Search Results (104,221)

Unmanned Underwater Vehicle (UUV) swarms have become increasingly crucial for underwater exploration and applications, where their coordinated operation offers significant advantages over single-vehicle systems. However, unlike single-vehicle systems, the development of swarm control systems is more complicated, especially because there are limited integrated toolchains that can cover both global scheme design and individual vehicle implementation. Engineers may have to develop a global scheme and then partition it manually for individual vehicle implementation, which can result in substantial efficiency losses. To address this difficulty, an integrated experimental framework is developed to support the complete workflow of UUV swarm control development, from unified algorithm design and system simulation to automated code generation and individual deployment. The architecture of the proposed platform incorporates three principal elements: a global simulation environment that enables virtual validation of swarm collective behavior, a rapid prototyping module that facilitates code generation/partitioning and individual implementation, and a digital twin visualization component that provides real-time monitoring capabilities. A case study demonstrates that the platform can integrate global design with individual implementation. In a comparative experiment where the same engineering team implemented a three-UUV formation control algorithm, the use of our platform reduced the time from algorithm design to successful deployment from an estimated 6 h (using manual coding and integration) to under one hour, representing about an 80% reduction in development time. Full article

To address the severe challenge of soil salinization, effective soil amelioration methods are urgently needed; however, current research on the microbial mechanisms of the combined application of multiple amendments is insufficient. Therefore, this study aims to investigate the impacts of biochar combined with humic acid (HA) on the physicochemical properties and microbial community structure of saline–alkali soils by a field experiment. The results showed that the co-application treatments significantly improved soil physicochemical properties and increased bacterial community richness; specific effects depended on the biochar feedstock. Notably, the H-MBC treatment was the most effective in reducing soil electrical conductivity (EC) by 44.1%, while the H-SBC treatment most significantly increased soil water content by 80.3%. Stochastic processes influenced the assembly of microbial communities, particularly the co-application group, forming a more complex and stable microbial network. Furthermore, Spearman correlation and random forest analyses revealed EC, nitrate nitrogen, and available phosphorus as the primary variables affecting microbial communities. These findings support the potential of the combined application of biochar and HA for saline–alkali soil amelioration, as this strategy mitigates salt stress and increases nutrient availability, thereby reshaping microbial communities toward states conducive to ecological restoration. Full article

Due to computational constraints, ocean numerical models are often executed on low-resolution (LR) grids. To maintain consistency between LR simulations and coarsened high-resolution (HR) solutions, a subgrid forcing term is commonly integrated into the LR model as a parameterization scheme. Although numerous data-driven parameterizations have been developed to establish the relationship between resolved LR variables and corresponding subgrid forcing, the accurate extraction of target subgrid forcing remains an open challenge that significantly impacts the performance of such parameterizations. Small-scale dissipation (ssd) operators are widely used to enhance numerical stability while introducing minimal energy dissipation; however, this study demonstrates that these operators critically influence the accurate representation of subgrid forcing: an aspect that has not been adequately addressed. Within a quasi-geostrophic ocean modeling framework, new formulations have been rigorously derived for subgrid forcing that explicitly accounts for ssd effects. Numerical experiments confirm that the proposed forcing enables LR simulations to reproduce coarsened HR results with high fidelity. This work demonstrates that greater attention to the specific numerical discretization scheme is required for the accurate extraction of subgrid forcing from HR simulations. Although these newly developed extraction algorithms are diagnostic in nature, they could provide accurate target data that facilitate the subsequent development of data-driven parameterization schemes. Full article

Manufactured nanoparticles are used in many consumer products and industries, and are known to enter our waste streams. Transport of nanoparticles in porous media has been studied extensively; however, the forces governing the interactions between nanoparticles and naturally porous media surfaces are still not fully understood. To examine the retention mechanisms and forces involved in nanoparticle transport, miscible–miscible transport experiments were performed and followed by force profile measurements by Atomic Force Microscopy (AFM). TiO₂ nanoparticles were used as the model nanoparticle, with silica sand as the model natural porous medium. Solution chemistries were varied from pH 4.5 (favorable attachment) to 8 (unfavorable attachment), and at 0.0015–30 mM ionic strength. Detachment transport experiments were performed for the unfavorable attachment conditions to determine if secondary minima attachment was present. DLVO calculations were performed to evaluate their predictive ability for force profiles under the experimental conditions. Mass recoveries for the transport experiments ranged from 28% to 80%, indicating significant attachment. Detachment was observed, indicating the presence of secondary minima. The magnitudes of attachment measured for the transport experiments were generally consistent with the results of the AFM measurements. In addition, the detachment observed at the highest pH was also consistent with the predictions, indicating the presence of secondary minima. DLVO theory underestimated the magnitudes of the attractive and repulsive forces measured by AFM but was able to qualitatively represent behavior observed at the lower two pHs. In contrast, it provided a poor representation of behavior at the highest pH. The integrated AFM measurements and miscible–displacement experiments employed in this study have provided insight into the retention of TiO₂, with implications for other nanoparticles during transport in porous media. Full article

Background/Objectives: In this proof-of-concept study, the objective was to evaluate the phenotypic CarbaLux combination rapid test in terms of guiding the therapy of infections caused by multidrug-resistant Gram-negative bacteria with carbapenemase inhibitors and carbapenems, and to compare its results and practicability with standard diagnostic methods. Methods: In the classical CarbaLux test, a fluorescent carbapenem serves as a UV–visible diagnostic surrogate for clinically used carbapenem antibiotics. When exposed to extracted carbapenemases from bacterial colony growth on agar plates, fluorescence rapidly disappears, showing whether monotherapy with carbapenems is possible or must be rejected. It was expected that a specific inhibitor that protects imipenem or meropenem from enzymatic deactivation during antibacterial therapy would perform the same in vitro with fluorescent carbapenem and preserve its fluorescence. The new additional CarbaLux combination test is used if the classic test is positive for carbapenemases: a classic test tube pre-dosed with fluorescent carbapenem is spiked with cloxacillin; with recently launched carbapenemase inhibitors, e.g., avibactam, relebactam, zidebactam, nacubactam, or vaborbactam; or with picolinic acid. Fourteen Enterobacterales and six Acinetobacter baumannii isolates were analyzed. Results: At fixed concentrations, the new inhibitors protected fluorescent carbapenem from bacterial KPC-mediated inactivation and partially from AmpC beta-lactamase-mediated inactivation. In addition, avibactam also effectively inhibited OXA-48-like enzymes. Cloxacillin selectively inhibited AmpC beta-lactamases extracted from Enterobacter complex species. Non-therapeutic picolinic acid was specific for metallo-beta-lactamases and thus identified infections by pathogens that cannot be treated with carbapenems alone or in combination. Conclusions: Inhibitor/fluorescent carbapenem mixtures corresponding to therapeutic inhibitor/carbapenem combinations allow us to visualize the efficacy of carbapenemase inhibitors. The in vitro results are consistent with clinical experience regarding combination therapy. Enzymatic assays provide a rapid yes/no answer for carbapenem mono- or combination therapy and offer several advantages over current carbapenemase testing methods. In contrast to PCR and lateral flow tests, which only target a selection of carbapenemases, enzymatic assays work by employing a reproducible phenotypic mechanism. They are simpler, broader in scope, and more cost-effective; they can also detect antimicrobial heteroresistance or AmpC beta-lactamase hyperproduction, which is normally undetected when performing automated antibiotic susceptibility testing. The new tests are suitable for clinical diagnosis, public health purposes, and infection control. Full article

Historically, clays have been widely used for the treatment of wounds and to stop hemorrhaging. The aim of this study was to combine four natural clay minerals (kaolinite, glauconite, montmorillonite, and bentonite) with magnetite (Fe₃O₄) nanoparticles to produce Fe₃O₄–clay complexes with enhanced antimicrobial properties and chemopreventive activity against melanoma. The magnetite–clay complexes were synthesized by the chemical co-precipitation method and characterized using XRD, TEM, STEM-EDS, SEM, and SQUID magnetometer. Antimicrobial properties were determined by evaluation of MIC values. The most promising materials were also subjected to direct contact antibacterial test according to the OECD standard for porous materials. Cytotoxicity of the complexes towards melanoma cells and normal human skin fibroblasts was assessed by MTT assay. We performed XRD, which confirmed the formation of Fe₃O₄–clay complex materials. It was also proven that complexes exhibited superparamagnetic properties. Microbiological experiments clearly revealed that modification of natural clays with magnetite significantly boosted their antimicrobial properties. Fe₃O₄–montmorillonite and Fe₃O₄–bentonite showed the strongest antimicrobial activity. Moreover, the mentioned complexes had the ability to reduce the viability of melanoma cells by 35–40%, while exhibiting no cytotoxicity against the normal human fibroblast (BJ) cell line, which is an extremely desirable feature. Thus, it may be concluded that Fe₃O₄–montmorillonite and Fe₃O₄–bentonite complexes hold promise for use in the management of infected wounds and wounds after melanoma excision. Full article

This paper investigates layered workplace exclusions experienced by African professionals in Australian workplaces. Through semi-structured interviews with 44 participants and a qualitative phenomenological design, the study reveals experiences of subtle exclusion, workplace gatekeeping, and power struggles that African professionals face from various sources—dominant cultural groups, other migrant communities, and within their own professional networks. An integrated theoretical framework combining Intersectionality Theory, Social Dominance Theory, and Bourdieu’s concepts of cultural capital and habitus examines how overlapping identities and power hierarchies shape workplace relationships and professional belonging. The findings show that diversity and inclusion efforts often neglect the layered nature of exclusion that African professionals navigate, limiting their effectiveness. This study contributes to migration and workplace diversity scholarship by highlighting the need for inclusion strategies that address the complex realities of workplace exclusion in multicultural professional environments rather than relying on simple majority–minority binaries. Full article

Efficient pesticide application remains a critical resource-management challenge in modern agriculture, where limited spray penetration reduces treatment efficacy, wastes chemical inputs, and increases environmental losses. This study quantified the effect of air-assisted spraying (AAS) on droplet deposition in two contrasting field crops, oilseed rape and wheat. Field trials were conducted using a sprayer equipped with an adjustable airflow module, and spray coverage was measured with water-sensitive papers at multiple canopy heights and orientations. In oilseed rape, AAS improved deposition on front-facing and top surfaces in the lower canopy, for example, increasing top-surface coverage at 90 cm from 53.4% to 65.5% at 6 km∙h⁻¹, indicating more uniform distribution and enhanced penetration. In wheat, which typically exhibits a more open canopy structure compared to oilseed rape, AAS effects were smaller and less consistent, with the greatest gain on front-facing lower surfaces (from 13.3% to 21.9% at 7 km∙h⁻¹). Although drift was not measured in this experiment, previous studies using the same sprayer prototype demonstrated measurable reductions, supporting the environmental relevance of improved deposition. These results highlight the role of canopy architecture in determining AAS performance and underscore the technology’s potential to reduce pesticide inputs, minimize off-target losses, and improve the resource efficiency of crop protection in line with EU Farm to Fork objectives. Full article

The specification of inlet boundary conditions plays a critical role in computational fluid dynamics (CFD) simulations of pollutant dispersion from nuclear facilities, particularly in regions characterized by uneven terrain. Previous studies have often simplified such terrain by approximating it as a flat surface to reduce computational complexity. However, this approach fails to adequately capture the realistic atmospheric boundary layer dynamics inherent to uneven topographies. To address this limitation, this study conducted atmospheric dispersion tracer experiments specifically designed for nuclear facilities situated on non-uniform terrain. A novel inlet boundary condition, termed the Atmospheric Boundary Layer of Uneven Terrain (ABLUT), was developed by modifying the existing atmBoundaryLayer model in OpenFOAM. Numerical simulations were performed using both the default and the proposed ABLUT boundary conditions, incorporating different turbulence models and examining the influence of turbulent Schmidt numbers across a range of 0.3 to 1.3. The results demonstrate that the ABLUT boundary condition, particularly when coupled with a turbulent Schmidt number of 0.7 and the $SSTk-\omega$ turbulence model, yields the closest agreement with experimental tracer dispersion data. Notably, comparative analyses between the default and improved models revealed significant discrepancies in near-surface wind speed profiles, with deviations becoming increasingly pronounced at higher elevations. Numerical simulations were conducted to assess the ground-level distribution of Total Effective Dose Equivalent (TEDE) for four typical radionuclides (³$H$, ¹⁴$C$, ⁸⁵$Kr$ and ¹²⁹$I$) emitted from nuclear facilities under both higher and lower wind speed conditions. Results demonstrate that the TEDE maxima across all scenarios remain orders of magnitude below regulatory annual limits. These findings provide critical insights for enhancing the accuracy of wind field simulations in the vicinity of nuclear facilities located on uneven terrain, thereby contributing to improved risk assessment and environmental impact evaluations. Full article

In mycorrhizal symbiotic relationships, non-photosynthetic myco-heterotrophic plants are unable to supply photosynthates to their associated fungi. On the contrary, they rely on fungal carbon to sustain their own growth. Mycorrhizal fungi can mediate plant interactions with the rhizosphere microbiome, which contributes to the promotion of plant growth and nutrient uptake. However, the microbial community and key microbial species that function during the growth of the myco-heterotrophic plant Cheilotheca humilis remain unclear. In this study, we evaluated the microbial community associated with Cheilotheca humilis, which was confirmed via morphological characteristics typical of this plant species. Metagenomic analysis showed that the Afipia carboxidovorans was dominant at species level. Based on the LDA score, Bradyrhizobium ottawaense exhibited the higher abundance in the CH-B group (related to bud) while Afipia carboxidovorans was identified from the CH-F group (related to flower). Microbial co-occurrence networks showed that the Rhizobium genus, Herbaspirillum genus, and Cyanobacteriota were defined as core functional microbial species. To explore the potential microorganisms, metagenome-assembled genomes (MAGs) of the rhizosphere microbiome identified 14 medium- and high-quality MAGs, mainly involved in carbon fixation, nitrogen transformation, and phosphorus metabolism, possibly providing nutrients for the plant. Furthermore, a total of 67 rhizospheric and 66 endophytic microorganisms were isolated and obtained. In vitro experiments showed that the mycorrhizal helper bacteria (MHBs) Rhizobium genus and Pseudomonas genus possessed the ability of nitrogen fixation, phosphate solubilization, and siderophores production. Most importantly, the mycorrhizal fungus Humicolopsis cephalosporioides was obtained, which could potentially produce cellulase to supply carbohydrates for host. The findings suggest the mycorrhizal fungus Humicolopsis cephalosporioides and helper bacteria have great potential in the growth of the myco-heterotrophic plant Cheilotheca humilis. Full article

The conical pick is an essential component of roadheaders used for cutting rock. During the rock-breaking process, these picks interact with the rock, resulting in self-rotation, which enhances the wear uniformity of conical picks, thereby prolonging their service life. Since the phenomenon of self-rotation is generated passively by random contact forces with the rock surface, it is challenging to quantitatively measure the extent of self-rotatory speed. In order to investigate the correlation between the self-rotatory speed of conical picks and wear, this article establishes various self-rotatory speeds for vertical rock-breaking wear experiments involving conical picks. It analyzes the relationship between quantitative parameters, such as the equivalent stress and wear, through simulation. The results of the study indicate that the optimal self-rotatory speed of the conical pick is 16 rpm when it is rotated vertically to break the rock, resulting in minimal wear. When the equivalent stress and Mohr–Coulomb safety factor are optimized, it is essential to consider the changes in normal force and the variation in the area affected by the safety factor. This leads to an increase in wear as the cutting distance increases, indicating that a higher self-rotatory speed does not necessarily improve the wear performance of conical picks. Full article

This study investigates the applicability of the Japanese forest education model, exemplified by the Whole Earth Nature School (WENS), to environmental education programs within urban parks and botanical gardens. Focusing on WENS’s approach—characterized by immersive natural experiences, innovative facilitation techniques, and support from interdisciplinary educator teams to foster independent thinking through experiential learning—the research identifies three transferable insights: (1) Reorienting educational philosophy to prioritize nature-based learning for holistic development, particularly within urban green spaces; (2) Developing localized curricula that leverage the unique ecological resources of specific park and garden environments; (3) Establishing dedicated professional development systems for educators focused on site-based pedagogy. The findings demonstrate that adapting the forest education model can significantly enhance environmental education initiatives in urban parks and botanical gardens, which offers actionable strategies for integrating experiential nature learning into their educational planning. Full article

Fencing demands a unique blend of endurance, explosive power, and asymmetric neuromuscular control. This study compared physiological profiles of elite (top 25 nationally ranked, n = 16) and non-elite (positions 26–102, n = 33) Polish male fencers using the Fencing Endurance Test (FET), countermovement jump (CMJ), 5-m sprint, body composition, and heart rate (HR) metrics. FET duration, CMJ-derived explosive power (flight time, reactive strength index), and relative lean mass were also assessed in relation to competitive experience. Quantile regression (age & BMI-adjusted), ROC analysis, and Spearman correlations evaluated group differences. Elite fencers demonstrated superior FET duration (median difference: +1.84 min, p < 0.0001), CMJ performance (e.g., 10.4 W/kg higher peak power, p = 0.014), and relative lean mass (+7.7%, p < 0.001), despite comparable 5-m sprint times. Elite athletes also showed more efficient HR recovery (HRR1) and lower pre-FET resting HR (p < 0.05). Competitive experience correlated strongly with FET endurance (rho = 0.62), CMJ power (rho = 0.42), and lean mass (rho = 0.55). ROC analysis identified FET ≥ 14.3 min, CMJ flight time ≥0.581 s, and ≥10 years of experience as optimal discriminators of elite status (AUCs 0.86–0.90). These findings confirm that elite performance is characterized by superior sport-specific endurance and explosive power, independent of age/BMI. The FET and CMJ emerge as practical tools for monitoring training progress, with identified thresholds serving as benchmarks for elite preparation. Training programs should prioritize individualized development of these traits, acknowledging inter-athlete variability in physiological strengths. Future research should explore sport-specific acceleration metrics and extended FET protocols for elite athletes. Full article

Establishing refuges is a primary strategy for managing resistance in target pests against Bt maize. The larval feeding and dispersal, and adult oviposition behaviors of Spodoptera exigua (Hübner) on Bt and non-Bt maize plants are critical factors in determining optimal refuge configurations. This study employed laboratory and field experiments to evaluate the larval feeding and dispersal behaviors, as well as the oviposition preferences of S. exigua moths, on Bt (Cry1Ab + Vip3Aa19) and non-Bt maize plants. Results showed that as time of the choice test increased, the larval selection rate on Bt maize leaves declined progressively, with all instars (1st–5th) preferring to feed on non-Bt maize. After 48 h, the selection rates of larvae for non-Bt and Bt maize were 40.63–66.25% and 9.38–33.75%, respectively. Female moths exhibited no significant oviposition preference between Bt and non-Bt plants under undamaged conditions; however, when non-Bt maize was infested by the larvae, females preferentially oviposited on Bt maize plants (73.55%). Under the seed-mixture refuge pattern in field conditions, increasing the proportion of non-Bt maize significantly enhanced larval dispersal distances and facilitated larval transit damage between Bt and non-Bt plants. Our research clarifies the behavioral patterns of S. exigua on Bt and non-Bt maize, provides a scientific basis for optimizing refuge strategy to delay the development of resistance. Full article

Semiconductor wafer manufacturing is one of the most complex and data-intensive industrial processes, comprising 500–1000 tightly interdependent steps, each requiring nanometer-level precision. As device nodes approach 3 nm and beyond, even minor deviations in parameters such as oxide thickness or critical dimensions can lead to catastrophic yield loss, challenging traditional physics-based control methods. In response, the industry has increasingly adopted regression analysis and predictive modeling as essential analytical frameworks. Classical regression, long used to support design of experiments (DOE), process optimization, and yield analysis, has evolved to enable multivariate modeling, virtual metrology, and fault detection. Predictive modeling extends these capabilities through machine learning and AI, leveraging massive sensor and metrology data streams for real-time process monitoring, yield forecasting, and predictive maintenance. These data-driven tools are now tightly integrated into advanced process control (APC), digital twins, and automated decision-making systems, transforming fabs into agile, intelligent manufacturing environments. This review synthesizes foundational and emerging methods, industry applications, and case studies, emphasizing their role in advancing Industry 4.0 initiatives. Future directions include hybrid physics–ML models, explainable AI, and autonomous manufacturing. Together, regression and predictive modeling provide semiconductor fabs with a robust ecosystem for optimizing performance, minimizing costs, and accelerating innovation in an increasingly competitive, high-stakes industry. Full article