Search Results (5,219)

To explore the dyeing technique and karyotype analysis of winter turnip rape (Brassica rape L.), the root tip of winter turnip rape Longyou 7 was used as the experimental material. Chromosome preparation technology was optimized, and karyotype analysis was carried out by changing the conditions of material collection time, pretreatment, fixation, and dissociation. The results showed that the optimal conditions for the preparation of dyeing winter turnip rape were as follows: the sampling time was 8:00–10:00, the ice–water mixture was pretreated at 4 °C for 20 h, the Carnot’s fixative solution I and 4 °C were fixed for 12 h, and the 1 mol/L HCl solution was bathed in a water bath at 60 °C for 10~15 min. Karyotype analysis showed that the number of chromosomes in winter turnip rape cells was 2n = 20, and the karyotype analysis formula was 2n = 2x = 20 = 16m + 4sm. The karyotype asymmetry coefficient was 58.85%, and the karyotype type belonged to type 2A, which may belong to the primitive type in terms of evolution. The results of this study provide a theoretical basis for further in-depth study of the phylogenetic evolution and genetic trend of Brassica rapa. Full article

Background: Spinal metastases (SMs) are associated with poor prognosis and significant morbidity. We hypothesize that artificial intelligence (AI) models can enhance the identification and clinical utility of genetic and molecular signatures associated with SMs, improving diagnostic accuracy and enabling personalized treatment strategies. Methods: A systematic review of five databases was conducted to identify studies that used AI to predict genetic alterations and SMs outcomes. Accuracy, area under the receiver operating curve (AUC), and sensitivity were used for comparison. Data analysis was performed in R. Results: Eleven studies met the inclusion criteria, covering three different primary tumor origins, comprising a total of 2211 patients with an average of 201 ± 90 patients (range: 76–359 patients) per study. EGFR, Ki-67, and HER-2 were studied in ten (90.9%), two (18.1%), and one (9.1%) study, respectively. The weighted average AUC is 0.849 (95% CI: 0.835–0.863) and 0.791 (95% CI: 0.738–0.844) for internal and external validation of the established models, respectively. Conclusions: AI, through radiomics and machine learning, shows strong potential in predicting molecular markers in SMs. Our study demonstrates that AI can predict molecular markers in SMs with high accuracy. Full article

Grass carp is an economically important cultured species in China. Triploid embryo production is widely applied in aquaculture to achieve reproductive sterility, improve somatic growth, and reduce ecological risks associated with uncontrolled breeding. In this study, a simple cold shock method for inducing triploid grass carp was developed. The triploid induction rate of 71.73 ± 5.00% was achieved by applying a cold treatment at 4 °C for 12 min, starting 2 min after artificial fertilization. Flow cytometry and karyotype analysis revealed that triploid individuals exhibited a 1.5-fold increase in DNA content compared to diploid counterparts, with a chromosomal composition of 3n = 72 (33m + 36sm + 3st). Additionally, embryonic transcriptome analysis demonstrated that, in the cold shock-induced embryos, genes associated with abnormal mesoderm and dorsal–ventral axis formation, zygotic genome activation (ZGA), and anti-apoptosis were downregulated, whereas pro-apoptotic genes were upregulated, which may contribute to the higher abnormal mortality observed during embryonic development. Overall, this study demonstrates optimized conditions for inducing triploidy in grass carp via cold shock and provides insights into the transcriptomic changes that take place in cold shock-induced embryos, which could inform future grass carp genetic breeding programs. Full article

Future $e^{+}{e}^{-}$ colliders are expected to play a fundamental role in measuring Standard Model (SM) parameters with unprecedented precision and in probing physics beyond the SM (BSM). This study investigates two-particle angular correlation distributions involving final-state SM charged hadrons. Unexpected correlation structures in these distributions is considered to be a hint for new physics perturbing the QCD partonic cascade and thereby modifying azimuthal and (pseudo)rapidity correlations. Using Pythia8 Monte Carlo generator and fast simulation, including selection cuts and detector effects, we study potential structures in the two-particle angular correlation function. We adopt the QCD-like Hidden Valley (HV) scenario as implemented in Pythia8 generator, with relatively light HV v-quarks (below about 100 GeV), to illustrate the potential of this method. Full article

Intercropping has been widely proven to boost agricultural yields and control diseases. This study examined the impact of sugarcane monoculture (SM) and sugarcane–pumpkin intercropping (IP) systems on soil physicochemical characteristics and microbial community dynamics. Compared to monoculture, intercropping significantly increased soil pH by 8.82% and total potassium (TK) by 17.92%, while reducing soil organic matter (SOM) by 25.56%. Bacterial communities under intercropping exhibited significantly higher alpha and beta diversity, whereas fungal community diversity remained unaffected. Notably, the relative abundances of certain taxa with known roles in plant growth promotion and pathogen suppression—such as Anaeromyxobacter, Nitrospira, and Massilia—were enriched. Canonical correlation analysis revealed that bacterial community composition was strongly associated with TK, while fungal community structure correlated with variations in soil available nitrogen (AN). These findings indicate that sugarcane–pumpkin intercropping reshapes soil microbial communities and contributes to some improvement in soil nutrient availability. Full article

Background: Chiari-like malformation (CM) and syringomyelia (SM) are commonly observed conditions in Pomeranian dogs. Affected dogs may develop clinical signs that significantly impact quality of life. Therefore, it is crucial to select only unaffected dogs for breeding. However, the progression of CM/SM has not been fully elucidated. Dogs that are unaffected or mildly affected may progress to severe SM over time. The primary aim of this study is to investigate the progression of CM/SM through repeated MRI scans. A secondary objective is to evaluate the effect of furosemide treatment on syrinx sizes, given its frequent prescription. Methods: Pomeranians that underwent two CM/SM screenings between 2015 and 2025 were included. CM/SM classifications were assessed, and quantitative syrinx measurements were conducted. Maximum syrinx diameter (MSD) and maximum syrinx-to-spinal cord diameter ratio (MSD/SCD-r) were measured and documented. Dogs were classified based on the progression of SM. Furosemide treatment was documented, and its effect on syrinx size was compared with that in dogs not receiving furosemide. Results: At the time of the second MRI, 39.6% of dogs either developed SM or showed substantial progression, whereas 12.5% demonstrated partial recovery. Of the dogs initially classified as free from SM, 20.7% had developed the condition. A significant increase was observed in both MSD (p = 0.0058) and MSD/SCD-r (p = 0.0038) between MRI1 and MRI2. Notably, the change in MSD between MRI1 and MRI2 was statistically significantly smaller in dogs treated with furosemide compared to untreated dogs (p = 0.030). Conclusions: These findings indicate that syrinx dimensions are dynamic and may fluctuate over time, although a general trend toward progression is observed. Furthermore, furosemide may mitigate the progression of SM. Full article

This paper addresses the trajectory tracking control problem of a six-degree-of-freedom Gough–Stewart Platform (GSP) by proposing a control strategy that combines a sliding mode (SM) controller with a rapid forward kinematics solution algorithm. The study first develops an efficient forward kinematics method that integrates Support Vector Regression (SVR) with the Levenberg–Marquardt algorithm, effectively resolving issues related to multiple solutions and local optima encountered in traditional iterative approaches. Subsequently, a SM controller based on the GSP’s dynamic model is designed to achieve high-precision trajectory tracking. The proposed control strategy’s robustness and effectiveness are validated through simulation experiments, demonstrating superior performance in the presence of model discrepancies and external disturbances. Comparative analysis with traditional PD controllers and linear SM controllers shows that the proposed method offers significant advantages in both tracking accuracy and control response speed. This research provides a novel solution for high-precision control in GSP applications. Full article

Monitoring soil moisture (SM) using permanently installed gamma radiation (GR) detectors is a promising non-invasive method based on the inverse relationship between SM and soil-emitted GR. In a previous study, we successfully estimated SM from environmental gamma radiation (EGR) measured by a low-cost counter-tube detector. Since this detector type provides a bulk GR response across a wide energy range, EGR signals are influenced by several confounding factors, e.g., soil radon emanation, biomass. To what extent these confounding factors deteriorate the accuracy of SM estimates obtained from EGR is not fully understood. Therefore, the aim of this study was to compare the accuracy of SM estimates from EGR with those from reference ⁴⁰K GR (1460 keV) measurements which are much less influenced by these factors. For this, a Geiger–Mueller counter (G–M), which is commonly used for EGR monitoring, and a gamma spectrometer were installed side by side in an agricultural field equipped with in situ sensors to measure reference SM and a meteorological station. The EGR_G–M and spectrometry-based ⁴⁰K measurements were related to reference SM using a functional relationship derived from theory. We found that daily SM can be predicted with an RMSE of 3.39 vol. % from ⁴⁰K using the theoretical value of α = 1.11 obtained from the effective ratio of GR mass attenuation coefficients for the water and solid phase. A lower accuracy was achieved for the EGR_G–M measurements (RMSE = 6.90 vol. %). Wavelet coherence analysis revealed that the EGR_G–M measurements were influenced by radon-induced noise in winter. Additionally, biomass shielding had a stronger impact on EGR_G–M than on ⁴⁰K GR estimates of SM during summer. In summary, our study provides a better understanding on the lower prediction accuracy of EGR_G–M and suggests that correcting for biomass can improve SM estimation from the bulk EGR data of operational radioactivity monitoring networks. Full article

Satureja montana (SM) is acknowledged as a highly pharmacologically important species within the vast Lamiaceae family, indigenous to the Balkan area. Traditionally, this plant has been employed as a culinary spice, especially in Bulgarian gastronomy. Additionally, it is widely recognized that mental health is affected by the nature and quality of dietary consumption. Results: Ethnopharmacological research underscores the potential of SM in influencing various chronic ailments, including depression and anxiety. This plant is distinguished by a rich variety of secondary metabolites that display a broad spectrum of biological activities, such as antioxidant, antidiabetic, anti-inflammatory, analgesic, antibacterial, antiviral, and antifungal effects. Particularly, two of its active phenolic compounds, rosmarinic acid and carvacrol, reveal notable anxiolytic and antidepressive properties. This review aims to explore the capacity of SM to improve mental health through its plentiful phenolic components. Recent studies indicate their efficacy in addressing Alzheimer’s-type dementia. A notable correlation exists among depression, anxiety, and cognitive decline, which includes dementia. Considering that Alzheimer’s disease (AD) is a multifaceted condition, it requires multi-targeted therapeutic strategies for both prevention and management. Conclusions: Satureja montana is recognized as potential candidate for both the prevention and management of various mental health disorders, including dementia. Full article

Carbon nanotubes (CNTs) and graphene nanoplatelets (GNPs) have attracted significant interest as hybrid reinforcements in epoxy (Ep) composites for enhancing mechanical performance in structural applications, such as aerospace and automotive. These 1D and 2D nanofillers possess exceptionally high aspect ratios and intrinsic mechanical properties, substantially improving composite stiffness and tensile strength. In this study, epoxy nanocomposites were fabricated with 0.1 wt.% and 0.3 wt.% of CNTs and GNPs individually, and with 1:1 CNT:GNP hybrid fillers at equivalent total loadings. Scanning electron microscopy of fracture surfaces confirmed that the CNTGNP hybrids dispersed uniformly, forming an interconnected nanostructured network. Notably, the 0.3 wt.% CNTGNP hybrid system exhibited minimal agglomeration and voids, preventing crack initiation and propagation. Mechanical testing revealed that the 0.3 wt.% CNTGNP/Ep composite achieved the highest tensile strength of approximately 84.5 MPa while maintaining a well-balanced stiffness profile (elastic modulus ≈ 4.62 GPa). The hybrid composite outperformed both due to its synergistic reinforcement mechanisms and superior dispersion despite containing only half the concentration of each nanofiller relative to the individual 0.3 wt.% CNT or GNP systems. In addition to mechanical performance, electrical conductivity analysis revealed that the 0.3 wt.% CNTGNP hybrid composite exhibited the highest conductivity of 0.025 S/m, surpassing the 0.3 wt.% CNT-only system (0.022 S/m), owing to forming a well-connected three-dimensional conductive network. The 0.1 wt.% CNT-only composite also showed enhanced conductivity (0.0004 S/m) due to better dispersion at lower filler loadings. These results highlight the dominant role of CNTs in charge transport and the effectiveness of hybrid networks in minimizing agglomeration. These findings demonstrate that CNTGNP hybrid fillers can deliver optimally balanced mechanical enhancement in epoxy matrices, offering a promising route for designing lightweight, high-performance structural composites. Further optimization of nanofiller dispersion and interfacial chemistry may yield even greater improvements. Full article

This study investigates the application of deep learning (DL) techniques for predicting temperature fields in the SM1 swirl-stabilized turbulent non-premixed flame. Two distinct DL approaches were developed using a comprehensive CFD database generated via the steady laminar flamelet model coupled with the SST k-ω turbulence model. The first approach employs a fully connected dense neural network to directly map scalar input parameters—fuel velocity, swirl ratio, and equivalence ratio—to high-resolution temperature contour images. In addition, a comparison was made with different deep learning networks, namely Res-Net, EfficientNetB0, and Inception Net V3, to better understand the performance of the model. In the first approach, the results of the Inception V3 model and the developed Dense Model were found to be better than Res-Net and Efficient Net. At the same time, file sizes and usability were examined. The second framework employs a U-Net-based convolutional neural network enhanced by an RGB Fusion preprocessing technique, which integrates multiple scalar fields from non-reacting (cold flow) conditions into composite images, significantly improving spatial feature extraction. The training and validation processes for both models were conducted using 80% of the CFD data for training and 20% for testing, which helped assess their ability to generalize new input conditions. In the secondary approach, similar to the first approach, studies were conducted with different deep learning models, namely Res-Net, Efficient Net, and Inception Net, to evaluate model performance. The U-Net model, which is well developed, stands out with its low error and small file size. The dense network is appropriate for direct parametric analyses, while the image-based U-Net model provides a rapid and scalable option to utilize the cold flow CFD images. This framework can be further refined in future research to estimate more flow factors and tested against experimental measurements for enhanced applicability. Full article

A standard approach to design begins with scaling up state-of-the-art machines to new target dimensions, moving towards larger rotors with lower specific energy to maximize revenue and enable power production in lower wind speed areas. This trend is particularly crucial in floating offshore wind in the Mediterranean Sea, where the high levelized cost of energy poses significant risks to the sustainability of investments in new projects. In this context, the conventional approach of scaling up machines designed for fixed foundations and strong offshore winds may not be optimal. Additionally, modern large-scale wind turbines for offshore applications face challenges in achieving high aerodynamic performance in thick root regions. This study proposes a holistic optimization framework that combines multi-fidelity analyses and tools to address the new challenges in wind turbine rotor design, accounting for the novel demands of this application. The method is based on a modular optimization framework for the aerodynamic design of a new wind turbine rotor, where the cost function block is defined with the aid of a model reduction strategy. The link between the full-order model required to evaluate the target rotor’s performance, the physical aspects of blade aerodynamics, and the optimization algorithm that needs several evaluations of the cost function is provided by the definition of a surrogate model (SM). An intelligent SM definition strategy is adopted to minimize the computational effort required to build a reliable model of the cost function. The strategy is based on the construction of a self-adaptive, automatic refinement of the training space, while the particular SM is defined by the use of stochastic radial basis functions. The goal of this paper is to describe the new aerodynamic design strategy, its performance, and results, presenting a case study of a 15 MW wind turbine blades optimized for specific deepwater sites in the Mediterranean Sea. Full article

The integration of forestry and agriculture has promoted edible fungi cultivation in forest understory spaces. However, the impact of spent mushroom substrates on forest soils remains unclear. This study explored the use of seafood mushroom spent substrates (SMS) and grass substrates to cultivate Dictyophora indusiata. After cultivation, soil pH stabilized, organic carbon increased by 34.02–62.24%, total nitrogen rose 1.1–1.9-fold, while soil catalase activity increased by 43.78–100.41% and laccase activity surged 3.3–11.2-fold. The 49% Cenchrus fungigraminus and 49% SMS treatment yielded the highest 4-coumaric acid levels in the soil, while all treatments reduced maslinic and pantothenic acid content. SMS as padding material with C. fungigraminus enhanced soil bacterial diversity in the first and following years. Environmental factors and organic acids influenced the recruitment of genus of Latescibacterota, Acidothermus, Rokubacteriales, Candidatus solibacter, and Bacillus, altering organic acid composition. In conclusion, cultivating D. indusiata understory enhanced environmental characteristics, microbial dynamics, and organic acid profiles in forests’ soil in short time. Full article

The Advanced Scatterometer (ASCAT), Soil Moisture Active Passive (SMAP), and European Space Agency-Climate Change Initiative (ESA–CCI) soil moisture (SM) products are widely used in agricultural drought monitoring, water resource management, and climate analysis applications. However, the performance of these SM products varies significantly across regions and environmental conditions, due to in sensor characteristics, retrieval algorithms, and the lack of localized calibration. This study proposes a multi-source long short-term memory (MLSTM) for improving ASCAT, ESA–CCI, and SMAP SM products by combining in-situ SM measurements and four key auxiliary variables: precipitation (PRE), land surface temperature (LST), fractional vegetation cover (FVC), and evapotranspiration (ET). First, the in-situ measured data from four in-situ observation networks were corrected using the LSTM method to match the grid sizes of ASCAT (0.1°), ESA–CCI (0.25°), and SMAP (0.1°) SM products. The RPE, LST, FVC, and ET were used as inputs to the LSTM to obtain loss data against in-situ SM measurements. Second, the ASCAT, ESA–CCI, and SMAP SM datasets were used as inputs to the LSTM to generate loss data, which were subsequently corrected using LSTM-derived loss data based on in-situ SM measurements. When the mean squared error (MSE) loss values were minimized, the improvement for ASCAT, ESA–CCI, and SMAP products was considered the best. Finally, the improved ASCAT, ESA–CCI, and SMAP were produced and evaluated by the correlation coefficient (R), root mean square error (RMSE), and standard deviation (SD). The results showed that the RMSE values of the improved ASCAT, ESA–CCI, and SMAP products against the corrected in-situ SM data in the OZNET network were lower, i.e., 0.014 cm³/cm³, 0.019 cm³/cm³, and 0.034 cm³/cm³, respectively. Compared with the ESA–CCI and SMAP products, the ASCAT product was greatly improved, e.g., in the SNOTEL network, the Root Mean-Square Deviation (RMSD) values of 0.1049 cm³/cm³ (ASCAT) and 0.0662 cm³/cm³ (improved ASCAT). Overall, the MLSTM-based algorithm has the potential to improve the global satellite SM product. Full article

The intergenic SNP (single-nucleotide polymorphism) rs80860411A>C was identified as a major QTL for drip loss measured on semimembranosus muscle (SM) in pigs. The SNP is located near the GALNT15. The purpose of this study was to analyze the association between rs80860411A>C and fattening, slaughter, and quality traits of Polish pigs. This study was conducted on 235 individuals belonging to two breeds, Polish Large White (n = 187) and Pulawska (n = 48). The rs80860411 genotypes were determined using the PCR-RFLP method. Association analysis was performed for each breed separately. It was shown that rs80860411A>C had a significant effect on fattening performance traits, on several slaughter performance traits, including width of the loin eye and carcass meat content (p ≤ 0.01, p ≤ 0.05), as well as on meat color—redness (a*) (p ≤ 0,05) in Pulawska breed. The obtained results indicate that the studied SNP has the potential to be a QTN and could be included in pig selection programs, especially in Pulawska pigs. Full article