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Conversational interfaces are increasingly popular as a way of connecting people to information. With the increased generative capacity of corpus‐based conversational agents comes the need to classify and filter out malevolent responses that are inappropriate in terms of content and dialogue acts. Previous studies on the topic of detecting and classifying inappropriate content are mostly focused on a specific category of malevolence or on single sentences instead of an entire dialogue. We make three contributions to advance research on the malevolent dialogue response detection and classification (MDRDC) task. First, we define the task and present a hierarchical malevolent dialogue taxonomy. Second, we create a labeled multiturn dialogue data set and formulate the MDRDC task as a hierarchical classification task. Last, we apply state‐of‐the‐art text classification methods to the MDRDC task, and report on experiments aimed at assessing the performance of these approaches. [ABSTRACT FROM AUTHOR]

This study uses precipitation oxygen isotopes (δ18Op) to examine key dynamics that deliver moisture to the southern slope of central Himalayas over different seasons. Results show that the majority of pre‐monsoon δ18Op values are relatively high and controlled by the westerlies and local moisture. However, some abnormally low δ18Op values coincide with higher precipitation amounts during the pre‐monsoon season due to moisture driven northwards from the Bay of Bengal and Arabian Sea to central Himalayas by anomalous circulations (quasi‐anticyclone, anticyclone, or/and westerlies trough). The size and location of the quasi‐anticyclone also influences the magnitude of the δ18Op decrease. In comparison, the monsoon δ18Op values are lower due to the combined effects of the Indian summer monsoon and convection. Our findings indicate that researchers need to consider the signals of abnormally low δ18Op values during the pre‐monsoon season when attempting to interpret ice core and tree‐ring records from central Himalayas. Plain Language Summary: How moisture is transported to the southern slope of central Himalayas remains unclear, especially for the frequent heavy precipitation events that occur during the pre‐monsoon season. Here, we address this issue using δ18Op measurements from the Asang station on the southern slope of central Himalayas during 2018–2019. We find that some abnormally low δ18Op values coincide with heavy precipitation during the pre‐monsoon season. These abnormally low δ18Op values are caused by the development of anomalous circulations that drives the Indian Ocean moisture to the Asang station. During the monsoon season, the δ18Op values are much lower than other seasons. Such low values are the product of the combined effects of the Indian summer monsoon and convection. We propose that the abnormally low δ18Op values during the pre‐monsoon season need to be considered in paleoclimate reconstructions using ice core and tree‐ring records in the region. The abnormally low δ18Op values during the pre‐monsoon season are closely correlated to anomalous circulations. This finding implies that δ18Op records from ice core and tree ring archives may have potential to reconstruct the frequency and intensity of such anomalous circulations during the pre‐monsoon season. Key Points: Abnormally low δ18Op values during the pre‐monsoon season coincide with heavy precipitation eventsOccurrences of anomalous circulations lead to the abnormally low δ18Op values during the pre‐monsoon seasonCombined effects of the Indian summer monsoon and convection cause lower δ18Op values during the monsoon season [ABSTRACT FROM AUTHOR]

Factorization machines are a generic supervised method for a wide range of tasks in the field of artificial intelligence, such as prediction, inference, etc., which can effectively model feature interactions. However, handling combinations of features is expensive due to the exponential growth of feature interactions with the order. In nature, not all feature interactions are equally useful for prediction. Recently, a large number of methods that perform feature interaction selection have attracted great attention because of their effectiveness at filtering out useless feature interactions. Current feature interaction selection methods suffered from the following limitations: (1) they assume that all users share the same feature interactions; and (2) they select pairwise feature interactions only. In this paper, we propose novel Bayesian variable selection methods, targeting feature interaction selection for factorization machines, which effectively reduce the number of interactions. We study personalized feature interaction selection to account for individual preferences, and further extend the model to investigate higher-order feature interaction selection on higher-order factorization machines. We provide empirical evidence for the advantages of the proposed Bayesian feature interaction selection methods using different prediction tasks. [ABSTRACT FROM AUTHOR]

Many parallel bridges have been recently designed and built around the world to accommodate the ever-increasing volumes of vehicle and rail traffic. Accordingly, the aerodynamic interference around the parallel girders becomes important to investigate for a more accurate estimation of wind-induced effects on bridges. In this study, a wide range of gap-width ratios (0–15) for parallel box girders are selected to investigate the aerodynamic interference using three-dimensional large eddy simulation at zero wind attack angle. Specific aerodynamic characteristics, including the flow structures, pressure distributions, mean values and standard deviations of the force coefficients, Strouhal number as well as spanwise correlations of the aerodynamic coefficients are examined with various gap-width ratios. The detailed comparison work demonstrates a good agreement with the experimental work. The simulation results reveal that all the aerodynamic characteristics are significantly influenced by the gap-width ratio. The three regions are bounded by critical gap-width ratios of G/B = 0.25 and G/B = 5. There are large changes in behavior at G/B = 0.25, whereas, for G/B > 5, interference effects are not evident. The interference effects on both mean and fluctuating aerodynamic coefficients of parallel box girders are also quantified and summarized. • A wide range of gap-width ratios(0–15) for parallel box girders is selected to investigate the aerodynamic interference using three-dimensional large eddy simulation. • The three regions are bounded by critical gap-width ratios of G/B = 0.25 and G/B = 5. There are large changes in behavior at G/B = 0.25, whereas for G/B > 5, interference effects are not evident.. • The aerodynamic interference factors for root mean square of fluctuating force coefficients are proposed to express the impact of aerodynamic interference effect. • The spanwise correlations of force coefficients suddenly increase at G/B = 0.25. [ABSTRACT FROM AUTHOR]