Temporal Detail Research Articles

A systematic review of methods used to study fish in saltmarsh flats

There is a growing body of research highlighting the importance of saltmarshes as habitats for fish for feeding, refuge from predation and reproduction. However, more work is needed on fish on vegetated marsh flats (or surfaces). We reviewed 60 studies that used 21 methods to sample fish assemblages on saltmarsh flats. Drop samplers, fyke nets and pop nets were most frequently employed, with considerably more studies being conducted in graminoid than succulent marsh. Reporting of sampling temporal and tidal details, environmental variables and fish attributes was inconsistent. Most of the papers focussed on one or more of conservation management, comparisons among habitat types, and the use of saltmarsh (including fish activity type or residency status). Important potential areas of research include the relationships between the fish assemblages of saltmarsh flats and coastal fisheries, the effects of invasive plant species and marsh restoration efforts in areas outside the United States, and the potential effects of sea-level rise on vegetated flats as fish habitat. Sampling methods that provide density measures are likely to be most useful for most of this research. Thus, drop samplers and pop nets are an appropriate choice, the former in graminoid saltmarshes and the latter in succulent saltmarshes.

The association between cognitive reserve and performance-related brain activity during episodic encoding and retrieval across the adult lifespan

Remembering associations between encoded items and their contextual setting is a feature of episodic memory. Although this ability generally deteriorates with age, there is substantial variability in how older individuals perform on episodic memory tasks. A current topic of debate in the cognitive neuroscience of aging literature revolves around whether this variability may stem from genetic and/or environmental factors related to reserve, allowing some individuals to compensate for age-related decline through differential recruitment of brain regions. In this fMRI study spanning a large adult lifespan sample (N = 154), we tested whether higher cognitive reserve was associated with better task-fMRI context memory performance, and functional compensatory activity patterns in the aging brain. We used multivariate Behaviour Partial Least Squares (B-PLS) analysis to examine how age, retrieval accuracy, and a proxy measure of cognitive reserve [i.e., a composite score consisting of years of education (EDU) and crystallized IQ], impacted brain activity during the encoding and retrieval of spatial and temporal contextual details. The results indicated that age-related increases in encoding activity within anterior and lateral frontal, inferior parietal, occipito-temporal and medial temporal cortices, was correlated with better subsequent memory performance; and may be indicative of age-related functional compensation at encoding. Interestingly this compensatory pattern was not correlated with our proxy measure of cognitive reserve but was associated with total brain volume (a measure of brain reserve). However, cognitive reserve was associated with age-invariant and task-general activity in superior temporal, occipital, and left inferior frontal regions. We conclude that the relationship between cognitive reserve, brain reserve and age-related functional compensation is complex, and that EDU and IQ may not fully account for individual differences in cognitive reserve when studying well educated, healthy aging cohorts.

Feature-First Add-On for Trajectory Simplification in Lifelog Applications.

Lifelog is a record of one’s personal experiences in daily lives. User’s location is one of the most common information for logging a human’s life. By understanding one’s spatial mobility we can figure out other pieces of context such as businesses and activities. With GPS technology we can collect accurate spatial and temporal details of a movement. However, most GPS receivers generate a huge amount of data making it difficult to process and store such data. In this paper, we develop a generic add-on algorithm, feature-first trajectory simplification, to simplify trajectory data in lifelog applications. It is based on a simple sliding window mechanism counting occurrence of certain conditions. By automatically identifying feature points such as signal lost and found, stall, and turn, the proposed scheme provides rich context more than spatio-temporal information of a trajectory. In experiments with a case study of commuting in personal vehicles, we evaluate the effectiveness of the scheme. We find the proposed scheme significantly enhances existing simplification algorithms preserving much richer context of a trajectory.

Live imaging of alterations in cellular morphology and organelles during cornification using an epidermal equivalent model

The stratum corneum plays a crucial role in epidermal barrier function. Various changes occur in granular cells at the uppermost stratum granulosum during cornification. To understand the temporal details of this process, we visualized the cell shape and organelles of cornifying keratinocytes in a living human epidermal equivalent model. Three-dimensional time-lapse imaging with a two-photon microscope revealed that the granular cells did not simply flatten but first temporarily expanded in thickness just before flattening during cornification. Moreover, before expansion, intracellular vesicles abruptly stopped moving, and mitochondria were depolarized. When mitochondrial morphology and quantity were assessed, granular cells with fewer, mostly punctate mitochondria tended to transition to corneocytes. Several minutes after flattening, DNA leakage from the nucleus was visualized. We also observed extension of the cell-flattening time induced by the suppression of filaggrin expression. Overall, we successfully visualized the time-course of cornification, which describes temporal relationships between alterations in the transition from granular cells to corneocytes.

Dynamic particle partitioning SPH model for high-speed fluids simulation

The popular SPH method still remains as one of the most widely-used methods in fluid simulation, exhibiting its longevity with new and diverse variants in recent decades. New progress in the SPH simulation in most recent years are still hampered by such challenge when simulating high-speed fluids. In this paper, our research efforts are devoted to the efficiency issue of the SPH simulation when the ratio of velocities among fluid particles is large. Specifically, we introduce a k-means clustering method into the SPH framework to dynamically partition fluid particles into two disjoint groups based on their velocities. Then, we use a two-scale time-step scheme for these two types of particles. The smaller time steps are for particles with higher speed in order to preserve temporal details and guarantee stability. In contrast, the larger time steps are used for particles with smaller speed to reduce the computational expense, and both types of particles are tightly coupled in the simulation. We conduct various experiments and compare our method with some of the most relevant works, which have manifested the advantages of our methods over the conventional SPH technique and its new variants in terms of efficiency and stability.

Transition between coherent and incoherent chirping mechanisms in electron-positron pair creation

We examine the effect of a frequency-chirped external force field on the final energy that has been absorbed by two classical mechanical oscillators, by quantum mechanical two- and three-level systems, and by electron-positron pairs that were created from the quantum field theoretical Dirac vacuum. By comparing the final dynamical responses to the original force field with that associated with the corresponding time-reversed field, we can test the sensitivity of each of these five systems to the temporal phase information contained in the field. We predict that the linear oscillator, the two-level atom, and the pair-creation process triggered by a spatially homogeneous field are remarkably immune to this phase, whereas the quartic oscillator, the three-level atom, or the pair-creation process caused by a space-time field absorb the provided energy differently depending on the temporal details of the external field.

Comparing Power-System and User-Oriented Battery Electric Vehicle Charging Representation and Its Implications on Energy System Modeling

Battery electric vehicles (BEV) provide an opportunity to balance supply and demand in future power systems with high shares of fluctuating renewable energy. Compared to other storage systems such as pumped-storage hydroelectricity, electric vehicle energy demand is highly dependent on charging and connection choices of vehicle users. We present a model framework of a utility-based stock and flow model, a utility-based microsimulation of charging decisions, and an energy system model including respective interfaces to assess how the representation of battery electric vehicle charging affects energy system optimization results. We then apply the framework to a scenario study for controlled charging of nine million electric vehicles in Germany in 2030. Assuming a respective fleet power demand of 27 TWh, we analyze the difference between power-system-based and vehicle user-based charging decisions in two respective scenarios. Our results show that taking into account vehicle users’ charging and connection decisions significantly decreases the load shifting potential of controlled charging. The analysis of marginal values of equations and variables of the optimization problem yields valuable insights on the importance of specific constraints and optimization variables. Assumptions on fleet battery availability and a detailed representation of fast charging are found to have a strong impact on wind curtailment, renewable energy feed-in, and required gas power plant flexibility. A representation of fleet connection to the grid in high temporal detail is less important. Peak load can be reduced by 5% and 3% in both scenarios, respectively. Shifted load is robust across sensitivity analyses while other model results such as curtailment are more sensitive to factors such as underlying data years. Analyzing the importance of increased BEV fleet battery availability for power systems with different weather and electricity demand characteristics should be further scrutinized.

Estimation of suspended sediment concentrations in the Rhine River using Landsat Satellite Images

The traditional methods for measuring water quality and suspended sediment concentrations (SSC) are time-consuming and often do not give the spatial and temporal detail needed for assessment of the water quality and sediment transport. The determination of the suspended sediment concentrations using remote sensing through the main channel and tributaries of Rhine River can provide valuable information to assess the spatial and temporal of the suspended sediment. The main objective of this study is to estimate the suspended sediment concentrations (SSC) using Landsat satellite images. This study developed a method of quantifying SSC based on Landsat imagery and corresponding SSC data from the International Commission for the Protection of the Rhine (IKSR) and Dutch Rijkswaterstaat from 1995 to 2016. The model was built using the ratio of logarithmic transformation of a red/green band and logarithmic transformation of SSC based on in-situ sampling measurements. The SSC model works well and shows satisfactory performance. Landsat satellites (Thematic Mapper (TM), Multi-Spectral Scanner (MSS), Enhanced Thematic Mapper (ETM), Operational Land Imager (OLI)) explained an acceptable result accuracy.

The Experience of Novelty and the Novelty of Experience.

In cognitive psychology novelty is an antecedent of attention, emotion, memory, and behavior. However, the relationship between novelty and experience memorability remains conceptually underdeveloped in tourism. This research applies cognitive appraisal theory (CAT) to explore the contribution of novelty and emotion to memorable tourism experiences (MTEs). Seventy-five novel travel episodes were identified through semi-structured interviews. Analysis focused on the antecedent and consequent conditions of novelty. Novel experiences, whether positive or negative, were identified as critical to experience memorability. Novelty could be segmented into trip-related and event-related dimensions. Novelty contributes to how spatial, temporal, and contextual details of tourism experiences are remembered and reconstructed due to the elicitation of intense emotions. Analysis revealed negative experiences deemed as novel were found to be re-evaluated and often remembered as a positive experience. A conceptual model titled “cognitive appraisal of novelty in memorable tourism experiences” is presented for consideration in future research. By applying a retrospective and prospective approach the conceptual model explores the role of novelty through the process of cognitive appraisal, identifying goals, attention, and prior experiences as central for the experience of novelty. Future research should consider the application of recent advance in CAT to advance inquiry on tourism experiences as a psychological phenomenon.

High spatial and temporal detail in timely prediction of tourism demand

AbstractWhat happens in forecasting problems when high frequency and high spatial detail data encounter significant publication delays? In this paper, we consider a monthly dynamic panel data model, augmented by Google Trends search query volume data, for tourism demand forecasting at high spatial detail, in which one of the main aspects is represented by a publication delay ranging from 8 to 15 months. Some findings in the tourism literature already specify forecasting/nowcasting applications considering a realistic time delay but not for more than 3 months.

Transport-related walking among young adults: when and why?

BackgroundThe existing smartphones’ technology allows for the objective measurement of a person’s movements at a fine-grained level of geographic and temporal detail, and in doing so, it mitigates the issues associated with self-report biases and lack of spatial details. This study proposes and evaluates the advantages of using a smartphone app for collecting accurate, fine-grained, and objective data on people’s transport-related walking.MethodsA sample of 142 participants (mostly young adults) was recruited in a large Australian university, for whom the app recorded all their travel activities over two weekdays during August–September 2014. We identified eight main activity nodes which operate as transport-related walking generators. We explored the participants’ transport-related walking patterns around and between these activity nodes through the use of di-graphs to better understand patterns of incidental physical activity and opportunities for intervention to increase incidental walking.ResultsWe found that the educational node — in other samples may be represented by the workplace — is as important as the residential node for generating walking trips. We also found that the likelihood of transport-related walking trips is larger during the daytime, whereas at night time walking trips tend to be longer. We also showed that patterns of transport-related walking relate to the presence of ‘chaining’ trips in the afternoon period.ConclusionsThe findings of this study show how the proposed data collection and analytic approach can inform urban design to enhance walkability at locations that are likely to generate walking trips. This study’s insights can help to shape public education and awareness campaigns that aim to encourage walking trips throughout the day by suggesting locations and times of the day when engaging in these forms of exercise is easiest and least intrusive.

Synergic Use of Multi-Sensor Satellite Data for Volcanic Hazards Monitoring: The Fogo (Cape Verde) 2014–2015 Effusive Eruption

Monitoring and retrieving information of volcanic eruptions are important tasks for assessing the hazard and its evolution in time. Satellite remote sensing data are nowadays suitable tools to perform such tasks, thanks to their capability to access disastrous event also in remote and under-monitored regions, with frequent revisit time and accurate spatial information. In this work, we have analyzed satellite images, coming from both Synthetic Aperture Radar (SAR) and Optical sensors, to characterize the 2014-2015 eruption of Fogo volcano, Cape Verde. In particular, we have exploited images collected by the European Space Agency (ESA) Sentinel-1, the Italian Space Agency (ASI) COSMO-SkyMed, and NASA/USGS Landsat-8 and Earth-Observing-1 missions, for studying the lava emplacement and volcanic source of the eruption that took place between November 2014 and January 2015. On one side, we have adopted a new automatic change detection technique for estimating the lava field and its temporal evolution, taking advantage of the intensity and the Interferometric SAR coherence. The two SAR-based features were combined using an innovative algorithm able to take full advantage of the Sentinel-1 mission’s six-day repeat cycle, thereby providing an unprecedented possibility to fully exploit the multi-temporal InSAR coherence to detect surface changes. On the other side, we have exploited the consolidated differential SAR interferometry technique to map the ground deformation and retrieve the feeding dyke by inverting syn-eruptive data. The proposed methods based on change detection for the estimation of the lava flow is capable of resolving with spatial and temporal detail the evolution of lava flows. Results from source modelling from the SAR data show a SW-NE oriented dyke, located inside Cha das Caldeiras, SW of the Pico do Fogo. The work suggests a multidisciplinary and multi-sensor approach, highlighting the benefits and limitations of satellite data and image processing techniques in an operational environment.

Two-stage electro\u2013mechanical coupling of a KV channel in voltage-dependent activation

In voltage-gated potassium (KV) channels, the voltage-sensing domain (VSD) undergoes sequential activation from the resting state to the intermediate state and activated state to trigger pore opening via electro–mechanical (E–M) coupling. However, the spatial and temporal details underlying E–M coupling remain elusive. Here, utilizing KV7.1’s unique two open states, we report a two-stage E–M coupling mechanism in voltage-dependent gating of KV7.1 as triggered by VSD activations to the intermediate and then activated state. When the S4 segment transitions to the intermediate state, the hand-like C-terminus of the VSD-pore linker (S4-S5L) interacts with the pore in the same subunit. When S4 then proceeds to the fully-activated state, the elbow-like hinge between S4 and S4-S5L engages with the pore of the neighboring subunit to activate conductance. This two-stage hand-and-elbow gating mechanism elucidates distinct tissue-specific modulations, pharmacology, and disease pathogenesis of KV7.1, and likely applies to numerous domain-swapped KV channels.

Two-stage “Hand-and-Elbow” Gating Mechanism of a KV Channel

During voltage-dependent activation, the voltage-sensing domain (VSD) of voltage-gated potassium (KV) channels activates in a stepwise manner from the resting state to the intermediate state and activated state, which then trigger pore opening via electro-mechanical (E-M) coupling. However, the spatial and temporal details underlying E-M coupling remain elusive. Leveraging the unique two open states of the KV7.1 channel that are associated with the VSD adopting the intermediate and activated conformations, here we report a two-stage E-M coupling mechanism in KV7.1 as triggered by the two-steps VSD activation. When the S4 segment transitions to the intermediate state, the hand-like C-terminus of the VSD-pore linker (S4-S5L) interacts with the pore in the same subunit. When S4 then proceeds on to the activated state, the elbow-like hinge between S4 and S4-S5L engages with the pore to activate conductance. This two-stage “hand-and-elbow” gating mechanism elucidates distinct tissue-specific modulations, pharmacology, and disease pathogenesis of KV7.1, and likely applies to numerous KV channels.

Value of technology in the U.S. electric power sector: Impacts of full portfolios and technological change on the costs of meeting decarbonization goals

Abstract Power sector decarbonization is an important pillar of climate mitigation efforts, but perspectives differ about the relative competitiveness of generation technologies and how limited portfolio approaches (e.g., where non-renewable generation options are prohibited) could alter the costs and likelihoods of reaching emissions reduction goals. The existing literature on impacts of technological availability and cost on electric sector planning typically use models that do not have sufficient technological, spatial, and temporal detail to adequately resolve the economic competitiveness of variable renewable energy vis-a-vis dispatchable generators. Using a state-of-the-art energy-economic model, this work examines impacts of technological availability and advanced generation technologies on U.S. electricity market outcomes across a range of regional, market, and policy contexts. We show that decarbonization costs are 11%–76% higher as technological options are removed from consideration (incremental compliance costs for a 95% CO2 reduction below 2005 levels are roughly twice as high when new nuclear, carbon-capture-equipped units, and transmission are not allowed). However, the economic and technical implications of limited portfolios depend on the market and policy contexts (e.g., costs are higher with stringent targets, more extensive end-use electrification, and lower gas prices) and the costs and capabilities of the remaining options. The analysis demonstrates how lower temporal and spatial resolution models likely understate the value of technology by omitting key economic and technical features of high variable renewable pathways. Additionally, the analysis quantifies how technological change can lower costs of emissions reductions by 7%–73% and how low-cost battery storage can provide a hedge against higher costs when technological portfolios are limited.

United States wildlife and wildlife product imports from 2000\u20132014

The global wildlife trade network is a massive system that has been shown to threaten biodiversity, introduce non-native species and pathogens, and cause chronic animal welfare concerns. Despite its scale and impact, comprehensive characterization of the global wildlife trade is hampered by data that are limited in their temporal or taxonomic scope and detail. To help fill this gap, we present data on 15 years of the importation of wildlife and their derived products into the United States (2000–2014), originally collected by the United States Fish and Wildlife Service. We curated and cleaned the data and added taxonomic information to improve data usability. These data include >2 million wildlife or wildlife product shipments, representing >60 biological classes and >3.2 billion live organisms. Further, the majority of species in the dataset are not currently reported on by CITES parties. These data will be broadly useful to both scientists and policymakers seeking to better understand the volume, sources, biological composition, and potential risks of the global wildlife trade.

Disruption in daily eating-fasting and activity-rest cycles in Indian adolescents attending school

A lifestyle with erratic eating patterns and habits predisposes youngsters to obesity. Through a two-phase feasibility study among Indian students living in the Delhi area, we longitudinally examined the following: (1) the daily eating-fasting cycles of students (N = 34) in school and college using smartphones as they transition from high school (aged 13-15 years; nIX = 13) to higher secondary school (HSSS; 16-18 years; nXII = 9) to their first year (FY) of college (18-19 years; nFC = 12); and (2) daily activity-rest cycles and light-dark exposure of 31 higher secondary school students (HSSS) using actigraphy. In phase 1, students' food data were analyzed for temporal details of eating events and observable differences in diet composition, such as an energy-dense diet (fast food (FF)), as confounding factors of circadian health. Overall, the mean eating duration in high school, higher secondary and FY college students ranged from 14.1 to 16.2h. HSSS exhibited the shortest night fasting. Although FY college students exhibited the highest fast food percentage (FF%), a positive correlation between body mass index (BMI) and FF% was observed only among HSSS. Furthermore, the body weight of HSSS was significantly higher, indicating that FF, untimely eating and reduced night fasting were important obesity-associated factors in adolescents. Reduced night fasting duration was also related to shorter sleep in HSSS. Therefore, food data were supplemented with wrist actigraphy, i.e., activity-rest data, in HSSS. Actigraphy externally validated the increased obesogenic consequences of deregulated eating rhythms in HSSS. CamNtech motion watches were used to assess the relationship between disturbed activity cycles of HSSS and other circadian clock-related rhythms, such as sleep. Less than 50% of Indian HSSS slept 6 hours or more per night. Seven of 31 students remained awake throughout the night, during which they had more than 20% of their daily light exposure. Three nonparametric circadian rhythm analysis (NPCRA) variables revealed circadian disruption of activity in HSSS. The present study suggests that inappropriate timing and quality of food and sleep disturbances are important determinants of circadian disruptions in adolescents attending school.

An improved replanning strategy for congested traffic conditions in MATSim

Abstract Agent-based transport models such as MATSim have been developed and used for the past few decades to simulate transportation systems in different cities and are capable of accurately reproducing travel patterns at different levels of aggregation. Given their disaggregate representation of both travel demand and supply as well as the high level of spatial and temporal detail, agent-based transport models also have the potential to allow for unprecedentedly detailed and disaggregated analysis. When simulating large study areas, it is often common to increase the replanning rate to achieve a quicker convergence. However, this comes at the cost of causing substantial oscillations in link-level dynamics which render disaggregate analysis difficult, if not impossible. This paper tries to reconcile both objectives: favour quicker convergence as with higher replanning rates while mitigating the strong oscillations of the link-level dynamics.

A Spatial Flow Clustering Method Based on the Constraint of Origin-Destination Points’ Location

With the development of mobile positioning technology, a large number of Origin-Destination (OD) flow data with spatial and temporal details have been produced. These OD flow could give us a great opportunity to research geographical phenomena such as spatial interaction and mobility patterns. The OD flow clustering approach is an effective way to explore the main mobility patterns of the objects. At the same time, similarity measurement plays a key role in OD flow clustering. However, most of the previous OD flow similarity measurement methods failed to make full use of the spatial information of the flow including spatial proximity and geometric similarity. In this paper, we considered both position information and geometric properties of OD flow and propose a new method to measure the spatial similarity between OD flows. Specifically, the proposed method sets the neighbor threshold with the length of OD flows and the parameter $\alpha $ dynamically. Based on the constraint of the OD points’ location, the directions of the flows are implicitly restricted. The sole-parameter $\alpha $ has a practical value as it determines the maximum length difference and the maximum directional difference that can be tolerated between similar flows. The proposed method passed a simulation experiment with synthetic flows and a case study with 283,008 taxi trips in Beijing in one day. The results show that the proposed method can discover the dominant mobility pattern from a large number of flow data effectively. In the case study, the dominant flow clusters reveal the taxi mobility patterns of residents at different distances in Beijing.

Mapping wetland characteristics using temporally dense Sentinel-1 and Sentinel-2 data: A case study in the St. Lucia wetlands, South Africa

Wetlands have been determined as one of the most valuable ecosystems on Earth and are currently being lost at alarming rates. Large-scale monitoring of wetlands is of high importance, but also challenging. The Sentinel-1 and -2 satellite missions for the first time provide radar and optical data at high spatial and temporal detail, and with this a unique opportunity for more accurate wetland mapping from space arises. Recent studies already used Sentinel-1 and -2 data to map specific wetland types or characteristics, but for comprehensive wetland characterisations the potential of the data has not been researched yet. The aim of our research was to study the use of the high-resolution and temporally dense Sentinel-1 and -2 data for wetland mapping in multiple levels of characterisation. The use of the data was assessed by applying Random Forests for multiple classification levels including general wetland delineation, wetland vegetation types and surface water dynamics. The results for the St. Lucia wetlands in South Africa showed that combining Sentinel-1 and -2 led to significantly higher classification accuracies than for using the systems separately. Accuracies were relatively poor for classifications in high-vegetated wetlands, as subcanopy flooding could not be detected with Sentinel-1’s C-band sensors operating in VV/VH mode. When excluding high-vegetated areas, overall accuracies were reached of 88.5% for general wetland delineation, 90.7% for mapping wetland vegetation types and 87.1% for mapping surface water dynamics. Sentinel-2 was particularly of value for general wetland delineation, while Sentinel-1 showed more value for mapping wetland vegetation types. Overlaid maps of all classification levels obtained overall accuracies of 69.1% and 76.4% for classifying ten and seven wetland classes respectively.