Search

This paper investigates the effect of different categories of essential COVID-19 data from 2020 to 2021 towards stock price dynamics and options markets. It applied the hypothetical method in which investors develop depression based on the understanding suggested by various green finance divisions. Furthermore, additional elements like panic, sentiment, and social networking sites may impact the attitude, size, and direction of green finance, subsequently impacting the security prices. We created new emotion proxies based on five groups of information, namely COVID-19, marketplace, lockdown, banking sector, and government relief using Google search data. The results show that (1) if the proportional number of traders' conduct exceeds the stock market, the effect of sentimentality indexes on jump volatility is expected to change; (2) the volatility index component jump radically increases with the COVID-19 index, city and market lockdown index, and banking index; and (3) expanding the COVID-19 index gives rise to the stock market index. Moreover, all indexes decreased in jump volatility but only after 5 days. These findings comply with the hypotheses proposed by our model.

A hydraulic jump forming in the stilling basin at the base of a high-head dam spillway is often characterized by high Froude number and inflow pre-aeration conditions. Although the air entrainment in hydraulic jump has been studied extensively, the effects of the inflow pre-air-entrainment on the downstream air–water flow properties and energy dissipation performance have not been investigated systematically, especially for high-Froude-number cases. This paper presents a comparative study of the pre-aeration effects on the air–water flow characteristics of high-Froude-number hydraulic jumps. Two pre-aeration levels were achieved using a smooth sloping chute and a ramp aerator on the chute. Apart from the change in jump length required for the same amount of energy dissipation, the major impact of the variation in pre-aeration was observed for the void fraction and air entrainment flux within the jet-shear region, whereas the bubble count rate and interfacial velocity were less affected. Differences were also observed from the prediction of previous studies under smaller Froude number and negligible pre-air-entrainment conditions. The pre-air-entrainment was found to affect the scale effects on the bubble counts and the interfacial area between air and water phases. This study may facilitate a bridging between the laboratory findings and the cases closer to the real engineering application of large-scale hydraulic jumps.

In the present paper, we study the homogenization of a class of quasilinear elliptic problems in a two-component domain (one connected and the other a disconnected union of small sets) with a jump of the solution on the interface, proportional to the flux. We prescribe $$L^1$$ data and coefficient periodic matrix fields A(y, t) only bounded for bounded t, which implies that we cannot use the variational setting for our problem. We instead use the adapted framework of renormalized solution, where the solution is suitably defined, and does not belong to the $$H^1$$ Sobolev space but only their truncated functions are in $$H^1$$ . To study the homogenization of the problem, we use the periodic unfolding method, which we can only apply to the truncated solutions, which are in $$H^1$$ . Nevertheless, we are able to identify the homogenized problem, which also has only a renormalized solution. The main difficulty here is managing the boundary integral that results from the jump on the interface, and the study of the properties of the solution in the disconnected component. Conditions for the uniqueness of both problems, the oscillating one and the homogenized are also stated.

This study investigated the relationship of executive functions and physical abilities in youth and adult elite soccer players. In all, 172 elite soccer players (12–34 years of age) performed a computer-based test battery assessing multiple-object tracking, working memory capacity, cognitive flexibility, and inhibition. Another series of tests measured endurance-performance at the individual anaerobic threshold (IAT), ability to repeatedly perform intense exercises (RIEA), and maximal anaerobic performance parameters (squat jump, counter movement jump, drop jump quotient, sprint time). Executive functions and maximal anaerobic parameters showed small to moderate correlations for example, working memory capacity and cognitive flexibility with sprint, countermovement- and drop jump along with a correlation of inhibition and RIEA. These findings favor specific motor–cognition associations rather than a one-fits-all association. Specifically, sprint and jump seem to be more closely linked to cognitive skills than endurance parameters and represent fundamental associations across several age groups.

This paper focuses on establishing an effective predictive model to quickly and accurately alert hypoglycemia and hyperglycemia for helping control blood glucose levels of people with diabetes. In general, a good predictive model is established on the features of data. Inspired by this, we first analyze the characteristics of continuous glucose monitoring (CGM) data by the equality of variances test and outlier detection, which show time-varying fluctuations and jump points in CGM data. Therefore, we incorporate the change detection method and the Winsorization method into the predictive model based on the autoregressive moving average (ARMA) model and the recursive least squares (RLS) method to fit the above characteristics. To the best of our knowledge, the proposed method is the first attempt to give a solution for matching the time-varying fluctuations and jump points of CGM data simultaneously. A case study using CGM data is given to validate the effectiveness of the proposed method under 30-min-ahead prediction. The results show that the proposed method can improve the true alarm ratio of hypoglycemia and hyperglycemia from 0.7983 to 0.8783, and lengthen the average advance detection time of hypoglycemia and hyperglycemia from 19.77 to 22.64 min.

Plyometric training has shown to improve vertical jump height, but the design and implementation of a plyometric training programme for adolescents requires consideration of several variables as well as the time of the season. The purpose of this study was to implement a pragmatic programme that improves vertical jump height, and to monitor the effects of a 15 week off-season plyometric and resistance training programme on the vertical jump height in adolescent female volleyball players. Ten adolescent female volleyball players (age: 15.1 ± 0.9 years, height: 1.71 ± 0.04 m, body mass: 63.6 ± 6.0 kg, volleyball training experience: 5.1 ± 1.4 years) underwent 15 weeks of plyometric and resistance training (twice and once a week, respectively). A single-targeted block periodised approach and a linear periodisation model were applied. Vertical jump height was assessed before the programme (T1), after 4 weeks (T2), after 12 weeks (T3) and at the end of the programme (T4). Jump height significantly increased by 8.8% over the full time of the investigation. No significant difference was found between T1 and T2 but for all other pairwise comparisons. Similarly, leg power was observed to increase by 6.5% (P = 0.001). The 15-weeks training programme showed to improve jump height and leg power. In consideration of its practical nature and its results in comparison with similar intervention studies, the programme suggests practical relevance for coaches.

In this study, the joint effects of submerged vanes and flow expansion on the hydraulic jump are experimentally investigated. Experiments include four expansions and four vane layouts with the Froude number ranging from 4.60 to 8.56. The results show, abrupt expansion and the vanes that are 5 cm apart are the best in dissipating energy, the energy loss increases about 30%, with respect to classical jump. The sequent depths ratio decreased up to 54% and the length of hydraulic jump decreased up to 45%. On the other hand, shear force coefficient shows a relative increase in the transition length of the hydraulic jump. We conclude that using the combination of the vanes and expansion in proper orientation relative to each other can be cost effective in the construction of the stilling basins.

Climate change and human activities have led to nonstationarity in hydrological series. To systematically consider nonstationarity in regional frequency analysis (RFA), the features accounting for temporal variability of data series were developed and a nonstationary index flood model considering the trend and jump mutations was proposed in this study. The features extracted by empirical mode decomposition (EMD) were regarded as attributes to identify homogeneous regions. The fuzzy c-means clustering (FCM) and the combination of the self-organizing feature map and Ward’s agglomerative hierarchical clustering (SOM+Ward) were compared. Then the complete nonstationary RFA was applied to the annual maximum daily precipitation (AMDP) of Jiangxi province, China. The results indicate that the regionalization with the attributes reflecting temporal variability of the data series is more detailed. Moreover, the performance of SOM+Ward is better than FCM. The comparison results of precipitation quantiles, which were estimated by stationary and the proposed nonstationary index model, indicate that ignoring nonstationarity in RFA affects the choice of the best-fit distribution and the determination of index flood. In addition, the complete framework of nonstationary RFA developed in this study can provide more proper information when stations with trend and jump mutations exist in the region.

Sensor-based human activity recognition and health monitoring are attaining great interest in the eye of the researcher as it maintained the privacy of an individual. A model based on the transfer learning for the vertical distribution of cross position sensor data is proposed in this paper. The whole human body participates during an activity like walking, jumping, running, etc. When someone walk, run, jump, upstairs downstairs his hands and lags both act as per the activity. Existing methods of human activity recognition using sensor data learn from one dataset and transfer that learning for another one but in the proposed work combine learning of accelerometer, magnetometer and gyroscope placed at ankle of the body is used as starting point for the lower arm of the body. combination of sensor data from three sensors (accelerometer, gyroscope, magnetometer) obtain better result as compare to an individual and other combinations. Two publically available datasets are used, i.e. mHEALTH and PAMAP2. The proposed model has been compared to the state of art approaches. The experimental results show that the proposed approach performs batter compare to state-of-the-art methods. Model score 98.48 and 98.63 % test accuracy for balanced and unbalanced mHEALTH dataset and achieved 92.00 and 94.19 % test accuracy for balanced and unbalanced PAMAP2 dataset.

The research purposes were to explore the high-risk injury factors of basketball players’ lower limb patellar tendon enthesis based on medical big data and accurately recognize players’ lower limb injuries. Middle school students in Nanchang, the capital of Jiangxi Province, were included as the research samples. Innovatively, deep learning and artificial intelligence were applied for statistics and analysis of the collected data. The training of included samples was tracked to collect kinetic and biological data and then to analyze the high-risk injury factors of lower limbs. The analysis of basic information of the participants indicated no significant differences between the two groups. Deep learning algorithm analysis suggests that the accuracy of high-risk group and non-high-risk group is 66.82% and 66.20%, respectively. The analysis of the mechanical characteristics of patellar tendon ends of participants indicated that when the maximum flexion angles of the knee joints of the high-risk group were significantly greater than that of the non-high-risk lower limb group, there were statistically significant differences (P

Background Jumps are predominant components in football (soccer). Interlimb functional difference in single-leg jump performance is a risk factor for lower extremities injuries. Screening uninjured athletes is essential to design prevention strategies and implement individual training interventions. The aims of this cross-sectional study were (1) to provide age-specific mean values and limb symmetry index (LSI) in young football players, (2) to detect age effect on LSI and interlimb functional differences and (3) to investigate the association of age with single-leg functional performance and LSI. Methods A total of 146 male football players (age 14.2 ± 2.3) performed the countermovement jump, jump for distance, side hop and speedy jump tests. Descriptive statistics, mean values (dominant/non-dominant) and LSI were provided according to age groups (U11–U19). Two-way mixed analysis of variance (ANOVA), one-way ANOVA and Pearson’s correlation were used for the statistical analysis. Results Participants showed on average perfect LSI (103.8 ± 14.2%) amongst all tests and age groups. Interlimb functional differences occurred in three out of four tests (p p > 0.05). Age effect was positively associated with single-leg functional performance (p p > 0.05), in all tests and age groups. Conclusion An LSI ≥100% in single-leg jump tests is proposed as a benchmark in young football players, but interlimb performance differences may occur without age interaction. Nevertheless, the growth process plays a crucial role in the development of functional capacities: older players may show a higher single-leg jump performance, but not a higher LSI, than younger players. In football practice, preventive intervention is advisable to counteract interlimb performance differences, for which unilateral strength, power and plyometric training is recommended.

In this paper, we emphasize on a novel fast fixed-time control strategy and its application to fixed-time synchronization control of semi-Markov jump delayed Cohen-Grossberg neural networks (SMJDCGNNs). First, we consider a class of SMJDCGNNs. Second, a novel fast fixed-time control strategy is proposed and designed to control the considered delayed system to achieve global synchronization within the derived fixed settling time. Third, the advantages of the derived theoretical results are discussed. Finally, we give a numerical example to show the effectiveness and feasibility of the obtained theoretical results.

This paper aims to apply the real options game theoretic to study the impact of sudden events on the optimal investment timing and capacity choice in a duopoly market. We model the market demand and investment cost as the geometric Brownian motions with jumps driven by the Poisson processes. A new computing method independent on specific distribution functions is proposed for the real option models with jump processes of random frequency and amplitude. Based on this method, we find that both firms delay investment with a larger capacity as uncertainties of demand and investment cost increase. We also demonstrate that two firms both invest later and the optimal capacity relationship between them is ambiguous in the presence of two sources of uncertainty. Numerical simulation reveals that upward (downward) jump in demand and downward (upward) jump in investment cost cause the firms to invest earlier (later) with a larger (smaller) capacity. Finally, in a duopoly with symmetric firms, the first investor invests earlier than in an asymmetric duopoly due to the threat of preemption.

This paper concerns some asymptotic analysis of stochastic convective Brinkman–Forchheimer (SCBF) equations subjected to multiplicative pure jump noise in two- and three-dimensional bounded domains. Using a weak convergence approach, we establish the Wentzell–Freidlin type large deviation principle for the strong solution to SCBF equations in a suitable Polish space.

This paper is concerned with the event-triggered control of positive semi-Markovian jump systems without/with input saturation. The considered systems are subject to a stochastic semi-Markovian process whose sojourn time is dependent on a non-exponential distribution. First, an event-triggering condition is introduced in a linear form for the systems. A class of event-triggered feedback controllers is proposed using matrix decomposition technique. By using a stochastic co-positive Lyapunov function, the systems’ positivity and stability are guaranteed. Then, the obtained results are developed for the systems with input saturation. A cone set is chosen as the attraction domain and the corresponding attraction domain gain matrix is designed in terms of standard linear programming approach. Finally, two numerical examples are provided to verify the validity and effectiveness of the presented theoretical findings.

A well-known Itô formula for finite-dimensional processes, given in terms of stochastic integrals with respect to Wiener processes and Poisson random measures, is revisited and is revised. The revised formula, which corresponds to the classical Itô formula for semimartingales with jumps, is then used to obtain a generalisation of an important infinite-dimensional Itô formula for continuous semimartingales from Krylov (Probab Theory Relat Fields 147:583–605, 2010) to a class of $$L_p$$ L p -valued jump processes. This generalisation is motivated by applications in the theory of stochastic PDEs.

This paper considers the topic of the observer-based non-fragile mixed passivity and H∞ state feedback control for time-varying delay and norm-bounded parameter uncertainties fuzzy stochastic Markovian jump system subject to quantized measurements. The aim of this paper is to provide a suitable observer-based non-fragile state feedback controller to enhance stochastic stabilization of the closed-loop system and satisfy mixed passivity and H∞ performance. By constructing mode-dependent Lyapunov-Krasovskii functional, novel conditions are achieved in virtue of linear matrix inequalities. Two examples including truck-trailer model are given to illustrate the effectiveness of the developed method.

The problem of change point detection can be solved either by online methods, based on a discrepancy measure, or by offline methods. The former tries to detect the change points one by one with a sliding window and leads to a lower computational time but are more sensitive to noise. Conversely, offline methods consider the entire data to detect all the change points which make them more robust against the noise but at a price of higher computational cost. In this paper, we propose an operational search method that combines the benefits of both approaches with the double aim to get higher noise resistance while keeping a blazingly fast time. The search method slides over the edges of the signal to determines their state by considering a global constrained energy. Thanks to the calculus of variation, the computation of this energy is reduced to the estimation of the effective jump for each edge. We study the performance and accuracy of our energy variation method to detect the change points in synthetic and real-world examples. The results compare favorably against state of the art algorithm in terms of speed and accuracy.

In order to reasonably allocate the capacity of distributed generation and realize the goal of stable, economic and clean operation of the system, a multi-objective optimization model with investment cost, environmental protection and power supply quality as indicators has been established, and the multi-objective sparrow search algorithm is used to optimize the solution. Although the multi-objective search algorithm is more efficient than the traditional single objective algorithm, it is easy to fall into local optimum. To this end, the niche optimization technology is used to improve the optimization effect of multi-objective sparrow search algorithm, and the Levy flight strategy is introduced to enhance the ability of multi-objective sparrow search algorithm to jump out of local optimum. The calculation example uses the traditional multi-object search algorithm and the niche multi-objective sparrow search algorithm with levy disturbance to solve the proposed model. The simulation results verify the effectiveness of the multi-objective sparrow search algorithm improved by levy disturbance and niche optimization technology.

We study a dynamic information design problem in a finite-horizon setting consisting of two strategic and long-term optimizing agents, namely a principal (he) and a detector (she). The principal observes the evolution of a Markov chain that has two states, one “good” and one “bad” absorbing state, and has to decide how to sequentially disclose information to the detector. The detector’s only information consists of the messages she receives from the principal. The detector’s objective is to detect as accurately as possible the time of the jump from the good to the bad state. The principal’s objective is to delay the detector as much as possible from detecting the jump to the bad state. For this setting, we determine the optimal strategies of the principal and the detector. The detector’s optimal strategy is described by time-varying thresholds on her posterior belief of the good state. We prove that it is optimal for the principal to give no information to the detector before a time threshold, run a mixed strategy to confuse the detector at the threshold time, and reveal the true state afterward. We present an algorithm that determines both the optimal time threshold and the optimal mixed strategy that could be employed by the principal. We show, through numerical experiments, that this optimal sequential mechanism outperforms any other information disclosure strategy presented in the literature. We also show that our results can be extended to the infinite-horizon problem, to the problem where the matrix of transition probabilities of the Markov chain is time-varying, and to the case where the Markov chain has more than two states and one of the states is absorbing.

To measure changes in strength, power, and agility over consecutive seasons based on competition level in figure skaters. A total of 197 competitive singles figure skaters (age range = 9–25 years old) completed combines with United States Figure Skating on two consecutive seasons between 2011 and 2018. Skaters either remained in the same competitive on-ice level or increased by one level on consecutive seasons. All athletes completed the hexagon agility test, maximal vertical jump, timed tuck jumps, push-ups, and bent knee v-ups. Repeated-measures analyses of variance separated by sex with Tukey’s post hoc were performed for each dependent variable and Cohen’s d effect sizes were calculated for all significant differences. Female skaters who remained in the same level demonstrated improved performance on vertical jump (3.66 cm higher), timed tuck jumps (3.77 more jumps), v-ups (1.59 more v-ups), and hexagon jump (1.17 s faster). There was an interaction for female skaters who remained in the same level (P = 0.004), with senior and junior levels outperforming intermediate level skaters on the hexagon jump test. Female skaters who increased level demonstrated improved performance on the vertical jump (2.24 cm higher), hexagon jump (1.16 cm faster), and tuck jump (3.03 more jumps). Male skaters did not demonstrate any changes in performance except v-ups (2.86 more v-ups) for those who increased level. The greatest changes were in lower level female skaters who remained in the same level, supporting the importance of participating in strength and conditioning programs earlier in skating careers to maximize athleticism before reaching the senior level, when changes in off-ice performance plateau.

Ant colony optimization has insufficient convergence and tends to fall into the local optima when solving the traveling salesman problem. This paper proposes a co-evolutionary multi-colony ant colony optimization (MCGACO) to overcome this deficiency and applies it to the Robot Path Planning. First, a dynamic grouping cooperation algorithm, combined with Ant Colony System and Max-Min Ant System, is introduced to form a heterogeneous multi-population structure. Each population co-evolves and complements each other to improve the overall optimization performance. Second, an adaptive guidance mechanism is proposed to accelerate convergence speed. The mechanism includes two parts: One is a dynamic evaluation network, which is used to evaluate and divide all solutions by the evaluation function. The other is a positive-negative incentive strategy, which can enhance the guiding role of solutions with higher evaluation value. Besides, to jump out of the local optima, an inter-specific co-evolution mechanism based on the game model is proposed. By dynamically determining the optimal communication combination, the diversity among populations can be well balanced. Finally, the experimental results demonstrate that MCGACO outperforms in terms of solution accuracy and convergence. Meanwhile, the proposed algorithm is also feasible for application in Robot Path Planning.

The detection of optimal trajectories with multiple coast arcs represents a significant and challenging problem of practical relevance in space mission analysis. Two such types of optimal paths are analyzed in this study: (a) minimum-time low-thrust trajectories with eclipse intervals and (b) minimum-fuel finite-thrust paths. Modified equinoctial elements are used to describe the orbit dynamics. Problem (a) is formulated as a multiple-arc optimization problem, and additional, specific multipoint necessary conditions for optimality are derived. These yield the jump conditions for the costate variables at the transitions from light to shadow (and vice versa). A sequential solution methodology capable of enforcing all the multipoint conditions is proposed and successfully applied in an illustrative numerical example. Unlike several preceding researches, no regularization or averaging is required to make tractable and solve the problem. Moreover, this work revisits problem (b), formulated as a single-arc optimization problem, while emphasizing the substantial analytical differences between minimum-fuel paths and problem (a). This study also proves the existence and provides the derivation of the closed-form expressions for the costate variables (associated with equinoctial elements) along optimal coast arcs.

A 1–0 Bg-RRT algorithm is proposed to reduce computational time and complexity, even in complex environments. Different from Rapidly-exploring Random Tree (RRT) and Bias-goal Rapidly-exploring Random Tree (Bg-RRT), using 1–0 Bg-RRT with 1 and 0 change probability biased to the target to construct the tree is faster and can jump out of the local minimum in time. Although unknown space path planning problem based on RRT is difficult to obtain satisfactory performance, but the improved algorithm provides a more superior compared with the basic RRT algorithm and Bg-RRT algorithm. The simulation results show that the 1–0 Bg-RRT algorithm has shorter computational time and shorter path than the traditional RRT algorithm.

The difficulty of the problem of the flow hydraulics in compound channels is due to the implicit interaction between the floodplains and the main channel, characterizing every particular shape of the compound channel. The problem is much more complicated when it comes to an energy dissipator like a hydraulic jump as is the case in the present study. In this paper, the general regression neural network (GRNN) was applied to predict the basic characteristics of hydraulic jumps in a straight rectangular compound channel: (i) the sequent depths ratios, (ii) the relative energy losses, and (iii) the relative lengths. Experiments were carried out with three different values of the ratio between the main channel width and the flood plain one (Wy). The Wy values were: (1/4, 1/3, and 1/2). For each Wy ratio, several values of inflow Froude number were considered according to the five inflow ratio depths’ (Wz) values (0.167, 0.200, 0.253, 0.287, and 0.333) between the first sequent depth and of the main channel one. The predicted values in the testing stages using GRNN followed the experimental ones with a correlation coefficient (R) of 0.990 for the sequent depth’s ratios, 0.982 for relative energy losses, and 0.873 for the relative lengths of hydraulic jumps. The best models have been selected among several input configurations for each of three considered characteristics of the jump.

Chatter is a very common phenomenon in the milling process. The occurrence of chatter will cause chatter marks on the processed surface, cause the tool to jump, and even bring sharp and harsh noise, making the processed surface unable to meet the accuracy requirements. Thin-walled parts are more prone to chatter due to their lower stiffness. In order to avoid the occurrence of chatter, this paper adopts the method of combining theoretical analysis with milling experiments to conduct in-depth research on the prediction of chatter. Considering the first-order and second-order modal parameters of the tool and thin-walled part as well as the specific processing parameters, based on the milling dynamics model, a semi-discretization method based on the improved Runge-Kutta method (IRKM-SDM) is used to draw the chatter stability lobe diagram. Through simulation and experiments, it is proved that in terms of simulation accuracy and calculation speed, compared with the zero-order analysis (ZOA), multi-frequency solution (MFS), and the traditional semi-discretization method (SDM), the stability lobe diagram obtained by the IRKM-SDM is more advantageous. This study is of great significance for optimizing cutting parameters and suppressing chatter in the actual machining process.

Made available in DSpace on 2022-04-29T08:45:31Z (GMT). No. of bitstreams: 0 Previous issue date: 2022-03-01 Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Purpose: This study compared the effects of plyometric training performed on the ground or on a mini-trampoline on jumping, balance and landing performance (and its recovery time) in basketball players. Methods: 30 male basketball athletes, between 17 and 21 years of age, were divided into three groups: plyometric training on the mini-trampoline (TPT, n = 11), on the ground (CPT, n = 9), and control group (CG, n = 10). Participants were evaluated on maximum height of their countermovement jumps, landing impact (peak ground reaction force) in single-leg drop landing jump, and balance (center of pressure [COP] Area, COP length) in the two single-leg standing tests (with closed or open eyes) before, immediately after, 15 min after, and 30 min after the training session. Results: CPT showed larger landing impact than CG (p =.031), larger COP area than TPT (p =.031) and longer COP length than CG (p =.024) in the opened-eyes condition. In the closed-eyes condition, a small decrease in COP length was observed. Conclusion: TPT does not lead to deterioration on balance, landing and performance as observed in CPT. Also, the minimum time for recovery balance after a plyometric session was estimated as 30 min. Ribeirão Preto College of Nursing University of São Paulo, Av. Bandeirantes, 3900, Monte Alegre, São Paulo Department of Bioscience São Paulo State University, São Paulo School of Dentistry at Piracicaba Campinas State University, São Paulo School of Physical Education and Sport University of São Paulo, São Paulo Movement Control and Neuroplasticity Group KU Leuven School of Physical Education and Sport of Ribeirão Preto University of São Paulo, São Paulo Department of Bioscience São Paulo State University, São Paulo CAPES: 001

We investigate periodic solutions of regime-switching jump diffusions. We first show the well-posedness of solutions to stochastic differential equations corresponding to the hybrid system. Then, we derive the strong Feller property and irreducibility of the associated time-inhomogeneous semigroups. Finally, we establish the existence and uniqueness of periodic solutions. Concrete examples are presented to illustrate the results.

In this article, the exponential stabilization of stochastic complex networks with time delays, uncertainties and switching jump diffusions (SCNTDUSJD) is investigated via adaptive aperiodically intermittent control. It deserves mentioning that switching jump diffusions are state dependent and adaptive aperiodically intermittent control is applied to study the stabilization of SCNTDUSJD for the first time. Primarily, the Lyapunov function of SCNTDUSJD is constructed. Based on graph theory and the Lyapunov method, some sufficient conditions are given to ensure the exponential stability of SCNTDUSJD, which reflects that the controller plays an important role in the realization of stabilization. At the same time, our results can be applied to stochastic coupled oscillators with switching jump diffusions. Finally, in order to explain the effectiveness of theoretical results, relative numerical results are presented.

Actuator faults usually cause security problem in practice. This paper is concerned with the security control of positive semi-Markovian jump systems with actuator faults. The considered systems are with mode transition-dependent sojourn-time distributions, which may also lead to actuator faults. First, the time-varying and bounded transition rate that satisfies the mode transition-dependent sojourn-time distribution is considered. Then, a stochastic co-positive Lyapunov function is constructed. Using matrix decomposition technique, a set of state-feedback controllers for positive semi-Markovian jump systems with actuator faults are designed in terms of linear programming. Under the designed controllers, stochastic stabilization of the systems with actuator faults are achieved and the security of the systems can be guaranteed. Furthermore, the proposed results are extended to positive semi-Markovian jump systems with interval and polytopic uncertainties. By virtue of a segmentation technique of the transition rates, a less conservative security control design is also proposed. Finally, numerical examples are provided to demonstrate the validity of the presented results.

There is a growing body of research examining the effects of plyometric jump training (PJT) on repeated sprint ability (RSA) in athletes. However, available studies produced conflicting findings and the literature has not yet been systematically reviewed. Therefore, the effects of PJT on RSA indices remain unclear. To explore the effects of PJT on RSA in athletes. Searches for this review were conducted in four databases. We included studies that satisfied the following criteria: (1) examined the effects of a PJT exercise intervention on measures of RSA; (2) included athletes as study participants, with no restriction for sport practiced, age or sex; and (3) included a control group. The random-effects model was used for the meta-analyses. The methodological quality of the included studies was assessed using the PEDro checklist. From 6367 search records initially identified, 13 studies with a total of 16 training groups (n = 198) and 13 control groups (n = 158) were eligible for meta-analysis. There was a significant effect of PJT on RSA best sprint (ES = 0.75; p = 0.002) and RSA mean sprint (ES = 0.36; p = 0.045) performance. We did not find a significant difference between control and PJT for RSA fatigue resistance (ES = 0.16; p = 0.401). The included studies were classified as being of “moderate” or “high” methodological quality. Among the 13 included studies, none reported injury or any other adverse events. PJT improves RSA best and mean performance in athletes, while there were no significant differences between control and PJT for RSA fatigue resistance. Improvements in RSA in response to PJT are likely due to neuro-mechanical factors (e.g., strength, muscle activation and coordination) that affect actual sprint performance rather than the ability to recover between sprinting efforts.

In this paper, a simple two-agent multi-objective scheduling system for flexible job-shop scheduling problem is proposed and corresponding framework is given. Under the framework, a broadcast communication mechanism with task mark and leader–follower control mode are designed and used to ensure orderly activities among agents. To obtain initial solution and improve it, competition and cooperation strategies are developed. To jump out of the local optimal solution and expend the search space, an adaptive iterative loop solving mechanism is designed. Three commonly used benchmark instance sets are adopted to test the performance of the proposed method. Computation results and comparison analysis with other excellent algorithms demonstrate that it is feasible and effective.

The present study investigated the velocity distribution and attenuation characteristics of the F jump on a rough bed. The underflow velocity, maximum velocity, central velocity, and surface velocity were chosen as the velocity scales. The variations of velocity scales along the flow direction were similar and were insensitive to the relative roughness and bed slopes. Based on the roller length Lr, there were three cross-sections in the forward flow, which were x = 0.4Lr, x = Lr, and x = 1.6Lr. And the velocity variation rule changed before and after these cross-sections. Thus, the velocity distribution was divided into four parts by these cross-sections. The experimental results showed that the attenuation rate of velocity in the bottom half of the water was greater than that in the top half of the water. The attenuation of the maximum velocity um mainly occurred from x = 0 to x = Lr. The results also showed that the energy loss of the F jump on the rough bed was greater than that of the F jump on the smooth bed and the free jump on the rough horizontal bed.

The paper contains a study of weighted exponential inequalities for differentially subordinate martingales, under the assumption that the underlying weight satisfies Muckenhoupt’s condition$$A_{\infty }$$A∞. The proof exploits certain functions enjoying appropriate size conditions and concavity. The martingales are adapted, uniformly integrable, and càdlàg - we do not assume any path-continuity restrictions. Because of this generality, we need to handle jump parts of processes which forces us to construct a Bellman function satisfying a stronger condition than local concavity. As a corollary, we will establish some new weighted$$L^p$$Lpestimates for differential subordinates of bounded martingales.

In the present paper, we show the first-order definability of the jump operator in the upper semi-lattice of the $$\omega $$ -enumeration degrees. As a consequence, we derive the isomorphicity of the automorphism groups of the enumeration and the $$\omega $$ -enumeration degrees.

The $l_{2}-l_{\\infty }$ stabilization issue for discrete-time networked singularly perturbed semi-Markov jump systems under the observer-based scheme is investigated in this paper. For networked systems, the measurement outputs are quantized before transmission. Moreover, an improved protocol generalizing the traditional weighted try-once-discard protocol is established to further optimize the utilization of communication resources. In contrast to the previous stabilization analysis for discrete-time semi-Markov jump systems, a novel processing method is proposed, based on which the $l_{2}-l_{\\infty }$ performance analysis for the investigated systems can be achieved effectively. Furthermore, two new constraints relevant to the improved protocol are constructed to obtain less conservatism results. Via constructing a piecewise Lyapunov function related to both the semi-Markov process and the improved protocol information, sufficient conditions which ensure that the closed-loop system is $\\delta$-error mean-square stable with a prescribed performance property are developed. Ulteriorly, the observer parameters and the controller gains can be co-designed by solving a convex optimization problem. A concise example is finally employed to demonstrate the validity and potential of the proposed scheme.

This paper is concerned with the problem of mode dependent H∞ filter for uncertainty Markovian jump system with neutral delay and retarded time-varying delay. By using free weight matrix (FWM) technique, the stability conditions of delay dependent are obtained under the framework of Lyapunov stability theory. Based on those result, the delay dependent conditions for full order and mode dependent Markovian jump linear filters are gained, which are expressed by Linear matrix inequalities (LMIs). Finally, a numerical example and a PEEC practical example are employed to prove the validity of the results.

In this paper, we use a unified framework to study Poisson stable (including stationary, periodic, quasi-periodic, almost periodic, almost automorphic, Birkhoff recurrent, almost recurrent in the sense of Bebutov, Levitan almost periodic, pseudo-periodic, pseudo-recurrent and Poisson stable) solutions for semilinear stochastic differential equations driven by infinite dimensional Levy noise with large jumps. Under suitable conditions on drift, diffusion and jump coefficients, we prove that there exist solutions which inherit the Poisson stability of coefficients. Further we show that these solutions are globally asymptotically stable in square-mean sense. Finally, we illustrate our theoretical results by several examples.

This paper addresses the observer-based finite-time $$H_{\infty }$$ control problem for Takagi–Sugeno (T–S) fuzzy semi-Markovian jump systems with mode-dependent fast-varying delays, actuator faults, parameter uncertainties and partly uncertain transition rates. Firstly, a more general actuator fault model is considered and the fuzzy reliable observer-based control scheme is designed. By applying the new Lyapunov functional candidates, free-weighting matrix method and slack matrix variables, some negative integral terms can be adopted and the nonlinear terms caused by time delay and partly unknown transition rates can be dealt. Furthermore, novel sufficient conditions on guaranteeing the closed-loop system is stochastically finite-time bounded (SFTB) with the prescribed $$H_{\infty }$$ level are proposed. Particularly, different from traditional slowly varying delays, the case of mode-dependent fast-varying delays which are more difficult to be dealt is considered in this paper. Lastly, a practical example is exploited to affirm the validity of the obtained results.

Jump locomotion is the basic movement of human. However, no thorough research on the recognition of jump sub-phases has been carried so far. This paper aims to use multi-sensor information fusion and machine learning to recognize the human jump phase, which is crucial to the development of exoskeleton that assists jumping. The method of information fusion for sensors including sEMG, IMU, and footswitch sensor is studied. The footswitch signals are filtered by median filter. A processing method of synthesizing Euler angles into phase angle is proposed, which is beneficial to data integration. The jump locomotion is creatively segmented into five phases. The onset and offset of active segment are detected by sample entropy of sEMG and standard deviation of acceleration signal. The features are extracted from analysis windows using multi-sensor information fusion, and the dimension of feature matrix is selected. By comparing the performances of state-of-the-art machine learning classifiers, feature subsets of sEMG, IMU, and footswitch signals are selected from time domain features in a series of analysis window parameters. The average recognition accuracy of sEMG and IMU is 91.76% and 97.68%, respectively. When using the combination of sEMG, IMU, and footswitch signals, the average accuracy is 98.70%, which outperforms the combination of sEMG and IMU (97.97%, p 0.01). Graphical Abstract The sub-phases of human locomotion are recognized based on multi-sensor information fusion and machine learning method. The feature data of the sub-phases is visualized in 3-dimensional space. The predicted states and the true states in a complete jump are compared along the time axis.

In this paper, we consider vulnerable options with jump risk and liquidity risk. In the proposed framework, we allow discontinuous changes in the information processes and the liquidity discount factors as well, and default risk is taken into consideration. Specially, we investigate the effect of jumps in the liquidity discount factors and find that the effects of jumps in the liquidity discount factors are stable for different maturities and alternative moneynesses. Further, option prices behave differently with respect to alternative intensities of common jumps, depending on whether there are jumps in the liquidity discount factors or not.

Partially filled pipes have many applications in hydraulic and environmental engineering; such as sewer and storm water collection pipes and circular culverts. Hydraulic jump can lead to scouring at hydraulic structures and thus excess energy should be dissipated to prevent scour and erosion. Calculation of conjugate depths in circular pipes and culverts is important in hydraulic engineering. The conjugate flow depths are commonly used to estimate the length of the hydraulic jump and the energy loss in the jump. Available relationships to estimate the conjugate depths in circular pipes are not accurate and wide application range. In comparison to easily available numerical solutions, a closed-form solution is a function of all input independent variables; and thus the dependence of the conjugate depth on each input independent variable can be easily interpreted. This study presents explicit solutions for the conjugate depths (pre- and post-jump depths) in partially filled pipes. The proposed solutions are examined over a wide range of the Froude number and geometric conditions, providing satisfactory estimations when compared with the exact solution obtained from the specific force relation. If the prejump flow depth of the hydraulic jump is known, the postjump flow depth can be determined using the proposed solution with a maximum relative error less than 1.4%. Inversely, if postjump flow depth is known, the prejump flow depth can be determined with a maximum relative error less than 2.3%. The proposed direct solutions are general, accurate, simple, and useful for studying the partially filled circular open channels.

Isometric strength training (IST) with rapid non-sustained contraction (RIST) is effective in improving the ability to generate force rapidly. However, the neuromuscular adaptation of IST with sustained contraction (SIST) and RIST is not known. Therefore, the aim of the study was to compare the neuromuscular adaptations of RIST with SIST. Thirty-three national floorball players (23.9 ± 3.1 years old; 1.69 ± 0.08 m; 64.6 ± 11.1 kg) were recruited for this study. Pre- and post-test included countermovement jump (CMJ), 30-m sprint (TT30), isometric squat at 90° (ISqT90) and 120° (ISqT120) knee angles. They were randomly assigned to either control (Con) (n = 9), RIST (n = 12) or SIST (n = 12) group and performed 12 sessions of intervention training. All groups performed the same sets of exercises, but RIST and SIST had to perform ISqT with and without sustained contraction, respectively. Time × group effect for CMJ height (P = 0.01, ƞ p 2 = 0.25), peak force (PF) (P = 0.03, ƞ p 2 = 0.22) and rate of force development (RFD) (P = 0.02, ƞ p 2 = 0.22) obtained from ISqT120 were noted. A main effect for time was observed in CMJ height, PF obtained from ISqT90 and ISqT120, and RFD obtained from ISqT90 (P

We consider versions of the Metropolis algorithm which avoid the inefficiency of rejections. We first illustrate that a natural Uniform Selection algorithm might not converge to the correct distribution. We then analyse the use of Markov jump chains which avoid successive repetitions of the same state. After exploring the properties of jump chains, we show how they can exploit parallelism in computer hardware to produce more efficient samples. We apply our results to the Metropolis algorithm, to Parallel Tempering, to a Bayesian model, to a two-dimensional ferromagnetic 4 $$\times $$ 4 Ising model, and to a pseudo-marginal MCMC algorithm.

Nonsmooth dynamics algorithms have been widely used to solve the problems of frictional contact dynamics of multibody systems. The linear complementary problems (LCP) based algorithms have been proved to be very effective for the planar problems of frictional contact dynamics. For the spatial problems of frictional contact dynamics, however, the nonlinear complementary problems (NCP) based algorithms usually achieve more accurate results even though the LCP based algorithms can evaluate the friction force and the relative tangential velocity approximately. In this paper, a new computation methodology is proposed to simulate the nonsmooth spatial frictional contact dynamics of multibody systems. Without approximating the friction cone, the cone complementary problems (CCP) theory is used to describe the spatial frictional continuous contact problems such that the spatial friction force can be evaluated accurately. A prediction term is introduced to make the established CCP model be applicable to the cases at high sliding speed. To improve the convergence rate of Newton iterations, the velocity variation of the nonsmooth dynamics equations is decomposed into the smooth velocities and nonsmooth (jump) velocities. The smooth velocities are computed by using the generalized- $\mathbf{a}$ algorithm, and the nonsmooth velocities are integrated via the implicit Euler algorithm. The accelerated projected gradient descend (APGD) algorithm is used to solve the CCP. Finally, four numerical examples are given to validate the proposed computation methodology.

We prove that the parabolic Harnack inequality implies the existence of jump kernel for symmetric pure jump process. This allows us to remove a technical assumption on the jumping measure in the recent characterization of the parabolic Harnack inequality for pure jump processes by Chen, Kumagai and Wang. The key ingredients of our proof are the Levy system formula and estimates on the heat kernel.

This paper studies H∞ control of Markovian jump linear singularly perturbed systems (MJLSPSs). A sufficient condition in terms of linear matrix inequalities (LMIs), different from ones in previous existing works, is given for designing H∞ control to overcome the difficulties of solving either Riccati equations or nonlinear matrix inequalities. Then, the jump H∞ controller can be obtained effectively by solving the proposed LMIs. Furthermore, a method is developed for evaluating an allowable upper bound of the singular perturbation parameter, in which a prescribed H∞ performance is satisfied. Finally, two numerical examples are presented to illustrate the effectiveness of the proposed design methods.

In this paper we prove an analogue of the Koml\'os-Major-Tusn\'ady (KMT) embedding theorem for random walk bridges. The random bridges we consider are constructed through random walks with i.i.d jumps that are conditioned on the locations of their endpoints. We prove that such bridges can be strongly coupled to Brownian bridges of appropriate variance when the jumps are either continuous or integer valued under some mild technical assumptions on the jump distributions. Our arguments follow a similar dyadic scheme to KMT's original proof, but they require more refined estimates and stronger assumptions necessitated by the endpoint conditioning. In particular, our result does not follow from the KMT embedding theorem, which we illustrate via a counterexample., Comment: 59 pages, 1 figure. Fixed a few typos in v2

In this study we focus on characteristics of SBs that have not or hardly been investigated previously. We find that the choice of the awakening period in the selection of SBs has consequences for the measured citation patterns. Focusing on medical SBs we analyze patterns in the time-development of the citation impact of SBs; the influence of self-citations on the awakening process; and the occurrence of medical research fields to which the SBs and their citing papers belong. An important finding is that SBs are generally characterized by a sleep that becomes less and less deep instead of a permanent deep sleep. The sleeping period is followed by a phase-transition-like jump as a start of the awakening period and a remarkable regularity is found for the citation impact immediately before and after the jump.