Natural ITD statistics predict human auditory spatial perception

A neural code adapted to the statistical structure of sensory cues may optimize perception. We investigated whether interaural time difference (ITD) statistics inherent in natural acoustic scenes are parameters determining spatial discriminability. The natural ITD rate of change across azimuth (ITDrc) and ITD variability over time (ITDv) were combined in a Fisher information statistic to assess the amount of azimuthal information conveyed by this sensory cue. We hypothesized that natural ITD statistics underlie the neural code for ITD and thus influence spatial perception. To test this hypothesis, sounds with invariant statistics were presented to measure human spatial discriminability and spatial novelty detection. Human auditory spatial perception showed correlation with natural ITD statistics, supporting our hypothesis. Further analysis showed that these results are consistent with classic models of ITD coding and can explain the ITD tuning distribution observed in the mammalian brainstem.

An information-theoretic approach to study spatial dependencies in small datasets

From epidemiology to economics, there is a fundamental need of statistically principled approaches to unveil spatial patterns and identify their underpinning mechanisms. Grounded in network and information theory, we establish a non-parametric scheme to study spatial associations from limited measurements of a spatial process. Through the lens of network theory, we relate spatial patterning in the dataset to the topology of a network on which the process unfolds. From the available observations of the spatial process and a candidate network topology, we compute a mutual information statistic that measures the extent to which the measurement at a node is explained by observations at neighbouring nodes. For a class of networks and linear autoregressive processes, we establish closed-form expressions for the mutual information statistic in terms of network topological features. We demonstrate the feasibility of the approach on synthetic datasets comprising 25–100 measurements, generated by linear or nonlinear autoregressive processes. Upon validation on synthetic processes, we examine datasets of human migration under climate change in Bangladesh and motor vehicle deaths in the United States of America. For both these real datasets, our approach is successful in identifying meaningful spatial patterns, begetting statistically-principled insight into the mechanisms of important socioeconomic problems.

Measuring individual identity information in animal signals: Overview and performance of available identity metrics

Identity signals have been studied for over 50 years but there is no consensus as to how to quantify individuality. While there are a variety of different metrics to quantify individual identity, or individuality, these methods remain un-validated and the relationships between them unclear.We contrasted three univariate and four multivariate metrics (and their different computational variants) and evaluated their performance on simulated and empirical datasets.Of the metrics examined, Beecher’s information statistic (HS) was the best one and could easily and reliably be converted into the commonly used discrimination score (and vice versa) after accounting for the number of individuals and calls per individual in a given dataset. Although Beecher’s information statistic is not entirely independent of sampling parameters, this problem can be removed by reducing the number of parameters or by increasing the number of individuals.Because it is easily calculated, has superior performance, can be used to describe single variables or signal as a whole, and because it tells us the maximum number of individuals that can be discriminated given a set of measurements, we recommend that individuality should be quantified using Beecher’s information statistic.

A Review of Safety Issues among Small Grade Contractors in Construction Industry

The construction industry is one of the largest industries in Malaysia. There were too many factors that contribute to construction project success. Construction industry comprises different participants including clients, consultants, and contractors (as construction business) that perform different roles from conception in order to complete the project. The contractors in Malaysia were categorized into seven Grades of contractors starting from contractor G1 to G7. These categories were graded based on a number of employees and the value of the project. In Malaysia, G1 to G4 contractors (small grade contractors) are the highest company were registered with the Construction Industry Development Board (CIDB). Unfortunately, small grade contractors are widely exposed to the highest rate of accidents or risky compared to medium and large grade contractors (G5-G7) in this industry. In order to adequately clarify the issues on this safety matter, this paper has discussed the problems faced by small grade contractors that influence the implementation of safety practice in a construction site. The objective of study is to identify the problems in small grade contractors in order to implement safety practice on site. This study was focused on small grade contractor in Malaysia. The data for this study were supported by previous studies are reported in the journal; statistic of accidents in the construction industry by Department of Occupational Safety and Health (DOSH); contractor information; statistic of contractors are registered under CIDB; safety book; and internet sources. This study had found that the small grade contractors have some issues related to safety practice whereas they did not have proper standard of safety (general safety act and regulation); they cannot appoint Safety Health Officer (SHO) to handle the site safety; have limited external resource; and also small grade contractors have financial constraints. Based on this review, it can be concluded that small grade contractors have more lacking in safety management and consequently, the rate of accidents still higher in the construction industry. However, safety management in small grade contractors can be improved with support by external resources such as researcher, large grade contractor, government, and pressure from authorities.

Breeding bird density does not drive vocal individuality

Many species produce individually specific vocalizations and sociality is a hypothesized driver of such individuality. Previous studies of how social variation influenced individuality focused on colonial or non-colonial avian species, and how social group size influenced individuality in sciurid rodents. Since sociality is an important driver of individuality, we expected that bird species that defend nesting territories in higher density neighborhoods should have more individually-distinctive calls than those that defend nesting territories in lower-density neighborhoods. We used Beecher’s information statistic to quantify individuality, and we examined the relationship between bird density (calculated with point-counts) and vocal individuality on seven species of passerines. We found non-significant relationships between breeding bird density and vocal individuality whether regressions were fitted on species values, or on phylogenetically-independent contrast values. From these results, we infer that while individuality may be explained by social factors, breeding bird density is unlikely to be generally important in driving the evolution of individually-specific vocalizations.

The Design of Crops Remote Sensing Monitoring System Based on Supermap Objects

The remote sensing monitoring system, which uses GIS technique, is mainly discussed in this paper. It takes SuperMap Objects as development platform and Visual C++ as the secondary development tools, with MYSQL for the relational database, to design the main interface. This system basically complete data entry editing, mapping, information browsing query, spatial analysis and information statistic, data maintenance and output. this system will provide better digital platform for resource reasonable exploitation and scientific management．

Genetic variation among Glomerella cingulata isolates from different Lauraceae hosts

Four populations of Glomerella cingulata 20 isolates each were sampled from avocado (Perseae americana) fruit from orchards throughout New Zealand and from Queensland Australia and from leaves of Beilschmeidia tawa and Beilschmeidia taraire in Hawkes Bay and the Waitakere Ranges respectively Among 80 isolates 44 different colony morphologies were identified with only three of these occurring in more than one of the four populations The population from B taraire showed less variation in colony morphology than did the other populations with a Shannon and Weaver information statistic H of 047 compared with 071 to 093 More of the diversity occurred within the populations (64) than between them (36) Sequence analysis of the ITS region using maximumparsimony identified two clades among the isolates with all isolates from the native New Zealand trees clustering in one clade and all avocado isolates in the other Some variation was detected within the clades although all isolates from B taraire had identical sequences This study indicates that G cingulata populations from avocado and native trees may represent genetically isolated populations that have evolved separately To identify geographic origin of fungal populations from avocado a different DNA sequence with more variation is required

Comparison of multivariate analyses using taxonomic data of Oxalis

Several multivariate techniques are used to analyze the resemblances between the 25 North American taxa of Oxalis section Ionoxalis. Results from each of three clustering strategies are subjected to stepwise discriminant analysis for refinement and reallocation. The resultant phenetic classifications are compared with each other and with a recent conventional treatment using the same data. Affinities of the taxa, along with new relationships indicated by these analyses, are discussed. A polythetic hierarchical clustering method using an information statistic produces the most efficient and reliable phenetic classification and is recommended for use in systematic studies.

Partition of information

The classification of quantitative ecological survey data has in the past encountered two serious difficulties: (i) no completely satisfactory information statistic model has been devised for this purpose, and the theoretically most attractive - the "diversity" model - appears usually to produce ecologically meaningless fusions; (ii) no satisfactory partition of information between qualitative and quantitative components has been known. The requirement is for an information statistic model which can be confidently used for either qualitative or quantitative data, and which can be partitioned into its qualitative and quantitative components. A new statistic is defined which meets these requirements, and its application to a small-scale test example is illustrated.