Remotely Triggerable Drug Delivery Systems

Triggerable drug delivery systems enable on‐demand controlled release profiles that may enhance therapeutic effectiveness and reduce systemic toxicity. Recently, a number of new materials have been developed that exhibit sensitivity to visible light, near‐infrared (NIR) light, ultrasound, or magnetic fields. This responsiveness can be triggered remotely to provide flexible control of dose magnitude and timing. Here we review triggerable materials that range in scale from nano to macro, and are activated by a range of stimuli.     

Analysis of tradeoff between data accuracy and performance of databases

Databases in large organizations are used for supporting the storage and manipulation of both operational and aggregate data. The operational data is characterized by frequent updates based on changes to values of items in the real world. Aggregate data is used in statistical analysis for decision making, forcasting and formulation of business strategies. The accuracy of the results of statistical processing depends on the processing resources allocated to the update transactions relative to the query and statistical reporting requests. Different types of statistical processing may require varying degress of data accuracy. For example, long range planning decisions may require less accurate data than those needed for tactical decisions. In this paper we propose a model for estimating the accuracy of a database and for the planning of computing resources based on database system performance and accuracy requirements of various groups of users.     

Higher approximations to the far viscous-wake solution

Summary Higher order approximations to the laminar boundary-layer flow of an incompressible fluid in the wake of a symmetrical disturbance are given in the present paper. The two-dimensional case, documented elsewhere in great detail, [1], [2], [3] and [4] is reconsidered. The Euler transformation is introduced and higher-order expansion terms are derived. The asymptotic expansions given in the paper are, of course, valid only to the extent that the boundary layer approximations apply, i.e. (for the rotationally symmetrical case) within a space of revolution with the centre of the wake as axis of symmetry. The terms neglected in the complete equations of motion become of order unity for very smallx, where the expansion is not applicable in any case (as becomes large), and at very large (respectively),x being given.The axisymmetrical case is expanded in a like manner, but in both cases the inner and outer coördinate expansion problem of matching with the near wake, considered by Meksyn [16] and Berger [11] is not treated: this, mainly, because its detailed form would depend on the particular upstream conditions obtaining, a subject which is outside the scope of the present work.     

Bit transposition for very large scientific and statistical databases

Conventional access methods cannot be effectively used in large Scientific/Statistical Database (SSDB) applications. A file structure (called bit transposed file (BTF)) is proposed which offers several attractive features that are better suited for the special characteristics that SSDBs exhibit. This file structure is an extreme version of the (attribute) transposed file. The data are stored by vertical bit partitions. The bit patterns of attributes are assigned using one of several data encoding methods. Each of these encoding methods is appropriate for different query types. The bit partitions can also be compressed using a version of the run length encoding scheme. Efficient operators on compressed bit vectors have been developed and form the basis of a query language. Because of the simplicity of the file structure and query language, optimization problems for database design, query evaluation, and common subexpression removal can be formalized and efficient exact solution or near optimal solution can be achieved. In addition to selective power with low overheads for SSDBs, the BTF is also amenable to special parallel hardware. Results from experiments with the file structure suggest that this approach may be a reasonable alternative file structure for large SSDBs.Supported by the Office of Energy Research, U.S. DOE under Contract No. DE-AC03-76SF00098.On leave from the Department of Computer Science, Heilongjiang University, China.     

Learning attribute-efficiently with corrupt oracles

We study learning in a modified EXACT model, where the oracles are corrupt and only few of the presented attributes are relevant. Both modifications were already studied in the literature [Dana Angluin, Mārti?š Krikis, Learning with malicious membership queries and exceptions (extended abstract), in: COLT ’94: Proceedings of the Seventh Annual Conference on Computational Learning Theory, ACM Press, 1994, pp. 56–57 [3]; Dana Angluin, Mārti?š Krikis, Robert H. Sloan, György Turán, Malicious omissions and errors in answers to membership queries, Machine Learning 28 (1997) 211–255; Laurence Bisht, Nader H. Bshouty, Lawrance Khoury, Learning with errors in answers to membership queries (extracted abstract), in: FOCS ’04: Proceedings of the 45th Annual IEEE Symposium on Foundations of Computer Science, FOCS’04, IEEE Computer Society, 2004, pp. 611–620; Nader H. Bshouty, Lisa Hellerstein, Attribute-efficient learning in query and mistake-bound models, J. Comput. System Sci. 56 (3) (1998) 310–319 [12]; Nick Littlestone, Learning quickly when irrelevant attributes abound: A new linear-threshold algorithm, Machine Learning 2 (4) (1988) 285–318; Robert H. Sloan, Gyorgy Turan, Learning with queries but incomplete information (extended abstract), in: COLT ’94: Proceedings of the Seventh Annual Conference on Computational Learning Theory, ACM Press, 1994, pp. 237–245 [5]], and efficient solutions were found to most of their variants. Nonetheless, their reasonable combination is yet to be studied, and integrating the existing solutions either fails or works with a complexity that can be significantly improved. In this paper we prove the equivalence of EXACT learning attribute-efficiently with and without corrupt oracles. For each of the possible scenarios we describe a generic scheme that enables learning in these cases using modifications of the standard learning algorithms. We also generalize and improve previous non-attribute-efficient algorithms for learning with corrupt oracles.     

Variety Evasive Sets

We give an explicit construction of a large subset \({S \subset \mathbb{F}^n}\) , where \({\mathbb{F}}\) is a finite field, that has small intersection with any affine variety of fixed dimension and bounded degree. Our construction generalizes a recent result of Dvir and Lovett (STOC 2012) who considered varieties of degree one (that is, affine subspaces).     

Light Manipulation by Guanine Crystals in Organisms: Biogenic Scatterers,Mirrors, Multilayer Reflectors and Photonic Crystals

Guanine crystals are widely used in nature to manipulate light. The first part of this feature article explores how organisms are able to construct an extraordinary array of optical “devices” including diffuse scatterers, broadband and narrowband reflectors, tunable photonic crystals, and image‐forming mirrors by varying the size, morphology, and arrangement of guanine crystals. The second part presents an overview of some of the properties of crystalline guanine to explain why this material is ideally suited for such optical applications. The high reflectivity of many natural optical systems ultimately derives from the fact that guanine crystals have an extremely high refractive index—a product of its anisotropic crystal structure comprised of densely stacked H‐bonded layers. In order to optimize their reflectivity, many organisms exert exquisite control over the crystal morphology, forming plate‐like single crystals in which the high refractive index face is preferentially expressed. Guanine‐based optics are used in a wide range of biological functions such as in camouflage, display, and vision, and exhibit a degree of versatility, tunability, and complexity that is difficult to incorporate into artificial devices using conventional engineering approaches. These biological systems could inspire the next generation of advanced optical materials.     

Magnetic Nanoplatelet‐Based Spin Memory Device Operating at Ambient Temperatures

There is an increasing demand for realizing a simple Si based universal memory device working at ambient temperatures. In principle, nonvolatile magnetic memory can operate at low power consumption and high frequencies. However, in order to compete with existing memory technology, size reduction and simplification of the used material systems are essential. In this work, the chiral‐induced spin selectivity effect is used along with 30–50 nm ferromagnetic nanoplatelets in order to realize a simple magnetic memory device. The vertical memory is Si compatible, easy to fabricate, and in principle can be scaled down to a single nanoparticle size. Results show clear dual magnetization behavior with threefold enhancement between the one and zero states. The magnetization of the device is accompanied with large avalanche like noise that is ascribed to the redistribution of current densities due to spin accumulation inducing coupling effects between the different nanoplatelets.