Temporal Constraints Research Articles

Neuroadaptive tracking control of uncertain nonlinear systems with spatiotemporal constraints

This study investigates the neuroadaptive tracking control problem for a class of strict-feedback nonlinear systems with spatiotemporal constraints. An adaptive neural network-based control system is developed to alleviate the effects of modeling uncertainties and external disturbances. In particular, the proposed method ensures that the system tracking error has a predefined performance boundary (spatial constraint). Moreover, using a novel time-scale transformation method, uncertain nonlinear systems can achieve a prescribed finite-time convergence to a time-varying scaling function in the pointing position (temporal constraint). Finally, the efficiency of the proposed method is verified with two simulation examples.

The social relevance and the temporal constraints of motor resonance in humans

In humans, motor resonance effects can be tracked by measuring the enhancement of corticospinal excitability by action observation. Uncovering factors driving motor resonance is crucial for optimizing action observation paradigms in experimental and clinical settings. In the present study, we deepen motor resonance properties for grasping movements. Thirty-five healthy subjects underwent an action observation task presenting right-hand grasping movements differing from their action goal. Single-pulse transcranial magnetic stimulation was applied over the left primary motor cortex at 100, 200, or 300 ms from the onset of the visual stimulus depicting the action. Motor-evoked potentials were recorded from four muscles of the right hand and forearm. Results show a muscle-specific motor resonance effect at 200 ms after movement but selectively for observing a socially relevant grasp towards another human being. This effect correlates with observers’ emotional empathy scores, and it was followed by inhibition of motor resonance at 300 ms post-stimulus onset. No motor resonance facilitation emerged while observing intransitive hand movement or object grasping. This evidence highlights the social side of motor resonance and its dependency on temporal factors.

Fast Parallel Algorithms for Enumeration of Simple, Temporal, and Hop-constrained Cycles

Cycles are one of the fundamental subgraph patterns and being able to enumerate them in graphs enables important applications in a wide variety of fields, including finance, biology, chemistry, and network science. However, to enable cycle enumeration in real-world applications, efficient parallel algorithms are required. In this work, we propose scalable parallelisation of state-of-the-art sequential algorithms for enumerating simple, temporal, and hop-constrained cycles. First, we focus on the simple cycle enumeration problem and parallelise the algorithms by Johnson and by Read and Tarjan in a fine-grained manner. We theoretically show that our resulting fine-grained parallel algorithms are scalable, with the fine-grained parallel Read-Tarjan algorithm being strongly scalable. In contrast, we show that straightforward coarse-grained parallel versions of these simple cycle enumeration algorithms that exploit edge- or vertex-level parallelism are not scalable. Next, we adapt our fine-grained approach to enable the enumeration of cycles under time-window, temporal, and hop constraints. Our evaluation on a cluster with 256 CPU cores that can execute up to 1,024 simultaneous threads demonstrates a near-linear scalability of our fine-grained parallel algorithms when enumerating cycles under the aforementioned constraints. On the same cluster, our fine-grained parallel algorithms achieve, on average, one order of magnitude speedup compared to the respective coarse-grained parallel versions of the state-of-the-art algorithms for cycle enumeration. The performance gap between the fine-grained and the coarse-grained parallel algorithms increases as we use more CPU cores.

Spatial–temporal enactments of home-schooling among low-income families of primary-aged children

ABSTRACT This paper focuses on spatial–temporal enactments of home-schooling among low-income families of primary-aged children in England. COVID-19 re-set boundaries and spaces of formal education for children across the globe, bringing it directly into homes and shifting the involvement of parents/carers in their children’s education. In England, “home-school” engagement was brought into sharp focus as “home” became a more visible quasi-public space through which multiple government COVID-19 policies were enacted. Despite emerging literature on home-schooling during the pandemic, voices of parents and children from low-income families have been little heard. Here we take a critical family approach and draw on interviews with low-income families to understand how education was negotiated, enacted and reconfigured within the home during the pandemic. Drawing on literatures relating to policy enactment, carescapes and home-school engagement, we offer unique insight into spatial and temporal constraints of the everyday and the necessary reconstitution of wholescale policy enactment among low-income families.

Broadly applicable methods for the detection of artefacts in electroencephalography acquired simultaneously with hemodynamic recordings

Electroencephalography (EEG) data, acquired simultaneously with magnetic resonance imaging (MRI), must be corrected for artefacts related to MR gradient switches (GS) and the cardioballistic (CB) effect. Canonical approaches require additional signal acquisition for artefact detection (e.g., MR volume onsets, ECG), without which the EEG data would be rendered uncleanable from these artefacts.•We present two broadly applicable methods for artefact detection based on peak detection combined with temporal constraints with respect to periodicity directly from the EEG data itself; no additional signals are required.We validated the performance of our methods versus the two canonical approaches for detection of GS/CB artefact, respectively, on 26 healthy human EEG-functional MRI resting-state datasets. Utilising various performance metrics, we found our methods to perform as well as – and sometimes better than - the canonical standard approaches. With as little as one EEG channel recording, our methods can be applied to detect GS/CB artefacts in EEG data acquired simultaneously with MRI in the absence of MR volume onsets and/or an ECG recording. The detected artefact onsets can then be fed into the standard artefact correction software.

Analysis the Nature of Logic: The Distinctions Between Logic and Mathematics

The paper aims to explore the distinctions between logic and mathematics. Logic and mathematics have always been important branches of human knowledge, closely related in many ways and with far-reaching consequences in areas such as science, technology and philosophy. Although logic and mathematics have much in common in terms of necessity, universality, a priori and a high degree of abstraction, leading to the belief that the two fields of study are identical, they are essentially two very different disciplines. While they do appear very similar owing to their universal necessity and independence from temporal and spatial constraints, logic and mathematics are, in essence, two very distinct disciplines. They can be strictly differentiated based on their focus and epistemological perspectives. This paper will first explain the fundamental concepts of mathematics and logic, then delve into the two main differences between logic and mathematics, and finally, point out the limitations in the study of mathematics and logic.

Tracking phishing on Ethereum: Transaction network embedding approach for accounts representation learning

The transaction volume of Ethereum has been witnessing a year-on-year increase, which has unfortunately been accompanied by significant losses due to phishing scams. To enhance the ability of downstream classifiers to distinguish phishing accounts more effectively, we produce dense representations of Ethereum accounts in latent space, leveraging the transaction network topology and associated statistical features. However, the task of learning representations from sparse yet voluminous transaction records presents a significant challenge. To address this, we introduce the Temporal-based Sequences Generator (TSG) and the Heterogeneous-based Sequences Generator (HSG). These generators create sequences from the transaction network, optimizing the use of transaction temporal constraints, diverse account types, and transaction amounts. Our method aims to capture latent higher-order information and generate dense vectors using a network embedding technique. Furthermore, we propose a novel Statistics-Based Sampling (SBS) method to mitigate label leakage. We validate our approach through experiments with various classic downstream classifiers, demonstrating that Phish2vec surpasses other comparative methods in performance and exhibits robustness and stability.

Exploring the role of miRNAs in early chicken embryonic development and their significance

In the early stages of embryonic development, a precise and strictly controlled hierarchy of gene expression is essential to ensure proper development of all cell types and organs. To better understand this gene control process, we constructed a small RNA library from 1- to 5-day-old chick embryos, and identified 2,459 miRNAs including 827 existing, 695 known, and 937 novel miRNAs with bioinformatic analysis. There was absolute high expression of a number of miRNAs in each stage, including gga-miR-363-3p (Em1d), gga-miR-26a-5p (Em2d and Em3d), gga-miR-10a-5p (Em4d), and gga-miR-199-5p (Em5d). We evaluated enriched miRNA profiles, identifying VEGF, Insulin, ErbB, MAPK, Hedgehog, TLR and Hippo signaling pathways as primary regulatory mechanisms enabling complex morphogenetic transformations within tight temporal constraints. Pathway analysis revealed miRNAs as pivotal nodes of interaction, coordinating cascades of gene expression critical for cell fate determination, proliferation, migration, and differentiation across germ layers and developing organ systems. Weighted Gene Co-Expression Network Analysis (WGCNA) generated hub miRNAs whose modular connections spanned regulatory networks, including: gga-miR-181a-3p (blue module), coordinating immunegenesis and myogenesis; gga-miR-126-3p (brown module), regulating vasculogenesis and angiogenesis; gga-miR-302c-5p (turquoise module), enabling pluripotency and self-renew; and gga-miR-429-3p (yellow module), modulating neurogenesis and osteogenesis. The findings of this study extend the knowledge of miRNA expression in early embryonic development of chickens, providing insights into the intricate gene control process that helps ensure proper development.

A real-time discovery method for vehicle companion via service collaboration

PurposeVehicle companion is one of the most common companion patterns in daily life, which has great value to accident investigation, group tracking, carpooling recommendation and road planning. Due to the complexity and large scale of vehicle sensor streaming data, existing work were difficult to ensure the efficiency and effectiveness of real-time vehicle companion discovery (VCD). This paper aims to provide a high-quality and low-cost method to discover vehicle companions in real time.Design/methodology/approachThis paper provides a real-time VCD method based on pro-active data service collaboration. This study makes use of dynamic service collaboration to selectively process data produced by relative sensors, and relax the temporal and spatial constraints of vehicle companion pattern for discovering more potential companion vehicles.FindingsExperiments based on real and simulated data show that the method can discover 67% more companion vehicles, with 62% less response time comparing with centralized method.Originality/valueTo reduce the amount of processing streaming data, this study provides a Service Collaboration-based Vehicle Companion Discovery method based on proactive data service model. And this study provides a new definition of vehicle companion through relaxing the temporal and spatial constraints for discover companion vehicles as many as possible.

Robust implementation of foreground extraction and vessel segmentation for X-ray coronary angiography image sequence

The extraction of contrast-filled vessels from X-ray coronary angiography (XCA) image sequence has important clinical significance for intuitively diagnosis and therapy. In this study, the XCA image sequence is regarded as a 3D tensor input, the vessel layer is regarded as a sparse tensor, and the background layer is regarded as a low-rank tensor. Using tensor nuclear norm (TNN) minimization, a novel method for vessel layer extraction based on tensor robust principal component analysis (TRPCA) is proposed. Furthermore, considering the irregular movement of vessels and the low-frequency dynamic disturbance of surrounding irrelevant tissues, the total variation (TV) regularized spatial–temporal constraint is introduced to smooth the foreground layer. Subsequently, for vessel layer images with uneven contrast distribution, a two-stage region growing (TSRG) method is utilized for vessel enhancement and segmentation. A global threshold method is used as the preprocessing to obtain main branches, and the Radon-Like features (RLF) filter is used to enhance and connect broken minor segments. The final binary vessel mask is constructed by combining the two intermediate results. The visibility of TV-TRPCA algorithm for foreground extraction is evaluated on clinical XCA image sequences and third-party dataset, which can effectively improve the performance of commonly used vessel segmentation algorithms. Based on TV-TRPCA, the accuracy of TSRG algorithm for vessel segmentation is further evaluated. Both qualitative and quantitative results validate the superiority of the proposed method over existing state-of-the-art approaches.

The Role of E-Commerce in Increasing Sales Using Unified Modeling Language

The advent of contemporary technology advancements and the proliferation of the internet have presented firms and retail establishments with significant prospects for augmenting their sales outreach via electronic commerce. E-commerce enables stores to engage in the sale of their products across Indonesia and international markets without being constrained by limitations of physical location or temporal constraints. E-commerce has the potential to offer consumers a more convenient, expedited, and efficient shopping experience. Consumers can conveniently look for and make choices on the things they intend to purchase, expediting and enhancing the efficiency of the transactional process. Furthermore, e-commerce can offer consumer satisfaction through many means, such as efficient delivery services, flexible return and refund policies, product exchanges, and responsive and amiable customer support. In contrast, e-commerce can enhance cost-effectiveness and improve operational efficiency within the sales process. E-commerce enables businesses to mitigate operating expenses, including expenditures related to physical store rentals, marketing initiatives, and inventory management. Furthermore, implementing e-commerce can facilitate inventory management and sales tracking for retail establishments. Hence, the significance of e-commerce in promoting the augmentation of store sales is noteworthy. Despite the significant profitability of e-commerce, retailers encounter other obstacles, including intensifying rivalry and the looming risk of cybercrime. Hence, retailers must develop a robust e-commerce strategy to compete effectively in the market and ensure secure and dependable services to their customers. This study uses the Unified Modeling Language, a precious tool for the design and modeling of software to be developed.

Analyzing sustainable competitiveness of inter-city coach from the impact of high-speed railway opening in Jiangsu Province, China

High-speed railway (HSR) decreases the geographic and temporal constraints between cities, which may exert influence on inter-city transportation market. The impact of HSR on airlines has been well studied, while studies relevant to its positioning and relationship with inter-city coach (ICC) are limited. Based upon a four-year longitudinal panel dataset of ICC in Jiangsu Province, China, we utilize a difference-in-differences (DID) method to explore the effects of HSR opening on measuring the sustainable competitiveness of ICC. The results show that the HSR opening dramatically reduces ICC volumes. By further exploring the effect of service differences, we construct continuous DID models and find that ICC passengers are more concerned about travel time than price. Furthermore, the influence of HSR on ICC routes is not statistically significant for distances within 100 km, but becomes significant for distances exceeding 100 km, with the most pronounced impact observed on routes surpassing 150 km in length. In addition, we find that the ICC volumes of feeder routes overlapping with HSR service have decreased, while those without HSR service have tended to increase. The findings of this study could provide beneficial insights into the sustainability and coordinated development of inter-city transportation services.

Towards a unified analysis of past and future tenses

While the literature has often highlighted the differences between the defining features of past and future tenses, little attention has been paid to the similarities that bring these linguistic forms together. Taking European Portuguese data as a point of departure, it was my goal in this paper to investigate some of the correspondences that arise between these structures. So, I will endorse the idea that, in both the past and the future domains, there are equivalent strategies to perform temporal location. Thus, tenses, such as the Pretérito Imperfeito do Indicativo (Imp) in the past or the Futuro Simples (FS) in the future, which do not display relevant temporal constraints beyond the mere location of an eventuality in an interval before or after t0, interact with and are more easily influenced by other semantic categories, namely aspect and modality. On the contrary, tenses that require more evident temporal restrictions, in particular the imposition of final or initial boundaries to the situations with which they are combined, such as the Pretérito Perfeito Simples (PPerf) or the construction ir (‘go’) + Infinitive, have in common that they are less permeable to the influence of other external factors, with temporal location being their most prominent meaning.

An algorithm of dynamic temporal constraints for the mission series in deep space detectors

Deep space exploration activities can effectively promote the development and application of space technology, which holds significant scientific and strategic value. The multi-mission and long-period detector is executed in deep space, and numerous temporal constraints are generated by mission planning. Moreover, scheduled missions may face external uncertainties, hindering their smooth execution. Therefore, temporal constraint processing strategies that possess dynamic adjustment capabilities play a crucial role in ensuring the successful execution of deep space detectors. Existing methods primarily concentrate on investigating fixed mission series, with limited efficiency in planning. Specifically, these methods do not rigorously enforce temporal constraints and lack the capability to handle the disruptions caused by emergencies, which hinder the smooth execution of planned missions. In this paper, we propose a dynamic temporal constraints algorithm, aiming to efficiently plan missions subject to temporal constraints and let it possess a certain degree of dynamic adjust capability. The simulation results demonstrate the effective simplification of redundant temporal constraints in mission networks by the proposed algorithm. In comparison to the classical algorithm, the computation time exhibits a clear advantage. Furthermore, the proposed algorithm possesses the capability to perform local, small-scale dynamic adjustments in response to emergencies that may disrupt the normal execution of missions. Consequently, this research establishes a robust basis for addressing temporal constraints in deep space detectors.

Governing Equation Identification of Nonlinear Single Degree-of-Freedom Oscillators With Coulomb Friction Using Explicit Stick and Slip Temporal Constraints

Abstract The friction force at joints of engineering structures is usually unknown and not directly identifiable. This contribution explores a procedure for obtaining the governing equation of motion and correctly identifying the unknown Coulomb friction force of a mass-spring-dashpot system. In particular, a single degree-of-freedom system is investigated both numerically and experimentally. The proposed procedure extends the state-of-the-art data-driven sparse identification of nonlinear dynamics (SINDy) algorithm by developing a methodology that explicitly imposes constraints encoding knowledge of the nonsmooth dynamics experienced during stick-slip phenomena. The proposed algorithm consists of three steps: (i) data segregation of mass-motion from mass-sticking during stick-slip response; (ii) application of SINDy on the mass-motion dataset to obtain the functional form of the governing equation; and (iii) applying sticking and slipping conditions to identify the unknown system parameters. It is shown that the proposed approach yields an improved estimate of the uncertain system parameters such as stiffness, viscous damping, and magnitude of friction force (all mass normalized) for various signal-to-noise ratios compared to SINDy.

Coastal landscape preference of residents and tourists according to the physical attributes and viewpoints of offshore wind farms as seen through virtual reality

The construction of offshore wind farms typically encounters two challenges: 1) conflicting opinions of relevant stakeholders and 2) localized attributes reflected in the landscape evaluation system. To solve these problems, this study conducts a virtual landscape preference survey for both residents and potential tourists. The 10 virtual offshore wind farms’ landscape profiles were established according to four attributes: the number of turbines, arrangement of turbines, distance, and altitude. As a result, residents and potential tourists were reported to hold opposing perspectives about changing the number of turbines, the arrangement of the turbines, and the distance, though they gave the same response about changing the altitude. However, the exposure time to offshore wind farms and the number of visits to coastal areas did not affect the landscape preference of offshore wind farms. The results indicated the importance of considering both residents and potential tourists. In addition, the definite change of preference for altitude explained the necessity of new attributes that reflect the situation of coastal areas. Last, using virtual reality with 3D simulations could improve the evaluation system of offshore wind farms by reducing the temporal and spatial constraints. Thus, the results of this study could be utilized to develop offshore wind farm evaluation systems, which could reflect the opinions of residents and tourists by considering localized factors.

Smartphone spectatorship in unenclosed environments: The physiological impacts of visual and sonic distraction during movie watching on mobile devices

Smartphones’ popularity is largely based on their pervasiveness, portability, and the wide range of functions they encompass: they can play high-definition moving-image content without spatial and temporal constraints. However, the lack of spatial and temporal frameworks can account for distractions. Distractions (generally sonic or visual information) can originate from the surrounding environment or from the device itself and they may or may not hold semantic links to the content being watched. In this paper, we argue that the distraction effect in movie watching is based on a distractor’s modality, neutrality, and ecological relevance to the movie. To test the effects of these properties, we recorded viewers’ gaze and electrodermal activity while they watched a narrative film sequence on smartphone and projector screens in the presence of sonic and visual distractors. We found that screen type can affect attention and arousal: in comparison to projector viewers, smartphone viewers experienced lower arousal and were more likely to shift their attention from the movie even when a distractor closely related to the movie was played. It was also observed that distractors that require urgent attention and are unrelated to the movie redirect the viewer’s attention and increases electrodermal activity values. In contrast, distractors with ecological relevance to the movie are less likely to induce changes in attention and arousal.

Data-Aware Declarative Process Mining with SAT

Process Mining is a family of techniques for analyzing business process execution data recorded in event logs. Process models can be obtained as output of automated process discovery techniques or can be used as input of techniques for conformance checking or model enhancement. In Declarative Process Mining, process models are represented as sets of temporal constraints (instead of procedural descriptions where all control-flow details are explicitly modeled). An open research direction in Declarative Process Mining is whether multi-perspective specifications can be supported, i.e., specifications that not only describe the process behavior from the control-flow point of view, but also from other perspectives like data or time. In this article, we address this question by considering SAT (Propositional Satisfiability Problem) as a solving technology for a number of classical problems in Declarative Process Mining, namely, log generation, conformance checking, and temporal query checking. To do so, we first express each problem as a suitable FO (First-Order) theory whose bounded models represent solutions to the problem, and then find a bounded model of such theory by compilation into SAT.

Integrated flexibility characterization and measurement of distributed multi-energy systems considering temporal coupling constraints

The integrated flexibility of distributed multi-energy systems (DMES) has been recognized as a valuable balancing resource to the centralized energy system, which can be characterized by an integrated flexible region (IFR) of multiple energy inputs. Notably, the IFR is only captured for one single period in previous studies, whereas the time coupling in consecutive periods has a significant impact on the integrated flexibility. This paper proposes a modified IFR-based approach to characterize and measure the integrated flexibility of DMES considering the temporal coupling constraints. First, operation constraints of the DMES are formulated, followed by a vertex search method to obtain the IFR, i. e, a polytope that visualizes those operation constraints. Then, an approximation approach is proposed to decompose the original IFR into a series of lower-dimension IFRs, each of which corresponds to a specific period. The influence of states of adjacent periods is directly reflected by the position change of the vertices. The decoupled IFRs can be incorporated conveniently into the multi-period economic dispatch of the centralized energy system. Moreover, the Volume of the IFRs (VFR) is introduced as an index to quantify the flexibility of the DMES. The performance of the proposed methods is verified by the case studies.

Can you See? Actuality Entailments in the Present

Abstract This paper argues that English present ability modal statements like “I can see Saturn” are ambiguous in the same way as past ability statements like “I was able to lift a fridge”: they can express either a general ability (‘I have the ability to see Saturn, in general’), or have an actualized (episodic) interpretation (‘I'm seeing Saturn, right now’). The challenge is to explain why in the present, actualized interpretations are only licensed when the modal's prejacent is a perception verb like see, and not with other predicates: “I can watch Saturn” only has the general ability reading available, and not the actualized one. I propose that (i) similar to what has been shown for past modal statements in the literature on Actuality Entailments (AEs) (Bhatt 1999), the ambiguity depends on grammatical aspect: general ability readings are due to the imperfective, which “removes” AEs by having the event occur in worlds introduced by a generic operator (Bhatt 1999), and actualized readings are due to the perfective, which directly combines with the prejacent event across the modal (Hacquard 2009); (ii) The usual unavailability of actualized interpretations in the present comes from the Present Perfective Paradox (Malchukov 2009): perfective aspect is incompatible with present tense, because the event time, a time interval, cannot be contained within the punctual speech time. (iii) Perception verbs are special in that they, and only they, are able to combine with perfective in the present, either because the PPP does not arise at all, or because they allow a specific type of aspectual coercion. This also explains their behavior in (non-modal) simple present sentences. A second challenge is that actualized interpretations in the present appear to occur exclusively with ability modals, and not when modals express other root flavors (e.g. teleological or deontic). I propose that this restriction is due to a further temporal orientation constraint.