• Digital Humanities and Cultural Heritage
• Natural Sciences and Engineering Re... close
• CN close

AbstractWe develop an anomaly detection method when systematic anomalies, possibly statistically very similar to genuine inputs, are affecting control systems at the input and/or output stages. The method allows anomaly free inputs (i.e., those before contamination) to originate from a wide class of random sequences, thus opening up possibilities for diverse applications. To illustrate how the method works on data, and how to interpret its results and make decisions, we analyze several actual time series, which are originally nonstationary but in the process of analysis are converted into stationary. As a further illustration, we provide a controlled experiment with anomaly free inputs following an ARMA time series model under various contamination scenarios.

AbstractThe Standard Generalized Markup Language (SGML) and the Extensible Markup Language (XML) allow users to define document-type definitions (DTDs), which are essentially extended context-free grammars expressed in a notation that is similar to extended Backus–Naur form. The right-hand side of a production, called a content model, is both an extended and a restricted regular expression. The semantics of content models for SGML DTDs can be modified by exceptions (XML does not allow exceptions). Inclusion exceptions allow named elements to appear anywhere within the content of a content model, and exclusion exceptions preclude named elements from appearing in the content of a content model. We give precise definitions of the semantics of exceptions, and prove that they do not increase the expressive power of SGML DTDs when we restrict DTDs according to accepted SGML practice. We prove the following results:1. Exceptions do not increase the expressive power of extended context-free grammars.2. For each DTD with exceptions, we can obtain a structurally equivalent extended context-free grammar.3. For each DTD with exceptions, we can construct a structurally equivalent DTD when we restrict the DTD to adhere to accepted SGML practice.4. Exceptions are a powerful shorthand notation—eliminating them may cause exponential growth in the size of an extended context-free grammar or of a DTD.

AbstractSaline alkaline lakes that precipitate sodium carbonate evaporites are most common in volcanic terrains in semi‐arid environments. Processes that lead to trona precipitation are poorly understood compared to those in sulphate‐dominated and chloride‐dominated lake brines. Nasikie Engida (Little Magadi) in the southern Kenya Rift shows the initial stages of soda evaporite formation. This small shallow (<2 m deep; 7 km long) lake is recharged by alkaline hot springs and seasonal runoff but unlike neighbouring Lake Magadi is perennial. This study aims to understand modern sedimentary and geochemical processes in Nasikie Engida and to assess the importance of geothermal fluids in evaporite formation. Perennial hot‐spring inflow waters along the northern shoreline evaporate and become saturated with respect to nahcolite and trona, which precipitate in the southern part of the lake, up to 6 km from the hot springs. Nahcolite (NaHCO3) forms bladed crystals that nucleate on the lake floor. Trona (Na2CO3·NaHCO3·2H2O) precipitates from more concentrated brines as rafts and as bottom‐nucleated shrubs of acicular crystals that coalesce laterally to form bedded trona. Many processes modify the fluid composition as it evolves. Silica is removed as gels and by early diagenetic reactions and diatoms. Sulphate is depleted by bacterial reduction. Potassium and chloride, of moderate concentration, remain conservative in the brine. Clastic sedimentation is relatively minor because of the predominant hydrothermal inflow. Nahcolite precipitates when and where pCO2 is high, notably near sublacustrine spring discharge. Results from Nasikie Engida show that hot spring discharge has maintained the lake for at least 2 kyr, and that the evaporite formation is strongly influenced by local discharge of carbon dioxide. Brine evolution and evaporite deposition at Nasikie Engida help to explain conditions under which ancient sodium carbonate evaporites formed, including those in other East African rift basins, the Eocene Green River Formation (western USA), and elsewhere.

Abstract. High-resolution 3-D P and S wave crustal velocity and Poisson's ratio models of the 1992 Landers earthquake (Mw 7.3) area are determined iteratively by a wave-equation based traveltime seismic tomography (WETST) technique as developed in the first paper. The details of data selection, synthetic arrival-time determination, and trade-off analysis of damping and smoothing parameters are presented to show the performance of this new tomographic inversion method. A total of 78 523 P wave and 46 999 S wave high-quality arrival-time data from 2041 local earthquakes recorded by 275 stations during the period of 1992–2013 is used to obtain the final tomographic models which costs around 10 000 CPU h. Checkerboard resolution tests are conducted to verify the reliability of inversion results for the chosen seismic data and the wave-equation based traveltime seismic tomography method. Significant structural heterogeneities are revealed in the crust of the 1992 Lander earthquake area which may be closely related to the local seismic activities. Strong variations of velocity and Poisson's ratio exist in the source regions of the Landers and three other strong earthquakes in this area. Most seismicity occurs in areas with high-velocity and low Poisson's ratio, which may be associated with the seismogenic layer. Pronounced low-velocity anomalies revealed in the lower crust along the Elsinore, the San Jacinto and the San Andreas faults may reflect the existence of fluids in the lower crust. The recovery of these strong heterogeneous structures are facilitated by the use of full wave equation solvers and WETST and verifies their ability in generating high-resolution tomographic models.

Abstract. The mid-Pliocene warm period (mPWP; ∼3.2 million years ago) is seen as the most recent time period characterized by a warm climate state, with similar to modern geography and ∼400 ppmv atmospheric CO2 concentration, and is therefore often considered an interesting analogue for near-future climate projections. Paleoenvironmental reconstructions indicate higher surface temperatures, decreasing tropical deserts, and a more humid climate in West Africa characterized by a strengthened West African Monsoon (WAM). Using model results from the second phase of the Pliocene Modelling Intercomparison Project (PlioMIP2) ensemble, we analyse changes of the WAM rainfall during the mPWP by comparing them with the control simulations for the pre-industrial period. The ensemble shows a robust increase in the summer rainfall over West Africa and the Sahara region, with an average increase of 2.5 mm/d, contrasted by a rainfall decrease over the equatorial Atlantic. An anomalous warming of the Sahara and deepening of the Saharan Heat Low, seen in >90 % of the models, leads to a strengthening of the WAM and an increased monsoonal flow into the continent. A similar warming of the Sahara is seen in future projections using both phase 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5). Though previous studies of future projections indicate a west–east drying–wetting contrast over the Sahel, PlioMIP2 simulations indicate a uniform rainfall increase in that region in warm climates characterized by increasing greenhouse gas forcing. We note that this effect will further depend on the long-term response of the vegetation to the CO2 forcing. International audience

In this paper, we propose a wave-equation-based travel-time seismic tomography method with a detailed description of its step-by-step process. First, a linear relationship between the travel-time residual Δt = Tobs–Tsyn and the relative velocity perturbation δ c(x)/c(x) connected by a finite-frequency travel-time sensitivity kernel K(x) is theoretically derived using the adjoint method. To accurately calculate the travel-time residual Δt, two automatic arrival-time picking techniques including the envelop energy ratio method and the combined ray and cross-correlation method are then developed to compute the arrival times Tsyn for synthetic seismograms. The arrival times Tobs of observed seismograms are usually determined by manual hand picking in real applications. Travel-time sensitivity kernel K(x) is constructed by convolving a~forward wavefield u(t,x) with an adjoint wavefield q(t,x). The calculations of synthetic seismograms and sensitivity kernels rely on forward modeling. To make it computationally feasible for tomographic problems involving a large number of seismic records, the forward problem is solved in the two-dimensional (2-D) vertical plane passing through the source and the receiver by a high-order central difference method. The final model is parameterized on 3-D regular grid (inversion) nodes with variable spacings, while model values on each 2-D forward modeling node are linearly interpolated by the values at its eight surrounding 3-D inversion grid nodes. Finally, the tomographic inverse problem is formulated as a regularized optimization problem, which can be iteratively solved by either the LSQR solver or a~nonlinear conjugate-gradient method. To provide some insights into future 3-D tomographic inversions, Fréchet kernels for different seismic phases are also demonstrated in this study.

In this paper, we present SemEval-2020 Task 4, Commonsense Validation and Explanation (ComVE), which includes three subtasks, aiming to evaluate whether a system can distinguish a natural language statement that makes sense to humans from one that does not, and provide the reasons. Specifically, in our first subtask, the participating systems are required to choose from two natural language statements of similar wording the one that makes sense and the one does not. The second subtask additionally asks a system to select the key reason from three options why a given statement does not make sense. In the third subtask, a participating system needs to generate the reason. We finally attracted 39 teams participating at least one of the three subtasks. For Subtask A and Subtask B, the performances of top-ranked systems are close to that of humans. However, for Subtask C, there is still a relatively large gap between systems and human performance. The dataset used in our task can be found at https://github.com/wangcunxiang/SemEval2020- Task4-Commonsense-Validation-and-Explanation; The leaderboard can be found at https://competitions.codalab.org/competitions/21080#results. Comment: Task description paper of SemEval-2020 Task 4: Commonsense Validation and Explanation