Signatures Of Events Research Articles

Disruption of awake sharp-wave ripples does not affect memorization of locations in repeated-acquisition spatial memory tasks.

Storing and accessing memories is required to successfully perform day-to-day tasks, for example for engaging in a meaningful conversation. Previous studies in both rodents and primates have correlated hippocampal cellular activity with behavioral expression of memory. A key role has been attributed to awake hippocampal replay - a sequential reactivation of neurons representing a trajectory through space. However, it is unclear if awake replay impacts immediate future behavior, gradually creates and stabilizes long-term memories over a long period of time (hours and longer), or enables the temporary memorization of relevant events at an intermediate time scale (seconds to minutes). In this study, we aimed to address the uncertainty around the timeframe of impact of awake replay by collecting causal evidence from behaving rats. We detected and disrupted sharp wave ripples (SWRs) - signatures of putative replay events - using electrical stimulation of the ventral hippocampal commissure in rats that were trained on three different spatial memory tasks. In each task, rats were required to memorize a new set of locations in each trial or each daily session. Interestingly, the rats performed equally well with or without SWR disruptions. These data suggest that awake SWRs - and potentially replay - does not affect the immediate behavior nor the temporary memorization of relevant events at a short timescale that are required to successfully perform the spatial tasks. Based on these results, we hypothesize that the impact of awake replay on memory and behavior is long-term and cumulative over time.

Signatures of neurological adverse events after vaccination

There have been reports associated with the development of neurological adverse events (AEs) post-vaccination. Here, we retrospectively examine the Vaccine Adverse Events Reporting System (VAERS) database for neurological AEs reported following vaccination. Since VAERS is a passive reporting system, to minimize reporting bias and to reduce background events, this retrospective study examines both age-stratified AE reports made with onset within 24 h of immunization, and age-stratified AE reports regardless of timeframe from immunization. Immediate temporal onset data patterns for febrile convulsion, seizure, and syncope AEs were observed for multiple vaccines. For age-stratified AEs in infants up to 3 years of age, the following patterns of high association were observed: (i) Aphasia, autism spectrum disorder, and speech disorder were found to be highly associated with the measles, mumps, and rubella and hepatitis B (HepB) vaccines; (ii) febrile convulsion and syncope were found to be highly associated with the meningococcal group B vaccine; and (iii) seizures were found to be highly associated with diphtheria and tetanus toxoids and whole-cell pertussis (DTP) vaccines.

Measuring and Assessing Long‐Duration Impacts for Truck and Trailer

ABSTRACTA vehicle's long‐duration impacts events are experienced during turning, braking, and accelerating and decelerating. These long‐duration events are mixed with random impacts and shocks from various patterns and magnitudes. This study reports a comprehensive measurement and assessment of horizontal long‐duration impact dynamics for less‐than‐truckload (LTL) transportation. The collected horizontal impacts were synchronized with GPS data, allowing for the geographical location and identification of the event's signatures. All critical horizontal long‐duration impacts were detected by a MATLAB‐based algorithm and clustered into designated groups. A maximum collected environment and statistical analysis were assessed for the collected data, including the range, mean and cumulative probabilities. The study revealed that horizontal impacts caused by left‐turning and longitudinal braking are likely the most critical horizontal impacts. Additionally, lateral and longitudinal linear jerks were obtained for comparison with the EUMOS standard.

Uganda chicken genetic resources: II. genetic diversity and population demographic history inferred from mitochondrial DNA D-loop sequences.

The genetic diversity of indigenous chickens, which comprise over 80% of the chicken resources in Uganda, is largely not well-characterized for their genetic contribution. This study assessed the genetic diversity and population structure of the indigenous chicken population in Uganda to serve as an essential component for improvement and conservation strategies. A set of 344 mitochondrial DNA (mtDNA) D-loop sequences among 12 Ugandan chicken populations was evaluated. Twenty-eight polymorphic sites, accounting for 4.26% of the total analyzed loci of 658bp, defined 32 haplotypes. The haplotype diversity (Hd) was 0.437, with a nucleotide diversity (π) of 0.0169, while the average number of nucleotide differences (k) was 0.576, indicating a population that is moderately genetically diverse. Analysis of molecular variance found 98.39% (ρ < 0.01) of the total sequence variation among the chicken haplotypes within populations, 1.08% (ρ < 0.05) among populations, and 0.75% (ρ > 0.05) among populations within regions. This revealed subtle genetic differentiation among the populations, which appeared to be influenced by population fragmentation, probably due to neutral mutation, random genetic drift, and/or balancing selection. All the haplotypes showed affinity exclusively to the haplogroup-E mtDNA phylogeny, with haplotype UGA01 signaling an ancestral haplotype in Uganda. Neutrality tests Tajima's D (-2.320) and Fu's Fs (-51.369), augmented with mismatch distribution to measure signatures of recent historical demographic events, supported a population expansion across the chicken populations. The results show one matrilineal ancestry of Ugandan chickens from a lineage widespread throughout the world that began in the Indian subcontinent. The lack of phylogeographic signals is consistent with recent expansion events with extensive within-country genetic intermixing among haplotypes. Thus, the findings in this study hold the potential to guide conservation strategies and breeding programs in Uganda, given that higher genetic diversity comes from within the chicken population.

Effective yields as tracers of feedback effects on metallicity scaling relations in the EAGLE cosmological simulations

ABSTRACT Effective yields, yeff, are defined by fundamental galaxy properties (i.e. stellar mass M⋆, gas mass Mgas, and gas-phase metallicity). For a closed-box model, yeff is constant and equivalent to the mass in metals returned to the gas per unit mass locked in long-lived stars. Deviations from such behaviour have been often considered observational signatures of past feedback events. By analysing eagle simulations with different feedback models, we evaluate the impact of supernovae (SNe) and active galactic nuclei (AGNs) feedback on yeff at redshift z = 0. When removing supermassive black holes (BHs) and, hence, AGN effects, in simulations, galaxies are located around a plane in the M⋆–Mgas–O/H parameter space (being O/H a proxy for gas metallicity, as usual), with such a plane roughly describing a surface of constant yeff. As the ratio between BH mass and M⋆ increases, galaxies deviate from that plane towards lower yeff as a consequence of AGN feedback. For galaxies not strongly affected by AGN feedback, a stronger SN feedback efficiency generates deviations towards lower yeff, while galaxies move towards the opposite side of the plane (i.e. towards higher values of yeff) as SN feedback becomes weaker. Star-forming galaxies observed in the Local Universe are located around a similar 3D plane. Our results suggest that the features of the scatter around the observed plane are related to the different feedback histories of galaxies, which might be traced by yeff.

Structural connectome architecture shapes the maturation of cortical morphology from childhood to adolescence

Cortical thinning is an important hallmark of the maturation of brain morphology during childhood and adolescence. However, the connectome-based wiring mechanism that underlies cortical maturation remains unclear. Here, we show cortical thinning patterns primarily located in the lateral frontal and parietal heteromodal nodes during childhood and adolescence, which are structurally constrained by white matter network architecture and are particularly represented using a network-based diffusion model. Furthermore, connectome-based constraints are regionally heterogeneous, with the largest constraints residing in frontoparietal nodes, and are associated with gene expression signatures of microstructural neurodevelopmental events. These results are highly reproducible in another independent dataset. These findings advance our understanding of network-level mechanisms and the associated genetic basis that underlies the maturational process of cortical morphology during childhood and adolescence.

Identifying and Constraining Marsh-Type Transitions in Response to Increasing Erosion over the Past Century

Marsh environments, characterized by their flora and fauna, change laterally in response to shoreline erosion, water levels and inundation, and anthropogenic activities. The Grand Bay coastal system (USA) has undergone multiple large-scale geomorphic and hydrologic changes resulting in altered sediment supply, depositional patterns, and degraded barrier islands, leaving wetland salt marshes vulnerable to increased wave activity. Two shore-perpendicular transect sites, one along a low-activity shoreline and the other in a high activity area of the same bay-marsh complex, were sampled to investigate how the marshes within 50 m of the modern shoreline have responded to different levels of increased wave activity over the past century. Surface sediments graded finer and more organic with increased distance from the shoreline while cores generally exhibited a coarsening upwards grain-size trend; all cores contained multiple large sedimentological shifts. 210Pb-based mass accumulation rates over the last two decades were greater than the long-term (centurial) average at each site with the fastest accumulation rates of 7.81 ± 1.58 and 7.79 ± 1.63 kg/m2/year at the sites nearest the shoreline. A shoreline change analysis of three time-slices (1848–2017, 1957–2017, 2016–2017) shows increased erosion at both sites since 1848 with modern rates of −0.95 and −0.88 m/year. Downcore sedimentology, mass accumulation rates, and shoreline change rates paired with foraminiferal biofacies and identification of local estuarine indicator species, Paratrochammina simplissima, aided in identifying paleo marsh types, their relative proximity to the shoreline, and sediment provenance. The high-energy marsh site transitioned from middle marsh to low marsh in the 1960s, and the low-energy marsh site transitioned later, at the end of the twentieth and early twenty-first century, due to its more protected location. Marsh type transition corresponds chronologically with the coarsening upwards grain-size trend observed and the degradation of Grand Batture Island; since its submergence, signatures of multiple storm event have been preserved downcore.

Robust Data-Driven Automation Based on Relaxed Supervised Hashing With Self-Optimized Labels

Recently, the Visual Internet of Things (VIoT) has been widely used in data-driven automation, where VIoT devices are used to monitor environmental dynamics and to trigger corresponding actuators after examining event signatures (e.g., hashes). Nonetheless, VIoT devices may collect partially observed data, e.g., largely occluded images, which cause biased labeling and oversensitivity during modeling. Moreover, in typical methods, class labels are rigid and fixed categorical variables, where marginal space between different classes is fixed and equal. In fact, margins may be unequally spaced. Such nonflexibility in class labels inevitably causes fitting difficulty. In light of such, this study proposes relaxed robust supervised hashing (Relaxed RSH) for generating reliable signatures that can simultaneously conquer the above problems caused by incomplete data and rigid margins. To accommodate oversensitivity, this study proposes measuring hash learning loss by robust half quadratic (HQ) functions for modeling incomplete data. In the initial label matrix, slack variables are added to relax binary constraints. Such slack variables can be self-optimized during the learning process and can be used to automatically adjust margins between different classes. Decorrelation, balancing, and normalization constraints based on Relaxed RSH are also devised to provide discriminant and compact codes. Experimental results based on open datasets showed that the proposed method yielded higher mAP and F1 than the baselines. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This work is motivated by the problems caused by incomplete data and rigid class margins during event signature (e.g., hash) learning, where hashes are used to trigger automation systems. In existing hashing methods, incomplete data (e.g., continuous occlusion, missing values, and sample-specific outliers) along with rigid class margins cause fitting biases, thereby challenging data-driven automation. This study proposes Relaxed RSH by designing robust HQ loss, self-optimized label learning, and corresponding constraints for generating discriminant hashes. This prevents actuators from being mistriggered by corrupted data. Experiments were conducted on various data corruption. Future research will address the design for incremental/decentralized hash learning.

Oligocene biostratigraphy, depositional patterns, and stable isotope values in the eastern Zagros basin: Novel insight into the signature of regional and global events

Biostratigraphy, depositional environment, sequence stratigraphy, and paleoclimate iterpretation of the Asmari carbonate reservoir are the subject of the current study. Two, earlier uninvestigated stratigraphic sections are studied and correlated over the eastern Zagros basin. The vertical distribution of foraminifera (benthic and planktic) reveals that the Asmari Formation deposited during the Rupelian-Chattian. Three shallow benthic foraminifera biozones are established, namely the Globigerina-Turborotalia cerroazulensis-Hantkenina Assemblage Zone, the Nummulites vascus-Nummulites fichteli Assemblage Zone, and the Archaias asmaricus- Archaias hensoni-Miogypsinoides complanatus Assemblage Zone. Ten microfacies types associated with the inner, middle and outer ramp of a carbonate platform are identified. Three depositional sequences are recognized in the eastern Zagros basin. The oldest sequence is Rupelian in age, and two others are of Rupelian-Chattian and Chattian in age. Two maximum flooding surfaces occur in the eastern Zagros basin. The isotope startigraphical data show that the more positive values of the δ18O and δ13C coincide with the maximum flooding surfaces, while these values show depletion over the sequence boundaries. The exception is observed at the upper boundary of the succession where the hypersalinity conditions affected the trend. The stable isotope values obtained from bulk samples enable to identify the Oligocene glacial events such as Oi2 and, Oi2a (Rupelian) and Oi2b (Chattian). The examination of the grain associations of the MF3 and MF5 prove these cooling events. We suggest the middle ramp microfacies and MFS2 of Sq.2 as signatures for tracing these cooling events throughout the eastern Zagros basin.

Unraveling the maternal and paternal origins of allotetraploid Vigna reflexo-pilosa

The genomic structures of Vigna hirtella Ridl. and Vigna trinervia (B.Heyne ex Wight & Arn.) Tateishi & Maxted, key ancestral species of the allotetraploid Vigna reflexo-pilosa var. glabra (Roxb.) N.Tomooka & Maxted, remain poorly understood. This study presents a comprehensive genomic comparison of these species to deepen our knowledge of their evolutionary trajectories. By comparing the genomic profiles of V. hirtella and V. trinervia with those of V. reflexo-pilosa, we investigate the complex genomic mechanisms underlying allopolyploid evolution within the genus Vigna. Comparison of the chloroplast genome revealed that V. trinervia is closely related to V. reflexo-pilosa. De novo assembly of the whole genome, followed by synteny analysis and Ks value calculations, confirms that V. trinervia is closely related to the A genome of V. reflexo-pilosa, and V. hirtella to its B genome. Furthermore, the comparative analyses reveal that V. reflexo-pilosa retains residual signatures of a previous polyploidization event, particularly evident in higher gene family copy numbers. Our research provides genomic evidence for polyploidization within the genus Vigna and identifies potential donor species of allotetraploid species using de novo assembly techniques. Given the Southeast Asian distribution of both V. hirtella and V. trinervia, natural hybridization between these species, with V. trinervia as the maternal ancestor and V. hirtella as the paternal donor, seems plausible.

Photon counting x-ray detectors as scatter probes.

Direct conversion x-ray Photon Counting Detectors (PCD) are posed to play a vital role in future medical imaging devices such as Computed Tomography (CT) scanners. PCD are expected to improve current CT technology on several fronts, such as resolution, dose utilization, and spectral performance. However, they are not readily expected to improve the handling of object scatter, one of the major sources of image artifacts in CT technology. We explore a potential method for obtaining in-situ object scatter estimation using the same PCD array used in the x-ray imaging system, such as in computed tomography. This unexpected benefit of using PCD has the potential to improve the image quality by providing better input into the scatter estimation and correction algorithms used in image reconstruction. In CT scanners the primary method for rejecting scatter signal originating from the scanned object relies on placing anti-scatter grids (ASG) close to the detector plane. This remains the case when transitioning to using PCD instead of energy integration detectors in CT. However, the combination of PCD and ASG opens a possibility to use some of the unique properties of PCD, namely, very low noise and coincidence counters to obtain, in addition to the attenuation data, a simultaneous and instantaneous estimate of the scatter signal reaching every detector element. When a small air gap is introduced between the ASG and the detector surface, the scatter radiation with large angular distribution has a greater probability of producing charge sharing events that can be detected by a coincidence counter. In this work we demonstrate the feasibility of such an approach in a tabletop experiment using PCD detector that lacks coincidence counting capability, instead we use the spectral signature of split charge events as proxy to coincidence counting. For this purpose, we first demonstrate the spectral impact of ASG misalignment using the same experimental setup. In addition, we perform a separate tabletop scattering experiment from a narrow column of water that demonstrates another potential use of the low noise capabilities of PCDs. We measured and quantified the high sensitivity of the spectral response to ASG alignment on the PCD detector pixel array, we found that the probability of energy misregistration of 60keV photons can increase by up to a factor of 3 when the ASG is poorly aligned. We then leveraged these results to obtain an estimate on the expected increase in coincidence counts for a wide range of scatter-to-primary (SPR) ratio and find a good match with expectations from a geometric modeling of the system, where the expected increase in coincidences was of the order of the SPR. Finally, the low noise detector also allowed us to measure the real space scatter signal associated with the coherent molecular form factor of water, revealing the ring-shaped scatter signal with an energy dependent distribution that was well captured by calculation. The advent of PCD detectors and their imminent use in commercial CT scanners opens new and exciting possibilities for utilizing PCD detectors in unexpected ways. In this proof-of-concept study, we showed how charge sharing, a spectral information degrading effect, can instead be used to obtain in-situ scatter estimation. We also demonstrated the PCD ability to perform extremely sensitive measurements using affordable benchtop setup for investigations normally reserved for synchrotron facilities.

Abstract B018: MTA-cooperative PRMT5 inhibitors selectively modulate RNA splicing in MTAP-deleted cancer cells across histologies

Abstract PRMT5 is a type II arginine methyltransferase that forms an active complex with methylosome protein 50 (MEP50) to catalyze the symmetric dimethylation (SDMA) of arginine residues in proteins that regulate biological roles including modulation of apoptosis, DNA damage response and RNA processing. Some of the best characterized PRMT5 substrates are SNRPB, SNRPD1 and SNRPD3, which are necessary for the formation of the spliceosome and therefore RNA splicing fidelity. The development of MTA-cooperative PRMT5 inhibitors, including the clinical stage inhibitors TNG908 and TNG462, have been shown in preclinical studies to selectively inhibit PRMT5 in MTAP-deleted cancer cells while sparing normal, MTAP-intact cells. Consistent with this selective, on-target mechanism, treatment with TNG908 in preclinical studies results in increased aberrant RNA splicing in MTAP-deleted cells relative to MTAP-intact cells. As MTAP loss occurs in 10-15% of all human cancer, the identification of a signature of alternative splicing events may report pharmacodynamic activity of PRMT5 inhibitors and potentially predict patient response. Similar splicing alterations caused by PRMT5 inhibition were identified in preclinical MTAP-deleted cancer models representing glioblastoma, non-small cell lung cancer, among others, suggesting the events are histology-agnostic. Additionally, titration of exogenous MTA, an endogenous inhibitor of PRMT5, recapitulated the observed splicing events in preclinical MTAP-proficient cells. Similar findings were observed utilizing a pharmacological inhibitor of MTAP suggesting that the identified alternative splicing events are dependent on accumulation of MTA. Collectively, these data suggest that a PRMT5-dependent RNA splicing signature can be developed to identify solid tumors that may best respond to MTA-cooperative PRMT5 inhibitors as well as monitor their pharmacodynamic activity. Citation Format: Matthew R Tonini, Samuel R Meier, Shangtao Liu, Kevin M Cottrell, John P Maxwell, Jannik N Andersen, Alan Huang, Luisa Cimmino, Kimberly J Briggs. MTA-cooperative PRMT5 inhibitors selectively modulate RNA splicing in MTAP-deleted cancer cells across histologies [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr B018.

Diversity and evolution of the MHC class II DRB gene in the Capra sibirica experienced a demographic fluctuation in China

The major histocompatibility complex (MHC) genes are the most polymorphic genes in vertebrates, and their proteins play a critical role in adaptive immunity for defense against a variety of pathogens. MHC diversity was lost in many species after experiencing a decline in size. To understand the variation and evolution of MHC genes in the Siberian ibex, Capra sibirica, which has undergone a population decline, we analyzed the variation of the second exon of MHC class II DRB genes in samples collected from five geographic localities in Xinjiang, China, that belong to three diverged mitochondrial clades. Consequently, we identified a total of 26 putative functional alleles (PFAs) with 260 bp in length from 43 individuals, and found one (for 27 individuals) to three (for 5 individuals) PFAs per individual, indicating the presence of one or two DRB loci per haploid genome. The Casi-DRB1*16 was the most frequently occurring PFA, Casi-DRB1*22 was found in only seven individuals, 14 PFAs occurred once, 7 PFAs twice, implying high frequency of rare PFAs. Interestingly, more than half (15) of the PFAs were specific to clade I, only two and three PFAs were specific to clades II and III, respectively. So, we assume that the polygamy and sexual segregation nature of this species likely contributed to the allelic diversity of DRB genes. Genetic diversity indices showed that PFAs of clade II were lower in nucleotide, amino acid, and supertype diversity compared to those of the other two clades. The pattern of allele sharing and FST values between the three clades was to some extent in agreement with the pattern observed in mitochondrial DNA divergence. In addition, recombination analyses revealed no evidence for significant signatures of recombination events. Alleles shared by clades III and the other two clades diverged 6 million years ago, and systematic neighbor grids showed Trans-species polymorphism. Together with the PAML and MEME analyses, the results indicated that the DRB gene in C. sibirica evolved under balancing and positive selection. However, by comparison, it can be clearly seen that different populations were under different selective pressures. Our results are valuable in understanding the diversity and evolution of the DRB gene in a mountain living C. sibirica and in making decisions on future long-term protection strategies.

Genetic signatures of lineage fusion closely resemble population decline.

Accurate interpretation of the genetic signatures of past demographic events is crucial for reconstructing evolutionary history. Lineage fusion (complete merging, resulting in a single panmictic population) is a special case of secondary contact that is seldom considered. Here, the circumstances under which lineage fusion can be distinguished from population size constancy, growth, bottleneck, and decline were investigated. Multi-locus haplotype data were simulated under models of lineage fusion with different divergence versus sampling lag times (D:L ratios). These pseudo-observed datasets also differed in their allocation of a fixed amount of sequencing resources (number of sampled alleles, haplotype length, number of loci). Distinguishability of lineage fusion versus each of 10 untrue non-fusion scenarios was quantified based on six summary statistics (neutrality tests). Some datasets were also analyzed using extended Bayesian skyline plots. Results showed that signatures of lineage fusion very closely resemble those of decline-high distinguishability was generally limited to the most favorable scenario (D:L = 9), using the most sensitive summary statistics (F S and Z nS), coupled with the optimal sequencing resource allocation (maximizing number of loci). Also, extended Bayesian skyline plots often erroneously inferred population decline. Awareness of the potential for lineage fusion to carry the hallmarks of population decline is critical.

Signatures of Oceanic Wind Events in Convection-Resolving WRF Model Simulations

Abstract Analyses of cloud-top temperature and lightning characteristics of 48 Weather Research and Forecasting (WRF) Model–simulated ocean-based wind events, with 1-min temporal and 0.5-km horizontal resolution, revealed signatures similar to the corresponding 13 observed events detected by buoys and Coastal-Marine Automated Network (C-MAN) stations as shown in prior research on ocean-based wind events by the first author. These events occurred in the eastern Gulf of Mexico and in the Atlantic Ocean from Florida northward through South Carolina. The coldest WRF cloud-top temperature (WCTT) and peak WRF-estimated lightning flash rate values of the model-simulated events, where each event was required to have a negative vertical velocity of at least 10 m s−1 in the lowest 2 km associated with a convective storm, occurred at an average of 4.2 and 1.1 min prior to the events, respectively. With 36 of the events, the peak estimated flash rate occurred within 5 min of the coldest WCTT. Cloud depth typically increased as the WCTT decreased, and the maximum depth occurred at an average of 2.9 min prior to the events. Thermal cooling and precipitation loading provided negative buoyancy needed to help drive the wind events. Environmental characteristics of the model-simulated ocean-based wind events also resembled those associated with land-based wet downbursts, including moist air near the surface, lapse rates near moist adiabatic, and low cloud bases.

Detecting Signatures of Convective Storm Events in GNSS‐SNR: Two Case Studies From Summer 2021 in Switzerland

AbstractGlobal Navigation Satellite Systems (GNSS) are not only a state‐of‐the‐art sensor for positioning and navigation applications but also a valuable tool for remote sensing. Through the usage of L‐band carrier frequencies, GNSS acts as an all‐weather‐operation system, offering substantial benefits compared to optical systems. Nevertheless, severe weather can still have an impact on the strength of signals received at a ground station, as we show in this study. We investigate GNSS Signal‐to‐Noise Ratio (SNR) observations during two severe convective storm events over the city of Zurich, Switzerland. We make use of a GNSS‐SNR‐based algorithm originally developed for the detection of hail particles from volcanic eruptions. Results indicate that, although GNSS observations are considered to be fairly insensitive to the presence of hydrometeors, convective storm events are visible in SNR observations. SNR levels of affected satellites show a significant drop during event periods, which are determined by weather radar observations.

Seismic signature detection during the 2018 Anak Krakatau flank collapse and tsunami using seismic amplitudes from regional-scale monitoring

On 22 December 2018, the major flank collapse of Anak Krakatau volcano generated a tsunami that struck the surrounding coasts of Java and Sumatra islands in Indonesia without warning. It was later suggested that the corresponding seismic event lacked the body-wave arrivals typical of tectonic earthquakes, causing difficulties for the automated detection system to recognize the event. We explore the possibility of detecting the seismic signature of such events without relying on the arrival times of body waves, by measuring seismic amplitudes in a regional seismic network at the expected arrival times from a fixed, potential source and comparing them to the theoretical attenuation of surface waves. We propose a fast detection method and evaluate the method using seismograms recorded during the flank collapse and tsunami episode as well as several known tectonic earthquakes. Detailed examinations of the detection results confirm the seismic signatures of the flank collapse and teleseismic events as suggested by previous studies. We also find more seismic signatures suggesting the occurrence of two possible smaller collapse events and variations in the eruptive activity related to the major flank collapse, as well as body and surface wave signals from two teleseismic earthquakes that were present during this episode. Finally, we construct a timeline of events during this devastating episode, combining our results with previous studies as well as insights from weather radar observations. With the ability to detect and discriminate various types of seismic events from each other, the detection method can be useful in assisting the existing monitoring and early warning systems in detecting major volcano-related tsunamigenic events.Graphical

Computed Protein-Protein Enthalpy Signatures as a Tool for Identifying Conformation Sampling Problems.

Understanding the thermodynamic signature of protein-peptide binding events is a major challenge in computational chemistry. The complexity generated by both components possessing many degrees of freedom poses a significant issue for methods that attempt to directly compute the enthalpic contribution to binding. Indeed, the prevailing assumption has been that the errors associated with such approaches would be too large for them to be meaningful. Nevertheless, we currently have no indication of how well the present methods would perform in terms of predicting the enthalpy of binding for protein-peptide complexes. To that end, we carefully assembled and curated a set of 11 protein-peptide complexes where there is structural and isothermal titration calorimetry data available and then computed the absolute enthalpy of binding. The initial "out of the box" calculations were, as expected, very modest in terms of agreement with the experiment. However, careful inspection of the outliers allows for the identification of key sampling problems such as distinct conformations of peptide termini not being sampled or suboptimal cofactor parameters. Additional simulations guided by these aspects can lead to a respectable correlation with isothermal titration calorimetry (ITC) experiments (R2 of 0.88 and an RMSE of 1.48 kcal/mol overall). Although one cannot know prospectively whether computed ITC values will be correct or not, this work shows that if experimental ITC data are available, then this in conjunction with computed ITC, can be used as a tool to know if the ensemble being simulated is representative of the true ensemble or not. That is important for allowing the correct interpretation of the detailed dynamics of the system with respect to the measured enthalpy. The results also suggest that computational calorimetry is becoming increasingly feasible. We provide the data set as a resource for the community, which could be used as a benchmark to help further progress in this area.

Signatures-and-sensitivity-based multi-criteria variational calibration for distributed hydrological modeling applied to Mediterranean floods

Classical calibration methods in hydrology typically rely on a single cost function computed on long-term streamflow series. Even when hydrological models achieve acceptable scores in NSE and KGE, imbalances can still arise between overall model performance and its ability to simulate flood events, particularly flash floods. Multi-scale signatures, which refer to hydrological signatures computed at different temporal and/or spatial scales, and distributed flood modeling, which accounts for spatial variability in input variables and model parameters, are important concepts in hydrological modeling. In this study, the potential of using multi-scale signatures is explored to enhance multi-criteria calibration methods for spatially distributed flood modeling, which remains considerable challenges. We present a novel signatures and sensitivity-based calibration approach implemented into a variational data assimilation algorithm capable to deal with high dimensional spatially distributed hydrological optimization problems. It is tested on 141 flash flood pronecatchments mostly located in the French Mediterranean region. Our approach involves computing several signatures, including flood event signatures, using an automated flood segmentation algorithm. We select suitable signatures for constraining the model based on their global sensitivity with the input parameters through global signature-based sensitivity analysis (GSSA). We then perform two multi-criteria calibration strategies using the selected signatures, including a single-objective optimization approach, which transforms the multi-criteria problem into a single-objective function, and a multi-objective optimization approach, which uses a simple additive weighting method to select an optimal solution from the Pareto set. Our results show significant improvements in both calibration and temporal validation metrics, especially for flood signatures, demonstrating the robustness and delicacy of our signatures-based calibration framework for enhancing flash flood forecasting systems.

CyPhERS: A cyber-physical event reasoning system providing real-time situational awareness for attack and fault response

Cyber–physical systems (CPSs) constitute the backbone of critical infrastructures such as power grids or water distribution networks. Operating failures in these systems can cause serious risks for society. To avoid or minimize downtime, operators require real-time awareness about critical incidents. However, online event identification in CPSs is challenged by the complex interdependency of numerous physical and digital components, requiring to take cyber attacks and physical failures equally into account. The online event identification problem is further complicated through the lack of historical observations of critical but rare events, and the continuous evolution of cyber attack strategies. This work introduces and demonstrates CyPhERS, a Cyber-Physical Event Reasoning System. CyPhERS provides real-time information pertaining the occurrence, location, physical impact, and root cause of potentially critical events in CPSs, without the need for historical event observations. Key novelty of CyPhERS is the capability to generate informative and interpretable event signatures of known and unknown types of both cyber attacks and physical failures. The concept is evaluated and benchmarked on a demonstration case that comprises a multitude of attack and fault events targeting various components of a CPS. The results demonstrate that the event signatures provide relevant and inferable information on both known and unknown event types.