Search Results (2,649)

The control of a biped robot is a challenging task due to the hard-to-stabilize dynamics. Generating a suitable walking reference trajectory is a key aspect of this problem. This article proposes a novel method of generating walking patterns for biped robots. The method integrates the double support phase and the single support phase into one step, and uses this step as the unit for trajectory generation through quadratic optimization with terminal constraints based on the Linear Inverted Pendulum Model, enabling us to shorten the optimization horizon while still generating natural walking trajectories. Moreover, by restricting the position and acceleration of the center of mass (COM) in the vertical direction, an excessive constraint is formed on the Zero Moment Point (ZMP) to offset the nonlinear effects of the COM’s vertical motion on the ZMP. This allows the COM of the robot to change in the vertical direction while maintaining the linearity of the optimization problem. Finally, the performance of the proposed method is validated by simulations and experiments of walking on flat ground and stairs using a position-controlled biped robot, Neubot. Full article

The continuous evolution of advanced wireless IoT systems necessitates novel network protocols capable of enhancing resource efficiency and performance to support increasingly demanding applications. Full-duplex (FD) communication emerges as a key advanced wireless technology to address these needs by doubling spectral efficiency. However, unlocking this potential is non-trivial, as it introduces complex interference scenarios and requires sophisticated management of heterogeneous Quality of Service (QoS) demands, presenting a significant challenge for existing MAC protocols. To overcome these limitations through protocol optimization, this paper proposes IDA-FDMAC, a novel MAC architecture tailored for FD-enabled IoT networks. At its core, IDA-FDMAC employs a dynamic priority scheduling mechanism that concurrently manages interference and provisions for diverse QoS requirements. A comprehensive theoretical model is developed and validated through extensive simulations, demonstrating that our proposed architecture significantly boosts system throughput and ensures QoS guarantees. This work thus contributes a robust, high-performance solution aligned with the development of next-generation wireless IoT systems. Full article

In recent years, China’s economic and social development has faced challenges such as urban-rural imbalance and ecological pressure. Digital inclusive finance and ecological resilience have become key concerns in academia and policymaking. This study empirically examines whether digital inclusive finance can enhance ecological resilience and its underlying mechanisms, drawing on quantitative evidence from provincial panel data covering 2011–2020. By providing robust empirical results, it contributes to understanding the role of digital finance in supporting high-quality growth and ecological civilization. While the findings align with national strategies such as the “dual carbon” goal and rural revitalization, the study’s primary contribution lies in advancing interdisciplinary exploration through rigorous evidence rather than solely at the policy level. By constructing a double fixed effects model and panel data from 30 Chinese provinces (2011–2020), the study finds that digital inclusive finance significantly enhances ecological resilience, both directly and indirectly through channels such as environmental regulation, artificial intelligence development, and green credit. Moreover, its ecological impact is moderated by regional economic levels and digital infrastructure, with stronger effects observed in eastern and digitally advanced regions. In summary, this study reveals the mechanisms through which digital inclusive finance promotes ecological resilience, offering a theoretical foundation and practical guidance for policy formulation. Its key contribution lies in systematically analyzing the link between digital inclusive finance and ecological resilience, enriching the theoretical framework and providing data support for policy optimization and financial institutions’ strategic adjustments. Future efforts should focus on strengthening policy coordination to enhance the ecological role of digital finance, promoting financial innovation to support resilience, and advancing regional coordination to narrow the digital divide and achieve shared ecological protection. Full article

Against the backdrop of accelerating global urbanization and intensifying ecological pressures, investigating the relationship between urbanization levels and ecological resilience in resource-based cities has become crucial for nations striving to achieve both sustainable development and ecological conservation. Utilizing panel data from 114 resource-based cities in China between 2010 and 2023, this study innovatively employs a composite nighttime light index to measure urbanization levels and constructs a comprehensive ecological resilience index using the entropy method. By applying a double machine learning model, this study thoroughly examines the impact, mechanisms, and heterogeneity of urbanization on ecological resilience in these cities. The findings reveal a gradual increase in ecological resilience among China’s resource-based cities, with the majority reaching high resilience levels by 2023. Spatial aggregation centers are identified in eastern China, the Yangtze River Delta, and the Pearl River Delta. Moreover, urbanization demonstrates a significant positive correlation with ecological resilience, a conclusion reinforced through robustness tests. Mechanism analysis reveals that industrial structure upgrading, green technology innovation, and energy efficiency improvement serve as key transmission channels. Heterogeneity analysis indicates that urbanization exerts a more pronounced effect on enhancing ecological resilience in regenerative resource-based cities as well as those located in eastern and central regions, while its impact is relatively weaker in declining resource-based cities and those in western and northeastern regions. Finally, this study proposes policy recommendations focusing on advancing industrial structure sophistication, constructing a green technology innovation ecosystem, implementing an energy efficiency enhancement initiative, deepening region-specific governance, and adopting targeted policy interventions. These findings provide theoretical support for precise policy formulation in resource-based cities and contribute to advancing academic understanding of the relationship between sustainable development and ecological resilience in such regions. Full article

The quantitative assessment of acoustic rain enhancement technology is highly significant for improving the ecological environment. A scientific and accurate evaluation of its operational effects provides an important basis for continued government and public support and investment in artificial weather modification activities. To effectively analyze the effects of acoustic rain enhancement on the vegetation of grassland ecosystems in arid and semi-arid areas and to clarify its mechanism, this study constructed eight vegetation indices based on Sentinel-2 satellite data. A comprehensive assessment of the changes in vegetation within the grassland ecosystem of the experimental zone was conducted by analyzing spatiotemporal distribution patterns, double-ratio analysis, and difference value comparisons. The results showed that (1) following the acoustic rain enhancement experiment, vegetation growth improved significantly. The mean values of all eight vegetation indices increased more substantially than before the experiment, with kNDVI showing the most notable gain. The proportion of the zone with kNDVI values greater than 0.417 increased from 52.62% to 71.59%, representing a relative increase of 36.05%. (2) The rain enhancement experiment significantly raised the values of eight vegetation indices: kNDVI increased by 0.042 (18.68%), ARVI by 0.043 (18.67%), and the remaining indices also increased to varying degrees (9.51–12.34%). (3) Vegetation improvement was more pronounced in areas closer to the acoustic rain enhancement site. Under consistent climate conditions, vegetation growth in the experimental zone showed significant enhancement. This study demonstrates that acoustic rain enhancement technology can mitigate drought and low rainfall, improve grassland ecosystem services, and provide a valuable foundation for ecological restoration and aerial water resource utilization in arid and semi-arid regions. Full article

Background/Objectives: Type 2 diabetes mellitus (T2DM) is a chronic metabolic disorder marked by insulin resistance, hyperglycemia, systemic inflammation, and immune imbalance. This randomized, double-blind, placebo-controlled, crossover trial investigated the effects of Bifidobacterium animalis subsp. lactis TISTR 2591 (BA-2591), a probiotic strain isolated in Thailand, on metabolic, immunologic, and safety parameters. Methods: A total of 44 Thai adults (aged 35–65) with T2DM receiving metformin monotherapy were administered BA-2591 (1 × 10⁹ CFU/g/day) or placebo for 6 weeks, followed by a 4-week washout and crossover. Results: Compared to placebo, BA-2591 significantly attenuated fasting blood glucose elevation (Δ = +1.143 mg/dL vs. +12.570 mg/dL; p < 0.001), minimized the increase in insulin resistance (HOMA-IR: Δ = +0.567 vs. +0.980; p = 0.006), and enhanced β-cell function (HOMA-β: Δ = +6.791% vs. −8.313%; p < 0.001). It also elevated immunoglobulin levels (IgM: +150.300 mg/dL; IgG: +261.500 mg/dL; p < 0.001), reduced LDL-C (p = 0.009), and decreased cathepsin D activity (p = 0.005), with no significant changes in IL-6, adiponectin, MDA, hs-CRP, or body composition. No severe adverse effects were reported. Conclusions: BA-2591 was safe and demonstrated modest, adjunctive benefits for fasting glycemia and immunologic profiles over 6 weeks, without changes in body weight or fat mass. These findings support BA-2591 as a potential adjunct to standard care in early T2DM; larger and longer-duration trials are needed to define its effects on longer-term outcomes. Full article

Chromium-doped hydroxyapatite (7CrHAp) and chromium-doped hydroxyapatite in chitosan matrix (7CrHAp-CH) coatings were synthesized in order to address the need for biomaterials with improved physico-chemical and biological properties for biomedical applications. Both chromium-doped hydroxyapatite (7CrHAp) and chromium-doped hydroxyapatite in chitosan matrix (7CrHAp-CH) coatings could represent promising materials for biomedical applications due to their superior properties. This study aims to evaluate the physico-chemical and in vitro biological properties of 7CrHAp and 7CrHAp-CH coatings to determine the impact of chitosan incorporation on the physico-chemical and biological features. The results reported in this study indicate that addition of chitosan improves surface uniformity and biological properties, highlighting their potential for uses in biomedical applications. In this study, coatings of chromium-doped hydroxyapatite (7CrHAp, with x_Cr = 0.07) and its composite variant embedded in a chitosan matrix (7CrHAp-CH) were systematically analyzed using a suite of characterization techniques: X-ray diffraction (XRD), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), Fourier-transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), atomic force microscopy (AFM), and metallographic microscopy (MM). The results of the XRD analysis revealed that the average crystal size was 19.63 nm for 7CrHAp and 16.29 nm for 7CrHAp-CH, indicating a decrease in crystallite size upon CH incorporation. The films were synthesized via the dip coating method using stable suspensions, whose stability was assessed through ultrasonic measurements (double-distilled water serving as the reference medium). The values obtained for the stability parameter were 2.59·10⁻⁶ s⁻¹ for 7CrHAp, 8.64·10⁻⁷ s⁻¹ for 7CrHAp-CH, and 3.14·10⁻⁷ s⁻¹ for chitosan (CH). These data underline that all samples are stable: CH is extremely stable, followed by 7CrHAp-CH (very stable) and 7CrHAp (stable). The in vitro biocompatibility of the 7CrHAp and 7CrHAp-CH coatings was evaluated with the aid of the MG63 cell line. The cytotoxic potential of these coatings towards MG63 cells was quantified using the MTT assay after 24 and 48 h of incubation. Our results highlight that both 7CrHAp and 7CrHAp-CH coatings exhibit high biocompatibility with MG63 cells, maintaining cell viability above 90% at both incubation times, thus supporting osteoblast-like cell proliferation. Furthermore, the antimicrobial efficacy of both 7CrHAp and 7CrHAp-CH samples was evaluated in vitro against the Pseudomonas aeruginosa 27853 ATCC (P. aeruginosa) reference strain. The in vitro antibacterial activity of the 7CrHAp and 7CrHAp-CH coatings was further evaluated against Pseudomonas aeruginosa 27853 ATCC (P. aeruginosa), Escherichia coli ATCC 25922 (E. coli) and Staphylococcus aureus ATCC 25923 (S. aureus) reference strains. In addition, atomic force microscopy (AFM) analysis was also used to investigate the ability of P. aeruginosa, E. coli and S. aureus cells to adhere and to develop colonies on the surfaces of the 7CrHAp and 7CrHAp-CH coatings. The results from the biological assays indicate that both coatings exhibit promising antibacterial properties, highlighting their potential for being used in biomedical applications, particularly in the development of novel antimicrobial devices. Full article

Optimizing pavement maintenance and rehabilitation (M&R) strategies is essential, especially in developing countries with limited budgets. This study presents an integrated framework combining a deterioration prediction model and a genetic algorithm (GA)-based optimization model to plan cost-effective M&R strategies for flexible pavements, including asphalt concrete (AC) and double bituminous surface treatment (DBST). The GA schedules multi-year interventions by accounting for varied deterioration rates and budget constraints to maximize pavement performance. The optimization process involves generating a population of candidate solutions representing a set of selected road sections for maintenance, followed by fitness evaluation and solution evolution. A mixed Markov hazard (MMH) model is used to model uncertainty in pavement deterioration, simulating condition transitions influenced by pavement bearing capacity, traffic load, and environmental factors. The MMH model employs an exponential hazard function and Bayesian inference via Markov Chain Monte Carlo (MCMC) to estimate deterioration rates and life expectancies. A case study on Cambodia’s road network evaluates six budget scenarios (USD 12–27 million) over a 10-year period, identifying the USD 18 million budget as the most effective. The framework enables road agencies to access maintenance strategies under various financial and performance conditions, supporting data-driven, sustainable infrastructure management and optimal fund allocation. Full article

Groundwater seepage plays a critical role in the long-term safety of high-level radioactive waste (HLW) disposal, yet its characterization remains challenging due to the complexity of fractured rock media. This study introduces the Double-Layered Seismo-Electric Method (DSEM) for imaging groundwater seepage fields with enhanced sensitivity and spatial resolution. By integrating elastic wave propagation with electrokinetic coupling in a stratified framework, DSEM improves the detection of hydraulic gradients and preferential flow pathways. Application at a representative disposal site demonstrates that the method effectively delineates seepage channels and estimates hydraulic conductivity, providing reliable input parameters for groundwater flow modeling. These results highlight the potential of DSEM as a non-invasive geophysical technique to support safety assessments and long-term monitoring in deep geological disposal of high-level radioactive waste. Full article

Inherited retinal dystrophies (IRDs) are clinically and genetically heterogeneous disorders. Most IRDs follow a monogenic inheritance pattern. However, an increasing number of unresolved cases suggest the possible contribution of oligogenic or digenic mechanisms. Here, we report two ultra-rare missense variants—AIPL1 R302L and BBS2 P134R—that co-segregate with early-onset nonsyndromic retinal degeneration in affected individuals from a non-consanguineous family. We performed a multi-level computational investigation to assess whether these variants may act through a convergent pathogenic mechanism. Using AlphaFold2-predicted structures, we modeled both wild-type and mutant proteins, introduced point mutations, and performed energy minimization and validation. FoldX, DynaMut2, and DUET all predicted destabilizing effects at the variant sites, corroborated by local disruption of secondary structure and altered surface electrostatics. Comparative docking (via HDOCK and ClusPro) identified a putative interaction interface between the TPR domain of AIPL1 and the β-sheet face of BBS2. This interface was destabilized in the double-mutant model. At the systems level, transcriptomic profiling confirmed co-expression of AIPL1 and BBS2 in human retina and fetal eye, while functional enrichment analysis highlighted overlapping involvement in ciliary and proteostasis pathways. Network propagation suggested that the two proteins may converge on shared interactors relevant to photoreceptor maintenance. Collectively, these in silico results provide structural and systems-level support for a candidate digenic mechanism involving AIPL1 and BBS2. While experimental validation remains necessary, our study proposes a testable mechanistic hypothesis and underscores the value of computational approaches in uncovering complex genetic contributions to IRDs. Full article

Background/Objectives: Cognitive impairment in older adults is a growing public health concern due to global population aging. Early detection is crucial, yet current screening methods are time-consuming and require clinical expertise. Gait analysis has emerged as a promising alternative for cognitive screening. The aim of the study was to identify gait variables associated with cognitive impairment and to develop predictive algorithms capable of distinguishing between cognitively impaired and non-impaired older adults using gold-standard gait analysis. Methods: A cross-sectional study was conducted with 42 adults aged > 60 years. Cognitive function was assessed using the Mini-Mental State Examination (MMSE), and participants were divided into high (MMSE > 24) and low (MMSE ≤ 24) cognitive function groups. Spatiotemporal gait parameters were recorded at participants’ usual pace using the Optogait system. Logistic regression models were developed using half of the sample (training group) and validated in the remaining participants (verification group). Results: Algorithms based on stride length and double support time demonstrated high classification performance. In the training group, the best-performing model achieved an AUC-ROC of 0.91, with a sensitivity of 71.4% and specificity of 92.3%. Validation in the verification group yielded an AUC-ROC of 0.84 and accuracy of 81.0%. Alternative models showed acceptable to excellent predictive power. Conclusions: Gait analysis using gold-standard methods can effectively identify cognitive impairment in older adults. The developed algorithms offer a rapid, objective, and accurate screening alternative with strong potential for clinical application. Full article

To address the challenge of asymmetric deformation and failure in the surrounding rock of main roadways within extra-thick coal seams caused by level differences under intense mining disturbance, this study systematically analyzed the evolution laws of principal stress fields, deviatoric stress fields, and their impact on surrounding rock stability in upper-, middle-, and lower-level roadways within a 20 m extra-thick coal seam during mining retreat. The analysis employed numerical simulation, similarity simulation, and field monitoring. Key findings include the following: ① As the working face advances, the principal stress vector lines deflect following a bias-unloading pattern, while the peak value of the deviatoric stress field (PVDSF) exhibits asymmetric bias-loading characteristics. The lower-layer roadway emerges as the primary load-bearing layer controlling surrounding rock stability. ② The evolution trend of the maximum principal stress vector orientation is consistent across different layers. The deflection trajectory manifests as “the deflection of the goaf side → the near layer orientation → the deflection of the solid coal side”. ③ The deviatoric stress peak zones (DSPZs) at all layers exhibit a characteristic “three-stage” evolution. The deviatoric loading pattern for the lower-layer roadway surrounding rock is the following: initial state double peak region crescent-shaped non-layer distribution type → the range of the bimodal region and the extreme value increased simultaneously, distributed in a non-layer manner → the asymmetrical distribution type of steep drop in the peak area of non-mining deviator stress. ④ The junctions between the mining-side rib and floor and the non-mining-side rib and roof were identified as critical control zones. An innovative zonal asymmetric directional anchoring control technology, “anchor cable foundation support + concrete floor + asymmetric reinforcing anchor cable support”, along with a “One Directional Penetration and Three Synergies” control methodology, was proposed. Field monitoring confirmed the significant effectiveness of the optimized support system. Full article

Efficient water management is critical for sustainable crop production in arid and semi-arid regions. This study investigated the effects of two irrigation regimes—25% and 50% Management Allowable Depletion (MAD) and two planting patterns (single-row and double-row) on evapotranspiration (ET) partitioning, water use efficiency (WUE), and water footprint (WF) in drip-irrigated faba bean (Vicia faba L.). Field data were combined with a leaf area index (LAI)-based model to estimate the relative contributions of transpiration (T) and evaporation (E) to total ET. The highest grain yield (6171 kg ha⁻¹) and the lowest blue (570 m³ ton⁻¹) and green (68 m³ ton⁻¹) water footprints were recorded under the 25% MAD with double-row planting. This treatment also achieved the highest proportion of transpiration in ET (70%), indicating a shift toward productive water use. In contrast, the lowest-performing treatment (50% MAD, single-row) had the highest total water footprint (792 m³ ton⁻¹) and the lowest transpiration share (44%). Although high-density planting slightly reduced WUE based on transpiration, it improved overall water efficiency when total input (ETc) was considered (1.57 kg m⁻³ for total input WUE, 4.17 kg/m⁻³ for T-based WUE). These findings highlight the importance of integrating irrigation scheduling and planting pattern to improve both physiological and agronomic water productivity. The approach offers a practical strategy for sustainable faba bean production in water-scarce environments and supports climate-resilient irrigation planning aligned with Iraq’s National Water Strategy. Full article

This study focuses on tourist-oriented urban historic districts. In recent years, many such districts have experienced commercial intensification and homogenization, placing pressure on sustainable development. The prior work is largely descriptive and offers limited mechanism-level guidance for governance. In response, this study employs Tianzifang as an empirical case and proposes an online-review-driven mechanism-identification framework. Drawing on 3005 online reviews, a quantitative–qualitative mixed approach was adopted: word-frequency and semantic-network analyses of the full corpus mapped topics and their relational structure; guided by these structures, grounded-theory coding was conducted on a negative-review subsample (n = 602); the results indicate a double-helix interaction between culture–commerce and expectation–reality, associated with lower perceived authenticity, affective disconnect, stronger negative word-of-mouth, and perceived declines in attractiveness. The main contributions are: a mechanism identification framework with a replicable quantitative–qualitative integration workflow; the construction of a double-helix mechanism coupling culture–commerce and expectation–reality; and, on this basis, a governance strategy framework to support fine-grained management and the sustainable renewal of urban historic districts. Full article

We investigate the Optimal Obstacle Placement (OOP) problem under uncertainty, framed as the dual of the Optimal Traversal Path problem in the Stochastic Obstacle Scene paradigm. We consider both continuous domains, discretized for analysis, and already discrete spatial grids that form weighted geospatial networks using 8-adjacency lattices. Our unified framework integrates OOP with stochastic geometry, modeling obstacle placement via Strauss (regular) and Matérn (clustered) processes, and evaluates traversal using the Reset Disambiguation algorithm. Through extensive Monte Carlo experiments, we show that traversal cost increases by up to 40% under strongly regular placements, while clustered configurations can decrease traversal costs by as much as 25% by leaving navigable corridors compared to uniform random layouts. In mixed (with both true and false obstacles) scenarios, increasing the proportion of true obstacles from 30% to 70% nearly doubles the traversal cost. These findings are further supported by statistical analysis and stochastic ordering, providing rigorous insights into how spatial patterns and obstacle compositions influence navigation under uncertainty. Full article