This paper presents a compliant variable admittance adaptive fixed-time sliding mode control (SMC) algorithm for trajectory tracking of robotic manipulators. Specifically, a compliant variable admittance algorithm and an adaptive fixed-time SMC algorithm are combined to construct a double-loop control structure. In the outer loop, the variable admittance algorithm is developed to adjust admittance parameters during a collision to minimize the collision time, which gives the robot compliance property and reduce the rigid collision influence. Then, by employing the Lyapunov theory and the fixed-time stability theory, a new nonsingular sliding mode manifold is proposed and an adaptive fixed-time SMC algorithm is presented in the inner loop. More precisely, this approach enables rapid convergence, enhanced steady-state tracking precision, and a settling time that is independent of system initial states. As a result, the effectiveness and improved performance of the proposed algorithm are demonstrated through extensive simulations and experimental results.

The current LiDAR-inertial odometry is prone to cumulative Z-axis error when it runs for a long time. This error can easily lead to the failure to detect the loop-closing in the correct scenario. In this paper, a ground-constrained LiDAR-inertial SLAM is proposed to solve this problem. Reasonable constraints on the ground motion of the mobile robot are incorporated to limit the Z-axis drift error. At the same time, considering the influence of initial positioning error on navigation, a keyframe selection strategy is designed to effectively improve the flatness and accuracy of positioning and the efficiency of loop detection. If GNSS is available, the GNSS factor is added to eliminate the cumulative error of the trajectory. Finally, a large number of experiments are carried out on the self-developed robot platform to verify the effectiveness of the algorithm. The results show that this method can effectively improve location accuracy in outdoor environments, especially in environments of feature degradation and large scale.

It is proved that Tutte’s $3$-flow conjecture is true for Cayley graphs on groups of order $8p$ where p is an odd prime.

Wind derivatives are financial instruments designed to mitigate losses caused by adverse wind conditions. With the rapid growth of wind power capacity due to efforts to reduce carbon emissions, the demand for wind derivatives to manage uncertainty in wind power production is expected to increase. However, existing wind derivative literature often assumes normally distributed wind speed, despite the presence of skewness and leptokurtosis in historical wind speed data. This paper investigates how the misspecification of wind speed models affects wind derivative prices and proposes the use of the generalized hyperbolic distribution to account for non-normality. The study develops risk-neutral approaches for pricing wind derivatives using the conditional Esscher transform, which can accommodate stochastic processes with any distribution, provided the moment-generating function exists. The analysis demonstrates that model risk varies depending on the choice of the underlying index and the derivative’s payoff structure. Therefore, caution should be exercised when choosing wind speed models. Essentially, model risk cannot be ignored in pricing wind speed derivatives.

In multi-population mortality modeling, autoregressive moving average (ARMA) processes are typically used to model the evolution of mortality differentials between different populations over time. While such processes capture only short-term serial dependence, it is found in our empirical work that mortality differentials often exhibit statistically significant long-term serial dependence, suggesting the necessity for using long memory processes instead. In this paper, we model mortality differentials between different populations with long memory processes, while preserving coherence in the resulting mortality forecasts. Our results indicate that if the dynamics of mortality differentials are modeled by long memory processes, mean reversion would be much slower, and forecast uncertainty over the long run would be higher. These results imply that the true level of population basis risk in index-based longevity hedges may be larger than what we would expect when ARMA processes are assumed. We also study how index-based longevity hedges should be calibrated if mortality differentials follow long memory processes. It is found that delta hedges are more robust than variance-minimizing hedges, in the sense that the former remains effective even if the true processes for mortality differentials are long memory ones.

Natural oscillations of sessile drops with a free or pinned contact line in different gravity environments are studied based on a linear inviscid irrotational theory. The inviscid Navier–Stokes equations and boundary conditions are reduced to a functional eigenvalue problem by the normal-mode decomposition. We develop a boundary element method model to numerically solve the eigenvalue problem for predicting the natural frequencies. Emphasis is placed on the frequency shifts of modes due to gravity for a wide range of contact angles $\alpha$ and Bond numbers $Bo$. Three types of $\alpha$–$Bo$ diagrams reflecting how gravity shifts the frequency are identified. Specifically, the frequency of zonal modes shifts downwards (upwards) when $\alpha$ is smaller (larger) than a critical value, while the frequencies of most sectoral modes are shifted downwards regardless of $\alpha$. As a result, gravity can transform the lowest mode from a zonal mode to a sectoral mode. The spectral degeneracy of hemispherical drops inherited from the Rayleigh–Lamb spectrum is also broken by gravity. However, we discover that gravity has no effect on the mode associated with the horizontal motion of the centre of mass, whose frequency is always zero regardless of $\alpha$ and $Bo$. This implies that the ‘walking’ drop instability reported in previous literature does not exist.

In this study, the length scaling for the boundary layer separation induced by two incident shock waves is experimentally and analytically investigated. The experiments are performed in a Mach 2.73 flow. A double-wedge shock generator with two deflection angles ($\alpha _1$ and $\alpha _2$) is employed to generate two incident shock waves. Two deflection angle combinations with an identical total deflection angle are adopted: ($\alpha _1 = 7^\circ$, $\alpha _2 = 5^\circ$) and ($\alpha _1 = 5^\circ$, $\alpha _2 = 7^\circ$). For each deflection angle combination, the flow features of the dual-incident shock wave–turbulent boundary layer interactions (dual-ISWTBLIs) under five shock wave distance conditions are examined via schlieren photography, wall-pressure measurements and surface oil-flow visualisation. The experimental results show that the separation point moves downstream with increasing shock wave distance ($d$). For the dual-ISWTBLIs exhibiting a coupling separation state, the upstream interaction length ($L_{int}$) of the separation region approximately linearly decreases with increasing $d$, and the decrease rate of $L_{int}$ with $d$ increases with the second deflection angle under the condition of an identical total deflection angle. Based on control volume analysis of mass and momentum conservations, the relation between $L_{int}$ and $d$ is analytically determined to be approximately linear for the dual-ISWTBLIs with a coupling separation region, and the slope of the linear relation obtained analytically agrees well with that obtained experimentally. Furthermore, a prediction method for $L_{int}$ of the dual-ISWTBLIs with a coupling separation region is proposed, and the relative error of the predicted $L_{int}$ in comparison with the experimental result is $\sim$10 %.

There has been a growing interest among pension plan sponsors in envisioning how the mortality experience of their active and deferred members may turn out to be if a pandemic similar to the COVID-19 occurs in the future. To address their needs, we propose in this paper a stochastic model for simulating future mortality scenarios with COVID-alike effects. The proposed model encompasses three parameter levels. The first level includes parameters that capture the long-term pattern of mortality, whereas the second level contains parameters that gauge the excess age-specific mortality due to COVID-19. Parameters in the first and second levels are estimated using penalised quasi-likelihood maximisation method which was proposed for generalised linear mixed models. Finally, the third level includes parameters that draw on expert opinions concerning, for example, how likely a COVID-alike pandemic will occur in the future. We illustrate our proposed model with data from the United States and a range of expert opinions.

Mortality volatility is crucially important to many aspects of index-based longevity hedging, including instrument pricing, hedge calibration and hedge performance evaluation. This paper sets out to develop a deeper understanding of mortality volatility and its implications on index-based longevity hedging. First, we study the potential asymmetry in mortality volatility by considering a wide range of generalised autoregressive conditional heteroskedasticity (GARCH)-type models that permit the volatility of mortality improvement to respond differently to positive and negative mortality shocks. We then investigate how the asymmetry of mortality volatility may impact index-based longevity hedging solutions by developing an extended longevity Greeks framework, which encompasses longevity Greeks for a wider range of GARCH-type models, an improved version of longevity vega, and a new longevity Greek known as “dynamic Delta”. Our theoretical work is complemented by two real-data illustrations, the results of which suggest that the effectiveness of an index-based longevity hedge could be significantly impaired if the asymmetry in mortality volatility is not taken into account when the hedge is calibrated.

A free standing 2D PS colloidal crystal with Au nanoshells/hydrogel composite film (CAuHCF) was fabricated by embedding a 2D PS colloidal crystal with Au nanoshells into a polyacrylic acid (PAA) hydrogel film. This CAuHCF can act as a visualized sensor with high diffraction intensity. The 2D PS colloidal crystal with Au nanoshells was prepared by depositing an Au layer on PS colloidal crystal obtained by interfacial self-assembly. The diffraction intensity of the CAuHCF was increased by about 30-fold than that of traditional 2D PS colloidal crystal/hydrogel composite film on transparent substrate due to large scattering cross section of Au shell. Such sensors based Au nanoshells array with the simple preparation process and the strong diffraction signal are promising ones for practical applications in visual detection. Additionally, with the simple preparation process and high diffraction intensity, other visualized sensors based different hydrogel matrix and the 2D PS colloidal crystal with Au nanoshells could be synthesized for monitoring various analysts.

Graphene nanoribbons as a quasi-one-dimensional form of graphene has attracted intensive attention in energy related devices. Upon oxidation and cutting of multiwall carbon nanotubes (MWCNTs), highly dispersive graphene oxide nanoribbons (GONRs) were obtained, on which Zn2+ and Sn4+ can be homogenously deposited. The reduced graphene oxide nanoribbons (rGONRs)/Zn2SnO4 composite with a homogeneous distribution of nanoparticles on the nanoribbons have been prepared through facile in situ chemical co-reduction process. It is worth noting that the size of Zn2SnO4 particles tightly dispersed on rGONRs is about 15 nm. Benefit from the introduction of rGONRs, the specific surface area and electrode conductivity of rGONRs/Zn2SnO4 can both be effectively enhanced. The as-prepared rGONRs/Zn2SnO4 as anode material for lithium-ion batteries displays desirable electrochemical performance (727.2 mA h/g after 50 cycles at the current density of 100 mA/g), which is mainly attributed to the uniformly distributed Zn2SnO4 nanoparticles and the immobilizing and conducting effects of rGONRs.

A 100-J-level Nd:glass laser system in nanosecond-scale pulse width has been constructed to perform as a standard source of high-fluence-laser science experiments. The laser system, operating with typical pulse durations of 3–5 ns and beam diameter 60 mm, employs a sequence of successive rod amplifiers to achieve 100-J-level energy at 1053 nm at 3 ns. The frequency conversion can provide energy of 50-J level at 351 nm. In addition to the high stability of the energy output, the most valuable of the laser system is the high spatiotemporal beam quality of the output, which contains the uniform square pulse waveform, the uniform flat-top spatial fluence distribution and the uniform flat-top wavefront.

Integrating theories of psychological ownership and stewardship, and taking a relational perspective, we examine key antecedents and outcomes of professional managers' psychological ownership in Chinese owner-managed family businesses. We tested the model using a survey of 166 Chinese professional managers (one from each of 166 family businesses). We find that owner–manager relationship closeness at work mediates the effect of both the owner's benevolent leadership and owner–manager friendship ties on the manager's psychological ownership. Psychological ownership, in turn, is positively related to the manager's intention to stay and to stewardship behaviour. Theoretical and practical implications are discussed.

Cloud Computing has become a well-known primitive nowadays; many researchers and companies are embracing this fascinating technology with feverish haste. In the meantime, security and privacy challenges are brought forward while the number of cloud storage user increases expeditiously. In this work, we conduct an in-depth survey on recent research activities of cloud storage security in association with cloud computing. After an overview of the cloud storage system and its security problem, we focus on the key security requirement triad, i.e., data integrity, data confidentiality, and availability. For each of the three security objectives, we discuss the new unique challenges faced by the cloud storage services, summarize key issues discussed in the current literature, examine, and compare the existing and emerging approaches proposed to meet those new challenges, and point out possible extensions and futuristic research opportunities. The goal of our paper is to provide a state-of-the-art knowledge to new researchers who would like to join this exciting new field.