Dynamic Domains Research Articles

Learning Qualitative Models by Demonstration

Creating software agents that learn interactively requires the ability to learn from a small number of trials, extracting general, flexible knowledge that can drive behavior from observation and interaction. We claim that qualitative models provide a useful intermediate level of causal representation for dynamic domains, including the formulation of strategies and tactics. We argue that qualitative models are quickly learnable, and enable model-based reasoning techniques to be used to recognize, operationalize, and construct more strategic knowledge. This paper describes an approach to incrementally learning qualitative influences by demonstration in the context of a strategy game. We show how the learned model can help a system play by enabling it to explain which actions could contribute to maximizing a quantitative goal. We also show how reasoning about the model allows it to reformulate a learning problem to address delayed effects and credit assignment, such that it can improve its performance on more strategic tasks such as city placement.

Correlation between dynamic magnetization process and dynamic domains of high saturation induction FeSiBNbCuMo nanocrystalline alloy with dual anisotropies

Improving the high-frequency properties of the relatively high saturation induction alloys is significance for widening the frequency range of the noise suppression of common mode chokes. Herein, transverse magnetic field annealing after having been nano-crystallized (TA) was performed to the as-quenched Fe76Si13B8Nb1.5Cu1Mo0.5 alloy, and the dynamic properties, microstructure, and dynamic domains were in detail studied comparing with those annealed without magnetic field (NA). It was found that TA at 400 °C caused an increase in permeability at 50 kHz by 41% and a decrease in core loss at 0.2 T and 50 kHz by 30%, in comparison with those of NA. TA at 400 °C induced the ratio of field induced anisotropy constant Ku to average random anisotropy constant<K1> to be ~ 1.3 and inhomogeneous rotation, leading to the promoted domain refinement with increasing frequency and improved high-frequency properties, compared with that of NA bears only<K1> ~5.4 J/m3. Moreover, the role of dual anisotropies on the magnetic domain structures, dynamic magnetization process and magnetic performances were obtained and its correlation model based on the experimental results was established. These results could provide a good guide for performance optimization to meet higher frequency requirements of common mode chokes application.

Automated Planning with Induced Qualitative Models in Dynamic Robotic Domains

Various methods of learning qualitative models by autonomous robots have previously been proposed as a viable alternative to traditional numerical modeling, but an efficient way of using such models for planning still remained an open problem. This paper summarizes a doctorat thesis, which proposes a novel domain-independent qualitative approach to automated planning and execution of robotic plans. The proposed method is demonstrated in five different robotic domains. Različne metode učenja kvalitativnih modelov v avtonomni robotiki so bile v preteklosti predlagane kot možna alternativa tradicionalnemu numeričnemu modeliranju, toda učinkovit način uporabe takšnih modelov za planiranje je še vedno ostal odprt problem. Ta članek povzema doktorska disertacijo, ki predlaga nov, domensko neodvisen kvalitativen pristop k avtomatiziranemu planiranju in izvedbi robotskih planov. Disertacija predlagano metodo demonstrira v petih različnih robotskih domenah.

Long-Range Control of Class Switch Recombination by Transcriptional Regulatory Elements.

Immunoglobulin class switch recombination (CSR) plays a crucial role in adaptive immune responses through a change of the effector functions of antibodies and is triggered by T-cell-dependent as well as T-cell-independent antigens. Signals generated following encounter with each type of antigen direct CSR to different isotypes. At the genomic level, CSR occurs between highly repetitive switch sequences located upstream of the constant gene exons of the immunoglobulin heavy chain locus. Transcription of switch sequences is mandatory for CSR and is induced in a stimulation-dependent manner. Switch transcription takes place within dynamic chromatin domains and is regulated by long-range regulatory elements which promote alignment of partner switch regions in CSR centers. Here, we review recent work and models that account for the function of long-range transcriptional regulatory elements and the chromatin-based mechanisms involved in the control of CSR.

Correlative nanophotonic approaches to enlighten the nanoscale dynamics of living cell membranes.

Dynamic compartmentalization is a prevailing principle regulating the spatiotemporal organization of the living cell membrane from the nano- up to the mesoscale. This non-arbitrary organization is intricately linked to cell function. On living cell membranes, dynamic domains or ‘membrane rafts' enriched with cholesterol, sphingolipids and other certain proteins exist at the nanoscale serving as signaling and sorting platforms. Moreover, it has been postulated that other local organizers of the cell membrane such as intrinsic protein interactions, the extracellular matrix and/or the actin cytoskeleton synergize with rafts to provide spatiotemporal hierarchy to the membrane. Elucidating the intricate coupling of multiple spatial and temporal scales requires the application of correlative techniques, with a particular need for simultaneous nanometer spatial precision and microsecond temporal resolution. Here, we review novel fluorescence-based techniques that readily allow to decode nanoscale membrane dynamics with unprecedented spatiotemporal resolution and single-molecule sensitivity. We particularly focus on correlative approaches from the field of nanophotonics. Notably, we introduce a versatile planar nanoantenna platform combined with fluorescence correlation spectroscopy to study spatiotemporal heterogeneities on living cell membranes at the nano- up to the mesoscale. Finally, we outline remaining future technological challenges and comment on potential directions to advance our understanding of cell membrane dynamics under the influence of the actin cytoskeleton and extracellular matrix in uttermost detail.

Error recovery training literature review: Implications for emergency field medicine

Training focused on recognizing when a medical procedure has not been implemented effectively may reduce preventable battlefield deaths. Although important research has been conducted about a range of error recovery training strategies, few studies have been conducted in the context of training for high stakes, dynamic domains such as combat medic training. We conducted a literature review to examine how error recovery training has been designed in other contexts, with the intent of abstracting recommendations for designing error recovery training to support military personnel providing emergency field medicine. Implications for combat medic training include: 1) a focus on error management rather than error avoidance, 2) a didactic training component may support training engagement and mental model development, 3) an experiential component may be designed to support perceptual skill development and anomaly detection, and 4) feedback should focus on allowing learners to make errors and encouraging them to learn from errors.

Forgiveness as a technology of the state

Forgiveness as a technology of the state

Experimental Real-Time Heuristic Search Results in a Video Game

In real-time domains such as video games, a planning algo- rithm has a strictly bounded time before it must return the next action for the agent to execute. We introduce a realistic video game benchmark domain that is useful for evaluating real-time heuristic search algorithms. Unlike previous bench- marks such as grid pathfinding and the sliding tile puzzle, this new domain includes dynamics and induces a directed graph. Using both the previous and new domains, we investigate sev- eral enhancements to a leading real-time search algorithm, LSS-LRTA*. We show experimentally that 1) it is not dif- ficult to outperform A* when optimizing goal achievement time, 2) it is better to plan after each action than to commit to multiple actions or to use a dynamically sized lookahead, 3) A*-based lookahead can cause undesirable actions to be selected, and 4) on-line de-biasing of the heuristic can lead to improved performance. We hope that this new domain and results will stimulate further research on applying real-time search to dynamic real-time domains.

Theoretical investigation and experiment of a disc-shaped triboelectric energy harvester with a magnetic bistable mechanism

Triboelectric energy harvesting has emerged as a promising route to scavenge ambient mechanical energy for cost-effective, clean and sustainable electricity. Disc-shaped triboelectric energy harvesters are suitable for two kinds of mechanical energy sources: continuous rotation and vibration. A majority of current studies about disc-shaped triboelectric energy harvesters focus on scavenging energy in continuous rotation, but there is a lack of investigations on angular vibration, especially in structural dynamics. In this work, a new disc-shaped triboelectric energy harvester with a bistable mechanism enabled by two repulsive magnets is developed for harvesting vibration energy. There are two discs in the harvester, one stationary and the other undergoing angular oscillation. Both have segmented triboelectric films on their contact surfaces. The magnetic bistable mechanism is utilized for the first time in a disc-shaped triboelectric energy harvester for efficiency enhancement. A comprehensive theoretical model coupling both structural dynamic and electric dynamic domains is established. A comparison between the coupled and uncoupled models reveals that the ET between electrodes can be ignored. Numerical simulations are carried out to investigate the effect of the potential wells due to the two magnets, basins of attractors and the influence of damping from the perspective of structural dynamics. A prototype is fabricated for experimental investigations, which demonstrate that the harvester with the bistable mechanism can achieve a better performance than the corresponding harvester without the bistable mechanism, and the output voltage of the harvester increases with the increase of excitation amplitude. Theoretical and experimental comparisons about the electric outputs between the triboelectric films with different segmentation structures reveal that increasing the number of sectors on the films effectively improves the harvesting efficiency. This work establishes a link between the structural dynamics and electric dynamics for the vibration-based disc-shaped triboelectric energy harvester, providing guidelines for its design and fabrication.

Rationally Constructed Surface Energy and Dynamic Hard Domains Balance Mechanical Strength and Self-Healing Efficiency of Energetic Linear Polymer Materials.

Polymeric materials that simultaneously possess excellent mechanical properties and high self-healing ability at room temperature, convenient healing, and facile fabrication are always a huge challenge. Herein, we report on surface-energy-driven self-healing energetic linear polyurethane elastomers (EPU) that were facilely fabricated by two-step methods to acquire high healing efficiency and mechanical properties. By constructing surface energy and dynamic hard domains, energetic linear polyurethane elastomers not only obtained high healing ability and mechanical properties at high or room temperature but also avoid the use of some assisted healing conditions and complex chemical structure design and decrease manufacturing difficulty. Based on the interfacial healing physical model, various trends of surface tension, radius, and depth of the crack bottom were calculated to analyze the healing mechanism. We propose that polyurethane elastomers with low junction density could generate excess surface energy resulting from damage and drive self-healing, and incorporating a small amount of disulfide bonds increases the slightly packed hard phase and decreases the healing energy barrier. This work may offer a novel strategy for improving mechanical tensile and healing ability in the field of self-healing material application.

Heuristic Algorithm for the Analysis of Fast Field Cycling (FFC) NMR Dispersion Curves.

Evaluation of nuclear magnetic relaxation dispersion (NMRD) curves obtained by the fast field cycling nuclear magnetic resonance (FFC-NMR) relaxometry technique is a valuable tool for analyzing the microscopic dynamics of condensed matter systems. However, quantitative data analysis involves several conceptual and practical issues. Moving forward from previous literature approaches, we propose a new analysis method, relying on the elaboration of the inverse integral transform of the NMRD curve. Our approach results in a true heuristic method, able to unambiguously individuate the dynamic domains in the system, thereby avoiding the possible introduction of any element of discretion. The analysis of some data sets relevant to real samples suggests the possibility that the results obtained with the heuristic method may be actually led back to some distinct physical/chemical features of the systems.

Lifelong Personalization via Gaussian Process Modeling for Long-Term HRI.

Across a wide variety of domains, artificial agents that can adapt and personalize to users have potential to improve and transform how social services are provided. Because of the need for personalized interaction data to drive this process, long-term (or longitudinal) interactions between users and agents, which unfold over a series of distinct interaction sessions, have attracted substantial research interest. In recognition of the expanded scope and structure of a long-term interaction, researchers are also adjusting the personalization models and algorithms used, orienting toward “continual learning” methods, which do not assume a stationary modeling target and explicitly account for the temporal context of training data. In parallel, researchers have also studied the effect of “multitask personalization,” an approach in which an agent interacts with users over multiple different tasks contexts throughout the course of a long-term interaction and learns personalized models of a user that are transferrable across these tasks. In this paper, we unite these two paradigms under the framework of “Lifelong Personalization,” analyzing the effect of multitask personalization applied to dynamic, non-stationary targets. We extend the multi-task personalization approach to the more complex and realistic scenario of modeling dynamic learners over time, focusing in particular on interactive scenarios in which the modeling agent plays an active role in teaching the student whose knowledge the agent is simultaneously attempting to model. Inspired by the way in which agents use active learning to select new training data based on domain context, we augment a Gaussian Process-based multitask personalization model with a mechanism to actively and continually manage its own training data, allowing a modeling agent to remove or reduce the weight of observed data from its training set, based on interactive context cues. We evaluate this method in a series of simulation experiments comparing different approaches to continual and multitask learning on simulated student data. We expect this method to substantially improve learning in Gaussian Process models in dynamic domains, establishing Gaussian Processes as another flexible modeling tool for Long-term Human-Robot Interaction (HRI) Studies.

The Contribution of Static and Dynamic Factors to Recidivism Prediction for Black and White Youth Offenders

Scholars have presented concerns about potential for racial bias in risk assessments as a result of the inclusion of static factors, such as criminal history in risk assessments. The purpose of this study was to examine the extent to which static factors add incremental validity to the dynamic factors in criminogenic risk assessments. This study examined the Youth Level of Service/Case Management Inventory (YLS/CMI) in a sample of 1,270 youth offenders from a medium-sized Midwestern county between June 2004 and November 2013. Logistic regression was used to determine the predictive validity of the YLS/CMI and the individual contribution of static and dynamic domains of the assessment. Results indicated that the static domain differentially predicted recidivism for Black and White youth. In particular, the static domain was a significant predictor of recidivism for White youth, but this was not the case for Black youth. The dynamic domain significantly predicted recidivism for both Black and White offenders, and static risk factors improved prediction of recidivism for White youth, but not for Black youth.

Application of constructivism and cognitive flexibility theory to build a Comprehensive, Integrated, Multimodal Interprofessional Education and Practice (CIM-IPEP) program

ABSTRACT Interprofessional Education (IPE) is challenging to implement and assess due to barriers preventing interprofessional communication, inadequately defined accreditation criteria, ambiguous professional roles and responsibilities, and the inherently “ill-structured” educational construct of IPE. To address these gaps, a novel comprehensive, integrated, and multimodal interprofessional education and practice (CIM-IPEP) curriculum involving students from pharmacy, medicine, psychology, and nursing professional degree programmes was created. CIM-IPEP was carefully designed based on cognitive flexibility theory (CFT) to reinforce the complexities associated with teaching and learning for multi-faceted and dynamic domains such as IPE. CFT emphasises pluralistic representation, repetition, and cognitive layering in experiential learning for ill-structured domains. Thus, CIM-IPEP was vertically and horizontally aligned within individual colleges and included diverse IPE experiences in required courses such as Foundations of IPE, and high-fidelity simulation events, culminating in an IPE-Hotspotting elective, which exposed learners to real-world patient cases. Cases were presented in a format of increasing complexity emphasising the integration of foundational and skills-based learning using constructivist methods such as Team-Based and Case-Based Learning. CIM-IPEP offers a novel IPE model. Here we present a stepwise development and implementation blueprint for similar IPE programmes that is readily transferable to other health profession education (HPE) programmes.

Does What We See Shape History? Examining Workload History as a Function of Performance and Ambient/Focal Visual Attention

Changes in task demands can have delayed adverse impacts on performance. This phenomenon, known as the workload history effect, is especially of concern in dynamic work domains where operators manage fluctuating task demands. The existing workload history literature does not depict a consistent picture regarding how these effects manifest, prompting research to consider measures that are informative on the operator's process. One promising measure is visual attention patterns, due to its informativeness on various cognitive processes. To explore its ability to explain workload history effects, participants completed a task in an unmanned aerial vehicle command and control testbed where workload transitioned gradually and suddenly. The participants’ performance and visual attention patterns were studied over time to identify workload history effects. The eye-tracking analysis consisted of using a recently developed eye-tracking metric called coefficient K , as it indicates whether visual attention is more focal or ambient. The performance results found workload history effects, but it depended on the workload level, time elapsed, and performance measure. The eye-tracking analysis suggested performance suffered when focal attention was deployed during low workload, which was an unexpected finding. When synthesizing these results, they suggest unexpected visual attention patterns can impact performance immediately over time. Further research is needed; however, this work shows the value of including a real-time visual attention measure, such as coefficient K , as a means to understand how the operator manages varying task demands in complex work environments.

Enhancing the Prefusion Conformational Stability of SARS-CoV-2 Spike Protein Through Structure-Guided Design.

The worldwide pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is unprecedented and the impact on public health and the global economy continues to be devastating. Although early therapies such as prophylactic antibodies and vaccines show great promise, there are concerns about the long-term efficacy and universal applicability of these therapies as the virus continues to mutate. Thus, protein-based immunogens that can quickly respond to viral changes remain of continued interest. The Spike protein, the main immunogen of this virus, displays a highly dynamic trimeric structure that presents a challenge for therapeutic development. Here, guided by the structure of the Spike trimer, we rationally design new Spike constructs that show a uniquely high stability profile while simultaneously remaining locked into the immunogen-desirable prefusion state. Furthermore, our approach emphasizes the relationship between the highly conserved S2 region and structurally dynamic Receptor Binding Domains (RBD) to enable vaccine development as well as the generation of antibodies able to resist viral mutation.

Physical Nature of Chromatin in the Nucleus.

Genomic information is encoded on long strands of DNA, which are folded into chromatin and stored in a tiny nucleus. Nuclear chromatin is a negatively charged polymer composed of DNA, histones, and various nonhistone proteins. Because of its highly charged nature, chromatin structure varies greatly depending on the surrounding environment (e.g., cations, molecular crowding, etc.). New technologies to capture chromatin in living cells have been developed over the past 10 years. Our view on chromatin organization has drastically shifted from a regular and static one to a more variable and dynamic one. Chromatin forms numerous compact dynamic domains that act as functional units of the genome in higher eukaryotic cells and locally appear liquid-like. By changing DNA accessibility, these domains can govern various functions. Based on new evidences from versatile genomics and advanced imaging studies, we discuss the physical nature of chromatin in the crowded nuclear environment and how it is regulated.

Market niches as dynamic, co-created resource domains

Competing in niches is a fundamental marketing strategy for SMEs in business-to-business markets yet how internationalizing SMEs come to compete in the niches they do is unclear. Using multiple case studies of competing firms in a single B2B industry sector, this research found that niches evolved in response to resources supplied or withdrawn by early customers, sales channels, shareholders and competitors. We show that market niches are dynamic resource domains where market actors co-create new, specialized value. SMEs may target new niches when they internationalize because they cannot access the resources needed to co-create their domestic niche or because resources are valued differently.

Diagnostic automated algorithms in neurodevelopmental disorders: Focus on automatic motor assessment

Difficulties in motor development are frequent and impairing. However, the assessment of these motor learning skills is difficult and limits early stage rehabilitation. Electronic sensors and algorithms can help to measure motor difficulties more easily and objectively. We will present a systematic review detailing these methods and challenges in Autism Spectrum Disorders (ASD). Electronic tablets, give access to handwriting features that are not usually evaluated in classical assessments. We describe how such digital features (in static, dynamic, pressure, and tilt domains) allow diagnosing dysgraphia and how they evolve during children development. From a finer analysis, three different clusters of dysgraphia emerge, longitudinal studies will allow to underline different patterns of development that seemingly require tailored remediation strategies. However, those digital features are not used in the context of conventional pen and paper therapies. It is possible to engage children with typical development in handwriting exercises by asking them to teach a robot to write. We implemented a long-term case study (20 sessions, 500 minutes in total) observing a child with severe Developmental Co-ordination Disorder who did not progress anymore with a classic pen and paper approach by enriching this setup with various training activities using real-time feedback loops (on tilt, pressure, dynamic, pauses). We show how this new method tackles previous child’s behaviour avoidances, boosting his motivation, and improving his motor and writing skills. This talk demonstrates how new motor digital features allow the implementation of innovative motor remediation interventions, which rely on fostering children’s personal characteristics and adaptation skills.DisclosureThe work presented in this talk was conducted during a PhD in computer science (funded by APHP and Paris 8 University, France). A company was funded by a PhD collaborator, dynamico.ch. The presenter does not have consultancy or financial connection with d

Reappraisal of the Mesozoic tectonic transition from the Paleo-Tethyan to Paleo-Pacific domains in South China

Abstract The southeastern (SE) South China Block was mainly influenced by the Paleo-Tethyan and Paleo-Pacific dynamic domains during the Mesozoic. The initial timing of the tectonic transition between these two domains in the SE South China Block still remains debated. The transition would affect the nature of the lithosphere and material provenance of sediments, and, therefore, igneous and sedimentary rocks in the area could record such dynamic processes. In this study, published geochronological and geochemical data of the Triassic and Jurassic igneous rocks and detrital zircon data of contemporaneous sedimentary rocks in the SE South China Block were compiled, aiming to provide constraints on the tectonic transition via tracing the spatial-temporal variations in the nature of the lithosphere and sedimentary provenance signals. The compiled results suggest that the magmatic intensity and volume decreased significantly from the Late Triassic to Early–Middle Jurassic, with an obvious magmatic quiescence between them, and increased from the Early–Middle Jurassic to Late Jurassic. The εNd(t) and zircon εHf(t) values of mafic rocks, granitoids, and shoshonitic rocks remarkably increased from the Late Triassic to Early–Middle Jurassic, indicative of variations in the lithospheric mantle and continental crust. Such variations suggest that the initial tectonic transition occurred at the earliest Early Jurassic. Based on the southward paleocurrents from Early Jurassic sandstone, E-W–trending extension of Early–Middle Jurassic mafic and shoshonitic rocks, and similar sedimentary provenances of Late Triassic and Early–Middle Jurassic sedimentary rocks, these features imply that the SE South China Block was not immediately influenced by the Paleo-Pacific domain during the Early–Middle Jurassic. However, from the Early–Middle Jurassic to Late Jurassic and Early Cretaceous, the spatial distribution, geochemical signatures, magmatic intensity, and magmatic volume of igneous rocks and provenance of sedimentary rocks exhibit obvious variations, and the regional fold hinge direction changed from E-W–trending to NE-trending, suggesting significant effects from Paleo-Pacific subduction on the SE South China Block. Thus, the Mesozoic tectonic transition from the Paleo-Tethyan to the Paleo-Pacific dynamic domain in the SE South China Block likely occurred during the Early–Middle Jurassic.