Scalable Multiuser Immersive Communications with Multi-numerology and Mini-slot

This paper studies multiuser immersive communications networks in which different user equipment may demand various extended reality (XR) services. In such heterogeneous networks, time-frequency resource allocation needs to be more adaptive since XR services are usually multi-modal and latency-sensitive. To this end, we develop a scalable time-frequency resource allocation method based on multi-numerology and mini-slot. To appropriately determining the discrete parameters of multi-numerology and mini-slot for multiuser immersive communications, the proposed method first presents a novel flexible time-frequency resource block configuration, then it leverages the deep reinforcement learning to maximize the total quality-of-experience (QoE) under different users' QoE constraints. The results confirm the efficiency and scalability of the proposed time-frequency resource allocation method

Multi-objective optimization design for a 15 MW semisubmersible floating offshore wind turbine using evolutionary algorithm

This paper introduces a framework designed to optimize the structural design of a 15 MW floating offshore wind turbine (FOWT) with a focus on cost-efficiency. The proposed framework employs a multi-objective evolutionary algorithm, integrating frequency domain (FD) simulations with equilibrium analysis to assess the response attributes of the floating platform and its mooring system. The objective function of the optimization includes the steel structural mass of the floating platform, the pitch heel angle, and the motion response amplitude operator (RAO) peak as determined by the FD simulation. Constraints pertinent to these objective functions, alongside the safety of the mooring system and the dynamic response and parameter settings of the FOWT, are meticulously enforced. The resulting optimized designs exhibit substantial improvements in the steel structural mass and pitch heel angle when contrasted with the initial design parameters. The practicality of this optimization framework is corroborated through time domain (TD) simulations, which elucidate the effects of the pitch heel angle and motion RAO peaks on the time domain response of the optimized structures. These insights offer reference for the future optimization of floating platforms and mooring systems in the realm of offshore wind energy

Effects of 8-Year Nitrogen and Phosphorus Treatments on the Ecophysiological Traits of Two Key Species on Tibetan Plateau

Understanding how nitrogen (N) and/or phosphorus (P) addition affects plants carbon- and water- related ecophysiological characteristics is essential for predicting the global change impact on the alpine meadow ecosystem structure and function in carbon and water cycling. The Qinghai-Tibetan Plateau (QTP) with the largest alpine meadow in the world is regarded as the third pole in the earth and has been experiencing increased atmospheric N deposition. In this project, we focused on two key species (Elymus dahuricus and Gentiana straminea) of the alpine meadow on the Tibetan Plateau and investigated the variability of photosynthetic and stomatal responses to 8-year N and/or P treatments through field measurements and modeling. We measured photosynthesis- and gs-response curves to generate parameter estimates from individual leaves with two widely used stomatal models (the BWB model and MED model) for validation of growth and ecosystem models and to elucidate the physiological basis for observed differences in productivity and WUE. We assessed WUE by means of gas exchange measurements (WUEi) and stable carbon isotope composition (Δ13C) to get the intrinsic and integrated estimates of WUE of the two species. P and N+P treatments, but not N, improved the photosynthetic capacity (Anet and Vcmax) for both species. Stomatal functions including instaneous measurements of stomatal conductance, intrinsic water-use efficiency and stomatal slope parameters of the two widely used stomatal models were altered by the addition of P or N+P treatment, but the impact varied across years and species. The inconsistent responses across species suggest that an understanding of photosynthetic, stomatal functions and water-use should be evaluated on species separately. WUE estimated by Δ13C values had a positive relationship with Anet and gs and a negative relationship with WUEi. Our findings should be useful for understanding the underlying mechanisms of the response of alpine plants growth and alpine meadow ecosystem to global change

A Finite Queue Model Analysis of PMRC-based Wireless Sensor networks

In our previous work, a highly scalable and fault- tolerant network architecture, the Progressive Multi-hop Rotational Clustered (PMRC) structure, is proposed for constructing large-scale wireless sensor networks. Further, the overlapped scheme is proposed to solve the bottleneck problem in PMRC-based sensor networks. As buffer space is often scarce in sensor nodes, in this paper, we focus on studying the queuing performance of cluster heads in PMRC-based sensor networks. We develop a finite queuing model to analyze the queuing performance of cluster heads for both non-overlapped and overlapped PMRC-based sensor network. The average queue length and average queue delay of cluster head in different layers are derived. To validate the analysis results, simulations have been conducted with different loads for both non- overlapped and overlapped PMRC-based sensor networks. Simulation results match with the analysis results in general and confirm the advantage of selecting two cluster heads over selecting single cluster head in terms of the improved queuing performance

Macro-mesoscopic perspective damage characteristics and energy-damage constitutive model of coal-rock composite structures subjected to cyclic loading

During deep coal mining processes, periodic mining disturbances cause the neighboring coal strata to bear the effects of cyclic loading and unloading, making it essential to study the mechanical responses and macro-micro failure characteristics of the coal-rock composite structures under different cyclic loads. In this study, three different loading rates were selected to perform uniaxial cyclic compression tests (with simultaneous acoustic emission signal measurement) under two types of cyclic loads, investigating the damage characteristics of coal-rock composites. Based on the principle of energy dissipation, an energy-damage constitutive model for the cyclic loading of composites was constructed and validated with experimental data. The results indicate that the loading rate is directly proportional to the peak strength of the composite specimen, where the peak stress increased by 22.44% and 28.89% for the gradual cyclic loading and unloading path (path I) and the cyclic loading and unloading path (Path II) respectively. The higher the loading rate, the faster the internal crack extension in the specimen, the crushing degree of the coal component in the coal-rock composite specimen is intensified, and the fractal dimension increases subsequently, and the faster the internal crack extension in the specimen becomes. With the increase of the loading rate, the damage along the matrix in the coal fraction increases. The paths with a large span of cyclic gradation (Path I) contribute to stress transfer within the specimen and provide favorable conditions for the development of cracks within the specimen, leading to a higher degree of damage in the corresponding specimen. The consistency between the test curves and the energy-damage constitutive model curves is relatively high, indicating that the proposed energy-damage constitutive model can well describe the deformation behavior of the coal-rock composite specimens during cyclic loading and unloading processes

Conserved MicroRNA Act Boldly During Sprout Development and Quality Formation in Pingyang Tezaocha (Camellia sinensis)

Tea tree [Camellia sinensis (L.) O. Kuntze] is an important leaf (sometimes tender stem)-using commercial plant with many medicinal uses. The development of newly sprouts would directly affect the yield and quality of tea product, especially significant for Pingyang Tezaocha (PYTZ) which takes up a large percent in the early spring tea market. MicroRNA (miRNA), particularly the conserved miRNAs, often position in the center of subtle and complex gene regulatory systems, precisely control the biological processes together with other factors in a spatio-temporal pattern. Here, quality-determined metabolites catechins, theanine and caffeine in PYTZ sprouts including buds (sBud), different development stages of leaves (sL1, sL2) and stems (sS1, sS2) were quantified. A total of 15 miRNA libraries of the same tissue with three repetitions for each were constructed to explore vital miRNAs during the biological processes of development and quality formation. We analyzed the whole miRNA profiles during the sprout development and defined conserved miRNA families in the tea plant. The differentially expressed miRNAs related to the expression profiles buds, leaves, and stems development stages were described. Twenty one miRNAs and eight miRNA-TF pairs that most likely to participate in regulating development, and at least two miRNA-TF-metabolite triplets that participate in both development and quality formation had been filtered. Our results indicated that conserved miRNA act boldly during important biological processes, they are (i) more likely to be linked with morphological function in primary metabolism during sprout development, and (ii) hold an important position in secondary metabolism during quality formation in tea plant, also (iii) coordinate with transcription factors in forming networks of complex multicellular organism regulation

Varying performance of eight evapotranspiration products with aridity and vegetation greenness across the globe

The wide application of the evapotranspiration (ET) products has deepened our understanding of the water, energy and carbon cycles, driving increased interest in regional and global assessments of their performance. However, evaluating ET products at a global scale with varying levels of dryness and vegetation greenness poses challenges due to a relative lack of reference data and potential water imbalance. Here, we evaluated the performance of eight state-of-the-art ET products derived from remote sensing, Land Surface Models, and machine learning methods. Specifically, we assessed their ability to capture ET magnitude, variability, and trend, using 1,381 global watershed water balance ET as a baseline. Furthermore, we created aridity and vegetation categories to investigate performance differences among products under varying environmental conditions. Our results demonstrate that the spatial and temporal performances of the ET products were strongly affected by aridity and vegetation greenness. The poorer performances, such as underestimation of interannual variability and misjudged trend, tend to occur in abundant humidity and vegetation. Our findings emphasize the significance of considering aridity and vegetation greenness into ET product generation, especially in the context of ongoing global warming and greening. Which hopefully will contribute to the directional optimizations and effective applications of ET simulations