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Experimental evaluation of multiscale damage evolution in fissured limestone under different wet–dry cycles and axial stress
Biomechanical analysis of Peking Opera hat-wing technique
Abstract The Peking Opera hat-wing technique is an intangible cultural heritage. This study adopted a single-subject case study design to characterize the movements of this technique, facilitating its intergenerational preservation and transmission. Biomechanical analysis was conducted to investigate the left-wing toss movement in the hat-wing technique, aiming to reveal the intrinsic biomechanical mechanism of the movement and provide a basis for its inheritance and training. An infrared motion capture system was used to collect kinematic parameters of the markers, and a three-dimensional force platform was employed to gather force data from the actor’s left and right feet. Three sets of data—including Center of Pressure (COP) position, head movement parameters, and knee joint angles—were analyzed to elucidate the operating mechanism of the left-wing toss movement. Based on the results, the left-wing toss movement was theoretically segmented, and the initiation principle of the movement was determined. Additionally, factors influencing the sustained movement of the left-wing toss and those required to achieve a relatively static state at the end of the movement were identified. The primary hypothesis was that the phase relationship between the L3 Z-axis displacement–time (L3 Z-T) curve and the head tilt angle–time (α-T) curve can effectively distinguish the initiation, maintenance, and termination stages of the left-wing toss movement. Quantitative analysis of five repeated trials showed high movement repeatability, with a coefficient of variation (CV) < 15% for all key kinematic metrics. Among them, the phase difference (CV = 6.0%) and peak angular velocity (CV = 10.6%) exhibited excellent repeatability (CV < 11%), and other indicators also met the repeatability requirements for single-subject case studies (CV < 15%). During the initiation stage, the peak head tilt angle reached 6° ± 0.8°, and the peak angular velocity was 29.3°/s ± 3.1°/s. Throughout the movement, the COP excursion in the anterior-posterior direction was 4.2 ± 0.5 cm, and the medial-lateral excursion was 2.1 ± 0.3 cm. These findings provide a scientific foundation for the standardized training and intergenerational preservation of the Peking Opera hat-wing technique, highlighting the value of biomechanical analysis in traditional performing arts heritage.
Two novel strains isolated from a brackish lake constitute Aeoliella fuhlenseeensis sp. nov. and Bythopirellula superficialaquae sp. nov. in the family Lacipirellulaceae
Abstract The strain collection of Heinz Schlesner (Kiel University, Germany) largely consists of budding bacteria collected from the 1980s to early 2000s. It still holds an untapped diversity of bacteria with uncommon morphologies and cell division modes. Here, we characterize two strains from his collection, SH292 T and SH678 T , that he isolated from Lake Fuhlensee, a slightly brackish lake in Northern Germany. Phylogenetic tree reconstruction places the novel strains in the family Lacipirellulaceae within the phylum Planctomycetota . More detailed analyses based on five phylogenetic markers suggest positions within the genera Aeoliella and Bythopirellula , respectively. The novel isolates have an aerobic and heterotrophic lifestyle and a mesophilic and neutrophilic growth profile. Optimal growth was observed at 25 °C and pH 7.0–7.5. Genome sequencing revealed slightly smaller genomes of 5.6–6.0 Mbp compared to those of the close relatives (6.1–7.8 Mbp). An analysis of genome-encoded features suggests differences in the portfolio of secondary metabolite-associated biosynthetic gene clusters and carbohydrate-active enzymes. Genomic and morphological differences support the results of the phylogenetic inferences that together delineate the novel strains from previously described species. Hence, we conclude that the two novel isolates belong to two novel species, for which we introduce the names Aeoliella fuhlenseeensis sp. nov. and Bythopirellula superficialaquae sp. nov. The novel taxa are represented by strains SH292 T (= DSM 116587 T = KCTC 102092 T ) and SH678 T (= DSM 116729 T = KCTC 102079 T ) as the corresponding type strains.
Multiple independent origins of neoteny reveal convergent relaxation of mitochondrial selection in beetles
Crop-weed classification using deep learning: a comparative study of CNNs, vision transformers, and interpretable models
Digital orientation enables disruptive technological innovation in agricultural technology enterprises
The effect of multimodal sensory stimulation on physiological parameters and consciousness levels in ICU-admitted traumatic brain injury patients: a clinical trial design
Effect of Al₂O₃ nanoparticle reinforcement and annealing on PMMA composite performance for prosthetic feet
The leg-swing interface: a novel approach to seated VR locomotion with balanced immersion and physical load
Anion-engineered CsInTiS₄₋ₓOₓ (x = 0.8) quantum dots for enhanced nonlinear photonics and optoelectronics
Classification of functional movement screening scores and reported fall-incident history from deep squat videos among logistics service workers using deep learning
E3 ubiquitin ligase RNF11 protects against liver ischemia reperfusion injury through HINT1 degradation-mediated PI3K/AKT activation
Dynamic multi-period optimal power flow considering renewable energy degradation and temperature derating
Abstract Renewable energy sources, such as solar and wind, play vital role in reducing emissions of carbon dioxide and combating climate change. However, their stochastic behavior has an impact on modern electric networks. Hence, Modelling variability and uncertainty in optimal power flow (OPF) concerns is critical for ensuring dependable and environmentally friendly grid operations. This study investigates the impact of climate change on the integration of wind and solar energy into power systems, with a specific focus on how temperature variations affect the performance and optimal dispatch of wind turbines and solar photovoltaic (PV) systems. To minimize total costs and carbon emissions, both single-objective and multi-objective optimization problems are developed, incorporating temperature-dependent de-rating effects on PV modules and wind turbines. Mayfly algorithm (MA) is applied to the IEEE-30 bus system for Optimal Power Flow (OPF), achieving a 0.6% and 0.5% reduction in fuel cost and carbon emissions compared to PSO and further techniques in single-objective OPF. The study extends to Stochastic OPF (SOPF) on a modified IEEE-30 system with two wind farms and one PV plant. Where, temperature-dependent models are used for both wind energy and solar energy. To additionally encourage and increase the reliance on renewable energy, Carbon credit concept is added to the total cost objective function as novel contribution. The results show that when the carbon credit is taken into account the total cost is reduced by 0.8% compared to the case when it is not considered. To assess the climate change impact, it is found that at 40 °C, the total cost and emissions increase by 21% and 45.67% respectively when minimizing cost, and by 9.67% and 45.7% when minimizing emissions. The multi-period analysis evaluates the evolution of renewable penetration over the 25-year lifetime by considering the gradual reduction in renewable output caused by annual degradation and temperature-related derating. The renewable penetration limits are therefore updated across the planning period to reflect the reduced contribution of PV and wind generation over time. where, this impact is on total cost and carbon emissions over 25-year lifetime through both single and multi-objective dynamic Multi-Period SOPF (MPOPF) problem. For single-objective MPSOPF problem, after 25 years, the results at 40 °C show that the total cost and emissions increase by 24.96% and 51.8% respectively when minimizing the total cost compared to the results obtained at the beginning of wind and solar plants operation. Moreover, Multi-Objective SOPF is solved, a fuzzy-based Pareto front is used, the outcomes show that when the ambient temperature rises to 40 °C, the compromise solution shows an increase of 16.65% total cost and 41.87% carbon emission respectively. For Multi-Objective MPSOPF problem, at 40 °C, the compromise solution shows a 20.16% cost and 60.1% emission increase after 25 years compared to the case when the temperature rise and degradation effect are not taken into account. The findings reveal that climate change and degradation adversely affect renewable energy integration, resulting in increased reliance on thermal power and emphasizing the need for informed planning of sustainable energy infrastructures and re-powering the renewable energy resources at the end of their lifetime.
Integrated XRD–SEM–EDS characterization of Al₂O₃ nano-enhanced engine oil and its influence on surface preservation of diesel engine cylinder liners
Deciphering Genetic control of grain quality, zinc, and iron content in rice using six-parameter generation mean analysis
Explainable machine learning identifies small high-performance gene signatures from full transcriptomes in human liver preservation cohorts
An intelligent wearable insole system for machine learning-based detection of high-risk postures in static symmetrical load-lifting tasks
Hyperchaotic fractional-order image encryption with Knight’s tour scrambling for satellite imagery
Abstract Secure dissemination of high-resolution satellite imagery remains challenging because many image-tailored ciphers either (i) emphasize permutation-heavy designs without sufficiently strong, plaintext-adaptive nonlinearity, or (ii) provide strong security metrics but fall short on scalable, near-real-time performance and robustness assessment under realistic channel impairments. To address these gaps, this work proposes a three-stage chaos-chess hybrid encryption pipeline for color satellite images that couples fractional-order hyperchaotic key generation with lightweight algebraic mixing, dynamic substitution, and structured bit-level diffusion. First, multiple images are optionally augmented and each RGB channel is partitioned into $$2\times 2$$ pixel matrices that are mixed via invertible matrices derived from a 6D fractional-order hyperchaotic Vaidyanathan system, providing efficient confusion suitable for parallelization. Second, plaintext-sensitive S-boxes are constructed online from a 4D fractional-order hyperchaotic system and applied per channel to enhance nonlinearity and satisfy stringent criteria (NL $$=108$$ , SAC $$\approx 0.5$$ , low LAP and DAP). Third, the resulting bit-streams are diffused by traversing $$8\times 8$$ blocks using Knight’s Tour paths and XORing with 4D hyperchaotic key-streams to amplify avalanche propagation. Experiments on satellite and natural images demonstrate high ciphertext randomness (entropy $$\approx 7.999$$ ), strong differential resistance (NPCR $$\approx 99.62\%$$ , UACI $$\approx 30.95\%$$ ), near-zero adjacent-pixel correlation (PCC $$\approx 0$$ ), and a large key space ( $$>2^{3827}$$ ), while measured runtimes indicate suitability for real-time or near-real-time operation. Noise-like ciphertexts and lossless recovery are verified via visual, histogram, and DFT analyses, and robustness under occlusion and noise attacks (salt-and-pepper, Gaussian) is evidenced. The resulting modular design provides a scalable pathway for protecting remote sensing data and supports future integration with ROI-aware processing and hardware acceleration.
An integrated SWOT-AHP strategic positioning framework for assessing sustainable forest wellness tourism development in mountain regions
Abstract Forest wellness tourism is an emerging form of nature-based tourism that leverages forest ecosystem services for health promotion while contributing to regional sustainable development. Although the integration of Strengths–Weaknesses–Opportunities–Threats (SWOT) analysis and the Analytic Hierarchy Process (AHP) has been applied in tourism planning, their combination with quantitative strategic positioning remains underexplored in the context of forest wellness tourism development in emerging economy mountain regions. This study applies an integrated SWOT-AHP strategic positioning framework to assess the sustainable development of forest wellness tourism in Shangluo City, Qinling Mountains, China. Through multi-round Delphi consultation (n = 46 for factor identification; n = 28 for AHP pairwise comparisons), 18 factors were identified across four SWOT dimensions. AHP weighting revealed that the Strengths dimension received the highest overall weight (dimension weight = 0.3652), with ecological resource quality ranking as the highest-weighted individual factor (composite weight = 0.1175), followed by policy support frameworks (0.0985) and traditional wellness culture (0.0871). Infrastructure deficits constituted the most prominent weakness (composite weight = 0.0647, representing 53.96% of total Weaknesses weight). Four-quadrant strategic positioning yielded coordinates P(0.2454, 0.1706), an intensity coefficient ρ = 0.2989, and an azimuth angle θ = 34.82°, placing Shangluo in Quadrant I (Strengths–Opportunities) and suggesting a competitive strategy that leverages internal advantages to capitalise on external opportunities. Sensitivity analysis confirmed the robustness of this positioning across all tested scenarios (ρ ranging from 0.2632 to 0.3489; Quadrant I maintained throughout). All findings should be interpreted as expert-perceived strategic priorities derived from structured expert judgment, rather than as objectively verified empirical outcomes of actual tourism demand, ecological measurement, or economic impact assessment.The findings provide case-based insights into how ecological resource endowment and institutional capacity are perceived by domain experts to jointly shape tourism development priorities in China’s western mountain regions, and illustrate one contextually grounded approach to reconciling economic development with ecological conservation in comparable mountain destination contexts.