This paper demonstrates the validity of the Naess–Gadai method for extrapolating extreme value statistics of second-order Volterra series processes through application on a representative model of a deep water small size tension leg platform (TLP), with specific focus on wave sum frequency effects affecting restrained modes: heave, roll and pitch. The wave loading was estimated from a second order diffraction code WAMIT, and the stochastic TLP structural response in a random sea state was calculated exactly using Volterra series representation of the TLP corner vertical displacement, chosen as a response process. Although the wave loading was assumed to be a second order (non-linear) process, the dynamic system was modelled as a linear damped mass-spring system. Next, the mean up-crossing rate based extrapolation method (Naess–Gaidai method) was applied to calculate response levels at low probability levels. Since exact solution was available via Volterra series representation, both predictions were compared in this study, namely the exact Volterra and the approximate one. The latter gave a consistent way to estimate efficiency and accuracy of Naess–Gaidai extrapolation method. Therefore the main goal of this study was to validate Naess–Gaidai extrapolation method by available analytical-based exact solution. Moreover, this paper highlights limitations of mean up-crossing rate based extrapolation methods for the case of narrow band effects, such as clustering, typically included in the springing type of response.

An 86-day growth trial was conducted to investigate the effect of dietary oxidized fish oil on the growth and cytopathology of juvenile channel catfish (Ictalurus punctatus). Four diets containing 0 g kg À1 (control: fresh fish oil), 30 g kg À1 (low-oxidized oil group), 60 g kg À1 (medium-oxidized oil group) and 90 g kg À1 (high-oxidized oil group) graded oxidized oil levels with the same dietary lipid level (90 g kg À1 diet) were evaluated. The results show that the specific growth rate decreased with increasing dietary oxidized oil level (P < 0.05). All examined liver and kidney tissues in all dose groups exhibited what appeared as dosedependent cellular modifications. In addition, lipid droplet accumulation in the hepatocytes of fish in all dose groups was increased, and their localizations were distinctly different between all dose groups. The ultrastructural changes suggest the progression of mitochondrial vacuolation, especially in the renal tubules, in all dose groups. These results reveal a previously underappreciated effect of dietary oxidized fish oil on channel catfish kidneys. Overall, a series of nutriphysiological responses were adversely affected by exposure to dietary oxidized fish oil, and the corresponding interference patterns on the metabolism and transport of nutrients within cells were observed.

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Existing wireless charging methods for one-dimensional space are not suitable for coal mine roadways due to the crowding problem of mobile chargers (MCs). To solve this problem, we propose a novel method called distributed cooperative wireless charging, in which a coal mine roadway segment is divided into sections, and each MC is responsible for charging the nodes in its own section. From time t = (K − 1/2)T , all the MCs of a segment start to work simultaneously, where K is the number of sections and T is the charging cycle. When the steady state is reached, distributed cooperative wireless charging is the fastest method to finish a round of charging. To guarantee the practicality of the algorithm, we also provide the method to determine the MC battery capacities and the roadway section lengths. The numerical simulations indicate that the proposed algorithm provides better charging efficiency than the existing onedimensional charging methods in coal mine roadways.INDEX TERMS Mine Internet of Things, cooperative wireless charging, mobile charger, energy usage effectiveness, coal mine roadway.

Accurate target localization technology plays a very important role in ensuring mine safety production and higher production efficiency. The localization accuracy of a mine localization system is influenced by many factors. The most significant factor is the non-line of sight (NLOS) propagation error of the localization signal between the access point (AP) and the target node (Tag). In order to improve positioning accuracy, the NLOS error must be suppressed by an optimization algorithm. However, the traditional optimization algorithms are complex and exhibit poor optimization performance. To solve this problem, this paper proposes a new method for mine time of arrival (TOA) localization based on the idea of comprehensive optimization. The proposed method utilizes particle filtering to reduce the TOA data error, and the positioning results are further optimized with fingerprinting based on the Manhattan distance. This proposed method combines the advantages of particle filtering and fingerprinting localization. It reduces algorithm complexity and has better error suppression performance. The experimental results demonstrate that, as compared to the symmetric double-sided two-way ranging (SDS-TWR) method or received signal strength indication (RSSI) based fingerprinting method, the proposed method has a significantly improved localization performance, and the environment adaptability is enhanced.

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It is of great importance to power the nodes of the rechargeable wireless sensor network to detect events continuously in the area of interest. This paper proposes a joint data transmission and on‐demand charging algorithm based on the space correlation. The new algorithm optimises the event detection, data forwarding and node charging jointly to improve the charging efficiency. First, the active nodes participating in the event detection are selected using an improved iterative node selection method to reduce the number of nodes working concurrently. Then, the greedy data transmission scheme based on grid partition is proposed to transmit the observed data to the sink node. Finally, the nodes in the networks are charged using the on‐demand charging method based on grid partition, which greatly decreases the charging frequency and energy loss of the mobile charger. The simulation results demonstrate that the proposed method has superior performance in the distance travelled by the mobile charger, the energy utilisation, the average energy consumption of the mobile charger and the node charging latency.

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