Dynamic Extensions Research Articles

Models and Rating Systems for Head-to-Head Competition

One of the most important tasks in sports analytics is the development of binary response models for head-to-head game outcomes to estimate team and player strength. We discuss commonly used probability models for game outcomes, including the Bradley–Terry and Thurstone–Mosteller models, as well as extensions to ties as a third outcome and to the inclusion of a home-field advantage. We consider dynamic extensions to these models to account for the evolution of competitor strengths over time. Full likelihood-based analyses of these time-varying models can be simplified into rating systems, such as the Elo and Glicko rating systems. We present other modern rating systems, including popular methods for online gaming, and novel systems that have been implemented for online chess and Go. The discussion of the analytic methods are accompanied by examples of where these approaches have been implemented for various gaming organizations, as well as a detailed application to National Basketball Association game outcomes.

Analysis of the radiative corrections and dynamic extensions to the local field in the effective refractive index of particle suspensions

We analyze the predictions of two recently developed effective-medium approximations for the effective refractive index of a system of either transparent or plasmonic spherical particles, dispersed randomly in a transparent liquid matrix, as a function of their geometrical and physical parameters. The importance and significance of these approximations is that besides the radiative corrections to the optical response of the particles, they include full dynamic corrections to the field exciting any given particle. We perform this analysis by comparing the values obtained using them with the ones obtained from three well-known and widely used effective-medium approximations: Maxwell Garnett, Maxwell Garnett-Mie and van de Hulst. We provide plots of the real and imaginary parts of the effective index of refraction, for the five approximations considered, for polystyrene and gold nanoparticles of different sizes, as a function of the filling fraction and wavelength, pointing out the relevance of the new predictions, as well as the actual physical processes behind the so-called dependent scattering and what we now call dependent absorption.

A survey on temporal knowledge graph embedding: Models and applications

Knowledge graph embedding (KGE), as a pivotal technology in artificial intelligence, plays a significant role in enhancing the logical reasoning and management efficiency of downstream tasks in knowledge graphs (KGs). It maps the intricate structure of a KG to a continuous vector space. Conventional KGE techniques primarily focus on representing static data within a KG. However, in the real world, facts frequently change over time, as exemplified by evolving social relationships and news events. The effective utilization of embedding technologies to represent KGs that integrate temporal data has gained significant scholarly interest. This paper comprehensively reviews the existing methods for learning KG representations that incorporate temporal data. It offers a highly intuitive perspective by categorizing temporal KGE (TKGE) methods into seven main classes based on dynamic evolution models and extensions of static KGE. The review covers various aspects of TKGE, including the background, problem definition, symbolic representation, training process, commonly used datasets, evaluation schemes, and relevant research. Furthermore, detailed descriptions of related embedding models are provided, followed by an introduction to typical downstream tasks in temporal KG scenarios. Finally, the paper concludes by summarizing the challenges faced in TKGE and outlining future research directions.

The role of pennation angle and architectural gearing to rate of force development in dynamic and isometric muscle contractions.

Associations between muscle architecture and rate of force development (RFD) have been largely studied during fixed-end (isometric) contractions. Fixed-end contractions may, however, limit muscle shape changes and thus alter the relationship between muscle architecture an RFD. We compared the correlation between muscle architecture and architectural gearing and knee extensor RFD when assessed during dynamic versus fixed-end contractions. Twenty-two recreationally active male runners performed dynamic knee extensions at constant acceleration (2000°s-2) and isometric contractions at a fixed knee joint angle (fixed-end contractions). Torque, RFD, vastus lateralis muscle thickness, and fascicle dynamics were compared during 0-75 and 75-150 ms after contraction onset. Resting fascicle angle was moderately and positively correlated with RFD during fixed-end contractions (r = 0.42 and 0.46 from 0-75 and 75-150 ms, respectively; p < 0.05), while more strongly (p < 0.05) correlated with RFD during dynamic contractions (r = 0.69 and 0.73 at 0-75 and 75-150 ms, respectively; p < 0.05). Resting fascicle angle was (very) strongly correlated with architectural gearing (r = 0.51 and 0.73 at 0-75 ms and 0.50 and 0.70 at 75-150 ms; p < 0.05), with gearing in turn also being moderately to strongly correlated with RFD in both contraction conditions (r = 0.38-0.68). Resting fascicle angle was positively correlated with RFD, with a stronger relationship observed in dynamic than isometric contraction conditions. The stronger relationships observed during dynamic muscle actions likely result from different restrictions on the acute changes in muscle shape and architectural gearing imposed by isometric versus dynamic muscle contractions.

Impacts of carbon market and climate policy uncertainties on financial and economic stability: Evidence from connectedness network analysis

We use the conditional network connectedness approach of Stenfors et al. (2022) along with its frequency-domain, and tail and dynamic extensions to explore complex linkages among the carbon market, climate policy uncertainty, economic stability, and financial market stability. We focus on whether the carbon market and climate policy uncertainty impact US economic and financial market stability, and how these impacts occur. We identify a dynamic impact of the carbon market on economic and financial market stability, with these impacts varying in different frequency-domains and different quantile levels. Energy consumption and production structures as well as carbon emissions are found to be important mediators for carbon market to affect economic stability, while renewable energy equity is found to be a mediator through which the carbon market affects financial market stability. Further, while the impact of climate policy uncertainty on economic and financial market stability is typically weak, it strengthens under some circumstances, particularly in the long-term frequency-domain, right-tailed, prior to 2020. In these cases, carbon market, energy production structure and financial market stability are found to be weak mediators for climate policy uncertainty to impact economic stability.

Dynamic scaling-based immersion and invariance adaptive pose tracking control using dual quaternions

This paper investigates the position and attitude (pose) tracking control of a rigid body with uncertain mass and inertia. By virtue of the dual quaternion description, a six-degree-of-freedom (6-DOF) relative motion model is established in an integrated and compact way. Then an adaptive pose tracking controller is proposed based on the immersion and invariance (I&I) theory, where the key integrability obstacle is overcome by the dynamic scaling technique. Compared with the existing filter system-based method that constructs a filter system to circumvent the integrability obstacle, the dynamic scaling-based method is directly designed based on the original system, which is capable of retaining all benefits of the I&I design with much lower dimension dynamic extensions. Comparisons with the filter system-based I&I method and the classical certainty equivalent method are first carried out from the theoretical analyses, which elucidate benefits of the proposed method in lower control demands. Then the comparative simulations are conducted to verify the features and effectiveness of the proposed dynamic scaling-based I&I adaptive control scheme.

The effect of low-frequency fatigue on the torque-velocity relationship in human quadriceps.

Low-frequency fatigue (LFF) is usually defined as the decline in low:high-frequency force of electrically evoked isometric muscle contractions. The influence of LFF on dynamic muscle function is not well studied. Our aim was to assess the effect of LFF on the electrically evoked torque-velocity relationship in humans. Sixteen participants underwent a series of electrically evoked knee extensions in an isokinetic dynamometer to establish torque-velocity relationships at 15 and 50 Hz using isokinetic contractions. Hereafter, fatigue was induced by five sets of 10 repetitions of maximal voluntary dynamic knee extensions. After 30 min of rest, torque-velocity tests were repeated. Maximal torque (Fmax) was measured, whereas maximal contraction velocity (Vmax) and maximal power (Pmax) were estimated using Hill's force-velocity equation, 15:50 Hz ratios were calculated for Fmax, Vmax, and Pmax as markers of LFF. Fmax decreased by 40% at 15 Hz (P = 0.001) and by 15% at 50 Hz (P = 0.001) in the fatigued state. No significant change was detected for Vmax at 15 Hz [-2%, (P = 0.349)] or 50 Hz [+3% (P = 0.763)], whereas 15 and 50 Hz Pmax decreased by 30% (P = 0.004) and 10% (P = 0.008), respectively. Following the fatigue protocol, the 15:50 Hz Fmax ratio decreased by 31% (P < 0.001), indicating LFF. The 15:50 Hz Pmax ratio also decreased by 23% (P = 0.002), whereas the 15:50 Hz Vmax ratio was unchanged (P = 0.313). In conclusion, fatiguing contractions decreased Fmax and Pmax at both high and low stimulation frequencies, whereas Vmax appeared unaffected. Nevertheless, LFF influences power production during human dynamic contractions at a range of submaximal velocities.NEW & NOTEWORTHY Force-velocity relationships were established using either low- or high-frequency electrical stimulation before and after fatiguing voluntary eccentric/concentric contractions of the knee extensors. Low-frequency fatigue was assessed by the relative decrease in low- and high-frequency maximal torque, maximal shortening velocity, and maximal power estimated by the force-velocity relationship. Low-frequency fatigue manifests itself as a large decrease in low-frequency maximal force and power with a modest decrease in high-frequency maximal force and power. Contraction velocity does not seem to decrease in the same manner.

Impact of priority assignment on schedule-based attacks in real-time embedded systems

In this paper, we investigate the impact of priority assignment on schedule-based attacks in fixed-priority real-time systems. Through the schedule-based attacks, attackers may manipulate the input and output buffers of victim tasks, cause instability, and/or steal hidden information. The success of those attacks highly depends on the proper positioning of the malicious task with respect to the victim tasks in the actual schedule. Firstly, we develop an optimal priority assignment algorithm that incorporates the user specified priority preferences that reflect task types (anterior task, posterior task, or victim task), while still meeting all the deadlines. Secondly, we propose a dynamic delaying algorithm to further reduce posterior schedule-based attacks at run-time. Finally, we derive and compare the performance of six attack-aware priority-assignment policies as well as their dynamic extensions through comprehensive simulations. Our results suggest that the well-known RMS algorithm can be easily outperformed in terms of reducing schedule-based attacks, by properly specifying the relative priorities of malicious, anterior, and posterior tasks through our optimal algorithm. In particular, the AMP assignment, which assigns the anterior, malicious, and posterior tasks execution priorities in decreasing order, is shown to offer rather robust and consistent performance even at high system utilizations. Our framework explicitly incorporates the logical execution time and attack effective window constraints to model schedule-based attacks in realistic manner.

Microtubule rescue control by drugs and MAPs examined with in vitro pedestal assay

Microtubules are essential cytoskeletal polymers, which exhibit stochastic transitions between assembly and disassembly, known as catastrophes and rescues. Understanding of catastrophes, rescues, and their control by drugs and microtubule associated proteins (MAPs) has been informed by in vitro reconstitutions of microtubule dynamics. In such experiments microtubules are typically observed on a flat surface of the coverslip. In contrast, we have recently proposed a modified setup in which microtubules assemble from stabilized seeds, overhanging from microfabricated pedestals, so that their dynamic extensions are fully isolated from contact with the coverslip. This assay allows to eliminate potential artifacts, which may substantially affect the frequency of microtubule rescues in vitro. Here we use the pedestal assay to study the sensitivity of microtubules to paclitaxel, one of the best-known inhibitors of microtubule dynamics. By comparing observations in the conventional and the pedestal assays, we find that microtubule dynamics are substantially more sensitive to paclitaxel when the polymers can contact the coverslip. We interpret this as a consequence of the coverslip-induced microtubule assembly perturbation, leading to formation of lattice with defects, and thereby enhancing the efficiency of paclitaxel binding to microtubules in the conventional assay. To test this idea, we use vinblastine, another small-molecule inhibitor, which had been previously shown to cause microtubule growth perturbations. We find that in the pedestal assay vinblastine sensitizes microtubules to paclitaxel to the level, observed in the conventional assay. Interestingly, a minimal fragment of MAP called CLASP2, a previously characterized rescue factor, has a strong effect on microtubule rescues, regardless of the type of assay. Overall, our study underscores the role of microtubule damage in promoting rescues and highlights the utility of the in vitro pedestal assay to study microtubule dynamics modulation by tubulin inhibitors and MAPs.

The RNF220 domain nuclear factor Teyrha-Meyrha (Tey) regulates the migration and differentiation of specific visceral and somatic muscles in Drosophila.

Development of the visceral musculature of the Drosophila midgut encompasses a closely coordinated sequence of migration events of cells from the trunk and caudal visceral mesoderm that underlies the formation of the stereotypic orthogonal pattern of circular and longitudinal midgut muscles. Our study focuses on the last step of migration and morphogenesis of longitudinal visceral muscle precursors and shows that these multinucleated precursors utilize dynamic filopodial extensions to migrate in dorsal and ventral directions over the forming midgut tube. The establishment of maximal dorsoventral distances from one another, and anteroposterior alignments, lead to the equidistant coverage of the midgut with longitudinal muscle fibers. We identify Teyrha-Meyhra (Tey), a tissue-specific nuclear factor related to the RNF220 domain protein family, as a crucial regulator of this process of muscle migration and morphogenesis that is further required for proper differentiation of longitudinal visceral muscles. In addition, Tey is expressed in a single somatic muscle founder cell in each hemisegment, regulates the migration of this founder cell, and is required for proper pathfinding of its developing myotube to specific myotendinous attachment sites.

Extending effectiveness to efficiency: Comparing energy and environmental assessment methods for a wet cooling tower

AbstractImproving the environmental performance and energy efficiency of cooling towers requires systematic evaluation. However, methodological challenges emerge when applying typical environmental assessment methods to cooling towers. Hence, this paper compares the methods, analyzes their strengths and weaknesses, and proposes adaptions for evaluating cooling towers. As a case study, we applied five methods for assessing the wet cooling system of the high‐performance data center in Stuttgart. These are material flow analysis (MFA), life cycle inventory, life cycle assessment (LCA), exergy analysis, and life cycle exergy analysis (LCEA). The comparison highlights that the LCA provides the most comprehensive environmental evaluation of cooling systems by considering several environmental impact dimensions. In the case of the wet cooling tower, however, electricity and water consumption cause more than 97% of the environmental impacts in all considered impact categories. Therefore, MFA containing energy flows suffices in many cases. Using exergy efficiency is controversially debated because exergy destruction is part of the technical principle applied in cooling towers and, therefore, difficult to interpret. The LCEA appears inappropriate because construction and disposal barely affect the exergy balance and are associated with transiting exergy. The method comparison demonstrates the need for further methodological development, such as dynamic extensions or the efficiency definition of cooling towers. The paper highlights that the methodological needs depend on the specific application.

School-Based Circuit Training Intervention Improves Local Muscular Endurance in Primary School Students: A Randomized Controlled Trial.

This study aimed to explore the effectiveness of a 12-week circuit training program in improving local muscular endurance in normal-weighted primary school students. The study involved a parallel-group randomized trial with 606 primary school boys assigned to an experimental or a control group. The participants underwent a 12-week circuit training program that involved multi-joint, total-body workouts using body weight, resistance bands, and medicine ball exercises. The study measured the participants' local muscular endurance during sit-ups, dynamic trunk extensions on a Roman bench (DTE), and push-ups. After adjusting for the baseline, the treatment-grade interaction was significant for sit-ups (F = 7.74, p < 0.001, ηp2 = 0.04), DTE (F = 6.49, p < 0.001, ηp2 = 0.03), and push-ups (F = 9.22, p < 0.001, ηp2 = 0.05), where the experimental treatment was more beneficial than the control. The treatment effect seemed to vary depending on the individual's baseline local muscle endurance capacity. As the baseline local muscular endurance values increased, the treatment and grade effects became less beneficial. A 12-week circuit training program involving body weight, resistance bands, and medicine ball exercises suits school-based programs and can improve local muscular endurance in normal-weighted primary school boys. The experimental treatment was more effective than the control, and the individual baseline muscular endurance should be considered when designing training programs.

An Economic Evaluation of the European Union’s 2030 Climate Policy Plan

Purpose: The purpose of the study is to evaluate the European Union’s “Fit for 55” plan, announced in 2021, which intends to meet a 2030 goal of reducing carbon emissions by 55 percent from 1990 levels.&#x0D; Design/methodology/approach: An analytical model is used to assess the impact of the EU environmental policies, including the carbon border tax, emissions trading system, energy efficiency, and emission standards.&#x0D; Findings: The study finds that the environmental policies achieve different policy criteria, including cost minimization, equalization of marginal abatement cost, minimization of general equilibrium cost, political feasibility, and minimization of inequitable impacts across income groups. But no single policy instrument is necessarily superior to the others. The paper finds that a revenue-neutral carbon border tax and an emissions trading system with auctioned permits satisfy the most evaluation criteria.&#x0D; Research limitations/implications: For the purpose of simplification, the model ignores dynamic extensions. That is, the adjustments of businesses to policy measures and the effects on emissions are beyond the scope of this analysis.&#x0D; Originality/value: The study develops a model that evaluates the European Union’s environmental policies in a unifying perspective, assessing the tradeoffs of policy design.

Density and Risk Prediction with Non-Gaussian COMFORT Models

The CCC-GARCH model, and its dynamic correlation extensions, form the most important model class for multivariate asset returns. For multivariate density and portfolio risk forecasting, a drawback of these models is the underlying assumption of Gaussianity. This paper considers the so-called COMFORT model class, which is the CCC-GARCH model but endowed with multivariate generalized hyperbolic innovations. The novelty of the model is that parameter estimation is conducted by joint maximum likelihood, of all model parameters, using an EM algorithm, and so is feasible for hundreds of assets. This paper demonstrates that (i) the new model is blatantly superior to its Gaussian counterpart in terms of forecasting ability, and (ii) also outperforms ad-hoc three-step procedures common in the literature to augment the CCC and DCC models with a fat-tailed distribution. An extensive empirical study confirms the COMFORT model’s superiority in terms of multivariate density and Value-at-Risk forecasting.

A conditional higher-moment CAPM

This paper investigates whether dynamic and moment extensions to the traditional CAPM can improve its empirical performance and offer some alternative explanation to the cross-section of average returns on portfolios of stocks double sorted on book-to-market ratios and size. We consider three extensions. First, we introduce time-varying factor loadings obtained from a multivariate GARCH and dynamic conditional correlations. Second, we extend the model to a four-moment CAPM, which incorporates coskewness and cokurtosis. Finally, we allow for time-varying risk premia, based on a Markov-switching process. Our results confirm that the higher-moment CAPM does not perform well in its unconditional version, but its performance is significantly improved when we introduce a conditional version that accounts for both time-varying factor loadings and time-varying risk premia. The four-moment CAPM tests lead to a positive total risk premium estimate of 0.67% per month over the period 1926–2021, with all risk premia (beta, coskewness, and cokurtosis) exhibiting the expected theoretical signs.

A role for the centrosome in regulating the rate of neuronal efferocytosis by microglia in vivo.

During brain development, many newborn neurons undergo apoptosis and are engulfed by microglia, the tissue-resident phagocytes of the brain, in a process known as efferocytosis. A hallmark of microglia is their highly branched morphology characterized by the presence of numerous dynamic extensions that these cells use for scanning the brain parenchyma and engulfing unwanted material. The mechanisms driving branch formation and apoptotic cell engulfment in microglia are unclear. By taking a live-imaging approach in zebrafish, we show that while microglia generate multiple microtubule-based branches, they only successfully engulf one apoptotic neuron at a time. Further investigation into the mechanism underlying this sequential engulfment revealed that targeted migration of the centrosome into one branch is predictive of phagosome formation and polarized vesicular trafficking. Moreover, experimentally doubling centrosomal numbers in microglia increases the rate of engulfment and even allows microglia to remove two neurons simultaneously, providing direct supporting evidence for a model where centrosomal migration is a rate-limiting step in branch-mediated efferocytosis. Conversely, light-mediated depolymerization of microtubules causes microglia to lose their typical branched morphology and switch to an alternative mode of engulfment, characterized by directed migration towards target neurons, revealing unexpected plasticity in their phagocytic ability. Finally, building on work focusing on the establishment of the immunological synapse, we identified a conserved signalling pathway underlying centrosomal movement in engulfing microglia.

Some notes on dynamic oligopsonies

Abstract A special oligopoly model is considered when the firms compete on the factor market, and the used factor volumes determine their outputs. In the Nfirm case conditions are given for the existence of the Nash equilibrium, and in the cooperative case, sufficient conditions are derived for the existence and uniqueness of the joint profit maximizer. In the case of a linear duopoly the dynamic extensions are introduced in both cases based on gradient adjustments. Conditions are given for the local asymptotic stability of the equilibrium and the joint profit maximizer without and with information delays.

The effects of facilitatory and inhibitory kinesiotaping of Vastus Medialis on the activation and fatigue of superficial quadriceps muscles

This study aimed to investigate how facilitatory and inhibitory KT of the Vastus Medialis affected the activation and the fatigue indices of VM, Vastus Lateralis (VL) and Rectus Femoris (RF) throughout a dynamic fatigue protocol. Seventeen collegiate athletes (Ten males, seven females, age: 24.76 ± 3.99 years, height: 1.73 ± 0.10 m, mass: 68.11 ± 8.54 kg) voluntarily participated in four dynamic fatigue protocol sessions in which no-tape (control condition), inhibitory, facilitatory and sham KTs were applied to the Vastus Medialis in each session. The protocol included 100 dynamic maximum concentric knee extensions at 90°/s using an isokinetic dynamometry device. The knee extensor muscle activities were recorded using wireless surface electromyography. The average muscle activity (Root mean square) during the first three repetitions and the repetitions number of 51–100, respectively, were used to calculate the before and after exhaustion muscle activity. Furthermore, median frequency slope during all repetitions was reported as the fatigue rate of muscles during different KT conditions and for the control condition (no-tape). The results showed neither muscle activation (significance for the main effect of KT; VM = 0.82, VL = 0.72, RF = 0.19) nor fatigue rate (significance for the main effect of KT; VM = 0.11 VL = 0.71, RF = 0.53) of the superficial knee extensor muscles were affected in all four conditions. These findings suggest that the direction of KT cannot reduce, enhance muscle activity or cause changes in muscle exhaustion. Future studies should investigate the generalizability of current findings to other populations.

Application of an open-loop dynamic wake model with high-frequency SCADA data

Future wind energy control applications require surrogate flow models that can capture processes on short time scales. Dynamic extensions of wake models might be a useful low cost solution. So far, studies have tested the proposals mostly in LES or LIDAR campaigns. At the same time, readily obtainable turbine SCADA measurements are increasingly being used directly for model input or validation. Newly available high resolution recordings allow for the study of processes on shorter time scales. The present study examines the modelling capabilities of a dynamic wake model by utilizing high frequency SCADA data. Therefore, the data is first analyzed for cross-correlation and time delays. Secondly, the dynamic wake model, initialized with SCADA measurements, is used to predict a two turbine wake interaction. An offline tuning algorithm is used to adapt the model for the shorter time scales.

Adaptive personalized routing for vulnerable road users

This research presents an adaptive and personalized routing model that enables individuals with mobility impairments to save their route preferences to a mobility assistant platform. The proactive approach based on anticipated user need accommodates vulnerable road users' personalized optimum dynamic routing rather than a reactive approach passively awaiting input. Most currently available trip planners target the general public's use of simpler route options prioritized based on static road characteristics. These static normative approaches are only satisfactory when conditions of intermediate intersections in the network are consistent, a constant rate of change occurs per each change of the segment condition, and the same fixed routes are valid every day regardless of the user preference. In this study, the vulnerable road user mobility problem is modeled by accommodating personalized preferences changing by time, sidewalk segment traversability, and the interaction between sidewalk factors and weather conditions for each segment contributing to a path choice. The developed reinforcement learning solution presents a lower average cost of personalized, accessible, and optimal path choices in various trip scenarios and superior to traditional shortest path algorithms (e.g., Dijkstra) with static and dynamic extensions.