Evolutionary psychology and the rehabilitation of offenders : constraints and consequences

The mainstream view in criminology and correctional psychology is that evolutionary perspectives have little to offer researchers or practitioners and may in fact lead to overly reductionist and crude responses to the complex issue of crime and its consequences. However, in our view all the major evolutionary approaches to the explanation of human behavior have something of value to contribute, with niche construction providing a particularly useful lens upon crime and its management. In this paper we analyze the concept of rehabilitation and describe the key features of effective rehabilitation. We argue that niche construction is responsive to the cognitive versatility and behavioral flexibility of human beings and can also accommodate the important role of social and cultural scaffolding in the rehabilitation process.

Evolutionary specialization of a tryptophan indole group for transition-state stabilization by eukaryotic transglutaminases

Covalent posttranslational protein modifications by eukaryotic transglutaminases proceed by a kinetic pathway of acylation and deacylation. Ammonia is released as the acylenzyme is formed, whereas the cross-linked product is released later in the deacylation step. Superposition of the active sites of transglutaminase type 2 (TG2) and the structurally related cysteine protease, papain, indicates that in the formation of tetrahedral intermediates, the backbone nitrogen of the catalytic Cys-277 and the N_Ɛ1 nitrogen of Trp-241 of TG2 could contribute to transition-state stabilization. The importance of this Trp-241 side chain was demonstrated by examining the kinetics of dansylcadaverine incorporation into a model peptide. Although substitution of the Trp-241 side chain with Ala or Gly had only a small effect on the Michaelis constant K_m (1.5-fold increase), it caused a >300-fold lowering of the catalytic rate constant k_cat. The wild-type and mutant TG2-catalyzed release of ammonia showed kinetics similar to the kinetics for the formation of cross-linked product, indicating that transitionstate stabilization in the acylation step was rate-limiting. In papain, a Gln residue is at the position of TG2-Trp-241. The conservation of Trp-241 in all eukaryotic transglutaminases and the finding that W241Q-TG2 had a much lower k_cat than wild-type enzyme suggest evolutionary specialization in the use of the indole group. This notion is further supported by the observation that transitionstate- stabilizing side chains of Tyr and His that operate in some serine and metalloproteases only partially substituted for Trp.

Minimum spanning trees for valley and ridge characterization in digital elevation maps

Texture synthesis employs neighbourhood matching to generate appropriate new content. Terrain synthesis has the added constraint that new content must be geographically plausible. The profile recognition and polygon breaking algorithm (PPA) [Chang et al. 1998] provides a robust mechanism for characterizing terrain as systems of valley and ridge lines in digital elevation maps. We exploit this to create a terrain characterization metric that is robust, efficient to compute and is sensitive to terrain properties.

Terrain regions are characterized as a minimum spanning tree derived from a graph created from the sample points of the elevation map which are encoded as weights in the edges of the graph. This formulation allows us to provide a single consistent feature definition that is sensitive to the pattern of ridges and valleys in the terrain Alternative formulations of these weights provide richer characteristicmeasures and we provide examples of alternate definitions based on curvature and contour measures.

We show that the measure is robust, with a significant portion derived directly from information local to the terrain sample. Global terrain characteristics introduce the issue of over- and underconnected valley/ridge lines when working with sub-regions. This is addressed by providing two graph construction strategies, which respectively provide an upper bound on connectivity as a single spanning tree, and a lower bound as a forest of trees.

Efficient minimum spanning tree algorithms are adapted to the context of terrain data and are shown to provide substantially better performance than previous PPA implementations. In particular, these are able to characterize valley and ridge behaviour at every point even in large elevation maps, providing a measure sensitive to terrain features at all scales.

The resulting graph based formulation provides an efficient and elegant algorithm for characterizing terrain features. The measure can be calculated efficiently, is robust under changes of neighbourhood position, size and resolution and the hybrid measure is sensitive to terrain features both locally and globally.

Involvement of rootstocks and their hydraulic conductance in the drought resistance of grafted rubber trees

Improving drought resistance of rubber trees has become a pressing issue with the extension of rubber plantations and the prevalence of seasonal drought. Root system is vital to water and nutrients uptake of all plants, therefore, rootstocks could play decisive roles in drought resistance of grafted rubber trees on a specific scion clone. To investigate the responses of different clone rootstocks and their grafted trees to water stress and find applicable methods for selecting drought resistant rootstocks, seven related parameters and root hydraulic properties of both seeds originated and grafted saplings of PB86, PR107, RRIM600 and GT1 were measured to assess their drought resistance. It was shown that the rootstock drought resistance and root hydraulic conductance may improve the drought resistance of the grafted rubber trees. Among the four clone rootstocks, GT1, which demonstrated more resistant to drought and higher root hydraulic conductance, was comparatively resistant to drought both for the seed propagation seedlings and grafted saplings. In addition, studies on the grafted saplings with different root hydraulic conductance further validated the possibility of selecting drought resistant rootstocks on the basis of rootstock hydraulic conductance using a high-pressure flow meter.

Conflict between genetic and phenotypic differentiation : the evolutionary history of a ‘lost and rediscovered’ shorebird

Understanding and resolving conflicts between phenotypic and genetic differentiation is central to evolutionary research. While phenotypically monomorphic species may exhibit deep genetic divergences, some morphologically distinct taxa lack notable genetic differentiation. Here we conduct a molecular investigation of an enigmatic shorebird with a convoluted taxonomic history, the White-faced Plover (Charadrius alexandrinus dealbatus), widely regarded as a subspecies of the Kentish Plover (C. alexandrinus). Described as distinct in 1863, its name was consistently misapplied in subsequent decades until taxonomic clarification ensued in 2008. Using a recently proposed test of species delimitation, we reconfirm the phenotypic distinctness of dealbatus. We then compare three mitochondrial and seven nuclear DNA markers among 278 samples of dealbatus and alexandrinus from across their breeding range and four other closely related plovers. We fail to find any population genetic differentiation between dealbatus and alexandrinus, whereas the other species are deeply diverged at the study loci. Kentish Plovers join a small but growing list of species for which low levels of genetic differentiation are accompanied by the presence of strong phenotypic divergence, suggesting that diagnostic phenotypic characters may be encoded by few genes that are difficult to detect. Alternatively, gene expression differences may be crucial in producing different phenotypes whereas neutral differentiation may be lagging behind.

Hybrid neural-evolutionary model for electricity price forecasting

Evolving artificial neural networks has attracted much attention among researchers recently, especially in the fields where plenty of data exist but explanatory theories and models are lacking or based upon too many simplifying assumptions. Financial time series forecasting is one of them. A hybrid model is used to forecast the hourly electricity price from the California Power Exchange. A collaborative approach is adopted to combine ANN and evolutionary algorithm. The main contributions of this thesis include: Investigated the effect of changing values of several important parameters on the performance of the model, and selected the best combination of these parameters; good forecasting results have been obtained with the implemented hybrid model when the best combination of parameters is used. The lowest MAPE through a single run is 5. 28134%. And the lowest averaged MAPE over 10 runs is 6.088%, over 30 runs is 6.786%; through the investigation of the parameter period, it is found that by including future values of the homogenous moments of the instant being forecasted into the input vector, forecasting accuracy is greatly enhanced. A comparison of results with other works reported in the literature shows that the proposed model gives superior performance on the same data set.

Extracting common subtrees from decision trees

This paper explores an efficient technique for the extraction of common subtrees in decision trees. The method is based on a Suffix Tree string matching process and the algorithm is applied to the problem of finding common decision rules in path planning.

Video indexing and similarity retrieval by largest common subgraph detection using decision trees

While the largest common subgraph (LCSG) between a query and a database of models can provide an elegant and intuitive measure of similarity for many applications, it is computationally expensive to compute. Recently developed algorithms for subgraph isomorphism detection take advantage of prior knowledge of a database of models to improve the speed of on-line matching. This paper presents a new algorithm based on similar principles to solve the largest common subgraph problem. The new algorithm significantly reduces the computational complexity of detection of the LCSG between a known database of models, and a query given on-line.

Taxonomic review and evolutionary trends of Levipustulini and Absenticostini (Brachiopoda) from Argentina : palaeobiogeographic and palaeoclimatic implications

The diagnosis and composition of the brachiopod Tribe Levipustulini Lazarev, 1985 is reviewed, leading to a detailed revision of the genera Levipustula Maxwell, 1951 and Lanipustula Klets, 1983, as well as a review of previous records of the species Levipustula levis Maxwell from Australia and Argentina. The presence of Lanipustula patagoniensis Simanauskas in Patagonia is confirmed with additional topotypic material described and illustrated. Based on this review, we reassign Levipustula levis from New South Wales, Australia to Lanipustula. Two new species, Lanipustula kletsi from the middle Pennsylvanian of Patagonia and the Absenticostinin Absenticosta bruntoneileenae from the latest Viséan of western Argentina, are proposed. Abstenticosta bruntoneileenae is suggested as a possible ancestral stock of the Patagonian Levipustulini through the lineage Lanipustula-Verchojania-Jakutoproductus-Piatnitzkya (Serpukhovian-middle Artinskian). The development of similar phylogenetic lineages of Levipustulini in high latitude regions of both northern and southern hemispheres (such as Siberia in Northeast Asia and Patagonia in southwestern Gondwana) is here interpreted as a consequence of parallel evolution. The progressive palaeobiogeographic isolation of Patagonia from mainland South America, coupled with its southward drift under cold palaeoclimatic conditions during middle Carboniferous-earliest Permian times, is proposed to have triggered the Levipustulini vicariance.

Bayesian networks and decision trees in the diagnosis of female urinary incontinence

This study compares the effectiveness of Bayesian networks versus Decision Trees in modeling the Integral Theory of Female Urinary Incontinence diagnostic algorithm. Bayesian networks and Decision Trees were developed and trained using data from 58 adult women presenting with urinary incontinence symptoms. A Bayesian Network was developed in collaboration with an expert specialist who regularly utilizes a non-automated diagnostic algorithm in clinical practice. The original Bayesian network was later refined using a more connected approach. Diagnoses determined from all automated approaches were compared with the diagnoses of a single human expert. In most cases, Bayesian networks were found to be at least as accurate as the Decision Tree approach. The refined Connected Bayesian Network was found to be more accurate than the Original Bayesian Network accurately discriminated between diagnoses despite the small sample size. In contrast, the Connected and Decision Tree approaches were less able to discriminate between diagnoses. The Original Bayesian Network was found to provide an excellent basis for graphically communicating the correlation between symptoms and laxity defects in a given anatomical zone. Performance measures in both networks indicate that Bayesian networks could provide a potentially useful tool in the management of female pelvic floor dysfunction. Before the technique can be utilized in practice, well-established learning algorithms should be applied to improve network structure. A larger training data set should also improve network accuracy, sensitivity, and specificity.

A GA-PSO layered encoding evolutionary approach to 0/1 knapsack optimization

This paper presents a layered encoding cascade evolutionary approach to solve a 0/1 knapsack optimization problem. A layered encoding structure is proposed and developed based on the schema theorem and the concepts of cascade correlation and multi-population evolutionary algorithms. Genetic algorithm (GA) and particle swarm optimization (PSO) are combined with the proposed layered encoding structure to form a generic optimization model denoted as LGAPSO. In order to enhance the finding of both local and global optimum in the evolutionary search, the model adopts hill climbing evaluation criteria, feature of strength Pareto evolutionary approach (SPEA) as well as nondominated spread lengthen criteria. Four different sizes benchmark knapsack problems are studied using the proposed LGAPSO model. The performance of LGAPSO is compared to that of the ordinary multi-objective optimizers such as VEGA, NSGA, NPGA and SPEA. The proposed LGAPSO model is shown to be efficient in improving the search of knapsack’s optimum, capable of gaining better Pareto trade-off front.