Spatial and time variations of seismicity before strong earthquakes in the southern part of the Balkans

A retrospective analysis of the spatial and time variations of three main statistical parameters of the seismicity before recent 4 stronger earthquakes (2015 – 2020) in the southern Balkans is presented. The modern extended software package ZMAP with various advanced seismological functions for earthquake catalog analysis is used for estimating the spatial-time variations in a- value (seismic activity), b-value (slope of the recurrence graph) and z-value (parameter of the relative seismic quiescence). The catalog data from constantly updated catalog of the University of Athens for the period 1964-2020 and spatial window 32° - 44° N and 10° – 30° E are used for the various statistical interpretations. The main result of the whole analysis is that the abnormally low b-values and high z-values, defining the zones of relatively seismic quiescence, may be an indicator of imminent release of more significant stress in areas adjacent to the zones of relatively high a-values. Thus, the result of the proposed joint interpretation of the spatial-time variations of these three statistical parameters of seismicity could be considered as a kind of predictor of the stronger recent seismic events in the southern part of Balkans.

Pre-Earthquake Ionospheric Perturbation Identification Using CSES Data via Transfer Learning

During the lithospheric buildup to an earthquake, complex physical changes occur within the earthquake hypocenter. Data pertaining to the changes in the ionosphere may be obtained by satellites, and the analysis of data anomalies can help identify earthquake precursors. In this paper, we present a deep-learning model, SeqNetQuake, that uses data from the first China Seismo-Electromagnetic Satellite (CSES) to identify ionospheric perturbations prior to earthquakes. SeqNetQuake achieves the best performance [F-measure (F1) = 0.6792 and Matthews correlation coefficient (MCC) = 0.427] when directly trained on the CSES dataset with a spatial window centered on the earthquake epicenter with the Dobrovolsky radius and an input sequence length of 20 consecutive observations during night time. We further explore a transferring learning approach, which initially trains the model with the larger Electro-Magnetic Emissions Transmitted from the Earthquake Regions (DEMETER) dataset, and then tunes the model with the CSES dataset. The transfer-learning performance is substantially higher than that of direct learning, yielding a 12% improvement in the F1 score and a 29% improvement in the MCC value. Moreover, we compare the proposed model SeqNetQuake with other five benchmarking classifiers on an independent test set, which shows that SeqNetQuake demonstrates a 64.2% improvement in MCC and approximately a 24.5% improvement in the F1 score over the second-best convolutional neural network model. SeqNetSquake achieves significant improvement in identifying pre-earthquake ionospheric perturbation and improves the performance of earthquake prediction using the CSES data.

Facilitation of neural responses to targets moving against optic flow

For the human observer, it can be difficult to follow the motion of small objects, especially when they move against background clutter. In contrast, insects efficiently do this, as evidenced by their ability to capture prey, pursue conspecifics, or defend territories, even in highly textured surrounds. We here recorded from target selective descending neurons (TSDNs), which likely subserve these impressive behaviors. To simulate the type of optic flow that would be generated by the pursuer’s own movements through the world, we used the motion of a perspective corrected sparse dot field. We show that hoverfly TSDN responses to target motion are suppressed when such optic flow moves syn-directional to the target. Indeed, neural responses are strongly suppressed when targets move over either translational sideslip or rotational yaw. More strikingly, we show that TSDNs are facilitated by optic flow moving counterdirectional to the target, if the target moves horizontally. Furthermore, we show that a small, frontal spatial window of optic flow is enough to fully facilitate or suppress TSDN responses to target motion. We argue that such TSDN response facilitation could be beneficial in modulating corrective turns during target pursuit.

Assessment of Global FY-3C/VIRR Sea Surface Temperature

Fengyun-3C (FY-3C) is a second-generation meteorological satellite of China that was launched on 23 September 2013. The on board Visible and Infrared Radiometer (VIRR) can be used to observe global sea surface temperature (SST). In this paper, the VIRR SST products are compared with MODIS SST products and buoy measurements from 2015 to 2019. The collocations of VIRR, MODIS, and buoy SST are generated separately during the day and night with the spatial window of 0.05° × 0.05°. The comparison results show that the biases of VIRR SST minus buoy SST during the day and night are −0.21 and −0.13 °C with a corresponding robust standard deviation (RSD) of 0.58 and 0.59 °C, respectively. The mean differences between VIRR and MODIS are −0.10 and 0.08 °C with RSDs of 0.53 and 0.58 °C for the daytime and nighttime, respectively. The consistency of VIRR SST accuracy from 2015 to 2019 and the dependence of VIRR SST error on SST and latitude are also investigated.

Towards pluvial flooding hazard assessment in an urban environment

<p>Urban pluvial floods are considered as a ubiquitous hazard. The increase in intensity and frequency of extreme rainfall events, combined with high population density makes urban areas vulnerable to pluvial flooding. Pluvial floods could occur anywhere depending on the existence of minimal areas for surface runoff generation and concentration. Detailed hydrologic and hydrodynamic simulations are computationally expensive and resource-intensive. This study applies two computationally inexpensive approaches to identify risk areas for pluvial flooding. One approach uses common GIS operations to detect flood-prone depressions from a high-resolution 1m x 1m Digital Elevation Model (DEM), to identify contributing catchments, and to represent runoff concentration by a fill-spill-merge approach. The second approach employs GIS to identify pluvial flood-prone hotspots in terms of the topographic wetness index (TWI).  Based on the exceedance of a TWI threshold, flood-prone areas are identified using a maximum likelihood method. The threshold is estimated by comparing the TWI to inundation profiles from a two-dimensional (2D) hydrodynamic model (TELEMAC 2D), calculated for various rainfall depths within a given spatial window. The two approaches are applied to two flooding hotspots in Berlin, which have been repeatedly subject to pluvial flooding in the last decades and the outputs are compared against the detailed output from TELEMAC 2D. </p>

Masking, crowding and grouping: Connecting low and mid-level vision

An important task for vision science is to build a unitary framework of low and mid-level vision. As a step on this way, our study examined differences and commonalities between masking, crowding and grouping – three processes that occur through spatial interactions between neighbouring elements. We measured contrast thresholds as functions of inter-element spacing and eccentricity for Gabor detection, discrimination, contour integration, using a common stimulus grid consisting of 9 Gabor elements. From these thresholds, we derived a) the baseline contrast necessary to perform each task and b) the spatial extent over which task performance was stable. This spatial window can be taken as an indicator of field size, where elements that fall within a putative field are readily combined. We found that contrast thresholds were universally modulated by inter-element distance, with a shallower and inverted effect for grouping compared to masking and crowding. Baseline contrasts for detecting stimuli and discriminating their properties were positively linked across the tested retinal locations (parafovea and near periphery), whereas those for integrating elements and discriminating their properties were negatively linked. Meanwhile, masking and crowding spatial windows remained uncorrelated across eccentricity, although they were correlated across participants. This suggests that the computation performed by each type of visual field operates over different distances that co-varies across observers, but not across retinal locations. Contrast-processing units may thus lie at the core of the shared idiosyncrasies across tasks reported in many previous studies, despite the fundamental differences in the extent of their spatial windows.

First Assessment of HY-1C COCTS Thermal Infrared Calibration Using MetOp-B IASI

The Chinese Ocean Color and Temperature Scanner (COCTS) onboard the Haiyang-1C (HY-1C) satellite was launched in September 2018. Accurate and stable calibration is one of the important factors when deriving geophysical parameters with high quality. The first assessment of HY-1C COCTS thermal infrared calibration is conducted in this research. We choose the Infrared Atmospheric Sounding Interferometer (IASI) onboard the MetOp-B satellite as the reference instrument, mainly due to its hyper-spectral characteristic and accurate calibration superiority. The brightness temperatures (BTs) from the two HY-1C COCTS thermal infrared bands centered near 11 and 12 µm are collocated with the IASI in the spatial window of 0.12° × 0.12° and temporal window of half an hour. The homogeneity filtering of matchups is also carried out by setting the relative standard deviation (RSD) thresholds on each collocated grid and its neighboring grids. Based on the filtered matchups, the HY-1C COCTS BTs from the 11 and 12 µm channels are compared with IASI. The mean differences of COCTS minus IASI are 2.68 and 3.18 K for the 11 and 12 μm channels, respectively. The corresponding standard deviations (SDs) are also 0.29 and 0.28 K, respectively. In addition, the BT differences show latitude-dependence and BT-dependence. In order to correct the HY-1C COCTS thermal infrared BTs, the latitude-dependent coefficients are obtained to express the relationship between the BT differences and IASI BTs using the linear robust regression. After the BT correction, the biases and BT-dependence of the COCTS original BT minus IASI differences are removed. Further, the SDs decrease to 0.21 K for the 11 and 12 μm channels. Overall, the calibration of the HY-1C COCTS thermal infrared channels remains stable and the accuracy is around 0.2 K after inter-calibration.

Unconscious information integration: A replication and the role of spatial window

Consciousness and high-level information integration have commonly been closely related to each other (Baars, 2002; Dehaene & Naccache, 2001; Tononi, 2004). Different results, however, have challenged this assumption by showing that information integration can occur for stimuli presented outside of conscious awareness. More recently, a re-examination of some of the data and different replication attempts questioned these results thereby again suggesting a close link between consciousness and information integration. The current study aimed at (i) replicating another piece of evidence for unconscious information integration and (ii) investigating if the size of the spatial window in which the information to be integrated is presented could explain why unconscious information integration sometimes fails. Results showed a reliable replication so providing further evidence for unconscious information integration. Furthermore, our results revealed that unconscious integration depends on the size of the spatial window in which the information is presented.

The perceptual continuity field is retinotopic

Visual perception is systematically biased towards input from the recent past: perceived orientation, numerosity, and face identity are pulled towards previously seen stimuli. To better understand the brain level at which serial dependence occurs, the present study examined its spatial tuning. In three experiments, serial dependence occurred between stimuli occupying the same retinal position. Serial dependence between stimuli at distant retinal locations was smaller, even when the stimuli occupied the same location in external space. The spatial window over which serial dependence occurs is thus retinotopic, but wide, suggesting that serial dependence occurs at late stages of visual processing.