Grounding spatial prepositions for video search

Spatial language video retrieval is an important real-world problem that forms a test bed for evaluating semantic structures for natural language descriptions of motion on naturalistic data. Video search by natural language query requires that linguistic input be converted into structures that operate on video in order to find clips that match a query. This paper describes a framework for grounding the meaning of spatial prepositions in video. We present a library of features that can be used to automatically classify a video clip based on whether it matches a natural language query. To evaluate these features, we collected a corpus of natural language descriptions about the motion of people in video clips. We characterize the language used in the corpus, and use it to train and test models for the meanings of the spatial prepositions "to," "across," "through," "out," "along," "towards," and "around." The classifiers can be used to build a spatial language video retrieval system that finds clips matching queries such as "across the kitchen."United States. Office of Naval Research (MURI N00014-07-1-0749

Late-Stage Diversification of Tryptophan-Derived Biomolecules.

Gruß H, Sewald N. Late-Stage Diversification of Tryptophan-Derived Biomolecules. Chemistry - A European Journal. 2020;26(24):5328-5340.Pd-mediated reactions have emerged as a powerful tool for the site-selective and bioorthogonal late-stage diversification of amino acids, peptides and related compounds. Indole moieties of tryptophan derivatives are susceptible to C2 H-activation, whereas halogenated aromatic amino acids such as halophenylalanines or halotryptophans provide a broad spectrum of different functionalisations. The compatibility of transition-metal-catalysed cross-couplings with functional groups in peptides, other biologically active compounds and even proteins has been demonstrated. This Review primarily compiles the application of different cross-coupling reactions to modify halotryptophans, halotryptophan containing peptides or halogenated, biologically active compounds derived from tryptophan. Modern approaches use regio- and stereoselective biocatalytic strategies to generate halotryptophans and derivatives on a preparative scale. The combination of bio- and chemocatalysis in cascade reactions is given by the biocompatibility and bioorthogonality of Pd-mediated reactions. © 2019 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA

Toward understanding natural language directions

Speaking using unconstrained natural language is an intuitive and flexible way for humans to interact with robots. Understanding this kind of linguistic input is challenging because diverse words and phrases must be mapped into structures that the robot can understand, and elements in those structures must be grounded in an uncertain environment. We present a system that follows natural language directions by extracting a sequence of spatial description clauses from the linguistic input and then infers the most probable path through the environment given only information about the environmental geometry and detected visible objects. We use a probabilistic graphical model that factors into three key components. The first component grounds landmark phrases such as "the computers" in the perceptual frame of the robot by exploiting co-occurrence statistics from a database of tagged images such as Flickr. Second, a spatial reasoning component judges how well spatial relations such as "past the computers" describe a path. Finally, verb phrases such as "turn right" are modeled according to the amount of change in orientation in the path. Our system follows 60% of the directions in our corpus to within 15 meters of the true destination, significantly outperforming other approaches.United States. Office of Naval Research (MURI N00014-07-1-0749

Grounding Verbs of Motion in Natural Language Commands to Robots

To be useful teammates to human partners, robots must be able to follow spoken instructions given in natural language. An important class of instructions involve interacting with people, such as “Follow the person to the kitchen” or “Meet the person at the elevators.” These instructions require that the robot fluidly react to changes in the environment, not simply follow a pre-computed plan. We present an algorithm for understanding natural language commands with three components. First, we create a cost function that scores the language according to how well it matches a candidate plan in the environment, defined as the log-likelihood of the plan given the command. Components of the cost function include novel models for the meanings of motion verbs such as “follow,” “meet,” and “avoid,” as well as spatial relations such as “to” and landmark phrases such as “the kitchen.” Second, an inference method uses this cost function to perform forward search, finding a plan that matches the natural language command. Third, a high-level controller repeatedly calls the inference method at each timestep to compute a new plan in response to changes in the environment such as the movement of the human partner or other people in the scene. When a command consists of more than a single task, the controller switches to the next task when an earlier one is satisfied. We evaluate our approach on a set of example tasks that require the ability to follow both simple and complex natural language commands. Keywords: Cost Function; Spatial Relation; State Sequence; Edit Distance; Statistical Machine TranslationUnited States. Office of Naval Research (Grant MURI N00014-07-1-0749

Correlating contexts and NFR conflicts from event logs

In the design of autonomous systems, it is important to consider the preferences of the interested parties to improve the user experience. These preferences are often associated with the contexts in which each system is likely to operate. The operational behavior of a system must also meet various non-functional requirements (NFRs), which can present different levels of conflict depending on the operational context. This work aims to model correlations between the individual contexts and the consequent conflicts between NFRs. The proposed approach is based on analyzing the system event logs, tracing them back to the leaf elements at the specification level and providing a contextual explanation of the system’s behavior. The traced contexts and NFR conflicts are then mined to produce Context-Context and Context-NFR conflict sequential rules. The proposed Contextual Explainability (ConE) framework uses BERT-based pre-trained language models and sequential rule mining libraries for deriving the above correlations. Extensive evaluations are performed to compare the existing state-of-the-art approaches. The best-fit solutions are chosen to integrate within the ConE framework. Based on experiments, an accuracy of 80%, a precision of 90%, a recall of 97%, and an F1-score of 88% are recorded for the ConE framework on the sequential rules that were mined

Spreading in Social Systems: Reflections

In this final chapter, we consider the state-of-the-art for spreading in social systems and discuss the future of the field. As part of this reflection, we identify a set of key challenges ahead. The challenges include the following questions: how can we improve the quality, quantity, extent, and accessibility of datasets? How can we extract more information from limited datasets? How can we take individual cognition and decision making processes into account? How can we incorporate other complexity of the real contagion processes? Finally, how can we translate research into positive real-world impact? In the following, we provide more context for each of these open questions.Comment: 7 pages, chapter to appear in "Spreading Dynamics in Social Systems"; Eds. Sune Lehmann and Yong-Yeol Ahn, Springer Natur

Formation of antihydrogen in antiproton - positron collision

A quantum mechanical approach is proposed for the formation of antihydrogen in the ground and excited states (2s, 2p) via the mechanism of three body recombination (TBR) inside a trapped plasma of anti proton and positron or in the collision between the two beams of them. Variations of the differential (DCS) as well as the total (TCS) formation cross sections are studied as a function of the incident energies of both the active and the spectator positrons. Significantly large cross sections are found at very low incident energies in the TBR process as compared to other processes leading to antihydrogen. The present formation cross section decreases with increasing positron energy (temperature) but no simple power law could be predicted for it covering the entire energy range, corroborating the experimental findings qualitatively. The formation cross sections are found to be much higher for unequal energies of the two positrons than for equal energies, as expected physically.Comment: 14 pages, 13 figure

Raman scattering study of LiKSO<SUB>4</SUB>-phases II and III

Detailed Raman scattering investigation of LiKSO4 in phases II and III across the transition temperature Tc &#x22CD; 700 K is reported. Abrupt change in frequency and line width of the external and internal modes have been observed. Analysis of the results suggests lithium positional disorder and sulphate orientational disorder in the high temperature phase (II). The results also throw some light on the existence of twin domains in the crystal