape covariance. These eigenvalues can be computed independently as a prior or posterior. We give a closed-form and optimal solution to deformable GPA based on an eigenvalue decomposition. This solution handles regularization, favoring smooth deformation fields. It requires the transformation model to satisfy a fundamental property of freetranslations, which asserts that the model can implement any translation. We show that this property fortunately holds true for most common transformation models, including the affine and TPS models. For the other models, we give another closed-form solution to GPA, which agrees exactly with the first solution for models with free-translation. We give pseudo-code for computing our solution, leading to the proposed DefGPA method, which is fast, globally optimal and widely applicable. We validate our method and compare it to previous work on six diverse 2D and 3D datasets, with special care taken to choose the hyperparameters from cross-validation.

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Cluster-based hierarchical routing protocols play an essential role in decreasing the energy consumption of wireless sensor networks (WSNs). A low-energy adaptive clustering hierarchy (LEACH) has been proposed as an application-specific protocol architecture for WSNs. However, without considering the distribution of the cluster heads (CHs) in the rotation basis, the LEACH protocol will increase the energy consumption of the network. To improve the energy efficiency of the WSN, we propose a novel modified routing protocol in this paper. The newly proposed improved energy-efficient LEACH (IEE-LEACH) protocol considers the residual node energy and the average energy of the networks. To achieve satisfactory performance in terms of reducing the sensor energy consumption, the proposed IEE-LEACH accounts for the numbers of the optimal CHs and prohibits the nodes that are closer to the base station (BS) to join in the cluster formation. Furthermore, the proposed IEE-LEACH uses a new threshold for electing CHs among the sensor nodes, and employs single hop, multi-hop, and hybrid communications to further improve the energy efficiency of the networks. The simulation results demonstrate that, compared with some existing routing protocols, the proposed protocol substantially reduces the energy consumption of WSNs.

Question: Does remote ischemic conditioning improve neurological function in patients with acute moderate ischemic stroke? Findings: In this randomized clinical trial that included 1893 participants with acute moderate ischemic stroke, excellent neurological function at 90 days in those randomized to remote ischemic conditioning compared with usual care occurred in 67.4% vs 62.0%, a difference that was statistically significant.Meaning: Although remote ischemic conditioning was associated with better neurological function in patients with acute moderate ischemic stroke, this trial requires replication before concluding efficacy for this intervention.

Mechanism of small heat shock protein function in vivo. A knock-in mouse model demonstrates that the R49C mutation in ␣A-crystallin enhances protein insolubility and cell death.

Quantum computing is a quickly growing research field. This article introduces the basic concepts of quantum computing, recent developments in quantum searching, and decoherence in a possible quantum dot realization.Q uantum computing combines computer science with quantum mechanics and it is a fast-growing research field (1). In 1982, Feynman (2) pointed out that to simulate a quantum system, the computer has to be working quantum mechanically, or one needs a quantum computer (QC). The first proposal for practical implementation of a QC was presented in 1993. The elementary unit of quantum information in a QC is the quantum bit (qubit). A single qubit can be envisaged as a two-state system such as a spin-half, a two-level atom. The potential power of a QC is based on the ability of quantum systems to be in superposition of its basic states. All of these numbers represented by the basic states can be manipulated simultaneously. Thus, a QC has enormous quantum parallelism.To perform quantum computations, one should have the following basic conditions: (i) a two-level system (͉0Ͼ and ͉1Ͼ) as a qubit, (ii) the ability to prepare the qubit in a given state, say ͉0Ͼ, (iii) the capability of measuring each qubit, (iv) construction of basic gate operations such as conditional logic gate (the control-not gate), and (v) sufficient long decoherence time. It is very important for a QC to be well isolated from any environmental interaction because they destroy the superposition of states. Furthermore, one has to use quantum error corrections, which have been invented in recent years.Several schemes, such as trapped ions, quantum optical systems, nuclear and electron spins, and superconductor Josephson junctions, have been proposed for embodying quantum computation in recent years. Quantum Searching and Phase MatchingFor a long time, QC research has been the luxury of just a few academic elite in the world, that is, until 1994 when Shor (3) invented his famous prime factorization algorithm. Shor showed in a concrete example that a QC could do much better than a classical computer. More importantly, the difficulty in factoring a large number is the basis of the Rivest-Shamir-Adleman (RSA) public key encryption scheme that is widely used today. Through Shor's algorithm, the QC has suddenly become a real possible threat, and this algorithm has sparked worldwide interests in the QC. Shor's algorithm is applicable only to a specific problem. Grover's algorithm (4), however, devised in 1996, is another that is applicable to many problems. Grover's quantum search algorithm solves the problem of unsorted database searching. Finding a marked state from an unsorted database requires N͞2 searches for a classical computer. Grover's algorithm finds a marked item in only ͌ N steps where N is the size of the database. Grover's algorithm has many applications such as deciphering the digital encryption scheme (DES) encryption scheme optimization.The standard Grover algorithm achieves quadratic speedup over classical searching algorithms. Thi...