Improving Artificial-Immune-System-based computing by exploiting intrinsic features of computer architectures

Biological systems have become highly significant for traditional computer architectures as examples of highly complex self-organizing systems that perform tasks in parallel with no centralized control. However, few researchers have compared the suitability of different computing approaches for the unique features of Artificial Immune Systems (AIS) when trying to introduce novel computing architectures, and few consider the practicality of their solutions for real world machine learning problems. We propose that the efficacy of AIS-based computing for tackling real world datasets can be improved by the exploitation of intrinsic features of computer architectures. This paper reviews and evaluates current existing implementation solutions for AIS on different computing paradigms and introduces the idea of “C Principles” and “A Principles”. Three Artificial Immune Systems implemented on different architectures are compared using these principles to examine the possibility of improving AIS through taking advantage of intrinsic hardware features

Constraint Handling in Genotype to Phenotype Mapping and Genetic Operators for Project Staffing

Project staffing in many organisations involves the assignment of people to multiple projects while satisfying multiple constraints. The use of a genetic algorithm with constraint handling performed during a genotype to phenotype mapping process provides a new approach. Experiments show promise for this technique

Fast Hierarchical Clustering and Other Applications of Dynamic Closest Pairs

We develop data structures for dynamic closest pair problems with arbitrary distance functions, that do not necessarily come from any geometric structure on the objects. Based on a technique previously used by the author for Euclidean closest pairs, we show how to insert and delete objects from an n-object set, maintaining the closest pair, in O(n log^2 n) time per update and O(n) space. With quadratic space, we can instead use a quadtree-like structure to achieve an optimal time bound, O(n) per update. We apply these data structures to hierarchical clustering, greedy matching, and TSP heuristics, and discuss other potential applications in machine learning, Groebner bases, and local improvement algorithms for partition and placement problems. Experiments show our new methods to be faster in practice than previously used heuristics.Comment: 20 pages, 9 figures. A preliminary version of this paper appeared at the 9th ACM-SIAM Symp. on Discrete Algorithms, San Francisco, 1998, pp. 619-628. For source code and experimental results, see http://www.ics.uci.edu/~eppstein/projects/pairs

Palmitoylated small GTPase ARL15 is translocated within Golgi network during adipogenesis

The small GTPase ARF family member ARL15 gene locus is associated in population studies with increased risk of type 2 diabetes, lower adiponectin and higher fasting insulin levels. Previously, loss of ARL15 was shown to reduce insulin secretion in a human β-cell line and loss of function mutations are found in some lipodystrophy patients. We set out to understand the role of ARL15 in adipogenesis and showed that endogenous ARL15 palmitoylated and localised in the Golgi of mouse liver. Adipocyte overexpression of palmitoylation-deficient ARL15 resulted in redistribution to the cytoplasm and a mild reduction in expression of some adipogenesis-related genes. Further investigation of the localisation of ARL15 during differentiation of a human white adipocyte cell line showed that ARL15 was predominantly co-localised with a marker of the cis face of Golgi at the preadipocyte stage and then translocated to other Golgi compartments after differentiation was induced. Finally, co-immunoprecipitation and mass spectrometry identified potential interacting partners of ARL15, including the ER-localised protein ARL6IP5. Together, these results suggest a palmitoylation dependent trafficking-related role of ARL15 as a regulator of adipocyte differentiation via ARL6IP5 interaction.</jats:p

Fusarium wilt of banana: Global problems and perspectives

Fusarium wilt of banana is recognized as one of the most destructive diseases of banana worldwide. In addition to an overview of the history of research into fusarium wilt of banana, a precis of the current global problems posed by this disease to producers and consumers of bananas is presented in this paper. Key issues and opportunities facing scientific researchers in their attempts to find solutions to the management of this disease are also discussed, with reference to the notion of sustainable agriculture

Dynamic Range Majority Data Structures

Given a set $P$ of coloured points on the real line, we study the problem of answering range $\alpha$-majority (or "heavy hitter") queries on $P$. More specifically, for a query range $Q$, we want to return each colour that is assigned to more than an $\alpha$-fraction of the points contained in $Q$. We present a new data structure for answering range $\alpha$-majority queries on a dynamic set of points, where $\alpha \in (0,1)$. Our data structure uses O(n) space, supports queries in $O((\lg n) / \alpha)$ time, and updates in $O((\lg n) / \alpha)$ amortized time. If the coordinates of the points are integers, then the query time can be improved to $O(\lg n / (\alpha \lg \lg n) + (\lg(1/\alpha))/\alpha))$. For constant values of $\alpha$, this improved query time matches an existing lower bound, for any data structure with polylogarithmic update time. We also generalize our data structure to handle sets of points in d-dimensions, for $d \ge 2$, as well as dynamic arrays, in which each entry is a colour.Comment: 16 pages, Preliminary version appeared in ISAAC 201

Orthogonal Range Reporting and Rectangle Stabbing for Fat Rectangles

In this paper we study two geometric data structure problems in the special case when input objects or queries are fat rectangles. We show that in this case a significant improvement compared to the general case can be achieved. We describe data structures that answer two- and three-dimensional orthogonal range reporting queries in the case when the query range is a \emph{fat} rectangle. Our two-dimensional data structure uses $O(n)$ words and supports queries in $O(\log\log U +k)$ time, where $n$ is the number of points in the data structure, $U$ is the size of the universe and $k$ is the number of points in the query range. Our three-dimensional data structure needs $O(n\log^{\varepsilon}U)$ words of space and answers queries in $O(\log \log U + k)$ time. We also consider the rectangle stabbing problem on a set of three-dimensional fat rectangles. Our data structure uses $O(n)$ space and answers stabbing queries in $O(\log U\log\log U +k)$ time.Comment: extended version of a WADS'19 pape