Search Results (964)

In the present paper, impedance spectroscopy was employed to study the corrosion and anodic oxidation of stainless steel (AISI 316L at 280 °C/9 MPa) in contact with the boron-free primary coolant of a small modular reactor at two levels of KOH concentration. Analysis of impedance spectra with a distribution of relaxation times revealed contributions from the oxide layer and its interface with the coolant. Glow-Discharge Optical Emission Spectroscopy (GDOES) was used to estimate the thickness and elemental composition of the formed oxides. A quantitative interpretation of the impedance data using the Mixed-Conduction Model allowed us to estimate the kinetic and transport parameters of oxide growth and dissolution, as well as iron dissolution through oxide. The film thicknesses following exposure agreed with ex-situ analyses. The obtained corrosion and release rates were used for comparison with laboratory and industrial data in nominal pressurized water reactor primary coolants. Full article

The exponential growth of autonomous systems demands robust security mechanisms that can operate within the extreme constraints of real-time embedded environments. This paper introduces SMART DShot, a groundbreaking machine learning-enhanced framework that transforms the security landscape of unmanned aerial vehicle motor control systems through seamless integration of adaptive timing correction and real-time anomaly detection within Digital Shot (DShot) communication protocols. Our approach addresses critical vulnerabilities in Electronic Speed Controller (ESC) interfaces by deploying four synergistic algorithms—Kalman Filter Timing Correction (KFTC), Recursive Least Squares Timing Correction (RLSTC), Fuzzy Logic Timing Correction (FLTC), and Hybrid Adaptive Timing Correction (HATC)—each optimized for specific error characteristics and attack scenarios. Through comprehensive evaluation encompassing 32,000 Monte Carlo test iterations (500 per scenario × 16 scenarios × 4 algorithms) across 16 distinct operational scenarios and PolarFire SoC Field-Programmable Gate Array (FPGA) implementation, we demonstrate exceptional performance with 88.3% attack detection rate, only 2.3% false positive incidence, and substantial vulnerability mitigation reducing Common Vulnerability Scoring System (CVSS) severity from High (7.3) to Low (3.1). Hardware validation on PolarFire SoC confirms practical viability with minimal resource overhead (2.16% Look-Up Table utilization, 16.57 mW per channel) and deterministic sub-10 microsecond execution latency. The Hybrid Adaptive Timing Correction algorithm achieves 31.01% success rate (95% CI: [30.2%, 31.8%]), representing a 26.5% improvement over baseline approaches through intelligent meta-learning-based algorithm selection. Statistical validation using Analysis of Variance confirms significant performance differences (F(3,1996) = 30.30, p < 0.001) with large effect sizes (Cohen’s d up to 4.57), where 64.6% of algorithm comparisons showed large practical significance. SMART DShot establishes a paradigmatic shift from reactive to proactive embedded security, demonstrating that sophisticated artificial intelligence can operate effectively within microsecond-scale real-time constraints while providing comprehensive protection against timing manipulation, de-synchronization, burst interference, replay attacks, coordinated multi-channel attacks, and firmware-level compromises. This work provides essential foundations for trustworthy autonomous systems across critical domains including aerospace, automotive, industrial automation, and cyber–physical infrastructure. These results conclusively demonstrate that ML-enhanced motor control systems can achieve both superior security (88.3% attack detection rate with 2.3% false positives) and operational performance (31.01% timing correction success rate, 26.5% improvement over baseline) simultaneously, establishing SMART DShot as a practical, deployable solution for next-generation autonomous systems. Full article

Many speech coding strategies have been developed over the years, but comparing them has been convoluted due to the difficulty in disentangling brand-specific and patient-specific factors from strategy-specific factors that contribute to speech understanding. Here, we present a comparison with a ‘virtual’ patient, by comparing two strategies from two different manufacturers, Advanced Combination Encoder (ACE) versus HiResolution Fidelity 120 (F120), running on two different implant systems in a computational model with the same anatomy and neural properties. We fitted both strategies to an expected T-level and C- or M-level based on the spike rate for each electrode contact’s allocated frequency (center electrode frequency) of the respective array. This paper highlights neural and electrical differences due to brand-specific characteristics such as pulse rate/channel, recruitment of adjacent electrodes, and presence of subthreshold pulses or interphase gaps. These differences lead to considerably different recruitment patterns of nerve fibers, while achieving the same total spike rates, i.e., loudness percepts. Also, loudness growth curves differ significantly between brands. The model is able to demonstrate considerable electrical and neural differences in the way loudness growth is achieved in CIs from different manufacturers. Full article

The high pH and heavy metal leaching of argon oxygen decarburization (AOD) slag limit its application in agriculture. Slag carbonation can aid in decreasing slag alkalinity and inhibit heavy metal release; the environmental safety of utilizing carbonated AOD slag (CAS) as a fertilizer remains a topic of significant debate, however. In this work, pakchoi (Brassica chinensis L.) was planted in CAS-fertilized soil to investigate the accumulation and migration behavior of heavy metals in the soil–plant system and perform an associated risk assessment. Our results demonstrated that CAS addition increases Ca, Si, and Cr concentrations but decreases Mg and Fe concentrations in soil leachates. Low rates (0.25–1%) of CAS fertilization facilitate the growth of pakchoi, resulting in the absence of soil contamination and posing no threat to human health. At the optimal slag addition rate of 0.25%, the pakchoi leaf biomass, stem biomass, leaf area, and seedling height increased by 34.2%, 17.2%, 26.3%, and 8.7%, respectively. The accumulation of heavy metals results in diverging characteristics in pakchoi. Cr primarily accumulates in the roots; in comparison, Pb, Cd, Ni, and Hg preferentially accumulate in the leaves. The migration rate of the investigated heavy metals from the soil to pakchoi follows the order of Cr > Cd > Hg > Ni > Pb; in comparison, that from the roots to the leaves follows the order Cd > Ni > Hg > Cr > Pb. Appropriate utilization of CAS as a mineral fertilizer can aid in improving pakchoi yield, achieving sustainable economic benefits, and preventing environmental pollution. Full article

With the rapid development of smart devices and the Internet of Things (IoT), the explosive growth of data has placed increasingly higher demands on real-time processing and intelligent decision making. Cloud-edge collaborative computing has emerged as a mainstream architecture to address these challenges. However, in sky-ground integrated systems, the limited computing capacity of edge devices and the inconsistency between cloud-side fusion results and edge-side detection outputs significantly undermine the reliability of edge inference. To overcome these issues, this paper proposes a cloud-edge collaborative model adaptation framework that integrates deep reinforcement learning via Deep Q-Networks (DQN) with local feature transfer. The framework enables category-level dynamic decision making, allowing for selective migration of classification head parameters to achieve on-demand adaptive optimization of the edge model and enhance consistency between cloud and edge results. Extensive experiments conducted on a large-scale multi-view remote sensing aircraft detection dataset demonstrate that the proposed method significantly improves cloud-edge consistency. The detection consistency rate reaches 90%, with some scenarios approaching 100%. Ablation studies further validate the necessity of the DQN-based decision strategy, which clearly outperforms static heuristics. In the model adaptation comparison, the proposed method improves the detection precision of the A321 category from 70.30% to 71.00% and the average precision (AP) from 53.66% to 53.71%. For the A330 category, the precision increases from 32.26% to 39.62%, indicating strong adaptability across different target types. This study offers a novel and effective solution for cloud-edge model adaptation under resource-constrained conditions, enhancing both the consistency of cloud-edge fusion and the robustness of edge-side intelligent inference. Full article

Microalage are broadly recognized as promising agents for sustainable wastewater treatment and biomass generation. However, industrial effluents such as petroleum refinery wastewater (WW) present challenges due to toxic growth inhibiting substances. Three marine microalgae species: Pseudochloris wilhelmii, Nannochloropsis gaditana and Synechococcus sp. MK568070 were examined for cultivation potential in oil refinery WW. Their performance was evaluated in terms of growth dynamics, lipid productivity, and toxicity reduction, with a focus on their suitability for largescale industrial use. N. gaditana demonstrated the highest growth rate and lipid content (37% d.w.) as well as lipid productivity (29.45 mg/(Lday)) with the N-uptake rate of 0.698 mmol/(gday). The highest specific DIN uptake rate was observed inn P. wilhelmii (0.895 mmol/(gday) along with the highest volumetric productivity (93.9 mg/L/day) and WW toxicity removal (76.5%), while Synechococcus sp. MK568070 demonstrated lower performance metrics. A simple numerical model was applied to calculate continuous operation based on empirical results of batch experiments. Sustainability of the microalgae-based WW remediation under the conditions of optimized lipid biomass production was estimated, regarding 2019–2022–2025 cost dynamics. Parameters for optimum open raceway pond cultivation were calculated, and the biomass production accumulation was estimated, with the highest biomass production noted in P. wilhelmii (171.38 t/year). Comparison of treatment costs, production costs and revenue showed that the best candidate for WW remediation is N. gaditana. Full article

The high cost of mushroom spawn remains a critical constraint to economically viable mushroom cultivation, particularly for small-scale farmers. This study investigated four spawn types, including stick (giant mimosa stalks, GMS), sawdust, sorghum, and liquid culture as inoculum sources for 10 edible mushroom species. The results indicated that GMS stick spawn provides excellent conditions for the mycelial growth of seven species, outperforming other spawn types in terms of colonization rate and pinhead formation. Mushrooms grown on GMS substrate demonstrated rapid development, with full colonization occurring within 11 to 26 days and pinhead initiation between 18 and 47 days, depending on the species. Among the mushroom species tested, Schizophyllum commune exhibited the fastest growth, reaching full colonization in 11 days and forming pinheads after 18 days of inoculation. In comparison, Auricularia polytricha showed the slowest development. Economically, GMS spawn was the most cost-effective at 0.074 USD per unit, significantly lower than sawdust (0.24 USD), sorghum (0.29 USD), and potato dextrose broth (PDB; 2.80 USD). The conversion from PDB with GMS could reduce industrial inoculum costs from 35,000 USD to 600 USD annually. These findings demonstrate the potential of GMS as an effective, low-cost, and sustainable spawn option that can enhance mycelial growth and support eco-friendly farming practices. Full article

Tussah immunoreactive pupa powder (IPP) is composed of various active substances. We speculated that it has the potential to improve key economic traits of sea urchins. Therefore, we conducted a 60-day experiment to examine the effects of IPP on growth, antioxidant capacity, gonad quality, and gut microbiota of sea urchins (Strongylocentrotus intermedius). The experiment involved the preparation of a kelp group and four types of feed containing 0% (the control group), 0.5%, 1.0%, and 1.5% IPP. The results indicated that IPP had no significant impact on the survival of sea urchins (p > 0.05). Firstly, adding IPP promoted the growth of sea urchins. The 1.0% IPP group showed the highest weight gain rate among the feed group, significantly higher than that of the control group (p < 0.05). Secondly, compared with the kelp group, the addition of IPP significantly improved the growth and quality of sea urchin gonads (p < 0.05), which demonstrated certain industrial value. Thirdly, following the addition of IPP, the activities of SOD, CAT, and POD significantly increased in comparison to the control group (p < 0.05). Lastly, added IPP increased the abundance of Firmicutes, Bacteroidetes, and Rhodobacteraceae, while reducing the abundance of Ralstonia and Vibrio. This indicates that added IPP may improve the digestive function and gut health of sea urchins. Overall, added IPP can improve certain economic traits and antioxidant capacity of sea urchins. This manuscript provides a theoretical reference for the healthful aquaculture of S. intermedius. Full article

Meat quality is influenced by factors such as age, breed, slaughter weight, and nutrition. This study investigated the growth performance, slaughter performance, and meat quality of ducks across different breeds and ages. Results indicated that at the same age, significant differences in body weight were observed among breeds (p < 0.05), with the weight ranking in descending order as follows: Cherry Valley ducks (C) > Wuqin 10 meat ducks (W) > Mianyang Partridge ducks (M) > Liancheng White ducks (L). A comparison of the same breed across different ages revealed that the pectoral muscle ratio tended to increase with age, whereas the leg muscle ratio showed the opposite trend; however, total meat production gradually rose. At all three growth stages, C ducks exhibited higher body weight and meat yield than the other breeds. W ducks demonstrated excellent meat quality traits and appropriate meat production, with indices such as shear force, water-holding capacity, and fat content all higher than those of the other breeds. L ducks and M ducks had relatively lower body weight and meat production compared to the other breeds, yet their shear force and water-holding capacity were superior to those of C ducks. The analysis of meat quality at different times showed that across all breeds, shear force, meat color, muscle fiber diameter, crude protein content, and fat content increased with age, while drip loss rate and muscle fiber density decreased. A comprehensive multi-index evaluation model for duck meat quality under different breeds was established, along with a four-factor principal component model (Z1, Z2, Z3, Z4). Using the comprehensive ranking equation K, the meat quality performance of different breeds at various ages, in descending order, was as follows: 63-day-old W > 90-day-old M > 63-day-old C > 90-day-old L > 63-day-old M > 90-day-old C > 63-day-old L > 90-day-old W > 42-day-old C > 42-day-old W. This study not only provides a theoretical basis for evaluating meat quality traits in different duck breeds but also offers insights for breed selection and age-related quality optimization. Full article

Happiness is defined as well-being and contentment with life. The growing imperative to evaluate well-being beyond economic growth alone has led to the formulation of holistic indices that better reflect quality of life and sustainable development goals. This has resulted in the emergence of the Happiness Score (HS), which adopts a more holistic and human-centred perspective on development and well-being. The present study takes the Happiness Score as a basis for the identification of some of the main determinants of happiness in an empirical and data-driven perspective. To this end, data from 145 countries was analysed, using statistical methodologies such as Generalised Linear Models (GLM), Principal Component Analysis (PCA), fuzzy set Qualitative Comparison Analysis (fsQCA) and the decision tree machine learning approach. A range of indices were considered to translate the reality of countries in different socio-economic dimensions, the level of development of each country, and the continent to which it belongs. The African continent demonstrates substantial disparities across virtually all variables and is frequently associated with the most unfavourable values for each index. The indicators that exerted the most profound influence on happiness were identified as the freedom to make life choices, literacy rate, and Gross Domestic Product (GDP) per capita. These results inform policy strategies aligned with sustainable development, emphasising that enhancing happiness requires multidimensional action beyond economic indicators—particularly in low- and middle-income countries. Full article

Silurus lanzhouensis is a large-sized commercial fish species endemic to the mid-upper reaches of the Yellow River, serving as a “Card of Aquatic Biological Species in the Yellow River”. However, due to factors such as overfishing and habitat changes, it has been listed as an endangered species. In order to protect and restore its wild resources, we conducted a detailed study for the first time from 2022 to 2024 on the age composition, growth characteristics, mortality rate, and current status of resource exploitation of the S. lanzhouensis population in the upper Yellow River. A total of 489 individuals underwent measurements for their total length (L) and body weight (W), with age determination conducted using lapillus otoliths. The collected samples exhibited a spectrum of total lengths spanning from 2.5 to 63.7 cm, body weights ranging from 0.11 to 1974.15 g, and ages ranging from 1 to 6 years. Further analysis of the length–weight relationships unveiled an allometric growth index (b) of 2.9562 for the overall samples, indicating an isometric growth pattern. Additionally, insights into the growth characteristics of S. lanzhouensis were provided by the von Bertalanffy growth function, revealing an asymptotic total length (L_∞) of 119.30 cm and a growth coefficient (K) of 0.1278 yr⁻¹. The growth characteristic index (φ) totaled 3.2598, suggesting a moderate growth rate in comparison to other Silurus species. The total mortality rate (Z) recorded for the population of S. lanzhouensis was found to be 0.5296 yr⁻¹. Through the application of three distinct methodologies on exhaustive samples, the average natural mortality rate (M) was calculated to be 0.3105 yr⁻¹. Consequently, the fishing mortality rate (F) for the entire sample set was determined to be 0.2191 yr⁻¹, leading to an exploitation rate (E) of 0.4137. Based on the survey findings, it is evident that the population of S. lanzhouensis has not been subjected to over-exploitation, attributable to ongoing stock enhancement. These results also provide foundational data for the protection and restoration of S. lanzhouensis in the upper Yellow River. Full article

The aim of this study is to investigate the physiological characteristics and regulatory mechanisms of porcine intramuscular fat (IMF), subcutaneous fat (take back fat (BF), for example), and visceral fat (take perienteric fat (PF), for example) to address the challenge of optimizing meat quality without excessive fat deposition. Many improved breed pigs have fast growth rates, high lean meat rates, and low subcutaneous fat deposits, but they also have low IMF content, resulting in poor meat quality. There is usually a positive correlation between intramuscular fat and subcutaneous fat deposits. This study selected eight-month-old female Tibetan pigs as experimental subjects. After slaughter, fat samples were collected. Histological differences in adipocyte morphology were observed via hematoxylin–eosin (HE) staining of tissue sections, and phenotypic characteristics of different adipose tissues were analyzed through fatty acid composition determination. Transcriptome sequencing and untargeted metabolomics were employed to perform pairwise comparisons between different fatty tissues to identify differentially expressed genes and metabolites. A siRNA interference model was constructed and combined with Oil Red O staining and lipid droplet optical density measurement to investigate the regulatory role of WNT16 in adipocyte differentiation. Comparative analysis of phenotypic and fatty acid composition differences in adipocytes from different locations revealed that IMF adipocytes have significantly smaller areas and diameters compared to other fat depots and contain higher levels of monounsaturated fatty acids. Integrated transcriptomic and metabolomic analyses identified differential expression of WNT16 and L-tyrosine, both of which are involved in the melanogenesis pathway. Functional validation showed that inhibiting WNT16 in porcine preadipocytes downregulated adipogenic regulators and reduced lipid droplet accumulation. This cross-level regulatory mechanism of “phenotype detection–multi-omics analysis–gene function research” highlighted WNT16 as a potential key regulator of site-specific fat deposition, providing new molecular targets for optimizing meat quality through nutritional regulation and genetic modification. Full article

This study focuses on the ancient buildings in Cicheng Old Town, a typical architectural heritage area in the Jiangnan region of China. These buildings are famous for their well-preserved Tang Dynasty urban layout and Ming and Qing Dynasty roof tiles. However, the natural aging, weathering, and biological erosion of the roof tiles seriously threaten the integrity of heritage protection. Given that current detection methods mostly depend on manual checks, which are slow and cover only a small area, this study suggests using deep learning technology for heritage protection and creating a smart model to identify damage in flat tiles using the YOLOv8 architecture. During this research, the team used drone aerial photography to collect images of typical building roofs in Cicheng Old Town. Through preprocessing, unified annotation, and system training, a damage dataset containing 351 high-quality images was established, covering five types of damage: breakage, cracks, the accumulation of fallen leaves, lichen growth, and vegetation growth. The results show that (1) the model has an overall mAP of 73.44%, an F1 value of 0.75 in the vegetation growth category, and a recall rate of 0.70, showing stable and balanced detection performance for various damage types; (2) the model performs well in comparisons using confusion matrices and multidimensional indicators (including precision, recall, and log-average miss rate) and can effectively reduce the false detection and missed detection rates; and (3) the research team applied the model to drone images of the roof of Fengyue Painted Terrace Gate in Cicheng Old Town, Jiangbei District, Ningbo City, Zhejiang Province, and automatically detected and located multiple tile damage areas. The prediction results are highly consistent with field observations, verifying the feasibility and application potential of the model in actual heritage protection scenarios. Full article

This study aims to increase the particle size of the precipitate, aiming for an increasing settling speed. The effluent contains 21.88 g/L of sulfate, 526.5 mg/L of calcium, 2.9 mg/L of cadmium, 4.73 g/L of magnesium, 332.8 mg/L of manganese, and 205.8 mg/L of zinc. Based on thermodynamic simulations, evaluating the pH increase up to 9.0, it was possible to determine that the main species are CaSO₄·2H₂O(s), Mg(OH)₂(s), MnO₂(s), ZnO(s), and Cd(OH)₂(s). In the precipitation tests, it was determined that a concentration of 2.0 mol/L of Ca(OH)₂ resulted in a particle size of 12.2 µm. The increase of temperature has an opposite effect, decreasing 40% of the particle size at 80 °C in comparison to 25 °C. On the other hand, the reaction time increases particle size, reaching 300% of an increase from 10 min to 3 h. In the seed tests, it was found that a seed ratio of 10 g/L to 100 g/L with the CaSO₄ (2) seed had the greatest impact on particle size growth, resulting in a 700% increase in particle size compared to the test without seeds. In the settling tests, a sedimentation rate of 177 mL/min was achieved using seeds and flocculants, compared to 50 mL/min in the test without reagents. Full article

In this study, using in-house code I-COSTA, importance analyses are performed on the phenomenological parameters in the aerosol dynamics using International Standard Problem No. 44. The analyses consider twelve parameters used in multicomponent sectional equations and Mason equations. For the first step of the analysis, Latin hypercube sampling is performed for the aforementioned parameters, and the number of samplings is determined using a comparison of averages and standard deviations between those samplings and the ones gathered from continuous distributions of the parameters. Sensitivity analyses are then performed on the airborne concentrations of the aerosol particles using I-COSTA, and the results are used to obtain the correlation coefficients between the parameters and the airborne concentrations. From the analyses, the dynamic shape factor, which accounts for the drag force of the non-spherical aerosol particles, is found to be one of the most important parameters in the aerosol dynamics. The saturation ratio in the Mason equation is also found to be an important parameter for aerosol particles with high solubility since the mass of the aforementioned particles is sensitive to the hygroscopic growth rate. Full article