Temporal Transfer Research Articles

Music and psychoacoustic perception abilities in cochlear implant users with auditory neuropathy spectrum disorder

ObjectiveAuditory neuropathy spectrum disorder (ANSD) is a condition wherein the pre-neural or cochlear outer hair cell activity is intact, but the neural activity in the auditory nerve is disrupted. Cochlear implant (CI) can be beneficial for subjects with ANSD; however, little is known about the music perception and psychoacoustic abilities of CI users with ANSD. Music perception in CI users is a multidimensional and complex ability requiring the contribution of both auditory and nonauditory abilities. Even though auditory abilities lay the foundation, the contribution of patient-related variables such as ANSD may affect the music perception. This study aimed to evaluate the psychoacoustic and music perception abilities of CI recipients with ANSD. Study designTwelve CI users with ANSD and twelve age- and gendermatched CI users with sensorineural hearing loss (SNHL) were evaluated. Music perception abilities were measured using the Turkish version of the Clinical Assessment of Music Perception (T-CAMP) test. Psychoacoustic abilities were measured using the spectral ripple discrimination (SRD) and temporal modulation transfer function (TMTF) tests. In addition, the age of diagnosis and implantation was recorded. ResultsPitch direction discrimination (PDD), timbre recognition, SRD, and TMTF performance of CI users with ANSD were concordant with those reported in previous studies, and differences between ANSD and SNHL groups were not statistically significant. However, the ANSD group performed poorly compared with SNHL group in melody recognition subtest of T-CAMP, and the difference was statistically significant. ConclusionCI can prove beneficial for patients with ANSD with respect to their music and psychoacoustic abilities, similar to patients with SNHL, except for melody recognition. Recognition of melodies requires both auditory and non-auditory abilities, and ANSD may have an extensive but subtle effect in the life of CI users.

Outcome dependency on the level of task: Gap detection threshold and temporal modulation transfer function

Introduction: It has been demonstrated that a listener's temporal-processing capability is predictive of his or her performance on speech recognition, especially in noisy and complex environments. Aims and Objectives: The objective of the study is to check the task-related dependency of gap detection threshold (GDT) and temporal modulation transfer function (TMTF) tests in adults and children. Methods and Materials: The study was conducted on 40 normal-hearing participants, in which 20 children and 20 adults. All the participants in the study were subjected to the basic audiological evaluation. Results: It was observed that there is a significant difference (P

Best sensitivity of temporal modulation transfer functions in laboratory mice matches the amplitude modulation embedded in vocalizations.

The perception of spectrotemporal changes is crucial for distinguishing between acoustic signals, including vocalizations. Temporal modulation transfer functions (TMTFs) have been measured in many species and reveal that the discrimination of amplitude modulation suffers at rapid modulation frequencies. TMTFs were measured in six CBA/CaJ mice in an operant conditioning procedure, where mice were trained to discriminate an 800 ms amplitude modulated white noise target from a continuous noise background. TMTFs of mice show a bandpass characteristic, with an upper limit cutoff frequency of around 567 Hz. Within the measured modulation frequencies ranging from 5 Hz to 1280 Hz, the mice show a best sensitivity for amplitude modulation at around 160 Hz. To look for a possible parallel evolution between sound perception and production in living organisms, we also analyzed the components of amplitude modulations embedded in natural ultrasonic vocalizations (USVs) emitted by this strain. We found that the cutoff frequency of amplitude modulation in most of the individual USVs is around their most sensitive range obtained from the psychoacoustic experiments. Further analyses of the duration and modulation frequency ranges of USVs indicated that the broader the frequency ranges of amplitude modulation in natural USVs, the shorter the durations of the USVs.

Criteria for selecting model updating methods for better temporal transferability

When older and more recent datasets have large and small numbers of observations, respectively, then discrete choice modellers must decide whether to utilise both datasets with model updating (transfer scaling, joint context estimation, Bayesian updating, and combined transfer estimation) or only the more recent dataset. This study investigates the case when the data collection time points and the number of observations from each time point differ. Bootstrapping was applied to commuting mode choice models utilising datasets from Nagoya, Japan. The following criteria are proposed: (1) when the more recent time point has a large number of observations, use only the more recent data; (2) when the more recent time point has a smaller number of observations, use transfer scaling or joint context estimation based on the differences in the contexts of the two time points and the sample size from the older time point.

Fluxonic Processing of Photonic Synapse Events

Much of the information processing performed by a biological neuron occurs in the dendritic tree. For artificial neural systems using light for communication, it is advantageous to convert signals to the electronic domain at synaptic terminals, so dendritic computation can be performed with electrical circuits. Here, we present circuits based on Josephson junctions and mutual inductors that act as dendrites, processing signals from synapses receiving single-photon communication events with superconducting detectors. We show simulations of circuits performing basic temporal filtering, logical operations, and nonlinear transfer functions. We further show how the synaptic signal from a single photon can fan out locally in the electronic domain to enable the dendrites of the receiving neuron to process a photonic synapse event or pulse train in multiple different ways simultaneously. Such a technique makes efficient use of photons, energy, space and information.

Intergenerational financial transfers and physical health of old people in rural China: evidence from CHARLS data

ABSTRACT: With the reduction of intergenerational temporal transfers, financial transfers from adult offspring to their elderly parents are prevailing in rural China. Although much has been done, little is known about the association between the expansion of intergenerational transfers and rural old people’s physical health in China. The purpose of this paper was to examine the effect of intergenerational financial transfers on the elders’ physical health in rural China. Using data collected from China Health and Retirement Longitudinal Study (CHARLS), panel data fixed effect model and threshold model are employed to estimate the impact of intergenerational financial transfers on the old people’s physical health in rural areas. Results showed that; although, the intergenerational financial transfers have a positive effect on the old people’s physical health, no linear relationship exists between them. Intergenerational financial transfers are clearly less effective for low-income old people’s physical health than those of middle-income, while the effect on high-income old people’s health is the most insignificant. Studies concerning the effect of intergenerational financial transfers on the elders’ health in developing countries remain limited. Findings of this paper provided great insights into how intergenerational transfers, such as intergenerational financial transfers, may affect the well-beings of old residents in rural areas. Additionally, this study can offer inspiration to policy makers regarding what measures they should take to enhance rural old residents’ well-beings.

The effect of seasonal variation on the activity patterns of the American black bear: an ecological niche modeling approach

AbstractThe American black bear (Ursus americanus) has very plastic activity patterns that maximize its ability to adapt to changing environments. Hibernation length is positively correlated with latitude, where northern populations remain in hibernation for up to 5 months during the winter; however, the species may not hibernate at all in its southern range. Several studies have focused on the description of the species’ ecology from specific locations; however, the macroecological perspective of the seasonal activity in black bears has not been explored. Using ecological niche models and temporal climate transfers, we tested for a correlation between the 971 monthly activity records we obtained for this species within its whole distribution and monthly climatic conditions. We observed that there was a high degree of geographic overlap among the monthly potential transferred areas and the monthly presence locality records. Thus, we suggest that climate is one of the main factors affecting the cycles of activity of this species and explains its hibernation patterns.

The temporal correlation transfer in layered bio-models

The temporal correlation functions are simulated for a two-layer model of a highly inhomogeneous medium which can be considered as the scull-brain imitation, or phantom. The temporal decay of correlations are considered for two different mechanisms of particle movement, either the Brownian diffusion, or the random velocity square mechanism. The results obtained are turned to be highly dependent on the form of the kinetics of scatterers.

Suprathreshold Processing and Cocktail Party Listening in Younger and Older Adults with Normal Hearing

Present study aimed to investigate the effect of age and suprathreshold processing on cocktail party listening in individuals with normal hearing sensitivity. A total of 92 participants with normal hearing sensitivity were included in the study. They were divided into two groups based on their age. Fifty two young normal hearing adults in the age range of 20–40 years and 40 older normal hearing adults in the age range of 60-80 years. Tests administered included speech perception in noise test, spatial selective attention, gap detection thresholds, temporal modulation transfer function, inter-aural time difference, differential limen of frequency and ripple noise discrimination. Results showed that older adults performed poorer than younger adults in all the tests. Also, temporal cues showed a better relation with speech perception in noise compared to the spectral cues. This can be attributed to the disrupted neural synchrony which is due to poor frequency selectivity as observed through ripple noise discrimination. Individuals rely more on temporal cues due to poorer frequency resolution and phase locking mechanism and also on top down processes such as selective attention too. A degraded speech input would lead them to rely more on their higher cognition.

Habitat and host factors associated with liver fluke (Fasciola hepatica) diagnoses in wild red deer (Cervus elaphus) in the Scottish Highlands

BackgroundRed deer (Cervus elaphus) are a common wild definitive host for liver fluke (Fasciola hepatica) that have been the subject of limited diagnostic surveillance. This study aimed to explore the extent to which coprological diagnoses for F. hepatica in red deer in the Scottish Highlands, Scotland, are associated with variability among hosts and habitats.MethodsOur analyses were based on coproantigen ELISA diagnoses derived from faecal samples that were collected from carcasses of culled deer on nine hunting estates during two sampling seasons. Sampling locations were used as centroids about which circular home ranges were quantified. Data were stratified by season, and associations between host, hydrological, land cover and meteorological variables and binary diagnoses during 2013–2014 (n = 390) were explored by mixed effect logistic regression. The ability of our model to predict diagnoses relative to that which would be expected by chance was quantified, and data collected during 2012–2013 (n = 289) were used to assess model transferability.ResultsDuring 2013–2014, habitat and host characteristics explained 28% of variation in diagnoses, whereby half of the explained variation was attributed to differences among estates. The probability of a positive diagnosis was positively associated with the length of streams in the immediate surroundings of each sampling location, but no non-zero relationships were found for land cover or lifetime average weather variables. Regardless of habitat, the probability of a positive diagnosis remained greatest for males, although males were always sampled earlier in the year than females. A slight decrease in prediction efficacy occurred when our model was used to predict diagnoses for out-of-sample data.ConclusionsWe are cautious to extrapolate our findings geographically, owing to a large proportion of variation attributable to overarching differences among estates. Nevertheless, the temporal transferability of our model is encouraging. While we did not identify any non-zero relationship between meteorological variables and probability of diagnosis, we attribute this (in part) to limitations of interpolated meteorological data. Further study into non-independent diagnoses within estates and differences among estates in terms of deer management, would improve our understanding of F. hepatica prevalence in wild deer.

NOVEL FINDINGS TWO DECADES FOLLOWING COGNITIVE TRAINING: FINDINGS FROM THE ACTIVE TRIAL

Although the only demonstrated panacea against cognitive decline, behavioral cognitive training usually fails to demonstrate transfer either to untrained cognitive abilities or to distal outcomes like everyday functioning. No such trials, however, have leveraged more than a decade of follow-up to adapt life-course perspectives. The Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) study remains the largest NIA-funded clinical trial of cognitively normal older adults. Efforts to re-invigorate the cohort after 20 years with external data linkages have coalesced around renewed interests in how training-related cognitive improvements affect long-term dementia risk, health care utilization and costs, credit scores, and active years in later life. The first presentation by Rebok overviews ACTIVE and its 20-year follow-up plans. Next, Gross and colleagues tested whether cognitive training attenuates the relationship between IADL difficulty and mortality; negative findings suggest proposed relationships between cognition and IADL difficulty are correlational, not causal, which has implications for transfer and trial outcomes. Third, Thomas tests a novel algorithm for classifying MCI, ushering opportunities to examine training effects on incidence of MCI after up to 20 years post-training. Marsiske then evaluates temporal transfer of training in reasoning ability, concluding that reasoning training and age, but not other baseline demographics, predict maintained alterations in reasoning abilities. Finally, Felix evaluates the stifling role of depressive symptoms on ability to benefit from training. Dr. Wally Boot, a recognized thought leader in transfer of cognitive training, will provide an illuminating discussion of promises and pitfalls of these lines of research.

Predicting the temporal transferability of model parameters through a hydrological signature analysis

Attention has recently increased on the use of hydrological signatures as a potential tool for assessing the fidelity of model structures and providing insights into the transfer of model parameters. The utility of hydrological signatures as model performance/reliability indicators in a calibration-validation testing scenario (i.e., the temporal transfer of model parameters) is the focus of this study. The Probability Distributed Model, a flexible conceptual hydrological model, is used to test the approach across a number of catchments included in the MOPEX data set. We explore the change in model performance across calibration and validation time periods and contrast it to the corresponding change in several hydrological signatures to assess signature worth. Results are explored in finer detail by utilizing a moving window approach to calibration and validation time periods. The results of this study indicated that the most informative signature can vary, both spatially and temporally, based on physical and climatic characteristics and their interaction to the model parameterization. Thus, one signature could not adequately illustrate complex watershed behaviors nor predict model performance in new analysis periods.

Automated Extraction of Antarctic Glacier and Ice Shelf Fronts from Sentinel-1 Imagery Using Deep Learning

Sea level rise contribution from the Antarctic ice sheet is influenced by changes in glacier and ice shelf front position. Still, little is known about seasonal glacier and ice shelf front fluctuations as the manual delineation of calving fronts from remote sensing imagery is very time-consuming. The major challenge of automatic calving front extraction is the low contrast between floating glacier and ice shelf fronts and the surrounding sea ice. Additionally, in previous decades, remote sensing imagery over the often cloud-covered Antarctic coastline was limited. Nowadays, an abundance of Sentinel-1 imagery over the Antarctic coastline exists and could be used for tracking glacier and ice shelf front movement. To exploit the available Sentinel-1 data, we developed a processing chain allowing automatic extraction of the Antarctic coastline from Seninel-1 imagery and the creation of dense time series to assess calving front change. The core of the proposed workflow is a modified version of the deep learning architecture U-Net. This convolutional neural network (CNN) performs a semantic segmentation on dual-pol Sentinel-1 data and the Antarctic TanDEM-X digital elevation model (DEM). The proposed method is tested for four training and test areas along the Antarctic coastline. The automatically extracted fronts deviate on average 78 m in training and 108 m test areas. Spatial and temporal transferability is demonstrated on an automatically extracted 15-month time series along the Getz Ice Shelf. Between May 2017 and July 2018, the fronts along the Getz Ice Shelf show mostly an advancing tendency with the fastest moving front of DeVicq Glacier with 726 ± 20 m/yr.

Improving Parameter Transferability of GR4J Model under Changing Environments Considering Nonstationarity

Hydrological nonstationarity has brought great challenges to the reliable application of conceptual hydrological models with time-invariant parameters. To cope with this, approaches have been proposed to consider time-varying model parameters, which can evolve in accordance with climate and watershed conditions. However, the temporal transferability of the time-varying parameter was rarely investigated. This paper aims to investigate the predictive ability and robustness of a hydrological model with time-varying parameter under changing environments. The conceptual hydrological model GR4J (Génie Rural à 4 paramètres Journalier) with only four parameters was chosen and the sensitive parameters were treated as functions of several external covariates that represent the variation of climate and watershed conditions. The investigation was carried out in Weihe Basin and Tuojiang Basin of Western China in the period from 1981 to 2010. Several sub-periods with different climate and watershed conditions were set up to test the temporal parameter transferability of the original GR4J model and the GR4J model with time-varying parameters. The results showed that the performance of streamflow simulation was improved when applying the time-varying parameters. Furthermore, in a series of split-sample tests, the GR4J model with time-varying parameters outperformed the original GR4J model by improving the model robustness. Further studies focus on more diversified model structures and watersheds conditions are necessary to verify the superiority of applying time-varying parameters.

Triple-adjacent-frame generative network for blind video motion deblurring

Photos and videos captured by handheld imaging devices are often accompanied by unwanted blur because of hand jitters and fast movement of objects during the exposure time. Most previous studies discussed single image deblurring and video deblurring but neglected detailed analyses of the spatiotemporal continuity between adjacent frames, which limits the deblurring effect. We propose a novel end-to-end blind video motion deblurring network that takes triple adjacent frames as input to deblur a blurry video frame. In our approach, a bidirectional temporal feature transfer between triple adjacent frames is implemented to pass the latent features of the central frame on to a group encoder of its neighbors. Then, a hybrid decoder decodes group features and estimates a sharper video frame relative to the central frame. Experimental results show that our model outperforms previous excellent methods in terms of traditional metrics (PSNR and SSIM) and visual quality within an acceptable time cost. The code is available at https://github.com/BITLIULONGEE/Triple-Adjacent-Frame-Generative-Network.

Effects of Low Frequency Residual Hearing on Music Perception and Psychoacoustic Abilities in Pediatric Cochlear Implant Recipients.

Studies have demonstrated the benefits of low frequency residual hearing in music perception and for psychoacoustic abilities of adult cochlear implant (CI) users, but less is known about these effects in the pediatric group. Understanding the contribution of combined electric and acoustic stimulation in this group can help to gain a better perspective on decisions regarding bilateral implantation. We evaluated the performance of six unilaterally implanted children between 9 and 13 years of age with contralateral residual hearing using the Clinical Assessment of Music Perception (CAMP), spectral ripple discrimination (SRD), and temporal modulation transfer function (TMTF) tests and compared findings with previous research. Our study sample performed similarly to normal hearing subjects in pitch direction discrimination (0.81 semitones) and performed well above typical CI users in melody recognition (43.37%). The performance difference was less in timbre recognition (48.61%), SRD (1.47 ripple/octave), and TMTF for four modulation frequencies. These findings suggest that the combination of low frequency acoustic hearing with the broader frequency range of electric hearing can help to increase clinical CI benefit in pediatric users and decisions regarding second-side implantation should consider these factors.

Cellular and Network Mechanisms for Temporal Signal Propagation in a Cortical Network Model.

The mechanisms underlying an effective propagation of high intensity information over a background of irregular firing and response latency in cognitive processes remain unclear. Here we propose a SSCCPI circuit to address this issue. We hypothesize that when a high-intensity thalamic input triggers synchronous spike events (SSEs), dense spikes are scattered to many receiving neurons within a cortical column in layer IV, many sparse spike trains are propagated in parallel along minicolumns at a substantially high speed and finally integrated into an output spike train toward or in layer Va. We derive the sufficient conditions for an effective (fast, reliable, and precise) SSCCPI circuit: (i) SSEs are asynchronous (near synchronous); (ii) cortical columns prevent both repeatedly triggering SSEs and incorrectly synaptic connections between adjacent columns; and (iii) the propagator in interneurons is temporally complete fidelity and reliable. We encode the membrane potential responses to stimuli using the non-linear autoregressive integrated process derived by applying Newton's second law to stochastic resilience systems. We introduce a multithreshold decoder to correct encoding errors. Evidence supporting an effective SSCCPI circuit includes that for the condition, (i) time delay enhances SSEs, suggesting that response latency induces SSEs in high-intensity stimuli; irregular firing causes asynchronous SSEs; asynchronous SSEs relate to healthy neurons; and rigorous SSEs relate to brain disorders. For the condition (ii) neurons within a given minicolumn are stereotypically interconnected in the vertical dimension, which prevents repeated triggering SSEs and ensures signal parallel propagation; columnar segregation avoids incorrect synaptic connections between adjacent columns; and signal propagation across layers overwhelmingly prefers columnar direction. For the condition (iii), accumulating experimental evidence supports temporal transfer precision with millisecond fidelity and reliability in interneurons; homeostasis supports a stable fixed-point encoder by regulating changes to synaptic size, synaptic strength, and ion channel function in the membrane; together all-or-none modulation, active backpropagation, additive effects of graded potentials, and response variability functionally support the multithreshold decoder; our simulations demonstrate that the encoder-decoder is temporally complete fidelity and reliable in special intervals contained within the stable fixed-point range. Hence, the SSCCPI circuit provides a possible mechanism of effective signal propagation in cortical networks.

Global drivers of minimum mortality temperatures in cities

Human mortality shows a pronounced temperature dependence. The minimum mortality temperature (MMT) as a characteristic point of the temperature-mortality relationship is influenced by many factors. As MMT estimates are based on case studies, they are sporadic, limited to data-rich regions, and their drivers have not yet been clearly identified across case studies. This impedes the elaboration of spatially comprehensive impact studies on heat-related mortality and hampers the temporal transfer required to assess climate change impacts. Using 400 MMTs from cities, we systematically establish a generalised model that is able to estimate MMTs (in daily apparent temperature) for cities, based on a set of climatic, topographic and socio-economic drivers. A sigmoid model prevailed against alternative model setups due to having the lowest Akaike Information Criterion (AICc) and the smallest RMSE. We find the long-term climate, the elevation, and the socio-economy to be relevant drivers of our MMT sample within the non-linear parametric regression model. A first model application estimated MMTs for 599 European cities (>100 000 inhabitants) and reveals a pronounced decrease in MMTs (27.8–16 °C) from southern to northern cities. Disruptions of this pattern across regions of similar mean temperatures can be explained by socio-economic standards as noted for central eastern Europe. Our alternative method allows to approximate MMTs independently from the availability of daily mortality records. For the first time, a quantification of climatic and non-climatic MMT drivers has been achieved, which allows to consider changes in socio-economic conditions and climate. This work contributes to the comparability among MMTs beyond location-specific and regional limits and, hence, towards a spatially comprehensive impact assessment for heat-related mortality.

Assessment of SWAT spatial and temporal transferability for a high-altitude glacierized catchment

Abstract. In this study, we investigated the application and the transferability of the Soil Water and Assessment Tool (SWAT) in a partly glacierized Alpine catchment characterized by extreme climatic conditions and steep terrain. The model was initially calibrated for the 10 km2 watershed of the Damma glacier Critical Zone Observatory (CZO) in central Switzerland using monitoring data for the period of 2009–2011 and then was evaluated for 2012–2013 in the same area. Model performance was found to be satisfactory against both the Nash–Sutcliffe criterion (NS) and a benchmark efficiency (BE). The transferability of the model was assessed by using the parameters calibrated on the small watershed and applying the model to the approximately 100 km2 catchment that drains into the hydropower reservoir of the Göscheneralpsee and includes the Damma glacier CZO. Model results were compared to the reservoir inflow data from 1997 to 2010 and it was found that the model predicted successfully snowmelt timing and autumn recession but could not accurately capture the peak flow for certain years. Runoff was slightly overestimated from late May to June, when it is dominated by snowmelt. Finally, we investigated the response of the greater catchment to climate change using three different climate change scenarios, and the results were compared to those of a previous study, where two different hydrological models, PREVAH and ALPINE3D, were used. The methodology presented here, where SWAT is calibrated for a small watershed and then applied for a bigger area with similar climatic conditions and geographical characteristics, could work even under extreme conditions like ours. However, greater attention should be given to the differences between glacier melt and snowmelt dynamics. In conclusion, this assessment test on the transferability of SWAT on different scales gave valuable information about the strengths and weaknesses of the model when it was applied under conditions different to those under which it was calibrated.

Submodularity of Storage Placement Optimization in Power Networks

In this paper, we consider the problem of placing energy storage resources in a power network when all storage devices are optimally controlled to minimize system-wide costs. We propose a discrete optimization framework to accurately model heterogeneous storage capital and installation costs as these fixed costs account for the largest cost component in most grid-scale storage projects. Identifying an optimal placement strategy is challenging due to the combinatorial nature of such placement problems, and the spatial and temporal transfers of energy via transmission lines and distributed storage devices. To develop a scalable near-optimal placement strategy with a performance guarantee, we characterize a tight condition under which the placement value function is submodular by exploiting our duality-based analytical characterization of the optimal cost and prices. The proposed polyhedral analysis of a parametric economic dispatch problem with optimal storage control also leads to a simple but rigorous verification method for submodularity, and the novel insight that the spatiotemporal congestion pattern of a power network is critical to submodularity. A modified greedy algorithm provides a $(1-1/e)$ -optimal placement solution and can be extended to obtain risk-aware placement strategies when submodularity is verified.