Burglar target selection : a cross-national comparison

Objectives This study builds on research undertaken by Bernasco and Nieuwbeerta and explores the generalizability of a theoretically derived offender target selection model in three cross-national study regions. Methods Taking a discrete spatial choice approach, we estimate the impact of both environment- and offender-level factors on residential burglary placement in the Netherlands, the United Kingdom, and Australia. Combining cleared burglary data from all study regions in a single statistical model, we make statistical comparisons between environments. Results In all three study regions, the likelihood an offender selects an area for burglary is positively influenced by proximity to their home, the proportion of easily accessible targets, and the total number of targets available. Furthermore, in two of the three study regions, juvenile offenders under the legal driving age are significantly more influenced by target proximity than adult offenders. Post hoc tests indicate the magnitudes of these impacts vary significantly between study regions. Conclusions While burglary target selection strategies are consistent with opportunity-based explanations of offending, the impact of environmental context is significant. As such, the approach undertaken in combining observations from multiple study regions may aid criminology scholars in assessing the generalizability of observed findings across multiple environments.

The preferences of private equity investors in selecting target acquisitions : an international investigation

This study investigates the characteristics and attributes that private equity investors prefer when selecting target acquisitions. These characteristics are examined against a matched sample of firms subject to corporate acquisitions via tender/merger offer during 2000-2009, across seven countries: Australia, Canada, the United Kingdom, the USA, France, Germany and Sweden. We show that firm-specific characteristics are more influential in target selection than external or institutional variables. In particular, private equity targets exhibit lower stock volatility and long-term growth prospects, are larger, and have greater abnormal operating income relative to tender/merger offer target firms. Further, private equity bidders exhibit 'home bias', implying that familiarity motivates target selection. Institutional factors remain largely insignificant across all tests.

Using incomplete online metric maps for topological exploration with the Gap Navigation Tree

This paper presents a general, global approach to the problem of robot exploration, utilizing a topological data structure to guide an underlying Simultaneous Localization and Mapping (SLAM) process. A Gap Navigation Tree (GNT) is used to motivate global target selection and occluded regions of the environment (called “gaps”) are tracked probabilistically. The process of map construction and the motion of the vehicle alters both the shape and location of these regions. The use of online mapping is shown to reduce the difficulties in implementing the GNT.

Wheat breeding nurseries, target environments, and indirect selection for grain yield

Use of appropriate nursery environments will maximize gain from selection for yield of wheat (Triticum aestivum L.) in the target population of environments of a breeding program. The objective of this study was to investigate how well-irrigated (low-stress) nursery environments predict yield of lines in target environments that varied in degree of water limitation. Fifteen lines were sampled from the preliminary yield evaluation stage of the Queensland wheat breeding program and tested in 26 trials under on-farm conditions (Target Environments) across nine years (1985 to 1993) and also in 27 trials conducted at three research stations (Nursery Environments) in three years (1987 to 1989). The nursery environments were structured to impose different levels of water and nitrogen (N) limitation, whereas the target environments represented a random sample of on-farm conditions from the target population of environments. Indirect selection and pattern analysis methods were used to investigate selection for yield in the nursery environments and gain from selection in the target environments. Yield under low-stress nursery conditions was an effective predictor of yield under similar low-stress target environments (r = 0.89, P < 0.01). However, the value of the low-stress nursery as a predictor of yield in the water-limited target environments decreased with increasing water stress (moderate stress r = 0.53, P < 0.05, to r = 0.38, P > 0.05; severe stress r = -0.08, P > 0.05). Yield in the stress nurseries was a poor predictor of yield in the target environments. Until there is a clear understanding of the physiological-genetic basis of variation for adaptation of wheat to the water-limited environments in Queensland, yield improvement can best be achieved by selection for a combination of yield potential in an irrigated low-stress nursery and yield in on-farm trials that sample the range of water-limited environments of the target population of environments.

HMM triangle relative entropy concepts in sequential change detection applied to vision-based dim target manoeuvre detection

The quick detection of abrupt (unknown) parameter changes in an observed hidden Markov model (HMM) is important in several applications. Motivated by the recent application of relative entropy concepts in the robust sequential change detection problem (and the related model selection problem), this paper proposes a sequential unknown change detection algorithm based on a relative entropy based HMM parameter estimator. Our proposed approach is able to overcome the lack of knowledge of post-change parameters, and is illustrated to have similar performance to the popular cumulative sum (CUSUM) algorithm (which requires knowledge of the post-change parameter values) when examined, on both simulated and real data, in a vision-based aircraft manoeuvre detection problem.

The Arabidopsis thaliana double-stranded RNA binding protein DRB1 directs guide strand selection from microRNA duplexes

In Arabidopsis thaliana (Arabidopsis), DICER-LIKE1 (DCL1) functions together with the double-stranded RNA binding protein (dsRBP), DRB1, to process microRNAs (miRNAs) from their precursor transcripts prior to their transfer to the RNA-induced silencing complex (RISC). miRNA-loaded RISC directs RNA silencing of cognate mRNAs via ARGONAUTE1 (AGO1)-catalyzed cleavage. Short interefering RNAs (siRNAs) are processed from viral-derived or transgene-encoded molecules of doublestranded RNA (dsRNA) by the DCL/dsRBP partnership, DCL4/DRB4, and are also loaded to AGO1-catalyzed RISC for cleavage of complementary mRNAs. Here, we use an artificial miRNA (amiRNA) technology, transiently expressed in Nicotiana benthamiana, to produce a series of amiRNA duplexes with differing intermolecular thermostabilities at the 5′ end of duplex strands. Analyses of amiRNA duplex strand accumulation and target transcript expression revealed that strand selection (amiRNA and amiRNA*) is directed by asymmetric thermostability of the duplex termini. The duplex strand possessing a lower 59 thermostability was preferentially retained by RISC to guide mRNA cleavage of the corresponding target transgene. In addition, analysis of endogenous miRNA duplex strand accumulation in Arabidopsis drb1 and drb2345 mutant plants revealed that DRB1 dictates strand selection, presumably by directional loading of the miRNA duplex onto RISC for passenger strand degradation. Bioinformatic and Northern blot analyses of DCL4/DRB4-dependent small RNAs (miRNAs and siRNAs) revealed that small RNAs produced by this DCL/dsRBP combination do not conform to the same terminal thermostability rules as those governing DCL1/DRB1-processed miRNAs. This suggests that small RNA processing in the DCL1/DRB1-directed miRNA and DCL4/DRB4-directed sRNA biogenesis pathways operates via different mechanisms.

A new plasmid display technology for the in vitro selection of functional phenotype–genotype linked proteins

Background: Display technologies which allow peptides or proteins to be physically associated with the encoding DNA are central to procedures which involve screening of protein libraries in vitro for new or altered function. Here we describe a new system designed specifically for the display of libraries of diverse, functional proteins which utilises the DNA binding protein nuclear factor κB (NF-κB) p50 to establish a phenotype–genotype link between the displayed protein and the encoding gene. Results: A range of model fusion proteins to either the amino- or carboxy-terminus of NF-κB p50 have been constructed and shown to retain the picomolar affinity and DNA specificity of wild-type NF-κB p50. Through use of an optimal combination of binding buffer and DNA target sequence, the half-life of p50–DNA complexes could be increased to over 47 h, enabling the competitive selection of a variety of protein–plasmid complexes with enrichment factors of up to 6000-fold per round. The p50-based plasmid display system was used to enrich a maltose binding protein complex to homogeneity in only three rounds from a binary mixture with a starting ratio of 1:108 and to enrich to near homogeneity a single functional protein from a phenotype–genotype linked Escherichia coli genomic library using in vitro functional selections. Conclusions: A new display technology is described which addresses the challenge of functional protein display. The results demonstrate that plasmid display is sufficiently sensitive to select a functional protein from large libraries and that it therefore represents a useful addition to the repertoire of display technologies.

A new plasmid display technology for the in vitro selection of functional phenotype-genotype linked proteins

Background Display technologies which allow peptides or proteins to be physically associated with the encoding DNA are central to procedures which involve screening of protein libraries in vitro for new or altered function. Here we describe a new system designed specifically for the display of libraries of diverse, functional proteins which utilises the DNA binding protein nuclear factor κB (NF-κB) p50 to establish a phenotype-genotype link between the displayed protein and the encoding gene. Results A range of model fusion proteins to either the amino- or carboxy-terminus of NF-κB p50 have been constructed and shown to retain the picomolar affinity and DNA specificity of wild-type NF-κB p50. Through use of an optimal combination of binding buffer and DNA target sequence, the half-life of p50-DNA complexes could be increased to over 47 h, enabling the competitive selection of a variety of protein-plasmid complexes with enrichment factors of up to 6000-fold per round. The p50-based plasmid display system was used to enrich a maltose binding protein complex to homogeneity in only three rounds from a binary mixture with a starting ratio of 1:108 and to enrich to near homogeneity a single functional protein from a phenotype-genotype linked Escherichia coli genomic library using in vitro functional selections. Conclusions A new display technology is described which addresses the challenge of functional protein display. The results demonstrate that plasmid display is sufficiently sensitive to select a functional protein from large libraries and that it therefore represents a useful addition to the repertoire of display technologies.

Identification of optimal epitopes for Plasmodium falciparum rapid diagnostic tests that target histidine-rich proteins 2 and 3

Rapid diagnostic tests (RDTs) represent important tools to diagnose malaria infection. To improve understanding of the variable performance of RDTs that detect the major target in Plasmodium falciparum, namely, histidine-rich protein 2 (HRP2), and to inform the design of better tests, we undertook detailed mapping of the epitopes recognized by eight HRP-specific monoclonal antibodies (MAbs). To investigate the geographic skewing of this polymorphic protein, we analyzed the distribution of these epitopes in parasites from geographically diverse areas. To identify an ideal amino acid motif for a MAb to target in HRP2 and in the related protein HRP3, we used a purpose-designed script to perform bioinformatic analysis of 448 distinct gene sequences from pfhrp2 and from 99 sequences from the closely related gene pfhrp3. The frequency and distribution of these motifs were also compared to the MAb epitopes. Heat stability testing of MAbs immobilized on nitrocellulose membranes was also performed. Results of these experiments enabled the identification of MAbs with the most desirable characteristics for inclusion in RDTs, including copy number and coverage of target epitopes, geographic skewing, heat stability, and match with the most abundant amino acid motifs identified. This study therefore informs the selection of MAbs to include in malaria RDTs as well as in the generation of improved MAbs that should improve the performance of HRP-detecting malaria RDTs.

Addressing factory needs in cane variety selection

Cane fibre content has increased over the past ten years. Some of that increase can be attributed to new varieties selected for release. This paper reviews the existing methods for quantifying the fibre characteristics of a variety, including fibre content and fibre quality measurements – shear strength, impact resistance and short fibre content. The variety selection process is presented and it is reported that fibre content has zero weighting in the current selection index. An updated variety selection approach is proposed, potentially replacing the existing selection process relating to fibre. This alternative approach involves the use of a more complex mill area level model that accounts for harvesting, transport and processing equipment, taking into account capacity, efficiency and operational impacts, along with the end use for the bagasse. The approach will ultimately determine a net economic value for the variety. The methodology lends itself to a determination of the fibre properties that have a significant impact on the economic value so that variety tests can better target the critical properties. A low-pressure compression test is proposed as a good test to provide an assessment of the impact of a variety on milling capacity. NIR methodology is proposed as a technology to lead to a more rapid assessment of fibre properties, and hence the opportunity to more comprehensively test for fibre impacts at an earlier stage of variety development.

Top-down influences on lexical selection during spoken word production: A 4T fMRI investigation of refractory effects in picture naming

Spoken word production is assumed to involve stages of processing in which activation spreads through layers of units comprising lexical-conceptual knowledge and their corresponding phonological word forms. Using high-field (4T) functional magnetic resonance imagine (fMRI), we assessed whether the relationship between these stages is strictly serial or involves cascaded-interactive processing, and whether central (decision/control) processing mechanisms are involved in lexical selection. Participants performed the competitor priming paradigm in which distractor words, named from a definition and semantically related to a subsequently presented target picture, slow picture-naming latency compared to that with unrelated words. The paradigm intersperses two trials between the definition and the picture to be named, temporally separating activation in the word perception and production networks. Priming semantic competitors of target picture names significantly increased activation in the left posterior temporal cortex, and to a lesser extent the left middle temporal cortex, consistent with the predictions of cascaded-interactive models of lexical access. In addition, extensive activation was detected in the anterior cingulate and pars orbitalis of the inferior frontal gyrus. The findings indicate that lexical selection during competitor priming is biased by top-down mechanisms to reverse associations between primed distractor words and target pictures to select words that meet the current goal of speech.

Feature overlap slows lexical selection: Evidence from the picture–word interference paradigm

How does the presence of a categorically related word influence picture naming latencies? In order to test competitive and noncompetitive accounts of lexical selection in spoken word production, we employed the picture–word interference (PWI) paradigm to investigate how conceptual feature overlap influences naming latencies when distractors are category coordinates of the target picture. Mahon et al. (2007. Lexical selection is not by competition: A reinterpretation of semantic interference and facilitation effects in the picture-word interference paradigm. Journal of Experimental Psychology. Learning, Memory, and Cognition, 33(3), 503–535. doi:10.1037/0278-7393.33.3.503) reported that semantically close distractors (e.g., zebra) facilitated target picture naming latencies (e.g., HORSE) compared to far distractors (e.g., whale). We failed to replicate a facilitation effect for within-category close versus far target–distractor pairings using near-identical materials based on feature production norms, instead obtaining reliably larger interference effects (Experiments 1 and 2). The interference effect did not show a monotonic increase across multiple levels of within-category semantic distance, although there was evidence of a linear trend when unrelated distractors were included in analyses (Experiment 2). Our results show that semantic interference in PWI is greater for semantically close than for far category coordinate relations, reflecting the extent of conceptual feature overlap between target and distractor. These findings are consistent with the assumptions of prominent competitive lexical selection models of speech production.

Model selection with misspecified spatial covariance structure

Spatial data analysis has become more and more important in the studies of ecology and economics during the last decade. One focus of spatial data analysis is how to select predictors, variance functions and correlation functions. However, in general, the true covariance function is unknown and the working covariance structure is often misspecified. In this paper, our target is to find a good strategy to identify the best model from the candidate set using model selection criteria. This paper is to evaluate the ability of some information criteria (corrected Akaike information criterion, Bayesian information criterion (BIC) and residual information criterion (RIC)) for choosing the optimal model when the working correlation function, the working variance function and the working mean function are correct or misspecified. Simulations are carried out for small to moderate sample sizes. Four candidate covariance functions (exponential, Gaussian, Matern and rational quadratic) are used in simulation studies. With the summary in simulation results, we find that the misspecified working correlation structure can still capture some spatial correlation information in model fitting. When the sample size is large enough, BIC and RIC perform well even if the the working covariance is misspecified. Moreover, the performance of these information criteria is related to the average level of model fitting which can be indicated by the average adjusted R square ( [GRAPHICS] ), and overall RIC performs well.