Ergonomic Aspects of a Virtual Environment

A virtual environment is an interactive graphic system mediated through computer technology that allows a certain level of reality or a sense of presence to access virtual information. To create reality in a virtual environment, ergonomics issues are explored in this paper, aiming to develop the design of presentation formats with related information, that is possible to attain and to maintain user-friendly application.     

Experimental investigation of hydrogen–air deflagrations and detonations in semi-confined flat layers

This paper presents results of an experimental investigation on the deflagration and deflagration-to-detonation transition (DDT) in an obstructed (blockage ratio BR = 50%), semi-confined flat layer filled with uniform hydrogen–air mixtures. The effect of mixture reactivity depending on flat layer thickness and its width is studied to evaluate the critical conditions for sonic flame propagation and the possibility for detonation onset. The experiments were performed in a transparent, rectangular channel with a length of 2.5 m. The flat layer thickness was varied from 0.06 to 0.24 m and the experiments were performed for different channel widths of 0.3, 0.6 and 0.9 m. The experimental results show flame velocity vs. hydrogen concentration for different thicknesses and widths of the semi-confined flat layer. Three different flame propagation regimes were observed: slow subsonic flame (M << 1), sonic deflagration (M ～ 1) and detonation (M >> 1). It is shown that flame acceleration (FA) to sonic speed is independent of the width of the flat layer. The critical expansion ratio for effective flame acceleration to sonic speed was found to be linearly dependent on the reciprocal layer thickness.     

An approach for domino effect reduction based on optimal layouts

An approach to reduce the probability of producing a domino effect in process industry is developed in this work. It is assumed that optimal layouts should include appropriate analysis to reduce risk during the process design stage. The model developed for this approach combines the estimation of probability of damage due to overpressure, proposed by Mingguang and Juncheng (2008), and escalation threshold values defined by Cozzani, Gubinelli, and Salzano (2006). These equations are combined with other typical layout constraints as well as bounding the probability constraint, which has resulted in a highly non-linear MINLP problem. Solving a case study used by other authors provides evidence for reliability of the developed approach. In this way, layouts are designed to reduce the escalation probability yielding safe distributions.     

Worst-case identification of gas dispersion for gas detector mapping using dispersion modeling

To quickly and accurately quantify the material release in process units, gas detectors may be placed according to the results of gas dispersion modeling. DNV's PHAST software is one of the most useful and reliable tools for material dispersion modeling. In this software, fluid dispersion is modeled based on the process conditions, the weather conditions and the specifications of the material release point. However, varying weather conditions throughout the year and the exact determination of the release point on the plot plan and the release elevation are problematic; these issues cause the results to be non-exact and non-integrated. Choosing the most appropriate conditions is challenging. In this paper, a scheme was provided to select the most appropriate conditions for gas dispersion modeling. This scheme approaches modeling based on the worst-case scenario (the situation in which the dispersed gas reaches the detector later in comparison to the other cases). Therefore, different weather conditions, release elevations and release points on the plot plan were modeled for an absorber tower of the Gonbadli Dehydration Unit of the Khangiran Refinery. The worst case of each release condition was then chosen. Finally, gas detectors were placed using the gas dispersion modeling results based on the worst-case scenario.     

Media surface properties and the development of nitrifying biofilms in mixed cultures for wastewater treatment

Plastic was tested to select biofilm support media that would enhance nitrification in the presence of heterotrophs. Eight different types (acrylonitrile butadiene styrene, nylon, polycarbonate, polyethylene, polypropylene, polytetrafluoroethylene (PTFE), polyvinyl chloride and tufnol) were immersed in an aerobic fed-batch reactor receiving domestic settled wastewater. Nitrification rates did not correlate with biomass concentrations, nor surface roughness of the plastics as measured by atomic force microscopy (AFM). The maximum nitrification rate of 1.5 g/m² d^?1 was obtained from biofilms growing on PTFE which had the lowest surface adhesion force (8 nN). Nitrification rates for the biofilms were inversely correlated with the attraction forces as measured by AFM.     

Biological methane production coupled with sulfur oxidation in a microbial electrosynthesis system without organic substrates

Methane is produced in a microbial electrosynthesis system (MES) without organic substrates. However, a relatively high applied voltage is required for the bioelectrical reactions. In this study, we demonstrated that electrotrophic methane production at the biocathode was achieved even at a very low voltage of 0.1 V in an MES, in which abiotic HS⁻ oxidized to SO₄²⁻ at the anodic carbon-cloth surface coated with platinum powder. In addition, microbial community analysis revealed the most probable pathway for methane production from electrons. First, electrotrophic H₂ was produced by syntrophic bacteria, such as Syntrophorhabdus, Syntrophobacter, Syntrophus, Leptolinea, and Aminicenantales, with the direct acceptance of electrons at the biocathode. Subsequently, most of the produced H₂ was converted to acetate by homoacetogens, such as Clostridium and Spirochaeta 2. In conclusion, the majority of the methane was indirectly produced by a large population of acetoclastic methanogens, namely Methanosaeta, via acetate. Further, hydrogenotrophic methanogens, including Methanobacterium and Methanolinea, produced methane via H₂.     

Effects of productivity on biodiversity in forest ecosystems across the United States and China

In the global campaign against biodiversity loss in forest ecosystems, land managers need to know the status of forest biodiversity, but practical guidelines for conserving biodiversity in forest management are lacking. A major obstacle is the incomplete understanding of the relationship between site primary productivity and plant diversity, due to insufficient ecosystem‐wide data, especially for taxonomically and structurally diverse forest ecosystems. We investigated the effects of site productivity (the site's inherent capacity to grow timber) on tree species richness across 19 types of forest ecosystems in North America and China through 3 ground‐sourced forest inventory data sets (U.S. Forest Inventory and Analysis, Cooperative Alaska Forest Inventory, and Chinese Forest Management Planning Inventory). All forest types conformed to a consistent and highly significant (P < 0.001) hump‐shaped unimodal relationship, of which the generalized coefficients of determination averaged 20.5% over all the forest types. That is, tree species richness first increased as productivity increased at a progressively slower rate, and, after reaching a maximum, richness started to decline. Our consistent findings suggest that forests of high productivity would sustain few species because they consist mostly of flat homogeneous areas lacking an environmental gradient along which a diversity of species with different habitats can coexist. The consistency of the productivity–biodiversity relationship among the 3 data sets we examined makes it possible to quantify the expected tree species richness that a forest stand is capable of sustaining, and a comparison between the actual species richness and the sustainable values can be useful in prioritizing conservation efforts.     

Vocal Activity as a Low Cost and Scalable Index of Seabird Colony Size

Although wildlife conservation actions have increased globally in number and complexity, the lack of scalable, cost‐effective monitoring methods limits adaptive management and the evaluation of conservation efficacy. Automated sensors and computer‐aided analyses provide a scalable and increasingly cost‐effective tool for conservation monitoring. A key assumption of automated acoustic monitoring of birds is that measures of acoustic activity at colony sites are correlated with the relative abundance of nesting birds. We tested this assumption for nesting Forster's terns (Sterna forsteri) in San Francisco Bay for 2 breeding seasons. Sensors recorded ambient sound at 7 colonies that had 15–111 nests in 2009 and 2010. Colonies were spaced at least 250 m apart and ranged from 36 to 2,571 m². We used spectrogram cross‐correlation to automate the detection of tern calls from recordings. We calculated mean seasonal call rate and compared it with mean active nest count at each colony. Acoustic activity explained 71% of the variation in nest abundance between breeding sites and 88% of the change in colony size between years. These results validate a primary assumption of acoustic indices; that is, for terns, acoustic activity is correlated to relative abundance, a fundamental step toward designing rigorous and scalable acoustic monitoring programs to measure the effectiveness of conservation actions for colonial birds and other acoustically active wildlife. La Actividad Vocal como un Índice Escalable y de Bajo Costo del Tamaño de Colonia de las Aves Marinas     

Spatial Patterns of Breeding Success of Grizzly Bears Derived from Hierarchical Multistate Models

Conservation programs often manage populations indirectly through the landscapes in which they live. Empirically, linking reproductive success with landscape structure and anthropogenic change is a first step in understanding and managing the spatial mechanisms that affect reproduction, but this link is not sufficiently informed by data. Hierarchical multistate occupancy models can forge these links by estimating spatial patterns of reproductive success across landscapes. To illustrate, we surveyed the occurrence of grizzly bears (Ursus arctos) in the Canadian Rocky Mountains Alberta, Canada. We deployed camera traps for 6 weeks at 54 surveys sites in different types of land cover. We used hierarchical multistate occupancy models to estimate probability of detection, grizzly bear occupancy, and probability of reproductive success at each site. Grizzly bear occupancy varied among cover types and was greater in herbaceous alpine ecotones than in low‐elevation wetlands or mid‐elevation conifer forests. The conditional probability of reproductive success given grizzly bear occupancy was 30% (SE = 0.14). Grizzly bears with cubs had a higher probability of detection than grizzly bears without cubs, but sites were correctly classified as being occupied by breeding females 49% of the time based on raw data and thus would have been underestimated by half. Repeated surveys and multistate modeling reduced the probability of misclassifying sites occupied by breeders as unoccupied to <2%. The probability of breeding grizzly bear occupancy varied across the landscape. Those patches with highest probabilities of breeding occupancy—herbaceous alpine ecotones—were small and highly dispersed and are projected to shrink as treelines advance due to climate warming. Understanding spatial correlates in breeding distribution is a key requirement for species conservation in the face of climate change and can help identify priorities for landscape management and protection. Patrones Espaciales del Éxito Reproductivo de Osos Pardos, Derivados de Modelos Jerárquicos Multi‐Estado     

Using empirical models of species colonization under multiple threatening processes to identify complementary threat‐mitigation strategies

Approaches to prioritize conservation actions are gaining popularity. However, limited empirical evidence exists on which species might benefit most from threat mitigation and on what combination of threats, if mitigated simultaneously, would result in the best outcomes for biodiversity. We devised a way to prioritize threat mitigation at a regional scale with empirical evidence based on predicted changes to population dynamics—information that is lacking in most threat‐management prioritization frameworks that rely on expert elicitation. We used dynamic occupancy models to investigate the effects of multiple threats (tree cover, grazing, and presence of an hyperaggressive competitor, the Noisy Miner (Manorina melanocephala) on bird‐population dynamics in an endangered woodland community in southeastern Australia. The 3 threatening processes had different effects on different species. We used predicted patch‐colonization probabilities to estimate the benefit to each species of removing one or more threats. We then determined the complementary set of threat‐mitigation strategies that maximized colonization of all species while ensuring that redundant actions with little benefit were avoided. The single action that resulted in the highest colonization was increasing tree cover, which increased patch colonization by 5% and 11% on average across all species and for declining species, respectively. Combining Noisy Miner control with increasing tree cover increased species colonization by 10% and 19% on average for all species and for declining species respectively, and was a higher priority than changing grazing regimes. Guidance for prioritizing threat mitigation is critical in the face of cumulative threatening processes. By incorporating population dynamics in prioritization of threat management, our approach helps ensure funding is not wasted on ineffective management programs that target the wrong threats or species.