Fermions in a loop quantum cosmological spacetime

Differences between the temporal and mandibular components of the temporomandibular joint in topographic distribution of osseous degenerative features on cone-beam computerized tomography

BackgroundAnimal movement arises from complex interactions between animals and their heterogeneous environment. To better understand the movement process, it can be divided into behavioural, temporal and spatial components. Although methods exist to address those various components, it remains challenging to integrate them in a single movement analysis.MethodsWe present an analytic workflow that integrates the behavioural, temporal and spatial components of the movement process and their interactions, which also allows for the assessment of the relative importance of those components. We construct a daily cyclic covariate to represent temporally cyclic movement patterns, such as diel variation in activity, and combine the three components in a multi-modal Hidden Markov Model framework using existing methods and R functions. We compare the trends and statistical fits of models that include or exclude any of the behavioural, spatial and temporal components, and perform variance partitioning on the model predictions that included all components to assess their relative importance to the movement process, both in isolation and in interaction.ResultsWe apply our workflow to a case study on the movements of plains zebra, blue wildebeest and eland antelope in a South African reserve. Behavioural modes impacted movement the most, followed by diel rhythms and then the spatial environment (viz. tree cover and terrain slope). Interactions between the components often explained more of the movement variation than the marginal effect of the spatial environment did on its own. Omitting components from the analysis led either to the inability to detect relationships between input and response variables, resulting in overgeneralisations when drawing conclusions about the movement process, or to detections of questionable relationships that appeared to be spurious.ConclusionsOur analytic workflow can be used to integrate the behavioural, temporal and spatial components of the movement process and quantify their relative contributions, thereby preventing incomplete or overly generic ecological interpretations. We demonstrate that understanding the drivers of animal movement, and ultimately the ecological phenomena that emerge from it, critically depends on considering the various components of the movement process, and especially the interactions between them.

In this paper we present the analytical solution of a one-dimensional (1D) parabolic differential equation (PDE), encountered in many engineering studies under the name of the heat equation. To solve the equation, we use the method of separation of variables together with Fourier series. After applying the separation of variables, the initial equation decomposes into two ordinary differential equations (ODE). The equations obtained correspond to the spatial (x) and temporal (t) components. The spatial solution, for the first equation, is expressed by sinusoidal functions corresponding to the eigenfunctions, and the temporal component, for the second equation, has a characteristic exponential dependence. The determination of the Fourier series coefficients is based on the initial condition. Thus, we constructed an exact solution in the form of convergent series. The method used in solving the equation, together with the boundary conditions and initial conditions, can be used as a reference for validating numerical methods or practical experiments performed in the laboratory.

This paper describes a method for estimating a set of spatial components (brain maps) and temporal components (waveforms) of brain potentials. These components play the role of bases of a coordinate system, in the sense that the brain potentials of any subject can be represented as superpositions of these components. The representation is unique given the spatial and temporal components, and this decomposition is particularly appealing for comparing the brain potentials of different subjects (say alcoholics and controls). It can also be used for single trial modeling, clinical classification of patients, and data filtering. The method is based on the topographic component model (TCM, Möcks 1988) which models brain potentials in a trilinear form. We extend the TCM in two aspects. First, the diagonal amplitude matrix is replaced by a general loading matrix based on some neurophysiological considerations. Secondly, the number of spatial components and the number of temporal components can be different. The spatial components and temporal components are obtained respectively by performing singular value decomposition (SVD). This method is illustrated with visual P3 data.

This paper presents a novel approach to target tracking using a measurement process based on spatio-temporal fractal error. Moving targets are automatically detected using one-dimensional temporal fractal error. A template derived from the two-dimensional spatial fractal error is then extracted for a designated target to allow for correlation-based template matching in subsequent frames. The outputs of both the spatial and temporal fractal error components are combined and presented as input to a kinematic tracking filter. It is shown that combining the two outputs provides improved tracking performance in the presence of noise, occlusion, other moving objects, and when the target of interest stops moving. Furthermore, reconciliation of the spatial and temporal components also provides a useful mechanism for detecting occlusion and avoiding template drift, a problem typically present in correlation-based trackers. Results are demonstrated using airborne MWIR sequences from the DARPA VIVID dataset.

Over the last two decades, considerable research has built on remote sensing of spectral diversity to assess plant diversity. The spectral variation hypothesis (SVH) proposes that spatial variation in reflectance data of an area is positively associated with plant diversity. While the SVH has exhibited validity in dense forests, it performs poorly in highly fragmented and temporally dynamic agricultural landscapes covered mainly by grasslands. Such underperformance can be attributed to the mosaic-like spatial structure of human-dominated landscapes with fields in varying phenological and management stages. Therefore, we argued for re-evaluating SVH’s flawed window-based spatial analysis and underutilized temporal component. In particular, we captured the spatial and temporal variation in reflectance and assessed the relationships between spatial and temporal components of spectral diversity and plant diversity at the parcel level as a unit that relates to management patterns. Our investigation spanned three grasslands on two continents covering a wide spectrum of agricultural usage intensities. To calculate different components of spectral diversity, we used multi-temporal spaceborne Sentinel-2 data. We showed that plant diversity was negatively associated with the temporal component of spectral diversity across all sites. In contrast, the spatial component of spectral diversity was related to plant diversity in sites with larger parcels. Our findings highlighted that in agricultural landscapes, the temporal component of spectral diversity drives the spectral diversity-plant diversity associations. Consequently, our results offer a novel perspective for remote sensing of plant diversity globally.

Evaluating the performance of regional-scale photochemical modeling systems. Part III—Precursor predictions

Perception of dynamic scenes in our environment results from the evaluation of visual features such as the fundamental spatial and temporal frequency components of a moving object. The ratio between these two components represents the object's speed of motion. The human middle temporal cortex hMT+ has a crucial biological role in the direct encoding of object speed. However, the link between hMT+ speed encoding and the spatiotemporal frequency components of a moving object is still under explored. Here, we recorded high resolution 7T blood oxygen level‐dependent BOLD responses to different visual motion stimuli as a function of their fundamental spatial and temporal frequency components. We fitted each hMT+ BOLD response with a 2D Gaussian model allowing for two different speed encoding mechanisms: (1) distinct and independent selectivity for the spatial and temporal frequencies of the visual motion stimuli; (2) pure tuning for the speed of motion. We show that both mechanisms occur but in different neuronal groups within hMT+, with the largest subregion of the complex showing separable tuning for the spatial and temporal frequency of the visual stimuli. Both mechanisms were highly reproducible within participants, reconciling single cell recordings from MT in animals that have showed both encoding mechanisms. Our findings confirm that a more complex process is involved in the perception of speed than initially thought and suggest that hMT+ plays a primary role in the evaluation of the spatial features of the moving visual input.

Micro-Doppler features can be regarded as a unique signature of an object with movements and provide additional information for classification, recognition and identification of the object. Independent component analysis (ICA) can decompose micro-Doppler features into independent basis functions that represent salient physical movement attributes of the object. To study ICA of micro-Doppler features, we used a dataset generated by simulation of radar returned signals from rotating objects and tumbling objects. Fast ICA algorithm was used in our study to decompose micro-Doppler features into a set of spatial and temporal independent components. Spatial characteristics of the independent components combined with the corresponding temporal characteristics can be used to improve performance of classification, recognition and identification.

AimThis study seeks to document and compare historical temporal and spatial components of fire regimes in two watersheds in mixed conifer forests of the western slope of the Sierra Nevada, California, USA.LocationWatersheds in the southern Sierra Nevada (Sugar Pine, 2358 ha) and north‐central Sierra Nevada (Last Chance, 3021 ha), California, USA are compared.MethodsTemporal (frequency, return interval, season) and spatial (extent, fire rotation, spatial mean fire interval) fire regime metrics were reconstructed from fire scar samples. Superposed epoch analysis (SEA) was used to examine relationships between fire occurrence and the Palmer drought severity index (PDSI) at each site. Thin plate splines were introduced as a tool for interpolating historical fire extent from dendroecological data. Point fire return intervals were compared between sites to better understand possible influences of historical Native American burning practices.ResultsDifferences emerged between sites in temporal and spatial fire regime metrics. The northern site had longer fire return intervals, more synchronized fire years, fewer point intervals < 4 years, longer fire rotation period and longer spatial mean fire interval. The northern site showed a significant reduction in PDSI values during fire years, whereas this climate–fire relationship in the southern site was likely decoupled by frequent Native American burning. Thin plate spline interpolation effectively reduced discontinuities at sample points compared to inverse distance weighting methods.Main conclusionsDifferences in both temporal and spatial fire regime metrics between sites were likely due to interplay in latitudinal influence on climate as well as differential Native American burning practices. Reconstruction of historical fire areas via geographical interpolation of fire scar data holds great promise for spatially explicit fire frequency reconstruction. The use of thin plate spline interpolation methods has the potential to reduce the impact of ‘false negatives’ in dendroecological data from frequent‐fire forests.

INTRODUÇÃO: Muitas alterações que ocorrem com o envelhecimento têm impacto de natureza funcional e acarretam, como uma das consequências mais importantes, distúrbios na marcha de pessoas idosas. OBJETIVOS:: Avaliar a eficácia de um programa de treinamento sensório-motor, no padrão da marcha de mulheres idosas. MATERIAIS E MÉTODOS: Atendendo-se aos critérios de exclusão e inclusão, formou-se um grupo de voluntários constituído por 15 idosas, que foram submetidas à análise do padrão da marcha por meio da videometria, cujas imagens foram processadas pelo software DgeeMe, versão 1.0. Em seguida, elas foram submetidas a um treinamento sensório-motor, por meio de um circuito que incluiu oito estações de exercícios com estímulos proprioceptivos e de equilíbrio. A frequência do treinamento foi de três sessões semanais com duração de 30 minutos, durante dois meses. Depois disso, foi realizada nova análise da marcha, considerando-se os componentes temporais e espaciais. RESULTADOS: Apesar de melhora nos componentes temporais e espaciais da marcha, só foi verificada significância estatística para o resultado observado na variável comprimento da passada (p = 0,02). CONCLUSÃO: Concluiu-se que o treinamento sensório-motor, muito embora possa melhorar o equilíbrio do indivíduo idoso, trazendo-lhe segurança para desenvolver a marcha, pode não afetar diretamente essa função nos seus aspectos biomecânicos.

Massive, massless and ghost modes of gravitational waves from higher-order gravity

Tensor-based models emerged only recently in modeling and analysis of the spatiotemporal road traffic data. They outperform other data models regarding the property of simultaneously capturing both spatial and temporal components of the observed traffic dataset. In this paper, the nonnegative tensor decomposition method is used to extract traffic patterns in the form of Speed Transition Matrix (STM). The STM is presented as the approach for modeling the large sparse Floating Car Data (FCD). The anomaly of the traffic pattern is estimated using Kullback–Leibler divergence between the observed traffic pattern and the average traffic pattern. Experiments were conducted on the large sparse FCD dataset for the most relevant road segments in the City of Zagreb, which is the capital and largest city in Croatia. Results show that the method was able to detect the most anomalous traffic road segments, and with analysis of the extracted spatial and temporal components, conclusions could be drawn about the causes of the anomalies. Results are validated by using the domain knowledge from the Highway Capacity Manual and achieved a precision score value of more than 90%. Therefore, such valuable traffic information can be used in routing applications and urban traffic planning.

The relationships between species abundance or occurrence versus spatial variation in climate are commonly used in species distribution models to forecast future distributions. Under “space‐for‐time substitution”, the effects of climate variation on species are assumed to be equivalent in both space and time. Two unresolved issues of space‐for‐time substitution are the time period for species' responses and also the relative contributions of rapid‐ versus slow reactions in shaping spatial and temporal responses to climate change. To test the assumption of equivalence, we used a new approach of climate decomposition to separate variation in temperature and precipitation in Fennoscandia into spatial, temporal, and spatiotemporal components over a 23‐year period (1996–2018). We compiled information on land cover, topography, and six components of climate for 1756 fixed route surveys, and we modeled annual counts of 39 bird species breeding in the mountains of Fennoscandia. Local abundance of breeding birds was associated with the spatial components of climate as expected, but the temporal and spatiotemporal climatic variation from the current and previous breeding seasons were also important. The directions of the effects of the three climate components differed within and among species, suggesting that species can respond both rapidly and slowly to climate variation and that the responses represent different ecological processes. Thus, the assumption of equivalent species' response to spatial and temporal variation in climate was seldom met in our study system. Consequently, for the majority of our species, space‐for‐time substitution may only be applicable once the slow species' responses to a changing climate have occurred, whereas forecasts for the near future need to accommodate the temporal components of climate variation. However, appropriate forecast horizons for space‐for‐time substitution are rarely considered and may be difficult to reliably identify. Accurately predicting change is challenging because multiple ecological processes affect species distributions at different temporal scales.

The importance of the spatial component of data items has been long recognized and gave rise to a successful line of research and development in Geographic Information Systems (GIS). In many application domains it is also essential to deal with the evolution of data along time and to integrate spatial, temporal and other aspects of the information domain in an expressive and operationally effective manner. Until recently, temporal solutions provided by spatial database systems were semi-temporal approaches lacking full temporal support. As a consequence, most spatial database systems manage snapshots of the present state of facts without fully exploiting historical temporal aspects. This paper provides preliminary results on a spatiotemporal database implementation. The proposed system builds on existing database technologies, TimeDB and Oracle Spatial, for temporal and spatial support, respectively. The justification for the choice of these technologies is given, based on the state of the art in spatial and temporal database research. The integration of the spatial and temporal components is achieved with the extension of the TimeDB implementation layer. A set of goals has been established in order to cover both the integration of the spatial support and the enforcement of the temporal requirements in the extended system. Issues and solutions are presented and illustrative examples show the use of the implemented functionalities.