New Level Of Detail Research Articles

Comprehensive and open model structure for the design of future energy systems with sector coupling

Energy system modeling supports the identification of the optimal technology mix to achieve decarbonization targets across multiple sectors. Especially when sector coupling is considered for future technology landscapes, the large solution space leads to a complex optimization problem in terms of computational feasibility and data requirements. The authors identify a research gap in developing an open-source model structure with consideration of the relevant future technologies of power, heat, other conversions, transport, and industry defined with a new level of detail in a sector-coupled energy world and in including detailed insights into the accompanying definition process. A strong focus is set on the transparency and reproducibility of the provided open-source structure and its flexible and consistent application to different framework families to foster the ease of applicability of this work. The paper first gives a detailed description of the model base, including an overview of the model frame definition process, the core adjustments to model sector coupling appropriately, and the measures to make the resulting problem computationally feasible. The core result of this work is the presentation of a detailed model structure to model sector coupling for a German energy system, yielding approximately 2000 processes that characterize the heterogeneous and technology-open landscape of existing and possible future technologies across relevant energy sectors. This supports energy system modelers in understanding and reproducing energy system models based on open-source data and thereby tries to accelerate the research on sector coupling and its role in the energy transition.

High-resolution assessment of the carrying capacity and utilization intensity in mountain rangelands with remote sensing and field data

Dry rangelands provide resources for half of the world's livestock, but degradation due to overgrazing is a major threat to system sustainability. Existing carrying capacity assessments are limited by low spatiotemporal resolution and high generalization, which hampers applied ecological management decisions. This paper provides an example for deriving the carrying capacity and utilization levels for cold drylands at a new level of detail by including major parts of the transhumance system. We combined field data on vegetation biomass and communities, forage quality, productivity, livestock species and quantities, grazing areas and their spatiotemporal variations with Sentinel-2 and MODIS snow cover satellite imagery to develop maps of forage requirements and availability. These products were used to calculate carrying capacity and grazing potential in the Pamir-Hindukush Mountains. Results showed high spatial variability of utilization rates between 5% and 77%. About 30% of the area showed unsustainable grazing above the carrying capacity. Utilization rates displayed strong spatial differences with unsustainable grazing in winter pastures and at lower elevations, and low rates at higher altitudes. The forage requirements of wild herbivores (ungulates and marmots) were estimated to be negligible compared to livestock, with one tenth of the biomass consumption and no increase in unsustainably grazed pastures due to the wider distribution of animals. The assessment was sensitive to model parameterization of forage requirements and demand, whereby conservative scenarios, i.e. lower fodder availability or higher fodder requirements of livestock due to climate and altitude effects, increased the area with unsustainable grazing practices to 50%. The presented approach enables an in-depth evaluation of the carrying capacity and corresponding management actions. It includes new variables relevant for transhumance systems, such as the combination of forage quantity and quality or accessibility restrictions due to snow, and shows utilization patterns at high spatial resolutions. Regional maps allow the identification of unsustainable utilization areas, such as winter pastures in this study.

Coevolution and smFRET Enhances Conformation Sampling and FRET Experimental Design in Tandem PDZ1-2 Proteins.

The structural flexibility of proteins is crucial for their functions. Many experimental and computational approaches can probe protein dynamics across a range of time and length-scales. Integrative approaches synthesize the complementary outputs of these techniques and provide a comprehensive view of the dynamic conformational space of proteins, including the functionally relevant limiting conformational states and transition pathways between them. Here, we introduce an integrative paradigm to model the conformational states of multidomain proteins. As a model system, we use the first two tandem PDZ domains of postsynaptic density protein 95. First, we utilize available sequence information collected from genomic databases to identify potential amino acid interactions in the PDZ1-2 tandem that underlie modeling of the functionally relevant conformations maintained through evolution. This was accomplished through combination of coarse-grained structural modeling with outputs from direct coupling analysis measuring amino acid coevolution, a hybrid approach called SBM+DCA. We recapitulated five distinct, experimentally derived PDZ1-2 tandem conformations. In addition, SBM+DCA unveiled an unidentified, twisted conformation of the PDZ1-2 tandem. Finally, we implemented an integrative framework for the design of single-molecule Förster resonance energy transfer (smFRET) experiments incorporating the outputs of SBM+DCA with simulated FRET observables. This resulting FRET network is designed to mutually resolve the predicted limiting state conformations through global analysis. Using simulated FRET observables, we demonstrate that structural modeling with the newly designed FRET network is expected to outperform a previously used empirical FRET network at resolving all states simultaneously. Integrative approaches to experimental design have the potential to provide a new level of detail in characterizing the evolutionarily conserved conformational landscapes of proteins, and thus new insights into functional relevance of protein dynamics in biological function.

Compound specific δ15N analysis of amino acids reveals unique sources and differential cycling of high and low molecular weight marine dissolved organic nitrogen

Marine dissolved organic nitrogen is the largest pool of reduced nitrogen (N) in the ocean. Yet, despite indications of a bacterial origin, few N-specific approaches have been developed to trace individual microbial N production and degradation mechanisms. Stable nitrogen isotope ratios (δ15N) are one of the most powerful tools to understand sources and cycling of organic N. However, δ15N measurements of total DON can only be made in the surface ocean and interpretations are complicated by the many factors influencing bulk δ15N values. Compound-specific isotope analysis of amino acids (CSI-AA) on isolated DON fractions represents a new approach for DON study throughout the water column with significantly greater information potential. Here, we compare for the first time δ15N amino acid (δ15N-AA) data on baseline inorganic N source and microbial loop processing in coupled ultrafiltered high molecular weight (HMW) and solid-phase extracted low molecular weight (LMW SPE-) DON from the surface to 2500 m deep in the Atlantic and Pacific Subtropical Gyres.δ15N-AA patterns were very different in HMW versus LMW SPE-DON, indicating unique formation and bacterial alteration mechanisms. HMW DON data supported a prior hypothesis that AA in surface HMW DON originate from heterotrophic bacterial production near the nitracline, but also suggests protozoan heterotrophy as an additional major process. In the mesopelagic, distinct HMW DON δ15N-AA patterns suggest heterotrophic bacterial resynthesis of suspended PON. In contrast, the first LMW DON δ15N-AA patterns were surprisingly similar to those of autotrophs, indicating limited resynthesis at any depth. Taken together with prior biomarker data, we hypothesize a direct bacterial surface source of LMW AA-containing molecules which are inherently refractory. Finally, within each size fraction, δ15N-AA patterns were remarkably similar between Station ALOHA and the BATS site, suggesting our findings can be extended to marine DON at least throughout global subtropical gyres.These findings demonstrate CSI-AA as a novel δ15N tool to understand sources and cycling of marine DON at a new level of detail and suggest a significant shift in our understanding of DON source and cycling. Specifically, we hypothesize that the production and degradation mechanisms of LMW AA-containing DON is fundamentally distinct from HMW DON, and that the majority of LMW refractory DON in the sea derives not from degradation of HMW material, but rather from surface production of intrinsically more refractory LMW molecules.

Moving beyond the language–Visualizing chemical concepts through one’s own creative expression

The aim of the study was to explore university students’ interpretations of chemical content in the form of physical constructions of atomic nuclei. Playdough was chosen as the means for expression, since it provided the students with the task of choosing the number, form, size, shape, and distance of particles. Data was collected in the form of photographs, written explanations as well as ad hoc notes. Data from 64 students was analyzed using the three levels of analysis as presented by Hedegaard and framed within the theories of models. Results show that students’ choices gave rise to 34 variations of the atomic nuclei. The analysis provided two different categories: models with close resemblance to the teaching model and models with less resemblance to the teaching model. Results show the limitations of verbal and written communication and add to the discussion concerning students’ interpretations of the multitude of atomic models used in teaching. The method was indeed a beneficial tool both for students, who could explore the composition of atomic nuclei and isotopes, and for teachers, who could connect their teaching to students’ interpretations of scientific content since the method brings a new level of detail to discussions.

Mahuika‐Auckland: A spatially and temporally resolved fossil fuel CO2 emissions data product for Auckland, New Zealand

AbstractAccurate, high‐resolution and sector‐specific greenhouse gas emissions information is increasingly needed for the development of local, targeted mitigation policies. We describe a detailed, spatially and temporally resolved CO2 emissions data product, Mahuika‐Auckland, for Auckland, New Zealand, based on Auckland's regional greenhouse gas and air emissions inventories. Emissions are provided at 500 m spatial resolution and at a 1‐hr time step, a level of detail not previously available for any New Zealand city. We divide fossil fuel emissions into six sectors that comprise the majority of Auckland Region's CO2 emissions profile: on‐road transport, industrial non‐point buildings and point sources, commercial non‐point buildings, residential non‐point buildings, air transport and sea transport. We also include separate layers representing biogenic CO2 emissions (primarily waste and wood burning), as these are significant sources in Auckland. We distribute emissions spatially and temporally based on activity data, energy and fuel consumption patterns, and population statistics. The code to generate Mahuika‐Auckland has been designed to be flexible so that updated information and/or data from more recent years can easily be incorporated. This data product improves upon New Zealand's current inventories that are only resolved at the regional and annual scale, providing a new level of detail that can be used as a prior estimate for atmospheric inversions, to inform emissions reduction policies and to guide the development of zero carbon pathways.

Indwelling robots for ruminant health monitoring: A review of elements

Maximizing the health, productivity, and sustainability of ruminant animals is an essential societal goal for a variety of reasons including food security, impact on the environment, and global nutrition; however, monitoring the metabolism of ruminant animals is currently a time-consuming and imprecise process. An indwelling robot residing within the ruminant gut would likely revolutionize metabolic monitoring in ruminants by providing a new level of detail into the complex and stratified chemistry of fermentation that goes on hour by hour. Indwelling robots could become an essential tool for ruminant health monitoring because many of the health, productivity, and sustainability challenges experienced by ruminants can be indicated and potentially influenced by changes in biomarkers within the rumen. We believe next-generation ruminant health monitoring will evolve from continuous biomarker measurement, reliable data transmission, and precise locomotion, all of which can be enabled by advances in indwelling ruminal robot design. Within this review, we summarize the requirements of and progress toward engineering advancements necessary to develop field-deployable robots for ruminant metabolic monitoring. The vital elements of an autonomous indwelling medical robot include locomotion, localization, wireless data transmission, and wireless power transfer. The state-of-the-art technologies associated with each element are articulated in this review. The comprehensive techniques of locomotion, the approaches for precise localization, as well as technologies for wireless power and data transmission that will make the indwelling robot entirely autonomous are enunciated, with a special focus on ruminants. The evaluated indices are potentially useful not only to assess the health of the ruminant but also to refine and standardize the assessment protocols. The overview presented in this article on the advances, imperative requirements, and challenges enables the deployment of the ruminal robot for health monitoring in ruminants.

Scan strategies in EBM-printed IN718 and the physics of bulk 3D microstructure development

Three-dimensional (3D) characterization provides opportunities for understanding processing-structure relationships in additively manufactured (AM) materials. Bulk samples of Inconel 718 were fabricated via electron beam melting (EBM) in order to study microstructural development as a function of energy input and beam scan strategy. TriBeam tomography of bulk Inconel 718 microstructures built under steady-state growth conditions reveals the sensitivity of microstructure formation and evolution to machine process parameters. In this study, samples manufactured using a narrow range of energy input per unit build area result in varied grain morphologies and crystallographic textures. Using TRUCHAS, a thermal simulation software, the thermal history of bulk scan strategies was predicted, and combined with a calibrated microstructure-processing map to accurately predict bulk grain morphologies. The solidification parameters and the 3D measured nucleation density are used to predict the transition between columnar and equiaxed grain morphologies, providing a process map to guide AM parameter choices to locally control as-printed microstructure. A two-dimensional metric for characterizing bulk grain morphology was also found to agree well with predictions from the process map calibrated by 3D data. Combined with 3D tomography and thermal modelling, the physics of structure development were understood at a new level of detail with respect to the competing processes of grain nucleation and epitaxial growth.

Distinct Populations of Spinal Projection Neurons Mediate Divergent Functions for Pain and Sensorimotor Integration

Pain is believed to be relayed from the spinal cord to brain through two major ascending pathways. One arises largely from the superficial dorsal horn, primarily targets the parabrachial nucleus (PBN), and is thought to mediate the aversive component of pain. The other arises predominantly from the deep dorsal horn, primarily targets the rostral aspect of the ventral posterior lateral (VPL) thalamus, and is thought to mediate the discriminative component of pain. However, the precise roles of these two populations have been a subject of ongoing controversy. Here, we investigate the anatomy and function of these output pathways at a new level of detail. Our study provides evidence that spinal-PBN neurons and spinal rostral VPL (rVPL) neurons are two distinct populations with different molecular characteristics by in situ hybridization and distinct patterns of collateralization through separate axon tracts. Chemogenetic activation of spinal-PBN neurons elicited spontaneous site-oriented nociceptive behavior (flinching/guarding and licking), and their collateral terminals were somatotopically organized in periductal gray (PAG) and caudal VPL. Moreover, optogenetic activation of different terminals of spinal-PBN neurons elicited distinct nociceptive behaviors. Meanwhile, chemogentic activation of spinal-rVPL neurons did not elicit spontaneous nociceptive behavior. Conversely, chemogenetically inhibiting spinal-rVPL neurons or VPL excitatory neurons did not affect pain behaviors but gave rise to a defect in fine motor coordination. Together, these findings challenge the current dogma and suggest that superficial spinal output neurons have a prominent role in conveying pain to the brain, whereas deep layer spinal output neurons are more likely to be involved in sensorimotor integration.

Potential of Deep Learning Methods for Deep Level Particle Characterization in Crystallization

Crystalline particle properties, which are defined throughout the crystallization process chain, are strongly tied to the quality of the final product bringing along the need of detailed particle characterization. The most important characteristics are the size, shape and purity, which are influenced by agglomeration. Therefore, a pure size determination is often insufficient and a deep level evaluation regarding agglomerates and primary crystals bound in agglomerates is desirable as basis to increase the quality of crystalline products. We present a promising deep learning approach for particle characterization in crystallization. In an end-to-end fashion, the interactions and processing steps are minimized. Based on instance segmentation, all crystals containing single crystals, agglomerates and primary crystals in agglomerates are detected and classified with pixel-level accuracy. The deep learning approach shows superior performance to previous image analysis methods and reaches a new level of detail. In experimental studies, L-alanine is crystallized from aqueous solution. A detailed description of size and number of all particles including primary crystals is provided and characteristic measures for the level of agglomeration are given. This can lead to a better process understanding and has the potential to serve as cornerstone for kinetic studies.

Female Genital Schistosomiasis (FGS) in Cameroon: A formative epidemiological and socioeconomic investigation in eleven rural fishing communities.

Female Genital Schistosomiasis (FGS) is most often caused by presence of Schistosoma haematobium eggs lodged in the female reproductive tract which results in chronic fibrosis and scarring. In Cameroon, despite high community prevalences of urine-patent S. haematobium infections, FGS has yet to be studied in depth. To shed light on the clinical prevalence and socioeconomic effects of FGS, we undertook a formative community-based epidemiological and qualitative survey. A cross sectional multidisciplinary study of 304 girls and women from 11 remote rural fishing communities in Cameroon was undertaken using parasitological sampling, clinical colposcopy, and interviews. The lived experiences of those with FGS were documented using a process of ethnography with participant observation and in-depth interviews. Amongst 304 women and girls aged >5 years (Median age: 18; Interquartile range: 9.6-28), 198 females were eligible for FGS testing and 58 adult women were examined by clinical colposcopy. Of these, 34 were positive for FGS (proportion: 58.6%; 95% CI: 45.8-70.4), younger girls showing a higher FGS prevalence, and older women not shedding eggs showing a pattern for cervical lesions from earlier infection. In a subset of women with FGS selected purposively (12/58), in-depth interviews with participant observation revealed out-of-pocket expenditures of up to 500USD related health spending for repeated diagnosis and treatment of gynecological illnesses, and 9 hours daily lost reproductive labour. Psychosocial unrest, loss in social capital, and despair were linked with sub-fertility and persistent vaginal itch. With our first formative evidence on prevalence, socioeconomic effects and experiences of FGS amongst women and girls in Cameroon, we have clarified to a new level of detail the deficit in provision of and access to peripheral health services in remote areas of Cameroon. Using this information, there is now strong evidence for national programs and services on women's health and schistosomiasis to update and revise policies targeted on prevention and management of FGS. We therefore stress the need for regular provision of Praziquantel treatment to adolescent girls and women in S. haematobium endemic areas, alongside better access to tailored diagnostic services that can detect FGS and appropriately triage care at primary health level.

Integration of Laser Scanner and Photogrammetry for Heritage BIM Enhancement

Digital 3D capture and reliable reproduction of architectural features is the first and most difficult step towards defining a heritage BIM. Three-dimensional digital survey technologies, such as TLS and photogrammetry, enable experts to scan buildings with a new level of detail. Challenges in the tracing of parametric objects in a TLS point cloud include the reconstruction of occluded parts, measurement of uncertainties relevant to surface reflectivity, and edge detection and location. In addition to image-based techniques being considered cost effective, highly flexible, and efficient in producing a high-quality 3D textured model, they also provide a better interpretation of surface linear characteristics. This article addresses an architecture survey workflow using photogrammetry and TLS to optimize a point cloud that is sufficient for a reliable HBIM. Fusion-based workflows were proposed during the recording of two heritage sites—the Matbouli House Museum in Historic Jeddah, a UNESCO World Heritage Site; and Asfan Castle. In the Matbouli House Museum building, which is rich with complex architectural features, multi-sensor recording was implemented at different resolutions and levels of detail. The TLS data were used to reconstruct the basic shape of the main structural elements, while the imagery’s superior radiometric data and accessibility were effectively used to enhance the TLS point clouds for improving the geometry, data interpretation, and parametric tracing of irregular objects in the facade. Furthermore, in the workflow that is considered to be the ragged terrain of the Castle of Asfan, here, the TLS point cloud was supplemented with UAV data in the upper building zones where the shadow data originated. Both datasets were registered using an ICP algorithm to scale the photogrammetric data and define their actual position in the construction system. The hybrid scans were imported and processed in the BIM environment. The building components were segmented and classified into regular and irregular surfaces, in order to perform detailed building information modeling of the architectural elements. The proposed workflows demonstrated an appropriate performance in terms of reliable and complete BIM mapping in the complex structures.

Exploring human-nature interactions in national parks with social media photographs and computer vision.

Understanding the activities and preferences of visitors is crucial for managing protected areas and planning conservation strategies. Conservation culturomics promotes the use of user-generated online content in conservation science. Geotagged social media content is a unique source of in situ information on human presence and activities in nature. Photographs posted on social media platforms are a promising source of information, but analyzing large volumes of photographs manually remains laborious. We examined the application of state-of-the-art computer-vision methods to studying human-nature interactions. We used semantic clustering, scene classification, and object detection to automatically analyze photographs taken in Finnish national parks by domestic and international visitors. Our results showed that human-nature interactions can be extracted from user-generated photographs with computer vision. The different methods complemented each other by revealing broad visual themes related to level of the data set, landscape photogeneity, and human activities. Geotagged photographs revealed distinct regional profiles for national parks (e.g., preferences in landscapes and activities), which are potentially useful in park management. Photographic content differed between domestic and international visitors, which indicates differences in activities and preferences. Information extracted automatically from photographs can help identify preferences among diverse visitor groups, which can be used to create profiles of national parks for conservation marketing and to support conservation strategies that rely on public acceptance. The application of computer-vision methods to automatic content analysis of photographs should be explored further in conservation culturomics, particularly in combination with rich metadata available on social media platforms.

A Case Study to Quantify Variability in Building Load Profiles

Recent technology development and penetration of advanced metering infrastructure (AMI), advanced building control systems, and the internet-of-things (IoT) in the built environment are providing detailed information on building operation, performance, and user’s comfort and behavior. Building owners can obtain a wide range of energy consumption details at various levels of time granularity to augment their decisions as they manage the building operation and interact with the grid. AMI data are providing a new level of detail and visibility that may enhance building services and assets in the smart grid domain and make buildings inch closer to becoming a grid-interactive energy efficient buildings (GEB). While utility-installed AMI typically records energy consumption at a 15, 30, or 60-minute resolution, building-owner-installed metering can record energy consumption at one-minute or sub-minute time scales, providing information about how much the energy consumption varies from one sub-minute to the other (i.e. variability) at a finer time resolutions than typically available from AMI. This paper examines one-minute building load profile data sets and presents a framework to study, define, extract, quantify and analyze variability in buildings’ load profiles. The discussion of variability and its analysis is based on a case study of an actual sub-minute time-resolution data set, collected in 2019, for two buildings in a Midwest state in the USA. The result shows that for the case studies, the level of variability in an end-use category is not simply proportional to its consumption. Furthermore, distinct and predictable daily variability patterns emerge in end-use load categories. This information is useful for a host of applications including prediction, forecasting, and modeling.

Pericytes on placental capillaries in terminal villi preferentially cover endothelial junctions in regions furthest away from the trophoblast

IntroductionPericytes are a common feature in the placental microvasculature but their roles are not well understood. Pericytes may provide physical or endocrine support for endothelium and in some tissues mediate vasoconstriction. MethodsThis study uses serial block-face scanning electron microscopy (SBFSEM) to generate three-dimensional (3D) reconstructions of placental pericytes of the terminal villi and transmission electron microscopy (TEM) to study pericyte endothelial cell interactions. The proportion of endothelial cell junctions covered by pericytes was determined. ResultsThe detailed 3D models of placental pericytes show pericyte structure at a new level of detail. Placental pericytes have many fingers extending from the cell body which can span multiple capillary branches. The proportion of endothelial cell-cell junctions covered by pericytes was significantly higher than pericyte coverage of capillary endothelium as a whole (endothelium: 14%, junctions: 43%, p < 0.0001). However, the proportion of endothelial cell-cell junctions covered by pericytes in regions adjacent to trophoblast was reduced compared to regions >3 μm away from trophoblast (27% vs 62% respectively, p < 0.001). No junctional complexes were observed connecting pericytes and endothelial cells but there were regions of cell membrane with features suggestive of intercellular adhesions. DiscussionThese data suggest that the localisation of pericytes on the villous capillary is not random but organised in relation to both endothelial junctions and the location of adjacent trophoblast. This further suggests that pericyte coverage may favour capillary permeability in regions that are most important for exchange, but limit capillary permeability in other regions.

Insight from imaging on plaque vulnerability: similarities and differences between coronary and carotid arteries-implications for systemic therapies.

Nowadays it is widely accepted that the rupture of the atherosclerotic plaque in coronary and carotid arteries plays a fundamental role in the development of acute myocardial infarctions or cerebrovascular events. In recent years, imaging techniques have explored, with a new level of detail, the atherosclerotic disease generating new evidences that some plaque characteristics are significantly associated to the risk of rupture and subsequent thrombosis or embolization. Moreover, the recent evidence of the anti-atherosclerotic effects determined by lipid-lowering and anti-inflammatory therapies poses a challenge for the choice of therapeutic approaches (best/optimal medical therapy vs. revascularization), maximized by the evidence that coronary and carotid atherosclerosis share common patterns but also differ regarding some important features. In this Review, we discuss the similarities and differences between coronary and carotid artery vulnerable plaque from the imaging point of view and the potential implications for systemic therapies according to the emerging evidence.

Davies, J.Q. 2014. Romantic Anatomies of Performance . Berkeley: University Of California Press.

What might a broken clavicle, a urinating Frederic Chopin, the execution of parricides, and Sigismund Thalberg’s “third hand” all have in common? According to James Davies, these practices, accidents, and medical woes share nothing less than a concern for defining musical bodies. Romantic Anatomies of Performance offers a richly detailed history of hands, voices, and the music they made circa 1830. Travelling between London and Paris with the same alacrity as early nineteenth–century musicians, Davies marshals an impressive array of primary sources, including testimony by performers, composers, listeners, critics, and scientific researchers. By thickly describing the conflicts among participants in musical culture, Davies argues that music was itself as a site on which theories and practices of embodiment took shape. Davies’s scholarship contributes to several musicological sub–fields, most notably to the study of music and embodiment. Carolyn Abbate (2004) and Elisabeth Le Guin (2006) have trenchantly re–asserted the centrality of the body for musical experience. Moreover, they have shown how attention to performance’s materialities may generate musical knowledge of a type traditionally outside the purview of musicology. Davies is taking the next step in the study of music and body, as he brings a concern for embodiment to bear on nineteenth–century music in a new level of detail. Such a study is especially germane, as the musical practices cemented in the commercial centers of nineteenth–century Europe were arguably central to the formation of ideologies of modern art music more generally.

Towards Criteria Characterizing the Metrological Performance of Full-field Measurement Techniques

Users of full-field measurement methods like Digital Image Correlation (DIC) often aim to perform measurements with the best trade-off between spatial resolution, bias and measurement resolution. Whenever two full-field methods are compared, it is essential that these criteria are taken into consideration. Recently a metrological efficiency indicator for full-field measurements has been proposed and discussed. This indicator combines measurement resolution and spatial resolution. It has been shown to be invariant to the subset size in the case of Local DIC. The goal of this article is to discuss a method, which determines both the spatial and the measurement resolutions for a given bias for two different DIC methods, in order to obtain the metrological efficiency indicator for each of these methods. The benefit of this indicator is that it does not depend on setting parameters such as the subset size, which are chosen by the user. As such, it can be considered as intrinsic to each technique, thus enabling fair comparison. Local DIC and triangular finite element based Global DIC will be the subject of this investigation. With this setting, their respective subset and triangular element sizes will be related to the spatial resolution of both methods for a given acceptable bias. By using the metrological efficiency indicator, the performance of the two methods will be compared and discussed to a new level of detail. Generally speaking, the indicator shows that the metrological performance of both methods is similar, confirming their popularity. However, it will be shown that, depending on the choice of what an acceptable bias is, one of the method may be preferred to another. The results show that for the specific DIC versions used in the study, for cases for which a significant bias is acceptable, Local DIC outperforms Global DIC, while the opposite is true in the case for which the bias requirements are more stringent. Finally, the quadratic versions of both DIC versions are shown to significantly outperform their respective linear versions.

Universal crossed beam imaging studies of polyatomic reaction dynamics.

The marriage between high level quantum calculations and experimental advances in laser technology, quantum state control, and detection techniques have opened the door to the study of molecular collision dynamics at a new level of detail. However, one current challenge lies in adapting these powerful strategies to address questions beyond the scope of the small ground state systems that have largely been the focus of reaction dynamics investigations to-date. For molecules with intermediate or large size (more than 6 atoms), lack of spectroscopic information and spectral congestion limit quantum state preparation, control and detection for experiment, and the large number of degrees of freedom of the system makes accurate quantum dynamics calculations prohibitively expensive. Nevertheless, studies of the chemical dynamics of such systems can reveal novel aspects of reactivity not anticipated based upon the behavior of smaller model systems. This Perspective will highlight applications of soft vacuum ultraviolet photoionization at 157 nm as a universal probe in combination with crossed beams and DC slice velocity map ion imaging to study bimolecular reaction dynamics of molecules of intermediate or large size, illuminated with support of high-level ab initio calculations. Here, we report on the chemical dynamics of atomic oxygen or chlorine reactions with organic compounds: propanol isomers, alkylamines (N(CH3)3 and NH(CH3)2), and isobutene ((CH3)2CCH2) studied using this approach. The polyatomic radical products from the hydrogen abstraction process have been detected by 157 nm photoionization and their slice ion images embody translational energy and angular information that directly reflect the underlying collision dynamics. Various reaction mechanisms (such as direct abstraction and addition-elimination) along with the involvement of roaming dynamics and novel intersystem crossing pathways are presented. These demonstrate the power of this technique to reveal fundamentally new aspects of reaction dynamics that arise in larger reaction systems.

Dynamics of animal joint space use: a novel application of a time series approach

BackgroundAnimal use is a dynamic phenomenon, emerging from the movements of animals responding to a changing environment. Interactions between animals are reflected in patterns of joint space use, which are also dynamic. High frequency sampling associated with GPS telemetry provides detailed data that capture space use through time. However, common analyses treat joint space use as static over relatively long periods, masking potentially important changes. Furthermore, linking temporal variation in interactions to covariates remains cumbersome. We propose a novel method for analyzing the dynamics of joint space use that permits straightforward incorporation of covariates. This method builds upon tools commonly used by researchers, including kernel density estimators, utilization distribution intersection metrics, and extensions of linear models.MethodsWe treat the intersection of the utilization distributions of two individuals as a time series. The series is linked to covariates using copula-based marginal beta regression, an alternative to generalized linear models. This approach accommodates temporal autocorrelation and the bounded nature of the response variable. Parameters are easily estimated with maximum likelihood and trend and error structures can be modeled separately. We demonstrate the approach by analyzing simulated data from two hypothetical individuals with known utilization distributions, as well as field data from two coyotes (Canis latrans) responding to appearance of a carrion resource in southern Texas.ResultsOur analysis of simulated data indicated reasonably precise estimates of joint space use can be achieved with commonly used GPS sampling rates (s.e.=0.029 at 150 locations per interval). Our analysis of field data identified an increase in spatial interactions between the coyotes that persisted for the duration of the study, beyond the expected duration of the carrion resource. Our analysis also identified a period of increased spatial interactions before appearance of the resource, which would not have been identified by previous methods.ConclusionsWe present a new approach to the analysis of joint space use through time, building upon tools commonly used by ecologists, that permits a new level of detail in the analysis of animal interactions. The results are easily interpretable and account for the nuances of bounded serial data in an elegant way.