Short Temporal Intervals Research Articles

Not so fast: Million-years of metal precipitation in Mississippi Valley type deposits inferred from in-situ petrochronology of hydrothermal carbonates

Mississippi Valley-type (MVT) deposits contain about 20% of global zinc resources and host critical raw materials crucial to the development of green technologies. Despite their economic and strategic importance, there is a lack of consensus on the duration of mineralizing fluid flow events in MVT systems. This study couples in-situ U-Pb dating with Sr-isotope and trace element analysis of syn- and post-ore gangue carbonates to establish: (1) timing and duration, (2) redox evolution, and (3) flow rates of mineralizing fluids in the world-class San Vicente Zn-(Pb) deposit (Peru). New radiometric ages bracket the crystallization of syn-mineralization dolomite, characterized by high Fe and Mn contents and Sr isotopic values overlapping with that of host carbonates, between 103.2 ± 4.1 Ma and 70.6 ± 5.6 Ma. This age interval reveals a direct genetic relationship between flow of mineralizing fluids and late Cretaceous Andean compressional tectonics. Basinal fluid expulsion coeval with known tectonic events continues in the district until Pliocene times, driving episodic crystallization of post-ore hydrothermal carbonates between 61.6 ± 9.3 and 2.7 ± 0.2 Ma. The low Mn and Fe content and high 87Sr/86Sr values characteristic of these post-ore, bedding-parallel and cross-cutting carbonate veins indicate a colder, oxidized environment. Our findings highlight the contribution of paired carbonate geochemistry and U-Pb geochronology in drawing links between tectonic events, fluid expulsion and the waxing and waning of mineralization potential in foreland basins. The results of this study challenge our understanding of timescales in MVT systems and imply that anomalous metal enrichment in basinal fluids over a short temporal interval is not a necessary precondition to form economic-sized, sediment-hosted Zn-Pb deposits. Rather, it is the coexistence of a focused fluid flow in an interconnected aquifer with suitable metal depositional mechanisms over a prolonged period of time (106–107 yr) that allows precipitation of economic amount of base metals at a specific site in the upper crust.

Myrtaceae flowering strategies in a gallery forest, Chapada Diamantina, Brazil

Abstract Tropical plants exhibit virtually all known phenological responses, which can range from near-continuous to brief events, and from complete synchrony to complete asynchrony. This wide variety of phenological patterns is related to high tropical biodiversity and complex interactions with diverse abiotic and biotic factors, such as plant-pollinator interactions. Changes in these factors will therefore influence plant phenology, and differences in those phenological responses can impact reproductive success and plant fitness. We report here interspecific variations in the reproductive ecology (flowering phenology, floral biology, reproductive systems, and pollination) of 10 Myrtaceae species in a gallery forest in northeastern, Brazil. We evaluated flowering patterns and strategies, considering the frequency and duration of each phenophase from monthly observations, using the semi-quantitative Fournier scale. We also analyzed floral biology, recorded floral visitors, conducted pollination experiments (autonomous self-pollination, hand self-pollination, hand cross-pollination, and natural/open pollination), and calculated sefl-incompatibility (SII) and autogamy (AI) indices. Most species exhibited synchronous and annual flowering lasting between 1 and 5 months, with a “pulsed bang” strategy (i.e., mass flowering concentrated within just a few days, with intervals). These patterns were repeated among congeneric species, except in Myrcia, in which half of the species accompanied were classified as having a “pulsed bang” and the other half a “big bang” strategy. The flowering strategies appeared to be associated with distinct patterns of inflorescence development, bud production, flowering duration, and the timing of flowering in individual plants. Bee species were considered pollinators. Most species studied were self-incompatible and allogamous. In general, the species produced large quantities of flowers during short temporal intervals, favoring crosses between individuals having precise synchrony.

Time perception in stimulant-dependent participants undergoing repetitive transcranial magnetic stimulation

BackgroundThe dopaminergic (DA) system is an important neural system for the modulation of time perception and the timing of motor actions. Dysregulation of the DA system is related to chronic use of stimulant drugs, which lead, among others, to executive dysfunctions. Little is known instead about the potential deficiencies in temporal processing of stimulant-dependent individuals. The present study aimed to investigate temporal processing using a time bisection task with different temporal intervals in chronic cocaine users undergoing repetitive transcranial magnetic stimulation (rTMS). MethodStudy 1: A time bisection task with short temporal intervals range (480/1920 ms) was administered to 18 cocaine use disorder (CocUD) patients and 20 healthy control before and after the intensive phase of rTMS treatment (5 days apart). Study 2: 22 CocUD participants and 23 control participants completed two temporal tasks (time bisection and time reproduction) with long temporal intervals range (1200/2640 ms) at baseline and immediately after the intensive phase of rTMS treatment. ResultsStudy 1: A shift in the psychometric function consistent with temporal overestimation in CocUD patients compared to controls was observed. However, no temporal impairment in CocUD patients at test session was found. Study 2: The analysis of temporal variability indices showed a significant difference between groups at baseline but not at Day 5 due to a significant difference between time points only in the CocUD group. ConclusionsThis study report a temporal overestimation in CocUD patients and a temporal variability reduction after an rTMS protocol in CocUD patients.

Contrasting lake changes in Tibet revealed by recent multi-modal satellite observations

The limited anthropogenic activities on the Tibetan Plateau make this an ideal natural laboratory to elucidate how climate change impacts lake changes. Previous studies have mainly focused on decadal lake changes, yet their rapid evolutions at short temporal intervals and the associated atmospheric origins remain elusive. Here, we produce a new lake area change dataset at monthly sampling over 2015–2020 from 16,801 satellite images. Our estimates achieve an accuracy of <30 m, as evidenced by in-situ GPS field survey validations of representative lake shorelines. We found contrasting patterns in recent rapid area changes: deaccelerating in the north and accelerating in the south. Such contrasting pattern was unprecedented in the last two decades and is likely caused by recent precipitation anomalies, indicating that lakes in TP may experience a tipping point. Lakes are found to store only a small portion (<5 %) of net precipitation in summer, increased to ∼11 % for years with heavy precipitation, which helps understand the water mass budget for lakes over there. Our study highlights the importance of investigating short-term lake area changes as a climate proxy to study their rapid responses to intra- and inter-annual climate variability.

Archaeological networks, community detection, and critical scales of interaction in the U.S. Southwest/Mexican Northwest

Archaeologists have long recognized that spatial relationships are an important influence on and driver of all manner of social processes at scales from the local to the continental. Recent research in the realm of complex networks focused on community detection in human and animal networks suggests that there may be certain critical scales at which spatial interactions can be partitioned, allowing researchers to draw potential boundaries for interaction that provide insights into a variety of social phenomena. Thus far, this research has been focused on short time scales and has not explored the legacies of historic relationships on the evolution of network communities and boundaries over the long-term. In this study, we examine networks based on material cultural similarity drawing on a large settlement and material culture database from the U.S. Southwest/Mexican Northwest (ca. 1000–1450 CE) divided into a series of short temporal intervals. With these temporally sequenced networks we: 1) demonstrate the utility of network community detection for partitioning interactions in geographic space, 2) identify key transitions in the geographic scales of network communities, and 3) illustrate the role of previous network configurations in the evolution of network communities and their spatial boundaries through time.

Quantum optical communication in the presence of strong attenuation noise

Is quantum communication possible over an optical fibre with transmissivity $\lambda\leq 1/2$ ? The answer is well known to be negative if the environment with which the incoming signal interacts is initialised in a thermal state. However, in [PRL 125:110504, 2020] the quantum capacity was found to be always bounded away from zero for all $\lambda>0$, a phenomenon dubbed "die-hard quantum communication" (D-HQCOM), provided that the initial environment state can be chosen appropriately (depending on $\lambda$). Here we show an even stronger version of D-HQCOM in the context of entanglement-assisted classical communication: entanglement assistance and control of the environment enable communication with performance at least equal to that of the ideal case of absence of noise, even if $\lambda>0$ is arbitrarily small. These two phenomena of D-HQCOM have technological potential provided that we are able to control the environment. How can we achieve this? Our second main result answers this question. Here we provide a fully consistent protocol to activate the phenomena of D-HQCOM without directly accessing the environment state. This is done by sending over the channel "trigger signals", i.e. signals which do not encode information, prior to the actual communication, with the goal of modifying the environment in an advantageous way. This is possible thanks to the memory effects which arise when the sender feeds signals separated by a sufficiently short temporal interval. Our results may offer a concrete scheme to communicate across arbitrarily long optical fibres, without using quantum repeaters. As a by-product of our analysis, we derive a simple Kraus representation of the thermal attenuator exploiting the associated Lindblad master equation.

Integrating ANNs and Cellular Automata–Markov Chain to Simulate Urban Expansion with Annual Land Use Data

Accurately simulating and predicting the urban expansion process, especially in expeditious urbanization areas, is an important aspect of managing limited land resources and adjusting flawed land use policies. This research was conducted on the basis of a high-temporal-resolution land use dataset to precisely model urban expansion in a rapidly developing zone by integrating the Artificial Neural Network (ANN), cellular automata (CA), and Markov Chain (MC). An urban suitability index (USI) map was created using ANN and fed to CA–MC to identify possible changed-to-urban cells. Two ANNs, multiple-layer perceptron (MLP) and long short-term memory network (LSTM), were implemented as simulation models for comparison. Due to its ability to capture more temporal information, LSTM outperformed MLP in modeling urban expansion dynamics over a short temporal interval. The simulated results were validated by (fuzzy) kappa simulation and the results revealed that the combination of ANN and CA–MC can precisely model the urban development locations due to its strength in revealing the nonlinear relationship between the expansion process and its drivers. The same model was applied to southern Auckland, and the compared results show that the most simulated variance is caused by the land use policies implemented by different types of governments.

Online action proposal generation using spatio-temporal attention network

Temporal action proposal generation aims to generate temporal boundaries containing action instances. In real-time applications such as surveillance cameras, autonomous driving, and traffic monitoring, the online localization and recognition of human activities occurring in short temporal intervals are important areas of research. Existing approaches of temporal action proposal generation consider only the offline and frame-level feature aggregation along the temporal dimension. Those offline methods also generate many redundant irrelevant proposal regions in the frames as temporal boundaries. This leads to higher computational cost along with slow processing speed which is not suitable for online tasks. In this study, we propose a novel spatio-temporal attention network for online action proposal generation as opposed to existing offline proposal generation methods. Our novel proposed approach incorporates the inter-dependency between the spatial and temporal context information of each incoming video clip to generate more relevant online temporal action proposals. First, we propose a windowed spatial attention module to capture the inter-spatial relationship between the features of incoming frames. The windowed spatial network produces more robust clip-level feature representation and efficiently deals with noisy features such as occlusion or background scenes. Second, we introduce a temporal attention module to capture relevant temporal dynamic information mutually to the localized spatial information to model the long inter-frame temporal relationship since most online real life videos are untrimmed in nature. By applying these two attention modules sequentially, the novel proposed spatio-temporal network model is able to generate precise action boundaries at a particular instant of time. In addition, the model generates fewer discriminative temporal action proposals while maintaining a low computational cost and high processing speed suitable for online settings.

Flood damage assessment with Sentinel-1 and Sentinel-2 data after Sardoba dam break with GLCM features and Random Forest method

Accurate mapping and monitoring of flooded areas are immensely required for disaster management purposes, such as for damage assessment and mitigation. In this study, the flood damage mapping performances of two satellite Earth Observation sensors, i.e., European Space Agency's Sentinel-1 (S1) synthetic aperture radar (SAR) and Sentinel-2 (S2) multispectral optical instruments, were evaluated using the Random Forest (RF) supervised classification method and various feature types. The study area was Sardoba Reservoir (Uzbekistan) and its surroundings, in which a disastrous dam failure occurred on May 1, 2020. After the failure of a part of the earthfill dam, a large region with settlements and agricultural areas in Uzbekistan and Kazakhstan was flooded. S1 and S2 cloudless data with a short temporal interval acquired soon after the event were available for the area. Four different data availability scenarios, such as (i) only S1 pre- and post-flood data; (ii) only S2 pre- and post-flood data; (iii) S1 pre- and post-flood and S2 pre-flood data; and (iv) S1 and S2 pre- and post-flood data were evaluated in terms of classification accuracy. In addition to the polarization information of S1 and the intensity values of S2 bands, feature maps produced from these datasets, such as vegetation and water indices, textural information obtained from gray level co-occurrence matrix (GLCM), and the principal component analysis (PCA) bands were employed in the RF method. The results show that the fusion of S1 and S2 data exhibit very high classification accuracy for the flooded areas and can separate the inundated vegetation as well. The use of S2 pre-event data together with the S1 pre- and post-event data is recommended for obtaining high accuracy even when post-event optical data is not available.

Sentinel-1 Coherence for Mapping Above-Ground Biomass in Semiarid Forest Areas

The interferometric coherence of repeat-pass C-band synthetic aperture radar observations has shown potential for mapping forest above-ground biomass (AGB) when images were acquired with short temporal repeat intervals and under stable environmental conditions. Since 2014, Sentinel-1 collects repeated interferometric image pairs at global scale with repeat intervals of 6 or 12 days. For a semiarid forest site in California, we evaluated one year of Sentinel-1 6- and 12-day (60 and 59 images, respectively) repeat-pass coherence images with the objective of retrieving AGB. The retrieval was performed by inverting the semiempirical Interferometric Water Cloud Model. The retrieval based on individual coherence images was most accurate (~50% relative root-mean-square difference with respect to a Lidar-derived map) when images were acquired in extended periods of dry conditions. The retrieval accuracy improved by approximately 15% units when combining multiple coherence images in the retrieval. Finally, the accuracy of the retrieval with multitemporal 6- or 12-day repeat-pass coherence images differed by only 2% units. The results of this study advocate consideration of Sentinel-1 repeat-pass coherence in AGB mapping efforts in semiarid forest areas.

Investigating Crime Pattern Stability at Micro-Temporal Intervals: Implications for Crime Analysis and Hotspot Policing Strategies

Studies of crime hotspot forecasts use various metrics to describe different characteristics of prediction patterns. However, few investigations consider how the stability of crime hotspot, estimated at relatively short temporal intervals, can impact hotspot policing efforts. In response, using address-level incident location data that were collected from six law enforcement agencies in the United States, the current study examines the daily stability of crime hotspots that were estimated over a 1-year period. Results suggest that micro-temporal stability patterns in crime hotspot forecasts are dependent on crime type, jurisdiction, and the interaction between these two factors. Implications for crime analysis and future research are discussed.

Making a Lecture Stick: the Effect of Spaced Instruction on Knowledge Retention in Medical Education

IntroductionPoor knowledge retention is a persistent problem among medical students. This challenging issue may be addressed by optimizing frequently used instructional designs, such as lectures. Guided by neuroscientific literature, we designed a spaced learning lecture in which the educator repeats the to-be-learned information using short temporal intervals. We investigated if this modified instructional design could enhance students’ retention.Materials and MethodsSecond-year medical students (n = 148) were randomly allocated to either the spaced lecture or the traditional lecture. The spaced lecture consisted of three 15-min instructional periods, separated by 5-min intervals. A short summary of the preceding information was provided after each interval. The traditional lecture encompassed the same information including the summary in the massed format, thus without the intervals. All students performed a baseline knowledge test 2 weeks prior to the lectures and students’ knowledge retention was assessed 8 days after the lectures.ResultsThe average score on the retention test (α = 0.74) was not significantly different between the spaced lecture group (33.8% ± 13.6%) and the traditional lecture group (31.8% ± 12.9%) after controlling for students’ baseline-test performance (F(1,104) = 0.566, p = 0.458). Students’ narrative comments showed that the spaced lecture format was well-received and subjectively benefitted their attention-span and cognitive engagement.Discussion and ConclusionWe were unable to show increased knowledge retention after the spaced lecture compared with the traditional lecture. Based on these findings, we provide recommendations for further research. Ultimately, we aim for optimized spaced learning designs to facilitate learning in the medical curriculum and to help educate health professionals with a solid knowledge base.

Simulating tonic activations in speech production

Studies of speech production have often focused on transient events—those that happen over short temporal intervals. We know, however, that speech is made up of movements that can be distributed over longer durations as well (e.g., tongue bracing, oralization, articulatory setting, laryngeal state, harmony, etc.). Such events, which involve maintaining continuous activation of a particular muscle group tonically over a long duration, have often been treated as qualitatively different from transient speech events. The present study considers examples of these types of movements in speech and non-speech (e.g., emotion expression, posture, etc.) domains. Biomechanical simulations are used to show how tonic activations operate on the same principles as transient ones (except for the difference in duration), and to show how tonic activations can overlap with multiple other activations—whether transient or tonic—through superposition [Bizzi et al. Science 253, 5017 (1991)]. This work aims to show how these previously anomalous kinds of movements fit seamlessly into broader theories of movement and speech. [Funding from NIH Grant DC-002717 and NSERC RGPIN-2015-05099.]

First Identification of Periodic Degassing Rhythms in Three Mineral Springs of the East Eifel Volcanic Field (EEVF, Germany)

We present a geochemical dataset acquired during continual sampling over 7 months (bi-weekly) and 4 weeks (every 8 h) in the Neuwied Basin, a part of the East Eifel Volcanic Field (EEVF, Germany). We used a combination of geochemical, geophysical, and statistical methods to describe and identify potential causal processes underlying the correlations of degassing patterns of CO2, He, Rn, and tectonic processes in three investigated mineral springs (Nette, Kärlich and Kobern). We provide for the first time, temporal analyses of periodic degassing patterns (1 day and 2–6 days) in springs. The temporal fluctuations in cyclic behavior of 4–5 days that we recorded had not been observed previously but may be attributed to a fundamental change in either gas source processes, subsequent gas transport to the surface, or the influence of volcano–tectonic earthquakes. Periods observed at 10 and 15 days may be related to discharge pulses of magma in the same periodic rhythm. We report the potential hint that deep low-frequency (DLF) earthquakes might actively modulate degassing. Temporal analyses of the CO2–He and CO2–Rn couples indicate that all springs are interlinked by previously unknown fault systems. The volcanic activity in the EEVF is dormant but not extinct. To understand and monitor its magmatic and degassing systems in relation to new developments in DLF-earthquakes and magmatic recharging processes and to identify seasonal variation in gas flux, we recommend continual monitoring of geogenic gases in all available springs taken at short temporal intervals.

Impact of the Surface–Atmosphere Variables on the Relation Between Air and Land Surface Temperatures

The energy, momentum and mass exchanges between the soil and the atmosphere take place in the surface layer. The difference between the screen temperature of the air at 2 m (T2) and the land surface temperature (LST) is a key parameter in their determination. Here an analysis of this difference is made with data from a site at the island of Mallorca, in the Western Mediterranean. While previous studies are often built for relatively short temporal intervals (from several days to few months), the current work analyzes 2-year-long series with a 30 min temporal resolution, in particular the diurnal and seasonal variability. The uncertainty of LST measured from near the ground is estimated to be at least 2 $$^{\circ }$$ C. The difference between T2 and LST (T2–LST) in the center of the day ranges between − 3 and − 10 $$^{\circ }$$ C, arriving at about − 18 $$^{\circ }$$ C for dry summer days. Statistically it is shown that these values are related to the net radiation heating of the surface transmitted upwards by thermal turbulence. The values in summer are much larger because the upper dry soil does not allow the heat to be transmitted efficiently into the ground. At night T2–LST is usually under 3 $$^{\circ }$$ C, with weak correlations of T2–LST with net radiation or ground flux, indicating that these processes are active and efficient transporting heat in most cases. The better correlated quantities at night with T2–LST are the upper soil temperature, the LST and the turbulent heat flux, reflecting the importance of the state of the surface. In summer nights T2–LST takes very small values, below 1 $$^{\circ }$$ C, even allowing unstable stratification. This is a result of a soil in which the first centimeters are very warm after sunset, not being able to send heat into the dry soil and releasing it into the atmosphere.

Tongue-driven sonar beam steering by a lingual-echolocating fruit bat.

Animals enhance sensory acquisition from a specific direction by movements of head, ears, or eyes. As active sensing animals, echolocating bats also aim their directional sonar beam to selectively “illuminate” a confined volume of space, facilitating efficient information processing by reducing echo interference and clutter. Such sonar beam control is generally achieved by head movements or shape changes of the sound-emitting mouth or nose. However, lingual-echolocating Egyptian fruit bats, Rousettus aegyptiacus, which produce sound by clicking their tongue, can dramatically change beam direction at very short temporal intervals without visible morphological changes. The mechanism supporting this capability has remained a mystery. Here, we measured signals from free-flying Egyptian fruit bats and discovered a systematic angular sweep of beam focus across increasing frequency. This unusual signal structure has not been observed in other animals and cannot be explained by the conventional and widely-used “piston model” that describes the emission pattern of other bat species. Through modeling, we show that the observed beam features can be captured by an array of tongue-driven sound sources located along the side of the mouth, and that the sonar beam direction can be steered parsimoniously by inducing changes to the pattern of phase differences through moving tongue location. The effects are broadly similar to those found in a phased array—an engineering design widely found in human-made sonar systems that enables beam direction changes without changes in the physical transducer assembly. Our study reveals an intriguing parallel between biology and human engineering in solving problems in fundamentally similar ways.

Derivation of Sea Surface Tidal Current From Spaceborne SAR Constellation Data

In this paper, we demonstrate an application of spaceborne synthetic aperture radar (SAR) constellation data to derive sea surface tidal current at high spatial resolution. The maximum cross correlation (MCC) method, which has been widely applied to optical remote sensing data to derive sea surface velocities, is applied to X-band SAR data from TerraSAR-X (TSX) and TanDEM-X (TDX), which were operating in pursuit monostatic mode. Because of the short temporal interval of TSX and TDX’s pursuit acquisitions, temporal de-correlation is minimized to derive tidal current fields that exhibit significant temporal and spatial variations. In addition, we combined data from TDX and another X-band SAR, COSMO-SkyMed, to obtain a virtual SAR constellation data pair, which was also analyzed using the MCC method to derive the tidal current field. Case studies of Hangzhou Bay in the East China Sea and Amrum Island in the North Sea are presented. The SAR-derived tidal current fields were compared to the results of numerical model simulations, high-frequency (HF) radar measurements and in situ measurements. MCC coefficients that are greater than 0.8 are an appropriate threshold for the further derivation of tidal currents. Comparisons to finite volume community ocean model, HF radar and general estuarine transport model results yield root-mean-square errors of 0.13, 0.06, and 0.05 m/s, respectively. Measurements from three field stations were also compared to the MCC SAR retrievals, yielding differences of 0.3, 0.07, and −0.09 m/s.

Soil moisture estimation in Chambal irrigation command using C-band HH polarization multi-incidence angle Radarsat-1 SAR and IRS LISS III data

Soil moisture is one of the key variables in agricultural water management, particularly in scheduling of irrigation in the major irrigation commands. Several studies have been carried out for modelling of soil moisture using synthetic aperture radar (SAR) which is sensitive to soil dielectric permittivity. However, two critical factors viz. random surface roughness and vegetation cover introduces complexities in the precise estimation of soil moisture. The estimation is further constrained when using single configuration SAR. In the present study, microwave and optical synergy were used wherein soil moisture in the Chambal Irrigation Command, India during 2002-03 winter season, was modelled in two steps. In the first step the surface roughness was modelled taking advantage of multi-incidence angle image acquisition by Radarsat-1 within a short temporal interval with the assumption that the soil moisture has not significantly changed. An output called ‘Roughness Normalized Backscatter Coefficient’ (RNBS) was generated which was used subsequently to correct the vegetation effect. In the second step RNBS was plotted against the normalized difference vegetation index (NDVI) generated from IRS-LISS III sensor as a function of volumetric soil moisture. Based upon the relation between RNBS and NDVI, several polynomial models at different moisture levels were generated and applied to the RNBS image to generate different regimes of soil moisture. The modelled soil moisture was validated based upon the independent samples collected from the field. The proposed methodology is found to be applicable under fallow and sparsely vegetated conditions where the NDVI is less than 0.4.

Temporal orienting of attention can be preserved in normal aging.

Being able to orient our attention to moments in time is crucial for optimizing behavioral performance. In young adults, flexible cue-based temporal expectations have been shown to modulate perceptual functions and enhance behavioral performance. Recent studies with older individuals have reported significant deficits in cued temporal orienting. To investigate the extent of these deficits, the authors conducted 3 studies in healthy old and young adults. For each study, participants completed 2 tasks: a reaction time (RT) task that emphasized speeded responding and a nonspeeded rapid-serial-visual-presentation task that emphasized visual discrimination. Auditory cues indicated the likelihood of a target item occurring after a short or long temporal interval (foreperiod; 75% validity). In the first study, cues indicating a short or a long foreperiod were manipulated across blocks. The second study was designed to replicate and extend the first study by manipulating the predictive temporal cues on a trial-by-trial basis. The third study extended the findings by including neutral cues so that it was possible to separate cueing validity benefits and invalidity costs. In all 3 studies, cued temporal expectation conferred significant performance advantages for target stimuli occurring after the short foreperiod for both old and young participants. Contrary to previous findings, these results suggest that the ability to allocate attention to moments in time can be preserved in healthy aging. Further research is needed to ascertain whether similar neural networks are used to orient attention in time as we age, and/or whether compensatory mechanisms are at work in older individuals.

GRACE, Climate Change and Future Needs: A Brief Review

Gravity Recovery and Climate Experiment (GRACE) is a satellite based observation of the Earth’s gravitational field through time. Earth’s gravitational field has long been studied to infer the densities of underlying rocks for geological characterization at various scales. Convention gravity measurements were done using spring gravimeters on ground. However continuous observations of temporal variations in the Earth’s gravity field have become available at an unprecedented resolution of a few hundreds of kilometres through satellite based sensors. With the launch of GRACE in 2002, the study of the exchange of mass both within the Earth and at its surface in the short temporal interval has become possible. This has huge implications in studying the impacts of earth’s surface processes involving the interaction of the atmosphere, hydrosphere, cryosphere and biosphere. GRACE gravity, therefore, has gained relevance for Earth scientists as an important tool to study the complex dynamics of the Earth system and climate change. The current article researches on the principles behind grave gravity variations and its applications to infer climate change and proposes the advances required to overcome the limitations of GRACE for climate change forecasting.