Differences In Peak Magnitude Research Articles

Enhancing flood event predictions: Multi-objective calibration using gauge and satellite data

Rainfall-runoff models are widely used for predicting watershed runoff. The accuracy of the predictions heavily relies on effective model calibration, which is majorly influenced by the employed objective functions that measure the agreement between predictions and real-world observations. In this study, we propose a novel multi-objective calibration approach with the aim of improving the flood event predictions of a conceptual rainfall-runoff model applied to a catchment in the Austrian Alps. To achieve this, we include a total of five carefully selected objective functions into calibration. Three of these objective functions can be regarded as more classical and are roughly based on comparing absolute deviations, square of the residuals, as well as bias, correlation and variability of the flow. Another objective function relies on remote observations of the snow covered area, for which the MODIS Terra (MOD10A1.061) and Aqua (MYD10A1.061) datasets are used. The final objective function measures the differences in peak magnitude and timing for the largest events in the observation period. To showcase the proposed approach’s effectiveness, we compare the calibration and validation results with those obtained by a model that was only calibrated for two runoff objective functions and to carefully selected benchmark cases. The presented study reveals that our approach enhances the model’s capacity to depict snow cover dynamics, a crucial factor in accurately predicting snow-driven flooding events. Additionally, the results underscore that incorporating an error metric targeting magnitude and timing errors of large flood events can enhance the model’s ability to predict peak runoff. The results of this study further suggest that in general a more robust model can be obtained by incorporating additional error metrics that specifically target physical states and individual parts of the runoff curve into model calibration.

A 0.05 m Change in Inertial Measurement Unit Placement Alters Time and Frequency Domain Metrics during Running.

Inertial measurement units (IMUs) provide exciting opportunities to collect large volumes of running biomechanics data in the real world. IMU signals may, however, be affected by variation in the initial IMU placement or movement of the IMU during use. To quantify the effect that changing an IMU's location has on running data, a reference IMU was 'correctly' placed on the shank, pelvis, or sacrum of 74 participants. A second IMU was 'misplaced' 0.05 m away, simulating a 'worst-case' misplacement or movement. Participants ran over-ground while data were simultaneously recorded from the reference and misplaced IMUs. Differences were captured as root mean square errors (RMSEs) and differences in the absolute peak magnitudes and timings. RMSEs were ≤1 g and ~1 rad/s for all axes and misplacement conditions while mean differences in the peak magnitude and timing reached up to 2.45 g, 2.48 rad/s, and 9.68 ms (depending on the axis and direction of misplacement). To quantify the downstream effects of these differences, initial and terminal contact times and vertical ground reaction forces were derived from both the reference and misplaced IMU. Mean differences reached up to -10.08 ms for contact times and 95.06 N for forces. Finally, the behavior in the frequency domain revealed high coherence between the reference and misplaced IMUs (particularly at frequencies ≤~10 Hz). All differences tended to be exaggerated when data were analyzed using a wearable coordinate system instead of a segment coordinate system. Overall, these results highlight the potential errors that IMU placement and movement can introduce to running biomechanics data.

Effects of latency and age structure on the dynamics and containment of COVID-19

In this paper we develop an SEIR-type model of COVID-19, with account for two particular aspects: non-exponential distribution of incubation and recovery periods, as well as age structure of the population. For the mean-field model, which does not distinguish between different age groups, we demonstrate that including a more realistic Gamma distribution of incubation and recovery periods may not have an effect on the total number of deaths and the overall size of an epidemic, but it has a major effect in terms of increasing the peak numbers of infected and critical care cases, as well as on changing the timescales of an epidemic, both in terms of time to reach the peak, and the overall duration of an outbreak. In order to obtain more accurate estimates of disease progression and investigate different strategies for introducing and lifting the lockdown, we have also considered an age-structured version of the model, which has allowed us to include more accurate data on age-specific rates of hospitalisation and COVID-19 related mortality. Applying this model to three comparable neighbouring regions in the UK has delivered some fascinating insights regarding the effect of lockdown in regions with different population structure. We have discovered that for a fixed lockdown duration, the timing of its start is very important in the sense that the second epidemic wave after lifting the lockdown can be significantly smaller or larger depending on the specific population structure. Also, the later the fixed-duration lockdown is introduced, the smaller is the resulting final number of deaths at the end of the outbreak. When the lockdown is introduced simultaneously for all regions, increasing lockdown duration postpones and slightly reduces the epidemic peak, though without noticeable differences in peak magnitude between different lockdown durations.

Peak magnitudes of supraglottal air pressure associated with affricated and nonaffricated stop consonant productions in Hindi

Peak magnitudes of supraglottal air pressure were obtained, under a variety of conditions, from three normal adult speakers in Hindi during the production of stop consonants. The stops were produced in CVCVC nonsense utterances which were embedded in the carrier phrase, “ye—hæ.” Significant differences in peak magnitudes associated with the stop productions were found as a function of place of articulation and utterance position. Peak magnitudes were always significantly higher for unvoiced stops than for voiced stops. Aspirated stops, in general, showed higher peak magnitudes than unaspirated stops, but a significant level of difference in peak magnitudes was reached only under voiced conditions. Differences in peak magnitudes as a function of stress were significant under voiced conditions; under unvoiced conditions the differences were less pronounced.

Peak magnitudes of supraglottal air pressure associated with affricated and nonaffricated stop consonant productions in Hindi

Peak magnitudes of supraglottal air pressure, under a variety of conditions, were obtained during stop productions from three normal adult speakers of Hindi. The stops were produced in CVCVC nonsense utterances which were embedded in the carrier phrase, “ye—hae.” Significant differences in peak magnitudes were found as a function of the place of articulation of a stop and its position in an utterance. Peak magnitudes were always significantly higher for unvoiced stops than for voiced stops. Aspirated stops, in general, showed higher peak magnitudes than unaspirated stops, but a significant level of difference in peak magnitudes was reached only under voiced conditions. Differences in peak magnitudes as a function of stress were significant under voiced conditions; under unvoiced conditions the differences were less pronounced.