994 resultados para problem complexity
Resumo:
Excessive consumption of alcohol is a serious public health problem. While intensive treatments are suitable for those who are physically dependent on alcohol, they are not cost-effective options for the vast majority of problem drinkers who are not dependent. There is good evidence that brief interventions are effective in reducing overall alcohol consumption, alcohol-related problems, and health-care utilisation among nondependent problem drinkers. Psychologists are in an ideal position to opportunistically detect people who drink excessively and to offer them brief advice to reduce their drinking. In this paper we outline the process involved in providing brief opportunistic screening and intervention for problem drinkers. We also discuss methods that psychologists can employ if a client is not ready to reduce drinking, or is ambivalent about change. Depending on the client's level of motivation to change, psychologists can engage in either an education-clarification approach, a commitment-enhancement approach, or a skills-training approach. Routine engagement in opportunistic intervention is an important public-health approach to reducing alcohol-related harm in the community.
Resumo:
Let g be the genus of the Hermitian function field H/F(q)2 and let C-L(D,mQ(infinity)) be a typical Hermitian code of length n. In [Des. Codes Cryptogr., to appear], we determined the dimension/length profile (DLP) lower bound on the state complexity of C-L(D,mQ(infinity)). Here we determine when this lower bound is tight and when it is not. For m less than or equal to n-2/2 or m greater than or equal to n-2/2 + 2g, the DLP lower bounds reach Wolf's upper bound on state complexity and thus are trivially tight. We begin by showing that for about half of the remaining values of m the DLP bounds cannot be tight. In these cases, we give a lower bound on the absolute state complexity of C-L(D,mQ(infinity)), which improves the DLP lower bound. Next we give a good coordinate order for C-L(D,mQ(infinity)). With this good order, the state complexity of C-L(D,mQ(infinity)) achieves its DLP bound (whenever this is possible). This coordinate order also provides an upper bound on the absolute state complexity of C-L(D,mQ(infinity)) (for those values of m for which the DLP bounds cannot be tight). Our bounds on absolute state complexity do not meet for some of these values of m, and this leaves open the question whether our coordinate order is best possible in these cases. A straightforward application of these results is that if C-L(D,mQ(infinity)) is self-dual, then its state complexity (with respect to the lexicographic coordinate order) achieves its DLP bound of n /2 - q(2)/4, and, in particular, so does its absolute state complexity.
Resumo:
Objectives: To document and describe the effects of woodstove burns in children. To identify how these accidents occur so that a prevention strategy can be devised. Design, Patients and Setting: Retrospective departmental database and case note review of all children with woodstove burns seen at the Burns Unit of a Tertiary Referral Children's Hospital between January 1997 and September 2001. Main outcome measures: Number and ages of children burned: circumstances of the accidents; injuries-sustained, treatment-required and long-term sequelae. Results. Eleven children, median age 1.0 year, sustained burns, usually to the hands, of varying thickness. Two children required skin grafting and five required scar therapy. Seven children intentionally placed their hands onto the Outside of the stove. In all children, burns occurred despite adult supervision Conclusions: Woodstoves area cause of burns in children. These injuries are associated with significant morbidity and financial costs. Through public education, woodstove burns can easily be prevented utilising simple safety measures. (C) 2002 Elsevier Science Ltd and ISBI All rights reserved.
Resumo:
The Hamilton-Waterloo problem asks for a 2-factorisation of K-v in which r of the 2-factors consist of cycles of lengths a(1), a(2),..., a(1) and the remaining s 2-factors consist of cycles of lengths b(1), b(2),..., b(u) (where necessarily Sigma(i)(=1)(t) a(i) = Sigma(j)(=1)(u) b(j) = v). In thus paper we consider the Hamilton-Waterloo problem in the case a(i) = m, 1 less than or equal to i less than or equal to t and b(j) = n, 1 less than or equal to j less than or equal to u. We obtain some general constructions, and apply these to obtain results for (m, n) is an element of {(4, 6)1(4, 8), (4, 16), (8, 16), (3, 5), (3, 15), (5, 15)}.
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The set of integers k for which there exist three latin squares of order n having precisely k cells identical, with their remaining n(2) - k cells different in all three latin squares, denoted by I-3[n], is determined here for all orders n. In particular, it is shown that I-3[n] = {0,...,n(2) - 15} {n(2) - 12,n(2) - 9,n(2)} for n greater than or equal to 8. (C) 2002 Elsevier Science B.V. All rights reserved.
Resumo:
We reinterpret the state space dimension equations for geometric Goppa codes. An easy consequence is that if deg G less than or equal to n-2/2 or deg G greater than or equal to n-2/2 + 2g then the state complexity of C-L(D, G) is equal to the Wolf bound. For deg G is an element of [n-1/2, n-3/2 + 2g], we use Clifford's theorem to give a simple lower bound on the state complexity of C-L(D, G). We then derive two further lower bounds on the state space dimensions of C-L(D, G) in terms of the gonality sequence of F/F-q. (The gonality sequence is known for many of the function fields of interest for defining geometric Goppa codes.) One of the gonality bounds uses previous results on the generalised weight hierarchy of C-L(D, G) and one follows in a straightforward way from first principles; often they are equal. For Hermitian codes both gonality bounds are equal to the DLP lower bound on state space dimensions. We conclude by using these results to calculate the DLP lower bound on state complexity for Hermitian codes.
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The enormous amount of information generated through sequencing of the human genome has increased demands for more economical and flexible alternatives in genomics, proteomics and drug discovery. Many companies and institutions have recognised the potential of increasing the size and complexity of chemical libraries by producing large chemical libraries on colloidal support beads. Since colloid-based compounds in a suspension are randomly located, an encoding system such as optical barcoding is required to permit rapid elucidation of the compound structures. We describe in this article innovative methods for optical barcoding of colloids for use as support beads in both combinatorial and non-combinatorial libraries. We focus in particular on the difficult problem of barcoding extremely large libraries, which if solved, will transform the manner in which genomics, proteomics and drug discovery research is currently performed.
Resumo:
This paper characterizes when a Delone set X in R-n is an ideal crystal in terms of restrictions on the number of its local patches of a given size or on the heterogeneity of their distribution. For a Delone set X, let N-X (T) count the number of translation-inequivalent patches of radius T in X and let M-X (T) be the minimum radius such that every closed ball of radius M-X(T) contains the center of a patch of every one of these kinds. We show that for each of these functions there is a gap in the spectrum of possible growth rates between being bounded and having linear growth, and that having sufficiently slow linear growth is equivalent to X being an ideal crystal. Explicitly, for N-X (T), if R is the covering radius of X then either N-X (T) is bounded or N-X (T) greater than or equal to T/2R for all T > 0. The constant 1/2R in this bound is best possible in all dimensions. For M-X(T), either M-X(T) is bounded or M-X(T) greater than or equal to T/3 for all T > 0. Examples show that the constant 1/3 in this bound cannot be replaced by any number exceeding 1/2. We also show that every aperiodic Delone set X has M-X(T) greater than or equal to c(n)T for all T > 0, for a certain constant c(n) which depends on the dimension n of X and is > 1/3 when n > 1.