Distance software: design and analysis of distance sampling surveys for estimating population size

1. Distance sampling is a widely used technique for estimating the size or density of biological populations. Many distance sampling designs and most analyses use the software Distance. 2. We briefly review distance sampling and its assumptions, outline the history, structure and capabilities of Distance, and provide hints on its use. 3. Good survey design is a crucial prerequisite for obtaining reliable results. Distance has a survey design engine, with a built-in geographic information system, that allows properties of different proposed designs to be examined via simulation, and survey plans to be generated. 4. A first step in analysis of distance sampling data is modeling the probability of detection. Distance contains three increasingly sophisticated analysis engines for this: conventional distance sampling, which models detection probability as a function of distance from the transect and assumes all objects at zero distance are detected; multiple-covariate distance sampling, which allows covariates in addition to distance; and mark–recapture distance sampling, which relaxes the assumption of certain detection at zero distance. 5. All three engines allow estimation of density or abundance, stratified if required, with associated measures of precision calculated either analytically or via the bootstrap. 6. Advanced analysis topics covered include the use of multipliers to allow analysis of indirect surveys (such as dung or nest surveys), the density surface modeling analysis engine for spatial and habitat-modeling, and information about accessing the analysis engines directly from other software. 7. Synthesis and applications. Distance sampling is a key method for producing abundance and density estimates in challenging field conditions. The theory underlying the methods continues to expand to cope with realistic estimation situations. In step with theoretical developments, state-of- the-art software that implements these methods is described that makes the methods accessible to practicing ecologists.

A Model-Based Approach for Making Ecological Inference from Distance Sampling Data

We consider a fully model-based approach for the analysis of distance sampling data. Distance sampling has been widely used to estimate abundance (or density) of animals or plants in a spatially explicit study area. There is, however, no readily available method of making statistical inference on the relationships between abundance and environmental covariates. Spatial Poisson process likelihoods can be used to simultaneously estimate detection and intensity parameters by modeling distance sampling data as a thinned spatial point process. A model-based spatial approach to distance sampling data has three main benefits: it allows complex and opportunistic transect designs to be employed, it allows estimation of abundance in small subregions, and it provides a framework to assess the effects of habitat or experimental manipulation on density. We demonstrate the model-based methodology with a small simulation study and analysis of the Dubbo weed data set. In addition, a simple ad hoc method for handling overdispersion is also proposed. The simulation study showed that the model-based approach compared favorably to conventional distance sampling methods for abundance estimation. In addition, the overdispersion correction performed adequately when the number of transects was high. Analysis of the Dubbo data set indicated a transect effect on abundance via Akaike’s information criterion model selection. Further goodness-of-fit analysis, however, indicated some potential confounding of intensity with the detection function.

Hausdorff Distance evaluation of orthodontic accessories' streaking artifacts in 3D model superimposition

The aim of this study was to determine whether image artifacts caused by orthodontic metal accessories interfere with the accuracy of 3D CBCT model superimposition. A human dry skull was subjected three times to a CBCT scan: at first without orthodontic brackets (T1), then with stainless steel brackets bonded without (T2) and with orthodontic arch wires (T3) inserted into the brackets' slots. The registration of image surfaces and the superimposition of 3D models were performed. Within-subject surface distances between T1-T2, T1-T3 and T2-T3 were computed and calculated for comparison among the three data sets. The minimum and maximum Hausdorff Distance units (HDu) computed between the corresponding data points of the T1 and T2 CBCT 3D surface images were 0.000000 and 0.049280 HDu, respectively, and the mean distance was 0.002497 HDu. The minimum and maximum Hausdorff Distances between T1 and T3 were 0.000000 and 0.047440 HDu, respectively, with a mean distance of 0.002585 HDu. In the comparison between T2 and T3, the minimum, maximum and mean Hausdorff Distances were 0.000000, 0.025616 and 0.000347 HDu, respectively. In the current study, the image artifacts caused by metal orthodontic accessories did not compromise the accuracy of the 3D model superimposition. Color-coded maps of overlaid structures complemented the computed Hausdorff Distances and demonstrated a precise fusion between the data sets.

A complex networks approach for data clustering

This work proposes a method for data clustering based on complex networks theory. A data set is represented as a network by considering different metrics to establish the connection between each pair of objects. The clusters are obtained by taking into account five community detection algorithms. The network-based clustering approach is applied in two real-world databases and two sets of artificially generated data. The obtained results suggest that the exponential of the Minkowski distance is the most suitable metric to quantify the similarities between pairs of objects. In addition, the community identification method based on the greedy optimization provides the best cluster solution. We compare the network-based clustering approach with some traditional clustering algorithms and verify that it provides the lowest classification error rate. (C) 2012 Elsevier B.V. All rights reserved.

Bioenergetics and neuromuscular determinants of the time to exhaustion at velocity corresponding to (V) over dotO(2)max in recreational long-distance runners

Bertuzzi, R, Bueno, S, Pasqua, LA, Acquesta, FM, Batista, MB, Roschel, H, Kiss, MAPDM, Serrao, JC, Tricoli, V, and Ugrinowitsch, C. Bioenergetics and neuromuscular determinants of the time to exhaustion at velocity corresponding to (V) over dotO(2)max in recreational long-distance runners. J Strength Cond Res 26(8): 2096-2102, 2012-The purpose of this study was to investigate the main bioenergetics and neuromuscular determinants of the time to exhaustion (T-lim) at the velocity corresponding to maximal oxygen uptake in recreational long-distance runners. Twenty runners performed the following tests on 5 different days: (a) maximal incremental treadmill test, (b) 2 submaximal tests to determine running economy and vertical stiffness, (c) exhaustive test to measured the T-lim, (d) maximum dynamic strength test, and (e) muscle power production test. Aerobic and anaerobic energy contributions during the T-lim test were also estimated. The stepwise multiple regression method selected 3 independent variables to explain T-lim variance. Total energy production explained 84.1% of the shared variance (p = 0.001), whereas peak oxygen uptake ((V) over dotO(2)peak) measured during T-lim and lower limb muscle power ability accounted for the additional 10% of the shared variance (p = 0.014). These data suggest that the total energy production, (V) over dotO(2)peak, and lower limb muscle power ability are the main physiological and neuromuscular determinants of T-lim in recreational long-distance runners.

Effect of surface area and air-drying distance on shear bond strength of etch-and-rinse adhesive

We evaluated the effects of air-drying distance and bond surface area on the shear bond strength of a 2-step etch-and-rinse adhesive. A total of 120 bovine anterior teeth were equally divided into 6 main groups based on bonding surface area. The main groups were divided into sub-groups (n = 5) according to air-drying distance. The shear strength was determined using a universal testing machine at a crosshead speed of 0.5 mm/min. The averaged results were subjected to two-way ANOVA and Tukey's test (alpha = 0.05). Two-way ANOVA testing identified no significant cross-product interactions (p > 0.05), but the main factors of area (p < 0.0001) and air-drying distance (p < 0.00001) significantly affected the mean bond strength. Shorter air-drying distances improved bond strength, and increased surface area decreased the bond strength.

MRKAd5 HIV-1 Gag/Pol/Nef Vaccine-Induced T-Cell Responses Inadequately Predict Distance of Breakthrough HIV-1 Sequences to the Vaccine or Viral Load

Background: The sieve analysis for the Step trial found evidence that breakthrough HIV-1 sequences for MRKAd5/HIV-1 Gag/Pol/Nef vaccine recipients were more divergent from the vaccine insert than placebo sequences in regions with predicted epitopes. We linked the viral sequence data with immune response and acute viral load data to explore mechanisms for and consequences of the observed sieve effect. Methods: Ninety-one male participants (37 placebo and 54 vaccine recipients) were included; viral sequences were obtained at the time of HIV-1 diagnosis. T-cell responses were measured 4 weeks post-second vaccination and at the first or second week post-diagnosis. Acute viral load was obtained at RNA-positive and antibody-negative visits. Findings: Vaccine recipients had a greater magnitude of post-infection CD8+ T cell response than placebo recipients (median 1.68% vs 1.18%; p = 0.04) and greater breadth of post-infection response (median 4.5 vs 2; p = 0.06). Viral sequences for vaccine recipients were marginally more divergent from the insert than placebo sequences in regions of Nef targeted by pre-infection immune responses (p = 0.04; Pol p = 0.13; Gag p = 0.89). Magnitude and breadth of pre-infection responses did not correlate with distance of the viral sequence to the insert (p. 0.50). Acute log viral load trended lower in vaccine versus placebo recipients (estimated mean 4.7 vs 5.1) but the difference was not significant (p = 0.27). Neither was acute viral load associated with distance of the viral sequence to the insert (p>0.30). Interpretation: Despite evidence of anamnestic responses, the sieve effect was not well explained by available measures of T-cell immunogenicity. Sequence divergence from the vaccine was not significantly associated with acute viral load. While point estimates suggested weak vaccine suppression of viral load, the result was not significant and more viral load data would be needed to detect suppression.

End-to-end Distance Distribution in Fluorescent Derivatives of Bradykinin in Interaction with Lipid Vesicles

Cellular membranes have relevant roles in processes related to proteases like human kallikreins and cathepsins. As enzyme and substrate may interact with cell membranes and associated co-factors, it is important to take into account the behavior of peptide substrates in the lipid environment. In this paper we report an study based on energy transfer in two bradykinin derived peptides labeled with the donor-acceptor pair Abz/Eddnp (ortho-aminobenzoic acid/N-[2,4-dinitrophenyl]-ethylenediamine). Time-resolved fluorescence experiments were performed in phosphate buffer and in the presence of large unilamelar vesicles of phospholipids, and of micelles of sodium dodecyl sulphate (SDS). The decay kinetics were analyzed using the program CONTIN to obtain end-to-end distance distribution functions f(r). Despite of the large difference in the number of residues the end-to-end distance of the longer peptide (9 amino acid residues) is only 20 % larger than the values obtained for the shorter peptide (5 amino acid residues). The proline residue, in position 4 of the bradykinin sequence promotes a turn in the longer peptide chain, shortening its end-to-end distance. The surfactant SDS has a strong disorganizing effect, substantially broadening the distance distributions, while temperature increase has mild effects in the flexibility of the chains, causing small increase in the distribution width. The interaction with phospholipid vesicles stabilizes more compact conformations, decreasing end-to-end distances in the peptides. Anisotropy experiments showed that rotational diffusion was not severely affected by the interaction with the vesicles, suggesting a location for the peptides in the surface region of the bilayer, a result consistent with small effect of lipid phase transition on the peptides conformations.

Quality Metric to Assess Video Streaming Service over TCP considering Temporal Location of Pauses

There is a wide range of video services over complex transmission networks, and in some cases end users fail to receive an acceptable quality level. In this paper, the different factors that degrade users' quality of experience (QoE) in video streaming service that use TCP as transmission protocol are studied. In this specific service, impairment factors are: number of pauses, their duration and temporal location. In order to measure the effect that each temporal segment has in the overall video quality, subjective tests. Because current subjective test methodologies are not adequate to assess video streaming over TCP, some recommendations are provided here. At the application layer, a customized player is used to evaluate the behavior of player buffer, and consequently, the end user QoE. Video subjective test results demonstrate that there is a close correlation between application parameters and subjective scores. Based on this fact, a new metrics named VsQM is defined, which considers the importance of temporal location of pauses to assess the user QoE of video streaming service. A useful application scenario is also presented, in which the metrics proposed herein is used to improve video services(1).

Toward the optimal dose metric in continuous renal replacement therapy

Purpose: There is no consensus on the optimal method to measure delivered dialysis dose in patients with acute kidney injury (AKI). The use of direct dialysate-side quantification of dose in preference to the use of formal blood-based urea kinetic modeling and simplified blood urea nitrogen (BUN) methods has been recommended for dose assessment in critically-ill patients with AKI. We evaluate six different blood-side and dialysate-side methods for dose quantification. Methods: We examined data from 52 critically-ill patients with AKI requiring dialysis. All patients were treated with pre-dilution CWHDF and regional citrate anticoagulation. Delivered dose was calculated using blood-side and dialysis-side kinetics. Filter function was assessed during the entire course of therapy by calculating BUN to dialysis fluid urea nitrogen (FUN) ratios q/12 hours. Results: Median daily treatment time was 1,413 min (1,260-1,440). The median observed effluent volume per treatment was 2,355 mL/h (2,060-2,863) (p<0.001). Urea mass removal rate was 13.0 +/- 7.6 mg/min. Both EKR (r(2)=0.250; p<0.001) and K-D (r(2)=0.409; p<0.001) showed a good correlation with actual solute removal. EKR and K-D presented a decline in their values that was related to the decrease in filter function assessed by the FUN/BUN ratio. Conclusions: Effluent rate (ml/kg/h) can only empirically provide an estimated of dose in CRRT. For clinical practice, we recommend that the delivered dose should be measured and expressed as K-D. EKR also constitutes a good method for dose comparisons over time and across modalities.

A Homonuclear Rotational Echo Double-Resonance Method for Measuring Site-Resolved Distance Distributions in I=1/2 Spin Pairs, Clusters, and Multispin Systems

Deutsche Forschungsgemeinschaft [SFB 858]

Effect of the relationship between particle size, inter-particle distance, and metal loading of carbon supported fuel cell catalysts on their catalytic activity

The effect of the relationship between particle size (d), inter-particle distance (x(i)), and metal loading (y) of carbon supported fuel cell Pt or PtRu catalysts on their catalytic activity, based on the optimum d (2.5-3 nm) and x(i)/d (>5) values, was evaluated. It was found that for y < 30 wt%, the optimum values of both d and x(i)/d can be always obtained. For y >= 30 wt%, instead, the positive effect of a thinner catalyst layer of the fuel cell electrode than that using catalysts with y < 30 wt% is concomitant to a decrease of the effective catalyst surface area due to an increase of d and/or a decrease of x(i)/d compared to their optimum values, with in turns gives rise to a decrease in the catalytic activity. The effect of the x(i)/d ratio has been successfully verified by experimental results on ethanol oxidation on PtRu/C catalysts with same particle size and same degree of alloying but different metal loading. Tests in direct ethanol fuel cells showed that, compared to 20 wt% PtRu/C, the negative effect of the lower x(i)/d on the catalytic activity of 30 and 40 wt% PtRu/C catalysts was superior to the positive effect of the thinner catalyst layer.

Long-distance correlations in TCABR biasing experiments

Long-distance correlations (LDCs) of plasma potential fluctuations in the plasma edge have been investigated in the TCABR tokamak in the regime of edge biasing H-mode using an array of multi-pin Langmuir probes. This activity was carried out as part of the scientific programme of the 4th IAEA Joint Experiment (2009). The experimental data confirm the effect of amplification of LDCs in potential fluctuations during biasing recently observed in stellarators and tokamaks. For long toroidal distances between probes, the cross-spectrum is concentrated at low frequencies f < 60 kHz with peaks at f < 5 kHz, f = 13-15 kHz and f similar to 40 kHz and low wave numbers with a maximum at k = 0. The effects of MHD activity on the LDCs in potential fluctuation are investigated.

Preoperative 6-min walking distance does not predict pulmonary complications in upper abdominal surgery

Background and objective: Field exercise tests have been increasingly used for pulmonary risk assessment. The 6-min walking distance (6MWD) is a field test commonly employed in clinical practice; however, there is limited evidence supporting its use as a risk assessment method in abdominal surgery. The aim was to assess if the 6MWD can predict the development of post-operative pulmonary complications (PPCs) in patients having upper abdominal surgery (UAS). Methods: This prospective cohort study included 137 consecutive subjects undergoing elective UAS. Subjects performed the 6MWD on the day prior to surgery, and their performance were compared with predicted values of 6MWD (p6MWD) using a previously validated formula. PPCs (including pneumonia, tracheobronchitis, atelectasis with clinical repercussions, bronchospasm and acute respiratory failure) were assessed daily by a pulmonologist blinded to the 6MWD results. 6MWD and p6MWD were compared between subjects who developed PPC (PPC group) and those who did not (no PPC group) using Student's t-test. Results: Ten subjects experienced PPC (7.2%) and no significant difference was observed between the 6MWD obtained in the PPC group and no PPC group (466.0 +/- 97.0 m vs 485.3 +/- 107.1 m; P = 0.57, respectively). There was also no significant difference observed between groups for the p6MWD (100.7 +/- 29.1% vs 90.6 -/+ 20.9%; P > 0.05). Conclusions: The results of the present study suggest that the 6-min walking test is not a useful tool to identify subjects with increased risk of developing PPC following UAS.

Relationship between global structural parameters and Enzyme Commission hierarchy: Implications for function prediction

In protein databases there is a substantial number of proteins structurally determined but without function annotation. Understanding the relationship between function and structure can be useful to predict function on a large scale. We have analyzed the similarities in global physicochemical parameters for a set of enzymes which were classified according to the four Enzyme Commission (EC) hierarchical levels. Using relevance theory we introduced a distance between proteins in the space of physicochemical characteristics. This was done by minimizing a cost function of the metric tensor built to reflect the EC classification system. Using an unsupervised clustering method on a set of 1025 enzymes, we obtained no relevant clustering formation compatible with EC classification. The distance distributions between enzymes from the same EC group and from different EC groups were compared by histograms. Such analysis was also performed using sequence alignment similarity as a distance. Our results suggest that global structure parameters are not sufficient to segregate enzymes according to EC hierarchy. This indicates that features essential for function are rather local than global. Consequently, methods for predicting function based on global attributes should not obtain high accuracy in main EC classes prediction without relying on similarities between enzymes from training and validation datasets. Furthermore, these results are consistent with a substantial number of studies suggesting that function evolves fundamentally by recruitment, i.e., a same protein motif or fold can be used to perform different enzymatic functions and a few specific amino acids (AAs) are actually responsible for enzyme activity. These essential amino acids should belong to active sites and an effective method for predicting function should be able to recognize them. (C) 2012 Elsevier Ltd. All rights reserved.