Caution: These polynomials are referred to as w0, w1, w2, ... in Sections 5-8 of [1]. However, beginning with Section 9 of [1], Hazewinkel uses the notations w1, w2, w3, ... for some different polynomials (the so-called big Witt polynomials, defined by formula (9.25) in [1]), which are not the same as our polynomials w1, w2, w3, ... (though they are related to them: in fact, the polynomial wk t...

We have investigated the dynamic rheological properties of concentrated multiple emulsions to characterize their amphiphile composition at interfaces. Multiple emulsions (W1/O/W2) consist of water droplets (W1) dispersed into oil globules (O), which are redispersed in an external aqueous phase (W2). A small-molecule surfactant and an amphiphilic polymer were used to stabilize the inverse emulsi...

The substantial non-response rate in depressive patients indicates a continuing need to identify predictors of treatment outcome. The aim of this 6-week, open-label study was (1) to compare the efficacy of a priori defined predictors: ≥20% reduction in MADRS score at week 1, ≥20% reduction in MADRS score at week 2 (RM ≥ 20% W2), decrease of cordance (RC), and increase of serum and plasma level ...

Conditions on weights u(·), v(·) are given so that a classical operator T sends the weighted Lorentz space Lrs(vdx) into Lpq(udx). Here T is either a fractional maximal operator Mα or a fractional integral operator Iα or a Calderón–Zygmund operator. A characterization of this boundedness is obtained for Mα and Iα when the weights have some usual properties and max(r, s) ≤ min(p, q). § 0. Introd...

In this work, we investigate solutions to the following question: Given two motion planning problems W1 and W2 with the same robot and similar obstacles, can we reuse the computation from W1 to solve W2 more efficiently? While the answer to this question can find many practical applications, all current motion planners ignore the correspondences between similar environments. Our study shows tha...

Example: Figure 1 shows Hospital and Temporal dimensions. The former’s instance is here on the RHS. K contains predicates Ward(·), Unit(·), Institution(·), etc. Instance DH gives them extensions, e.g. Ward = {W1,W2,W3,W4}. L contains, e.g. WardUnit(·, ·), with extension: WardUnit = {(W1, standard), (W2, standard), (W3, intensive), (W4, terminal)}. In the middle of Figure 1, categorical relation...

Storing a 3D citymodel, its levels of detail and the correspondences between objects as a 4D combinatorial map. Ken Arroyo Ohori, Hugo Ledoux and Jantien Stoter. In Alias Abdul Rahman, Umit Isikdag and Francesc Antón Castro (eds.), ISPRS Joint International Geoinformation Conference 2015, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences II–2/W2, ISPRS, Kuala L...

Given n weights, w I, w2, . . . , w,, such that 0 G w 1 G w2 S. . . s w ,, we examine a property of permutation #, where 7~* = (w,, w,,, w2, w,,_r, . . .), concerning alphabetical binary trees. For each permutation ‘CT of these n weights, there is an optimal alphabetical binary tree corresponding to ‘TT, we denote it’s cost by V(m). There is also an optimal almost uniform alphabetical binary tr...